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ORIGINAL RESEARCH article
Front. Plant Sci.
Sec. Plant Genetics, Epigenetics and Chromosome Biology
Volume 16 - 2025 | doi: 10.3389/fpls.2025.1557748
Long-read sequencing reveals novel structural variation markers for key agronomic and quality traits of food-grade soybean
Provisionally accepted
Zhibo Wang 1*
Kassaye Belay 2
Joe Paterson 2
Patrick Bewick 2
William M. Singer 2
QIJIIAN SONG 3
Bo Zhang 2
Song Li 2*- 1 Donald Danforth Plant Science Center, St Louis, United States
- 2 Virginia Tech, Blacksburg, Virginia, United States
- 3 United States Department of Agriculture (USDA), Washington, District of Columbia, United States
Long read sequencing has been widely used to detect structure variations that are not captured by short read sequencing in plant genomic research. In this letter, we described an analysis of whole genome re-sequencing of 29 soybean varieties using nanopore long-read sequencing. The compiled germplasm reflects diverse applications of food-grade soybeans, including soy milk and tofu production, as well as consumption of natto, sprouts, and vegetable soybeans (edamame). We have identified 365,497 structural variations in these newly resequenced genomes and found that the newly identified structural variations are associated with important agronomic traits. These traits include seed weight, flowering time, plant height, oleic acid content, methionine content, and trypsin inhibitor content, all of which significantly impact soybean production and quality. Experimental validation supports the roles of predicted candidate genes and structural variant in these biological processes. Our research provides a new source for rapid marker discovery in crop genomes using structural variation and whole genome sequencing.
Keywords: Long-read sequencing technology, structural variation, Gene Expression, Food-grade soybean, Seed weight, Plant height, trypsin inhibitor content Deleted: structural variation
Received: 09 Jan 2025; Accepted: 17 Mar 2025.
Copyright: © 2025 Wang, Belay, Paterson, Bewick, Singer, SONG, Zhang and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Zhibo Wang, Donald Danforth Plant Science Center, St Louis, United States
Song Li, Virginia Tech, Blacksburg, 24061, Virginia, United States
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