Identification of DNA methylation characteristics associated with metastasis and prognosis in colorectal cancer.

Colorectal cancer (CRC) is prone to metastasis and recurrence after surgery, which is one of the main causes for its poor treatment and prognosis. Therefore, it is essential to identify biomarkers associated with metastasis and recurrence in CRC. DNA methylation has a regulatory role in cancer metastasis, tumor immune microenvironment (TME), and prognosis and may be one of the most valuable biomarkers for predicting CRC metastasis and prognosis. We constructed a diagnostic model and nomogram that can effectively predict CRC metastasis based on the differential methylation CpG sites (DMCs) between metastatic and non-metastatic CRC patients. Then, we identified 17 DMCs associated with progression free survival (PFS) of CRC and constructed a prognostic model. The prognosis model based on 17 DMCs can predict the PFS of CRC with medium to high accuracy. The results of immunohistochemical analysis indicated that the protein expression levels of the genes involved in prognostic DMCs were different between normal and colorectal cancer tissues. According to the results of immune-related analysis, we found that the low-risk patients had better immunotherapy response. In addition, high risk scores were negatively correlated with high tumor mutation burden (TMB) levels, and patients with low TMB levels in the high-risk group had the worst PFS. Our work shows the clinical value of DNA methylation in predicting CRC metastasis and PFS, as well as their correlation with TME, immunotherapy, and TMB, which helps understand the changes of DNA methylation in CRC metastasis and improving the treatment and prognosis of CRC.

Setd2 supports GATA3+ST2+ thymic-derived Treg cells and suppresses intestinal inflammation.

Treg cells acquire distinct transcriptional properties to suppress specific inflammatory responses. Transcription characteristics of Treg cells are regulated by epigenetic modifications, the mechanism of which remains obscure. Here, we report that Setd2, a histone H3K36 methyltransferase, is important for the survival and suppressive function of Treg cells, especially those from the intestine. Setd2 supports GATA3+ST2+ intestinal thymic-derived Treg (tTreg) cells by facilitating the expression and reciprocal relationship of GATA3 and ST2 in tTreg cells. IL-33 preferentially boosts Th2 cells rather than GATA3+ Treg cells in Foxp3Cre-YFPSetd2 flox/flox mice, corroborating the constraint of Th2 responses by Setd2 expression in Treg cells. SETD2 sustains GATA3 expression in human Treg cells, and SETD2 expression is increased in Treg cells from human colorectal cancer tissues. Epigenetically, Setd2 regulates the transcription of target genes (including Il1rl1) by modulating the activity of promoters and intragenic enhancers where H3K36me3 is typically deposited. Our findings provide mechanistic insights into the regulation of Treg cells and intestinal immunity by Setd2.

PGG.Han: the Han Chinese genome database and analysis platform.

As the largest ethnic group in the world, the Han Chinese population is nonetheless underrepresented in global efforts to catalogue the genomic variability of natural populations. Here, we developed the PGG.Han, a population genome database to serve as the central repository for the genomic data of the Han Chinese Genome Initiative (Phase I). In its current version, the PGG.Han archives whole-genome sequences or high-density genome-wide single-nucleotide variants (SNVs) of 114 783 Han Chinese individuals (a.k.a. the Han100K), representing geographical sub-populations covering 33 of the 34 administrative divisions of China, as well as Singapore. The PGG.Han provides: (i) an interactive interface for visualization of the fine-scale genetic structure of the Han Chinese population; (ii) genome-wide allele frequencies of hierarchical sub-populations; (iii) ancestry inference for individual samples and controlling population stratification based on nested ancestry informative markers (AIMs) panels; (iv) population-structure-aware shared control data for genotype-phenotype association studies (e.g. GWASs) and (v) a Han-Chinese-specific reference panel for genotype imputation. Computational tools are implemented into the PGG.Han, and an online user-friendly interface is provided for data analysis and results visualization. The PGG.Han database is freely accessible via http://www.pgghan.org or https://www.hanchinesegenomes.org.

Chromatin Interaction Analysis with Updated ChIA-PET Tool (V3).

Understanding chromatin interactions is important because they create chromosome conformation and link the cis- and trans- regulatory elements to their target genes for transcriptional regulation. Chromatin Interaction Analysis with Paired-End Tag (ChIA-PET) sequencing is a genome-wide high-throughput technology that detects chromatin interactions associated with a specific protein of interest. We developed ChIA-PET Tool for ChIA-PET data analysis in 2010. Here, we present the updated version of ChIA-PET Tool (V3) as a computational package to process the next-generation sequence data generated from ChIA-PET experiments. It processes short-read and long-read ChIA-PET data with multithreading and generates statistics of results in an HTML file. In this paper, we provide a detailed demonstration of the design of ChIA-PET Tool V3 and how to install it and analyze RNA polymerase II (RNAPII) ChIA-PET data from human K562 cells with it. We compared our tool with existing tools, including ChiaSig, MICC, Mango and ChIA-PET2, by using the same public data set in the same computer. Most peaks detected by the ChIA-PET Tool V3 overlap with those of other tools. There is higher enrichment for significant chromatin interactions from ChIA-PET Tool V3 in aggregate peak analysis (APA) plots. The ChIA-PET Tool V3 is publicly available at GitHub.

A Comprehensive Characterization of the Function of LincRNAs in Transcriptional Regulation Through Long-Range Chromatin Interactions.

LincRNAs are emerging as important regulators with various cellular functions. However, the mechanisms behind their role in transcriptional regulation have not yet been fully explored. In this report, we proposed to characterize the diverse functions of lincRNAs in transcription regulation through an examination of their long-range chromatin interactions. We found that the promoter regions of lincRNAs displayed two distinct patterns of chromatin states, promoter-like and enhancer-like, indicating different regulatory functions for lincRNAs. Notably, the chromatin interactions between lincRNA genes and other genes suggested a potential mechanism for lincRNAs in the regulation of other genes at the RNA level because the transcribed lincRNAs could function at local spaces on other genes that interact with the lincRNAs at the DNA level. These results represent a novel way to predict the functions of lincRNAs. The GWAS-identification of SNPs within the lincRNAs revealed that some lincRNAs were disease-associated, and the chromatin interactions with those lincRNAs suggested that they were potential target genes of these lincRNA-associated SNPs. Our study provides new insights into the roles that lincRNAs play in transcription regulation.

Chromatin Interaction Analysis with Paired-End Tag (ChIA-PET) sequencing technology and application.

BACKGROUND: Long-range chromatin interactions play an important role in transcription regulation. Chromatin Interaction Analysis with Paired-End-Tag sequencing (ChIA-PET) is an emerging technology that has unique advantages in chromatin interaction analysis, and thus provides insight into the study of transcription regulation. RESULTS: This article introduces the experimental protocol and data analysis process of ChIA-PET, as well as discusses some applications using this technology. It also unveils the direction of future studies based on this technology. CONCLUSIONS: Overall we show that ChIA-PET is the cornerstone to explore the three-dimensional (3D) chromatin structure, and certainly will lead the forthcoming wave of 3D genomics studies.