Author
Elizabeth L. Wilder
Bio: Elizabeth L. Wilder is an academic researcher from National Institutes of Health. The author has contributed to research in topics: Epigenome & Variety (cybernetics). The author has an hindex of 8, co-authored 12 publications receiving 5043 citations.
Papers
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Drexel University1, Yeshiva University2, Roswell Park Cancer Institute3, Virginia Commonwealth University4, Van Andel Institute5, Science Applications International Corporation6, Massachusetts Institute of Technology7, Harvard University8, University of Miami9, Icahn School of Medicine at Mount Sinai10, University of Chicago11, Howard Hughes Medical Institute12, University of Geneva13, Stanford University14, University of Oxford15, University of North Carolina at Chapel Hill16, National Institutes of Health17
TL;DR: The Genotype-Tissue Expression (GTEx) project is described, which will establish a resource database and associated tissue bank for the scientific community to study the relationship between genetic variation and gene expression in human tissues.
Abstract: Genome-wide association studies have identified thousands of loci for common diseases, but, for the majority of these, the mechanisms underlying disease susceptibility remain unknown. Most associated variants are not correlated with protein-coding changes, suggesting that polymorphisms in regulatory regions probably contribute to many disease phenotypes. Here we describe the Genotype-Tissue Expression (GTEx) project, which will establish a resource database and associated tissue bank for the scientific community to study the relationship between genetic variation and gene expression in human tissues.
6,545 citations
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TL;DR: Five broad areas are identified that would help propel the field of cellular senescence in tissues and organs forward.
42 citations
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TL;DR: The NIH Roadmap Epigenomics Program was launched to deliver reference epigenomic data from human tissues and cells, develop tools and methods for analyzing the epigenome, discover novel epigenetic marks, develop methods to manipulate the epigenomes, and determine epigenetic contributions to diverse human diseases.
Abstract: The NIH Roadmap Epigenomics Program was launched to deliver reference epigenomic data from human tissues and cells, develop tools and methods for analyzing the epigenome, discover novel epigenetic marks, develop methods to manipulate the epigenome, and determine epigenetic contributions to diverse human diseases. Here, we comment on the outcomes from this program: the scientific contributions made possible by a consortium approach and the challenges, benefits, and lessons learned from this group science effort.
29 citations
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TL;DR: A mechanism for funding biomedical research at NIH that transcends Institute and Center boundaries is bearing fruit and each of the initial Roadmap programs that emerged was designed to achieve defined goals or transition to other sources of support within 10 years.
Abstract: A fundamental challenge facing all institutions of science, including the National Institutes of Health (NIH), is whether their structures and disciplines, inherited from the past, continue to reflect the reality of current science and the needs of future science. Without an explicit process of adaptation to changes that often transcend established scientific structures and disciplines, the risk of missing emerging opportunities grows. This is why, 10 years ago, NIH launched an approach to the support of science that transcended all Institutes and Centers, known as the “NIH Roadmap” ( 1 ). The NIH Director and the Director of each of the NIH Institutes engaged in a broad priority-setting exercise, informed by extramural and intramural NIH scientists, public representatives, and leaders from other government agencies and the private sector. We asked three questions: What are today's most pressing scientific challenges? What are the roadblocks to progress and what must be done to overcome them? Which efforts are beyond the mandate of one or a few institutes, but are the responsibility of NIH as a whole? Each of the initial Roadmap programs that emerged was designed to achieve defined goals or transition to other sources of support within 10 years. As we have reached the 10th anniversary of these programs, a look back is in order.
23 citations
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TL;DR: Almost 4 years ago, one of us (F.S.C.) wrote an Editorial affirming the continued importance of basic research to the National Institutes of Health mission.
Abstract: Almost 4 years ago, one of us (F.S.C.) wrote an Editorial ([ 1 ][1]) affirming the continued importance of basic research to the National Institutes of Health (NIH) mission. The Editorial emphasized that basic scientific discovery is the engine that powers the biomedical enterprise, and NIH
20 citations
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TL;DR: GEPIA (Gene Expression Profiling Interactive Analysis) fills in the gap between cancer genomics big data and the delivery of integrated information to end users, thus helping unleash the value of the current data resources.
Abstract: Tremendous amount of RNA sequencing data have been produced by large consortium projects such as TCGA and GTEx, creating new opportunities for data mining and deeper understanding of gene functions. While certain existing web servers are valuable and widely used, many expression analysis functions needed by experimental biologists are still not adequately addressed by these tools. We introduce GEPIA (Gene Expression Profiling Interactive Analysis), a web-based tool to deliver fast and customizable functionalities based on TCGA and GTEx data. GEPIA provides key interactive and customizable functions including differential expression analysis, profiling plotting, correlation analysis, patient survival analysis, similar gene detection and dimensionality reduction analysis. The comprehensive expression analyses with simple clicking through GEPIA greatly facilitate data mining in wide research areas, scientific discussion and the therapeutic discovery process. GEPIA fills in the gap between cancer genomics big data and the delivery of integrated information to end users, thus helping unleash the value of the current data resources. GEPIA is available at http://gepia.cancer-pku.cn/.
5,980 citations
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TL;DR: This work presents a method named HISAT2 (hierarchical indexing for spliced alignment of transcripts 2) that can align both DNA and RNA sequences using a graph Ferragina Manzini index, and uses it to represent and search an expanded model of the human reference genome.
Abstract: The human reference genome represents only a small number of individuals, which limits its usefulness for genotyping. We present a method named HISAT2 (hierarchical indexing for spliced alignment of transcripts 2) that can align both DNA and RNA sequences using a graph Ferragina Manzini index. We use HISAT2 to represent and search an expanded model of the human reference genome in which over 14.5 million genomic variants in combination with haplotypes are incorporated into the data structure used for searching and alignment. We benchmark HISAT2 using simulated and real datasets to demonstrate that our strategy of representing a population of genomes, together with a fast, memory-efficient search algorithm, provides more detailed and accurate variant analyses than other methods. We apply HISAT2 for HLA typing and DNA fingerprinting; both applications form part of the HISAT-genotype software that enables analysis of haplotype-resolved genes or genomic regions. HISAT-genotype outperforms other computational methods and matches or exceeds the performance of laboratory-based assays. A graph-based genome indexing scheme enables variant-aware alignment of sequences with very low memory requirements.
4,855 citations
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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
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TL;DR: The genome sequence of single cells isolated from brain glioblastomas was examined, which revealed shared chromosomal changes but also extensive transcription variation, including genes related to signaling, which represent potential therapeutic targets.
Abstract: Human cancers are complex ecosystems composed of cells with distinct phenotypes, genotypes, and epigenetic states, but current models do not adequately reflect tumor composition in patients. We used single-cell RNA sequencing (RNA-seq) to profile 430 cells from five primary glioblastomas, which we found to be inherently variable in their expression of diverse transcriptional programs related to oncogenic signaling, proliferation, complement/immune response, and hypoxia. We also observed a continuum of stemness-related expression states that enabled us to identify putative regulators of stemness in vivo. Finally, we show that established glioblastoma subtype classifiers are variably expressed across individual cells within a tumor and demonstrate the potential prognostic implications of such intratumoral heterogeneity. Thus, we reveal previously unappreciated heterogeneity in diverse regulatory programs central to glioblastoma biology, prognosis, and therapy.
3,475 citations