Epigenetic plasticity is likely to exacerbate climate change vulnerability
Data files
Sep 05, 2025 version files 167.63 MB
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bioclimate_raw.csv
15.95 KB
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cand-methylation.csv
5.30 MB
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code_for_GCB.R
18.25 KB
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env.csv
12.33 KB
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MethylationSitesRaw.csv
5.30 MB
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OffsetValues_2041-2060year.csv
78.49 MB
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OffsetValues_2081-2100year.csv
78.49 MB
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README.md
2.97 KB
Abstract
Climate change poses a significant threat to global biodiversity. Evolutionary processes, including adaptation and migration, have been integrated to study vulnerability to changing environments. However, the role of plasticity as a source of variation in fitness-related traits remains less explored when assessing climate change vulnerability. Epigenetic modifications can mediate both evolved and plastic responses to environmental change, thereby contributing crucially to species persistence. Here, we estimated the influence of epigenetic plasticity on the responses of threespine stickleback (Gasterosteus aculeatus) to climate change. We showed that vulnerability to projected climates was the greatest if only plastic loci were available to populations; however, the increased vulnerability could be mitigated by short-distance migration. Our study advances beyond current range modelling by incorporating plasticity into predictions of species’ responses to climate change and demonstrates the contrasting roles of different evolutionary processes in shaping responses to projected environments.
https://doi.org/10.5061/dryad.kkwh70sdh
Description of the data and file structure
The uploaded script is used to recreate all results in the study, including the following analyses. Necessary notes are left in the script for better understanding:
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Redundant analysis for selecting climate-associated CpG sites,
Gradient forest model for ranking the contribution of bioclimatic variables,
Epigenomic turnover for the full model as an example,
Procrustes residuals between the full and plastic models,
Local offset calculation based on the full model as an example,
Permutation analysis to determine whether the increased epigenetic offset values calculated from the plastic model were greater than expected by chance,
Migration distance to offset the increased epigenetic offset due to plasticity,
Difference in local offset based on the full model between marine and freshwater habitats. These were provided as "code_for_GCB.txt".
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Raw methylation data used for the following analysis were provided as "MethylationSitesRaw.csv".
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"OffsetValues_2041-2060year.csv": This file contains local and forward offset values under climate conditions in 2041–2060 years under SSP126 and SSP585. Under each emission scenario, the table consists of longitudes and latitudes of sampling sites, local offset values predicted from the full model, local offset values from the plastic model, and offset values predicted from the plastic model within limited distances ranging from 5 km, 10 km to 20 km. The last column of the table indicates whether the sampling sites are located in freshwater or marine environments. The summarized results of this table can be referred to Table S2 in the supplementary material.
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"OffsetValues_2081-2100year.csv": This file contains local and forward offset values under climate conditions in 2081–2100 years under SSP126 and SSP585. Under each emission scenario, the table consists of longitudes and latitudes of sampling sites, local offset values predicted from the full model, local offset values from the plastic model, and offset values predicted from the plastic model within limited distances ranging from 5 km, 10 km to 20 km. The last column of the table indicates whether the sampling sites are located in freshwater or marine environments. The summarized results of this table can be referred to Table S2 in the supplementary material.
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"bioclimate_raw.csv": This file contains 19 bioclimatic variables (1971–2000, 2.5 arcmin resolution) extracted from WorldClim for sampling sites.
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"env.csv": This file contains geographic, ecological, and bioclimatic variables.
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"cand-methylation.csv": This file contains DNA methylation levels for individual samples.
Code/software
All scripts in the file are written in R (code_for_GCB.R).