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Genomic signals of local adaptation in Picea crassifolia
BACKGROUND: Global climate change poses a grave threat to biodiversity and underscores the importance of identifying the genes and corresponding environmental factors involved in the adaptation of tree species for the purposes of conservation and forestry. This holds particularly true for spruce spe...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10623705/ https://www.ncbi.nlm.nih.gov/pubmed/37919677 http://dx.doi.org/10.1186/s12870-023-04539-7 |
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author | Feng, Shuo Xi, Erning Wan, Wei Ru, Dafu |
author_facet | Feng, Shuo Xi, Erning Wan, Wei Ru, Dafu |
author_sort | Feng, Shuo |
collection | PubMed |
description | BACKGROUND: Global climate change poses a grave threat to biodiversity and underscores the importance of identifying the genes and corresponding environmental factors involved in the adaptation of tree species for the purposes of conservation and forestry. This holds particularly true for spruce species, given their pivotal role as key constituents of the montane, boreal, and sub-alpine forests in the Northern Hemisphere. RESULTS: Here, we used transcriptomes, species occurrence records, and environmental data to investigate the spatial genetic distribution of and the climate-associated genetic variation in Picea crassifolia. Our comprehensive analysis employing ADMIXTURE, principal component analysis (PCA) and phylogenetic methodologies showed that the species has a complex population structure with obvious differentiation among populations in different regions. Concurrently, our investigations into isolation by distance (IBD), isolation by environment (IBE), and niche differentiation among populations collectively suggests that local adaptations are driven by environmental heterogeneity. By integrating population genomics and environmental data using redundancy analysis (RDA), we identified a set of climate-associated single-nucleotide polymorphisms (SNPs) and showed that environmental isolation had a more significant impact than geographic isolation in promoting genetic differentiation. We also found that the candidate genes associated with altitude, temperature seasonality (Bio4) and precipitation in the wettest month (Bio13) may be useful for forest tree breeding. CONCLUSIONS: Our findings deepen our understanding of how species respond to climate change and highlight the importance of integrating genomic and environmental data in untangling local adaptations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12870-023-04539-7. |
format | Online Article Text |
id | pubmed-10623705 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-106237052023-11-04 Genomic signals of local adaptation in Picea crassifolia Feng, Shuo Xi, Erning Wan, Wei Ru, Dafu BMC Plant Biol Research BACKGROUND: Global climate change poses a grave threat to biodiversity and underscores the importance of identifying the genes and corresponding environmental factors involved in the adaptation of tree species for the purposes of conservation and forestry. This holds particularly true for spruce species, given their pivotal role as key constituents of the montane, boreal, and sub-alpine forests in the Northern Hemisphere. RESULTS: Here, we used transcriptomes, species occurrence records, and environmental data to investigate the spatial genetic distribution of and the climate-associated genetic variation in Picea crassifolia. Our comprehensive analysis employing ADMIXTURE, principal component analysis (PCA) and phylogenetic methodologies showed that the species has a complex population structure with obvious differentiation among populations in different regions. Concurrently, our investigations into isolation by distance (IBD), isolation by environment (IBE), and niche differentiation among populations collectively suggests that local adaptations are driven by environmental heterogeneity. By integrating population genomics and environmental data using redundancy analysis (RDA), we identified a set of climate-associated single-nucleotide polymorphisms (SNPs) and showed that environmental isolation had a more significant impact than geographic isolation in promoting genetic differentiation. We also found that the candidate genes associated with altitude, temperature seasonality (Bio4) and precipitation in the wettest month (Bio13) may be useful for forest tree breeding. CONCLUSIONS: Our findings deepen our understanding of how species respond to climate change and highlight the importance of integrating genomic and environmental data in untangling local adaptations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12870-023-04539-7. BioMed Central 2023-11-03 /pmc/articles/PMC10623705/ /pubmed/37919677 http://dx.doi.org/10.1186/s12870-023-04539-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Feng, Shuo Xi, Erning Wan, Wei Ru, Dafu Genomic signals of local adaptation in Picea crassifolia |
title | Genomic signals of local adaptation in Picea crassifolia |
title_full | Genomic signals of local adaptation in Picea crassifolia |
title_fullStr | Genomic signals of local adaptation in Picea crassifolia |
title_full_unstemmed | Genomic signals of local adaptation in Picea crassifolia |
title_short | Genomic signals of local adaptation in Picea crassifolia |
title_sort | genomic signals of local adaptation in picea crassifolia |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10623705/ https://www.ncbi.nlm.nih.gov/pubmed/37919677 http://dx.doi.org/10.1186/s12870-023-04539-7 |
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