Incorporating genetic load contributes to predicting Arabidopsis thaliana’s response to climate change. Jiang, J., Chen, J., Li, X., Wang, L., Mao, J., Wang, B., & Guo, Y. Nature Communications, 16(1):2752, March, 2025. Publisher: Nature Publishing Group![Incorporating genetic load contributes to predicting Arabidopsis thaliana’s response to climate change [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Understanding how species respond to climate change can facilitate species conservation and crop breeding. Current prediction frameworks about population vulnerability focused on predicting range shifts or local adaptation but ignored genetic load, which is also crucial for adaptation. By analyzing 1115 globally distributed Arabidopsis thaliana natural accessions, we find that effective population size (Ne) is the major contributor of genetic load variation, both along genome and among populations, and can explain 74-94% genetic load variation in natural populations. Intriguingly, Ne affects genetic load by changing both effectiveness of purifying selection and GC biased gene conversion strength. In particular, by incorporating genetic load, genetic offset and species distribution models (SDM), we predict that, the populations at species’ range edge are generally at higher risk. The populations at the eastern range perform poorer in all aspects, southern range have higher genetic offset and lower SDM suitability, while northern range have higher genetic load. Among the diverse natural populations, the Yangtze River basin population is the most vulnerable population under future climate change. Overall, here we deciphered the driving forces of genetic load in A. thaliana, and incorporated SDM, local adaptation and genetic load to predict the fate of populations under future climate change.
@article{jiang_incorporating_2025,
title = {Incorporating genetic load contributes to predicting {Arabidopsis} thaliana’s response to climate change},
volume = {16},
copyright = {2025 The Author(s)},
issn = {2041-1723},
url = {https://www.nature.com/articles/s41467-025-58021-z},
doi = {10.1038/s41467-025-58021-z},
abstract = {Understanding how species respond to climate change can facilitate species conservation and crop breeding. Current prediction frameworks about population vulnerability focused on predicting range shifts or local adaptation but ignored genetic load, which is also crucial for adaptation. By analyzing 1115 globally distributed Arabidopsis thaliana natural accessions, we find that effective population size (Ne) is the major contributor of genetic load variation, both along genome and among populations, and can explain 74-94\% genetic load variation in natural populations. Intriguingly, Ne affects genetic load by changing both effectiveness of purifying selection and GC biased gene conversion strength. In particular, by incorporating genetic load, genetic offset and species distribution models (SDM), we predict that, the populations at species’ range edge are generally at higher risk. The populations at the eastern range perform poorer in all aspects, southern range have higher genetic offset and lower SDM suitability, while northern range have higher genetic load. Among the diverse natural populations, the Yangtze River basin population is the most vulnerable population under future climate change. Overall, here we deciphered the driving forces of genetic load in A. thaliana, and incorporated SDM, local adaptation and genetic load to predict the fate of populations under future climate change.},
language = {en},
number = {1},
urldate = {2025-04-04},
journal = {Nature Communications},
author = {Jiang, Juan and Chen, Jia-Fu and Li, Xin-Tong and Wang, Li and Mao, Jian-Feng and Wang, Bao-Sheng and Guo, Ya-Long},
month = mar,
year = {2025},
note = {Publisher: Nature Publishing Group},
keywords = {Conservation biology, Evolutionary genetics, Molecular evolution, Population genetics},
pages = {2752},
}
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By analyzing 1115 globally distributed Arabidopsis thaliana natural accessions, we find that effective population size (Ne) is the major contributor of genetic load variation, both along genome and among populations, and can explain 74-94% genetic load variation in natural populations. Intriguingly, Ne affects genetic load by changing both effectiveness of purifying selection and GC biased gene conversion strength. In particular, by incorporating genetic load, genetic offset and species distribution models (SDM), we predict that, the populations at species’ range edge are generally at higher risk. The populations at the eastern range perform poorer in all aspects, southern range have higher genetic offset and lower SDM suitability, while northern range have higher genetic load. Among the diverse natural populations, the Yangtze River basin population is the most vulnerable population under future climate change. 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