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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.
Pubmed ID: 29777220 RIS Download
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Software package for quantifying gene and isoform abundances from single end or paired end RNA Seq data. Accurate transcript quantification from RNA Seq data with or without reference genome. Used for accurate quantification of gene and isoform expression from RNA-Seq data.
View all literature mentionsAn Antibody supplier; Dako was purchased by Agilent in 2012 and several years later the websites began to reflect the Dako products as part of the Agilent catalog.
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View all literature mentionsMus musculus with name B6N.129-Rpl22tm1.1Psam/J from IMSR.
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View all literature mentionsThis polyclonal targets Iba1
View all literature mentionsThis polyclonal targets Iba1
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