A spatially resolved brain region- and cell type-specific isoform atlas of the postnatal mouse brain

Journal Article (2021)
Author(s)

Anoushka Joglekar (Weill Cornell Medicine, New York)

Andreyi Prjibelski (St. Petersburg State University)

Ahmed Mahfouz (Leiden University Medical Center, TU Delft - Electrical Engineering, Mathematics and Computer Science)

Paul Collier (Weill Cornell Medicine, New York)

Susan Lin (Weill Cornell Medicine, New York, Weill Cornell Medical College)

Anna Katharina Schlusche (Weill Cornell Medicine, New York)

Jordan Marrocco (The Rockefeller University)

Stephen R. Williams (10x Genomics)

Bettina Haase (The Rockefeller University)

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Research Group
Pattern Recognition and Bioinformatics
DOI related publication
https://doi.org/10.1038/s41467-020-20343-5 Final published version
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Publication Year
2021
Language
English
Research Group
Pattern Recognition and Bioinformatics
Issue number
1
Volume number
12
Article number
463
Pages (from-to)
1-16
Downloads counter
193
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Institutional Repository
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Abstract

Splicing varies across brain regions, but the single-cell resolution of regional variation is unclear. We present a single-cell investigation of differential isoform expression (DIE) between brain regions using single-cell long-read sequencing in mouse hippocampus and prefrontal cortex in 45 cell types at postnatal day 7 (www.isoformAtlas.com). Isoform tests for DIE show better performance than exon tests. We detect hundreds of DIE events traceable to cell types, often corresponding to functionally distinct protein isoforms. Mostly, one cell type is responsible for brain-region specific DIE. However, for fewer genes, multiple cell types influence DIE. Thus, regional identity can, although rarely, override cell-type specificity. Cell types indigenous to one anatomic structure display distinctive DIE, e.g. the choroid plexus epithelium manifests distinct transcription-start-site usage. Spatial transcriptomics and long-read sequencing yield a spatially resolved splicing map. Our methods quantify isoform expression with cell-type and spatial resolution and it contributes to further our understanding of how the brain integrates molecular and cellular complexity.