Machine learning reveals spatiotemporal genome evolution in asian rice domestication

Hajime Ohyanagi, Kosuke Goto, Sónia Negrão, Rod A. Wing, Mark A. Tester, Kenneth L. McNally, Vladimir B. Bajic, Katsuhiko Mineta, Takashi Gojobori

Research output: Contribution to journalArticlepeer-review


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 crops. With the aim of understanding the whole domestication process of Asian rice and by employing the Oryza sativa subspecies (indica and japonica) as an Asian rice domestication model, we scrutinized 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 so-called Selective Sweep Regions, we provide a definitive answer to a long-standing controversy in plant science: Asian rice phylogeny appears to depend on which regions and time frames are examined.

Original languageEnglish (US)
JournalUnknown Journal
StatePublished - Nov 2 2019
Externally publishedYes

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • Immunology and Microbiology(all)
  • Neuroscience(all)
  • Pharmacology, Toxicology and Pharmaceutics(all)

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