Genomic prediction and QTL analysis for grain Zn content and yield in Aus-derived rice populations
Zinc (Zn) biofortification of rice can address Zn malnutrition in Asia. Identification and introgression of QTLs for grain Zn content and yield (YLD) can improve the efficiency of rice Zn biofortification. In four rice populations we detected 56 QTLs for seven traits by inclusive composite interval...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Journal Article |
| Language: | Inglés |
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Springer
2024
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| Online Access: | https://hdl.handle.net/10568/163811 |
| _version_ | 1855518886784401408 |
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| author | Hore, Tapas Kumer Balachiranjeevi, C.H. Inabangan-Asilo, Mary Ann Deepak, C.A. Palanog, Alvin D. Hernandez, Jose E. Gregorio, Glenn B. Dalisay, Teresita U. Diaz, Maria Genaleen Q. Neto, Roberto Fritsche Kader, Md. Abdul Biswas, Partha Sarathi Swamy, B.P. Mallikarjuna |
| author_browse | Balachiranjeevi, C.H. Biswas, Partha Sarathi Dalisay, Teresita U. Deepak, C.A. Diaz, Maria Genaleen Q. Gregorio, Glenn B. Hernandez, Jose E. Hore, Tapas Kumer Inabangan-Asilo, Mary Ann Kader, Md. Abdul Neto, Roberto Fritsche Palanog, Alvin D. Swamy, B.P. Mallikarjuna |
| author_facet | Hore, Tapas Kumer Balachiranjeevi, C.H. Inabangan-Asilo, Mary Ann Deepak, C.A. Palanog, Alvin D. Hernandez, Jose E. Gregorio, Glenn B. Dalisay, Teresita U. Diaz, Maria Genaleen Q. Neto, Roberto Fritsche Kader, Md. Abdul Biswas, Partha Sarathi Swamy, B.P. Mallikarjuna |
| author_sort | Hore, Tapas Kumer |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Zinc (Zn) biofortification of rice can address Zn malnutrition in Asia. Identification and introgression of QTLs for grain Zn content and yield (YLD) can improve the efficiency of rice Zn biofortification. In four rice populations we detected 56 QTLs for seven traits by inclusive composite interval mapping (ICIM), and 16 QTLs for two traits (YLD and Zn) by association mapping. The phenotypic variance (PV) varied from 4.5% (qPN 4.1 ) to 31.7% (qPH 1.1 ). qDF 1.1 , qDF 7.2 , qDF 8.1 , qPH 1.1 , qPH 7.1 , qPL 1.2 , qPL 9.1, qZn 5.1 , qZn 5.2 , qZn 6.1 and qZn 7.1 were identified in both dry and wet seasons; qZn 5.1 , qZn 5.2 , qZn 5.3, qZn 6.2, qZn 7.1 and qYLD 1.2 were detected by both ICIM and association mapping. qZn 7.1 had the highest PV (17.8%) and additive effect (2.5 ppm). Epistasis and QTL co-locations were also observed for different traits. The multi-trait genomic prediction values were 0.24 and 0.16 for YLD and Zn respectively. qZn 6.2 was co-located with a gene (OsHMA2) involved in Zn transport. These results are useful for Zn biofortificatiton of rice. |
| format | Journal Article |
| id | CGSpace163811 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | Springer |
| publisherStr | Springer |
| record_format | dspace |
| spelling | CGSpace1638112025-10-26T12:56:11Z Genomic prediction and QTL analysis for grain Zn content and yield in Aus-derived rice populations Hore, Tapas Kumer Balachiranjeevi, C.H. Inabangan-Asilo, Mary Ann Deepak, C.A. Palanog, Alvin D. Hernandez, Jose E. Gregorio, Glenn B. Dalisay, Teresita U. Diaz, Maria Genaleen Q. Neto, Roberto Fritsche Kader, Md. Abdul Biswas, Partha Sarathi Swamy, B.P. Mallikarjuna Zinc (Zn) biofortification of rice can address Zn malnutrition in Asia. Identification and introgression of QTLs for grain Zn content and yield (YLD) can improve the efficiency of rice Zn biofortification. In four rice populations we detected 56 QTLs for seven traits by inclusive composite interval mapping (ICIM), and 16 QTLs for two traits (YLD and Zn) by association mapping. The phenotypic variance (PV) varied from 4.5% (qPN 4.1 ) to 31.7% (qPH 1.1 ). qDF 1.1 , qDF 7.2 , qDF 8.1 , qPH 1.1 , qPH 7.1 , qPL 1.2 , qPL 9.1, qZn 5.1 , qZn 5.2 , qZn 6.1 and qZn 7.1 were identified in both dry and wet seasons; qZn 5.1 , qZn 5.2 , qZn 5.3, qZn 6.2, qZn 7.1 and qYLD 1.2 were detected by both ICIM and association mapping. qZn 7.1 had the highest PV (17.8%) and additive effect (2.5 ppm). Epistasis and QTL co-locations were also observed for different traits. The multi-trait genomic prediction values were 0.24 and 0.16 for YLD and Zn respectively. qZn 6.2 was co-located with a gene (OsHMA2) involved in Zn transport. These results are useful for Zn biofortificatiton of rice. 2024-06 2024-12-19T12:53:02Z 2024-12-19T12:53:02Z Journal Article https://hdl.handle.net/10568/163811 en Open Access Springer Hore, Tapas Kumer; Balachiranjeevi, C. H.; Inabangan-Asilo, Mary Ann; Deepak, C. A.; Palanog, Alvin D.; Hernandez, Jose E.; Gregorio, Glenn B.; Dalisay, Teresita U.; Diaz, Maria Genaleen Q.; Neto, Roberto Fritsche; Kader, Md. Abdul; Biswas, Partha Sarathi and Swamy, B. P. Mallikarjuna. 2024. Genomic prediction and QTL analysis for grain Zn content and yield in Aus-derived rice populations. J. Plant Biochem. Biotechnol., Volume 33 no. 2 p. 216-236 |
| spellingShingle | Hore, Tapas Kumer Balachiranjeevi, C.H. Inabangan-Asilo, Mary Ann Deepak, C.A. Palanog, Alvin D. Hernandez, Jose E. Gregorio, Glenn B. Dalisay, Teresita U. Diaz, Maria Genaleen Q. Neto, Roberto Fritsche Kader, Md. Abdul Biswas, Partha Sarathi Swamy, B.P. Mallikarjuna Genomic prediction and QTL analysis for grain Zn content and yield in Aus-derived rice populations |
| title | Genomic prediction and QTL analysis for grain Zn content and yield in Aus-derived rice populations |
| title_full | Genomic prediction and QTL analysis for grain Zn content and yield in Aus-derived rice populations |
| title_fullStr | Genomic prediction and QTL analysis for grain Zn content and yield in Aus-derived rice populations |
| title_full_unstemmed | Genomic prediction and QTL analysis for grain Zn content and yield in Aus-derived rice populations |
| title_short | Genomic prediction and QTL analysis for grain Zn content and yield in Aus-derived rice populations |
| title_sort | genomic prediction and qtl analysis for grain zn content and yield in aus derived rice populations |
| url | https://hdl.handle.net/10568/163811 |
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