The human disease methylation database (DiseaseMeth, http://bioinfo.hrbmu.edu.cn/diseasemeth/) is an interactive database that aims to present the most complete collection and annotation of aberrant DNA methylation in human diseases, especially various cancers. Recently, the high-throughput microarray and sequencing technologies have promoted the production of methylome data that contain comprehensive knowledge of human diseases. In this DiseaseMeth update, we have increased the number of samples from 3610 to 32 701, the number of diseases from 72 to 88 and the disease–gene associations from 216 201 to 679 602. DiseaseMeth version 2.0 provides an expanded comprehensive list of disease–gene associations based on manual curation from experimental studies and computational identification from high-throughput methylome data. Besides the data expansion, we also updated the search engine and visualization tools. In particular, we enhanced the differential analysis tools, which now enable online automated identification of DNA methylation abnormalities in human disease in a case-control or disease–disease manner. To facilitate further mining of the disease methylome, three new web tools were developed for cluster analysis, functional annotation and survival analysis. DiseaseMeth version 2.0 should be a useful resource platform for further understanding the molecular mechanisms of human diseases.

Tumour heterogeneity is an obstacle to effective breast cancer diagnosis and therapy. DNA methylation is an important regulator of gene expression, thus characterizing tumour heterogeneity by epigenetic features can be clinically informative. In this study, we explored specific prognosis‐subtypes based on DNA methylation status using 669 breast cancers from the TCGA database. Nine subgroups were distinguished by consensus clustering using 3869 CpGs that significantly influenced survival. The specific DNA methylation patterns were reflected by different races, ages, tumour stages, receptor status, histological types, metastasis status and prognosis. Compared with the PAM50 subtypes, which use gene expression clustering, DNA methylation subtypes were more elaborate and classified the Basal‐like subtype into two different prognosis‐subgroups. Additionally, 1252 CpGs (corresponding to 888 genes) were identified as specific hyper/hypomethylation sites for each specific subgroup. Finally, a prognosis model based on Bayesian network classification was constructed and used to classify the test set into DNA methylation subgroups, which corresponded to the classification results of the train set. These specific classifications by DNA methylation can explain the heterogeneity of previous molecular subgroups in breast cancer and will help in the development of personalized treatments for the new specific subtypes.

Epigenetic mechanisms play important regulatory roles in hematopoiesis and hematopoietic stem cell (HSC) function. Subunits of polycomb repressive complex 1 (PRC1), the major histone H2A ubiquitin ligase, are critical for both normal and pathological hematopoiesis; however, it is unclear which of the several counteracting H2A deubiquitinases functions along with PRC1 to control H2A ubiquitination (ubH2A) level and regulates hematopoiesis in vivo. Here we investigated the function of Usp16 in mouse hematopoiesis. Conditional deletion of Usp16 in bone marrow resulted in a significant increase of global ubH2A level and lethality. Usp16 deletion did not change HSC number but was associated with a dramatic reduction of mature and progenitor cell populations, revealing a role in governing HSC lineage commitment. ChIP- and RNA-sequencing studies in HSC and progenitor cells revealed that Usp16 bound to many important hematopoietic regulators and that Usp16 deletion altered the expression of genes in transcription/chromosome organization, immune response, hematopoietic/lymphoid organ development, and myeloid/leukocyte differentiation. The altered gene expression was partly rescued by knockdown of PRC1 subunits, suggesting that Usp16 and PRC1 counterbalance each other to regulate cellular ubH2A level and gene expression in the hematopoietic system. We further discovered that knocking down Cdkn1a (p21cip1), a Usp16 target and regulated gene, rescued the altered cell cycle profile and differentiation defect of Usp16-deleted HSCs. Collectively, these studies identified Usp16 as one of the histone H2A deubiquitinases, which coordinates with the H2A ubiquitin ligase PRC1 to regulate hematopoiesis, and revealed cell cycle regulation by Usp16 as key for HSC differentiation.

Posttranslational histone modifications play important roles in regulating chromatin-based nuclear processes. Histone H2AK119 ubiquitination (H2Aub) is a prevalent modification and has been primarily linked to gene silencing. However, the underlying mechanism remains largely obscure. Here we report the identification of RSF1 (remodeling and spacing factor 1), a subunit of the RSF complex, as a H2Aub binding protein, which mediates the gene-silencing function of this histone modification. RSF1 associates specifically with H2Aub, but not H2Bub nucleosomes, through a previously uncharacterized and obligatory region designated as ubiquitinated H2A binding domain. In human and mouse cells, genes regulated by RSF1 overlap significantly with those controlled by RNF2/Ring1B, the subunit of Polycomb repressive complex 1 (PRC1) which catalyzes the ubiquitination of H2AK119. About 82% of H2Aub-enriched genes, including the classic PRC1 target genes, are bound by RSF1 around their transcription start sites. Depletion of H2Aub levels by Ring1B knockout results in a significant reduction of RSF1 binding. In contrast, RSF1 knockout does not affect RNF2/Ring1B or H2Aub levels but leads to derepression of H2Aub target genes, accompanied by changes in H2Aub chromatin organization and release of linker histone H1. The action of RSF1 in H2Aub-mediated gene silencing is further demonstrated by chromatin-based in vitro transcription. Finally, RSF1 and Ring1 act cooperatively to regulate mesodermal cell specification and gastrulation during early embryonic development. Taken together, these data identify RSF1 as a H2Aub reader that contributes to H2Aub-mediated gene silencing by maintaining a stable nucleosome pattern at promoter regions.

Super-enhancers (SEs) are critical for the transcriptional regulation of gene expression. We developed the super-enhancer archive version 3.0 (SEA v. 3.0, http://sea.edbc.org) to extend SE research. SEA v. 3.0 provides the most comprehensive archive to date, consisting of 164 545 super-enhancers. Of these, 80 549 are newly identified from 266 cell types/tissues/diseases using an optimized computational strategy, and 52 have been experimentally confirmed with manually curated references. We now support super-enhancers in 11 species including 7 new species (zebrafish, chicken, chimp, rhesus, sheep, Xenopus tropicalis and stickleback). To facilitate super-enhancer functional analysis, we added several new regulatory datasets including 3 361 785 typical enhancers, chromatin interactions, SNPs, transcription factor binding sites and SpCas9 target sites. We also updated or developed new criteria query, genome visualization and analysis tools for the archive. This includes a tool based on Shannon Entropy to evaluate SE cell type specificity, a new genome browser that enables the visualization of SE spatial interactions based on Hi-C data, and an enhanced enrichment analysis interface that provides online enrichment analyses of SE related genes. SEA v. 3.0 provides a comprehensive database of all available SE information across multiple species, and will facilitate super-enhancer research, especially as related to development and disease.

Evidence, demonstrating long noncoding RNAs (lncRNAs) as critical players in cancer, remains to increase. lncRNA SBF2‐AS1 was reported to be involved in several cancers, such as hepatocellular carcinoma. However, the role of SBF2‐AS1 in colorectal cancer (CRC) is unknown. We showed lncRNA SBF2‐AS1 expression was growing in CRC samples, especially in advanced cases. Accordingly, SBF2‐AS1 possesses higher expression in CRC cell lines than in normal cell line. Moreover, SBF2‐AS1 high expression indicated a low survival rate. Functionally, SBF2‐AS1 knockdown suppressed the proliferation, migration, and invasion of CRC cells. In terms of mechanism, SBF2‐AS1 upregulation restrained the activity of miR‐619‐5p and led to overexpression of HDAC3. Importantly, downregulation of miR‐619‐5p or HDAC3 overexpression reversed SBF2‐AS1‐silencing‐caused suppression on proliferation and metastasis. Summarily, our findings elucidated a crucial role of SBF2‐AS1 as a miR‐619‐5p sponge, shedding novel light on lncRNA‐related prognostics.

Chromosomal translocations of MLL1 (Mixed Lineage Leukemia 1) yield oncogenic chimeric proteins containing the N-terminal portion of MLL1 fused with distinct partners. The MLL1–AF10 fusion causes leukemia through recruiting the H3K79 histone methyltransferase DOT1L via AF10’s octapeptide and leucine zipper (OM-LZ) motifs. Yet, the precise interaction sites in DOT1L, detailed interaction modes between AF10 and DOT1L, and the functional configuration of MLL1–AF10 in leukeomogenesis remain unknown. Through a combined approach of structural and functional analyses, we found that the LZ domain of AF10 interacts with the coiled-coil domains of DOT1L through a conserved binding mode and discovered that the C-terminal end of the LZ domain and the OM domain of AF10 mediate the formation of a DOT1L–AF10 octamer via tetramerization of the binary complex. We reveal that the oligomerization ability of the DOT1L–AF10 complex is essential for MLL1–AF10’s leukemogenic function. These findings provide insights into the molecular basis of pathogenesis by MLL1 rearrangements.

BackgroundIt is generally believed that DNA methylation, as one of the most important epigenetic modifications, participates in the regulation of gene expression and plays an important role in the development of cancer, and there exits epigenetic heterogeneity among cancers. Therefore, this study tried to screen for reliable prognostic markers for different cancers, providing further explanation for the heterogeneity of cancers, and more targets for clinical transformation studies of cancer from epigenetic perspective.MethodsThis article discusses the epigenetic heterogeneity of cancer in detail. Firstly, DNA methylation data of seven cancer types were obtained from Illumina Infinium HumanMethylation 450 K platform of TCGA database. Then, differential methylation analysis was performed in the promotor region. Secondly, pivotal gene markers were obtained by constructing the DNA methylation correlation network and the gene interaction network in the KEGG pathway, and 317 marker genes obtained from two networks were integrated as candidate markers for the prognosis model. Finally, we used the univariate and multivariate COX regression models to select specific independent prognostic markers for each cancer, and studied the risk factor of these genes by doing survival analysis.ResultsFirst, the cancer type-specific gene markers were obtained by differential methylation analysis and they were found to be involved in different biological functions by enrichment analysis. Moreover, specific and common diagnostic markers for each type of cancer was sorted out and Kaplan-Meier survival analysis showed that there was significant difference in survival between the two risk groups.ConclusionsThis study screened out reliable prognostic markers for different cancers, providing a further explanation for the heterogeneity of cancer at the DNA methylation level and more targets for clinical conversion studies of cancer.