Neural cell diversity in the light of single-cell transcriptomics.

IF 3.6 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Transcription-Austin Pub Date : 2023-06-01 Epub Date: 2024-01-23 DOI:10.1080/21541264.2023.2295044
Sandra María Fernández-Moya, Akshay Jaya Ganesh, Mireya Plass
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引用次数: 0

Abstract

The development of highly parallel and affordable high-throughput single-cell transcriptomics technologies has revolutionized our understanding of brain complexity. These methods have been used to build cellular maps of the brain, its different regions, and catalog the diversity of cells in each of them during development, aging and even in disease. Now we know that cellular diversity is way beyond what was previously thought. Single-cell transcriptomics analyses have revealed that cell types previously considered homogeneous based on imaging techniques differ depending on several factors including sex, age and location within the brain. The expression profiles of these cells have also been exploited to understand which are the regulatory programs behind cellular diversity and decipher the transcriptional pathways driving them. In this review, we summarize how single-cell transcriptomics have changed our view on the cellular diversity in the human brain, and how it could impact the way we study neurodegenerative diseases. Moreover, we describe the new computational approaches that can be used to study cellular differentiation and gain insight into the functions of individual cell populations under different conditions and their alterations in disease.

从单细胞转录组学看神经细胞的多样性
高度并行且价格合理的高通量单细胞转录组学技术的发展彻底改变了我们对大脑复杂性的认识。我们利用这些方法绘制了大脑及其不同区域的细胞图谱,并对每个区域在发育、衰老甚至疾病期间的细胞多样性进行了编目。现在我们知道,细胞的多样性远远超出了以前的想象。单细胞转录组学分析表明,以前根据成像技术被认为是同质的细胞类型会因性别、年龄和在大脑中的位置等多种因素而有所不同。人们还利用这些细胞的表达谱来了解细胞多样性背后的调控程序,并破译驱动它们的转录途径。在这篇综述中,我们总结了单细胞转录组学如何改变了我们对人脑中细胞多样性的看法,以及它如何影响我们研究神经退行性疾病的方式。此外,我们还介绍了新的计算方法,这些方法可用于研究细胞分化,深入了解不同条件下单个细胞群的功能及其在疾病中的改变。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Transcription-Austin
Transcription-Austin BIOCHEMISTRY & MOLECULAR BIOLOGY-
CiteScore
6.50
自引率
5.60%
发文量
9
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