Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Feng, Shuo, Xi, Erning, Wan, Wei, Ru, Dafu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
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
_version_ 1785130790470811648
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
work_keys_str_mv AT fengshuo genomicsignalsoflocaladaptationinpiceacrassifolia
AT xierning genomicsignalsoflocaladaptationinpiceacrassifolia
AT wanwei genomicsignalsoflocaladaptationinpiceacrassifolia
AT rudafu genomicsignalsoflocaladaptationinpiceacrassifolia