M. Talajoor
Suppression of Rust Resistance in Wheat
A virulent (top) and avirulent (bottom) race of
stem rust on the cultivar Chinese Spring
Mina Talajoor
Department of Plant Sciences & Plant Pathology
Montana State University
Fall 2011
PI: Li Huang
Project Duration: 2 Years
Total Budget Amount: $71,600
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M. Talajoor
Project Summary
This project investigates the suppression of rust resistance genes in wheat. We aim
to characterize the specificity of a stem rust-resistance gene suppressor in the
cultivar Canthatch that has been previously located to 7DL. Our objectives include
validating its previously claimed specificity for stem rust-resistance genes, as well as
determining a pattern of suppression related to genome or chromosome location.
Our ability to delineate the mode of action of the Canthatch suppressor will give
researchers the potential to “unlock” genes already present in the genetic
background of wheat.
Introduction
Wheat rusts (Puccinia spp.), including leaf, stem, and stripe rust, are fungal
pathogens that cause billions of dollars in losses worldwide each year. Many
developing countries rely on bread wheat (Triticum aestevum L.) as a staple food,
but the use of foliar fungicides is not an economic reality. Therefore, an important
strategy to protect wheat from rust diseases is resistance breeding (Caldwell, 1968).
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Bread wheat is a hexaploid species (2n=6x=42). It consists of three genomes, A, B,
and D, which it inherited from its diploid progenitors during two separate
hybridization events. The genomes of the donor species are compatible with wheat
and provide a great genetic resource for breeding (Feuillet et al., 2008, Johal et al.,
2008). While this strategy has been used successfully, breeders sometimes
encounter problems when attempting to introduce a new resistance gene. Once
crossed into a cultivar, some genes don’t express resistance as predicted. This
phenomenon has stumped many breeders, and it unfortunately hinders their ability
to take advantage of the abundance of rust resistance genes within the ancestors’
gene pools.
Agricultural practices are commonly subject to devastating diseases and crop loss.
As motivation to find more durable, cost-efficient alternatives increases, interest in
finding a way to “unlock” resistance genes within wheat also increases.
My research will focus on one particular case of suppression of resistance that was
observed in the spring wheat cultivar Canthatch. A gene on the long arm of
chromosome 7D suppresses resistance conferred by several stem rust resistance
genes. When the suppressor was deactivated through mutagenesis, resistance to
stem rust was restored. The genes suppressed in Canthatch (Table 1) are all located
on either the A or B genome.
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Table 1. Stem rust genes suppressed by gene on 7DL in Canthatch.
Four stem rust genes are suppressed by a gene on 7DL in Canthatch (Kerber & Green,
1980).
We will further investigate the specificity of the Canthatch suppressor, as it
presumably suppresses stem rust resistance genes. More specifically, we have two
main objectives:
Objective 1: To determine if the suspected stem-rust specificity is truly a genetic
characteristic, or simply a result of the absence of any leaf rust or stripe rust
resistance genes in the Canthatch background.
Objective 2: To identify patterns of suppression related to genomes or chromosome
locations.
By understanding the specificity of the suppressors, we can more competently
strategize our approaches to breed for genetic resistance wheat.
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Literature Review
Cross breeding wheat enables breeders to introduce new resistance genes into the
background of traditionally susceptible cultivars. Occasionally when breeders cross
rust resistance genes into a cultivar, resistance is not expressed. This apparent
suppression of stem rust resistance was noted in the spring wheat cultivar
Canthatch. Kerber and Green investigated the suppression to begin to characterize
this quandary (1980). TetraCanthatch, a tetraploid (2n=28=AABB), was noticed
having increased resistance to stem rust races compared to its hexaploid counterpart
Canthatch (2n=42=AABBDD). The removal of the D genome somehow relieved
suppression of stem rust resistance. To narrow their target gene(s), Kerber and
Green tested Canthatch nullisomic for each of the 7 chromosomes. Canthatch
nullisomic 7D (lacking the 7D chromosomes) showed enhanced resistance to stem
rust. Furthermore, Canthatch ditelosomic 7DS (the long arm of 7D is absent)
showed an increase of stem rust resistance. Conversely, Canthatch ditelosomic 7DL
(the short arm of 7D is absent), showed susceptibility to stem rust similar to
Canthatch. Therefore, Kerber and Green determined that a gene(s) on 7DL was
responsible for suppression of stem rust resistance.
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Serious inquiry into the Canthatch suppressor was not pursued until over 20 years
later. In 1991, Kerber published a paper about Canthatch treated with the mutagen
ethane methyl sulfonate (EMS) and induced a mutation on 7DL that showed an
enhance resistance to stem rust races that are virulent on wild type Canthatch
(Figure 1). The inactivation of the suppressor supposedly did not seem to provide
an increased level of resistance to leaf or stripe rust.
Though no accounts of suppression of resistance to leaf or stripe rust are
documented, the evidence is inconclusive. There is limited mention of testing for
resistance to leaf or stripe rust in Canthatch and it’s subsequent genetic variants.
Unfortunately the rust races used in Kerber and Green’s study cannot easily be
tracked since a standardized system for rust isolate nomenclature had not yet been
developed. It is possible that, to begin with, Canthatch did not have a gene in its
background that conferred resistance to races of leaf and stripe rust. So, even if the
suppressor was deactivated, there was no resistance gene present to be expressed.
Therefore, further inquiry into the specificity of resistance genes that are suppressed
would provide us with incredibly valuable information.
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4
5
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Figure 1. Seedling wheat leaves infected with stem rust. The same rust isolate has differing
virulence on cultivars. 1-Canthatch shows moderate susceptibility to the stem rust isolate;
2-mutant Canthatch shows increased resistance; 3-6 –controls from left to right: Chinese
Spring, Thatcher, Marquillo, Morocco.
(Image courtesy of Peng Zhang)
Approaches
Objective 1: Determine the specificity of the Canthatch suppressor.
To investigate whether or not the Canthatch 7D suppressor is specific to Sr genes,
we will cross Canthatch with cultivars carrying Lr or Yr genes located on the same
chromosomes of the stem rust resistance genes suppressed by the suppressor (Table
2).
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Table 2. Leaf, stem, and stripe rust resistance genes whose genome location is known to be
on chromosome 4A, 2B, or 3B.
Objective 2: Identify patterns of suppression related to genomes or chromosome
locations.
I will introduce several resistance genes for the three rusts that are on homeologous
chromosomes of the different genomes as the genes previously shown to be
suppressed in Canthatch (Table 3).
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Table 3. Resistance genes to be used in the study.
Resistance genes shown in bold have been shown to be suppressed (Kerber & Green, 1979).
Resistance genes on different chromosomes or genomes will be used in an attempt to
identify a pattern of suppression associated with location in the genome.
Other suppressors of rust resistance genes have been discovered, particularly in the
D genome (Bai & Knott, 1992). As such, if we observe suppression of resistance in
the cross, we cannot be sure that it is because of our suppressor and not another
suppressor in the background. To account for this unknown, we will perform control
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crosses with a mutant of Canthatch, mNS1Can. This mutant line has a non-functional
copy of the suppressor on 7DL. For each resistance gene that we cross with
Canthatch, we will also cross it with mNS1Can. If any of the crosses suggest that
resistance has been suppressed in Canthatch (a susceptible F1), then we will then
inoculate the F1 seedlings of the mutant cross. A susceptible seedling infection type
would suggest that resistance is suppressed by a different gene in the background,
since our suppressor of interest has been knocked out. A resistant seedling
infection type would suggest that our gene is responsible, and that loss of resistance
is dependent on a functional copy of the gene on 7DL.
For each crossing pair, reciprocal crosses will be made. This will account for any
cytosolic effects that may play a role. At least two crossing events will be made per
cross, either by two different people or by one person on different days. This will
reduce human error such as misread labels, contaminated crossing equipment, etc.
To determine if the resistance genes are suppressed by the Canthatch suppressor,
we will inoculate 20 F1 seedlings from each of the crosses that were made. We will
use a race of rust that is virulent on Canthatch but avirulent on the resistance gene.
Canthatch and the resistant parent will be included as controls.
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Measurement Methods
We will use the Stakeman scale to quantify infection type (IT) (Figure 2). If all of the
F1 seedlings show an infection type similar to that of the resistant parent, it would
suggest that the resistance gene is not being suppressed and is conferring rust
resistance in the seedlings. If all of the F1 seeds show an IT similar to that of
Canthatch, it would suggest that the resistance gene has been suppressed.
Figure2. Stakeman infection type scale (Roelfs, A. & Singh, R. 1992.)
Statistical Methods
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We will be observing the infection type of F1 progeny created from two parents
homozygous for resistance and suppression (See Appendix A). Because we are
investigating the specificity of a suppressor in the progeny with one copy of each
gene (rust resistance and suppressor), we expect all of the progeny to segregate
together –either all resistant or all susceptible. If this is not the case, we will analyze
our observed segregation ratio for goodness of fit with one and two-gene
segregations (See Appendix B).
Adequacy of Design
The cultivars being used in this study will come from multiple sources. Even though
we expect the parent seeds to be homozygous, it is important to verify that all of
the parents are homozygous for resistance and show the expected infection type.
The ability to detect segregation increases with the number of seedlings tested
(Figure 3). We will plant 20 parent seeds to screen and, accounting for nongerminating seeds, aim to record the IT of at least 16 seedlings. Since all the
resistance genes in our study are dominant, the most likely segregation we will see
is 3:1, where one quarter of the population is recessive (susceptible). The probability
of failing to detect segregation with 16 individuals is less than 1% (See Appendix C).
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Probability
M. Talajoor
# Seedlings
Figure 3. Probability of failing to detect a recessive phenotype in a 3:1 segregating
population. As the number of seedlings increases, the probability of missing a susceptible
seedling decreases.
The limiting factor of this experiment is the ability to distinguish between a
susceptible and resistant reaction in the F1 progeny. This underscores the
importance of selecting an appropriate race of rust by screening the parents. The
larger the difference in infection type between the two parents, the more clearly we
can assess IT in the F1. For example, if we choose a race of rust that gives the R
gene an IT of ; and Canthatch an IT of 4, we increase our chances of detecting
suppression of rust resistance in the progeny. Even if the F1 seedlings show a
moderately resistant IT of 2, we can infer that the expression of the resistance gene
is being suppressed.
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(Please refer to Appendix D for a flowchart overview of the experimental design.)
Timetable
Fall
Spring
Summer
Fall
Spring
Cross wheat
Cross wheat
Cross wheat
Apply for rust
acquisition
permit
Screen parents
to find
compatible
rust race
Screen
seedlings for IT
Collect results
for analysis
Budget
Personnel
Yearly
Total
Primary Researcher
20,000
40,000
Assistant Researcher
13,500
27,000
Equipment
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Greenhouse Rental
2,000
4,000
Crossing Equipment
100
200
Chemical Applications
200
400
$35,800
$71,600
Supplies & Services
Total
Qualifications
BIOO433- Plant Physiology
VTMB505- Eukaryotic Gene Regulation
BIOE424- Ecology of Fungi
PSPP516- Research Design and Analysis
Literature Cited
Bai, D., Knott, D.R. 1992. Suppression of rust resistance in bread wheat (Triticum
aestivum L.) by D-genome chromosomes. Genome. 35(2): 276-282.
Caldwell, R.M. 1968. Breding for general and/or specific plant disease resistance.
Proceedings of the third International Wheat Genetics Symposium.
Feuillet, C., Langridge, P. & Waugh, R. 2008. Cereal breeding takes a walk on the
wild side. Trends in Genetics 24, 24–32.
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Johal, G.S., Balint-Kurti, P. & Weil, C.F. 2008. Mining and Harnessing Natural
Variation: A Little MAGIC. Crop Science. 48, 2066.
Kerber, E.R. 1991. Stem rust resistance in Canthatch hexaploid wheat induced by a
nonsuppressor mutation on chromosome 7DL. Genome. 34:935-939.
Kerber, E.R., and Green, G.J. 1980. Suppression of stem rust resistance in the
hexaploid wheat cv. Canthatch by chromosome 7DL. Can. J. Botany.
58(12):1347-1350.
McIntosh, R.A., C.R. Wellings, and R.F. Park. 1995. Wheat rusts: an atlas of resistance
genes. Kluwer Academic Publishers, Boston.
Roelfs, A. & Singh, R. 1992. Rust diseases of wheat: Concepts and methods of
disease management.
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Appendix A:
Sample IT scoring with summary table for one cross (Canthatch crossed with Stem
Rust resistance gene 31). The cross consists of three replications. Parents of the
cross serve as controls for differences in environmental conditions. Variability in IT
within groups is expected to be minimal.
IT Summary Table of above cross.
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Appendix B:
R-code for one and two gene segregation analysis
##########################################################
# Segregation Analysis
# Test Segregation Ratios of resistant and susceptible individuals
# Null hypothesis is that the observed and expected are the same. If we fail to reject H0 (if p>.05)
# then our observed fits into that ratio
##############################################################
# Fill in the number of observed for each category
R <- 16
# number of resistant individuals observed
S <- 4
# number of susceptible individuals observed
###########################
# This conditional organizes the values so the largest number is associated with the larges proportion
########################
if(R>S) {
RtoSratio <- c(R,S) }
if(R<S) {
RtoSratio <- c(S,R) }
#### 3:1 Ratio #####
threetoone <- c(3/4,1/4)
print("3:1 Ratio Analysis p-value")
results <- chisq.test(RtoSratio,p=threetoone)
threetoone <- results$p.value
print(threetoone)
##### 9:3:3:1 Ratio #########
#The two possible ratios for two-gene segregation that we can observe are
# 15:1
fifteentoone <- c(15/16,1/16)p
print("15:1 Ratio Analysis p-value")
results <- chisq.test(RtoSratio,p=fifteentoone)
fifteentoone <- results$p.value
print(fifteentoone)
# 9:7
ninetoseven <- c(9/16,7/16)
print("9:7 Ratio Analysis p-value")
results <- chisq.test(RtoSratio,p=ninetoseven)
ninetoseven <- results$p.value
print(ninetoseven)
print("NOTE:If sample size is <95, we are unable to confidently distinguish between 9:7 & 3:1 segregation")
###################
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# Predicting most likely gene segregation ratio based on p-value
###################
pvalues <- c(threetoone,fifteentoone,ninetoseven) # load all of the p-values in one vector
phighest <- which.max(pvalues)
# find the max p-value
print("Segregation Ratio Most Likely Seen:")
if(phighest==1) print("3:1")
if(phighest==2) print("15:1")
if(phighest==3) print("9:7")
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Appendix C:
R-code to assist in determining how many individuals to screen
############################
# Bootstrap Analysis to determine optimal number of seedlings to include to
# detect a recessive phenotype in a 3:1 ratio
# The outer loop steps through numbers of seedlings to include from 1 to n seedlings
# while the inner loop calculates the average probability of failing to detect the recessive phenotype
# at each n
##################################
rm(list=ls()) #clear workspace
set.seed(1) #set the seed
ntr <- 1000
#number of trials
#### define the parameters of the bionomial to be used in our loop #####
n <- 50 #number of seedlings that are inoculated
N <- 1000 #number of replications
######### Create the outer loop to incrementally step through number of seedlings included in a
screen##########
pprec <- vector(mode="numeric", length=n)
# store the results from each sample size in vector pprec
for(j in 1:n) {
##### create a vector for probability of finding recessive individuals in the screening #####
prec <- vector(mode='numeric', length=ntr) # store the results within a given sample size in vector prec
########create a loop to sample from a binomial population with a 3:1 gene-segregation ratio###########
### where 75% of the population shows the dominant phenotype and 25% shows the recessive phenotype
#####
for(i in 1:ntr) {
rec <- rbinom(N, j, .25)
# rec stores the number of recessives detected in each j-seedling screen
sumrec <- sum(rec==0)
# tally up how many times a set of screenings fails to detect any recessives
prec[i] <-sumrec/N
# calculate the probability of missing a recessive in the screen
}
pprec[j] <- mean(prec)
}
p <- plot(pprec)
print(p)
#plot the probability of missing a recessive in a screen at various n-individuals screened
# h <- hist(prec)
# print(h)
# print("probability of missing a recessive in a screen:")
# print(mean(prec))
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Appendix D:
Flowchart of Experimental Design. The flowchart is organized in a logical fashion,
and doesn’t necessarily correlate with the chronological order.
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