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Deciphering Brain Complexity Using Single-cell Sequencing 被引量:4

Deciphering Brain Complexity Using Single-cell Sequencing
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摘要 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. 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.
出处 《Genomics, Proteomics & Bioinformatics》 SCIE CAS CSCD 2019年第4期344-366,共23页 基因组蛋白质组与生物信息学报(英文版)
基金 supported by the Research Grants Council (RGC) (Grant No. 26102719),Hong Kong Special Administrative Region (SAR), China the National Natural Science Foundation of China (NSFC) (No. 31922088) NSFC-RGC Joint Research Scheme (Grant No. N_HKUST606/17), Hong Kong SAR, China the Collaborative Research Fund (CRF) (Grant Nos. C6002-17GF and C7065-18GF), Hong Kong SAR, China the Hong Kong Epigenomics Project (Epi HK) the Innovation and Technology Commission (ITCPD/17-9, ITS/480/18FP), Hong Kong SAR, China
关键词 NEUROSCIENCE Single-cell RNA-seq Cell type Brain development Brain diseases Neuroscience Single-cell RNA-seq Cell type Brain development Brain diseases
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