Deciphering the cellular heterogeneity of the insect brain with single-cell RNA sequencing

文献类型： 外文期刊

第一作者： Wang, Xiaofei

作者： Wang, Xiaofei;Zhai, Yifan;Zheng, Hao;Wang, Xiaofei;Zheng, Hao;Zhai, Yifan;Zhai, Yifan

作者机构：

关键词： behavior; brain; cell type; insect; single-cell RNA sequencing

期刊名称：INSECT SCIENCE （ 影响因子：4.0； 五年影响因子：3.6 ）

ISSN： 1672-9609

年卷期： 2023 年

页码：

收录情况： SCI

摘要： Insects show highly complicated adaptive and sophisticated behaviors, including spatial orientation skills, learning ability, and social interaction. These behaviors are controlled by the insect brain, the central part of the nervous system. The tiny insect brain consists of millions of highly differentiated and interconnected cells forming a complex network. Decades of research has gone into an understanding of which parts of the insect brain possess particular behaviors, but exactly how they modulate these functional consequences needs to be clarified. Detailed description of the brain and behavior is required to decipher the complexity of cell types, as well as their connectivity and function. Single-cell RNA-sequencing (scRNA-seq) has emerged recently as a breakthrough technology to understand the transcriptome at cellular resolution. With scRNA-seq, it is possible to uncover the cellular heterogeneity of brain cells and elucidate their specific functions and state. In this review, we first review the basic structure of insect brains and the links to insect behaviors mainly focusing on learning and memory. Then the scRNA applications on insect brains are introduced by representative studies. Single-cell RNA-seq has allowed researchers to classify cell subpopulations within different insect brain regions, pinpoint single-cell developmental trajectories, and identify gene regulatory networks. These developments empower the advances in neuroscience and shed light on the intricate problems in understanding insect brain functions and behaviors. Single-cell RNA sequencing (scRNA-seq) has emerged in the past decade and profoundly accelerated our understanding of brain complexity. scRNA-seq has a higher resolution than bulk RNA-seq, which enables novel cell type classification, dynamic trajectory construction, and gene regulatory network identification. To give a general understanding of scRNA-seq application in brain science, we depict a brief overview of the experimental workflow and a typical downstream data analysis in this graphical abstract.image

分类号：

  • 相关文献
作者其他论文 更多>>

微信小程序