Elucidating molecular mechanisms and understanding genetic heterogeneity in cancer biology can be achieved through high-throughput gene expression analysis and pathway assignment. Recent advances in RNA-seq methodologies have enabled accurate gene expression profiling from single cells, but analyzing hundreds or thousands of cells is an arduous exercise in library prep. Here, we describe a high-throughput 3’ RNA-seq library prep methodology termed Ultraplex. With QIAseq Ultraplex, reverse transcription is performed directly on lysed cells, while simultaneously assigning a unique ‘cell index’ to all cDNA synthesized from a cell. All subsequent transcriptome or targeted panel library steps that follow occur in a single pooled sample; with up to 384 samples assigned per sequencing index. Each 384-plex library is assigned a standard sample index, such that up to 384 pooled 384X libraries can be sequenced together. With this methodology, thousands of transcriptomes or targeted RNA panels can be prepared and sequenced together. Here, we analyze the heterogeneity of an ostensibly uniform population of cancer cells, identifying unique signatures of genes that drive cellular clustering. With QIAseq UPX, high-throughput transcriptomic analysis enables the identification and characterization of gene signatures which divide cells into discrete sub-populations based on vectoral gene expression components.
Kreutz, J. Shaffer, Q. Jiang, S. Rulli, E. Lader