A map of integrated cis-regulatory elements enhances gene-regulatory analysis in maize.

cis-regulatory elements (CREs) are non-coding DNA sequences that modulate gene expression. Their identification is essential to the study of transcriptional regulation of genes that control key traits involved in plant growth and development. CREs are also critical for the delineation of gene-regulatory networks (GRNs), which map regulatory interactions between transcription factors (TFs) and target genes. In maize, CREs have been profiled using various computational and experimental methods, but the extent to which these approaches complement each other when identifying functional CREs remains unclear. Here, we report the data-driven integration of multiple maize CRE-profiling methods to optimize the capture of experimentally confirmed TF-binding sites, resulting in a map of integrated CREs (iCREs) with improved completeness and precision. We combined these iCREs with diverse gene expression datasets generated under drought conditions to perform motif enrichment analyses and infer drought-specific GRNs. Mining these organ-specific GRNs identified both known and novel candidate regulators of maize drought responses and revealed significant overlap with drought-associated eQTL regulatory interactions. Furthermore, analysis of transposable elements (TEs) overlapping with iCREs identified several TE superfamilies with epigenetic features characteristic of regulatory DNA that potentially mediate specific TF-target gene interactions. Overall, our study showcases the utility of multi-omics data integration to generate a high-quality collection of CREs and illustrates their potential to improve the characterization of gene regulation in the complex maize genome.