This presentation outlines the use of scRNA-seq in heart tissue, using various mouse models, including angiotensin II-induced hypertension and diabetic heart disease models. The techniques employed include the 10X Genomics platform and the Parse Biosciences Evercode system, highlighting their respective advantages and challenges.
10X Genomics uses droplet-based scRNA-seq, while Parse Biosciences Evercode employs combinatorial barcoding, allowing for larger cell sizes and no droplet limitations. Simpson discussed the challenges faced during the analysis of cardiomyocytes, such as their large size and sensitivity to isolation processes. He noted the common approach of nuclei isolation, which, while effective, results in the loss of cytoplasmic data.
Initial results from the nuclei isolation method showed effective cell type characterisation, although few cardiomyocytes were detected initially due to incomplete lysis. After optimising the lysis protocol, more nuclei were obtained, including those from cardiomyocytes, leading to better data quality.
The presentation also covers the analysis of fibroblasts in the context of cardiac hypertrophy and failure, using network analysis to identify gene expression changes associated with fibrosis.
A significant part of the seminar addresses the relevance of mouse models in human studies. By analysing single-cell data, the team aims to identify similarities and differences between mouse and human heart tissues, focusing on how certain cell types respond differently to treatments. The integration of datasets from the Human Heart Cell Atlas and various mouse datasets allows for a comparative analysis of gene expression across species.
Launch of HIVE Browser
Towards the end of the presentation, Simpson introduces the HIVE browser, a new software tool designed to simplify the analysis of single-cell RNA-seq data. This tool allows researchers to visualize and analyse differential gene expression without requiring extensive coding knowledge. The software is available for public use and aims to support researchers in their data analysis efforts.
