Approaches in characterizing genetic structure and mapping in a rice multiparental population
Multi-parent Advanced Generation Intercross (MAGIC) populations are fast becoming mainstream tools for research and breeding, along with the technology and tools for analysis. This paper demonstrates the analysis of a rice MAGIC population from data filtering to imputation and processing of genetic...
| 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/10568/165047 |
| _version_ | 1855517654102573056 |
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| author | Raghavan, Chitra Mauleon, Ramil Lacorte, Vanica Jubay, Monalisa Zaw, Hein Bonifacio, Justine Singh, Rakesh Kumar Huang, B Emma Leung, Hei |
| author_browse | Bonifacio, Justine Huang, B Emma Jubay, Monalisa Lacorte, Vanica Leung, Hei Mauleon, Ramil Raghavan, Chitra Singh, Rakesh Kumar Zaw, Hein |
| author_facet | Raghavan, Chitra Mauleon, Ramil Lacorte, Vanica Jubay, Monalisa Zaw, Hein Bonifacio, Justine Singh, Rakesh Kumar Huang, B Emma Leung, Hei |
| author_sort | Raghavan, Chitra |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Multi-parent Advanced Generation Intercross (MAGIC) populations are fast becoming mainstream tools for research and breeding, along with the technology and tools for analysis. This paper demonstrates the analysis of a rice MAGIC population from data filtering to imputation and processing of genetic data to characterizing genomic structure, and finally quantitative trait loci (QTL) mapping. In this study, 1316 S6:8 indica MAGIC (MI) lines and the eight founders were sequenced using Genotyping by Sequencing (GBS). As the GBS approach often includes missing data, the first step was to impute the missing SNPs. The observable number of recombinations in the population was then explored. Based on this case study, a general outline of procedures for a MAGIC analysis workflow is provided, as well as for QTL mapping of agronomic traits and biotic and abiotic stress, using the results from both association and interval mapping approaches. QTL for agronomic traits (yield, flowering time, and plant height), physical (grain length and grain width) and cooking properties (amylose content) of the rice grain, abiotic stress (submergence tolerance), and biotic stress (brown spot disease) were mapped. Through presenting this extensive analysis in the MI population in rice, we highlight important considerations when choosing analytical approaches. The methods and results reported in this paper will provide a guide to future genetic analysis methods applied to multi-parent populations. |
| format | Journal Article |
| id | CGSpace165047 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2017 |
| publishDateRange | 2017 |
| publishDateSort | 2017 |
| publisher | Oxford University Press |
| publisherStr | Oxford University Press |
| record_format | dspace |
| spelling | CGSpace1650472025-01-24T14:12:12Z Approaches in characterizing genetic structure and mapping in a rice multiparental population Raghavan, Chitra Mauleon, Ramil Lacorte, Vanica Jubay, Monalisa Zaw, Hein Bonifacio, Justine Singh, Rakesh Kumar Huang, B Emma Leung, Hei Multi-parent Advanced Generation Intercross (MAGIC) populations are fast becoming mainstream tools for research and breeding, along with the technology and tools for analysis. This paper demonstrates the analysis of a rice MAGIC population from data filtering to imputation and processing of genetic data to characterizing genomic structure, and finally quantitative trait loci (QTL) mapping. In this study, 1316 S6:8 indica MAGIC (MI) lines and the eight founders were sequenced using Genotyping by Sequencing (GBS). As the GBS approach often includes missing data, the first step was to impute the missing SNPs. The observable number of recombinations in the population was then explored. Based on this case study, a general outline of procedures for a MAGIC analysis workflow is provided, as well as for QTL mapping of agronomic traits and biotic and abiotic stress, using the results from both association and interval mapping approaches. QTL for agronomic traits (yield, flowering time, and plant height), physical (grain length and grain width) and cooking properties (amylose content) of the rice grain, abiotic stress (submergence tolerance), and biotic stress (brown spot disease) were mapped. Through presenting this extensive analysis in the MI population in rice, we highlight important considerations when choosing analytical approaches. The methods and results reported in this paper will provide a guide to future genetic analysis methods applied to multi-parent populations. 2017-06-01 2024-12-19T12:54:38Z 2024-12-19T12:54:38Z Journal Article https://hdl.handle.net/10568/165047 en Oxford University Press Raghavan, Chitra; Mauleon, Ramil; Lacorte, Vanica; Jubay, Monalisa; Zaw, Hein; Bonifacio, Justine; Singh, Rakesh Kumar; Huang, B Emma and Leung, Hei. 2017. Approaches in characterizing genetic structure and mapping in a rice multiparental population. G3-Genes Genomes Genetics, volume 7, no. 6; pages 1721-1730, ill. Ref. |
| spellingShingle | Raghavan, Chitra Mauleon, Ramil Lacorte, Vanica Jubay, Monalisa Zaw, Hein Bonifacio, Justine Singh, Rakesh Kumar Huang, B Emma Leung, Hei Approaches in characterizing genetic structure and mapping in a rice multiparental population |
| title | Approaches in characterizing genetic structure and mapping in a rice multiparental population |
| title_full | Approaches in characterizing genetic structure and mapping in a rice multiparental population |
| title_fullStr | Approaches in characterizing genetic structure and mapping in a rice multiparental population |
| title_full_unstemmed | Approaches in characterizing genetic structure and mapping in a rice multiparental population |
| title_short | Approaches in characterizing genetic structure and mapping in a rice multiparental population |
| title_sort | approaches in characterizing genetic structure and mapping in a rice multiparental population |
| url | https://hdl.handle.net/10568/165047 |
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