Biology subjects

Orkin, S. H.

Publications and source records attributed to Orkin, S. H..

4 recordsLinked to original sources

bioRxiv2018

CRISPR-SURF: Discovering regulatory elements by deconvolution of CRISPR tiling screen data

Tiling screens using CRISPR-Cas technologies provide a powerful approach to map regulatory elements to phenotypes of interest, but computational methods that effectively model these experimental approaches for different CRISPR technologies are not readily available. Here we present CRISPR-SURF, a deconvolution framework to identify functional regulatory regions in the genome from data generated by CRISPR-Cas nuclease, CRISPR interference (CRISPRi), or CRISPR activation (CRISPRa) tiling screens. We validated CRISPR-SURF on previously published and new data, identifying both experimentally validated and new potential regulatory elements. With CRISPR tiling screens now being increasingly used to elucidate the regulatory architecture of the non-coding genome, CRISPRSURF provides a generalizable and accessible solution for the discovery of regulatory elements.

bioinformatics↗

bioRxiv2017

The Polycomb-dependent epigenome controls β-cell dysfunction, dedifferentiation and diabetes

Chromatin is the physical template that stabilizes and specifies transcriptional programs. To date, it remains largely unclear to what extent chromatin machinery contributes to the susceptibility and progression of complex diseases. Here, we combined deep epigenome mapping with single cell transcriptomics to mine for evidence of chromatin dysregulation in type-2 diabetes. We identify two chromatin-state signatures that track the trajectory of {beta}-cell dysfunction in mice and humans: ectopic activation of bivalent Polycomb-domains and a loss of expression at a subclass of highly active domains containing key lineage-defining genes. {beta}-cell specific deletion of Polycomb (Eed/PRC2) triggers parallel transcriptional signatures. Intriguingly, these {beta}-cell Eed-knockouts also exhibit highly penetrant hyperglycemia-independent dedifferentiation indicating that Polycomb dysregulation sensitizes the {beta}-cell for dedifferentiation. These findings provide novel resources for exploring transcriptional and epigenetic control of {beta}-cell (dys)function. They identify PRC2 as necessary for long-term maintenance of {beta}-cell identity. The data suggest a two-hit model for loss of {beta}-cell identity in diabetes and highlight epigenetic therapeutic potential to block dedifferentiation.

genomics↗

bioRxiv2017

Dissecting super-enhancer hierarchy based on chromatin interactions

Recent studies have highlighted super-enhancers (SEs) as important regulatory elements for gene expression, but their intrinsic properties remain incompletely characterized. Through an integrative analysis of Hi-C and ChIP-seq data, we find that a significant fraction of SEs are hierarchically organized, containing both hub and non-hub enhancers. Hub enhancers share similar histone marks with non-hub enhancers, but are distinctly associated with cohesin and CTCF binding sites and disease-associated genetic variants. Genetic ablation of hub enhancers results in profound defects in gene activation and local chromatin landscape. As such, hub enhancers are the major constituents responsible for SE functional and structural organization.

bioinformatics↗

bioRxiv2017

Integrated Computational Guide Design, Execution, And Analysis Of Arrayed And Pooled CRISPR Genome Editing Experiments

CRISPR genome editing experiments offer enormous potential for the evaluation of genomic loci using arrayed single guide RNAs (sgRNAs) or pooled sgRNA libraries. Numerous computational tools are available to help design sgRNAs with optimal on-target efficiency and minimal off-target potential. In addition, computational tools have been developed to analyze deep sequencing data resulting from genome editing experiments. However, these tools are typically developed in isolation and oftentimes not readily translatable into laboratory-based experiments. Here we present a protocol that describes in detail both the computational and benchtop implementation of an arrayed and/or pooled CRISPR genome editing experiment. This protocol provides instructions for sgRNA design with CRISPOR, experimental implementation, and analysis of the resulting high-throughput sequencing data with CRISPResso. This protocol allows for design and execution of arrayed and pooled CRISPR experiments in 4-5 weeks by non-experts as well as computational data analysis in 1-2 days that can be performed by both computational and non-computational biologists alike.

molecular biology↗