RT Journal Article SR Electronic T1 Environmental gene regulatory influence networks in rice (Oryza sativa): response to water deficit, high temperature and agricultural environments JF bioRxiv FD Cold Spring Harbor Laboratory SP 042317 DO 10.1101/042317 A1 Olivia Wilkins A1 Christoph Hafemiester A1 Anne Plessis A1 Meisha-Marika Holloway-Phillips A1 Gina Pham A1 Addrienne B. Nicotra A1 Glenn B. Gregorio A1 S. V. Krishna Jagadish A1 Endang M. Septiningsih A1 Richard Bonneau A1 Michael Purugganan YR 2016 UL http://biorxiv.org/content/early/2016/03/03/042317.abstract AB We inferred an environmental gene regulatory influence network (EGRIN) of the response of tropical Asian rice (Oryza sativa) to high temperatures, water deficit and agricultural environments. This network integrates transcriptome data (RNA-seq) and chromatin accessibility measurements (ATAC-seq) from five rice cultivars that were grown in controlled experiments and in agricultural fields. We identified open chromatin regions covering ~2% of the genome. These regions were highly overrepresented proximal to the transcriptional start sites of genes and were used to define the promoters for all genes. We used the occurrences of known cis-regulatory motifs in the promoters to generate a network prior comprising 77,071 interactions. We then estimated the regulatory activity of each TF (TFA;143 TFs) based on the expression of its target genes in the network prior across 360 experimental conditions. We inferred an EGRIN using the estimated TFA, rather than the TF expression, as the regulator. The EGRIN identified hypotheses for 4,052 genes regulated by 113 TFs; of these, 18% were in the network prior. We resolved distinct regulatory roles for members of a large TF family, including a putative regulatory connection between abiotic stress and the circadian clock, as well as specific regulatory functions for TFs in the drought response. We find that TFA estimation is an effective way of incorporating multiple genome-scale measurements into network inference and that supplementing data from controlled experimental conditions with data from outdoor field conditions increases the resolution of EGRIN inference.