Assessing characteristics of RNA amplification methods for single cell RNA sequencing

BMC Genomics

Research Article

Rui Liu¹  Kun Zhang¹  Sean McGroty²  Junhyong Kim²  Jamie Shallcross²  Stephen A. Fisher²  Bo Ding³  Andre Wildberg³  Rizi Ai³  Wei Wang³  Lina Zheng³  Hannah R. Dueck⁴  William J. Mack⁵  Jennifer M. Spaethling⁶  Jinhui Wang⁶  James Eberwine⁶  Tae Kyung Kim⁷  Robert H. Chow⁸  Reymundo Dominguez⁸  Ming-Yi Lin⁸  Adrian Camarena⁹  Kai Wang⁹  James A. Knowles⁹  Tade Souaiaia⁹  Jennifer S. Herstein⁹  Oleg V. Evgrafov⁹  Jae Mun (Hugo) Kim⁹  Joseph D. Nguyen⁹  Christopher P. Walker⁹  Neeraj Salathia^1,10  Jian-Bing Fan^1,10 

[1] Department of Bioengineering, University of California at San Diego, La Jolla, CA, USA;Department of Biology, University of Pennsylvania, 415 S. University Ave, 19104, Philadelphia, PA, USA;Department of Chemistry and Biochemistry, University of California at San Diego, La Jolla, CA, USA;Department of Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;Department of Neurological Surgery, Zilkha Neurogenetic Institute, University of Southern California, Los Angeles, CA, USA;Department of Pharmacology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;Department of Pharmacology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;Present address: Allen Institute for Brain Science, Seattle, WA, USA;Department of Physiology & Biophysics, Zilkha Neurogenetic Institute, University of Southern California, Los Angeles, CA, USA;Department of Psychiatry & The Behavioral Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA;Illumina, Inc., San Diego, CA, USA;

关键词: Single-cell RNA-sequencing;    Biotechnology;    Bioinformatics;    Genomics;   

DOI  :  10.1186/s12864-016-3300-3

 received in 2016-05-07, accepted in 2016-11-15,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundRecently, measurement of RNA at single cell resolution has yielded surprising insights. Methods for single-cell RNA sequencing (scRNA-seq) have received considerable attention, but the broad reliability of single cell methods and the factors governing their performance are still poorly known.ResultsHere, we conducted a large-scale control experiment to assess the transfer function of three scRNA-seq methods and factors modulating the function. All three methods detected greater than 70% of the expected number of genes and had a 50% probability of detecting genes with abundance greater than 2 to 4 molecules. Despite the small number of molecules, sequencing depth significantly affected gene detection. While biases in detection and quantification were qualitatively similar across methods, the degree of bias differed, consistent with differences in molecular protocol. Measurement reliability increased with expression level for all methods and we conservatively estimate measurements to be quantitative at an expression level greater than ~5–10 molecules.ConclusionsBased on these extensive control studies, we propose that RNA-seq of single cells has come of age, yielding quantitative biological information.

【 授权许可】

CC BY   
© The Author(s). 2016