Dataset Information

ECHO: an application for detection and analysis of oscillators identifies metabolic regulation on genome-wide circadian output.

ABSTRACT: MOTIVATION:Time courses utilizing genome scale data are a common approach to identifying the biological pathways that are controlled by the circadian clock, an important regulator of organismal fitness. However, the methods used to detect circadian oscillations in these datasets are not able to accommodate changes in the amplitude of the oscillations over time, leading to an underestimation of the impact of the clock on biological systems. RESULTS:We have created a program to efficaciously identify oscillations in large-scale datasets, called the Extended Circadian Harmonic Oscillator application, or ECHO. ECHO utilizes an extended solution of the fixed amplitude oscillator that incorporates the amplitude change coefficient. Employing synthetic datasets, we determined that ECHO outperforms existing methods in detecting rhythms with decreasing oscillation amplitudes and in recovering phase shift. Rhythms with changing amplitudes identified from published biological datasets revealed distinct functions from those oscillations that were harmonic, suggesting purposeful biologic regulation to create this subtype of circadian rhythms. AVAILABILITY AND IMPLEMENTATION:ECHO's full interface is available at https://github.com/delosh653/ECHO. An R package for this functionality, echo.find, can be downloaded at https://CRAN.R-project.org/package=echo.find. SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.

SUBMITTER: De Los Santos H

PROVIDER: S-EPMC7523678 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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ECHO: an application for detection and analysis of oscillators identifies metabolic regulation on genome-wide circadian output.

De Los Santos Hannah H Collins Emily J EJ Mann Catherine C Sagan April W AW Jankowski Meaghan S MS Bennett Kristin P KP Hurley Jennifer M JM

Bioinformatics (Oxford, England) 20200201 3

<h4>Motivation</h4>Time courses utilizing genome scale data are a common approach to identifying the biological pathways that are controlled by the circadian clock, an important regulator of organismal fitness. However, the methods used to detect circadian oscillations in these datasets are not able to accommodate changes in the amplitude of the oscillations over time, leading to an underestimation of the impact of the clock on biological systems.<h4>Results</h4>We have created a program to effi ...[more]

PMID: 31384918

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Project description:MotivationCircadian oscillations have been observed in animals, plants, fungi and cyanobacteria and play a fundamental role in coordinating the homeostasis and behavior of biological systems. Genetically encoded molecular clocks found in nearly every cell, based on negative transcription/translation feedback loops and involving only a dozen genes, play a central role in maintaining these oscillations. However, high-throughput gene expression experiments reveal that in a typical tissue, a much larger fraction ([Formula: see text]) of all transcripts oscillate with the day-night cycle and the oscillating species vary with tissue type suggesting that perhaps a much larger fraction of all transcripts, and perhaps also other molecular species, may bear the potential for circadian oscillations.ResultsTo better quantify the pervasiveness and plasticity of circadian oscillations, we conduct the first large-scale analysis aggregating the results of 18 circadian transcriptomic studies and 10 circadian metabolomic studies conducted in mice using different tissues and under different conditions. We find that over half of protein coding genes in the cell can produce transcripts that are circadian in at least one set of conditions and similarly for measured metabolites. Genetic or environmental perturbations can disrupt existing oscillations by changing their amplitudes and phases, suppressing them or giving rise to novel circadian oscillations. The oscillating species and their oscillations provide a characteristic signature of the physiological state of the corresponding cell/tissue. Molecular networks comprise many oscillator loops that have been sculpted by evolution over two trillion day-night cycles to have intrinsic circadian frequency. These oscillating loops are coupled by shared nodes in a large network of coupled circadian oscillators where the clock genes form a major hub. Cells can program and re-program their circadian repertoire through epigenetic and other mechanisms.Availability and implementationHigh-resolution and tissue/condition specific circadian data and networks available at http://circadiomics.igb.uci.edu.Contactpfbaldi@ics.uci.eduSupplementary informationSupplementary data are available at Bioinformatics online.

Dataset Information

ECHO: an application for detection and analysis of oscillators identifies metabolic regulation on genome-wide circadian output.

Publications

ECHO: an application for detection and analysis of oscillators identifies metabolic regulation on genome-wide circadian output.

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