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Haplotype-based allele mining in the Japan-MAGIC rice population
Multi-parent advanced generation inter-cross (MAGIC) lines have broader genetic variation than bi-parental recombinant inbred lines. Genome-wide association study (GWAS) using high number of DNA polymorphisms such as single-nucleotide polymorphisms (SNPs) is a popular tool for allele mining in MAGIC...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5847589/ https://www.ncbi.nlm.nih.gov/pubmed/29531264 http://dx.doi.org/10.1038/s41598-018-22657-3 |
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author | Ogawa, Daisuke Yamamoto, Eiji Ohtani, Toshikazu Kanno, Noriko Tsunematsu, Hiroshi Nonoue, Yasunori Yano, Masahiro Yamamoto, Toshio Yonemaru, Jun-ichi |
author_facet | Ogawa, Daisuke Yamamoto, Eiji Ohtani, Toshikazu Kanno, Noriko Tsunematsu, Hiroshi Nonoue, Yasunori Yano, Masahiro Yamamoto, Toshio Yonemaru, Jun-ichi |
author_sort | Ogawa, Daisuke |
collection | PubMed |
description | Multi-parent advanced generation inter-cross (MAGIC) lines have broader genetic variation than bi-parental recombinant inbred lines. Genome-wide association study (GWAS) using high number of DNA polymorphisms such as single-nucleotide polymorphisms (SNPs) is a popular tool for allele mining in MAGIC populations, in which the associations of phenotypes with SNPs are investigated; however, the effects of haplotypes from multiple founders on phenotypes are not considered. Here, we describe an improved method of allele mining using the newly developed Japan-MAGIC (JAM) population, which is derived from eight high-yielding rice cultivars in Japan. To obtain information on the haplotypes in the JAM lines, we predicted the haplotype blocks in the whole chromosomes using 16,345 SNPs identified via genotyping-by-sequencing analysis. Using haplotype-based GWAS, we clearly detected the loci controlling the glutinous endosperm and culm length traits. Information on the alleles of the eight founders, which was based on the effects of mutations revealed by the analysis of next-generation sequencing data, was used to narrow down the candidate genes and reveal the associations between alleles and phenotypes. The haplotype-based allele mining (HAM) proposed in this study is a promising approach to the detection of allelic variation in genes controlling agronomic traits in MAGIC populations. |
format | Online Article Text |
id | pubmed-5847589 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-58475892018-03-19 Haplotype-based allele mining in the Japan-MAGIC rice population Ogawa, Daisuke Yamamoto, Eiji Ohtani, Toshikazu Kanno, Noriko Tsunematsu, Hiroshi Nonoue, Yasunori Yano, Masahiro Yamamoto, Toshio Yonemaru, Jun-ichi Sci Rep Article Multi-parent advanced generation inter-cross (MAGIC) lines have broader genetic variation than bi-parental recombinant inbred lines. Genome-wide association study (GWAS) using high number of DNA polymorphisms such as single-nucleotide polymorphisms (SNPs) is a popular tool for allele mining in MAGIC populations, in which the associations of phenotypes with SNPs are investigated; however, the effects of haplotypes from multiple founders on phenotypes are not considered. Here, we describe an improved method of allele mining using the newly developed Japan-MAGIC (JAM) population, which is derived from eight high-yielding rice cultivars in Japan. To obtain information on the haplotypes in the JAM lines, we predicted the haplotype blocks in the whole chromosomes using 16,345 SNPs identified via genotyping-by-sequencing analysis. Using haplotype-based GWAS, we clearly detected the loci controlling the glutinous endosperm and culm length traits. Information on the alleles of the eight founders, which was based on the effects of mutations revealed by the analysis of next-generation sequencing data, was used to narrow down the candidate genes and reveal the associations between alleles and phenotypes. The haplotype-based allele mining (HAM) proposed in this study is a promising approach to the detection of allelic variation in genes controlling agronomic traits in MAGIC populations. Nature Publishing Group UK 2018-03-12 /pmc/articles/PMC5847589/ /pubmed/29531264 http://dx.doi.org/10.1038/s41598-018-22657-3 Text en © The Author(s) 2018 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Ogawa, Daisuke Yamamoto, Eiji Ohtani, Toshikazu Kanno, Noriko Tsunematsu, Hiroshi Nonoue, Yasunori Yano, Masahiro Yamamoto, Toshio Yonemaru, Jun-ichi Haplotype-based allele mining in the Japan-MAGIC rice population |
title | Haplotype-based allele mining in the Japan-MAGIC rice population |
title_full | Haplotype-based allele mining in the Japan-MAGIC rice population |
title_fullStr | Haplotype-based allele mining in the Japan-MAGIC rice population |
title_full_unstemmed | Haplotype-based allele mining in the Japan-MAGIC rice population |
title_short | Haplotype-based allele mining in the Japan-MAGIC rice population |
title_sort | haplotype-based allele mining in the japan-magic rice population |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5847589/ https://www.ncbi.nlm.nih.gov/pubmed/29531264 http://dx.doi.org/10.1038/s41598-018-22657-3 |
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