| Autor: |
Acevedo A; Biomedical Engineering Department, Rutgers University, Piscataway, NJ, USA., Mavroudis PD; Quantitative Pharmacology, DMPK, Sanofi, Waltham, MA, USA., DuBois D; Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, State University of New York at Buffalo, Buffalo, NY, USA.; Department of Biological Sciences, State University of New York at Buffalo, Buffalo, NY, USA., Almon RR; Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, State University of New York at Buffalo, Buffalo, NY, USA.; Department of Biological Sciences, State University of New York at Buffalo, Buffalo, NY, USA., Jusko WJ; Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, State University of New York at Buffalo, Buffalo, NY, USA.; Department of Biological Sciences, State University of New York at Buffalo, Buffalo, NY, USA., Androulakis IP; Biomedical Engineering Department, Rutgers University, Piscataway, NJ, USA. yannis@soe.rutgers.edu.; Chemical and Biochemical Engineering Department, Rutgers University, Piscataway, NJ, USA. yannis@soe.rutgers.edu.; Department of Surgery, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ, USA. yannis@soe.rutgers.edu. |
| Abstrakt: |
A computational framework is developed to enable the characterization of genome-wide, multi-tissue circadian dynamics at the level of "functional groupings of genes" defined in the context of signaling, cellular/genetic processing and metabolic pathways in rat and mouse. Our aim is to identify how individual genes come together to generate orchestrated rhythmic patterns and how these may vary within and across tissues. We focus our analysis on four tissues (adipose, liver, lung, and muscle). A genome-wide pathway-centric analysis enables us to develop a comprehensive picture on how the observed circadian variation at the individual gene level, orchestrates functional responses at the pathway level. Such pathway-based "meta-data" analysis enables the rational integration and comparison across platforms and/or experimental designs evaluating emergent dynamics, as opposed to comparisons of individual elements. One of our key findings is that when considering the dynamics at the pathway level, a complex behavior emerges. Our work proposes that tissues tend to coordinate gene's circadian expression in a way that optimizes tissue-specific pathway activity, depending of each tissue's broader role in homeostasis. |
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