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 PMID:27703156  

Genome-wide compendium and functional assessment of in vivo heart enhancers.

Diane E Dickel | Iros Barozzi | Yiwen Zhu | Yoko Fukuda-Yuzawa | Marco Osterwalder | Brandon J Mannion | Dalit May | Cailyn H Spurrell | Ingrid Plajzer-Frick | Catherine S Pickle | Elizabeth Lee | Tyler H Garvin | Momoe Kato | Jennifer A Akiyama | Veena Afzal | Ah Young Lee | David U Gorkin | Bing Ren | Edward M Rubin | Axel Visel | Len A Pennacchio
Nature communications | 2016

Whole-genome sequencing is identifying growing numbers of non-coding variants in human disease studies, but the lack of accurate functional annotations prevents their interpretation. We describe the genome-wide landscape of distant-acting enhancers active in the developing and adult human heart, an organ whose impairment is a predominant cause of mortality and morbidity. Using integrative analysis of >35 epigenomic data sets from mouse and human pre- and postnatal hearts we created a comprehensive reference of >80,000 putative human heart enhancers. To illustrate the importance of enhancers in the regulation of genes involved in heart disease, we deleted the mouse orthologs of two human enhancers near cardiac myosin genes. In both cases, we observe in vivo expression changes and cardiac phenotypes consistent with human heart disease. Our study provides a comprehensive catalogue of human heart enhancers for use in clinical whole-genome sequencing studies and highlights the importance of enhancers for cardiac function.

Pubmed ID: 27703156

Associated grants

  • Agency: NHGRI NIH HHS, United States
    Id: R01 HG003988
  • Agency: NIDDK NIH HHS, United States
    Id: U24 DK092993
  • Agency: NIGMS NIH HHS, United States
    Id: K12 GM068524
  • Agency: NIDCR NIH HHS, United States
    Id: U01 DE024427
  • Agency: NCRR NIH HHS, United States
    Id: S10 RR029668
  • Agency: NCRR NIH HHS, United States
    Id: S10 RR027303
  • Agency: NHLBI NIH HHS, United States
    Id: UM1 HL098166
  • Agency: NHGRI NIH HHS, United States
    Id: U54 HG006997
  • Agency: NHLBI NIH HHS, United States
    Id: R24 HL123879

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This is a list of tools and resources that we have found mentioned in this publication.


VISTA Enhancer Browser (tool)

RRID:SCR_007973

Resource for experimentally validated human and mouse noncoding fragments with gene enhancer activity as assessed in transgenic mice. Most of these noncoding elements were selected for testing based on their extreme conservation in other vertebrates or epigenomic evidence (ChIP-Seq) of putative enhancer marks. Central public database of experimentally validated human and mouse noncoding fragments with gene enhancer activity as assessed in transgenic mice. Users can retrieve elements near single genes of interest, search for enhancers that target reporter gene expression to particular tissue, or download entire collections of enhancers with defined tissue specificity or conservation depth.

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International HapMap Project (tool)

RRID:SCR_002846

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. A multi-country collaboration among scientists and funding agencies to develop a public resource where genetic similarities and differences in human beings are identified and catalogued. Using this information, researchers will be able to find genes that affect health, disease, and individual responses to medications and environmental factors. All of the information generated by the Project will be released into the public domain. Their goal is to compare the genetic sequences of different individuals to identify chromosomal regions where genetic variants are shared. Public and private organizations in six countries are participating in the International HapMap Project. Data generated by the Project can be downloaded with minimal constraints. HapMap project related data, software, and documentation include: bulk data on genotypes, frequencies, LD data, phasing data, allocated SNPs, recombination rates and hotspots, SNP assays, Perlegen amplicons, raw data, inferred genotypes, and mitochondrial and chrY haplogroups; Generic Genome Browser software; protocols and information on assay design, genotyping and other protocols used in the project; and documentation of samples/individuals and the XML format used in the project.

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American Heart Association (tool)

RRID:SCR_007210

The American Heart Association (AHA) publishes medical scientific statements on various cardiovascular disease and stroke topics. AHA volunteer scientists and healthcare professionals write the papers. The statements are supported by scientific studies published in recognized journals and have a rigorous review and approval process. Scientific statements generally include a review of data available on a specific subject, an evaluation on its relationship to overall cardiovascular disease science, and often an American Heart Association position on the basis of that evaluation. The American Heart Association sponsors accredited scientific conferences and professional development seminars to disseminate new and emerging scientific knowledge and stimulate discussion on future research and the application of knowledge. Keywords: Heart, Cardiovascular, Disease, Stroke, Volunteer, Scientist, Healthcare, Development, Knowledge,

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A statistical framework for genomic data fusion (tool)

RRID:SCR_007219

A statistical framework for genomic data fusion is a computational framework for integrating and drawing inferences from a collection of genome-wide measurements. Each dataset is represented via a kernel function, which defines generalized similarity relationships between pairs of entities, such as genes or proteins. The kernel representation is both flexible and efficient, and can be applied to many different types of data. Furthermore, kernel functions derived from different types of data can be combined in a straightforward fashion. Recent advances in the theory of kernel methods have provided efficient algorithms to perform such combinations in a way that minimizes a statistical loss function. These methods exploit semidefinite programming techniques to reduce the problem of finding optimizing kernel combinations to a convex optimization problem. Computational experiments performed using yeast genome-wide datasets, including amino acid sequences, hydropathy profiles, gene expression data and known protein-protein interactions, demonstrate the utility of this approach. A statistical learning algorithm trained from all of these data to recognize particular classes of proteins--membrane proteins and ribosomal proteins--performs significantly better than the same algorithm trained on any single type of data. Matlab code to center a kernel matrix and Matlab code for normalization are available.

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Ambion Inc. (tool)

RRID:SCR_008406

A division of Applied Biosystems selling products for the isolation, detection, quantification, amplification, and characterization of RNA.

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MMPC-University of California Davis (tool)

RRID:SCR_015357

Center that provides the scientific community with metabolic and physiologic phenotyping tests, services, and procedures for mouse models of diabetes, diabetic complications, obesity and related disorders in order to advance medical and biological research.

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RefSeq (tool)

RRID:SCR_003496

Collection of curated, non-redundant genomic DNA, transcript RNA, and protein sequences produced by NCBI. Provides a reference for genome annotation, gene identification and characterization, mutation and polymorphism analysis, expression studies, and comparative analyses. Accessed through the Nucleotide and Protein databases.

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Bowtie (tool)

RRID:SCR_005476

Software ultrafast memory efficient tool for aligning sequencing reads. Bowtie is short read aligner.

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HTSeq (tool)

RRID:SCR_005514

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software Python package that provides infrastructure to process data from high-throughput sequencing assays. While the main purpose of HTSeq is to allow you to write your own analysis scripts, customized to your needs, there are also a couple of stand-alone scripts for common tasks that can be used without any Python knowledge.

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Suite of Nucleotide Analysis Programs (tool)

RRID:SCR_009399

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone., documented September 29, 2016. A workbench tool to make existing population genetic software more accessible and to facilitate the integration of new tools for analyzing patterns of DNA sequence variation, within a phylogenetic context. Collectively, SNAP tools can serve as a bridge between theoretical and applied population genetic analysis. The exploration of DNA sequence variation for making inferences on evolutionary processes in populations requires the coordinated implementation of a Suite of Nucleotide Analysis Programs (SNAP), each bound by specific assumptions and limitations.

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HOMER (tool)

RRID:SCR_010881

Software tools for Motif Discovery and next-gen sequencing analysis. Used for analyzing ChIP-Seq, GRO-Seq, RNA-Seq, DNase-Seq, Hi-C and numerous other types of functional genomics sequencing data sets. Collection of command line programs for unix style operating systems written in Perl and C++.

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edgeR (tool)

RRID:SCR_012802

Bioconductor software package for Empirical analysis of Digital Gene Expression data in R. Used for differential expression analysis of RNA-seq and digital gene expression data with biological replication.

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MACS (tool)

RRID:SCR_013291

Software Python package for identifying transcript factor binding sites. Used to evaluate significance of enriched ChIP regions. Improves spatial resolution of binding sites through combining information of both sequencing tag position and orientation. Can be used for ChIP-Seq data alone, or with control sample with increase of specificity.

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Cufflinks (tool)

RRID:SCR_014597

Software tool for transcriptome assembly and differential expression analysis for RNA-Seq. Includes script called cuffmerge that can be used to merge together several Cufflinks assemblies. It also handles running Cuffcompare as well as automatically filtering a number of transfrags that are likely to be artifacts. If the researcher has a reference GTF file, the researcher can provide it to the script to more effectively merge novel isoforms and maximize overall assembly quality.

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Visual Statistics Group (tool)

RRID:SCR_008317

The general goal is to achieve a deeper understanding of natural image statistics because from this knowledge it should be possible to explain the behavior of the visual cortex and propose new alternatives in a number of applications in image processing and computer vision in which the basic problem is the choice of an appropriate signal representation. The range of basic and applied topics in which we are currently working include: * Mathematical models of human vision * Statistical image models * Image distortion metrics * Image coding * Motion estimation * Video coding * Image restoration * Color representation

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C57BL/6J (tool)

RRID:IMSR_JAX:000664

Mus musculus with name C57BL/6J from IMSR.

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