Literature DB >> 17277367

Genomewide analysis of epistatic effects for quantitative traits in barley.

Shizhong Xu1, Zhenyu Jia.   

Abstract

The doubled-haploid (DH) barley population (Harrington x TR306) developed by the North American Barley Genome Mapping Project (NABGMP) for QTL mapping consisted of 145 lines and 127 markers covering a total genome length of 1270 cM. These DH lines were evaluated in approximately 25 environments for seven quantitative traits: heading, height, kernel weight, lodging, maturity, test weight, and yield. We applied an empirical Bayes method that simultaneously estimates 127 main effects for all markers and 127(127-1)/2=8001 interaction effects for all marker pairs in a single model. We found that the largest main-effect QTL (single marker) and the largest epistatic effect (single pair of markers) explained approximately 18 and 2.6% of the phenotypic variance, respectively. On average, the sum of all significant main effects and the sum of all significant epistatic effects contributed 35 and 6% of the total phenotypic variance, respectively. Epistasis seems to be negligible for all the seven traits. We also found that whether two loci interact does not depend on whether or not the loci have individual main effects. This invalidates the common practice of epistatic analysis in which epistatic effects are estimated only for pairs of loci of which both have main effects.

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Year:  2007        PMID: 17277367      PMCID: PMC1855123          DOI: 10.1534/genetics.106.066571

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


  23 in total

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Review 6.  QTL-based evidence for the role of epistasis in evolution.

Authors:  Russell L Malmberg; Rodney Mauricio
Journal:  Genet Res       Date:  2005-10       Impact factor: 1.588

7.  An empirical Bayes method for estimating epistatic effects of quantitative trait loci.

Authors:  Shizhong Xu
Journal:  Biometrics       Date:  2007-06       Impact factor: 2.571

8.  Quantitative trait locus (QTL) mapping using different testers and independent population samples in maize reveals low power of QTL detection and large bias in estimates of QTL effects.

Authors:  A E Melchinger; H F Utz; C C Schön
Journal:  Genetics       Date:  1998-05       Impact factor: 4.562

9.  Bayesian mapping of multiple quantitative trait loci from incomplete inbred line cross data.

Authors:  M J Sillanpää; E Arjas
Journal:  Genetics       Date:  1998-03       Impact factor: 4.562

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Authors:  E S Lander; D Botstein
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  48 in total

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Authors:  Crispin M Mutshinda; Mikko J Sillanpää
Journal:  Genetics       Date:  2010-08-30       Impact factor: 4.562

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4.  Functional mapping of quantitative trait loci associated with rice tillering.

Authors:  G F Liu; M Li; J Wen; Y Du; Y-M Zhang
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5.  Association mapping in Populus reveals the interaction between Pto-miR530a and its target Pto-KNAT1.

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6.  Identification of Ug99 stem rust resistance loci in winter wheat germplasm using genome-wide association analysis.

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7.  Inclusive composite interval mapping (ICIM) for digenic epistasis of quantitative traits in biparental populations.

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8.  Hierarchical generalized linear models for multiple quantitative trait locus mapping.

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Journal:  Genetics       Date:  2009-01-12       Impact factor: 4.562

9.  Genetic analysis and major QTL detection for maize kernel size and weight in multi-environments.

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Review 10.  Epistasis--the essential role of gene interactions in the structure and evolution of genetic systems.

Authors:  Patrick C Phillips
Journal:  Nat Rev Genet       Date:  2008-11       Impact factor: 53.242

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