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This is to certify that the
dissertation entitled

MOLECULAR AND MORPHO-PHYSIOLOGICAL STUDY ON
DROUGHT TOLERANCE IN TURFGRASSES

presented by

JIANPING WANG

has been accepted towards fulﬁllment
of the requirements for the

PhD degree in Plant Breeding and Genetics
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2/05 cz/cmciomeom'ma-p'.15"

MOLECULAR AND MORPHO-PHYSIOLOGICAL STUDY ON DROUGHT
TOLERANCE IN TURFGRASSES

By

Jianping Wang

A DISSERTATION

Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Crop and Soil‘ Sciences
Plant Breeding and Genetics Program

2005

ABSTRACT

MOLECULAR AND MORPHO-PHYSIOLOGICAL STUDY ON DROUGHT
TOLERANCE IN TURFGRASSES

By

Jianping Wang

Drought stress is a major limiting factor for the growth of cool season grasses
particularly in the transitional and warm climatic regions. Selecting grasses with
improved drought tolerance is the best strategy to increase survival and growth of grass
during time of drought. An Atlas fescue (F estuca mairei, Fm) selection and three tall
fescue (F. amndinacea Schreb.) cultivars were subjected to drought treatment. The
drought stress had a signiﬁcant negative effect on leaf elongation, leaf water content, and
leaf water potential for all grasses. Fm maintained leaf growth, leaf water content, and
leaf water potential longer than the tall fescue grass species and had an exceptional ability
to accumulate water in leaf tissue when under severe drought stress, suggesting the better

drought tolerance of Fm and its potential value for grass drought tolerance improvement.

Intergeneric hybridization between F estuca and Lolium can generate improved
cultivars by combining stress tolerance of F estuca and rapid establishment of Lolium.
However, wide-distance hybridizations usually result in the wild genome being
eliminated from the hybrid. RAPD and SSR markers were used to detect the parental
genome composition of hybrids and backcross derivatives from crosses between Fm and

perennial ryegrass (Lolium perenne). Each progeny exhibited integration of Pm and

perennial ryegrass genomes with varying levels of genome ratios. The non-coinheritance
of the linked markers suggested chromosome crossover between two parents. Cluster
and principle component analyses of the progeny consistently revealed four groups.
These results would be useful to guide the breeding program.

Increasing knowledge of genes induced by drought in Fm would be essential to
understand the molecular mechanism of drought tolerance in grasses and to facilitate
gene manipulation for grass breeding programs. In order to apply cDNA ampliﬁed
fragment length polymorphism (cDNA-AFLP) technique to identify genes involved in
drought tolerance in Fm, we empirically evaluated the experimental conditions of this
technique in Festuca species. Results showed that NspI coupled Tan were a pair of
efﬁcient enzymes for transcript derived fragment (TDF) discovery in Fm. The number of
repeatable bands was not affected by magnesium concentration and dilution of pre-
ampliﬁcation products, suggesting the high reproducibility of this technique. The
chimeric fragments derived from ligation between digested fragments were not
eliminated by increasing adapter concentration. The application of the cDNA-AFLP
technique to identify genes responding to drought stress in Fm revealed a total of 464
(4.1% of 11,346 TDFs) differentially expressed fragments (DEFs). The differential
expression pattern for 171 (42.1% of 406) DEFs were conﬁrmed by macroarray
hybridization analysis. Functional analysis of conﬁrmed DEFs using BLASTX revealed
17 functional categories. Some novel genes were identiﬁed in Fm during the drought
response procedure. The combination of data from studies on the genetic model plant
and on diverse plant species will provide a better understand the underlying mechanism

of drought tolerance in plants.

Cepyright by
JIANPING WANG
2005

iiLJlttl‘Cﬁkééﬁtiﬁéiﬁﬂ‘liA: 346%? (if) . Iiﬁﬁ (581E) . Eaﬁiﬁ (£133?) . "516MB (it/L),
Eli‘ﬁiilﬁ (till). iEiiﬂiiﬂlillﬂﬁB‘JEM, Ii‘v’r, EDGE.

Dedicated to my parents Zhian Wang and Lianmei Lu, to my husband Xiaoping Zhang, and to my

daughters Zexi and Jenny for their understanding, support, and everlasting encouragement.

ACKNOWLEDGMENTS

I would like to speciﬁcally thank my major adviser Dr. Suleiman Bughrara for his
guidance, kindness, patience, and support. I appreciate him for trusting my potential,
giving me the opportunity to pursuing my Ph.D degree in his lab, providing me a free
environment to propose and test research idea, and encouraging me during the trouble
shooting period. I wish to thank the members of my guidance committee, Dr. Dr. Amy
Iezzoni, Dr. James Kelly, and Dr. Donald Penner for their advise, encouragement, and
teaching during the ﬁve years.

I would like to express my gratitude to Drs. Mitch McGrath and Steven
VanNocker for allowing me to use their lab equipment. Thanks also go to their lab
members for tolerance when I was interrupting. I wish to thank statistic consulting center
for guidance and assistance in statistical analysis. Especially thank Dr. Sasha
Kravchenko, Xuewen Huang, and Lan Xiao for their great help. Thanks also go to Drs.
Mian Rouf and Malay Saha in Noble foundation for providing SSR primers and
conducting part of SSR analysis. I am thankful to C88 and PBG stuff for preparing the
paper work and providing useful information and assistance during my Ph.D study.

I am grateful to Drs. Gregg and Flory for their help and suggestion on
physiological measurements in greenhouse. I am also grateful to Costas, Hua Zhang,
Voronica, Daniele, Scott Show, Jianrong Shi, Yiwu Chen, Nat, and Holly for helpful
discussion and sharing their experience in molecular biology techniques. I am
particularly thankful to my colleagues in turfgrass breeding and genetics lab: Dr. Gina

vergara, Han Zhao, Dr. Yuexia Wang, Dr. Weixin Liu, Dean Smith, Lorri William,

vi

Shiranee Gunasekera, and Dr. Xinquan Zhang. Thanks go to them for their invaluable
assistance in laboratory, greenhouse, and ﬁeld, also for their friendship.

I would like to express a special thanks to Michigan Turfgrass Foundation, the
Graduate School, Council of Graduate Students, Kirk and Marjorie Lawton, Plant
Breeding and Genetics Program, College of Agriculture and Natural Resources for the
ﬁnancial support.

Finally, I would like to express my sincere gratitude to my core family members,
my parents-in-law, brothers, brothers-in-law, and my close ﬁiends for their love,

understanding, and encouragement throughout my course of study. Thank you.

vii

TABLES OF CONTENTS

LIST OF TABLES ................................................................................... xi
LIST OF FIGURES ................................................................................ xiii
INTRODUCTION .............................................................................................................. 1
Importance of turfgrass and drought stress problem ................................................... 1
Two important grass genera and their drought tolerance ............................................ 2
Drought tolerance mechanism in plant ....................................................................... 3
Genetic approaches for drought tolerance improvement ............................................ 4
Molecular basis study of drought tolerance ................................................................ 5
cDNA-AF LP technique ............................................................................................... 7
Marker assisted selection ............................................................................................ 9
Objectives and hypothesis ......................................................................................... 10
REFERENCES .............................................................................................................. 11
CHAPTER I ...................................................................................................................... 16
Morpho-physiological Responses of Several Fescue Grasses to Drought Stress ............. 16
ABSTRACT .................................................................................................................. 16
INTRODUCTION ........................................................................................................ 17
MATERIALS AND METHODS .................................................................................. 20
Plant materials and drought treatment application .................................................... 20

Soil water content measurement ............................................................................... 21
Leaf elongation measurement ................................................................................... 21
Leaf water content measurement .............................................................................. 22
Leaf water potential measurement ............................................................................ 22
Root length and biomass measurement ..................................................................... 22
Statistical analyses .................................................................................................... 23
RESULTS ..................................................................................................................... 23
Soil water content and leaf water potential ............................................................... 23
Leaf elongation .......................................................................................................... 25
Leaf water content ..................................................................................................... 26
Root length and biomass ........................................................................................... 27
DISCUSSION ............................................................................................................... 28
REFERENCES .............................................................................................................. 44
CHAPTER II ..................................................................................................................... 47

Parental Genome Composition and Genetic Classiﬁcations of F1 Hybrids and
BackcrossProgeny Derived from Intergeneric Crosses of F estuca mairei and Lolium

perenne Assessed by RAPD and SSR Markers ................................................................ 47
ABSTRACT .................................................................................................................. 47
INTRODUCTION ........................................................................................................ 48
MATERIALS AND METHODS .................................................................................. 51

Plant materials ........................................................................................................... 51

viii

DNA isolation ........................................................................................................... 52

RAPD screening Protocol ......................................................................................... 52
SSR Screening Protocol ............................................................................................ 53
Data Analysis ............................................................................................................ 54
RESULTS ..................................................................................................................... 55
Polymorphism and fragment segregation .................................................................. 55
Genetic classiﬁcation analysis .................................................................................. 58
DISCUSSION ............................................................................................................... 60
Molecular marker application for genome composition detection ........................... 6O
Fm-Lp genome recombination in the 4x F1 .............................................................. 61
F m-Lp genome recombination in the progeny .......................................................... 62
Classiﬁcation of the progeny .................................................................................... 63
Application of the Fm-Lp progeny for turfgrass breeding ........................................ 64
REFERENCES .............................................................................................................. 77
CHARPTER III ................................................................................................................. 79
Detection of An Efﬁcient Restriction Enzyme Combination and Evaluation of the
Experimental Condition for cDNA-AFLP Analysis in F estuca mairei ............................ 79
ABSTRACT .................................................................................................................. 79
INTRODUCTION ........................................................................................................ 80
MATERIALS AND METHODS .................................................................................. 84
Plant material and template preparation .................................................................... 84
Digestion and ligation ............................................................................................... 85
Pre-ampliﬁcation and selective ampliﬁcation ........................................................... 85
AF LP proﬁling .......................................................................................................... 86
Fragment isolation, cloning and sequencing ............................................................. 86
Sequence search and restriction map analysis ........................................................... 87
Experimental design and data analysis ..................................................................... 88
RESULTS AND DISCUSSION ................................................................................... 89
Selection of the optimal restriction enzymes ............................................................ 89
Effects of magnesium concentration and pre-ampliﬁcation dilution on number of
TDFs in AFLP proﬁles .............................................................................................. 91
Evaluation of chimeric TDF identity ........................................................................ 92
REFERENCES ............................................................................................................ 107
CHAPTER IV ................................................................................................................. 109
Monitoring of Gene Expression Proﬁles and Identiﬁcation of Candidate Genes Involved
in Drought Tolerance in F estuca mairei ......................................................................... 109
ABSTRACT ................................................................................................................ 109
INTRODUCTION ...................................................................................................... 111
METERIALS AND METHODS ................................................................................ 115
Plant materials and drought treatment ..................................................................... 115
Relative leaf water content measurement ............................................................... 116
RNA isolation and cDNA synthesis ........................................................................ 116
cDNA-AFLP analysis ............................................................................................. l 17

ix

Identiﬁcation of differentially expressed fragments and fragment recovery from

polyacrylamide gel .................................................................................................. 118
Macroarray hybridization and data analysis ........................................................... 119
DNA fragment sequencing and sequence analysis ................................................. 121
RESULTS ................................................................................................................... 121
Plant performance during the drought stress ........................................................... 121
cDNA-AFLP analysis ............................................................................................. 122
Macroarray hybridization analysis .......................................................................... 123
Sequence analysis and functional category ............................................................. 124
Predicted function of up-regulated DEFs ................................................................ 125
Predicted function of down-regulated DEF s ........................................................... 127
Predicted function of up-then-down regulated and transiently expressed DEFs 128
DISCUSSION ............................................................................................................. 128
Functional approach to identify the stress response gene ....................................... 128
Drought inducible genes ......................................................................................... 130
Drought repressible genes ....................................................................................... 132
Application of drought stress and DEFs ................................................................. 133
REFERENCES ............................................................................................................ 152
SUMMARIES ................................................................................................................ 156

LIST OF TABLES

Table 1. Proposed genomic formula of F estuca species (Sleper, 1985). ............................ 3

Table 2.1. The name and sequence of 41 RAPD polymorphic primers and the number of
fragments ampliﬁed. All the RAPD oligonucleotides are from Operon
Technologies. ............................................................................................................ 66

Table 2.2. The sequences, annealing temperatures and sources for both ryegrass
genomic- and tall fescue EST-SSR primer pairs ....................................................... 67

Table 2.3. Linkage location of the EST-SSR markers on ryegrass linkage groups. ........ 69

Table 2.4. The segregation of polymorphic bands among the Fm-Lp complexes based on

the parent bands pattern from SSR and RAPD screening. ........................................ 70
Table 2.5. The Fm/Lp genome speciﬁc band ratios of the Fm-Lp complexes based on

SSR and RAPD marker screening ............................................................................. 71
Table 3.1. Sequences of the primers and linkers used for AFLP analysis. ...................... 95

Table 3.2. The recognition of 8 restriction enzymes on the complete cDNA sequences
from Festuca genera searched in the web site. ......................................................... 97

Table 3.3. The size distribution of the bands generated from AF LP analysis with
EcoRI/Taql and NspI/Taql restriction enzyme system, respectively ........................ 98

Table 3.4. The ANOVA of the number of repeatable bands generated from F. mairei
cDNA-AFLP proﬁle at two magnesium concentrations and 3 dilutions. ................. 99

Table 3.5. The ANOVA of the number of bands generated ﬁom kanamycin cDNA-
AFLP proﬁle at ﬁve different adapter concentrations. ........................................... 100

Table 4.1. Sequences of the linkers and primers used for cDNA-AF LP analysis
synthesized by MWG Biotech Inc. ......................................................................... 136

Table 4.2. Distribution of functional category of the differentially expressed fragments
(DEFs) during drought stress cycle in F. mairei. Classiﬁcation was performed for
101 DEFs with strong statistical similarity to GenBank plant protein sequence (E
values lower than 1.00E-06) by BLASTX search. The functional category was
assigned based on function classiﬁcation criteria in the website of Munich
information center for protein sequences (MIPS) (http://mipsgsfde). .................. 137

Table 4.3. Function annotation and size of the differentially expressed fragments (DEFs)
up-regulated by drought stress in F. mairei. ........................................................... 138

xi

Table 4.4. Functional annotation and size of the differentially expressed fragments
(DEFs) down-regulated by drought stress in F. mairei ........................................... 139

Table 4.5. Functional annotation and size of the differentially expressed fragments

(DEF s) transiently expressed and up-then-down-regulated during drought stress in
F. mairei. ................................................................................................................. 143

xii

LIST OF FIGURES

Figure 1.1. Soil water content during the drought stress period. Error bars indicate
standard errors. *, ** Signiﬁcantly different means among the stressed plants of
four grasses at certain week at P S 0.05 and 0.01 respectively. ................................ 32

Figure 1.2. Leaf water potential during the drought stress period. Error bars indicate
standard errors. *, ** Signiﬁcantly different means between control and stressed
plants at certain week at P S 0.05 and 0.01 respectively ........................................... 33

Figure 1.3. The relationship between soil water content and leaf water potential ............ 34
Figure 1.4. Leaf elongation of the treatment control plants during the drought period.
Columns with the same letter indicate there are no signiﬁcant differences among

them at P S 0.05. Error bars indicate standard errors. .............................................. 35

Figure 1.5. Leaf elongation during the drought stress period. Error bars indicate standard
errors. *, ** Signiﬁcantly different means between control and stressed plants at

certain week at P S 0.05 and 0.01 respectively. ........................................................ 36
Figure 1.6. The relationship between leaf elongation and soil water content. .................. 37
Figure 1.7. The relationship between leaf elongation and leaf water potential ................ 38

Figure 1.8. Leaf water content during the drought stress period. Error bars indicate
standard errors. * Signiﬁcantly different means among the stressed plants of four

grasses at certain week at P S 0.05. ........................................................................... 39
Figure 1.9. The relationship between soil water content and leaf water content .............. 40
Figure 1.10 The relationship between leaf water potential and leaf water content ........... 41

Figure 1.11. Root length and biomass comparisons of treatment control and stress treated
plants. Error bars indicate standard errors. Bars with the same letter indicate there
are no signiﬁcant differences between them at P S 0.05. *, ** Signiﬁcantly
different means between control and stressed plants at certain week at P S 0.01 ..... 42

Figure 1.12. The phenotypes of the Atlas fescue (A), Barolex (B), Kentucky 31(C), and
Falcon II (D) before imposing drought stress. .......................................................... 43

Figure 2.1.a. The image of SSR primer screening with ethidium bromide staining. M is a
1000bp ladder. Size standards are labeled on the left-side of the panel. Every two
lanes are a proﬁle of one primer pair screened against F m (F estuca mairei) and Lp
(Lolium perenne). Primer names are on the top of the panel. .................................. 72

xiii

Figure 2.1.b. The image of SSR primer screening with silver staining. M is100 bp ladder.
Size standards are labeled on the left-side of the panel. Every four lanes are a proﬁle
of one primer pair screened against Fm (F estuca mairei), Lpl (Lolium perenne,
Citation II), Lp2 (Lolium perenne, Calypso) and F1 (le x Lp2). Primer names are
at the top of the panel. ............................................................................................... 73

Figure 2.1.c. Agarose gel image of RAPD primer screening. M ileOO bp ladder. Size
standards are labeled on the right-side of the panel. Every four lanes are a proﬁle of
one primer screened against Fm (F estuca mairei), Lpl (Lolium perenne, Citation II),
Lp2 (Lolium perenne, Calypso) and F1 (le x Lp2). Primer names are at the top of
the panel. ................................................................................................................... 74

Figure 2.2. The dendrogram from UPGMA cluster analysis based on the merged SSR
and RAPD data The accessions include Fm (F estuca mairei), Lpl (Lolium
perenne, Citation II), Lp2 (Lolium perenne, Calypso), D1 (amphidiploid), G6 -
G30b (backcross progeny). Numbers at branches are bootstrapping value (%).
Group numbers are indicated at right-side of the ﬁgure. .......................................... 75

Figure 2.3. The 3-dimensiona1 scatterplot of principle component analysis based on the
merged SSR and RAPD data. The four groups were deﬁned following the cluster
analysis. R1, R2, and R3 are axes of the three principle components, which
explained 76 % of the total variation. Accessions include Fm (Festuca mairei), Lpl
(Lolium perenne, Citation H), Lp2 (Lolium perenne, Calypso), D1 (amphidiploid),
G6 - G30b (backcross progeny). ............................................................................... 76

Figure 3.1. The restriction diagram of the cDNA of the kanamycin resistant gene with
Taql enzyme. A. Single strand cDNA sequence. The arrows point to the restriction
sites of Taql. B. Fragments with double sticky ends restricted by Taql. ............... 101

Figure 3.2. The cDNA-AFLP banding pattern generated from the EcoRI/Taql enzyme
combination (A) and the NspI/Taql enzyme combination (B). .............................. 103

Figure 3.3. Effect of magnesium concentration and dilution levels on the cDNA-AFLP
proﬁling. Every four lanes are four replications. .................................................... 104

Figure 3.4. The diagram of the composition of the 710bp band. Two ends of the
fragment are the Taql adapters. Two middle fragments are 403bp (917-515) (left)
and 274bp (239-512) (right). T14 is the Taql selective primer: T+GT. ................ 105

Figure 3.5. Effect of adapter concentration on the cDNA-AFLP proﬁling. Panels 1 and 2
show primer pairs of N4/T l4 and N3/T11 respectively. 1, 2, 3, 4, and 5 are ﬁve
levels of adapter concentration with two replications. ............................................ 106

Figure 4.1. The spot arrangement on the nylon array for macroarray hybridization. The
controls were spotted in different sections of the membrane to compensate for

xiv

variable background levels. All samples were presented with two replications on
each array. ............................................................................................................... 144
Figure 4.2. Relative leaf water content of F. mairei during the drought stress cycle. 145

Figure 4.3. An example of cDNA-AF LP proﬁle for treatment control F. mairei. All
transcript derived fragments were constitutively expressed at the same level ........ 146

Figure 4.4. Distribution of the size of transcript derived fragment from cDNA-AFLP
performed on F. mairei. .......................................................................................... 147

Figure 4.5. Distribution of the pattern of differentially expressed fragments revealed by
cDNA-AF LP during drought stress cycle in F. mairei. .......................................... 148

Figure 4.6. A portion of the hybridized macroarray. The differentially expressed
fragments (DEFs) from cDNA-AFLP were arrayed on nylon membranes A and B
identically. Membranes were seperatively hybridized to treatment control (A) and 5
days stress treated (B) cDNA probes, respectively. Spots in squares indicated the
housekeeping controls used for normalization between arrays (In present case,
signals in membrane A were stronger than B. Therefore, the housekeeping controls
were used to balance the two arrays). Spots in the circle indicated the negative
controls used to eliminate the background effect. Spots in the up-triangle indicated
example of up-regulated DEFs. Spots in the down-triangle showed example of
down-regulated DEFs .............................................................................................. 149

Figure 4.7. Comparison of ﬁmctional categories between up-regulated and down-
regulated differentially expressed fragments (DEFs) during drought stress cycle in
F. mairei. Each DEF was searched against the GenBank plant protein database by
BLASTX. The functional category was assigned based on function classiﬁcation
criteria on the website of Munich Information Center for Protein Sequences (MIPS)

(hgpzllmipsgsfde). ................................................................................................. 150

XV

INTRODUCTION

Importance of turfgrass and drought stress problem

Turfgrass is used extensively on sports ﬁelds, golf courses, parks, lawns, and
roadsides. The turfgrass contributes considerably to our environment by adding pleasant
beauty to the surroundings, providing a safe playing surface for sports and recreation,
controlling dust and pollen in the air, absorbing gaseous pollutants, and preventing
erosion. However, a healthy, vigorous turf requires abundant water. In some sections of
the country, water use for turf irrigation accounts for 50 percent or more of the

consumption of city water supplies during the summer (Duble, 2005).

It has been estimated that over half the world’s land surface is exposed to periodic
drought (Boyer, 1982). In urban environments, drought stress is exacerbated due to soil
factors as well as elevated temperatures (Cregg, 1995). Drought stress is a major limiting
factor for the growth of cool season grasses in dry time of the year. Because of less than
optimal water supply, the turfgrass quality often declines. Problematically, as regions
experiencing drought conditions increase, and cities and municipalities declare water
emergencies, water for turfgrass irrigation will be severely restricted. Turfgrass
managers have put signiﬁcant effort into cultural modiﬁcations in lawn management to
reduce water consumption, but the effects were not signiﬁcant. Using more drought
tolerant varieties or cultivars will be a promising approach to alleviate stress in current

lawns, fairways, and parks.

Two important grass genera and their drought tolerance

Turfgrasses are comprised of highly diverse grass genera and species. These
species differ in their drought stress adaptation, as some can survive much greater
drought stress than others. Lolium and F estuca are two important turfgrass genera (Table
1). Both belong to the tribe Poeae, subfamily Pooideae in which the basic chromosome
number (x) is 7 (Jauhar, 1993). Lolium contains eight species (Clayton and Renvoize,
1986). The two most important species used extensively as turfgrass are L. perenne,
commonly known as perennial ryegrass and L. multiﬂorum known as Italian ryegrass.
Ryegrass (2n=2x=14, LL) is widely distributed cool-season grass throughout the United
States, Europe, and in the temperate regions of the world. It has become a very popular
turfgrass for over-seeding athletic ﬁelds, golf courses and lawns. The improved turf-type
ryegrass varieties have better turf characteristics: ﬁner texture, greater density, darker
color, and better establishment. However, ryegrass is the least drought tolerant turfgrass
species and needs frequent irrigation in the spring and early summer (Morrison et a1
1980; Turgeon, 1991). F estuca is a large diverse genus comprising about 450 species
(Clayton and Renvoize, 1986) and is widely distributed across the cool regions of the
world. The most useful turfgrass species are F. arundinacea var. genuina — tall fescue
(hexaploid, 2n=6x=42) and F. pratensis- meadow fescue (diploid, 2n=14), F. rubra-
creeping red fescue, F. ovina- sheep fescue and F. longifolia- hard fescue. All of the
fescues have been recognized for their exceptional drought tolerance (Aronson et al.,
1987; Fry and Butler, 1989; Humphreys and Thomas, 1993; Turgeon, 1991). Festuca

mairei St. Yves is a xerophytic tetraploid (2n=4x=28, M1M1M2M2) species, commonly

known as atlas fescue. It tolerates high temperature and drought, and has a high

photosynthetic rate, but lacks turf quality (Borill et a1, 1971; Marlatt et al, 1997).

Table 1. Proposed genomic formula of Festuca species (Sleper, 1985)

 

 

Species Chromosome Proposed genomic formula
number (2n)

F. pratensis 14 PP

F. arundinacea var. glaucescens 28 G1G1G2G2

F. mairei 28 M1M1M2M2

F. arundinacea var. genuina 42 PP GlGleGz

F. arundinacea var. atlantigene 56 G1G1G2G2 M1M1M2M2

 

Drought tolerance mechanism in plant

Drought resistant mechanisms can be classiﬁed into three primary categories (Jones
et al., 1981): Drought escape mechanisms are related to rapid phenological development.
The plant completes its life cycle before a serious plant water deﬁcit develops as
evidenced by desert ephemerals. Such a mechanism would not be useful for turfgrass.
Drought avoidance is the mechanism of drought tolerance where the plant maintains high
tissue water potential through the ability to maintain water uptake or reduce water loss.
Large root systems, which increase water uptake efﬁciency, and adapted leaf morphology
such as lower speciﬁc leaf areas and lower stomatal density, that reduce water loss, are
the most recognized morphological adaptations of drought avoidance. The physiological

adaptations in increasing drought tolerance at high tissue water potential are related to

water conservation through low stomatal conductance (rapid stomatal closure) and low
transpiration rate, which contribute to reduce water loss. Drought resistance mechanism
is drought tolerance at low tissue water potential indicated by maintenance of stomatal
conductance, transpiration rate and other physiological processes. Drought tolerance is
usually achieved by osmotic adjustment. Under water deﬁcit conditions, plant growth is
substantially reduced, partly because lower turgor pressure in the cells results in a lower
cell expansion rate (Pattanagul and Madore, 1999). The osmotic adjustment in the plant
maintains cell elongation. The production and partitioning of metabolically important
non-structural carbohydrates (sugars, starch, and sugar alcohols) have been found to be
altered by drought in a number of different ways (Vyas et al., 1985; Jacomini etal., 1988;
Keller and Ludlow, 1993; Volaire and Thomas, 1995). Sugars may serve as compatible
solutes permitting osmotic adjustment to maintain the water potential during mild drought
(Bohnert, 1995). Enzymes of sugar metabolism are probably critical in desiccation
tolerance. In addition to sugars, other compatible solutes also contribute to osmotic
adjustment. Enzymes involved in the synthesis of proline and glycine betaine are clearly

up-regulated during drought (Bohnert, 1995).

The genotypes with a relatively high capacity to osmotically adjust (i.e., decrease
osmotic potential in response to drought stress) may be better able to maintain
photosynthesis and other physiological processes during drought than those that lack the
ability to osmotically adjust. Therefore, it is possible that the ability to osmotically adjust
during drought may serve as a criterion for the drought tolerance selection program

(Cregg, 1993).

Genetic approaches for drought tolerance improvement

Genetic improvement is one of the most effective ways to increase drought
tolerance of turfgrass. Classical breeding through sexual hybridization has been the
principal approach for turfgrass improvement over the past half century. Intergeneric
hybridization between Lolium and some F estuca species has been a long time goal to
combine the complementary traits of these species since they allow certain levels of
intergeneric chromosome pairing, recombination, and gene exchange (Morgan and
Thomas, 1991; Crowder, 1953), and cultivars derived from crosses between Lolium and
Festuca have been released (Buckner et al, 1977; 1983). However, progress in breeding
turfgrass for drought resistance has still been very slow, primarily because of the genetic
complexity of drought stress responses and lack of knowledge of the major genetic

components underlying drought tolerance of plants.

Successful breeding program depends on a broad understanding of the genetic
architecture of the relevant trait (Humphreys et al., 2004). Due to the biological
complexity of grass species and the associated difﬁculties encountered by traditional
breeding methods, the potential of molecular breeding for the development of improved
cultivars is evident. Molecular improvement presents both new challenges and clear
opportunities for the application of biotechnology. Major genes associated with drought
tolerance include both genes with major effects, which are directly involved in the
biochemical pathway, and genes contributing to the expression of the major gene, such as
transcription factors. Knowledge of gene function and characterization will facilitate the
target modiﬁcation of drought tolerance through transgenic approaches or gene

introgression.

Molecular basis study of drought tolerance

A drought stress response is initiated when a plant recognizes the stress, which
then activates signal transduction pathways to transmit the information within individual
cells and throughout the plants. Ultimately, changes in gene expression will occur and

are integrated into plant’s adaptive responses to modify growth and development.

Several hundred genes are differentially expressed in response to dehydration in
the resurrection plant Craterostigma plantagineum, as evidenced by transcript proﬁling
(Bockel et al., 1998). In Arabidopsis, genes involved in many different pathways are
expressed in response to drought stress (Seki et al., 2002). All these identiﬁed genes can
be assigned to diverse biological pathways, such as sugar metabolism and biosynthesis
(Bohnert, 1995), ion and water channel proteins synthesis (Guerrero et al., 1990) cell wall
ligniﬁcation processes (Peleman et al., 1989) detoxiﬁcation of active oxygen species
(Williams et al., 1994; Mittler et al., 1994) and so on. Although the precise functions of
these genes has not yet been demonstrated, Bartels and Salamini (2001) have summarized
all the drought inducible genes and grouped them into ﬁve main categories, as genes
encoding (a) proteins with protective properties, (b) membrane proteins involved in
transport processes, (0) enzymes related to carbohydrate metabolism, ((1) regulatory
molecules, such as transcription factors, kinases, or other putative signaling molecules,

and (e) open reading frames that show no homologies to known sequences.

Obviously a network of signal transduction pathways allows the plant to adjust its
metabolism to the demands imposed by water deﬁcit (Shinozaki and Yamaguchi-
Shinozaki, 2000; Kirch et al., 2001). The complex signal transduction cascade can be

divided into three basic steps (Ingram and Bartels, 1996): (a) perception of stimulus, (b)

signal ampliﬁcation and integration, and (c) response reaction in the form of de novo
gene expression. The signaling molecules involved in the signal transmission process
and the activation of gene expression in response to stress have been identiﬁed. One
molecule is the plant hormone abscisic acid (ABA). Endogenous ABA levels have been
reported to increase as a result of water deﬁcit in many physiological studies, and
therefore ABA is thought to be involved in the signal transduction (Chandler 1994;
Giraudat 1994). Besides the ABA-mediated gene expression, the investigation of
drought-induced genes in A. thaliana has also revealed ABA-independent signal
transduction pathways (Yamaguchi and Shinozaki, 1994). Both ABA-dependent and -
independent stress signaling ﬁrst modiﬁes constitutively expressed transcription factors,
leading to the expression of early response transcriptional activators, which then activate

downstream stress tolerance effective genes (Zhu, 2001).

Even though a large number of drought induced genes have been identiﬁed in a
wide range of species and impressive progress has been made in gene annotation, the
molecular basis still remains far from being completely understood (Ingram and Bartels,
1996). It is important to identify more drought inducible genes and analyze the functions
of the genes. Increasing knowledge of the function of these genes would be essential to
understand the molecular mechanism of drought tolerance in plant and to facilitate gene

manipulation for breeding programs.

cDNA-AFLP technique

Transcript proﬁling is playing a substantial role in annotating and determining

gene functions by revealing gene expression on a genome-wise scale. A variety of high-

throughput transcript proﬁling techniques have been established including cDNA-
ampliﬁed restriction length polymorphism (cDNA-AFLP), serial analysis of gene
expression (SAGE), massively parallel signature sequencing (MPSS), expressed
sequence tag (EST) sequencing, differential display PCR (DD-PCR), cDNA microarray,
oligo-chips, and suppression subtractive hybridization (SSH). cDNA-AFLP analysis is
an mRNA ﬁngerprinting technique that demonstrates high reproducibility and sensitivity,
good correlation with northern blot analysis and low set-up cost, even though it requires a
comprehensive reference database (Donson, et al., 2002). Recently, the rapidly
expanding ﬁeld of genomics, the creation of a large-scale EST database from various
species, and the complete sequencing of Arabidopsis (Arabidopsis genome initiative
[AGI], 2000) and rice genome (Yu et al., 2002) were made public. This genomic
information source can provide a vast reference database for evaluating the coordinated
function and expression of genes identiﬁed by using the cDNA-AF LP approach. cDNA-
AFLP has been successfully used to identify differentially expressed transcript derived
fragments (TDFs) from almond (Prunus amygdalus) treated with abscisic acid (ABA)
(Campalans et al., 2001); tissue-speciﬁc TDFs during potato (Solanum tuberosum L.)
tuber development (Bachem et al., 2001); and TDFs associated with putative
pathogenicity factors during infection of tuber by potato cyst nematode (Globodera
rostochiensis) (Qin, et al., 2000). cDNA-AFLP technique was found to be an efﬁcient

method of isolating differentially expressed genes or TDFs.

Marker assisted selection

The genetic improvement for drought tolerance is slow and complicated,
especially by conventional breeding approaches. The main reason is the low heritability
of traits associated with drought tolerance. Marker assisted selection (MAS) provides
breeders with valuable tools to develop newer germplasm with improved drought
tolerance (Quarrie et al., 1999; Hoisington et a1, 1996). Drought tolerance involves a
cascade of events and is controlled by multiple genes. To clarify the genetic network
involved, key agronomic traits need to be clariﬁed into individual components to reduce
complex analysis (Modarres et al., 1998; Tollenaar and Wu, 1999). After speciﬁc
components of the genes corresponding to drought tolerance are isolated and cloned, they
can be used for transgenic breeding or be converted into PCR-based markers to assist in
selection, which is more effective as their expressions are independent of environment.
For PCR-based marker development, sequence data is used to design PCR primers
speciﬁc to the differential genes or fragments, and use PCR to produce speciﬁc fragments
from genomic DNA. These markers are suited for identifying the desired form of the
gene (allele) ﬁom the onset of the selection process and allow us to rapidly identify
genetic lines that had the desired allele and discard those without. Revealing the genes
function in drought tolerance and converting the cloned genes into PCR-based markers to

assist the selection would be more effective and efﬁcient in a drought tolerance breeding

program.

Objectives and hypothesis

The main goal of this research is to identify speciﬁcally expressed drought
tolerant genes in F. mairei to understand the molecular genetic basis underlying drought
tolerance in grasses and to introgress the drought tolerance of F. mairei into perennial
ryegrass. This study is based on the hypothesis that a) there must be a genetic code
responsible for the drought tolerance and the genetic code would be able to be isolated
and deﬁned, and that b) drought tolerance observed in F. mairei can be genetically

transferred into the hybrids of F. mairei X L. perenne.
The speciﬁc objectives are as follows:
1. To evaluate the morpho-physiological drought tolerance characteristics of F. mairei;

2. To assess the genome introgression of F .mairei into L. perenne hybrids using SSR and

RAPD markers.

3. To optimize the experiment conditions of cDNA-AF LP procedure in discovering

transcript derived ﬁ'agments in F. mairei;

4. To identify the differentially expressed fragments (DEF) in F. mairei during drought

stress treatment by using cDNA-AF LP coupled with macroarray hybridization;

5. To functionally analyze the DEFs identiﬁed in F mairei during drought stress

treatment;

10

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15

CHAPTER I

Morpho-physiological Responses of Several Fescue Grasses to

Drought Stress

ABSTRACT

An Atlas fescue (F estuca mairei) selection and three tall fescue (F. arundinacea
Schreb.) cultivars, Barolex, Kentucky 31, and Falcon II were subjected to drought stress
imposed for a 12-week period. Soil water content (SWC), leaf elongation (LE), leaf
water content (LWC), and leaf water potential (‘Pw) were measured weekly, and root
length (RL) and biomass (RM) were recorded after 12 weeks. The SWC declined
progressively during the 12 weeks drought period. The SWC decreasing rates of the
three tall fescue cultivars were similar, but declined faster than Atlas fescue indicating
that Atlas fescue extracted soil water slower and developed less intensive stress than the
three tall fescue cultivars. The imposed drought treatment had a signiﬁcant negative
effect on LE, LWC, and ‘PW for all grasses. These three parameters of the treated plants
for Atlas fescue remained similar to control plants longer than the three tall fescue
cultivars. The relationships between LE and LWC verses SWC and WW respectively
were ﬁtted to a polynomial function. Results suggested that (l) the LE of Atlas fescue

and Falcon II were less sensitive to the imposed drought stress than Barolex and

16

Kentucky 31 as SWC and ‘PW decreased; (2) a mechanism may exist in Falcon II and
Atlas fescue to maintain cell turgor necessary for cell expansion as SWC declined and
‘PW became more negative; (3) all the grasses conserved water as the drought stress
initiated and Atlas fescue maintained water in the leaf tissue longer than the three grasses;
(4) Atlas fescue had an exceptional ability to accumulate water in leaf tissue under
severe drought stress (‘I’w = -1.2 ~ -2.4 Mpa). The long root system (115-132 cm) of the
four grasses may help avoid the effect of drought by absorbing more water from soil
through extensive root systems. The slower decline of LB, LWC, and ‘PW in Atlas fescue
during the drought stress period suggested that Atlas fescue possessed drought tolerance

and afforded potential to improve drought tolerance in turfgrass breeding program.

Key words: Atlas fescue, tall fescue, drought tolerance, leaf elongation, leaf water

content, leaf water potential, root.

INTRODUCTION

It has been estimated that over half the world’s land surface is exposed to periodic
drought (Boyer, 1982). In urban environments, drought stress is exacerbated due to
negative soil factors as well as elevated temperatures (Cregg, 1995). Drought stress is a
major limiting factor for the grth of cool season grasses in the transitional and warm
climatic regions of the world. Because of less optimal water supply, the turfgrass quality
and forages yield often declines. Problematically, as water conservation becomes an

important issue, water for landscape and agronomic irrigation is restricted. This

17

suggested identiﬁcation and screening of grasses with improved drought tolerance and
reduced water use may be the best strategy to increase survival and growth of grass in
drought prone areas through plant breeding.

In general, drought resistance is the capacity of a plant to survive or grow during
drought stress. The mechanisms of drought resistance have been classiﬁed into three
primary categories: drought escape, drought avoidance and drought resistance (Jones et
al., 1981). Drought escape mechanisms are related to rapid phenological development.
The plant completes its life cycle before a serious plant water deﬁcit develops as
evidenced by desert ephemerals. Drought avoidance is the mechanism of drought
tolerance where plants maintain high water potential in tissues through the ability to
maintain water uptake or reduce water loss. Large root systems that increase water
uptake efﬁciency (McCully 1999; Weerathaworn et al., 1992) and adapted leaf
morphology such as lower speciﬁc leaf areas and lower stomatal density that reduce
water loss are the two morphological adaptations that plants use to avoid drought. The
physiological adaptations related to water conservation are through low stomatal
conductance (rapid stomatal closure) and low transpiration rate to reduce water loss
(Jones et al., 1981). Drought resistance mechanism in plants is the drought tolerance at
low tissue water potential indicated by maintenance of regular physiological processes.
Drought tolerance through resistance mechanism is usually achieved by osmotic
adjustment. Under water deﬁcit conditions, plant growth is substantially reduced, partly
because lower turgor pressure in cells affected by low water potential results in a lower
cell expansion rate (Pattanagul and Madore, 1999). The osmotic adjustment in response

to water deﬁcit can results in maintenance of cell elongation or enhancement of turgor

18

(Begg and Turner, 1976), which may sustain cell expansion and leaf elongation (Hsiao,
1973). A dormancy mechanism can also be related to long-term responses to severe
drought in perennial grasses. When perennial grasses are quiescent or dormant, plants
temporally suspense visible growth of any structure containing a meristem such as basal
buds, to avoid drought damage and allow survival (Mcwilliam, 1968).

Grass genotypes and cultivars vary in their responses to drought stress, which
involve changes in various morphological and physiological factors (Wu and Huff,
1983). Knowledge of relative involvement of various morphological and physiological
characteristics in drought tolerance is important in selecting grass genotypes that persist
during drought stress and facilitate the breeding of drought tolerant cultivars. In the
current study, we sought to investigate drought responses of a selection of Atlas fescue
(F etuca mairei) grass compared with three tall fescue (F. arundinacea Schreb.) cultivars,
“Kentucky 31”, “Falcon II”, and “Barolex”. Tall fescue is the most useful turfgrass and
forage species in cool and transition zone regions. This species is originated from Europe
and has been recognized for its exceptional drought tolerance (Norris and Thomas, 1982;
Fry and Butler, 1989). Within tall fescue species, cultivars also vary in drought
resistance (White etal., 1993; Carrow, 1996). Kentucky 31 and Falcon H have been
identiﬁed as good drought tolerant cultivars (Huang and Gao, 1999; Huang, 2001).
Barolex is a new tall fescue forage type cultivar, and its drought tolerance is unknown.
Atlas fescue Species is only found in the Atlas Mountain ranges of northwest Africa.
There is no deﬁnitive report of drought tolerance of Atlas fescue, although this grass
species has a xerophytic adaptation to survive long summers under drought stress

(Marlatt et al., 1997).

19

The objectives of this study are to (i) determine the leaf elongation, leaf water
content, leaf water potential, root biomass and length of a selection of Atlas fescue,
Barolex, Kentucky 31, and Falcon 11 during drought stress imposed for 12 weeks; and (ii)

investigate the drought responses of Atlas fescue compared with tall fescue cultivars.

MATERIALS AND METHODS

Plant materials and drought treatment application

Four grasses of F estuca species were compared. One was an Atlas fescue
selection, originally collected from Morocco. The other three grasses were commercial
tall fescue cultivars used for turf and forage: “Barolex”, “Falcon H”, and “Kentucky-3 1”.
A single tiller of each grass was used to propagate vegetatively a mature plant in the
greenhouse. From each plant, two tillers were transplanted into each of six PVC tubes
(100 cm deep x 34 cm in diameter). These tubes were ﬁlled with the same weight (11.8
kg) of substrate (recommended soil for athletic ﬁelds, 85% sand and 15% ﬁeld soil).
Between the tube and substrate, a heavy duty plastic sleeve was placed inside the tube, to
facilitate moving the root system from the tube at the end of the experiment. All the
transplanted plants were established for 15 weeks in the greenhouse during fall with
regular irrigation, fertilizer and trimming. The greenhouse temperature was 25 i 3 °C,
with average 13 h/day photoperiod. A pre-conditioned drought was applied by
withholding water for two weeks. Plants were recovered by irrigation for one week and

then trimmed to same height (around three inches). Then, three tubes of each plant were

20

randomly allocated to a block for drought treatment and the other three tubes were
randomly allocated to the other block as treatment control. Drought stress was imposed
by withholding water progressively from plants in the drought treatment by supplying
200 ml (up to 100% soil capacity in the tube), 150 ml, 100 ml, and 50 ml water in the
ﬁrst four weeks respectively and stopping water during the remaining 12-week drought
period. The plants in the control treatment were irrigated regularly during this period.
The PVC tubes were re-randomized weekly during this drought period to minimize

effects of possible environmental gradients within the greenhouse.

Soil water content measurement

The PVC tubes were weighed every week at the same time (1 :00 pm.) to
determine gravimetric soil water content (SWC) from water loss. The mass of soil
mixture was measured for each tube at the beginning of the experiment, which also
ensured the same weight of substrate (11.8 kg) in each tube. The moisture of the soil

mixture was estimated by weighing 10 fresh, and then 80°C oven dried soil samples.

Leaf elongation measurement

After 15 weeks establishment, three tillers in each tube were randomly chosen and
labeled with wires of different color for consistent leaf elongation (LE) measurement.
Length of the top two freshly -emerged leaves on the labeled tiller were measured from
the tip of each lamina to the ligule of the next oldest leaf (Norris and Thomas, 1982)

every week until leaf growth of drought stressed plant ceased.

21

Leaf water content measurement

A fully-extended leaf of the drought stressed plants was detached weekly for leaf
water content (LWC) measurement. Control plants were sampled in 3‘“, 6‘“, and 9th week
only during the drought period. The fresh weight (FW) (weight of the leaf immediately
after detachment), turgor weight (TW) (weight of the leaf after soaked in the miniQ water
for 24 hr at room temperature), and dry weight (DW) (weight of the leaf after dry in oven
at 80°C for 24 hr) of the leaf were used to calculate the relative LWC described by Slavik

(1974) and White et al., (1992): LWC (%) = (FW-DW)/(TW-DW) x 100.

Leaf water potential measurement

All the plants were covered by a black plastic sheet in the evening to imitate a
pre-dawn condition (closed stomata and low respiration). The following morning,
duplicated fully-emerged, undamaged laminae in each tube were sampled every week and
immediately were subjected to leaf water potential CPw) measurements by using a
pressure chamber (Soil moisture equipment corp., Santa Barbara, CA). All the
measurements were conducted at 22-25 °C within 2 hours in the greenhouse. The data

was eliminated when the ‘Pw of the control was greater than -0.6 MPa.

Root length and biomass measurement

At the end of the experiment, the heavy duty plastic sleeve, which contained the
root system, were taken out of each tube. The soil substrate was gently removed from the
root system by ﬂowing water from. Length of root system (RL) was measured using a

ruler. Biomass of the root (RM) was weighed after blotted dry using paper towel and

22

further evaporated at room temperature for around 6 hr to remove surface moisture of the

root.

Statistical analyses

The data of LE, LWC, SWC, and ‘PW, were subjected to analysis of variation
(ANOVA), using repeated measurements in time by SAS program (SAS Institute Inc.
2003). Comparisons were made within the four grasses by one-way AN OVA and
between drought and control treatments by student t test at speciﬁed week. Mean
separations were performed by a least signiﬁcant difference (LSD) procedure where the
F -value were signiﬁcant at the 0.05 probability level. RL and RM data were subjected to
one way AN OVA analysis to compare within the four grasses and between stressed and
control plants. The relationships between parameters were ﬁtted to appropriate nonlinear

regressions model in Microsoft Ofﬁce Excel (Microsoft Co. 2002).

RESULTS

Soil water content and leaf water potential

When the soil was at full water capacity, the SWC for the grasses included in this
experiment was 9.33%. SWC declined signiﬁcantly (P < 0.0001) starting at the second
week of the drought treatment (Figure 1.1). The rate of soil water depletion was similar
among the grasses except it was higher with Atlas fescue. Speciﬁcally, during the four-

to eight-week of drought stress treatment, SWC of Atlas fescue was signiﬁcantly higher,

23

indicating that Atlas fescue extracted less soil water and developed severe stress status
slower than the tall fescue cultivars.

‘Pw has been widely accepted as a deﬁnitive indicator of plant water status and
stress level. The imposed drought stress had a signiﬁcant effect on ‘Pw of the grasses we
studied. In irrigated plants, ‘I‘w was similar (P = 0.086) among the grasses, and remained
relatively high across the 12-week drought treatment period. ‘l’w of stressed plants
decreased differently among the four grasses (Figure 1.2). ‘I’w of stressed plants showed
signiﬁcant difference from the irrigated ones after four (Falcon II), ﬁve (Kentucky 31),
six ( Barolex), and eight (Atlas fescue) weeks respectively. The results indicated that
Atlas fescue maintained ‘I’w at the level of irrigated plants longer than the three cultivars
during drought period, suggesting that Atlas fescue developed stress status relatively
slower.

The variation of ‘I’w highly depended on SWC through a power equation (Figure
1.3). The ‘Pw in response to declining SWC showed a roughly similar trend for the four
grasses: ‘l’w remained constant at a high level (> -1 Mpa) on a wide range of SWC from
9.33 to about 2.8 %, then decreased rapidly. The results reﬂected that soil water was
readily available and kept sufﬁcient for the plants in the SWC range from 9.33 to 2.8 %.
The critical SWC of 2.8 % was basically in agreement with the threshold of SWC for
initial stomatal closure due to drought stress in tobacco (Nicotiana tabacum) (Riga and
Vartanian, 1999). For Atlas fescue, ‘Pw decreased steeply from a SWC of around 1%,
while for the three grasses, ‘I’w declined dramatically from a relatively higher SWC (1.5
~ 1.8 %), suggesting Atlas fescue was less sensitive to soil water deﬁcits than the tall

fescue cultivars.

24

Leaf elongation

LE of all grasses was negatively affected by the imposed drought stress (P <
0.0001). In irrigated plants, the average LE for Atlas fescue, Barolex, and Kentucky 31
across the 12-week period were similar and signiﬁcantly greater than that of Falcon H,
while Atlas fescue was less than Barolex and Kentucky 31 in the ﬁrst week, (Figure 1.4).
These results revealed that Falcon H grew relatively slower than other grasses at normal
condition, and Atlas fescue initially had a low LE and greatly increased in later weeks
during the drought stress period (Figure 1.5). Between 8th and 10th week, LE of the
irrigated plants was greater than the ﬁrst seven weeks during the drought treatment
period. At 10th week, the leaf elongation of irrigated plants of Kentucky 31 dropped
dramatically, when the plants started to bloom and vegetative growth was switched to
reproductive growth. In drought treated plants, the average LE for four grasses across the
whole drought stress period was not signiﬁcantly different (P = 0.5078). For the three
tall fescue cultivars, the LE of stressed plants started to decrease to below the level of
irrigated plants at 5'h or 6th week stress treatment, whereas for Atlas fescue, LE started to
reduce later, at 7th week stress. The LE of drought treated plants in Barolex and Falcon II
ceased after nine weeks treatment, while in Atlas fescue and Kentucky LE last longer, up
to 10tb week.

The relation between LE and SWC was ﬁtted to a second order polynomial
function (Figure 1.6). When the SWC was high close to full soil capacity (8-9.33 %), the
LE of Barolex and Kentucky 31 were higher than that of Falcon II and Atlas fescue,
indicating that Barolex and Kentucky 31 were growing faster at a high SWC. As the

SWC was declining, LE decreased differently among the four grasses. Falcon II and

25

Atlas fescue showed a relatively slow decreasing rate compared with Barolex and
Kentucky 31, because the slopes of trend line for Falcon II and Atlas fescue were less
steep, suggesting that the growth of Falcon II and Atlas fescue was less sensitive to the
declining SWC.

The LE responded to the decreasing ‘I’w following a polynomial function (Figure
1.7). As ‘l’w was declining and becoming more negative, the LE decreased for all grasses
at different rates. The decreasing rate of LB in Atlas fescue and Falcon II was less than
that of Barolex and Kentucky 31, reﬂecting that LE of Atlas fescue and Falcon II was

relatively insensitive to the increasing severity of drought stress.

Leaf water content

Drought stress treatment had a signiﬁcant (P < 0.0001) effect on the LWC of the
grasses. In irrigated plants, LWC remained constant at a relatively high level (around
87.7%) during the whole experimental period (Figure 1.8). In plants subjected to drought
stress treatment, LWC decreased differently among the four grasses. For the tall fescue
cultivars, LWC of stressed plants was at the level of irrigated plants during the ﬁrst three
or four weeks of growth, whereas for Atlas fescue, LWC maintained the same level as
irrigated plants much longer, up to eight weeks in the drought treatment period. The
LWC of Atlas fescue was signiﬁcantly higher than that of the tall fescue cultivars
between sixth and ninth week in the drought stress treatment. The results implied that
Atlas fescue may accumulate or conserve water in leaf tissue as the stress triggered plants

to maintain the turgor through adapted leaf and root morphology.

26

The LWC in response to SWC showed three stages (Figure 1.9). In the ﬁrst stage,
when SWC was high (8-9.33 %), LWC of the grasses maintained at a high level (around
80-90 %). In the second stage, as SWC was decreasing from 8 % to around 4 %, the
LWC showed a slightly increasing trend. It was clearer in Atlas fescue, the LWC
increased faster than the tall fescue cultivars. In the third stage, when the SWC was
decreasing from 4 % to zero, the LWC reduced dramatically for all the grasses. It was
notable that when SWC was between 2 and 6 %, a medium drought stress status, LWC of
Atlas fescue was higher than that of the other three grasses.

The variation of LWC was dependent on the ‘l’w through a polynomial function
(Figure 1.10). As ‘l’w was becoming more negative, specifically between -1 and -2.5
Mpa, the LWC of grasses was declining. However, Atlas fescue maintained much higher
LWC than the other grasses. In addition, decreasing rate of LWC for Atlas fescue was
less than the other grasses under severe drought stress, speciﬁcally at ‘I’w = -1.2 ~ -2.4
Mpa. The results again suggested that Atlas fescue had an exceptional ability to

accumulate or conserve water in leaf tissue under severe drought stress.

Root length and biomass

The RL of the grasses ranged from 115 to 132 cm and varied signiﬁcantly (P =
0.0335) among the four grasses. Barolex had the longest root system, while Kentucky 31
had the shortest one (Figure 1.11. A). RL of Falcon H was negatively affected by the
drought treatment, whereas there was no signiﬁcant difference in RL between ini gated
and drought treated plants for Atlas fescue, Barolex, and Kentucky 31. No signiﬁcant

difference was found in RM among these grasses across the irrigated and drought stress

27

treatments (P=0.07l7). However, the drought treatment had an signiﬁcant (P=0.0003)
effect on RM. The stressed plants had signiﬁcantly less RM than that of irrigated plants
for Atlas fescue, Barolex, and Falcon, but not for Kentucky 31 (Figure 1.11. B). The
results suggested that Barolex and Atlas fescue with longer roots might be more adaptive
to drought stress than Kentucky 31. However, the RM of Kentucky 31 was not reduced
by severe drought stress suggested that Kentucky 31 may tolerant the drought stress
through maintenance of viable root capable of extracting available water, even though it

had a shorter root.

DISCUSSION

Understanding drought tolerance mechanisms in grass species and the genetic
variation among genotypes would guide breeding and management programs in
improving the drought tolerance in grass species. Several mechanisms have been
implicated in causing differences in drought tolerance of plants (Levitt, 1972; Jones,
1981). Unlike annual plants that can escape drought by maturing before stress becomes
severe, perennial grasses can not escape drought completely by ﬂowering early. In our
study, no drought stress treated plant was ﬂowering, except some control plants, which
supported the grasses we studied did not escape drought by earlier mature, but oppositely,
reproductive growth was inhibited by the imposed drought stress. In our study, all the
four grass maintained leaf elongation until a very low SWC (1.2 %) (Figures 1.1 and 1.5),
suggesting they are active rather than dormant during the drought stress period. As we

observed, with the SWC decreasing, leaves of all the four grasses rolled initially. As

28

SWC decreased ﬁrrther, the leaf tip showed ﬁring and lower leaves became bleached.
These symptoms suggested that these grasses may employ similar strategy to reduce the
transpiration surface area and close stomata to limit plant water loss. Tall fescue relied
primarily on an extensive root system for drought tolerance (Qian et al., 1997), because
the longer root system had greater volume and surface areas of roots in contact with soil
to facilitate water and nutrient uptakes under drought stress. Root system has been
chosen as a selection trait in breeding programs to improve drought tolerance of fescue
(Torvert, et al., 1990). In one previous study, the root length of 16 tall fescue cultivars,
which represented four growth types, dwarf, turf, intermediate, and forage, was 60-75 cm
(Kim, et al., 1999). In our study, however, the RL of the four grasses was 115-132 cm,
although varied, and was much greater than previously reported values (60-75 cm). The
results of this study implied that the four grasses can at least avoid the drought
consequences by producing extensive roots to absorb more water from soil. Barolex had
a relative longer root, but did not maintain LE and LWC optimally longer than other
grasses, suggesting that beside the adapted leaf and root characters, the grasses employ
other mechanism to resist drought stress to avoid drought stress. Usually, drought
tolerant genotypes will posses more than one mechanism, and many factors can
contribute to drought tolerance of plants (Aussenac et al., 1989).

During water stress, numerous physiological functions are affected before the
leaves show signs of wilting. However, cell expansion is the most sensitive trait (Boyer,
1988) and is reduced by drought before any other physiological process (Wardlaw, 1969).
In our study, LE was measured weekly during the drought stress as a major indicator of

the status of plant response to drought. Notably, for Atlas fescue and Kentucky 31, LE

29

had a signiﬁcant decline even one week earlier than ‘l’w, which has been shown to be an
effective measurement of the maximum soil water potential available to roots (Tardieu
and Simonneau, 1998) (Figures 1.2 and 1.5). The results conﬁrmed the value of LE for
its sensitiveness as a parameter for drought tolerance evaluation in plants. In addition, it
was not possible to make measurements of ‘l’w on severely drought stressed leaves due to
the limitation of equipment, but LE could be measured at any time and situation. Cell
expansion directly contributes to the leaf elongation. A reduced leaf growth is mainly
caused by a decrease in turgor pressure of enlarging cells (Matyssek et al., 1988).
Osmotic adjustment may enable a leaves to maintain sufficiently high turgor pressure in
the growing zone to maintain the leaf elongation. The LE of Falcon H and Atlas fescue
declined slower as the SWC and WW were decreasing (Figures 1.6 and 1.9). The result
suggested that the osmotic adjustment may play a role in maintaining cell pressure
necessary for LE, which is the resistance mechanism employed by the grass to resist
drought stress.

The LE and LWC data (Figures 1.5 and 1.8) showed that Atlas fescue maintained
leaf growth and regular LWC longer than the other three grasses. It can be debated that
maintenance of growth and LWC of Atlas fescue may be the result of a relatively low
rate of water use by Atlas fescue, because in studies of container-grown plants, dry-down
responses are often confounded with plant size (Graves et al., 2002). The small size plant
may not evaporate sufﬁcient water to cause severe stress. Therefore, SWC and ‘Pw may
decline slower in large plants, regardless of their relative drought tolerance. However, in
our study, plant size was controlled to be the same by establishment for 15 weeks and

trimming to same height (Figure 1.12). In order to eliminate any possible effect of plant

30

size or rapidness of stress development on the leaf water loss and reduced leaf growth, a
regression analysis was performed between LE and LWC verses SWC (Figures 1.6 and
1.9) and ‘PW (Figures 1.7 and 1.10), respectively. Results of comparison suggested that
(1) the LE of Atlas fescue and Falcon H were less sensitive to the drought stress than
Barolex and Kentucky 31 as SWC and ‘PW were decreasing (Figures 1.6 and 1.9); (2) a
marked mechanism may exist in Falcon II and Atlas fescue to maintain the cell turgor
necessary for cell expansion as SWC was declining and ‘PW was becoming more
negative; (3) all the grasses intended to accumulate more water as they sense the drought
stress and Atlas fescue was more capable to have an earlier sense and to accrue more
water in the leaf tissue than the other three grasses (Figures 1.7 and 1.9); (4) Atlas fescue
had an exceptional ability to accumulate water in leaf tissue under severe drought stress
(at ‘l’w = -1.2 ~ -2.4 Mpa) (Figure 1.10). Atlas fescue consumed less volume of soil
water between the fourth and eighth week of drought stress (Figure 1.5), but maintained
LE and LWC higher (Figures 1.5 and 1.8) further indicating its efﬁcienct water use and
expression of drought tolerance.

In summary, drought stress reduced LE, LWC, ‘l’w, root biomass & length of the
grasses. Grasses avoid drought stress through changes in leaf and root morphology and
through osmotic adjustment to maintain sufﬁcient high turgor pressure in the growing
zone for leaf elongation. The slower decrease in LE, LWC, and ‘Pw for Atlas fescue
during the drought stress period suggested its greater drought tolerance and the potential

value for grass drought tolerance enhencement in the breeding program.

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Nguyen, H.T. Babu, RC. and Blum A. 1997. Breeding for drought resistance in rice:
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Pattanagul, W., Madore, MA. 1999. Water deﬁcit effects on rafﬁnose family
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Qian, Y.L., Fry, J .D., Upham W.S. 1997 Rooting and drought avoidance of warm-season
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45

Wardlaw, LP. 1969. The effect of water stress on translocation in relation to
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46

CHAPTER 11

Parental Genome Composition and Genetic Classiﬁcations of
F1 Hybrids and Backcross Progeny Derived from Intergeneric

Crosses of Festuca mairei and Lolium perenne

(Published in Crop Sci. (2003) 43:2154-2161)

ABSTRACT

Intergeneric hybridization between Festuca and Lolium has been a long-term goal
of forage and turfgrass breeders to generate improved cultivars by combining stress
tolerance of F estuca with rapid establishment of Lolium. However, wide-distance
hybridizations usually result in one of the genomes being eliminated from the hybrid due
to incomplete chromosome pairings and crossovers. In this study, RAPD and SSR
markers were used to detect the parental genome composition of hybrids and backcross
derivatives generated from crosses between F estuca mairei St. Yves (Fm) and Lolium
perenne L. (Lp). A total of 229 RAPD and 127 SSR polymorphic bands were used to
estimate the parental genome composition of two F 1 hybrids, one amphiploid and 13
backcross progeny. Each of the 16 progeny exhibited integration of Fm and Lp genomes
with varying levels of Frn/Lp genome ratios. Correlation (r=0.80) between the Fm/Lp

genome ratios assessed by SSR and RAPD markers was highly signiﬁcant (P = 0.0004).

47

The non-coinheritance of the linked markers suggested chromosome crossover between
the two parents. Cluster and principle component analyses of the progeny consistently
revealed four groups. Group I composed of one backcross progeny that had a distinctly
different genetic background from other individuals. Group H included seven progeny
that introgressed more of the Frn than Lp genome and clustered with the Fm parent.
Group III comprised of six progeny showing similar amounts of genome introgression
from both parents. Group IV contained two backcross progeny that introgressed more of
the Lp genome and clustered with Lp parents. These results provide information on
parental genome composition and classiﬁcations of 16 intergeneric progeny that would

be useful to forage and turfgrass breeders.

Keyword: Festuca mairei, Lolium perenne, Simple sequence repeats (SSR), Random

ampliﬁed polymorphic DNA (RAPD), Parental genome composition.

INTRODUCTION

Perennial ryegrass (Lolium perenne L.) (Lp) is a cool-season grass (2n=2x=14,
LL) that has been widely used as turf and forage with superior quality and rapid
establishment. However, lack of drought tolerance makes Lp less persistent during hot
and dry summers. One approach for improvement of drought tolerance in perennial
ryegrass is introgression of alien genomes from other drought tolerant genera, such as
F estuca (Riewe and Mondart 1985). Intergeneric hybridization followed by
backcrossing or by chromosome doubling can produce alien chromosome addition,

substitution, or translocation progeny (Shanna et al. 1995). Derivatives from

48

intergeneric hybrids between F estuca and Lolium combining desirable agronomic

attributes, or creation of novel allopolyploids may have great potential in grass breeding.

F estuca mairei St. Yves (Fm), commonly known as Atlas fescue, is a xerophytic
tetraploid (2n=4x=28, M1M1M2M2). Fm tolerates high temperature and drought (Borill et
al. 1971) and has a high photosynthetic rate (Randall et al. 1985). Combining the
genomes of Fm and Lp could be an effective means to produce hybrids of high
agronomic potential. Fm and Lp genomes show a distant relationship due to a low level
of homeologous chromosome pairing and hence less genetic recombination (Chen et al.
1995). Using genomic in situ hybridization (GISH), homeologous chromosome pairing
between L and M genomes has been detected in hybrids from crosses between Fm and Lp
(Cao et al. 2000). This ﬁnding raises the expectation that chromosome crossover and
genetic recombination may occur between the Lp and Fm genomes and the possibility of
introgression of desirable genes from Fm into Lp exists. This possibility has also been
conﬁrmed by cytogenetic studies of the Lolium/Festuca complex (Humphreys et a1.
1997)

Molecular markers have been widely used for efficiently detecting alien
chromosome segments in many crops and are of increasing importance in distinguishing
genomes between plant species. Fluorescence in situ hybridization (FISH), which utilizes
chromosome-speciﬁc DNA probes, could be a powerful tool to detect alien genome
introgression in such hybrids and backcross progeny. Compared to PCR-based molecular
markers, the procedure of FISH is more difﬁcult, needs trained personnel, and is
relatively expensive. In addition, the amount of information obtained by the FISH

procedure is very limited. The PCR based markers such as simple sequence repeat (SSR)

49

and random ampliﬁed polymorphic DNA (RAPD) are important genetic markers for
plant genome analysis due to their genome-wide distribution, simple assay by PCR, and
high levels of polymorphism. SSR markers are co-dominantly inherited and have been
successfully isolated from perennial ryegrass, which constitute a valuable resource of
markers for the molecular breeding of ryegrass (Kubik et al. 2001; Jones et al. 2001). In
tall fescue (F estuca arundinacea Schreb.) (PA), a large number of SSR markers have
been generated through mining the FA expressed sequence tag (EST) database, which
could be applied in molecular mapping, comparative genomics, and molecular plant
breeding across a wide range of turfgrass species (Saha et al. 2004). RAPD is another
marker of choice for routine ﬁngerprinting of germplasm and cultivars because of the low
cost and random distribution throughout the genome. Even though RAPD markers are
dominantly inherited, they are useful for monitoring genome introgressions from wild
donor species to cultivated species (Bemabdelmouna et al. 1999; Siffelova et al. 1997).
Assessment of the genome introgression status of the progeny from intergeneric
hybridization by using SSR and RAPD markers will be critical in directing breeding
programs to develop improved grass cultivar. With the goal of transferring drought
tolerance of Frn into Lp, a population comprised of hybrids, amphidiploid, and backcross
progeny derived from intergeneric crosses between Fm and Lp were generated (Chen et
al. 1995). For breeding application, evaluating or monitoring the Fm and Lp genome
compositions in these progeny will assist in identifying individuals with desirable
genome combinations and as a result new perennial ryegrass cultivars with improved

drought tolerance can be developed.

50

The objectives of this study were to determine the Fm and Lp genome
compositions of hybrids and backcross progeny using PCR-based molecular markers and

to estimate relatedness between progeny and parents.

MATERIALS AND METHODS

Plant materials

A single Fm plant (le) was chosen from a population collected in Morocco.
This Fm population was adapted to the hot and dry summers of Northwest Africa (Borill
et al. 1971). The other single plant of Fm (Fm2) was obtained from plant introduction, PI
283313. Two single Lp plants from turfgrass cultivars ‘Citation II’ (Lpl) and ‘Calypso’
(Lp2), respectively, were also chosen. Reciprocal intergeneric crosses between selected
Fm and Lp plants were made to introduce drought tolerance of Fm to Lp (Chen et al.
1995). Three 3x F1 hybrids (2n=3x=21) with reproductive tillers and two 4x F1 hybrids
(2n=4x=28) were generated. The 4x F1 was generated by 2n gamete production (Chen et
al. 1997). The partially fertile 4x F 1 hybrids, used as the female parents, were back-
crossed to the diploid Lp (Chen 1996). The BC] progeny were open-pollinated in
isolation and 13 backcross progeny were obtained. A triploid F1 hybrid from the le x
Lpl cross was treated with 0.25% colchicine at room temperature for 24 hr and an
amphidiploid (2n=6x=42) plant was produced by successful chromosome doubling (Chen
1996). Plant materials used in this study included parental plants (le, Lpl and Lp2),
two F1 hybrids: a 4x F1 (lepr2) and a 3x F1 (Lp2me2), 13 backcross progeny, and

the amphidiploid (the Fm2 plant was not included because it died after crossing).

51

DNA isolation

Total genomic DNA was extracted from young growing leaves. Plant cells were
lysed using the extraction buffer (0.1M Tris- HCl, 0.05M EDTA-Na, 0.25M NaCl,
PH=8.0 and 0.04M dodecyl sulfate (SDS)). Potassium acetate (5M) was used for
deproteinization and recovery of DNA. Nucleic acid was precipitated by isopropanol
followed by RN ase treatment to degrade the RNA. The DNA concentration was
measured by spectrophotometer readings at 260 nm and the purity was determined by the
ratio of the absorptions at 260 nm and 280 nm. DNA quality was checked by loading 100

ng DNA in a 1% agarose gel by electrophoresis at 72 V for 2 hr.

RAPD screening Protocol

Forty-one decamer RAPD oligonucleotides (Operon Technologies, Alameda,
California) (Table 2.1) were used in screening and detecting maximum polymorphism
between the Fm and Lp parents and a F1 hybrid. These 41 primers were mostly ﬁ'om C
and Y kits (Charmet et al. 1997; Siffelova et al. 1997). Genomic DNAs from all the
progeny were used as templates for RAPD analyses with these 41 polymorphic primers.
The 25 ul RAPD reaction mixture contained lOmM Tris-HCl (pH=8.3), 4 mM MgC12,
0.24 mM of each dNTP, 1.2 M of primers, 30 ng of template DNA, and l U Taq.
Ampliﬁcation conditions were as follows: 3 pre-ampliﬁcation cycles (94°C for l min,
35°C for 1 min and 72°C for 2 min). After initiation of the reaction, 35 ampliﬁcation
cycles were conducted (94°C for 20 s, 40°C for 20 s, and 72°C for 2 min). The last cycle

was followed by 5 min at 72°C to ensure that primer extension reactions proceeded to

52

completion. RAPD proﬁles were generated in 2% agarose gel with 0.003% ethidium
bromide subjected to electrophoresis at 72 V for 3.5 hr. A 1 Kb ladder was used to mark
the size of the fragments. RAPD images were obtained through an Eagle Eye II still

video system V3.2 (Stratagene, La Jolla, California).

SSR Screening Protocol

Seventy-six tall fescue EST-SSR primer pairs developed at the Samuel Roberts
Noble Foundation (Saha et al. 2004), and 32 SSR primer pairs developed from ryegrass
(Kubik et al. 2001; Jones et al. 2001) were tested on the Fm and Lp parents. The primer
combinations that produced polymorphic bands between parents (Table 2.2) were then
utilized to test all plant materials. The ethidium bromide detection protocol was used for
ryegrass and 19 tall fescue EST-SSR primer pairs and the silver staining protocol was
used for screening of the remaining primer pairs.

In ethidium bromide detection protocol, 10 pl PCR reaction mixture contained
lOmM Tris-HCl (pH=8.3), 3 mM MgC12, 0.25 mM of each dNTP, 0.2 uM of forward and
reverse primers, 10 ng of template DNA, and 1 U Taq polymerase (Gibco Invitrogene,
Grand Island, New York). PCR ampliﬁcation was conducted in a PT C-100
programmable thermal controller (MJ Research, Waltham, Massachusetts).
Ampliﬁcation conditions were as follows: initial denaturation at 95°C for 5 min, 40
ampliﬁcation cycles [95°C for 50 s, 42~60°C (the optimum annealing temperature for
each primer pair, Table 2.2) for 50 s, and 72°C for 90 s], and the ﬁnal extension of the
reaction at 72°C for 10 min. SSR proﬁles were generated by running PCR products in a

6% non-denaturing polyacrylamide gel for 2.5 hrs at 350V. TBE buffer with 0.002%

53

ethidium bromide ﬁlled in the positive node tank was pre-run one hour for visualizing
bands under UV light.

In silver staining protocol, 20 ng of DNA was used as a template for each PCR
reaction. The PCR reactions consisted of one unit of AmpliTaq Gold® with GeneAmp
PCR buffer II (Applied Biosystems/Roche, Branchburg, NJ), 3 mM MgC12, 0.2 mM of
dNTPs, and 0.2 uM of each primer in a 10 pl reaction. PCR ampliﬁcation conditions
were same as in ethidium bromide detection protocol. PCR products were resolved on
6% polyacrylamide denaturing gels (Gel Mix 6, Invitrogen Life Technologies). Gels
were silver stained using Silver Sequence Kit (Promega, Madison, WI) for SSR band

detection.

Data Analysis

Intense and repeatable bands in RAPD proﬁles were scored as 0 and 1 for absence
and presence, respectively. In SSR proﬁles, the intense bands within the expected size
range were scored as 0 and 1 for absence and presence, respectively. Parental Fm/Lp
genome speciﬁc band ratios (Fm/Lp genome ratio) of the Fm-Lp hybrids and backcross
progeny were calculated as the ratio of the percentage of Fm-speciﬁc-bands to that of Lp-
speciﬁc bands with an assumption that all the markers are randomly dispersed in the
whole genome. Dice coefﬁcient (Dice 1945) was used to calculate similarity matrices for
both SSR and RAPD data by running similarity for the qualitative data module using the
numerical taxonomy and multivariate analysis system (NT SYSpc version 2.1, Exeter

software, Setauket, New York). The Dice coefﬁcient similarity matrices from SSR and

54

RAPD data were applied for cluster analysis independently with the option of sequential
agglomerative hierarical nested (SAHN) cluster analysis and the unweighted pair-group
method, an arithmetic average (U PGMA). The goodness of ﬁt of each clustering with the
distance matrix was tested using cophenetic matrix correlation. Resulting dendrograms
from SSR and RAPD data were compared using cophenetic matrices and mantel test
(Mantel 1967). Merged data from RAPD and SSR was used for cluster analysis to
generate a ﬁnal dendrogram. Bootstrap analysis was applied to assess the significance of
the clusters in the dendrogram using FreeTree software (Pavlicek et al. 1999) with a
resampling method of 2000 repetition counts. Principle component analysis was
conducted using a correlation matrix from merged RAPD and SSR data and three
eigenvectors were extracted. The data was projected onto these three eigenvectors and

displayed by the Mod3D plot module.

RESULTS

Polymorphism and fragment segregation

1. Detected by SSR markers

The preliminary screening detected eight out of 32 ryegrass primer pairs and 27 of
76 tall fescue EST-SSR primer pairs that were polymorphic between the parents.
Sequences and sources of these polymorphic primers are presented in Table 2.2.
Ampliﬁcation of ryegrass genomic SSRs and tall fescue EST-SSRs in the preliminary

screening panel are presented in Figure 2.1.a and 2.1.b, respectively. A total of 127

55

polymorphic bands were scored from the 35 SSR primer pairs. Among the 127 bands, 23
(18.1%) were present in the Fm-Lp progeny but not in the three parents (Fm, Lpl, and
Lp2). Such bands probably were contributed by the lost parent (Fm2). Fiﬁy-one (40.2%)
were Fm-speciﬁc and 51 were Lp-speciﬁc bands (12 Lpl-speciﬁc, 22 Lp2-speciﬁc and
17 common bands between Lpl and Lp2). The relatively large number of bands common
to Lpl and Lp2 indicated a close relationship between these two genotypes. Only one
common band was found between Fm and Lpl as well as between Pm and Lp2, which
indicate wide genetic distances between the Fm and Lp genomes.
All 127 bands segregated among the Fm-Lp progeny (Table 2.4). More than half of the
alleles of both parents (le and Lpl/Lp2) were combined in the 4x Fl hybrid (le x
Lp2) and the amphiploid derived from a 3x Fl (le x Lpl) crosses, indicating successful
wide crosses. In all backcross progeny, different levels of alleles of both Fm and Lp
parents were present in each individual (Table 2.4), which suggested segregation of
alleles from both parents during backcrossing.

Table 2.5 showed the Fm/Lp genome ratio of the Fm-Lp progeny. The higher
Fm/Lp genome ratio basically indicated more Fm genome introgression into the progeny.
Results revealed all the progeny had an Fm/Lp genome ratio above zero indicating that
the Fm genome was successfully introgressed into these individuals. However, the ratios
ranged from 0.09 (G14) to 1.95 (le x Lp2) indicating that the Fm genome had been
retained in these progeny at various extents.

Of the 27 polymorphic EST-SSR loci, 15 have been mapped to ryegrass linkage
groups (LGs) (Warnke et al. 2004) (Table 2.3). Three groups of these marker loci were

uniquely mapped on both male and female maps. NFFA031 and NFFA75 were mapped

56

on LG 1 with an interval of 19 cM. NFFA015, 036, and 048 were mapped on LG 6 with
the interval of 29 and 17 cM, respectively. NFFA019 and NFFA069 were tightly linked
on LG 7 with an interval of 6 cM. To investigate the event of chromosome crossover
between genome M and L, the co-segregation of markers on each of the three LGs was
assessed among the Fm-Lp hybrids and backcross individuals. The results indicated that
all the linked markers, including the tightly linked NFFA019 and NFFA069, were not co-
inherited into the hybrids or backcross individuals. The separations of the linked markers
suggested the crossover of homeologous chromosomes and M and L genome
recombination in the progeny from intergeneric hybridization.
2. Detected by RAPD markers

Ampliﬁcation of RAPD primers in the preliminary screening panel is presented in
Figure 2.1.0. In total, 229 polymorphic bands were generated ﬁ'om 41 RAPD primers.
The number of polymorphic bands scored for each primer ranged from 1 to 11.
Distribution of the 222 RAPD bands among the parents was similar to that of the SSR
markers. Thirty-six bands (15.7%) were present in the progeny but not in the three
parents indicating the contribution of the Fm2 genome. Ninety-six (41.9%) were F m-
speciﬁc and 87 (38.0%) were Lp-speciﬁc bands including the Lpl- and Lp2-speciﬁc
bands and the bands common to both parents. Similar to the SSR results, a higher
number of common bands between Lpl and Lp2 (41, 17.9%) suggested a relatively close
relationship between Lpl and Lp2, and a lower number of common bands between Fm
and Lp (Lpl, 4.5%; Lp2, 3.0%) suggested a distant relationship between Fm and Lp.

RAPD results were consistent with SSR results as both parent- speciﬁc bands

were inherited in the F1 hybrids and amphiploid, and various levels of segregation

57

occurred in the backcross progeny (Table 2.4). Fm/Lp genome ratios (Table 2.5) of these
Fm-Lp progeny ranged from 0.08 (G1 la) to 1.79 (le x Lp2). This result conﬁrmed
that all progeny retained the Fm genome at different levels. The correlation coefﬁcient
(F080) of the Fm/Lp genome ratios assessed by SSR and RAPD markers was highly
signiﬁcant (P = 0.0004), which reﬂected the reliability of the two marker systems in

assessing genome introgression.

Genetic classiﬁcation analysis

Cluster analysis of RAPD and SSR data generated two similar dendrograms. The
goodness of ﬁt of the clustering with the similarity matrix was tested using cophenetic
matrix correlation. Both dendrograms were ﬁtted with the corresponding similarity
matrices by showing a correlation value of 0.778 with SSR data and 0.884 with RAPD
data. The two dendrograms were compared using cophenetic matrices and mantel tests.
The correlation between the two dendrograms was signiﬁcant (r=0.723, Prob. Random
Z< obs. Z: P=I.000), and therefore SSR and RAPD data were merged to yield one
pairwise similarity matrix. The similarity coefﬁcients ranged from 0.063 (between Pm]
and Lp2) to 0.868 (between G6 and G27a), demonstrating a wide distance between
parents and a varied range of genetic distances among the progeny. Cluster analysis
based on this similarity matrix generated a dendrogram (Figure 2.2) with a high goodness

of ﬁt (F0864).

The cluster analysis revealed four groups (Figure 2.2). Group I contained only

one backcross progeny individual, G8. Group H consisted of the parent le, 4x F1

58

hybrid of le x Lp2, the amphiploid derivative from the chromosome-doubled 3x F; of
le x Lpl and 5 backcross progeny: G6, G16, G26, G27a, and G30b. Group 111
included a 3x F1 hybrid of Lp2 x Fm2, and 5 backcross progeny: G1 lb, G15, G24, G27b,
and G30a. Group IV had two Lp parents and two backcross progeny, G1 1a and G14.
Results suggested that: (1) G8 in group I has a distinct genetic background and
differentiated from the F m-Lp genetic basis by showing novel fragments in both RAPD
and SSR analysis, because all the other progeny except G8 formed one distinct branch
from group I with a bootstrapping value of 99% (Figure 2.2), (2) progeny within group II
introgressed more of the Fm genomes, because of clustering with le, (3) group III was
between the two parental groups, the progeny in this group showed similar amount of
genomes from both Fm and Lp, and (4) in group IV the two backcross progeny had
retained very little of the Fm genomes and therefore were highly Lp-like progeny. The
reliability of the clusters was evident by relatively high bootstrapping values at all the

branches (Figure 2.2).

The principle component analysis, which is based on the original data from SSR
and RAPD, rather than a similarity matrix, was performed for ﬁirther conﬁrmation of the
genetic differences of the progeny (Figure 2.3). The three-dimensional scatter plot
distribution of the Fm-Lp progeny consistently revealed the four groups derived from
cluster analysis. Group I with only G8 was distinct from the other individuals in the
analysis by showing a high R3 value. This result suggested a big genome change or
rearrangement in G8, which may have happened during hybridization of the wide cross
between Fm and Lp, or G8 might have been mislabeled in the greenhouse. Fm-Lp

progeny in group II were relatively more sparsely scattered between the parents, Pm and

59

Lp, particularly G16, which is consistent with the cluster analysis showing a relatively
lower bootstrapping value (47%). Group III was located further away on the edge of the
graph along the R1 and R2 axes, which suggested genetic differences between Pm] and
Fm2 plants. Group IV was tightly clustered indicating the close relationship among the
two backcross progeny and two Lp parents and suggested that this two backcross progeny
had less Fm genome and more Lp genome, which is consistent with the Fm/Lp genome

ratio results (Table 2.5).

DISCUSSION

Molecular marker application for genome composition detection

Reproducibility of some PCR-based markers (e. g., RAPD) can be a source of
concern. In this study, we took an approach involving two steps for screening the
molecular markers. First, the markers were tested only on the two parents for PCR
ampliﬁcation and the sizes of high intensity clean bands were recorded. Second, the
parents were included along with the progeny for recording the segregation and
inheritance of only the bands that were previously detected in the parents. This approach
improved the reproducibility of the markers and increased the reliability of the analysis.
Signiﬁcant correlation between the Fm/Lp genome ratios assessed by SSR and RAPD
markers veriﬁed the value of the PCR-based markers in genome introgression
assessments, which is in agreement with previous studies (Charmet et al. 1997; Prakash

et al. 2002).

60

The mapped EST-SSR markers on ryegrass LGs showed a great applicable value
in assessment of the homeologous chromosome cross-over and genome recombination in
the intergeneric hybrid, which is normally tested by sophisticated cytogenetic studies. In
addition, the map location of EST-SSRs derived from transcripts with known functions,
may provide functional genetic markers for direct characterization of the QTLs for
putatively correlated traits (Saha et al. 2005). Genomic SSRs are highly variable because
they are mostly in the non-coding sequence and are less conserved, which limits their
uses across different species. EST-SSR markers are derived from transcribed regions of
the DNA, and are generally more conserved and have a higher rate of transferability
when compared with genomic SSR markers (Scott et al. 2000). Gupta (2002) found 95%
of the EST-SSR primer pairs exhibited 100% similarity between Hordeum and T riticum,
which indicated that the ﬂanking sequences of SSRs were not only conserved across
species but also across related genera within Poaceae (Triticeae EST-SSR Coordination).
In this study, a total of 32 SSR markers developed from the perennial ryegrass genome
were screened against Fm and Lp and 8 (25%) displayed distinct and polymorphic
ampliﬁcation ﬁ'om both genomes, whereas 27 of 76 EST-SSR markers (35.5%)
successfully discriminated between Fm and Lp. The relatively higher rate of cross genera
ampliﬁcation might reﬂect the usefulness of EST-derived microsatellite markers for

molecular genetic analysis for wide distance hybridization.

Fm-Lp genome recombination in the 4x F;

In the 4 x F, hybrids derived from Fm x Lpl, 84.3 and 90.6% of Fm-speciﬁc SSR

and RAPD bands were inherited, respectively (Table 2.4). Theoretically, at these loci, the

61

genotype of Fm, as an autotetraploid, could be Aaaa, AAaa, AAAa or AAAA and the Lp
genotype is a. As a result, the band ratios of F1 should be 1:1 for Aaaa x aa, 5:1 for
AAaa x a, 1:0 for AAAa x a and AAAA x a. If the four Fm genotypes among these
loci have the same ratio, then on average, the F1 could have 83.2% Fm-speciﬁc bands.
The x2 test was used to test the signiﬁcance of consistency of observed Fm-speciﬁc
bands presented in the 4x F1 with the theoretical expectation. The analysis revealed that,
for both SSR and RAPD data, the observations were consistent with the expectation
(P=0.8 and P=0.05 for SSR and RAPD data, respectively). Fm was considered an
autotetraploid or at least a partial allotetraploid because the genomes of M1 and M2 are
closely related and readily paired in the F ls of Fm and Lp (Chen et al. 1995). Our results
supported the autotetraploidy of Fm. The genome of the other parent, Lpl was
transferred into the 4x F1 by 75% and 53% dominant alleles detected by SSR and RAPD,
respectively. Lpl was transferred to the F1 through 2n pollen and the relatively high rate
of dominant alleles transfer suggests that the Zn pollen were produced through ﬁrst

division restitution (FDR) (Chen et al. 1997).

Fm-Lp genome recombination in the progeny

Exploitation of available variability for improvement of any crop depends on the
ability to introgress the desirable genome of source plants to cultivated varieties (Prakash
et al, 2002). This strategy is largely facilitated by precise monitoring of alien and
cultivated genome combinations at a molecular level. In backcross progeny detected in
this study, dominant alleles from both Fm and Lp parents were present in each individual

at various levels (Table 2.4), suggesting segregation of alleles of both parents during the

62

backcrossing. Estimating allelic segregation ratios was not useful because of the
involvement of two genotypes of Lp, the interpollination for the generation of backcross
progeny and the limited population size. In general, the Fm/Lp genome ratios (Table 2.5)
could reﬂect recombination of the two genomes from different genera in backcross
individuals. Fm/Lp genome ratios estimated for the two F1 hybrids and amphiploid
(Table 2.5) did not indicate the ratio of the parents’ genome involvement. The reason is
that for the estimation of genome ratios, the number of Lp-speciﬁc bands including both
Lpl- and Lp2-speciﬁc bands was used, but for generation of F1 hybrids, only one
genotype of Lp (either Lpl or Lp2) was utilized for crossing. For example, in 4x F1 of
Fm x Lpl, the Fm/Lp genome ratio from the SSR marker is 1.95, which is derived from
the ratio of the percentage of Fm-speciﬁc to Lp-speciﬁc bands. However, the Fm/Lp
genome ratio should be the percentage of Fm-speciﬁc bands to Lpl-speciﬁc bands and
should equal 1.12 (84.3/75).

In backcross progeny G6 and G27a, the Fm/Lp genome ratios assessed by SSR
and RAPD markers were not highly consistent (Table 2.5) because of the lower ratios
obtained by SSR markers and much higher ratios by RAPD markers. This result could be

due to limited number of markers applied.

Classiﬁcation of the progeny

Weak grouping and low bootstrapping value typically associate with a ﬂow of
genetic information among the individuals (Prakash et al, 2002). In this study, grouping
from cluster analysis and bootstrap (Figure 2.2) was highly consistent with the grouping

from principle component analysis (Figure 2.3), and the bootstrapping values at all the

63

branches were greater or at least equal to 47%. This result might suggest the process of
genome stabilization in the Fm-Lp progeny.

Most backcross individuals contained large amounts of the Fm genome, and
therefore, either clustered with Fm or in the middle of parental groups, except G1 1a and
G14, which closely clustered with Lp. Also, the 4x F1 of Frn x Lp was clustered with Fm
and the amphiploid was closer to Fm than to Lp (Figure 2.2, Figure 2.3, and Table 2.5).
The Fm-biased classiﬁcation might be due to larger amounts of Fm-speciﬁc bands that
were detected and used in this study. Even though, more backcross generations are
necessary to recover more of the Lp genome and at the same time maintain the desired
introgressed Fm characteristics. In general, cluster analysis and the principal component
analysis consistently provided visualized information on the introgression status of these
Fm-Lp progeny, which could be used as a guide in breeding programs, such as which
progeny retained the Fm alien genome, and which progeny should be backcrossed to the

cultivated Lp to recover good turf quality.

Application of the Fm-Lp progeny for turfgrass breeding

The partially fertile 4x F1 hybrid could be very useful in a backcross-breeding
program to develop a diploid perennial ryegrass, which hopefully would inherit a certain
level of drought tolerance from Fm. The 3x F 1 hybrid was sterile, however, fertility
could largely be restored through chromosome doubling and therefore has potential use in
developing new cultivars. With several generations of backcrossing and selection for
meiotic stability and turf quality, a drought tolerant cultivar could be developed. In this

study, progeny G1 1a and G14 recovered most of the Lp genome with only one generation

of backcrossing to Lp (Table 2.5). They could be tested for improved drought tolerance
and meiotic stability to evaluate the potential for new cultivar release. The other
backcross progeny need more generations of backcrossing to Lp to recover more
perennial ryegrass attributes.

The ability of molecular marker to discriminate between Lolium and Festuca
DNA in hybrids and backcross progeny enables introgression maps to be created if these
markers have been localized on a linkage map. By combining the genetic mapping
approach and physiological complex trait dissection, it should be possible to identify and
localize the importance of trait components that contribute to drought tolerance
(Humphreys et al, 1997). Markers associated with trait components can be applied to
assist in drought tolerant progeny selection and speed up the breeding process. It is worth
noting that in our study a number of F m-Lp progeny successfully combined both
genomes from Fm and Lp and some of those progeny showed desirable agronomical
traits in our initial greenhouse evaluation (unpublished data, 2005). The results provide
information that the Fm-Lp progeny could be used not only as the basis for new cultivar

release but also for drought tolerance associated marker development.

65

Table 2.1. The name and sequence of 41 RAPD polymorphic primers and the number of
fragments ampliﬁed. All the RAPD oligonucleotides are from Operon Technologies.

 

 

Primer Sequence Number of polymorphic fragments scored
OPA-04 5'-AATCGGGCTG-3' 7
OPA-05 5'-AGGGGTC'ITG-3' 4
OPA-07 5'-GAAACGGGTG-3' 6
CPA-08 5'-GTGACGTAGG-3' 6
OPA-20 5'-GTTGCGATCC-3' 4
OPB-12 5'-CCTTGACGCA-3' 9
OPC-Ol 5'-TTCGAGCCAG-3' 9
OPC-02 5'-GTGAGGCGTC-3' 5
OPC-04 5'-CCGCATCTAC-3' 2
OPC-OS 5'-GATGACCGCC-3' 1 1
OPC-06 5'-GAACGGACTC-3' 3
OPC-07 5'-GTCCCGACGA-3' 5
OPC-08 5'-TGGACCGGTG-3' 1 1
OPC-09 5'-CTCACCGTCC-3' 9
OPC-lO 5'-TGTCTGGGTG-3' 5
OPC-l 1 5'-AAAGCTGCGG-3' 7
OPC-13 5'-AAGCCTCGTC-3' 7
OPC-15 5'-GACGGATCAG-3' 7
OPC-16 5'-CACACTCCAG-3' 4
OPC-19 5'-GTTGCCAGCC-3' 3
OPC-20 5'-AC'I'I‘CGCCAC-3' 6
OPE-09 5'-CTTCACCCGA-3' 4
OPY-Ol 5'-GTGGCATCTC-3' 5
OPY-02 5'-CATCGCCGCA-3' 10
OPY-03 5'-ACAGCCTGCT-3' 6
OPY-05 5'-GGCTGCGACA-3' 7
OPY-06 5'-AAGGCTCACC-3' 5
OPY-07 5'-AGAGCCGTCA-3' 4
OPY-09 5'-AGCAGCGCAC-3' 5
OPY-10 5'-CAAACGTGGG-3' 4
OPY-l3 5'-GGGTCTCGGT-3' 1
OPY-14 5'-GGTCGATCTG-3' 5
OPY-lS 5'-AGTCGCCCTT-3' 3
OPY-l6 5'-GGGCCAATGT-3' 4
OPY-17 5'-GACGTGGTGA-3' 6
OPY-l8 5'-GTGGAGTCAG-3' 2
OPY-19 5'-TGAGGGTCCC-3' 5
OPY-20 5'-AGCCGTGGAA-3' 5
OPX-Ol 5'-CTGGGCACGA-3' 1 1
OPX-06 5'-ACGCCAGAGG-3' 4
OPX-13 5'-ACGGGAGCAA-3' 3

Total 229

 

66

Table 2.2. The sequences, annealing temperatures and sources for both ryegrass

genomic- and tall fescue EST-SSR primer pairs.

 

No. ' Locus Source or Forward primer Reverse primer Tmb
Sequence ID sequence sequence (°C)
1. PR14 Kubik et al. 2001 agg gtt cgt ctg cat tc agc aga acc gag 47
ccg tc
2. PRG Kubik et a1. 2001 gcc gag tgt cat caa cct ttt cgc ctt cgt a 42
ggt
3. LP8 Kubik et al. 2001 tga ctt ctc tcg atc ct atg tga cta caa aac 40
ca
4. M4 213 Kubik et al. 2001 cac ctc ccg ctg cat tac aac gac atg tca 45
88° atgt 388
5. H01E10 Jones et al. 2001 cgc agc tta att tag to get ttg agt atg taa 40
agt t
6. H02C11; Jones et al. 2001 tgg aat aac gat gaa cat cac gaa tta aca 40
aag aga g
7. K01A03 Jones et al. 2001 gga cga act gcc gag cgg gca tgg tga 52
aca gaa gga
8. H01H06 Jones et al. 2001 att gac tgg ctt ccg tgt cgc gat tgc aga ttc 47
t ttg
9. NFFA001 FA42E11LF087 ctg ctg ctg cca aga taa ggg gag cga 60
aag t gct aca ga
10. NFFA013 FA10F10LF090 tca ttg tgt tcg ctc tcc cct tcg tcg cca tgg 62
tg tag
1 1. NFFA015 FA03G10RT072 gcg tcc act aac aac agc aag gcc agc 60
acc aa aaa aat ta
12. NFFA019 FA01E03 ST023 tgg att tgc aat tag cct gct cgt gta tgg cct 60
ca tea at
13. NFFA021 FA29F08DSO75 cac agc tcg tat agg ctt gtc gaa gag 62
cgt ca cgg gaa c
14. NFFA022 FAOZBO4RT032 atg atg tcc gag gag cat cat gat cca gtg 60
gag a cot tg
15. NFFA024 FA37F03LF031 tgc cca cga ggt cta tct age ttc ccc ttc att 60
to cca ct
16. NFFA027 FA12H05RT048 cga ggt etc at cct cca gac aga gac gac 62
tt gac gac at
17. NFFA030 FAOSDOSRT042 agt cgg tgg tga agc aca act agg ggg 62
tga ag ctg gtc a
18. NFFA031 FA46C01LF006 acg gtc tgt acc gtg gat gct gta gac tca 64
gt gcc gaa cc
19. NFFA032 FA28D02LF026 acg gtc tgt acc gtg gat get gta gac tca 64
gt gcc gaa cc

 

67

Table 2.2. The sequences, annealing temperatures and sources for both ryegrass genomic-

and tall fescue EST-SSR primer pairs (cont’d).

 

No. ' Locus Source or Forward primer Reverse primer Tmb
Sequence ID sequence sequence (°C)

20. NFFA035 FA31F07DS063 tgc tag cag ggg tct cac acg tac cac gtc 62
aag ga tcc at

21. NFFA036 FA18B10RT089 aga gga aga gcg aaa ccc tgg tac tcg tgg 60
gag ca atg tt

22. NFFA038 FAZZBO4RT041 gtg gtg gtg gtg tgt tgt gca gat tta cca gcc 62
tg aag ga

23. NFFA039 FA51A08LF065 gtc tgc acc cct etc etc etc ctt atc ttg gcg 64
to atg ga

24. NFFA042 FAZSBO6DS057 ctg tcg tgg acg agg cac gat acc cag ttc 60
aga a aag ca

25. NFFA043 FA08D07RT060 tcc agg ttc cac tcc cac agc cga aac cag att 60
t gga c

26. NFFA045 FA55E03D8023 acg agg gaa agg tag gat gaa gcc aat ttc 60
88t it C“ 88

27. NFFA048 FAOSEI 1LF087 cag gct gtt aac ggt gtc cct tct tct tgg gag 60
ct gga aa

28. NFFA051 FA39D12LF102 ttt gca ctc tcg gac cta cgg tac acc ttc tgc 62
go acc tt

29. NFFA056 FA20E05D8039 gca cga ggc tct ttc ctc ggt gct tgg cct tct 62
ta too

30. NF FA061 FA16B03DS029 tgg att tgc aat tag cct get cgt gta tgg cct 60
ca tea at

31. NFFA064 FA11E11DS087 tca ttt gac gcc act tga gtc tta gcg cct tcc 60
ac ttg gt

32. NFFA065 FA34A01RT005 gga tgg atc ctc aca ctc ctc ctc tcc tcc 64
atg ct agc tc

33. NFFA069 FA32F09LF079 ccc aag aag aag acg acg acc gaa tgg aca 62
acc a gag ac

34. NFFA071 FA29A02RT017 tcc taa gca gag ctc gat gag gtt ggc gaa ctt 62
cc cct c

35. NFFA075 FA34E06DS049 ctc tgc cct tcc ttc ctc atg gtc tcc ctc tgc 60
tt tcg ta

 

a Loci numbered 1-8 were from Lp genomic SSR (1-4 from Kubik et al. 2001 and 5-8

from Jones et al. 2001). Loci numbered 9-35 were from fall fescue EST-SSR (Saha et al.

2004)

b Annealing temperature.

68

Table 2.3. Linkage location of the EST-SSR markers on ryegrass linkage groups.

 

 

Locus Linkage location '
NFAOIS A6, B6
NFA019 A7, B7
NFA021 A2, A7, B7
NFA024 B7
NFA027 A5, BS
NFAO3O BZ

NF A03 1 Al , B l
NFAO36 A6, B6
NFAO39 A2, B2
NFAO45 A4, B4
NFAO48 A6, B6
NFAO61 B7
NFAO64 A5
NFAO69 A7, B7
NFA075 Al , Bl

 

3 Refer to Warnke et al. 2004.

69

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70

Table 2.5. The Fm/Lp genome speciﬁc band ratios of the Fm-Lp complexes based on

SSR and RAPD marker screening.

 

Genotype '

le x Lp2
Lp2 x Fm2
D1
G6
G8
G11a
G11b
G14
G15
G16
G24
026
G27a
GZ7b
6302:

GB Ob

 

SSR RAPD
Lp-specific Fm-specific Fm/Lp genome Lp-specific Fm-speciﬁc Fm/Lp
bands bands speciﬁc band bands bands genome
(N=Sl)(%) (N=51)(%) ratios " (N=87)(%) (N=96)(%) specific band
ratios
22 (43.1) 43 (84.3) 1.95 44 (50.6) 87 (90.6) 1.79
22 (43.1) 24 (47.1) 1.09 36 (41.4) 35 (36.5) 0.88
24 (47.1) 33 (64.7) 1.38 36 (41.4) 68 (70.8) 1.71
29 (56.9) 16 (31.4) 0.55 45 (51.7) 62 (64.6) 1.25
11 (21.6) 12 (23.5) 1.09 19 (21.8) 16 (16.7) 0.76
36 (70.6) 5 (9.8) 0.14 54 (62.1) 5 (5.2) 0.08
25 (49.0) 20 (39.2) 0.80 41 (47.1) 40 (41.7) 0.88
32 (62.8) 3 (5.9) 0.09 45 (51.7) 7 (7.3) 0.14
19 (37.3) 22 (43.1) 1.16 36 (41.4) 44 (45.8) 1.11
31 (60.8) 22 (43.1) 0.71 51 (58.6) 37 (38.5) 0.66
27 (52.9) 29 (56.9) 1.07 35 (40.2) 45 (46.9) 1.17
27 (52.9) 16 (31.4) 0.59 52 (59.8) 56 (58.3) 0.98
30 (58.8) 14 (27.5) 0.47 44 (50.6) 59 (61.5) 1.22
22 (43.1) 24 (47.1) 1.09 32 (36.8) 40 (41.7) 1.13
27 (52.9) 25 (49.0) 0.93 32 (36.8) 48 (50.0) 1.36
26 (51.0) 20 (39.2) 0.77 48 (55.2) 53 (55.2) 1.00

 

’ Fm, (F estuca mairei); Lpl, (Lolium perenne, Citation II); Lp2 (Lolium perenne,
Calypso); D1, amphidiploid; G6 ~ G30b, backcross lines.
" Fm/Lp genome speciﬁc band ratios = percentage of Fm-speciﬁc bands/ percentage of
Lp-speciﬁc bands.

71

M NFFAOI NFFAIS NFFAI7 NFFA24 NFFA23 NFFA34 NFFA36 NFFA4I NFFASO
"w , m , a - . -_

r

     

1;;

Figure 2.1.3. The image of SSR primer screening with ethidium bromide staining. M is a
1000bp ladder. Size standards are labeled on the left-side of the panel. Every two lanes
are a proﬁle of one primer pair screened against Fm (F estuca mairei) and Lp (Lolium

perenne). Primer names are on the top of the panel.

72

 

Figure 2.1 .b. The image of SSR primer screening with silver staining. M ile bp ladder.
Size standards are labeled on the left-side of the panel. Every four lanes are a proﬁle of
one primer pair screened against Fm (Festuca mairei), Lpl (Lolium perenne, Citation II),
Lp2 (Lolium perenne, Calypso) and F. (le x Lp2). Primer names are at the top of the

panel.

73

OPX01 OPY02 OPCOB OPC1 1

     

le Lp2 LplFl leLp2 Lpl F1 le Lp2 Lpl F1 Fminz Lpl F1 M

Figure 2.1.c. Agarose gel image of RAPD primer screening. M isIOOO bp ladder. Size
standards are labeled on the right-side of the panel. Every four lanes are a profile of one
primer screened against Fm (F estuca mairei), Lpl (Lolium perenne, Citation II), Lp2

(Lolium perenne, Calypso) and F1 (le x Lp2). Primer names are at the top of the panel.

74

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Figure 2.3. The 3-dimensional scatterplot of principle component analysis based on the
merged SSR and RAPD data. The four groups were deﬁned following the cluster
analysis. C1, C2, and C3 are axes of the three principle components, which explained 76
% of the total variation. Accessions include le (Festuca mairei), Lpl (Lolium perenne,
Citation II), Lp2 (Lolium perenne, Calypso), D1 (amphidiploid), G6 - G30b (backcross

progeny).

76

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Wamke S.E., Barker R.E., Jung G., Sim S.C., Mian M.A.R., Saha M.C., Brilman L.A.,

Dupal M.P., Forster J .W. 2004. Genetic linkage mapping of an annual x perennial
ryegrass population. Theor. Appl. Genet. 109: 294-304.

78

CHAPTER III

Detection of An Efficient Restriction Enzyme Combination and
Evaluation of the Experimental Conditions for cDNA-AFLP

Analysis in F estuca mairei

(Published in M01. Biotech. (2005) 29:211-220)

ABSTRACT

In cDNA-ampliﬁed fragment length polymorphism (cDNA-AF LP) analysis, it is
critical to choose a suitable pair of restriction enzymes for tagging sites in cDNA for
ampliﬁcation. The experimental conditions might affect the efﬁciency of cDNA-AF LP
technique in detecting transcript derived fragments (TDF). Possibility of production of
chimeric fragments ﬁ'om cDNA-AFLP analysis remains to be researched. The objectives
of this study were to (I) detect an efﬁcient restriction enzyme combination for cDNA-
AF LP analysis when F estuca species was used as template; (2) evaluate the effect of the
experimental conditions on the efﬁciency of discovering TDF; and (3) evaluate the
identity of transcript-derived ﬁagments (TDFs) from cDNA-AFLP analysis. We found
that NspI coupled with Taql was a pair of highly efﬁcient enzymes by generating a much
higher number of TDFs than the commonly used EcoRI and Taql. This was the ﬁrst

study to apply NspI for AF LP analysis, suggesting that this enzyme may have valuable

79

application potential for other species. The number of repeatable bands was not
signiﬁcantly affected by magnesium concentration and dilution of pre-ampliﬁcation
products, suggesting that the cDNA-AFLP analysis was relatively insensitive to
ampliﬁcation conditions and had high reproducibility across treatments. The identity of
TDF was evaluated by sequencing a TDF and comparing it with the sequence of the
template cDNA. The result showed that the chimeric fragments derived from ligation
between digested fragments was generated and could not be eliminated by increasing
adapter concentration. Although the existence of chimeric fragments should be carefully
considered, the unexpected sequence in the chimeric TDF may not seriously inﬂuence the
sequencing and BLAST searching analyses. Conclusively, cDNA-AFLP is a reliable and
high throughput transcript proﬁling technique suitable to TDFs discovery in grasses such

as F. mairei.

Key words: cDNA-ampliﬁed fragment length polymorphism (cDNA-AF LP), Transcript

derived fragments (TDFs), Restriction enzyme combination, F estuca mairei.

INTRODUCTION

Transcript proﬁling is playing a substantial role in annotating and determining
gene functions, having advanced from methods of one-gene-at-a-time to technologies that
provide a holistic review of the genome (Donson, et al., 2002). A variety of high-
throughput transcript proﬁling techniques have been established, which can be

categorized into two types. First is a direct analysis including procedures involving

80

nucleotide sequencing and fragment sizing, such as cDNA-ampliﬁed restriction length
polymorphism (cDNA-AFLP), serial analysis of gene expression (SAGE), massively
parallel signature sequencing (MPSS), expressed sequence tag (EST) sequencing, and
differential display PCR (DD-PCR). Second is an indirect analysis involving nucleic
acid hybridization of mRNA or cDNA fragments, such as cDNA microarray, oligo-chips
and suppression subtractive hybridization (SSH). These techniques differ in their
expense, convenience, sensitivity, and repeatability (Kuhn, 2001).

The cDNA-AFLP analysis is an mRNA ﬁngerprinting technique showing high
reproducibility and sensitivity, good correlation with northern blot analysis and low set-
up cost, even though it requires a comprehensive reference database (Donson et al.,
2002). In contrast to the direct analysis techniques, cDNA-AF LP does not require prior
sequence information and can reveal differential expression of any gene carrying suitable
restriction sites (Bachem et al., 1996). cDNA-AF LP also overcomes the limitations of
other PCR-based techniques by using selective fragment ampliﬁcation under stringent
PCR conditions (Jones and Harrower, 1998). In cDNA-AFLP analysis, non-selective
PCR products can be eliminated by increasing the length of selective primers for
ampliﬁcation (Bachem et al., 1996). cDNA-AFLP has been successfully used to identify
differentially expressed transcript derived fragments (TDFs) from almond (Prunus
amygdalus) treated with abscisic acid (ABA) (Campalans et al., 2001); tissue-speciﬁc
TDFs during potato (Solanum tuberosum L.) tuber development (Bachem et al., 2001);
and TDFs associated with putative pathogenicity factors during infection of tubers by the

potato cyst nematode (Globodera rostochiensis) (Qin et al., 2000).

81

The cDNA-AF LP procedure involves ﬁve major steps: i) double strand (ds)
cDNA synthesis; ii) digestion of the ds cDNA with two restriction enzymes and ligation
of adapters to the termini of the digested cDNA fragments; iii) pre-ampliﬁcation of the
ligated fragments with primers corresponding to the adapters; iv) selective ampliﬁcation
of the pre-ampliﬁed fragments with selective primers; and v) visualization of the ﬁnal
ampliﬁcation products to generate the ﬁngerprint (Bachem et al., 1998). A detailed
cDNA-AF LP procedure has been reported and effects of PCR cycle number, template
dilution level, and Mg2+ concentration during ampliﬁcation on number of TDFs have
been researched in potato (Bachem et al., 1998).

Efﬁciency of cDNA-AF LP, as a PCR-based technique, in discovering TDFs
depends on the type of polymerase, base composition of template and primers,
composition of buffer and the PCR program for the reaction (Bachem et al., 1998).
Choosing a suitable pair of restriction enzymes is critical for the cDNA-AFLP technique.
Restriction enzymes are used to tag sites in cDNA molecules to generate fragments with
appropriate" sizes, and also to introduce sticky termini for ligation to adapters (Bachem et
al., 1998). To investigate the whole genome expression pattern or to discover TDFs
throughout the target genome, restriction enzymes should optimally recognize and cut
every single cDNA molecule derived ﬁ'om the target genome. Iftranscribed genes could
not be recognized by the enzyme, an opportunity to discover these genes will be missed.
Currently, EcoRI/Msel is the most widely used enzyme pair for genomic DNA AFLP,
and AseI/Tan was the ﬁrst enzyme used for cDNA AF LP. It has also been reported that
EcoRI, BamHI, and PstI in combination with Tan or MseI have equal potential for

identiﬁcation of TDFs (Bachem et al., 1998).

82

F estuca is a large diverse genus comprising of about 450 species and is widely
distributed across the cool regions of the world. It contains the most useful grass species
(Clayton and Renvoize, 1986). Festuca has good drought resistance and has desired
value for both turfgrass and forage usage (Aronson et al., 1987; Fry and Butler, 1989).
Although the cDNA-AF LP technique has been successfully used for gene discovery and
global gene expression in many species (Campalans et al., 2001; Bachem et al., 2001;
Qin et al., 2000), it has not been reported on the F estuca species. It remains to be
determined whether a speciﬁc restriction enzyme combination is needed to achieve high
efﬁciency of cDNA-AFLP for F estuca. Magnesium concentration for the PCR reaction
is a key parameter affecting the efﬁciency of the AF LP in detecting individual ﬁagments
(Bachem et al., 1998; Du-Toit et al., 1993). A magnesium concentration of 2.5 mM was
recommended to generate bands with high clarity (Bachem et al., 1998). However, our
preliminary study showed that bands generated ﬁ'om PCR at 1.5 mM Mg2+ were clearer
(visually adjusted) than at 2.5 mM. It is necessary to determine whether these two
magnesium concentrations will signiﬁcantly affect the number of reliable or repeatable
TDFs. Quantity of cDNA for cDNA-AFLP analysis is usually limited because of i)
inefﬁciency of obtaining total RNA from some speciﬁc tissues (such as wood, old leaves,
potato tubers, and anthers), ii) small mRNA proportion in total RNA (1 to 5%), and iii)
low yield of ds cDNA synthesis (around 10%). The dilution level of pre-ampliﬁcation
product can reﬂect the amount of starting template cDNA. It is applicable to determine
how dilution levels affect efﬁciency of TDFs discovery. In previous studies, the chimeric
fragments generated from the cDNA-AFLP analysis had not been adequately addressed.

The objectives of present study were to (1) select an effective restriction enzyme

83

combination to achieve high efﬁciency of cDNA-AFLP in the monocotyledon species
such as F estuca; (2) detect the effect of cDNA-AF LP conditions on TDFs discovery, and
(3) evaluate the chimeric ﬁ'agment by sequencing a TDF and comparing it with the

sequence of the template.

MATERIALS AND METHODS

Plant material and template preparation

Fresh leaf samples of the F. mairei plant were collected and immediately frozen
in liquid nitrogen. For each sample, total RNA was extracted from approximately 100
mg of leaf tissue using plant RNA puriﬁcation reagent (Invitrogen Life Technologies,
Carlsbad, CA). The total RNA quantity was measured using a spectrophotometer at a
wavelength of 260 nm. The purity of the RNA was evaluated by the ratio of absorbency
at 260 nm to 280 nm. Quality of the RNA was checked by running 2 pg of the total RNA
on 1.2% denature agarose gel with 2.5% formaldehyde in 40 mM 3-(N-morpholino)
propan sulfonic acid (MOPS) with a running buffer for 2.5 hr. The mRNA was isolated
from total RNA using PolyATract mRNA isolation systems 111 (Promega, Madison, WI).
The mRNA solution in 250 pl was concentrated to a ﬁnal volume of 10 ul using a speed
vacuum.

Double-stranded (ds) cDNA was synthesized from mRNA using the Universal
RiboClone cDNA Synthesis System (Promega). The mRNA sample of a kanamycin

resistant gene (Promega) was used as a control for ds cDNA synthesis (sequence in

84

Figure 3.1 A). Synthesized ds cDNA was extracted with an equal volume of TE-
saturated phenol: chloroform: isoamyl alcohol (25:24: 1). The quantity of ds cDNA was

measured using Hoechst 33258 (bisbenzimide) dye, on a DyNA quant 200 ﬂuorometer.

Digestion and ligation

Thirty nanograms of cDNA was digested with 5 U EcoRI or NspI (rare cutters)
(as comparison) at 37°C for 2.5 hr, and then immediately digested with 5 U of Taql
(frequent cutter) at 65°C for 2.5 hr, followed by heat inactivation at 80°C for 20 min.
The digestions were conducted in NEbuffer 2 (New England Biolabs, Beverly, MA) with
a total volume of 30 ul.

Adapters were prepared by annealing two linkers (see Table 3.1 for sequences) on
peltier thermal cycler (PTC-225) (MJ Research, Waltham, MA) using the following
program proﬁles: 70°C, 10 min; 70°C (-l°C/cycle), 30 5 (+2 5 /cyc1e) for 45 cycles. A11
oligo-nucleotides used in this study were synthesized by MWG Biotech, Inc. (Charlotte,
NC) (see Table 3.1 for sequences). The digestion mix (20 ul) was ligated with 0.5 mM
adapter for rare cutter and 2.5 mM adapter for ﬁ'equent cutter, using 1 U of T4 ligase
supplemented with T4 DNA ligase buffer (Promega) in a total volume of 30 al. The

ligation mix was incubated at room temperature for 12 hr.

Pre-ampliﬁcation and selective ampliﬁcation

Reaction solution (20 111) for pre-ampliﬁcation contained 1 ul ligation mix, 0.5

uM of each primer, 0.3 mM dNTP mix, and 0.5 U Taq polymerase supplemented with 1x

85

Taq polymerase buffer (Promega). For optimization, two levels of Mg2+ concentration,
1.5 mM or 2.5 mM, were used. The PCR reaction was conducted on the PTC-225 using
the proﬁle: 72°C, 2 min; 94°C, 1 min; 15 cycles of 94°C, 30 s; 56°C, 30 s; and 72°C, 1
min; then followed by 10 min at 72°C for a ﬁnal extension. Product was diluted to 2x, 5x,
and 10x for optirrrization. The PCR mixture for selective ampliﬁcation included 1 pl of
5x diluted pre-ampliﬁcation product, 0.4 pM of each selective primer (Table 3.1), 0.3
mM dNT P mix, and 0.4 U Taq polymerase supplemented with 1x Taq polymerase buffer
to total 15 p1 reaction volume. The selective ampliﬁcation was performed using the
program: 10 cycles: 94°C, 30 s; 65°C (- 0.7°C /cycle), 30 s; 72°C, 1 min and 25 cycles:
94°C, 30 s; 56°C, 30 s; 72°C, 1 min; followed by a ﬁnal extension step of 10 min at

72°C.

AFLP proﬁling

The selective ampliﬁcation product (15 p1) was denatured at 96°C for 6 min after
adding 9 p1 loading buffer (98% formamide). Six microliters of the sample were
fractionated on a 5% polyacrylamide sequencing gel with 45.4% urea at 90 W for 2.5 hr
and the gel was stained using the Silver Sequence DNA staining reagents (Promega).

The gel was allowed to dry overnight at room temperature for scoring on a light box.

Fragment isolation, cloning and sequencing

The band of interest was excised from the polyacrylamide gel with a sterile

surgical blade. DNA was eluted by soaking the excised gel in 50 pl water 12 hr. The

86

DNA fragment was re-ampliﬁed using the same condition used for selective
ampliﬁcation and was run on 1% agarose gel for separation from possible DNA
contamination. The re-ampliﬁed DNA fragment with a target size was excised and
puriﬁed from the gel with QIAquick gel extraction kit (QIAGEN Inc., Valencia, CA).
The puriﬁed DNA ﬁagment was cloned into the pGEM-T easy vector (Promega)
and transformed into E. coli by electroporation using electroporator II (Invitrogen Life
Technologies, Carlsbad, CA). Plasmid DNA was extracted using the Wizard plus SV
minipreps DNA puriﬁcation system (Promega). Puriﬁed plasmid DNA with the desired
insert was sequenced on an ABI PRISM 3100 genetic analyzer (Applied Biosystems,

Foster City, CA).

Sequence search and restriction map analysis

To choose an enzyme combination that would have at least one recognition site in
each cDNA molecule, the information of F estuca cDNA sequences was obtained from
the National Center for Biotechnology Information (N CBI ) website
(http://www.ncbi.nlm.nih.gov/entrez/query.fcgi). The restriction maps of the cDNA
sequences were analyzed using the restriction analysis program from the website
(http://www.arabidopsis.org/cgi-bin/patmatch/RestrictionMapper.pl). Recognition sites
of eight restriction enzymes including six rare cutters (ApoI, AseI, BamHI, EcoRI, NspI,
and PstI) with a recognition site of 6 bases, and two frequent cutters (MseI and Taql)

with a 4-base recognition site were surveyed on the restriction maps of cDNA sequences.

87

Experimental design and data analysis

Under direction of the information from the website, the efﬁciency of the selected
enzyme combination (N spI/Tan) in detecting TDFs was compared with a commonly
applied and acknowledged enzyme pair (EcoRI/Taql) (Qin et al.; 2000, Bachem et al.,
1998; Qin et al., 2001). The efﬁciency of the cDNA-AFLP in detecting TDFs using the
enzyme combination was determined by the number of TDFs generated from all of the
possible primer pairs designed for an enzyme combination. For EcoRI/Tan, the possible
selective primer pairs were 256 (16x16), while for NspI/Tan, there were 128 (8x16)
selective primer combinations. In the cDNA-AF LP procedure, 128 selective primer
combinations for NspI/Taql and 136 randomly chosen selective primer combinations for
EcoRI/Taql were screened using Festuca mairei cDNA as a template. The number of
scorable (clearly visualized by the naked eye) bands in the AF LP proﬁles was recorded.

For detecting the effect of cDNA-AFLP conditions on TDFs discovery, 3 split
plot design having two factors with four replications was used. Factor 1 was Mg2+
concentration at two levels: 1.5 mM and 2.5 mM. Factor 2 was dilution of pre-
ampliﬁcation product at three levels: 2x, 5x, and 10x. Three dilution levels represented
approximately 500 pg, 200 pg, and 100 pg of starting cDNA respectively. After pre-
ampliﬁcation, each of four replications at two levels of factor 1 was divided into three
aliquots, which were then diluted 2x, 5x, and 10x respectively. Selective ampliﬁcation
was then conducted at a Mg2+ concentration consistent with the level in pre-
ampliﬁcation. Four randomly chosen selective primer combinations (N 7/T 7, N4/T 14,
N3/T11, and N7/T 4) were used to perform the selective ampliﬁcation (Table 3.1).

Number of repeatable bands in the AF LP proﬁle was counted if two bands with same size

88

in two adjacent lanes of replications were clearly visualized. ANOVA analysis was
conducted using PROC MIXED function in SAS system V8 (SAS Institute, 2002, Cary,
NC).

To evaluate the identity of ampliﬁed TDFs, a cDNA sample from a kanamycin
resistance gene (Promega) was used as a template and subjected to four randomly picked
selective primer combinations (N7/T 7, N4/T 14, N3/T1 l, and N7/T 4) in the AFLP
process. The number of scorable bands in the AFLP proﬁles was counted. The template
cDNA sequence has ﬁve restriction sites for Taql, and has no restriction sites for NspI
(Figure 3.1.A). The resulted ﬁagrnents ﬁ'om the digestion of Taql (and NspI) are 92 bp,

274 bp, 403 bp, and 93 bp (Figure 3.1.8).

RESULTS AND DISCUSSION

Selection of the optimal restriction enzymes

From NCBI website, 18 complete cDNA sequences of the F estuca species were
available and obtained (Table 3.2). Restriction mapping analyses of these 18 sequences
were conducted using 8 restriction enzymes. Results showed that of the six rare cutters
(Apol, AseI, BamHI, EcoRI, NspI, and PstI), NspI could recognize 94.4% of the cDNA
sequences of the F estuca species (Table 3.2). Of the two ﬁ'equent cutters (Msel and
Taql), Taql could cut all of the cDNA sequences of the Festuca species (Table 3.2).
Therefore, NspI and Taql were initially chosen as the enzyme combination for the

cDNA-AFLP analysis in the Festuca species.

89

The efﬁciency of NspI/Tan in detecting TDFs was compared with a pair of
commonly applied and acknowledged enzymes, EcoRI/Taql. All of the 128 primer pairs
for NspI/Tan were screened, and in total 11,364 scorable bands (TDFs) ranging from
50bp to 1000bp were generated. Most of the bands (48.26%) had a size of 100-200bp
(Table 3.3). In contrast, 136 out of 256 primer pairs for EcoRI/Tan enzyme combination
were randomly screened and in total generated 532 scorable bands. Only 17 (12.5%) of
the 256 primer pairs generated more than 10 bands (Figure 3.2). This result demonstrated
that the NspI/Taql enzyme combination was more efﬁcient than EcoRI/Tan to discover
the TDFs in the F estuca species.

The linkers and primers for the NspI enzyme were designed in this study based on
the same principle applied in designing other enzymes (Table 3.1), since this enzyme has
never been used before in AF LP analysis. Clear and abundant bands were generated
from these primers, indicating the designing of the linkers and primers was successful.
Application value of NspI was also conﬁrmed when comparing with EcoRI (Table 3.3,
Figure 3.2). NspI was not reported to be used for AF LP analysis before, and thus was not
compared with other enzymes. This study prompts the potential value of NspI/Taql used
for cDNA-AFLP procedure across species. Or at least, NspI/Taql could be put into
consideration when selecting restriction enzyme for cDNA-AFLP analysis.

Because EcoRI recognizes 5’ GAAAT'I‘ C 3’, whereas NspI recognizes 5’Pu
CATGAPy 3’ (Pu=A or G and Py = T or C), our study suggested that most of the cDNAs
from F. mairei do not have AATT but do have CATG sequences. Two possible
explanations are that (1) AATT is mostly present in uncoding regions of genomic DNA,

while the template molecules are transcripts ﬁom coding regions in the cDNA-AF LP

90

procedure, and (2) the restriction site of NspI is not unique. To test the ﬁrst hypothesis,
both the genomic DNA and cDNA from F. mairei were subjected to AF LP analysis using
the two enzyme combinations, NspI/Tan verses EcoRI/Tan. Results showed that when
the NspI/Taql enzyme combination was applied, more bands were generated with either
genomic DNA or cDNA template. This result implied that when compared to EcoRI,
NspI was an efﬁcient enzyme irrespective of genomic DNA or cDNA molecule due to its
non-unique-restriction-site property. In general, restriction enzyme selection is critical
for high efﬁciency of cDNA-AF LP technique, even though it has been reported that other
enzyme combinations had similar potential for identiﬁcation of TDFs (Bachem et al.,

1998).

Effects of magnesium concentration and pre-ampliﬁcation dilution on number of

TDFs in AFLP proﬁles

The number of repeatable bands in AF LP proﬁles generated from four randomly
selected primer-combinations was evaluated to determine the effects of Mg2+
concentration and pre-ampliﬁcation product dilution on the TDFs in AFLP proﬁle. The
ANOVA showed that differences in the number of repeatable bands at two levels of Mgz+
concentration were not statistically signiﬁcant (P=0.22), although the mean value of
94.86 at 1.5 mM Mg2+ was greater than 84.89 at 2.5 mM Mg2+ (Table 3.4). Dilutions of
the pre-ampliﬁcation product did not signiﬁcantly affect the number of repeatable bands
in AFLP proﬁles (Table 3.4, Figure 3.3). Interaction between Mg2+ concentration and
primer combination was not signiﬁcant. The results indicated that neither of the two

Mg“ concentrations nor three dilutions signiﬁcantly affected the number of repeatable

91

bands generated from cDNA-AF LP, which suggested that the cDNA-AF LP analysis was
relatively insensitive to ampliﬁcation conditions used and thus high reproducibility across
treatments can be obtained. The statistic analysis in this study supports the experimental
conditions optimized in potato (Solanum tuberosum) (Bachem et al., 1998).

In general, the number and pattern of AF LP bands were not signiﬁcantly affected
by Mg2+ concentrations and dilutions of the pre-ampliﬁcation implying that the technique
is relatively independent on the experimental conditions. A dilution level corresponding
to 100 pg of starting cDNA material generated the same amount of information as the
dilution level corresponding to 200 pg and 500 pg of starting cDNA material (Table 3.4).
This result indicated that the real amount of cDNA required for AF LPs could be at least
as low as 100 pg for around 25 selective ampliﬁcations, implying the high sensitivity of
this technique in discovery of TDFs. This result also proved that cDNA- AF LP was an
applicable technique when the starting material is limited. A higher DNA input
concentration would lead to a background smear and the adverse effects on ampliﬁcation
of some individual TDFs likely due to competitive inhibition between fragments during

the PCR (Bachem et al., 1998).

Evaluation of chimeric TDF identity

A cDNA sample from a kanamycin resistance gene had been subjected to
standard AFLP procedure with four randomly picked selective primer pairs: NWT 7,
N4/T l4, N3/T l l, and N7/T 4 (see Table 3.1 for sequences). Numbers of resultingbands
from each primer pair were 32, 35, 20 and 6. In addition to the four expected bands, 92

bp, 93 bp, 274 bp and 403 bp plus the primer sequence (Figure 3.1 B), many bands of

92

unexpected size were produced. To investigate the origin of these unexpected hands, a
fragment of 710 bp was randomly selected for sequencing. Pair-wise BLAST analysis
between the sequenced fragment and the original sequence of the template molecule was
performed. Results showed that the 710 bp fragment contained a 403 bp and a 274 bp
fragment, which were 99% and 98% identical to the original template sequences
respectively. The 274 bp fragment was reversely joined with the 403 bp ﬁagment
(Figure 3.1 B and Figure 3.4). This result indicated that the 710 bp fragment was
ampliﬁed ﬁ'om a reversely ligated chimeric fragment between two digested template
fragments (a 403 bp and a 274 bp fragment) plus the two adapters at the end.
To investigate whether the chimeric bands derived ﬁom ligation between digested
fragments could be prevented or at least minimized by increasing the adapter
concentration in ligation reaction, ligations were conducted by adding ﬁve different
amounts of adapter mixture (7 pM Taql adapter) to each 20 pl of digestion solution: 10
pl, 15 pl, 20 pl, 25 pl, and 30 pl. The ﬁnal molecular ratios of the template cDNA to the
adapter in the ligations were 1:1842, 1:2763, 1:3684, 1:4605, and 1:5526 respectively.
The ﬁve ligations at different adapter concentrations were replicated twice and subjected
to four randomly picked selective primer combinations (N 7/T 7, N4/T14, N3/T l l, and
NWT 4) in the AF LP process. The number of bands was compared. Results showed that
there was no signiﬁcant difference among the number of bands generated from the ﬁve
different adapter concentrations. The chimeric bands were not minimized by increasing
the adapter concentration.

The existence of chimeric fragments should be carefully considered when a

mixture of thousands of TDF is identiﬁed from the proﬁle. A set of more speciﬁc

93

experiments could be planned to address the possibility of elimination or minimization of
the accidental production of chimeric fragments from the established cDNA-AF LP
protocol. Fortunately, the density and size of the band derived from ligation of the two
fragments was highly reproducible in independent experiments (Figure 3.5). The high
reproducibility of these fragments suggested that they did not severely affect the
discovery of TDFs, but the number of TDFs derived from the same transcript was
increased (Figure 3.5). When obtaining the sequence of TDF and using BLAST search to
ﬁnd the potential function of the TDF, the unexpected sequence in the chimeric TDF can
be viewed as an uninforrnative tail that may not severely inﬂuence the sequencing and
BLAST searching analysis.

In summery, NspI/Tan is a high efﬁcient enzyme combination in the AF LP
analysis. It has less primer combinations, and might have valuable application potential in
other species. cDNA-AFLP is relatively insensitive to the experimental conditions by
showing consistent band number, density, and pattern in independent and variable
conditioning experiments. Even though some chimeric fragments could be produced
using the cDNA-AFLP procedure, similar to many other techniques, the discovery of
TDFs will not be badly affected with the awareness of the possibility of chimeric
fragment existence. In conclusion, cDNA-AFLP is a reliable and high throughput

transcript proﬁling technique suitable to TDFs discovery in grasses such as F. mairei.

94

Table 3.1. Sequences of the primers and linkers used for AF LP analysis.

 

Primers and linkers

Initial Sequences (5’-3’)

 

EcoRI linker l

13le linker 2

EcoRl pre-ampliﬁcation primer

EcoRI selective ampliﬁcation primer 1
EcoRI selective ampliﬁcation primer 2
EcoRI selective ampliﬁcation primer 3
EcoRI selective ampliﬁcation primer 4
EcoRI selective ampliﬁcation primer 5
EcoRI selective ampliﬁcation primer 6
EcoRI selective ampliﬁcation primer 7
EcoRI selective ampliﬁcation primer 8
EcoRI selective ampliﬁcation primer 9
EcoRI selective ampliﬁcation primer 10
EcoRI selective ampliﬁcation primer ll
EcoRI selective ampliﬁcation primer 12
EcoRI selective ampliﬁcation primer l3
EcoRI selective ampliﬁcation primer 14
EcoRI selective ampliﬁcation primer 15
EcoRI selective ampliﬁcation primer 16
Nspl linker 1

Nspl linker 2

Nspl pre-ampliﬁcation primer

Nspl selective ampliﬁcation primer 1
Nspl selective ampliﬁcation primer 2
Nspl selective ampliﬁcation primer 3
Nspl selective ampliﬁcation primer 4
Nspl selective ampliﬁcation primer 5
Nspl selective ampliﬁcation primer 6
Nspl selective ampliﬁcation primer 7
Nspl selective ampliﬁcation primer 8
Taql linker 1

Taql linker 2

Taql pre-ampliﬁcation primer

Taql selective ampliﬁcation primer 1
Taql selective ampliﬁcation primer 2
Taql selective ampliﬁcation primer 3
Taql selective ampliﬁcation primer 4
Taql selective ampliﬁcation primer 5
Taql selective ampliﬁcation primer 6
Taql selective ampliﬁcation primer 7
Taql selective ampliﬁcation primer 8

E1
E2
E3
E4
E5
E6
E7
E8
E9
E10
E11
E12
E13
E14
E15
E16

N 1
N2
N3
N4
N5
N6
N7
N8

T1
T2
T3
T4
T5
T6
T7
T8

95

CTCGTAGACTGCGTACC
AATTGGTACGCAGTCTAC
GACTGCGTACCAATTC
GACTGCGTACCAATTCAA
GACTGCGTACCAATTCAT
GACTGCGTACCAATTCAC
GACTGCGTACCAATTCAG
GACTGCGTACCAATTCTA
GACTGCGTACCAATTCTT
GACTGCGTACCAATTCTC
GACTGCGTACCAATTCTG
GACTGCGTACCAATTCCA
GACTGCGTACCAATTCCT
GACTGCGTACCAATTCGC
GACTGCGTACCAATTCCG
GACTGCGTACCAATTCGA
GACTGCGTACCAATTCGT
GACTGCGTACCAATTCGC
GACTGCGTACCAATTCGG
GTAGACTGCGTTCCCATG
GGAACGCAGTCTACGAG
GTAGACTGCGTTCCCATG
GTAGACTGCGTTCCCATGTA
GTAGACTGCGTTCCCATG”
GTAGACTGCGTTCCCATGTC
GTAGACTGCGTTCCCATGTG
GTAGACTGCGTTCCCATGCA
GTAGACTGCGTTCCCATGCT
GTAGACTGCGTTCCCATGCC
GTAGACTGCGTTCCCATGCG
AAGTCCTGAGTAGCAC
CGTTCAGGACTCATC
CACGATGAGTCCTGAACG
CACGATGAGTCCTGAACGAAA
CACGATGAGTCCTGAACGAAT
CACGATGAGTCCTGAACGAAC
CACGATGAGTCCTGAACGAAG
CACGATGAGTCCTGAACGATA
CACGATGAGTCCTGAACGATT
CACGATGAGTCCTGAACGATC
CACGATGAGTCCTGAACGATG

Table 3.1. Sequences of the primers and linkers used for AFLP analysis (cont’d).

 

 

Primers and linkers Initial Sequences (5’-3’)

Taql selective ampliﬁcation primer 9 T9 CACGATGAGTCCTGAACGACA
Taql selective ampliﬁcation primer 10 T10 CACGATGAGTCCTGAACGACT
Taql selective ampliﬁcation primer 11 T11 CACGATGAGTCCTGAACGACC
Taql selective ampliﬁcation primer 12 T12 CACGATGAGTCCTGAACGACG
Taql selective ampliﬁcation primer 13 T13 CACGATGAGTCCTGAACGAGA
Tan selective ampliﬁcation primer14 T14 CACGATGAGTCCTGAACGAGT
Taql selective ampliﬁcation primer 15 T15 CACGATGAGTCCTGAACGAGC
Taql selective ampliﬁcation primer 16 T16 CACGATGAGTCCTGAACGAGG

 

96

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97

Table 3.3. The size distribution of the bands generated from AFLP analysis with

EcoRI/Taql and Nspl/Taql restriction enzyme system, respectively.

 

 

Size range of the band EcoRI/Taql (%) Nspl/Taql (%)
700-1000bp 24 (4.51) 103 (0.91)
600-700bp 9 (1.69) 131 (1.15)
500-600bp 24 (4.51) 337 (2.97)
400-500bp 15 (2.82) 565 (4.97)
300-400bp 49 (9.21) 1,140 (10.03)
200-300bp 67 (12.59) 2,480 (21.82)
100-200bp 197 (37.03) 5,484 (48.26)

50—100bp 147 (27.63) 1,124 (9.89)
Total 532 (100.00) 11,364 (100.00)

 

98

Table 3.4. ANOVA of the number of repeatable bands generated from F. mairei cDNA-

AF LP proﬁle at two magnesium concentrations and 3 dilutions.

 

 

Effect Magnesium Dilution Estimated Standard Pr > F
Ismean error

Magnesium 1.5 mM 94.8611 10.9463 0.2212 ns
Magnesium 2.5 mM 84.8889

Dilution 2x 91.7917 10.5813 0.4900 ns
Dilution 5x 89.2083

Dilution 10x 88.6250

Magnesium"Dilution 1.5 mM 2x 96.7500 11.1834 0.6915 ns
Magnuesium’Dilution 1.5 mM 5x 95.4167

Magnesium‘Dilution 1.5 mM 10x 92.4167

Magnesium*Dilution 2.5 mM 2x 86.8333

Magnesium‘Dilution 2.5 mM 5x 83.0000

Magnesium*Dilution 2.5 mM 10x 84.8333

 

ns: not signiﬁcant.

99

Table 3.5. ANOVA of the number of bands generated from kanamycin cDNA-AF LP

proﬁle at ﬁve different adapter concentrations.

 

 

Adapter concentrations“ Estimated means Standard error Pr > F

1 22.6250 7.1675 0.4632ns*
2 23.6250

3 22.5000

4 23.0000

5 19.5000

 

*: l to 5 indicates 5 different volumes of adapter mixture added to each 20ul of digestion
solution: lOul, 15ul, 20ul, 25ul and 30ul.

ns, not signiﬁcant.

100

A

1 GMTACAAGC TTGGGCGTGT CTCAAAATCT CTGATGTTAC ATTGCACAAG
51 ATAAAAATAT ATCATCATGA ACMTAAAAC TGTC'I’GCTTA CATAAACAGT

101 AATACAAGGG GTGTTATGAG CCATATTCAA CGGGAAACGT CTI'GCTCG AG
151 GCCGCGATTA AATTCCAACA TGGATGCTGA TITATATGGG TATAAATGGG

201 CTCGCGATAA TGTCGGGCAA TCAGGTGCGA CAATCTATCG ATTGTATGGG
251 AAGCCCGATG CGCCAGAGTT GTTTCTGAAA CATGGCAAAG GTAGCGTTGC
301 CAATGATGTT ACAGATGAGA TGGTCAGACT AAACTGGCTG ACGGAATTTA
351 TGCCTCTTCC GACCATCAAG CAT'HTATCC GTACTCCTGA TGATGCATGG
401 TTACTCACCA CTGCGATCCC CGGGAAAACA GCATTCCAGG TATTAGAAGA
451 ATATCCT GAG TCAGGTGAAA ATATTGTTGA TGCGCTGGCA GTGTTCCTGC

501 GCCGGTTGCA TTCG ATTCCT GTTTGTAATT GTCCTTTTAA CAGCGATCGC
551 GTATTTCGTC TCGCTCAGGC GCAATCACGA ATGAATAACG GTTTGGTTGA
601 TGCGAGTGAT TTTGATGACG AGCGTAATGG CTGGCCTGTT GAACAAGTCT
651 GGAAAGAAAT GCATAAGCTT 'I'TGCCATTCT CACCGGATTC AGTCGTCACT
701 CATGGTGATT TCTCACTTGA TAACCTTATT TTI'GACGAGG GGAAATTAAT
751 AGGTTGTATT GATGTTGGAC GAGTCGGAAT CGCAGACCGA TACCAGGATC
801 TTGCCATCCT ATGGAACTGC CTCGGTGAGT TTTCTCCTTC ATTACAGAAA
851 CGGCTT'ITTC AAAAATATGG TATTGATAAT CCTGATATGA ATAAATTGCA

901 GTTTCATTI'G ATGCTCG ATG AGTTTTTCTA ATCAGAATTG GTTAATTGGT
951 TGTAACACTG GCAGAGCATT ACGCTGACTI’ GACGGGACGG CGGCTTTGTT

1001 GAATAAATCG AACTTTTGCT GAGTTGAAGG ATCAGATCAC GCATCTTCCC
1051 GACAACGCAG ACCGTTCCGT GGCAAAGCAA AAGTTCAAAA TCACCAACTG
1101 GTCCACCTAC AACAAAGCTC TCATCAACCG TGGCGACTCT AGAGGATCCC
1151 CGGGCGAGCT CCCAAAAAAA AAAAAAAAAA MAMMAAA MACCGAATT

Figure 3.1. The restriction diagram of the cDNA of the kanamycin resistant gene with

Taql enzyme. A. Single strand cDNA sequence. The arrows point to the restriction sites

of Taql. B. Fragments with double sticky ends restricted by Taql.

101

 

 

 

 

 

 

 

 

 

 

 

147 148 149 150 151 236 237 238
C G A G C ............ 92bpfragment ......... T A T

T C G A T A G C
239 240 241 242 243 510 511 512
C G A T T ........... 274bp fragment .......... A T T

T A A T A A G C
513 514 515 516 517 913 914 915
C G A T T ............ 403bpfragment ........ G C T

T A A C G A G C
916 917 918 919 920 1006 1007 1008
C G A T G ............ 93bp fragment ......... A A T

T A C T T A G C

 

 

 

Figure 3.1. The restriction diagram of the cDNA of the kanamycin resistant gene with

Taql enzyme. A. Single strand cDNA sequence. The arrows point to the restriction sites

of Taql. B. Fragments with double sticky ends restricted by Taql (cont’d).

102

 

Figure 3.2. The cDNA-AFLP banding pattern generated from the EcoRI/I‘aql enzyme

combination (A) and the Nspl/Taql enzyme combination (B).

103

 

, I '1i5mM nagaessam'
91,1269n1- ,1. .,.Di|.ut,19n.z-...l.._..

 

 

 

 

 

 

 

Figure 3.3. Eﬂ'ect of magnesium concentration and dilution levels on the cDNA-AFLP

proﬁling. Every four lanes are four replications.

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105

 

Figure 3.5. Effect of adapter concentration on the cDNA-AFLP proﬁling. Panels 1 and 2

show primer pairs of N4/‘T 14 and N3/Tll respectively. 1, 2, 3, 4, and 5 are ﬁve levels of

adapter concentration with two replications.

106

REFERENCES

Aronson, L., Gold, J. and R.J. Gull. 1987. Cool-season turfgrass response to drought
stress. Crop Sci. 27, 1261-1266.

Bachem, C.W.B., Horvath, B. Trindade, L., Claassens, M., Davelaar, E., Jordi, W. and
Visser, R.G.F. 2001. A potato tuber-expressed mRNA with homology to steroid
dehydrogenases affects gibberellin levels and plant development. The Plant J. 25,

595-604.

Bachem, C.W.B., Oomen, R.J.F.J. and Visser, R.G.F. 1998. Transcript imaging with
cDNA-AFLP: A step-by—step protocol. Plant Mol Biol Rep. 16, 157-173.

Bachem, C.W.B., Van der Hoeven, R.S., de Brunijn, S.M., Vreugdenhil, D., Zabeau, M.,
and Visser, R.G.F. 1996. Visualization of differential gene expression using a
novel method of RNA ﬁnger-printing based on AFLP: analysis of gene
expression during potato tuber development. The Plant J. 9, 745-753.

Campalans, A., Pages, M. and Messeguer, R. 2001. Identiﬁcation of differentially
expressed genes by the cDNA-AF LP technique during dehydration of almond
(Prunus amygdalus). Tree Physiol. 21, 633—643.

Clayton W.D. Renvoize, S.A. 1986. Genera graminum. Grasses of the world. Her
Majesty’s Stationary Ofﬁce, London.

Du-Toit, R., T.C. Victor and RD. Van-Helden. 1993. Empirical evaluation of conditions
inﬂuencing the polymerase chain reaction: enterotoxigenic Escherichia coli as a
test case. Euro J Clin Chem Clin Biochem. 31:225-231.

Donson, J ., Fang, Y., Espiritu-Santo, G., Xing, W., Salazar, A., Miyamoto, S.,
Armendarez, V., and Volkmuth, W. 2002. Comprehensive gene expression
analysis by transcript proﬁling. Plant Mol. Biol. 48, 75-97.

Fry, J .D. and Butler, J .D. 1989. Responses of tall fescue and hard fescue to deﬁcit
irrigation. Crop Sci. 29, 1535-1541.

Jones, J .T. and Harrower, BE. 1998. A comparison of the efﬁciency of differential
display and cDNA-AFLPs as tools for the isolation of differentially expressed
parasite genes. Funda. App. Nema. 21, 81-88.

Kuhn, E. 2001. From library screening to microarray technology: strategies to determine

gene expression proﬁles and to identify differentially regulated genes in plants.
Ann. Bot. 87, 139-155.

107

Qin L., Prins, P., Jones, J.T., Popeijus, H., Smant, G., Bakker, J ., and Helder, J. 2001.
GenEST, a powerful bidirectional link between cDNA sequence data and gene
expression proﬁles generated by cDNA-AFLP. Nucl. Acids Res. 29: 1616-1622.

Qin, L., Oyermars, H., Helder, J ., Popeijus, H., van-der—Voort, R.,Groenink, W., van-
Koert, P.,Schots, A., Baker, J ., and Smant, G. 2000. An efﬁcient cDNA-AFLP-
based strategy for the identiﬁcation of putative pathogenicity factors from the
potato cyst nematode Globodera rostochiensis. Molec. Plant Micr. Inter. 13, 830-

836.

108

CHAPTER IV

Gene Expression Proﬁles and Candidate Genes Involved in

Drought Tolerance in Festuca mairei

(Submitted to Plant Mol. Bio.)

ABSTRACT

To understand the molecular genetic basis underlying drought tolerance in
grasses, the cDNA-ampliﬁed fragment length polymorphism (cDNA-AF LP) technique
was applied for identiﬁcation of genes responding to drought stress in F estuca mairei
showing xerophytic adaptation. One hundred and twenty eight primer combinations for
cDNA-AF LP were conducted on nine plant samples with one sample per day during
drought stress treatment. A total of 11,346 transcript derived fragments (TDFs) were
detected with size distribution between 50 and 1000bp, and, 464 (4.1%) TDFs were
identiﬁed as differentially expressed fragments (DEF 3) across the nine days. The
expression patterns of these DEFs included up-regulated (29.7%), down-regulated
(54.3%), transiently-expressed (12.3%), and up-then-down-regulated (3.7%). To conﬁrm
the differential expression pattern, 406 DEF s were subjected to macroarray hybridization

analysis. Consequently 171 (42.1%) DEFs showed a consistent expression pattern with

109

the cDNA-AF LP analysis. Sequences of 163 conﬁrmed DEFs were compared to the
GenBank plant protein database by using BLASTX to target the potential function of
these gene fragments. Results showed 62 sequences had no signiﬁcant hits in the
database. Predicted functions of the 101 sequences were subdivided into 17 functional
categories and 11 DEFs were found to be function-unknown, hypothetical or unclassiﬁed
protein. The down-regulated genes involved in metabolism and cellular biogenesis were
nearly twice the number of the up-regulated. On the other hand, more than two times the
amount of up-regulated DEFs were involved in transcription, defense, cell cycle and
DNA processing compared to down-regulated DEF s. The results suggested that during
drought stress generally more metabolic function and biogenesis of cellular components
in the plant were under degenerative processes, and the plant system may rescue energy
for new gene transcription and stress defense. Predicted function of some DEF 8 had
previously been reported as stress induced genes in other species indicating our analysis
system was functioning properly to ﬁnd stress-inducible genes. Some novel genes were
identiﬁed in F. mairei during the drought response procedure. The combination of data
from studies on the genetic model plant and on diverse plant species will help us to better

understand the underlying mechanism of drought tolerance in plants.

Key words: Drought stress, cDNA-ampliﬁed fragment length polymorphism (cDNA-

AFLP), Macroarray, Transcript derived fragments (TDFs), Differential expression.

110

INTRODUCTION

Abiotic stresses such as drought, high salinity, and extreme temperatures can
severely impair plant growth and performance. Thus, the plant response to these abiotic
stresses has been the focus of a number of researchers for decades at physiological and
genetic levels (Levitt, 1980; Quarrie et al., 1994) and more recently targeting the
molecular and genomic aspects (Seki et al., 2001; Ozturk, et al., 2002). Among these
stresses, drought or water deﬁcit is the most severe and complex limiting factor on plant
growth and crop production (Seki et al., 2002). Drought stress triggers a wide range of
plant responses manifested by changes in growth rates, physiological, and metabolic
processes, to altered gene expression. A drought stress response is initiated when a plant
recognizes the stress, which then activates signal transduction pathways to transmit the
information within individual cells and throughout the plants. Ultimately, changes in
gene expression will occur and are integrated into plant adaptive response to modify
growth and development.

Several hundred genes are differentially expressed in response to dehydration in
the resurrection plant Craterostigma plantagineum, as evidenced by transcript proﬁling
(Bockel et al., 1998). In Arabidopsis, which has been extensively studied as a model
plant that tolerates moderate water deﬁcit, genes involved in many different pathways are
expressed in response to drought stress (Seki et al., 2002). All these identiﬁed genes can
be assigned to diverse metabolic pathways. In one example, genes encoding enzymes
involved in sugar metabolism and biosynthesis of other compounds acting as compatible

solutes have been found up-regulated in response to drought in many species (Bohnert,

lll

1995). In another example, the ion and water channel proteins are likely to be important
in regulating water ﬂux, which has been supported by isolation of channel protein genes
from pea (Pisum sativum) in response to water deﬁcit (Guerrero et al., 1990). In
addition, enzymes required for cell wall ligniﬁcation processes seem to be increased in
drought stressed Arabidopsis thaliana tissue (Peleman et al., 1989). Genes encoding
proteins similar to proteases and enzymes that detoxify active oxygen species have also
been induced by drought in some species such as Arabidopsis and pea (Williams et al.,
1994; Mittler et al., 1994). Although the precise function of these genes has not been
demonstrated yet, Bartels and Salamini (2001) have summarized all the drought inducible
genes and grouped them into ﬁve main categories, as genes encoding (a) proteins with
protective properties, (b) membrane proteins involved in transport processes, (c) enzymes
related to carbohydrate metabolism, (d) regulatory molecules, such as transcription
factors, kinases, or other putative signaling molecules, and (e) open reading frames that
show no homologies to known sequences.

It has become obvious that a network of signal transduction pathways allows the
plant to adjust its metabolism to the demands imposed by water deﬁcit (Shinozaki and
Yamaguchi-Shinozaki, 2000; Kirch et al., 2001). The molecular complexity of the
process during drought stress response was illustrated nicely by recent microarray
experiments on Arabidopsis (Seki et al., 2002). The complex signal transduction cascade
can be divided into three basic steps (Ingram and Bartels, 1996): (a) perception of
stimulus, (b) signal ampliﬁcation and integration, and (c) response reaction in the form of
de novo gene expression. Signaling molecules involved in the signal transmission

process and the activation of gene expression in response to stress have been identiﬁed

112

through several experimental approaches. Most information is derived from promoter
analyses and from differential screening procedures. One molecule that is central to
dehydration-regulated gene expression is the plant hormone abscisic acid (ABA).
Endogenous ABA levels have been reported to increase as a result of water deﬁcit in
many physiological studies, and therefore ABA is thought to be involved in the signal
transduction (Chandler 1994; Giraudat 1994). Besides the ABA-mediated gene
expression, the investigation of drought-induced genes in A. thaliana has revealed ABA-
independent signal transduction pathways (Y amaguchi, 1994). Both ABA-dependent and
-independent stress signaling ﬁrst modiﬁes constitutively expressed transcription factors,
leading to the expression of early response transcriptional activators, which then activate
downstream stress tolerance effective genes (Zhu, 2001). Even though a large number of
drought induced genes have been identiﬁed in a wide range of species and an impressive
progress has been made in this area, the molecular basis still remains far from being
understood (Ingram and Bartels, 1996).

F estuca mairei St. Yves is a tetraploid (2n=4x=28, MIMleMz) species,
commonly known as atlas fescue. It shares the M1M2 genomes with F. arundinacea var.
atlantigena (GlGlGZGZMlMlMZMZ), which is only found near the Atlas Mountain ranges
in northwest Africa. The M genome in Festuca is associated with a xerophytic
adaptation allowing the plant to survive long summers under drought stress (Marlatt et
al., 1997). We consider that F. mairei must have evolved highly developed systems for
growing under severe drought conditions. As a polyploidy monocot species, F. mairei
can serve as a reference system for drought tolerance study on some grass species, such

as ornamental grasses, turfgrass and forage, which are grown for their desired traits of

113

vegetative growth and performance, rather than for grain production. The functional
genomics of these species lags far behind other plant systems. Molecular genetic
mechanisms conditioning the expression of drought tolerance in these species also
remains to be illustrated, though a signiﬁcant effort has been invested into the studies of
physiological mechanisms (Levitt, 1980; Youngner, 1985; Qian, 1997) and developing
and evaluating drought resistance in grass species (Aronson et al., 1987; Fry and Butler,
1989). It is important to identify more drought inducible genes and analyze the functions
of those genes. Increasing knowledge of the function of genes induced by drought in F.
mairei would be essential to understand the molecular mechanism of drought tolerance in
grasses and to facilitate gene manipulation for grass breeding programs.

The advent of whole genomic-related technology for differential gene expression
provides the necessary and efﬁcient tools to identify the key genes on a large scale that
respond to drought stress and relate their regulation to adaptive events occurring during
stress. A variety of techniques allow insight to be gained into differential gene
expression during stress. cDNA ampliﬁed fragment length polymorphism (cDNA-

AF LP) is an extremely efﬁcient method for isolating differentially expressed fragments
(DEF s) or transcript derived fragments (T DFs) in a genome wide scale (Bachem et al.
1996). cDNA-AFLP shows high reproducibility and sensitivity, good correlation with
northern blot analysis and low set-up cost, even though it requires a comprehensive
reference database (Donson et al., 2002). Recently, the creation of a large-scale EST
database from various species, and the complete sequencing of Arabidopsis (Arabidopsis
genome initiative [AGI], 2000) and rice genome (Y u et al., 2002) were made public.

This genomic information source can provide a vast reference database for evaluating the

“4

coordinated function and expression of genes identiﬁed by using the cDNA-AF LP
approach.

The objectives of this study were to monitor the gene expression proﬁles of
drought response in F. mairei by cDNA-AF LP procedure, to identify genes involved in
drought stress response, and thus to gain insight into the molecular genetic basis of

drought tolerance in grass species.

MATERIALS AND METHODS

Plant materials and drought treatment

Ten plants of F. mairei clone were transplanted into polyethylene pots (20.32 cm
diameter at the top, 15.24 cm diameter at the bottom, and 35.56 cm height) ﬁlled with
90% sand and 10% silt and clay. The plants had been established for three months with
regular irrigation and fertilization in a uniform greenhouse environment condition. After
establishment, ﬁve F. mairei plants were deprived of water until they were severely
stressed and the other ﬁve plants, as a treatment control, were watered daily throughout
the drought stress period. During the drought stress treatment, leaf samples from both the
stressed and the control F. mairei plants were collected at noon every day to eliminate the
variation due to any diurnal changes of gene expression and the samples were
immediately frozen in liquid nitrogen and stored in — 80 °C for consequent RNA

isolation.

115

Relative leaf water content measurement

Fully extended leaves of the F. mairei plant were detached every other day during
the drought stress treatment for relative leaf water content measurement. The fresh
weight (FW) (weigh the leaf immediately after detachment), turgor weight (TW) (weigh
the leaf after being soaked in the miniQ water for 24 hr at room temperature), and dry
weight (DW) (weigh the leaf after being dried in an oven at 80°C for 24 hr) of the leaf
were used to calculate the relative leaf water content (RWC) following the formula:

ch (%) = (FW-DW)/(TW-DW) x 100 (White et al., 1992).

RNA isolation and cDNA synthesis

Total RNA was isolated with plant RNA puriﬁcation reagent (Invitrogen Life
Technologies, Carlsbad, CA) and then quantiﬁed using a spectrophotometer at a
wavelength of 260 nm. Quality of the RNA was checked by running 2 pg of the total
RNA on 1.2% denature agarose gel with 2.5% formaldehyde in 40 mM 3-(N-morpholino)
propan sulfonic acid (MOPS) running buffer for 2.5 hrs. Poly (A)+ RNA was isolated
from the total RNA by using PolyATract mRNA isolation systems III (Promega,
Madison, WI). Double-stranded (ds) cDNA was synthesized from Poly(A)+ RNA using
the Universal RiboClone cDNA Synthesis System (Promega) and puriﬁed with an equal
volume of TE-saturated phenol: chloroform: isoamyl alcohol (25:2421). The ds cDNA
was quantiﬁed using Hoechst 33258 (bisbenzimide) dye on DyNA quant 200 ﬂuorometer

(Hoefer Pharmacia Biotech, Inc., San Francisco, CA).

116

cDNA-AFLP analysis

The cDNA-AFLP procedure followed the description of Bachem et al., (1998)
with some modiﬁcations. Thirty nanograms of cDNA were digested with 5 U Nspl at
37°C for 2.5 hrs., and then immediately digested with 5 U of Taql at 65 °C for 2.5 hrs.
followed by heat inactivation at 80°C for 20 min. The two steps of digestion were
conducted in NEbuffer 2 (New England Biolabs, Beverly, MA) in a total volume of 30
pl. The digestion mix (20pl) was ligated to 0.5 mM Nspl adapter and 2.5 mM Taql
adapter using 1 U of T4 ligase supplemented with T4 DNA ligase buffer (Promega). All
oligo-nucleotides (adapters and primers) in this study were synthesized by MWG
Biotech, Inc. (Charlotte, NC) (see Table 4.1 for sequences). PCR reaction solution (20
pl) for pre-ampliﬁcation contained 1 pl digestion mix, 0.5 pM of each primer, 0.3 mM
dNTP mix, 1.5 mM Mg”, and 0.5 U Taq polymerase (Promega). The PCR reaction was
conducted on the FTC-225 at: 72°C, 2 min; 94°C, 1 min; 15 cycles of 94°C, 30 s; 56°C,
30 s; and 72°C, 1 min; then followed by 10 min at 72°C for a ﬁnal extension. For
selective ampliﬁcation, the PCR solution included 1 pl of 5x diluted pre-ampliﬁcation
product, 0.4 pM of each selective primer, 1.5 mM Mg“, 0.3 mM dNT P mix, and 0.4 U
Taq polymerase in 15 p1 total reaction volume. The PCR reaction was performed
following the program: 10 cycles: 94°C, 30 s; 65°C (- 0.7°C /cycle), 30 s; 72°C, 1 min
and 25 cycles: 94°C, 30 s; 56°C, 30 s; 72°C, 1 min; followed by a ﬁnal extension step of
10 min at 72°C.

The selective PCR product (15 pl) was denatured at 96°C for 6 min after adding 9
pl of 98% forrnamide loading buffer. The denatured PCR product (6 pl) was loaded into

a 5% denatured polyacrylamide sequencing gel with 45.4% urea for fractionation by

117

electrophoresis at 90 W for 2.5 hrs. The fractionated fragments on the gel were then
detected by using the Silver Sequence DNA Sequencing System (Promega). The gel on
the back plate was allowed to dry overnight at room temperature for scoring on a light
box. For recovery of TDFs from the polyacrylamide gel, silver staining has advantages

over radioactive ﬁngerprints by being directly visualized and excised from the gel.

Identiﬁcation of differentially expressed fragments and fragment recovery from

polyacrylamide gel

For each primer combination, the ﬁnal PCR products from a series of days of
drought stress were loaded in order into lanes next to each other in the sequencing gel for
comparison of band density for bands of the same size. If the density of the bands
increases from lane to lane gradually across the time points, the bands were identiﬁed as
up-regulated differentially expressed fragments. If they decrease gradually, the bands
were identified as down-regulated DEFs (Bachem et al., 1996). If the bands show up
only at a speciﬁc time point, these bands were identiﬁed as transient expressed DEF s. A
few bands were also identiﬁed as up-then-down regulated DEFs, which means the
density of the bands increases at ﬁrst several lanes and then decreases at the last several
lanes.

The ﬁur types of DEFs were excised from the polyacrylamide gel with a sterile
surgical blade. DNA was eluted by soaking the excised gel in 50 pl water for 12 hrs and
then was used as the template to re-amplify the DNA fragment using the same PCR
condition as used for selective ampliﬁcation. The re-ampliﬁed product was run on an 1%

agarose gel in l x TBE buffer for conﬁrmation of the target fragment and separation from

118

possible DNA contamination. DNA fragments with the target size were puriﬁed from the
agarose gel with a QIAquick gel extraction kit (QIAGEN, Inc., Valencia, CA) and eluted

in 50 pl sterile water.

Macroarray hybridization and data analysis

Double stranded cDNA samples from control and stressed plants at different time
points were labeled with DIG-dUTP by using a PCR DIG probe synthesis kit (Roche
Applied Science, Penzberg, Germany). The labeled product was puriﬁed with a high
pure PCR product puriﬁcation kit (Roche).

Ten microliters of both the recovered DEF DNA samples and control samples
were denatured with 10 pl denature solution (0.4 N sodium hydroxide, 0.01 M EDTA,
pH=8.0) at 37°C for 15 minutes and then neutralized with 10 pl 2 M ammonium acetate
(pH=7.0). Controls included a negative control, which contained sterile water but not
DNA, and a housekeeping control, which contained only DNA fragment with the same
expression level (constitutively expressed) throughout the control and the different days
of the stressed plant. All of the above denatured solutions of the DEF and controls were
spotted on a nylon membrane (115 x 76 mm) (Nalge Nunc International, Naperville, IL)
with two replications using the Beckrnan BioMek® 2000 laboratory automation
workstation (Dilks et al., 2003). The controls were spotted in different sections of the
membrane to compensate for variable background levels. The spot arrangement on the
nylon array is shown in Figure 4.1. Five identical nylon arrays were prepared serially
and then subjected to separate hybridization with labeled ds cDNA probes. The

hybridization and washing were performed by using DIG high prime DNA labeling and

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detection starter kit 11 (Roche). The luminescent signal on the membrane was exposed to
Lumi-Film Chemiluminescent detection ﬁlm (Roche).

The array image on the ﬁlm was scanned and saved as an individual “.TIFF” ﬁle
and was then analyzed with BIORAD® Quantity One Software 4.2.3 (Bio-Rad
Laboratories, Hercules, CA). For each array image, all of the spots were delimitated with
the same size circles, which could include all the pixels in the spot. The volume (=pixel
intensity x area of the circled spot) of each spot was reported from the software. The
average volume of negative control spots on the array image was subtracted from the
volume of each of the other spots to eliminate background effect. The average volume of
housekeeping control spots on the array image was used to normalize the spots of
unknown DEFs between array images. The ratio of the average volume of housekeeping
spots between images was applied as a scaling factor for the volume of unknown DEF
spots, which were compared to its counterpart between membranes to conﬁrm the
differential expression pattern. For up-regulated and down-regulated DEFs, the
membrane arrays hybridized with a treatment control cDNA probe were compared to the
5-day stressed cDNA probe. For up-then-down regulated DEFs, the membrane arrays
hybridized with the 3-day stressed cDNA probe were compared to the control cDNA
probe for up-regulation and to the 5-day stress for down-regulation. For the transiently
expressed DEFs, the membrane hybridized with the cDNA probe of a certain number of
day's stress, at which the DEFs were exclusively expressed, were compared to the probe
of the day before and after respectively. The volume ratio of the DNA dots from the two

replications greater than 1 were accepted as conﬁrmed DEF.

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DNA fragment sequencing and sequence analysis

The DEF s recovered from the polyacrylamide gel whose differential expression
pattern were conﬁrmed with macroarray analysis, were cloned into pGEM—T easy vector
(Promega) and transformed into JM109 component cells (Promega) by heat shock.
Plasmid DNA was extracted from successful transforrnants using the Wizard plus SV
minipreps DNA puriﬁcation system (Promega), and plasmid inserts were sequenced
using an ABI PRISM 3 100 genetic analyzer (Applied Biosystems, Foster City, CA) at
The Genomics Technology Support Facility (Michigan State University).

The sequences of the DEFs were searched against the AGI (Arabidopsis Genome
Initiative) protein database using BLASTX (http://wwwaﬂbidopsisorg/Blast/).
Additional analysis using BLASTX against GenBank plant protein database and
TBLASTX against GenBank plant dbEST were performed for DEFs with zero matches
or low similarity (E value greater than 1E-6) in AGI protein database. A tool of the
“Blast 2 sequences”, which can be found at:
http://www.ncbi.n1m.nih. govlblast/blZseq/wblastZ.cgi, was used for sequence

comparisons.

RESULTS

Plant performance during the drought stress

The treatment control plants of F. mairei remained green and survived throughout

the stress treatment period. Plants under stress were green for the ﬁrst three days after

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being deprived of water, and then began discoloring and ﬁring at the 4th day after water
deprivation. The RWC of the stressed plant decreased dramatically from 83% to 26%
between 3rd and 5th day of drought stress (Figure 4.2). At 8th day of drought stress, the
leaves of the stressed plants were completely ﬁred with a RWC around 17%. These eight
days covered dynamic changes of the plants responding to drought stress, and the 4th day
under stress was a critical time point during the response (Figure 4.2). The eight days
plus the day before application of stress (a total of 9 days) were considered to be a whole
drought stress period. With each day as a time point, there were nine time points within

this stress period.

cDNA-AFLP analysis

To investigate the possibility of the DEFs induced by plant development or
changes of greenhouse conditions during the drought stress period, cDNA-AF LP analysis
was performed on the treatment control plants of F. mairei over the nine days using ﬁve
randomly picked primer combinations. No DEF was detected across the nine time-points
in control plants (Figure 4.3), suggesting both greenhouse conditions and plant
development did not affect gene expression in F. mairei plants during the days of
application of the drought stress.

cDNA-AFLP analysis was conducted using all of the 128 primer combinations
over nine days of the stressed F. mairei plants and revealed 11,346 transcript derived
fragments (TDFs) with an average of 89 ﬁ'agments obtained per primer pair. The size
distribution of the fragments was between 50 and 1000bp (Figure 4.4). Of these TDFs,

464 fragments (4.1%) were identiﬁed as being differentially expressed across the nine

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time-points during the drought stress, indicating the gene expression had been altered by
the drought conditions. The expression pattern of these DEFs included up-regulated
(138, 29.7%), down-regulated (252, 54.3%), transient-expressed (57, 12.3%), and up-
then-down-regulated (17, 3.7%) (Figure 4.5). Of these 464 DEFs, 434 (94%) fragments
were recovered from acrylamide gel and isolated as genes potentially related with plant

response to drought stress.

Macroarray hybridization analysis

In addition to 13 positive and 13 negative controls, 406 samples of 434 recovered
DEF s were printed on the membrane with two replications (Figure 4.1). Twenty eight
DEFs with sizes of less than 100 bp were not included in the macroarray analysis. The
dot intensity volume of two or three identical membrane arrays hybridized with cDNA
probes from different time-point respectively were compared for conﬁrmation of the
differential expression pattern of the 406 DEFs (see Materials and Methods). Figure 4.6
shows an image of a portion of the hybridized macroarray. The comparison results
revealed that 54 of 128 (42.2%) up-regulated, 97 of 210 (46.2%) down-regulated, 14 of
51 (27.5%) transiently expressed, and 6 of 17 (35.3%) up-then-down regulated DEFs
showed the consistent differential expression pattern. In total, the expression pattern of
171 (42.1%) DEFs were conﬁrmed. These 171 DEFs were cloned as drought inducible

and repressible gene fragments.

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Sequence analysis and functional category

All 171 DEFs were sequenced and an expected size sequence was obtained for
166. Among the 166 sequences, three pairs of fragments were aligned with above 98%
similarity and one of each pair was excluded from further analysis. BLASTX analysis
was conducted against the GenBank protein database of the 163 sequences (92 down-
regulated, 50 up-regulated, 15 transiently expressed, and 6 up-then-down-regulated). The
results revealed that 101 DEFs (62.0%) showed signiﬁcant homology to a protein
sequence in the database (E value less than lE-6) and the other 62 DEFs (38.0%) showed
zero match (no hits found) or no signiﬁcant homology (E value higher than lE-6). When
the entire GenBank EST database was screened for the presence of sequences similar to
these 62 DEFs (TBLASTX analysis), 23 DEFs showed statistically signiﬁcant degrees of
similarity to the public available ESTs. The remaining 39 DEFs were deﬁned as novel
sequences, which have not previously been described from other organisms. The 39
novel DEFs included 13 down-regulated, 6 transiently expressed, and 20 up-regulated
sequences. Therefore, 40% of the 50 up-regulated, 15 transiently expressed DEFs
respectively and 14.1% of the 92 down-regulated DEF were found to be novel in F.
mairei under drought stress.

The function predicted for the 101 DEF 5 could be subdivided into 1? functional
categories and 4.8% of these DEFs were function unknown, hypothetical or unclassiﬁed
protein based on function classiﬁcation criteria in the website of MIPS (Munich
Information Center for Protein Sequences) (http://mips.gs£de) (Table 4.2). Most of the
proteins fell into more than one functional category with statistical signiﬁcance, and all of

those categories were counted. In comparison of the ﬁrnctional category between the up-

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regulated and the down-regulated DEF (Figure 4.7), the down-regulated genes involved
in metabolism and cellular biogenesis were found to be nearly twice that of the up-
regulated. More than two times the amount of the up-regulated DEFs were involved in
transcription, defense, cell cycle and DNA processing compared to down—regulated
DEF 3. During drought stress, the results reﬂected, generally more metabolic function
and biogenesis of cellular components in the plants were under degenerative processes.
The plant system appeared to save energy for new gene transcription and stress defense.
More genes involved in cell cycle and DNA synthesis were up-regulated suggesting an
increasing activity of growth in some speciﬁc guard cells for stress defense. The
transiently expressed DEF s were primarily involved in subcellular localization, defense,
or acted as heavy metal carriers for transport reﬂecting the temporary needs for sets of
genes in defense, transport and subcellular localization during plant response to drought.
The up-then-down regulated DEFs were mostly involved in transport, subcellular
localization, and energy indicating that some genes for electron/hydrogen transport,
subcellular localization, and photosynthesis were stimulated by drought stress signal

ﬁrstly, and then inactivated by continued or severe stress.

Predicted function of up—regulated DEF s

Twenty two DEF s up-regulated or induced by drought stress in F. mairei had
signiﬁcant similarity with protein sequences in the GenBank database (Table 4.3). Most
of them had the highest similar hits in the monocot species such as rice (Oryza sativa),
maize (Zea mays), and wheat (T riticum aestivum). SSBII-HZ, SSBI-B6, and SSBI-CO9

encoded enzymes, respectively, involved in biosynthesis of purine nucleotide, raffrnose,

125

which has also been induced by water stress in Cicer arietinum (Romo et al., 2001), and
trehalose, the most effective osmoprotectant sugar in terms of minimum concentration
required (Crowe et al., 1992). The SSBI—Dll encoding of an enzyme for C-compound
and carbohydrate utilization has been identiﬁed as a transcript differentially expressed in
response to high salinity in the mangrove, Bruguiera gymnorrhiza (Banzai et al., 2002).
The farnesylated protein encoded by SSBI-B9 has been found to be a nuclear protein
involved in stress response and leaf senescence in Hordeum vulgare (Barth et al., 2004).
SSBI-D4, SSBI-D9, SSBII-A3, and SSBI-A4 encoded a ﬁber protein Fbl9, a
dehydration-responsive family protein, a type-1 pathogenesis-related protein, and a
DNAJ heat shock N-terrninal domain-containing protein, respectively, which have been
widely studied in association with stress response. SSBI-E2 encoded a 34 kD ﬁbrillin-
like protein, the major constituent of elastin-associated extracellular microﬁbrils, and has
been recently identiﬁed in a network of rice genes associated with stress response
(Cooper et al., 2003), even though this protein was classiﬁed as categories of
transcription and subcellular localization on the website of MIPS. SSBI-AS encoded a
brown planthopper susceptibility protein and shared similarity with the sequence of a rice
gene induced in response to herbivore grazing. Several DEF s encoded proteins involved
in heavy metal ion transport, electron/hydrogen transport, and membrane channel,
reﬂecting the plant actively adjusted the ion and water status for homeostasis. The DEF s
encoding proteins for transcription and translation regulation were induced such as zinc
ﬁnger protein, MYB transcription factor, and peptide chain release factor suggesting the

some stress-responsive genes are activated by these factors for positive stress defense.

126

Predicted function of down-regulated DEFs

In total, 70 down-regulated DEFs showed signiﬁcant similarity to previously
identiﬁed proteins (Table 4.4). A much larger quantity of down-regulated DEFs than up-
regulated were isolated in F. mairei during drought stress indicating that the plant was
mainly under degenerative processes imposed by the stress. Down-regulated genes were
involved in a number of basic metabolic or biosynthetic functions and systemic
development or growth. For example, light-inducible protein HV58 (SSBII-D7) was for
photosynthesis; chlorophyll A-B binding farnily protein (SSBI-BIO) was for respiration;
victorin binding protein (a glycine dehydrogenase P protein) (SSBI-B12) was for amino
acid metabolism; GTP-binding protein typA (SSBII-C2) was for oligopeptide synthesis;
UDP-glycosyltransferase 88Bl (SSBII-G7) was for c-compound and carbohydrate
metabolism; homeobox protein knotted-7 (SSBI-H3) was for tissue development; DNA
helicase (DNA-binding protein) (SSBI-GlO) was for cell division and so on. In addition,
some proteins for transport facilitation were down-regulated, such as ADP-ribosylation
factor for vesicular transport (SSBII-HS), iron-phytosiderophore transporter protein for
aligopeptide transport (SSBII-B8), ferric reductase for electron transport (SSBII-BZ),
cation diffusion facilitator for ion transport (SSBII-Cl), and triose phosphate translocator
for c-compound transport (SSBI-E7). Moreover, several proteins involved in
transcription and signal transduction were also down-regulated indicating some pathways
for signaling and basic biosynthesis or metabolism were turned down in the plant during
drought stress. Those proteins included cleavage and polyadenylation speciﬁcity factor
(SSBII-FlO), homeobox gene knotted 7 (SSBI-H3), TATA-binding protein associated

factor (SSBII-F 3), SEUSS transcriptional co-regulator (repressor) (SSBI-B7),

127

EREBPltranscription factor (SSBI-ClO), zinc ﬁnger protein (SSBII-ES), and

phosphatidylinositol-4-phosphate 5-kinase (SSBII-G2).

Predicted function of up-then-down regulated and transiently expressed DEFs

Five up-then-down regulated and four transiently expressed DEF s were identiﬁed
sharing signiﬁcant similarity with proteins in the public database (Table 4.5). The rieske
Fe-S precursor protein (SSBI—F 10), a chlorophyll a/b-binding protein (SSBII-DS),
digalactosyldiacylglycerol synthase (SSBI-D3), and a disease resistance protein (SSBI-
D5) were up-regulated at the earlier stress period and then turned down with the stress
continuing, indicating that these proteins may have a positive response to the mild stress
but were not retained during the severe stress. The glutamine-dependent asparagine
synthase, plasma membrane H+ ATPase, small heat shock protein Hsp23.5, and type 2
metallothioneine were temporally expressed at only around day 4 stress suggesting the

transient regulation of these protein might be critical for drought stress response.

DISCUSSION

Functional approach to identify stress response genes

In this study, an effective enzyme combination, Nspl/Taql was used to conduct
the cDNA-AFLP procedure for a sufﬁcient data extraction (Wang et al., 2005). The DEF

was ﬁrst identiﬁed with cDNA-AFLP analysis, and then the macroarray analysis was

128

performed to verify the differential expression pattern. Around 42% DEFs were
consistently expressed, but the expression of 58% DEFs were not consistent between the
two techniques. The inconsistency could be due to: (1) the subjective evaluation on the
DEF in the cDNA-AF LP gel; (2) the different macroarray hybridization intensities and or
background between the membranes compared; (3) possible cross hybridization of
closely related sequences in macroarray; and (4) low expression genes in the probe for
macroarray hybridization (Miller et al., 2002). Therefore, we excluded more than half
(58%) of the DEF from subsequent sequence analysis to have a more correct data set.
Some of the drought inducible DEFs identiﬁed by cDNA-AF LP coupled with macroarray
had previously been reported as stress-inducible genes in other species (see Results).
These discoveries indicated our analysis system functioned properly to ﬁnd stress-
inducible genes.

Previously, a large number of identiﬁed genes, transcripts and proteins were stress
inducible or up-regulated. The down-regulated genes were basically underestimated.
Only one or two time-point stresses were compared with the control, especially by
microarray analysis. Some genes, such as transiently expressed genes, and up-then-down
regulated genes, could not be identiﬁed. However, the plant response to stress is a
complicated procedure. Down-regulation or other types of regulation may also play
important roles in stress response or even tolerance. Investigation of the systemic and
dynamic changes of the gene expression will provide more complete information for
understanding the molecular mechanism of stress response. In this study, nine days in
the drought stress cycle were taken for analysis, which covered the whole dynamic

change of the plant responding to the stress. Four different differential expression

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patterns were detected by the cDNA-AF LP analysis, even though the transient and up-
then-down expression patterns were not abundant. Further study on genes with all of
these differential expression patterns, including spatial and temporal regulation patterns,
will lead to a programmed control of the desiccation response, and thus, will increase our
knowledge on the stress response mechanism at the gene regulation level. The cDNA-
AFLP technique not only provided a means to generate genomic sequence information
and functional analysis but also served as a powerful tool for the identiﬁcation of genes

with different kinds of differential expression patterns for stress response.

Drought inducible genes

Stress-inducible genes have been transferred into several crops to improve the
stress tolerance of plants (Bajaj et al., 1999). Functional analyses of the stress-inducible
genes are important for increasing our knowledge on molecular mechanisms of stress
response and for stress tolerance improvement of crops. To date, more than 200 drought
inducible genes have been reported (Seki et al., 2002, Ozturk et al., 2002). Identiﬁcation
of more novel drought-inducible genes will provide more complete information about
genes involved in stress tolerance and cis-acting promoter elements that function in
drought speciﬁc gene expression (Seki et al., 2001). In our study, 50 drought inducible
gene fragments were identiﬁed ﬁ'om the drought adaptive monocot plant, F. mairei.
Only 22 (44%) had hits with signiﬁcant similarity in the protein database and were
assigned functions. The remaining 28 (56%) either had hits with no signiﬁcant similarity
in the protein database, or had signiﬁcant hits in the EST database with unknown

function, or had no hits in either database and were deﬁned as novel drought-inducible

130

gene fragments. Among the gene products of the 22 informative DEFs, several have
been reported as up-regulated by stress in Arabidopsis such as zinc ﬁnger and MYB
family transcription factors, raffmose synthases and trehalose-6-phosphate synthase, heat-
shock protein, auxin-regulated protein, and so on (Seki et al., 2002).

The products of the stress-inducible genes can be classiﬁed into two groups: (1)
those that directly protect against environmental stresses; and (2) those that regulate gene
expressions and signal transductions in stress response (Seki et al., 2002). The proteins
in the ﬁrst group have the ability to function in stress tolerance. The rafﬁnose synthases
and trehalose-6-phosphate synthase were osmoprotectant biosynthesis-related proteins for
adjusting the osmotic pressure under stress conditions. The heat-shock proteins have
been reported to be involved in protecting macromolecules such as enzymes and lipids
(Shinozaki and Yamaguchi-Shinozaki, 1999). The ﬁbrillin and ﬁber proteins might
contribute to cell wall structure modiﬁcation. The type-1 pathogenesis-related protein is
considered to be a protein with antifungal activity (Antoniw et al., 1980) that may have
multiple stress-related roles even though the function is still unknown. Tonoplast
intrinsic protein (aquaporin) functions as a water channel to transport water through
plasma membrane and tonoplast to adjust the osmotic pressure under stress conditions
(Daniels et al., 1994). The transporters for anion and zinc may function in adjustment of
ion homeostasis. The second group contains regulatory proteins involved in regulation of
signal transduction and gene expression in stress responses. The zinc ﬁnger and MYB
family transcription factors may ﬁmction in the regulation of stress-inducible gene
expression. The peptide chain release factor induced by drought stress reﬂected that the

post-transcriptional regulatory mechanism also affected the gene expression. Ankyrin

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protein kinase is thought to be involved in signal transduction and in further regulating
the functional genes under stress conditions. The auxin-regulated gene was identiﬁed as
drought-inducible suggesting a link between auxin and drought stress signaling pathways.
Some DEF s annotated to the same ﬁrnctional genes were probably derived from
the same gene or ﬁom redundant homologous genes. Currently, functions of most of
these genes are not fully understood. Moreover, 56% of the drought inducible gene
fragments in this study were still functionally unknown and remain to be elucidated.
Functional analysis of such sets of DEFs might be informative to follow up in later

experiments based on more natural drying plants in the ﬁeld.

Drought repressible genes

Analysis of drought-repressible genes is as important as analysis of drought-
inducible genes in understanding the molecular mechanism of plant response to stress. In
this study, many photosynthesis-related genes were found such as chlorophyll afb binding
protein, ribulose-1,5-bisphosphate carboxylase, high molecular mass early light-inducible
protein HVS 8, etc., all reﬂecting that photosynthesis was inhibited by the water deﬁcit.
This can be due to a reduction in light interception as leaf senesce, or to a reduction of
intercellular C02 concentration as closure of stomata (Bartels D. and Salarrrini F., 2001).
The beneﬁt of the depressed photosynthesis appears to be the switch toward another
carbohydrate utilization pathway, which leads to the production of valuable stress
tolerance molecules (Pattanagul and Madore, 1999). Bockel & Bartels (unpublished
data) proposed that down-regulation of photosynthesis-related genes possibly contributed

to reduced photooxidative stress.

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Lipoxygenase, glutamate synthase, malate dehydrogenase up-regulated under
drought in barley (Ozturk et al., 2002) but were down-regulated in this study. Some
clones have been up-regulated by drought in Arabidopsis encoding protein products the
same as protein encoded by down-regulated clones, eg. Cytochrome P450 protein and
malate dehydrogenase have shown in both up-regulated and down regulated groups (Seki
et al., 2002). This distinct behavior has also been found in barley and rice (Kawasaki et
al., 2001). Their role and importance in tolerance or sensitivity is impossible to judge
based on the experiments alone under controlled environment conditions. But these
DEFs, at least, provide clues about the genes differentially expressed with a reference

database for comparison later on with data from nature ﬁeld drought conditions.

Application of drought stress and DEFs

Plant response to drought stress will vary as the time, duration, and intensity of
the stress applied on plants differs. Growth chambers and greenhouses allow very precise
control of the timing, duration and intensity of stress control, but they are least like the
plant‘s natural environment or farmers’ ﬁelds, where the crops are ultimately evaluated in
breeding programs (Bruce et al., 2002). If water loss occurs slowly enough to allow
metabolism to adapt the stress by activating a speciﬁc program of gene expression, plants
will develop the ability to survive desiccation. If dehydration occurs too rapidly, plants
will not acquire enough tolerance to desiccation (Bartels and Salamini, 2001). However,
in recent functional genomic studies, the drought-inducible transcripts have been
identiﬁed in hours or one day, which might lead to omission of some important tolerance

transcripts or genes. In this study responses to the whole stress cycle were evaluated, but

133

more information will need to be collected before breeders can use this information. All
the DEF 3 including the novel ones should be analyzed with breeding lines under more
natural drought conditions to further conﬁrm the correlation of expression pattern of the
transcripts with drought tolerance. The particular functions of these DEFs need to be
studied by using knock-out mutants and transgenics, such as over-expression, antisense
suppression, and double-stranded RNA interference (RNAi). It has been found that
some genes induced by drought stress have no effect on drought tolerance in transgenic
plants (Karakas et al., 1997). Therefore, a challenge for future research is to distinguish
between gene products with a potential in osmoprotection and those that are only
involved in secondary reaction. The combination of quantitative transcript proﬁles with
an appropriate QTL analysis could possibly lead to the identiﬁcation of candidate genes
for agronomically valuable traits.

In general, most advances in understanding the drought tolerance mechanism will
be obtained from studies on the mild drought tolerant model species, Arabidopsis.
However, these studies will not be sufﬁcient to explain the adaptation of the F estuca
species to severe drought stress. The research on F. mairei has uncovered a number of
GenBank novel genes. The combination of data from studies on the genetic model plant
and on diverse plant species should help us to better understand the underlying
mechanism of drought tolerance in plants. Existence of variety of drought responsive
genes suggests a complex process of plant response to the stress. The genes are involved
in drought stress tolerance and stress responses. Although more work is necessary to
deﬁne gene functions and dissect the complex regulation of gene expression, the genes

isolated and characterized to date give us many intriguing insights into the protective

134

mechanisms that determine desiccation tolerance. Reverse genetic approach as well as
classical genetics will become more important to understand not only functions of stress-

inducible genes but also the complex signaling process in environmental stress response.

135

Table 4.1. Sequences of the linkers and primers used for cDNA-AF LP analysis

synthesized by MWG Biotech Inc.

 

Primers and linkers

Sequences (5’-3’)

 

Nspl linker 1

Nspl linker 2

Nspl pre-ampliﬁcation primer

Nspl selective ampliﬁcation primer 1
Nspl selective ampliﬁcation primer 2
Nspl selective ampliﬁcation primer 3
Nspl selective ampliﬁcation primer 4
Nspl selective ampliﬁcation primer 5
Nspl selective ampliﬁcation primer 6
Nspl selective ampliﬁcation primer 7
Nspl selective ampliﬁcation primer 8
T an linker 1

T an linker 2

Taql pre-ampliﬁcation primer

Taql selective ampliﬁcation primer 1
T an selective ampliﬁcation primer 2
T an selective ampliﬁcation primer 3
Taql selective ampliﬁcation primer 4
Taql selective ampliﬁcation primer 5
T an selective ampliﬁcation primer 6
T an selective ampliﬁcation primer 7
Taql selective ampliﬁcation primer 8
Taql selective ampliﬁcation primer 9
Taql selective ampliﬁcation primer 10
T an selective ampliﬁcation primer 11
Taql selective ampliﬁcation primer 12
Taql selective ampliﬁcation primer 13
Taql selective ampliﬁcation primer 14
T an selective ampliﬁcation primer 15
Taql selective ampliﬁcation primer 16

GTAGACTGCGTTCCCATG
GGAACGCAGTCTACGAG
GTAGACTGCGTTCCCATG
GTAGACTGCGTTCCCATGTA
GTAGACTGCGTTCCCATGTT
GTAGACTGCGTTCCCATGTC
GTAGACTGCGTTCCCATGTG
GTAGACTGCGTTCCCATGCA
GTAGACTGCGTTCCCATGCT
GTAGACTGCGTTCCCATGCC
GTAGACTGCGTTCCCATGCG
AAGTCCTGAGTAGCAC
CGTTCAGGACTCATC
CACGATGAGTCCTGAACG
CACGATGAGTCCTGAACGAAA
CACGATGAGTCCTGAACGAAT
CACGATGAGTCCTGAACGAAC
CACGATGAGTCCTGAACGAAG
CACGATGAGTCCTGAACGATA
CACGATGAGTCCTGAACGATT
CACGATGAGTCCTGAACGATC
CACGATGAGTCCTGAACGATG
CACGATGAGTCCTGAACGACA
CACGATGAGTCCTGAACGACT
CACGATGAGTCCTGAACGACC
CACGATGAGTCCTGAACGACG
CACGATGAGTCCTGAACGAGA
CACGATGAGTCCTGAACGAGT
CACGATGAGTCCTGAACGAGC
CACGATGAGTCCTGAACGAGG

 

136

Table 4.2. Distribution of ﬁrnctional category of the differentially expressed fragments
(DEF 5) during drought stress cycle in F. mairei. Classiﬁcation was performed for 101
DEFs with strong statistical similarity to GenBank plant protein sequence (E values lower
than 1.00E-06) by BLASTX search. The functional category was assigned based on
function classiﬁcation criteria in the website of Munich information center for protein

sequences (MIPS) (http://mips.gsf.de).

 

 

Function category Total Up- Down- Transiently Up—then-
(%) regulated regulated expressed down
(%) (%) (%) regulated

(%)

Metabolism 16.45 9.76 19.63 9.09 6.25

Energy 7.36 4.88 7.98 0.00 12.5

Biogenesis of cellular 4.76 2.44 5.52 '0.00 6.25

components

Subcellular 22.94 17.07 24.54 27.27 18.75

localization

Transport 10.39 9.76 9.20 9.09 25

Transcription 5.19 12.20 4.29 0.00 0

Signal transduction 2.60 0.00 3.07 0.00 6.25

Interaction with the 3.90 4.88 3.68 9.09 0

cellular environment

Protein synthesis 1.73 2.44 1.84 0.00 0

Protein with binding 5.63 4.88 4.91 18. 18 6.25

function

Defense 6.93 17.07 3.68 18.18 6.25

Development 2. 16 2.44 2.45 0.00 0

Cell fate . 1.30 2.44 1.23 0.00 0

Cell cycle and DNA 0.87 2.44 0.61 0.00 0

processing

Protein fate 2.16 0.00 2.45 0.00 6.25

Cell type 0.43 0.00 0.00 9.09 0

differentiation

Protein activity 0.43 0.00 0.61 0.00 0

regulation

Function unknown, 4.76 7.32 4.29 0.00 6.25

hypothetical, and

unclassiﬁed protein

 

137

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I Positive control spot El Negative control spot El Unknown sample spot

Figure 4.1. The spot arrangement on the nylon array for macroarray hybridization. The
controls were spotted in different sections of the membrane to compensate for variable

background levels. All samples were presented with two replications on each array.

20
10

Relative leaf water content (%)
8

 

 

 

 

 

 

 

 

 

 

 

d1 d3 d5 d7

Drought stress period (Day)

Figure 4.2. Relative leaf water content of F. mairei during the drought stress cycle.

145

d01d1 d2 d3 d4 d5 d6 Md8

 

Figure 4.3. An example of cDNA-AFLP proﬁle for treatment control F. mairei. All

transcript derived fragments were constitutively expressed at the same level.

146

60 _ . - ...H,.4,,,w. ._._.

Total 11,346 TDFS

 

 

 

 

8

 

 

 

 

Persentage (%)
8 8

 

1o~

 

 

 

1000-700 600-700 500-600 400-500 300-400 ZOO-300 100-200 50-100

Size (bp)

Figure 4.4. Distribution of the size of transcript derived fragment from cDNA-AF LP

performed on F. mairei.

147

 

 

 

 

 

  

 

 

 

252

250 -ﬁ . y

200
E
E 150 ~
3
z

100 -

50 ~ —
17
0 .1 - .31- .. . ,
Up-regulated DoeregLIated Transient- Up-then-down
expressed regulated

Expresslon pattern

Figure 4.5. Distribution of the pattern of differentially expressed fragments revealed by

cDNA-AFLP during drought stress cycle in F. mairei.

148

 

Figure 4.6. A portion of the hybridized macroarray. The differentially expressed
fragments (DEFs) from cDNA-AFLP were arrayed on nylon membranes A and B
identically. Membranes were seperatively hybridized to treatment control (A) and 5 days
stress treated (B) cDNA probes, respectively. Spots in squares indicated the
housekeeping controls used for normalization between arrays (In present case, signals in
membrane A were stronger than B. Therefore, the housekeeping controls were used to
balance the two arrays). Spots in the circle indicated the negative controls used to
eliminate the background effect. Spots in the up-triangle indicated example of up-

regulated DEFs. Spots in the down-triangle showed example of down-regulated DEFs.

149

Figure 4.7. Comparison of functional categories between up-regulated and down-
regulated differentially expressed fragments (DEFs) during drought stress cycle in F.
mairei. Each DEF was searched against the GenBank plant protein database by
BLASTX. The ﬁmctional category was assigned based on function classiﬁcation criteria
on the website of Munich Information Center for Protein Sequences (MIPS)

(http://mips.gs£de).

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SUMMARIES

Compared with three tall fescue (F. arundinacea Schreb.) cultivars, the leaf
elongation and leaf water content of Atlas fescue (F estuca mairei) was less sensitive
to the drought stress treatment.

Atlas fescue had an exceptional ability to accumulate water in leaf tissue under severe
drought stress.

A mechanism may exist in Atlas fescue to maintain cell turgor necessary for cell
expansion as soil water content declined and leaf water potential became more
negative.

Atlas fescue possessed drought tolerance and afforded potential to improve drought
tolerance in turfgrass breeding program.

The genome of Atlas fescue had been successﬁilly transferred into drought
susceptible perennial ryegrass through intergeneric hybridization.

The parental genome composition of the hybrid progeny ranged widely when
detected by SSR and RAPD markers.

The non-coinheritance of the linked markers suggested chromosome crossover
between the two parents.

Cluster and principle component analyses of the progeny consistently revealed three
major groups. Group I included progeny that introgressed more of the Atlas fescue
than perennial ryegrass genome. Group II comprised of progeny showing similar
amounts of genome introgression from both parents. Group III contained progeny

that introgressed more of the perennial ryegrass genome.

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For the progeny with more Atlas fescue genome, more backcrosses should be
conducted to recover the good turf quality of ryegrass.

Drought tolerant cultivar can be released from these progeny after drought tolerance
and turf quality evaluations.

In cDNA-AFLP analysis, Nspl coupled with Taql was a pair of highly efﬁcient
enzymes for detecting transcript derived fragments in Atlas fescue species. This
enzyme combination may have valuable application potential for other species.

The cDNA-AFLP analysis was relatively insensitive to ampliﬁcation conditions and
had high reproducibility across treatments.

The chimeric fragments derived from ligation between digested fragments were
generated and could not be eliminated by increasing adapter concentration.

The cDNA-AFLP analysis is a reliable and high throughput transcript proﬁling
technique suitable to transcript derived fragments (TDFs) discovery in grasses such as
Atlas fescue species.

Among a total of 11,346 TDFs revealed by cDNA-AFLP in Atlas fescue species, 464
(4.1%) TDFs were identiﬁed as differentially expressed ﬁagments (DEFs with size
distribution between 50 and 1000bp. The expression patterns of these DEFs included
up-regulated (29.7%), down-regulated (54.3%), transiently-expressed (12.3%), and
up-then-down-regulated (3.7%).

The differential expression pattern of 171 (42.1% of 406) DEFs from cDNA-AF LP
analysis was conﬁrmed by macroarray hybridization analysis.

cDNA-AF LP technique coupled with macroarray hybridization analysis was an

efﬁcient procedure in detecting differentially expressed genes.

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Sequences of 163 conﬁrmed DEF s were compared to the GenBank plant protein
database by using BLASTX to target the potential function of these gene fragments.
Predicted functions of the 101 sequences were subdivided into 17 functional
categories, suggesting Atlas fescue responded to drought stress at a comprehensive
molecular regulation level.

Some DEFs discovered in Atlas fescue are novel genes, suggesting Atlas fescue
might apply current unknown mechanism to defense drought stress.

During drought stress treatment in Atlas fescue, more metabolic function and
biogenesis of cellular components in the plant were under degenerative processes, and

the plant system may rescue energy for new gene transcription and stress defense.

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