Comparison of Single Cell Transcriptome Sequencing Methods: Of Mice and Men

Hornung, Bastian V. H.; Azmani, Zakia; den Dekker, Alexander T.; Oole, Edwin; Ozgur, Zeliha; Brouwer, Rutger W. W.; van den Hout, Mirjam C. G. N.; van IJcken, Wilfred F. J.

doi:10.3390/genes14122226

Open AccessArticle

Comparison of Single Cell Transcriptome Sequencing Methods: Of Mice and Men

by

Bastian V. H. Hornung

^1,2,

Zakia Azmani

^1,2,

Alexander T. den Dekker

^1,2

,

Edwin Oole

^1,2,

Zeliha Ozgur

^1,2,

Rutger W. W. Brouwer

^1,2,

Mirjam C. G. N. van den Hout

^1,2

and

Wilfred F. J. van IJcken

^1,2,*

¹

Department of Cell Biology, Erasmus University Medical Center Rotterdam, Wytemaweg 80, 3015CN Rotterdam, The Netherlands

²

Genomics Core Facility, Erasmus University Medical Center Rotterdam, Wytemaweg 80, 3015CN Rotterdam, The Netherlands

^*

Author to whom correspondence should be addressed.

Genes 2023, 14(12), 2226; https://doi.org/10.3390/genes14122226

Submission received: 31 October 2023 / Revised: 4 December 2023 / Accepted: 13 December 2023 / Published: 16 December 2023

(This article belongs to the Special Issue Computational Analysis of Single-Cell Transcriptome Data)

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Abstract

Single cell RNAseq has been a big leap in many areas of biology. Rather than investigating gene expression on a whole organism level, this technology enables scientists to get a detailed look at rare single cells or within their cell population of interest. The field is growing, and many new methods appear each year. We compared methods utilized in our core facility: Smart-seq3, PlexWell, FLASH-seq, VASA-seq, SORT-seq, 10X, Evercode, and HIVE. We characterized the equipment requirements for each method. We evaluated the performances of these methods based on detected features, transcriptome diversity, mitochondrial RNA abundance and multiplets, among others and benchmarked them against bulk RNA sequencing. Here, we show that bulk transcriptome detects more unique transcripts than any single cell method. While most methods are comparable in many regards, FLASH-seq and VASA-seq yielded the best metrics, e.g., in number of features. If no equipment for automation is available or many cells are desired, then HIVE or 10X yield good results. In general, more recently developed methods perform better. This also leads to the conclusion that older methods should be phased out, and that the development of single cell RNAseq methods is still progressing considerably.

Keywords: single cell sequencing; PlexWell; Smart-Seq3; 10X genomics; FLASH-seq; SORT-seq; VASA-seq; HIVE; transcriptomics; benchmarking

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MDPI and ACS Style

Hornung, B.V.H.; Azmani, Z.; den Dekker, A.T.; Oole, E.; Ozgur, Z.; Brouwer, R.W.W.; van den Hout, M.C.G.N.; van IJcken, W.F.J. Comparison of Single Cell Transcriptome Sequencing Methods: Of Mice and Men. Genes 2023, 14, 2226. https://doi.org/10.3390/genes14122226

AMA Style

Hornung BVH, Azmani Z, den Dekker AT, Oole E, Ozgur Z, Brouwer RWW, van den Hout MCGN, van IJcken WFJ. Comparison of Single Cell Transcriptome Sequencing Methods: Of Mice and Men. Genes. 2023; 14(12):2226. https://doi.org/10.3390/genes14122226

Chicago/Turabian Style

Hornung, Bastian V. H., Zakia Azmani, Alexander T. den Dekker, Edwin Oole, Zeliha Ozgur, Rutger W. W. Brouwer, Mirjam C. G. N. van den Hout, and Wilfred F. J. van IJcken. 2023. "Comparison of Single Cell Transcriptome Sequencing Methods: Of Mice and Men" Genes 14, no. 12: 2226. https://doi.org/10.3390/genes14122226

APA Style

Hornung, B. V. H., Azmani, Z., den Dekker, A. T., Oole, E., Ozgur, Z., Brouwer, R. W. W., van den Hout, M. C. G. N., & van IJcken, W. F. J. (2023). Comparison of Single Cell Transcriptome Sequencing Methods: Of Mice and Men. Genes, 14(12), 2226. https://doi.org/10.3390/genes14122226

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Comparison of Single Cell Transcriptome Sequencing Methods: Of Mice and Men

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