G3 Genes Genomes GeneticsSystems BiologyPeer-reviewed journal article
The PAICE Suite Reveals Circadian Post-Transcriptional Timing of Non-Coding RNAs and Spliceosome Components in Mus musculus Macrophages
Sharleen M. BueliD, Shayom DebopadhayaiD, Hannah De los SantosiD, Kaelyn M. Edwards, Alexandra M David, Uyen H Dao, Kristin P. BennettiD, Jennifer HurleyiD
Abstract
Circadian rhythms broadly regulate physiological functions by tuning oscillations in the levels of mRNAs and proteins to the 24-hour day/night cycle. Globally assessing which mRNAs and proteins are timed by the clock necessitates accurate recognition of oscillations in RNA and protein data, particularly in large omics data sets. Tools that employ fixed-amplitude models have previously been used to positive effect. However, the recognition of amplitude-change in circadian oscillations required a new generation of analytical software to enhance the identification of these oscillations. To address this gap, we created the Pipeline for Amplitude Integration of Circadian Exploration (PAICE) suite. Here, we demonstrate the PAICE suites increased detection of circadian trends through the joint modeling of the Mus musculus macrophage transcriptome and proteome. Our enhanced detection confirmed extensive circadian post-transcriptional regulation in macrophages, but highlighted that some of the reported discrepancy between mRNA and protein oscillations was due to noise in data. We further applied the PAICE suite to investigate the circadian timing of non-coding RNAs, documenting extensive circadian timing of long non-coding RNAs and small nuclear RNAs, which control the recognition of mRNA in the spliceosome complex. By tracking oscillating spliceosome complex proteins using the PAICE suite, we noted that the clock broadly regulates the spliceosome, particularly the major spliceosome complex. As most of the above-noted rhythms had damped amplitude changes in their oscillations, this work highlights the importance of the PAICE suite in the thorough enumeration of oscillations in omics-scale datasets.
- organism: mouse
- assay: bulk RNA-seq
- assay: proteomics
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: database / resource
- research focus: software / tool
- approach: statistical model
- Citations
- 3
- FWCI
- 0.26
- Field percentile
- 46th percentile
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