Biocuration of a Transcription Factors Network Involved in Submergence Tolerance during Seed Germination and Coleoptile Elongation in Rice (Oryza sativa)

Modeling biological processes and genetic-regulatory networks using in silico approaches provides a valuable framework for understanding how genes and associated allelic and genotypic differences result in specific traits. Submergence tolerance is a significant agronomic trait in rice; however, the gene-gene interactions linked with this polygenic trait remain largely unknown. In this study, we constructed a network of 57 transcription factors involved in seed germination and coleoptile elongation under submergence. The gene-gene interactions were based on the co-expression profiles of genes and the presence of transcription factor binding sites in the promoter region of target genes. We also incorporated published experimental evidence, wherever available, to support gene-gene, gene-protein, and protein-protein interactions. The co-expression data were obtained by re-analyzing publicly available transcriptome data from rice. Notably, this network includes OSH1, OSH15, OSH71, Sub1B, ERFs, WRKYs, NACs, ZFP36, TCPs, etc., which play key regulatory roles in seed germination, coleoptile elongation and submergence response, and mediate gravitropic signaling by regulating OsLAZY1 and/or IL2. The network of transcription factors was manually biocurated and submitted to the Plant Reactome Knowledgebase to make it publicly accessible. We expect this work will facilitate the re-analysis/re-use of OMICs data and aid genomics research to accelerate crop improvement.

Automated summary

Modeling biological processes and genetic-regulatory networks using in silico approaches is valuable for understanding how genes and variations result in specific traits. This study constructed a network of 57 transcription factors to explore gene-gene interactions in seed germination and coleoptile elongation under submergence. The network incorporates co-expression data and experimental evidence, and is publicly accessible to facilitate re-analysis of OMICs data and accelerate crop improvement.