Abstract
AbstractCis-regulatory elements (CREs) are non-coding DNA sequences that modulate gene expression. Their identification is critical to study the transcriptional regulation of genes controlling key traits that govern plant growth and development. They are also crucial components for the delineation of gene regulatory networks, which represent regulatory interactions between transcription factors (TFs) and target genes. In maize, CREs have been profiled using different computational and experimental methods, but the extent to which these methods complement each other in identifying functional CREs is unclear. Here, we report the data-driven integration of different maize CRE profiling methods to optimize the capture of experimentally-confirmed TF binding sites, resulting in maps of integrated CREs (iCREs) showing increased levels of completeness and precision. We combined the iCREs with a wide diversity of gene expression data under drought conditions to perform motif enrichment and infer drought-specific GRNs. Mining these organ-specific GRNs revealed previously characterized and novel candidate regulators of maize drought response. Furthermore, by studying the transposable elements (TEs) overlapping with iCREs, we identified few TE superfamilies displaying typical epigenetic features of regulatory DNA that are potentially involved in wiring specific TF-target gene regulatory interactions. Overall, our study showcases the integration of different omics data sources to generate a high-quality collection of CREs, together with their applicability to better characterize gene regulation in the complex maize genome.
Publisher
Cold Spring Harbor Laboratory