Wellcome Sanger Institute
Sanger Institute Science Collaboration

NeuroSeq

The NeuroSeq project was a collaboration between CGaP and the Gaffney faculty team, using single-cell 10x sequencing assays to analyse the gene expression across dopaminergic differentiation to identify regulatory variants and gene targets that affect transcriptome level, cell-to cell heterogeneity and the dynamics of cell differentiation.

About NeuroSeq

The impact of genetic variants on molecular pathways that give rise to neurodegenerative diseases such as Alzheimer’s and Parkinson’s is best elucidated in the appropriate cell types and molecular contexts. Existing studies before this project focused on bulk profiling of mixed cell types, but ignored assaying genetic effects across development and cell differentiation.

The NeuroSeq project used single-cell 10x sequencing assays to study genetic effects during differentiation of neuronal cell types to identify the sequence of molecular events from variants to healthy and diseased cell states in a cell-specific manner, and identify drug targets of disease that are the putative intervention points which interrupt disease pathogenesis.

Differentiation to dopaminergic neurons was carried out using a protocol derived from Kriks et al. 2011, applied to existing and established iPSC lines, spanning 52 days. These lines were pooled (~20 lines per pool) prior to seeding for differentiation. Differentiating lines were harvested for gene expression analysis on Days 11, 30 and 52 of the process. The project completed in 2019 with 21 iPS pools (comprising 249 cell lines in total) successfully banked, and 19 of these pools (comprising 237 cell lines) successfully differentiated and sequenced.

Sanger people

Previous Sanger people

Photo of James Haldane

James Haldane

Advanced Research Assistant

Photo of Dr Daniel Gaffney

Dr Daniel Gaffney

Former Group Leader

Affiliated Sites

External

Neuronal Dissociation Protocol

Published protocol for 'Dissociation of neuronal culture to single cells for scRNA-seq (10x Genomics)'