Chuah Joshua, Cordi Carmalena, Hahn Juergen, Hurley Jennifer
Department of Electrical, Computer, and Biomedical Engineering, Union College, 807 Union St, 12308, NY, USA,.
Department of Biomedical Engineering, Rensselaer Polytechnic Institute, 110 8th St, 12180, NY, USA,.
bioRxiv. 2024 Oct 14:2024.10.10.617622. doi: 10.1101/2024.10.10.617622.
The circadian clock is a central driver of many biological and behavioral processes, regulating the levels of many genes and proteins, termed clock controlled genes and proteins (CCGs/CCPs), to impart biological timing at the molecular level. While transcriptomic and proteomic data has been analyzed to find potential CCGs and CCPs, multi-omic modeling of circadian data, which has the potential to enhance the understanding of circadian control of biological timing, remains relatively rare due to several methodological hurdles. To address this gap, a Dual-approach Co-expression Analysis Framework (D-CAF) was created to perform perturbation-robust co-expression analysis on time-series measurements of both transcripts and proteins. Applying this D-CAF framework to previously gathered transcriptomic and proteomic data from mouse macrophages gathered over circadian time, we identified small, highly significant clusters of oscillating transcripts and proteins in the unweighted similarity matrices and larger, less significant clusters of of oscillating transcripts and proteins using the weighted similarity network. Functional enrichment analysis of these clusters identified novel immunological response pathways that appear to be under circadian control. Overall, our findings suggest that D-CAF is a tool that can be used by the circadian community to integrate multi-omic circadian data to improve our understanding of the mechanisms of circadian regulation of molecular processes.
生物钟是许多生物和行为过程的核心驱动因素,它调节许多基因和蛋白质(称为生物钟控制基因和蛋白质,即CCGs/CCPs)的水平,在分子水平上赋予生物节律。虽然已经分析了转录组学和蛋白质组学数据以寻找潜在的CCGs和CCPs,但由于几个方法上的障碍,昼夜节律数据的多组学建模,这种有可能增强对生物节律控制生物时间的理解的方法,仍然相对较少。为了填补这一空白,创建了一种双方法共表达分析框架(D-CAF),用于对转录本和蛋白质的时间序列测量进行抗干扰共表达分析。将这个D-CAF框架应用于先前收集的小鼠巨噬细胞在昼夜节律时间内的转录组学和蛋白质组学数据,我们在未加权相似性矩阵中识别出了振荡转录本和蛋白质的小而高度显著的簇,并使用加权相似性网络识别出了振荡转录本和蛋白质的更大但不太显著的簇。对这些簇的功能富集分析确定了似乎受昼夜节律控制的新的免疫反应途径。总体而言,我们的研究结果表明,D-CAF是一种生物钟研究领域可以使用的工具,用于整合多组学昼夜节律数据,以增进我们对分子过程昼夜节律调节机制的理解。