![Linkage disequilibrium (LD)
• Two alleles at different loci that occur together on the same
chromosome (or gamete) more often than would be predicted
by random chance is known as linkage disequilibrium.
• It is a measure of co-segregation of alleles in a population.
• The difference between the coupling and repulsion product is
known as linkage disequilibrium ‘d’[(Ab) x (aB ) - (AB) x (ab) = d ].
• linkage disequilibrium is the basis for detection of linkage
between a gene and a marker](https://image.slidesharecdn.com/random-250704151711-4e7d1f90/85/Linkage-and-Quantitative-trait-locus-4-320.jpg)
Linkage and Quantitative trait locus ....
- 1. LINKAGE AND QTL ANALYSIS
- 2. Linkage • When two genes lie in vicinity of each other on a chromosome they tend to inherit together. • The closer the two genes the more tight will be linkage between them and the more often they will be inherited together. • A marker can be linked with an allele of interest either in coupling or repulsion phase
- 4. Linkage disequilibrium (LD) • Two alleles at different loci that occur together on the same chromosome (or gamete) more often than would be predicted by random chance is known as linkage disequilibrium. • It is a measure of co-segregation of alleles in a population. • The difference between the coupling and repulsion product is known as linkage disequilibrium ‘d’[(Ab) x (aB ) - (AB) x (ab) = d ]. • linkage disequilibrium is the basis for detection of linkage between a gene and a marker
- 5. Establishment of linkage between marker and the trait Mapping populations are required for establishing linkage between molecular marker and the trait of interest. It is prepared by studying segregation of markers in the mapping population and their association with the trait of interest.
- 6. Estimation of linkage distance • Genetic linkage has to be determined essentially either from backcross or F2 segregation data • Linkage has to be established through genetic studies by applying statistical tests. • First step is detection of linkage and second step is estimation of linkage in terms of centimorgan (cM). • significant variation of observed number from the expected number will indicate that the traits (genes) in question are linked.
- 7. Linkage maps • Linkage map is a map of the genes on a chromosome based on linkage analysis. • In terms of molecular markers, it is the relative placement of markers on a chromosome based on genetic linkage study involving a segregating population. • Construction of genetic map can be very interesting as during map construction one can gather data, which is useful in systematic or evolutionary studies.
- 8. Gene mapping • In constructing genetic maps, the amount of information generated depends on three factors: completeness of detection of recombinational events, linkage distance between loci and number of individuals assayed. • Polymorphic parents and more informative markers increase the number of loci that can be mapped
- 9. Quantitative trait loci (QTL) • QTLs are short segments of DNA (locus) that have some contribution towards the phenotypic value of quantitative traits. • Such locus may carry single or group of genes that are tightly linked and mostly inherited together. • Many such loci determine the total phenotypic value of the trait (e.g., yield). Each of these loci are called QTLs.
- 10. Basic steps in QTL analysis 1. Make cross and generate mapping population 2. Identify markers that are polymorphic between the parents 3. Generate marker data 4. Generate linkage maps of molecular markers 5. Collect phenotypic measurements of QTL trait 6. Map QTLs (Association of QTL with marker).
- 11. Cluster analysis • Given a set of varieties each of which belongs to one set of class, the statistical/computational techniques used to place the objects in the class to which they belong is called cluster analysis. • The number or proportion of shared bands is expected to be larger if the two individuals are biologically related. It is, therefore, important to objectively measure the expected degree of similarity due to chance or relatedness.
- 12. Scoring of markers and development of molecular data set Band 1 Band 2 Band 3 Band 4 Plant A 1 0 0 1 Plant B 0 1 0 1 Plant C 1 1 1 0 Plant D 1 1 0 1 Plant E 0 1 0 1 Plant F 1 0 0 1 Plant G 1 0 1 0
- 13. Softwares used for interpreting molecular data • NTSYSpc (Numerical taxonomy and multivariate analysis system) can be used to discover pattern and structure in multivariate data. • neighbour-joining or UPGMA ((Unweighted Pair Group Method with Arithmetic Mean) methods for constructing dendrograms - phylogenetic tree
- 14. Softwares and their application in molecular breeding MAPMANAGER Application Interval mapping, multiple QTL modeling Population F2 backcross, RIL, DH Language Unix QTLSTAT Application Interval mapping using non linear regression Population F2 backcross, RIL, DH Language Unix PGRI Application t-test, conditional t-test, linear regression Population F2 backcross, RIL, DH, F1, OP Language Unix QTL Cartographer Application t-test, Composite Interval mapping, permutation test, bootstrap, jackknife Population F2 backcross, RIL, DH Language Unix/Mac/PC Windows MAPQTL Application Interval mapping, MQM Population F2 backcross, RIL, DH, F1 Language Vax/Unix/Mac/ PC Windows Map Manager QT Application Interval mapping using regression, MQM Population F2 backcross Language MAC OS QGENE Application linear regression Population F2 backcross Language MAC