4.8 Article

Internally controlled RNA sequencing comparisons using nucleoside recoding chemistry

期刊

NUCLEIC ACIDS RESEARCH
卷 50, 期 19, 页码 -

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OXFORD UNIV PRESS
DOI: 10.1093/nar/gkac693

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资金

  1. NIH NIGMS [T32GM007223]
  2. NIH [K99 GM135533, T32 GM67543-19, R01 GM132358, R01 GM137117]
  3. NIH New Innovator Award [DP2 HD083992-01]

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Quantitative comparisons of RNA levels using TILAC can distinguish biological variation from variable sample preparation, making it a valuable tool for improving biological insights. TILAC uses metabolic labels to differentially label RNAs and allows for pooling of experimental and control samples before downstream manipulations. The method has been successfully applied to uncover differences in mRNA association with actively translating ribosomes and identify translationally upregulated transcripts.
Quantitative comparisons of RNA levels from different samples can lead to new biological understanding if they are able to distinguish biological variation from variable sample preparation. These challenges are pronounced in comparisons that require complex biochemical manipulations (e.g. isolating polysomes to study translation). Here, we present Transcript Regulation Identified by Labeling with Nucleoside Analogues in Cell Culture (TILAC), an internally controlled approach for quantitative comparisons of RNA content. TILAC uses two metabolic labels, 4-thiouridine (s(4)U) and 6-thioguanosine (s(6)G), to differentially label RNAs in cells, allowing experimental and control samples to be pooled prior to downstream biochemical manipulations. TILAC leverages nucleoside recoding chemistry to generate characteristic sequencing signatures for each label and uses statistical modeling to compare the abundance of RNA transcripts between samples. We verified the performance of TILAC in transcriptome-scale experiments involving RNA polymerase II inhibition and heat shock. We then applied TILAC to quantify changes in mRNA association with actively translating ribosomes during sodium arsenite stress and discovered a set of transcripts that are translationally upregulated, including MCM2 and DDX5. TILAC is broadly applicable to uncover differences between samples leading to improved biological insights.

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