Project 8 - Development of a pipeline for single-cell RNAseq analysis of lichens and other symbiotic associations

Applying for Summer 2025

Supervisors: Dr Ellen Cameron and Professor Irene Papathedorou

Introduction: Lichens are a composite organism formed through the symbiotic association between a fungal partner (mycobiont) and algal partner (photobiont). The study of lichens has presented challenges in the past arising from slow growth rates and the inability to cultivate a mature lichen in a laboratory setting. Advances in high-throughput sequencing provides new opportunities for characterizing these symbiotic associations. Metagenomic approaches have been applied to characterize the organisms present and transcriptomics to identify trends in gene expression corresponding to environmental conditions. Single-cell RNA sequencing will advance the study of lichens and other symbiotic associations further by providing a high-resolution cellular view on gene expression, and subsequently their functional profiles and how this may be used to inform species interactions.

To date, single-cell RNA sequencing has largely been applied in model organisms in the context of health, disease, and developmental processes. While standardized workflows and techniques for the analysis of this data are in place for well-characterized organisms, challenges remain in the analysis of diverse, non-model organisms. These challenges are amplified when the dataset in question includes multiple species from different taxonomic lineages. Single-cell sequencing data for the first lichen cell-atlas has been generated representing both fungal and algal partners present. As additional complex, multi-species associations are sequenced using single-cell approaches, a pipeline is required to expediate data analysis.

Objective: The development of a pipeline for analysis of single-cell RNA sequencing data generated from symbiotic associations containing multiple species.

Skills gained and essential prior knowledge: This project is based in Irene Papatheodorou’s team at the Earlham Institute based at the Norwich Research Park and will work alongside Ellen Cameron. The project will be entirely computational with no lab benchwork. Students should have basic programming knowledge (e.g., Python, R) and be comfortable working in the command line interface. This project will provide students the opportunity to improve their bioinformatics skills and will provide an introduction to the analysis of single-cell RNA sequencing data, and opportunity to explore additional research topics including gene co-expression analysis and improving functional annotations of symbiont genomes.