Journal Article

Association between Sex-Biased Gene Expression and Mutations with Sex-Specific Phenotypic Consequences in <i>Drosophila</i>

Tim Connallon and Andrew G. Clark

in Genome Biology and Evolution

Published on behalf of Society for Molecular Biology and Evolution

Volume 3, issue , pages 151-155
Published in print January 2011 |
Published online February 2011 | e-ISSN: 1759-6653 | DOI: http://dx.doi.org/10.1093/gbe/evr004

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Genome-wide mRNA transcription profiles reveal widespread molecular sexual dimorphism or “sex-biased” gene expression, yet the relationship between molecular and phenotypic sexual dimorphism remains unclear. A major unresolved question is whether sex-biased genes typically perform male- and female-specific functions (whether these genes have sex-biased phenotypic or fitness consequences) or have similar functional importance for both sexes. To elucidate the relationship between sex-biased transcription and sex-biased fitness consequences, we analyzed a large data set of lethal, visible, and sterile mutations that have been mapped to the Drosophila melanogaster genome. The data permitted us to classify genes according to their sex-specific mutational effects and to infer the relationship between sex-biased transcription level and sex-specific fitness consequences. We find that mutations in female-biased genes are (on average) more deleterious to females than to males and that mutations in male-biased genes tend to be more deleterious to males than to females. Nevertheless, mutations in most sex-biased genes have similar phenotypic consequences for both sexes, which suggests that sex-biased transcription is not necessarily associated with functional genetic differentiation between males and females. These results have interesting implications for the evolution of sexual dimorphism and sex-specific adaptation.

Keywords: sexual dimorphism; sexual selection; sexual antagonism; deleterious mutation; fitness variation

Journal Article.  3107 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology ; Evolutionary Biology ; Genetics and Genomics

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