Hudson and his multi-institution collaborators will select and grow soybean lines, shipping extracted DNA to the JGI for long-read sequencing as part of the JGI’s Community Science Program. Hudson’s team, along with partners at U. of I.’s AIFARMS, will take the lead in analyzing the output.
“AIFARMS was designed to deal with large datasets coming out of agriculture projects,” Hudson said. “Having this dataset is going to be a boost for our other digital ag activities.”
With its inclusion of wild relatives and the sheer number of reference and high-quality draft genomes set for sequencing, the project will drastically improve the current soybean reference genome. Hudson explains that genetic diversity is the raw material for crop improvement, but the crop’s diversity is not reflected in the reference genome. He likens it to the first human genome, which was pieced together only from Caucasian individuals.
“There’s an increasing effort to have the reference human genome reflect all of the variation in people. We think there are equally big reasons to do the same thing in crops,” Hudson said. “But it’s hard to locate the missing diversity by any other means than sequencing more genomes.”
The team plans to consult the global soybean breeding community, including industry partners, in deciding priority lines to include.
Ultimately, Hudson said, the project will “enable deep analysis of the evolution and domestication of modern soybean and empower soybean researchers and breeders to directly select for otherwise hidden genetic variation in genes that can be targeted for variety development. As soybean is becoming increasingly important as a worldwide crop, as well as being a key bioenergy crop, this project will have global impact and be particularly relevant to U.S. agriculture."
Source : illinois.edu