Identification of candidate genes and isoforms associated with genetic resistance to Marek's disease from RNA-Seq data
Marek's disease (MD) in chickens is characterized by T celllymphomas caused by the Marek's disease virus (MDV), anα-herpesvirus. MD is a major economical problem forthe poultry industry as it causes approximately $2 billionin worldwide losses annually. Although vaccination has beeneffective at preventing tumor formation, it has not beenable to prevent MDV infection or replication. Consequently,more virulent field strains have emerged over the pastdecades following the introduction of new vaccines. Poorpractices of vaccination and incomplete immunity have beenspeculated to play a role in driving the evolution of thevirus with greater virulence. Therefore, it is criticallyimportant to develop more sustainable control measures tothe disease in the long run.Development of genetically resistant chickens has been analternative approach to control the virus and a number of studieshave been conducted to identify specific genes that contribute toMD resistance. The major histocompatibility (MHC) locus has beenfound to be strongly associated with resistance or susceptibilityto MD, and several alleles have been well characterized. Non-MHCgenes also play a major role in resistance to MD. Two inbredlines (line 6 and line 7) maintained at Avian and OncologyLaboratory share the same MHC allele (B2), yetline 6 is resistant and line 7 is susceptible to MD,respectively. These two lines have been used as a model to studynon-MHC genes that contribute to resistance and susceptibility tothe disease.To identify non-MHC genes contributing resistance to MD, acomputational pipeline was developed to integrate gene modelsfrom Ensembl, de novo assembly, and reference-basedassembly (Cufflinks) of sequencing reads to construct a morecomplete set of gene models that include more completeuntranslated regions (UTRs) and isoforms predicted from RNA-Seqdata. The results from expression analysis suggest that theimmune response in line 7 is more active at the early stage ofinfection (4 days post-infection) compared to line 6.Differentially expressed genes are enriched in pathways involvedin both the innate and the adaptive immune response in line 7,whereas, only genes involved in the innate immune response aresignificantly enriched in line 6. Due to the cell-associatednature of MDV and the current model of MDV infection, the virusis thought to transfer from B cells and antigen presenting cells(APCs) to activated T cells during the lytic infection.Therefore, repressed or delayed activation of the adaptive immuneresponse in line 6 may be a key mechanism conferring MDresistance.Investigation of differential exon usage suggests that genesinvolved in the cytoskeleton pathway may play a role inrepressing the activation of the adaptive immune response.For instance, the ITGB2 gene encodes integrinβ2, a componentof several molecules including the lymphocytefunction-associated antigen 1 (LFA-1). LFA-1 is exclusivelyexpressed on the surface of leukocytes and plays animportant role in cell-to-cell contact and antigenpresentation. It could be speculated that an alternativeisoform of ITGB2 affects a function of LFA-1 and prevents Tcells from being activated by APCs or B cells resulting inthe delayed activation of the adaptive immune response orthe lower number of activated T cells, the target of MDV.The results from this study show that many genes not identifiedas differentially expressed at a gene level are differentiallyexpressed at an isoform level; therefore, they will not beidentified by gene expression analysis alone. Using the pipelinedeveloped in this study, one can iteratively incorporate ENSEMBLmodels and RNA-seq data to construct better gene models thatinclude genes and isoforms expressed in all samples and performdifferential gene and isoform expression analysis to identifygenes and isoforms that are responsible for resistance to MD.Although functions of most isoforms are not fully annotated,we have shown that methods, such as protein prediction andpathway analysis, can be used to predict the putativefunctions of the isoforms and their potential roles in MDresistance, which could open up a new direction for MDresearch. Moreover, prediction of causative cis-regulatoryelements in those genes will lead to identification ofprecise genetic factors contributing to MD resistance.
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- In Collections
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Electronic Theses & Dissertations
- Copyright Status
- In Copyright
- Material Type
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Theses
- Authors
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Preeyanon, Likit
- Thesis Advisors
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Brown, C. Titus
- Committee Members
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Cheng, Hans H.
Dodgson, Jerry B.
Yu, Kefei
Fu, Wenjiang
- Date Published
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2014
- Program of Study
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Microbiology and Molecular Genetics - Doctor of Philosophy
- Degree Level
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Doctoral
- Language
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English
- Pages
- xii, 88 pages
- ISBN
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9781321306149
1321306148
- Permalink
- https://doi.org/doi:10.25335/41j2-ha60