2021
DOI: 10.1038/s41467-020-20343-5
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A spatially resolved brain region- and cell type-specific isoform atlas of the postnatal mouse brain

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 pr… Show more

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Cited by 151 publications
(172 citation statements)
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“…A similar underestimation of hybrid exons is true when conditioning on annotated exons and comparing to HIT index classifications (Figure 3D). Consistent with previous work (28), we find that only a minority of annotated exons are expressed in a single cell type and of these, many hybrid exons are mis-classified as internal exons. Together, our new classifications show that a reliance on genome annotations in RNA-seq analyses underestimates the usage of alternative terminal exons by mis-classifying hybrid exons.…”
Section: Resultssupporting
confidence: 92%
“…A similar underestimation of hybrid exons is true when conditioning on annotated exons and comparing to HIT index classifications (Figure 3D). Consistent with previous work (28), we find that only a minority of annotated exons are expressed in a single cell type and of these, many hybrid exons are mis-classified as internal exons. Together, our new classifications show that a reliance on genome annotations in RNA-seq analyses underestimates the usage of alternative terminal exons by mis-classifying hybrid exons.…”
Section: Resultssupporting
confidence: 92%
“…The hippocampus has cell- and compartment-specific transcriptomes, as it is divided into 4 major subregions (CA1, CA2, CA3, and the dentate gyrus) with diverse gene expression schemes to control subregion-specific properties and functions (Masser et al, 2014 ; Cembrowski et al, 2016 ; Farris et al, 2019 ). Several studies have identified alternative splicing programs that readily distinguish neuron cell classes (glutamatergic, GABAergic, glia; Zhang et al, 2014 ; Furlanis et al, 2019 ; Sapkota et al, 2019 ; Feng et al, 2021 ; Joglekar et al, 2021 ) and to a lesser extent distinguish neuron subclasses (CA1, CA3; Furlanis et al, 2019 ; Joglekar et al, 2021 ), indicating that alternate isoform expression is a driver of functional specification (Furlanis et al, 2019 ). Cell-specific expression of transcription factors and epigenetic modifiers likely induce expression of these specialized transcriptomes, but it is still unknown how they communicate with the splicing machinery to induce expression of one isoform over another.…”
Section: Are There Subregion-specific Splicing Programs In the Hippocampus?mentioning
confidence: 99%
“…Alternative isoform expression is one regulatory mechanism well poised to mediate spatial and temporal gene expression in neurons. Alternative isoform expression results from the interplay of many different RNA regulatory processes, including alternative promoter usage (alternative first exon; Twine et al, 2013 ), alternative exon splicing (Ha et al, 2021 ; Joglekar et al, 2021 ), alternative last exon usage (Taliaferro et al, 2016 ), and alternative polyadenylation (APA; Fontes et al, 2017 ; Ha et al, 2021 ; Figure 1 ). This coordinated inclusion or exclusion of specific cis RNA sequences can determine the spatiotemporal expression profile of a given transcript via differential binding of trans -acting factors.…”
Section: Introductionmentioning
confidence: 99%
“…Higher order brain functions, and those functions critical to sustain life are facilitated by the concerted activity of different cell types, each functionally driven by distinct, context dependent gene expression and gene expression regulation patterns ( Hawrylycz et al, 2012 ; Mitra et al, 2021 ). Recently, the application of single cell RNA-sequencing technologies has begun to reveal at single cell resolution this dynamic and distinct gene expression patterns and how they respond to stimulus or activity ( Agarwal et al, 2020 ; Pfisterer et al, 2020 ; Joglekar et al, 2021 ; Song et al, 2021 ).…”
Section: Introductionmentioning
confidence: 99%