e: n. . .16:le . n... I; If! . 1;. . $4 ., A ‘ 9 is..- .fléi... .25)? Mme /'1 ,n (’2 00% swam This is to certify that the dissertation entitled STUDIES OF THE GATA-3 TRANSCRIPTION FACTOR AS A POSITIONAL CANDIDATE GENE FOR A MURINE MODEL OF ASTHMA presented by Xingnan Li has been accepted towards fulfillment of the requirements for the PhD. degree in Genetics Graduate Prowm {*Mflu '01:k Major Professors Signature 5i/i 31m}; Date MSU is an Affirmative Action/Equal Opportunity Institution 0!. ,g. 3""" 7‘0‘ fi...- . 4 r - air-fir“ ' .- ....‘ Ir ~ ~- " or" ‘0' University WI Michigan State PLACE IN RETURN BOX to remove this checkout from your record. TO AVOID FINES return on or before date due. MAY BE RECALLED with earlier due date if requested. DATE DUE DATE DUE DATE DUE 04 11 0 5 ‘ Q4 11 li 5 6/01 c:/CIRC/Dat90ue.p65~p.15 STUDIES OF THE GATA-3 TRANSCRIPTION FACTOR AS A POSITIONAL CANDIDATE GENE FOR A MURINE MODEL OF ASTHMA By Xingnan Li A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Genetics Graduate Program 2004 ABSTRACT STUDIES OF THE GATA-3 TRANSCRIPTION FACTOR AS A POSITIONAL CANDIDATE GENE FOR A MURINE MODEL OF ASTHMA By Xingnan Li Asthma is a respiratory inflammatory disorder due to inappropriate immune responses to common environmental allergens in genetically susceptible persons. Asthma is characterized by increased serum immunoglobulin E levels, ainivay infiltration of eosinophils, airway hyperresponsiveness (AHR), mucus hypersecretion, and overexpression of T helper 2 cell (Th2) type cytokines. Quantitative trait loci for allergen-induced AHR, termed Abhr1 and Abhr2, mapped to chromosome 2 in a murine model of asthma. The GATA-3 gene (Gata3) mapped within the Abhr1 interval and was a strong positional candidate gene for this phenotype because it underlies the Th2 immune pathway. Thus, the working hypothesis for this study was that the allergen-induced AHR phenotype was due to over—expression of GATA—3. To more closely determine the location of Abhr1 and Abhr2 relative to Gata3, Abhr1 and Abhr2 regions were fine-mapped (~2 cM) by genotyping 450 backcross mice derived from hyper- (NJ) and hypo-responsive (C3H/HeJ) parental strains for 37 densely clustered DNA markers on chromosome 2. Gata3 was mapped within the Abhr1 confidence interval (lod = 4.3). Genomic DNA was sequenced to determine Gata3 polymorphisms between NJ and C3H/HeJ mice. A polymorphic microsatellite was identified in intron 5. No other inter-strain polymorphisms were found in exons, splicing sites, and part of the promoter region and 3’ untranslated region (12,069 bp total). A time course of the allergen-induced mRNA levels of GATA-3, interleukin (lL)-4, lL-5, lL-12, lL-13 and interferon gamma was determined in NJ and C3H/HeJ mice using real-time reverse transcriptase-polymerase chain reaction (RT-PCR). GATA-3 expression was induced by ovalbumin (OVA) treatment at the earliest time point (6 hr) in lymph nodes and spleens of NJ mice, but not C3H/HeJ mice. Unexpectedly, no GATA-3 expression difference was observed in lungs at any time point. Th2 cytokine expression was in general greater in NJ mice than in C3H/HeJ mice, while CSH/HeJ mice tended to surpass AIJ mice in Th1 cytokine expression. To investigate the role of GATA—3 in mediating allergen-induced AHR, Western blot was used to determine the levels of GATA-3 protein in splenocytes examined 72 hr following allergen exposure of these strains. A/J mice showed a strong GATA-3 signal subsequent to OVA challenge, but C3H/HeJ mice did not. In summary, we found strain-specific and treatment-specific quantitative differences in GATA-3 mRNA and protein levels, but no qualitative differences between NJ and CBH/HeJ mice were detected in Gata3 at the DNA level. These results reconfirmed the important role of GATA-3 in allergen-induced AHR. However, they do not provide direct evidence in support of Gata3 as a positional candidate gene for Abhr1 in the NJ and C3H/HeJ murine model of asthma. Copyright by XINGNAN LI 2004 DEDICATION This dissertation is dedicated to: My lovely wife, Huashi Li, whose love is the most important stimulation for my career; my parents, Dawan Li and Zhongxi Li, who always encourage and support me by all hearts; my parents-in-law, Rongjie Li and Chunfu Quan, who support my family spiritually and commercially; and my sister, Changshu Li’s family, for their love and support. ACKNOWLEDGMENTS This dissertation could not be completed without the excellent guidance, insight, and encouragement of Dr. Susan L. Ewart. Dr. Ewart is not only a great mentor but also a good friend. I am grateful to Dr. Marsha Wills-Karp, who acts as my co-adviser. I am also grateful to my committee members, Dr. Sarah H. Elsea, Dr. Jack R. Harkema, and Dr. Patrick J. Venta, for their invaluable suggestions. I would like to thank Dr. Norbert E. Kaminski’s laboratory, especially Robert B. Crawford for their suggestions and technique support on TaqMan real-time RT-PCR and Western Blot. I would like to thank the colleagues in my lab, especially Dennis Shubitowski for his technique support on DNA sequencing and genetic linkage analysis. I would also like to thank Annette S. Hamilton and Ravisankar A. Ramadas for their help with inbred mouse production and sacrifice. Finally, I would like to thank my wife for her statistical inputs as well as her support and love. vi TABLE OF CONTENTS LIST OF TABLES ................................................................................. ix LIST OF FIGURES ................................................................................ x LIST OF ABBREVIATION ...................................................................... xii Chapter One: Background and Significance ................................................ 1 A. Asthma ....................................................................................... 1 B. Th1 and Th2 pathways .................................................................. 8 C. Transcription factors in the Th1/Th2 pathways .................................. 13 D. GATA-3 .................................................................................... 18 E. A“ and C3H/HeJ mouse model for asthma ...................................... 27 F. Summary .................................................................................. 31 Chapter Two: F ine-mapping of Abhr1 and Abhr2 loci ................................... 32 A. Introduction ................................................................................ 32 B. Massachusetts Institute of Technology (MIT) microsatellite markers ...... 34 C. Self-designed microsatellite markers ............................................... 37 D. Hemolytic complement (Hc) RFLP marker ....................................... 42 E. Polymerase chain reaction-based genotyping ................................... 45 F. Multipoint linkage analysis ............................................................ 47 G. Comparison of our linkage results to published linkage maps ............... 50 H. Positional candidate genes ........................................................... 55 I. Summary .................................................................................. 57 Chapter Three: Comparison of Gata3 sequence in two murine strains ............ 58 A. Introduction ............................................................................... 58 B. Gata3 gene structure ................................................................... 59 C. Sequencing of Gata3 .................................................................. 61 D. Comparison of our sequence to public databases .............................. 83 E. Summary .................................................................................. 86 Chapter Four: Comparison of GATA-3 and cytokine gene mRNA expression in two murine strains ............................................................................. 87 A. Introduction ............................................................................... 87 B. TaqMan real-time RT-PCR ........................................................... 89 C. Experimental time line ................................................................. 98 D. Expression profiles for cytokine genes : II4, [[5, [[12, II13, and Ifng ...... 100 E. GATA-3 gene expression profile ................................................... 107 F. Summary ................................................................................. 1 11 vii Chapter Five: Comparison of GATA-3 protein in two murine strains .............. 113 A. Introduction .............................................................................. 113 B. GATA-3 Western blot assay development ...................................... 115 C. Experimental time line ................................................................ 117 D. Western blot of GATA-3 ............................................................. 119 E. Summary ................................................................................. 122 Discussion ........................................................................................ 123 Materials and Methods ........................................................................ 132 A. Genomic DNA isolation from mouse kidney .................................... 132 B. Polymerase chain reaction (PCR) ................................................ 133 C. 839 I digestion for Ho genotyping ................................................. 135 D. MAPMAKER program ................................................................ 135 E. JoinMap program ...................................................................... 136 F. DNA primer design .................................................................... 137 G. DNA sequencing ....................................................................... 137 H. Ovalbumin sensitization and challenge .......................................... 139 I. TaqMan real-time RT-PCR ......................................................... 140 J. Statistic analysis of mRNA expression data .................................... 142 K. Nuclear protein isolation from EL-4 cells and splenocytes .................. 144 L. GATA-3 protein quantitation by Western blot .................................. 146 Appendix .......................................................................................... 149 Table 8. Mouse ID reference and APTI value ...................................... 149 Table 9. Genotyping data of 450 NJ backcross mice by 37 markers ........ 155 Table 10. Genes within Abhr1 and Abhr2 ........................................... 169 Table 11. GATA-3 expression in lungs ............................................... 185 Table 12. GATA-3 expression in tracheobronchial lymph nodes .............. 200 Table 13. GATA-3 expression in spleens ............................................ 203 Bibliography ..................................................................................... 213 viii LIST OF TABLES Table 1. MIT microsatellite markers on chromosome 2 ............................... 35 Table 2. Self-designed microsatellite markers .......................................... 41 Table 3. Comparison of our linkage results with MIT linkage map ................. 53 Table 4. Comparison of our linkage results with Jackson lab RH map, Celera physical map, and UCSC physical map ............................. 54 Table 5. Positional candidate genes on chromosome 2 .............................. 56 Table 6. Sequencing primers for Gata3 .................................................. 62 Table 7. Comparison of our sequencing data with public databases ............. 85 Table 8. Mouse ID reference and APTI value ......................................... 149 Table 9. Genotyping data of 450 NJ backcross mice by 37 markers .......... 155 Table 10. Genes within Abhr1 and Abhr2 .............................................. 169 Table 11. GATA-3 expression in lungs ................................................. 185 Table 12. GATA-3 expression in tracheobronchial lymph nodes ................ 200 Table 13. GATA-3 expression in spleens .............................................. 203 ix LIST OF FIGURES Figure 1. Th1 and Th2 pathways ............................................................ 12 Figure 2. Processes of identifying microsatellite markers in Gad2 .................. 38 Figure 3. Ho genotyping ........................................................................ 43 Figure 4. Genotyping microsatellite marker DZMit416 .................................. 46 Figure 5. Mouse chromosome 2 genetic linkage map .................................. 49 Figure 6. Gata3 gene structure ............................................................... 60 Figure 7. An example of a Gata3 sequencing gel ....................................... 66 Figure 8. An example of automated sequencing chromatograph of Gata3 ....... 67 Figure 9. Gata3 gene sequence of NJ and C3H/HeJ mice ........................... 69 Figure 10. The process of TaqMan real-time RT-PCR ................................. 92 Figure 11. The threshold cycle of TaqMan real-time RT-PCR ........................ 93 Figure 12. GATA-3 and 18s rRNA amplification plots .................................. 96 Figure 13. Standard curves of GATA-3 and 18s rRNA ................................. 97 Figure 14. Experimental time line of in vivo allergen exposure ...................... 99 Figure 15. lL-4 expression in ulngs and tracheobronchial lymph nodes ......... 102 Figure 16. lL-5 expression in lungs and tracheobronchial lymph nodes ......... 103 Figure 17. lL-13 expression in lungs and tracheobronchial lymph nodes ....... 104 Figure 18. lL-12p40 expression in lungs and tracheobronchial lymph nodes..105 Figure 19. lFN-y expression in lungs and tracheobronchial lymph nodes ...... 106 Figure 20. GATA-3 TaqMan primer pair and probe .................................. 108 Figure 21. GATA-3 expression in lungs, TaqMan and SYBR green assay....109 Figure 22. GATA-3 expression in tracheobranchial lymph nodes and spleens.110 Figure 23. EL-4 cell Western blot gel ...................................................... 116 Figure 24. Experimental time line for splenocyte nuclear protein isolation. .. ...1 18 Figure 25. Western blot of GATA-3 8hr splenocytes samples ..................... 120 Figure 26. Western blot of GATA-3, 4, 12, 24 hr splenocytes samples .......... 121 xi AHR APC APTI BAL BHR cAMP CD CDC CTLA-4 DC ELISA FEV FOG FVC GATA-3 Gata3 HLA lCAM-1 lFN-y lgE IKB lL Jaks LFA—1 MHC MIT NFAT NF—xB OVA PBS PMA QTL RFLP ROG RT-PCR SNP STAT Tc TCR TGF-B Th TNF Ts LIST OF ABBREVIATIONS airway hyperresponsiveness antigen-presenting cells ainrvay pressure time index bronchoaleveolar lavage bronchial hyperresponsiveness cyclic adenosine monophosphate cluster of differentiation antigens Centers for Disease Control and Prevention cytolytic T lymphocyte-associated antigen 4 dendritic cells enzyme-linked immunosorbent assay forced expiratory volume friend of GATA forced vital capacity GATA-binding protein 3 (protein or mRNA) GATA-binding protein 3 (DNA) human leucocyte associated antigens intercellular adhesion molecule-1 interferon gamma immunoglobulin E NF-KB inhibitor interleukin Janus family protein tyrosine kinases lymphocyte function-associated antigen 1 major histocompatibility complex Massachusetts Institute of Technology nuclear factor of activated T cells nuclear factor of kappa light chain gene enhancer in B-cells ovalbumin phosphate-buffered saline phorbol 12-myristate 13-acetate quantitative trait locus restriction fragment length polymorphism repressor of GATA-3 reverse transcription-polymerase chain reaction single nucleotide polymorphism signal transducer and activator of transcription cytotoxic T cells T cell receptors transforming growth factor-8 T helper cells tumor necrosis factor suppressor T cells xii Chapter One: Background and Significance A. Asthma Phenotype description Asthma is a chronic respiratory disease characterized by ainrvay hyperresponsiveness (AHR), infiltration of eosinophils, mast cells and lymphocytes, airway obstruction, increased immunoglobulin E (IgE) level, increased mucus secretion, and overexpression of T helper cell type 2 (Th2) cytokines, such as interleukin (lL)-4, lL-5, and lL-13 [1, 2]. Asthma is a chronic syndrome of the ainivay with recurrent wheezing, coughing, chest tightness, and shortness of breath. Persistent ainrvay inflammation, which leads to AHR, is critical to the pathogenesis of asthma. Asthma is an inflammatory disorder due to inappropriate immune responses to common environmental antigens in genetically susceptible persons. Expression ‘of asthma phenotype is affected by both genetic and environmental factors. Various environmental factors, such as viral infection, allergen exposure, and exercise, contribute to asthma. Various genes, such as lL-4, lL-13, T-cell antigen receptor, high-affinity lgE receptor, may be involved in asthma. Thus, asthma is a complex genetic syndrome [3]. However, the mechanism and the genetic reasons for asthma remain unclear. Epidemiology The prevalence, morbidity, and mortality of asthma have increased dramatically in recent years, especially in developed countries. According to National Health Interview Survey (NHIS), in 2001, 20.3 million (7.3 %) people of the United States had asthma at the time of the interview [4]. The rates of asthma decreased with age: 8.7% (6.3 million) of 0-17 years children had asthma compared with 6.9% (14 million) 18 years and over adults [4]. The rates of asthma varied among different racial groups: asthma prevalence of non-Hispanic blacks was approximately 10% and 40% higher than non-Hispanic whites and Hispanics, respectively [4]. The rates of asthma were also different between sexes: adult females had a 30% higher prevalence than adult male; however, boys had over 30% higher prevalence than girls [4]. Various forms of asthma Asthma is a complex genetic disorder with numerous expressions, such as AHR, bronchoconstriction, ainNay edema, and atopy. Defining the phenotype of asthma is the first step to study it. According to its severity, asthma can be classified into intermittent, mild persistent, moderate persistent, and severe persistent [3]. Based on the level of lgE-mediated response, it can be classified into atopic and non-atopic. Additionally, etiologic classifications include occupational, exercise-induced, aspirin sensitive, and persistent respiratory infected [5]. Based on ages, four asthma phenotypes are defined in children: transient infant wheezing, nonatopic wheezing of the toddler, IgE-mediated wheezing/asthma, and late-onset childhood asthma [5]. In adult, asthma can be either adult-onset or childhood-related, however, the phenotypes of adult-onset asthma are poorly defined [5]. Due to the heterogeneous genotypes and phenotypes, asthma is more likely to be a syndrome rather than a specific disease entity [1, 3]. Diagnosis Various diagnostic methods exist based on different aspects of the asthma phenotypes. Ainrvay obstruction can be determined by pulmonary function tests such as the decreasing ratio of forced expiratory volume to forced vital capacity (FEV1/FVC). Total serum lgE levels can be tested by enzyme-linked immunosorbent assay (ELISA). Ainivay eosinophil infiltration can be shown by cell counting from bronchoalveolar lavage (BAL). AHR refers to the ability of the ainrvays to constrict when exposed to small concentrations of inhaled bronchoconstrictor mediators or naturally occurring bronchoconstrictor stimuli. AHR is a subset phenotype of asthma and considered a key feature [6], therefore AHR was used as an index of the asthma phenotype in the current study. Therapy Asthma has become a global disease; effective and specific therapy is urgently needed. Because asthma is driven by chronic ainrvay inflammation, anti-inflammatory therapy forms the basis for asthma control. Glucocorticoids are the most effective and widely used anti- inflammatory agents in the treatment of asthma. Glucocorticoids can repress the translocation of nuclear factor of kappa light chain gene enhancer in B—cells (NF-KB) through inducing the expression of NF-KB inhibitor (IKB). Since NF-KB stimulates inflammatory cytokines, such as tumor necrosis factor alpha (TNF-a), lL-1l3, and lL-2, glucocorticoids have potential anti-inflammatory function by interfering with the NF-KB pathway [7]. Bz-adrenergic agonists are also widely used to treat asthma due to their bronchodilatory function. Bz-adrenergic receptors are widely located in ainrvay smooth muscle and activated when associated with trimeric Gs protein and guanosine triphosphate (Gs-GTP). Activated Bz-adrenergic receptors can increase cyclic adenosine monophosphate (cAMP) levels, which will induce airway smooth muscle relaxation. BZ-adrenergic agonists may stabilize activated [32 receptors-Gs-GTP complex and thus act as a bronchodilator [8]. Other anti-inflammatory drugs or drugs that act on the nervous system, such as leukotriene receptor antagonists, anticholinergics, theophylline, cromolyn, and nedocromil, are also used [1]. However, all the currently used drugs are non-specific and may have side effects. The only way to resolve this problem is to uncover the basic mechanism of asthma, so that targeted therapies can be developed. New ways to treat asthma such as antisense DNA, CpG oligodeoxynucleotides, and transcription factor agonists or antagonists may be available in the future [9, 10]. Genetics Asthma as a heritable disease has been established by twin studies and family studies. Genetic linkage analysis and association studies further show that asthma is a complex trait instead of a simple Mendelian disease. Twin studies have contributed a lot to our understanding of the genetics of asthma and the interaction between genes and the environment [11]. In a study of 381 Australian twin pairs, strong genetic associations between asthma, atopy. and bronchial hyperresponsiveness (BHR) were indicated [12]. A nation-wide Finnish twin study showed that genetic factors could explain 87% of variations of asthma incidence in twins with affected parents, however susceptibility to asthma in twins with unaffected parents was largely explained by environmental effects [13]. Interestingly, a comparative study of monozygotic and dizygotic twins showed that pollen allergen had a greater genetic correlation, while indoor allergen was more environmentally correlated [14]. Genome-wide screens and genetic linkage analyses have been used to locate the quantitative trait loci (QTL) for asthma and positional candidate genes. A number of different linkages have been identified in different populations. One group of genes that have been repeatedly linked with asthma phenotypes are the genes involved in the Th2 cell pathway. One of the earliest studies was a sib-pair study of 11 Amish families that revealed the linkage of chromosome 5q31.1 with total serum lgE concentration and suggested IL4 or nearby genes on 5q31.1 may be involved [15]. The linked region of chromosome 5q contains a cytokine gene cluster: IL3, IL4, IL5, IL9, IL1ZB, IL13, and granulocyte—macrophage colony-stimulating factor (GMCSF). Recent studies have shown a sequence variant on the IL4 promoter region (C589T) associated with FEV1 and asthma [16]. A variant in the IL13 coding region (Gln110Arg) has also been associated with asthma [17]. The receptors of IL-4 and IL- 13 share the lL-4 receptor alpha chain and are both involved in lgE regulation. lL-5 is important for maturation and differentiation of eosinophils, and asthma. The linkage of chromosome 5q to circulating eosinophils have been shown [18]. Further studies on 5q regions revealed some new candidate genes including the hepatitis A virus receptor (HAVCR1), interleukin 12 p40 (IL12B) [19], CD14 [20], and serine protease inhibitor, kazal type 5 (SPINK5) [21]. Besides the chromosome 5q region, other genes on other chromosomes have also been consistently identified with asthma-related phenotypes: major histocompatibility complex (MHC) [22] and tumor necrosis factor alpha (TNF-a) on chromosome 6 [23], B-chain of the high- affinity receptor for lgE (chRl-B) on chromosome 11q13 [24]. According to an extensive review by Hoffjan et al, to date variants in 64 genes have been shown to be associated with asthma or related phenotypes among different populations and they are located on chromosome 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 16, 17, 19, 21, and X [25]. In summary, asthma is a complex genetic syndrome due to inappropriate immune responses to common environmental antigens in genetically susceptible persons. Lots of environmental factors and genes are involved in asthma, which leads to the heterogeneity of asthma phenotypes and genotypes. Genetic linkage analyses based on different human populations often reveal different QTL, which may not be applicable to other populations because of the genetic heterogeneity. To study this complex disease more effectively and easily, a murine model was utilized in the current study. Although the results of the murine model cannot be directly applied to humans, it is invaluable for revealing mechanisms of asthma due to molecular homology and common pathways between mice and humans. B. Th1 and Th2 pathways Antigen-presenting cells (APQ Major histocompatibility complex (MHC) molecules, also known as histocompatibility antigens, are glycoproteins expressed on the cell surface of higher vertebrates. They were first discovered in mice and called H-2 antigens, which are encoded by genes on chromosome 17. The counterparts in human are called human leucocyte associated antigens (HLA), which are encoded by genes on chromosome 6 [26, 27]. High polymorphism is one of the distinctive features of MHC molecules, which is important for antigen processing and presenting functions. There are two principal classes of MHC molecules: MHC I and MHC II. MHC I molecules are expressed on all nucleated cells and deal with intracellular microbes such as viruses and antigens in the cytosol. By contrast, MHC II molecules are expressed on specialized cells, such as B cells, macrophages, and other antigen-presenting cells (APC) that take up foreign antigens from intracellular vesicles [27]. When foreign antigens enter the respiratory tract, antigen-presenting cells residing there can recognize and process them. The main APC in the lung are dendritic cells (DC), which have two subtypes: DC1 and D02 [28]. D02 or immature DCs, located on mucosal surface of the lung, express mainly IL-10 and low levels of MHC II. In contrast, DC1 or mature DCs, located in the lymphoid organs, express mainly lL-12 and higher level of MHC II on their surface [29]. CD28 is a glycoprotein molecule that is expressed on the surface of T cells and serves as a receptor for the B7 costimulatory molecule, which is expressed on APC, activated T cells, or activated B cells. Antigens presented by MHC II and co-stimulatory signals presented by B7 molecules on the surface of DCs are recognized by T cell receptors (TCR) and CDZ8 molecules, respectively, on naive T helper (Th0) cells located on peripheral lymphoid organs. Both TCR signals and costimulatory signals are required for Th0 cell activation [27]. T helper 1 Th) cells Specific cluster of differentiation (CD) antigens also are required for DOS and T cells recognition besides MHC-TCR and B7-CD28 interactions. CDB antigen is expressed on cytotoxic T (Tc) cells and suppressor T (Ts) cells, which recognizes MHC I molecules. CD4 antigen is expressed specially on T helper (Th) cells and recognizes MHC II molecules. Tc (CD8+) cells respond to viruses, tumors or transplanted organs. Th (CD4+) cells can stimulate nonspecific effector cells to produce specific immunity during cell-mediated immune response. With regard to the humoral immune response, Th (CD4+) cells are essential for inducing antibody production by B cells. Th cells make up the predominant lymphocyte population that infiltrates the airways in asthmatics [30]; Th cells multiply rapidly following certain stimuli; Th cells can also lead to cell- mediated or humoral immune responses. For these reasons, Th cells are believed to play a central role in asthmatic inflammation [2, 28]. T cell differentiation Antigen-activated na'ive Th0 (CD4+) cells can differentiate into two subsets, Th1 and Th2, based on their distinct functions and the profile of secreted cytokines [2, 28] (Figure 1). The cytokine environment, type and dose of antigen, and costimulatory signals are all important for Th cell differentiation [31, 32]. Pfeiffer and colleagues have shown that strong binding of TCR and MHC lI/antigen polarized Th1-like cells, but weak binding of TCR and MHC ll/antigen favored Th2-like cells [33]. Weak TCR signaling favored lL-4 expression and Th2 differentiation by increasing nuclear factor of activated T cells (NFAT)c to NFATp ratio [34]. Dosage of antigen also affects Th0 cell differentiation. For example, naive Th cells secreted more lL-4, a Th2 type cytokine, when treated with low dosage of ovalbumin (5 to 50 nM); but secreted more interferon gamma (lFN-y), a Th1 type cytokine, when high dosage of antigen (3 50 nM) was used [35]. Since the costimulatory signal through the interaction between B7 and CD28 is required for T cell stimulation, the two types of B7 molecule, B7-1 and B7-2, may be also important for Th0 cell differentiation. For example, the dominant presence of B7-2 molecules on Th0 cells may favor the Th2 pathway [31]. Based on a mitogenic anti-0028 study, strong costimulation of 0028 versus TCR signal might favor the Th2 versus Th1 pathway [36]. CD28 costimulation signals might also control histone hyperacetylation and activation of lL-5 gene through the NFKB and GATA-3 pathway [37]. Recently, cytolytic T 10 lymphocyte-associated antigen 4 (CTLA-4) was shown to be an important T cells differentiation regulator. CTLA-4 is also a receptor for the B7 costimulatory signal. CTLA-4 deficient T cells polarized to Th2 differentiation with increased activation of NF-KB and expression of GATA- 3 by a STAT-6 independent mechanism [38]. The ligation of intercellular adhesion molecule-1 (lCAM-1) on T cells and lymphocyte function- associated antigen 1 (LFA-1) on DC favored human Th1 development in a lL-12 independent manner [39]. However, the cytokine environment is the most important factor determining the Th cell differentiation. IL-12 can induce Th0 cells to differentiate into the Th1 subset through signal transducer and activator of transcription 4 (STAT4) and inhibit the Th2 pathway. lL-4 is critical for Th2 subset formation through STAT6 and inhibit Th1 pathway. Th1 cells produce lL-2, lFN-y, and TNF-8, and promote strong cell-mediated immune responses. On the contrary, Th2 cells produce IL-4, lL-13, and lL-5 [28]. lL-4 and lL-13 are mportant for stimulating B cells to produce lgE [40]. lL-5 is essential for eosinophil maturation and infiltration [41]. Based on ainNay lavage and biopsy samples, Th2 cytokines (IL-4 and lL-5) were overexpressed in asthmatics [30]. Elevated lL-4 expression in asthmatics was correlated with elevated lgE level, and increased lL-5 expression was associated with eosinophilia [30]. Thus, it is believed that Th2 cells are critical in asthma. 11 83:58 89:5 332.8 @E m__8 .86; a N we: 6 :E 2.8 599.. E. _. cab 95 oumzcocotfi :3 SF: m__oo 539. h o>._.mz .99553 NE. ucm E... .F 939”. 12 wmocofimcommotomhm cask/Ed. n52 ZEQOGEOM 0mm mUm mo: T500304 mocmboxsod ”MAE 05953:.— .nLSSfio: bougsgi H2 C. Transcription factors in the Th1/Th2 pathways Intmthion lL-4 and lL-12 are believed to be the main cytokines polarizing nai’ve Th cells to Th2 and Th1 pathways, respectively. However, the regulation of Th1/Th2 differentiation is a complicated signal transduction network in which lots of transcription factors are involved, such as STAT, NFAT, c- Maf, NF-KB, T-bet, and GATA-3 [28, 42, 43]. Among these transcription factors, GATA-3 and T-bet are believed to be the key players for the Th2 and Th1 pathways, respectively. §anal transducer and activator of transcriptioan TA T) The signal transducer and activator of transcription (Stat) family, with six family members (Stat1-6), is a group of transcription factors involved in cytokine-induced cell responses. The binding of a specific cytokine to its receptor can dimerize cytokine receptors and activate the Janus family protein tyrosine kinases (Jaks) associated with the cytokine receptors. Jaks are a group of tyrosine kinases with four family members (Jak1-3 and Tyk2). The activated Jaks can phosphorylate and activated specific Stats. The activated Stats will form dimers, translocate into nuclei, and act as transcription factors to regulate downstream gene expression. Association of lL-4 or lL—13 with its receptors will activate Jak1 and Jak3, which will in turn activate Stat6. Stat6 will up-regulate lgE production, B cell proliferation, and Th2 pathway [44]. In contrast, lL-12 and lL-12 receptor 13 recognition will activate Tyk2, and then Stat4. Stat4 will subsequently up- regulate lFN-y expression and the Th1 pathway [44]. Thus, lL—4 and lL-12 can induce the Th2 and Th1 pathways through Stat6 and Stat4, respectively. NucleaI factor of activated T cells (NFA T) The NFAT gene family has five members: NFAT1 (NFATp), NFAT2 (NFATc), NFAT3, NFAT4, and NFAT5 [45]. NFAT is a transcription complex composed of subunits that exist in the cytoplasm of unstimulated T cells. Upon T cell stimulation, NFAT translocates to the nuclear where it acts as a transcriptional regulator [43]. NFATc deficient animals showed decreased serum lgE level. NFATc deficient Th (CD4+) cells lost the lL-6- induced lL-4 expression [46]. On the contrary, T cells in atopic patients had high levels of IL-4 but low levels of NFATp binding to the lL-4 promoter [47]. This evidence indicates NFATc and NFATp are positive and negative regulators for the Th2 pathway, respectively. Mt c-Maf is a basic-leucine zipper (b-Zip) transcription factor, which can bind to AP-1 and CRE sites of the target DNA promoters [48]. c-Maf is a Th2 specific transcription factor and favors Th2 differentiation mainly through lL-4 dependent mechanisms. c-Maf can also stimulate the Th2 pathway through an IL-4-independent and CD25-mediated mechanism 14 [49]. A c-Maf deficient mice study showed that lL-4 expression was dramatically decreased, but lL-5 and IL-13 expressions were still at normal levels [50]. Thus, c-Maf is not only Th2 specific, but also an lL-4 specific transcription factor. M In mammals, the NF-KB transcription factor family has five members: NF-K31 (p50/p105), NF-xBZ (p52/p100), RelA (p65), RelB, and c-Rel [51]. NF-KB functions as homo- or hetero-dimers dependent on the specific stimuli. In unstimulated cells, NF-KB dimers reside in the cytoplasm as an inactive form associated with inhibitors of KB (IKB). IKB family members include lea, IKBB, IKBS, IKBQ, IK85 (p100), ley (p105), and Bcl-3 [51, 52]. In stimulated cells, the NF-KB dimer dissociates from IKB and translocates into the nucleus to act as a transcription factor. NF-KB family members are involved in numerous immune responses, such as innate immunity, T-cell activation, and B—cell activation, depending on the components of the homo— or hetero-dimer [51]. p50 deficient mice were unable to produce Th2 type cytokines such as lL-4, lL-5, and lL-13, and airway eosinophilic inflammation [53]. Thus, NF-xB is a positive regulator of Th2 differentiation. 15 _T_-b_et T-bet is a newly identified transcription factor of the T-box family. T-bet is the only Th1 specific transcription factor found to date that induces IFN- y expression and inhibits the Th2 pathway [54]. In human asthmatic subjects, the expression of T-bet was much lower than in healthy controls. Furthermore, mice with a targeted T-bet deletion showed spontaneous inflammatory phenotypes without allergen exposure [55]. The Th1 pathway may be induced by lL-12 through the STAT-4 pathway or by IFN- y through the STAT-1 pathway. Recently, T-bet was found to be induced by lFN-y through the STAT1 signaling pathway, instead of ll.-12 through STAT-4, and upregulated IL-12R82 and lFN-y expression [56]. Thus, T-bet is believed to be the key player of Th1/Th2 differentiation as a Th1 specific transcription factor. In contrast, GATA-3 is believed to be the other key player of Th1/Th2 differentiation, but as a Th2 specific transcription factor. Ectopic expression of GATA-3 or T-bet in human T cells without polarizing cytokines could lead T cells to Th2 or Th1 phenotypes, respectively [57]. The histone hyperacetylation of lL-4 or lFN-y locus during Th2/Th1 differentiation was dependent on GATA-3 or T-bet, respectively [58]. It was believed that the chromatin remodeling of lL-4 and IFN-y was initiated by TCR signaling, and was maintained and extended by GATA-3 and T- bet, respectively [59]. The mRNA expression ratio of GATA-3 to T-bet reflected the changes of lL-4 to IFN-y expression, and could be quantitated by RT-PCR as an index of Th2/Th1 balance [60]. 16 Qflerflnscnption factors Many other transcription factors are also involved in the Th1/Th2 pathways. AP-1, C/EBPB, and JunB are positive regulators of the Th2 pathway, while BCL-6 is a negative regulator of the Th2 pathway [28, 42]. In fact, all transcription factors involved in Th1/Th2 pathways form a signal transduction network and may be important for asthma. 17 D. GATA-3 _GA TA family The GATA family is a group of transcription factors with specific distributions and functions. Six members (GATA—1-6) of the GATA family were originally described in chicken erythroid cells [61]. Their homologues in other species, such as mice and human, have also been found [62]. According to sequence alignment, GATA family members share quite similar sequences. The most striking feature of the GATA family is that they all have a conserved C4 zinc finger structure, through which they can bind to WGATAR (W=AlT, R=A/G) conserved sequence on DNA [63]. The six GATA family members can be classified into two groups based on their expression sites and functions: GATA—1, GATA—2, and GATA-3 belong to the hematopoietic group because they are normally expressed in hematopoietic cells and are required for hematopoietic processes; GATA-4, GATA-5, and GATA-6 belong to the nonhematopoietic group because they are normally expressed in nonhematopoietic cells and involved in cardiogenesis and gut epithelium differentiation [64, 65]. GATA-1 is expressed in hematopoietic cells, spleen, lymph nodes, and thymus. GATA-1 mutations have been implicated in Down syndrome, transient myeloproliferative disorder, and acute megakaryoblastic leukemia [66]. GATA-2 is broadly expressed in almost all kinds of tissues. The functions of GATA-2 and GATA-1 were overlapped for normal hematopoiesis at the yolk sac stage [67]. GATA—4 is expressed in heart, 18 intestine, and testis. GATA-4 was found to regulate cardiac morphogenesis by inducing N-cadherin gene expression [68]. GATA-6 is expressed in lung, liver, colon, kidney, and spleen. GATA-6, together with GATA-4 was required for adrenal gene regulation and development [69]. GATA-5 as well as GATA-4 and GATA-6 is expressed in heart and intestine, and involved in intestinal gene regulation [70]. GA TA-3 expression tissues GATA-3 was first identified in chicken, where it was found to be expressed in adult erythrocytes and also abundantly expressed in T lymphocytes and brain tissue [61]. Murine and human homologs (mGATA- 3 and hGATA-3) to chicken GATA-3 (cGATA-3) were expressed mainly in T cells but not B cells with a great amino acid sequence similarity (3 95%) among these three species [71]. mGATA-3 was also expressed in embryonic central nervous system, peripheral nervous system, kidney, thymus, placenta, inner ear, epidermis, lens fibers, whisker follicles, and in the primary palate besides the whole T lymphocyte differentiation process [62, 72]. GATA-3 has been found to be important for embryonic development, for example, the mutation of one GATA-3 allele around the zinc finger domain in humans generated the hypoparathyroidism, sensorineural deafness, renal anomaly syndrome due to haplo- insufficiency [73, 74]. 19 More important, GATA-3 was expressed in naive spleen Th0 cells at a very low level, inhibited in Th1 cells, and induced and constitutively expressed in Th2 cells differentiated from Th0 cells [75]. According to a conditional knockout study, GATA-3 was required for development and maintenance of Th2 cells in vivo and in vitro [76]. Thus, GATA-3 is a transcription factor specific for Th2 cells. GA TA-3 structure The mGATA-3 gene contains approximately 23 kb of coding region, 13 kb of 5’ promoter region, and 8 kb of 3’ flanking region [62]. It is composed of six exons with sizes ranging from 125 bp to 828 bp and five introns with sizes from 418 bp to 6.5 kb [62]. The functional domains of mGATA-3 protein are two zinc fingers (Cys-X2-Cys-X17-Cys-X2-Cys): (1) an amino zinc finger (N-finger) (2) a carboxyl zinc finger (C-finger), located in exon 4 and exon 5, respectively [62, 71]. Although both N-finger and C-finger are necessary and important for GATA-3 DNA-binding activity, they may have different specificities. DNase I hypersensitivity assay revealed that the C- finger but not the N-finger was essential for lL-4/lL-13 chromatin remodeling; however, the N-finger was required for lL-5 promoter binding and induction [77, 78]. Normally, the N-finger and the C-finger function together to recognize the GATA motif on the DNA target; however, the N- finger with two basic regions on either side can independently bind to the GATC motif without the help of the C-finger [65]. 20 The range of the GATA-3 promoter region has not been clearly identified. The enhancer region is located within 3 kb surrounding the transcriptional initiation site, including exon 1 and intron 1 [62]. A new promoter region (exon 1a), which is important for Th2 development, was recently identified approximately 10 kb upstream [79]. A silencer region, located around 8.3 to 5.9 kb upstream of the transcription initiation site was also found [80]. Astonishingly, a 625 kb yeast artificial chromosome (YAC), containing ~450 kb 5’ and ~150 kb 3’ flanking regions of GATA-3 contained insufficient sequence to support fully the tissue-specific expression of GATA-3 in thymus and specific neural crest-derived cells based on a LacZ reporter gene study [81]. Therefore, there are additional regulatory sequences that exist either further upstream or downstream of the 625 kb GATA-3 region. GA TA-3 in T cell differentiation GATA-3 recognizes and activates the human T cell receptor 6 gene (TCRS) through the GATA motif located on the TCR6 gene enhancer [71]. Similarly, GATA-3 binds to the GATA motif on the enhancer of other TCR genes, such as TCRa and TCRB [82, 83]. Furthermore, the GATA-3(-/—) embryonic stem cells failed to produce CD4/CD8(-/-) T cells in a CS7BL/6 complementation systems [84]. This evidence indicates that GATA-3 is important for T cell development. 21 Besides its function in T cell development, GATA-3 also determines the Th1/Th2 balance, and favors Th2 differentiation. GATA-3 was expressed at low levels in naive Th cells, induced dramatically in Th2 cells, but inhibited in Th1 cells [75]. Zheng and colleagues have shown that the expression of Th2 type cytokines (IL-4, lL-5, and IL-13) in Th2 cells was inhibited following antisense GATA-3 treatment, while the expression of Th2 type cytokines (IL-4, lL-5, and lL-10) in Th1 cells of GATA-3 trangenic mice was induced. Thus, they concluded that GATA-3 was essential and sufficient for Th2 cytokine expression in CD4+ T cells [85]. Furthermore, Zhang and colleagues have shown that GATA-3 and cAMP were necessary for lL-5 expression in a murine thymoma EL-4 cell line through the two overlapping GATA-3 binding motifs on the promoter of IL-5 [75, 86]. Based on the studies of ectopic GATA-3 expression in B cells and antisense GATA-3 treatment in Th2 cells, GATA-3 was sufficient for lL-5 expression, but not for lL-4 expression [87]. The study of retroviral transduction of GATA-3 into developing T cells has shown that GATA-3 was helpful but not sufficient for inducing lL-4 expression to normal levels [88]. According to studies of ectopic expression of GATA-3 in committed Th1 cells and DNasel hypersensitivity test, GATA-3 induced Th2 cytokine genes expression in Th1 cells and led to chromatin remodeling around IL- 4llL-13 locus [77, 89]. A conserved GATA-3 response element upstream of IL-13 was identified and might be important for GATA-3 binding, histone hyperacetylation, and activation of IL-13 expression [90]. Thus, GATA-3 22 may regulate IL-5 expression by directly binding to the lL-5 promoter, but regulate lL-4 and lL-13 expression by indirect chromatin remodeling. Besides inducing Th2 cytokine expression, GATA-3 downregulates Th1 cytokines (IL-12 and lFN-y) expression in developing Th1 cells through an lL-4 independent mechanism [91, 92]. Retroviral expression of GATA-3 in developing Th1 cells could block Th1 development by repressing STAT—4 expression, but had no effect on lL-12j32 chain or T-bet expression [93]. Thus, GATA-3 is a key player for T cell development and Th1/Th2 differentiation. GA TA-3 in asthma It is clear that the Th2 cells correlate with the asthmatic phenotype, such as AHR, eosinophil infiltration and elevated serum lgE. GATA-3 is critical for Th2 cell differentiation. Through regulating lL-5 expression, GATA-3 is associated with airway infiltration by eosinophils. GATA-3 is related to lgE synthesis via regulation of IL-4 and lL-13 expression. Finally, GATA—3 inhibits or even inverses the Th1 pathway by way of lL-12 and lFN-y expression inhibition. Thus, GATA-3 is an important determinant of Th1/Th2 balance making it a molecule of interest in the study of asthma. GATA-3 expression in the ainNay of atopic asthmatic patients was significantly higher than in healthy controls and correlated with AHR and reduced airway caliber [94]. GATA-3 expression after allergen challenge in the nasal mucosa of patients was also much higher than controls and 23 strongly correlated with the number of cells expressing IL-5 [95]. Since GATA-3 is required for the early stages of T cell and nervous system development, GATA-3 gene knockout in mice have defects of embryonic liver hematopoiesis and nervous system, with embryonic lethality [96]. To bypass this barrier, dominant negative mutant and antisense GATA-3 approaches were used. A GATA-3 dominant negative mutant (KRR mutant) was generated by site directed mutagenesis of the KRR amino acid sequence located between the N-finger and the C-finger [97]. Through the overexpression of this dominant negative mutant of GATA—3 in a murine model of asthma, the function of endogenous wild-type GATA- 3 was inhibited, which led to the inhibition of airway eosinophilia, mucus production, Th2 cytokines expression, and lgE synthesis in mice sensitized and challenged with ovalbumin [98]. Through a local antisense GATA-3 treatment in a different murine model of asthma, endogenous GATA-3 translation was blocked, which led to the inhibition of allergic ainNay inflammation and AHR [99]. Thus, GATA-3 is an important factor for asthma, as well as a potential point for asthma therapy. GA TA-3 expression regulation Although the genes regulated by GATA-3 have been extensively studied, the regulation of GATA-3 itself remains largely unclear. The IL4- induced STAT-6 pathway is the typical way to induce GATA-3 expression. The initial sources of lL-4 may come from cytotoxic (CD8+) T cells, natural 24 killer (NK) cells, or naive Th cells [32, 100]. Ectopic expression of STAT-6 could induce GATA-3 and c-Maf expression, and inhibit lL-12 82 chain and lFN-y expression in the absence of IL-4, which indicated that STAT-6 was upstream of GATA-3 [101]. Ouyang et al found a new STAT-6 independent GATA-3 autoactivation pathway that favored Th2 development in an IL4-independent manner [102]. This GATA-3 autoactivation might function through the binding of GATA-3 to a GATA motif located within GATA-3 gene [103]. The expression of GATA-3 by STAT-6 dependent or independent pathways can induce Th2 type cytokine expression and determine the Th2 differentiation. NF-KB p50 subunit deficient (p50-/-) mice could not generate eosinopilia due to their inability to produce lL-4, IL-5, and IL-13 [53]. Furthermore, CD4+ T cells from the p50-/- mice could not produce GATA- 3 under Th2 differentiating conditions, and the inhibition of NF-KB activity blocked GATA-3 expression in developing, but not committed Th2 cells, which indicated that NF-KB might be an upstream positive regulator of GATA-3 [53]. In a polycomb group gene (Mel18) disrupted mouse, the expression of GATA-3 and Th2 type cytokines were significantly reduced, which indicated that Mel18 might be a positive regulator of GATA-3 [104]. Repressor of GATA-3 (ROG) is a lymphoid specific and GATA-3 interacting protein. The overexpression of ROG inhibited the GATA-3 induced Th2 cytokine expression, and Th1 type cytokines as well [105]. Friend of GATA (FOG), a zinc finger transcription factor, might be another 25 repressor of GATA-3 because it blocked the GATA-3 induced Th2 cell development [106, 107]. Fetal liver zinc finger protein 1 (Fliz1) could repress GATA-3 expression in vivo and in vitro through binding to an intronic negative cis-acting element of GATA-3 [108]. Runx1, a transcription factor, might be another negative regulator of GATA-3 because expression of Runx1 in T cells inhibited the Th2 differentiation by repressing GATA-3 expression [109]. Transforming growth factor B (TGF- 13) could suppress Th2 development through inhibition of GATA-3 expression at the transcription level and Th1 differentiation as well. Thus, TGF-B was a general immune response suppressor [110]. The post-translation regulation of GATA-3 is also important for GATA- 3 activity. The increased phosphorylation of GATA-3 and Th2 cytokines expression is due to the activation of p38 mitogen-activated protein kinase by cAMP [111]. The acetylation of amino acids 305-307 (KRR) of GATA-3 was required for its activity because the mutation of these amino acids led to the dominant negative mutant [112]. Thus, while there are many potential mechanisms for GATA-3 regulation, the putative positive and negative regulators need to be further explored. 26 E. AIJ and C3HIHeJ mouse model for asthma Anima_l models The results obtained from human studies can be applied to human disease directly, however, humans are not laboratory animals precluding the use of many experimental techniques. Studying complex genetic traits in humans is even more difficult due to genetic heterogeneity, incomplete penetrance, gene interaction, phenocopies, and rarity [113, 114]. For asthma studies in humans, the availability of human ainrvay tissues, types of medications that can be used, and the difficulty of utilizing repeated invasive procedures in clinical studies are also limiting [115]. To avoid these problems, animal models are widely used in human disease research, as well as in asthma studies. Based on the phenotypic similarity to humans, animal models of asthma can be divided into three classes: animals that have naturally occurring recurrent ainrvay obstruction, such as cats and ponies; animals that have naturally occurring AHR, such as dogs, rats, and mice; animals that develop reversible ainrvay obstruction and/or increased AHR after allergen exposure, such as rabbits, sheep, guinea pigs, rats, dogs, monkeys, and mice [115]. Inbred Mouse models Although naturally occurring reversible ainlvay obstruction has not been observed in mice, they are still the most widely used animal model for asthma. There are many advantages to using inbred mice instead of 27 humans for genetic and physiologic studies. Inbred mice have genetic homozygosity (identical alleles) at all genetic loci and genetic identity among individuals. This largely reduces the problem of genetic complexity of humans and facilitates genetic studies. As laboratory animals, mice can be maintained in carefully controlled environments, eliminating the gene- environment interactions that confound the study of human complex genetic diseases. Inbred mice have a short life span (1.5-2.5 years), good litter size (~6-8), and early sexual maturity (~6 weeks), which means we can generate ample numbers of study subjects within a relatively short period. Furthermore, there is extensive information regarding mouse genetics and immunology, thus we can compare the mouse genome and immune pathways to those of humans. Finally, it is relatively easy to manipulate the mouse genome by means of creating congenic mice, transgenics, or mice with gene-targeted deletions (knock-outs) to further probe basic genetic mechanisms. One thing to keep in mind is that animal models are not identical to humans, so there are limitations that mandate care when applying these data to humans. However, information obtained from inbred mouse models is invaluable to reveal the common pathways of human disease [115]. 28 NJ and C3HlHeJ inbred mouse model The characteristics of human asthma include ainrvay inflammation, increased lgE level, eosinophil infiltration, and AHR. The AIJ and C3HlHeJ mouse model utilized in the current study has all these asthma-related phenotypes. Ainlvay hyperresponsiveness or hyporesponsiveness to acetylcholine (Ach) were observed in AIJ or C3HlHeJ mice, respectively, without allergen challenge. Linkage analysis mapped this QTL for non- inflammatory AHR to murine chromosome 6, including IL-5 receptor as a positional candidate gene [116]. Following an allergen exposure protocol (sensitize with ovalbumin (OVA) or phosphate-buffered saline (PBS) on day 0, challenge with OVA or PBS on day 14, and collect data on day 17), AIJ mice showed increased ain/vay responsiveness, increased lgE level, and eosinophil infiltration. However, C3HlHeJ had no airway responsiveness increase, much lower lgE increase and limited eosinophil infiltration after allergen exposure [117]. Among these asthma-related phenotypes, AHR was pursued in the current studies because it is an outcome that most closely mimics the clinical manifestations of asthma. AHR was determined in anesthetized mice instrumented to measure airway pressure and flow. The time-integrated rise in peak inspiratory pressure subsequent to intravenous acetylcholine challenge was calculated and reported as the airway pressure time index (APTI). [118]. Without OVA treatment, AIJ mice had higher APTI than that of C3HlHeJ mice. Following OVA treatment, the APTI of AIJ mice increased 29 sharply relative to that of untreated A/J mice. In contrast, no significant changes occurred in C3HlHeJ mice following allergen challenge. The APTI of F1 mice (AIJ x C3HlHeJ or C3HlHeJ x NJ) was intermediate to the parental strains and no changes occurred following OVA treatment [117]. To determine the inheritance pattern of allergen-induced airway responsiveness the frequency distributions of APTI were measured in C3HlHeJ, AIJ, F1, F2 (F1 x F 1), AN backcross ((C3H/HeJ x A/J) F1 x AIJ) and C3HlHeJ backcross ((C3H/HeJ x A/J) F1 x C3HlHeJ) mice following OVA sensitization and challenge [117]. AIJ backcross mice had a broad APTI distribution, almost covering those of AIJ and C3HlHeJ mice; therefore they were suitable for linkage analysis. Thus, to determine the chromosomal locations that contribute to allergen-induced AHR, a genome wide linkage analysis was performed in NJ backcross mice by using 164 microsatellite markers spaced at approximately 10 cM intervals [117]. Two QTL were found on chromosome 2: Abhr1 (between DZMit359 and DZMit416, with lod=4.2) and Abhr2 (between DZMit238 and DZMit298, with lod=3.7). The Gata3 gene maps within Abhr1 region. Since Gata3 is critical in Th1/Th2 differentiation and is related to asthma, it was chosen as the strongest positional candidate gene for Abhr1. Complement factor 5 (C5) is a positional candidate gene for Abhr2 and has been extensively pursued in related studies [119]. 30 F. Summary Asthma is a chronic ainNay inflammatory disease due to inappropriate immune responses to common environmental factors, which is characterized by AHR, infiltration of eosinophils, airway obstruction, increased lgE level, increase mucus secretion, and overexpression of Th2 type cytokines (IL—4, lL-5 and lL-13). The differentiation of naive T helper cells into Th2 cells is believed to be critical in asthma. Among many transcription factors involved in Th1/Th2 pathways, GATA-3 is a key player in driving the Th2 pathway and thus, may be related to asthma. A genome-wide linkage analysis was performed in NJ backcross mice ((C3H/HeJ x AIJ) F1 x A/J) revealed two QTL on chromosome 2: Abhr1 and Abhr2. The Gata3 gene maps within the Abhr1 region. Because of its location and function, Gata3 was considered the most important positional candidate gene for Abhr1. To investigate its role in allergen-induced AHR in our mouse model, Gata3 was studied at DNA, mRNA, and protein levels in this project. 31 Chapter Two: Fine-mapping of Abhr1 and Abhr2 loci A. Introduction Prior to the initiation of this dissertation research, two quantitative trait loci (QTL) for allergen-induced AHR were identified on murine chromosome 2: Abhr1 (between DZMit359 and DZMit416, with lod = 4.2) and Abhr2 (between DZMit 238 and DZMit298, with lod = 3.7). This was accomplished by means of a genome-wide linkage analysis for airway hyperresponsiveness (AHR) in 176 NJ backcross mice ([AlJ x (C3HlHeJ x AIJ)F1] or [(C3H/HeJ x A/J)F1 x A/J]) using 164 microsatellite markers spaced at approximately 10 cM intervals [117]. Based on the current understanding of the immunologic basis of asthma, GATA-3 was the most attractive positional candidate gene in the Abhr1 region. To more closely determine the locations of Abhr1 and Abhr2 relative to GATA-3, these QTL were fine mapped by genotyping more A/J backcross mice (n = 450) for additional densely clustered markers (n = 37) on chromosome 2. Many types of DNA sequence-based markers are available: (1) restriction fragment length polymorphisms (RFLP), based on the different length of DNA fragments following endonuclease digestion, (2) single nucleotide polymorphisms (SNP), based on alternate nucleotides at a single position, (3) sequence-tagged sites (STS), which are also due to the DNA sequence polymorphisms and can be identified through polymerase chain reaction (PCR), which include expressed sequence tag (EST) and microsatellites [120]. EST are a subset of STS markers that 32 can be expressed into mRNA. Microsatellites (or simple sequence repeats, SSR) are a subset of STS markers, with variability in the copy number of a tandem repetition of a short DNA sequence, usually 2 to 4 nucleotides [121]. They are ubiquitously distributed throughout the genome with high polymorphism information content, and are relatively easy to be analyzed by PCR. Furthermore, a comprehensive database of murine microsatellite markers has been characterized in 12 of inbred strains by the Massachusetts Institute of Technology (MIT) Genome Center (www-genome.wi.mit.edu). Primers for these markers are commercially available (Research Genetics, Inc, Huntsville, AL). Based on these attractive features, microsatellite markers were most commonly used for genotyping in this project. 33 8. Massachusetts Institute of Technology (MIT) microsatellite markers The Massachusetts Institute of Technology (MIT) Genome Center (www-genomewimitedu) identified 6,331 microsatellite markers, mapped on an Ob (C57/6J-Ob, an obese variant of C57 black mouse) x Cast (Mus castaneus) F2 intercross with an average resolution of 1.1 cM. The polymorphic repeats were characterized on a series of inbred mouse strains, including NJ and CBH/HeJ strains. Those MIT microsatellite markers located on chromosome 2 and with polymorphisms between AIJ and C3HlHeJ strains were chosen for fine mapping the Abhr1 and Abhr2 loci. Thirty-one MIT microsatellite markers met these criteria (Table 1). 34 Table 1. MIT microsatellite markers on chromosome 2 PCR anealing AIJ size C3HlHeJ IMarker Primers (5' - :g) temp. £C)(bp) lsize pr) DZMit355 (Forward) GTCTTCCTI'I'GGGTAGTTCTCG 56 142 147 (Reverse) AAATAAATGTCTGCCTCTTTCCC DZMit359 (Forward) GGATCTAGAGATACGTTACATI’CCTT 51 96 106 (Reverse) TGAAATCTAACTCTGGTTGAAAAGC DZMit1 17 (Forward) CCCAAAGAACATACATCAATGTG 55 170 176 (Reverse) TGGAGATGCATGTTI'AAAACTCA DZMit31 (Forward) ATTTGAAAAGACTGGACTCCTCC 56 140 136 Reverse) TGACTGGGAATAACCTCTCTGC DzMit416 (Fonrvard) CCGACATTTGGTTGTGTATACG 55 116 124 (Reverse) ATGTATGTGT‘I‘I’CCCATGTGTACC D2Mit6 (Fonrvard) AACAAACAAACCCCTTGCCC 59 124 132 (Reverse) CTCTAACACAGCCCCAGGTG DZMitBO (Forward)TAGCCTACAGAGTGGACAGCC 52 180 192 (Reverse) CTAGGCTTI'ATGTAGCCTCT‘ITGC D2Mit465 (Fonrvard) CCTI'GGGG'ITTTGATTACCA 55 122 128 (Reverse) TCTAAACTTCCCTGCCTCCC DzMit60 (Forward) TGCCAGACAATGAACTCTGG 553 148 150 (Reverie) AGAGGGTTCATCCTTGGAGG DZMit81 (Forward) ATGAGTI’CTGCGGGCACTAT 55 156 150 (Reverse) GCCCTACTAACTAATCAGAATGCA DZMit293 (Forward) TACACACTI'GGGATAAAGTAAGTGTG 55 194 180 (Reverse) A'ITI'CAGCACCT‘ITAGCCACA DZMit82 (Forward) GGACAATGGCTCTGGGTTTA 61-53 D 214 198 Reverse) GCTTTCTAACCTCAAGCATTAAGC DZMit417 (Forward) GTTC'I'TATTI'TACTGGGGTCATGG 55 128 122 (Reverse) TGGGTCACCTTAACAAGAATAATT DZMit152 (Fonivard) CACAGATCTI'GTAAGACCACGTG 53 107 113 (Reverse) TGCCATGAGTGTGGGACTAA DZMit235 (Forward) AGCACTGCCAACTGAGCC 52 126 120 (Reverse) TC'ITTCCCCAATI'TTGTI'TCC DZMit367 (Fonivard) GCCTGTGCTAAAAAAGAGGTG 55 162 149 (Reverse) GCCCTGAGAACTACCCTCCT D2Mit238 (Forward) ACCATCATTITTGAACTCCACC 57 153 135 (Reverse) ACGCATATGCTCAGGACACA D2Mit203 (Forward) CACAAA‘ITGCCCTCTAACTTCC 54 139 149 (Reverse) GAATCTI'TCCCCGGGATTAA 35 Table 1 (Cont’d). FOR I . . ' anealing AIJ size C3HlHeJ Marker Primers (5 - 3) term). LC)i(bp) rze (bp) DZMit298 (FonNard)AGGGGACGAAACTCTGGTTI’ 55" 128 124 (Reverse) AGCCAGGGCTACACAGAGAA DZMit323 (Forward) AGAATCCTAAGTGGTGGTTAGAGG 55 126 110 LReverse) ACCCAAAGT‘I’GTCTI'TAAGTACACA D2Mit182 (Forward) CTGAGAGCAAATCCCTCCTG 55" 147 151 (Reverse) GAGAAACAGATGAGTAGACCCCC D2Mit380 (Forward) CCTCAGGTCTGAAATGAGGTG 51 132 120 Reverse) AATGATGTGCATGTGCGC DZMit91 (Forward) CCATTCTTTGC‘I‘I'CTGTCTCTG 55 180 174 (Reverse) CCACCTTI'GCAAAATACATGC DZMit11 (Forward) CAAACCCCCAGCTCTCTCTT 578 232 226 (Reverse)CCATACCCAGGCTCCATCTA DZMit10 ForwardLCATCAGGAAACACAGGACCA 553 156 150 (Reverse) ACCTAACCCTAATGATGGGG DZMit63 (Forward) GCAGTCTACCAGGAGCAACC 53a 232 218 (Reverse) TGGATGTAGGCATGTGCCT DZMit307 Forward) AGTTCCAGGGAATGAAACACC 57 150 172 (Reverse) ACACCTCTGCCAACAGTGC DZMit451 FonrvartD CATTAGATAGACTGGGCAAGGG 57 116 142 (Reverse)TCCTCCCTCCAAACCCTC DzMit53 (Forward) GTGGACATTCCCTGAGAAACA 573 148 150 (Reverse) GGGGTI'TGATCAGCTCATGT DZMit113 Forward) CTCACGTGAGGGTCATGAGA 55 128 146 (Reverse) CTTCTCTACCTTCCTCAGAAGCC DZMitZOO (Forward) ATGGCCTCTGCTAAATGGTG 57 136 114 (Reverse) GCTAGCAGGAGCGTCATAGG a. Amplicons with small size differences (5 4 bp) between strains were amplified with incorporation of [a-33P] dCTP and separated on acrylamide gels. All other primer pairs were amplified without radionuclides and separated on agarose gels. b. Two-step PCRs were performed with two continuous annealing steps due to Tm differences within the primer pair. 36 C. Self-designed microsatellite markers Since the number of informative MIT microsatellite markers on mouse chromosome 2 was limited, more markers were required for further fine- mapping of the Abhr1 and Abhr2 regions. The Celera Database (www.celeradiscovervsvstemscom) was searched to obtain the genomic sequences of several genes (Gata3, Prkcq, ll2ra, Mrc1 and Gad2) located in the Abhr1 and Abhr2 regions. We focused on the most common microsatellites positions, which are normally located in the intron region of the genes. After identifying simple nucleotide tandem repeats (3 15 repeats), we designed primer pairs covering the repeat region, amplified the regions in NJ, C3HlHeJ, and F1 (C3HlHeJ x AIJ) mice, and compared the product sizes on 4.5% agarose gels. We were able to detect product size differences as small as 4 bp by this method. Clean products with different band sizes in NJ and C3HlHeJ strains were indicative of sequence polymorphisms in the target region. To conflrrn potential polymorphisms, we sequenced the PCR products of NJ and C3HlHeJ strains. For example, four pairs of primers covering four different simple tandem repeats regions of the Gad2 gene were designed and tested by PCR, one of the primer pairs showed a clear product size difference between NJ and C3HlHeJ mice. The PCR products of this primer pair were sequenced: the NJ product was 119 bp, with 16 tetranucleotide (CTTT) repeats, while the C3HlHeJ product was 107 bp, with 13 CTTT repeats (Figure 2). 37 (A)ACFACFACFACF | 1 | 2 | 3 | 4 | Primer pair # 119bp 107 bp (B) Primer pair # 4: CACATTGTAA AAGTATCQQT TGGGATTGGT TTTCTTTCTT r _______ (Forward primer) TCTTTCTTTC TTTCTTTCTT TCTTTCTTTC TTTCTTTCTT (CTTT tetranucleotide repeats) TCTTTCTTTC TTTCTTTAAG ATTTGCTTAT TTAATGTGA (Reverse primer) 38 (C) A/J C3HlHeJ GATC GATC Figure 2. Processes of identifying microsatellite markers in Gad2. (A) Four primer pairs within the Gad2 gene were tested in AM (A), C3HlHeJ (C), and (C3HlHeJ x A/J)F1 (F) mice. PCR products were separated on a 4.5% agarose gel. A strain-specific size distinction was apparent in primer pair 4, while smaller differences may be present in primer pairs 1 and 3. (B) The location of the forward and reverse primer in relationship to the target sequence is shown. The target sequence was based on Celera database. (C) Sequencing gel of the primer pair #4 PCR products of NJ and C3HlHeJ. NJ has 16 CTTT repeats, and C3HlHeJ has 13 C'ITT repeats. 39 Using the same methods, four other microsatellite markers were found in the intron regions of Gata3, Prkcq, ll2ra and Mrc1 genes (Table 2). Typically, among three or four primer pairs designed for each gene, one microsatellite marker could be identified. 40 Table 2. Self-designed microsatellite markers PCR annealing AIJ size C3HlHeJ Marker Primer pair (5’ - 3') temp. (’0) (bp) size (bp) Gata3 (ForwardLAGTGTAGACAGCGCAAAGT 56 192 196 (Reverse) CCTAGAATTCTATGGCTCCGT Prkcq (Fonrvard) GGCCAAGGAACTCTAAAC 51 310 322 (Reverse)TCCCACCCACAGAAATCATAC ll2ra (Forward) GATGCGGCATGGTCAG 53 315 311 (Reverse) CCATCCTAGCATAGGCG‘ITGT Mrc1 Forward) AAAAATCCAATAGAAGTI'TGT 51 318 31 3 (Reverse) ATATGTTCCTCCACATCTATC Gad2 Fonlvard) CACATTGTAAAAGTATCCC 44 1 19 107 (Reverse) TCACATTAAATAAGCAAATCT 41 D. Hemolytic complement (Hc) RFLP marker The murine H0 gene is an important positional candidate gene in the Abhr2 region. Its human analog is the fifth complement component (C5) gene. It has been found that a two base pair (TA) deletion in a 5’-exon of Ho results in C5 deficiency in AIJ mice, however, C3HlHeJ Hc has no such deletion and thus is C5 sufficient [122]. Subsequently, A/J mice have low 05 gene expression, C3HlHeJ mice have relatively high CS gene expression, as determined by microarray analysis [119]. A primer pair, based on the primer pair designed by Wetsel [122], was designed to amplify Hc genomic DNA that covers the two base pair deletion region (forward primer: 5’-CAA'ITAAAGCTAACTATAAGAAGGAT‘ITTACAA-3’ and reverse primer: 5’-CAAG'I'I'AGAACTAAGCACTAGCTACTCAAACAA- 3’). The 2 bp deletion in AIJ mice produces the endonuclease Bsgl recognition site. C3HlHeJ mice have no such recognition site and thus still have a single 210 bp product; the AIJ amplicon can be digested by Bsgl to form two fragments of 180 bp and 28 bp sizes, respectively (Figure 3). 42 (A) (BsgI cutting site) CAATTAAAGC TAACTATAAG AAGGATTTTA CAéCAACTGG (Forward primer) AACTGCATAC TTTGAAATTA AAGAATATGG TAATCTCTAA (BsgI recognition site & TA deletion site) TATTAATATA TTATTATAAC TAAGAGGGAT TTTGCAGTAC CTTTGGTATG ACTGGAAGTA CCAGAAGAGG GTGGGGGGAG ACAGATGTAC GTAGTCAEEG TTTGAGTAGC TAGTGCTTAG (Reverse primer) TTCTAACTTG (B) 123456789101112 ~~M~mw~~~~urwm 43 (C) FFFAFFAFFCAF / 210 bp \ 180 bp unassuming-nus... N ~—_. 4— 28 bp Figure 3. Ho genotyping (A) He primers, Bsgl recognition and cutting sites, and target sequence. (B) PCR products from 12 NJ backcross mice were separated on a 1.5% agarose gel. (C) Fragments after Bsg / digestion were separated on a 4.5% agarose gel. Strain specific product sizes were C3HlHeJ (C) = 210 bp, A/J (A) = 180 bp + 28 bp, and (C3HlHeJ x A/J)F1 (F) = 210 bp +180 bp + 28 bp. 44 E. Polymerase chain reaction-based genotyping Polymerase chain reactions were performed on 31 MIT microsatellite markers, 5 self-designed microsatellite markers, and the Ho RFLP marker. Since polymorphisms existed in these markers between AIJ and CSH/HeJ strains, the sizes of the PCR products differed between these two strains. The smaller PCR product migrates faster and the larger product migrates slower during gel electrophoresis, thus AIJ homozygotes (A), CSH/HeJ homozygotes (C), or AIJ and CBH/HeJ heterozygotes (F) were distinguishable by this method (Figure 4). Using the polymerase chain reaction-based genotyping method, 37 markers (36 microsatellite markers and 1 Ho RFLP marker) on chromosome 2 were genotyped on 450 NJ backcross mice with extreme APTI values (APTI < 620 or APTI > 797 cmH20.sec) (Table 8 and Table 9). On average, the 13 markers in the Abhr1 region (0 — 11 cM) were genotyped in 408 mice, the 16 markers in the Abhr2 region (11 — 40 cM) was genotyped in 343 mice, and each of the other 8 markers in more distant region (40 - 90 cM) was genotyped in 108 mice. 25 double crossover sites were found for all genotyping data (N = 11656) at rate of 0.2% (25/11656). Because double crossover sites may be the result of genotyping error, they were double checked by re-genotyping. Based on re-genotyping of these 25 double crossovers, 18 were reconfirmed and kept as original data, 4 were not sure and deleted from database, and 3 were genotyping errors and changed to the right data. 45 LFAFCFBFAFFFAABFFFFL A/ 124 bp 116 bp Figure 4. Genotyping microsatellite marker D2Mit416. PCR products were separated on a 4.5% agarose gel. Lanes identifiers are as follows: L = 100 bp DNA ladder, B = blank, A = AIJ, C = CBH/HeJ, F = (C3HlHeJ x A/J)F1. The AIJ amplicon is 116 bp and the C3HlHeJ amplicon is 124 bp. 46 F. Multipoint linkage analysis The data from 37 markers genotyped in 450 AIJ backcross mice were analyzed using MAPMAKER software [123, 124]. MAPMAKER/EXP 3.0 was used to perform multipoint linkage analysis on the raw genotyping data and to calculate the map order and map distance. MAPMAKER/QTL 1.1 was used to link phenotype with genotype and identify QTL by interval mapping and simultaneous search techniques (Table 9). Multipoint linkage analysis was also performed by the JoinMap 3.0 program [125]. The order, distance, and Iod score of the markers were calculated by the JoinMap program (Figure 5). Lod scores above 3.3 (P value = 1.0 x 10") were accepted as significant evidence for linkage; Iod scores above 1.9 (P value = 3.4 x 103) were considered as suggestive evidence for linkage [126]. The first QTL, Abhr1, was maximized at DZMit355 (2.3 cM, lod = 4.42); the second QTL, Abhr2, was maximized at DZMit238 (19.9 cM, Iod = 3.55). The interval of Abhr1 region was narrowed to about 1 cM (13 markers/11 cM). GATA-3 is located within Abhr1 region, with the Iod score of 4.26. MAPMAKER is a MS-DOS based program that can be downloaded without cost from the MIT Genome Center website. Chromosome cross- over positions are most clearly depicted in the MAPMAKER program (Table 9). JoinMap is a Windows-based program. JoinMap advantages over MAPMAKER include a user-friendly interface and superior graphics data display capabilities (Figure 5). Both linkage analysis programs are 47 based on multipoint interval linkage analysis. Comparing the results of these two programs, the relative position of markers and lod scores match quite well. 48 0.0 2‘3\:\~.,'\—« 29\,"\, 3.2 / 3.6 72.1 ifl/ 82. 6 {I 87.0 ’ 2'11]; .'-.' 1 1'1 it" 1 i1” .5, 1 11 r. , . I I‘l IO ,2 Gata3 DZMlt355 ,2 DZMit359 - _ DZMit1 17 ’j ‘ D2Mi131 [1,111,253 a 1,3 \ P rk c q fll2ra erc1 1 DZMit41 6 DZMit6 ‘iDZMit80 1.: readz 0211411465 ;, f’DZMit60 ll1rn D2Mrt81 13.2 3 r1 DZMit293 I l I‘ DZMIt082 2?” \g 0211411417 ” .,02M11152 If DZMit367 I ,‘ID2Mit238 l .1 D2Mit203 1,, 1'" C58 ’12: Ff [2), DZMit298 “‘ DZMit323 ” " DZMI't182 “ DZMit380 ’ r—I ., 021141191 1 l " DZMit11 DZMIt10 1”; {DZMI't63 ”&02Mit307 fDZMI't451 Iii DZMit53 \’ DZMit1 13 DZMlt200 LOD 2.0 4.0 6.0 oo—o ,- _, "".‘-—-". . ..... - ‘. .4‘—‘ “~._ '1‘" 0’ Abhr1 a Abhr2 i \. \\ \ ‘0. \ Figure 5. Mouse chromosome 2 genetic linkage map. The map was drawn using JoinMap program. Markers and their genetic locations are listed on the left figure, the Iod scores of these markers are shown on the right figure. G. Comparison of our linkage results to published linkage maps We compared our map constructed of 31 MIT microsatellite markers genotyped on AIJ backcross mice [AIJ X (C3HlHeJ X AIJ) F1 and (C3HlHeJ X AIJ) F1 X AIJ] with the MIT Genome Center map based on the same microsatellite markers (except D2Mit60, whose information comes from the Jackson lab) in an Ob (C57/6J-Ob, an obese variant of C57 black mouse) x Cast (Mus castaneus) F2 intercross mice. Overall, the order and relative spacing of our markers matched quite well with the MIT genetic linkage map (Table 3). Comparison between these two maps indicated that the markers within the Abhr1 and Abhr2 regions were particularly well aligned, with the exception of the distance between the most centromeric two markers, which was smaller in our dataset than in the MIT map. Indeed, our map was more detailed due to the large number of mice (n = 450) genotyped in the Abhr1 and Abhr2 regions, compared with that of the MIT map. For example, D2Mit359, D2Mit117, and D2Mit31 were distinguished at 2.9, 3.2, and 3.6 cM, respectively in our linkage map, while these three markers were indistinguishable at 7.7 cM in the MIT map. The inter-map alignment was not as highly conserved for markers in the more distal portion of chromosome 2, which may be due to the smaller number of mice genotyped (n = 108) through this region. The orders of two pairs of neighboring markers (D2Mit380 and D2Mit91, and DZMit11 and DZMit10) were inversed on our map as compared to the MIT map. 50 DNA markers can be classified into Type I and Type II markers. Type I markers are located within genes, while Type II marker are located outside genes. We genotyped 7 Type | markers in AIJ backcross mice: 5 self-designed microsatellite markers in Gata3, Prkcq, Il2ra, Mrc1, and Gad2 respectively, 1 RFLP marker in Ho, and the D2Mit60 marker that located in ll1m gene. We compared our Type I marker genetic map with The Jackson Laboratory (JAX) T31 radiation hybrid (RH) mouse mapping panel (www.iax.org). The JAX RH database integrates its RH mapping data with many other databases, such as the Whitehead Institute (www.wi.mit.edu), the MRC Mouse Genome Center (www.mrc.ac.uk), and Genoscope CNS (www.genoscope.cns.fr). Thus, the JAX map is a composite linkage map, with the data derived from many different experiments in different mouse strains. This likely contributed to the disparity we observed in marker order between our map and JAX, as two pairs of neighboring genes had reversed orders (Table 4). However, the relative map distances were surprisingly consistent for 5 of the 7 genes. Furthermore, our linkage map order is identical to those of the Celera and UCSC (genome.ucsc.edu) physical maps (Table 4). Physical maps are based on the absolute DNA sequences, therefore, they are the standards for the relative orders of markers. In contrast, genetic linkage maps are based on the frequency of chromosome crossovers during meiosis. Although the genetic linkage map distances between markers are relative and may vary due to the number of meioses genotyped, the relative 51 orders should align with the physical maps. Based on the conservation of marker order between our map and the Celera and UCSC physical maps, we believe that our genetic linkage map is accurate and is a valuable tool for genetic studies. 52 Table 3. Comparison of our linkage results with MIT linkage map Current study lMarker Lod score Linkagimap (cM) MIT linkage map (CM) DZMit355 4.42 2.3 2.2 DZMit359 3.39 2.9 7.7 DZMit117 3.79 3.2 7.7 D2Mit31 3.76 3.6 7.7 DZMit416 3.06 9.5 12 DZMit6 3.06 9.5 12 DZMitBO 3.06 9.7 12 DZMit465 2.64 10.1 12 DZMit60 2.52 1 1 .2 10a DZMit81 2.66 11.6 14.2 DZMit293 2.66 13.2 15.3 DZMit82 2.87 15.4 17.5 DZMit417 2.9 16 20.8 DZMit152 3.2 18.7 23 DZMit235 3.37 19.1 24 DZMit367 3.29 19.3 26.2 DZMit238 3.55 19.9 27.3 DZMit203 3.13 20.2 27.3 DZMit298 3.34 24.1 29. 5 DZMit323 2.25 31.5 31.7 DZMit182 1.28 36.6 38.3 DZMit380 1 .32 36.9 40.4 DZMitQ‘I 1.33 39 38.3 D2Mit11 0.86 43.1 42.6 DZMit10 0.54 45.2 41.5 DZMit63 0.43 58.3 54.6 DZMit307 0.44 62.1 61.2 DZMit451 0.38 69.8 73.2 DZMit53 0.14 72.1 84.2 DZMit113 0.07 82.6 87.4 DZMitZOO 0.04 87 97.3 a. DZMit60 is located within the ll1m gene. Subsequent to our data collection, D2Mit60 was removed from the Whitehead Institute website (www.wi.mit.edu). Therefore, its map location comes from the JAX database (www.jax.org). 53 Table 4. Comparison of our linkage results with Jackson lab RH map, Celera physical map, and UCSC physical map Linkage maps ch) Pthical maps (bp) Lod Current Marker score studt JAX RH Celera UCSC 6,795,337 - 9,795,868 - Gata3 4.26 0 7 6,815,972 9,815,813 8,093,753 - 11,110,400 - Prkcq 3.54 4.4 2 8,222,740 11,239,245 8,560,395 - 11,646,316 - Il2ra 3.55 5 6.4 8,608,396 11,696,658 11,132,506 - 14,231,672 - Mrc1 3.71 6.7 5 11,233,984 14,334,048 19,352,183 - 22,825,513 - Gad2 2.64 10.1 9 19,421,655 22,894,186 Il1m 21,056,292 - 24,603,317 - (D2Mit60) 2.52 11.2 10 21,070,434 24,617,939 31,677,653 - 35,256,298 - Hc (C5a) 3.5 20.5 23.5 31,755,923 35,334,364 54 H. Positional candidate genes Our genetic linkage map indicated that the Abhr1 region spans 0 — 11 cM and the Abhr2 region is from 11 — 40 cM on murine chromosome 2. Based on the Celera mouse database (www.celeradiscoverysvstemscom) and the Jackson lab mouse database (www.iax.oLg), there are approximately 200 genes located within the Abhr1 and the Abhr2 regions (Table 10). Based on their locations relative to the Abhr QTL and functions, several positional candidate genes were identified (Table 5). The Gata3 gene was prioritized and selected for further study based on its located within the Abhr1 region (Iod = 4.26) and its involvement in the Th2 pathway. 55 Table 5. Positional candidate genes on chromosome 2 Position Human Positional candidate gene (cM) homologue Functions PRKCQ TCR-mediated T cell Protein Kinase C, theta (Prkcq) 2.0 10p15 activation Macrophage Mannose MRC1 Recognize glycoprotein Receptor, C type 1 (Mrc1) 5.0 10p13 antigens Interleukin 15 Receptor, alpha |L15RA NK cells, CD8+ T chain (II15ra) 6.4 10p15-p14 lymphocytes development Interleukin 2 Receptor, alpha lL2RA chain (IIZra) 6.4 10p15-p14 T cells proliferation GATA3 GATA-binding Protein 3 (Gata3) 7.0 10p15 Induce Th2 pathway Interleukin 1 Receptor IL1RN Inhibit lL-1 signal Antagonist (II1m) 10.0 2q14.2 transduction Complement Component 8, C86 Component of complement gamma subunit (08g) 12.3 9q34.3 attack complex C5 Component of complement Hemolytic Complement (Hc) 23.5 9q34.1 system LCN2 Transport LPS and Lipocalin 2 (Lcn2) 27.0 9q34 formylpeptides Prostaglandin-endoperoxide PTGS1 Synthase 1 (Ptgs1) 29.0 9q32-q33.3 Synthesize prostaglandin 56 Summary To fine map the Abhr1 and Abhr2 loci, we identified 31 informative MIT microsatellite markers and 1 RFLP marker, and designed 5 microsatellite markers within 5 genes on murine chromosome 2, concentrating on the regions around Abhr1 and Abhr2. We genotyped these 37 markers in up to 450 NJ backcross mice and created a refined linkage map of murine chromosome 2. GATA-3 was located within Abhr1 region (Iod = 4.26), which is a strong positional candidate gene in our mouse model. Thus, further testing of DNA, mRNA, and protein of GATA- 3 in AIJ and C3HlHeJ were required. 57 Chapter Three: Comparison of Gata3 sequence in two murine strains A. Introduction According to the refined linkage map described in chapter 2, Gata3 is located within the Abhr1 region (Iod = 4.26) on murine chromosome 2. GATA-3 also has a tight relationship with the Th2 pathway and asthma. Thus, it was selected as the strongest positional candidate gene for allergen-induced AHR in our mouse model of asthma. To investigate the role of GATA-3 in allergen-induced airway hyperresponsiveness (AHR), the first step was to compare its gene sequence between AIJ and C3HlHeJ mice to determine whether DNA polymorphisms were present. Gata3 was sequenced at the MSU Genomics Technology Support Facility (genomics.msu.edu) using the fluorescence-labeled dideoxy method. Coding regions are translated to protein and variations in these regions are most likely to have functional consequences; therefore, we first sequenced the coding region. Furthermore, to ensure the sequence accuracy, we repeated the sequencing reactions of the coding region using the radioactivity-labeled dideoxy method. Because errors of splicing sites may lead to altered protein products, we also sequenced all 5’ and 3' splicing sites. Since the protein expression is regulated by the promoter region, we sequenced the identified promoter region. We also sequenced the 3’ untranslated region (3’ UTR), as it is involved in mRNA transportation and stability. 58 B. Gata3 gene structure The Gata3 gene contains approximately 23 kb of coding region, 13 kb of 5’ promoter region, and 8 kb of 3’ flanking region [62]. It is composed of six exons with size ranging from 125 bp to 828 bp and five introns with sizes from 418 bp to 6.5 kb [62]. The functional domains of GATA-3 protein are two zinc fingers: an amino zinc finger and a carboxyl zinc finger, located in exon 4 and exon 5, respectively (Figure 6) [62, 71]. The range of the Gata3 promoter region has not been clearly identified. The enhancer region is located within 3 kb surrounding the transcriptional initiation site, including exon 1 and intron 1 [62]. A new promoter region (exon 1a), which is important for Th2 development, was recently identified approximately 10 kb upstream [79]. A silencer region, located around 5.9 to 8.3 kb upstream of the transcription initiation site was also found [80]. Astonishingly, even the 625 kb YAC, containing ~450 kb 5’ and ~150 kb 3’ flanking regions of Gata3 is still not enough to support fully the tissue- specific expression of Gata3 [81]. 59 Exon 1a Exon1 2 3 4 5 6 r H 3’ UTR I—L Promoter A Silencer ATG Amino zinc Carboxyl zinc TAG finger finger Componen Size and characteristics ComponentSize and splicing sites Exon 1 189 bp, 5’ noncoding end Intron 1 420 bp, with GT....AG Exon 2 632 bp, with start codon (ATG) Intron 2 2.5 kb, with GT....AG Exon 3 537 bp Intron 3 5.5 kb, with GT....AG Exon 4 146 bp, with amino zinc finfir Intron 4 6.5 kb, with GT....AG Exon 5 126 bp, with carboxyl zinc flgge Intron 5 4.5 kb, with GT....AG Exon 6 802 bp, with stoLcodon (TAG) Figure 6. Gata3 gene structure. The size and characteristics of Gata3 exons come from published sequence [62]. Intron sizes and characteristics are based on the Celera database (www.celeradiscovervsvstems.com). 60 C. Sequencing of Gata3 Primer pairs were designed for the coding region based on the sequence published at www.ncbi.nlm.gov (entry number: NM_008091). Primers for the promoter region come from BALB/c mice Gata3 sequence published by George KM [62]. The primers for the introns, 3’ UTR, and the remaining regulatory regions were based on the sequence of 129X1/SvJ, 129S1/SvlmJ, DBA/2J, and AIJ strains from the Celera database (www.celeradiscovervsvstemscom). In total, 24 pairs of primers were designed to cover Gata3 exons, splicing sites, 3’ UTR region and parts of the promoter regions (Table 6). 61 Table 6. Sequencing primers for Gata3 (Reverse) AGCCAGGGCAGAGATCCGT 3716 Product Primer pair (5'-3’) Position size (bp) (Forward) CCCACCCGGTCCAAC Exon 1a, -9371 to ~8753 619 Reversg ACCCCAAG'ITCTGCTAGCTC (Forward) CCTCCAGTTCCAATATACCA Silencer, -8307 to -7212 1096 (Reverse) CCCTTCGGTCCTACTCAC (Forward) GGAACCCAACCCGTACCTT Promoter, -4566 to -3559 1008 (Reverse) ATTI’GGAAGCCCTGATTGAA (Fonivard)CGGAGTCAGGTTCGGGTTGTT Promoter, -3674 to -2943 732 (Reverse) TCCGGGCCTCGT‘I’AAG (Forward) AGGCAGCAGCGGCAACA Promoter, -3130 to -2462 669 (Reverse) TCCAGCCTGTAGGGGGTAWT (Fonivard) GCGGACCGGCTGGGAATTAC Promoter, -2507 to -1929 579 (Reverse) CTAAAAGGCCCGGGATTAAGA (Forward) GAAGCTGTGAACTAGGGA Promoter, -2043 to -1600 444 (Reverse) CCCCTI'TTACATCTGATCTT (Forward) CTGGCAGCTTGA'ITGG Promoter, -1816 to -1308 509 (Reverse) TTGGCTITAGAGGGTTACTG (Forward) GAAAGGGCTTGTCGGGAATC Promoter, -1413 to -938 476 (Reverse) TGGACCCAGCCGCAACTTC (Forward) CCTCTCTACTGGGCGTCTTC Promoter, -1045 to —625 421 Reverse) CCGCGTTATTGTTATGGTCT (Forward) CATCGCGTTGTCACTAAGGTC Promoter, -757 to -344 414 (Reverse) CATTCGGGCTCAGTAGA‘I‘I’ (FonNard) GGCAGCCGGG‘I‘I’TCACTCGTA Promoter, -389 to 143 532 (Reverse) CCCGGTCAGATTGCGTAGCTC (Fonivard)GGCGCGGATGACACTAGAAC Exon 1& Intron 1 (5' splicing site), 571 (Reverse) CTGCAGGGCCGACTCAC -50 to 521 (FonNard) CTTTTGGAGGATTTGTAGTG Intron 1 (3' splicing site), 326 to 490 Reverse) TCTTTGCGGGATAG‘ITTAG 815 (Fonrvard) CCC'I'TGCAGGTGATCGGAAGA Exon 2 & Intron 2 (5' splicing 696 (Reverse) GGACCCAGGAAAACAAACGC Site), 601 to 1296 (Forward) ACCACGTCCCGTCCTACT Intron 2 (5’ splicing site), 1173 to 252 (Reverse) AACTCTCCCAACCAGCGACAC 1424 (Forward) CTGGGCCT‘I‘I’CGTC‘I‘TAGAGT Intron 2 (3' splicing site), 3391 to 326 62 Table 6 (cont’d). Reverse) AGCTCTCCACCGCATGTC Product Primer pair (5’-3') Position izejbp) Intron 2 (3’ splicing site), Exon 3 & (Forward) GCTCTCACTGCGGTATTCT Intron 3 (5' splicing site), 3580 740 (Reverse) AGCCCTCACAGAGACCCTTAG to 431 9 Intron 3 (5' splicing site), Exon4 & (Fonrvard) ACGCTTTCCTTCCCTAAGTGA Intron 4 (5' splicing site), 9643 to 434 (Reverse) AATTTCAGAAGCGATITAACC 10076 Intron 4 (3' splicing site), Exon 5 & (Forward) AGAAAGAAAGTTCGGTAT Intron 5 (5' splicing site), 15121 538 Reverse) ATATAATAAACTCAAGCCTAC to 15658 (Forward) AGGAAGAAGAGGCAATCAACA Intron 5 (3' splicing site), Exon 6, 468 (Reverse) GGAGGAACTCTTCGCACAC 19833 to 20300 (Forward) ATGCTGACCACACCGA Exon 6 & 3' UTR (poly A tail), 845 (Reverse) CAATTACAGGGACTGATTCAC 20152 to 20996 (Forward) GGGCAATGGGTGTGTGATCTC 3' UTR, 20910 to 21561 652 (Reverse) GCCGTCACGTTGATACAATG (Fonivard) GCCCCTGTGTGTTCTGTA'ITA 3' UTR, 21438 to 22295 858 63 Sequencing was performed either by radioactivity-labeled dideoxy method, using the Thermo Sequenase Radiolabeled Terminator Cycle Sequencing kit (Figure 7) or by fluorescence-labeled dideoxy method, using the ABI Prism BigDye Terminator Cycle Sequencing Ready Reaction kit (Figure 8). A total of 12,069 bp were sequenced in both AIJ and C3HlHeJ mice (Figure 9). Some important sites related to the Gata3 gene are indicated in Figure 9 and described here: (1) Position -9371 to - 8753 is exon 1a [79]. (2) Position -8307 to -7212 is the silencer position [80]. (3) Position 1 is the starting point of exon 1 [62]. (4) Position 1004 to 1006 “ATG” is the start codon. (5) Positions 1 to 189, 610 to 1241, 3668 to 4204, 9687 to 9832, 15372 to 15497, and 19957 to 20758 are exon 1, 2, 3, 4, 5, and 6 respectively. (6) N-terminal zinc finger is in exon 4; C- terminal zinc finger is in exon 5 (shown as QXXQ ......... QXXQ). (7) Positions 190 to 609, 1242 to 3667, 4205 to 9686, 9833 to 15371, and 15498 to 19956 are intron 1, 2, 3, 4, and 5 respectively. (8) Positions 190 to 191, 1242 to 1243, 4205 to 4206, 9833 to 9834, and 15498 to 15499 “GT” are the 5’ splicing site for intron 1, 2, 3, 4, and 5 respectively. (9) Positions 608 to 609, 3666 to 3667, 9685 to 9686, 15370 to 15371, and 19955 to 19956 “AG” are the 3’ splicing site for intron 1, 2, 3, 4, and 5 respectively. (10) Position 17346 to 17537 is the microsatellite marker for Gata3 in intron 5. NJ = (GT)26, C3HlHeJ = (GT)28. (11) Position 20239 to 20241 “TAG” is the stop codon. 64 A microsatellite marker was found on intron 5 of Gata3 (Figure 8). No other sequence polymorphisms were found between AIJ and C3HlHeJ mice. This microsatellite sequence contained (GT)26 in NJ and (GT)28 in C3HlHeJ mice. We developed a PCR-based marker for this microsatellite, which was used in genotyping experiments to determine the Gata3 position on the refined linkage map. However, this microsatellite is not likely to be functionally important for regulation of GataS gene expression. 65 v: AIJ " ' ' ” ' cslHéJ Figure 7. An example of a Gata3 sequencing gel. [or-33F] dideoxynucleotide (ddNTP) chain termination sequencing was performed. PCR products were separated on polyacrylamide gel. Both AIJ and C3HlHeJ mice have the same sequence and read as 5’-GCAGTTCATGGAGATCTTGTGGCACTGTGTG GTCAGATTGCTI'TACCAAGTAGTGATGACA-3’ 66 UEUEUUUE Dow om. cm on 00 L .1... .. ‘4ll. I /mq\ Guru-FEED UEEWFi—iw Ui—uiPnUme—FUGU LIEUiFi—u. "UM-EU mun-[PU “HUI—1U E: F PEI—.82 67 .859 £2 m 8:5 E .3sz 9:62.390? scrimo Amy ©ng 53> m co._E_ E .9.sz 9___9mmo_o_E 2< ago 0059: >636 Uo_mnm_-mocoow90:= 9: 9.6: 80533 mm; m 5:5 «.660 .9366 so camaoumEoEo 96538 862.9% 06 29:96 c< .m 93mm 68 Figure 9. Gata3 gene sequence of NJ and C3HlHeJ mice -9400 XXXXXXXXXX ~9360 CAACTCAGTT -9320 TTGCAATTCC -9280 CCTCCTCCTA ~9240 CTACACTGAG- -9200 GCAAGGATTC -9160 GCCTGGCTGA -9120 GAGCGTCAGC -9080 TCAGATCTCC -9040 CAAAAACCAA -9000 GGTCAGTGAG -8960 CTTCTCCTTG -8920 CCGCCATGGG -8880 ACCCCAGCCC -8840 TTGGCTTTCT -8800 GTGTGTGGAT -876O CTTGGGGT ~8320 XXXXXXXXXX -8280 ATAGAACACA -8240 CACACACACA -8200 AAGGAGAGTC -8160 GCTTTATTAT XXXXXXXXXX TCACACACCT CTCCCTCCCC CCCCTTTGCA CCAAGGGAGG ACATCAGCCA GATGCAGTGA AACAGTGAAG AGCAAGGCGG ACCAGCTGGC TACATAGCTA ATTCCCATGG GATAGCTGCC TTTATTGTTC GCAGTGACCT GCCCTTGTTT XXXCCTCCAG CACACACACA CACACACAGG TGGTGAATCT TTTTTTTAAA XXXXXXXXXC CTGATGTGCG CTCCTTCTTT ACCCGGAAGA CAGAGGGGAG GGTTTTACCT AGCAGCCGCC TCTGCCTGTC GTGGAAAAAA CTTCAGGAGA TCTCCTTTTC CGAGAATTAA TCTGAAAGAA TTTCTGGGCA TGGGTGATCA GGAAGAAGGA TTCCAATATA CACACACACA ATAATGTTAA GAGATATGAG GGCGATTTCT 69 CCACCCGGTC GTTTGTGTGT\ CCTCCTCCCC GCTCTGCTGT GGGGCTCTTA CTGGCTGGAA GCTGCTGTGG ATTTCTACCT AACAAAAAAA GAGCTGCCCT CTCTGTTATC GAGGAGGTCT AGTGAACCAG CTGGAAGTCT TGGTGTGGAA GCTAGCAGAA) CCATTCAGAA\ CACACACACA AATGCAAGGA CAGAGCCGTT TTAATAGAGCJ (Exon 1a) (Silencer) -8120 -8080 -8040 -8000 —7960 -7920 —7880 —7840 -7800 —7760 -7720 -7680 -7640 -7600 —7560 -7520 —7480 —7440 —7400 —7360 -7320 -7280 -7240 AGGGTAACAA AATGAAGTAG TAGTTCCATA CACCAGGACC CTGAAGGGGG CCTCACTCTT GCGGCAGGTT TCGCTATATG CAAAAATGTT ATTTCTGTCC GAACTCTGTT GAAGGCCCAG GCCTAAGGTT AATAGCATGC ATTGGTCTTT CTGTTACAAT CCTTTATTTC GTGTAGTGGG TGCAAGCCTT CAATTGCCCA GGTGTATGGA TTGTGTGCCC ATTCTGACCC ACTGACAGGT CTGTGCCCGC TTTTTTGACA CTGAAATCAC ACAAATAATG CCGCAGTGGT ATTTCTAAAC TGGGGAAGAG CTCTATCAGT TGCTAGAACA TACTGATTGA CTTCAAGGTT TCTGGCTCTG ATGGCAGTGG GCTAGCAGCC CCAAAGCCCA CTATGTTGAC GTTCAGGCAT AGGACAGGTA AAGCCACACA AGTCCTAAGG TGCAGTGAAG CGTGAGTAGG GTGATTCCAT TGGACCCCTT TCTCCTCCCC AGTTTGAGAG AAGGTACCCT GGTAGTGGGC AAGAAGCTTG GGCTTCCTAT TTGCACTAGG AGACTCATGC TTTAGCATTA CAAGCCAGTG GGACACAACA TTGACATCAC CCAGATTCTC GGGCAGGCGA TCTGCCTTCT AGGTGGAGTG GTGTCCTTCT GAAAGGCCAA CTTCCATCTT ACTTTGATAG ACCGAAGGG 7O CCAGAATAGG GCTGTAGGTG TTATAGACCA ACCCAGAATT TTGTGCAGCC TGTCCCCCCA GCTGCCCAAA AAAATGAGAA TCTAGATGTA AGGCATCAAT GGATTTAGCA GCTCAATGCG GGGCATAGAG CTTCTACATA TAGTCCTCTT TCTGCATTTT TGCAGAAAAT AAAAGATGGG GTGTGTTTGC GGAAGTTGCA TTTTGACAAT AGAAATAAGA ooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo (Silencer) (cont’d) -4600 -4560 -4520 -4880 —4840 -4800 -4760 -4720 -4680 -4640 -46OO —4560 -4520 -4480 —4440 —4400 -4360 -4320 —4280 -4240 —3800 -3760 -3720 -3680 XXXXXXXXXX CAACCCGTAC GGCCTGCATA CACGGAATCG TCGCTAATTG CACCCAATTA CCACCGCCCC CGGGTTGTGA TGGATACCTC GACCACGGTC ATGGAAGGAA TTTCCCTAGT TTTAATTTCT ACCTCCCAGC TAACCGCGCC CCGGGAGGAG TTTTCCAGCC TACTATTCCG AACACGCTCA TTTCTACCCC CCCCCGGGGT GCGCTCAACA AGCATCTTTT CTCTCTCGGA XXXXXXXXXX CTTCACAACC TCGCAGAGCC AATTAAACGC CTTCAACAAT AAGGTCCCGC GCTTCCCTAG ACCGGTGGTA TGCCCTTCGC TTTTCACTTC GATTGATCGA CCTTGGGTCG GGCCTTCGGT CCTTCAGGTT ATCAGATCCG GGACAAGGCA TGCAAACATT CTTGCGCTCG AATGACAGCC TGCCCAGGAT TTGGCTTTGC AACCCCCCCC CGCATCTCGG GTCAGGTTCG XXXXXXXXXX AGACCCTCCG CGGGCGGGGA ATCTCGGTGG GGCCACTGTT GCGGTCTCCC TCCGAGGCGA AGGGGGTACC TTCCTTCCCA GTTTTCTATT GCTGGAATGG TCGGGGTCCC GCTGCTCTGC CCGGGCTTCA CCCAGGCCGG GCACGCCCCG TGCTGCCTCT GCGTGCAAAG CTAGGCATTC TAGTAACTAT AGGTCACTCT ACCCCCGCGA CCCCGCGGAG GGTTGTTGAC 71 XXXXGGAACC GGTTATCCCA TTGCAGCGTG TTATTGTCTC AAAACGGATA TGGGTTCTCG TGTAGACCTC GGCGCCGGCC GACGCACAGC AATCAATCGC GAAGTGACTT GGGCTGTGAA TTTCTCCCCG CTTCAGTCGG CGCCTTGGCT CTCCGCTTCG AGGAGAATCC TCCCTAAGTA CGAGGCACGC AGTACTTCGA CTGGAGGGCT CCCCCAAAGT CTCGCCTGGT TCTGGGTGGA (Promoter) -3640 -3600 -3560 -3520 -3480 -3440 -3400 -3360 -3320 -3280 -3240 -3200 ~3160 -3120 -3080 -304O -3000 -2960 —2920 -2880 -2840 -2800 -2760 TTTCTACCTT AATCACTCGC ATTCTGAAGG GGGTCGCCCT GGGCAAGTGT GTGTGTAGGG ATAGAGTAAG GGGCACACAT GCCTCAAGGC GGCTATCCAA GAGCCTTTGC GAACCGTAGC GCCTCATGAA GGCAACAGCA CCCAGCTCCG GGTACACCGA GGTGGTGGCA CCCTTAACGA CTGAAGGATT CCTCCCCTCC GGCCTGCATT TCCTGGCCCA CCACGCGCCG CTGGGTCCAT TAAACCTTTT GGACCGGTTG AGTGAAGGCG GTGTGTGTGT GGGTGAGGGG TCAGATCCAT ACCCTGCTCA CTGGGTTTTC GTACAACAGC CTGCTCCGCT GTTCGTCAGC CTGCAGGAGC TTCTCCTTGA CCAGATGCTC GCCAGACCCG CCCCAGGTCT GGCCCGGATC GGGACCACCT CCCACCACCC TGCGAGCAAG GACCCCCGGA CAGCCTCTCC GGCCCCAAGT TTTTCAATCA TGTCTACTTC AGTGGGAGGG GTGTGTGTGT TGTCTCAGCT TTCTTACCCT ACTTGACGCC AGATAGGCCA CCCAGATCCC CCAGATGCTG CCCTTACCCT CAAAGACTCC TGGCTTTCTC CAGGGGAAGA GTGTGCCTTG TTAAGGGGGC AGCTTTGTAG TTCCCTCCGG GCCAAGGGAA GCGGGTCAGA GTCCAGCTCT GGACTCGATC 72 GATGAGGCCC GGGCTTCCAA TAGAGGGATG ACCTGAGGAT GTGTGTGTGT TACTCCACGC TTCCCCAAGA TCCAGCAGCA AATTGACTCC GGTTCTAGCT AGTCCCCAGG ATAGAGAGAG AGGCAGCAGC TTGCCTTTCC AGGGGAATGC GGGTTGTGGT ACCCAGACGTa CTCTCTGGAA CCTCAAGCCC GAGGAAGCCC CCGGCGCCTG CCGCCTCAGG CCTTCCCCCT (Promoter) (cont’d) -2720 —2680 -2640 -2600 -2560 -2520 -2480 -2440 -2400 -2360 -2320 -228O -2240 -2200 —2160 —2120 -2080 -2040 -2000 -l960 -1920 -1880 -1840 -1800 TCTTCCCGGT TCCGGTATCC GCTCTGTGTT ACCCAGTGTG CAAAAGAGCA TCCGGGAACA ATACCCCCTA CCTCAGGCCC TCAGACCTGG GGGAGGGGAG GATTGAATTA ACATCTATTA TTTCAGAAGT CTAAGCCGTA CAGCTTTCTT TTAAAAAAAT CGGGACCAAA GCTGTGAACT TCATGAGTGA CTCATTCTAG TGTGTGCGGT GTGAATGTTA GAGCGCCGTG CCCAGGAGAG GGGTCTCGGA CCCTCCTCTC TCTGACTCTG GCGTCGGCGA ACGTCCTCTT GGGGCGGACC CAGGCTGGAT CCTACCCCTC AGGGGCCTAT TGTCTTTGCA AGACGAATAA GAGAGGCGCC ATATTCTTTT TAGACTAACA TCTTGTCTCC TATTATTATT GAGATATGCT AGGGACTGGC TACAGCAATA ATCTTAATCC CTTCTCTGCT GACAGCAACT AGCTGGAAGA ATGGGTTGGT GCCGACCTCG TTTTTCCCTC GGGCCGGCCC GACTGGCCGG TCCCAATTAC GGCTGGGAAT CCAGTGCCCG TCTGCCAACC TAGATATTTT TCCAGTCTAG TCCTCTCCAT CCTACTAGGG TCAGTCTTTA TGTTCAGTTC AGAAGGATTT ATCATCTACA TACTCGAGAC TGACTGATGC GTATTTTTCC CGGGCCTTTT TGTTTATGGA AAATAATTAA GATGCTGGCA CAAAGAGTGA 73 GCCCTCCCTC CCCCTCCCCT GTGACGTCAA CGCGGGCCAT CCACTGTCAG TACATGTTAA GGGCGCCTAG CTAAACTACC GTTTTTCCAA CTCCTCTGGT CCCCACTACT AAGCCATCCT AAAATACGTT TTGGCGTCAG CTTTTGCGCA TCTCGGTGCC TTTTCTCGAA CTTATACAAC CTTTTAAACT AGCAAAAATG ATGGTTTCCG AAGGTTTTGA GCTTGATTGG AAGTAAAAAA (Promoter) (cont’d) -1760 -l720 -1680 -l640 —1600 -1560 -1520 -l480 -1440 -1400 -1360 ~1320 -1280 -1240 -1200 -ll6O -1120 -1080 -lO4O -1000 ~96O -920 -880 ATCGATATTC CCAAGGGGTG GTTTTTAAAA ATTCAGCCTT GGGGGGGTGT GCACATTTCT TTGTAAAAAG GGCTTCAAGG ATAGAAGAAG GGGAATCCAA AAAGAAATGA CCTCTAAAGC AACACCTCTT TTCGGACCTT GCTGCAGAAA AAAGGACGGA CGGGGCGACT GGTCCTTACA CTACTGGGCG GGCCCTCCCA CAGGGAAGTT GGATATTATA AATAAAGTAG TAAGACTGGG CAGGGTGAAC AAAAGGTATC GATTTCAGTC CAGGAGAAGC AAATAAATTT AACGCACCTT TAGATATTGA TTACTTGGAA GTTTTGAATA AGAGGGGATG CAAGCTCTCT ACACTGCCCT GCTCATCCGG CCTCAACGCC ACAGGGCCGC GCGGCCCGGT AATGGCCCCG TCTTCCAGCC CCAGACCCTG GCGGCTGGGT GAGGGGACCG CACCCCGAGC CCGCCCTCAT TCAGAAGGGA TTCGTAATTT AAAGATCAGA TCCAAACCCA TGTCTTCTTC CCCTCTCCCC TGGCTTTTCT CTTTTAAGAA AGTGGGAAAT ACGCCTTCAG GCCCTGGAGG GGGGTGCACC GCAGTGTTTT ACTAGGGGAT AGAGGTTGGA CGTGGTATCT CCCTCGTCCG TCTCTCCTGT TCCCAGAGAC CCACCCCGGA TTTTCCTCGG TAGGCGAAGA 74 AAACGTGGGA GGGAAGACTC GTATTTAGAA TGTAAAAGGG AGCCCGCAGG AAGGGTTGTA GCACTCCACT CCACAGTAGA AGGGCTTGTC ATTATGGGGT TTCCAGTAAC GTGGAATGGG CGAAGTCTCT CTGGACCCAG GCAGTGACTC GCCCGTGGGG CCCGATGATT' CCCAGCCTCT GTCAGCTTGC CCAAAATGTC GGTCAGGGTT GTGAAAGCAG GAAAAGTTAG (Promoter) (cont’d) ——£34IO —-E?C)C) ——'7 65C) -—'7'22(D *“l +£¥l +81 GCTATCGCAG CGGGGACCAG ATGCATCGCG GATATCATTA GCTGTTCGTT CATAACAATA TCCGCGCGAT GCAAATCTTC GTTTTACATG AAACGTTCTG TTTTAAAAAA TTTATGAATG TCTACTGAGC GGCCAGAGAG CAAGCCCGGG CTGCCCTAGG TAGAGGGGCG TGGGGGGGAT GGGTTTGGGT CCTCCTGCCA ACACTAGAAC TGCGAACACT 4 exon 1) GAAAGAATGC GGAGAGGAGA CAAAGATCAA GTTAGTTGTA TGAGCCTAGG TCTCGCTAAG TTGTCACTAA GGTCAAAAGC GATCCGAAAA AGACAGCTGC CTGGAGAGGT TTGGGAAAGC ACGCGGGCGT CCGAATCAAA TCAGCAGCCT CCCGGAAAGC AGTTACTTCG CCATGAAACT CACATAGCCC CTAAGCTGAT GCTTGAATCC TAATTTAAAA GTATCGAAAA GTCTGCTTAT GGGCAGCCGG GTTTCACTCG CCGAATGAAT CGGCTTTGCT CGAATTCCCT CCTGCCTGTC CGGGCCTCGC CCACCCTGCC CGGCCCTTGG CGGCGCCCCT GGAGGAGGGG CGGCGGTGTG GGGATGGGGG TGGAGGTGAA TGCAGTTTCC TTGTGCTGAG GCGCCAGGCT CCTCCCCCTC CTCCTTAAGT TGCGTCGCGC GAGCTGCCTG GCGCCGTCTT ATTCCCTGTA AAAAAAAAAT AAGAGAGAGA GACTGAGAGA 75 CACGGTACTT CCAGCTTTTT ACACATTGAT AACAGCTGAC AAGCAGAGAC GCCCAGGTCC TGGTTCGGAG TTTCTAATCT ATAAACTGAA GTTTGCTCAT GGAAATTAGC TACGGAATAA ACATTTAAAG CCCTCTGCCC CGCGGCCCCT TTCCGGTCAG CCGGGGTGGG GTCCTGGAGC GATCGTGTCC. GGCGCGGATG CACAGCTGTC GATAGTTTCA ACTGAGAGAG GCGAGACATA (Promoter) (cont’d) (Exon 1) GAGAGCTACG CCTCCTCCTC GACTTGTGAC CCCTCCTCTT GGTTTGTTTG TTCTCCTTTT GGGCCGGTGT ATTGCTTAGT GGAGGTGTGC TTCGCGTGCG GGAAGCTTGC GTTAAAAGTT CCCTTGCAGG (intron 1 ‘AAGGAATCAG CTCCCTCCTT TCCGTGTCTG TTCTTTTCTT ACTATCCCGC TTTTTGCTCT CATTAAACGA CCGCGGACCT AGGGTTCCGG GACATGGAGG M E CAATCTGACC TACGCTCCTT TTTTTTTTTT GGAGGGACTG TTTGGTTTTT GGAGGATTTG CCTCCAGGGA CAGTCCTGGG TGCGGAGCTT TGTGCACGTC GAAGACCTAG CTTACACCTC TGATCGGAAG exon 2) TGTGCAGTGT TTTTTTTTTT CTTTTTTTTT TTTCTTCTTT AAAGATTTTT CCTTTTCTAT CCCCTCTCCT CCCAGGCCGA GCCGGGCGAG TGACTGCGGA V T A D GGGCAGGTCA GCTACTCAGG (exon 1 ‘ TTTTTAAGTT TTTGTGTGTG TGTAAACTAA TAGTGGTTGG GGACTTGTCC CTCCTGCGAG GGCTTCTTTC CCGGGTGAGT TGCCCTCCAG ATTCAGGTCT AGCAACCGTC GGTCACACTC TTTTTTGACC GGGGGGGGGG CCCTTCCTTT CTTTCCTCCC ACCCTTAACT GGGCCTCCGA CAGCCCTCCC AGGGCGCGAG CCAGCCGCGC QPR 76 CACGCCTCCT TTGGTATTGT intron 1) TGATATCACT\ TGTGTTTGGG AAGCTCAGCT AAAGATCCTG CCAAGTTTTA CCTGGCTGTC CCTCCGGGTC CGGCCCTGCA AATTTCAGGT CTCTTTCTCT TCTGAGCGCC GGATTCCTCT CCTTTATTCC ATCGCCCTCA CTTTTGCTAA TAAACCCTCC GCAAACAAAC CGGCAGGAGT TCTACCCGCG CACAGCCGAG TGGGTGAGCC W’ V S (Exon 1) (cont’d) (Intron 1) (Exon 2) (Start j codon) +1 04 1 ACCATCACCC CGCGGTCCTC AACGGTCAGC ACCCAGACAC\ asap AVL NGQ HPDT + 1 o 8 1 GCACCACCCG GGCCTCGGCC ATTCGTACAT GGAAGCTCAG HHP GLG HSYM EAQ + 1 1 2 1 TATCCGCTGA CGGAAGAGGT GGACGTACTT TTTAACATCG YPL TEEV DVL FNI + 1 1 6 1 ATGGTCAAGG CAACCACGTC CCGTCCTACT ACGGAAACTC DGQG NHV PSY YGNS + 1 2 o 1 CGTCAGGGCT ACGGTGCAGA GGTATCCTCC GACCCACCAC van TVQ RYPP THH/ +— 1 2 4 1 GTGAGTCCA CCTTGGCGCT GGAACCTTTT GGATCCGCGT (exon 2 intron 2) + :L 2 8 1 TTGTTTTCCT GGGTCCACGA GACCGCCAGA GACCCTGGCT t l 3 2 1 GGGCAGAGCA AGCCAAAGCT CCTAAGTGTG TTACTAGTTC + l 3 6 1 ATTTAAAAAA AGTATCGGGG GCCCGGAAAT GGGCGAGGAA + l 4 O 1 GCAGTGTCGC TGGTTGGGAG AGTT +3 3 9 l CTGGGCCTTT CGTCTTAGAG TTGGCGAGTG TGGACAGGGC +3 4 3 IL CTGCTTCTAT CTTGAGGCAT GTGGGCCTGG TACTCCTGGG +3 4 7 :L ACCACGGAGA TTAGCGTATG TTTGAGCTCA ATTGCGGTTG +3 5 l :L AGCCTGGAGG TTTGGCTGAC TGGGAGGTTG GAAGCGCCAG +3 5 5 l GGGGAAATCT TCAGGTGTGT CTCAGGGCAG CTCTCACTGC 1‘ 3 5 9 l GGTATTCTTC TTTTTTTTTT CTCCTCCTCA TCTTCTCTCC] ‘1‘ 3 6 3 l CCCACTCGCC CCGCCGCCGC CATCGCTGGC ATCACAGGGA\ +3 (intron 2 AG ' 67 l GCCAGGTATG CCGCCCGCCT CTGCTGCACG GATCTCTGCC ' +37 SQVCRPPLLHGSLP 1 l CTGGCTGGAT GGCGGCAAAG CCCTCAGCAG CCACCACACC +37 WLDGGKALSSHHT 51 GCCTCGCCCT GGAACCTCAG CCCCTTCTCC AAGACGTCCA +3 ASPWNLSPFSKTS 7 91 TCCACCACGG CTCTCCGGGG CCTCTGTCCG TTTACCCTCC * IBHGSPGPLSVYPP 3331 GGCTTCATCC TCTTCTCTGG CGGCCGGCCA CTCCAGTCCT ASS SSL AAGH $39] 77 (Exon 2) (cont’d) (Intron 2) (Exon 3) CCTTCCCGCC T F P P GTCGCTGTCC S L S GATGAGAAAG D E K ATAGCATGAA D S M K GACCACCCTG T T L ATTACCACCT I T T GACTCTTCCC G L F P CGGGTTCGGA G F G ACAGGTAAGC CACCCCGCCG T P P ACCCCGGGAT T P G AGTGCCTCAA E C L K GCTGGAGACG L E T GGTGGGGCCT G G A ATCCGCCCTA Y P P Y ACCCAGCAGC P S S TGTAAGTCGA C K S GCCACCTCTA T A intron 3) CCTCCTATTT GGTTTTCTTT GCGCTATATC ACTCCAAACT AAAGACGTCT\ K D v CCGCCGGGTC s A G s GTATCAGGTG Y Q v TCTCACTCTC s H s CATCCTCAGC s s s A TGTGCCCGAG v P E CTGCTGGGAG L L G GGCCCAAGGC R P K .A ) CCCCTGGGAA CAGGTCAGGG AAGGGTCTCT oooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo +3871 CATCTCTTCA H L F +3911 CCCCAGACCC S P D P +3951 -GGCCAGGCAA A R Q +3991 CAGCTGCCAG Q L P +4031 GAGGCAGCAT R G S M +4071 CCACCACCCC H H P +4111 TACAGCTCTG Y S S +4151 GATCCCCTAC G S P T +4191 ACGATCCAGC R S S +4231 TCTTTTGCTC +4271 CAAAAAAGGG +4311 GTGAGGGCT +9641 XXACGCTTTC +9681 TTCCAGAAGG (intron 3 ‘E G +9721 TACCCCACTG T P L +9761 TGCAATGCCT '9 N .A +9801 ACCGGCCCCT N R P L +9841 TTGGAAGTAC +9881 TGTCGTCTCT +9921 CTGGTAGTTT +9961 TACTGTTTCT +10001 CCTTTTATAC +10041 ATTTTTATTT CTTCCCTAAG CAGGGAGTGT R E g TGGCGGCGAG w R R GCGGACTCTA .g G L Y TATCAAGCCC I K p TGAGCTCATT GAGAAGAATG TCTCTCCTTT CCTCCACCTT TTTTTCAAAT TTCATGGTTA TGACTTATCT GTGAACTGCG v N 'g ATGGTACCGG o c T c CCATAAAATG H K. M AAGCGAAGGC K R R TATCTGTTTT GCTTTCTGCA ATTTTTCTTC TTATTTCTTT TAAATAAAAA AATCGCTTCT GTGACCTTGT GGGCAACCTC‘j G A. T S GCACTACCTT H Y L AATGGGCAGA N G Q TGGTAAGTTC/ L 'ntron 4)\ ACGTTTTCTG GGAAACTGGC CCTTCTTTTT TATCTCTTTT AAAACTTTGT (Exon 3) (cont’d) (Intron 3) (Exon 4) (Intron 4) +15121 +15161 +15201 +15241 +15281 +15321 +15361 +15401 +15441 +15481 +15521 +15561 +15601 +15641 AGAAAGAAAG GTCCAAGACT TGATGTGGGA GGTTTTGATT TCTTTGGAAG CATATTTACT CTCATCCCCA (intron 4 CGCGAACTGT A N ‘g AACGCTAATG N A. N ACTACAAGCT Y Y K L GGATGGGGGT TTCACCAGCA CCTTGGAGCT GGCTTGAGTT TTCGGTATTT CTAGATTGGC CCTTGATGAC TCAATGTCTT ACTTCAAGCC GTGTGTTCCA GTCGGCAGCA ,xs A. A CAGACCACCA Q T T GGGACCCGGT G D P V TCATAATGTA GCCTGTTGAG TACATCTTTC TTTCATGTTG TTTTTTTTTT AGTCTTCATA ATTTTATCTT AGGAGAGCAG R R .A CCACCACCCT T T T L CTGCAATGCC .g N A. AGCGGGACTG H NA intron 5) GGGGAGCCAT TCCAGATTTC AAACAATTTG TATTATAT CCTGACCATG TGATGGGTTT TTCAGATAAA GCCCAAAAAA) TTCTCAAGGA CCCACTTGCT TTTTTCGATG GCTCTGCCAA CTCCTCTCTT GGACATCCTG\ c T s [Q CTGGAGGAGG W' R R TGTGGGCTGT .9 c L J GAACCAGCCG ACCTTGAAAC CAGTCACCTT TAATGCAGTA oooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo +17341 +17381 +17421 +17461 +17501 XXXXXAGTGT AGACAGCGCA AAGTCTATTT AGCAGGGTGT ACAGTGCCAC TGTGTGTGTG CATCACTACT D' TGGTAAAGCA CAGCTGTCCT ATCTGACCAC AAGATCTCCA TGAACTGCCG TGTGTGTGTG Microsatellite marker for Gata3 TGTGTGTGTG TGTGTGTGTG TGTGTGTGTG A/J = (GT)26, C3H/HeJ = (GT)28 :TTCTCTACC ACCTCCACGG AGCCATAGAA TTCTAGG oooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo +19831 +19871 +19911 XXAGGAAGAA GAGGCAATCA ACACAGGAAC ACATCCCTGG CCTGGGGCCT GTGCTACTGT GCAAAAGCTT TTATCATTTC) AAAGGCAGCA AAAAAGTAAA AAAAAAAAAA ATTGATCTTT 79 (Intron 4) (cont’d) (Exon 5) (Intron 5) +19951 GTTTAGATTA (intron 5 AI +19991 +20031 +20071 +20111 +20151 +20191 +20231 +20271 +20311 +20351 +2039l +20431 +20471 +2051l +20551 +20591 +20631 +20671 +20711 +20751 +20791 +20831 TCCAGACCCG I Q T R GTGCAAAAAG c K K AGCAGCTCCT s s s CATCCCTGAG s s L s CATGCTGACC M L T CTCTCCTTCG L S F CCATGGGTTA ACAGACCCCT N R P L AAACCGGAAG N R K GTGCATGACG V H D TCAACCCGGC F N P A CCACATCTCT H I S ACACCGACGC T P T GACCTCACCA G P H H GAGAGGCAGA A 'M G * GGAGTCTCCA ACTTGCGTTT GCGACAGATC TGCTTCTTTT CCAACCACTG CAGACTCATA GAAAAAAATA AAGAAATACT GATAGCTGTA AGGAATATAG CCACTAAGTC GTTTCCCTTC AGAAAGAAAA TAAATTAAAA TCTAAGAAAA AGTGTGCGAA TTCGCAGGAG TGTGTTTTTG TTCAAAGGAG AATCCGGATC TTCCCTATTT TTGCTGAACA GTACATTTGA AGAAAGGCAT GGGGATTAAA TGATGTCCAA AGTTGTTTGA AGAAAAAAAG AAAAAAAAAA AAAAAAAAAA GACTATGAAG T ‘M K ATGTCTAGCA M S S CGCTGGAGGA A L E D CGCTCTCTCC A L S CCCTTCAGCC P F S CCATGCATCC P M H P CCCTTCCAGC P S S GCCCTGCTCC GAGTTCCTCC CAGTATCATG AAGGCAGAAA CTCGAGGTGG CCATTTGTGA AACAGGGTCT TTGCATATAA GGAAGACTTT GAAGGACGCC GTATGGAGAT ATGGGCACAC TGCATTTAAA GGGGGGGGGG AAAAAGAAAA GGTTGTAGGC 80 AAAGAAGGCA\ K E G AATCGAAAAA K S K K CTTCCCCAAG F P K AGACACATGT R H M ACTCCAGCCA H S S H GCCCTCCGGC P S G ATGGTCACCG M 'V T ACATGCGTGA GACCCCTTCT\ AAGCCCGAAA GCAAAATGTT TGTCTGCATT ATAAGCCATT CTAGTGCTGT CTTATATTGT ATTGTACCTG AAGAGTTTTA ACAGAAGAAA TGTCAGTTTT AAAAAAAAAA GAGAAAAAAA GAAAGAAAAA AAATCATTTG) (Exon 6) (Stop codon) (3’ UTR) +2087l +20911 +20951 +20991 +21031 +21071 +21111 +21151 +21191 +21231 +21271 +21311 +21351 +21391 +21431 +21471 +21511 +21551 +21591 +21631 +21671 +21711 +21751 TTCCAGGCTG GGCAATGGGT TGTCATGGCT TAATTGTTGT AGAAAAGATG AATTGTTGTA GCTTTTTTTT TTGTTTTTTG GTTGAATAAA TGTACTCTGG TGATGGTATT CCTGTCTTTT AGGTAGCAGC CCGGCCACTC ACTGTTAGCC TTTAAACAGT AAAGTTAAAA AACGTGACGG CTAATTTCAG AATATGGTAG GAGAGAATAG CCCTGGGCAG TGAGATACGT TGAGCCTGTG GTGTGATCTC AGGCCTACAT TTGTATGTAT TAGATTTATT TAAATTTATT TTTTTTTTGG TTTTTTTTTT CTAGATTGCT AGGGTTTATT TATTAAATAG TCGTCACTTT GTACCAGCTA ACAGGCCTGG CCTGTGTGTT CTGTTGGAAT TATTTTAAAA CCAAGCTCTT AGTTGTTTTC TTATTCACCA TGAGTTCTAC GCACAGCTTC GCTGTTCTTG CAAAAGAGAT ACCCACTGAA GCTCTGTGAA AATTCAGAAG TCATCATATT TACTGCTAGT TTTTAATGTT TCTTTCTCTC TTCAGTTGAC TTTCCTTTTA CTTCTATGGG TCTTGCAGCC CCAACATGCA TCCTGAGAGC CTGTATTAGT AATACTATAA CAACAAAGTA ACAGAAATTG TTTTTAAGCA GGAAATCATA TATTGTATAG TGGGTCCTCC AGTATCTCCT 81 TTCAGATCTG GATCTGAGAA TCAGTCCCTG CACCAAAATA ATACAGACTG GTTAGGAACT TTTTTTTTTT TGGATTTTTG TTAAGGTGGA TTATTATTTT CCCGGCGGTA TAAACTATGA TGTCAGAGAC CACCTGGCTG GATCACTGCC AAATAATAAT ACATTGTATC GTAGCACCAG TCCCAAAGCA TCCCTTGAAT AGAAATCTAT AGTTAGATGC] GAGACAAGCT (3’ UTR) (cont’d) +21791 +21831 +21871 +21911 +21951 +21991 +22031 +22071 +22111 +22151 +2219l +22231 +22271 TAAAGGGAGA CGCCTTTAAT TTTCTGAGTT CAGGACAGGC AAAACAAAAC GTTTCCAGGT TGCTACAGCA ATCTTGCTTT GTGACTGGGA AGCCGGCTGG ACTTATGAAT AGTTTAAGTC GAGAAGGGAC GTGGCAAACT CCCAGCACTT CGAGACAAGC AGGGCTACAC AAACAAAGAG CTATCTACTG AGCCAGCCAG GCCACTTCCT TGTCTGCAAG ATATTCATTC CTGTTACCTG CAAAGCTGAA ATGCGGTGGA CGATGGGCGG GGGAGGCAGA CTGGTCTACA AGAGAAACCC TGGCAAACTC TCGGAGGGTG GTGCTCCTCA TTGCTACTCG ACACAAAGTT CCTTCGTGAC CCTCTGCTTT TGTTGAAATA GAGCT 82 TGGTGGCGCA\ GGCAGGCGGA AAGTGAGGTC TGTCTCGAAA CTCAGCTGAG GATTCCTCTT GTTCATCCCC CAATGGAGGG ACCCTTTTGA TCTGGCACAC CTTAGCAAAT GAAAGAGTAA (3’ UTR) (cont’d) D. Comparison of our sequence to public databases Although no functional polymorphisms were found between AIJ and C3HlHeJ mice, many sequence differences were identified between our sequence results and published sequences. The differences may be due to the different strains used for sequencing, or may be due to sequencing errors. We compared our sequencing results with the Celera database (129X1/SvJ, 12981/SvlmJ, DBA/2J, and NJ strains) as well as the results of George et al (BALB/c mice) [62]. Overall, Celera data match our results closely, while George and colleagues report many differences as compared to both our results and the Celera database (Table 7). Based on the facts that we obtained duplicate sequence in two strains, repeated sequencing of all exons, and identified high sequence similarity with the Celera database, we have high confidence in the accuracy of our sequence results. It is not a surprise that no polymorphism within Gata3 exons were found because Gata3 is important for both T cell differentiation and neural development. Gata3 knockout mice will die at embryonic stage, thus the mutations that totally destroy the function of Gata3 are lethal. However, it is a little surprise that only one microsatellite marker was found among 12,069 bp Gata3 sequence. Wade and colleagues studied the rate of single nucleotide polymorphisms (SNPs) of inbred mice strains and found that the average rate was 14 SNPs per 10 kb [127]. However, the distribution of SNPs was highly non-uniform on long segments of 83 genome, either extremely high (40 SNPs/10 kb) or extremely low (0.5 SNPs/10 kb) [127]. Gata3 may be located in the extremely low SNPs rate region, therefore, no SNP was found on approximately 12 kb sequence. 84 Table 7. Comparison of our sequencing data with public databases [Nucleotide position Our sequence Celera database George et al. -1562 to -1558 GGGCA GGGCA CAGG -1000 to -999 GG GG G -991 A A T -979 to -977 CCC CCC CC -961 to -960 CC CC C -940 to -939 CC CC C -931 to -930 GA GTA GA -907 to -904 GGGG GGGGG GGGG -693 to -962 TG TG TCG 54 to 56 CCC CCCC CCC 354 c c Ya 389 to 392 CCCC CCCC CCC 470 to 475 CCCTCC cccrcc 'NbCNbCC 479 T T A 485 c c Nb 547 to 548 CC CC CCC 689 to 706 (T)18 (T)18 (T)19 962 to 964 GGG GGG GG 20573 A c N/Ac a. Y represents C or T. b. N represents A, G, C, or T. c. N/A means no sequence information available. 85 E. Summary I sequenced 12,069 bp of Gata3 gene in both AIJ and C3HlHeJ strains, including all exons, splicing sites, part of the promoter and 3’ UTR regions. A microsatellite marker in intron 5 was found; however, no other functional polymorphisms were found. The sequencing data do not support Gata3 as a positional candidate gene. GATA-3 protein has no amino acid sequence difference between these two strains. However, the Gata3 expression regulatory region has not been determined totally; thus, it may be located in further upstream, downstream, or even in intron regions. Since we cannot sequence the whole Gata3 gene, it is still too early to exclude the possibility that Gata3 expression levels are differently regulated in NJ and C3HlHeJ mice. That is the reason we continued to compare the expression level differences of these two strains. 86 Chapter Four: Comparison of GATA-3 and cytokine gene mRNA expression in two murine strains A. Introduction The comparative sequence analysis described in chapter 2 revealed no polymorphisms between AIJ and C3HlHeJ mice in Gata3 exons and splicing sites. Therefore, GATA—3 mRNA of these two strains should also have identical sequences. However, polymorphisms of Gata3 regulatory regions may still exist in the unsequenced locations. Any such polymorphism may lead to expression level differences of GATA-3 mRNA of these two strains. Thus, we quantitated the GATA-3 mRNA expression in AIJ and C3HlHeJ mice. Cytokine environment is the most important factor that determines the Th1/Th2 differentiation, thus, the expression profiles of some important cytokine genes (IL-4, lL-5, lL-12, lL-13, and lFN-y) involved in Th1fTh2 regulation were also studied. lL—4 is the key cytokine determining the Th2 pathway through STAT-6 signaling. lL—4 and lL-13 are important for stimulating B cells to produce lgE [40]. IL-5 is essential for eosinophil maturation and infiltration [41]. Therefore, lL-4, lL-5, and lL-13 were chosen as the marks for Th2 responses. The Th1 pathway may be induced by IL-12 through the STAT-4 pathway or by lFN-y through the STAT-1 pathway. T-bet, the key player for the Th1 pathway, was found to be induced by lFN-y through the STAT1 87 signaling pathway [56]. lL-12 is a heterodimer composed of lL-12p40 and lL-12p35 subunits. lL-12p40 expression is induced earlier than IL-12p35 and is an important interface between innate and adaptive immune responses [128]. Normally, the expression of IL-12p40 is believed to be interchangeable with that of lL-12. Therefore, lFN-y and IL-12p40 were chosen as marks for Th1 responses. GATA-3 is a transcription factor that induces Th2 cytokine and inhibits Th1 cytokine expressions; thus, the expression of GATA-3 is the upstream event of the cytokine gene regulations. GATA-3 expression in Th2 cells is constitutive due to autoactivation [102]. Therefore, GATA-3 mRNA expression were studied at both early (6 and 12 hr) and late (24, 48, and 72 hr) time points following allergen exposure. 88 B. TaqMan real-time RT-PCR A variety of techniques are available to detect mRNA, such as Northern blot hybridization, competitive quantitative reverse transcription- polymerase chain reaction (RT-PCR), SYBR green real-time RT-PCR, and fluorogenic 5’ nuclease assay (referred to by the commercial product name “TaqMan” real-time RT-PCR). Northern blot hybridization requires radioactive labeled DNA or RNA probes, and is not very sensitive: approximately 10 ug of total RNA or 5 x 10 A 5 copies of an RNA transcript are needed for each sample. Competitive quantitative RT-PCR is much more sensitive than Northern blot hybridization, but designing optimal PCR internal standards is laborious. SYBR green and TaqMan real-time RT—PCR are currently the most widely utilized assays, because these methods are very sensitive, detecting as few as 500 copies of RNA transcripts. Additionally, they are carried out as closed-tube reactions preventing contamination and they are quantitative. SYBR green real-time RT-PCR uses SYBR green I dye molecule to detect all double stranded DNA, which may also detect primer dimers and other non-specific products along with target products. SYBR green methods are flexible since no probes required and no fixed annealing temperatures are needed. Therefore, SYBR green methods have utility as preliminary screening tests and are valuable for those genes with sequence that is not amenable to TaqMan primer/probe design. Compared with SYBR Green methods, TaqMan real-time RT-PCR assays are more specific due to the 89 sequence-specific fluorescent probe, although they are more costly and difficult to design. Based on the desire for maximum sensitivity and specificity, we utilized TaqMan real-time RT-PCR assays as the primary method to quantitate mRNA. TaqMan real-time RT-PCR assays are commercially available (Applied Biosystems (www.appliedbiosvstemscom) or target sequence-specific primer pairs and probes can be designed using Primer Express 6.0 software. The probes are labeled with 5’ reporter (FAM or VIC) and 3’ quencher (T AMRA or non-fluorescent) dyes [129] (Figure 10). When the probe is intact, the quencher dye suppresses the reporter dye, thus no fluorescent signal is detected. During the PCR process, the 5’-3’ nucleolytic activity of the AmpIiTaq Gold DNA polymerase cleaves the probe when it is bound to the target. The reporter dye linked to the cut fragment shows the fluorescent signal. The strength of the fluorescent signal is proportional to the number of copies of amplified target, and is detected by the ABI Prism 7700 sequence detection system (PE Biosystems, Foster City, CA). During the PCR process, the PCR product is exponentially amplified and the fluorescent signal increases proportional to the exponential amplification of the PCR product. The threshold cycle (CT) value is the cycle number at which a statistically significant increase in fluorescent signal over background is first detected [129] (Figure 11). The CT value is used as the index of the original copy numbers of target mRNA. The higher the original copy number of target mRNA, the lower the 90 CT value. One CT unit difference is equal to a two-fold difference in target mRNA difference. 91 Polymerization @ = Reporter F cl pggfrr ® ® g = Quencher 5’ D 5 . . 3’ 3’ 5’ 5’ 3’ 4 5’ Reverse Drimer Cleavage A {9. ' fl ’ 5’ F 3 3’ 5. 5’ 3' 4 5’ Polymereriztion v Q, 3’ 5! + 3! 3! ' 5! Figure 10. The process of TaqMan real-time RT-PCR. The TaqMan probe is linked with 5’ reporter and 3’ quencher dyes. The quencher dye is near to reporter dye and suppresses the reporter signal in intact probe. During PCR process, AmpliTaq Gold DNA polymerase not only amplify the target DNA through its polymerase activity, but also cleaves the probe by its 5’ nuclease activity. The separated reporter dye shows the fluorescent signal whose strength is proportional to its concentration. 92 Rn : i E I ‘ 1 : 3 ! r ' 5 3: I 3 d -«.~»-+— 4,- — 5 2 ~ ' 5 T Rn+ g l i g . 1 .' , { f ; . ‘ i - .'.. >ARn ‘Threshold [fi f'. . . r , . , , . . - I ' . , . . I . ' ' I I l ‘ . ' r I ' I - i, ' l . . , t I v ' > , ‘ t ' 1 . ' . v I . , . I - I , ‘ r ‘ . y , ' A ' . , I l‘ . . . . '_ ' r ‘ -. I . , , . I . . . . ~ : I . ' . I , ‘ . ' I . I I‘ . , ‘ l I I . . ‘: I i . . - , I . . , : ' . I , r l I _- r . r r ' u .' ’ r I l ' ' r r 1 . ; ' ' l - I . A' ' . , : ' . . I I i ._ I ‘ I I . I l l , ‘ . r ( l . . . , A - , I I , I I r . | f . ' ‘, r .j I , ' ' I -7 .-<—-.- ...........'....I_..40m«-o---.—<-~ ---~»-¢‘-’ v r I 4 q : . i : ‘ I r I 5 ' r r . ' ' ' | 1 I r y i i I l ‘ 4' 1 l , 1 l 1 l A J A A 5 T ‘ r 1 Y r. > I ' I + , I ’ ‘ y I t I r 5 4 ‘ I l ’ ‘ I ; . ‘, j ‘1 .' . I I . . . I - ‘ I : . . l ' ' r . , . ; . I I v ‘ ‘ I l . I I - A. _‘ .4.‘.- r 4...... ,4 .J. -4.--. _I..—-~a~--'.—v . " Ct i; 1“ ; z-. 2: I I ' f ' I ‘ , , . I r _ l , - r I . I . 4 , i g 3 g - g i ‘ 2 . i -. f 1 i ‘ ' . I I l I‘ i - 1 1 1 1 I 1 , I . . I . I l 5 11.:111, 1 r r r r'ririiiriirrrirrr11rrrr i 4 6 3 1D 12 14 16 18 20 22 24 26 28 3D 32 34 36 38 40 Cg ole Figure 11. The threshold cycle of TaqMan real-time RT—PCR. Rn is the ratio of the emission intensity of the reporter dye to the passive reference (ROX). Rn- is the Rn value of the unreacted sample or early cycles without signal increases (baseline). Rn+ is the Rn value of a reaction sample. ARn is the difference between Rn+ and Rn-, which shows the signal increases due to PCR amplification. The threshold cycle (CT) is the cycle at which a statistically significant signal increase in ARn is first detected. 93 Since we were more interested in the relative gene expression between AIJ and C3HlHeJ mice and between PBS and OVA-treated mice, rather than the absolute gene copy numbers, a relative quantitation of gene expression method was used. Because 18$ rRNA is stably expressed in all tissues, it was used as an internal control. The ratio of target product relative to 18$ rRNA was used as the index of relative amount of target gene. An example of GATA-3 and 183 rRNA amplification plots is shown in Figure 12. The probes of GATA-3 and 183 rRNA were labeled with FAM dye and VIC dye, respectively. The concentrations of 183 rRNA and GATA-3 were quite different as CT values for 185 rRNA ranged from 12 to 20 and CT values for GATA-3 ranged from 30 to 36 (Figure 12). Along with concentration differences, there were also differences of amplification efficiency between the PCR amplicons as indicated by the values of the slopes in Figure 13. Multiplexing of the internal standard and the target amplicon in the same reaction vial results in data error when the difference in amplification efficiencies between the two amplicons is greater than 10%, therefore, separate tubes were used to amplify 18s rRNA and GATA-3. Two analysis methods are available CT data; the standard curve and the comparative CT methods [130]. The comparative CT method has the advantage of using a single sample as a calibrator, but requires similar amplification efficiencies of the target gene and internal control gene. Since the amplification efficiency of 18s rRNA was near 100% (standard curve slope = -3.2) and that of GATA-3 was near 90% (standard curve 94 slope = -4.1), they were too different for analysis by the comparative CT method (Figure 13). So, we used standard curve method to analyze our data. The standard curve method compares the results of each sample with a series of dilutions analyzed simultaneously with the test samples. A series dilution of 20, 10, 5, 2, 1, and 0.5 ng of total RNA of a specific sample were used as our standard curve. Samples were amplified in the same plate with standard curve, and the sample CT values were compared to the standard curve to calculate the relative amounts of target RNA. In brief, every sample was duplicated and the CT values of duplicates were averaged to calculate the relative amounts of target RNA by referring to the standard curve. The amounts of target RNA were divided by the amounts of 183 rRNA to get the relative ratio. The samples from the same strain/treatment/exposure-time group were averaged to get group average. The strain/treatment/exposure-time group averages were compared to show the effects of strain, treatment, and exposure-time. The data were analyzed by two-factor analysis of variance and Student- Newman-Keul test was used for painNise comparisons. 95 (A) .. anon - "Amplification- 10172002¥gata3 ' "some (3) ii'illiill'iiiiIi'ililliilillirlil.iiIrI-r~.i1: O 2 4.6 810112141618 20.22 24 26 28 3O 32 .34 33639 4D ' Cycle "(soon . 7 5.000 — , 1.000 “’Z f Honing .. ‘ [4.000 '- ; .mo- f 2.000 - f Amplification .- 1 01 72002-183 iIiililililllllIIIIIIIiITTiIiIiiI ' 31.0007 Figure 12. GATA-3 and 18$ rRNA amplification plots. Taqman assays were performed on cDNA derived from total RNA isolated from murine lung tissues. (A) The GATA-3 probe was labeled with FAM dye (B) 18s rRNA probe was labeled with VIC dye. Note the earlier rise in signal in the . i 4 6 31012141610 2022 24 26 28 50 32 34 36 38 ‘10 Cu do more abundant 18s rRNA as compared to GATA-3. 96 Standard Curves of GATA-3 & 18s rRNA l —GATA-3 l l Log ng Total RNA ‘ ,,,,, 18$ rRNA ‘ ‘ Figure 13. Standard curves of GATA-3 and 183 rRNA. A serial dilution of cDNA reverse transcribed from 20, 10, 5, 2, 1 and 0.5 ng total RNA from a lung sample was used as the standard curve. R2 indicates the linearity of the standard curve. The slope indicates the amplification efficiency. 97 C. Experimental time line NJ and C3HlHeJ male mice were obtained from the Jackson Laboratory (Bar Harbor, ME) at 4 weeks of age and allowed one week to acclimate before experiment. Animals were housed 3/cage, under high- efficiency particulate air (HEPA) filtered laminar flow hoods and allowed free access to ovalbumin (OVA)-free rodent chow and water. On day 0, mice were sensitized (n = 6/group) intraperitoneally with 10 ug chicken egg OVA (crude grade IV; Sigma, St. Louis, MO) in 200 Lil phosphate-buffered saline (PBS) or PBS alone. On day 14, mice were anesthetized (ketamine, 45 mg/kg and xylazine, 8 mg/kg, intraperitoneally), and challenged with a tracheopharyngeal instillation of 1.5% OVA (675 ug) in 45 ul PBS or PBS alone, then recovered from anesthesia. Mice were euthanized by overdose'd pentobarbital. Lungs, tracheobronchial lymph nodes, and spleens were harvested at 6, 12, 24, 48, and 72 hr after challenge (Figure 14). The tissues were homogenized in Trizol reagent and stored at — 80 °C. 98 Challenge Senflfization OVA (or saline) 45 ul 1.5% OVA (or saline) 10”9 ”3 tracheopharyngeal instillation day 0 day 14 6, 12, 24,48, 72hr f Tissue harvest Figure 14. Experimental time line of in vivo allergen exposure 99 D. Expression profiles for cytokine genes: II4, II5, II12, II13, and lfng To support the hypotheses that A/J mice respond to allergen via the Th2 pathway and C3HlHeJ mice deviate to the Th1 pathway following OVA exposure, Th2 type cytokine genes (II4, II5, and ”13) and Th1 type cytokine genes (”12 and lfng) were quantitated by TaqMan real-time RT- PCR. lL—4 expression was induced early in lungs of AIJ and C3HlHeJ mice by OVA exposure, reached maximal expression at 6 hr, and subsequently declined (Figure 15). lL-4 expression was also induced in tracheobronchial lymph nodes of NJ and C3HlHeJ mice by OVA exposure from 6 hr through 72 hr and did not vary in a time-dependent manner (Figure 15). Overall, A/J mice have higher expression of lL-4 following OVA exposure than C3HlHeJ mice. lL-5 expression was induced by OVA exposure in lungs and tracheobronchial lymph nodes of NJ mice at all time points and in C3HlHeJ mice at the earlier time points (Figure 16). lL—5 expression was comparable between AIJ and C3HlHeJ mice at the early time points, while expression was greater in AIJ mice after 24 hr. lL—5 expression in tracheobronchial lymph nodes of AIJ mice was biphasic with expression maximal at 6 hr, subsiding by 24 hr, and increasing again by 72 hr (Figure 16). lL-13 expression was induced in lungs and tracheobronchial lymph nodes of both AIJ and C3HlHeJ mice at all time points. lL-13 expression 100 decreased over time in lungs of C3HlHeJ mice, while expression increased in in a time-dependent manner in AIJ mice. It was greater in NJ mice than C3HlHeJ mice at 24 hr and beyond (Figure 17). lL-13 expression in tracheobronchial lymph nodes was comparable between NJ and C3HlHeJ mice at from 6 hr to 48 hr, while greater in AIJ mice at 72 hr (Figure 17). OVA treatment of AIJ mice resulted in suppression of lL-12p40 expression in lungs at all time points and in tracheobronchial lymph nodes at 24 hr through 72 hr samples (Figure 18). lL-12p40 expression in C3HlHeJ mice was largely unaffected by OVA exposure. Overall, AIJ mice tended to have lower expression of lL-12p40 following OVA exposure, as compared to C3HlHeJ mice (Figure 18). lFN-y expression was induced in lungs at 6 hr through 24 hr time points in CSH/HeJ mice. lFN-y expression was induced in lungs of AIJ mice at 24 hr and 72 hr time points, but the levels were significantly lower than those C3HlHeJ mice at 6 hr and 24 hr (Figure 19). lFN-y expression in tracheobronchial lymph nodes was largely unchanged by OVA exposure in both AIJ and C3HlHeJ mice, but the trend was for higher expression in C3HlHeJ mice as compared to NJ mice (Figure 19). 101 (A) .3. N 63HIHeJ eallne m C3HlHeJ OVA = AIJ saline - AIJ OVA * .5 O IL-4 I 188 rRNA relative ratio ea 6 24 72 Time (hr) post challenge 20 - —C3HIHeJ saline m c 3 H IH eJ o v A E: AIJ ea Iln e 2 - AIJ 0 VA + E * 1 5 - o * * e’. s l I 8 + < 1 0 d e 3 * :5: * * ‘- 2°: ‘ 5 .. .3; IE: . * =l :;: z;: 1 l;:;: ;:; -.; :0: I :0: :0: 0:. ::° } .=E= :3" 5:2: 32 - 2:2 ‘ o _ 71::in ’45] 72:2. 221 x.:§:l 6 ‘I 2 2 4 4 8 7 2 Time (hr) post challenge Figure 15. lL-4 expression in lungs and tracheobronchial lymph nodes. (A) lL-4 expression in lungs. (B) lL-4 expression in tracheobronchial lymph nodes. A/J or C3HlHeJ mice were exposed with PBS or OVA (n = 6 mice/group). Tissues were collected at 6, 12, 24, 48, and 72 hr following challenge. *Significant difference due to treatment (p 5 0.05). *Significant difference due to strain (p 5 0.05). 102 (A) csHlfleJ saline ‘1' m 63HIHsJ OVA * O : AIJ saline g 8 q - AIJ OVA + O _— * > 'f‘. .. a . E < z a ‘E 4 - . 0 a 1- m :E :1 2 "‘ :I o a 6 24 72 Time (hr) post challenge (B) 5 n C3HlHeJ saline m C3HlHeJ OVA : AIJ saline ,9 — AIJ OVA a 4 d E * ... o .2 I * ‘5 3 i + 2 E * * a» < I z : l '5 2 - E E u - . co : : " I I 3 1 - E -: - -: fl: ,. ¢ 2: E w := 2 :2 : éi =E fl: 0 _ I o 2 O 12 24 48 7 Time (hr) post challenge Figure 16. lL-5 expression in lungs and tracheobronchial lymph nodes. (A) lL-5 expression in lungs. (B) lL-5 expression in tracheobronchial lymph nodes. A/J or C3HlHeJ mice were exposed with PBS or OVA (n = 6 mice/group). Tissues were collected at 6, 12, 24, 48, and 72 hr following challenge. *Significant difference due to treatment (p 5 0.05). +Significant difference due to strain (p 5 0.05). 103 (A) CJHIHsJ saline an: CJHIHeJ OVA : AIJ saline — AIJ OVA 5+ iL-13 I 18s rRNA relative ratio b Time (hr) post challenge (B) 12 - C3HlHeJ saline m C3HlHeJ OVA '1' ,2 1o - [:1 AIJ saline * ‘n'i - AIJ OVA L 3 '5 8 “ r; 2 :2; * * 2 If: * < . {:5 * E 6 :5: ': * ,., 1:2 : * g 3:; : v 4 ‘ :5: E ~ ;.; - fl :1; i ‘1- ;2; i :' 2 " :3; l 5:: J o :3: . l 6 1 2 24 48 72 Time (hr) post challenge Figure 17. lL-13 expression in lungs and tracheobronchial lymph nodes. (A) lL- 13 expression in lungs. (B) lL-13 expression in tracheobronchial lymph nodes. AIJ or C3HlHeJ mice were exposed with PBS or OVA (n = 6 mice/group). Tissues were collected at 6, 12, 24, 48, and 72 hr following challenge. *Significant difference due to treatment (p 5 0.05). +Significant difference due to strain (p 5 0.05). 104 (A) 3 , C3HlHeJ saline T .o m C3HlHeJ OVA 1 ‘5. i: AIJ ssiins o _ AIJ OVA + .5 t is 7 E 2 1 + a: < :5: ' a :I:I: co -:-:- P I I I - 1 '1 I:I I a :-:: 3 :i:: t! EEEE :1 EE 0 A. __ 9:32: 6 24 72 Time (hr) post challenge (3) 2 q czHlfleJ saline .2 m C3HlHeJ OVA ‘5 [:21 AIJ saline .1, — AIJ OVA 5 2 2 § ‘5 1 1 'I / in %= 22 2 , s all 2 i gig: a 2’1 1:1: /'3 :3: N gig; Z : 7,— ”:5: " 523:3 / 3 23:3 é ;.; ..'i éiziz ¢ 3 ;3:3 %:3: - fit? a .s 1:1: ¢3 o 1 /% éé § 23 6 12 24 48 72 Time (hr) post challenge Figure 18. lL-12p40 expression in lungs and tracheobronchial lymph nodes. (A) lL-12p40 expression in lungs. (B) lL-12p40 expression in tracheobronchial lymph nodes. AIJ or C3HlHeJ mice were exposed with PBS or OVA (n = 6 mice/group). Tissues were collected at 6, 12, 24, 48, and 72 hr following challenge. *Significant difference due to treatment (p 5 0.05). +Significant difference due to strain (p 5 0.05). 105 C3HlHeJ saline m C3HIHOJ OVA .2 E AIJ saline 8 - AIJ OVA 3 3 fl * * 'a 2 2 < z 2 'i + E * a * 2 ‘3. 1 + + 'I 3 T + E: I: :5 0 6 24 72 Time (hr) post challenge C3HlHeJ saline m C3HlHeJ OVA E AIJ saline - AIJ OVA N 1 Il- .2 I! o .2 3 ¢ I'I : I l l:: 2 :: /l~l . :5 a; 7 %:=: I; a I. Z15 ¢::: + i:: no . :. /I:3 f::: "' F 1 I. %.0: /I:I * III \ ¢ I: /::o ¢:I: I'I /'I /’o’ /I"I IIIIII 3 35: as $5: u. ¢ :5 /:§: ¢E:E :E: "' /I: ék: /::: ::: §E= 35:5 éfi: i=5 0 4 ': éfi: M " 6 1 2 24 4 8 7 2 Time (hr) post challenge Figure 19. iFN-y expression in lungs and tracheobronchial lymph nodes. (A) iFN- 7 expression in lungs. (B) lFN-g expression in tracheobronchial lymph nodes. AIJ or C3HlHeJ mice were exposed with PBS or OVA (n = 6 mice/group). Tissues were collected at 6, 12, 24, 48, and 72 hr following challenge. *Significant difference due to treatment (p 5 0.05). +Significant difference due to strain (p 5 0.05). 106 E. GATA-3 gene expression profile The GATA-3 TaqMan primer pair and probe were designed using Primer Express software. The fonNard primer was located in exon 3, and reverse primer was located at the border of exon 3 and exon 4, making it specific for RNA amplification by avoiding genomic DNA amplification (Figure 20). This primer pair was also used with SYBR green reagents. GATA-3 expression in lungs was unaffected by OVA exposure in both AN and CBH/HeJ mice as assessed by both TaqMan and SYBR green assays (Figure 21 and Table 11). in contrast, GATA-3 expression was induced in NJ mice at 6 hr in both tracheobronchial lymph nodes and spleens (Figure 22, Table 12, and Table 13). A decrease in GATA-3 expression in tracheobronchial lymph nodes was observed in C3HlHeJ mice following OVA exposure at the 24 hr though 72 hr time points (Figure 22 and Table 12). 107 exon 3 exon 4 CCTACCGGGTTCGGATGTAfiGTCGAGGCCCAAGGCACGATCCAGCACA AAGGC 4—— Forward primer probe AGGGAG TGTGTG Reverse primer Figure 20. GATA-3 TaqMan primer pair and probe. Exon 3 is shown in regular font and exon 4 is shown in bold. 108 (A) C3HlHeJ saline C3HlHeJ OVA AIJ saline AIJ OVA \' \ IUE§ 0.. sea .00. GATA-3! 18s rRNA relative ratio 0 O O O O O O O O O O g g. é: O O O O O O O O O O O .0 .0 O O ..\.\.\.\.\.\.\.\.\.\.\.\.\.\x \))\))))§?>)§)§ >.\>.\.\.\.\.\.\.\>.\.\.\\‘ O A o o o N N b # 3.0.0.0333‘933 °° — (\\\\\\\\\\V N °o°o°.’o°:':':°:’o’ o o o N _ (B) C3HlHeJ saline m C3HlHeJ OVA I: AIJ saline — AIJ OVA O. .4 O O .1 0 4 GATA-3 I 18s rRNA relative ratio 6 12 24 48 Time (hr) post challenge N N Figure 21. GATA-3 expression in lungs, TaqMan and SYBR green assay. (A) GATA-3 expression in lungs, TaqMan assay. (B) GATA-3 expression in lungs, SYBR green assay. AIJ or C3HlHeJ mice were exposed with PBS or OVA (n = 6 mice/group). Tissues were collected at 6, 12, 24, 48, and 72 hr following challenge. *Significant difference due to treatment (p 5 0.05). +Significant difference due to strain (p 5 0.05). 109 (A) 4 ., _///. C3HlHeJ saline m C3HlHeJ OVA 0 E AIJ saline ‘3 - AIJ OVA E 3 n G g + 2 * / 5 7 7 3 - ¢ % é' a é % / < / I / - 2 l i- 1 . f 49 /:- ' < 7 / / /” é‘ o / /-. /-- /:.- /°. 3? fig" 3% 3% a? /$ /2 /§ /§ /3 Z: 32' $2 3% $5 0 _ é g: 4 2: 4 :3: 45: 4'2 6 12 24 48 72 Time (hr) post challenge (3) 5 - 'I/I/ CSHIHOJ saline m CSHIHOJ OVA .3 + I: AIJ saline 8 4‘ * I-IAUCWA 3 a 5 2 3 _ E ‘E a 2 + E» I i5 1 « < (D 00 oevvsvvvossvv'v' 00000000000000. 0 o o e'o‘e'o‘o'o'o'o'o‘o' 0.0.0.0.0...0.0-0‘0.0.0.0.1 .\\\\\\\‘\V. x\\\\\\\\\\\\ \\\\\\\\V' 0 6 12 24 48 72 Time (hr) post challenge Figure 22. GATA-3 expression in tracheobronchial lymph nodes and spleens. (A) GATA-3 expression in tracheobronchial lymph nodes. (B) GATA-3 expression in spleens. AIJ or CBH/HeJ mice were exposed with PBS or OVA (n = 6 mice/group). Tissues were collected at 6, 12, 24, 48, and 72 hr following challenge. *Significant difference due to treatment (p 5 0.05). +Significant difference due to strain (p 5 0.05). 110 F. Summary According to TaqMan real-time RT-PCR data, Th2 type cytokines (lL-4, lL-5, and IL-13) were induced in AU mice following OVA exposure at much higher levels than in C3HlHeJ mice. However, Th1 type cytokines (lL-12 and lFN-g) in lungs and tracheobronchial lymph nodes were generally higher in C3HlHeJ than AIJ mice following OVA treatment, but this was as much a function of cytokine suppression in NJ mice as induction in C3HlHeJ mice. The cytokines expression profiles reconfirmed our hypothesis that AIJ mice have stronger Th2 responses and CBH/HeJ have stronger Th1 responses following OVA treatment. GATA-3 expression was induced in AIJ mice at 6 hr following OVA exposure, but not in C3HlHeJ mice in both lymph nodes and spleens. These results also reconfirmed our expectation since GATA-3 is a transcription factor and should be induced in NJ mice at earlier time points than the cytokine genes whose expression is regulated by GATA-3. Unexpectedly, GATA-3 expression was not induced in lungs of AIJ mice at 6 hr or any other time points. The different results between lungs and lymphoid organs (spleens and tracheobronchial lymph nodes) might be due to the composition of cell types of each tissue. Spleen and tracheobronchial lymph nodes are mainly composed of immune response related cells, thus their gene expression profiles may reflect immune response more closely. Lungs contain a high proportion of epithelial cells, which may contribute to higher background GATA-3 expression. Perhaps, that is the reason why we did not Observe 111 the GATA-3 induction by OVA treatment in NJ mice at 6 hr in lungs. Since the proteins are the final factor of biological pathways, GATA-3 protein level differences were compared between NJ and C3HlHeJ mice. 112 Chapter Five: Comparison of GATA—3 protein in two murine strains A. Introduction Since proteins are the real executants of biological functions, the phenotype difference between AIJ and CBH/HeJ mice may be determined by either the GATA-3 protein amino acid sequence difference or by the concentration difference of GATA-3 protein. Since no coding polymorphisms were detected between these two strains, the GATA-3 protein is predicted to have the same amino acid sequences. Based on the results of GATA-3 expression studies described in chapter 4, concentration differences in GATA-3 protein may exist between these two strains. Two popular methods are available for protein semi-quantitation; electrophoretic mobility shift assay (EMSA) and Western blot. EMSA uses a specific DNA probe to assay the binding between protein and DNA, while the Western blot is based on specific antigen-antibody recognition. Since GATA-3 is a transcription factor, it functions through binding to the target DNA promoter. Therefore, we initially attempted to use the EMSA method to study GATA-3. However, EMSA require delicate protein-DNA binding conditions which we were unable to achieve. After repeated unsuccessful attempts to optimize probe, salt and DNA concentrations, we abandoned the EMSA method and pursued the Western blot. GATA-3 is a transcription factor; thus, it has to be transported into the nucleus where it binds to the target DNA promoter. For this reason we 113 isolated nuclear protein instead of whole cell protein. We demonstrated in the expression studies described in chapter 4 that cytokines were induced differently in AIJ and CBH/HeJ mice even after 72 hr OVA exposure; therefore, we chose to examine protein levels at the 72 hr time point after challenge in spleen cells. 114 B. GATA-3 Western blot assay development Miaw and colleagues [105] have previously demonstrated that GATA-3 mRNA is expressed in both stimulated (phorbol 12-myristate 13-acetate (PMA) + ionomycin) and unstimulated EL-4 (T lymphoma cell) cells. Dibutyryl cyclic AMP (BtchMP) is a cAMP analogue, which can stimulate cytokine production in Th cells through the p38 mitogen-activated protein (MAP) kinase pathway. PMA activates T cells through the protein kinase C pathway (PKC). Based on this information, we anticipated stable expression of GATA-3 protein in EL—4 cells; thus, we tested them for use as a positive control. We treated EL-4 cells with 25 ng/ml PMA + 1 mM BtchMP in ethanol or ethanol alone. EL-4 cells were harvested and nuclear proteins were isolated 2 hr and 8 hr after treatment. The nuclear proteins were examined by Western blot (Figure 23). GATA-3 proteins were expressed in both treated and untreated EL-4 cells. Comparing lanes 1 and 2 or lanes 3 and 4, GATA-3 protein was increased subsequent to PMA and BtchMP treatment. Protein levels were higher in the 8 hr than the 2 hr samples. 115 Stimulation - + Time (hr) 2 2 8 8 Lane 2 GATA-3 (50 kD) Figure 23. EL—4 cell Western blot gel. Lane 1, EL-4 untreated 2 hr (30 ug). Lane 2, EL-4 treated 2 hr (30 ug). Lane 3, EL-4 untreated 8 hr (60 ug). Lane 4, EL-4 treated 8 hr (60 ug). 116 C. Experimental time line NJ and C3HlHeJ male mice were obtained from the Jackson Laboratory (Bar Harbor, ME) at 4 weeks of age and allowed one week to acclimate before experimentation. Animals were housed 4/cage, under high-efficiency particulate air (HEPA) laminar flow hoods and allowed free access to ovalbumin (OVA)—free rodent chow and water. On day 0, mice were sensitized (n = 8/group) intraperitoneally with 10 ug chicken egg OVA (crude grade IV; Sigma, St. Louis, MO) in 200 ul phosphate-buffered saline (PBS) or PBS alone. On day 14, mice were anesthetized (ketamine, 45 mglkg and xylazine, 8 mglkg, intraperitoneally), and challenged with a tracheopharyngeal aspiration of 1.5% OVA in 45 ul PBS or PBS alone, then recovered from anesthesia. Spleens were harvested 72 hr after in vivo challenge (Figure 24). The 8 spleens within each group were combined. The spleens were disaggregated, and the cells spread on to 8 petri dishes under treated or control conditions. After 4, 8, 12, or 24 hr in vitro stimulation (25 ng/ml PMA + 1 mM Bt2cAMP), splenocytes were collected and nuclear proteins were isolated to perform Western blot. 117 Sensitization OVA (or saline) 10 ug IP 1 day 0 Challenge OVA (or saline) 45 ul 1.5% inhalation 1 day 14 Spleen harvest and treatment with 25 ng/ml PMA + 1 mM BtZCAMP i day 17 4.8.12. and 24 hr A Nuclear protein isolation Figure 24. Experimental time line for splenocyte nuclear protein isolation 118 D. Western blot of GATA-3 Western blot of GATA-3 was first performed on the samples of splenocytes nuclear protein following 8 hr of in vitro stimulation. Actin was stained as an internal control (Figure 25). Only A/J OVA-treated mice showed a strong GATA-3 signal, which was independent of cAMP/PMA stimulation (lane 8 and 9). GATA—3 was not readily detected in OVA- exposed or control C3HlHeJ mice, nor in AIJ mice not exposed to OVA. However, weak bands were visible for these other groups when the gel was developed longer, indicating far lower levels of GATA-3 production (data not shown). As we expected, GATA-3 protein expression was induced by OVA in AIJ mice, but not in C3HlHeJ mice. Western blot of GATA-3 was then performed in 4, 12, and 24 hr samples (Figure 26). Our results demonstrate that GATA-3 production was not induced by OVA treatment in C3HlHeJ mice even after 24 hr of in vitro stimulation (lane 2 and 3). On the contrary, in AIJ mice GATA-3 protein production was induced by OVA at all time points (from lane 4 to lane 9) and increased in a time-dependent manner. However, in vitro cAMP/PMA stimulation had little effect over in vivo OVA exposure (compare lane 4 with lane 5, lane 6 with lane 7, and lane 8 with lane 9). 119 Strain C C C C A A A Rx P P O O P P O Stimulation - + - + - + - Lane 1 2 3 4 5 6 7 GATA-3 Actin Figure 25. Western blot of GATA-3 8 hr splenocytes samples. Lane 1, C3HlHeJ PBS, unstimulated (10 ug). Lane 2, C3HlHeJ PBS, stimulated (10 ug). Lane 3, CBH/HeJ OVA, unstimulated (10 ug). Lane 4, C3HlHeJ OVA, stimulated (10 ug). Lane 5, NJ PBS, unstimulated (10 ug). Lane 6, AIJ PBS, stimulated (10 ug). Lane 7, AIJ OVA, unstimulated (10 ug). Lane 8, NJ OVA, stimulated (10 ug). Actin was used as internal control. C3HlHeJ (C), A/J (A), PBS (P), OVA (0). 120 Strain Rx Stimulation Time (hr) Lane GATA-3 Actin Figure 26. Western blot of GATA-3, 4, 12, and 24 hr splenocytes samples. Lane 1, EL—4 (30 ug). Lane 2, CBH/HeJ OVA, unstimulated, 24 hr (20 ug), Lane 3, C3HlHeJ OVA, stimulated, 24 hr (20 ug). Lane 4, NJ OVA, unstimulated, 4 hr (20 ug). Lane 5, AIJ OVA, stimulated, 4 hr (20 ug). Lane 6, NJ OVA, unstimulated, 12 hr (20 ug). Lane 7, NJ OVA, stimulated, 12 hr (20 ug). Lane 8, AIJ OVA, unstimulated, 24 hr (20 ug). Lane 9, NJ OVA, stimulated, 24 hr (20 ug). C3HlHeJ (C), A/J (A), PBS (P), OVA (0). 121 E. Summary Western blot analysis of spleen cell nuclear proteins indicated that GATA-3 protein was induced in NJ mice, but not in C3HlHeJ mice, at 72 hr following OVA challenge. GATA-3 mRNA was induced only in AIJ mice spleen at 6 hr following OVA challenge, but not in C3HlHeJ mice or other time points (shown in chapter 4). This discrepancy may be due to the relative stability of protein compared with mRNA. These results reconfirmed that GATA-3 was differently expressed in NJ and CBH/HeJ mice in response to OVA exposure. The induction of GATA-3 in AIJ mice following OVA exposure indicated its important role in cytokine gene expression regulation, Th1/Th2 pathway determination, and airway hyperresponsiveness. 122 DISCUSSION The goal of this project was to further define the loci and underlying genes controlling allergen-induced AHR in a murine model of asthma. The studies conducted for this dissertation research reflect our approach to refine the map positions of the Abhr loci and then test the highest priority positional candidate gene, which was Gata3. To more closely determine the location of Abhr1 and Abhr2 relative to Gata3, these QTL were fine-mapped (~2 cM) by genotyping 450 NJ backcross mice for 37 densely clustered DNA markers on chromosome 2. AIJ backcross mice (n = 450) with extreme airway responsiveness phenotypes (APTI 5 620 or APTI 3 797 cmH20.sec) were selected for genotyping from approximately 1,000 A/J backcross mice. Because asthma is a complex disease, several genes may be involved and interact to lead to the asthmatic phenotype [1]. The mice with extreme phenotypes were chosen because it was likely that their genomes included more genes carrying asthma- supportive alleles. Thirty one MIT microsatellite markers with polymorphisms between NJ and CBH/HeJ mice on chromosome 2 were available at the initiation of this project. To find more markers, especially the type 1 markers within positional candidate genes, the Celera mouse genome database was searched to obtain the sequences of identified positional candidate genes. Primer pairs were designed to amplify simple nucleotide tandem repeats regions, which were normally 123 located within introns. The primer pairs were used as microsatellite markers if the PCR products had clear size differences between NJ and C3HlHeJ strains. Five new type I markers within genes Gata3, Mrc1, Prkcq, Gad2, and II2ra on chromosome 2 were designed. These five newly identified type I markers may be useful in other mouse strains that are polymorphic at these alleles. The map constructed with the markers genotyped in this study was compared to published maps. The relative positions of our markers were similar to the MIT linkage map and the Celera physical map, thus ours appears to be a consistent and accurate genetic linkage map. Furthermore, the map constructed in this study was a detailed map, for example, the Abhr1 interval contains 13 markers in 11 cM). In mice, 1 cM genetic (or recombination) unit is approximately equal to 2 Mb of genomic DNA, thus our linkage map is detailed to approximately 2 Mb. Due to the large number of mice (n = 450) used for genotyping, our map discerned the location differences of a number of markers that were not distinguishable by the MIT linkage map. More information regarding additional markers on chromosome 2 can in the future be easily incorporated into our current map to make an even more detailed map. This refined map will also be useful for accurate dissection the DNA fragments in a related congenic mouse project ongoing in our laboratory. Within Abhr1 and Abhr2 regions, approximately 200 identified genes exist. Hc (C53) was an important positional candidate gene for the Abhr2 region (Iod = 3.5) [119]. GataB mapped within the Abhr1 confidence interval (lod = 4.3) and was reconfirmed to be a strong positional candidate gene for this locus. Other 124 positional candidate genes, such as Mrc1, Il1m, Lcn2, and Ptgs1, also merit future attention. To determine Gata3 polymorphisms between AIJ and C3HlHeJ mice, Gata3 exons, splicing sites, and part of the promoter region and 3’ untranslated region (12,069 bp total) were sequenced in both NJ and C3HlHeJ strains. One microsatellite marker (type I) in intron 5 of Gata3 was identified and used to genotype Gata3 on our linkage map. However, this marker may not be functionally important because it is a simple tandem repeats marker. No additional polymorphisms were found on approximately 12 kb of Gata3 sequence. Based on the sequence comparison between mouse strains 36 and 129, the average SNPs rate was 14 SNPs/10 kb [127]. However, the distribution of SNPs were mosaic rather than uniform throughout the genome. That is, the long segments of DNA had either extremely high (40 SNPs/10 kb) or extremely low (0.5 SNPs/ 10 kb) SNPs rate [127]. Our results indicate that Gata3 gene is located in an extremely low SNPs rate DNA segment, therefore, no SNP was found in 12 kb sequences of AIJ and C3HlHeJ strains. Similarly, based on the National Center for Biotechnology Information (NCBI) SNP database, only two SNPs were found in murine Gata3; in intron 4 (SNP lD: rs6312556) and intron 3 (SNP lD: rs6314548), but these SNPs were not polymorphic between NJ and C3HlHeJ strains. According to Roche mouse SNPs database (mousesnp.roche.com), there were two SNPs far upstream of Gata3 (950,950 bp and 247,098 bp upstream) polymorphic between AIJ and C3HlHeJ mice. The 125 functions of these two SNPs 5' to Gata3 merit further study because they may belong to the Gata3 promoter region. Since no polymorphisms were found in exons and splicing sites of Gata3, there should be no qualitative difference in GATA-3 mRNA or amino acid sequences between NJ and C3HlHeJ mice. Although no functional polymorphisms were identified, polymorphisms may exist in unidentified regulatory regions or unsequenced introns. Polymorphisms in introns may lead to alternate splicing or expression level difference of GATA-3 mRNA. Only one alternative splicing form of Gata3 promoter has been reported: exon 1a, which is selectively expressed in the brain, substitutes the previously identified exon 1 in the alternative form [79]. This alternative form of GATA-3 mRNA may lead to tissue-specific expression, but will not produce a new form of GATA-3 protein since it is located at Gata3 promoter region. Polymorphisms in regulatory regions may lead to quantitative differences in GATA-3 mRNA and proteins. In future studies, larger ranges of the genome around the Gata3 location could be sequenced to pursue regulatory region polymorphisms. Alternatively, the whole Abhr1 and Abhr2 regions may be sequenced and compared between AIJ and C3HlHeJ mice to identify all the polymorphisms. This complete sequencing information would be useful to narrow and identify the positional candidate gene(s). TO compare GATA-3 expression between AIJ and CBH/HeJ, the levels of GATA-3 mRNA at different time points (6, 12, 24, 48, 72 hr) following allergen exposure and in control mice of these strains were determined by real-time RT- 126 PCR. Both early and late time points were studied to show the relative complete immune response profile in the mice. Expression of cytokine genes lL-4, lL-5, IL- 12, lL-13, and lFN-y were also tested by TaqMan real-time RT-PCR. Overall, Th1 type cytokines (IL-12 and lFN-y) have relatively higher gene expression levels following allergen treatment in the CSH/HeJ strain; however, Th2 type cytokines (IL-4, lL—5, and lL-13) were induced higher in the AIJ strain. The results support our expectation that the hyperresponsive AIJ strain has stronger Th2 responses due to allergen exposure. Interestingly, the expressions of Th2 type cytokines (IL-4, lL-5, and lL-13) were induced at similar levels at the earliest time point (6 hr) in both NJ and C3HlHeJ strains, but declined quickly in C3HlHeJ mice. lFN-y was also induced in both strains in almost all time points, although it tended to be higher in C3HlHeJ than AIJ mice. lL-12 was largely not changed in C3HlHeJ at all time points, although it was inhibited in AIJ mice. In vitro CD4 T cell differentiation studies also showed that low levels of lL-4 and lFN-y could be detected after 24 hr of Th1 and Th2 priming, however after 48 hr, Th1 and Th2 cells expressed only lFN-y and lL-4, respectively [85]. Overall, it seems like C3HlHeJ mice or NJ mice did not develope purely Th1 or Th2 responses, especially at the earliest time point. It is quite possible that the early time point (6 hr) is still the determination stage with combined Th1/Th2 responses in both strains. However, with effects of transcription factors, such as GATA-3, NJ and C3HlHeJ mice favor Th2 and Th1 pathways, respectively, at later time points. Because lL-5 is essential for eosinophil differentiation and maturation, the numbers of eosinophils lining the main axial airway of the left lung lobe following 127 OVA exposure in NJ and C3HlHeJ mice were counted in accordance with the lL- 5 expression assay of the right lung lobe. At 6 hr following OVA exposure, the numbers of eosinophils were increased in both AIJ and CSHIHeJ strains. However, at 72 hr after OVA exposure, only A/J mice had significantly increased number of eosinophils (unpublished data from Dr. Harkema). Eosinophil numbers at both early and late time points matched well with the lL-5 expression data. Since lL-4 can induce mucin gene expression and mucus secretion by goblet cells in the airways [131], the intraepithelial mucosubstances in the surface epithelium lining the main axial ainlvay at generation 5 of the left lung lobe following OVA exposure in AIJ and C3HlHeJ mice were stained and counted in accordance with the lL-4 expression assay of the right lung lobe. Mucosubstances increased only in AIJ mice following OVA exposure at 24, 48, and 72 hr, and peaked at 72 hr (unpublished data from Dr. Harkema). IL-4 expression in lungs increased early (6hr) following OVA exposure in both AIJ and C3HlHeJ mice, but decreased quickly in C3HlHeJ mice. At 72 hr after OVA challenge, lL-4 expression increased significantly only in AIJ mice but not C3HlHeJ mice. Mucosubstances quantitation also matched well with IL-4 expression data. Overall, the histological data were consistent with the cytokine gene expression results. GATA-3 expression was induced by OVA treatment at the earliest time point (6 hr) in lymph nodes of AIJ mice, and reduced at late time points in C3HlHeJ mice. GATA-3 expression profile in spleen was similar to lymph nodes, specifically, GATA-3 was induced only in AIJ mice at 6 hr by OVA. These results 128 reconfirmed the early induction of GATA-3 expression and may indicate its important role in cytokine expression regulation. Since both tracheobronchial lymph nodes and spleens are lymphoid organ, the cell types are similar and largely composed of immune response related cells, therefore the expression profiles of lymph nodes and spleens should be similar. Unexpectedly, no difference of GATA-3 expression was Observed in lungs at all time points, which may due to the high background expression in this tissue by epithelial cells (UniGene Cluster Hs.413375). Laser capture technique may be used to select specific immune response related cell types from lungs to prevent background expression of other cells. In vitro T cell differentiation studies have shown GATA-3 mRNA was constitutively expressed and induced during Th2 cell differentiation even after 120 hr following Th2 priming [75, 92]. In contrast, our in vivo assay only showed that GATA-3 mRNA expression increased at 6 hr following OVA exposure in spleens and tracheobronchial lymph nodes. This discrepancy may come from the differences between in Vivo and in vitro stimulation or single cell line and whole tissue message source. Since CD4 T cells are the most important cell type involved in asthma, the in vitro studies of T cell differentiation can show the profile of this asthma-related cell accurately. However, the in vivo whole animal study has its own advantages, that is it reflects the real events happening in the animals more closely. Since GATA-3 is a transcription factor upstream of cytokine genes, the induction of GATA-3 expression should be earlier than that of Th2 type cytokines. 129 GATA-3 induction by OVA happened quite early at 6 hr, its expression at earlier time points such as 0.5, 1, 2, and 4 hr could be tested in future studies to show its complete expression profile. DNA is transcribed into mRNA before translation into protein, thus, the protein response should follow the mRNA regulation. To investigate the role of GATA-3 in mediating allergen-induced AHR, the levels of GATA-3 protein in splenocytes at 72 hr following allergen exposure and in control mice of these strains were measured by Western-blot. A/J mice showed a strong GATA-3 signal following OVA challenge, but not C3HlHeJ mice. Cyclic AMP in vitro stimulation had no further effects on GATA-3 protein expression in this study. In contrast, the electrophoretic mobility shift assays (EMSA) have shown cAMP could induce the target DNA binding activity of GATA-3 [75, 86]. Because cAMP activates GATA-3 phosphorylation through the p30 MAP kinase pathway and phosphorylation may be important for the DNA binding activity of GATA-3 [111], cAMP may have little effects on the expression of GATA-3. It seems like GATA-3 proteins were constitutively induced in NJ mice following OVA exposure even after 72 hr. In contrast GATA-3 mRNA induction was only observed at 6 hr in spleens. It is possible that the GATA-3 protein is more stable than mRNA. When antigens, such as OVA in this study, enter the respiratory airways of mice, dendritic cells will process antigens and circulate to peripheral lymphoid organs through blood and lymphoid fluids. Tracheobronchial lymph nodes and spleens are peripheral lymphoid organs where the naive T cells are activated by antigen-carrying dendritic cells. The early (6 hr) induction of GATA-3 mRNA in 130 the tracheobronchial lymph nodes and spleens of AIJ mice following OVA exposure can lead naive T cells into Th2 cells. Our protein analysis showed that GATA-3 proteins were induced in splenocytes of AIJ mice following OVA exposure even after 72 hr, which further indicated that AIJ mice favored Th2 pathway following OVA exposure. The activated lymphocytes will move to the target organs, such as the lung in this study, to deal with the antigens. Although the induction of GATA-3 mRNA in the lungs of NJ mice following OVA exposure could not be detected in this study, the relatively higher induction of Th2 type cytokines in AIJ mice lungs indicated the infiltration of Th2 cells and eosinophils. GATA-3 mRNA and protein expression data confirmed our hypothesis that GATA-3 is differently expressed in NJ and C3HlHeJ mice following allergen challenge. It indicates that the expression level difference of GATA-3 may be important for cytokine gene expression, Th1/Th2 pathway determination, and ainivay hyperresponsiveness. In summary, we found strain-specific and treatment-specific quantitative differences in GATA-3 mRNA and protein levels, but no qualitative differences between AIJ and CBH/HeJ mice were detected in Gata3 at the DNA level. These results reconfirmed the important role of GATA-3 in allergen-induced AHR. However, they do not provide direct evidence in support of Gata3 as a positional candidate gene for Abhr1 in the NJ and C3HlHeJ murine model of asthma. 131 Materials and Methods A. Genomic DNA isolation from mouse kidney In preparation for this procedure the 5810R centrifuge (Hamburg, Germany) was cooled to 4°C and a waterbath (Fisher Scientific, Pittsburgh, PA) was warmed to 42-47°C. 15 ml polypropylene tubes were put on ice. One kidney was placed in each dounce with 4.5 ml cold lso-Hi- pH [0.14 M NaCl (J.T. Baker, Phillipsburg, NJ), 0.01 M Tris (pH 8.4) (lnvitrogen, Carlsbad, CA), 0.15 mM MgCl2 (J.T. Baker, Phillipsburg, NJ), 0.05% NP-40 (Sigma, St. Louis, MO), and H20 to suitable volume. Sterilize final solution by autoclave or filter, and store at 4°C.]. The tissues were homogenized using 7-10 strokes, the pestle rinsed with 1 ml cold lso-Hi-pH and the homogenate transferred to a cold 15 ml tube using a transfer pipet. Homogenates were spun at 3,000 rpm, for 25 min, at 4°C, then supernatants were discarded. 400 ul lso-Hi-pH buffer was added to 15 ml tubes and the pellets were resuspended using a transfer pipet. then the suspensions were transferred to new 2 ml eppendorf tubes. lso-Hi-pH + SDS + PK (400 ul) [75% lso-Hi-pH, 2% SDS (Sigma, St. Louis, MO) and 1 mg/ml proteinase K (Sigma, St. Louis, M0) were added. This solution must be made freshly each day.] and inverted to mix. Eppendorfs were incubated in a waterbath at 42-47°C for 2-3 hr. The eppendorfs were filled with phenol/chloroform/isoamyl alcohol mixture [phenol (Boehringer, Indianapolis, IN) / chloroform (Sigma, St. Louis, MO) I isoamyl alcohol 132 (Sigma, St. Louis, MO): at 112111048 volume ratios. It must be made freshly each week.]. Tubes were inverted to mix, and centrifuged at 12,000 rpm for 3 min. The top layer was transferred to a new 2 ml eppendorf and refilled with phenol/chloroform/isoamyl alcohol mixture. Tubes were inverted to mix, and centrifuged at 12,000 rpm for 3 min again. The top layer was transferred to a new 15 ml polypropylene tube. 70 ul 3 M KCl were added, then 2-3X volumes (~2.5 ml) cold 95% alcohol. DNA was spooled onto flamed glass rods, rinsed with 70% alcohol. DNA was allowed to dry without contamination. DNA was dissolved in 300 ul 10 mM TE buffer [0.5 ml 2 M Tris-Cl (pH 8.0), 0.2 ml 0.5 M EDTA (pH 8.0) (lnvitrogen, Carlsbad, CA), and 99.3 ml ddeO. Sterilize by autoclave or 0.2 um filter], and stored at 4°C. . Polymerase chain reaction (PCR) PCR reactions were generally performed in 15 ul volumes containing: 1.5 ul 10X PCR buffer (lnvitrogen, Carlsbad, CA), 0.45 ul 50 mM Mg++ (lnvitrogen, Carlsbad, CA), 1.2 ul 1 mM dNTPs (lnvitrogen, Carlsbad, CA), 1 ul 10 uM forward primer (lDT, Coralville, IA), 1 ul 10 uM reverse primer (lDT, Coralville, IA), 0.075 ul 5 unit/ul Taq polymerase (Invitrogen, Carlsbad, CA), 6.775 ul ddHZO, and 3 ul 10 ng/ul DNA template. A 100X master mixture of all components (except DNA template) was made for each 96 well plate, 96 well plates were loaded with master mix, and then 3 ul DNA template was added separately to each well. PCR reactions were performed in a GeneAmp PCR System 9600 (Perkin Elmer, Norvvalk, CT). 133 PCR products were checked on 1% agarose gels (lnvitrogen, Carlsbad, CA) for common use, or on 4.5% agarose gels (3% of agarose + 1.5% of NuSieve GTG agarose (Cambrex Bio Science, Rockland, ME) for genotyping experiments. Gels were run in 1X TAE buffer (Diluted from 50X TAE: 242 g of Tris, 57.1 ml glacial acetic acid, and 100 ml 0.5 M EDTA (pH 8.0)) for common use, or in 0.5X TBE buffer (Diluted from 5X TBE: 54 g Tris, 27.5 g boric acid, and 20 ml 0.5 M EDTA (pH 8.0)) for genotyping experiments. PCR cycling conditions were routinely performed as following: 94°C (denaturing, 4 min), followed by 35 cycles of 94°C (denaturing, 30 sec), *57°C (annealing, 60 sec), and 72°C (extension, **90 sec). After cycling, a final extension was performed (72°C, 10 min) followed by an indefinite hold at 4°C. *Annealing temperatures were dependent on the base pair content of the primer pairs, normally ranging from 50°C to 60°C. "Extension times were dependent on the length of the products (approximately, 1 min/1000 bp). For two-step PCR (used for DZMit82), all the components and reactions were the same as regular PCR, except there was a two-step annealing: 61°C (45 sec) and 53°C (45 sec), since the Tm Of forward and reverse primers were dramatically different. Radiolabeled reactions were required to distinguish small differences in product sizes. For these reactions all the components were the same as the regular PCR, except that 0.5 ul of 1000-3000 Ci/mmol [a-33P] labeled 134 dCTP (ICN, Costa Mesa, CA) was added into the 100X master mixtures, and PCR products were separated on sequencing gels. C. Bsg I digestion for He genotyping l Bsg l recognition site is 5’...GTGCAG(N)16...3’ 3’...CACGTC(N)14...5’ T PCR products (15 ul) were mixed with 2 ul 10X NE buffer 4, 0.05 ul 400X SAM, 3 ul of 50 mM MgCIZ, and 0.5 ul of 3 units/ul Bsg I (New England Biolabs |nc., Beverly, MA) and incubate at 37°C, overnight. D. MAPMAKER program MAPMAKER is a computer package for constructing genetic linkage maps and finding QTL of complex traits [123], [123]. MAPMAKER 3.0 contains two programs: MAPMAKER/EXP 3.0 and MAPMAKER/QTL 1.1. MAPMAKER/EXP 3.0 performs multipoint linkage analysis based on raw genotyping data simultaneously to calculate map order and distance. MAPMAKER/QTL 1.1 uses interval mapping and simultaneous search techniques to find QTL based on the data generated from MAPMAKER/EXP 3.0. Interval mapping calculates the map distance between markers and QTL. Simultaneous search can fit multiple QTLs to the genome at the same time. Genotype data were prepared as text only files. The first line was “data type f2 backcross”, which means A/J backcross. The second line was “450 37 1”, which means 450 mice, 37 markers, and 1 quantitative 135 trait. The default codes for F2 backcross were homozygote (A), heterozygote (H), and missing data (-). Genotype data were listed as “*Iocus# genotypes”. Quantitative trait data came after genotype data and were listed as “*weight quantitative data”. Raw genotype data were analyzed by MAPMAKER/EXP to determine map order and distance; transformed data were analyzed by MAPMAKER/QTL to determine QTL locations. The computer codes were provided in the MAPMAKER protocols [123]. E. JoinMap program JoinMap 3.0 is a computer program for the calculation of genetic linkage maps, designed by Plant Research International, Wageningen, Netherlands [125]. Overall, the principle of JoinMap program is similar to the MAPMAKER program, that is multipoint interval mapping methods. However, it is more user-friendly, since its interface is based on MS- Windows. The user only needs to provide genotype data, and JoinMap will select and group the subsets of loci and individuals. Data were loaded into the project file, for example, genotype data were stored in locus genotype file. The genotype data were grouped and ordered by JoinMap 3.0. Finally, *LOD score and QTL was calculated by MapQTL 4.0 [132]. *LOD = log10(Probability (Datal Linkage) / Probablity (Datal Unlinkage)) 136 F. DNA primer design DNA primers were designed by Oligo primer design software (Molecular Biology Insights, lnc., Cascade, CO). The program setting included: (1) mouse databases, (2) duplex-free oligonucleotides, (3) highly specific oligos (3’-end stability), (4) eliminate false priming oligonucleotides, (5) eliminate homo-oligomers/sequence repeats, (6) the length of primer is between 15 and 25 nt, and (7) GC content is approximately 50-60%. Based on the exported results, the primers were further selected to eliminate potential primer dimer formation (especially 3’ primer dimer), prevent hairpin structure, and avoid large melting temperature differences within pairs of primers. G. DNA sequencing Primer pairs were designed by the Oligo program (Method F. DNA primer design). PCR were performed as described above (Method B. Polymerase chain reaction). PCR products were separated on 1.8% agarose gels. Target DNA bands were extracted using QlAquick gel extraction kits (QIAGEN Inc. Valencia, CA). The DNA fragments were excised from the agarose gels to which was added 3 volumes of Buffer QG to 1 volume of gel (100 mg ~ 100 ul). Typically, 500 ul was enough for one band. The mixture was incubate at 50 °C for 10 min and mixed by vortexing the tube 137 every 2-3 min until the gel had completely melted. The color of the mixture should be yellow. QlAquick spin columns were put in the provided 2 ml collection tubes. Samples were applied to QlAquick spin columns, and centrifuged for 1 min at 14,000 rpm to bind DNA to the membrane of the column. The flow-through was discarded, 0.5 ml of Buffer QG was added to column, and column was centrifuged 1 min at 14,000 rpm to remove any agarose remaining. 0.75 ml of Buffer PE was added to the columns and centrifuged for 1 min at 14,000 rpm to remove the salt. The flow- through was discarded and centrifuged again to remove trivial Buffer PE left. QlAquick columns were placed into new 1.5 ml eppendorf tubes. 30 ul ddeO was added to the center of the OIAquick membrane, the column was allowed to set for 1 min, and then centrifuged for 1 min at 14,000 rpm. Purified DNA product was stored at 4 °C. Sequencing reaction was based on [a-33P]dideoxynucleotide (ddNTP) chain termination reactions. Protocols and reagents were from Thermo Sequenase Radiolabeled Terminator Cycle Sequencing kits (USB corporation, Cleveland, OH). The 4 termination (labeled as “”,G “”,A “T”, and “0”) mixes were prepared as follows: 1 X Semnce (ul) G A T C dGTP or leP master mix 2.0 2.0 2.0 2.0 [a-33P]ddGTP 0.5 - - - [a-33P]ddATP - 0.5 - - [or-33P]ddTTP — - 0.5 - [a-33P]ddCTP - - - 0.5 138 The reaction mixtures were prepared as follows: 10 ul ddeO + 2 ul reaction buffer + 5ul DNA + 1u| 10 ng / ui primer + 2 ul Thermo sequenase, mix well. Transfer 4.5 ul mixture to each of four termination tubes (labeled as “’G’, “”,A “T”, and “0”), mix well. Cycle 30-60 times as follows: dGTP leP 95 °C, 30 sec 95 °C, 30 sec 55 °C, 30 sec 50 °C, 30 sec 72 °C, 1 min 60 °C, 5-10 min Reactions were stopped by adding 4 ul stop solution, store at 4 °C. Long Ranger Singel (BioWhittaker Molecular Applications, Rockland, ME) gels were used for gel electrophoresis. The sequencing gels were pre-run at 75 watt, for about 2 hr. Samples were heated at 70 °C, for 5 min. Samples were loaded and run at 55 watt. The gels were dried at 80 °C, for about 45 min (Heto Dry GD-1 gel dryer, Heto Lab Equipment, Denmark). Dried gels were exposed to Kodak BioMax film (Eastman Kodak Company, Rochester, NY). The films were developed using a Canon gel development machine. H. Ovalbumin sensitization and challenge AIJ and C3HlHeJ male mice were obtained from the Jackson Laboratory (Bar Harbor, ME) at 4 weeks of age and allowed one week to 139 acclimate before experiment. Animals were housed 3/cage, under high- efficiency particulate absolute (HEPA) laminar flow hoods and allowed free access to ovalbumin (OVA)-free rodent chow and water. On day 0, mice were sensitized (n = 6/group) intraperitoneally with 10 ug chicken egg OVA (crude grade lV; Sigma, St. Louis, MO) in 200 ul phosphate-buffered saline (PBS) or PBS alone. On day 14, mice were anesthetized (ketamine, 45 mglkg and xylazine, 8 mglkg, intraperitoneally), and challenged with an aspiration of 1.5% OVA in 45 ul PBS or PBS alone, then recovered from anesthesia. Lungs, tracheobronchial lymph nodes, and spleens were harvested at 6, 12, 24, 48, and 72 hr after challenge. TaqMan real-time RT-PCR Total RNA was extracted from lung, lymph node or spleen tissues using TRIzol reagent (lnvitrogen life technologies, Carlsbad, CA). Tissues were homogenized in 10 ml tissue dounces at room temperature in 2 ml TRlzol reagent using about 10 strokes. The pestle was rinsed with 1 ml TRlzol reagent. This 1.5 ml mixture was stored at -70°C for future use. The 1.5 ml mixture was poured into a sterile microfuge tube. The sample was incubated at room temperature for 5 min to allow complete dissociation of cells. Subsequently, 200 ul chloroform was added, tubes were capped securely and shaken vigorously by hand for 15 sec, then incubated at room temperature for an additional 3 min. Sample were 140 centrifuged at 12,000 rpm at 4°C for 15 min. The upper, aqueous phase containing the RNA was transferred to a new, sterile 1.5 ml microfuge tube and RNA precipitated by adding 500 ul isopropyl alcohol. This mixture was incubated at room temperature for 10 min. Samples were centrifuged at 12,000 rpm at 4°C for 10 min. The RNA precipitate formed a gel-like paste on the bottom of the tube. The supernatants were carefully removed and the pellets washed with 1 ml 75% ethanol. The samples were vortexed and centrifuged at 9,500 rpm for 5 min at 4°C. The supernatants were carefully removed and air-dried for 15-30 min being careful not to contaminate samples by aerosol or over dry. RNA pellets were dissolved in 300 ul 0.2% DEPC-treated water and stored at -70°C. Genomic DNA was removed by DNAse l treatment. Total RNA (300 ul) was combined with 20 ul 1 M Tris (pH = 7.5), 4 ul 1 M MgClz, 2 ul 10 mg/ml BSA, 4 ul DNAse l (RNAse free), and 70 ul DEPC-HZO to make 400 ul total volume. This was incubated at 37°C for 30 min and then precipitated with 40 ul 3 M sodium acetate (pH = 5.2). The tubes were filled with ice-cold 95-100% ethanol and incubated at -20°C for 30 min, then centrifuged at 12,000 rpm for 5 min at room temperature. The supernatants were carefully removed and 1 ml 75% ethanol was added, the samples were vortexed, and re-spun under the same conditions. The pellets were air dried for 5-10 min and resuspended in 300 ul DEPC-HZO. cDNA was reversed transcribed from total RNA using Reverse transcription kit ( Applied Biosystems, Foster City, CA). According to the 141 manufacturer’s instructions, 10 ul 10X RT buffer was combined with 22ul 25 mM MgCl2, 20 ul deoxy NTPs mixture, 5 ul random hexamers, 2 ul RNAse inhibitor, 6.25 ul 50 unit/ul Multiscribe reverse transcriptase, 2 ug total RNA, and a suitable amount of DEPC-HZO to make 100 ul total volume. At other times, a 10 ul total volume was prepared by combining these reagents in proportional amounts. The reagents were capped, gently tapped, and centrifuged to mix well in 0.2 ml Micro-Amp tubes. Thermal cycling was conducted as follows: 25°C (10 min) - 37°C (60 min) - 95°C (5 min). Samples were diluted to 5 ng cDNA/ul in DEPC-HZO. TaqMan Pre-Developed Assay Reagents (PDAR) and TaqMan universal PCR master mix were Obtained from Applied Biosystems. For these assays, 10.25 ul DEPC-HZO was combined with 12.5 ul 2 x TaqMan universal PCR master mix, 1.25 ul 20 x PDAR of target gene, and 1 ul cDNA template to make a 25 ul reaction system. TaqMan Real-time RT- PCR was performed as: 50°C (2 min) - 95°C (10 min) — 95°C (15 sec)/ 60°C (1 min) (40 cycles). . Statistic analysis of mRNA expression data cDNA samples from a single time point (n = 24) as well as a standard curve were loaded into 96 well plates in duplicate. The standard curve was made from a single AIJ OVA lung sample as a series dilution of 10, 2, 1, 0.2, 0.1 ng of total RNA based on spectrometer. The CT values of duplicates were averaged to calculate the relative nanogram of the target 142 RNA by referring to the nanogram of the standard curve. The amounts of target RNA were divided by the amounts of 183 rRNA to get the relative ratio. After a ratio was calculated for each individual sample, the ratios from each strain/treatment/exposure-time group were averaged to get the group average. The standard error (SEM) of a group was calculated using the formula: SEM = ((2 (Xi -_x-) A 2) / (n A 2 — n)) A 0.5. The group averages were divided by the group average of 6 hr CSH/HeJ PBS and termed as Normalizor1. The SEM of each group was divided by its Normalizor1 to Obtain SEMI. The Normalizor1 and SEMI of strain/treatment/exposure-time groups were compared to show the effects of strain, treatment, and exposure-time. The data of the relative ratio of target gene/18s rRNA were analyzed using the SigmaStat 2.03 program (SPSS Inc., Chicago, IL). Due to the unbalanced data, the three-way ANOVA did not work for SigmaStat program. The data were analyzed by two-way analysis of variance (ANOVA). The normality of the data was scanned by SigmaStat program. If the normality test was failed, the data were transformed by logarithm to match the normality requirement. Student-Newman-Keul test was used for pairwise comparisons of the mean responses among different treatment groups. P value 5 0.05 was used as the standard for significant difference. 143 K. Nuclear protein isolation from EL-4 cells and splenocytes NJ and C3HlHeJ mice (8 mice/group) were sensitized and challenged as described above. Mice were sacrificed and spleens were harvested at 72 hr after challenge. 8 spleens of the same group were disaggregated by squeezing in 20 ml of RPMI medium. Cells were centrifuged at 1,200 rpm for 8 min, supernatants were discarded, and pellets suspended with 16 ml of RPMI (1 spleen/2 ml RPMI, 1 spleen = 10"8 cells). RPMI medium was made as follows: RPMI medium powder (for IL, with L-glutamine, without Na2C03, GIBCO) was dissolved into 800 ml ddeO, 2 g of NaZCO3 and 15 ul of 1M HEPES were added. The mixture was spun and mixed well, and brought up to 1 L using ddeO. 500 ml medium were filtered through a 0.25 um filter and kept for future use at 4°C. 50 ml of 10X serum stock and 5 ml of 100X penicillin/streptomycin was added to the other 500 ml medium, which was now ready for cell culture. 32 petri dishes were labeled as the combination of “AIJ or C3HlHeJ”, ”PBS or OVA”, “4 hr, 8 hr, 12 hr, or 24 hr”, “unstimulated or stimulated”. 18 ml RPMI was added to each of them, then 2 ml of spleenocytes were added to each dish and mixed well (5 x 10"6 cells/ml). For stimulated dishes, 20 ul 1000X PMA (Sigma, St. Louis, MO) and 200 ul 100 x Bt2cAMP (Sigma, St. Louis, M0) were added. For unstimulated dishes, 20 ul ethanol and 200 ddHZO were added. Spleenocytes were cultured at 37°C, in a 5% C02 incubator. Cells were harvested after 4, 8, 12, or 24 hr stimulation. Spleenocytes were centrifuged at 3,000 rpm, 5 min, 4°C. Supernatants were discarded, 0.5 ml 144 Gey’s buffer was added, and the samples were mixed well. Then 3 ml Gey’s lysis solution was added and samples were incubated on ice for 5 min, mixing well every 1 min. An additional 10 ml Gey’s buffer was added, centrifuged at 3,000 rpm, 5 min, 4°C. 4 ml HB buffer (0.5 M HEPES 1 ml, 1M MgCl2 75 ul, use ddHZO to fill up to 50 ml) was added and incubated on ice for 15 min. Samples were centrifuged at 3,000 rpm, 5 min, 4°C and supernatants discarded. Nuclear pellets were washed twice with 1 ml MDHK (0.5 M HEPES 5 ml, 2 M NaCl 5 ml, 1 M MgCl2 0.3 ml, using ddHZO to fill up to 100 ml), transferred to 1.5 ml eppendorf tubes, centrifuged and supernatants again discarded. 100 ill of Buffer C was added (0.5 M HEPES 1.5 ml, 1M MgCl2 37.5 ul, 0.5 M EDTA 15 ul, 100% glycerol 2.5 ml, 2 M NaCl 5.625 ml, lgepal CA-630 25 ul, use ddHZO to fill up to 25 ml. Freshly add protease inhibitor before use). Nuclei in Buffer C can be stored at - 80°C stably. Samples were rocked on ice for 1 hr, then centrifuged at 14,000 rpm, 15 min, 4°C. Supernatants (about 90 ul) were removed and combined with equal volume of Buffer D (0.5 M HEPES 3.0 ml, 1M MgCl2 75 ul, 0.5 M EDTA 30 ul, 100% glycerol 5 ml, use ddH2O to fill up to 50 ml. Freshly add protease inhibitor before use). Protein concentration was determined by Bicinchoninic Acid Protein Assay kit (Sigma). EL-4 cells (2 x 1047 cells/vial) were removed from storage in a liquid nitrogen tank. EL-4 cells were thawed at 37°C, 1 ml was pipetted into 50 ml RPMI medium, the cells were grown in cell grow flasks at 37°C, in 5% 145 CO2, overnight. Cells were transferred to 50 ml centrifuge tubes, centrifuged at 200 g, for 5 min, in 4°C. Supernatants were discarded, 10 ml fresh RPMI medium was added, and mixed well. Cell numbers were counted on a Bright-line hemacytometer after staining with Trypan Blue solution. Petri dishes were labeled as “EL—4, unstimulated, 2hr”, “EL-4, stimulated, 2 hr”, “EL-4, unstimulated, 8 hr”, or “EL-4, stimulated, 8 hr”. EL-4 cells were diluted to make 106 cells/ml, 20 ml/dish. For stimulated dishes, 20 ul 1000 x PMA and 200 ul 100 x BtchMP were added. For unstimulated dishes, 20 ul ethanol and 200 ddH20 were added. EL-4 cells were cultured at 37°C, in a 5% C02 incubator. Cells were harvested after 2 or 8 hr stimulation. Cells were spun down at 200 g, for 5 min, in 4°C. The cells were washed with 1 ml ice cold PBS and spun down at 3,000 rpm, for 5 min, in 4°C. The following nuclear protein isolation steps were the same as spleenocytes nuclear protein isolation. Nuclear proteins were stored in a -80°C freezer. . GATA-3 protein quantitation by Western blot Separating gels (10%) were made as follows: ddH20 4 ml, 4 x separating buffer 2.5 ml (Tris 36.3 g dissolve in ddH20, use HCl to adjust pH to 8.8, use ddH20 to fill up to 200 ml), Ultrapure ProtoGel (30% Acrylamide:0.8% Bisacrylamide, National Diagnostics, Atlanta, GA) 3.3 ml, 10% SDS 0.1 ml, 10% APS (freshly made) 0.1 ml, and 10 ul TEMED were combined to make 10 ml separating gel. The separating gels were poured 146 and sealed with water-saturated butanol for 30 min until polymerization. The water-saturated butanol was then removed by suction. Stacking gels (4%) were made as follows: ddH20 3 ml, 4 x stacking buffer 1.25 ml (Tris 6 g dissolve in ddH20, use HCi to adjust pH to 6.8, use ddH20 to fill up to 100 ml), Ultrapure ProtoGel (0.66 mi, 10% SDS 0.05 ml, 10% APS (freshly made) 0.05 ml, and 5 ul TEMED were combined to make 5 ml separating gels. The stacking gels were poured on the top of the polymerized separating gel. The gels were allowed to polymerize overnight at 4°C. Then 4 x protein loading buffer was added to nuclear protein samples, which were then boiled at 95-100°C for 5-10 min. The protein ladder and samples were loaded, and run in 1 X running buffer (5 x stock: Tris 15.1 9 (Sigma, St. Louis, MO), Glycine 72 9, SDS 5 9 (Sigma, St. Louis, MO), use ddH20 to fill up to 1L) at 100 v for about 2 hr. The gels were soaked in Transfer buffer (Tris 3.03 g, Glycine 14.4 g, Methanol 200 ml, use ddeO to fill up to IL) for 2 x 15 min. Six pieces of filter papers and two pieces of sponges were soaked in Transfer buffer. Nitrocellulose membranes were soaked in ddH20 to activate, then soaked in Transfer buffer just before use. The gel transfer equipment was set up in the order of cathode side of folder, sponge, 3 filter papers, gel, membrane, 3 filter papers, sponge, and anode side Of folder. The gels were transferred at 15 v in 4°C, overnight, with a stir bar to circulate the buffer. The membranes were removed and rinsed with TBST (Tris 3.636 9, NaCl 26.31 g, Tween20 3 ml, use ddH20 to fill up to 3L) 2 x 15 min. The membranes were blocked in 5% non-fat 147 milk for 2 hr. Then GATA-3 antibody (Santa Cruz Biotechnology, Santa Cruz, CA) 1 ug/ml was added and shaken for 1 hr. Membranes were washed with TBST 5 x 5 min. Sheep-Anti-mouse lgG-HRP conjugated antibody (Amersham) was added at 1:5000 dilution, and incubated at room temperature for 20 min. Membranes were washed with TBST 10 x 5 min. A mixture of 1 ml of Super Signal West Femto Stable Peroxide buffer was combined with 1 ml of LuminolEnhancer Solution (Pierce) and applied to the membrane for 4 min. Membranes were then exposed and developed on film. TO quantitate Actin, the internal control protein, the membrane was submerged in stripping buffer (100 mM 2-mercaptoethanol, 2% sodium dodecyl sulphate, 62.5 mM Tris-HCI pH6.7), and incubated at 37°C for 30 min with occasional agitation. The membrane was washed 2 X 10 min in TBST at room temperature. The membrane was blocked in 5% blocking reagent for 1 hr at room temperature. Immunodetection was performed as described above except using for first antibody to Actin (1 :25,000 dilution, Sigma). 148 Table 8. Mouse ID reference and APTI value Mouse lD* Mouse fl APTI Mouse ID* Mouse if APTI 1 ALABX 0002 514 44 AgiBX 0132 1881 2 Ag-ABX 0005 407 45 ALABX 0135 1335 3 ALABX 0006 2251 46 Ag—ABX 0136 1465 4 AQ-ABX 0007 606 47 AflBX 0137 580 5 ALABX 0008 1685 48 A$ABX 0138 480 6 A9;ABX 0016 350 49 ALABX 0140 1679 7 ALABX 0018 355 50 Ag-ABX 0142 610 8 AgiBX 0019 508 51 AQ—ABX 0144 534 9 ALABX 0021 447 52 _Ag-ABX 0150 469 10 ALABX 0023 524 53 Ag-ABX 01 51 1352 1 1 AtABX 0026 1418 54 ‘AgABX 0159 436 12 ALABX 0028 1240 55 AgiBX 0160 389 13 fig-ABX 0029 1 123 56 AngBX 0162 606 14 AgiBX 0044 1280 57 Ag-ABX 0163 1429 15 AgiBX 0052 1586 58 AQABX 0165 518 16 AEABX 0057 2168 59 AgitBX 0166 471 17 Agflax 0082 264 60 max 0168 1166 18 Ag—ABX 0083 585 61 Ag-ABx 0169 1149 19 AgiBX 0084 2349 62 AgfiBX 0179 415 20 ALABX 0085 403 63 max 0181 424 21 Ag-ABX 0086 461 64 AgiBX 0185 440 22 Ag-ABX 0088 544 65 AgiBX 0188 1500 23 AQABX 0089 444 66 AQ—ABX 0190 404 24 AgllLBX 0091 620 67 Ag-ABX 0191 2138 25 Ag-ABX 0092 265 68 firtABX 0192 1420 26 AgiXBX 0094 384 69 Ag-ABX 0195 508 27 AgiBX 0095 1057 70 Ag—ABX 0197 545 28 Ag-ABX 0096 1171 71 AflBX 0200 1127 29 AgiBX 0097 542 72 Ag-ABX 0201 1339 30 ALABX 0098 467 73 Ag-ABX 0202 1795 31 Ag;ABX 0099 409 74 Ag-ABX 0203 1530 32 AgiBX 0101 442 75 Ag-ABX 0204 605 33 AgiBX 0102 387 76 Ag-ABX 0206 1283 34 AQABX 0103 1357 77 ALABX 0207 1589 35 AgfiBX 0105 476 78 Ag-ABX 0212 526 36 Ag-ABX 0107 466 79 Ag-ABX 0213 2323 37 AflBX 0109 436 80 AQABX 0214 490 38 AgiBX 01 16 2217 81 Ag—ABX 0217 455 39 AgiBX 0117 1041 82 Agitex 0218 483 40 Ag-ABX 0124 1309 83 AgiBX 0222 441 41 AgiBX 0126 1 367 84 Ag-ABX 02 24 1 358 42 Ag-ABX 0130 1406 85 AgiBX 0225 256 43 AQABX 0131 1520 86 Ag-ABX 0232 1469 149 Table 8 (cont’d). Mouse ID* Mouse # APTI Mouse ID* Mouse # APTI 87 AiABX 0233 384 130 AgiBX 0320 1 122 88 ALABX 0236 385 131 Ag-ABX 0321 1018 89 Ag-ABX 0242 379 132 AgiBX 0322 1818 90 MEX 0246 408 133 AiABX 0323 1062 91 AQ-ABX 0248 284 134 ALABX 0324 1436 92 AgitBX 0249 320 135 ALABX 0325 1293 93 ALABX 0250 1261 136 A913th 0326 1204 94 AflBX 0251 1691 137 Ag-ABX 0327 1650 95 Al-ABX 0253 460 138 AgfiBX 0328 1436 96 AgABX 0258 532 139 AQABX 0334 1652 97 AQABX 0261 457 140 Ag-ABX 0336 491 98 AgABX 0262 1400 141 AflBX 0337 447 99 AgiBX 0264 613 142 Ag;ABX 0341 1497 100 él—ABX 0265 592 143 AfiBX 0345 1417 101 Ag-ABX 0267 546 144 AgiBX 0346 601 102 ALABX 0268 576 145 Ag-ABX 0351 1 125 103 Ag-ABx 0270 387 146 Ag-ABX 0357 329 104 Ag-ABX 0271 1239 147 Ag—ABX 0358 241 105 Ag-ABX 0272 354 148 Ag-ABX 0360 271 106 AgfiBX 0273 501 149 AgiBX 0362 267 107 AgiBX 0276 1009 1 50 AgiBX 0364 255 108 AQ-ABX 0277 1208 151 Ag-ABX 0365 406 109 Ag—ABX 0278 353 152 ‘Ag-ABX 0366 254 1 10 AQ-ABX 02 79 286 153 AEABX 0368 366 111 Ag-ABX 0280 1571 154 Agitax 0369 313 1 12 AflBX 0281 573 155 AQ-ABX 0372 482 113 AgiBX 0282 371 156 Ag-ABX 0373 302 1 14 ALABX 0283 608 157 Ag-ABX 0376 1790 1 15 A9;ABX 0284 573 158 AgiBX 0377 1940 116 étABX 0285 51 1 159 Ag—ABX 0379 488 1 17 AqE-ABX 0290 991 160 Ai-ABX 0384 335 118 MEX 0291 377 161 AQ-ABX 0388 1329 1 19 Ag-ABX 0292 379 162 Ag-ABX 0390 1532 120 Ag-ABX 0294 385 163 Ag-ABX 0393 510 121 AtABX 0295 604 164 AgitBX 0394 532 122 AgiBX 0297 401 165 Ag-ABX 0395 589 123 AQABX 0300 1395 166 Aq—ABX 0396 1296 124 iAg-ABX 0310 1439 167 Ag-ABX 0398 410 125 Ag-ABX 0315 1480 168 Ag-ABX 0399 413 126 Ag-ABX 0316 1038 169 SAg-ABX 0401 1166 127 AgfiBX 0317 1873 170 AgiBX 0403 2117 128 Ag-ABX 0318 1407 171 AQ—ABX 0404 1331 129 AQ-ABX 0319 994 172 Ag-ABX 0405 489 150 Table 8 (cont’d). Mouse ID* Mouse # APTI Mouse ID* Mouse # APTI 173 AflEX 0407 1589 216 Ag-AEX 0522 2075 1 74 MEX 0409 510 21 7 gq-AEX 0523 562 175 MEX 0411 1995 218 AgitEX 0524 1175 176 AgitEX 0412 493 219 gtl-AEX 0526 1 133 177 AgitEX 0420 1 196 220 :AgitEX 0527 1000 178 Ag-AEX 0425 1025 221 ALAEX 0528 1302 179 Ag-AEX 0427 1 163 222 AgéAEX 0533 1787 180 ég—AEX 0428 1000 223 Ag-AEX 0534 408 181 Ag-AEX 0429 617 224 étAEX 0537 1053 182 AJLAEX 0430 1 157 225 Ag-AEX 0538 570 183 AgiEX 0431 1512 226 AflEX 0540 340 184 AtAEX 0432 602 227 Ag—ABX 0541 315 185 AgiEX 0433 1804 228 AgiEX 0542 1065 186 Ag-AEX 0434 1 1 14 229 Ag-AEX 0543 291 187 max 0436 2124 230 Ag-ABX 0544 2565 188 ALABX 0453 267 231 AgitEX 0547 565 189 AgfiEX 0455 421 232 fiAQ—AEX 0549 614 190 AgfiEX 0456 1003 233 AgitEX 0550 1065 191 Ag-AEX 0457 1228 234 AgiEX 0551 497 192 AgiEX 0458 577 235 Ag-AEX 0553 468 193 Ag-ABX 0459 566 236 MEX 0554 452 194 A -AEX 0460 588 237 Ag-AEX 0555 334 195 AgiEX 0463 499 238 ég-AEX 0556 1322 196 ALAEX 0465 1 190 239 AQAEX 0557 1527 197 Ag-AEX 0466 573 240 MEX 0558 530 198 Ag-AEX 0467 307 241 AgfiEX 0561 1500 199 AgiEX 0468 1536 242 Ag-AEX 0562 61 1 200 AgiEX 0489 561 243 AgitEX 0563 620 201 AQ-AEX 0490 1077 244 AgiEX 0564 1 192 202 ALAEX 0491 1354 245 Ag-AEX 0565 1201 203 AkAEX 0492 1501 246 Ag-AEX 0566 1484 204 max 0493 1743 247 Ag-ABX 0568 478 205 MEX 0496 1535 248 Ag-AEX 0569 1686 206 Ag-AEX 0498 1499 249 Ag-AEX 0570 1891 207 AQJAEX 0501 1324 250 AglAEX 0571 568 208 Agflax 0509 476 251 Ag-ABX 0572 2162 209 ALAEX 0512 1965 252 MEX 0575 1027 210 AflEX 0514 1047 253 Ag-ABX 0576 1545 21 1 Ag-AEX 0516 1599 254 Ag-AEX 0586 1627 212 ALABX 0517 1191 255 Max 0587 482 213 Ag—AEX 0518 1642 256 Ag-AEX 0590 1737 214 AMEX 0519 573 257 Ag-AEX 0593 1339 215 _AflEX 0521 1248 258 Ag-AEX 0617 1086 151 Table 8 (cont’d). Mouse lD* Mouse # APTI Mouse ID” Mouse # APTI 259 ALAEX 0618 1335 302 Ag-AEX 0741 587 260 fl-AEX 0620 1208 303 Ag-ABX 0742 1381 261 Ag—AEX 0621 1242 304 Ag-AEX 0743 1 516 262 AgiEX 0623 2433 305 AgiEX 0744 1760 263 Ag-AEX 0624 997 306 Ag-AEX 0745 1151 264 ALAEX 0628 453 307 MEX 0746 1592 265 Ag—AEX 0630 515 308 Pg-AEX 0747 1248 266 AflBX 0631 375 309 Ag-ABx 0748 610 267 Ag-AEX 0633 549 310 Pg-AEX 0749 467 268 Ag-AEX 0662 1031 311 Ag-AEX 0750 571 269 Ag-AEX 0663 1200 312 MEX 0751 2072 270 ALAEX 0664 1 101 313 ég-ABX 0753 553 271 Ag-AEX 0665 1432 314 AgiEX 0754 561 272 Ag—AEX 0668 1361 315 AfiAEX 0755 1417 273 AgiEX 0669 1310 316 AflAEX 0758 594 274 AflBX 0670 1713 317 max 0759 1145 275 AgiEX 0672 1319 318 Ag-AEX 0760 1 166 276 ég—AEX 0673 1075 319 Ag-AEX 0762 1343 277 AkAEX 0674 1224 320 AflEX 0764 434 278 Ag-AEX 0676 1985 321 AflEX 0765 1025 279 Ag-AEX 0678 2192 322 AgiEX 0766 407 280 AflEX 0679 1684 323 ALAEX 0767 1410 281 AMBX 0680 2512 324 AgfiEX 0774 1207 282 Ag-AEX 0681 1045 325 ALAEX 0776 1269 283 AgiEX 0684 1521 326 Ag-AEX 0777 1 102 284 ég-AEX 0685 1739 327 Ag-AEX 0778 1066 285 AEABX 0686 1282 328 Ag-AEX 0779 1810 286 ALAEX 0687 1546 329 MEX 0780 388 287 A9~AEX 0688 619 330 AgiEX 0793 1399 288 Ag-AEX 0689 984 331 ALAEX 0796 1841 289 Ag—AEX 0691 1295 332 Ag-AEX 0817 508 290 AgiXEX 0693 1563 333 Ag-ABX 0819 396 291 Al-ABX 0719 1009 334 Ag-AEX 0820 345 292 MEX 0720 507 335 Ag-AEX 0821 472 293 AgiBX 0721 1037 336 Ag-ABx 0825 369 294 fl-AEX 0729 1446 337 Ag-AEX 0838 471 295 AflEX 0730 335 338 AflEX 0839 525 296 AQ—AEX 0731 1 164 339 Ag-AEX 0844 1283 297 AQ—AEX 0734 1 179 340 AggEX 0845 1031 298 AgiEX 0737 616 341 Ag-AEX 0847 984 299 AflEX 0738 1480 342 Ag-AEX 0849 1 1 1 1 300 Ag-AEX 0739 1422 343 Ag-AEX 0853 203 301 Ag-AEX 0740 1501 344 Ag-AEX 0854 1054 152 Table 8 (cont’d). Mouse lD* Mouse if APTI Mouse lD* Mouse # APTI 345 ALAEX 0855 502 388 Ari-AEX 0947 270 346 iAg-ABX 0856 1693 389 AflEX 0948 526 347 AgéAEX 0857 1333 390 Ag-AEX 0949 396 348 A9_':ABX 0860 1088 391 Ag-AEX 0950 539 349 Ag;AEX 0861 1557 392 AQAEX 0951 393 350 AgiEX 0862 1570 393 Ag-AEX 0952 401 351 AEAEX 0864 618 394 AgitEX 0953 578 352 Ag-ABX 0865 1015 395 é$ABX 0954 515 353 Aq-AEX 0867 1091 396 Agj_EX 0955 1056 354 EABX 0869 1287 397 SALABX 0956 381 355 Ag-AEX 0870 1571 398 Ag-AEX 0957 401 356 AgiEX 0872 1389 399 AgiEX 0958 439 357 Agflx 0873 1240 400 AgitEX 0959 588 358 Ag-AEX 0875 1147 401 Ag-AEX 0960 565 359 Ag-ABX 0876 997 402 Ag-ABX 0961 364 360 Ag-AEX 0877 571 403 Ag-AEX 0962 504 361 Ag-ABx 0878 1251 404 Ag-ABx 0963 400 362 Ag-ABx 0879 593 405 max 0964 581 363 ALAEX 0880 1044 406 AgfiEX 0966 390 364 Agflax 0882 600 407 Aflx 0984 346 365 Aq—AEX 0883 594 408 Ag-AEX 0985 382 366 Ag-AEX 0891 1039 409 Ag-AEX 0986 373 367 ég-AEX 0892 570 410 Ag-AEX 0987 308 368 ALABX 0898 511 411 ALABX 0989 346 369 AfiAEX 0899 1090 412 Ag-AEX 0990 383 370 Ag-AEX 0902 398 413 AgfiEX 0991 434 371 ALAEX 0905 605 414 Ag-AEX 0992 438 372 Ag-ABX 0906 603 415 Ag-ABX 0993 388 373 AIL-AEX 0908 521 416 AQAEX 0994 491 374 ALAEX 0909 403 417 Ag—AEX 0995 494 375 iAg-AEX 0910 480 418 AQ—ABX 0997 195 376 AflEX 0911 292 419 AgiEX 0998 797 377 AgiEX 0912 238 420 rig-AEX 1000 507 378 ACL-AEX 0933 578 421 AgiEX 1019 1082 379 AflEX 0935 619 422 Ag-AEX 1020 529 380 égfiex 0938 450 423 Ag-ABX 1022 518 381 @AEX 0939 104 424 AkAEX 1026 1650 382 Ag-AEX 0940 369 425 Ag-AEX 1028 1567 383 ég-AEX 0942 475 426 Ag-AEX 1029 1161 384 Ag-AEX 0943 323 427 Aq-AEX 1031 1033 385 Aq-AEX 0944 474 428 Ag-AEX 1033 394 386 iAg-AEX 0945 323 429 Ag-AEX 1034 1 123 387 Ag-AEX 0946 474 430 Ag-AEX 1035 1015 153 Table 8 (cont’d). Mouse ID* Mouse # APTI Mouse ID* Mouse # APTI 431 :Ag-AEX 1036 1 174 441 AQ-AEX 1048 241 432 Ag-AEX 1037 1 131 442 Ag-ABX 1049 1 1 16 433 Ag-ABX 1038 471 443 Ag-ABX 1050 400 434 Aglotex 1040 607 444 Ag-ABX 1051 537 435 ég-AEX 1041 543 445 Ag-AEX 1053 101 1 436 Ag;AEX 1042 998 446 AkAEX 1055 2778 437 Ag-ABx 1043 4361 447 _Ag-ABX 1056 1025 438 Ag-ABX 1044 565 448 Ag-ABX 1057 513 439 Ag-ABX 1046 1138 449 Ag-ABX 1058 602 440 flAEX 1047 463 450 Ag-AEX 1059 1881 *450 AIJ backcross mice with extreme APTI values (104 5 APTI 3 620 and 797 5 APTI 34361) were given ID numbers (1-450). 154 Table 9. Genotyping data of 450 AIJ backcross mice by 37 markers leuse ID Marke4 Genotype Gata3 D2M355 D2M359 D2M117 D2M031 Prkcq Iera Mrc1 DZM416 D2M006 D2M080 Gad2 D2M465 D2M060 D2M081 D2M293 D2MO82 D2M417 D2M152 D2M235 D2M367 D2M238 D2M203 HC D2M298 4.5 CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO OOOOOOOOOllllllll112222222222333333333344444444445 12345678901234567890123456789012345678901234567890 AAAAAAAHHHAAAHAH-HAA-AHHHAHHHAHHAAAHHAAHA—AAHAAAAH X X AAAAAAHHHHAAA-AH-HAHHAHHHAHHHAHHAAAHHAAHA-AAHAAAAH X AAAAAAHHHHAAAHAH-HAAHAHHHAHHHAHHAAAHHAAHA-AAHAAAAH X AAAAAAHHHHAAAHAH-HAAAAHHHAHHHAHHAAAHHAAHA-AAHAAAAH X X AA-AAAAHHHAAAHAH-HAAHA-HH-HHHAHHAAAHHAAHA-AAHAAAAH AAAAAAAHHHAAAHAH-HAAHAHHHAHHHA--A-AHHAAHA--AHAAAAH AAAAAAAHHHAAAHAH-HAA-AHHHAHHHAAHAAAHHAAHA-AAHAAAAH AAAAAAAHHHAAAH-H-HAAHAHHHA--HAAHAAAH-AA-A-AAHA-AAH AAAAAAAHHHAAAHAH-HAAHAHHHAHHHAAHAAAHHAEHA-AAH-AAAH AAAAAAAHHHAAAHAH-HAAHAHHHAHHHAAHAAAHHAHHA-AAHAAAAH AAAAAA-H--AAAHAH-HAAHA-HHAHHHAAHAAAHHAH-A-AAHAAAAH AAAAAAA-HHAAA-AH-HAAHAHHHAHHHAAHAAAH-AHHA-AAH-AAAH AAAAAAAHHHAAAHAH-HAAHAHHHAHHHAAHAA-HHAHHA-AAHAA-AH AAA--AAHHHA---AH--AAH-H-HA---AAHAAAHHA-HA--AHA-AA- X AAAAAAAHHHAAAHAH-HAH-AHHHAHHHAAHAAAHHA-HA-AAH-A-AH AAAAAAAHHH-AA--H-HA-HAHHHAHHHAA-AAAHHAHHA-AAHAAAAH AAA-AAAHHHAAA-AH--AHH-HHHAH--:AHAAAH-AHHA-AAH-AAAH AAAAAAAHHHAAAHAH--AHHAHHHAHHHHAHAAAHHAHHA-AAH-AAAH AAAAAAAHHHAAAHAH-HAHHAHHHAHHHHAHAAAHHAHHA-AAH-AAAH AAAAAAAHH-AAA-A--H-~HAHH-AHHHHAHAAAH---H--AAHAA--H AAAAAAAHHHAA-HAH-HAHHAHHHAHHHHAHAAAHHAH-A-AAHAAAAH AAAAAAAHHHAAAHAH-HAHHAHHHAHHHHAHAAAHHAHHA-A-HAAAAH AAAAAAAHHHAAAHAH-H:HHAHHHAHH-HAHAAAHHAHHA-AAHA-AA- X AAAAAAAHHHAAAHAH-HAHHAHHHAHHHHAHAAAHHAHHA-AAHAAAAH X X AAA-HAAHHHA--HAH--AHH-H-HA---HAAAAAHHA-HA-AAH--AA- 155 5.4 CM X D2M323 AAAAHAAHHHAAAAAH—HAHHAHHHAHH—HAAAAAHHAHHA-AAH-AAAH 5.9 CM X D2M182 ——————— AHH —————————— H—H ----------- A --------- H--A-- 1.2 CM D2M38 O AAA-HAAAHHA--AAH--AHH-H-H----HHAAAAHHA-HA—A—H--AA- 1.5 CM D2M091 AAAAHAAAHHAAHAAH—HAHHAHHHAHHHHHAAAAHHAHHA—AAHAAAAH 7.6 CM X X X D2M011 —HA-HAAAHAA-——HHH—AHH-H—HA-———HAAAAHHA-HAAAAHA—AA- 1.4 CM DZMOlO -HA—HAAAHAA——AHH——AHH-H-HA-——HHAAAAHHA—HA-AAH——AA— 13.5 CM X X X X D2MO63 HHH—HAA———A—-AHA-—AH—-—-HH---HHAAA——HA--A-AA-A--H- 3.9 CM X X D2M307 HHH-HHA---A--AHA--AH----AH—--HHAAA--HA--A-AA-A--H- 8.7 CM X X DZM451 —HH—HHH---H—-AHA——AH-—-—AH———HHAAA——HA-—A—AA—A——H— 3.0 CM X D2M053 HHH-HHH--—H——AHH——AH———-AH--—HHAAA——HA—-A—AA-A—-H— 11.6 cM D2M113 —H——HHH—-—H---HHA-AH-—--AH—--—HAAA——HA-—AHAA—A——H— 4.4 CM DZMZOO HHH—HHH———H——AHH——AH——-—AH—-—HHAAA—-HA—-A—AA-A——H— #Recs: 01101131011001120023200011000101000000100000000010 Mbuse ID 0000000000000000OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO1 55555555566666666667777777777888888888899999999990 Marker Genotype 12345678901234567890123456789012345678901234567890 Gata3 HHHHAHAAHAH—AHAAAHAAAAAAAHAAAAHAAAHAH ----- HAAHAAHH 4.5 CM X X X X XX X D2M355 HHHHHHHAHAH-AHAAAHAAHAAAAHAAAAAAHHHHH ----- HAAHAAHH 1.6 CM X X D2M359 HHHHHHHAHAH—AHAAAHAAHAAAAHAAHAAAAHHHH ————— HAA-AAHH 0.8 CM X X D2M117 HHHHHHHAHAH—AHAAAHAAHAAAAHAAAAAAHHHHH ————— HAAHAA-- 0.5 CM D2M031 HHHHHHHAHAH—AHAAAHAAHAAAAHAAAAAAHHHHH ----- HAAHAAHH 1.2 CM X Prkcq HHHHHHHAHAH--HAAAHAAHAAAAHAAAAAAHHHHH ----- HAHHAAHH 1.6 CM Iera HHHHHHHAHAH-AHAAAHAAHAAAAHAAAAAAHHHHH ----- HAHHAAHH 2.4 CM Mrc1 HHHHHH-AHAH-AHAAAHAAHAAAAHAAAAAAHHHHH ————— HAHHAAHH 2.6 CM X X D2M416 HHHHHHHAHAH-AHHAAHAAHAAAAHAHAAA—HHHHH ----- HAHH—AHH 0.0 CM DZMO O 6 HHHHHHHAHAH-AHHAAHAAHAAAAHAHAAAAHHHHH ----- HAHHAAHH 0.0 CM 156 D2M080 Gad2 D2M465 D2MO60 D2MO81 D2M293 D2M082 D2M4l7 D2M152 D2M235 D2M367 D2M238 D2M203 HC D2M298 D2M323 D2M182 D2M380 D2MO91 D2M011 D2M01O D2MO63 D2M307 D2M451 D2M053 D2M113 D2M200 0.2 CM HHHHH-HA--H-AHHAAHAAHAAAAHAHAAAAHHH-H ----- HAHHAAHH HHHHHHHAHAH-AHHAAHAAHAAAAHAHAAAAHHHHH ----- HAHHAAHH HHHHHHHAHAH-AHHAAH-AH-AAAHAHAAAAHHHHH ----- HAHHAAHH X -HHHA-HAH---AHH-AHA--AAA--AHAA-AHHHHH ------ AH-AA-- HHHHAHHAHAH-AHHAAHAAHAAAAHAHAAAAHHHHH ----- HAHHAAHH X HHHHAAH-HAH--HHAA-AAH-AAAHA--A--HHHHH ----- HA-H-AHH X HHHHAAHAHAH"AAHAAHAAHAAAAHAHAAAAHHHHH ----- H-HHAAHH HHHHAAHAHAH-AAHAAHAAHAAAAHAHAAAAHHHHH ----- HAHHAAHH X AHHHAAHAHAH-AAHAAHAAHAAAAHAHAAAAHHHHH ----- HAHHAAHH AHHHAAHAHAH-AAHAAHAAHAAAAHAHAAAAHHHHH ----- HAHHAAHH AHHHAAHAHAH-AAHAAHAAHAAAAHAHAAAAHHHHH ----- HAHHAAHH AHHHA-HAHAH-AAHAAHAAHAAAAHAHAAAAHHH-H ----- HAHHAAHH AHHHAAHAHAH—AAHAAHAAHAAAAHAHAAAAHHHHH ----- HAHHAAHH AHHHAAHAHAH-AAHAAHAAHAAAAHAHAAAAHHHHH ----- HAHHAAHH X X X -HHHA-HAH---AAHHAHH--AAA-HAHAAHAHH--H ------ AH-AA-- AHHHAAHAHAH-AAHHAH-AHAAAAHAHAAHAHHHHH ----- HAHHAAAH X ------- AH--------—H--H----—H-AHA—-----------H----- X -HHHA-AAH---AAHHAHH--A-A-HAHAAHAHHAHH ------- H-AH-- X X AHHHAAAAHAH-AAHH--HAAH--AH-HAAHAHHAHH ----- HA-HAAAH X X X -HHA--AAH--HAAHHAHH--HAA-HAHAAHAHHAAHHHAAH-AH--H-- X -HHAA-AAH---AAHHAHH--HAA—HHHAAHAHHAAH ------ AH--H-- XX X X --HAA-A ----- HHHHHH----AA—-H-A---HHAAA ------ A--AH-- X —-AAA-A ----- HHHHHH-—--AA--H-A---HHAAA ------ A--AH-- X --AAA-A ----- HAHHHH----AA--H-A---HHAAA ------ A--AH-- --AAA-A ----- HAHHHH----AA--H-A---HHAAA ------ A--AH-- X X --AA--H ----- HAHHHH----AH--H-A---HHAAAAAAAA-A---H-- X X X --AHA-H ----- HAAHHH----AH--H-A---AHAAA ------ A--AH-- —_—-——_——_——_—__———____—__——._..—_____._.————_—___r_——_—_____————______——__—_____— _————__—____._.—_._.______—_____.._._.___——._.__—_—_—__.._.______.—.____.________—_——_— leuse ID 11111111111111111111111111111111111111111111111111 OOOOOOOOOlllllll1112222222222333333333344444444445 Marker lGenotype 12345678901234567890123456789012345678901234567890 Gata3 HAHHHHHAHHAAHAAAAAAHAA---HA-AAH-A-AA---HH-AHA ----- 4.5 CM X X X D2M355 HHHHHHHHHHAA-AAAAAAHAA-—-HA—A-H—H-AA-—--HAAHA ----- 1.6 CM D2M359 --H-HHH-HHAAHAAAAAAHAA---HA-AAH-H-AA---HHAAHA ----- 0.8 CM D2M117 HAHHHHHHHHAAHAAAAAAHAA---HA—AAH—H-AA-—-HHAAHA ----- 0.5 CM D2M031 HAHHHHHHHHAAHAAAAAAHAA———HA—AAH—H—AA-—-HHAAHA ----- 1.2 CM Prkcq HAHHHHHHHHA-HAAAAAAHAA--~HA-AAH-H-AA----HAAHA ----- 1.6 CM X X Iera HAHHHHHHHHAAHA-AAAAHAA---HA-AHH-H-HA---HHAAHA ----- 2.4 CM X X Mrc1 HAHHHHHHHHAAHAAAAAA-AA---HA—AAH-H-AA---HHAAHA ----- 2.6 CM X X D2M416 HHHHHHHHHHAAHAAAAA-HAA——-HA-AAH—H-AA-—-HHAAAA ————— 0.0 CM D2M006 HHHHHHHHHHAAHAAAAAAHAA---HA-AAH-H-AA---HHAAAA ----- 0.0 CM D2M080 HHHHH—H-HHAAHA-AAAAH-A—--H--AAH—H—AA—-—-HAAAA ----- 0.5 CM Gad2 HHHHHHHHHHAAHAAAAAAHAA---HA-AAH-H—AA-—-HHAAAA ----- 0.0 CM D2M465 HHHHHHHHHHAAHAAAAAAHAA---HA-AAH-H-AA---H-AAAA ----- 0.7 CM D2MO6O --H-HH--HHA-H--A-AAH-A ----------------- HHAA ------- 0.7 CM D2M081 HHHHHHHHHHAAH-AAAAAHAA---HA-AAH—H-AA---HHAAAA ----- 1.4 CM D2M293 -H-H-HHHH—-A-AAAAAAHAA-—-HA-AAH-H-AA—--—HAAAA ----- 1.6 CM D2M082 HHHHHHHHHHAAHAAAAAAHAA—-—HA-A-H-H—AA--—HHAAAA ————— 0.5 CM D2M417 HHHHHHHHHHAAHAAAAAAHAA--—HA—AAH—H-AA——-HHAAAA ----- 2.4 CM X XX X D2M152 AHHHHHHHHHAAHAHHAAAHHA—-—HA—AAH-H—AA—-—HHAAAA ----- 0.2 CM D2M235 AHHHH-HHHHAAHAHHAAAHHA---HA-AAH-H-AA---HH-AAA ----- 0.2 CM x D2M367 AHHHHHHHHHAAHAHHAAAHHA---HA-AAH-H-AH---HHAAAA ----- 0.5 CM D2M238 AHHH-HHHHHAAHAHHAAAHHA-—-HA-AAH-H-AH---HHAAAA ----- 0.2 CM D2M203 AHHHHHHHHHAAHAHHAAAHHA-—-HA-AA—-H-AH—--HHAAAA ----- 0.7 CM X HC AHHHHHHHHHAAHAHHAAAHHA—--HA—AAH—H—AH——-HHHAAA ————— 5.4 CM D2M298 —-H-HH-—HHA-H—-H—AAH—A ————————————————— HHHA ------- 5.4 CM D2M323 AHHHHHHHHHAAHAHHAAAHHA—-—HA-AAA-H—AH-—-HHHAAH ----- 5.9 CM 02M182 ——————————————— H ———————————————————————— H ————————— D2M380 --H-HH--AHH-H——H—AHH-A ————————————————— HHHA _______ 1.5 CM D2MO91 AHHHHHHHAHHAHAHHAAHHHA——-HH-AAA—H—AH—-—HHHAAH ----- 7.6 CM D2M01l --H—HH--AHH-H-—H-AHH-AHH—-—H--—A-H--H-A-HHA--HHHHH 1.4 CM D2M01O --H-HH--AHH-H--H—AHH-A ----------------- HHHA ------- 13.5 CM D2M063 --H-H---AHH—H—--—AHH—A ----------------- H-HA ------- 3.9 CM D2M307 --H-H---AHH ------ AHH-A ----------------- H-HA ------- 8.7 CM D2M451 --H—H—-—AHH-H——--AHH—A ————————————————— H—HA ------- 3.0 CM D2M053 --H-H---AHH ------ AHH-A ----------------- H—HA ——————— 11.6 CM X XX D2M113 ——A—H—--HAH—A—-——AHH—AHHA——H———H—H——H—A—-HA--HAHHH 4.4 CM D2M200 --A-H—-—HAH-A—--—AHH—A ————————————————— H-HA ——————— [Mouse ID 11111111111111111111111111111111111111111111111112 55555555566666666667777777777888888888899999999990 Marker Genotype 12345678901234567890123456789012345678901234567890 Gata3 ----HHHAHHAAHHHHHAAAHHHHAAAAAAHAHHAAAAHAHAHAAAAHAH 4.5 CM X D2M355 ----HHHAHBAA-HHHHAAAH-HHAHAAAAHAHHAAAAHAH-HAAAAHAH 1.6 CM D2M359 ---—HHHAHHAAHH~H—AAAHHHHAHAAAAHAHH—A-—HAHAHAAAAHAH 0.8 CM D2M117 ----- HHAHHAAHHHHHAAA—HHHAHAAAAHA-H-AAAHAHAHAAAAHAH 0.5 CM DZMO31 ----HHHAHHAA-HH-HAAAH-HHA-AAAAHAHHAAAA-AHAHAAAAHAH 1.2 CM Prkcq ----HHHA-HAAHHHHHAAAHHHHAHAAAAHAHHAAAAHAHAHAAAAHAH 1.6 CM Iera ----HHHAHHAAHHHHHAAAHHHHAHAAAAHAHHAAAAHAHAHAAAAHAH 2.4 CM Mrc1 ----HH-AHHAAHHHHHAAAHHHHAHAAAAHAHHAAAA—AHAHA-AAHAH 2.6 CM D2M416 ----HHHAHHAAHHHHHAAAHHHHAHAAAAHAHHAAAAHAHAHAAAAHAH 0.0 CM D2MOO6 —--—HHHAHHAAHHHHHAAAHHHHAHAAAAHAHHAAAAHAHAHAAAAHAH 0.0 CM D2M080 ----HHHAHHAAH-HHHAAA-HHHAHAAAAHAHHAAAAHAHAHAA--HA- 0.5 CM Gad2 ----HHHAHHAA-HHHHAAAHHHHAHAAAAHAHHAAAAHAHAHAAAAHAH 0.0 CM 159 D2M465 ----HHHAHHAAHHHHHAAAHHHHAHAAAAHAHHAAA-HAHAHAAAAHAH 0.7 CM D2MO6O ----HHHAHHAAH--HHA-AHHHHAH ------ H-A-AAH ----- A--HA- 0.7 CM D2MO81 ----HHHAHHAAHHH-HAAAHHHHAHAAAAHAHHAAAAHAHAHAAAAHAH 1.4 CM D2M293 ----HHHAHHAA-HHHHAA-HH---HAAAAHAHHAAAAHAHAHA—AAHAH 1.6 CM X D2M082 ----HHHAHHAAHHHHHAAAHHHHAHAAAAHAHHAAAAHAHAHHAAAHA- 0.5 CM DZM417 ----HHHAHHAAHHHHHAAAHHHHAHAA-AHAHHAAAAHAHAHHAAAHA- 2.4 CM D2M152 ---—HHHAHHAAHHHHHAAAHHHHAHAAAAHAHHAAAAHAHAHHAAAHAH 0.2 CM D2M235 ---—HHHAHHAAHHHHHAAAHHHHAHAAAAHAHHAAAAHAHAHHAAAHAH 0.2 CM D2M367 ----HHHAHH—AHHHHHAAAHHH—AHAAAAHAHHAAAAHAHAHHAAAHAH 0.5 CM D2M238 ----HHHAHHAAHHHHHAAAHHHHAHAAAAHAHHAAAAHAHAHHAAAHAH 0.2 CM D2M203 ----HHHAHHAA-HHHHAAAHHHHAHAAAAHAHHAAAAHAHAHHAAAHAH 0.7 CM HC ----HHHAHHAAHHHHHAAAHHHHAHAAAAHAHHAAAAHAHAHHAAAHAH 5.4 CM D2M298 ----HHHA-HAAH--HHA—AHH-HAH ------ H-A-AAH ----- A--HA- 5.4 CM X X X D2M323 -—--HHHAHHAAAHH-AAA-HHAHAHAAAAHHHHAAAAHAHAHHHAHHAH 5.9 CM D2M182 —---H——-H-A --------- HH—H ———————— H-A-AAH --------- A- l.2 CM D2M38O --—-HHHAHHAHA--HAA-AHHAHAH ------ H—A—AAH ----- H--HA- 1.5 CM D2MO91 ----HHHAHHAHAHHHAAAAHHAHAHAAAAHHHHAAAAHHHAAHHAHHAH 7.6 CM X D2M011 AHHAHHHHHHAH---H-A-AHHAHA ------- H-A-AAH --------- A- l.4 CM X D2M010 ----HHHHHHAHA--HAA-AHHAHHH ------ H-A-AAH ----- H--AA- 13.5 CM D2MO63 ----- HHH-H-HA---AA-A----HH ------------------ H—-A-- 3.9 CM DZM307 ----- HHH-H-HA---AA-A--A-HH ------------------ H--A-- 8.7 CM X DZM451 ----- HHH-A-HA—--AA-A--A-HH —————————————————— H——A—— 3.0 CM X D2M053 ----- HHH-A-HA---AA-A--A-HH ------------------ A--A—- 11.6 CM X DZMll3 AHHA-HHH-A-H----AA-H--A-H ------------------------- 4.4 CM D2M200 ----- HHH-A—HA—--AA-H-—A-HH ------------------ A-—A-- #Recs: OOOOOOOlOlOOlOOOlOOlOOOOllOOOOOOOOOOOOOOOOO1200000 _~—h‘ “ ‘___“_____————_—————-—-———————__————————_——____——————_———_—____———H-— 160 Mbuse ID 222222 22222 222222 2222 22222 222222222222 00000000011111111112 22222 33333 344444444445 Marker Genotype 12345678 0123456 89 3456 23 89012 567890 Gata3 A AAAHHHAHAHAAAHAHAHHAHHHAHAHAAHAHHHAAAAHAAHHAHAAH 4 5 CM X D2M355 A AAAHHHAHAHAAAHAHAHHAHHHAHA~AAHAHHHAAAAHAAHHAH~AA l 6 CM X D2M359 A AAAHHHAHAHAAAHAHAHHAHHHAHAHAAHAHHHAAAAHAAHHAHAAH O 8 CM D2M117 AHAAAHHHAHAHA~AHAHAHHAHHHAHAHAAHAHHHAAAAHAAHHAH~AH O 5 CM D2MO31 AHAAAH-HAHAHA~~HAHAHHAHHHAHA~AAHAHHHAAA~HAAHHAHAAH l 2 CM Prkcq A AAAHHHAHAHAAAHAHAHHAHHHAHAHAAHAHHHA~AAHAAHHAHAAH 1 6 CM Il2ra A AAAHHHAHAHAAAHAHAHHAHHHHHAHAAHAHHHAAAAHAAHHAHAAH 2 4 M MrCl AHAAAHHHAHAHAAAHAHAHHAHHHHHAHHAHAHHHAAA‘HAAHHAHAAH 2 6 CM D2M416 A AAAHHHAHAHAAAHAHAHHAHHHHHAHHAHAHHHAAAAHAAHHAHAA O 0 CM D2MOO6 AH.AAHHHAHAHAAAHAHAHHAHHHHHAHHAHAHHHAAAAHAAHHAHAA O O M D2M080 AHAAAHH~AHAH~~~~A AHHAHHHHHAHHA~AHHHAAA~H~~~~AHAA~ 0.5 CM Gad2 AHAAAHHHAHAHAAAHAHAHHAHHHHHAHHAHAH HAAA HAAHHAHAA O 0 CM D2M465 AHAAAHHHAHAHAAAHA~AHHAHHHHHAHHAHAHHHAAAAHAAHHAHAA O 7 CM D2MO6O ~HAAAHHHA~A‘A ~~~~~~~ HAH~~HH~HH~~~HHHAAA~H~~~~AHAA~ O 7 CM D2M081 AAAHHHAHAHAAAHAHH~HAHHHHHAHHAHAHHHAAAAHAAHHAHAA l 4 CM X D2M293 A~~AA ~~AHAHAAAHAHHH~A~HH~HAH~AHA~HAAAAAHAAHHAHAAH l 6 CM 02M082 A AAAHHHAHAHAAAHAHHHHAHHHHHAHHAHAHHAAAAA~AAH~AHAAH O 5 CM X D2M417 A AAAHHHAHAHAAAHAHHHHAHHHHHAHHAHAHHAAAAAAAAHHHHAAH 2 4 CM X D2M152 A AAAHHHAHAHAAAHAHHHHAHHHHHAHHAHAHHAAAAAAAAHH~HHAH O 2 CM D2M235 AAAHH~AH~HAAAHAHHHHAHHHHHA‘HAHAHHAAAAAAAAHH~HHAH O 2 CM D2M367 A AAAHHHAHAHAAAHAHHHHAHHHHHAHHAHAH~AAAAAAAAHHHHHAH O 5 CM DZM238 AHAAAHHHAHAHAAAHAHHHHAHHHHHAHHAHAHHAAAAAAAAHHHHHAH O 2 C. 02M2O3 A AAAHHHAHAHAAAHAHHHHAHHHHHAHHAHAHHAAAAAAAAHHHHHAH O 7 CM HC AHAAAHHHAHAHAHAHAHHHHAHHHHHAHHAHAHHAAAAAAAAHHHHHAH 5 4 CM X D2M2EN3 ~HAAAHHHA‘A‘A ~~~~~~~ HAH~~HH~HH~‘~HAAAAA~A~~~-H—HA‘ 5 4 CM D2M3233 HAAAHHHAHAAAHAHAAHHHAHHHHHAAHAHAHAAAAAAAHAHHHHHAH 5 9 CM X X DZMIBQ? ~~AAHH~A~~A‘A ~~~~~~~ H~H ~~~~~ A ~~~~~ A~AAA~A~~~~HHHA~ 1. CM D2M380 1. CM D2MO91 7. CM D2M011 1. CM D2M010 13. CM D2MO63 3. CM D2M307 8. CM D2M451 3. CM D2MO53 11. CM D2M113 4. CM D2M200 #Recs: leuse ID Marker Genotype Gata3 4. CM D2M355 1. CM D2M359 0. CM D2M117 0. CM D2M031 1. CM Prkcq 1. CM 112ra 2. CM Mrc1 2. CM D2M416 0. CM D2M006 0. CM D2M080 0. CM Gad2 CM —HAAHHHAA-A-A ------- HAH--HH-AH——-HAAAAA—A----H-HA- AHAAZHHAA-AAAHAHHAHHHAHHHHHAAHHHAHAAAAAAAHAHHHHHAH -HAA:H—A—-A—A ——————— H—H ————— AH---HA-A:A-A----HHHA- -HAAHHHAA-A-A ------- HHH--HH—AH—--HAAAHA—A————HHHA— x —————— A-A--———-—-———-H-—~HH~-—-————A—--—-—-----—-- —————— A-A————----—---H—--HH-—-——--—A—-—--—----—--— —————— A-A---—-----—-—H-—-HH--——-——-A--------———-—- ------ A-A--—-——--———-H—--HH---—----A—--——--——-—--— ------ A—A----—-————-—H---AH——-—————H--—--———-———-— 66663611656661666666666661661166661161656666615165 22222222222222222222222222222222222222222222222223 55555555566666666667777777777888888888899999999990 12345678901234567890123456789012345678901234567890 AAAAAAAHHAHAHAHAHHHAAAHAHHAAAHAHAAAAHHHAHAHAAHHAHA AAAAAAAHHAHAHAHAH-HAAAHAHHAAAHAHAAAAH-HAHAHAAHHEHA AAAAAAAHHAHAHAHAHHHAAAHAHHAAAHAHAAAAHHHAHAHAAHHHHA AAAAAAAHHAHAHAHAHH-AAAHAHHAAAHAHAAAAHHHA-AHAAHHHHA AAAAAAAHHAHAHAHAHHHAAAHAHHAAAHAHAAAAHHHAHAHAA-HHHA AAAA-AAHHAHAHAHAHHHAAAHAHHAAAHAHAAAAHHHAHAHAAHHHH- X AAAAAAAHHAHAHAH-HHHAAAHAHHAAAH--AAHAHHHAHAHAAHHHHH X X -AAAAAAHHAHAHAHAHHHAAAHAHHAAAHA-AAAAHHHAHAHAAHHH-A X AAAAAAAHHAHAHAHAHHHAAAHAHHAAAHAHAAA-HHHHHAHAAHHHHA AAAAAAAHHAHAHAHAHHHAAAHAHHAAAHAHAAAAHHHHHAHAAHHHHA AAAAAAAHH--AHA-AHH-AAAHAHHAAAHAHAAA-HH-HHAHAAHHHHA X HAAAAAAHHAHAHAHAHHHAAAHAH--AAHAHAAAAHHHHHAHAAHHHHA 162 D2M465 D2MO6O D2M081 D2M293 D2M082 DZM417 D2M152 D2M235 D2M367 D2M238 D2M203 HC D2M298 DZM323 D2M182 D2M380 D2MO91 D2M011 D2M010 D2MO63 D2M307 D2M451 DZMOSB D2M113 D2M200 0.2 CM 0.2 CM 0.5 CM 0.2 CM 3.9 CM #Recs: HAAAAAAHHAHAHAHAHHHAAAHAHHHAAHAHAAAAHHHHHAHAAHHHHA H-AA-AA-H--A ————————————————————————————— A—AA—--HA H-AAAAAHHAHAHAHAHHHAAAHAHHHAAHA-AAAA-AHHHAHAAHHHHA X X X -AAAA-AHHHHAHAHAHHHAAAHAHHHAAHAHAAAAHAHHHHHAAHAHH- HAAAAAAHHHHAHAHAHH-AAAHAHHHAAHAHAA--HAHHHHHAAHAHHA HAAAAAAHHHHAHAHAHHHAAAHAHHHAAHAHAAAAHAHHHHHAAHAHHA HAAAAAAHHHHAHAHAHHHAAAHAHHHAA-AHAAAAHAHHHHHAAHAHHA HAAAAAAHHHHAHAHAHHHAAAHAHHHAAHAHAAAAHAHHHHHAAHAHHA HAAAAAAHHHHAHAHAHHHAAAHAHHHAAHAHAA-AHAHHHHHAAHAHHA HAAAAAAHHHHAHAHAHHHAAAHAHHHAAHAHAAAAHAHHHHHAAHAHHA HAAAAAAHHHHAHAHAHHHAAAHAHHHAAHAHAAAAHAHHHHHAAHAHHA HAAAAAAHHHHAHAHAHH-AAAH-HHHAAHAHAAAAHAHHHHHAAHAHHA H-AA—A-—H——A ----------------------------- H-AA-—-HA X HAAAAAHHHHAHHAAAHA-AA—HAAH-AAHAHAAAAAAHHAHHAAHAHHA H—AA-AH—H-—H ————————————————————————————— H-AA--—HA H-AA-AH—H—-H ————————————————————————————— H—AA—--HA HAAAAAHHHHAHHAAAHA-AAAHAAHHA-HAHAA-AAAHHAHHAA-AHH- H—AA—AH-H--H ————————————————————————————— H-AA--—HA H-AA-AH-H--H ————————————————————————————— H—AA—--HA ——_———————————————————————————————_._—————-—-——-——— 100000000101000OOOOOOOOOOOOOOOOOOOZOOOO10100001101 ._—_u—_———_—_—-——_.—_._.__——..__._m_—__.__—___——____—————______._____————_———_—_H—— 163 lMouse ID Marker I Genotype Gata3 D2M355 D2M359 D2M117 D2M031 Prkcq 112ra Mrc1 D2M416 D2MOO6 DZMOBO Gad2 D2M465 D2MO6O D2M081 D2M293 D2M082 D2M417 D2M152 D2M235 DZM367 D2M238 D2M203 HC D2M298 D2M323 D2M182 CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM 33333333333333333333333333333333333333333333333333 00000000011111111112222222222333333333344444444445 12345678901234567890123456789012345678901234567890 HHHHAHHHAHAHHAAAHHAAAHHHAAHHAHAAAHHAHAHAAAHHHAAAAH X X HHHHHHHHHHAHHAAAHHAAAHHHAAH-AHAAAHH-HAHAAAHHHAA-AH X HHHHHHHHAHAHHAAAHHAAAHHHAAHHAHAAAHHAHAHAAAHHHAAAAH —HHHH-HHAHAHHAAAHHAAAHHHAAHHAHAAAHH—HAHAAAHHHAA—AH HHHHHHHHAHAHHAAAHHAAAHHHAAHHAHAAAHHAHAHAAAHHHAAAAH HHHHHHHHAHAHHAAAHHAAAHHHAAHHAHAAAHHAHAHAAAHHHAAAAH HH—HHHHHAHAH—AAAHHAAAHHHAAHHAHAAAHHAHAHAAAHHHAAAAH x xx HHHHHHHHAHAHHAAAAHAHHHHHAAHHAHAAAHHA-AHAAAHHHA-AAH x x x HHHHHHHHAHAHAAAAAHAHHHHAAAHHAHHAAHHAAAHAAAHHHAHAAH HHHHHHHHAHAHAAAAAHAHHHHAAA-HAHHAAHHAAAHAAAHHHAHAAH HHH—HH—HAHAHAAAAAHAHHHHAAAHHAHHAAHHAAAHAAAHHHAHAAH HHHHHHHHAH—HAAAAAHAHHHHAAAHHAHHAAHHAA-HA—AHHHAHAAH HHHH-HHHAHAHAAAAAHAHHHHAAAHHAHHAAHHAAAHAAAHHHAHAAH H--HH-H——H-H-—A---—H-H —————— A-HAAH-—--H ----------- HHHHHHHHAHAHAAAAAHAHHHHAAAHHAHHAAHHAAAHAAAHHHAHAAH —H—HHHHHA-EHAAAAAHAHHHHAAAHHAHHAAHHAAAHAAAHHHAHAAH HHHHHHHHAHHHAAAAAHAHHHHAAAHHAHHAAHHAAAHAAAHiHAHAAH HHHHHHHHAHHHAAAAAHAHHHHAAAHHAHHAAHHAAAHAAAHAHAHAAH HHHHHHiHAHHHAAAAA—AHHHHAA-HHA—HAAHH-—AHAA—HAHAHA-- :HHHHHAHAHHHAAAAAHAHHHHAAAHHAHHAAHHAAAHAAAHAHAHAAH AHH—HHAHAHHHAAAAAHAHHHHAAAHHAHHAAHHA-AHAA—HAHAHAAH AHHHHHAHAHHHAAAAAHAHHHHAAAHHAHHAAHHAAAiAAAHAHAHAAH AHHHHHAHAHHHAAAAAHAHHHHAAAHHAHHAAHHAAAAAAAHAHAHAAH AHHHHHAHAHHHAAAAAHAHHHHAAAHHAHHAAHHAAAAAAAHAHAHAAH A~HHH—A——H-H--A--—-H—H —————— A-HAAH----A ----------- AHHHHAAHAHHHAAAAAHAHHHHAAAHHAHHAAHHAAAAAAAHAAAHAHH x A--HH—A--A—H--A———-H-H ------ A—-AAH ---------------- 164 D2M380 D2MO91 D2M011 DZMOlO D2MO63 D2M307 D2M451 D2M053 D2M113 DZMZOO 1. CM 1. CM 7. CM 1. CM 13. CM 3. CM 8. CM 3. CM 11. CM 4. CM #Recs: lMouse ID Markerl Genotype Gata3 D2M355 D2M359 D2M117 D2M031 Prkcq Iera Mrc1 DZM416 D2MOO6 DZMO8O Gad2 CM CM CM CM CM CM CM CM CM CM CM CM A-HHH-A--A-H-—A----H—H--—--—A-HAAH----A ——————————— AHHHHAAHAAHHA-AAAHHHH--AAHHHAHHA-HHHAHAAAAHAAAHAHH A--:H—A—-A-H--A---—H-H —————— A—-AAH ———————————————— A—HAH-A--A-H--A--—-H-H—---——A—HAAH----A ----------- ______________________________ H___-___A___________ ——A ——————————————————————————— H ——————— A ----------- x x -—A --------------------------- A ------- H ----------- --A ——————————————————————————— A ——————— H ——————————— --A --------------------------- A ——————— H ----------- 15611616211616661661165166666636666668266661666666 33333333333333333333333333333333333333333333333334 55555555566666666667777777777888888888899999999990 12345678901234567890123456789012345678901234567890 HHHHAAAHHHHHAAAAAHAHHHAAAHHHHHHHHAAHHAHHAAHHHHHHAA HHHHAA--HHHHAAAAAH-HHHAAAHHHHHHH-AA-HAHHAAHHHHHHAA HHHHAAAHHHHHAAAAAHAHHHAAAHHHHHHHHAAHHAHHAAHHHHHHAA HHHH"AAHHHHHAAAAAHAHHHAAAHHHHHHHHAAHHAHHAAHHHHHHAA HHHHAAAHHHHHAAAAAHAHHHAAAHHHHHHHHAAHHAHHAAHHHHHHAA X X HHHHAAHHHH-HAAAAAH-HHHAAAHAHHHHHHA-HHAHHAAHHHHHHAA X HHH-AA-HHHHHAAAAAHAHHHAAAHHHHHHHHAAHHAHHAAHHHHHHAA HHHHAAAHHHHHAAAAAHAHHHAAAHHHH-HHHA-HHAHHAAHHHHHHAA HHHHAAAHHHHHAAAAAHAHHHAAAHHHHHHHHAHHHAHHAAHHHHHHAA HHHHAAAHHHHHA--AAHAHHHAAAHHHHHH-HAHHHAHHAAHHHHHHAA HHHHAAAHHHHHAAAAAHA-HHAAAHHHHHHH-AHHHAHHAAHHHHHHAA HHHHAAAHHHHHAAAAAHAHHHAAAHHH-HHHHAHHHAHHAAHHHHHHAA 165 D2M465 D2MO6O D2M081 D2M293 D2M082 D2M417 D2M152 D2M235 D2M367 D2M238 D2M203 HC D2M298 D2M323 D2M182 D2M380 D2MO91 D2M011 D2M010 D2MO63 D2M307 D2M451 D2M053 D2M113 DZMZOO 13.5 CM #Recs: HHHHAAAHHHHHAAAAAHAHHHAAAHHHHHHHHAHHHAHHAAHHHHHHAA _______________________________ H------------------ HHHHAAAHHHHHAAAAAHAHHHAAAHHHHHHHHAHHHAHHAAHHAHHHAA HHHHAAAHHHHHAAAAAHAHHHAAAHHHHHH-HAHHHAHHAAHHAHHHAA HHHHAAAHHHHHAAAAAHAHHHAAAHHHHHHHHAHHHAHHAAHHA-HiAA HHHHAAAHHHHHAAAAAHAHHHAAAHHHHHHHHAHHHA-HAAHHAHHAAA X HHHHAAAHHfliHAAA-AHAHHHAAAHHHHHHHHHHHHAHHAAHHAHHAAA HHHHAAAHHHAHAAAAAHAHHHAAAHHHHHH-HHHHHAHHAAHHAHHAAA HHHHAAAHHHAHAAAAAHAHHHAAAHHHHH—HH--HHAHHAAHHAHHAA- HHHHAAAHHHAHAAAAAHAHHHAAAHHHHHHHHHHHHAHHAAHHAHHAEA HHHHAAAHHHAHAAAAAHAHHHAAAHHHHHHHHH-HHAHHAAHHAHHAHA HHHHAAAHHHAHAAAAAHAHHHAAAH-HHHHHHHHHHAHHAAHHAHHAHA _______________________________ H____._._.____________ HAHHAAAHHHAHAAHAHHAHHHAAAHHHHHHHAHHAHAHAAAHHAHHAHA OOOOOO1000lOOOOOOOOOOOOOOOZOOOOOOlCOOOOOOOOOOOOl10 fl__-___———_—___._——___—_—..—____._____.___—__________—_____—._____————-—___—_—fi_—_—_ 166 leuse ID Marker lGenotype Gata3 D2M355 D2M359 D2M117 D2M031 Prkcq 112ra Mrc1 D2M416 D2MOO6 D2M080 Gad2 D2M465 D2MO6O D2M081 D2M293 D2M082 D2M417 D2M152 D2M235 DZM367 D2M238 D2M203 HC D2M298 D2M323 DZM182 CM CM CM CM CM cM CM CM CM cM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM CM 44444444444444444444444444444444444444444444444444 00000000011111111112222222222333333333344444444445 12345678901234567890123456789012345678901234567890 AHHAAAHAHHHAHHHAAHHAAHHHHAHHAAHHHHHHHAHAAAHHHHAHHA A-HAAEHAHHH-HHHAAH-AAHHH-A-HAAHHHHHHHAHAAAHHHHAHHA AHHAAXHAHHHAHHHAAHHAAH‘HHAHHAAHHHHHHHAHAAAHHHHAHHA AHHAAAHAHHH-HHHAA-HAAHHH-AHHAAHHHHHHHAHAAAHHHHAHHA AHHAAAHAHHH-HHHAAHHAAHHHHAHHAAHHHHHHHAHAAAHHHHAHHA AHHAEAHAHHH-H-HAA-HA-HHHHA--AAH-HHHHHAHAAAHHHHAHHA AHHAHAHAHHH-HHHAAHHAAH-H-AHHAAHHHHHHHA-AAAHHHHAHHA AHHAHAHAHH--H-HAAHHAAHHHHAHHAAHHHHHHHAHAAAHHHHAHHA AHHAHAHAHHHAHHHAAHHAAHHHHAHHAAHHHHHHHAHAAAHHHHAHHA AHHAHAHAHHHAHHHAAHHAAHHHHAHHAAHHHHHHHAHAAAHHHHAHHA AHHAHAHAHHHAHHHAAHHAAHHHHAHHAAHHHHHHHAHAAAHHHHAHHA AHHAHAHAHHH-H-HAAHHAAHHHHAHHAAHHHHHHHAHAAAHHHHAHH- AHHAHAHAHHHAHHHAAHHAAHHHHAHHAAHHHHHHHAHAAAHHHHAHHA ----------------------------- A-------------------A AHHAHAHAHHHAHHHAAHHAAHHHAAHHAAHHHHHHHAHAAAHHHHAHHA AHHAHAHAHHHAHHHAAHHAAHHHAAHHAAHHHHHHHAHAAAHHHHAHHA :HHAHAHAHHHAHH-AAHHAAHHHA-HHAAHHHHHHHAHAAAHHHH-HHA HHHAHAHAHHHEHHHAAHHAAHHHAAHHAAHHHHHHHAHAAAHHHHAHHA HHHAHAHAHHHHHHHAAHHAAHHHAAHHEAHHHHHHHAHAAAHHHHAHHA HHHAHAHAHHHH-HHAAHHAAHHHAAHHHAHHHHHHHAHAAAHHHHAHHA HHHAHAHAHHHHHHHAAHHAAHHHAAHHHAHHHHHHHAHAAAHHHHAHHA HHHAHAHAHHHHHHHAAHHAAHHHAAHHHAHHHHHHHAHAAAHHHHAHHA HHHAHAHAHHHHHHHAAHHAAHHHAAHHHAHHHHHHHAHAAAHHHHAHHA HHHAHAHAHHHHHHHAAHHAAHHHAAHHHAHHHHHHHAHAAAHHHHAHHA ----------------------------- A----------A--------A HHHAHAHAHHHHHHHAAAHHAHAHAAHHHAHHAHHHHAHAAHHHHHAHHA ————————————————————————————— A—-----—---A-———-—-—A D2M380 D2MO91 D2M011 D2M010 D2MO63 D2M307 D2M451 D2M053 D2M113 DZMZOO 1. CM 1. CM 7. CM 1. cM 13. CM 3. CM 8. CM 3. CM 11. CM 4. 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