Abstract
Single-cell RNA sequencing (scRNA-seq) is generally used for profiling transcriptome of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently used scRNA-seq platforms, yet there are only a few thorough and systematic comparisons of their advantages and limitations. Here, by directly comparing the scRNA-seq data generated by these two platforms from the same samples of CD45− cells, we systematically evaluated their features using a wide spectrum of analyses. Smart-seq2 detected more genes in a cell, especially low abundance transcripts as well as alternatively spliced transcripts, but captured higher proportion of mitochondrial genes. The composite of Smart-seq2 data also resembled bulk RNA-seq data more. For 10X-based data, we observed higher noise for mRNAs with low expression levels. Approximately 10%−30% of all detected transcripts by both platforms were from non-coding genes, with long non-coding RNAs (lncRNAs) accounting for a higher proportion in 10X. 10X-based data displayed more severe dropout problem, especially for genes with lower expression levels. However, 10X-data can detect rare cell types given its ability to cover a large number of cells. In addition, each platform detected distinct groups of differentially expressed genes between cell clusters, indicating the different characteristics of these technologies. Our study promotes better understanding of these two platforms and offers the basis for an informed choice of these widely used technologies.
Highlights
Following the first single-cell RNA sequencing method developed in 2009 [1], scRNA-seq has dramatically influenced many research fields ranging from cancer biology, stem cell biology to immunology [2,3,4,5]
Smart-seq2 is based on microtiter plates [10, 11], where mRNA is isolated and reverse transcribed to cDNA for high-throughput sequencing for each cell [12]
We found that the gene expression coefficient of variation (CV) across cells were associated with dropout ratios. 10X had more genes with large CV
Summary
Following the first single-cell RNA sequencing (scRNA-seq) method developed in 2009 [1], scRNA-seq has dramatically influenced many research fields ranging from cancer biology, stem cell biology to immunology [2,3,4,5]. Compared with RNA-seq of bulk tissues with millions of cells, scRNA-seq offers the opportunity to dissect the composition of tissues and the dynamic of transcriptional states, as well as to discover rare cell types. Smart-seq is based on microtiter plates [10, 11], where mRNA is isolated and reverse transcribed to cDNA for high-throughput sequencing for each cell [12]. 10X is a droplet-based scRNA-seq method, allowing genome-wide expression profiling for thousands of cells at once.
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