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Protocol for Projecting Allele Frequency Change under Future Climate Change at Adaptive-Associated Loci
We describe how to predict population-level allele frequency change at loci associated with locally adapted traits under future climate conditions. Our method can identify populations that are at higher risk of local extinction and those that might be prime targets for conservation intervention. We...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7580235/ https://www.ncbi.nlm.nih.gov/pubmed/33111101 http://dx.doi.org/10.1016/j.xpro.2020.100061 |
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author | Blumstein, Meghan Richardson, Andrew Weston, David Zhang, Jin Muchero, Wellington Hopkins, Robin |
author_facet | Blumstein, Meghan Richardson, Andrew Weston, David Zhang, Jin Muchero, Wellington Hopkins, Robin |
author_sort | Blumstein, Meghan |
collection | PubMed |
description | We describe how to predict population-level allele frequency change at loci associated with locally adapted traits under future climate conditions. Our method can identify populations that are at higher risk of local extinction and those that might be prime targets for conservation intervention. We draw on previously developed community ecology statistical methods and apply them in novel ways to plant genomes. While a powerful diagnostic tool, our method requires a wealth of genomic data for use. For complete details on the use and execution of this protocol, please refer to Blumstein et al. (2020). |
format | Online Article Text |
id | pubmed-7580235 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-75802352020-10-26 Protocol for Projecting Allele Frequency Change under Future Climate Change at Adaptive-Associated Loci Blumstein, Meghan Richardson, Andrew Weston, David Zhang, Jin Muchero, Wellington Hopkins, Robin STAR Protoc Protocol We describe how to predict population-level allele frequency change at loci associated with locally adapted traits under future climate conditions. Our method can identify populations that are at higher risk of local extinction and those that might be prime targets for conservation intervention. We draw on previously developed community ecology statistical methods and apply them in novel ways to plant genomes. While a powerful diagnostic tool, our method requires a wealth of genomic data for use. For complete details on the use and execution of this protocol, please refer to Blumstein et al. (2020). Elsevier 2020-07-15 /pmc/articles/PMC7580235/ /pubmed/33111101 http://dx.doi.org/10.1016/j.xpro.2020.100061 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Protocol Blumstein, Meghan Richardson, Andrew Weston, David Zhang, Jin Muchero, Wellington Hopkins, Robin Protocol for Projecting Allele Frequency Change under Future Climate Change at Adaptive-Associated Loci |
title | Protocol for Projecting Allele Frequency Change under Future Climate Change at Adaptive-Associated Loci |
title_full | Protocol for Projecting Allele Frequency Change under Future Climate Change at Adaptive-Associated Loci |
title_fullStr | Protocol for Projecting Allele Frequency Change under Future Climate Change at Adaptive-Associated Loci |
title_full_unstemmed | Protocol for Projecting Allele Frequency Change under Future Climate Change at Adaptive-Associated Loci |
title_short | Protocol for Projecting Allele Frequency Change under Future Climate Change at Adaptive-Associated Loci |
title_sort | protocol for projecting allele frequency change under future climate change at adaptive-associated loci |
topic | Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7580235/ https://www.ncbi.nlm.nih.gov/pubmed/33111101 http://dx.doi.org/10.1016/j.xpro.2020.100061 |
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