HTPathwaySeq, a Novel Application for High-throughput RNA Sequencing Based Pathway Phenotyping

Abstract
Different technologies support researchers in probing the transcriptome. The choice among these technologies is guided in part by the balance between the amount of data one wishes to obtain for a given sample and the number of samples being tested. Typically, these parameters are inversely correlated. At the opposite ends of this spectrum, deep RNA sequencing and qPCR yield in depth data for tens of samples starting at a total cost of at least 300€/sample or very directed information for thousands of samples at a cost below 10€ per sample, respectively. We here present HTPathwaySeq, a technology situated in the middle of this spectrum, tailored towards researchers looking for maximal molecular insights for their in vitrostudies.
At a cost below 100 EUR/sample, HTPathwaySeq processes 384 cell lysates with RNA seq to generate expression data analyzed at pathway level. Our data shows that shallow sequencing of crude cell lysates reproducibly detects over 5000 genes with at least 10 reads. Subsampling of deep sequencing datasets demonstrated that differential pathway analysis is largely unaffected when reducing the number of genes to this level. Consequently, reliable pathway insights can be obtained at high throughput and relatively low cost while not being limited to a predefined set of genes or pathways. In cell perturbation screenings (small molecules, RNAi, antisense or CRISPR), HTPathwaySeq can provide in depth information on the mode of action underlying the induced cellular phenotypes as well as molecular similarity scores to identify those perturbations acting similar to a reference condition or via shared molecular mechanisms. We will show results from a lead compound dose response study, illustrating the potential of HTPathwaySeq.