High-resolution scRNA-seq reveals genomic determinants of antigen expression hierarchy in African Trypanosomes

Description of the repository:

This repository contains the data analysis workflows for the manuscript entitled "High-resolution scRNA-seq reveals genomic determinants of antigen expression hierarchy in African Trypanosomes".

Due to space limitations on Zenodo, all the input raw sequencing data files were deposited in the European Nucleotide Archive (ENA) under project number PRJEB72370.

The folder "Switching_Hierarchy_Paper_Analysis_Pipelines.tar.gz" contains three subfolders: "Genomes" ; "Pre-processing" and "Downstream_Analysis" :

• The "Genomes" folder contains all the input fasta files and annotation files used in this project.
• The "Data_Pre-processing" folder contains worklows for preprocessing the sequencing data (i.e., subsampling of reads, alignments, production of count matrices, generation of single-cell coverage files, de-novo single-cell transcriptome assembly). The raw sequencing data files need to be downloaded from ENA (PRJEB72370) and placed in the "input/reads" folder of each respective pre-processing folder. The workflow for each dataset is in a bash script named "run.sh" , designed to run on a High-performance computer cluster with the SLURM job scheduling system. Accessory scripts are located in the "bin" folder. Final output files used in downstream analysis are in the "output" folder. Intermediate output files were not retained due to space limiatations. The required software environment can be recreated using the provided yaml file: "SS3x_mapping_counting_VSGhierarchy_env.yaml".
• The "Downstream_Analysis" folder contains, for each dataset, Jupyter notebooks and input files to generate all figures and analysis conducted during this project based on the sequencing data. The required software environment can be recreated using the provided yaml file: "scAnalysis_env.yaml"

Abstract

Antigenic variation is an immune evasion strategy used by many different pathogens. It involves the periodic, non-random switch in the expression of different antigens throughout an infection. How the observed hierarchy in antigen expression is achieved has remained a mystery. A key challenge in uncovering this process has been the inability to track transcriptome changes and potential genomic rearrangements in individual cells during a switch event. Here, we report the establishment of a highly sensitive single-cell RNA-seq (scRNA-seq) approach for the model protozoan parasite Trypanosoma brucei. This approach has revealed genomic rearrangements that occur in individual cells during a switch event. Our data show that following a double-strand break (DSB) in the transcribed antigen-coding gene – an important trigger for antigen switching – the type of repair mechanism and the resultant antigen expression depend on the availability of a homologous repair template in the genome. When such a template was available, repair proceeded through segmental gene conversion, creating new, mosaic antigen-coding genes. Conversely, in the absence of a suitable template, a telomere-adjacent antigen-coding gene from a different part of the genome was activated by break-induced replication. Our results reveal the critical role of available repair sequence in the antigen selection mechanism. Additionally, our study demonstrates the power of highly sensitive scRNA-seq methods in detecting genomic rearrangements that drive transcriptional changes at the single-cell level.