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

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• High-throughput single-cell RNA sequencing (scRNA-seq) is crucial but costly due to extensive sequencing demands.
• Standard next-generation sequencing (NGS) methods contribute significantly to high experimental costs, limiting sample sizes and statistical power.
• Emerging sequencing technologies offer potentially lower-cost alternatives for scRNA-seq library preparation.

Purpose of the Study:

• To compare the performance of MGI's DNA nanoball sequencing (DNBSEQ) against standard Illumina sequencing by synthesis (SBS) for mouse scRNA-seq libraries.
• To evaluate if alternative sequencing platforms provide comparable or superior data quality and analytical outcomes for scRNA-seq.
• To assess the cost-effectiveness of DNBSEQ for scRNA-seq applications.

Main Methods:

• Mouse scRNA-seq libraries were sequenced using both Illumina SBS and MGI DNBSEQ platforms.
• Sequence quality metrics (Phred scores, duplication rates, gene mapping) were analyzed.
• Single-cell analysis parameters (gene detection, saturation, cell identification, cell type annotation, differential gene expression) were compared between the two platforms.

Main Results:

• Both DNBSEQ and Illumina SBS demonstrated similar overall performance for scRNA-seq.
• DNBSEQ showed slightly better sequence quality (higher Phred scores, lower duplication rates, more mapped genes).
• These quality differences did not result in meaningful variations in single-cell analysis outcomes, including gene detection, cell identification, or differential expression analysis.

Conclusions:

• Alternative sequencing technologies, such as MGI DNBSEQ, can effectively sequence scRNA-seq libraries.
• Results generated by DNBSEQ are virtually indistinguishable from those produced by standard Illumina SBS.
• DNBSEQ offers a cost-effective alternative for scRNA-seq, enabling comparable scientific insights.