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An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
Published on: November 3, 2010
Single-cell analyses reveal increased gene expression variability in human neurodevelopmental conditions
Suraj Upadhya1, Jenny A Klein1, Anna Nathanson1
1Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA.
Neurodevelopmental conditions, like Down syndrome (Trisomy 21) and CHD8 haploinsufficiency, increase gene expression variability in brain cells. This heightened variability may explain diverse phenotypic outcomes in these conditions.
Area of Science:
- Genomics
- Neuroscience
- Developmental Biology
Background:
- Interindividual variation in neurodevelopmental conditions is common but poorly understood.
- Gene expression can vary even within genetically identical cells, suggesting stochastic processes are at play.
Purpose of the Study:
- To investigate if neurodevelopmental conditions increase gene expression variability, beyond differential expression.
- To explore the mechanisms and implications of this variability in brain development.
Main Methods:
- Analysis of single-cell and single-nucleus RNA sequencing datasets from human brain-relevant cell and tissue types.
- Comparison of gene expression variability in conditions like Trisomy 21 and CHD8 haploinsufficiency versus controls.
Main Results:
- Trisomy 21 and CHD8 haploinsufficiency significantly increase gene expression variability in brain cells.
- This increase in variability is global, partly stochastic, and uncoupled from average transcript abundance.
- Highly variable genes are often cell-type specific and associated with repressive histone marks, while less variable genes are constrained and linked to active marks.
Conclusions:
- Neurodevelopmental conditions can drive increased gene expression variability in brain cells, potentially contributing to diverse phenotypic outcomes.
- Understanding gene expression variability is crucial for deciphering genotype-phenotype relationships in neurodevelopmental disorders.
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