26 research outputs found
An expansive human regulatory lexicon encoded in transcription factor footprints.
Regulatory factor binding to genomic DNA protects the underlying sequence from cleavage by DNase I, leaving nucleotide-resolution footprints. Using genomic DNase I footprinting across 41 diverse cell and tissue types, we detected 45 million transcription factor occupancy events within regulatory regions, representing differential binding to 8.4 million distinct short sequence elements. Here we show that this small genomic sequence compartment, roughly twice the size of the exome, encodes an expansive repertoire of conserved recognition sequences for DNA-binding proteins that nearly doubles the size of the human cis-regulatory lexicon. We find that genetic variants affecting allelic chromatin states are concentrated in footprints, and that these elements are preferentially sheltered from DNA methylation. High-resolution DNase I cleavage patterns mirror nucleotide-level evolutionary conservation and track the crystallographic topography of protein-DNA interfaces, indicating that transcription factor structure has been evolutionarily imprinted on the human genome sequence. We identify a stereotyped 50-base-pair footprint that precisely defines the site of transcript origination within thousands of human promoters. Finally, we describe a large collection of novel regulatory factor recognition motifs that are highly conserved in both sequence and function, and exhibit cell-selective occupancy patterns that closely parallel major regulators of development, differentiation and pluripotency
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The accessible chromatin landscape of the human genome
DNaseI hypersensitive sites (DHSs) are markers of regulatory DNA and have underpinned the discovery of all classes of cis-regulatory elements including enhancers, promoters, insulators, silencers, and locus control regions. Here we present the first extensive map of human DHSs identified through genome-wide profiling in 125 diverse cell and tissue types. We identify ~2.9 million DHSs that encompass virtually all known experimentally-validated cis-regulatory sequences and expose a vast trove of novel elements, most with highly cell-selective regulation. Annotating these elements using ENCODE data reveals novel relationships between chromatin accessibility, transcription, DNA methylation, and regulatory factor occupancy patterns. We connect ~580,000 distal DHSs with their target promoters, revealing systematic pairing of different classes of distal DHSs and specific promoter types. Patterning of chromatin accessibility at many regulatory regions is choreographed with dozens to hundreds of co-activated elements, and the trans-cellular DNaseI sensitivity pattern at a given region can predict cell type-specific functional behaviors. The DHS landscape shows signatures of recent functional evolutionary constraint. However, the DHS compartment in pluripotent and immortalized cells exhibits higher mutation rates than that in highly differentiated cells, exposing an unexpected link between chromatin accessibility, proliferative potential and patterns of human variation
The accessible chromatin landscape of the human genome
DNaseI hypersensitive sites (DHSs) are markers of regulatory DNA and have underpinned the discovery of all classes of cis-regulatory elements including enhancers, promoters, insulators, silencers, and locus control regions. Here we present the first extensive map of human DHSs identified through genome-wide profiling in 125 diverse cell and tissue types. We identify ~2.9 million DHSs that encompass virtually all known experimentally-validated cis-regulatory sequences and expose a vast trove of novel elements, most with highly cell-selective regulation. Annotating these elements using ENCODE data reveals novel relationships between chromatin accessibility, transcription, DNA methylation, and regulatory factor occupancy patterns. We connect ~580,000 distal DHSs with their target promoters, revealing systematic pairing of different classes of distal DHSs and specific promoter types. Patterning of chromatin accessibility at many regulatory regions is choreographed with dozens to hundreds of co-activated elements, and the trans-cellular DNaseI sensitivity pattern at a given region can predict cell type-specific functional behaviors. The DHS landscape shows signatures of recent functional evolutionary constraint. However, the DHS compartment in pluripotent and immortalized cells exhibits higher mutation rates than that in highly differentiated cells, exposing an unexpected link between chromatin accessibility, proliferative potential and patterns of human variation
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Cell-of-origin chromatin organization shapes the mutational landscape of cancer
Cancer is a disease potentiated by mutations in somatic cells. Cancer mutations are not distributed uniformly along the genome. Instead, different genomic regions vary by up to 5-fold in the local density of somatic mutations1, posing a fundamental problem for statistical methods of cancer genomics. Epigenomic organization has been proposed as a major determinant of the cancer mutational landscape1-5. However, both somatic mutagenesis and epigenomic features are highly cell-type-specific6,7. We investigated the distribution of mutations in multiple samples of diverse cancer types and compared them to cell-type-specific epigenomic features. Here, we show that chromatin accessibility and modification, together with replication timing, explain up to 86% of the variance in mutation rates along cancer genomes. Overwhelmingly, the best predictors of local somatic mutation density are epigenomic features derived from the most likely cell type of origin of the corresponding malignancy. Moreover, we find that cell-of-origin chromatin features are much stronger determinants of cancer mutation profiles than chromatin features of cognate cancer cell lines. We show further that the cell type of origin of a cancer can be accurately determined based on the distribution of mutations along its genome. Thus, DNA sequence of a cancer genome encompasses a wealth of information about the identity and epigenomic features of its cell of origin
Integrated epigenomic profiling reveals endogenous retrovirus reactivation in renal cell carcinomaReseach in context
Background: Transcriptional dysregulation drives cancer formation but the underlying mechanisms are still poorly understood. Renal cell carcinoma (RCC) is the most common malignant kidney tumor which canonically activates the hypoxia-inducible transcription factor (HIF) pathway. Despite intensive study, novel therapeutic strategies to target RCC have been difficult to develop. Since the RCC epigenome is relatively understudied, we sought to elucidate key mechanisms underpinning the tumor phenotype and its clinical behavior. Methods: We performed genome-wide chromatin accessibility (DNase-seq) and transcriptome profiling (RNA-seq) on paired tumor/normal samples from 3 patients undergoing nephrectomy for removal of RCC. We incorporated publicly available data on HIF binding (ChIP-seq) in a RCC cell line. We performed integrated analyses of these high-resolution, genome-scale datasets together with larger transcriptomic data available through The Cancer Genome Atlas (TCGA). Findings: Though HIF transcription factors play a cardinal role in RCC oncogenesis, we found that numerous transcription factors with a RCC-selective expression pattern also demonstrated evidence of HIF binding near their gene body. Examination of chromatin accessibility profiles revealed that some of these transcription factors influenced the tumor's regulatory landscape, notably the stem cell transcription factor POU5F1 (OCT4). Elevated POU5F1 transcript levels were correlated with advanced tumor stage and poorer overall survival in RCC patients. Unexpectedly, we discovered a HIF-pathway-responsive promoter embedded within a endogenous retroviral long terminal repeat (LTR) element at the transcriptional start site of the PSOR1C3 long non-coding RNA gene upstream of POU5F1. RNA transcripts are induced from this promoter and read through PSOR1C3 into POU5F1 producing a novel POU5F1 transcript isoform. Rather than being unique to the POU5F1 locus, we found that HIF binds to several other transcriptionally active LTR elements genome-wide correlating with broad gene expression changes in RCC. Interpretation: Integrated transcriptomic and epigenomic analysis of matched tumor and normal tissues from even a small number of primary patient samples revealed remarkably convergent shared regulatory landscapes. Several transcription factors appear to act downstream of HIF including the potent stem cell transcription factor POU5F1. Dysregulated expression of POU5F1 is part of a larger pattern of gene expression changes in RCC that may be induced by HIF-dependent reactivation of dormant promoters embedded within endogenous retroviral LTRs. Keywords: Transcription factors, Kidney cancer, Renal cell carcinoma, Cancer epigenetics, Cancer stem cell, Regulatory genomic
Hematopoietic Protein-1 Regulates the Actin Membrane Skeleton and Membrane Stability in Murine Erythrocytes
<div><p>Hematopoietic protein-1 (Hem-1) is a hematopoietic cell specific member of the WAVE (Wiskott-Aldrich syndrome verprolin-homologous protein) complex, which regulates filamentous actin (F-actin) polymerization in many cell types including immune cells. However, the roles of Hem-1 and the WAVE complex in erythrocyte biology are not known. In this study, we utilized mice lacking Hem-1 expression due to a non-coding point mutation in the <em>Hem1</em> gene to show that absence of Hem-1 results in microcytic, hypochromic anemia characterized by abnormally shaped erythrocytes with aberrant F-actin foci and decreased lifespan. We find that Hem-1 and members of the associated WAVE complex are normally expressed in wildtype erythrocyte progenitors and mature erythrocytes. Using mass spectrometry and global proteomics, Coomassie staining, and immunoblotting, we find that the absence of Hem-1 results in decreased representation of essential erythrocyte membrane skeletal proteins including α- and β- spectrin, dematin, p55, adducin, ankyrin, tropomodulin 1, band 3, and band 4.1. <em>Hem1<sup>−/−</sup></em> erythrocytes exhibit increased protein kinase C-dependent phosphorylation of adducin at Ser724, which targets adducin family members for dissociation from spectrin and actin, and subsequent proteolysis. Increased adducin Ser724 phosphorylation in <em>Hem1<sup>−/−</sup></em> erythrocytes correlates with decreased protein expression of the regulatory subunit of protein phosphatase 2A (PP2A), which is required for PP2A-dependent dephosphorylation of PKC targets. These results reveal a novel, critical role for Hem-1 in the homeostasis of structural proteins required for formation and stability of the actin membrane skeleton in erythrocytes.</p> </div
Model of the erythrocyte membrane cytoskeleton in wildtype and Hem-1 null mice.
<p>(<i>top</i>) The red cell membrane in WT mice consists of a lipid bilayer embedded with two main complexes of structural proteins: The ankyrin complex and the junctional complex (also known as the 4.1R complex), which are connected by horizontal flexible helices of α- and β- spectrin heterodimers and tetramers. Stability of the complexes is regulated in part by phosphorylation of adducin (on Serine 724 in mice) by protein kinase C (PKC), which leads to decreased F-actin capping and dissociation of spectrin from actin. Since PKC-mediated serine phosphorylation is typically opposed by protein phosphatase 2A (PP2A), we propose that PP2A dephosphorylates adducin. PP2A, PKC (bottom), and Hem-1 (top) have all been shown to associate with Rac1. Loss of Hem-1 results in decreased PP2a regulatory subunit B (PP2Ar) and structural subunit A protein expression and increased PKC-mediated phosphorylation of Ser724 on adducin (bottom). Phospho-adducin is then degraded, resulting in the dissociation of spectrin from actin and decreased stability of junctional complex proteins and the membrane cytoskeleton. GPA (Glycophorin A), GPC (Glycophorin C), PP2Ac (protein phosphatase 2A catalytic subunit), PP2Ar (protein phosphatase 2A regulatory subunit).</p
Lifespan of transfused <i>Hem1<sup>−/−</sup></i> erythrocytes is decreased compared to transfused WT erythrocytes.
<p>Purified WT (open diamonds, <i>n</i> = 4 mice) and <i>Hem1<sup>−/−</sup></i> (filled triangles, <i>n</i> = 3 mice) erythrocytes (5×10<sup>8</sup> per mouse) were labeled with CFSE dye and transfused via retro-orbital injection into <i>Rag2<sup>−/−</sup>γ<sub>c</sub><sup>−/−</sup></i> host mice. Host mice were tail bled starting Day 1 post-transfusion and samples were analyzed via flow cytometry to determine the percentage of CFSE-labeled erythrocytes. Percent CFSE labeled cells remaining post transfusion were determined relative to Day 1 (100% labeling). <i>P</i>-values are noted above each time-point.</p
<i>Hem1<sup>−/−</sup></i> erythrocytes contain increased phospho-adducin and decreased levels of essential membrane skeletal proteins.
<p>SDS-PAGE analysis of purified erythrocyte ghosts was used to evaluate relative levels of erythrocyte membrane skeletal proteins between WT and <i>Hem1<sup>−/−</sup></i> mice. (A) Coomassie-stained polyacrylamide gel (representative of 6 animals per genotype). Lanes contain equivalent amounts of total protein. β-actin immunoblot is shown below. (B) Immunoblots of erythrocyte membrane ghosts from purified WT and <i>Hem1<sup>−/−</sup></i> erythrocytes, loaded according to total protein and equivalent β-actin. Each pair is representative of results for at least 5 individuals of each genotype. (C) Activation of PKC results in increased phosphorylation of adducin on Serine 724. Purified WT and <i>Hem1<sup>−/−</sup></i> erythrocytes were stimulated with the phorbol ester PMA (20 ng/ml) and were harvested and lysed at the indicated timepoints post-stimulation. A representative immunoblot of three separate experiments is shown (3 animals per genotype). (D) Erythrocyte ghosts from <i>Hem1<sup>−/−</sup></i> mice contain increased PP2A catalytic subunit (PP2Ac) and decreased PP2A regulatory subunit (PP2Ar) protein relative to WT erythrocytes. Shown are total protein levels determined by immunoblot. Numbers below each scan represent relative protein expression levels in <i>Hem1<sup>−/−</sup></i> versus WT samples. Samples were loaded according to levels of total protein. (E) WT and <i>Hem1<sup>−/−</sup></i> erythroblasts were stimulated in Okadaic acid (OA) and were harvested and lysed at the indicated timepoints post-stimulation. A representative immunoblot of 3 separate experiments is shown. Samples were loaded based on equivalent cell number.</p