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Abstract

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.

Details

Title
Pathway-level analysis of genome-wide circadian dynamics in diverse tissues in rat and mouse
Author
Acevedo, Alison 1 ; Mavroudis Panteleimon D 2 ; DuBois, Debra 3 ; Almon, Richard R 3 ; Jusko, William J 3 ; Androulakis, Ioannis P 4   VIAFID ORCID Logo 

 Rutgers University, Biomedical Engineering Department, Piscataway, USA (GRID:grid.430387.b) (ISNI:0000 0004 1936 8796) 
 Sanofi, Quantitative Pharmacology, DMPK, Waltham, USA (GRID:grid.417555.7) (ISNI:0000 0000 8814 392X) 
 State University of New York at Buffalo, Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, Buffalo, USA (GRID:grid.273335.3) (ISNI:0000 0004 1936 9887); State University of New York at Buffalo, Department of Biological Sciences, Buffalo, USA (GRID:grid.273335.3) (ISNI:0000 0004 1936 9887) 
 Rutgers University, Biomedical Engineering Department, Piscataway, USA (GRID:grid.430387.b) (ISNI:0000 0004 1936 8796); Rutgers University, Chemical and Biochemical Engineering Department, Piscataway, USA (GRID:grid.430387.b) (ISNI:0000 0004 1936 8796); Rutgers-Robert Wood Johnson Medical School, Department of Surgery, New Brunswick, USA (GRID:grid.430387.b) (ISNI:0000 0004 1936 8796) 
Pages
361-374
Publication year
2021
Publication date
Jun 2021
Publisher
Springer Nature B.V.
ISSN
1567567X
e-ISSN
15738744
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2531422391
Copyright
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021.