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...
| Main Authors: | , , , , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Oxford University Press
2017
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| Online Access: | https://hdl.handle.net/10568/165091 |
| _version_ | 1855533618126913536 |
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| author | Furuta, Tomoyuki Ashikari, Motoyuki Jena, Kshirod K. Doi, Kazuyuki Reuscher, Stefan |
| author_browse | Ashikari, Motoyuki Doi, Kazuyuki Furuta, Tomoyuki Jena, Kshirod K. Reuscher, Stefan |
| author_facet | Furuta, Tomoyuki Ashikari, Motoyuki Jena, Kshirod K. Doi, Kazuyuki Reuscher, Stefan |
| author_sort | Furuta, Tomoyuki |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| 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 | Journal Article |
| id | CGSpace165091 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2017 |
| publishDateRange | 2017 |
| publishDateSort | 2017 |
| publisher | Oxford University Press |
| publisherStr | Oxford University Press |
| record_format | dspace |
| spelling | CGSpace1650912025-05-14T10:24:20Z Adapting genotyping-by-sequencing for rice F2 populations Furuta, Tomoyuki Ashikari, Motoyuki Jena, Kshirod K. Doi, Kazuyuki Reuscher, Stefan 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. 2017-03-01 2024-12-19T12:54:42Z 2024-12-19T12:54:42Z Journal Article https://hdl.handle.net/10568/165091 en Oxford University Press Furuta, Tomoyuki; Ashikari, Motoyuki; Jena, Kshirod K; Doi, Kazuyuki and Reuscher, Stefan. 2017. Adapting genotyping-by-sequencing for rice F2 populations. G3: Genes|Genomes|Genetics, volume 7; pages 881-893, ill. Ref. |
| spellingShingle | 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 |
| url | https://hdl.handle.net/10568/165091 |
| work_keys_str_mv | AT furutatomoyuki adaptinggenotypingbysequencingforricef2populations AT ashikarimotoyuki adaptinggenotypingbysequencingforricef2populations AT jenakshirodk adaptinggenotypingbysequencingforricef2populations AT doikazuyuki adaptinggenotypingbysequencingforricef2populations AT reuscherstefan adaptinggenotypingbysequencingforricef2populations |