Incorporating genetic load contributes to predicting Arabidopsis thaliana’s response to climate change
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 a...
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| Format: | Article |
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Nature Portfolio
2025-03-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-58021-z |
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| author | Juan Jiang Jia-Fu Chen Xin-Tong Li Li Wang Jian-Feng Mao Bao-Sheng Wang Ya-Long Guo |
| author_facet | Juan Jiang Jia-Fu Chen Xin-Tong Li Li Wang Jian-Feng Mao Bao-Sheng Wang Ya-Long Guo |
| author_sort | Juan Jiang |
| collection | DOAJ |
| description | 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 (N e ) 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, N e 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. |
| format | Article |
| id | doaj-art-5f51abe05e124dbea80c6fa2e2c240bf |
| institution | DOAJ |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-5f51abe05e124dbea80c6fa2e2c240bf2025-08-20T02:52:19ZengNature PortfolioNature Communications2041-17232025-03-0116111210.1038/s41467-025-58021-zIncorporating genetic load contributes to predicting Arabidopsis thaliana’s response to climate changeJuan Jiang0Jia-Fu Chen1Xin-Tong Li2Li Wang3Jian-Feng Mao4Bao-Sheng Wang5Ya-Long Guo6State Key Laboratory of Plant Diversity and Specialty Crops/State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of SciencesState Key Laboratory of Plant Diversity and Specialty Crops/State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of SciencesState Key Laboratory of Plant Diversity and Specialty Crops/State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of SciencesAgricultural Synthetic Biology Center, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural SciencesDepartment of Plant Physiology, Umeå Plant Science Centre, Umeå UniversityKey Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of SciencesState Key Laboratory of Plant Diversity and Specialty Crops/State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of SciencesAbstract 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 (N e ) 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, N e 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.https://doi.org/10.1038/s41467-025-58021-z |
| spellingShingle | Juan Jiang Jia-Fu Chen Xin-Tong Li Li Wang Jian-Feng Mao Bao-Sheng Wang Ya-Long Guo Incorporating genetic load contributes to predicting Arabidopsis thaliana’s response to climate change Nature Communications |
| title | Incorporating genetic load contributes to predicting Arabidopsis thaliana’s response to climate change |
| title_full | Incorporating genetic load contributes to predicting Arabidopsis thaliana’s response to climate change |
| title_fullStr | Incorporating genetic load contributes to predicting Arabidopsis thaliana’s response to climate change |
| title_full_unstemmed | Incorporating genetic load contributes to predicting Arabidopsis thaliana’s response to climate change |
| title_short | Incorporating genetic load contributes to predicting Arabidopsis thaliana’s response to climate change |
| title_sort | incorporating genetic load contributes to predicting arabidopsis thaliana s response to climate change |
| url | https://doi.org/10.1038/s41467-025-58021-z |
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