Project description:In this work, we have improved our previously published bacterial single-cell RNA-sequencing protocol (MATQ-seq), providing enhancements that achieve a higher cell throughput while also including integration of automation. We selected a more efficient reverse transcriptase which led to a lower drop-out rate and higher workflow robustness, and we also successfully implemented a Cas9-based ribosomal RNA depletion protocol into the MATQ-seq workflow. Applying this improved protocol on a large set of single Salmonella cells sampled over growth revealed improved gene coverage and a higher gene detection limit, allowing us to reveal the expression of small regulatory RNAs such as GcvB or CsrB at a single-cell level. In addition, we were able to confirm previously described phenotypic heterogeneity in Salmonella in regards to expression of pathogenicity-associated genes.
Project description:In this work, we have improved our previously published bacterial single-cell RNA-sequencing protocol (MATQ-seq), providing enhancements that achieve a higher cell throughput while also including integration of automation. We selected a more efficient reverse transcriptase which led to a lower drop-out rate and higher workflow robustness, and we also successfully implemented a Cas9-based ribosomal RNA depletion protocol into the MATQ-seq workflow. Applying this improved protocol on a large set of single Salmonella cells sampled over growth revealed improved gene coverage and a higher gene detection limit, allowing us to reveal the expression of small regulatory RNAs such as GcvB or CsrB at a single-cell level. In addition, we were able to confirm previously described phenotypic heterogeneity in Salmonella in regards to expression of pathogenicity-associated genes.
Project description:BackgroundOnce bulk RNA-seq data has been processed, i.e. aligned and then expression and differential tables generated, there remains the essential process where the biology is explored, visualized and interpreted. Without the use of a visualisation and interpretation pipeline this step can be time consuming and laborious, and is often completed using R. Though commercial visualisation and interpretation pipelines are comprehensive, freely available pipelines are currently more limited.ResultsHere we demonstrate Searchlight, a freely available bulk RNA-seq visualisation and interpretation pipeline. Searchlight provides: a comprehensive statistical and visual analysis, focusing on the global, pathway and single gene levels; compatibility with most differential experimental designs irrespective of organism or experimental complexity, via three workflows; reports; and support for downstream user modification of plots via user-friendly R-scripts and a Shiny app. We show that Searchlight offers greater automation than current best tools (VIPER and BioJupies). We demonstrate in a timed re-analysis study, that alongside a standard bulk RNA-seq processing pipeline, Searchlight can be used to complete bulk RNA-seq projects up to the point of manuscript quality figures, in under 3 h.ConclusionsCompared to a manual R based analysis or current best freely available pipelines (VIPER and BioJupies), Searchlight can reduce the time and effort needed to complete bulk RNA-seq projects to manuscript level. Searchlight is suitable for bioinformaticians, service providers and bench scientists. https://github.com/Searchlight2/Searchlight2 .