Literature DB >> 10689805

Estimating the genetic architecture of quantitative traits.

Z B Zeng1, C H Kao, C J Basten.   

Abstract

Understanding and estimating the structure and parameters associated with the genetic architecture of quantitative traits is a major research focus in quantitative genetics. With the availability of a well-saturated genetic map of molecular markers, it is possible to identify a major part of the structure of the genetic architecture of quantitative traits and to estimate the associated parameters. Multiple interval mapping, which was recently proposed for simultaneously mapping multiple quantitative trait loci (QTL), is well suited to the identification and estimation of the genetic architecture parameters, including the number, genomic positions, effects and interactions of significant QTL and their contribution to the genetic variance. With multiple traits and multiple environments involved in a QTL mapping experiment, pleiotropic effects and QTL by environment interactions can also be estimated. We review the method and discuss issues associated with multiple interval mapping, such as likelihood analysis, model selection, stopping rules and parameter estimation. The potential power and advantages of the method for mapping multiple QTL and estimating the genetic architecture are discussed. We also point out potential problems and difficulties in resolving the details of the genetic architecture as well as other areas that require further investigation. One application of the analysis is to improve genome-wide marker-assisted selection, particularly when the information about epistasis is used for selection with mating.

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Substances:

Year:  1999        PMID: 10689805     DOI: 10.1017/s0016672399004255

Source DB:  PubMed          Journal:  Genet Res        ISSN: 0016-6723            Impact factor:   1.588


  97 in total

1.  Bayesian model choice and search strategies for mapping interacting quantitative trait Loci.

Authors:  Nengjun Yi; Shizhong Xu; David B Allison
Journal:  Genetics       Date:  2003-10       Impact factor: 4.562

2.  A penalized likelihood method for mapping epistatic quantitative trait Loci with one-dimensional genome searches.

Authors:  Martin P Boer; Cajo J F Ter Braak; Ritsert C Jansen
Journal:  Genetics       Date:  2002-10       Impact factor: 4.562

3.  The genetic architecture of Drosophila sensory bristle number.

Authors:  Christy L Dilda; Trudy F C Mackay
Journal:  Genetics       Date:  2002-12       Impact factor: 4.562

4.  Stochastic search variable selection for identifying multiple quantitative trait loci.

Authors:  Nengjun Yi; Varghese George; David B Allison
Journal:  Genetics       Date:  2003-07       Impact factor: 4.562

5.  Multiple-interval mapping for quantitative trait loci controlling endosperm traits.

Authors:  Chen-Hung Kao
Journal:  Genetics       Date:  2004-08       Impact factor: 4.562

6.  Multivariate whole genome average interval mapping: QTL analysis for multiple traits and/or environments.

Authors:  Arūnas P Verbyla; Brian R Cullis
Journal:  Theor Appl Genet       Date:  2012-06-13       Impact factor: 5.699

7.  Identification of QTL for increased fibrous roots in soybean.

Authors:  Hussein Abdel-Haleem; Geung-Joo Lee; Roger H Boerma
Journal:  Theor Appl Genet       Date:  2010-12-17       Impact factor: 5.699

Review 8.  Statistical analysis of genetic interactions.

Authors:  Nengjun Yi
Journal:  Genet Res (Camb)       Date:  2010-12       Impact factor: 1.588

9.  An efficient resampling method for assessing genome-wide statistical significance in mapping quantitative trait Loci.

Authors:  Fei Zou; Jason P Fine; Jianhua Hu; D Y Lin
Journal:  Genetics       Date:  2004-12       Impact factor: 4.562

10.  Modeling quantitative trait Loci and interpretation of models.

Authors:  Zhao-Bang Zeng; Tao Wang; Wei Zou
Journal:  Genetics       Date:  2005-01-16       Impact factor: 4.562

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