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Transcriptional profiling of tauopathies in human IPS-derived neurons (2019-08-21)

This project is a pilot study, in collaboration with Maria Grazia Spillantini and Mariangela Iovino (Cambridge Centre for Brain Repair), to investigate the utility of IPS-derived neurons for the study of neurodegenerative disorders. Our aim is to characterise the transcriptional consequences of tauopathies using neurons derived from differentiated IPSCs as a model system. We will use IPS cells derived from six individuals, four with known mutations in the tau protein, 2 without. RNA will be extracted at Day 0 and Day 65 of differentiation by which time the neuronal tauopathy is apparent. RNA will be extracted and the transcriptome of each line characterised using RNAseq. We will then search for genes that are differentially expressed between the transcriptomes of individuals with tau mutations versus those in controls. My lab will analyse the RNAseq data, comparing both affected and controls and both time-points, to establish candidate genes. Darren Logan’s lab, along with our collaborators, will experimentally verify and further investigate these genes in additional lines and animal models. From this analysis we will generate a list of candidate genes that are differentially expressed between cases and controls. This study will not only help us understand the molecular basis of tauopathies, but also identify gene candidates for biomarkers of neurodegenerative disease. It will serve as a proof of principle for future planned studies into generating and transcriptomically analysing an allelic series of Tau mutations in IPSCs with a controlled genetic background. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2019-08-21.

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Studies are experimental investigations of a particular phenomenon, e.g., case-control studies on a particular trait or cancer research projects reporting matching cancer normal genomes from patients.

Study ID Study Title Study Type
Transcriptome Analysis

This table displays only public information pertaining to the files in the dataset. If you wish to access this dataset, please submit a request. If you already have access to these data files, please consult the download documentation.

ID File Type Size Located in
EGAF00000168214 bam 2.7 GB
EGAF00000168215 bam 2.6 GB
EGAF00000168216 bam 2.8 GB
EGAF00000168217 bam 2.5 GB
EGAF00000168218 bam 2.4 GB
EGAF00000168219 bam 2.7 GB
EGAF00000168220 bam 2.7 GB
EGAF00000168221 bam 2.3 GB
EGAF00000168222 bam 2.8 GB
EGAF00000168223 bam 2.4 GB
EGAF00000168224 bam 2.7 GB
EGAF00000168225 bam 2.7 GB
EGAF00000168226 bam 2.6 GB
EGAF00000168227 bam 2.8 GB
EGAF00000168228 bam 2.5 GB
EGAF00000168229 bam 2.4 GB
EGAF00000168230 bam 2.7 GB
EGAF00000168231 bam 2.7 GB
EGAF00000168232 bam 2.3 GB
EGAF00000168233 bam 2.8 GB
EGAF00000168234 bam 2.4 GB
EGAF00000168235 bam 2.7 GB
EGAF00000168236 bam 2.7 GB
EGAF00000168237 bam 2.6 GB
EGAF00000168238 bam 2.8 GB
EGAF00000168239 bam 2.5 GB
EGAF00000168240 bam 2.4 GB
EGAF00000168241 bam 2.7 GB
EGAF00000168242 bam 2.7 GB
EGAF00000168243 bam 2.3 GB
EGAF00000168244 bam 2.8 GB
EGAF00000168245 bam 2.4 GB
EGAF00000168246 bam 2.7 GB
33 Files (86.0 GB)