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)

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What does QTL mean for trait/phenotype ?

1. Survival of seedlings (20%)

2. Na concentration (root and shoot) (15%)

3. K concentration (root and shoot) (25%)

4. Na uptake (10%)

5. K uptake (6%)

6. Na and K ratio (4%)

7. Dry mass (20%)

Salt tolerance

For eg., A salt tolerant genotype may have many QTLs controlling salt tolerance like 1

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Individual component QTLs: Spread across the genomeIR4630 / IR15324 (2001)

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1. Survival of seedlings (20%)2. Na concentration (root and shoot) (15%)3. K concentration (root and shoot) (25%)4. Na uptake (10%)5. K uptake (6%)6. Na and K ratio (4%)7. Dry mass (20%)

Combinations of QTL for salt tolerance

Low tolerance Score

High tolerance Score

How to identify these QTL?

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

Steps in QTL mapping

Local Linkage maps

Mapping analysisBased 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

Simple T-test analysis

ANOVA

Multiple regression

Linear regression

Single point analysis – uses one marker at a time

Flanking marker analysis – uses a pair of markers simultaneously

Maximum likelihoodMaximum 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,

Marker regression

Composite interval mapping

Standard marker-trait regressions considered for specific marker intervals

Multiple interval mapping

Composite multipoint mapping – uses multiple markers simultaneously

Mapmaker/QTLMap Manager

QTL cartographerQgene

PlabQTLR QTL

Joinmap

MAP MANAGER QTX

- Windows based- Simpler

Gene/QTL mapping software

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 LODLRS/4.6 = LOD73.9/4.6 = 16.1

Detection of QTL using Mapmanager QTX

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 (Additive/Dominant allelic interaction)

Like Mendelian genes, QTLs do interact with each other and

such interactions can be classified as

- Additive QTL interaction

- 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 (Interaction between different QTLs- Epistasis)

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)

Detection of QTL using Mapmanager QTX (Mapping population sizes and marker spacing)

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.

PThe 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.

AddThe additive regression coefficient for the association.Dom (intercross only)The dominance regression coefficient for the association.

Marker Regression Window of Mapmanager QTX

Thank you