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Circadian Clocks Are Resounding in Peripheral Tissues

Overview of attention for article published in PLoS Computational Biology, March 2006
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Title
Circadian Clocks Are Resounding in Peripheral Tissues
Published in
PLoS Computational Biology, March 2006
DOI 10.1371/journal.pcbi.0020016
Pubmed ID
Authors

Andrey A Ptitsyn, Sanjin Zvonic, Steven A Conrad, L. Keith Scott, Randall L Mynatt, Jeffrey M Gimble

Abstract

Circadian rhythms are prevalent in most organisms. Even the smallest disturbances in the orchestration of circadian gene expression patterns among different tissues can result in functional asynchrony, at the organism level, and may to contribute to a wide range of physiologic disorders. It has been reported that as many as 5%-10% of transcribed genes in peripheral tissues follow a circadian expression pattern. We have conducted a comprehensive study of circadian gene expression on a large dataset representing three different peripheral tissues. The data have been produced in a large-scale microarray experiment covering replicate daily cycles in murine white and brown adipose tissues as well as in liver. We have applied three alternative algorithmic approaches to identify circadian oscillation in time series expression profiles. Analyses of our own data indicate that the expression of at least 7% to 21% of active genes in mouse liver, and in white and brown adipose tissues follow a daily oscillatory pattern. Indeed, analysis of data from other laboratories suggests that the percentage of genes with an oscillatory pattern may approach 50% in the liver. For the rest of the genes, oscillation appears to be obscured by stochastic noise. Our phase classification and computer simulation studies based on multiple datasets indicate no detectable boundary between oscillating and non-oscillating fractions of genes. We conclude that greater attention should be given to the potential influence of circadian mechanisms on any biological pathway related to metabolism and obesity.

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Geographical breakdown

Country Count As %
United Kingdom 2 2%
United States 2 2%
Netherlands 1 <1%
Sweden 1 <1%
Chile 1 <1%
China 1 <1%
France 1 <1%
Unknown 101 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 25%
Researcher 13 12%
Professor 11 10%
Student > Bachelor 10 9%
Student > Postgraduate 10 9%
Other 29 26%
Unknown 10 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 40 36%
Biochemistry, Genetics and Molecular Biology 15 14%
Medicine and Dentistry 12 11%
Neuroscience 6 5%
Sports and Recreations 4 4%
Other 15 14%
Unknown 18 16%