Detection of gene cis-regulatory element perturbations in single-cell transcriptomes
Name
journal.pcbi.1008789.pdf
Description
Published version
Size
2.48 MB
Format
Adobe PDF
Checksum (MD5)
d3658ff5f64bca7a644017cc4e279be2
Author(s)
Yeo, Grace Hui Ting
Juez, Oscar
Chen, Qing
Banerjee, Budhaditya
Chu, Lendy
Shen, Max Walt
Sabry, May
Logister, Ive
Sherwood, Richard I.
Gifford, David K
Date Issued
March 2021
Journal
PLoS Computational Biology
Publisher
Public Library of Science (PLoS)
Citation
Yeo, Grace Hui Ting et al. "Detection of gene cis-regulatory element perturbations in single-cell transcriptomes." PLoS Computational Biology 17, 3 (March 2021): e1008789. © 2021 Yeo et al.
Version
Final published version
Abstract
We introduce poly-adenine CRISPR gRNA-based single-cell RNA-sequencing (pAC-Seq), a method that enables the direct observation of guide RNAs (gRNAs) in scRNA-seq. We use pAC-Seq to assess the phenotypic consequences of CRISPR/Cas9 based alterations of gene cis-regulatory regions. We show that pAC-Seq is able to detect cis-regulatory-induced alteration of target gene expression even when biallelic loss of target gene expression occurs in only ~5% of cells. This low rate of biallelic loss significantly increases the number of cells required to detect the consequences of changes to the regulatory genome, but can be ameliorated by transcript-targeted sequencing. Based on our experimental results we model the power to detect regulatory genome induced transcriptomic effects based on the rate of mono/biallelic loss, baseline gene expression, and the number of cells per target gRNA.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Computational and Systems Biology Program
Terms of Use
Creative Commons Attribution 4.0 International license
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DOI of Published Version
https://doi.org/10.1371/journal.pcbi.1008789
