The transcriptional cofactor Tle3 reciprocally controls effector and central memory CD8+ T cell fates.

Antigen-experienced CD8+ T cells form effector and central memory T cells (TEM and TCM cells, respectively); however, the mechanism(s) controlling their lineage plasticity remains incompletely understood. Here we show that the transcription cofactor Tle3 critically regulates TEM and TCM cell fates and lineage stability through dynamic redistribution in antigen-responding CD8+ T cell genome. Genetic ablation of Tle3 promoted CD8+ TCM cell formation at the expense of CD8+ TEM cells. Lineage tracing showed that Tle3-deficient CD8+ TEM cells underwent accelerated conversion into CD8+ TCM cells while retaining robust recall capacity. Tle3 acted as a coactivator for Tbet to increase chromatin opening at CD8+ TEM cell-characteristic sites and to activate CD8+ TEM cell signature gene transcription, while engaging Runx3 and Tcf1 to limit CD8+ TCM cell-characteristic molecular features. Thus, Tle3 integrated functions of multiple transcription factors to guard lineage fidelity of CD8+ TEM cells, and manipulation of Tle3 activity could favor CD8+ TCM cell production.

Tcf1 preprograms the mobilization of glycolysis in central memory CD8+ T cells during recall responses.

The mechanisms underlying the heightened protection mediated by central memory CD8+ T (TCM) cells remain unclear. Here we show that the transcription factor Tcf1 was required in resting TCM cells to generate secondary effector CD8+ T cells and to clear pathogens during recall responses. Recall stimulation of CD8+ TCM cells caused extensive reprogramming of the transcriptome and chromatin accessibility, leading to rapid induction of glycolytic enzymes, cell cycle regulators and transcriptional regulators, including Id3. This cluster of genes did not require Tcf1 in resting CD8+ TCM cells, but depended on Tcf1 for optimal induction and chromatin opening in recall-stimulated CD8+ TCM cells. Tcf1 bound extensively to these recall-induced gene loci in resting CD8+ TCM cells and mediated chromatin interactions that positioned these genes in architectural proximity with poised enhancers. Thus, Tcf1 preprogramed a transcriptional program that supported the bioenergetic and proliferative needs of CD8+ TCM cells in case of a secondary challenge.

UTX condensation underlies its tumour-suppressive activity.

UTX (also known as KDM6A) encodes a histone H3K27 demethylase and is an important tumour suppressor that is frequently mutated in human cancers1. However, as the demethylase activity of UTX is often dispensable for mediating tumour suppression and developmental regulation2-8, the underlying molecular activity of UTX remains unknown. Here we show that phase separation of UTX underlies its chromatin-regulatory activity in tumour suppression. A core intrinsically disordered region (cIDR) of UTX forms phase-separated liquid condensates, and cIDR loss caused by the most frequent cancer mutation of UTX is mainly responsible for abolishing tumour suppression. Deletion, mutagenesis and replacement assays of the intrinsically disordered region demonstrate a critical role of UTX condensation in tumour suppression and embryonic stem cell differentiation. As shown by reconstitution in vitro and engineered systems in cells, UTX recruits the histone methyltransferase MLL4 (also known as KMT2D) to the same condensates and enriches the H3K4 methylation activity of MLL4. Moreover, UTX regulates genome-wide histone modifications and high-order chromatin interactions in a condensation-dependent manner. We also found that UTY, the Y chromosome homologue of UTX with weaker tumour-suppressive activity, forms condensates with reduced molecular dynamics. These studies demonstrate a crucial biological function of liquid condensates with proper material states in enabling the tumour-suppressive activity of a chromatin regulator.

DNA fragility at topologically associated domain boundaries is promoted by alternative DNA secondary structure and topoisomerase II activity.

CCCTC-binding factor (CTCF) binding sites are hotspots of genome instability. Although many factors have been associated with CTCF binding site fragility, no study has integrated all fragility-related factors to understand the mechanism(s) of how they work together. Using an unbiased, genome-wide approach, we found that DNA double-strand breaks (DSBs) are enriched at strong, but not weak, CTCF binding sites in five human cell types. Energetically favorable alternative DNA secondary structures underlie strong CTCF binding sites. These structures coincided with the location of topoisomerase II (TOP2) cleavage complex, suggesting that DNA secondary structure acts as a recognition sequence for TOP2 binding and cleavage at CTCF binding sites. Furthermore, CTCF knockdown significantly increased DSBs at strong CTCF binding sites and at CTCF sites that are located at topologically associated domain (TAD) boundaries. TAD boundary-associated CTCF sites that lost CTCF upon knockdown displayed increased DSBs when compared to the gained sites, and those lost sites are overrepresented with G-quadruplexes, suggesting that the structures act as boundary insulators in the absence of CTCF, and contribute to increased DSBs. These results model how alternative DNA secondary structures facilitate recruitment of TOP2 to CTCF binding sites, providing mechanistic insight into DNA fragility at CTCF binding sites.

Fob1-dependent condensin recruitment and loop extrusion on yeast chromosome III.

Despite recent advances in single-molecule and structural analysis of condensin activity in vitro, mechanisms of functional condensin loading and loop extrusion that lead to specific chromosomal organization remain unclear. In Saccharomyces cerevisiae, the most prominent condensin loading site is the rDNA locus on chromosome XII, but its repetitiveness deters rigorous analysis of individual genes. An equally prominent non-rDNA condensin site is located on chromosome III (chrIII). It lies in the promoter of a putative non-coding RNA gene called RDT1, which is in a segment of the recombination enhancer (RE) that dictates MATa-specific chrIII organization. Here, we unexpectedly find that condensin is recruited to the RDT1 promoter in MATa cells through hierarchical interactions with Fob1, Tof2, and cohibin (Lrs4/Csm1), a set of nucleolar factors that also recruit condensin to the rDNA. Fob1 directly binds to this locus in vitro, while its binding in vivo depends on an adjacent Mcm1/α2 binding site that provides MATa cell specificity. We also uncover evidence for condensin-driven loop extrusion anchored by Fob1 and cohibin at RDT1 that unidirectionally extends toward MATa on the right arm of chrIII, supporting donor preference during mating-type switching. S. cerevisiae chrIII therefore provides a new platform for the study of programmed condensin-mediated chromosome conformation.

Interpretable meta-learning of multi-omics data for survival analysis and pathway enrichment.

MOTIVATION: Despite the success of recent machine learning algorithms' applications to survival analysis, their black-box nature hinders interpretability, which is arguably the most important aspect. Similarly, multi-omics data integration for survival analysis is often constrained by the underlying relationships and correlations that are rarely well understood. The goal of this work is to alleviate the interpretability problem in machine learning approaches for survival analysis and also demonstrate how multi-omics data integration improves survival analysis and pathway enrichment. We use meta-learning, a machine-learning algorithm that is trained on a variety of related datasets and allows quick adaptations to new tasks, to perform survival analysis and pathway enrichment on pan-cancer datasets. In recent machine learning research, meta-learning has been effectively used for knowledge transfer among multiple related datasets. RESULTS: We use meta-learning with Cox hazard loss to show that the integration of TCGA pan-cancer data increases the performance of survival analysis. We also apply advanced model interpretability method called DeepLIFT (Deep Learning Important FeaTures) to show different sets of enriched pathways for multi-omics and transcriptomics data. Our results show that multi-omics cancer survival analysis enhances performance compared with using transcriptomics or clinical data alone. Additionally, we show a correlation between variable importance assignment from DeepLIFT and gene coenrichment, suggesting that genes with higher and similar contribution scores are more likely to be enriched together in the same enrichment sets. AVAILABILITY AND IMPLEMENTATION: https://github.com/berkuva/TCGA-omics-integration.

Genome-wide mapping of HATs and HDACs reveals distinct functions in active and inactive genes.

Histone acetyltransferases (HATs) and deacetylases (HDACs) function antagonistically to control histone acetylation. As acetylation is a histone mark for active transcription, HATs have been associated with active and HDACs with inactive genes. We describe here genome-wide mapping of HATs and HDACs binding on chromatin and find that both are found at active genes with acetylated histones. Our data provide evidence that HATs and HDACs are both targeted to transcribed regions of active genes by phosphorylated RNA Pol II. Furthermore, the majority of HDACs in the human genome function to reset chromatin by removing acetylation at active genes. Inactive genes that are primed by MLL-mediated histone H3K4 methylation are subject to a dynamic cycle of acetylation and deacetylation by transient HAT/HDAC binding, preventing Pol II from binding to these genes but poising them for future activation. Silent genes without any H3K4 methylation signal show no evidence of being bound by HDACs.

BART3D: inferring transcriptional regulators associated with differential chromatin interactions from Hi-C data.

SUMMARY: Identification of functional transcriptional regulators (TRs) associated with chromatin interactions is an important problem in studies of 3-dimensional genome organization and gene regulation. Direct inference of TR binding has been limited by the resolution of Hi-C data. Here, we present BART3D, a computational method for inferring TRs associated with genome-wide differential chromatin interactions by comparing Hi-C maps from two states, leveraging public ChIP-seq data for human and mouse. We demonstrate that BART3D can detect relevant TRs from dynamic Hi-C profiles with TR perturbation or cell differentiation. BART3D can be a useful tool in 3D genome data analysis and functional genomics research. AVAILABILITY AND IMPLEMENTATION: BART3D is implemented in Python and the source code is available at https://github.com/zanglab/bart3d. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Deciphering essential cistromes using genome-wide CRISPR screens.

Although millions of transcription factor binding sites, or cistromes, have been identified across the human genome, defining which of these sites is functional in a given condition remains challenging. Using CRISPR/Cas9 knockout screens and gene essentiality or fitness as the readout, we systematically investigated the essentiality of over 10,000 FOXA1 and CTCF binding sites in breast and prostate cancer cells. We found that essential FOXA1 binding sites act as enhancers to orchestrate the expression of nearby essential genes through the binding of lineage-specific transcription factors. In contrast, CRISPR screens of the CTCF cistrome revealed 2 classes of essential binding sites. The first class of essential CTCF binding sites act like FOXA1 sites as enhancers to regulate the expression of nearby essential genes, while a second class of essential CTCF binding sites was identified at topologically associated domain (TAD) boundaries and display distinct characteristics. Using regression methods trained on our screening data and public epigenetic profiles, we developed a model to predict essential cis-elements with high accuracy. The model for FOXA1 essentiality correctly predicts noncoding variants associated with cancer risk and progression. Taken together, CRISPR screens of cis-regulatory elements can define the essential cistrome of a given factor and can inform the development of predictive models of cistrome function.

Active enhancers are delineated de novo during hematopoiesis, with limited lineage fidelity among specified primary blood cells.

Tissues may adopt diverse strategies to establish specific transcriptional programs in daughter lineages. In intestinal crypts, enhancers for genes expressed in both major cell types appear broadly permissive in stem and specified progenitor cells. In blood, another self-renewing tissue, it is unclear when chromatin becomes permissive for transcription of genes expressed in distinct terminal lineages. Using chromatin immunoprecipitation (ChIP) combined with deep sequencing (ChIP-seq) to profile activating histone marks, we studied enhancer dynamics in primary mouse blood stem, progenitor, and specified cells. Stem and multipotent progenitor cells show scant H3K4me2 marking at enhancers bound by specific transcription factors in their committed progeny. Rather, enhancers are modulated dynamically and serially, with substantial loss and gain of H3K4me2, at each cellular transition. Quantitative analysis of these dynamics accurately modeled hematopoiesis according to Waddington's notion of epigenotypes. Delineation of enhancers in terminal blood lineages coincides with cell specification, and enhancers active in single lineages show well-positioned H3K4me2- and H3K27ac-marked nucleosomes and DNaseI hypersensitivity in other cell types, revealing limited lineage fidelity. These findings demonstrate that enhancer chronology in blood cells differs markedly from that in intestinal crypts. Chromatin dynamics in hematopoiesis provide a useful foundation to consider classical observations such as cellular reprogramming and multilineage locus priming.

Assessing acute myeloid leukemia susceptibility in rearrangement-driven patients by DNA breakage at topoisomerase II and CCCTC-binding factor/cohesin binding sites.

An initiating DNA double strand break (DSB) event precedes the formation of cancer-driven chromosomal abnormalities, such as gene rearrangements. Therefore, measuring DNA breaks at rearrangement-participating regions can provide a unique tool to identify and characterize susceptible individuals. Here, we developed a highly sensitive and low-input DNA break mapping method, the first of its kind for patient samples. We then measured genome-wide DNA breakage in normal cells of acute myeloid leukemia (AML) patients with KMT2A (previously MLL) rearrangements, compared to that of nonfusion AML individuals, as a means to evaluate individual susceptibility to gene rearrangements. DNA breakage at the KMT2A gene region was significantly greater in fusion-driven remission individuals, as compared to nonfusion individuals. Moreover, we identified select topoisomerase II (TOP2)-sensitive and CCCTC-binding factor (CTCF)/cohesin-binding sites with preferential DNA breakage in fusion-driven patients. Importantly, measuring DSBs at these sites, in addition to the KMT2A gene region, provided greater predictive power when assessing individual break susceptibility. We also demonstrated that low-dose etoposide exposure further elevated DNA breakage at these regions in fusion-driven AML patients, but not in nonfusion patients, indicating that these sites are preferentially sensitive to TOP2 activity in fusion-driven AML patients. These results support that mapping of DSBs in patients enables discovery of novel break-prone regions and monitoring of individuals susceptible to chromosomal abnormalities, and thus cancer. This will build the foundation for early detection of cancer-susceptible individuals, as well as those preferentially susceptible to therapy-related malignancies caused by treatment with TOP2 poisons.

YY1 is a cis-regulator in the organoid models of high mammographic density.

MOTIVATION: Our previous study has shown that ERBB2 is overexpressed in the organoid model of MCF10A when the stiffness of the microenvironment is increased to that of high mammographic density (MD). We now aim to identify key transcription factors (TFs) and functional enhancers that regulate processes associated with increased stiffness of the microenvironment in the organoid models of premalignant human mammary cell lines. RESULTS: 3D colony organizations and the cis-regulatory networks of two human mammary epithelial cell lines (184A1 and MCF10A) are investigated as a function of the increased stiffness of the microenvironment within the range of MD. The 3D colonies are imaged using confocal microscopy, and the morphometries of colony organizations and heterogeneity are quantified as a function of the stiffness of the microenvironment using BioSig3D. In a surrogate assay, colony organizations are profiled by transcriptomics. Transcriptome data are enriched by correlative analysis with the computed morphometric indices. Next, a subset of enriched data are processed against publicly available ChIP-Seq data using Model-based Analysis of Regulation of Gene Expression to predict regulatory transcription factors. This integrative analysis of morphometric and transcriptomic data predicted YY1 as one of the cis-regulators in both cell lines as a result of the increased stiffness of the microenvironment. Subsequent experiments validated that YY1 is expressed at protein and mRNA levels for MCF10A and 184A1, respectively. Also, there is a causal relationship between activation of YY1 and ERBB2 when YY1 is overexpressed at the protein level in MCF10A. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Estrogen-regulated feedback loop limits the efficacy of estrogen receptor-targeted breast cancer therapy.

Endocrine therapy resistance invariably develops in advanced estrogen receptor-positive (ER+) breast cancer, but the underlying mechanisms are largely unknown. We have identified C-terminal SRC kinase (CSK) as a critical node in a previously unappreciated negative feedback loop that limits the efficacy of current ER-targeted therapies. Estrogen directly drives CSK expression in ER+ breast cancer. At low CSK levels, as is the case in patients with ER+ breast cancer resistant to endocrine therapy and with the poorest outcomes, the p21 protein-activated kinase 2 (PAK2) becomes activated and drives estrogen-independent growth. PAK2 overexpression is also associated with endocrine therapy resistance and worse clinical outcome, and the combination of a PAK2 inhibitor with an ER antagonist synergistically suppressed breast tumor growth. Clinical approaches to endocrine therapy-resistant breast cancer must overcome the loss of this estrogen-induced negative feedback loop that normally constrains the growth of ER+ tumors.

Specific inhibition of DPY30 activity by ASH2L-derived peptides suppresses blood cancer cell growth.

DPY30 facilitates H3K4 methylation by directly binding to ASH2L in the SET1/MLL complexes and plays an important role in hematologic malignancies. However, the domain on DPY30 that regulates cancer growth is not evident, and the potential of pharmacologically targeting this chromatin modulator to inhibit cancer has not been explored. Here we have developed a peptide-based strategy to specifically target DPY30 activity. We have designed cell-penetrating peptides derived from ASH2L that can either bind to DPY30 or show defective or enhanced binding to DPY30. The DPY30-binding peptides specifically inhibit DPY30's activity in interacting with ASH2L and enhancing H3K4 methylation. Treatment with the DPY30-binding peptides significantly inhibited the growth of MLL-rearranged leukemia and other MYC-dependent hematologic cancer cells. We also revealed subsets of genes that may mediate the effect of the peptides on cancer cell growth, and showed that the DPY30-binding peptide sensitized leukemia to other types of epigenetic inhibitors. These results strongly support a critical role of the ASH2L-binding groove of DPY30 in promoting blood cancers, and demonstrate a proof-of-principle for the feasibility of pharmacologically targeting the ASH2L-binding groove of DPY30 for potential cancer inhibition.

Universal correction of enzymatic sequence bias reveals molecular signatures of protein/DNA interactions.

Coupling molecular biology to high-throughput sequencing has revolutionized the study of biology. Molecular genomics techniques are continually refined to provide higher resolution mapping of nucleic acid interactions and structure. Sequence preferences of enzymes can interfere with the accurate interpretation of these data. We developed seqOutBias to characterize enzymatic sequence bias from experimental data and scale individual sequence reads to correct intrinsic enzymatic sequence biases. SeqOutBias efficiently corrects DNase-seq, TACh-seq, ATAC-seq, MNase-seq and PRO-seq data. We show that seqOutBias correction facilitates identification of true molecular signatures resulting from transcription factors and RNA polymerase interacting with DNA.

Modeling cis-regulation with a compendium of genome-wide histone H3K27ac profiles.

Model-based analysis of regulation of gene expression (MARGE) is a framework for interpreting the relationship between the H3K27ac chromatin environment and differentially expressed gene sets. The framework has three main functions: MARGE-potential, MARGE-express, and MARGE-cistrome. MARGE-potential defines a regulatory potential (RP) for each gene as the sum of H3K27ac ChIP-seq signals weighted by a function of genomic distance from the transcription start site. The MARGE framework includes a compendium of RPs derived from 365 human and 267 mouse H3K27ac ChIP-seq data sets. Relative RPs, scaled using this compendium, are superior to superenhancers in predicting BET (bromodomain and extraterminal domain) -inhibitor repressed genes. MARGE-express, which uses logistic regression to retrieve relevant H3K27ac profiles from the compendium to accurately model a query set of differentially expressed genes, was tested on 671 diverse gene sets from MSigDB. MARGE-cistrome adopts a novel semisupervised learning approach to identify cis-regulatory elements regulating a gene set. MARGE-cistrome exploits information from H3K27ac signal at DNase I hypersensitive sites identified from published human and mouse DNase-seq data. We tested the framework on newly generated RNA-seq and H3K27ac ChIP-seq profiles upon siRNA silencing of multiple transcriptional and epigenetic regulators in a prostate cancer cell line, LNCaP-abl. MARGE-cistrome can predict the binding sites of silenced transcription factors without matched H3K27ac ChIP-seq data. Even when the matching H3K27ac ChIP-seq profiles are available, MARGE leverages public H3K27ac profiles to enhance these data. This study demonstrates the advantage of integrating a large compendium of historical epigenetic data for genomic studies of transcriptional regulation.

BART: a transcription factor prediction tool with query gene sets or epigenomic profiles.

Summary: Identification of functional transcription factors that regulate a given gene set is an important problem in gene regulation studies. Conventional approaches for identifying transcription factors, such as DNA sequence motif analysis, are unable to predict functional binding of specific factors and not sensitive enough to detect factors binding at distal enhancers. Here, we present binding analysis for regulation of transcription (BART), a novel computational method and software package for predicting functional transcription factors that regulate a query gene set or associate with a query genomic profile, based on more than 6000 existing ChIP-seq datasets for over 400 factors in human or mouse. This method demonstrates the advantage of utilizing publicly available data for functional genomics research. Availability and implementation: BART is implemented in Python and available at http://faculty.virginia.edu/zanglab/bart. Supplementary information: Supplementary data are available at Bioinformatics online.

Discrete roles of STAT4 and STAT6 transcription factors in tuning epigenetic modifications and transcription during T helper cell differentiation.

Signal transducer and activator of transcription 4 (STAT4) and STAT6 are key factors in the specification of helper T cells; however, their direct roles in driving differentiation are not well understood. Using chromatin immunoprecipitation and massive parallel sequencing, we quantitated the full complement of STAT-bound genes, concurrently assessing global STAT-dependent epigenetic modifications and gene transcription by using cells from cognate STAT-deficient mice. STAT4 and STAT6 each bound over 4000 genes with distinct binding motifs. Both played critical roles in maintaining chromatin configuration and transcription of a core subset of genes through the combination of different epigenetic patterns. Globally, STAT4 had a more dominant role in promoting active epigenetic marks, whereas STAT6 had a more prominent role in antagonizing repressive marks. Clusters of genes negatively regulated by STATs were also identified, highlighting previously unappreciated repressive roles of STATs. Therefore, STAT4 and STAT6 play wide regulatory roles in T helper cell specification.