Re-evaluating microglia expression profiles using RiboTag and cell isolation strategies

Nature Immunology
Zhana HaimonSteffen Jung

Abstract

Transcriptome profiling is widely used to infer functional states of specific cell types, as well as their responses to stimuli, to define contributions to physiology and pathophysiology. Focusing on microglia, the brain's macrophages, we report here a side-by-side comparison of classical cell-sorting-based transcriptome sequencing and the 'RiboTag' method, which avoids cell retrieval from tissue context and yields translatome sequencing information. Conventional whole-cell microglial transcriptomes were found to be significantly tainted by artifacts introduced by tissue dissociation, cargo contamination and transcripts sequestered from ribosomes. Conversely, our data highlight the added value of RiboTag profiling for assessing the lineage accuracy of Cre recombinase expression in transgenic mice. Collectively, this study indicates method-based biases, reveals observer effects and establishes RiboTag-based translatome profiling as a valuable complement to standard sorting-based profiling strategies.

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Citations

Jul 6, 2018·European Journal of Immunology·Christiane Ruedl, Steffen Jung
Nov 9, 2018·European Journal of Immunology·Sigalit Boura-HalfonAssaf Rudich
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Datasets Mentioned

BETA
GSE114001

Methods Mentioned

BETA
immunoprecipitation
pulldown
transgenic
RNA-seq
flow cytometry
fluorescence-activated cell sorting

Software Mentioned

HOMER
RSEM
DESeq2
Olympus browser
CreER
GENCODE
Treestar
Sort
IPA
IP

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