QTL analysis and
Marker aided selection

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
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 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
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Mapping quantitative trait loci
(QTL)
QTL = underlying genes controlling quantitative traits
• Measured with large error effects resulting
• Result is continuous phenotypic distributions aa AA
Phenotypic value
1 Leibowitz et al., 1987

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
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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)?
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DNA markers can be used to map useful genes using recombination frequencies of linked genes:
A M
QTL a m
Marker
• Markers near QTLs co-segregate with them
• Markers tightly linked to QTL detected by ANOVA
• Most gametes from this F
1
= AM or am. If crossover between marker & QTL, Am & aM gametes will be produced
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Recombination between M and A is R
 In RILs derived from MmAa F
1
, 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
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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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QTL mapping with molecular markers
DNA markers used to map useful genes using recombination frequencies of linked genes:
M
1
A M
2 m
1 a m
2
• Markers near QTLs co-segregate with them
• Markers tightly linked to QTL detected by ANOVA
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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 F
2
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
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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 F
2
-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
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200
Mean of
MM – mm lines (kg/ha)
100
QTL?
QTL mapping strategy: single-marker analysis
QTL?
• ANOVA done for each marker
• QTL declared if t significant
0 20 40 60 80
Map position (cM)
100 120

(taken from Kearsey and Pooni, pp. 137-142)
• 25 RILs produced from an F
1 parents between 2 homzygous
• 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
Is there a QTL in this region?
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P
2
 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 σ
P
2
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 F
2
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
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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
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Measure of marker contribution to σ
P
2
Y = m + G + e
= m + G
(M)
+ M + e
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Broad-sense heritability for a trial in which 1 QTL is detected
H =
σ 2
G
σ 2
P
=
σ 2
G(QTL)
+ σ 2
A
σ 2
G(QTL)
+ σ 2
A
+ (σ 2 e
/r)
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R 2
=
R 2 is the proportion of σ 2
P explained by the QTL A
σ 2
A
σ 2
P
=
σ 2
A
σ 2
G(QTL)
+ σ 2
A
+ (σ 2 e
/r)
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QTL mapping strategy: single-marker analysis
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)
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QTL mapping strategy:
Interval mapping
• 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
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Finding the position of QTL with molecular markers
DNA markers can be used to map useful genes using recombination frequencies of linked genes:
M
1
A M
2 m
1 a m
2
Recombinant gametes: M
1 a, m
1
A,
Parental gametes: M
1
A, m
1 a,
Frequency of recombinants is map distance

• 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)
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Linkage mapping with molecular markers
Double crossover products look like parental types, leading to map distance underestimates:
M
1
A M
2 m
1 a m
2
Haldane and Kosambi mapping functions used to correct recombination frequencies
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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
• 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
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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
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• Main application of gene-tagging is markerassisted 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
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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
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Some guidelines for successful QTL mapping
• 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)
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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
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single-marker analysis & interval mapping)
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• 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
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• 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
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