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Illumina SBS sequencing and DNBSEQ perform similarly for single-cell transcriptomics

GSE277740 Mus musculus Expression profiling by high throughput sequencing 8 samples Submitted 2025/09/01 Platform GPL28330
Summary
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. In this study, we compared data generated from scRNA-seq libraries sequenced with both standard Illumina sequencing by synthesis (Illumina SBS) and MGI’s DNA nanoball sequencing (DNBSEQ). 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 of 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. Overall, our data demonstrate that alternative technologies can be applied to sequence scRNA-seq libraries, generating virtually undiscernible results compared to standard methods, and providing cost-effective alternatives.
Published in
Illumina SBS Sequencing and DNBSEQ Perform Similarly for Single-Cell Transcriptomics
Bestard-Cuche N, Munro DAD, Beniazza M et al. · Genes 2024 · PMID 39596636 · doi:10.3390/genes15111436
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Direct links to NCBI, no account and no request form: the whole study as GSE277740_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 8 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1163712 and SRA study SRP534014. Searching any of these in the dataset finder brings you back here.

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