Literature DB >> 27105018

The role of isoforms in the evolution of cryptic coloration in Peromyscus mice.

Ricardo Mallarino1, Tess A Linden1, Catherine R Linnen2, Hopi E Hoekstra1.   

Abstract

A central goal of evolutionary biology is to understand the molecular mechanisms underlying phenotypic adaptation. While the contribution of protein-coding and cis-regulatory mutations to adaptive traits has been well documented, additional sources of variation - such as the production of alternative RNA transcripts from a single gene, or isoforms - have been understudied. Here, we focus on the pigmentation gene Agouti, known to express multiple alternative transcripts, to investigate the role of isoform usage in the evolution of cryptic colour phenotypes in deer mice (genus Peromyscus). We first characterize the Agouti isoforms expressed in the Peromyscus skin and find two novel isoforms not previously identified in Mus. Next, we show that a locally adapted light-coloured population of P. maniculatus living on the Nebraska Sand Hills shows an upregulation of a single Agouti isoform, termed 1C, compared with their ancestral dark-coloured conspecifics. Using in vitro assays, we show that this preference for isoform 1C may be driven by isoform-specific differences in translation. In addition, using an admixed population of wild-caught mice, we find that variation in overall Agouti expression maps to a region near exon 1C, which also has patterns of nucleotide variation consistent with strong positive selection. Finally, we show that the independent evolution of cryptic light pigmentation in a different species, P. polionotus, has been driven by a preference for the same Agouti isoform. Together, these findings present an example of the role of alternative transcript processing in adaptation and demonstrate molecular convergence at the level of isoform regulation.
© 2016 John Wiley & Sons Ltd.

Entities:  

Keywords:  development and evolution; ecological genetics; gene structure and function; mammals; molecular evolution; population genetics

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Year:  2016        PMID: 27105018     DOI: 10.1111/mec.13663

Source DB:  PubMed          Journal:  Mol Ecol        ISSN: 0962-1083            Impact factor:   6.185


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