Genomics for monitoring and understanding species responses to global climate change

Bernatchez, Louis; Ferchaud, Anne-Laure; Berger, Chloé Suzanne; Venney, Clare J.; Xuereb, Amanda

doi:10.1038/s41576-023-00657-y

Cited by 6 publications

(8 citation statements)

References 226 publications

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“…Next, allele frequencies/read counts/methylation scores (response) and environmental (predictor) data are used for genotype–environment association (GEA) analyses to identify climate‐associated outlier variants (see Bernatchez et al. (2023) for a detailed overview of GEA approaches) (2a–c). Allele frequencies/read counts/methylation scores from outlier variants are used alongside current and projected future environmental data in a modelling framework to generate genomic offset estimates (3a,b).…”

Section: Implementing Genomic Offset In Marine Managementmentioning

confidence: 99%

“…Despite some limitations and challenges, including validation and management buy-in (Rellstab et al, 2021), the approach seems to accurately estimate climate change vulnerability when compared to experimental predictions (e.g., Fitzpatrick et al, 2021). Bernatchez et al (2023) provide a comprehensive overview of this method, among others, in their recent review of genomics-based monitoring approaches, but to date, no study has assessed these methods in specific ecological contexts. Given the potential of genomic offset estimates to inform climate change predictions, and the observation that marine species are already being impacted by climate change, an evaluation of the method's applicability to marine species is warranted.…”

Section: Introductionmentioning

confidence: 99%

“…Bernatchez et al. (2023) provide a comprehensive overview of this method, among others, in their recent review of genomics‐based monitoring approaches, but to date, no study has assessed these methods in specific ecological contexts. Given the potential of genomic offset estimates to inform climate change predictions, and the observation that marine species are already being impacted by climate change, an evaluation of the method's applicability to marine species is warranted.…”

Section: Introductionmentioning

confidence: 99%

“…The global reliance F I G U R E 1 The first step in calculating genomic offset estimates in the marine environment is to sample populations from across the range, ideally from steep environmental gradients, to inform population structure in the species of interest (1a-c). Next, allele frequencies/ read counts/methylation scores (response) and environmental (predictor) data are used for genotype-environment association (GEA) analyses to identify climate-associated outlier variants (seeBernatchez et al (2023) for a detailed overview of GEA approaches) (2a-c). Allele frequencies/read counts/methylation scores from outlier variants are used alongside current and projected future environmental data in a modelling framework to generate genomic offset estimates (3a,b).…”

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confidence: 99%

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Predicting the future of our oceans—Evaluating genomic forecasting approaches in marine species

Layton,

Brieuc,

Castilho

et al. 2024

Global Change Biology

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Climate change is restructuring biodiversity on multiple scales and there is a pressing need to understand the downstream ecological and genomic consequences of this change. Recent advancements in the field of eco‐evolutionary genomics have sought to include evolutionary processes in forecasting species' responses to climate change (e.g., genomic offset), but to date, much of this work has focused on terrestrial species. Coastal and offshore species, and the fisheries they support, may be even more vulnerable to climate change than their terrestrial counterparts, warranting a critical appraisal of these approaches in marine systems. First, we synthesize knowledge about the genomic basis of adaptation in marine species, and then we discuss the few examples where genomic forecasting has been applied in marine systems. Next, we identify the key challenges in validating genomic offset estimates in marine species, and we advocate for the inclusion of historical sampling data and hindcasting in the validation phase. Lastly, we describe a workflow to guide marine managers in incorporating these predictions into the decision‐making process.

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Section: Implementing Genomic Offset In Marine Managementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Predicting the future of our oceans—Evaluating genomic forecasting approaches in marine species

Layton,

Brieuc,

Castilho

et al. 2024

Global Change Biology

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“…Given the high levels of genetic divergence between Green Bay, Muskegon, and the main basin sites, we used a genome-wide scan to determine if any regions of the genome are suggestive of genetic adaptation to the different environments (67,68). We retained a total of 13 outlier windows from nine chromosomes that were shared in at least 80% of comparisons between Green Bay and the main basin collection sites as well as Muskegon Lake and the main basin populations (see Methods; Supplementary Table 8).…”

Section: Candidate Genes Underlying Genetic Adaptationmentioning

confidence: 99%

Rapid, simultaneous increases in the effective sizes of adaptively divergent yellow perch (Perca flavescens) populations

Yin,

Schraidt,

Sparks

et al. 2024

Preprint

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Aquatic ecosystems are highly dynamic environments vulnerable to a wide variety of natural and anthropogenic disturbances. High-economic value fisheries are one of many ecosystem services affected by these disturbances and it is critical to accurately characterize their genetic diversity and effective population sizes through time. We used genome-wide data to reconstruct the demographic histories of economically important yellow perch (Perca flavescens) populations. In two isolated and genetically divergent populations, we provide strong evidence for simultaneous increases in effective population sizes over both historic and contemporary time scales including negative genome-wide estimates of Tajima's D, 3.1 times more SNPs than adjacent populations, and effective population sizes that have increased 10- and 47-fold from their minimum. We also identified parallel, genetic adaptation to reduced visual clarity in the same two habitats. These results suggest that the synchrony of key ecological and evolutionary processes can drive parallel demographic and evolutionary trajectories across independent populations.

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Environmental change drives multi-generational shifts in the gut microbiome that mirror changing animal fitness

Williams,

King

et al. 2023

Preprint

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Gut microbiomes can dramatically affect host health and fitness and can also be highly dynamic in response to changing environmental conditions. This intricate interplay between gut microbiota, environmental pressures, and host health necessitates accounting for all these variables when predicting the response of animals to a changing environment. These predictions are of broad concern but are highly relevant to conservation biology, and more specifically to populations transitioning from the wild to human care for the purposes of ex-situ breeding programs. Captivity can dramatically alter both host-associated microbial communities and host health, but the dynamics of how the host and microbiome transition between the wild and captive state--within and across generations--are not well described. Here, we evaluate the microbiome and host fitness metrics for Pacific pocket mice (Perognathus longimembris pacificus) during the establishment of an ex-situ conservation breeding program to characterize how pocket mice and their microbiomes respond to the environmental pressures of captivity across five generations. We found that the microbiome assumes a novel, stable conformation after two to three generations in captivity and that the patterns observed in the transitioning microbiota mirror the patterns of transitioning hosts' weight and reproductive metrics. Moreover, we identify several microbial taxa which are correlated with successful reproduction. Our results provide insight not only into the effects of captivity but can be broadly applicable for understanding the effects of environmental change on organisms and their gut microbiota, which we propose may require multiple generations to reach an alternative stable state.

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Genomics for monitoring and understanding species responses to global climate change

Cited by 6 publications

References 226 publications

Predicting the future of our oceans—Evaluating genomic forecasting approaches in marine species

Predicting the future of our oceans—Evaluating genomic forecasting approaches in marine species

Rapid, simultaneous increases in the effective sizes of adaptively divergent yellow perch (Perca flavescens) populations

Environmental change drives multi-generational shifts in the gut microbiome that mirror changing animal fitness

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