I am a Post-Doctoral Research Associate at the Donald Danforth Plant Science Center, focusing on big data applications in agricultural sciences. My primary research involves leveraging historical breeding data, genomics, and transcriptomics, for efficient soybean product development. I hold a Ph.D. in Agricultural Sciences from the University of Melbourne, where I studied the impact of environmental stress on plant reproduction in canola. Alongside my research, I am passionate about teaching and sharing knowledge in data and plant sciences to cultivate new insights and skills among STEM students.
36
Understanding soybean genomic diversity and transcriptomic response to environmental stresses
N. LOHANI, W. SHEN, G. GIRMA, L.B. GOMEZ-LUCIANO, Z.WANG, M. LI, Y.Q AN
Danforth Plant Science Center, 975 N Warson Rd, St. Louis, MO 63132 USA
Understanding of soybean genomic diversity and the molecular mode of action underlying its response to diverse environmental changes are critical to soybean improvement. With this aim, we utilized the massive amounts of genome and transcriptome sequencing data generated by the soybean research community. We consolidated genome sequences of 5,000 diverse soybean accessions and identified ~8 million SNPs, ~2.3 million InDels, and 102,742 Structural Variations by employing a genomic variant discovery pipeline. We demonstrated that SVs may help in finding causative variants in genome-wide association analysis. Further, we identified hot-spots for SVs and their distribution across different gene features. Parallelly, we consolidated and analyzed a total of 7,356 transcriptome sequencing data representing 2,696 distinct biological processes and developed an algorithm to infer the relationship of the inter-related biological processes in soybean. This transcriptome analysis will enhance our ability to predict the mode of action and the yet-to-be-identified genes that participate in various biological processes governing plant development, yield, and stress tolerance in soybean. Consequently, we are integrating genomics and transcriptomics to study the genetic diversity and artificial selection of the transcriptional program in soybeans in response to environmental changes. These insights can help develop strategies for improving soybean resilience to climate change.