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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.
Afiliación
  • Kim HJ; Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA.
  • Booth G; Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA.
  • Saunders L; Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA.
  • Srivatsan S; Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA.
  • McFaline-Figueroa JL; Department of Biomedical Engineering, Columbia University, New York City, NY, 10027, USA.
  • Trapnell C; Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA. coletrap@uw.edu.
Nat Commun ; 13(1): 2666, 2022 05 13.
Article en En | MEDLINE | ID: mdl-35562344
ABSTRACT
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Perfilación de la Expresión Génica / Análisis de la Célula Individual Idioma: En Revista: Nat Commun Asunto de la revista: BIOLOGIA / CIENCIA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Perfilación de la Expresión Génica / Análisis de la Célula Individual Idioma: En Revista: Nat Commun Asunto de la revista: BIOLOGIA / CIENCIA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos