Assessing characteristics of RNA amplification methods for single cell RNA sequencing

被引:23
作者
Dueck, Hannah R. [2 ]
Ai, Rizi [3 ]
Camarena, Adrian [4 ]
Ding, Bo [3 ]
Dominguez, Reymundo [5 ]
Evgrafov, Oleg V. [4 ]
Fan, Jian-Bing [6 ]
Fisher, Stephen A. [1 ]
Herstein, Jennifer S. [4 ]
Kim, Tae Kyung [7 ,8 ]
Kim, Jae Mun [4 ]
Lin, Ming-Yi [5 ]
Liu, Rui
Mack, William J. [10 ]
McGroty, Sean [1 ]
Nguyen, Joseph D.
Salathia, Neeraj
Shallcross, Jamie [1 ]
Souaiaia, Tade [4 ]
Spaethling, Jennifer M. [7 ]
Walker, Christopher P. [4 ]
Wang, Jinhui [7 ]
Wang, Kai [4 ]
Wang, Wei [3 ]
Wildberg, Andre [3 ]
Zheng, Lina [3 ]
Chow, Robert H. [5 ]
Eberwine, James
Knowles, James A. [4 ]
Zhang, Kun [9 ]
Kim, Junhyong [1 ]
机构
[1] Univ Penn, Dept Biol, 415 S Univ Ave, Philadelphia, PA 19104 USA
[2] Univ Penn, Perelman Sch Med, Dept Genom & Computat Biol, Philadelphia, PA 19104 USA
[3] Univ Calif San Diego, Dept Chem & Biochem, La Jolla, CA 92093 USA
[4] Univ Southern Calif, Keck Sch Med, Dept Psychiat & Behav Sci, Los Angeles, CA 90033 USA
[5] Univ Southern Calif, Zilkha Neurogenet Inst, Dept Physiol & Biophys, Los Angeles, CA USA
[6] Illumina Inc, San Diego, CA USA
[7] Univ Penn, Perelman Sch Med, Dept Pharmacol, Philadelphia, PA 19104 USA
[8] Allen Inst Brain Sci, Seattle, WA USA
[9] Univ Calif San Diego, Dept Bioengn, La Jolla, CA 92093 USA
[10] Univ Southern Calif, Zilkha Neurogenet Inst, Dept Neurol Surg, Los Angeles, CA USA
基金
美国国家科学基金会;
关键词
Single-cell RNA-sequencing; Biotechnology; Bioinformatics; Genomics; MONOALLELIC GENE-EXPRESSION; SEQ; NOISE;
D O I
10.1186/s12864-016-3300-3
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
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 similar to 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.
引用
收藏
页数:22
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