Abstract
Multidimensional landscapes of regulatory genes in neuronal phenotypes at whole-brain levels in the vertebrate remain elusive. We generated single-cell transcriptomes of ~67,000 region- and neurotransmitter/neuromodulator-identifiable cells from larval zebrafish brains. Hierarchical clustering based on effector gene profiles ('terminal features') distinguished major brain cell types. Sister clusters at hierarchical termini displayed similar terminal features. It was further verified by a population-level statistical method. Intriguingly, glutamatergic/GABAergic sister clusters mostly expressed distinct transcription factor (TF) profiles ('convergent pattern'), whereas neuromodulator-type sister clusters predominantly expressed the same TF profiles ('matched pattern'). Interestingly, glutamatergic/GABAergic clusters with similar TF profiles could also display different terminal features ('divergent pattern'). It led us to identify a library of RNA-binding proteins that differentially marked divergent pair clusters, suggesting the post-transcriptional regulation of neuron diversification. Thus, our findings reveal multidimensional landscapes of transcriptional and post-transcriptional regulators in whole-brain neuronal phenotypes in the zebrafish brain.
Highlights
The vertebrate brain harbors highly diverse neuronal types that are interconnected to form functional circuits (Kepecs and Fishell 2014, Armananzas and Ascoli 2015, Moffitt, Bambah-Mukku et al 2018)
We found out of 11 effector genes-based sister clusters, only 1 pairs could be found in transcriptional factor (TF)-based sister clusters (Clusters 9/61, “matched pattern”, Figure 3-figure supplement 2B)
Our analysis demonstrated the landscape of TFs in 364 whole brain-wide neuronal phenotypes in the larval zebrafish brain
Summary
The vertebrate brain harbors highly diverse neuronal types that are interconnected to form functional circuits (Kepecs and Fishell 2014, Armananzas and Ascoli 2015, Moffitt, Bambah-Mukku et al 2018). The scRNA-seq analysis of nearly 200 genetically marked mouse neuronal populations showed that neurons could be classified by the expression level of various transcription factors (TFs), ion channels, synaptic proteins, and cell adhesion molecules (Sugino, Clark et al 2019). These studies provided extensive information on the molecules that could be used to define neuronal types. We generated the multidimensional landscape of regulator genes in effector gene-based neuronal phenotypes (terminal features) at the whole-brain level by combining single-cell transcriptome data obtained from the whole brain, specific brain regions, as well as neurotransmitter- and neuromodulator-defined neuronal populations. Our findings reveal multidimensional landscapes of transcriptional and post-transcriptional regulators in the whole zebrafish brain
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