Multi-model genome-wide association studies for appearance quality in rice
Improving the quality of the appearance of rice is critical to meet market acceptance. Mining putative quality-related genes has been geared towards the development of effective breeding approaches for rice. In the present study, two SL-GWAS (CMLM and MLM) and three ML-GWAS (FASTmrEMMA, mrMLM, and F...
| Main Authors: | , , , , , , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Frontiers Media
2024
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| Online Access: | https://hdl.handle.net/10568/163854 |
| _version_ | 1855514363529527296 |
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| author | Sachdeva, Supriya Singh, Rakesh Maurya, Avantika Singh, Vikas Kumar Singh, Uma Maheshwar Kumar, Arvind Singh, Gyanendra Pratap |
| author_browse | Kumar, Arvind Maurya, Avantika Sachdeva, Supriya Singh, Gyanendra Pratap Singh, Rakesh Singh, Uma Maheshwar Singh, Vikas Kumar |
| author_facet | Sachdeva, Supriya Singh, Rakesh Maurya, Avantika Singh, Vikas Kumar Singh, Uma Maheshwar Kumar, Arvind Singh, Gyanendra Pratap |
| author_sort | Sachdeva, Supriya |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Improving the quality of the appearance of rice is critical to meet market acceptance. Mining putative quality-related genes has been geared towards the development of effective breeding approaches for rice. In the present study, two SL-GWAS (CMLM and MLM) and three ML-GWAS (FASTmrEMMA, mrMLM, and FASTmrMLM) genome-wide association studies were conducted in a subset of 3K-RGP consisting of 198 rice accessions with 553,831 SNP markers. A total of 594 SNP markers were identified using the mixed linear model method for grain quality traits. Additionally, 70 quantitative trait nucleotides (QTNs) detected by the ML-GWAS models were strongly associated with grain aroma (AR), head rice recovery (HRR, %), and percentage of grains with chalkiness (PGC, %). Finally, 39 QTNs were identified using single- and multi-locus GWAS methods. Among the 39 reliable QTNs, 20 novel QTNs were identified for the above-mentioned three quality-related traits. Based on annotation and previous studies, four functional candidate genes (LOC_Os01g66110, LOC_Os01g66140, LOC_Os07g44910, and LOC_Os02g14120) were found to influence AR, HRR (%), and PGC (%), which could be utilized in rice breeding to improve grain quality traits. |
| format | Journal Article |
| id | CGSpace163854 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | Frontiers Media |
| publisherStr | Frontiers Media |
| record_format | dspace |
| spelling | CGSpace1638542025-12-08T10:29:22Z Multi-model genome-wide association studies for appearance quality in rice Sachdeva, Supriya Singh, Rakesh Maurya, Avantika Singh, Vikas Kumar Singh, Uma Maheshwar Kumar, Arvind Singh, Gyanendra Pratap Improving the quality of the appearance of rice is critical to meet market acceptance. Mining putative quality-related genes has been geared towards the development of effective breeding approaches for rice. In the present study, two SL-GWAS (CMLM and MLM) and three ML-GWAS (FASTmrEMMA, mrMLM, and FASTmrMLM) genome-wide association studies were conducted in a subset of 3K-RGP consisting of 198 rice accessions with 553,831 SNP markers. A total of 594 SNP markers were identified using the mixed linear model method for grain quality traits. Additionally, 70 quantitative trait nucleotides (QTNs) detected by the ML-GWAS models were strongly associated with grain aroma (AR), head rice recovery (HRR, %), and percentage of grains with chalkiness (PGC, %). Finally, 39 QTNs were identified using single- and multi-locus GWAS methods. Among the 39 reliable QTNs, 20 novel QTNs were identified for the above-mentioned three quality-related traits. Based on annotation and previous studies, four functional candidate genes (LOC_Os01g66110, LOC_Os01g66140, LOC_Os07g44910, and LOC_Os02g14120) were found to influence AR, HRR (%), and PGC (%), which could be utilized in rice breeding to improve grain quality traits. 2024-01-11 2024-12-19T12:53:05Z 2024-12-19T12:53:05Z Journal Article https://hdl.handle.net/10568/163854 en Open Access Frontiers Media Sachdeva, Supriya; Singh, Rakesh; Maurya, Avantika; Singh, Vikas Kumar; Singh, Uma Maheshwar; Kumar, Arvind and Singh, Gyanendra Pratap. 2024. Multi-model genome-wide association studies for appearance quality in rice. Front. Plant Sci., Volume 14 |
| spellingShingle | Sachdeva, Supriya Singh, Rakesh Maurya, Avantika Singh, Vikas Kumar Singh, Uma Maheshwar Kumar, Arvind Singh, Gyanendra Pratap Multi-model genome-wide association studies for appearance quality in rice |
| title | Multi-model genome-wide association studies for appearance quality in rice |
| title_full | Multi-model genome-wide association studies for appearance quality in rice |
| title_fullStr | Multi-model genome-wide association studies for appearance quality in rice |
| title_full_unstemmed | Multi-model genome-wide association studies for appearance quality in rice |
| title_short | Multi-model genome-wide association studies for appearance quality in rice |
| title_sort | multi model genome wide association studies for appearance quality in rice |
| url | https://hdl.handle.net/10568/163854 |
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