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The Application of Multi-Locus GWAS for the Detection of Salt-Tolerance Loci in Rice

Improving the salt-tolerance of direct-seeding rice at the seed germination stage is a major goal of breeders. Efficiently identifying salt tolerance loci will help researchers develop effective rice breeding strategies. In this study, six multi-locus genome-wide association studies (GWAS) methods (...

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Autores principales: Cui, Yanru, Zhang, Fan, Zhou, Yongli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6180169/
https://www.ncbi.nlm.nih.gov/pubmed/30337936
http://dx.doi.org/10.3389/fpls.2018.01464
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author Cui, Yanru
Zhang, Fan
Zhou, Yongli
author_facet Cui, Yanru
Zhang, Fan
Zhou, Yongli
author_sort Cui, Yanru
collection PubMed
description Improving the salt-tolerance of direct-seeding rice at the seed germination stage is a major goal of breeders. Efficiently identifying salt tolerance loci will help researchers develop effective rice breeding strategies. In this study, six multi-locus genome-wide association studies (GWAS) methods (mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, pKWmEB, and ISIS EM-BLASSO) were applied to identify quantitative trait nucleotides (QTNs) for the salt tolerance traits of 478 rice accessions with 162,529 SNPs at the seed germination stage. Among the 371 QTNs detected by the six methods, 56 were identified by at least three methods. Among these 56 QTNs, 12, 6, 7, 4, 13, 12, and 12 were found to be associated with SSI-GI, SSI-VI, SSI-MGT, SSI-IR-24h, SSI-IR-48h, SSI-GR-5d, and SSI-GR-10d, respectively. Additionally, 66 candidate genes were identified in the vicinity of the 56 QTNs, and two of these genes (LOC_Os01g45760 and LOC_Os10g04860) are involved in auxin biosynthesis according to the enriched GO terms and KEGG pathways. This information will be useful for identifying the genes responsible for rice salt tolerance. A comparison of the six methods revealed that ISIS EM-BLASSO identified the most co-detected QTNs and performed best, with the smallest residual errors and highest computing speed, followed by FASTmrMLM, pLARmEB, mrMLM, pKWmEB, and FASTmrEMMA. Although multi-locus GWAS methods are superior to single-locus GWAS methods, their utility for identifying QTNs may be enhanced by adding a bin analysis to the models or by developing a hybrid method that merges the results from different methods.
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spelling pubmed-61801692018-10-18 The Application of Multi-Locus GWAS for the Detection of Salt-Tolerance Loci in Rice Cui, Yanru Zhang, Fan Zhou, Yongli Front Plant Sci Plant Science Improving the salt-tolerance of direct-seeding rice at the seed germination stage is a major goal of breeders. Efficiently identifying salt tolerance loci will help researchers develop effective rice breeding strategies. In this study, six multi-locus genome-wide association studies (GWAS) methods (mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, pKWmEB, and ISIS EM-BLASSO) were applied to identify quantitative trait nucleotides (QTNs) for the salt tolerance traits of 478 rice accessions with 162,529 SNPs at the seed germination stage. Among the 371 QTNs detected by the six methods, 56 were identified by at least three methods. Among these 56 QTNs, 12, 6, 7, 4, 13, 12, and 12 were found to be associated with SSI-GI, SSI-VI, SSI-MGT, SSI-IR-24h, SSI-IR-48h, SSI-GR-5d, and SSI-GR-10d, respectively. Additionally, 66 candidate genes were identified in the vicinity of the 56 QTNs, and two of these genes (LOC_Os01g45760 and LOC_Os10g04860) are involved in auxin biosynthesis according to the enriched GO terms and KEGG pathways. This information will be useful for identifying the genes responsible for rice salt tolerance. A comparison of the six methods revealed that ISIS EM-BLASSO identified the most co-detected QTNs and performed best, with the smallest residual errors and highest computing speed, followed by FASTmrMLM, pLARmEB, mrMLM, pKWmEB, and FASTmrEMMA. Although multi-locus GWAS methods are superior to single-locus GWAS methods, their utility for identifying QTNs may be enhanced by adding a bin analysis to the models or by developing a hybrid method that merges the results from different methods. Frontiers Media S.A. 2018-10-04 /pmc/articles/PMC6180169/ /pubmed/30337936 http://dx.doi.org/10.3389/fpls.2018.01464 Text en Copyright © 2018 Cui, Zhang and Zhou. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Cui, Yanru
Zhang, Fan
Zhou, Yongli
The Application of Multi-Locus GWAS for the Detection of Salt-Tolerance Loci in Rice
title The Application of Multi-Locus GWAS for the Detection of Salt-Tolerance Loci in Rice
title_full The Application of Multi-Locus GWAS for the Detection of Salt-Tolerance Loci in Rice
title_fullStr The Application of Multi-Locus GWAS for the Detection of Salt-Tolerance Loci in Rice
title_full_unstemmed The Application of Multi-Locus GWAS for the Detection of Salt-Tolerance Loci in Rice
title_short The Application of Multi-Locus GWAS for the Detection of Salt-Tolerance Loci in Rice
title_sort application of multi-locus gwas for the detection of salt-tolerance loci in rice
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6180169/
https://www.ncbi.nlm.nih.gov/pubmed/30337936
http://dx.doi.org/10.3389/fpls.2018.01464
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