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Here, you can explore the single-cell RNA sequencing (scRNA-Seq) results from Trypanosoma brucei blood stages, slender and stumpies

The analysis was carried out using the Seurat pipeline for differential expression. Further details can be found in our paper summarized below which you should cite if you use our data.

Paper significance statement

The life cycles of African trypanosomes are dependent on several differentiation steps, where the parasites transition between replicative and non-replicative forms specialised for infectivity and survival in mammal and tsetse fly niches. Here, we use single cell transcriptomics (scRNA-seq) to reconstruct the asynchronous differentiation of replicative slender to transmissible stumpy bloodstream form Trypanosoma brucei. Using oligopeptide-rich media to induce differentiation, we accurately modelled stumpy development in vitro and captured the transcriptomes of 9,344 slender and stumpy stage parasites and in parasites transitional between these extremes. Using this framework, we detail the relative order of biological events during development, profile dynamic gene expression patterns and identify putative novel regulators. Using marker genes to deduce the cell cycle phase of each parasite, we additionally map the cell cycle of proliferating parasites and position stumpy cell cycle exit at early G1, with subsequent progression to a distinct G0 state. We also explored the role of one gene found to peak in expression at the key slender to stumpy transition point, ZC3H20. By further scRNA-seq analysis of ZC3H20 null parasites exposed to oligopeptides and mapping the resulting cells to our atlas of differentiation, we identified the point of action for this key regulator. Using a developmental transition relevant for virulence in the mammalian host, our data provide a paradigm for the temporal mapping of differentiation events and regulators in the trypanosome life cycle.

Key results

Results
A: UMAP of the integrated data.

Single gene DE visualization

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Dotplot for multiple gene DE visualization

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DE scatterplot

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DE table

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