Literature DB >> 12702692

Fine mapping of complex trait genes combining pedigree and linkage disequilibrium information: a Bayesian unified framework.

Miguel Pérez-Enciso1.   

Abstract

We present a Bayesian method that combines linkage and linkage disequilibrium (LDL) information for quantitative trait locus (QTL) mapping. This method uses jointly all marker information (haplotypes) and all available pedigree information; i.e., it is not restricted to any specific experimental design and it is not required that phases are known. Infinitesimal genetic effects or environmental noise ("fixed") effects can equally be fitted. A diallelic QTL is assumed and both additive and dominant effects can be estimated. We have implemented a combined Gibbs/Metropolis-Hastings sampling to obtain the marginal posterior distributions of the parameters of interest. We have also implemented a Bayesian variant of usual disequilibrium measures like D' and r(2) between QTL and markers. We illustrate the method with simulated data in "simple" (two-generation full-sib families) and "complex" (four-generation) pedigrees. We compared the estimates with and without using linkage disequilibrium information. In general, using LDL resulted in estimates of QTL position that were much better than linkage-only estimates when there was complete disequilibrium between the mutant QTL allele and the marker. This advantage, however, decreased when the association was only partial. In all cases, additive and dominant effects were estimated accurately either with or without disequilibrium information.

Mesh:

Year:  2003        PMID: 12702692      PMCID: PMC1462504     

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


  28 in total

1.  Assessment of linkage disequilibrium by the decay of haplotype sharing, with application to fine-scale genetic mapping.

Authors:  M S McPeek; A Strahs
Journal:  Am J Hum Genet       Date:  1999-09       Impact factor: 11.025

2.  Sibling-based tests of linkage and association for quantitative traits.

Authors:  D B Allison; M Heo; N Kaplan; E R Martin
Journal:  Am J Hum Genet       Date:  1999-06       Impact factor: 11.025

3.  Mapping of complex traits by single-nucleotide polymorphisms.

Authors:  L P Zhao; C Aragaki; L Hsu; F Quiaoit
Journal:  Am J Hum Genet       Date:  1998-07       Impact factor: 11.025

Review 4.  Linkage disequilibrium mapping of complex disease: fantasy or reality?

Authors:  J D Terwilliger; K M Weiss
Journal:  Curr Opin Biotechnol       Date:  1998-12       Impact factor: 9.740

5.  Combined linkage and association sib-pair analysis for quantitative traits.

Authors:  D W Fulker; S S Cherny; P C Sham; J K Hewitt
Journal:  Am J Hum Genet       Date:  1999-01       Impact factor: 11.025

6.  A comparison of linkage disequilibrium measures for fine-scale mapping.

Authors:  B Devlin; N Risch
Journal:  Genomics       Date:  1995-09-20       Impact factor: 5.736

7.  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

8.  Mapping-linked quantitative trait loci using Bayesian analysis and Markov chain Monte Carlo algorithms.

Authors:  P Uimari; I Hoeschele
Journal:  Genetics       Date:  1997-06       Impact factor: 4.562

9.  Likelihood methods for locating disease genes in nonequilibrium populations.

Authors:  N L Kaplan; W G Hill; B S Weir
Journal:  Am J Hum Genet       Date:  1995-01       Impact factor: 11.025

10.  Fine-mapping of quantitative trait loci by identity by descent in outbred populations: application to milk production in dairy cattle.

Authors:  J Riquet; W Coppieters; N Cambisano; J J Arranz; P Berzi; S K Davis; B Grisart; F Farnir; L Karim; M Mni; P Simon; J F Taylor; P Vanmanshoven; D Wagenaar; J E Womack; M Georges
Journal:  Proc Natl Acad Sci U S A       Date:  1999-08-03       Impact factor: 11.205

View more
  22 in total

1.  Bayesian association-based fine mapping in small chromosomal segments.

Authors:  Mikko J Sillanpää; Madhuchhanda Bhattacharjee
Journal:  Genetics       Date:  2004-09-15       Impact factor: 4.562

2.  A two-stage approximation for analysis of mixture genetic models in large pedigrees.

Authors:  D Habier; L R Totir; R L Fernando
Journal:  Genetics       Date:  2010-04-09       Impact factor: 4.562

3.  Nested association mapping for identification of functional markers.

Authors:  Baohong Guo; David A Sleper; William D Beavis
Journal:  Genetics       Date:  2010-06-15       Impact factor: 4.562

Review 4.  Overview of techniques to account for confounding due to population stratification and cryptic relatedness in genomic data association analyses.

Authors:  M J Sillanpää
Journal:  Heredity (Edinb)       Date:  2010-07-14       Impact factor: 3.821

5.  Simultaneous fine mapping of multiple closely linked quantitative trait Loci using combined linkage disequilibrium and linkage with a general pedigree.

Authors:  S H Lee; J H J Van der Werf
Journal:  Genetics       Date:  2006-06-04       Impact factor: 4.562

6.  Using dominance relationship coefficients based on linkage disequilibrium and linkage with a general complex pedigree to increase mapping resolution.

Authors:  S H Lee; J H J Van der Werf
Journal:  Genetics       Date:  2006-09-01       Impact factor: 4.562

7.  Multipoint identity-by-descent prediction using dense markers to map quantitative trait loci and estimate effective population size.

Authors:  Theo H E Meuwissen; Mike E Goddard
Journal:  Genetics       Date:  2007-06-11       Impact factor: 4.562

8.  Combined linkage disequilibrium and linkage mapping: Bayesian multilocus approach.

Authors:  P Pikkuhookana; M J Sillanpää
Journal:  Heredity (Edinb)       Date:  2013-11-20       Impact factor: 3.821

9.  The impact of genetic relationship information on genomic breeding values in German Holstein cattle.

Authors:  David Habier; Jens Tetens; Franz-Reinhold Seefried; Peter Lichtner; Georg Thaller
Journal:  Genet Sel Evol       Date:  2010-02-19       Impact factor: 4.297

10.  Linear models for joint association and linkage QTL mapping.

Authors:  Andrés Legarra; Rohan L Fernando
Journal:  Genet Sel Evol       Date:  2009-09-29       Impact factor: 4.297

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.