Detecting Signatures Of Selection In Regulatory Variation

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1038/s41559-022-01761-8. This is version 1 of this Preprint.

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Authors

Peter D Price, Daniela H Palmer Droguett, Jessica A Taylor, Dong W Kim, Elsie S Place, Thea F Rogers, Judith E Mank, Christopher R Cooney, Alison E Wright

Abstract

A substantial amount of phenotypic diversity results from changes in gene regulation. Understanding how regulatory diversity evolves is therefore a key priority in identifying mechanisms of adaptive change. However, in contrast to powerful models of sequence evolution, we lack a consensus model of regulatory evolution. Furthermore, recent work has shown that many of the comparative approaches used to study gene regulation are subject to biases that can lead to false signatures of selection. In this review, we first outline the main approaches for describing regulatory evolution and their inherent biases. Next, we bridge the gap between the fields of comparative phylogenetic methods and transcriptomics to reinforce the main pitfalls of inferring regulatory selection and use simulation studies to show that shifts in tissue composition can heavily bias inferences of selection. We close by highlighting the multi-dimensional nature of regulatory variation and identifying major, unanswered questions in disentangling how selection acts on the transcriptome.

DOI

https://doi.org/10.32942/osf.io/dt69z

Subjects

Ecology and Evolutionary Biology, Evolution, Genetics and Genomics, Genomics, Life Sciences

Keywords

phylogenetics, Regulatory Evolution, RNAseq

Dates

Published: 2021-12-29 05:23

License

CC-By Attribution-NonCommercial-NoDerivatives 4.0 International