Author
Lisa Helbling Chadwick
Other affiliations: Case Western Reserve University, Duke University
Bio: Lisa Helbling Chadwick is an academic researcher from National Institutes of Health. The author has contributed to research in topics: Epigenome & Epigenomics. The author has an hindex of 11, co-authored 13 publications receiving 4736 citations. Previous affiliations of Lisa Helbling Chadwick include Case Western Reserve University & Duke University.
Topics: Epigenome, Epigenomics, X chromosome, X-inactivation, Chromatin
Papers
More filters
Massachusetts Institute of Technology1, Broad Institute2, University of California, Los Angeles3, University of British Columbia4, Baylor College of Medicine5, Howard Hughes Medical Institute6, University of Washington7, Ludwig Institute for Cancer Research8, University of California, San Francisco9, University of Connecticut10, University of Zagreb11, University of Texas at Austin12, Washington University in St. Louis13, University of Queensland14, Harvard University15, Cold Spring Harbor Laboratory16, University of Southern California17, University of California, Santa Cruz18, Simon Fraser University19, Morgridge Institute for Research20, University of Texas at Dallas21, National Institutes of Health22
TL;DR: It is shown that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease.
Abstract: The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.
5,037 citations
TL;DR: Key features of the websites where users will find data, protocols and analysis tools developed by the consortium, and a perspective on how this unique resource will facilitate and inform human disease research, both immediately and in the future are described.
Abstract: The NIH Roadmap Reference Epigenome Mapping Consortium is developing a community resource of genome-wide epigenetic maps in a broad range of human primary cells and tissues. There are large amounts of data already available, and a number of different options for viewing and analyzing the data. This report will describe key features of the websites where users will find data, protocols and analysis tools developed by the consortium, and provide a perspective on how this unique resource will facilitate and inform human disease research, both immediately and in the future.
185 citations
French Institute of Health and Medical Research1, Harvard University2, Katholieke Universiteit Leuven3, University of Rennes4, University of Wisconsin–Milwaukee5, Dartmouth College6, University of Occupational and Environmental Health Japan7, University of Rochester8, Columbia University9, University of Illinois at Chicago10, University of Cincinnati11, University of Missouri12, Boston University13, University of Queensland14, University of Turku15, University of Texas Health Science Center at Houston16
TL;DR: Vulnerable exposure windows that can occur as early as the preconception period and epigenetics as a major mechanism than can lead to disadvantageous "reprogramming" of the genome, thereby potentially resulting in transgenerational effects are highlighted.
Abstract: The Developmental Origins of Health and Disease (DOHaD) paradigm is one of the most rapidly expanding areas of biomedical research. Environmental stressors that can impact on DOHaD encompass a variety of environmental and occupational hazards as well as deficiency and oversupply of nutrients and energy. They can disrupt early developmental processes and lead to increased susceptibility to disease/dysfunctions later in life. Presentations at the fourth Conference on Prenatal Programming and Toxicity in Boston, in October 2014, provided important insights and led to new recommendations for research and public health action. The conference highlighted vulnerable exposure windows that can occur as early as the preconception period and epigenetics as a major mechanism than can lead to disadvantageous “reprogramming” of the genome, thereby potentially resulting in transgenerational effects. Stem cells can also be targets of environmental stressors, thus paving another way for effects that may last a lifetime. Current testing paradigms do not allow proper characterization of risk factors and their interactions. Thus, relevant exposure levels and combinations for testing must be identified from human exposure situations and outcome assessments. Testing of potential underpinning mechanisms and biomarker development require laboratory animal models and in vitro approaches. Only few large-scale birth cohorts exist, and collaboration between birth cohorts on a global scale should be facilitated. DOHaD-based research has a crucial role in establishing factors leading to detrimental outcomes and developing early preventative/remediation strategies to combat these risks.
135 citations
TL;DR: It is shown conclusively that Xce is the only major locus to influence X inactivation patterns in the crosses analyzed and defines a 1.85-Mb interval encompassing all the major elements of the Xce locus.
Abstract: In early mammalian development, one of the two X chromosomes is silenced in each female cell as a result of X chromosome inactivation, the mammalian dosage compensation mechanism. In the mouse epiblast, the choice of which chromosome is inactivated is essentially random, but can be biased by alleles at the X-linked X controlling element (Xce). Although this locus was first described nearly four decades ago, the identity and precise genomic localization of Xce remains elusive. Within the X inactivation center region of the X chromosome, previous linkage disequilibrium studies comparing strains of known Xce genotypes have suggested that Xce is physically distinct from Xist, although this has not yet been established by genetic mapping or progeny testing. In this report, we used quantitative trait locus (QTL) mapping strategies to define the minimal Xce candidate interval. Subsequent analysis of recombinant chromosomes allowed for the establishment of a maximum 1.85-Mb candidate region for the Xce locus. Finally, we use QTL approaches in an effort to identify additional modifiers of the X chromosome choice, as we have previously demonstrated that choice in Xce heterozygous females is significantly influenced by genetic variation present on autosomes (Chadwick and Willard 2005). We did not identify any autosomal loci with significant associations and thus show conclusively that Xce is the only major locus to influence X inactivation patterns in the crosses analyzed. This study provides a foundation for future analyses into the genetic control of X chromosome inactivation and defines a 1.85-Mb interval encompassing all the major elements of the Xce locus.
69 citations
Washington University in St. Louis1, University of Pennsylvania2, Baylor College of Medicine3, Johns Hopkins University4, Case Western Reserve University5, University of Michigan6, University of Chicago7, North Carolina State University8, Duke University9, University of North Carolina at Chapel Hill10, National Institutes of Health11
TL;DR: It is critical to determine whether epigenetic alterations are conserved across tissues in such a way that easily sampled surrogate tissues could be used to assess the impact of environmental exposure on diseaserelevant but inaccessible target tissues.
Abstract: 225 in response to pertinent environmental exposures. Additionally, it is impossible to sample all relevant tissues involved in disease pathogenesis in human populations. To make direct connections between exposure-induced epigenetic changes and health outcomes, it is therefore critical to determine whether epigenetic alterations are conserved across tissues in such a way that easily sampled surrogate tissues could be used to assess the impact of environmental exposure on diseaserelevant but inaccessible target tissues (Table 1). The correlation between The NIEHS TaRGET II Consortium and environmental epigenomics
65 citations
Cited by
More filters
Massachusetts Institute of Technology1, Broad Institute2, University of California, Los Angeles3, University of British Columbia4, Baylor College of Medicine5, Howard Hughes Medical Institute6, University of Washington7, Ludwig Institute for Cancer Research8, University of California, San Francisco9, University of Connecticut10, University of Zagreb11, University of Texas at Austin12, Washington University in St. Louis13, University of Queensland14, Harvard University15, Cold Spring Harbor Laboratory16, University of Southern California17, University of California, Santa Cruz18, Simon Fraser University19, Morgridge Institute for Research20, University of Texas at Dallas21, National Institutes of Health22
TL;DR: It is shown that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease.
Abstract: The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.
5,037 citations
TL;DR: Enrichr is an easy to use intuitive enrichment analysis web-based tool providing various types of visualization summaries of collective functions of gene lists, and can be embedded into any tool that performs gene list analysis.
Abstract: System-wide profiling of genes and proteins in mammalian cells produce lists of differentially expressed genes/proteins that need to be further analyzed for their collective functions in order to extract new knowledge. Once unbiased lists of genes or proteins are generated from such experiments, these lists are used as input for computing enrichment with existing lists created from prior knowledge organized into gene-set libraries. While many enrichment analysis tools and gene-set libraries databases have been developed, there is still room for improvement. Here, we present Enrichr, an integrative web-based and mobile software application that includes new gene-set libraries, an alternative approach to rank enriched terms, and various interactive visualization approaches to display enrichment results using the JavaScript library, Data Driven Documents (D3). The software can also be embedded into any tool that performs gene list analysis. We applied Enrichr to analyze nine cancer cell lines by comparing their enrichment signatures to the enrichment signatures of matched normal tissues. We observed a common pattern of up regulation of the polycomb group PRC2 and enrichment for the histone mark H3K27me3 in many cancer cell lines, as well as alterations in Toll-like receptor and interlukin signaling in K562 cells when compared with normal myeloid CD33+ cells. Such analyses provide global visualization of critical differences between normal tissues and cancer cell lines but can be applied to many other scenarios. Enrichr is an easy to use intuitive enrichment analysis web-based tool providing various types of visualization summaries of collective functions of gene lists. Enrichr is open source and freely available online at: http://amp.pharm.mssm.edu/Enrichr
.
4,713 citations
TL;DR: The landscape of gene expression across tissues is described, thousands of tissue-specific and shared regulatory expression quantitative trait loci (eQTL) variants are cataloged, complex network relationships are described, and signals from genome-wide association studies explained by eQTLs are identified.
Abstract: Understanding the functional consequences of genetic variation, and how it affects complex human disease and quantitative traits, remains a critical challenge for biomedicine. We present an analysi...
4,418 citations
01 Feb 2015
TL;DR: In this article, the authors describe the integrative analysis of 111 reference human epigenomes generated as part of the NIH Roadmap Epigenomics Consortium, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression.
Abstract: The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.
4,409 citations
TL;DR: An update to the Galaxy-based web server deepTools, which allows users to perform complete bioinformatic workflows ranging from quality controls and normalizations of aligned reads to integrative analyses, including clustering and visualization approaches, is presented.
Abstract: We present an update to our Galaxy-based web server for processing and visualizing deeply sequenced data. Its core tool set, deepTools, allows users to perform complete bioinformatic workflows ranging from quality controls and normalizations of aligned reads to integrative analyses, including clustering and visualization approaches. Since we first described our deepTools Galaxy server in 2014, we have implemented new solutions for many requests from the community and our users. Here, we introduce significant enhancements and new tools to further improve data visualization and interpretation. deepTools continue to be open to all users and freely available as a web service at deeptools.ie-freiburg.mpg.de The new deepTools2 suite can be easily deployed within any Galaxy framework via the toolshed repository, and we also provide source code for command line usage under Linux and Mac OS X. A public and documented API for access to deepTools functionality is also available.
4,359 citations