Literature DB >> 19968911

Epistatic interactions attenuate mutations affecting startle behaviour in Drosophila melanogaster.

Akihiko Yamamoto1, Robert R H Anholt, Trudy F C MacKay.   

Abstract

Epistasis is an important feature of the genetic architecture of quantitative traits. Previously, we showed that startle-induced locomotor behaviour of Drosophila melanogaster, a critical survival trait, is highly polygenic and exhibits epistasis. Here, we characterize epistatic interactions among homozygous P-element mutations affecting startle-induced locomotion in the Canton-S isogenic background and in 21 wild-derived inbred genetic backgrounds. We find pervasive epistasis for pairwise combinations of homozygous P-element insertional mutations as well as for mutations in wild-derived backgrounds. In all cases, the direction of the epistatic effects is to suppress the mutant phenotypes. The magnitude of the epistatic interactions in wild-derived backgrounds is highly correlated with the magnitude of the main effects of mutations, leading to phenotypic robustness of the startle response in the face of deleterious mutations. There is variation in the magnitude of epistasis among the wild-derived genetic backgrounds, indicating evolutionary potential for enhancing or suppressing effects of single mutations. These results provide a partial glimpse of the complex genetic network underlying the genetic architecture of startle behaviour and provide empirical support for the hypothesis that suppressing epistasis is the mechanism underlying genetic canalization of traits under strong stabilizing selection. Widespread suppressing epistasis will lead to underestimates of the main effects of quantitative trait loci (QTLs) in mapping experiments when not explicitly accounted for. In addition, suppressing epistasis could lead to underestimates of mutational variation for quantitative traits and overestimates of the strength of stabilizing selection, which has implications for maintenance of variation of complex traits by mutation-selection balance.

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Year:  2009        PMID: 19968911     DOI: 10.1017/S0016672309990279

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


  21 in total

Review 1.  Evolution of Epistatic Networks and the Genetic Basis of Innate Behaviors.

Authors:  Robert R H Anholt
Journal:  Trends Genet       Date:  2019-11-07       Impact factor: 11.639

Review 2.  Cryptic genetic variation: evolution's hidden substrate.

Authors:  Annalise B Paaby; Matthew V Rockman
Journal:  Nat Rev Genet       Date:  2014-03-11       Impact factor: 53.242

Review 3.  Charting the genotype-phenotype map: lessons from the Drosophila melanogaster Genetic Reference Panel.

Authors:  Trudy F C Mackay; Wen Huang
Journal:  Wiley Interdiscip Rev Dev Biol       Date:  2017-08-22       Impact factor: 5.814

Review 4.  Making scents of behavioural genetics: lessons from Drosophila.

Authors:  Robert R H Anholt
Journal:  Genet Res (Camb)       Date:  2010-12       Impact factor: 1.588

Review 5.  Mutations and quantitative genetic variation: lessons from Drosophila.

Authors:  Trudy F C Mackay
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-04-27       Impact factor: 6.237

6.  Dissecting the Genetic Architecture of Behavior in Drosophila melanogaster.

Authors:  Robert R H Anholt; Trudy F C Mackay
Journal:  Curr Opin Behav Sci       Date:  2015-04

Review 7.  Does your gene need a background check? How genetic background impacts the analysis of mutations, genes, and evolution.

Authors:  Christopher H Chandler; Sudarshan Chari; Ian Dworkin
Journal:  Trends Genet       Date:  2013-02-28       Impact factor: 11.639

Review 8.  Epistasis and quantitative traits: using model organisms to study gene-gene interactions.

Authors:  Trudy F C Mackay
Journal:  Nat Rev Genet       Date:  2013-12-03       Impact factor: 53.242

Review 9.  Life-History Evolution and the Genetics of Fitness Components in Drosophila melanogaster.

Authors:  Thomas Flatt
Journal:  Genetics       Date:  2020-01       Impact factor: 4.562

10.  Use of pleiotropy to model genetic interactions in a population.

Authors:  Gregory W Carter; Michelle Hays; Amir Sherman; Timothy Galitski
Journal:  PLoS Genet       Date:  2012-10-11       Impact factor: 5.917

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