Download Na concentration (root and shoot) (15%)

QTL Mapping
R. M. Sundaram
QTL (Quantitative Trait Loci)
 Polygenic inheritance, also known as quantitative or
multifactorial inheritance refers to inheritance of a
phenotypic characteristic (trait) that is attributable to two or
more genes and their interaction with the environment
 Unlike monogenic traits, polygenic traits do not follow
patterns of Mendelian inheritance (qualitative traits).
 Instead, their phenotypes typically vary along a continuous
gradient depicted by a bell curve
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QTL individually follow Mendelian rules
 Many genes control any given trait

• Individual gene effects are small
 The genes involved can be dominant, or co-dominant with
respect allelic interaction at a single QTL
 In addition the different QTLs can interact with each other
(additive or epistatic interactions)
What does QTL mean for trait/phenotype ?
Salt tolerance
For eg., A salt tolerant genotype may have
many QTLs controlling salt tolerance like
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1. Survival of seedlings (20%)
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2. Na concentration (root and shoot) (15%)
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3. K concentration (root and shoot) (25%)
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4. Na uptake (10%)
5. K uptake (6%)
6. Na and K ratio (4%)
7. Dry mass (20%)
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Individual component QTLs: Spread across the genome
IR4630 / IR15324 (2001)
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Combinations of QTL for salt tolerance
Low tolerance
Score
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High tolerance
Score
Survival of seedlings (20%)
Na concentration (root and shoot) (15%)
K concentration (root and shoot) (25%)
Na uptake (10%)
K uptake (6%)
Na and K ratio (4%)
Dry mass (20%)
How to identify these QTL?
Steps in QTL mapping
1. Selection of target trait
2. Identification of parents differing in the trait of interest, development of
appropriate mapping population and parental polymorphism survey using
markers
3. Screening the population for the target trait (Phenotyping)
4. Genotyping of the mapping population and development of linkage maps
5. Identification of major QTLs controlling the trait
6. Validation of the major QTLs (with > 15-20% influence on trait phenotype)
across environments/populations
7. Utilization of the major QTLs in breeding programs
Local Linkage maps
Mapping analysis
Based on recombination frequency
i.e. regression between marker genotype and trait phenotype
Single point analysis
– uses one marker at a time
Flanking marker analysis
– uses a pair of markers simultaneously
Composite multipoint mapping
– uses multiple markers simultaneously
Single point analysis – uses one marker at a time
Simple T-test analysis
ANOVA
Linear regression
Multiple regression
Flanking marker analysis – uses a pair of
markers simultaneously
Maximum likelihood
Maximum likelihood estimation through regression
In each method of estimation, a likelihood profile of the
region between two flanking markers is produced.
The log of each likelihood is then mapped against
chromosome position to produce a likelihood map,
Composite multipoint mapping – uses
multiple markers simultaneously
Marker regression
Composite interval mapping
Multiple interval mapping
Standard marker-trait regressions
considered for specific marker intervals
Gene/QTL mapping software
Mapmaker/QTL
Map Manager
QTL cartographer
Qgene
PlabQTL
R QTL
Joinmap
MAP MANAGER QTX
-Windows based
- Simpler
Detection of QTL using Mapmanager QTX
 Detection of a QTL depends on a statistical test
 To detect QTLs, trait values are tested for
statistical association with genotypes of marker
loci in the progeny of a cross
 QTX fits a regression equation for the effect of a
hypothetical QTL at the position of each marker
locus and at regular intervals between the
marker loci
Detection of QTL using Mapmanager QTX
Regression
Free model 
Additive
Recessive
Interval mapping
QTL presence and estimates position in a map
Simple interval mapping – a single QTL without effects
Composite interval mapping – a single QTL with effects on other
QTL
Detection of QTL using Mapmanager QTX
 Likelihood Ratio Statistic (LRS) is a measure of the significance of a
possible QTL like LOD values calculated by other QTL mapping
software.
 LOD score compares the likelihood of obtaining the test data if the two
loci are indeed linked, to the likelihood of observing the same data
purely by chance
 Positive LOD/LRS scores favor the presence of linkage, whereas
negative LOD scores indicate that linkage is less likely
 By convention, a LOD score greater than 3.0 is considered evidence
for linkage
 A LOD score of +3 indicates 1000 to 1 odds that the linkage being
observed did not occur by chance
Likelihood ratio statistic (LRS) and LOD
LRS/4.6 = LOD
73.9/4.6 = 16.1
Detection of QTL using Mapmanager QTX
(Additive/Dominant allelic interaction)

Additive genetic effects consist of the effects of the two alleles
located at a single QTL combined in such a way that the sum of
their effects in unison is equal to the sum of their effects
individually.

Such phenomena are only possible when the alleles involved
do not interact with one another in such a way that would
modify, hinder, or amplify the effects of any one gene involved.

If the average trait value of a heterozygote is midway between
the average trait values of the homozygotes, the QTL alleles are
additive

If the heterozygotic value is the same as one of the
homozygotic values, one allele is recessive and the other is
dominant (Dominant interaction)
Detection of QTL using Mapmanager QTX (Interaction
between different QTLs- Epistasis)

Like Mendelian genes, QTLs do interact with each other and
such interactions can be classified as
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Additive QTL interaction
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Epistatic QTL interaction (masking effect of one QTL on
another)

Additive QTLs are always better than epistatic QTLs since
additive QTLs can easily be combined together
Detection of QTL using Mapmanager QTX
(Mapping population sizes and marker spacing)
 Mapping population size of 250 is enough for unravelling
a major QTL;
But several hundreds are needed for discovering a minor
QTL
Ideal spacing of markers for better QTL detection – 20
cM apart across the genome
Boot strap analysis
Detection of QTL using Mapmanager QTX
(Mapping population sizes and marker spacing)
The p-value that QTX calculates for QTL mapping is
the probability of a ‘false positive’
Recommended p-value = < 0.001
For F2 – minimum LRS is 20 (LOD 4.3)
For BC – minimum LRS is 15 (LOD 3.3)
Interactions between/among the QTLs are also
measured with a model that measures the main effects
of each locus and interactions involving both loci
-Morgan = complete interference
-Haldane = no interference
-Kosambi = intermediate interference (Ideal)
Marker Regression Window of Mapmanager QTX
Stat (LRS/LOD statistic)
The likelihood ratio statistic (LRS) for the association of the trait with this
locus (LRS/4.6 = LOD)
% (Percentage of trait variance explained by a particular QTL)
The amount of the total trait variance which would be explained by a QTL
at this locus, as a percent. For simple regression (no background loci),
this is the difference between the total trait variance and the residual
variance, expressed as a percent of the total variance.
P
The probability of an association this strong happening by chance.
CI (Confidence interval)
An estimate of the size of a 95% confidence interval for a QTL of this
strength, using the estimate of Darvasi and Soller (1997.
Add
The additive regression coefficient for the association.
Dom (intercross only)
The dominance regression coefficient for the association.