2008Unpublished venueRequires access

Methods of bioinformatic analysis for candidate genes underlying quantitative trait loci(QTLs)

Xusheng Wang

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Abstract

Almost all crops have been studied on QTL(quantitative trait loci) mapping with many QTL mapping methods,such as IM(interval mapping),CIM(composite interval mapping),MCIM(mixed-model based composite interval mapping) and Bayesian QTL mapping having been developed.However,these methods have had shortcomings,namey,the genomic region of the QTL detected,within which there were probably hundreds of candidate genes was still too large.In this paper,a better understanding of the molecular functions of QTLs was obtained by first briefly reviewing methods of analyzing the candidate gene within QTL intervals based on bioinformatics.Then,in order to provide a new analytical method for better use of QTLs in the future,the genetics,genome organization,gene expression and function of candidate genes located on QTL region were analyzed.

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What this paper is about

Almost all crops have been studied on QTL(quantitative trait loci) mapping with many QTL mapping methods,such as IM(interval mapping),CIM(composite interval mapping),MCIM(mixed-model based composite interval mapping) and Bayesian QTL mapping having been developed.However,these methods have had shortcomings,namey,the genomic region of the QTL detected,within which there were probably hundreds of candidate genes was still too large.In this paper,a better understanding of the molecular functions of QTLs was obtained by first briefly reviewing methods of analyzing the candidate gene within QTL intervals based on bioinformatics.Then,in order to provide a new analytical method for better use of QTLs in the future,the genetics,genome organization,gene expression and function of candidate genes located on QTL region were analyzed.

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Available abstract

Almost all crops have been studied on QTL(quantitative trait loci) mapping with many QTL mapping methods,such as IM(interval mapping),CIM(composite interval mapping),MCIM(mixed-model based composite interval mapping) and Bayesian QTL mapping having been developed.However,these methods have had shortcomings,namey,the genomic region of the QTL detected,within which there were probably hundreds of candidate genes was still too large.In this paper,a better understanding of the molecular functions of QTLs was obtained by first briefly reviewing methods of analyzing the candidate gene within QTL intervals based on bioinformatics.Then,in order to provide a new analytical method for better use of QTLs in the future,the genetics,genome organization,gene expression and function of candidate genes located on QTL region were analyzed.

Key concepts: Quantitative trait locus, Family-based QTL mapping, Candidate gene, Inclusive composite interval mapping, Biology, Genetics, Gene, Computational biology

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