Genome biologyMolecular BiologyPeer-reviewed journal article
Pluripotent stem cell derived models of neurological diseases reveal early transcriptional heterogeneity
Matan SorekiD, Walaa Oweis, Malka Nissim‐Rafinia, Moria Maman, Shahar SimoniD, Cynthia C. Hession, Xian AdiconisiD, Sean SimmonsiD, Neville E. SanjanaiD, Xi ShiiD, Congyi LuiD, Jen Q. PaniD, Xiaohong XuiD, Mahmoud A. PouladiiD, Lisa EllerbyiD, Feng ZhangiD, Joshua Z. LeviniD, Eran MeshoreriD
Abstract
BackgroundMany neurodegenerative diseases (NDs) develop only later in life, when cells in the nervous system lose their structure or function. In genetic forms of NDs, this late onset phenomenon remains largely unexplained. ResultsAnalyzing single cell RNA sequencing (scRNA-seq) from Alzheimers disease (AD) patients, we find increased transcriptional heterogeneity in AD excitatory neurons. We hypothesized that transcriptional heterogeneity precedes ND pathologies. To test this idea experimentally, we used juvenile forms (72Q; 180Q) of Huntingtons disease (HD) iPSCs, differentiated them into committed neuronal progenitors, and obtained single cell expression profiles. We show a global increase in gene expression variability in HD. Autophagy genes become more stable, while energy and actin-related genes become more variable in the mutant cells. Knocking-down several differentially-variable genes resulted in increased aggregate formation, a pathology associated with HD. We further validated the increased transcriptional heterogeneity in CHD8+/- cells, a model for autism spectrum disorder. ConclusionsOverall, our results suggest that although NDs develop over time, transcriptional regulation imbalance is present already at very early developmental stages. Therefore, an intervention aimed at this early phenotype may be of high diagnostic value.
- organism: human
- assay: scRNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: cell type annotation
- approach: statistical model
- Citations
- 17
- FWCI
- 0.63
- Field percentile
- top 39%
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