Integrating a genome‐wide association study with a large‐scale transcriptome analysis to predict genetic regions influencing the glycaemic index and texture in rice
Reliably generating rice varieties with low glycaemic index (GI) is an important nutritional intervention given the high rates of Type II diabetes incidences in Asia where rice is staple diet. We integrated a genome‐wide association study (GWAS) with a transcriptome‐wide association study (TWAS) to...
| Autores principales: | , , , , , , , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Wiley
2019
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| Acceso en línea: | https://hdl.handle.net/10568/164741 |
| _version_ | 1855523239330054144 |
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| author | Anacleto, Roslen Badoni, Saurabh Parween, Sabiha Butardo, Vito M. Misra, Gopal Cuevas, Rosa Paula Kuhlmann, Markus Trinidad, Trinidad P. Mallillin, Aida C. Acuin, Cecilia Bird, Anthony R. Morell, Matthew K. Sreenivasulu, Nese |
| author_browse | Acuin, Cecilia Anacleto, Roslen Badoni, Saurabh Bird, Anthony R. Butardo, Vito M. Cuevas, Rosa Paula Kuhlmann, Markus Mallillin, Aida C. Misra, Gopal Morell, Matthew K. Parween, Sabiha Sreenivasulu, Nese Trinidad, Trinidad P. |
| author_facet | Anacleto, Roslen Badoni, Saurabh Parween, Sabiha Butardo, Vito M. Misra, Gopal Cuevas, Rosa Paula Kuhlmann, Markus Trinidad, Trinidad P. Mallillin, Aida C. Acuin, Cecilia Bird, Anthony R. Morell, Matthew K. Sreenivasulu, Nese |
| author_sort | Anacleto, Roslen |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Reliably generating rice varieties with low glycaemic index (GI) is an important nutritional intervention given the high rates of Type II diabetes incidences in Asia where rice is staple diet. We integrated a genome‐wide association study (GWAS) with a transcriptome‐wide association study (TWAS) to determine the genetic basis of the GI in rice. GWAS utilized 305 re‐sequenced diverse indica panel comprising ~2.4 million single nucleotide polymorphisms (SNPs) enriched in genic regions. A novel association signal was detected at a synonymous SNP in exon 2 of LOC_Os05g03600 for intermediate‐to‐high GI phenotypic variation. Another major hotspot region was predicted for contributing intermediate‐to‐high GI variation, involves 26 genes on chromosome 6 (GI6.1). These set of genes included GBSSI, two hydrolase genes, genes involved in signalling and chromatin modification. The TWAS and methylome sequencing data revealed cis‐acting functionally relevant genetic variants with differential methylation patterns in the hot spot GI6.1 region, narrowing the target to 13 genes. Conversely, the promoter region of GBSSI and its alternative splicing allele (G allele of Wxa) explained the intermediate‐to‐high GI variation. A SNP (C˃T) at exon‐10 was also highlighted in the preceding analyses to influence final viscosity (FV), which is independent of amylose content/GI. The low GI line with GC haplotype confirmed soft texture, while other two low GI lines with GT haplotype were characterized as hard and cohesive. The low GI lines were further confirmed through clinical in vivo studies. Gene regulatory network analysis highlighted the role of the non‐starch polysaccharide pathway in lowering GI. |
| format | Journal Article |
| id | CGSpace164741 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | Wiley |
| publisherStr | Wiley |
| record_format | dspace |
| spelling | CGSpace1647412025-12-08T09:54:28Z Integrating a genome‐wide association study with a large‐scale transcriptome analysis to predict genetic regions influencing the glycaemic index and texture in rice Anacleto, Roslen Badoni, Saurabh Parween, Sabiha Butardo, Vito M. Misra, Gopal Cuevas, Rosa Paula Kuhlmann, Markus Trinidad, Trinidad P. Mallillin, Aida C. Acuin, Cecilia Bird, Anthony R. Morell, Matthew K. Sreenivasulu, Nese Reliably generating rice varieties with low glycaemic index (GI) is an important nutritional intervention given the high rates of Type II diabetes incidences in Asia where rice is staple diet. We integrated a genome‐wide association study (GWAS) with a transcriptome‐wide association study (TWAS) to determine the genetic basis of the GI in rice. GWAS utilized 305 re‐sequenced diverse indica panel comprising ~2.4 million single nucleotide polymorphisms (SNPs) enriched in genic regions. A novel association signal was detected at a synonymous SNP in exon 2 of LOC_Os05g03600 for intermediate‐to‐high GI phenotypic variation. Another major hotspot region was predicted for contributing intermediate‐to‐high GI variation, involves 26 genes on chromosome 6 (GI6.1). These set of genes included GBSSI, two hydrolase genes, genes involved in signalling and chromatin modification. The TWAS and methylome sequencing data revealed cis‐acting functionally relevant genetic variants with differential methylation patterns in the hot spot GI6.1 region, narrowing the target to 13 genes. Conversely, the promoter region of GBSSI and its alternative splicing allele (G allele of Wxa) explained the intermediate‐to‐high GI variation. A SNP (C˃T) at exon‐10 was also highlighted in the preceding analyses to influence final viscosity (FV), which is independent of amylose content/GI. The low GI line with GC haplotype confirmed soft texture, while other two low GI lines with GT haplotype were characterized as hard and cohesive. The low GI lines were further confirmed through clinical in vivo studies. Gene regulatory network analysis highlighted the role of the non‐starch polysaccharide pathway in lowering GI. 2019-07 2024-12-19T12:54:14Z 2024-12-19T12:54:14Z Journal Article https://hdl.handle.net/10568/164741 en Open Access Wiley Anacleto, Roslen; Badoni, Saurabh; Parween, Sabiha; Butardo, Vito M.; Misra, Gopal; Cuevas, Rosa Paula; Kuhlmann, Markus; Trinidad, Trinidad P.; Mallillin, Aida C.; Acuin, Cecilia; Bird, Anthony R.; Morell, Matthew K. and Sreenivasulu, Nese. 2019. Integrating a genome‐wide association study with a large‐scale transcriptome analysis to predict genetic regions influencing the glycaemic index and texture in rice. Plant Biotechnology Journal, Volume 17 no. 7 p. 1261-1275 |
| spellingShingle | Anacleto, Roslen Badoni, Saurabh Parween, Sabiha Butardo, Vito M. Misra, Gopal Cuevas, Rosa Paula Kuhlmann, Markus Trinidad, Trinidad P. Mallillin, Aida C. Acuin, Cecilia Bird, Anthony R. Morell, Matthew K. Sreenivasulu, Nese Integrating a genome‐wide association study with a large‐scale transcriptome analysis to predict genetic regions influencing the glycaemic index and texture in rice |
| title | Integrating a genome‐wide association study with a large‐scale transcriptome analysis to predict genetic regions influencing the glycaemic index and texture in rice |
| title_full | Integrating a genome‐wide association study with a large‐scale transcriptome analysis to predict genetic regions influencing the glycaemic index and texture in rice |
| title_fullStr | Integrating a genome‐wide association study with a large‐scale transcriptome analysis to predict genetic regions influencing the glycaemic index and texture in rice |
| title_full_unstemmed | Integrating a genome‐wide association study with a large‐scale transcriptome analysis to predict genetic regions influencing the glycaemic index and texture in rice |
| title_short | Integrating a genome‐wide association study with a large‐scale transcriptome analysis to predict genetic regions influencing the glycaemic index and texture in rice |
| title_sort | integrating a genome wide association study with a large scale transcriptome analysis to predict genetic regions influencing the glycaemic index and texture in rice |
| url | https://hdl.handle.net/10568/164741 |
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