Author(s):

KLY Tejaswini, PV Ramana Rao and Shashi Bhushan Kumar

Abstract: Most of the traits of interest in plant breeding (e.g., height, yield etc.) are quantitative with continuous (normal) distribution, multifactorial or complex traits. A quantitative trait is a measurable trait that depends on the cumulative action of many genes and their interaction with the environment. A QTL is defined as “A region of the genome that is associated with an affect on a quantitative trait”. A QTL can be a single gene, or it may be a cluster of linked genes that effect the trait. Among all the available markers, AFLP and SSR markers are most commonly used markers in the development of new linkage maps and QTL studies. Use of QTL linkage for identification of a particular trait was first performed by Payne (1918)^[25], where he demonstrated that several of the loci that responded to selection for high scutellar bristle number in <em>Drosophila melanogaster </em>were closely linked to known markers on the first and third chromosomes. Thereafter several QTLs from different crops were identified which includes yield traits, pest and disease resistance traits, quality improvement traits etc., which can be used for improving those crops. Hence one can say that QTLs play a great role in crop improvement. The process of constructing linkage maps and conducting QTL analysis is to identify genomic regions associated with traits which is known as QTL mapping (McCouch &amp; Doerge, 1995). QTL mapping’ is based on the segregation of genes and markers <em>via</em> chromosome recombination (called crossing-over) during meiosis (i.e. sexual reproduction), thus allowing their analysis in the progeny (Paterson, 1996). Although there have been numerous QTL mapping studies for a wide range of traits in diverse crop species, relatively few markers have actually been implemented in plant breeding programs. This is due to lack of adoption is that the markers used have not been reliable in predicting the desired phenotype. New developments and improvements in marker technology, the integration of functional genomics with QTL mapping, and the availability of more high-density maps would greatly affect the accuracy and efficiency of QTL Mapping. It is expected that the development of high resolution maps will also facilitate the isolation of actual genes (rather than markers) via ‘mapbased cloning’ (also ‘positional cloning’)

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