Chiemeka Nwakama

Brassica rapa is a morphologically diverse crop that diverged from Arabidopsis ~20 million of years ago and underwent a genome triplication, resulting in the expansion of the genome. Local adaptation and breeding have led to differences in gene expression regulation both within and across morphotypes. Many of these differences likely contribute to the variation in stress tolerance traits observed across B. rapa. For example, extensive variation is found in cold tolerance across B. rapa accessions. To identify transcription factors (TFs) contributing to cold tolerance, gene regulatory networks (GRNs) were generated across 14 B. rapa morphotypes using time course gene expression data previously collected at the end of a five-day cold acclimation experiment. GRNs were created across different tolerant and intolerant B. rapa lines and different temperature response types (warm and cold). Individual GRNs were constructed using a random forest algorithm (GENIE3) that predicts candidate targets for known TFs. 

To determine what TF-target connections were conserved across tolerant lines, consensus networks were generated with similarly cold tolerant B. rapa lines. Networks were converted into adjacency matrices and sorted so that each network shared the same order. These adjacency matrices were then summed to form a consensus network, indicating the number of networks sharing each TF-target connection. This consensus network can then be filtered based on the desired number of networks for each TF-target connection, identifying correlated networks. In addition, these GRNs will be used to identify promoter elements contributing to cold responsiveness. Promoter regions for six morphotypes will be used to identify motifs that are shared among cold-responsive paralogs. In developing these networks, the goal is to deepen our understanding of plant adaptation to environmental stresses and provide insights into potential targets for enhancing crop resilience in an ever-changing climate.