Using genomics to characterize evolutionary potential for conservation of wild populations

TLDR

Genomics offers the potential to enhance conservation by maximizing evolutionary potential, yet challenges arise from polygenic traits, regulatory network effects, and cryptic epigenetic variation that are difficult to detect with conventional adaptive‑variation methods. The authors aim to examine the complexity of adaptation genetics and evaluate the strengths and limitations of genomics for assessing evolutionary potential in conservation management. They analyze how genomic screens can capture small‑effect loci and cryptic variation, and discuss methodological considerations for integrating genomic data into management decisions. They conclude that genome‑wide variation screening provides a robust, generalized measure of evolutionary potential that, when applied within an adaptive management framework, yields the best conservation outcomes.

Abstract

Genomics promises exciting advances towards the important conservation goal of maximizing evolutionary potential, notwithstanding associated challenges. Here, we explore some of the complexity of adaptation genetics and discuss the strengths and limitations of genomics as a tool for characterizing evolutionary potential in the context of conservation management. Many traits are polygenic and can be strongly influenced by minor differences in regulatory networks and by epigenetic variation not visible in DNA sequence. Much of this critical complexity is difficult to detect using methods commonly used to identify adaptive variation, and this needs appropriate consideration when planning genomic screens, and when basing management decisions on genomic data. When the genomic basis of adaptation and future threats are well understood, it may be appropriate to focus management on particular adaptive traits. For more typical conservations scenarios, we argue that screening genome-wide variation should be a sensible approach that may provide a generalized measure of evolutionary potential that accounts for the contributions of small-effect loci and cryptic variation and is robust to uncertainty about future change and required adaptive response(s). The best conservation outcomes should be achieved when genomic estimates of evolutionary potential are used within an adaptive management framework.