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Genome sequencing of rice subspecies and genetic analysis of recombinant lines reveals regional yield- and quality-associated loci

Overview of attention for article published in BMC Biology, September 2018
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Title
Genome sequencing of rice subspecies and genetic analysis of recombinant lines reveals regional yield- and quality-associated loci
Published in
BMC Biology, September 2018
DOI 10.1186/s12915-018-0572-x
Pubmed ID
Authors

Xiukun Li, Lian Wu, Jiahong Wang, Jian Sun, Xiuhong Xia, Xin Geng, Xuhong Wang, Zhengjin Xu, Quan Xu

Abstract

Two of the most widely cultivated rice strains are Oryza sativa indica and O. sativa japonica, and understanding the genetic basis of their agronomic traits is of importance for crop production. These two species are highly distinct in terms of geographical distribution and morphological traits. However, the relationship among genetic background, ecological conditions, and agronomic traits is unclear. In this study, we performed the de novo assembly of a high-quality genome of SN265, a cultivar that is extensively cultivated as a backbone japonica parent in northern China, using single-molecule sequencing. Recombinant inbred lines (RILs) derived from a cross between SN265 and R99 (indica) were re-sequenced and cultivated in three distinct ecological conditions. We identify 79 QTLs related to 15 agronomic traits. We found that several genes underwent functional alterations when the ecological conditions were changed, and some alleles exhibited contracted responses to different genetic backgrounds. We validated the involvement of one candidate gene, DEP1, in determining panicle length, using CRISPR/Cas9 gene editing. This study provides information on the suitable environmental conditions, and genetic background, for functional genes in rice breeding. Moreover, the public availability of the reference genome of northern japonica SN265 provides a valuable resource for plant biologists and the genetic improvement of crops.

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Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 26%
Researcher 7 18%
Student > Master 4 11%
Student > Bachelor 3 8%
Lecturer 1 3%
Other 1 3%
Unknown 12 32%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 42%
Biochemistry, Genetics and Molecular Biology 7 18%
Social Sciences 3 8%
Unknown 12 32%