Department of Biological Sciences, Rensselaer Polytechnic Institute, Troy, NY 12180, USA.
The MITRE Corporation, Bedford, MA 01730, USA.
G3 (Bethesda). 2022 Aug 25;12(9). doi: 10.1093/g3journal/jkac176.
Circadian rhythms broadly regulate physiological functions by tuning oscillations in the levels of mRNAs and proteins to the 24-h 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 suite. Here, we demonstrate the Pipeline for Amplitude Integration of Circadian Exploration suite's increased utility to detect circadian trends through the joint modeling of the Mus musculus macrophage transcriptome and proteome. Our enhanced detection confirmed extensive circadian posttranscriptional 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 Pipeline for Amplitude Integration of Circadian Exploration suite to investigate the circadian timing of noncoding RNAs, documenting extensive circadian timing of long noncoding 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.
昼夜节律广泛地通过将 mRNA 和蛋白质水平的波动与 24 小时的日/夜周期相匹配来调节生理功能。全面评估哪些 mRNA 和蛋白质受时钟调控,需要准确识别 RNA 和蛋白质数据中的波动,尤其是在大型组学数据集。以前曾使用采用固定幅度模型的工具来产生积极影响。然而,昼夜节律波动幅度变化的识别需要新一代的分析软件来增强对这些波动的识别。为了解决这一差距,我们创建了昼夜节律探索分析套件的幅度整合分析流程。在这里,我们通过对 Mus musculus 巨噬细胞转录组和蛋白质组的联合建模,展示了昼夜节律探索分析套件的幅度整合分析流程的增强实用性,以检测昼夜节律趋势。我们增强的检测结果证实了巨噬细胞中广泛存在的昼夜转录后调控,但也强调了一些报道的 mRNA 和蛋白质波动之间的差异是由于数据中的噪声所致。我们进一步应用昼夜节律探索分析套件来研究非编码 RNA 的昼夜节律计时,记录了长非编码 RNA 和小核 RNA 的广泛昼夜节律计时,这些 RNA 控制着剪接体复合物中 mRNA 的识别。通过使用 PAICE 套件跟踪波动的剪接体复合物蛋白,我们注意到时钟广泛调节剪接体,特别是主要剪接体复合物。由于上述大多数节律在其波动中幅度变化衰减,因此这项工作强调了 PAICE 套件在全面列举组学规模数据集中的波动的重要性。