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Correlations of Genotype with Climate Parameters Suggest Caenorhabditis elegans Niche Adaptations
Species inhabit a variety of environmental niches, and the adaptation to a particular niche is often controlled by genetic factors, including gene-by-environment interactions. The genes that vary in order to regulate the ability to colonize a niche are often difficult to identify, especially in the...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Genetics Society of America
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5217117/ https://www.ncbi.nlm.nih.gov/pubmed/27866149 http://dx.doi.org/10.1534/g3.116.035162 |
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author | Evans, Kathryn S. Zhao, Yuehui Brady, Shannon C. Long, Lijiang McGrath, Patrick T. Andersen, Erik C. |
author_facet | Evans, Kathryn S. Zhao, Yuehui Brady, Shannon C. Long, Lijiang McGrath, Patrick T. Andersen, Erik C. |
author_sort | Evans, Kathryn S. |
collection | PubMed |
description | Species inhabit a variety of environmental niches, and the adaptation to a particular niche is often controlled by genetic factors, including gene-by-environment interactions. The genes that vary in order to regulate the ability to colonize a niche are often difficult to identify, especially in the context of complex ecological systems and in experimentally uncontrolled natural environments. Quantitative genetic approaches provide an opportunity to investigate correlations between genetic factors and environmental parameters that might define a niche. Previously, we have shown how a collection of 208 whole-genome sequenced wild Caenorhabditis elegans can facilitate association mapping approaches. To correlate climate parameters with the variation found in this collection of wild strains, we used geographic data to exhaustively curate daily weather measurements in short-term (3 month), middle-term (one year), and long-term (three year) durations surrounding the date of strain isolation. These climate parameters were used as quantitative traits in association mapping approaches, where we identified 11 quantitative trait loci (QTL) for three climatic variables: elevation, relative humidity, and average temperature. We then narrowed the genomic interval of interest to identify gene candidates with variants potentially underlying phenotypic differences. Additionally, we performed two-strain competition assays at high and low temperatures to validate a QTL that could underlie adaptation to temperature and found suggestive evidence supporting that hypothesis. |
format | Online Article Text |
id | pubmed-5217117 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Genetics Society of America |
record_format | MEDLINE/PubMed |
spelling | pubmed-52171172017-01-09 Correlations of Genotype with Climate Parameters Suggest Caenorhabditis elegans Niche Adaptations Evans, Kathryn S. Zhao, Yuehui Brady, Shannon C. Long, Lijiang McGrath, Patrick T. Andersen, Erik C. G3 (Bethesda) Investigations Species inhabit a variety of environmental niches, and the adaptation to a particular niche is often controlled by genetic factors, including gene-by-environment interactions. The genes that vary in order to regulate the ability to colonize a niche are often difficult to identify, especially in the context of complex ecological systems and in experimentally uncontrolled natural environments. Quantitative genetic approaches provide an opportunity to investigate correlations between genetic factors and environmental parameters that might define a niche. Previously, we have shown how a collection of 208 whole-genome sequenced wild Caenorhabditis elegans can facilitate association mapping approaches. To correlate climate parameters with the variation found in this collection of wild strains, we used geographic data to exhaustively curate daily weather measurements in short-term (3 month), middle-term (one year), and long-term (three year) durations surrounding the date of strain isolation. These climate parameters were used as quantitative traits in association mapping approaches, where we identified 11 quantitative trait loci (QTL) for three climatic variables: elevation, relative humidity, and average temperature. We then narrowed the genomic interval of interest to identify gene candidates with variants potentially underlying phenotypic differences. Additionally, we performed two-strain competition assays at high and low temperatures to validate a QTL that could underlie adaptation to temperature and found suggestive evidence supporting that hypothesis. Genetics Society of America 2016-11-17 /pmc/articles/PMC5217117/ /pubmed/27866149 http://dx.doi.org/10.1534/g3.116.035162 Text en Copyright © 2017 Evans et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Investigations Evans, Kathryn S. Zhao, Yuehui Brady, Shannon C. Long, Lijiang McGrath, Patrick T. Andersen, Erik C. Correlations of Genotype with Climate Parameters Suggest Caenorhabditis elegans Niche Adaptations |
title | Correlations of Genotype with Climate Parameters Suggest Caenorhabditis elegans Niche Adaptations |
title_full | Correlations of Genotype with Climate Parameters Suggest Caenorhabditis elegans Niche Adaptations |
title_fullStr | Correlations of Genotype with Climate Parameters Suggest Caenorhabditis elegans Niche Adaptations |
title_full_unstemmed | Correlations of Genotype with Climate Parameters Suggest Caenorhabditis elegans Niche Adaptations |
title_short | Correlations of Genotype with Climate Parameters Suggest Caenorhabditis elegans Niche Adaptations |
title_sort | correlations of genotype with climate parameters suggest caenorhabditis elegans niche adaptations |
topic | Investigations |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5217117/ https://www.ncbi.nlm.nih.gov/pubmed/27866149 http://dx.doi.org/10.1534/g3.116.035162 |
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