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Author

Arina D. Omer

Other affiliations: Rice University, Baylor University
Bio: Arina D. Omer is an academic researcher from Baylor College of Medicine. The author has contributed to research in topics: Biology & Medicine. The author has an hindex of 5, co-authored 7 publications receiving 5176 citations. Previous affiliations of Arina D. Omer include Rice University & Baylor University.

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
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

01 Oct 2017
TL;DR: All loop domains are eliminated, but neither compartment domains nor histone marks are affected, and many megabase-sized loops recovered in under an hour, consistent with a model where loop extrusion is rapid.
Abstract: The human genome folds to create thousands of intervals, called "contact domains," that exhibit enhanced contact frequency within themselves. "Loop domains" form because of tethering between two loci-almost always bound by CTCF and cohesin-lying on the same chromosome. "Compartment domains" form when genomic intervals with similar histone marks co-segregate. Here, we explore the effects of degrading cohesin. All loop domains are eliminated, but neither compartment domains nor histone marks are affected. Loss of loop domains does not lead to widespread ectopic gene activation but does affect a significant minority of active genes. In particular, cohesin loss causes superenhancers to co-localize, forming hundreds of links within and across chromosomes and affecting the regulation of nearby genes. We then restore cohesin and monitor the re-formation of each loop. Although re-formation rates vary greatly, many megabase-sized loops recovered in under an hour, consistent with a model where loop extrusion is rapid.

287 citations

Posted ContentDOI
28 Jan 2018-bioRxiv
TL;DR: A new module for Juicebox is introduced, which provides a point-and-click interface for using Hi-C heatmaps to identify and correct errors in a genome assembly, and greatly reduce the cost of accurately assembling complex eukaryotic genomes.
Abstract: Hi-C contact maps are valuable for genome assembly (Lieberman-Aiden, van Berkum et al. 2009; Burton et al. 2013; Dudchenko et al. 2017). Recently, we developed Juicebox, a system for the visual exploration of Hi-C data (Durand, Robinson et al. 2016), and 3D-DNA, an automated pipeline for using Hi-C data to assemble genomes (Dudchenko et al. 2017). Here, we introduce “Assembly Tools,” a new module for Juicebox, which provides a point-and-click interface for using Hi-C heatmaps to identify and correct errors in a genome assembly. Together, 3D-DNA and the Juicebox Assembly Tools greatly reduce the cost of accurately assembling complex eukaryotic genomes. To illustrate, we generated de novo assemblies with chromosome-length scaffolds for three mammals: the wombat, Vombatus ursinus (3.3Gb), the Virginia opossum, Didelphis virginiana (3.3Gb), and the raccoon, Procyon lotor (2.5Gb). The only inputs for each assembly were Illumina reads from a short insert DNA-Seq library (300 million Illumina reads, maximum length 2x150 bases) and an in situ Hi-C library (100 million Illumina reads, maximum read length 2x150 bases), which cost

204 citations

Journal ArticleDOI
01 Feb 2022-Cell
TL;DR: In this paper , the authors show that SARS-CoV-2 infection causes widespread downregulation of olfactory receptors (ORs) and of their signaling components, followed by a dramatic reorganization of the neuronal nuclear architecture, which results in dissipation of genomic compartments harboring OR genes.

124 citations


Cited by
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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: This model produces TADs and finer-scale features of Hi-C data because each TAD emerges from multiple loops dynamically formed through extrusion, contrary to typical illustrations of single static loops.

1,479 citations

Journal ArticleDOI
TL;DR: This work applied HiC-Pro to different Hi-C datasets, demonstrating its ability to easily process large data in a reasonable time and its fast implementation of the iterative correction method.
Abstract: HiC-Pro is an optimized and flexible pipeline for processing Hi-C data from raw reads to normalized contact maps. HiC-Pro maps reads, detects valid ligation products, performs quality controls and generates intra- and inter-chromosomal contact maps. It includes a fast implementation of the iterative correction method and is based on a memory-efficient data format for Hi-C contact maps. In addition, HiC-Pro can use phased genotype data to build allele-specific contact maps. We applied HiC-Pro to different Hi-C datasets, demonstrating its ability to easily process large data in a reasonable time. Source code and documentation are available at http://github.com/nservant/HiC-Pro .

1,444 citations

Journal ArticleDOI
19 Feb 2015-Nature
TL;DR: Mapping genome-wide chromatin interactions in human embryonic stem cells and four human ES-cell-derived lineages reveals extensive chromatin reorganization during lineage specification, providing a global view of chromatin dynamics and a resource for studying long-range control of gene expression in distinct human cell lineages.
Abstract: Higher-order chromatin structure is emerging as an important regulator of gene expression. Although dynamic chromatin structures have been identified in the genome, the full scope of chromatin dynamics during mammalian development and lineage specification remains to be determined. By mapping genome-wide chromatin interactions in human embryonic stem (ES) cells and four human ES-cell-derived lineages, we uncover extensive chromatin reorganization during lineage specification. We observe that although self-associating chromatin domains are stable during differentiation, chromatin interactions both within and between domains change in a striking manner, altering 36% of active and inactive chromosomal compartments throughout the genome. By integrating chromatin interaction maps with haplotype-resolved epigenome and transcriptome data sets, we find widespread allelic bias in gene expression correlated with allele-biased chromatin states of linked promoters and distal enhancers. Our results therefore provide a global view of chromatin dynamics and a resource for studying long-range control of gene expression in distinct human cell lineages.

1,393 citations