Detection of multiple QTL with epistatic effects under a mixed inheritance model in an outbred population. Export

@article{citeulike:1073995, abstract = {A quantitative trait depends on multiple quantitative trait loci (QTL) and on the interaction between two or more QTL, named epistasis. Several methods to detect multiple QTL in various types of design have been proposed, but most of these are based on the assumption that each QTL works independently and epistasis has not been explored sufficiently. The objective of the study was to propose an integrated method to detect multiple QTL with epistases using Bayesian inference via a Markov chain Monte Carlo (MCMC) algorithm. Since the mixed inheritance model is assumed and the deterministic algorithm to calculate the probabilities of QTL genotypes is incorporated in the method, this can be applied to an outbred population such as livestock. Additionally, we treated a pair of QTL as one variable in the Reversible jump Markov chain Monte Carlo (RJMCMC) algorithm so that two QTL were able to be simultaneously added into or deleted from a model. As a result, both of the QTL can be detected, not only in cases where either of the two QTL has main effects and they have epistatic effects between each other, but also in cases where neither of the two QTL has main effects but they have epistatic effects. The method will help ascertain the complicated structure of quantitative traits.}, address = {Laboratory of Animal Breeding and Genetics, Division of Applied Biosciences, Graduate School of Agriculture, Kyoto University, Kyoto 606-8502, Japan.}, author = {Narita, A. and Sasaki, Y.}, citeulike-article-id = {1073995}, citeulike-linkout-0 = {http://dx.doi.org/10.1051/gse:2004009}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/15231232}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=15231232}, doi = {10.1051/gse:2004009}, issn = {0999-193X}, journal = {Genet Sel Evol}, keywords = {epistasis, multiqtl, qtl}, number = {4}, pages = {415--433}, posted-at = {2007-01-29 08:27:55}, priority = {2}, title = {Detection of multiple QTL with epistatic effects under a mixed inheritance model in an outbred population.}, url = {http://dx.doi.org/10.1051/gse:2004009}, volume = {36}, year = {2004} }

TY - JOUR ID - citeulike:1073995 L3 - citeulike-article-id:1073995 N2 - A quantitative trait depends on multiple quantitative trait loci (QTL) and on the interaction between two or more QTL, named epistasis. Several methods to detect multiple QTL in various types of design have been proposed, but most of these are based on the assumption that each QTL works independently and epistasis has not been explored sufficiently. The objective of the study was to propose an integrated method to detect multiple QTL with epistases using Bayesian inference via a Markov chain Monte Carlo (MCMC) algorithm. Since the mixed inheritance model is assumed and the deterministic algorithm to calculate the probabilities of QTL genotypes is incorporated in the method, this can be applied to an outbred population such as livestock. Additionally, we treated a pair of QTL as one variable in the Reversible jump Markov chain Monte Carlo (RJMCMC) algorithm so that two QTL were able to be simultaneously added into or deleted from a model. As a result, both of the QTL can be detected, not only in cases where either of the two QTL has main effects and they have epistatic effects between each other, but also in cases where neither of the two QTL has main effects but they have epistatic effects. The method will help ascertain the complicated structure of quantitative traits. IS - 4 JF - Genet Sel Evol SN - 0999-193X AD - Laboratory of Animal Breeding and Genetics, Division of Applied Biosciences, Graduate School of Agriculture, Kyoto University, Kyoto 606-8502, Japan. EP - 433 TI - Detection of multiple QTL with epistatic effects under a mixed inheritance model in an outbred population. VL - 36 SP - 415 KW - epistasis KW - multiqtl KW - qtl AU - Narita, A AU - Sasaki, Y PY - 2004///g UR - http://dx.doi.org/10.1051/gse:2004009 ER -