Biology subjects

Gersbach, C.

Publications and source records attributed to Gersbach, C..

4 recordsLinked to original sources

bioRxiv2022

Multi-center integrated analysis of non-coding CRISPR screens

The ENCODE Consortiums efforts to annotate non-coding, cis-regulatory elements (CREs) have advanced our understanding of gene regulatory landscapes which play a major role in health and disease. Pooled, non-coding CRISPR screens are a promising approach for systematically investigating gene regulatory mechanisms. Here, the ENCODE Functional Characterization Centers report 109 screens comprising 346,970 individual perturbations across 13.3Mb of the genome, using a variety of methods, readouts, and statistical analyses. Across 332 functionally confirmed CRE-gene links, we identify principles for screening endogenous, non-coding elements for causal regulatory mechanisms. Nearly all CREs show strong evidence of open chromatin, and targeting accessibility peak summits is a critical component of our proposed sgRNA design rules. We provide experimental guidelines to accurately detect CREs with variable, often low, transcriptional effects. We discover a previously undescribed DNA strand-bias for CRISPRi in transcribed regions with implications for screen design and analysis. Benchmarking five screen analysis tools, we find CASA produces the most conservative CRE calls and is robust to artifacts of low-specificity sgRNAs. Together, we provide an accessible data resource, predesigned sgRNAs targeting 3,275,697 ENCODE SCREEN candidate CREs, and screening guidelines to accelerate functional characterization of the non-coding genome.

genomics↗

bioRxiv2021

Genome-wide annotation of gene regulatory elements linked to cell fitness

Noncoding regulatory elements control gene expression and thus govern nearly all biological processes. Epigenomic profiling assays have identified millions of putative regulatory elements, but systematically determining the function of those regulatory elements remains a substantial challenge. Here we adapt CRISPR screening by epigenetic repression to screen all 111,619 putative non-coding regulatory elements defined by open chromatin sites in human K562 leukemia cells for their role in regulating essential cellular processes and proliferation. In an initial screen containing 1,084,704 gRNAs, we implemented an analysis framework to quantify perturbation effects, and nominate 1,108 regulatory elements that strongly impact cell fitness. We tested 8,845 of the primary screen elements in a secondary screen, evaluated their cell-type specificity in a second cancer cell line, and then used a single-cell RNA-seq CRISPR screen to discover 63 connections between distal regulatory elements and target genes. This comprehensive and quantitative genome-wide map of essential gene regulatory elements presents a framework for extensive characterization of noncoding regulatory elements that drive complex cell phenotypes and for prioritizing non-coding genetic variants that may contribute to common traits and disease risk.

genomics↗

bioRxiv2021

Transgenic mice for in vivo epigenome editing with CRISPR-based systems

The discovery, characterization, and adaptation of the RNA-guided clustered regularly interspersed short palindromic repeat (CRISPR)-Cas9 system has greatly increased the ease with which genome and epigenome editing can be performed. Fusion of chromatin-modifying domains to the nuclease-deactivated form of Cas9 (dCas9) has enabled targeted gene activation or repression in both cultured cells and in vivo in animal models. However, delivery of the large dCas9 fusion proteins to target cell types and tissues is an obstacle to widespread adoption of these tools for in vivo studies. Here we describe the generation and validation of two conditional transgenic mouse lines for targeted gene regulation, Rosa26:LSL-dCas9-p300 for gene activation and Rosa26:LSL-dCas9-KRAB for gene repression. Using the dCas9p300 and dCas9KRAB transgenic mice we demonstrate activation or repression of genes in both the brain and liver in vivo, and T cells and fibroblasts ex vivo. We show gene regulation and targeted epigenetic modification with gRNAs targeting either transcriptional start sites (TSS) or distal enhancer elements, as well as corresponding changes to downstream phenotypes. These mouse lines are convenient and valuable tools for facile, temporally controlled, and tissue-restricted epigenome editing and manipulation of gene expression in vivo.

genomics↗

bioRxiv2017

Incomplete MyoD-induced transdifferentiation is associated with chromatin remodeling deficiencies

Our current understanding of cellular transdifferentiation systems is limited. It is oftentimes unknown, at a genome-wide scale, how much transdifferentiated cells differ quantitatively from both the starting cells and the target cells. Focusing on transdifferentiation of primary human skin fibroblasts by forced expression of myogenic transcription factor MyoD, we performed quantitative analyses of gene expression and chromatin accessibility profiles of transdifferentiated cells compared to fibroblasts and myoblasts. In this system, we find that while many of the early muscle marker genes are reprogrammed, global gene expression and accessibility changes are still incomplete when compared to myoblasts. In addition, we find evidence of epigenetic memory in the transdifferentiated cells, with reminiscent features of fibroblasts being visible both in chromatin accessibility and gene expression. Quantitative analyses revealed a continuum of changes in chromatin accessibility induced by MyoD, and a strong correlation between chromatin-remodeling deficiencies and incomplete gene expression reprogramming. Classification analyses identified genetic and epigenetic features that distinguish reprogrammed from non-reprogrammed sites, and suggested ways to potentially improve transdifferentiation efficiency. Our approach for combining gene expression, DNA accessibility, and protein-DNA binding data to quantify and characterize the efficiency of cellular transdifferentiation on a genome-wide scale can be applied to any transdifferentiation system.

genomics↗