Landscape of genomic diversity and trait discovery in soybean

Babu Valliyodan, Qiu Dan Qiu, Gunvant Patil, Peng Zeng, Jiaying Huang, Lu Dai, Chengxuan Chen, Yanjun Li, Trupti Joshi, Li Song, Tri D. Vuong, Theresa A. Musket, Dong Xu, J. Grover Shannon, Cheng Shifeng, Xin Liu, Henry T. Nguyen

Research output: Contribution to journalArticlepeer-review

71 Scopus citations

Abstract

Cultivated soybean [Glycine max (L.) Merr.] is a primary source of vegetable oil and protein. We report a landscape analysis of genome-wide genetic variation and an association study of major domestication and agronomic traits in soybean. A total of 106 soybean genomes representing wild, landraces, and elite lines were re-sequenced at an average of 17x depth with a 97.5% coverage. Over 10 million high-quality SNPs were discovered, and 35.34% of these have not been previously reported. Additionally, 159 putative domestication sweeps were identified, which includes 54.34 Mbp (4.9%) and 4,414 genes; 146 regions were involved in artificial selection during domestication. A genome-wide association study of major traits including oil and protein content, salinity, and domestication traits resulted in the discovery of novel alleles. Genomic information from this study provides a valuable resource for understanding soybean genome structure and evolution, and can also facilitate trait dissection leading to sequencing-based molecular breeding.

Original languageEnglish (US)
Article number23598
JournalScientific reports
Volume6
DOIs
StatePublished - Mar 31 2016

Bibliographical note

Funding Information:
We acknowledge funding support from the Missouri Soybean Merchandising Council for soybean genomics and breeding research program at the University of Missouri. We also acknowledge Xiaolei Wu, Xiangyang Xu, and Jill A. Coombs (former members of the Nguyen Lab, University of Missouri) for initial discussions related to this project; and Juexin Wang, Yang Liu, and Saad Khan (from the Dong Xu lab, University of Missouri) for data handling and submissions to databases.

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