Single-cell multi-omics integration in Alzheimer’s disease
Mentor: Umran Yaman and Theodoros Koutsandreas
Overview:
Overview:
Genome-wide association studies have unveiled a multitude of non-coding loci associated with Alzheimer’s disease (AD) risk, yet a comprehensive understanding of their mechanisms and the specific transcriptional regulatory circuitry linked to AD remains elusive. In Xiong et al.’s 2023[1] study, 850,000 nuclei from 92 individuals were profiled, integrating epigenetic and transcriptional changes across different stages of AD. The analysis included co-accessibility modules and peak-to-gene links in a cell-type-specific context.
In this course, trainees will analyse the downsampled scRNA-seq and scATAC-seq datasets, including assessing the quality control metrics of each data layer before the integration. They will perform scRNA-seq and scATAC-seq integration to TF motifs, cell-cell communication, and differential expression analysis (DEA). In the end, they will be able to extract cell type-specific signalling networks across disease pathology.
Zenodo link: https://doi.org/10.5281/zenodo.14915226
Dataset:
Downsampled scRNA-seq and scATAC-seq dataset
Project Aims
- Handling scRNA-seq and sc-ATAC-seq datasets
- Identifying disease-caused key genes and regulators through integration
- Cell-specific epigenomics and transcriptomics changes potentially contribute to the disease
Reference:
Xiong X, James BT, Boix CA, et al. Epigenomic dissection of Alzheimer’s disease pinpoints causal variants and reveals epigenome erosion. Cell. 2023;186(20):4422-4437.e21. doi:10.1016/j.cell.2023.08.040