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

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. brain tissue harvests and dissociations were performed at a consistent time of day for all 8 mice, with processing of mice of different genotypes being mixed to reduce batch effects. Tissues were rapidly processed without perfusion, and thalami were dissected from both hemisphere and processed. We generated brain single-cell suspensions using the Adult Brain Dissociation Kit (130-107-677, Miltenyi Biotec). Cell sorting was conducted to exclude doublets, erythrocytes, and debris. Post-sorting viability confirmation was performed, and single cells were processed using the Chromium Single Cell Platform. Illumina-compatible libraries generated using the 10X Genomics 3’ V3.1 workflow were converted for MGI sequencing using the PCR-based MGI Easy Universal Library Conversion kit (App-A) following the manufacturer’s instructions. The kit adds a 5’phosphate modification to the 10X library to enable circularisation and subsequent DNA Nanoball generation as part of the DNBSEQ sequencing process. 50 ng inputs were used and 5 cycles of PCR, to avoid the possibility of introducing errors through PCR. The libraries were sequenced on an MGI DNBSEQ-T7 instrument with an E1 flow cell. The sequencing consisted of 28 cycles for Read1, 90 cycles for Read2 and 10 cycles for the barcode indexes.