Summary Understanding the topological configurations of chromatin may reveal valuable insights into how the genome and epigenome act in concert to control cell fate during development. Here we generate high-resolution architecture maps across seven genomic loci in embryonic stem cells and neural progenitor cells. We observe a hierarchy of 3-D interactions that undergo marked reorganization at the sub-Mb scale during differentiation. Distinct combinations of CTCF, Mediator, and cohesin show widespread enrichment in looping interactions at different length scales. CTCF/cohesin anchor long-range constitutive interactions that form the topological basis for invariant sub-domains. Conversely, Mediator/cohesin together with pioneer factors bridge shortrange enhancer-promoter interactions within and between larger sub-domains. Knockdown of Smc1 or Med12 in ES cells results in disruption of spatial architecture and down-regulation of genes found in cohesin-mediated interactions. We conclude that cell type-specific chromatin organization occurs at the sub-Mb scale and that architectural proteins shape the genome in hierarchical length scales.

SUMMARY The immunoglobulin heavy chain (IgH) gene locus undergoes radial re-positioning within the nucleus and locus contraction in preparation for gene recombination. We demonstrate that IgH locus conformation involves two levels of chromosomal compaction. At the first level the locus folds into several multi-looped domains. One such domain at the 3′ end of the locus requires an enhancer, Eμ; two other domains at the 5′ end are Eμ-independent. At the second level, these domains are brought into spatial proximity by Eμ-dependent interactions with specific sites within the VH region. Eμ is also required for radial re-positioning of IgH alleles indicating its essential role in large scale chromosomal movements in developing lymphocytes. Our observations provide a comprehensive view of the conformation of IgH alleles in pro-B cells and the mechanisms by which it is established.

Identification of clinically relevant tumor subtypes and omics signatures is an important task in cancer translational research for precision medicine. Large-scale genomic profiling studies such as The Cancer Genome Atlas (TCGA) Research Network have generated vast amounts of genomic, transcriptomic, epigenomic, and proteomic data. While these studies have provided great resources for researchers to discover clinically relevant tumor subtypes and driver molecular alterations, there are few computationally efficient methods and tools for integrative clustering analysis of these multi-type omics data. Therefore, the aim of this article is to develop a fully Bayesian latent variable method (called iClusterBayes) that can jointly model omics data of continuous and discrete data types for identification of tumor subtypes and relevant omics features. Specifically, the proposed method uses a few latent variables to capture the inherent structure of multiple omics data sets to achieve joint dimension reduction. As a result, the tumor samples can be clustered in the latent variable space and relevant omics features that drive the sample clustering are identified through Bayesian variable selection. This method significantly improve on the existing integrative clustering method iClusterPlus in terms of statistical inference and computational speed. By analyzing TCGA and simulated data sets, we demonstrate the excellent performance of the proposed method in revealing clinically meaningful tumor subtypes and driver omics features.

Emerging studies demonstrate that long noncoding RNAs (lncRNA) participate in the regulation of various cancers. In the current study, a novel has been identified and explored in esophageal squamous cell carcinoma (ESCC). To discover a new regulatory circuitry in which RNAs crosstalk with each other, the transcriptome of lncRNA-miRNA-mRNA from ESCC and adjacent nonmalignant specimens were analyzed using multiple microarrays and diverse bioinformatics platforms. The functional role and mechanism of a novel were further investigated by gain-of-function and loss-of-function assays and An ESCC biomarker panel, consisting of, , and, was validated by qRT-PCR and hybridization using samples from 148 patients. as an oncogene is highly expressed in ESCC tissues and cell lines, and promotes ESCC cell proliferation and metastasis. Mechanistically, promotes expression of transcription factor Snail1 by competitively binding, resulting in the epithelial-mesenchymal transition (EMT) cascade. Moreover, also induces FSCN1 expression by sponging and upregulation of mRNA-stabilizing protein HuR, which further promotes ESCC invasion cascades. We also discovered and validated a clinically applicable ESCC biomarker panel, consisting of ,, and , that is significantly associated with overall survival and provides additional prognostic evidence for ESCC patients. As a novel regulator, plays an important role in ESCC cell proliferation and metastasis. The regulatory axis provides bona fide targets for anti-ESCC therapies. .

The long non-coding RNA, HOTTIP, has an important role in tumorigenesis. It is known that HOTTIP regulates HOX gene family; however, its regulatory mechanism in esophageal squamous cell carcinoma (ESCC) remains elusive. In this study, we investigated the role of HOTTIP in ESCC and observed that HOTTIP/HOXA13 was upregulated in ESCC and promoted cell proliferation and metastasis in vivo and in vitro. Interestingly, harboring a miR-30b-binding site, HOTTIP as a molecular sponge mainly regulated miR-30b level in the nucleus and modulated the repression of HOXA13 mediated by miR-30b in the cytoplasm, resulting in the positive HOTTIP/HOXA13 correlation. In addition, HOTTIP upregulated snail1 by competitively binding miR-30b, subsequently promoting epithelial-mesenchymal transition (EMT) and invasion. HOTTIP directly bound the adaptor protein WDR5 and drove histone H3 lysine 4 trimethylation and HOXA13 gene transcription in ESCC cells. In conclusion, our findings indicated that HOTTIP modulated HOXA13 at both the transcriptional and posttranscriptional levels in ESCC cells and HOTTIP-miR-30b-HOXA13 axis may serve as potential diagnostic markers or drug targets for ESCC therapies.