Effective detection of variation in single-cell transcriptomes using MATQ-seq

Kuanwei Sheng; Wenjian Cao; Yichi Niu; Qing Deng; Chenghang Zong

doi:10.1038/nmeth.4145

Effective detection of variation in single-cell transcriptomes using MATQ-seq

Nat Methods. 2017 Mar;14(3):267-270. doi: 10.1038/nmeth.4145. Epub 2017 Jan 16.

Authors

Kuanwei Sheng^{1

2}, Wenjian Cao¹, Yichi Niu¹, Qing Deng¹, Chenghang Zong^{1

2

3

4}

Affiliations

¹ Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA.
² Integrative Molecular and Biomedical Sciences Graduate Program, Baylor College of Medicine, Houston, Texas, USA.
³ Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA.
⁴ McNair Medical Institute, Baylor College of Medicine, Houston, Texas, USA.

PMID: 28092691
DOI: 10.1038/nmeth.4145

Abstract

The quantification of transcriptional variation in single cells, particularly within the same cell population, is currently limited by the low sensitivity and high technical noise of single-cell RNA-seq assays. We report multiple annealing and dC-tailing-based quantitative single-cell RNA-seq (MATQ-seq), a highly sensitive and quantitative method for single-cell sequencing of total RNA. By systematically determining technical noise, we show that MATQ-seq captures genuine biological variation between whole transcriptomes of single cells.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Cell Line
Gene Expression Profiling / methods*
Genomics / methods*
HEK293 Cells
High-Throughput Nucleotide Sequencing / methods*
Humans
RNA / genetics*
Sequence Analysis, RNA / methods*
Single-Cell Analysis* / methods
Transcriptome / genetics

Substances

RNA