Literature DB >> 24196145

Bayesian analysis of linkage between genetic markers and quantitative trait loci. I. Prior knowledge.

I Hoeschele1, P M Vanraden.   

Abstract

Prior information on gene effects at individual quantitative trait loci (QTL) and on recombination rates between marker loci and QTL is derived. The prior distribution of QTL gene effects is assumed to be exponential with major effects less likely than minor ones. The prior probability of linkage between a marker and another single locus is a function of the number and length of chromosomes, and of the map function relating recombination rate to genetic distance among loci. The prior probability of linkage between a marker locus and a quantitative trait depends additionally on the number of detectable QTL, which may be determined from total additive genetic variance and minimum detectable QTL effect. The use of this prior information should improve linkage tests and estimates of QTL effects.

Year:  1993        PMID: 24196145     DOI: 10.1007/BF00215034

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  22 in total

1.  Assessing the effect of multiple linkage tests in complex diseases.

Authors:  F Clerget-Darpoux; M C Babron; C Bonaïti-Pellié
Journal:  Genet Epidemiol       Date:  1990       Impact factor: 2.135

2.  An analytical model for the estimation of chromosome substitution effects in the offspring of individuals heterozygous at a segregating marker locus.

Authors:  M R Dentine; C M Cowan
Journal:  Theor Appl Genet       Date:  1990-06       Impact factor: 5.699

3.  Quantitative genetic variance associated with chromosomal markers in segregating populations.

Authors:  J C Dekkers; M R Dentine
Journal:  Theor Appl Genet       Date:  1991-02       Impact factor: 5.699

4.  Mapping mendelian factors underlying quantitative traits using RFLP linkage maps.

Authors:  E S Lander; D Botstein
Journal:  Genetics       Date:  1989-01       Impact factor: 4.562

5.  The Isolation of Polygenic Factors Controlling Bristle Score in Drosophila Melanogaster. II. Distribution of Third Chromosome Bristle Effects within Chromosome Sections.

Authors:  A E Shrimpton; A Robertson
Journal:  Genetics       Date:  1988-03       Impact factor: 4.562

6.  Mendelian factors underlying quantitative traits in tomato: comparison across species, generations, and environments.

Authors:  A H Paterson; S Damon; J D Hewitt; D Zamir; H D Rabinowitch; S E Lincoln; E S Lander; S D Tanksley
Journal:  Genetics       Date:  1991-01       Impact factor: 4.562

7.  Regular responses to selection. 3. Interaction between located polygenes.

Authors:  S G Spickett; J M Thoday
Journal:  Genet Res       Date:  1966-02       Impact factor: 1.588

8.  Power of daughter and granddaughter designs for determining linkage between marker loci and quantitative trait loci in dairy cattle.

Authors:  J I Weller; Y Kashi; M Soller
Journal:  J Dairy Sci       Date:  1990-09       Impact factor: 4.034

9.  Association of genetic defects with yield and type traits: the weaver locus effect on yield.

Authors:  I Hoeschele; T R Meinert
Journal:  J Dairy Sci       Date:  1990-09       Impact factor: 4.034

10.  The use of map functions in multipoint mapping.

Authors:  L Pascoe; N E Morton
Journal:  Am J Hum Genet       Date:  1987-02       Impact factor: 11.025

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  10 in total

1.  Mapping of epistatic quantitative trait loci in four-way crosses.

Authors:  Xiao-Hong He; Hongde Qin; Zhongli Hu; Tianzhen Zhang; Yuan-Ming Zhang
Journal:  Theor Appl Genet       Date:  2010-09-09       Impact factor: 5.699

2.  Multiple-interval mapping for ordinal traits.

Authors:  Jian Li; Shengchu Wang; Zhao-Bang Zeng
Journal:  Genetics       Date:  2006-04-03       Impact factor: 4.562

3.  Mapping quantitative trait loci for expression abundance.

Authors:  Zhenyu Jia; Shizhong Xu
Journal:  Genetics       Date:  2007-03-04       Impact factor: 4.562

4.  Bayesian mapping of quantitative trait loci for multiple complex traits with the use of variance components.

Authors:  Jianfeng Liu; Yongjun Liu; Xiaogang Liu; Hong-Wen Deng
Journal:  Am J Hum Genet       Date:  2007-07-03       Impact factor: 11.025

5.  A Monte Carlo method for Bayesian analysis of linkage between single markers and quantitative trait loci. I. Methodology.

Authors:  G Thaller; I Hoeschele
Journal:  Theor Appl Genet       Date:  1996-11       Impact factor: 5.699

6.  A Monte Carlo method for Bayesian analysis of linkage between single markers and quantitative trait loci. II. A simulation study.

Authors:  G Thaller; I Hoeschele
Journal:  Theor Appl Genet       Date:  1996-11       Impact factor: 5.699

7.  Bayesian analysis of linkage between genetic markers and quantitative trait loci. II. Combining prior knowledge with experimental evidence.

Authors:  I Hoeschele; P M Vanraden
Journal:  Theor Appl Genet       Date:  1993-02       Impact factor: 5.699

8.  Efficiency of direct selection on quantitative trait loci for a two-trait breeding objective.

Authors:  G J de Koning; J I Weller
Journal:  Theor Appl Genet       Date:  1994-08       Impact factor: 5.699

9.  Identification of Quantitative Trait Loci Conditioning the Main Biomass Yield Components and Resistance to Melampsora spp. in Salix viminalis × Salix schwerinii Hybrids.

Authors:  Paweł Sulima; Jerzy A Przyborowski; Anna Kuszewska; Dariusz Załuski; Małgorzata Jędryczka; Witold Irzykowski
Journal:  Int J Mol Sci       Date:  2017-03-22       Impact factor: 5.923

10.  Genomics-assisted breeding in minor and pseudo-cereals.

Authors:  Shiori Yabe; Hiroyoshi Iwata
Journal:  Breed Sci       Date:  2020-02-01       Impact factor: 2.086

  10 in total

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