The human brain contains billions of highly differentiated and interconnected cells that form intricate neural networks and collectively control the physical activities and high-level cognitive functions, such as memory, decision-making, and social behavior. Big data is required to decipher the complexity of cell types, as well as connectivity and functions of the brain. The newly developed single-cell sequencing technology, which provides a comprehensive landscape of brain cell type diversity by profiling the transcriptome, genome, and/or epigenome of individual cells, has contributed substantially to revealing the complexity and dynamics of the brain and providing new insights into brain development and brain-related disorders. In this review, we first introduce the progresses in both experimental and computational methods of single-cell sequencing technology. Applications of single-cell sequencing-based technologies in brain research, including cell type classification, brain development, and brain disease mechanisms, are then elucidated by representative studies. Lastly, we provided our perspectives into the challenges and future developments in the field of single-cell sequencing. In summary, this mini review aims to provide an overview of how big data generated from single-cell sequencing have empowered the advancements in neuroscience and shed light on the complex problems in understanding brain functions and diseases.
人脑包含数十亿个高度分化的细胞，这些细胞相互连接成复杂的神经网络，共同控制身体活动和高级认知功能，例如记忆，决策和社会行为。大数据(Big data) 为解密细胞类型的复杂性、大脑的连接网络和功能提供了前所未有的机会。近年开发的单细胞测序技术通过表征单个细胞的转录组、基因组和表观基因组，提供了脑细胞类型多样性的全面概况，对揭示大脑的复杂性和动态性做出了重大贡献，并为大脑发育和大脑相关疾病的机理提供了新的理解。在这篇综述中，我们首先介绍了单细胞测序技术在实验和计算方法上的进展。随后，通过代表性研究阐明了基于单细胞测序的技术在脑研究中的应用，包括细胞类型分类、脑发育过程，以及脑疾病机制。最后，我们提供了对单细胞测序领域挑战和未来发展的看法。总而言之，本小型综述旨在概述单细胞测序产生的大数据如何促进神经科学的发展，并阐明理解脑功能和疾病的复杂问题。





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