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Identifying loci with breeding potential across temperate and tropical adaptation via EigenGWAS and EnvGWAS
Understanding the genomic basis of adaptation in maize is important for gene discovery and the improvement of breeding germplasm, but much remains a mystery in spite of significant population genetics and archaeological research. Identifying the signals underpinning adaptation are challenging as ada...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6851670/ https://www.ncbi.nlm.nih.gov/pubmed/31287919 http://dx.doi.org/10.1111/mec.15169 |
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author | Li, Jing Chen, Guo‐Bo Rasheed, Awais Li, Delin Sonder, Kai Zavala Espinosa, Cristian Wang, Jiankang Costich, Denise E. Schnable, Patrick S. Hearne, Sarah J. Li, Huihui |
author_facet | Li, Jing Chen, Guo‐Bo Rasheed, Awais Li, Delin Sonder, Kai Zavala Espinosa, Cristian Wang, Jiankang Costich, Denise E. Schnable, Patrick S. Hearne, Sarah J. Li, Huihui |
author_sort | Li, Jing |
collection | PubMed |
description | Understanding the genomic basis of adaptation in maize is important for gene discovery and the improvement of breeding germplasm, but much remains a mystery in spite of significant population genetics and archaeological research. Identifying the signals underpinning adaptation are challenging as adaptation often coincided with genetic drift, and the base genomic diversity of the species in massive. In this study, tGBS technology was used to genotype 1,143 diverse maize accessions including landraces collected from 20 countries and elite breeding lines of tropical lowland, highland, subtropical/midaltitude and temperate ecological zones. Based on 355,442 high‐quality single nucleotide polymorphisms, 13 genomic regions were detected as being under selection using the bottom‐up searching strategy, EigenGWAS. Of the 13 selection regions, 10 were first reported, two were associated with environmental parameters via EnvGWAS, and 146 genes were enriched. Combining large‐scale genomic and ecological data in this diverse maize panel, our study supports a polygenic adaptation model of maize and offers a framework to enhance our understanding of both the mechanistic basis and the evolutionary consequences of maize domestication and adaptation. The regions identified here are promising candidates for further, targeted exploration to identify beneficial alleles and haplotypes for deployment in maize breeding. |
format | Online Article Text |
id | pubmed-6851670 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-68516702019-11-18 Identifying loci with breeding potential across temperate and tropical adaptation via EigenGWAS and EnvGWAS Li, Jing Chen, Guo‐Bo Rasheed, Awais Li, Delin Sonder, Kai Zavala Espinosa, Cristian Wang, Jiankang Costich, Denise E. Schnable, Patrick S. Hearne, Sarah J. Li, Huihui Mol Ecol ORIGINAL ARTICLES Understanding the genomic basis of adaptation in maize is important for gene discovery and the improvement of breeding germplasm, but much remains a mystery in spite of significant population genetics and archaeological research. Identifying the signals underpinning adaptation are challenging as adaptation often coincided with genetic drift, and the base genomic diversity of the species in massive. In this study, tGBS technology was used to genotype 1,143 diverse maize accessions including landraces collected from 20 countries and elite breeding lines of tropical lowland, highland, subtropical/midaltitude and temperate ecological zones. Based on 355,442 high‐quality single nucleotide polymorphisms, 13 genomic regions were detected as being under selection using the bottom‐up searching strategy, EigenGWAS. Of the 13 selection regions, 10 were first reported, two were associated with environmental parameters via EnvGWAS, and 146 genes were enriched. Combining large‐scale genomic and ecological data in this diverse maize panel, our study supports a polygenic adaptation model of maize and offers a framework to enhance our understanding of both the mechanistic basis and the evolutionary consequences of maize domestication and adaptation. The regions identified here are promising candidates for further, targeted exploration to identify beneficial alleles and haplotypes for deployment in maize breeding. John Wiley and Sons Inc. 2019-08-18 2019-08 /pmc/articles/PMC6851670/ /pubmed/31287919 http://dx.doi.org/10.1111/mec.15169 Text en © 2019 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | ORIGINAL ARTICLES Li, Jing Chen, Guo‐Bo Rasheed, Awais Li, Delin Sonder, Kai Zavala Espinosa, Cristian Wang, Jiankang Costich, Denise E. Schnable, Patrick S. Hearne, Sarah J. Li, Huihui Identifying loci with breeding potential across temperate and tropical adaptation via EigenGWAS and EnvGWAS |
title | Identifying loci with breeding potential across temperate and tropical adaptation via EigenGWAS and EnvGWAS |
title_full | Identifying loci with breeding potential across temperate and tropical adaptation via EigenGWAS and EnvGWAS |
title_fullStr | Identifying loci with breeding potential across temperate and tropical adaptation via EigenGWAS and EnvGWAS |
title_full_unstemmed | Identifying loci with breeding potential across temperate and tropical adaptation via EigenGWAS and EnvGWAS |
title_short | Identifying loci with breeding potential across temperate and tropical adaptation via EigenGWAS and EnvGWAS |
title_sort | identifying loci with breeding potential across temperate and tropical adaptation via eigengwas and envgwas |
topic | ORIGINAL ARTICLES |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6851670/ https://www.ncbi.nlm.nih.gov/pubmed/31287919 http://dx.doi.org/10.1111/mec.15169 |
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