The practice and promise of temporal genomics for measuring evolutionary responses to global change

Abstract

Understanding the evolutionary consequences of anthropogenic change is imperative for estimating long‐term species resilience. While contemporary genomic data can provide us with important insights into recent demographic histories, investigating past change using present genomic data alone has limitations. In comparison, temporal genomics studies, defined herein as those that incorporate time series genomic data, utilize museum collections and repeated field sampling to directly examine evolutionary change. As temporal genomics is applied to more systems, species and questions, best practices can be helpful guides to make the most efficient use of limited resources. Here, we conduct a systematic literature review to synthesize the effects of temporal genomics methodology on our ability to detect evolutionary changes. We focus on studies investigating recent change within the past 200 years, highlighting evolutionary processes that have occurred during the past two centuries of accelerated anthropogenic pressure. We first identify the most frequently studied taxa, systems, questions and drivers, before highlighting overlooked areas where further temporal genomic studies may be particularly enlightening. Then, we provide guidelines for future study and sample designs while identifying key considerations that may influence statistical and analytical power. Our aim is to provide recommendations to a broad array of researchers interested in using temporal genomics in their work.

Continuously fluctuating selection reveals extreme granularity and parallelism of adaptive tracking

“…As these alleles exhibited undetectable systematic change throughout the experiment, they would likely be inferred to be neutral using inference approaches based on coarse temporal sampling or static snapshots of population genomic data. Thus, our high frequency sampling revealed a functional relevance to standing variation that would have remained hidden, bolstering recent calls for the procurement of well-resolved, time series genomic sampling (9, 10, 12, 13, 31–33).…”

“…Determining whether such conditions are met in natural populations hinges upon well-resolved, time-series genomic data. Procuring such data may ultimately reveal a functional relevance of standing genetic variation that remains hidden from inference approaches using static snapshots of population genomic variation (9)(10)(11)(12)(13).…”

Rapid evolution of pesticide resistance via adaptation and interspecific introgression in a major North American crop pest

“…While genomic surveillance has become a critical technology for the management of pests and invasive species (Hamelin & Roe 2020; Chown et al 2015), in practice the detection of adaptation can be limited by the complex genetic architectures and demographic nonequilibrium. Incorporating QTL metadata and sampling over a time-series can address these issues – reinforcing the need for sustained genomic monitoring programmes – though this is not always possible (Taylor et al 2021; Clark et al 2023; Pélissié et al 2018). Although we only sample individuals at a single timepoint, we show that relevant population genetic statistics can be estimated with sufficient accuracy to not only identify a putative target of selection for pesticide resistance, but to precisely infer recent allele frequency change at the locus.…”

Genomic tools for comparative conservation genetics among three recently diverged stag beetles (Lucanus, Lucanidae)

“…Note that we are not arguing that local anthropogenic exploitation is not important; instead, the impact of local exploitation may be masked by the impact of global environmental changes. A better sampling strategy, such as time serial sampling with historical samples, may help reveal the demographic nuances associated with more subtle differences in Anthropocene (Clark et al, 2023). Specifically, because of the relatively long generation time of the beetles (4 years; Huang, 2014), we could not employ time serial sampling in this study.…”

“…First, conventionally used molecular markers, for example, Sanger sequencing loci and microsatellites, have been effective in detecting genetic structure within species and in reconstructing demographic histories in the Pliocene/Pleistocene (e.g., Chou et al, 2021; Huang & Lin, 2010; Sun et al, 2020), but the power of using these markers to detect fine‐scale geographic genetic variation and demographic change in the Anthropocene is limited (Nunziata & Weisrock, 2018). The ability to detect recent demographic change (<100 years) using molecular data, however, is crucial for statistically evaluating the efficacy of conservation acts and could be better explored using population genomic data (e.g., Clark et al, 2023; DeWoody et al, 2022; Hoey et al, 2022; Hogg et al, 2022; Nunziata et al, 2017). More importantly, recent changes in land use (e.g., forest loss due to the development of recreational areas or agricultural land) and the launch of various conservation acts (e.g., the establishment of national parks) are well documented in Taiwan (Chen et al, 2019).…”