Machine learning reveals spatiotemporal genome evolution in Asian rice domestication
Domestication is anthropogenic evolution that fulfills mankind’s critical food demand. As such, elucidating the molecular mechanisms behind this process promotes the development of future new food resources including crops. With the aim of understanding the long-term domestication process of Asian r...
| Autores principales: | , , , , , , , , |
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| Formato: | Preprint |
| Lenguaje: | Inglés |
| Publicado: |
Cold Spring Harbor Laboratory
2019
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| Acceso en línea: | https://hdl.handle.net/10568/164602 |
| _version_ | 1855523663287156736 |
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| author | Ohyanagi, Hajime Goto, Kosuke Negrão, Sónia Wing, Rod A. Tester, Mark A. McNally, Kenneth L. Bajic, Vladimir B. Mineta, Katsuhiko Gojobori, Takashi |
| author_browse | Bajic, Vladimir B. Gojobori, Takashi Goto, Kosuke McNally, Kenneth L. Mineta, Katsuhiko Negrão, Sónia Ohyanagi, Hajime Tester, Mark A. Wing, Rod A. |
| author_facet | Ohyanagi, Hajime Goto, Kosuke Negrão, Sónia Wing, Rod A. Tester, Mark A. McNally, Kenneth L. Bajic, Vladimir B. Mineta, Katsuhiko Gojobori, Takashi |
| author_sort | Ohyanagi, Hajime |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Domestication is anthropogenic evolution that fulfills mankind’s critical food demand. As such, elucidating the molecular mechanisms behind this process promotes the development of future new food resources including crops. With the aim of understanding the long-term domestication process of Asian rice and by employing the Oryza sativa subspecies (indica and japonica) as an Asian rice domestication model, we scrutinized past genomic introgressions between them as traces of domestication. Here we show the genome-wide introgressive region (IR) map of Asian rice, by utilizing 4,587 accession genotypes with a stable outgroup species, particularly at the finest resolution through a machine learning-aided method. The IR map revealed that 14.2% of the rice genome consists of IRs, including both wide IRs (recent) and narrow IRs (ancient). This introgressive landscape with their time calibration indicates that introgression events happened in multiple genomic regions over multiple periods. From the correspondence between our wide IRs and the so-called selective sweep regions, we provide a definitive answer to a long-standing controversy over the evolutionary origin of Asian rice domestication, single or multiple origins: It heavily depends upon which regions you pay attention to, implying that wider genomic regions represent immediate short history of Asian rice domestication as a likely support to the single origin, while its ancient history is interspersed in narrower traces throughout the genome as a possible support to the multiple origin. |
| format | Preprint |
| id | CGSpace164602 |
| 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 | CGSpace1646022024-12-19T14:12:27Z Machine learning reveals spatiotemporal genome evolution in Asian rice domestication Ohyanagi, Hajime Goto, Kosuke Negrão, Sónia Wing, Rod A. Tester, Mark A. McNally, Kenneth L. Bajic, Vladimir B. Mineta, Katsuhiko Gojobori, Takashi Domestication is anthropogenic evolution that fulfills mankind’s critical food demand. As such, elucidating the molecular mechanisms behind this process promotes the development of future new food resources including crops. With the aim of understanding the long-term domestication process of Asian rice and by employing the Oryza sativa subspecies (indica and japonica) as an Asian rice domestication model, we scrutinized past genomic introgressions between them as traces of domestication. Here we show the genome-wide introgressive region (IR) map of Asian rice, by utilizing 4,587 accession genotypes with a stable outgroup species, particularly at the finest resolution through a machine learning-aided method. The IR map revealed that 14.2% of the rice genome consists of IRs, including both wide IRs (recent) and narrow IRs (ancient). This introgressive landscape with their time calibration indicates that introgression events happened in multiple genomic regions over multiple periods. From the correspondence between our wide IRs and the so-called selective sweep regions, we provide a definitive answer to a long-standing controversy over the evolutionary origin of Asian rice domestication, single or multiple origins: It heavily depends upon which regions you pay attention to, implying that wider genomic regions represent immediate short history of Asian rice domestication as a likely support to the single origin, while its ancient history is interspersed in narrower traces throughout the genome as a possible support to the multiple origin. 2019-11-02 2024-12-19T12:54:06Z 2024-12-19T12:54:06Z Preprint https://hdl.handle.net/10568/164602 en Cold Spring Harbor Laboratory Ohyanagi, Hajime; Goto, Kosuke; Negrão, Sónia; Wing, Rod A.; Tester, Mark A.; McNally, Kenneth L.; Bajic, Vladimir B.; Mineta, Katsuhiko and Gojobori, Takashi. 2019. Machine learning reveals spatiotemporal genome evolution in Asian rice domestication. bioRxiv, 39 pages |
| spellingShingle | Ohyanagi, Hajime Goto, Kosuke Negrão, Sónia Wing, Rod A. Tester, Mark A. McNally, Kenneth L. Bajic, Vladimir B. Mineta, Katsuhiko Gojobori, Takashi Machine learning reveals spatiotemporal genome evolution in Asian rice domestication |
| title | Machine learning reveals spatiotemporal genome evolution in Asian rice domestication |
| title_full | Machine learning reveals spatiotemporal genome evolution in Asian rice domestication |
| title_fullStr | Machine learning reveals spatiotemporal genome evolution in Asian rice domestication |
| title_full_unstemmed | Machine learning reveals spatiotemporal genome evolution in Asian rice domestication |
| title_short | Machine learning reveals spatiotemporal genome evolution in Asian rice domestication |
| title_sort | machine learning reveals spatiotemporal genome evolution in asian rice domestication |
| url | https://hdl.handle.net/10568/164602 |
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