Complexity and graded regulation of neuronal cell-type–specific alternative splicing revealed by single-cell RNA sequencing

Abstract

The enormous cellular diversity in the mammalian brain, which is highly prototypical and organized in a hierarchical manner, is dictated by cell-type–specific gene-regulatory programs at the molecular level. Although prevalent in the brain, the contribution of alternative splicing (AS) to the molecular diversity across neuronal cell types is just starting to emerge. Here, we systematically investigated AS regulation across over 100 transcriptomically defined neuronal types of the adult mouse cortex using deep single-cell RNA-sequencing data. We found distinct splicing programs between glutamatergic and GABAergic neurons and between subclasses within each neuronal class. These programs consist of overlapping sets of alternative exons showing differential splicing at multiple hierarchical levels. Using an integrative approach, our analysis suggests that RNA-binding proteins (RBPs) Celf1/2, Mbnl2, and Khdrbs3 are preferentially expressed and more active in glutamatergic neurons, while Elavl2 and Qk are preferentially expressed and more active in GABAergic neurons. Importantly, these and additional RBPs also contribute to differential splicing between neuronal subclasses at multiple hierarchical levels, and some RBPs contribute to splicing dynamics that do not conform to the hierarchical structure defined by the transcriptional profiles. Thus, our results suggest graded regulation of AS across neuronal cell types, which may provide a molecular mechanism to specify neuronal identity and function that are orthogonal to established classifications based on transcriptional regulation.

Robust and annotation-free analysis of alternative splicing across diverse cell types in mice

“…Cells in the splicing latent space strongly cluster by cell type (annotated by Yao et al [24] based on gene expression). A similar analysis was recently performed [36] on a different cortex subregion in which most, but not all, neuron subclasses could be distinguished based on splicing profiles (e.g., L6 CT and L6b could not be separated). However, the authors only considered annotated skipped exons, a subset of the events we quantify, and used a different dimensionality reduction technique.…”

Applications of single-cell genomics and computational strategies to study common disease and population-level variation

“…Previous studies have shown that genes showing changes in alternative splicing may reflect different biological processes from those with DE. For example, a recent scRNA-seq study in the adult mouse cortex found differences in splicing dynamics across cells were not explained by neuronal cell type definitions based on differences in isoform-agnostic transcript expression levels, suggesting that alternative splicing regulation might be orthogonal to transcriptional regulation in specifying neuronal identity and function (Feng et al 2021). Therefore, differential alternative splicing may complement DE analysis in characterizing gene regulation.…”

Spatiotemporal Regulation of Transcript Isoform Expression in the Hippocampus

“…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.…”

“…Alternative isoform expression is regulated by a complex interplay of splicing factors (Fischer et al, 2011 ; Carey and Wickramasinghe, 2018 ), epigenetic modifications (Zhang et al, 2020 ), transcription factors (Thompson et al, 2019 ), enhancers/repressors (Conboy, 2021 ), and RNA binding proteins (Yee et al, 2019 ). Neuron-enriched RBPs, such as RBFOX1 (Jacko et al, 2018 ; Begg et al, 2020 ), ELAVL (Hinman et al, 2013 ; Yokoi et al, 2017 ), NOVA (Jensen et al, 2000 ; Ule et al, 2006 ), and MBNL2 (Wang et al, 2012 , 2015 ; Taliaferro et al, 2016 ), regulate neuronal-specific, or even neuron class-specific (Feng et al, 2021 ), splicing programs by binding to highly conserved sequence motifs in pre-mRNAs and recruiting spliceosome factors to promote or inhibit splicing of specific exons.…”