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Benchmarking full-length transcript single cell mRNA sequencing protocols

BACKGROUND: Single cell mRNA sequencing technologies have transformed our understanding of cellular heterogeneity and identity. For sensitive discovery or clinical marker estimation where high transcript capture per cell is needed only plate-based techniques currently offer sufficient resolution. RE...

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Autores principales: Probst, Victoria, Simonyan, Arman, Pacheco, Felix, Guo, Yuliu, Nielsen, Finn Cilius, Bagger, Frederik Otzen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9801581/
https://www.ncbi.nlm.nih.gov/pubmed/36581800
http://dx.doi.org/10.1186/s12864-022-09014-5
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author Probst, Victoria
Simonyan, Arman
Pacheco, Felix
Guo, Yuliu
Nielsen, Finn Cilius
Bagger, Frederik Otzen
author_facet Probst, Victoria
Simonyan, Arman
Pacheco, Felix
Guo, Yuliu
Nielsen, Finn Cilius
Bagger, Frederik Otzen
author_sort Probst, Victoria
collection PubMed
description BACKGROUND: Single cell mRNA sequencing technologies have transformed our understanding of cellular heterogeneity and identity. For sensitive discovery or clinical marker estimation where high transcript capture per cell is needed only plate-based techniques currently offer sufficient resolution. RESULTS: Here, we present a performance evaluation of four different plate-based scRNA-seq protocols. Our evaluation is aimed towards applications taxing high gene detection sensitivity, reproducibility between samples, and minimum hands-on time, as is required, for example, in clinical use. We included two commercial kits, NEBNext® Single Cell/ Low Input RNA Library Prep Kit (NEB®), SMART-seq® HT kit (Takara®), and the non-commercial protocols Genome & Transcriptome sequencing (G&T) and SMART-seq3 (SS3). G&T delivered the highest detection of genes per single cell. SS3 presented the highest gene detection per single cell at the lowest price. Takara® kit presented similar high gene detection per single cell, and high reproducibility between samples, but at the absolute highest price. NEB® delivered a lower detection of genes but remains an alternative to more expensive commercial kits. CONCLUSION: For the tested kits we found that ease-of-use came at higher prices. Takara can be selected for its ease-of-use to analyse a few samples, but we recommend the cheaper G&T-seq or SS3 for laboratories where a substantial sample flow can be expected. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-022-09014-5.
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spelling pubmed-98015812022-12-31 Benchmarking full-length transcript single cell mRNA sequencing protocols Probst, Victoria Simonyan, Arman Pacheco, Felix Guo, Yuliu Nielsen, Finn Cilius Bagger, Frederik Otzen BMC Genomics Research Article BACKGROUND: Single cell mRNA sequencing technologies have transformed our understanding of cellular heterogeneity and identity. For sensitive discovery or clinical marker estimation where high transcript capture per cell is needed only plate-based techniques currently offer sufficient resolution. RESULTS: Here, we present a performance evaluation of four different plate-based scRNA-seq protocols. Our evaluation is aimed towards applications taxing high gene detection sensitivity, reproducibility between samples, and minimum hands-on time, as is required, for example, in clinical use. We included two commercial kits, NEBNext® Single Cell/ Low Input RNA Library Prep Kit (NEB®), SMART-seq® HT kit (Takara®), and the non-commercial protocols Genome & Transcriptome sequencing (G&T) and SMART-seq3 (SS3). G&T delivered the highest detection of genes per single cell. SS3 presented the highest gene detection per single cell at the lowest price. Takara® kit presented similar high gene detection per single cell, and high reproducibility between samples, but at the absolute highest price. NEB® delivered a lower detection of genes but remains an alternative to more expensive commercial kits. CONCLUSION: For the tested kits we found that ease-of-use came at higher prices. Takara can be selected for its ease-of-use to analyse a few samples, but we recommend the cheaper G&T-seq or SS3 for laboratories where a substantial sample flow can be expected. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-022-09014-5. BioMed Central 2022-12-29 /pmc/articles/PMC9801581/ /pubmed/36581800 http://dx.doi.org/10.1186/s12864-022-09014-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Probst, Victoria
Simonyan, Arman
Pacheco, Felix
Guo, Yuliu
Nielsen, Finn Cilius
Bagger, Frederik Otzen
Benchmarking full-length transcript single cell mRNA sequencing protocols
title Benchmarking full-length transcript single cell mRNA sequencing protocols
title_full Benchmarking full-length transcript single cell mRNA sequencing protocols
title_fullStr Benchmarking full-length transcript single cell mRNA sequencing protocols
title_full_unstemmed Benchmarking full-length transcript single cell mRNA sequencing protocols
title_short Benchmarking full-length transcript single cell mRNA sequencing protocols
title_sort benchmarking full-length transcript single cell mrna sequencing protocols
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9801581/
https://www.ncbi.nlm.nih.gov/pubmed/36581800
http://dx.doi.org/10.1186/s12864-022-09014-5
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