Next-generation sequencing (NGS) has revolutionized genomics, decreasing sequencing costs and allowing researchers to draw correlations between diseases and DNA or RNA changes. Technical advances have enabled the analysis of RNA expression changes between single cells within a heterogeneous population, known as single-cell RNA-seq (scRNA-seq). Despite resolving transcriptomes of cellular subpopulations, scRNA-seq has not replaced RNA-seq, due to higher costs and longer hands-on time.
Researchers from Boehringer Ingelheim Pharma have developed an automated workflow to increase throughput (up to 48 reactions) and to reduce by 75% the hands-on time of scRNA-seq library preparation, using the 10X Genomics Single Cell 3’ kit. After gel bead-in-emulsion (GEM) generation on the 10X Genomics Chromium Controller, cDNA amplification was performed, and the product was normalized and subjected to either the manual, standard library preparation method or a fully automated, walk-away method using a Biomek i7 Hybrid liquid handler. Control metrics showed that both quantity and quality of the single-cell gene expression libraries generated were equivalent in size and yield. Key scRNA-seq downstream quality metrics, such as unique molecular identifiers count, mitochondrial RNA content, and cell and gene counts, further showed high correlations between automated and manual workflows. Using the UMAP dimensionality reduction technique to visualize all cells, the researchers were able to further correlate the results observed between the manual and automated methods (R=0.971). The method developed here allows for the fast, error-free, and reproducible multiplex generation of high-quality single-cell gene expression libraries.
Single-cell suspensions were assessed quantitatively and qualitatively using the NucleoCounter system prior to GEM generation in the Chromium Controller device. Subsequently, cDNA amplification and cleanup are performed followed by a quality check. After cDNA normalization, each sample was prepared for manual or automated (Biomek i7 Hybrid workstation) library preparation. Sequencing libraries were then assessed quantitatively and qualitatively before normalization, pooling and sequencing. Demultiplexing and data processing were performed, and side-by-side comparison of key single-cell metrics was done.