Biology subjects

Aviv Regev

Publications and source records attributed to Aviv Regev.

5 recordsLinked to original sources

bioRxiv2016

Landscape of X chromosome inactivation across human tissues

X chromosome inactivation (XCI) silences the transcription from one of the two X chromosomes in mammalian female cells to balance expression dosage between XX females and XY males. XCI is, however, characteristically incomplete in humans: up to one third of X-chromosomal genes are expressed from both the active and inactive X chromosomes (Xa and Xi, respectively) in female cells, with the degree of \"escape\" from inactivation varying between genes and individuals1,2 (Fig. 1). However, the extent to which XCI is shared between cells and tissues remains poorly characterized3,4, as does the degree to which incomplete XCI manifests as detectable sex differences in gene expression5 and phenotypic traits6. Here we report a systematic survey of XCI using a combination of over 5,500 transcriptomes from 449 individuals spanning 29 tissues, and 940 single-cell transcriptomes, integrated with genomic sequence data (Fig. 1). By combining information across these data types we show that XCI at the 683 X-chromosomal genes assessed is generally uniform across human tissues, but identify examples of heterogeneity between tissues, individuals and cells. We show that incomplete XCI affects at least 23% of X-chromosomal genes, identify seven new escape genes supported by multiple lines of evidence, and demonstrate that escape from XCI results in sex biases in gene expression, thus establishing incomplete XCI as a likely mechanism introducing phenotypic diversity6,7. Overall, this updated catalogue of XCI across human tissues informs our understanding of the extent and impact of the incompleteness in the maintenance of XCI.\n\nO_FIG O_LINKSMALLFIG WIDTH=114 HEIGHT=200 SRC=\"FIGDIR/small/073957_fig1.gif\" ALT=\"Figure 1\">\nView larger version (33K):\norg.highwire.dtl.DTLVardef@1c902f7org.highwire.dtl.DTLVardef@1e1b14dorg.highwire.dtl.DTLVardef@3f56feorg.highwire.dtl.DTLVardef@687c65_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO Schematic overview of the study. Previous expression-based surveys of XCI1,2 have established the incomplete and variable nature of XCI, showing that XCI is incomplete for up to 30% of X-chromosomal genes, but these studies have been limited in the tissue types and samples assessed. To investigate the landscape of XCI across human tissues, we combined three approaches: 1) sex-biases in expression using population-level GTEx data across 29 tissue types, 2) allelic expression in 16 tissue samples from a female GTEx donor with fully skewed XCI, and 3) validation using single cell RNA-seq by combining allelic expression and genotype phasing. WGS, whole genome sequencing; WES, whole exome sequencing; scRNA-seq, single-cell RNA-seq.\n\nC_FIG

Genomics↗

bioRxiv2016

C2c2 is a single-component programmable RNA-guided RNA-targeting CRISPR effector

The CRISPR-Cas adaptive immune system defends microbes against foreign genetic elements via DNA or RNA-DNA interference. We characterize the Class 2 type VI-A CRISPR-Caseffector C2c2 and demonstrate its RNA-guided RNase function. C2c2 from the bacterium Leptotrichia shahii provides interference against RNA phage.In vitro biochemical analysis show that C2c2 is guided by a single crRNA and can be programmed to cleave ssRNA targets carrying complementary protospacers. In bacteria, C2c2 can be programmed to knock down specific mRNAs. Cleavage is mediated by catalytic residues in the two conserved HEPN domains, mutations in which generate catalytically inactive RNA-binding proteins. These results broaden our understanding of CRISPR-Cas systems and suggest that C2c2 can be used to develop new RNA-targeting tools.

Molecular Biology↗

bioRxiv2016

High-resolution interrogation of functional elements in the noncoding genome

The noncoding genome plays a major role in gene regulation and disease yet we lack tools for rapid identification and manipulation of noncoding elements. Here, we develop a large-scale CRISPR screen employing ~18,000 sgRNAs targeting >700 kb of noncoding sequence in an unbiased manner surrounding three genes (NF1, NF2, and CUL3) involved in resistance to the BRAF inhibitor vemurafenib in the BRAF-mutant melanoma cell line A375. We identify specific noncoding locations near genes that modulate drug resistance when mutated. These sites have predictive hallmarks of noncoding function, such as physical interaction with gene promoters, evolutionary conservation and tissue-specific chromatin accessibility. At a subset of identified elements at the CUL3 locus, we show that engineered mutations lead to a loss of gene expression associated with changes in transcription factor occupancy and in long-range and local epigenetic environments, implicating these sites in gene regulation and chemotherapeutic resistance. This demonstration of an unbiased mutagenesis screen across large noncoding regions expands the potential of pooled CRISPR screens for fundamental genomic discovery and for elucidating biologically relevant mechanisms of gene regulation.

Molecular Biology↗

bioRxiv2016

Div-Seq: A single nucleus RNA-Seq method reveals dynamics of rare adult newborn neurons in the CNS

Transcriptomes of individual neurons provide rich information about cell types and dynamic states. However, it is difficult to capture rare dynamic processes, such as adult neurogenesis, because isolation from dense adult tissue is challenging, and markers for each phase are limited. Here, we developed Div-Seq, which combines Nuc-Seq, a scalable single nucleus RNA-Seq method, with EdU-mediated labeling of proliferating cells. We first show that Nuc-Seq can sensitively identify closely related cell types within the adult hippocampus. We apply Div-Seq to track transcriptional dynamics of newborn neurons in an adult neurogenic region in the hippocampus. Finally, we find rare adult newborn GABAergic neurons in the spinal cord, a non-canonical neurogenic region. Taken together, Nuc-Seq and Div-Seq open the way for unbiased analysis of any complex tissue.

Neuroscience↗

bioRxiv2015

Evolutionary analysis across mammals reveals distinct classes of long noncoding RNAs

BACKGROUNDRecent advances in transcriptome sequencing have enabled the discovery of thousands of long non-coding RNAs (lncRNAs) across multitudes of species. Though several lncRNAs have been shown to play important roles in diverse biological processes, the functions and mechanisms of most lncRNAs remain unknown. Two significant obstacles lie between transcriptome sequencing and functional characterization of lncRNAs: 1) identifying truly noncoding genes from de novo reconstructed transcriptomes, and 2) prioritizing hundreds of resulting putative lncRNAs from each sample for downstream experimental interrogation.\n\nRESULTSWe present slnckv, a computational lncRNA discovery tool that produces a high-quality set of lncRNAs from RNA-Sequencing data and further prioritizes lncRNAs by characterizing selective constraint as a proxy for function. Our filtering pipeline is comparable to manual curation efforts and more sensitive than previously published approaches. Further, we develop, for the first time, a sensitive alignment pipeline for aligning lncRNA loci and propose new evolutionary metrics relevant for both sequence and transcript evolution. Our analysis reveals that selection acts in several distinct patterns, and uncovers two notable classes of lncRNAs: one showing strong purifying selection at RNA sequence and another where constraint is restricted to the regulation but not the sequence of the transcript.\n\nCONCLUSIONOur novel comparative methods for lncRNAs reveals 233 constrained lncRNAs out of tens of thousands of currently annotated transcripts, which we believe should be prioritized for further interrogation. To aid in their analysis we provide the slncky Evolution Browser as a resource for experimentalists.

Evolutionary Biology↗