Chapter 9: Genetic linkage and maps in 					breeding applications
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Chapter 9: Genetic linkage and maps in breeding applications. BSA for finding a linked marker Construction of genetic linkage maps and tagging economically important genes Introgression QTL-analysis. Genetic linkage. 2nd law of Mendel: independent segregation of 2 loci.

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Chapter 9: Genetic linkage and maps in breeding applications

BSA for finding a linked marker

Construction of genetic linkage maps and tagging economically important genes



Genetic linkage applications

2nd law of Mendel: independent segregation of 2 loci.

Is valid for loci on different chromosomes or far apart on the same chromosome.

Two loci closely together are physically and genetically linked, i.e. they segregate together.

Recombination can unlink 2 loci by a cross-over

Genetic linkage applications

  • The recombination frequency depends on the distance on the chromosome.

  • The distance along a genetic map is measured in terms of the frequency of recombination between genetic markers. This is called the genetic distance (different from the genetic distance in Chapter 8).

  • 1 cM (centiMorgan) corresponds to 1 recombinant in 100 (1% recombination).

  • To analyse linkage of genes or markers, a ‘mapping population’ is needed. This is a progeny from a cross between parents that are different enough to have many polymorphisms segregating.

Cross pollinator applications



Genetic linkage

Backcross population




F2 population




Mapping populations


Genetic linkage applications

  • The probability of double recombination (same result for 2 markers as no recombination) is proportional to the square of the recombination distance between two loci.

  • Formulas for the estimation of recombination distance (bv. Kosambi, Haldane) adjust for the possibility of double recombination.

applicationsGenetic linkage

The precision with which genetic distance is measured, is directly related to the number of individuals which is studied (if no recombinants found a sample of 20 progeny plants => recombination fraction = 0; but analyzing 80 additional individuals 1 recombinant can appear => recombination fraction = 1).

Typically a primary genetic map is constructed based on 50-100 individuals, permitting to detect recombination between markers 1-3 cM apart.

If higher precision is required, more individuals should be analysed

applicationsGenetic linkage

Creation of a Linkage map + mapping of the trait

  • The chromosomal location of a ‘phenotype’ or a ‘mutation’ is determined by identifying nearby genetic markers which are co-transmitted from parent to progeny with the phenotype

  • Requires extensive phenotyping and genotyping of many plants of a mapping (=segregating) population

  • Typical experiment: parents and >100 offspring plants + hundreds to thousands of molecular markers

Backcross (F applications1 x recurrent parent) progeny :

3 SSR markers + 1 phenotypic trait

Recurrent parent

Donor parent

F1 hybrid






























 Genetic linkage

Number of recombinants:

AC = 6/20 (1, 3, 10, 13, 18, 19)

AD = 4/20 (1, 3, 10, 13)

CD = 2/20

C = 1/20 (plant number 18)

D = 1/20 (plant number 19)

Adapted from Paterson (1996).

applicationsGenetic linkage

Creation of a Linkage map + mapping of the trait

  • Main disadvantage: large progenies and many DNA-markers are required => time-consuming and expensive

  • For some applications, not necessary to know the location of the trait (or linked marker) on a linkage map

    => Alternative approach developed (Bulk segregant analysis = BSA)

Bulk segregant analysis definition


Bulk Segregant Analysis - Definition

  • Bulk: it makes use of bulked samples

    => saves time and money

  • Segregant: it makes use of a segregating population

    => but it does not require map information!!!

  • Analysis: it screens the whole genome

  • Typical experiment: parents and 2 bulks + hundreds to thousands of molecular markers

Parents applications


Segregating population












  • BSA compares 2 pooled DNA samples of individuals from a segregating population originating from a single cross

  • Within each bulk the individuals are identical for the locus of interest but are arbitrary for all other loci

  • Markers polymorphic between the pools are markers putatively linked to the locus involved in the trait of interest



AA Aa aA Aa Aa AA

aa aa aa aa aa aa

At a locus linked to the trait, using dominant markers

Sample of F2 individuals with recessive phenotype harboring the selected locus:

only the homozygote recessive will be included in this bulk, made using only phenotypic information

Sample of F2 individuals with dominant phenotype harboring the selected locus:

this bulk is made using only phenotypic information and homozygote dominants cannot be distinguished from heterozygotes



BSA applications

In this scheme the resistance (R) gene is linked to an RAPD marker. The susceptible bulk does not have this marker


Bulk Segregant Analysis – How to set-up an experiment

  • Create a segregating population from a single cross (for example, F1 or BC progeny)

  • Phenotype the progeny and identify individuals with extreme trait-phenotypes

  • Construct DNA bulks of the individuals displaying the most extreme trait-phenotypes

  • Genotype the parents and the bulks using hundreds to thousands of DNA-markers

  • Identify those markers which distinguish the bulks and the parents

applicationsBSA example

The first published example of BSA = identification of downy mildew genes in lettuce:

Michelmore et al. (1991) Identification of markers linked to disease-resistance genes by bulked segregant analysis: a rapid method to detect markers in specific genomic regions by using segregating populations.

Proc Nat Acad Sci USA 88: 9828-9832.

BSA applicationsexample

1 2 3 4 5 6 7

Ninh Thuan Phd: molecular mapping of blast resistance genes in a traditional Vietnamese rice cultivar (Chiembac)

1-7 are different AFLP- primer combinations, each time tested on the parents and the bulks

A band from PC6 (primer combination 6) is linked to the resistance

SCAR applications

  • This marker PC6 could be used to select rice plants at the seedling stage for resistance, without the need for an infection test.

  • However, an AFLP or RAPD are not very practical to use for this purpose (AFLP is complex, RAPD not very reproducible). Therefore, these kind of markers are often converted in to a simple PCR marker, called a SCAR sequence characterised amplified region.

  • This is done by sequencing the DNA band and designing 2 primers to amplify a specific region of it that will reveal the polymorphism.

Genetic map applications

  • In some cases it may be interesting to localise markers on a genetic map: for example 2 AFLP markers linked to rice blast resistance were mapped to chromosome 12 with the help of STR markers that were already on the genetic map (the AFLP markers were genetically linked to those STR).

  • Knowing the map position may help in cloning the gene or to search for more closely linked markers in the neighbourhood

Genetic map applications

  • Software to produce linkage maps

    • Joinmap

    • Mapmaker

  • Example of website that collects information on genome and genetic research, including genetic maps: on corn

Example 1 creation of mapping population

applicationsGenetic map

Example: 1. Creation of mapping population

Resistant AB

Susceptible CD

F1 population

(ac; ad; bc; bd)

2 detection of polymorphic loci

SSR markers applications

STS markers (RGA marker)








size std

size std






AFLP markers

RFLP markers

F1 individuals


probe A8

Genetic map

2. detection of polymorphic loci


3 analysis of segregation of markers

applicationsGenetic map

3. Analysis of segregation of markers

applicationsGenetic map

3. Analysis of segregation of markers

4 selection of linkage groups

applicationsGenetic map

4. Selection of linkage groups

5 map construction genetic distances

applicationsGenetic map

5. Map construction – genetic distances

Genetic map applications

Use of Linkage Maps

  • Visualize genomic organisation

  • Fine mapping of genes

  • Map based cloning

  • QTL analysis

  • Comparison of maps

    • Maps of same species

    • Maps of related species (comparative mapping)

Introgression applications

In a backcross it is important to have as much of the recurrent genome as fast as possible to speed up the breeding process (less generation times). Molecular markers can be used to screen for this while selecting for the desirable characteristic of the introgression parent.

In this way 2 BCs + markers will be better than 4 BCs

Introgression applications

Molecular markers are especially interesting to avoid linkage drag : linkage of undesirable characteristics linked to the desired trait. In a first back cross about 300 plants are genotyped to look for a cross-over as close as possible on one side of the desired trait. This plant is then used for the second backcross. In this way 2 back-crosses with molecular analysis are better than 100 random backcrosses.


Frequency distribution


Quantitative trait

  • Multiple genes affect the expression of the trait

  • The expression in the population is a ‘bell-shaped’ curve: there are many genotypes and there are no clear phenotypic differences among them:

If we want to find DNA-markers that can help us to predict this phenotype, we are searching for several genetic loci simultaneously

There exist standard experimental approaches for this (e.g. QTL analysis)


  • A QTLis the location of a gene (or set of genes) that affects a trait that is measured on a quantitative scale. Examples of quantitative traits are plant height or grain yield.

  • These traits are typically affected by more than one gene, and also by the environment

  • Mapping QTL is not as simple as mapping a single gene that affects a qualitative because it involves the simultaneousidentification of the chromosomal locations of all the genetic factors affecting the trait

  • Tools required:

    • Many polymorphic molecular markers ordered in a linkage map

    • Detailed and accurate phenotypic data of the segregating population

    • Appropriate statistical tools

applications QTL

Statistical methods for the detection of QTLs

  • Single marker analysis

    • Tests for differences in the means of the genetic marker classes: for every polymorphic (-/+) marker the mean of all the – plants is compared with the mean of all the + plants. If these means are different, this indicates linkage of the marker to a gene that has an effect on the quantitative trait.

    • Rough estimation of the location of a QTL

applications QTL

Statistical methods for the detection of QTLs

  • Single marker analysis

     Robust to violations of normality in phenotypic data

    • The order of the Marker and the QTL on the genetic map remains unknown

    • Low power if the markers are far apart

    • Large progenies required

    • It is not possible to distinguish between size of a QTL effect and it position (relative to the marker): a marker close to a QTL of small effect will give the same ‘signal’ as a marker some distance from a QTL of large effect

applications QTL

Statistical methods for the detection of QTLs

  • Interval mapping (requires linkage map)

    • Estimates the position of a QTL between two markers

    • Systematically searches the genome by calculating a test statistic at each position of the genome

    • Originally based on the maximum likelihood estimates

    • Intervals between adjacent markers along a chromosome are scanned and the LOD of there being one QTL versus no QTL at a particular point is estimated

    •  and : see further.

QTL applications

  • LOD-score= logarithm ofthe odds =

  • Logarithmprobability together due to linkage

  • probability together due to chance

  • For a good LOD score (>3) it is necessary to have data from a large progeny and many markers.

  • The higher the value of the LOD score, the more likely the data are if there was a QTL present compared to the situation when there is no QTL

QTL applications

  • A LOD-profile is constructed along the chromosome, and the maxima in this profile which exceed a specified significance level, indicate likely sites of a QTL

applications QTL

Statistical methods for the detection of QTLs

  • Interval mapping (requires linkage map)

     • By considering several markers simultaneously, it allows accurate estimation of QTL-positions

    •It is possible to separate the distance and the size of the gene effect

     The effect of other QTLs present in the genome is neglected, and only the QTLs with the biggest phenotypic QTL on a chromosome, estimated positions and effect may be biased

     Multiple QTL mapping (MQM)


QTL with RFLP markers:

QTL with RFLP markers:

QTL with RFLP markers:

Overview different marker applications
Overview different marker applications with RFLP markers:

  • Identification individual/cultivar: multilocus SSR (or AFLP)

  • Analysis relationship:

    • Sequence if between genera or species

    • AFLP within genus or species

    • Multilocus SSR within species

  • Overview genome: AFLP, multilocus SSR or SNP

  • Specific marker for diagnosis or for marker assisted breeding SCAR or SNP-detectie