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: | Article |
| Language: | English |
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Oxford University Press
2017-03-01
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| Series: | G3: Genes, Genomes, Genetics |
| Subjects: | |
| Online Access: | http://g3journal.org/lookup/doi/10.1534/g3.116.038190 |
| _version_ | 1818567993246875648 |
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| author | Tomoyuki Furuta Motoyuki Ashikari Kshirod K. Jena Kazuyuki Doi Stefan Reuscher |
| author_facet | Tomoyuki Furuta Motoyuki Ashikari Kshirod K. Jena Kazuyuki Doi Stefan Reuscher |
| author_sort | Tomoyuki Furuta |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-14T06:30:26Z |
| format | Article |
| id | doaj.art-43bbf1a0122b4651818f006cf2bf6e9c |
| institution | Directory Open Access Journal |
| issn | 2160-1836 |
| language | English |
| last_indexed | 2024-12-14T06:30:26Z |
| publishDate | 2017-03-01 |
| publisher | Oxford University Press |
| record_format | Article |
| series | G3: Genes, Genomes, Genetics |
| spelling | doaj.art-43bbf1a0122b4651818f006cf2bf6e9c2022-12-21T23:13:32ZengOxford University PressG3: Genes, Genomes, Genetics2160-18362017-03-017388189310.1534/g3.116.03819013Adapting Genotyping-by-Sequencing for Rice F2 PopulationsTomoyuki FurutaMotoyuki AshikariKshirod K. JenaKazuyuki DoiStefan ReuscherRapid 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.http://g3journal.org/lookup/doi/10.1534/g3.116.038190genotyping-by-sequencingSNP markerrice breedingtrait mapping |
| spellingShingle | Tomoyuki Furuta Motoyuki Ashikari Kshirod K. Jena Kazuyuki Doi Stefan Reuscher Adapting Genotyping-by-Sequencing for Rice F2 Populations G3: Genes, Genomes, Genetics genotyping-by-sequencing SNP marker rice breeding trait mapping |
| 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 | genotyping-by-sequencing SNP marker rice breeding trait mapping |
| url | http://g3journal.org/lookup/doi/10.1534/g3.116.038190 |
| work_keys_str_mv | AT tomoyukifuruta adaptinggenotypingbysequencingforricef2populations AT motoyukiashikari adaptinggenotypingbysequencingforricef2populations AT kshirodkjena adaptinggenotypingbysequencingforricef2populations AT kazuyukidoi adaptinggenotypingbysequencingforricef2populations AT stefanreuscher adaptinggenotypingbysequencingforricef2populations |