29th - 30th January 2025 | ExCeL, London
Optimizing and Implementing Single-Cell Technologies to Uncover Complex Biology
Date: Day 2, Thursday 30th January 2025
Time: 11:15 - 15:40
Location: The Single-Cell & Spatial Dome
Single-cell analysis has long been used to detect cellular heterogeneity, signalling pathways, and disease mechanisms. Despite the advent of spatial analysis and new techniques, single-cell continues to be the dominant tool in revealing cell population differences and cellular evolutionary relationships. This workshop aims to help participants decipher single-cell data, improve analysis workflows and demonstrate how to integrate existing datasets to uncover novel biological insights.
Learning Objectives
- Recognize how sharing phenotype-linked variant data advances rare disease diagnosis and research, enhancing the identification and understanding of rare genetic conditions.
- Familiarize yourself with tools like DECIPHER that offer powerful interfaces and databases for accurate genomic variant interpretation, supporting diagnosis and research efforts.
- Learn and apply ACGS guidelines to score and sub-divide variants of uncertain significance, determine reportable variants, follow recommendations for additional testing, and navigate reclassification for precise genetic analysis.
Workshop Format
Dreamcatcher allows accurate identification and quantification of bacterial reads in single-cell, spatial, and bulk RNA-seq
- Microbial reads are often discovered in RNA-seq samples; however, accurate identification of relevant bacteria is very challenging.
- We have developed a pipeline that allows us to remove computational false positives, evaluate "contaminome" contribution, and analyze single cell/spatial reads together with the host data.
- We will present a tutorial on performing this analysis and the types of biological information that can be learned from our approach.
Computational analyses of single-cell: technology landscape and its best practices
- Dreamcatcher allows accurate identification and quantification of bacterial reads in single cell, spatial, and bulk RNA-seq.
- Discuss different possibilities enabled by technology using single-cell. Discuss the best practices in choosing the right pipeline for an analysis.
- A workshop of developing small pipeline for an analysis.
Integrating single cell and spatial transcriptomics to uncover novel immune functions of adipocytes to parasitic infection
- Trypanosoma brucei is an extracellular parasite that causes adipose tissue wasting and weight loss, and poses a massive risk to the health of people living in Sub-Saharan countries in Africa
- By integrating single cell and spatial transcriptomics of the skin and subcutaneous adipose tissue, we uncovered novel interactions between adipocytes and IL-17A+ immune cells, such as gdT cells, that may lead to adipose tissue wasting
- Our integrated analyses also led us to identify that adipocyte IL-17 signalling is important for controlling local parasite number, demonstrating that adipocytes form an immune hub during infection, integrating local immune signals to orchestrate the immune response
Single-cell RNA-sequencing of PBMCs in Rheumatoid Arthritis and Rheumatoid Arthritis-Associated Interstitial Lung Disease
- Rheumatoid arthritis-associated interstitial lung disease (RA-ILD) is a severe extra-articular manifestation of RA that affects up to 15% of RA patients.
- RA-ILD is a major driver of increased morbidity, mortality and increased healthcare utilization.
- There has been limited investigation of cellular biomarkers that may shed light on RA-ILD pathogenesis and progression.
- In this study, we use single-cell RNA sequencing to identify cellular biomarkers associated with the development of RA-ILD.
- We investigate the cellular signatures associated with the development of RA-ILD and its fibrotic and inflammatory subtypes in peripheral blood mononuclear cells (PBMC) samples from patients with RA-ILD using the Flex assay.
- The 10x Genomics Gene Expression Flex protocol allows the single cell profiling of fixed or frozen samples which preserves fragile cell types and streamlines the workflow of sample processing.
- Our findings will further elucidate key pathogenic mechanisms in the development of RA-ILD and identify peripheral blood biomarkers to improve future screening and treatment strategies.
Q & A
This Q & A session is your chance to ask any burning questions Q&A
Workshop Leaders
Alexander Predeus
Principal Bioinformatician
Wellcome Sanger Institute
Tamara Salloum
Single-Cell Genomic Technology Specialist
Brigham and Women’s Hospital
Bodhayan Prasad
Bioinformatician
University of Glasgow