Background Bread wheat is an allohexaploid species with a 16-Gb genome that has large intergenic regions, which presents a big challenge for pinpointing regulatory elements and further revealing the transcriptional regulatory mechanisms. Chromatin profiling to characterize the combinatorial patterns of chromatin signatures is a powerful means to detect functional elements and clarify regulatory activities in human studies. Results In the present study, through comprehensive analyses of the open chromatin, DNA methylome, seven major chromatin marks, and transcriptomic data generated for seedlings of allohexaploid wheat, we detected distinct chromatin architectural features surrounding various functional elements, including genes, promoters, enhancer-like elements, and transposons. Thousands of new genic regions and cis-regulatory elements are identified based on the combinatorial pattern of chromatin features. Roughly 1.5% of the genome encodes a subset of active regulatory elements, including promoters and enhancer-like elements, which are characterized by a high degree of chromatin openness and histone acetylation, an abundance of CpG islands, and low DNA methylation levels. A comparison across sub-genomes reveals that evolutionary selection on gene regulation is targeted at the sequence and chromatin feature levels. The divergent enrichment of cis-elements between enhancer-like sequences and promoters implies these functional elements are targeted by different transcription factors. Conclusions We herein present a systematic epigenomic map for the annotation of cis-regulatory elements in the bread wheat genome, which provides new insights into the connections between chromatin modifications and cis-regulatory activities in allohexaploid wheat. Electronic supplementary material The online version of this article (10.1186/s13059-019-1746-8) contains supplementary material, which is available to authorized users.

SummaryHigh‐throughput technology has become a powerful approach for routine plant research. Interpreting the biological significance of high‐throughput data has largely focused on the functional characterization of a large gene list or genomic loci that involves the following two aspects: the functions of the genes or loci and how they are regulated as a whole, i.e. searching for the upstream regulators. Traditional platforms for functional annotation largely help resolving the first issue. Addressing the second issue is essential for a global understanding of the regulatory mechanism, but is more challenging, and requires additional high‐throughput experimental evidence and a unified statistical framework for data‐mining. The rapid accumulation of ’omics data provides a large amount of experimental data. We here present Plant Regulomics, an interface that integrates 19 925 transcriptomic and epigenomic data sets and diverse sources of functional evidence (58 112 terms and 695 414 protein−protein interactions) from six plant species along with the orthologous genes from 56 whole‐genome sequenced plant species. All pair‐wise transcriptomic comparisons with biological significance within the same study were performed, and all epigenomic data were processed to genomic loci targeted by various factors. These data were well organized to gene modules and loci lists, which were further implemented into the same statistical framework. For any input gene list or genomic loci, Plant Regulomics retrieves the upstream factors, treatments, and experimental/environmental conditions regulating the input from the integrated ’omics data. Additionally, multiple tools and an interactive visualization are available through a user‐friendly web interface. Plant Regulomics is available at http://bioinfo.sibs.ac.cn/plant-regulomics.