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The landscape of regulatory genes in brain-wide neuronal phenotypes of a vertebrate brain.
Zhang, Hui; Wang, Haifang; Shen, Xiaoyu; Jia, Xinling; Yu, Shuguang; Qiu, Xiaoying; Wang, Yufan; Du, Jiulin; Yan, Jun; He, Jie.
Afiliação
  • Zhang H; Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.
  • Wang H; University of Chinese Academy of Sciences, Beijing, China.
  • Shen X; Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China.
  • Jia X; Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.
  • Yu S; Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China.
  • Qiu X; Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.
  • Wang Y; Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China.
  • Du J; Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.
  • Yan J; Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China.
  • He J; Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.
Elife ; 102021 12 13.
Article em En | MEDLINE | ID: mdl-34895465
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.
The brain harbors an astounding diversity of interconnected cells. Each cell contains the same basic set of genetic instructions, but only a fraction of the genome is used in each cell to assemble proteins. This selective gene expression gives rise to each cell's characteristic properties, such as their shape and location, or whether they can activate or inhibit neighbouring cells. How these defining features are encoded on a genetic level and selectively activated in cells to produce such diversity in the brain is not fully understood. One way to study gene expression in single cells involves profiling the transcriptome, the full range of intermediary RNA molecules a cell produces from its genes to make proteins. Zhang et al. used transcriptome profiling to better understand how thousands of regulatory genes encoding regulatory proteins called transcription factors create different types of neurons in the zebrafish brain, which is similar to but much simpler than the human brain. To do so, they analysed transcriptome data extracted from cell populations located in specific brain regions and displaying different properties. Zhang et al. identified distinct clusters of neurons in the larval zebrafish brain. Mathematical models then analysed the transcriptome profiles of these neuronal clusters with characteristic features. They revealed that neurons with similar characteristics did not necessarily share the same transcription factors. In other words, distinct sets of transcription factors gave rise to the same types of cells. Zhang et al. described this observation as a 'convergent' pattern. On the contrary, some neurons with dissimilar features expressed the same sorts of transcription factors, suggesting a 'divergent' developmental pattern also exists. In summary, this work sheds light on variable gene expression patterns akin to design principles that shape neuronal diversity in the brain. It gives a new appreciation of how neuronal subtypes result from a complex set of regulatory factors controlling gene expression.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Fenótipo / Peixe-Zebra / Genes Reguladores / Regulação da Expressão Gênica no Desenvolvimento / Transcriptoma / Neurônios Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Revista: Elife Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Fenótipo / Peixe-Zebra / Genes Reguladores / Regulação da Expressão Gênica no Desenvolvimento / Transcriptoma / Neurônios Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Revista: Elife Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China
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