Genomic reaction norms inform predictions of plastic and adaptive responses to climate change

Abstract

Genomic reaction norms represent the range of gene expression phenotypes (usually mRNA transcript levels) expressed by a genotype along an environmental gradient. Reaction norms derived from common‐garden experiments are powerful approaches for disentangling plastic and adaptive responses to environmental change in natural populations. By treating gene expression as a phenotype in itself, genomic reaction norms represent invaluable tools for exploring causal mechanisms underlying organismal responses to climate change across multiple levels of biodiversity. Our goal is to provide the context, framework and motivation for applying genomic reaction norms to study the responses of natural populations to climate change. Here, we describe the utility of integrating genomics with common‐garden‐gradient experiments under a reaction norm analytical framework to answer fundamental questions about phenotypic plasticity, local adaptation, their interaction (i.e. genetic variation in plasticity) and future adaptive potential. An experimental and analytical framework for constructing and analysing genomic reaction norms is presented within the context of polygenic climate change responses of structured populations with gene flow. Intended for a broad eco‐evo readership, we first briefly review adaptation with gene flow and the importance of understanding the genomic basis and spatial scale of adaptation for conservation and management of structured populations under anthropogenic change. Then, within a high‐dimensional reaction norm framework, we illustrate how to distinguish plastic, differentially expressed (difference in reaction norm intercepts) and differentially plastic (difference in reaction norm slopes) genes, highlighting the areas of opportunity for applying these concepts. We conclude by discussing how genomic reaction norms can be incorporated into a holistic framework to understand the eco‐evolutionary dynamics of climate change responses from molecules to ecosystems. We aim to inspire researchers to integrate gene expression measurements into common‐garden experimental designs to investigate the genomics of climate change responses as sequencing costs become increasingly accessible.

Strong effects of temperature, population and age-at-maturity genotype on maturation probability for Atlantic salmon in a common garden setting

“…With the inherent variation in life history between Atlantic salmon populations, a key question is how this variation relates to changes in temperature, and how climate change impact might depend on the life-history strategy composition of a population. While there is a growing body of literature of studies on thermal reaction norms between fish of different populations and other genetic backgrounds, looking at traits like growth, survival, metabolism, and gene transcription (Hutchings, 2011; Oomen & Hutchings, 2015, 2022) few studies have investigated population differences in reaction norms between temperature and maturation timing, nor interactions with large-effect locus genotypes. Such research can help to better understand the potential impacts of global warming on the future life-history strategy composition of natural populations.…”

Towards a unified eco-evolutionary framework for fisheries management: Coupling advances in next-generation sequencing with species distribution modelling

“…While the abovementioned strategies aim to sequence the whole of the nuclear DNA molecule, HTS have further expanded to sequence the full spectrum of DNA replication via the characterizing of transcriptomes and proteomes. Sequencing these DNA provides strong evidence of functionality, reinforcing the putative links between genotypic and phenotypic variation that can be observed at individual, population, or species level (Oomen and Hutchings, 2022).…”

The importance of eco-evolutionary dynamics for predicting and managing insect range shifts

“…Alternatively, common garden or reciprocal transplant studies can be used to establish causality. Such common garden studies can also be combined with more complex breeding designs coupled to sequencing, to experimentally disentangle and quantify genetic and environmental factors [51].…”