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Adapting Genotyping-by-Sequencing for Rice F2 Populations
Rapid and cost-effective genotyping of large mapping populations can be achieved by sequencing a reduced representation of the genome of every individual in a given population, and using that information to generate genetic markers. A customized genotyping-by-sequencing (GBS) pipeline was developed...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Genetics Society of America
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5345719/ https://www.ncbi.nlm.nih.gov/pubmed/28082325 http://dx.doi.org/10.1534/g3.116.038190 |
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author | Furuta, Tomoyuki Ashikari, Motoyuki Jena, Kshirod K. Doi, Kazuyuki Reuscher, Stefan |
author_facet | Furuta, Tomoyuki Ashikari, Motoyuki Jena, Kshirod K. Doi, Kazuyuki Reuscher, Stefan |
author_sort | Furuta, Tomoyuki |
collection | PubMed |
description | Rapid and cost-effective genotyping of large mapping populations can be achieved by sequencing a reduced representation of the genome of every individual in a given population, and using that information to generate genetic markers. A customized genotyping-by-sequencing (GBS) pipeline was developed to genotype a rice F2 population from a cross of Oryza sativa ssp. japonica cv. Nipponbare and the African wild rice species O. longistaminata. While most GBS pipelines aim to analyze mainly homozygous populations, we attempted to genotype a highly heterozygous F2 population. We show how species- and population-specific improvements of established protocols can drastically increase sample throughput and genotype quality. Using as few as 50,000 reads for some individuals (134,000 reads on average), we were able to generate up to 8154 informative SNP markers in 1081 F2 individuals. Additionally, the effects of enzyme choice, read coverage, and data postprocessing are evaluated. Using GBS-derived markers, we were able to assemble a genetic map of 1536 cM. To demonstrate the usefulness of our GBS pipeline, we determined quantitative trait loci (QTL) for the number of tillers. We were able to map four QTL to chromosomes 1, 3, 4, and 8, and partially confirm their effects using introgression lines. We provide an example of how to successfully use GBS with heterozygous F2 populations. By using the comparatively low-cost MiSeq platform, we show that the GBS method is flexible and cost-effective, even for smaller laboratories. |
format | Online Article Text |
id | pubmed-5345719 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Genetics Society of America |
record_format | MEDLINE/PubMed |
spelling | pubmed-53457192017-03-21 Adapting Genotyping-by-Sequencing for Rice F2 Populations Furuta, Tomoyuki Ashikari, Motoyuki Jena, Kshirod K. Doi, Kazuyuki Reuscher, Stefan G3 (Bethesda) Investigations Rapid and cost-effective genotyping of large mapping populations can be achieved by sequencing a reduced representation of the genome of every individual in a given population, and using that information to generate genetic markers. A customized genotyping-by-sequencing (GBS) pipeline was developed to genotype a rice F2 population from a cross of Oryza sativa ssp. japonica cv. Nipponbare and the African wild rice species O. longistaminata. While most GBS pipelines aim to analyze mainly homozygous populations, we attempted to genotype a highly heterozygous F2 population. We show how species- and population-specific improvements of established protocols can drastically increase sample throughput and genotype quality. Using as few as 50,000 reads for some individuals (134,000 reads on average), we were able to generate up to 8154 informative SNP markers in 1081 F2 individuals. Additionally, the effects of enzyme choice, read coverage, and data postprocessing are evaluated. Using GBS-derived markers, we were able to assemble a genetic map of 1536 cM. To demonstrate the usefulness of our GBS pipeline, we determined quantitative trait loci (QTL) for the number of tillers. We were able to map four QTL to chromosomes 1, 3, 4, and 8, and partially confirm their effects using introgression lines. We provide an example of how to successfully use GBS with heterozygous F2 populations. By using the comparatively low-cost MiSeq platform, we show that the GBS method is flexible and cost-effective, even for smaller laboratories. Genetics Society of America 2017-01-11 /pmc/articles/PMC5345719/ /pubmed/28082325 http://dx.doi.org/10.1534/g3.116.038190 Text en Copyright © 2017 Furuta 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 Furuta, Tomoyuki Ashikari, Motoyuki Jena, Kshirod K. Doi, Kazuyuki Reuscher, Stefan Adapting Genotyping-by-Sequencing for Rice F2 Populations |
title | Adapting Genotyping-by-Sequencing for Rice F2 Populations |
title_full | Adapting Genotyping-by-Sequencing for Rice F2 Populations |
title_fullStr | Adapting Genotyping-by-Sequencing for Rice F2 Populations |
title_full_unstemmed | Adapting Genotyping-by-Sequencing for Rice F2 Populations |
title_short | Adapting Genotyping-by-Sequencing for Rice F2 Populations |
title_sort | adapting genotyping-by-sequencing for rice f2 populations |
topic | Investigations |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5345719/ https://www.ncbi.nlm.nih.gov/pubmed/28082325 http://dx.doi.org/10.1534/g3.116.038190 |
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