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Population Structure of Nation-Wide Rice in Thailand

BACKGROUND: Thailand is a country with large diversity in rice varieties due to its rich and diverse ecology. In this paper, 300 rice accessions from all across Thailand were sequenced to identify SNP variants allowing for the population structure to be explored. RESULTS: The result of inferred popu...

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Autores principales: Vejchasarn, Phanchita, Shearman, Jeremy R., Chaiprom, Usawadee, Phansenee, Yotwarit, Suthanthangjai, Arissara, Jairin, Jirapong, Chamarerk, Varapong, Tulyananda, Tatpong, Amornbunchornvej, Chainarong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8542525/
https://www.ncbi.nlm.nih.gov/pubmed/34693480
http://dx.doi.org/10.1186/s12284-021-00528-2
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author Vejchasarn, Phanchita
Shearman, Jeremy R.
Chaiprom, Usawadee
Phansenee, Yotwarit
Suthanthangjai, Arissara
Jairin, Jirapong
Chamarerk, Varapong
Tulyananda, Tatpong
Amornbunchornvej, Chainarong
author_facet Vejchasarn, Phanchita
Shearman, Jeremy R.
Chaiprom, Usawadee
Phansenee, Yotwarit
Suthanthangjai, Arissara
Jairin, Jirapong
Chamarerk, Varapong
Tulyananda, Tatpong
Amornbunchornvej, Chainarong
author_sort Vejchasarn, Phanchita
collection PubMed
description BACKGROUND: Thailand is a country with large diversity in rice varieties due to its rich and diverse ecology. In this paper, 300 rice accessions from all across Thailand were sequenced to identify SNP variants allowing for the population structure to be explored. RESULTS: The result of inferred population structure from admixture and clustering analysis illustrated strong evidence of substructure in each geographical region. The results of phylogenetic tree, PCA analysis, and machine learning on population identifying SNPs also supported the inferred population structure. CONCLUSION: The population structure inferred in this study contains five subpopulations that tend to group individuals based on location. So, each subpopulation has unique genetic patterns, agronomic traits, as well as different environmental conditions. This study can serve as a reference point of the nation-wide population structure for supporting breeders and researchers who are interested in Thai rice. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12284-021-00528-2.
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spelling pubmed-85425252021-11-10 Population Structure of Nation-Wide Rice in Thailand Vejchasarn, Phanchita Shearman, Jeremy R. Chaiprom, Usawadee Phansenee, Yotwarit Suthanthangjai, Arissara Jairin, Jirapong Chamarerk, Varapong Tulyananda, Tatpong Amornbunchornvej, Chainarong Rice (N Y) Original Article BACKGROUND: Thailand is a country with large diversity in rice varieties due to its rich and diverse ecology. In this paper, 300 rice accessions from all across Thailand were sequenced to identify SNP variants allowing for the population structure to be explored. RESULTS: The result of inferred population structure from admixture and clustering analysis illustrated strong evidence of substructure in each geographical region. The results of phylogenetic tree, PCA analysis, and machine learning on population identifying SNPs also supported the inferred population structure. CONCLUSION: The population structure inferred in this study contains five subpopulations that tend to group individuals based on location. So, each subpopulation has unique genetic patterns, agronomic traits, as well as different environmental conditions. This study can serve as a reference point of the nation-wide population structure for supporting breeders and researchers who are interested in Thai rice. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12284-021-00528-2. Springer US 2021-10-24 /pmc/articles/PMC8542525/ /pubmed/34693480 http://dx.doi.org/10.1186/s12284-021-00528-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/) .
spellingShingle Original Article
Vejchasarn, Phanchita
Shearman, Jeremy R.
Chaiprom, Usawadee
Phansenee, Yotwarit
Suthanthangjai, Arissara
Jairin, Jirapong
Chamarerk, Varapong
Tulyananda, Tatpong
Amornbunchornvej, Chainarong
Population Structure of Nation-Wide Rice in Thailand
title Population Structure of Nation-Wide Rice in Thailand
title_full Population Structure of Nation-Wide Rice in Thailand
title_fullStr Population Structure of Nation-Wide Rice in Thailand
title_full_unstemmed Population Structure of Nation-Wide Rice in Thailand
title_short Population Structure of Nation-Wide Rice in Thailand
title_sort population structure of nation-wide rice in thailand
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8542525/
https://www.ncbi.nlm.nih.gov/pubmed/34693480
http://dx.doi.org/10.1186/s12284-021-00528-2
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