SLAM-ITseq: sequencing cell type-specific transcriptomes without cell sorting.
View / Open Files
Authors
Herzog, Veronika A
Neumann, Tobias
Gapp, Katharina
Zuber, Johannes
Publication Date
2018-07-11Journal Title
Development
ISSN
0950-1991
Publisher
The Company of Biologists
Volume
145
Issue
13
Language
eng
Type
Article
Physical Medium
Electronic
Metadata
Show full item recordCitation
Matsushima, W., Herzog, V. A., Neumann, T., Gapp, K., Zuber, J., Ameres, S. L., & Miska, E. (2018). SLAM-ITseq: sequencing cell type-specific transcriptomes without cell sorting.. Development, 145 (13) https://doi.org/10.1242/dev.164640
Abstract
Cell type-specific transcriptome analysis is an essential tool for understanding biological processes in which diverse types of cells are involved. Although cell isolation methods such as fluorescence-activated cell sorting (FACS) in combination with transcriptome analysis have widely been used so far, their time-consuming and harsh procedures limit their applications. Here, we report a novel in vivo metabolic RNA sequencing method, SLAM-ITseq, which metabolically labels RNA with 4-thiouracil in a specific cell type in vivo followed by detection through an RNA-seq-based method that specifically distinguishes the thiolated uridine by base conversion. This method has successfully identified the cell type-specific transcriptome in three different tissues: endothelial cells in brain, epithelial cells in intestine and adipocytes in white adipose tissue. As this method does not require isolation of cells or RNA prior to the transcriptomic analysis, SLAM-ITseq provides an easy yet accurate snapshot of the transcriptional state in vivo.
Keywords
Brain, Endothelial Cells, Animals, Mice, Thiouracil, RNA, Flow Cytometry, Staining and Labeling, Adipocytes, White, High-Throughput Nucleotide Sequencing, Transcriptome
Sponsorship
Cancer Research UK (18583)
Wellcome Trust (092096/Z/10/Z)
Wellcome Trust (104640/Z/14/Z)
Cancer Research Uk (None)
Identifiers
External DOI: https://doi.org/10.1242/dev.164640
This record's URL: https://www.repository.cam.ac.uk/handle/1810/283428
Statistics
Total file downloads (since January 2020). For more information on metrics see the
IRUS guide.