AGRISCIENCE RESEARCH
The Clevenger lab is developing better computational tools to
help introduce beneficial agricultural traits into crop plants like the peanut.
Another major threat to domesticated crops like peanut is aflatoxins. These carcinogenic toxins are produced by certain molds like Aspergillus flavus and related Aspergillus species which grow in soil, decay- ing vegetation, hay, and grains. Children are especially susceptible to aflatoxin exposure, symptoms of which include stunted growth, delayed development, liver damage, and liver cancer. The FDA sets action levels for aflatoxin presence in food, and has recalled food prod- ucts as a precautionary measure to prevent exposure. In an effort to identify targets to mitigate aflatox- in-related crop loss and human exposure to aflatoxin, Clevenger and colleagues developed reference genomes of two Aspergillus flavus strains: a moderately stress tolerant strain with average aflatoxin production, and a highly stress tolerant strain with high aflatoxin pro- duction 2 . The reference-grade assemblies were created through a combination of PacBio ® long-read sequencing and optical mapping. Through analysis of the genomes, they identified a large gene insertion in the stress tol- erant strain that is very young on an evolutionary scale. It contains extra genes, including a novel version of a transcription factor that controls the oxidative stress response pathway and aflatoxin biosynthesis. The results highlight the utility of long-read se- quencing since the gene insertion had not been previ- ously discovered using short-read technology. These reference genomes also represent a valuable asset for use by the Aspergillus research community, and will serve as a starting point for continuing research into the
biology of these organisms, particularly for stress biol- ogy related to oxidative stress and aflatoxin production. As part of the pipeline to identify and introduce beneficial traits into plants, Clevenger and his team are also developing new and improved computational meth- ods to help identify the QTLs and selection markers. While next generation sequencing has facilitated high throughput identification of genome-wide variants, the high number of markers is difficult for linkage map and QTL mapping software to handle. Clevenger’s computa- tional pipeline aims to create faster and more efficient computational methods to handle this data and identify useful QTLs and selection markers. As an example, in an effort to better map resis- tance to tomato spotted-wilt virus, some of Clevenger’s colleagues re-sequenced a population of peanut and used Clevenger’s computational pipeline to effectively analyze the genotyping data. The collaborative team re- ported the development of the first map using SNPs ob- tained from whole genome re-sequencing data in a pa- per published in Scientific Reports 3 . Using the map, the group has identified several QTLs and candidate genes for disease resistance. These studies represent only a snapshot of the many efforts Clevenger and his team are making to improve polyploid genomics for practical applica- tions in crop improvement efforts. They continue to improve these computational technologies and breeding methods to benefit not only their peanut genomics work, but also crop genomics as a whole. n
2019-20 Research Report 35
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