bioRxivMolecular BiologyPreprint
Degradation intermediates as an indicator of mRNA and cell metabolism
Yusheng LiuiD, Yiwei ZhangiD, Hu NieiD, Falong LuiD, Jiaqiang WangiD
Abstract
Traditional mRNA degradation rate measurements involves complex experimental design with RNA labeling or transcription blocking together with sampling at multiple timepoints1,2. These experimental requirements limit the application of transcriptome-wide mRNA degradation rate analysis mainly in cultured cells, but rarely in in vivo samples. Therefore, a direct and simple strategy needs to be developed to study mRNA degradation rate. Here, we defined mRNA degradation intermediates as transcripts where decay is about to occur or has partially occurred in the 3-untranslated regions after poly(A) tail deadenylation, and found that the proportion of mRNA degradation intermediates is a very simple and convenient indicator for evaluating the degradation rate of mRNA in mouse and human cell lines. In addition, we showed that a higher proportion of mRNA degradation intermediates is correlated with faster cell cycle and higher turnover rate of mouse tissues. Further, we validated that in mouse maturing oocytes where transcription is silent3,4, the proportion of mRNA degradation intermediates is positively correlated with the mRNA degradation rate. Together, these results demonstrate that degradation intermediates can function as a good indicator of mRNA, cell, and tissue metabolism, and can be easily assayed by total RNA 3-end sequencing from a single bulk cell sample without the need for drug treatment or multi-timepoint sampling. This finding is of great potential for studies on mRNA degradation rate at the molecular, cellular, or organic level, including samples or systems that cannot be assayed with previous methods. In addition, further application of the findings into single cells will likely greatly aid the identification and study of rare cells with unique cellular metabolism dynamics such as tissue stem cells and tumor cells.
- organism: mouse
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: database / resource
- research focus: benchmarking
- approach: statistical model
- Citations
- 0
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