Pleiotropy, constraint, and modularity in the evolution of life histories: insights from genomic analyses
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Date
2016-12-09
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Citation of Original Publication
Hughes, K.A. and Leips, J. (2017), Pleiotropy, constraint, and modularity in the evolution of life histories: insights from genomic analyses. Ann. N.Y. Acad. Sci., 1389: 76-91. https://doi.org/10.1111/nyas.13256
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This is the peer reviewed version of the following article: Hughes, K.A. and Leips, J. (2017), Pleiotropy, constraint, and modularity in the evolution of life histories: insights from genomic analyses. Ann. N.Y. Acad. Sci., 1389: 76-91. https://doi.org/10.1111/nyas.13256, which has been published in final form at https://doi.org/10.1111/nyas.13256. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.
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Abstract
Multicellular organisms display an enormous range of life history (LH) strategies and present an evolutionary conundrum; despite strong natural selection, LH traits are characterized by high levels of genetic variation. To understand the evolution of life histories and maintenance of this variation, the specific phenotypic effects of segregating alleles and the genetic networks in which they act need to be elucidated. In particular, the extent to which LH evolution is constrained by the pleiotropy of alleles contributing to LH variation is generally unknown. Here, we review recent empirical results that shed light on this question, with an emphasis on studies employing genomic analyses. While genome-scale analyses are increasingly practical and affordable, they face limitations of genetic resolution and statistical power. We describe new research approaches that we believe can produce new insights and evaluate their promise and applicability to different kinds of organisms. Two approaches seem particularly promising: experiments that manipulate selection in multiple dimensions and measure phenotypic and genomic response and analytical approaches that take into account genome-wide associations between markers and phenotypes, rather than applying a traditional marker-by-marker approach.