planning breeding programs for impact qtl analysis and marker aided selection
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Planning breeding programs for impact
QTL analysis and
Marker aided selection
IRRI: Planning Breeding Programs for Impact
Marker aided selection and QTL analysis
References: • Kearsey, M.J. and Pooni, H.S. 1996. The genetical
analysis of quantitative traits. Chapter 7
• Bernardo, R. 2002. Breeding for quantitative traits in plants. Chapters 13 and 14
IRRI: Planning Breeding Programs for Impact
A gene or chromosomal region that affects a quantitative trait
Must be polymorphic (have allelic variation) to have an effect in a population
Must be linked to a polymorphic marker allele to be detected
Can anyone describe what a QTL is?
aa AA
Phenotypic value 1Leibowitz et al., 1987
QTL = underlying genes controlling quantitative traits
• Measured with large error effects resulting
• Result is continuous phenotypic distributions
Mapping quantitative trait loci (QTL)
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Example: In progeny derived from cross AA x aa:
•Mean of AA lines is 3100 ± s.e.m
•Mean of aa lines is 2900 ± s.e.m
BUT, AA and aa individuals can’t be visually distinguished
Some AA lines will have low yield due to e’s or other genes
Some aa lines will have high yield due to e’s or other genes
QTL mapping
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Additive effect of a QTL allele = a
Average value of random lines from a cross between AA and aa parents = P
Mean of AA lines is P + a
Mean of aa lines is P – a
From previous example, what is the effect of the QTL (a)?
QTL effect
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DNA markers can be used to map useful genes using recombination frequencies of linked genes:
• Markers near QTLs co-segregate with them
• Markers tightly linked to QTL detected by ANOVA
• Most gametes from this F1 = AM or am. If crossover between marker & QTL, Am & aM gametes will be produced
A
a
M
mQTL Marker
Single-marker analysis
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Recombination between M and A is R
In RILs derived from MmAa F1, individuals with MM marker genotype are made up of 2 QTL genotypes: AA & aa
- If M and A are tightly linked, most = AA
- If M and A are far apart, as many as half = aa
Effect of a marker linked to a QTL
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So, the effect of marker M is a function of:
(i) distance from the QTL
(ii) size of the QTL effect
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• MM lines are easily distinguished from mm lines, but AA lines can’t be distinguished from aa lines
• If M and A are linked, average of MM lines will differ from average of mm lines
• Size of difference can be between 0 and a, depending on marker-QTL distance
• Means of MM and mm recombinant inbred lines
MM = P + a(1-2R)
mm = P – a(1-2R)R = 2r/(1+2r)
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DNA markers used to map useful genes using recombination frequencies of linked genes:
M1 A
m1 a
M2
m2
• Markers near QTLs co-segregate with them
• Markers tightly linked to QTL detected by ANOVA
QTL mapping with molecular markers
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All marker-based mapping experiments have same basic strategy:
1. Select parents that differ for a trait
2. Screen the two parents for polymorphic marker loci
3. Generate recombinant inbred lines (can use F2-derived lines)
4. Phenotype (screen in field)
5. Contrast the mean of the MM and mm lines at every marker locus
6. Declare QTL where (MM-mm) is greatest
QTL mapping strategies
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1. Select parents that differ for a trait
2. Screen the two parents for polymorphic marker loci
3. Generate recombinant inbred lines (can use F2-derived lines)
4. Phenotype (screen in field)
5. Do a separate ANOVA on the effect of each marker
6. Declare QTL where F-test is significant
Single-marker analysis
0 20 40 60 80 100 120
Map position (cM)
Mean of MM – mm lines (kg/ha)
200
100
QTL?QTL?
• ANOVA done for each marker
• QTL declared if t significant
QTL mapping strategy: single-marker analysis
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(taken from Kearsey and Pooni, pp. 137-142)
• 25 RILs produced from an F1 between 2 homzygous parents
• Parents differ at marker loci A, B, and C on 1 chromosome:
A-------------B------------------------------C
19 cM 51 cM
• Lines are evaluated in 4-rep trial
Single-marker analysis: example
Is there a QTL in this region?
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Measure of QTL contribution to σP2
Recall that the simplest QTL model divides the genotypic effect into a QTL effect (A) and an effect of all other genes within QTL classes (G(QTL)):
Y = m + G + e
= m + G(QTL) + A + e
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Measure of marker contribution to σP2
Y = m + G + e
= m + G(M) + M + e
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1. Select parents that differ for a trait
2. Screen the two parents for polymorphic marker loci
3. Generate recombinant inbred lines (can use F2-derived lines)
4. Phenotype (screen in field)
5. Do a separate ANOVA on the effect of each marker
6. Declare QTL where F-test is significant
Single-marker analysis example
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F-test for the difference between marker genotype classes = highly significant at locus B
Therefore, there is a QTL at or near marker B
Single-marker analysis example
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Measure of marker contribution to σP2
Y = m + G + e
= m + G(M) + M + e
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σ2G
σ2P
=H
σ2G(QTL) + σ2
A
σ2G(QTL) + σ2
A + (σ2e /r)
=
Broad-sense heritability for a trial in which 1 QTL is detected
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σ2A
σ2G(QTL) + σ2
A + (σ2e /r)
=
σ2A
σ2P
=R2
R2 is the proportion of σ2P
explained by the QTL A
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Problems with single-marker analysis:
Not very accurate at assigning QTL position because of recombination between marker and QTL
Doing a t-test at every marker results in many false positives (this is a general problem with QTLs)
QTL mapping strategy: single-marker analysis
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• Marker interval = the segment between 2 markers
• Interval mapping methods use information on values of 2 flanking markers to estimate QTL position
• The probability that the data could be obtained assuming a QTL at several positions between the markers is calculated
• QTL = declared where the probability of obtaining the observed data is highest
QTL mapping strategy: Interval mapping
DNA markers can be used to map useful genes using recombination frequencies of linked genes:
M1 A
m1 a
M2
m2
Recombinant gametes: M1a, m1A,
Parental gametes: M1A, m1a,
Frequency of recombinants is map distance
Finding the position of QTL with molecular markers
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• Can’t resolve 2 QTL in a marker interval
• Although the LOD thresholds seem very high, too many QTLs are declared (all methods do)
• Ignores epitasis
• Not accurate for QTL with small effects (no methods are)
What are the problems with interval mapping?
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Double crossover products look like parental types, leading to map distance underestimates:
M1 A
m1 a
M2
m2
Haldane and Kosambi mapping functions used to correct recombination frequencies
Linkage mapping with molecular markers
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• LOD of 2 means that it is 100x more likely that a QTL exists in the interval than that there is no QTL
• LOD of 3 means that it is 1000x more likely
QTL mapping strategy: interval mapping
Significance test:
Logarithm of the odds ratio (LOD score):
probability of the data occurring with a QTL
Odds ratio = probability of the data occurring with no QTL
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• To be useful in breeding applications, gene of interest must be tightly linked to marker
• Ideally, gene itself is used as marker
• Process of “tagging” gene means it must be cloned through:
1. Fine-mapping
2. Assigning to a cloned fragment in a DNA library
3. Sequencing
Fine mapping
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• Main application of gene-tagging is marker-assisted backcrossing of recessive genes
• Permits “pyramiding” of resistance genes with similar phenotypic effects in a screen, e.g Pi1 and Pi2
• Permits rapid recovery of recurrent-parent genome
Marker-assisted backcrossing
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1. QTL mapping = very inaccurate for detecting, localizing, and estimating the effect size of genes with a small effect
2. If repeatability QTL phenotyping experiment = low QTL map very unreliable
3. QTL mapping works very well to find single genes with large effects
4. QTL mapping requires a phenotypic screening system with high H
How is QTL mapping best used?
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Does anyone else have other advice on QTL
usage?
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• Focus on lines that are easy to see in a good screen
• Derive traits where difference between susceptible and resistant mapping populations from crosses between highly resistant and highly susceptible lines
• Use highly reliable screening systems, and that are known to differentiate resistant from susceptible lines
• Do analysis on the means of repeated screens rather than single trials
• Ensure that repeatability of your screen is as high as possible (0.7 or higher)
Some guidelines for successful QTL mapping
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• QTLs with small effects = hard to accurately map
• Only QTLs that are localized to very small chromosome segments can be successfully used in marker-aided backcrossing
• Fine-mapped QTLs with big effects in most genetic backgrounds and most environments are most useful
e.g. disease resistance genes, Sub1
Using QTL in breeding
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Can anyone briefly explain QTL mapping strategy?
(single-marker analysis & interval mapping)
IRRI: Planning Breeding Programs for Impact
• QTL mapping = process of locating genes with effects on quantitative traits using molecular markers
• QTL mapping strategies = based on measuring the mean difference between lines with contrasting marker alleles
• QTL mapping = preliminary step in the discovery of useful genes for marker-aided backcrossing
Summary
IRRI: Planning Breeding Programs for Impact
• So far, only successful with disease resistance and stress tolerance genes having very large effects
• QTL mapping = basic research activity requiring careful planning of crosses and high-precision phenotyping
Summary