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Article

Illumina SBS Sequencing and DNBSEQ Perform Similarly for Single-Cell Transcriptomics

by
Nadine Bestard-Cuche
1,
David A. D. Munro
2,
Meryam Beniazza
1,
Josef Priller
2,3,
Anna Williams
1,2,*,† and
Andrea Corsinotti
1,*,†
1
Centre for Regenerative Medicine, Institute for Regeneration and Repair, MS Society Edinburgh Centre for MS Research, University of Edinburgh, Edinburgh EH16 4UU, UK
2
UK Dementia Research Institute, University of Edinburgh, Edinburgh EH8 9AL, UK
3
Department of Psychiatry and Psychotherapy, School of Medicine and Health, Klinikum Rechts der Isar, Technical University Munich, and German Center for Mental Health (DZPG), 80333 Munich, Germany
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Genes 2024, 15(11), 1436; https://doi.org/10.3390/genes15111436
Submission received: 20 September 2024 / Revised: 1 November 2024 / Accepted: 4 November 2024 / Published: 6 November 2024
(This article belongs to the Section Molecular Genetics and Genomics)

Highlights

What are the main findings?
  • DNBSEQ exhibited mildly superior sequence quality compared to Illumina SBS, as evidenced by a higher Phred score and a greater number of genes mapping to the reference genome.
  • However, these improvements did not translate into significant differences in the single-cell applications. There was no significant difference in the annotation of cells into different cell types, and both technologies yielded the same top differentially expressed genes between the experimental conditions.
What is the implication of the main finding?
  • As we show that the quality between these two technologies is similar, researchers choosing a sequencing technology can give more weight to other external factors such as support, cost, and convenience.
  • Competition is gradually driving down scRNA-seq reagent prices. Researchers being aware of different NGS alternatives will increase competition in the sequencing market and also help to reduce sequencing costs.
  • This may open the doors to scRNAseq for researchers with limited budgets or allow researchers to add more samples using the same budget, enabling them to answer the same biological questions with a greater statistical power or explore new questions.

Abstract

Background/Objectives: High-throughput single-cell RNA sequencing (scRNA-seq) workflows produce libraries that demand extensive sequencing. However, standard next-generation sequencing (NGS) methods remain expensive, contributing to the high running costs of single-cell experiments and often negatively affecting the sample numbers and statistical strength of such projects. In recent years, a plethora of new sequencing technologies have become available to researchers through several manufacturers, often providing lower-cost alternatives to standard NGS. Methods: In this study, we compared data generated from mouse scRNA-seq libraries sequenced with both standard Illumina sequencing by synthesis (Illumina SBS) and MGI’s DNA nanoball sequencing (DNBSEQ). Results: Our findings reveal similar overall performance using both technologies. DNBSEQ exhibited mildly superior sequence quality compared to Illumina SBS, as evidenced by higher Phred scores, lower read duplication rates and a greater number of genes mapping to the reference genome. Yet these improvements did not translate into meaningful differences in single-cell analysis parameters in our experiments, including detection of additional genes within cells, gene expression saturation levels and numbers of identified cells, with both technologies demonstrating equally robust performance in these aspects. The data produced by both sequencing platforms also produced comparable analytical outcomes for single-cell analysis. No significant difference in the annotation of cells into different cell types was observed and the same top genes were differentially expressed between populations and experimental conditions. Conclusions: Overall, our data demonstrate that alternative technologies can be applied to sequence scRNA-seq libraries, generating virtually indistinguishable results compared to standard methods, and providing cost-effective alternatives.
Keywords: single-cell RNAseq; DNBSEQ sequencing; Illumina SBS sequencing single-cell RNAseq; DNBSEQ sequencing; Illumina SBS sequencing

Share and Cite

MDPI and ACS Style

Bestard-Cuche, N.; Munro, D.A.D.; Beniazza, M.; Priller, J.; Williams, A.; Corsinotti, A. Illumina SBS Sequencing and DNBSEQ Perform Similarly for Single-Cell Transcriptomics. Genes 2024, 15, 1436. https://doi.org/10.3390/genes15111436

AMA Style

Bestard-Cuche N, Munro DAD, Beniazza M, Priller J, Williams A, Corsinotti A. Illumina SBS Sequencing and DNBSEQ Perform Similarly for Single-Cell Transcriptomics. Genes. 2024; 15(11):1436. https://doi.org/10.3390/genes15111436

Chicago/Turabian Style

Bestard-Cuche, Nadine, David A. D. Munro, Meryam Beniazza, Josef Priller, Anna Williams, and Andrea Corsinotti. 2024. "Illumina SBS Sequencing and DNBSEQ Perform Similarly for Single-Cell Transcriptomics" Genes 15, no. 11: 1436. https://doi.org/10.3390/genes15111436

APA Style

Bestard-Cuche, N., Munro, D. A. D., Beniazza, M., Priller, J., Williams, A., & Corsinotti, A. (2024). Illumina SBS Sequencing and DNBSEQ Perform Similarly for Single-Cell Transcriptomics. Genes, 15(11), 1436. https://doi.org/10.3390/genes15111436

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