Literature DB >> 23298448

Modelling of genetic interactions improves prediction of hybrid patterns--a case study in domestic fowl.

José M Álvarez-Castro1, Arnaud Le Rouzic, Leif Andersson, Paul B Siegel, Örjan Carlborg.   

Abstract

A major challenge in complex trait genetics is to unravel how multiple loci and environmental factors together cause phenotypic diversity. Both first (F(1)) and second (F(2)) generation hybrids often display phenotypes that deviate from what is expected under intermediate inheritance. We have here studied two chicken F(2) populations generated by crossing divergent chicken lines to assess how epistatic loci, identified in earlier quantitative trait locus (QTL) studies, contribute to hybrid deviations from the mid-parent phenotype. Empirical evidence suggests that the average phenotypes of the intercross birds tend to be lower than the midpoint between the parental means in both crosses. Our results confirm that epistatic interactions, despite a relatively small contribution to the phenotypic variance, play an important role in the deviation of hybrid phenotypes from the mid-parent values (i.e. multi-locus hybrid genotypes lead to lower rather than higher body weights). To a lesser extent, dominance also appears to contribute to the mid-parent deviation, at least in one of the crosses. This observation coincides with the hypothesis that hybridization tends to break up co-adapted gene complexes, i.e. generate Bateson-Dobzhansky-Muller incompatibilities.

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Year:  2012        PMID: 23298448     DOI: 10.1017/S001667231200047X

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


  6 in total

1.  Epistatic effects on abdominal fat content in chickens: results from a genome-wide SNP-SNP interaction analysis.

Authors:  Fangge Li; Guo Hu; Hui Zhang; Shouzhi Wang; Zhipeng Wang; Hui Li
Journal:  PLoS One       Date:  2013-12-05       Impact factor: 3.240

2.  A genome-wide association study reveals dominance effects on number of teats in pigs.

Authors:  Marcos S Lopes; John W M Bastiaansen; Barbara Harlizius; Egbert F Knol; Henk Bovenhuis
Journal:  PLoS One       Date:  2014-08-26       Impact factor: 3.240

Review 3.  Detecting epistasis in human complex traits.

Authors:  Wen-Hua Wei; Gibran Hemani; Chris S Haley
Journal:  Nat Rev Genet       Date:  2014-09-09       Impact factor: 53.242

4.  Estimating directional epistasis.

Authors:  Arnaud Le Rouzic
Journal:  Front Genet       Date:  2014-07-14       Impact factor: 4.599

5.  Evolutionary footprint of epistasis.

Authors:  Gabriele Pedruzzi; Ayuna Barlukova; Igor M Rouzine
Journal:  PLoS Comput Biol       Date:  2018-09-17       Impact factor: 4.475

6.  Genome-wide association scan for heterotic quantitative trait loci in multi-breed and crossbred beef cattle.

Authors:  Everestus C Akanno; Liuhong Chen; Mohammed K Abo-Ismail; John J Crowley; Zhiquan Wang; Changxi Li; John A Basarab; Michael D MacNeil; Graham S Plastow
Journal:  Genet Sel Evol       Date:  2018-10-05       Impact factor: 4.297

  6 in total

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