Germplasm-regression-combined marker-trait association identification in plants
Author(s) -
Chengjiang Ruan
Publication year - 2010
Publication title -
african journal of biotechnology
Language(s) - English
Resource type - Journals
ISSN - 1684-5315
DOI - 10.5897/ajb09.001
Subject(s) - germplasm , quantitative trait locus , biology , trait , identification (biology) , family based qtl mapping , association mapping , marker assisted selection , genetic marker , selection (genetic algorithm) , linkage (software) , molecular marker , genetic association , genetic linkage , genetics , microbiology and biotechnology , gene mapping , single nucleotide polymorphism , genotype , botany , computer science , artificial intelligence , gene , chromosome , programming language
In the past 20 years, the major effort in plant breeding has changed from quantitative to molecular genetics with emphasis on quantitative trait loci (QTL) identification and marker assisted selection (MAS). However, results have been modest. This has been due to several factors including absence of tight linkage QTL, non-availability of mapping populations and lack of substantial time needed to develop such populations. To overcome these limitations and as an alternative to planned populations, molecular marker- trait associations have been identified by the combination between germplasm and the regression technique. In the present preview, we first surveyed the successful applications of germplasm-regression-combined (GRC) molecular marker-trait association identification in plants; secondly, we described how to do the GRC analysis and its differences from mapping QTL based on a linkage map reconstructed from the planned populations; thirdly, we considered the factors that affect the GRC association identification, including selections of optimal germplasm and molecular markers and testing of identification efficiency of markers associated with traits; and finally we discussed the future prospects of GRC marker-trait association analysis used in plant MAS/QTL breeding programs, especially in long-juvenile woody plants when no other genetic information such as linkage maps and Quantitative Trait Loci are available.
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