3D-Epigenomic Regulation of Gene Transcription in Hepatocellular Carcinoma.

The fundamental cause of transcription dysregulation in hepatocellular carcinoma (HCC) remains elusive. To investigate the underlying mechanisms, comprehensive 3D-epigenomic analyses are performed in cellular models of THLE2 (a normal hepatocytes cell line) and HepG2 (a hepatocellular carcinoma cell line) using integrative approaches for chromatin topology, genomic and epigenomic variation, and transcriptional output. Comparing the 3D-epigenomes in THLE2 and HepG2 reveal that most HCC-associated genes are organized in complex chromatin interactions mediated by RNA polymerase II (RNAPII). Incorporation of genome-wide association studies (GWAS) data enables the identification of non-coding genetic variants that are enriched in distal enhancers connecting to the promoters of HCC-associated genes via long-range chromatin interactions, highlighting their functional roles. Interestingly, CTCF binding and looping proximal to HCC-associated genes appear to form chromatin architectures that overarch RNAPII-mediated chromatin interactions. It is further demonstrated that epigenetic variants by DNA hypomethylation at a subset of CTCF motifs proximal to HCC-associated genes can modify chromatin topological configuration, which in turn alter RNAPII-mediated chromatin interactions and lead to dysregulation of transcription. Together, the 3D-epigenomic analyses provide novel insights of multifaceted interplays involving genetics, epigenetics, and chromatin topology in HCC cells

Chromatin topology reorganization and transcription repression by PML-RARα in acute promyeloid leukemia.

BACKGROUND: Acute promyeloid leukemia (APL) is characterized by the oncogenic fusion protein PML-RARα, a major etiological agent in APL. However, the molecular mechanisms underlying the role of PML-RARα in leukemogenesis remain largely unknown. RESULTS: Using an inducible system, we comprehensively analyze the 3D genome organization in myeloid cells and its reorganization after PML-RARα induction and perform additional analyses in patient-derived APL cells with native PML-RARα. We discover that PML-RARα mediates extensive chromatin interactions genome-wide. Globally, it redefines the chromatin topology of the myeloid genome toward a more condensed configuration in APL cells; locally, it intrudes RNAPII-associated interaction domains, interrupts myeloid-specific transcription factors binding at enhancers and super-enhancers, and leads to transcriptional repression of genes critical for myeloid differentiation and maturation. CONCLUSIONS: Our results not only provide novel topological insights for the roles of PML-RARα in transforming myeloid cells into leukemia cells, but further uncover a topological framework of a molecular mechanism for oncogenic fusion proteins in cancers

BRD9-SMAD2/3 orchestrates stemness and tumorigenesis in pancreatic ductal adenocarcinoma

Background and Aims The dismal prognosis of pancreatic ductal adenocarcinoma (PDAC) is linked to the presence of pancreatic cancer stem-like cells (CSCs) that respond poorly to current chemotherapy regimens. The epigenetic mechanisms regulating CSCs are currently insufficiently understood, which hampers the development of novel strategies for eliminating CSCs. Methods By small molecule compound screening targeting 142 epigenetic enzymes, we identified that bromodomain-containing protein BRD9, a component of the BAF histone remodeling complex, is a key chromatin regulator to orchestrate the stemness of pancreatic CSCs via cooperating with the TGFβ/Activin-SMAD2/3 signaling pathway. Results Inhibition and genetic ablation of BRD9 block the self-renewal, cell cycle entry into G0 phase and invasiveness of CSCs, and improve the sensitivity of CSCs to gemcitabine treatment. In addition, pharmacological inhibition of BRD9 significantly reduced the tumorigenesis in patient-derived xenografts mouse models and eliminated CSCs in tumors from pancreatic cancer patients. Mechanistically, inhibition of BRD9 disrupts enhancer-promoter looping and transcription of stemness genes in CSCs. Conclusions Collectively, the data suggest BRD9 as a novel therapeutic target for PDAC treatment via modulation of CSC stemness

Time-series interval prediction under uncertainty using modified double multiplicative neuron network

This paper presents a hybrid intelligent approach for constructing prediction intervals (PIs) of terrain profiles over time under uncertainty. It utilizes the double multiplicative neuron (DMN) model and the modified particle swarm optimization (MPSO) algorithm to calculate the upper and lower bounds of unknown elevations ahead on terrain profiles based on the vehicles’ track. MPSO withholds particles generating the positive PIs in the training epochs, in order to prevent the occurrence of unreasonable upside-down PIs that are brought by conventional methods. MPSO adjusts the parameters of the DMN model iteratively by minimizing the value of the proposed cost function. The fitness function aims to enhance DMN's capability of forecasting terrain trends by integrating a trend indicator with PIs coverage probability and interval widths. This study utilizes the terrain profiles of 3 arc-seconds resolution to verify the effectiveness of the proposed MPSO-DMNT approach for one-step and multi-step PIs estimation. Experimental results demonstrate that the proposed approach (1) overcomes the limitations of the conventional PIs indicators; (2) improves the prediction accuracy for terrain trends by 18.8% in the training data and 15.4% in the testing data, and reduces the computational burden by 31.6% in the training data and 8% in the testing data over the lower upper bound estimation (LUBE) method; (3) achieves comparative coverage probability and interval widths to LUBE using a low-complexity single-layered network. The proposed hybrid approach can be used as an auxiliary decision-making tool for terrain avoidance and terrain following in flight.The authors would like to acknowledge support from the State Scholarship Fund (No. 201906835048) granted by the China Scholar-ship Council and the National Science and Technology Major Project (No. 2017-IV-0008-0045)

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 Robust Dual Reference Computing-in-Memory Implementation and Design Space Exploration Within STT-MRAM

International audienceDue to the "memory wall" in conventional Von-Neumann computer architectures, the limited bandwidth between processors and memories has become one of the most critical bottlenecks to improve system performance. With the emerging of non-volatile memories, the computing-in-memory (CIM) paradigm has regained interest to tackle the issue at the architecture level. CIM can effectively alleviate the stress on the limitted bandwidth by performing logic operations within memories. However, CIMs are not yet studied carefully at the circuit level, and even its reliability and performance. In this paper, we proposed a CIM implementation: dual reference (DualRef) scheme at the circuit level within STT-MRAM (Spin Transfer Torque Magnetic Random Access Memory) array. Simulations were carried out to verify the functionality and assess the reliability and performance of DualRef scheme in terms of operation error rate, sensing margin, operation delay and dynamic energy consumption. Simulation results validate DualRef scheme and reveal that it is reliable to perform bitwise logic opertions within STT-MRAM while the TMR (Tunnel Magnetoresistance Ratio) varying between 100% and 300% and supply voltage Vdd varying from 0.9V to 1.2V. This work provides a robust circuitry scheme and design space to effectively implement CIM in STT-MRAM

ChIA-PIPE: A fully automated pipeline for comprehensive ChIA-PET data analysis and visualization.

ChIA-PET (chromatin interaction analysis with paired-end tags) enables genome-wide discovery of chromatin interactions involving specific protein factors, with base pair resolution. Interpretation of ChIA-PET data requires a robust analytic pipeline. Here, we introduce ChIA-PIPE, a fully automated pipeline for ChIA-PET data processing, quality assessment, visualization, and analysis. ChIA-PIPE performs linker filtering, read mapping, peak calling, and loop calling and automates quality control assessment for each dataset. To enable visualization, ChIA-PIPE generates input files for two-dimensional contact map viewing with Juicebox and HiGlass and provides a new dockerized visualization tool for high-resolution, browser-based exploration of peaks and loops. To enable structural interpretation, ChIA-PIPE calls chromatin contact domains, resolves allele-specific peaks and loops, and annotates enhancer-promoter loops. ChIA-PIPE also supports the analysis of other related chromatin-mapping data types