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Nuclear oligo hashing improves differential analysis of single-cell RNA-seq

Single-cell RNA sequencing (scRNA-seq) offers a high-resolution molecular view into complex tissues, but suffers from high levels of technical noise which frustrates efforts to compare the gene expression programs of different cell types. “Spike-in” RNA standards help control for technical variation...

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Autores principales: Kim, Hyeon-Jin, Booth, Greg, Saunders, Lauren, Srivatsan, Sanjay, McFaline-Figueroa, José L., Trapnell, Cole
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9106741/
https://www.ncbi.nlm.nih.gov/pubmed/35562344
http://dx.doi.org/10.1038/s41467-022-30309-4
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author Kim, Hyeon-Jin
Booth, Greg
Saunders, Lauren
Srivatsan, Sanjay
McFaline-Figueroa, José L.
Trapnell, Cole
author_facet Kim, Hyeon-Jin
Booth, Greg
Saunders, Lauren
Srivatsan, Sanjay
McFaline-Figueroa, José L.
Trapnell, Cole
author_sort Kim, Hyeon-Jin
collection PubMed
description Single-cell RNA sequencing (scRNA-seq) offers a high-resolution molecular view into complex tissues, but suffers from high levels of technical noise which frustrates efforts to compare the gene expression programs of different cell types. “Spike-in” RNA standards help control for technical variation in scRNA-seq, but using them with recently developed, ultra-scalable scRNA-seq methods based on combinatorial indexing is not feasible. Here, we describe a simple and cost-effective method for normalizing transcript counts and subtracting technical variability that improves differential expression analysis in scRNA-seq. The method affixes a ladder of synthetic single-stranded DNA oligos to each cell that appears in its RNA-seq library. With improved normalization we explore chemical perturbations with broad or highly specific effects on gene regulation, including RNA pol II elongation, histone deacetylation, and activation of the glucocorticoid receptor. Our methods reveal that inhibiting histone deacetylation prevents cells from executing their canonical program of changes following glucocorticoid stimulation.
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spelling pubmed-91067412022-05-15 Nuclear oligo hashing improves differential analysis of single-cell RNA-seq Kim, Hyeon-Jin Booth, Greg Saunders, Lauren Srivatsan, Sanjay McFaline-Figueroa, José L. Trapnell, Cole Nat Commun Article Single-cell RNA sequencing (scRNA-seq) offers a high-resolution molecular view into complex tissues, but suffers from high levels of technical noise which frustrates efforts to compare the gene expression programs of different cell types. “Spike-in” RNA standards help control for technical variation in scRNA-seq, but using them with recently developed, ultra-scalable scRNA-seq methods based on combinatorial indexing is not feasible. Here, we describe a simple and cost-effective method for normalizing transcript counts and subtracting technical variability that improves differential expression analysis in scRNA-seq. The method affixes a ladder of synthetic single-stranded DNA oligos to each cell that appears in its RNA-seq library. With improved normalization we explore chemical perturbations with broad or highly specific effects on gene regulation, including RNA pol II elongation, histone deacetylation, and activation of the glucocorticoid receptor. Our methods reveal that inhibiting histone deacetylation prevents cells from executing their canonical program of changes following glucocorticoid stimulation. Nature Publishing Group UK 2022-05-13 /pmc/articles/PMC9106741/ /pubmed/35562344 http://dx.doi.org/10.1038/s41467-022-30309-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Kim, Hyeon-Jin
Booth, Greg
Saunders, Lauren
Srivatsan, Sanjay
McFaline-Figueroa, José L.
Trapnell, Cole
Nuclear oligo hashing improves differential analysis of single-cell RNA-seq
title Nuclear oligo hashing improves differential analysis of single-cell RNA-seq
title_full Nuclear oligo hashing improves differential analysis of single-cell RNA-seq
title_fullStr Nuclear oligo hashing improves differential analysis of single-cell RNA-seq
title_full_unstemmed Nuclear oligo hashing improves differential analysis of single-cell RNA-seq
title_short Nuclear oligo hashing improves differential analysis of single-cell RNA-seq
title_sort nuclear oligo hashing improves differential analysis of single-cell rna-seq
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9106741/
https://www.ncbi.nlm.nih.gov/pubmed/35562344
http://dx.doi.org/10.1038/s41467-022-30309-4
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