Core transcriptional regulatory circuitry in human hepatocytes

FoxA1/2-dependent epigenomic reprogramming drives lineage switching in lung adenocarcinoma

The ability of cancer cells to undergo identity changes (i.e., lineage plasticity) plays a key role in tumor progression and response to therapy. Loss of the pulmonary lineage specifier NKX2-1 in KRAS-driven lung adenocarcinoma (LUAD) enhances tumor progression and causes a FoxA1/2-dependent pulmonary-to-gastric lineage switch. However, the mechanisms by which FoxA1/2 activate a latent gastric identity in the lung remain largely unknown. Here, we show that FoxA1/2 reprogram the epigenetic landscape of gastric-specific genes after NKX2-1 loss in mouse models by facilitating ten-eleven translocation (TET)2/3 recruitment, DNA demethylation, histone 3 lysine 27 acetylation (H3K27ac) deposition, and three-dimensional (3D) chromatin interactions. FoxA1/2-mediated DNA methylation changes are highly conserved in human endodermal development and in progression of human lung and pancreatic neoplasia. Furthermore, oncogenic signaling is required for specific elements of FoxA1/2-dependent epigenetic reprogramming. This work demonstrates the role of FoxA1/2 in rewiring the DNA methylation and 3D chromatin landscape of NKX2-1-negative LUAD to drive cancer cell lineage switching.

Machine-guided design of cell-type-targeting cis-regulatory elements

Cis-regulatory elements (CREs) control gene expression, orchestrating tissue identity, developmental timing and stimulus responses, which collectively define the thousands of unique cell types in the body1-3. While there is great potential for strategically incorporating CREs in therapeutic or biotechnology applications that require tissue specificity, there is no guarantee that an optimal CRE for these intended purposes has arisen naturally. Here we present a platform to engineer and validate synthetic CREs capable of driving gene expression with programmed cell-type specificity. We take advantage of innovations in deep neural network modelling of CRE activity across three cell types, efficient in silico optimization and massively parallel reporter assays to design and empirically test thousands of CREs4-8. Through large-scale in vitro validation, we show that synthetic sequences are more effective at driving cell-type-specific expression in three cell lines compared with natural sequences from the human genome and achieve specificity in analogous tissues when tested in vivo. Synthetic sequences exhibit distinct motif vocabulary associated with activity in the on-target cell type and a simultaneous reduction in the activity of off-target cells. Together, we provide a generalizable framework to prospectively engineer CREs from massively parallel reporter assay models and demonstrate the required literacy to write fit-for-purpose regulatory code.

Super-enhancer trapping by the nuclear pore via intrinsically disordered regions of proteins in squamous cell carcinoma cells

Master transcription factors such as TP63 establish super-enhancers (SEs) to drive core transcriptional networks in cancer cells, yet the spatiotemporal regulation of SEs within the nucleus remains unknown. The nuclear pore complex (NPC) may tether SEs to the nuclear pore where RNA export rates are maximal. Here, we report that NUP153, a component of the NPC, anchors SEs to the NPC and enhances TP63 expression by maximizing mRNA export. This anchoring is mediated through protein-protein interaction between the intrinsically disordered regions (IDRs) of NUP153 and the coactivator BRD4. Silencing of NUP153 excludes SEs from the nuclear periphery, decreases TP63 expression, impairs cellular growth, and induces epidermal differentiation of squamous cell carcinoma. Overall, this work reveals the critical roles of NUP153 IDRs in the regulation of SE localization, thus providing insights into a new layer of gene regulation at the epigenomic and spatial level.

The transcriptional regulatory network modulating human trophoblast stem cells to extravillous trophoblast differentiation

During human pregnancy, extravillous trophoblasts play crucial roles in placental invasion into the maternal decidua and spiral artery remodeling. However, regulatory factors and their action mechanisms modulating human extravillous trophoblast specification have been unknown. By analyzing dynamic changes in transcriptome and enhancer profile during human trophoblast stem cell to extravillous trophoblast differentiation, we define stage-specific regulators, including an early-stage transcription factor, TFAP2C, and multiple late-stage transcription factors. Loss-of-function studies confirm the requirement of all transcription factors identified for adequate differentiation, and we reveal that the dynamic changes in the levels of TFAP2C are essential. Notably, TFAP2C pre-occupies the regulatory elements of the inactive extravillous trophoblast-active genes during the early stage of differentiation, and the late-stage transcription factors directly activate extravillous trophoblast-active genes, including themselves as differentiation further progresses, suggesting sequential actions of transcription factors assuring differentiation. Our results reveal stage-specific transcription factors and their inter-connected regulatory mechanisms modulating extravillous trophoblast differentiation, providing a framework for understanding early human placentation and placenta-related complications.

Single-cell spatial multi-omics and deep learning dissect enhancer-driven gene regulatory networks in liver zonation

In the mammalian liver, hepatocytes exhibit diverse metabolic and functional profiles based on their location within the liver lobule. However, it is unclear whether this spatial variation, called zonation, is governed by a well-defined gene regulatory code. Here, using a combination of single-cell multiomics, spatial omics, massively parallel reporter assays and deep learning, we mapped enhancer-gene regulatory networks across mouse liver cell types. We found that zonation affects gene expression and chromatin accessibility in hepatocytes, among other cell types. These states are driven by the repressors TCF7L1 and TBX3, alongside other core hepatocyte transcription factors, such as HNF4A, CEBPA, FOXA1 and ONECUT1. To examine the architecture of the enhancers driving these cell states, we trained a hierarchical deep learning model called DeepLiver. Our study provides a multimodal understanding of the regulatory code underlying hepatocyte identity and their zonation state that can be used to engineer enhancers with specific activity levels and zonation patterns.

Machine-guided design of synthetic cell type-specific cis-regulatory elements

Cis-regulatory elements (CREs) control gene expression, orchestrating tissue identity, developmental timing, and stimulus responses, which collectively define the thousands of unique cell types in the body. While there is great potential for strategically incorporating CREs in therapeutic or biotechnology applications that require tissue specificity, there is no guarantee that an optimal CRE for an intended purpose has arisen naturally through evolution. Here, we present a platform to engineer and validate synthetic CREs capable of driving gene expression with programmed cell type specificity. We leverage innovations in deep neural network modeling of CRE activity across three cell types, efficient in silico optimization, and massively parallel reporter assays (MPRAs) to design and empirically test thousands of CREs. Through in vitro and in vivo validation, we show that synthetic sequences outperform natural sequences from the human genome in driving cell type-specific expression. Synthetic sequences leverage unique sequence syntax to promote activity in the on-target cell type and simultaneously reduce activity in off-target cells. Together, we provide a generalizable framework to prospectively engineer CREs and demonstrate the required literacy to write regulatory code that is fit-for-purpose in vivo across vertebrates.

FOXA1/2 depletion drives global reprogramming of differentiation state and metabolism in a human liver cell line and inhibits differentiation of human stem cell-derived hepatic progenitor cells

FOXA factors are critical members of the developmental gene regulatory network (GRN) composed of master transcription factors (TF) which regulate murine cell fate and metabolism in the gut and liver. How FOXA factors dictate human liver cell fate, differentiation, and simultaneously regulate metabolic pathways is poorly understood. Here, we aimed to determine the role of FOXA2 (and FOXA1 which is believed to compensate for FOXA2) in controlling hepatic differentiation and cell metabolism in a human hepatic cell line (HepG2). siRNA mediated knockdown of FOXA1/2 in HepG2 cells significantly downregulated albumin (p < .05) and GRN TF gene expression (HNF4α, HEX, HNF1ß, TBX3) (p < .05) and significantly upregulated endoderm/gut/hepatic endoderm markers (goosecoid [GSC], FOXA3, and GATA4), gut TF (CDX2), pluripotent TF (NANOG), and neuroectodermal TF (PAX6) (p < .05), all consistent with partial/transient reprograming. shFOXA1/2 targeting resulted in similar findings and demonstrated evidence of reversibility of phenotype. RNA-seq followed by bioinformatic analysis of shFOXA1/2 knockdown HepG2 cells demonstrated 235 significant downregulated genes and 448 upregulated genes, including upregulation of markers for alternate germ layers lineages (cardiac, endothelial, muscle) and neurectoderm (eye, neural). We found widespread downregulation of glycolysis, citric acid cycle, mitochondrial genes, and alterations in lipid metabolism, pentose phosphate pathway, and ketogenesis. Functional metabolic analysis agreed with these findings, demonstrating significantly diminished glycolysis and mitochondrial respiration, with concomitant accumulation of lipid droplets. We hypothesized that FOXA1/2 inhibit the initiation of human liver differentiation in vitro. During human pluripotent stem cells (hPSC)-hepatic differentiation, siRNA knockdown demonstrated de-differentiation and unexpectedly, activation of pluripotency factors and neuroectoderm. shRNA knockdown demonstrated similar results and activation of SOX9 (hepatobiliary). These results demonstrate that FOXA1/2 controls hepatic and developmental GRN, and their knockdown leads to reprogramming of both differentiation and metabolism, with applications in studies of cancer, differentiation, and organogenesis.

Transcriptional regulation of the thymus master regulator Foxn1

FOXN1 is a transcription factor critical for the development of both thymic epithelial cell (TEC) and hair follicle cell (HFC) compartments. However, mechanisms controlling its expression remain poorly understood. To address this question, we performed thorough analyses of the evolutionary conservation and chromatin status of the Foxn1 locus in different tissues and states and identified several putative cis-regulatory regions unique to TECs versus HFCs. Furthermore, experiments using genetically modified mice with specific deletions in the Foxn1 locus and additional bioinformatic analyses helped us identify key regions and transcription factors involved in either positive or negative regulation of Foxn1 in both TECs and HFCs. Specifically, we identified SIX1 and FOXN1 itself as key factors inducing Foxn1 expression in embryonic and neonatal TECs. Together, our data provide important mechanistic insights into the transcriptional regulation of the Foxn1 gene in TEC versus HFC and highlight the role of FOXN1 in its autoregulation.

Dynamic regulatory module networks for inference of cell type-specific transcriptional networks

Changes in transcriptional regulatory networks can significantly alter cell fate. To gain insight into transcriptional dynamics, several studies have profiled bulk multi-omic data sets with parallel transcriptomic and epigenomic measurements at different stages of a developmental process. However, integrating these data to infer cell type-specific regulatory networks is a major challenge. We present dynamic regulatory module networks (DRMNs), a novel approach to infer cell type-specific cis-regulatory networks and their dynamics. DRMN integrates expression, chromatin state, and accessibility to predict cis-regulators of context-specific expression, where context can be cell type, developmental stage, or time point, and uses multitask learning to capture network dynamics across linearly and hierarchically related contexts. We applied DRMNs to study regulatory network dynamics in three developmental processes, each showing different temporal relationships and measuring a different combination of regulatory genomic data sets: cellular reprogramming, liver dedifferentiation, and forward differentiation. DRMN identified known and novel regulators driving cell type-specific expression patterns, showing its broad applicability to examine dynamics of gene regulatory networks from linearly and hierarchically related multi-omic data sets.

Predicting Prenatal Developmental Toxicity Based On the Combination of Chemical Structures and Biological Data

For hazard identification, classification, and labeling purposes, animal testing guidelines are required by law to evaluate the developmental toxicity potential of new and existing chemical products. However, guideline developmental toxicity studies are costly, time-consuming, and require many laboratory animals. Computational modeling has emerged as a promising, animal-sparing, and cost-effective method for evaluating the developmental toxicity potential of chemicals, such as endocrine disruptors, without the use of animals. We aimed to develop a predictive and explainable computational model for developmental toxicants. To this end, a comprehensive dataset of 1244 chemicals with developmental toxicity classifications was curated from public repositories and literature sources. Data from 2140 toxicological high-throughput screening assays were extracted from PubChem and the ToxCast program for this dataset and combined with information about 834 chemical fragments to group assays based on their chemical-mechanistic relationships. This effort revealed two assay clusters containing 83 and 76 assays, respectively, with high positive predictive rates for developmental toxicants identified with animal testing guidelines (PPV = 72.4 and 77.3% during cross-validation). These two assay clusters can be used as developmental toxicity models and were applied to predict new chemicals for external validation. This study provides a new strategy for constructing alternative chemical developmental toxicity evaluations that can be replicated for other toxicity modeling studies.

Preparation of Functional Human Hepatocytes Ex Vivo

Hepatocytes are liver parenchymal cells involved in performing various metabolic reactions. During the development of therapeutic drugs, toxicological assays are conducted using hepatocyte cultures before clinical trials. However, since primary hepatocytes cannot proliferate and rapidly lose their functions in vitro, many efforts have been put into modifying culture conditions to expand primary hepatocytes and induce hepatocyte functions in intrinsic and extrinsic stem/progenitor cells. In this chapter, we summarize recent advances in preparing hepatocyte cultures and induction of hepatocytes from various cellular sources.

ConsensusPathDB 2022: molecular interactions update as a resource for network biology

Molecular interactions are key drivers of biological function. Providing interaction resources to the research community is important since they allow functional interpretation and network-based analysis of molecular data. ConsensusPathDB (http://consensuspathdb.org) is a meta-database combining interactions of diverse types from 31 public resources for humans, 16 for mice and 14 for yeasts. Using ConsensusPathDB, researchers commonly evaluate lists of genes, proteins and metabolites against sets of molecular interactions defined by pathways, Gene Ontology and network neighborhoods and retrieve complex molecular neighborhoods formed by heterogeneous interaction types. Furthermore, the integrated protein–protein interaction network is used as a basis for propagation methods. Here, we present the 2022 update of ConsensusPathDB, highlighting content growth, additional functionality and improved database stability. For example, the number of human molecular interactions increased to 859 848 connecting 200 499 unique physical entities such as genes/proteins, metabolites and drugs. Furthermore, we integrated regulatory datasets in the form of transcription factor–, microRNA– and enhancer–gene target interactions, thus providing novel functionality in the context of overrepresentation and enrichment analyses. We specifically emphasize the use of the integrated protein–protein interaction network as a scaffold for network inferences, present topological characteristics of the network and discuss strengths and shortcomings of such approaches.

Direct reprogramming of somatic cells into induced hepatocytes: Cracking the Enigma code

There is an unmet need for functional primary human hepatocytes to support the pharmaceutical and (bio)medical demand. The unique discovery, a decade ago, that somatic cells can be drawn out of their apparent biological lockdown to reacquire a pluripotent state has revealed a completely new avenue of possibilities for generating surrogate human hepatocytes. Since then, the number of papers reporting the direct conversion of somatic cells into induced hepatocytes (iHeps) has burgeoned. A hepatic cell fate can be established via the ectopic expression of native liver-enriched transcription factors in somatic cells, thereby bypassing the need for an intermediate (pluripotent) stem cell state. That said, understanding and eventually controlling the processes that give rise to functional iHeps remains challenging. In this review, we provide an overview of the state-of-the-art reprogramming cocktails and techniques, as well as their corresponding conversion efficiencies. Special attention is paid to the role of liver-enriched transcription factors as hepatogenic reprogramming tools and small molecules as facilitators of hepatic transdifferentiation. To conclude, we formulate recommendations to optimise, standardise and enrich the in vitro production of iHeps to reach clinical standards, and propose minimal criteria for their characterisation.

Computational biology approaches for mapping transcriptional regulatory networks

Transcriptional Regulatory Networks (TRNs) are mainly responsible for the cell-type- or cell-state-specific expression of gene sets from the same DNA sequence. However, so far there are no precise maps of TRNs available for each cell-type or cell-state, and no ideal tool to map those networks clearly and in full from biological samples. In this review, major approaches and tools to map TRNs from high-throughput data are presented, depending on the type of methods or data used to infer them, and their advantages and limitations are discussed. After summarizing the main principles defining the topology and structure–function relationships in TRNs, an overview of the extensive work done to map TRNs from bulk transcriptomic data will be presented by type of methodological approach. Most recent modellings of TRNs using other types of molecular data or integrating different data types, including single-cell RNA-sequencing and chromatin information, will then be discussed, before briefly concluding with improvements expected to come in the field.

Super-enhancer-mediated core regulatory circuitry in human cancer

Super-enhancers (SEs) are congregated enhancer clusters with high level of loading of transcription factors (TFs), cofactors and epigenetic modifications. Through direct co-occupancy at their own SEs as well as each other's, a small set of so called "master" TFs form interconnected core regulatory circuitry (CRCs) to orchestrate transcriptional programs in both normal and malignant cells. These master TFs can be predicted mathematically using epigenomic methods. In this Review, we summarize the identification of SEs and CRCs in cancer cells, the mechanisms by which master TFs and SEs cooperatively regulate cancer-type-specific expression programs, and the cancer-type- and subtype-specificity of CRC and the significance in cancer biology.

A computer-guided design tool to increase the efficiency of cellular conversions

Human cell conversion technology has become an important tool for devising new cell transplantation therapies, generating disease models and testing gene therapies. However, while transcription factor over-expression-based methods have shown great promise in generating cell types in vitro, they often endure low conversion efficiency. In this context, great effort has been devoted to increasing the efficiency of current protocols and the development of computational approaches can be of great help in this endeavor. Here we introduce a computer-guided design tool that combines a computational framework for prioritizing more efficient combinations of instructive factors (IFs) of cellular conversions, called IRENE, with a transposon-based genomic integration system for efficient delivery. Particularly, IRENE relies on a stochastic gene regulatory network model that systematically prioritizes more efficient IFs by maximizing the agreement of the transcriptional and epigenetic landscapes between the converted and target cells. Our predictions substantially increased the efficiency of two established iPSC-differentiation protocols (natural killer cells and melanocytes) and established the first protocol for iPSC-derived mammary epithelial cells with high efficiency.

Integrative Epigenomic Analysis of Transcriptional Regulation of Human CircRNAs

Circular RNAs (circRNAs) are evolutionarily conserved and abundant non-coding RNAs whose functions and regulatory mechanisms remain largely unknown. Here, we identify and characterize an epigenomically distinct group of circRNAs (TAH-circRNAs), which are transcribed to a higher level than their host genes. By integrative analysis of cistromic and transcriptomic data, we find that compared with other circRNAs, TAH-circRNAs are expressed more abundantly and have more transcription factors (TFs) binding sites and lower DNA methylation levels. Concordantly, TAH-circRNAs are enriched in open and active chromatin regions. Importantly, ChIA-PET results showed that 23–52% of transcription start sites (TSSs) of TAH-circRNAs have direct interactions with cis-regulatory regions, strongly suggesting their independent transcriptional regulation from host genes. In addition, we characterize molecular features of super-enhancer-driven circRNAs in cancer biology. Together, this study comprehensively analyzes epigenomic characteristics of circRNAs and identifies a distinct group of TAH-circRNAs that are independently transcribed via enhancers and super-enhancers by TFs. These findings substantially advance our understanding of the regulatory mechanism of circRNAs and may have important implications for future investigations of this class of non-coding RNAs.

EWS-FLI1 regulates and cooperates with core regulatory circuitry in Ewing sarcoma

Core regulatory circuitry (CRC)-dependent transcriptional network is critical for developmental tumors in children and adolescents carrying few gene mutations. However, whether and how CRC contributes to transcription regulation in Ewing sarcoma is unknown. Here, we identify and functionally validate a CRC 'trio' constituted by three transcription factors (TFs): KLF15, TCF4 and NKX2-2, in Ewing sarcoma cells. Epigenomic analyses demonstrate that EWS-FLI1, the primary fusion driver for this cancer, directly establishes super-enhancers of each of these three TFs to activate their transcription. In turn, KLF15, TCF4 and NKX2-2 co-bind to their own and each other's super-enhancers and promoters, forming an inter-connected auto-regulatory loop. Functionally, CRC factors contribute significantly to cell proliferation of Ewing sarcoma both in vitro and in vivo. Mechanistically, CRC factors exhibit prominent capacity of co-regulating the epigenome in cooperation with EWS-FLI1, occupying 77.2% of promoters and 55.6% of enhancers genome-wide. Downstream, CRC TFs coordinately regulate gene expression networks in Ewing sarcoma, controlling important signaling pathways for cancer, such as lipid metabolism pathway, PI3K/AKT and MAPK signaling pathways. Together, molecular characterization of the oncogenic CRC model advances our understanding of the biology of Ewing sarcoma. Moreover, CRC-downstream genes and signaling pathways may contain potential therapeutic targets for this malignancy.

Core transcriptional regulatory circuitries in cancer

Transcription factors (TFs) coordinate the on-and-off states of gene expression typically in a combinatorial fashion. Studies from embryonic stem cells and other cell types have revealed that a clique of self-regulated core TFs control cell identity and cell state. These core TFs form interconnected feed-forward transcriptional loops to establish and reinforce the cell-type-specific gene-expression program; the ensemble of core TFs and their regulatory loops constitutes core transcriptional regulatory circuitry (CRC). Here, we summarize recent progress in computational reconstitution and biologic exploration of CRCs across various human malignancies, and consolidate the strategy and methodology for CRC discovery. We also discuss the genetic basis and therapeutic vulnerability of CRC, and highlight new frontiers and future efforts for the study of CRC in cancer. Knowledge of CRC in cancer is fundamental to understanding cancer-specific transcriptional addiction, and should provide important insight to both pathobiology and therapeutics.

Multiomics data integration unveils core transcriptional regulatory networks governing cell-type identity

A plethora of computational approaches have been proposed for reconstructing gene regulatory networks (GRNs) from gene expression data. However, gene regulatory processes are often too complex to predict from the transcriptome alone. Here, we present a computational method, Moni, that systematically integrates epigenetics, transcriptomics, and protein–protein interactions to reconstruct GRNs among core transcription factors and their co-factors governing cell identity. We applied Moni to 57 datasets of human cell types and lines and demonstrate that it can accurately infer GRNs, thereby outperforming state-of-the-art methods.

SEanalysis: a web tool for super-enhancer associated regulatory analysis

Super-enhancers (SEs) have prominent roles in biological and pathological processes through their unique transcriptional regulatory capability. To date, several SE databases have been developed by us and others. However, these existing databases do not provide downstream or upstream regulatory analyses of SEs. Pathways, transcription factors (TFs), SEs, and SE-associated genes form complex regulatory networks. Therefore, we designed a novel web server, SEanalysis, which provides comprehensive SE-associated regulatory network analyses. SEanalysis characterizes SE-associated genes, TFs binding to target SEs, and their upstream pathways. The current version of SEanalysis contains more than 330 000 SEs from more than 540 types of cells/tissues, 5042 TF ChIP-seq data generated from these cells/tissues, DNA-binding sequence motifs for ∼700 human TFs and 2880 pathways from 10 databases. SEanalysis supports searching by either SEs, samples, TFs, pathways or genes. The complex regulatory networks formed by these factors can be interactively visualized. In addition, we developed a customizable genome browser containing >6000 customizable tracks for visualization. The server is freely available at http://licpathway.net/SEanalysis.

Master transcription factors form interconnected circuitry and orchestrate transcriptional networks in oesophageal adenocarcinoma

OBJECTIVE

While oesophageal squamous cell carcinoma remains infrequent in Western populations, the incidence of oesophageal adenocarcinoma (EAC) has increased sixfold to eightfold over the past four decades. We aimed to characterise oesophageal cancer-specific and subtypes-specific gene regulation patterns and their upstream transcription factors (TFs).  DESIGN: To identify regulatory elements, we profiled fresh-frozen oesophageal normal samples, tumours and cell lines with chromatin immunoprecipitation sequencing (ChIP-Seq). Mathematical modelling was performed to establish (super)-enhancers landscapes and interconnected transcriptional circuitry formed by master TFs. Coregulation and cooperation between master TFs were investigated by ChIP-Seq, circularised chromosome conformation capture sequencing and luciferase assay. Biological functions of candidate factors were evaluated both in vitro and in vivo.

RESULTS

We found widespread and pervasive alterations of the (super)-enhancer reservoir in both subtypes of oesophageal cancer, leading to transcriptional activation of a myriad of novel oncogenes and signalling pathways, some of which may be exploited pharmacologically (eg, leukemia inhibitory factor (LIF) pathway). Focusing on EAC, we bioinformatically reconstructed and functionally validated an interconnected circuitry formed by four master TFs-ELF3, KLF5, GATA6 and EHF-which promoted each other's expression by interacting with each super-enhancer. Downstream, these master TFs occupied almost all EAC super-enhancers and cooperatively orchestrated EAC transcriptome. Each TF within the transcriptional circuitry was highly and specifically expressed in EAC and functionally promoted EAC cell proliferation and survival.

CONCLUSIONS

By establishing cancer-specific and subtype-specific features of the EAC epigenome, our findings promise to transform understanding of the transcriptional dysregulation and addiction of EAC, while providing molecular clues to develop novel therapeutic modalities against this malignancy.

Emergent Properties of the HNF4α-PPARγ Network May Drive Consequent Phenotypic Plasticity in NAFLD

Non-alcoholic fatty liver disease (NAFLD) is the most common form of chronic liver disease in adults and children. It is characterized by excessive accumulation of lipids in the hepatocytes of patients without any excess alcohol intake. With a global presence of 24% and limited therapeutic options, the disease burden of NAFLD is increasing. Thus, it becomes imperative to attempt to understand the dynamics of disease progression at a systems-level. Here, we decoded the emergent dynamics of underlying gene regulatory networks that were identified to drive the initiation and the progression of NAFLD. We developed a mathematical model to elucidate the dynamics of the HNF4α-PPARγ gene regulatory network. Our simulations reveal that this network can enable multiple co-existing phenotypes under certain biological conditions: an adipocyte, a hepatocyte, and a "hybrid" adipocyte-like state of the hepatocyte. These phenotypes may also switch among each other, thus enabling phenotypic plasticity and consequently leading to simultaneous deregulation of the levels of molecules that maintain a hepatic identity and/or facilitate a partial or complete acquisition of adipocytic traits. These predicted trends are supported by the analysis of clinical data, further substantiating the putative role of phenotypic plasticity in driving NAFLD. Our results unravel how the emergent dynamics of underlying regulatory networks can promote phenotypic plasticity, thereby propelling the clinically observed changes in gene expression often associated with NAFLD.

Gene co-regulation and co-expression in the aryl hydrocarbon receptor-mediated transcriptional regulatory network in the mouse liver

Four decades after its discovery, the aryl hydrocarbon receptor (AHR), a ligand-inducible transcription factor (TF) activated by the persistent environmental contaminant 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD), remains an enigmatic molecule with a controversial endogenous role. Here, we have assembled a global map of the AHR gene regulatory network in female C57BL/6 mice orally gavaged with 30 µg/kg of TCDD from a combination of previously published gene expression and genome-wide TF-binding data sets. Using Kohonen self-organizing maps and subspace clustering, we show that genes co-regulated by common upstream TFs in the AHR network exhibit a pattern of co-expression. Directly bound, indirectly bound, and non-genomic AHR target genes exhibit distinct expression patterns, with the directly bound targets associated with highest median expression. Interestingly, among the directly bound AHR target genes, the expression level increases with the number of AHR-binding sites in the proximal promoter regions. Finally, we show that co-regulated genes in the AHR network activate distinct groups of downstream biological processes. Although the specific findings described here are restricted to hepatic effects under short-term TCDD exposure, this work describes a generalizable approach to the reconstruction and analysis of transcriptional regulatory cascades underlying cellular stress response, revealing network hierarchy and the nature of information flow from the initial signaling events to phenotypic outcomes. Such reconstructed networks can form the basis of a new generation of quantitative adverse outcome pathways.

dbCoRC: a database of core transcriptional regulatory circuitries modeled by H3K27ac ChIP-seq signals

Core transcription regulatory circuitry (CRC) is comprised of a small group of self-regulated transcription factors (TFs) and their interconnected regulatory loops. Studies from embryonic stem cells and other cellular models have revealed the elementary roles of CRCs in transcriptional control of cell identity and cellular fate. Systematic identification and subsequent archiving of CRCs across diverse cell types and tissues are needed to explore both cell/tissue type-specific and disease-associated transcriptional networks. Here, we present a comprehensive and interactive database (dbCoRC, http://dbcorc.cam-su.org) of CRC models which are computationally inferred from mapping of super-enhancer and prediction of TF binding sites. The current version of dbCoRC contains CRC models for 188 human and 50 murine cell lines/tissue samples. In companion with CRC models, this database also provides: (i) super enhancer, typical enhancer, and H3K27ac landscape for individual samples, (ii) putative binding sites of each core TF across the super-enhancer regions within CRC and (iii) expression of each core TF in normal or cancer cells/tissues. The dbCoRC will serve as a valuable resource for the scientific community to explore transcriptional control and regulatory circuitries in biological processes related to, but not limited to lineage specification, tissue homeostasis and tumorigenesis.

Multiomics Analyses of HNF4α Protein Domain Function during Human Pluripotent Stem Cell Differentiation

During mammalian development, liver differentiation is driven by signals that converge on multiple transcription factor networks. The hepatocyte nuclear factor signaling network is known to be essential for hepatocyte specification and maintenance. In this study, we have generated deletion and point mutants of hepatocyte nuclear factor-4alpha (HNF4α) to precisely evaluate the function of protein domains during hepatocyte specification from human pluripotent stem cells. We demonstrate that nuclear HNF4α is essential for hepatic progenitor specification, and the introduction of point mutations in HNF4α's Small Ubiquitin-like Modifier (SUMO) consensus motif leads to disrupted hepatocyte differentiation. Taking a multiomics approach, we identified key deficiencies in cell biology, which included dysfunctional metabolism, substrate adhesion, tricarboxylic acid cycle flux, microRNA transport, and mRNA processing. In summary, the combination of genome editing and multiomics analyses has provided valuable insight into the diverse functions of HNF4α during pluripotent stem cell entry into the hepatic lineage and during hepatocellular differentiation.

Identification and Conservation Analysis of Cis-Regulatory Elements in Pig Liver

The liver plays a key role in metabolism and affects pig production. However, the functional annotation of noncoding regions of the pig liver remains poorly understood. We revealed the landscape of cis-regulatory elements and their functional characterization in pig liver. We identified 102,373 cis-regulatory elements in the pig liver, including enhancers, promoters, super-enhancers, and broad H3K4me3 domains, and highlighted 26 core transcription regulatory factors in the pig liver as well. We found similarity of cis-regulatory elements among those of pigs, humans, and cattle. Despite the low proportion of functionally conserved enhancers (~30%) between pig and human liver tissue, ~78% of the pig liver enhancer orthologues sequence could play an enhancer role in other human tissues. Additionally, we observed that the ratio of consistent super-enhancer-associated genes was significantly higher than the ratio of functionally conserved super-enhancers. Approximately 54% of the core regulation factors driven by super-enhancers were consistent across the liver from these three species. Our pig liver annotation and functional characterization studies provide a system and resource for noncoding annotation for future gene regulatory studies in pigs. Furthermore, our study also showed the high level functional conservation of cis-regulatory elements in mammals; it also improved our understanding of regulation function of mammal cis-regulatory elements.

Insight into the combinatorial transcriptional regulation on α-amylase gene in animal groups with different dietary nutrient content

Gene expression is generally regulated by multiple transcription factors (TFs). Despite previous findings of individual TFs regulating pancreatic α-amylase gene expression, the combinatorial transcriptional regulation is not fully understood. To gain insight into multiple TF regulation for pancreatic α-amylase gene, we employed a function conservation approach to predict interacting TFs regulating pancreatic α-amylase gene for 3 dietary animal groups. To this end, we have identified 77, 25, and 118 interacting TFs for herbivore, omnivore, and carnivore, respectively. Computational modeling of TF regulatory networks demonstrated that known pancreas-specific TFs (e.g. GR, NFAT, and PR) may play important roles in recruiting non pancreas-specific TFs to the TF-TF interaction networks, offering specificity and flexibility for controlling pancreatic α-amylase gene expression in different dietary animal groups. The findings from this study indicate that combinatorial transcriptional regulation could be a critical component controlling pancreatic α-amylase gene expression.

SEdb: a comprehensive human super-enhancer database

Super-enhancers are important for controlling and defining the expression of cell-specific genes. With research on human disease and biological processes, human H3K27ac ChIP-seq datasets are accumulating rapidly, creating the urgent need to collect and process these data comprehensively and efficiently. More importantly, many studies showed that super-enhancer-associated single nucleotide polymorphisms (SNPs) and transcription factors (TFs) strongly influence human disease and biological processes. Here, we developed a comprehensive human super-enhancer database (SEdb, http://www.licpathway.net/sedb) that aimed to provide a large number of available resources on human super-enhancers. The database was annotated with potential functions of super-enhancers in the gene regulation. The current version of SEdb documented a total of 331 601 super-enhancers from 542 samples. Especially, unlike existing super-enhancer databases, we manually curated and classified 410 available H3K27ac samples from >2000 ChIP-seq samples from NCBI GEO/SRA. Furthermore, SEdb provides detailed genetic and epigenetic annotation information on super-enhancers. Information includes common SNPs, motif changes, expression quantitative trait locus (eQTL), risk SNPs, transcription factor binding sites (TFBSs), CRISPR/Cas9 target sites and Dnase I hypersensitivity sites (DHSs) for in-depth analyses of super-enhancers. SEdb will help elucidate super-enhancer-related functions and find potential biological effects.

Molecular regulation of mammalian hepatic architecture

The essential liver exocrine and endocrine functions require a precise spatial arrangement of the hepatic lobule consisting of the central vein, portal vein, hepatic artery, intrahepatic bile duct system, and hepatocyte zonation. This allows blood to be carried through the liver parenchyma sampled by all hepatocytes and bile produced by the hepatocytes to be carried out of the liver through the intrahepatic bile duct system composed of cholangiocytes. The molecular orchestration of multiple signaling pathways and epigenetic factors is required to set up lineage restriction of the bipotential hepatoblast progenitor into the hepatocyte and cholangiocyte cell lineages, and to further refine cell fate heterogeneity within each cell lineage reflected in the functional heterogeneity of hepatocytes and cholangiocytes. In addition to the complex molecular regulation, there is a complicated morphogenetic choreography observed in building the refined hepatic epithelial architecture. Given the multifaceted molecular and cellular regulation, it is not surprising that impairment of any of these processes can result in acute and chronic hepatobiliary diseases. To enlighten the development of potential molecular and cellular targets for therapeutic options, an understanding of how the intricate hepatic molecular and cellular interactions are regulated is imperative. Here, we review the signaling pathways and epigenetic factors regulating hepatic cell lineages, fates, and epithelial architecture.

Derivation and molecular characterization of pancreatic differentiated MODY1-iPSCs

Maturity onset diabetes of the young (MODY) is a hereditary form of diabetes mellitus presenting at childhood or adolescence, which eventually leads to pancreatic β-cells dysfunction. The underlying genetic basis of MODY disorders is haploinsufficiency, where loss-of-function mutations in a single allele cause the diabetic phenotype in heterozygous patients. MODY1 is a type of MODY disorder resulting from a mutation in the transcription factor hepatocyte nuclear factor 4 alpha (HNF4α). In order to establish a human based model to study MODY1, we generated patient-derived induced pluripotent stem cells (iPSCs). Differentiation of these pluripotent cells towards the pancreatic lineage enabled to evaluate the effects of the MODY1 mutation and its impact on endodermal and pancreatic cells. Analyzing the gene expression profiles of differentiated MODY1 cells, revealed the outcome of HNF4α haploinsufficiency on its targets. This molecular analysis suggests that the differential expression of HNF4α target genes in MODY1 is affected by the number of HNF4α binding sites, their distance from the transcription start site, and the number of other transcription factor binding sites. These features may help explain the molecular manifestations of haploinsufficiency in MODY1 disease.

Genomic positional conservation identifies topological anchor point RNAs linked to developmental loci

BACKGROUND

The mammalian genome is transcribed into large numbers of long noncoding RNAs (lncRNAs), but the definition of functional lncRNA groups has proven difficult, partly due to their low sequence conservation and lack of identified shared properties. Here we consider promoter conservation and positional conservation as indicators of functional commonality.

RESULTS

We identify 665 conserved lncRNA promoters in mouse and human that are preserved in genomic position relative to orthologous coding genes. These positionally conserved lncRNA genes are primarily associated with developmental transcription factor loci with which they are coexpressed in a tissue-specific manner. Over half of positionally conserved RNAs in this set are linked to chromatin organization structures, overlapping binding sites for the CTCF chromatin organiser and located at chromatin loop anchor points and borders of topologically associating domains (TADs). We define these RNAs as topological anchor point RNAs (tapRNAs). Characterization of these noncoding RNAs and their associated coding genes shows that they are functionally connected: they regulate each other's expression and influence the metastatic phenotype of cancer cells in vitro in a similar fashion. Furthermore, we find that tapRNAs contain conserved sequence domains that are enriched in motifs for zinc finger domain-containing RNA-binding proteins and transcription factors, whose binding sites are found mutated in cancers.

CONCLUSIONS

This work leverages positional conservation to identify lncRNAs with potential importance in genome organization, development and disease. The evidence that many developmental transcription factors are physically and functionally connected to lncRNAs represents an exciting stepping-stone to further our understanding of genome regulation.

The Three Ds of Transcription Activation by Glucagon: Direct, Delayed, and Dynamic

Upon lowered blood glucose occurring during fasting, glucagon is secreted from pancreatic islets, exerting various metabolic effects to normalize glucose levels. A considerable portion of these effects is mediated by glucagon-activated transcription factors (TFs) in liver. Glucagon directly activates several TFs via immediate cyclic adenosine monophosphate (cAMP)- and calcium-dependent signaling events. Among these TFs, cAMP response element-binding protein (CREB) is a major factor. CREB recruits histone-modifying enzymes and cooperates with other TFs on the chromatin template to increase the rate of gene transcription. In addition to direct signal transduction, the transcriptional effects of glucagon are also influenced by dynamic TF cross talk. Specifically, assisted loading of one TF by a companion TF leads to increased binding and activity. Lastly, transcriptional regulation by glucagon is also exerted by TF cascades by which a primary TF induces the gene expression of secondary TFs that bring about their activity a few hours after the initial glucagon signal. This mechanism of a delayed response may be instrumental in establishing the temporal organization of the fasting response by which distinct metabolic events separate early from prolonged fasting. In this mini-review, we summarize recent advances and critical discoveries in glucagon-dependent gene regulation with a focus on direct TF activation, dynamic TF cross talk, and TF cascades.

Novel Traits, Flower Symmetry, and Transcriptional Autoregulation: New Hypotheses From Bioinformatic and Experimental Data

A common feature in developmental networks is the autoregulation of transcription factors which, in turn, positively or negatively regulate additional genes critical for developmental patterning. When a transcription factor regulates its own expression by binding to cis-regulatory sites in its gene, the regulation is direct transcriptional autoregulation (DTA). Indirect transcriptional autoregulation (ITA) involves regulation by proteins expressed downstream of the target transcription factor. We review evidence for a hypothesized role of DTA in the evolution and development of novel flowering plant phenotypes. We additionally provide new bioinformatic and experimental analyses that support a role for transcriptional autoregulation in the evolution of flower symmetry. We find that 5' upstream non-coding regions are significantly enriched for predicted autoregulatory sites in Lamiales CYCLOIDEA genes-an upstream regulator of flower monosymmetry. This suggests a possible correlation between autoregulation of CYCLOIDEA and the origin of monosymmetric flowers near the base of Lamiales, a pattern that may be correlated with independently derived monosymmetry across eudicot lineages. We find additional evidence for transcriptional autoregulation in the flower symmetry program, and report that Antirrhinum DRIF2 may undergo ITA. In light of existing data and new data presented here, we hypothesize how cis-acting autoregulatory sites originate, and find evidence that such sites (and DTA) can arise subsequent to the evolution of a novel phenotype.

Complexity and conservation of regulatory landscapes underlie evolutionary resilience of mammalian gene expression

To gain insight into how mammalian gene expression is controlled by rapidly evolving regulatory elements, we jointly analysed promoter and enhancer activity with downstream transcription levels in liver samples from 15 species. Genes associated with complex regulatory landscapes generally exhibit high expression levels that remain evolutionarily stable. While the number of regulatory elements is the key driver of transcriptional output and resilience, regulatory conservation matters: elements active across mammals most effectively stabilize gene expression. In contrast, recently evolved enhancers typically contribute weakly, consistent with their high evolutionary plasticity. These effects are observed across the entire mammalian clade and are robust to potential confounders, such as the gene expression level. Using liver as a representative somatic tissue, our results illuminate how the evolutionary stability of gene expression is profoundly entwined with both the number and conservation of surrounding promoters and enhancers.

MicroRNA-337-3p controls hepatobiliary gene expression and transcriptional dynamics during hepatic cell differentiation

Transcriptional networks control the differentiation of the hepatocyte and cholangiocyte lineages from embryonic liver progenitor cells and their subsequent maturation to the adult phenotype. However, how relative levels of hepatocyte and cholangiocyte gene expression are determined during differentiation remains poorly understood. Here, we identify microRNA (miR)-337-3p as a regulator of liver development. miR-337-3p stimulates expression of cholangiocyte genes and represses hepatocyte genes in undifferentiated progenitor cells in vitro and in embryonic mouse livers. Beyond the stage of lineage segregation, miR-337-3p controls the transcriptional network dynamics of developing hepatocytes and balances both cholangiocyte populations that constitute the ductal plate. miR-337-3p requires Notch and transforming growth factor-β signaling and exerts a biphasic control on the hepatocyte transcription factor hepatocyte nuclear factor 4α by modulating its activation and repression. With the help of an experimentally validated mathematical model, we show that this biphasic control results from an incoherent feedforward loop between miR-337-3p and hepatocyte nuclear factor 4α.

CONCLUSION

Our results identify miR-337-3p as a regulator of liver development and highlight how tight quantitative control of hepatic cell differentiation is exerted through specific gene regulatory network motifs. (Hepatology 2018;67:313-327).

Aberrant Activation of a Gastrointestinal Transcriptional Circuit in Prostate Cancer Mediates Castration Resistance

Prostate cancer exhibits a lineage-specific dependence on androgen signaling. Castration resistance involves reactivation of androgen signaling or activation of alternative lineage programs to bypass androgen requirement. We describe an aberrant gastrointestinal-lineage transcriptome expressed in ∼5% of primary prostate cancer that is characterized by abbreviated response to androgen-deprivation therapy and in ∼30% of castration-resistant prostate cancer. This program is governed by a transcriptional circuit consisting of HNF4G and HNF1A. Cistrome and chromatin analyses revealed that HNF4G is a pioneer factor that generates and maintains enhancer landscape at gastrointestinal-lineage genes, independent of androgen-receptor signaling. In HNF4G/HNF1A-double-negative prostate cancer, exogenous expression of HNF4G at physiologic levels recapitulates the gastrointestinal transcriptome, chromatin landscape, and leads to relative castration resistance.

Leukemia-Initiating Cells in T-Cell Acute Lymphoblastic Leukemia

T-cell acute lymphoblastic leukemia (T-ALL) is a hematological malignancy characterized by the clonal proliferation of immature T-cell precursors. T-ALL has many similar pathophysiological features to acute myeloid leukemia, which has been extensively studied in the establishment of the cancer stem cell (CSC) theory, but the CSC concept in T-ALL is still debatable. Although leukemia-initiating cells (LICs), which can generate leukemia in a xenograft setting, have been found in both human T-ALL patients and animal models, the nature and origin of LICs are largely unknown. In this review, we discuss recent studies on LICs in T-ALL and the potential mechanisms of LIC emergence in this disease. We focus on the oncogenic transcription factors TAL1, LMO2, and NOTCH1 and highlight the significance of the transcriptional regulatory programs in normal hematopoietic stem cells and T-ALL.

Footprint-free human fetal foreskin derived iPSCs: A tool for modeling hepatogenesis associated gene regulatory networks

Induced pluripotent stem cells (iPSCs) are similar to embryonic stem cells and can be generated from somatic cells. We have generated episomal plasmid-based and integration-free iPSCs (E-iPSCs) from human fetal foreskin fibroblast cells (HFF1). We used an E-iPSC-line to model hepatogenesis in vitro. The HLCs were characterized biochemically, i.e. glycogen storage, ICG uptake and release, UREA and bile acid production, as well as CYP3A4 activity. Ultra-structure analysis by electron microscopy revealed the presence of lipid and glycogen storage, tight junctions and bile canaliculi- all typical features of hepatocytes. Furthermore, the transcriptome of undifferentiated E-iPSC, DE, HE and HLCs were compared to that of fetal liver and primary human hepatocytes (PHH). K-means clustering identified 100 clusters which include developmental stage-specific groups of genes, e.g. OCT4 expression at the undifferentiated stage, SOX17 marking the DE stage, DLK and HNF6 the HE stage, HNF4α and Albumin is specific to HLCs, fetal liver and adult liver (PHH) stage. We use E-iPSCs for modeling gene regulatory networks associated with human hepatogenesis and gastrulation in general.

Down-regulation of hepatocyte nuclear factor-4α and defective zonation in livers expressing mutant Z α1-antitrypsin

α₁ -Antitrypsin (AAT) deficiency is one of the most common genetic disorders and the liver disease due to the Z mutant of AAT (ATZ) is a prototype of conformational disorder due to protein misfolding with consequent aberrant intermolecular protein aggregation. In the present study, we found that livers of PiZ transgenic mice expressing human ATZ have altered expression of a network of hepatocyte transcriptional factors, including hepatocyte nuclear factor-4α, that is early down-regulated and induces a transcriptional repression of ATZ expression. Reduced hepatocyte nuclear factor-4α was associated with activation of β-catenin, which regulates liver zonation. Livers of PiZ mice and human patients with AAT deficiency were both found to have a severe perturbation of liver zonation. Functionally, PiZ mice showed a severe defect of ureagenesis, as shown by increased baseline ammonia, and reduced urea production and survival after an ammonia challenge. Down-regulation of hepatocyte nuclear factor-4α expression and defective zonation in livers have not been recognized so far as features of the liver disease caused by ATZ and are likely involved in metabolic disturbances and in the increased risk of hepatocellular carcinoma in patients with AAT deficiency.

CONCLUSION

The findings of this study are consistent with the concept that abnormal AAT protein conformation and intrahepatic accumulation have broad effects on metabolic liver functions. (Hepatology 2017;66:124-135).

TAL1 as a master oncogenic transcription factor in T-cell acute lymphoblastic leukemia

In hematopoietic cell development, the transcriptional program is strictly regulated in a lineage- and stage-specific manner that requires a number of transcription factors to work in a cascade or in a loop, in addition to interactions with nonhematopoietic cells in the microenvironment. Disruption of the transcriptional program alters the cellular state and may predispose cells to the acquisition of genetic abnormalities. Early studies have shown that proteins that promote cell differentiation often serve as tumor suppressors, whereas inhibitors of those proteins act as oncogenes in the context of acute leukemia. A prime example is T-cell acute lymphoblastic leukemia (T-ALL), a malignant disorder characterized by clonal proliferation of immature stage thymocytes. Although a relatively small number of genetic abnormalities are observed in T-ALL, these abnormalities are crucial for leukemogenesis. Many oncogenes and tumor suppressors in T-ALL are transcription factors that are required for normal hematopoiesis. The transformation process in T-ALL is efficient and orchestrated; the oncogene disrupts the transcriptional program directing T-cell differentiation and also uses its native ability as a master transcription factor in hematopoiesis. This imbalance in the transcriptional program is a primary determinant underlying the molecular pathogenesis of T-ALL. In this review, we focus on the oncogenic transcription factor TAL1 and the tumor-suppressor E-proteins and discuss the malignant cell state, the transcriptional circuit, and the consequence of molecular abnormalities in T-ALL.

The activity of the carbamoyl phosphate synthase 1 promoter in human liver-derived cells is dependent on hepatocyte nuclear factor 3-beta

Carbamoyl phosphate synthase 1 (CPS1) is the rate‐limiting enzyme in the first step of the urea cycle and an indispensable enzyme in the metabolism of human liver. However, CPS1 epigenetic regulation involves promoter analysis and the role of liver‐enriched transcription factors (LETFs), which is not fully elucidated. In this work, the promoter region of hCPS1 gene was cloned, and its activity was investigated. An LETF, hepatocyte nuclear factor 3‐beta (HNF3β), was found to promote the transcriptional expression of CPS1 in liver‐derived cell lines. In addition, dual‐luciferase reporter assay shows that the essential binding sites of the HNF3β may exist in the oligonucleotide −70 nt to +73 nt. Two putative binding sites are available for HNF3β. Mutation analysis results show that the binding site 2 of HNF3β was effective, and the transcriptional activity of CPS1 promoter significantly decreased after mutation. Electrophoretic mobile shift assay (EMSA) and ChIP assay confirmed that HNF3β can interact with the binding site in the CPS1 promoter region of −70 nt to +73 nt promoter region in vivo and in vitro to regulate the transcription of CPS1. Moreover, HNF3β overexpression enhanced the transcription of CPS1 and consequently improved the mRNA and protein levels of CPS1, whereas the knockdown of HNF3β showed the opposite effects. Finally, urea production in cells was measured, and ammonia detoxification improved significantly in cells after transfection with HNF3β. HNF3β plays a vital role in regulation of CPS1 gene and could promote the metabolism of ammonia by regulating CPS1 expression.

Unraveling the Mysterious Interactions Between Hepatitis C Virus RNA and Liver-Specific MicroRNA-122

Many viruses encode or subvert cellular microRNAs (miRNAs) to aid in their gene expression, amplification strategies, or pathogenic signatures. miRNAs typically downregulate gene expression by binding to the 3' untranslated region of their mRNA targets. As a result, target mRNAs are translationally repressed and subsequently deadenylated and degraded. Curiously, hepatitis C virus (HCV), a member of the Flaviviridae family, recruits two molecules of liver-specific microRNA-122 (miR-122) to the 5' end of its genome. In contrast to the canonical activity of miRNAs, the interactions of miR-122 with the viral genome promote viral RNA accumulation in cultured cells and in animal models of HCV infection. Sequestration of miR-122 results in loss of viral RNA both in cell culture and in the livers of chronic HCV-infected patients. This review discusses the mechanisms by which miR-122 is thought to enhance viral RNA abundance and the consequences of miR-122-HCV interactions. We also describe preliminary findings from phase II clinical trials in patients treated with miR-122 antisense oligonucleotides.

The mutational spectrum of FOXA2 in endometrioid endometrial cancer points to a tumor suppressor role

BACKGROUND

Forkhead box protein A2 (FOXA2) plays an important in development, cellular metabolism and tumorigenesis. The Cancer Genome Atlas (TCGA) identified a modest frequency of FOXA2 mutations in endometrioid endometrial cancers (EEC). The current study sought to determine the relationship between FOXA2 mutation and clinicopathologic features in EEC and FOXA2 expression.

METHODS

Polymerase chain reaction (PCR) amplification and sequencing were used to identify mutations in 542 EEC. Western blot, quantitative reverse transcriptase PCR (qRT-PCR) and immunohistochemistry (IHC) were used to assess expression. Methylation analysis was performed using combined bisulfite restriction analysis (COBRA) and sequencing. Chi-squared, Fisher's exact, Student's t- and log-rank tests were performed.

RESULTS

Fifty-one mutations were identified in 49 tumors (9.4% mutation rate). The majority of mutations were novel, loss of function (LOF) (78.4%) mutations, and most disrupted the DNA-binding domain (58.8%). Six recurrent mutations were identified. Only two tumors had two mutations and there was no evidence for FOXA2 allelic loss. Mutation status was associated with tumor grade and not associated with survival outcomes. Methylation of the FOXA2 promoter region was highly variable. Most tumors expressed FOXA2 at both the mRNA and protein level. In those tumors with mutations, the majority of cases expressed both alleles.

CONCLUSION

FOXA2 is frequently mutated in EEC. The pattern of FOXA2 mutations and expression in tumors suggests complex regulation and a haploinsufficient or dominant-negative tumor suppressor function. In vitro studies may shed light on how mutations in FOXA2 affect FOXA2 pioneer and/or transcription factor functions in EEC.

Every transcription factor deserves its map: Scaling up epitope tagging of proteins to bypass antibody problems

Genome-wide identification of transcription factor binding sites with the ChIP-seq method is an extremely important scientific endeavor - one that should ideally be performed for every transcription factor in as many cell types as possible. A major hurdle on the way to this goal is the necessity for a specific, ChIP-grade antibody for each transcription factor of interest, which is often not available. Here, we describe CETCh-seq, a recently published method utilizing genome engineering with the CRISPR/Cas9 system to circumvent the need for a specific antibody. Using the CETCh-seq method, targeted genomic editing results in an epitope-tagged transcription factor, which is recognized by a well-characterized, standard antibody, efficacious for ChIP-seq. We have used CETCh-seq in human cancer cell lines as well as mouse embryonic stem cells. We find that roughly 60% of transcription factors tagged using CETCh-seq produce a high quality ChIP-seq map, a significant improvement over traditional antibody-based methods.

Developmental Stage-Specific Embryonic Induction of HepG2 Cell Differentiation

BACKGROUND

Although hepatocellular carcinoma cells can sometimes undergo differentiation in an embryonic microenvironment, the mechanism is poorly understood.

AIM

The developmental stage-specific embryonic induction of tumor cell differentiation was investigated.

METHODS

Both chick and mouse liver extracts and hepatoblast-enriched cells at different developmental stages were used to treat human hepatoma HepG2 cells, and the effects on the induction of differentiation were evaluated. The nuclear factors controlling differentiation, hepatocyte nuclear factor (HNF)-4α, HNF-1α, HNF-6 and upstream stimulatory factor-1 (USF-1), and the oncogene Myc and alpha-fetoprotein (AFP) were measured. HNF-4α RNA interference was used to verify the role of HNF-4α. Embryonic induction effects were further tested in vivo by injecting HepG2 tumor cells into immunodeficient nude mice.

RESULTS

The 9-11-days chick liver extracts and 13.5-14.5-days mouse hepatoblast-enriched cells could inhibit proliferation and induce differentiation of HepG2 cells, leading to either death or maturation to hepatocytes. The maturation of surviving HepG2 cells was confirmed by increases in the expressions of HNF-4α, HNF-1α, HNF-6, and USF-1, and decreases in Myc and AFP. The embryonic induction of HepG2 cell maturation could be attenuated by HNF-4α RNA interference. Furthermore, the 13.5-days mouse hepatoblast culture completely eliminated HepG2 tumors with inhibited Myc and induced HNF-4α, confirming this embryonic induction effect in vivo.

CONCLUSIONS

This study demonstrated that developmental stage-specific embryonic induction of HepG2 cell differentiation might help in understanding embryonic differentiation and oncogenesis.

Computational Detection of Stage-Specific Transcription Factor Clusters during Heart Development

Transcription factors (TFs) regulate gene expression in living organisms. In higher organisms, TFs often interact in non-random combinations with each other to control gene transcription. Understanding the interactions is key to decipher mechanisms underlying tissue development. The aim of this study was to analyze co-occurring transcription factor binding sites (TFBSs) in a time series dataset from a new cell-culture model of human heart muscle development in order to identify common as well as specific co-occurring TFBS pairs in the promoter regions of regulated genes which can be essential to enhance cardiac tissue developmental processes. To this end, we separated available RNAseq dataset into five temporally defined groups: (i) mesoderm induction stage; (ii) early cardiac specification stage; (iii) late cardiac specification stage; (iv) early cardiac maturation stage; (v) late cardiac maturation stage, where each of these stages is characterized by unique differentially expressed genes (DEGs). To identify TFBS pairs for each stage, we applied the MatrixCatch algorithm, which is a successful method to deduce experimentally described TFBS pairs in the promoters of the DEGs. Although DEGs in each stage are distinct, our results show that the TFBS pair networks predicted by MatrixCatch for all stages are quite similar. Thus, we extend the results of MatrixCatch utilizing a Markov clustering algorithm (MCL) to perform network analysis. Using our extended approach, we are able to separate the TFBS pair networks in several clusters to highlight stage-specific co-occurences between TFBSs. Our approach has revealed clusters that are either common (NFAT or HMGIY clusters) or specific (SMAD or AP-1 clusters) for the individual stages. Several of these clusters are likely to play an important role during the cardiomyogenesis. Further, we have shown that the related TFs of TFBSs in the clusters indicate potential synergistic or antagonistic interactions to switch between different stages. Additionally, our results suggest that cardiomyogenesis follows the hourglass model which was already proven for Arabidopsis and some vertebrates. This investigation helps us to get a better understanding of how each stage of cardiomyogenesis is affected by different combination of TFs. Such knowledge may help to understand basic principles of stem cell differentiation into cardiomyocytes.

Models of human core transcriptional regulatory circuitries

A small set of core transcription factors (TFs) dominates control of the gene expression program in embryonic stem cells and other well-studied cellular models. These core TFs collectively regulate their own gene expression, thus forming an interconnected auto-regulatory loop that can be considered the core transcriptional regulatory circuitry (CRC) for that cell type. There is limited knowledge of core TFs, and thus models of core regulatory circuitry, for most cell types. We recently discovered that genes encoding known core TFs forming CRCs are driven by super-enhancers, which provides an opportunity to systematically predict CRCs in poorly studied cell types through super-enhancer mapping. Here, we use super-enhancer maps to generate CRC models for 75 human cell and tissue types. These core circuitry models should prove valuable for further investigating cell-type–specific transcriptional regulation in healthy and diseased cells.