Single-Cell Transcriptional Analysis

Despite being a relatively recent technological development, single-cell transcriptional analysis through high-throughput sequencing has already been used in hundreds of fruitful studies to make exciting new biological discoveries that would otherwise be challenging or even impossible. Consequently,...

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Published inAnnual review of analytical chemistry (Palo Alto, Calif.) Vol. 10; no. 1; pp. 439 - 462
Main Authors Wu, Angela R, Wang, Jianbin, Streets, Aaron M, Huang, Yanyi
Format Journal Article
LanguageEnglish
Published United States Annual Reviews 12.06.2017
Annual Reviews, Inc
Subjects
Animals
Bioinformatics
Biology
Computation
Computer applications
DNA - analysis
DNA - chemistry
DNA - metabolism
gene expression
Gene sequencing
heterogeneity
High-Throughput Nucleotide Sequencing
Humans
Instrumentation
Microfluidics
Molecular biology
Next-generation sequencing
Polymerase Chain Reaction
Ribonucleic acid
RNA
RNA Splicing
RNA-seq
Sample preparation
Sequence Analysis, RNA
Single-Cell Analysis - methods
Technology assessment
Transcription
RNA-seq
next-generation sequencing
microfluidics
gene expression
heterogeneity
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Summary:Despite being a relatively recent technological development, single-cell transcriptional analysis through high-throughput sequencing has already been used in hundreds of fruitful studies to make exciting new biological discoveries that would otherwise be challenging or even impossible. Consequently, this has fueled a virtuous cycle of even greater interest in the field and compelled development of further improved technical methodologies and approaches. Thanks to the combined efforts of the research community, including the fields of biochemistry and molecular biology, technology and instrumentation, data science, computational biology, and bioinformatics, the single-cell RNA-sequencing field is advancing at a pace that is both astounding and unprecedented. In this review, we provide a broad introduction to this revolutionary technology by presenting the state-of-the-art in sample preparation methodologies, technology platforms, and computational analysis methods, while highlighting the key considerations for designing, executing, and interpreting a study using single-cell RNA sequencing.
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ISSN:1936-1327
1936-1335
DOI:10.1146/annurev-anchem-061516-045228