Biology subjects

Aiden, E. L.

Publications and source records attributed to Aiden, E. L..

3 recordsLinked to original sources

bioRxiv2018

EndoC-βH1 multi-genomic profiling defines gene regulatory programs governing human pancreatic β cell identity and function

EndoC-{beta}H1 is emerging as a critical human beta cell model to study the genetic and environmental etiologies of beta cell function, especially in the context of diabetes. Comprehensive knowledge of its molecular landscape is lacking yet required to fully take advantage of this model. Here, we report extensive chromosomal (spectral karyotyping), genetic (genotyping), epigenetic (ChIP-seq, ATAC-seq), chromatin interaction (Hi-C, Pol2 ChIA-PET), and transcriptomic (RNA-seq, miRNA-seq) maps of this cell model. Integrated analyses of these maps define known (e.g., PDX1, ISL1) and putative (e.g., PCSK1, mir-375) beta cell-specific chromatin interactions and transcriptional cis-regulatory networks, and identify allelic effects on cis-regulatory element use and expression.\n\nImportantly, comparative analyses with maps generated in primary human islets/beta cells indicate substantial preservation of chromatin looping, but also highlight chromosomal heterogeneity and fetal genomic signatures in EndoC-{beta}H1. Together, these maps, and an interactive web application we have created for their exploration, provide important tools for the broad community in the design and success of experiments to probe and manipulate the genetic programs governing beta cell identity and (dys)function in diabetes.

genomics↗

bioRxiv2018

The Juicebox Assembly Tools module facilitates de novo assembly of mammalian genomes with chromosome-length scaffolds for under $1000

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 <$1000.

genomics↗

bioRxiv2017

Juicebox.js provides a cloud-based visualization system for Hi-C data

Contact mapping experiments such as Hi-C explore how genomes fold in 3D. Here, we introduce Juicebox.js, a cloud-based web application for exploring the resulting datasets. Like the original Juicebox application, Juicebox.js allows users to zoom in and out of such datasets using an interface similar to Google Earth. Furthermore, Juicebox.js encodes the exact state of the browser in a shareable URL. Creating a public browser for a new Hi-C dataset does not require coding and can be accomplished in under a minute.

bioinformatics↗