Biology subjects

Cusanovich, D. A.

Publications and source records attributed to Cusanovich, D. A..

3 recordsLinked to original sources

bioRxiv2017

The cis-regulatory dynamics of embryonic development at single cell resolution

Single cell measurements of gene expression are providing new insights into lineage commitment, yet the regulatory changes underlying individual cell trajectories remain elusive. Here, we profiled chromatin accessibility in over 20,000 single nuclei across multiple stages of Drosophila embryogenesis. Our data reveal heterogeneity in the regulatory landscape prior to gastrulation that reflects anatomical position, a feature that aligns with future cell fate. During mid embryogenesis, tissue granularity emerges such that cell types can be inferred by their chromatin accessibility, while maintaining a signature of their germ layer of origin. We identify over 30,000 distal elements with tissue-specific accessibility. Using transgenic embryos, we tested the germ layer specificity of a subset of predicted enhancers, achieving near-perfect accuracy. Overall, these data demonstrate the power of shotgun single cell profiling of embryos to resolve dynamic changes in open chromatin during development, and to uncover the cis-regulatory programs of germ layers and cell types.

genomics↗

bioRxiv2017

Comprehensive single cell transcriptional profiling of a multicellular organism by combinatorial indexing

Conventional methods for profiling the molecular content of biological samples fail to resolve heterogeneity that is present at the level of single cells. In the past few years, single cell RNA sequencing has emerged as a powerful strategy for overcoming this challenge. However, its adoption has been limited by a paucity of methods that are at once simple to implement and cost effective to scale massively. Here, we describe a combinatorial indexing strategy to profile the transcriptomes of large numbers of single cells or single nuclei without requiring the physical isolation of each cell (Single cell Combinatorial Indexing RNA-seq or sci-RNA-seq). We show that sci-RNA-seq can be used to efficiently profile the transcriptomes of tens-of-thousands of single cells per experiment, and demonstrate that we can stratify cell types from these data. Key advantages of sci-RNA-seq over contemporary alternatives such as droplet-based single cell RNA-seq include sublinear cost scaling, a reliance on widely available reagents and equipment, the ability to concurrently process many samples within a single workflow, compatibility with methanol fixation of cells, cell capture based on DNA content rather than cell size, and the flexibility to profile either cells or nuclei. As a demonstration of sci-RNA-seq, we profile the transcriptomes of 42,035 single cells from C. elegans at the L2 stage, effectively 50-fold \"shotgun cellular coverage\" of the somatic cell composition of this organism at this stage. We identify 27 distinct cell types, including rare cell types such as the two distal tip cells of the developing gonad, estimate consensus expression profiles and define cell-type specific and selective genes. Given that C. elegans is the only organism with a fully mapped cellular lineage, these data represent a rich resource for future methods aimed at defining cell types and states. They will advance our understanding of developmental biology, and constitute a major step towards a comprehensive, single-cell molecular atlas of a whole animal.

genomics↗

bioRxiv2016

Paired CRISPR/Cas9 guide-RNAs enable high-throughput deletion scanning (ScanDel) of a Mendelian disease locus for functionally critical non-coding elements

The extent to which distal non-coding mutations contribute to Mendelian disease remains a major unknown in human genetics. Given that a genes in vivo function can be appropriately modeled in vitro, CRISPR/Cas9 genome editing enables the large-scale perturbation of distal non-coding regions to identify functional elements in their native context. However, early attempts at such screens have relied on one individual guide RNA (gRNA) per cell, resulting in sparse mutagenesis with minimal redundancy across regions of interest. To address this, we developed a system that uses pairs of gRNAs to program thousands of kilobase-scale deletions that scan across a targeted region in a tiling fashion (\"ScanDel\"). As a proof-of-concept, we applied ScanDel to program 4,342 overlapping 1- and 2- kilobase (Kb) deletions that tile a 206 Kb region centered on HPRT1, the gene underlying Lesch-Nyhan syndrome, with median 27-fold redundancy per base. Programmed deletions were functionally assayed by selecting for loss of HPRT1 function with 6-thioguanine. HPRT1 exons served as positive controls, and all were successfully identified as functionally critical by the screen. Remarkably, HPRT1 function appeared robust to deletion of any intergenic or deeply intronic non-coding region across the 206 Kb locus, indicating that proximal regulatory sequences are sufficient for its expression. A sparser mutagenesis screen of the same 206 Kb with individual gRNAs also failed to identify critical distal regulatory elements. Although our screen did find programmed deletions and individual gRNAs with putative functional consequences that targeted exon-proximal non-coding sequences (e.g. the promoter), long-read sequencing revealed that this signal was driven almost entirely by rare, unexpected deletions that extended into exonic sequence. These targeted validation experiments defined a small region surrounding the transcriptional start site as the only non-coding sequence essential to HPRT1 function. Overall, our results suggest that distal regulatory elements are not critical for HPRT1 expression, and underscore the necessity of comprehensive edited-locus genotyping for validating the results of CRISPR screens. The application of ScanDel to additional loci will enable more insight into the extent to which the disruption of distal non-coding elements contributes to Mendelian diseases. In addition, dense, redundant, large-scale deletion scanning with gRNA pairs will facilitate a deeper understanding of endogenous gene regulation in the human genome.

genomics↗