转录组
生物
计算生物学
基因组
基因
核糖核酸
基因表达
遗传学
作者
Dheeraj Chandra Joshi,Surendra Singh Patel,Beena Pillai
出处
期刊:Elsevier eBooks
[Elsevier]
日期:2022-10-14
卷期号:: 175-197
标识
DOI:10.1016/b978-0-323-91810-7.00019-4
摘要
Spatio-temporal regulation of gene expression lies at the core of many biological phenomena like memory, self-organization, and growth and differentiation. Sequencing of the human and other genomes collectively showed that although only a fraction of the genome codes for proteins, it is pervasively transcribed. The expression profile of thousands of RNA transcripts, protein-coding, or otherwise, provides invaluable information about the identity, fate, and potential of tissues. However, homogenization of a large number of cells to collect RNA for transcriptomics studies masks rare cells and underplays the role of spatial organization. A new set of techniques, collectively called spatial transcriptomics, aims to detect thousands of gene transcripts at high resolution in tissues and cells. Here, we discuss the principle used in two major types of spatial transcriptomics techniques. Further we describe how spatial transcriptomics is contributing to the growth of key areas of biology.
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