Structural variants in 3000 rice genomes
Investigation of large structural variants (SVs) is a challenging yet important task in understanding trait differences in highly repetitive genomes. Combining different bioinformatic approaches for SV detection, we analyzed whole-genome sequencing data from 3000 rice genomes and identified 63 milli...
| Autores principales: | , , , , , , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Cold Spring Harbor Laboratory
2019
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/100877 |
| _version_ | 1855541216450445312 |
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| author | Fuentes, Roven Rommel Chebotarov, Dmytro Duitama, Jorge Smith, Sean Hoz, Juan Fernando de la Mohiyuddin, Marghoob Wing, Rod A. McNally, Kenneth L. Tatarinova, Tatiana Grigoriev, Andrey Mauleon, Ramil Alexandrov, Nickolai |
| author_browse | Alexandrov, Nickolai Chebotarov, Dmytro Duitama, Jorge Fuentes, Roven Rommel Grigoriev, Andrey Hoz, Juan Fernando de la Mauleon, Ramil McNally, Kenneth L. Mohiyuddin, Marghoob Smith, Sean Tatarinova, Tatiana Wing, Rod A. |
| author_facet | Fuentes, Roven Rommel Chebotarov, Dmytro Duitama, Jorge Smith, Sean Hoz, Juan Fernando de la Mohiyuddin, Marghoob Wing, Rod A. McNally, Kenneth L. Tatarinova, Tatiana Grigoriev, Andrey Mauleon, Ramil Alexandrov, Nickolai |
| author_sort | Fuentes, Roven Rommel |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Investigation of large structural variants (SVs) is a challenging yet important task in understanding trait differences in highly repetitive genomes. Combining different bioinformatic approaches for SV detection, we analyzed whole-genome sequencing data from 3000 rice genomes and identified 63 million individual SV calls that grouped into 1.5 million allelic variants. We found enrichment of long SVs in promoters and an excess of shorter variants in 5′ UTRs. Across the rice genomes, we identified regions of high SV frequency enriched in stress response genes. We demonstrated how SVs may help in finding causative variants in genome-wide association analysis. These new insights into rice genome biology are valuable for understanding the effects SVs have on gene function, with the prospect of identifying novel agronomically important alleles that can be utilized to improve cultivated rice. |
| format | Journal Article |
| id | CGSpace100877 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | Cold Spring Harbor Laboratory |
| publisherStr | Cold Spring Harbor Laboratory |
| record_format | dspace |
| spelling | CGSpace1008772025-03-13T09:45:40Z Structural variants in 3000 rice genomes Fuentes, Roven Rommel Chebotarov, Dmytro Duitama, Jorge Smith, Sean Hoz, Juan Fernando de la Mohiyuddin, Marghoob Wing, Rod A. McNally, Kenneth L. Tatarinova, Tatiana Grigoriev, Andrey Mauleon, Ramil Alexandrov, Nickolai genomes rice Investigation of large structural variants (SVs) is a challenging yet important task in understanding trait differences in highly repetitive genomes. Combining different bioinformatic approaches for SV detection, we analyzed whole-genome sequencing data from 3000 rice genomes and identified 63 million individual SV calls that grouped into 1.5 million allelic variants. We found enrichment of long SVs in promoters and an excess of shorter variants in 5′ UTRs. Across the rice genomes, we identified regions of high SV frequency enriched in stress response genes. We demonstrated how SVs may help in finding causative variants in genome-wide association analysis. These new insights into rice genome biology are valuable for understanding the effects SVs have on gene function, with the prospect of identifying novel agronomically important alleles that can be utilized to improve cultivated rice. 2019-05 2019-04-23T18:23:10Z 2019-04-23T18:23:10Z Journal Article https://hdl.handle.net/10568/100877 en Open Access Cold Spring Harbor Laboratory Fuentes, Roven Rommel; Chebotarov, Dmytro; Duitama, Jorge; Smith, Sean; de la Hoz, Juan Fernando; Mohiyuddin, Marghoob; Wing, Rod A.; McNally, Kenneth L.; Tatarinova, Tatiana; Grigoriev, Andrey; Mauleon, Ramil & Alexandrov, Nickolai (2019). Importance of considering technology growth in impact assessments of climate change on agriculture. Genome Research, 29:1-11 p. |
| spellingShingle | genomes rice Fuentes, Roven Rommel Chebotarov, Dmytro Duitama, Jorge Smith, Sean Hoz, Juan Fernando de la Mohiyuddin, Marghoob Wing, Rod A. McNally, Kenneth L. Tatarinova, Tatiana Grigoriev, Andrey Mauleon, Ramil Alexandrov, Nickolai Structural variants in 3000 rice genomes |
| title | Structural variants in 3000 rice genomes |
| title_full | Structural variants in 3000 rice genomes |
| title_fullStr | Structural variants in 3000 rice genomes |
| title_full_unstemmed | Structural variants in 3000 rice genomes |
| title_short | Structural variants in 3000 rice genomes |
| title_sort | structural variants in 3000 rice genomes |
| topic | genomes rice |
| url | https://hdl.handle.net/10568/100877 |
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