The pandemic dilemma

Pairwise overlaps of TAD boundaries. The pairwise overlaps of TAD boundaries are shown for all samples of this study, after calling boundaries using hicratio (all reads, d = 0500). Before TAD calling, the Hi-C matrices were either unprocessed (filtered) or corrected using iterative correction (IC) (resolution = 40 kb). (PDF 3847 kb

Regulation of transcriptional elongation in pluripotency and cell differentiation by the PHD-finger protein Phf5a

Pluripotent embryonic stem cells (ESCs) self-renew or differentiate into all tissues of the developing embryo and cell-specification factors are necessary to balance gene expression. Here we delineate the function of the PHD-finger protein 5a (Phf5a) in ESC self-renewal and ascribe its role in regulating pluripotency, cellular reprogramming, and myoblast specification. We demonstrate that Phf5a is essential for maintaining pluripotency, since depleted ESCs exhibit hallmarks of differentiation. Mechanistically, we attribute Phf5a function to the stabilization of the Paf1 transcriptional complex and control of RNA polymerase II elongation on pluripotency loci. Apart from an ESC-specific factor, we demonstrate that Phf5a controls differentiation of adult myoblasts. Our findings suggest a potent mode of regulation by the Phf5a in stem cells, which directs their transcriptional program ultimately regulating maintenance of pluripotency and cellular reprogramming

Three-dimensional chromatin landscapes in T cell acute lymphoblastic leukemia

Analysis of 3D chromatin architecture in T-ALL identifies differences in intra-TAD interactions and TAD boundary insulation. Inhibition of oncogenic signal transduction or epigenetic regulation can alter specific 3D interactions. Differences in three-dimensional (3D) chromatin architecture can influence the integrity of topologically associating domains (TADs) and rewire specific enhancer-promoter interactions, impacting gene expression and leading to human disease. Here we investigate the 3D chromatin architecture in T cell acute lymphoblastic leukemia (T-ALL) by using primary human leukemia specimens and examine the dynamic responses of this architecture to pharmacological agents. Systematic integration of matched in situ Hi-C, RNA-seq and CTCF ChIP-seq datasets revealed widespread differences in intra-TAD chromatin interactions and TAD boundary insulation in T-ALL. Our studies identify and focus on a TAD 'fusion' event associated with absence of CTCF-mediated insulation, enabling direct interactions between the MYC promoter and a distal super-enhancer. Moreover, our data also demonstrate that small-molecule inhibitors targeting either oncogenic signal transduction or epigenetic regulation can alter specific 3D interactions found in leukemia. Overall, our study highlights the impact, complexity and dynamic nature of 3D chromatin architecture in human acute leukemia

Tumor immune infiltration estimated from gene expression profiles predicts colorectal cancer relapse

A substantial fraction of patients with stage I-III colorectal adenocarcinoma (CRC) experience disease relapse after surgery with curative intent. However, biomarkers for predicting the likelihood of CRC relapse have not been fully explored. Therefore, we assessed the association between tumor infiltration by a broad array of innate and adaptive immune cell types and CRC relapse risk. We implemented a discovery-validation design including a discovery dataset from Moffitt Cancer Center (MCC; Tampa, FL) and three independent validation datasets: (1) GSE41258 (2) the Molecular Epidemiology of Colorectal Cancer (MECC) study, and (3) GSE39582. Infiltration by 22 immune cell types was inferred from tumor gene expression data, and the association between immune infiltration by each cell type and relapse-free survival was assessed using Cox proportional hazards regression. Within each of the four independent cohorts, CD4+ memory activated T cell (HR: 0.93, 95% CI: 0.90-0.96; FDR = 0.0001) infiltration was associated with longer time to disease relapse, independent of stage, microsatellite instability, and adjuvant therapy. Based on our meta-analysis across the four datasets, 10 innate and adaptive immune cell types associated with disease relapse of which 2 were internally validated using multiplex immunofluorescence. Moreover, immune cell type infiltration was a better predictors of disease relapse than Consensus Molecular Subtype (CMS) and other expression-based biomarkers (Immune-AICMCC:238.1-238.9; CMS-AICMCC: 241.0). These data suggest that transcriptome-derived immune profiles are prognostic indicators of CRC relapse and quantification of both innate and adaptive immune cell types may serve as candidate biomarkers for predicting prognosis and guiding frequency and modality of disease surveillance

Colorectal Cancer and Basement Membranes: Clinicopathological Correlations

Colorectal cancer (CRC) is the third most commonly diagnosed cancer in males and the second in females. In 2008, an estimated 1.2 million people were diagnosed with and 608,700 people died of CRC. Besides diagnosis and treatment, prognosis is an important matter for cancer patients. Today, clinicopathological correlations have many applications in cancer prognostication. Examples include the prediction of the medium patient survival and the screening for patients suitable for specific therapeutic approaches. Apart from traditional prognostic factors, such as tumor stage and grade, new markers may be useful in clinical practice. Possible markers may result from the study of basement membranes (BMs). BM seems to play a role in the pathogenesis of colorectal cancer, so BM alterations may have prognostic significance as well. The purpose of this review is to briefly describe BMs and their relationship with CRC, in the aspect of clinicopathological correlations

HiC-bench: initial release (v0.1)

HiC-bench: a Hi-C analysis pipeline that allows combinatorial parameter exploration and benchmarking HiC-bench is a configurable computational pipeline that allows comprehensive and reproducible analysis of Hi-C sequencing data. It has the following characteristics: It performs complete Hi-C analysis starting with the alignment of reads (fastq files) and ending with the annotation of specific interactions, their visualization and enrichment analysis. It is the first Hi-C pipeline that integrates TAD calling using published methods and our own algorithm. It performs calculation of boundary scores using our own methods and existing ones. Every pipeline step is followed by summary statistics (when applicable) and visualization of the results. This allows quality control and facilitates troubleshooting. It is fully expandable and customizable. Users can follow the included wrapper script template in order to add new tools. It allows parameter exploration and comparison of different methods in a combinatorial fashion. This unique feature facilitates the design and execution of complex benchmark studies that may involve combinations of multiple parameter/tool choices in each step It has been built with reproducibility in mind. All parameter settings are automatically logged

HiC-bench : comprehensive and reproducible Hi-C data analysis designed for parameter exploration and benchmarking

Background: Chromatin conformation capture techniques have evolved rapidly over the last few years and have provided new insights into genome organization at an unprecedented resolution. Analysis of Hi-C data is complex and computationally intensive involving multiple tasks and requiring robust quality assessment. This has led to the development of several tools and methods for processing Hi-C data. However, most of the existing tools do not cover all aspects of the analysis and only offer few quality assessment options. Additionally, availability of a multitude of tools makes scientists wonder how these tools and associated parameters can be optimally used, and how potential discrepancies can be interpreted and resolved. Most importantly, investigators need to be ensured that slight changes in parameters and/or methods do not affect the conclusions of their studies. Results: To address these issues (compare, explore and reproduce), we introduce HiC-bench, a configurable computational platform for comprehensive and reproducible analysis of Hi-C sequencing data. HiC-bench performs all common Hi-C analysis tasks, such as alignment, filtering, contact matrix generation and normalization, identification of topological domains, scoring and annotation of specific interactions using both published tools and our own. We have also embedded various tasks that perform quality assessment and visualization. HiC-bench is implemented as a data flow platform with an emphasis on analysis reproducibility. Additionally, the user can readily perform parameter exploration and comparison of different tools in a combinatorial manner that takes into account all desired parameter settings in each pipeline task. This unique feature facilitates the design and execution of complex benchmark studies that may involve combinations of multiple tool/parameter choices in each step of the analysis. To demonstrate the usefulness of our platform, we performed a comprehensive benchmark of existing and new TAD callers exploring different matrix correction methods, parameter settings and sequencing depths. Users can extend our pipeline by adding more tools as they become available. Conclusions: HiC-bench consists an easy-to-use and extensible platform for comprehensive analysis of Hi-C datasets. We expect that it will facilitate current analyses and help scientists formulate and test new hypotheses in the field of three-dimensional genome organization

Opposing functions of H2BK120 ubiquitylation and H3K79 methylation in the regulation of pluripotency by the Paf1 complex

Maintenance of stem cell plasticity is determined by the ability to balance opposing forces that control gene expression. Regulation of transcriptional networks, signaling cues and chromatin-modifying mechanisms constitute crucial determinants of tissue equilibrium. Histone modifications can affect chromatin compaction, therefore co-transcriptional events that influence their deposition determine the propensities toward quiescence, self-renewal, or cell specification. The Paf1 complex (Paf1C) is a critical regulator of RNA PolII elongation that controls gene expression and deposition of histone modifications, however few studies have focused on its role affecting stem cell fate decisions. Here we delineate the functions of Paf1C in pluripotency and characterize its impact in deposition of H2B ubiquitylation (H2BK120-ub) and H3K79 methylation (H3K79me), 2 fundamental histone marks that shape transcriptional regulation. We identify that H2BK120-ub is increased in the absence of Paf1C on its embryonic stem cell targets, in sharp contrast to H3K79me, suggesting opposite functions in the maintenance of self-renewal. Furthermore, we found that core pluripotency genes are characterized by a dual gain of H2BK120-ub and loss of H3K79me on their gene bodies. Our findings elucidate molecular mechanisms of cellular adaptation and reveal novel functions of Paf1C in the regulation of the self-renewal network

Stratification of TAD boundaries reveals preferential insulation of super-enhancers by strong boundaries

Topologically associating domains (TADs) detected by Hi-C technologies are megabase-scale areas of highly interacting chromatin. Here Gong, Lazaris et al. develop a computational approach to improve the reproducibility of Hi-C contact matrices and stratify TAD boundaries based on their insulating strength

Additional file 3: Table S2. of HiC-bench: comprehensive and reproducible Hi-C data analysis designed for parameter exploration and benchmarking

HiC-bench input-output objects. The table summarizes the inputs and outputs of the TAD-calling task using three different methods with parameter values stored in the params files (column 2). The first column describes the tree structure of the input directories that are essentially the different Hi-C matrices for each sample, before (filtered) and after matrix correction using different methods (e.g., IC). The second column lists all the different parameter scripts and the third column corresponds to the tree structure of the generated output objects. (XLSX 10 kb