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Home >> Plant Biotechnology and Genomics >>Construction of Molecular Maps and Synteny (Collinearity) >>Identification and Mapping of Quantitative Trait Loci (QTLs) using Molecular Markers
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Identification and mapping of quantitative trait loci (QTLs) using molecular markers
Many quantitative traits of economic value are under polygenic control and are selected for, directly. Such a selection is often ineffective, since the effect of each gene is small, which is also influenced by the environment. Therefore, one would welcome a procedure for indirect selection, which is not influenced by the environment. For this purpose, linkage between genes for quantitative traits and marker loci should be known. Such markers involving morphological traits have been identified and mapped in Drosophila and in several crop plants. Isozyme marker loci linked to quantitative traits of economic value had also been earlier identified in tomato and maize. Initially, RFLPs were extensively used in a variety of crop plants to identify and map quantitative trait loci (QTLs). More recently (1995-2002), SSR and AFLPs became the markers of choice and were widely used. In future, SNPs will also be used in many crops.
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For the study of marker-trait association, the experimental procedures differ for self pollinated and cross pollinated species, although with the availability of inbred lines in cross pollinated species, similar methods can be used in the two cases. In self pollinated genotypes and among inbred lines (in cross pollinated species), parents are first selected which differ for a number of markers as well as for mean values of the quantitative traits. Once such parental lines are selected, they are crossed and F2 plants are derived. In the F2 population, a chromosomal segment representing linkage between a molecular marker and a QTL will be present in the background of random genetic variation due to independent assortment and recombination.
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By growing samples of F2 population in different environments, one may also study the linkage under different environments. In these cases if mean values of a particular quantitative trait are determined in two groups of plants representing alternative alleles of a molecular marker, a significant difference in means (of two groups) for quantitative trait will indicate marker- QTL linkage. The observed marker associated difference in quantitative trait value will be a function of allelic effects at the QTL. Map distance between the marker and a QTL can also be determined.
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In results of an initial experiment are shown where in tomato, linkage is evident between one of the two molecular markers (A1 A2) and a QTL for high soluble solids in the fruits. Two lines (cultivars VF 36 and its near isogenic line LA 1563) used in the cross had molecular markers (RFLPs) that identified L. esculentum (~5% soluble solids) and L. chmielewskii (~10% soluble solids), and also differed significantly for soluble solids (~5% and 7-8%).
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The data on soluble solids content (mean per cent values) and two RFLPs in an F2
{F2 was derived from a cross between a tomato cultivar (~5% soluble solids) and its near isogenic line (NIL) carrying a QTL for high (7-8%) soluble solids derived from L. chmielewskii with 10% soluble solids; data from Osborn et al., 1987.
| RFLP locus |
% Soluble solids |
RFLP allele e/e (L. esculentum) |
RFLP allele c/c (L. chmielewskii) |
A1 |
5.82 |
6.24 |
A2 |
5.93 |
5.96 |
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In F2, allele c of the marker A1 showed association with the QTL for high mean value of soluble solids, while the allele e of A1 and both the alleles of A2 did not, suggesting that this QTL is found in the vicinity of A1. RFLPs, associated with the expression of complex traits like insect resistance and WUE, i.e. water use efficiency, were also identified
and mapped in tomato. Subsequently, thousands of such marker-trait associations were reported in a number of crops. For instance, about one hundred such associations have been reported each in wheat and rice. In the experiments like the above, if parents differ for a sufficient number of molecular markers, which are spaced out throughout the genome, a single cross can allow identification and mapping of all those QTLs for which the parents differ.
New analytical methods for the analysis of quantitative trait loci in plants using mapped molecular markers were later suggested. These new methods included maximum likelihood or regression method for interval mapping which was earlier used in humans. Interval mapping assesses the effects of small genome segments (each~2cM), located between a pair of marker loci, rather than the effect of a QTL associated with a single RFLP. This provides greater precision. Lod scores (log of the score of odds for the presence of a linkage against the odds of not having this linkage, e.g. if the score is 100: 1 in favour of linkage, the lod score is 2) are also used in this method to reduce the probability of false positives for linkage (detecting linkage, when it is actually absent). The results are depicted as QTL likelihood maps. The technique of interval mapping allowed the QTLs to be mapped to intervals of 20 cM which was a poor resolution. Therefore the technique of interval mapping was supplemented through the use of substitution mapping using selected overlapping recombinant chromosomes. This technique is analogous to the use of overlapping deletions and allowed fine mapping of QTLs. The method has been successfully used for a study of tomato fruit characters, including mass per fruit; soluble solid concentration and fruit pH. The QTLs for these characters were mapped at intervals, as small as 3 cM.
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