Molecular breeding

1. What is QTL?

QTL = a gene or chromosomal region that affects a quantitative trait.

It must be polymorphic (have allelic variation) to have an effect in a population and it must be linked to a polymorphic marker allele to be detected

2. Mapping quantitative trait loci (QTL)

QTL = underlying genes controlling quantitative traits

• Measured with large error effects resulting

• Result is continuous phenotypic distributions

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

3. The QTL effect

• The 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

4. Single-marker analysis

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

5. Effect of a marker linked to a QTL

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 are AA

• If M and A are far apart, as many as half are aa

-->So, the effect of marker M is a function of:

1. distance from the QTL

2. size of the QTL effect

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 the average of mm lines. The size of difference can be between 0 and a, depending on the marker-QTL distance

Means of MM and mm  recombinant inbred lines

6. QTL mapping with molecular markers

DNA markers 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

7. QTL mapping strategies

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

7.1 QTL mapping strategies: Single-marker analysis

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

example:

25 RILs produced from an F1 between 2 homzygous parents

Parents differ at marker loci A, B, and C on 1 chromosome:

Lines are  evaluated in 4-rep trial  

--> Is there a QTL in this region?

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)):

Measure of marker contribution to σP2

F-test for the difference between marker genotype classes

is highly significant at locus B

Therefore, there is a QTL at or near marker B

Broad-sense heritability for a trial in which 1 QTL is detected

R2 is the proportion of σP2 explained by the QTL A

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)

7.2 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

Finding the position of QTL with molecular markers

DNA markers can be used to map useful genes using recombination frequencies of linked genes:

Recombinant gametes: M1a, m1A,

Parental gametes:     M1A, m1a,

Frequency of recombinants is map distance

What are the problems with interval mapping?

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)

Linkage mapping with molecular markers

Double crossover products look like parental types, leading to map distance underestimates:

Haldane and Kosambi mapping functions used to correct recombination frequencies

Significance test:

Logarithm of the odds ratio (LOD score):

• 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

8. Fine mapping

• 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

9. Marker-assisted backcrossing

• 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

10. How is QTL mapping best used?

• QTL mapping = very inaccurate for detecting, localizing, and estimating the effect size of genes with a small effect

• If repeatability QTL phenotyping experiment = low QTL map very unreliable

• QTL mapping works very well to find single genes with large effects

• QTL mapping requires a phenotypic screening system with high H

11. 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)

12. Using QTL in breeding

• 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

Let's conclude

Summary

• 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

• 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

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