Abstract

Genetic perturbations of cerebral cortical development can lead to neurodevelopmental disease, including autism spectrum disorder (ASD). To identify genomic regions crucial to corticogenesis, we mapped the activity of gene-regulatory elements generating a single-cell atlas of gene expression and chromatin accessibility both independently and jointly. This revealed waves of gene regulation by key transcription factors (TFs) across a nearly continuous differentiation trajectory into glutamatergic neurons, distinguished the expression programs of glial lineages, and identified lineage-determining TFs that exhibited strong correlation between linked gene- regulatory elements and expression levels. These highly connected genes adopted an active chromatin state in early differentiating cells, consistent with lineage commitment. Basepair-resolution neural network models identified strong cell-type specific enrichment of noncoding mutations predicted to be disruptive in a cohort of ASD subjects and identified frequently disrupted TF binding sites. This approach illustrates how cell-type specific mapping can provide insights into the programs governing human development and disease.

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scRNA

Cell Explorer (Expression)

Explore the scRNA data in the cellxgene browser. The session includes cell anotation and normalized gene expression.

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scATAC

Cell Explorer (Chromatin)

Explore the scATAC data in the cellxgene browser. The session includes cell anotation and TF motif chromatin accessibility.

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scATAC

Genome Browser (Chromatin)

Explore the track data in the WashU Epigenome Browser browser.

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Data availability

Links to raw data archives and related resources.

Repository Reference
GEO Super-series: GSE162170
WashU Epigenome Browser Trackhub

Browser session: Session

Trackhub: JSON

Code availability

Links to code repositories.

Repository Description Reference
brainchromatin Miscellaneous analysis scripts used to analyze scRNA and scATAC data. GitHub
Brain_ASD Repository contains scripts for training the neural network models used for prioritizing ASD mutations with the fetal brain ATAC-seq atlas. GitHub
ChrAccR R package for the analysis of chromatin accessbility data. Provides a pipeline and functions for the analysis of our scATAC data. GitHub

Citation

If you use this resource in your research, please cite:

Trevino*, A. E., Müller*, F., Andersen*, J., Sundaram*, L., Kathiria, A., Shcherbina, A., Farh, K., Chang, H. Y., Pasca, A. M., Kundaje, A., Pasca#, S. P., & Greenleaf#, W. J. (2021). Chromatin and gene-regulatory dynamics of the developing human cerebral cortex at single-cell resolution. Cell. DOI: 10.1016/j.cell.2021.07.039


© 2021; Greenleaf and Pasca labs at Stanford University; Site created by Fabian Müller