Literature DB >> 25377463

Natural allelic variations of xenobiotic-metabolizing enzymes affect sexual dimorphism in Oryzias latipes.

Takafumi Katsumura1, Shoji Oda2, Shigeki Nakagome3, Tsunehiko Hanihara4, Hiroshi Kataoka2, Hiroshi Mitani2, Shoji Kawamura2, Hiroki Oota5.   

Abstract

Sexual dimorphisms, which are phenotypic differences between males and females, are driven by sexual selection. Interestingly, sexually selected traits show geographical variations within species despite strong directional selective pressures. This paradox has eluded many evolutionary biologists for some time, and several models have been proposed (e.g. 'indicator model' and 'trade-off model'). However, disentangling which of these theories explains empirical patterns remains difficult, because genetic polymorphisms that cause variation in sexual differences are still unknown. In this study, we show that polymorphisms in cytochrome P450 (CYP) 1B1, which encodes a xenobiotic-metabolizing enzyme, are associated with geographical differences in sexual dimorphism in the anal fin morphology of medaka fish (Oryzias latipes). Biochemical assays and genetic cross experiments show that high- and low-activity CYP1B1 alleles enhanced and declined sex differences in anal fin shapes, respectively. Behavioural and phylogenetic analyses suggest maintenance of the high-activity allele by sexual selection, whereas the low-activity allele possibly has experienced positive selection due to by-product effects of CYP1B1 in inferred ancestral populations. The present data can elucidate evolutionary mechanisms behind genetic variations in sexual dimorphism and indicate trade-off interactions between two distinct mechanisms acting on the two alleles with pleiotropic effects of xenobiotic-metabolizing enzymes.
© 2014 The Author(s) Published by the Royal Society. All rights reserved.

Entities:  

Keywords:  cytochrome P450; genetic polymorphisms; sexual dimorphism; sexual selection

Mesh:

Substances:

Year:  2014        PMID: 25377463      PMCID: PMC4241003          DOI: 10.1098/rspb.2014.2259

Source DB:  PubMed          Journal:  Proc Biol Sci        ISSN: 0962-8452            Impact factor:   5.349


  28 in total

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7.  Medaka Population Genome Structure and Demographic History Described via Genotyping-by-Sequencing.

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