Assessing characteristics of RNA amplification methods for single cell RNA sequencing. (December 2016)

• Record Type: Journal Article
• Authors: Dueck, Hannah; Ai, Rizi; Camarena, Adrian; Ding, Bo; Dominguez, Reymundo; Evgrafov, Oleg; Fan, Jian-Bing; Fisher, Stephen; Herstein, Jennifer; Kim, Tae; Kim, Jae; Lin, Ming-Yi; Liu, Rui; Mack, William; McGroty, Sean; Nguyen, Joseph; Salathia, Neeraj; Shallcross, Jamie; Souaiaia, Tade; Spaethling, Jennifer; Walker, Christopher; Wang, Jinhui; Wang, Kai; Wang, Wei; Wildberg, Andre; Zheng, Lina; Chow, Robert; Eberwine, James; Knowles, James; Zhang, Kun; Kim, Junhyong;
• Is Part Of: BMC genomics. Volume 17:Number 1(2016)
• Page Start: 1
• Page End: 22
• Publication Date: 2016-12
• Subjects: Single-cell RNA-sequencing -- Biotechnology -- Bioinformatics -- Genomics; Genomes -- Periodicals; Gene mapping -- Periodicals; Genomics -- Periodicals; Base Sequence -- Periodicals; Chromosome Mapping -- Periodicals; Genetic Techniques -- Periodicals; Sequence Analysis, DNA -- Periodicals; 572.8605
• DOI: 10.1186/s12864-016-3300-3
• Languages: English
• ISSNs: 1471-2164

Abstract

Abstract Background Recently, 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. Results Here, 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. Conclusions Based on these extensive control studies, we propose that RNA-seq of single cells has come of age, yielding quantitative biological information.