Enhancers are distal cis-regulatory elements that activate the transcription of their target genes. They regulate a wide range of important biological functions and processes, including embryogenesis, development, and homeostasis. As more and more large-scale technologies were developed for enhancer identification, a comprehensive database is highly desirable for enhancer annotation based on various genome-wide profiling datasets across different species. Here, we present an updated database EnhancerAtlas 2.0 (http://www.enhanceratlas.org/indexv2.php), covering 586 tissue/cell types that include a large number of normal tissues, cancer cell lines, and cells at different development stages across nine species. Overall, the database contains 13 494 603 enhancers, which were obtained from 16 055 datasets using 12 high-throughput experiment methods (e.g. H3K4me1/H3K27ac, DNase-seq/ATAC-seq, P300, POLR2A, CAGE, ChIA-PET, GRO-seq, STARR-seq and MPRA). The updated version is a huge expansion of the first version, which only contains the enhancers in human cells. In addition, we predicted enhancer–target gene relationships in human, mouse and fly. Finally, the users can search enhancers and enhancer–target gene relationships through five user-friendly, interactive modules. We believe the new annotation of enhancers in EnhancerAtlas 2.0 will facilitate users to perform useful functional analysis of enhancers in various genomes.

Motivation: Multiple high-throughput approaches have recently been developed and allowed the discovery of enhancers on a genome scale in a single experiment. However, the datasets generated from these approaches are not fully utilized by the research community due to technical challenges such as lack of consensus enhancer annotation and integrative analytic tools. Results: We developed an interactive database, EnhancerAtlas, which contains an atlas of 2,534,123 enhancers for 105 cell/tissue types. A consensus enhancer annotation was obtained for each cell by summation of independent experimental datasets with the relative weights derived from a cross-validation approach. Moreover, EnhancerAtlas provides a set of useful analytic tools that allow users to query and compare enhancers in a particular genomic region or associated with a gene of interest, and assign enhancers and their target genes from a custom dataset. Availability and Implementation: The database with analytic tools is available at http://www.enhan ceratlas.org/.

We reported an integrated database of Compendium of Protein Lysine Modifications (CPLM; http://cplm.biocuckoo.org) for protein lysine modifications (PLMs), which occur at active ε-amino groups of specific lysine residues in proteins and are critical for orchestrating various biological processes. The CPLM database was updated from our previously developed database of Compendium of Protein Lysine Acetylation (CPLA), which contained 7151 lysine acetylation sites in 3311 proteins. Here, we manually collected experimentally identified substrates and sites for 12 types of PLMs, including acetylation, ubiquitination, sumoylation, methylation, butyrylation, crotonylation, glycation, malonylation, phosphoglycerylation, propionylation, succinylation and pupylation. In total, the CPLM database contained 203 972 modification events on 189 919 modified lysines in 45 748 proteins for 122 species. With the dataset, we totally identified 76 types of co-occurrences of various PLMs on the same lysine residues, and the most abundant PLM crosstalk is between acetylation and ubiquitination. Up to 53.5% of acetylation and 33.1% of ubiquitination events co-occur at 10 746 lysine sites. Thus, the various PLM crosstalks suggested that a considerable proportion of lysines were competitively and dynamically regulated in a complicated manner. Taken together, the CPLM database can serve as a useful resource for further research of PLMs.