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Comparative performance of the BGI and Illumina sequencing technology for single-cell RNA-sequencing

The libraries generated by high-throughput single cell RNA-sequencing (scRNA-seq) platforms such as the Chromium from 10× Genomics require considerable amounts of sequencing, typically due to the large number of cells. The ability to use these data to address biological questions is directly impacte...

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Autores principales: Senabouth, Anne, Andersen, Stacey, Shi, Qianyu, Shi, Lei, Jiang, Feng, Zhang, Wenwei, Wing, Kristof, Daniszewski, Maciej, Lukowski, Samuel W, Hung, Sandy S C, Nguyen, Quan, Fink, Lynn, Beckhouse, Anthony, Pébay, Alice, Hewitt, Alex W, Powell, Joseph E
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7671348/
https://www.ncbi.nlm.nih.gov/pubmed/33575589
http://dx.doi.org/10.1093/nargab/lqaa034
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author Senabouth, Anne
Andersen, Stacey
Shi, Qianyu
Shi, Lei
Jiang, Feng
Zhang, Wenwei
Wing, Kristof
Daniszewski, Maciej
Lukowski, Samuel W
Hung, Sandy S C
Nguyen, Quan
Fink, Lynn
Beckhouse, Anthony
Pébay, Alice
Hewitt, Alex W
Powell, Joseph E
author_facet Senabouth, Anne
Andersen, Stacey
Shi, Qianyu
Shi, Lei
Jiang, Feng
Zhang, Wenwei
Wing, Kristof
Daniszewski, Maciej
Lukowski, Samuel W
Hung, Sandy S C
Nguyen, Quan
Fink, Lynn
Beckhouse, Anthony
Pébay, Alice
Hewitt, Alex W
Powell, Joseph E
author_sort Senabouth, Anne
collection PubMed
description The libraries generated by high-throughput single cell RNA-sequencing (scRNA-seq) platforms such as the Chromium from 10× Genomics require considerable amounts of sequencing, typically due to the large number of cells. The ability to use these data to address biological questions is directly impacted by the quality of the sequence data. Here we have compared the performance of the Illumina NextSeq 500 and NovaSeq 6000 against the BGI MGISEQ-2000 platform using identical Single Cell 3′ libraries consisting of over 70 000 cells generated on the 10× Genomics Chromium platform. Our results demonstrate a highly comparable performance between the NovaSeq 6000 and MGISEQ-2000 in sequencing quality, and the detection of genes, cell barcodes, Unique Molecular Identifiers. The performance of the NextSeq 500 was also similarly comparable to the MGISEQ-2000 based on the same metrics. Data generated by both sequencing platforms yielded similar analytical outcomes for general single-cell analysis. The performance of the NextSeq 500 and MGISEQ-2000 were also comparable for the deconvolution of multiplexed cell pools via variant calling, and detection of guide RNA (gRNA) from a pooled CRISPR single-cell screen. Our study provides a benchmark for high-capacity sequencing platforms applied to high-throughput scRNA-seq libraries.
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spelling pubmed-76713482021-02-10 Comparative performance of the BGI and Illumina sequencing technology for single-cell RNA-sequencing Senabouth, Anne Andersen, Stacey Shi, Qianyu Shi, Lei Jiang, Feng Zhang, Wenwei Wing, Kristof Daniszewski, Maciej Lukowski, Samuel W Hung, Sandy S C Nguyen, Quan Fink, Lynn Beckhouse, Anthony Pébay, Alice Hewitt, Alex W Powell, Joseph E NAR Genom Bioinform Methart The libraries generated by high-throughput single cell RNA-sequencing (scRNA-seq) platforms such as the Chromium from 10× Genomics require considerable amounts of sequencing, typically due to the large number of cells. The ability to use these data to address biological questions is directly impacted by the quality of the sequence data. Here we have compared the performance of the Illumina NextSeq 500 and NovaSeq 6000 against the BGI MGISEQ-2000 platform using identical Single Cell 3′ libraries consisting of over 70 000 cells generated on the 10× Genomics Chromium platform. Our results demonstrate a highly comparable performance between the NovaSeq 6000 and MGISEQ-2000 in sequencing quality, and the detection of genes, cell barcodes, Unique Molecular Identifiers. The performance of the NextSeq 500 was also similarly comparable to the MGISEQ-2000 based on the same metrics. Data generated by both sequencing platforms yielded similar analytical outcomes for general single-cell analysis. The performance of the NextSeq 500 and MGISEQ-2000 were also comparable for the deconvolution of multiplexed cell pools via variant calling, and detection of guide RNA (gRNA) from a pooled CRISPR single-cell screen. Our study provides a benchmark for high-capacity sequencing platforms applied to high-throughput scRNA-seq libraries. Oxford University Press 2020-05-13 /pmc/articles/PMC7671348/ /pubmed/33575589 http://dx.doi.org/10.1093/nargab/lqaa034 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Methart
Senabouth, Anne
Andersen, Stacey
Shi, Qianyu
Shi, Lei
Jiang, Feng
Zhang, Wenwei
Wing, Kristof
Daniszewski, Maciej
Lukowski, Samuel W
Hung, Sandy S C
Nguyen, Quan
Fink, Lynn
Beckhouse, Anthony
Pébay, Alice
Hewitt, Alex W
Powell, Joseph E
Comparative performance of the BGI and Illumina sequencing technology for single-cell RNA-sequencing
title Comparative performance of the BGI and Illumina sequencing technology for single-cell RNA-sequencing
title_full Comparative performance of the BGI and Illumina sequencing technology for single-cell RNA-sequencing
title_fullStr Comparative performance of the BGI and Illumina sequencing technology for single-cell RNA-sequencing
title_full_unstemmed Comparative performance of the BGI and Illumina sequencing technology for single-cell RNA-sequencing
title_short Comparative performance of the BGI and Illumina sequencing technology for single-cell RNA-sequencing
title_sort comparative performance of the bgi and illumina sequencing technology for single-cell rna-sequencing
topic Methart
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7671348/
https://www.ncbi.nlm.nih.gov/pubmed/33575589
http://dx.doi.org/10.1093/nargab/lqaa034
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