Multiomics of a rice population identifies genes and genomic regions that bestow low glycemic index and high protein content
To counter the rising incidence of diabetes and to meet the daily protein needs, we created low glycemic index (GI) rice varieties with protein content (PC) surpassing 14%. In the development of recombinant inbred lines using Samba Mahsuri and IR36 amylose extender (IR36ae) as parental lines, we ide...
| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Journal Article |
| Language: | Inglés |
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Proceedings of the National Academy of Sciences
2024
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/168150 |
| _version_ | 1855521338739916800 |
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| author | Badoni, Saurabh Pasion-Uy, Erstelle A. Kor, Sakshi Kim, Sung-Ryul Tiozon, Rhowell N. Misra, Gopal Buenafe, Reuben James Q. Labarga, Luster May Ramos-Castrosanto, Ana Rose Pratap, Vipin Slamet-Loedin, Inez Steimker, Julia von Alseekh, Saleh Fernie, Alisdair R. Kohli, Ajay Khush, Gurudev S. Sreenivasulu, Nese |
| author_browse | Alseekh, Saleh Badoni, Saurabh Buenafe, Reuben James Q. Fernie, Alisdair R. Khush, Gurudev S. Kim, Sung-Ryul Kohli, Ajay Kor, Sakshi Labarga, Luster May Misra, Gopal Pasion-Uy, Erstelle A. Pratap, Vipin Ramos-Castrosanto, Ana Rose Slamet-Loedin, Inez Sreenivasulu, Nese Steimker, Julia von Tiozon, Rhowell N. |
| author_facet | Badoni, Saurabh Pasion-Uy, Erstelle A. Kor, Sakshi Kim, Sung-Ryul Tiozon, Rhowell N. Misra, Gopal Buenafe, Reuben James Q. Labarga, Luster May Ramos-Castrosanto, Ana Rose Pratap, Vipin Slamet-Loedin, Inez Steimker, Julia von Alseekh, Saleh Fernie, Alisdair R. Kohli, Ajay Khush, Gurudev S. Sreenivasulu, Nese |
| author_sort | Badoni, Saurabh |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | To counter the rising incidence of diabetes and to meet the daily protein needs, we created low glycemic index (GI) rice varieties with protein content (PC) surpassing 14%. In the development of recombinant inbred lines using Samba Mahsuri and IR36 amylose extender (IR36ae) as parental lines, we identified quantitative trait loci and genes associated with low GI, high amylose content (AC), and high PC. By integrating genetic techniques with classification models, this comprehensive approach identified candidate genes on chromosome 2 (qGI2.1/qAC2.1 spanning the region from 18.62 Mb to 19.95 Mb), exerting influence on low GI and high amylose. Notably, the phenotypic variant with high value was associated with the recessive allele of the starch branching enzyme 2b (sbeIIb). The genome-edited sbeIIb line confirmed low GI phenotype in milled rice grains. Further, combinations of alleles created by the highly significant SNPs from the targeted associations and epistatically interacting genes showed ultralow GI phenotypes with high amylose and high protein. Metabolomics analysis of rice with varying AC, PC, and GI revealed that the superior lines of high AC and PC, and low GI were preferentially enriched in glycolytic and amino acid metabolisms, whereas the inferior lines of low AC and PC and high GI were enriched with fatty acid metabolism. The high amylose high protein recombinant inbred line (HAHP_101) was enriched in essential amino acids like lysine. Such lines may be highly relevant for food product development to address diabetes and malnutrition. |
| format | Journal Article |
| id | CGSpace168150 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | Proceedings of the National Academy of Sciences |
| publisherStr | Proceedings of the National Academy of Sciences |
| record_format | dspace |
| spelling | CGSpace1681502026-01-06T12:03:45Z Multiomics of a rice population identifies genes and genomic regions that bestow low glycemic index and high protein content Badoni, Saurabh Pasion-Uy, Erstelle A. Kor, Sakshi Kim, Sung-Ryul Tiozon, Rhowell N. Misra, Gopal Buenafe, Reuben James Q. Labarga, Luster May Ramos-Castrosanto, Ana Rose Pratap, Vipin Slamet-Loedin, Inez Steimker, Julia von Alseekh, Saleh Fernie, Alisdair R. Kohli, Ajay Khush, Gurudev S. Sreenivasulu, Nese inbred lines varieties starch proteins rice genomics To counter the rising incidence of diabetes and to meet the daily protein needs, we created low glycemic index (GI) rice varieties with protein content (PC) surpassing 14%. In the development of recombinant inbred lines using Samba Mahsuri and IR36 amylose extender (IR36ae) as parental lines, we identified quantitative trait loci and genes associated with low GI, high amylose content (AC), and high PC. By integrating genetic techniques with classification models, this comprehensive approach identified candidate genes on chromosome 2 (qGI2.1/qAC2.1 spanning the region from 18.62 Mb to 19.95 Mb), exerting influence on low GI and high amylose. Notably, the phenotypic variant with high value was associated with the recessive allele of the starch branching enzyme 2b (sbeIIb). The genome-edited sbeIIb line confirmed low GI phenotype in milled rice grains. Further, combinations of alleles created by the highly significant SNPs from the targeted associations and epistatically interacting genes showed ultralow GI phenotypes with high amylose and high protein. Metabolomics analysis of rice with varying AC, PC, and GI revealed that the superior lines of high AC and PC, and low GI were preferentially enriched in glycolytic and amino acid metabolisms, whereas the inferior lines of low AC and PC and high GI were enriched with fatty acid metabolism. The high amylose high protein recombinant inbred line (HAHP_101) was enriched in essential amino acids like lysine. Such lines may be highly relevant for food product development to address diabetes and malnutrition. 2024-09-03 2024-12-20T15:56:31Z 2024-12-20T15:56:31Z Journal Article https://hdl.handle.net/10568/168150 en Open Access application/pdf Proceedings of the National Academy of Sciences Badoni, Saurabh, Erstelle A. Pasion-Uy, Sakshi Kor, Sung-Ryul Kim, Rhowell N. Tiozon Jr, Gopal Misra, Reuben James Q. Buenafe et al. "Multiomics of a rice population identifies genes and genomic regions that bestow low glycemic index and high protein content." Proceedings of the National Academy of Sciences 121, no. 36 (2024): e2410598121. |
| spellingShingle | inbred lines varieties starch proteins rice genomics Badoni, Saurabh Pasion-Uy, Erstelle A. Kor, Sakshi Kim, Sung-Ryul Tiozon, Rhowell N. Misra, Gopal Buenafe, Reuben James Q. Labarga, Luster May Ramos-Castrosanto, Ana Rose Pratap, Vipin Slamet-Loedin, Inez Steimker, Julia von Alseekh, Saleh Fernie, Alisdair R. Kohli, Ajay Khush, Gurudev S. Sreenivasulu, Nese Multiomics of a rice population identifies genes and genomic regions that bestow low glycemic index and high protein content |
| title | Multiomics of a rice population identifies genes and genomic regions that bestow low glycemic index and high protein content |
| title_full | Multiomics of a rice population identifies genes and genomic regions that bestow low glycemic index and high protein content |
| title_fullStr | Multiomics of a rice population identifies genes and genomic regions that bestow low glycemic index and high protein content |
| title_full_unstemmed | Multiomics of a rice population identifies genes and genomic regions that bestow low glycemic index and high protein content |
| title_short | Multiomics of a rice population identifies genes and genomic regions that bestow low glycemic index and high protein content |
| title_sort | multiomics of a rice population identifies genes and genomic regions that bestow low glycemic index and high protein content |
| topic | inbred lines varieties starch proteins rice genomics |
| url | https://hdl.handle.net/10568/168150 |
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