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Neva C. Durand

Bio: Neva C. Durand is an academic researcher from Baylor College of Medicine. The author has contributed to research in topics: Genome & Chromatin. The author has an hindex of 16, co-authored 33 publications receiving 9987 citations. Previous affiliations of Neva C. Durand include Rice University & Massachusetts Institute of Technology.

Papers
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Journal ArticleDOI
18 Dec 2014-Cell
TL;DR: In situ Hi-C is used to probe the 3D architecture of genomes, constructing haploid and diploid maps of nine cell types, identifying ∼10,000 loops that frequently link promoters and enhancers, correlate with gene activation, and show conservation across cell types and species.

5,945 citations

Journal ArticleDOI
TL;DR: Juicer as mentioned in this paper is an open-source tool for analyzing terabase-scale Hi-C datasets, which allows users without a computational background to transform raw sequence data into normalized contact maps with one click.
Abstract: Hi-C experiments explore the 3D structure of the genome, generating terabases of data to create high-resolution contact maps. Here, we introduce Juicer, an open-source tool for analyzing terabase-scale Hi-C datasets. Juicer allows users without a computational background to transform raw sequence data into normalized contact maps with one click. Juicer produces a hic file containing compressed contact matrices at many resolutions, facilitating visualization and analysis at multiple scales. Structural features, such as loops and domains, are automatically annotated. Juicer is available as open source software at http://aidenlab.org/juicer/.

1,649 citations

Journal ArticleDOI
TL;DR: It is shown that it is possible to disrupt, restore, and move loops and domains using targeted mutations as small as a single base pair at CTCF sites, and it is found that the observed contact domains are inconsistent with the equilibrium state for an ordinary condensed polymer.
Abstract: We recently used in situ Hi-C to create kilobase-resolution 3D maps of mammalian genomes. Here, we combine these maps with new Hi-C, microscopy, and genome-editing experiments to study the physical structure of chromatin fibers, domains, and loops. We find that the observed contact domains are inconsistent with the equilibrium state for an ordinary condensed polymer. Combining Hi-C data and novel mathematical theorems, we show that contact domains are also not consistent with a fractal globule. Instead, we use physical simulations to study two models of genome folding. In one, intermonomer attraction during polymer condensation leads to formation of an anisotropic "tension globule." In the other, CCCTC-binding factor (CTCF) and cohesin act together to extrude unknotted loops during interphase. Both models are consistent with the observed contact domains and with the observation that contact domains tend to form inside loops. However, the extrusion model explains a far wider array of observations, such as why loops tend not to overlap and why the CTCF-binding motifs at pairs of loop anchors lie in the convergent orientation. Finally, we perform 13 genome-editing experiments examining the effect of altering CTCF-binding sites on chromatin folding. The convergent rule correctly predicts the affected loops in every case. Moreover, the extrusion model accurately predicts in silico the 3D maps resulting from each experiment using only the location of CTCF-binding sites in the WT. Thus, we show that it is possible to disrupt, restore, and move loops and domains using targeted mutations as small as a single base pair.

1,390 citations

Journal ArticleDOI
07 Apr 2017-Science
TL;DR: In this paper, the authors combine Hi-C data with existing draft assemblies to generate chromosome-length scaffolds, which are then combined with draft sequences to create genome assemblies of the Aedes aegypti and Culex quinquefasciatus.
Abstract: The Zika outbreak, spread by the Aedes aegypti mosquito, highlights the need to create high-quality assemblies of large genomes in a rapid and cost-effective way. Here we combine Hi-C data with existing draft assemblies to generate chromosome-length scaffolds. We validate this method by assembling a human genome, de novo, from short reads alone (67× coverage). We then combine our method with draft sequences to create genome assemblies of the mosquito disease vectors Ae. aegypti and Culex quinquefasciatus, each consisting of three scaffolds corresponding to the three chromosomes in each species. These assemblies indicate that almost all genomic rearrangements among these species occur within, rather than between, chromosome arms. The genome assembly procedure we describe is fast, inexpensive, and accurate, and can be applied to many species.

1,173 citations

Journal ArticleDOI
TL;DR: Hi-C experiments study how genomes fold in 3D, generating contact maps containing features as small as 20 bp and as large as 200 Mb, and Juicebox, a tool for exploring Hi-C and other contact map data, is introduced.
Abstract: Hi-C experiments study how genomes fold in 3D, generating contact maps containing features as small as 20 bp and as large as 200 Mb. Here we introduce Juicebox, a tool for exploring Hi-C and other contact map data. Juicebox allows users to zoom in and out of Hi-C maps interactively, just as a user of Google Earth might zoom in and out of a geographic map. Maps can be compared to one another, or to 1D tracks or 2D feature sets.

971 citations


Cited by
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01 May 1993
TL;DR: Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems.
Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

29,323 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

01 Jan 2011
TL;DR: The sheer volume and scope of data posed by this flood of data pose a significant challenge to the development of efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data.
Abstract: Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.

2,187 citations

Journal ArticleDOI
TL;DR: Juicer as mentioned in this paper is an open-source tool for analyzing terabase-scale Hi-C datasets, which allows users without a computational background to transform raw sequence data into normalized contact maps with one click.
Abstract: Hi-C experiments explore the 3D structure of the genome, generating terabases of data to create high-resolution contact maps. Here, we introduce Juicer, an open-source tool for analyzing terabase-scale Hi-C datasets. Juicer allows users without a computational background to transform raw sequence data into normalized contact maps with one click. Juicer produces a hic file containing compressed contact matrices at many resolutions, facilitating visualization and analysis at multiple scales. Structural features, such as loops and domains, are automatically annotated. Juicer is available as open source software at http://aidenlab.org/juicer/.

1,649 citations