Genome-wide correlation analysis to identify amplitude regulators of circadian transcriptome output

Abstract Cell-autonomous circadian system, consisting of core clock genes, generates near 24-h rhythms and regulates the downstream rhythmic gene expression. While it has become clear that the percentage of rhythmic genes varies among mouse tissues, it remains unclear how this variation can be gener...

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Autores principales:	Evan S. Littleton, Madison L. Childress, Michaela L. Gosting, Ayana N. Jackson, Shihoko Kojima
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/0c2d30fa82e44ea6bd4b258bf1673672
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spelling	oai:doaj.org-article:0c2d30fa82e44ea6bd4b258bf16736722021-12-02T12:03:16ZGenome-wide correlation analysis to identify amplitude regulators of circadian transcriptome output10.1038/s41598-020-78851-92045-2322https://doaj.org/article/0c2d30fa82e44ea6bd4b258bf16736722020-12-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-78851-9https://doaj.org/toc/2045-2322Abstract Cell-autonomous circadian system, consisting of core clock genes, generates near 24-h rhythms and regulates the downstream rhythmic gene expression. While it has become clear that the percentage of rhythmic genes varies among mouse tissues, it remains unclear how this variation can be generated, particularly when the clock machinery is nearly identical in all tissues. In this study, we sought to characterize circadian transcriptome datasets that are publicly available and identify the critical component(s) involved in creating this variation. We found that the relative amplitude of 13 genes and the average level of 197 genes correlated with the percentage of cycling genes. Of those, the correlation of Rorc in both relative amplitude and the average level was one of the strongest. In addition, the level of Per2AS, a novel non-coding transcript that is expressed at the Period 2 locus, was also linearly correlated, although with a much lesser degree compared to Rorc. Overall, our study provides insight into how the variation in the percentage of clock-controlled genes can be generated in mouse tissues and suggests that Rorc and potentially Per2AS are involved in regulating the amplitude of circadian transcriptome output.Evan S. LittletonMadison L. ChildressMichaela L. GostingAyana N. JacksonShihoko KojimaNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 10, Iss 1, Pp 1-13 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Evan S. Littleton Madison L. Childress Michaela L. Gosting Ayana N. Jackson Shihoko Kojima Genome-wide correlation analysis to identify amplitude regulators of circadian transcriptome output
description	Abstract Cell-autonomous circadian system, consisting of core clock genes, generates near 24-h rhythms and regulates the downstream rhythmic gene expression. While it has become clear that the percentage of rhythmic genes varies among mouse tissues, it remains unclear how this variation can be generated, particularly when the clock machinery is nearly identical in all tissues. In this study, we sought to characterize circadian transcriptome datasets that are publicly available and identify the critical component(s) involved in creating this variation. We found that the relative amplitude of 13 genes and the average level of 197 genes correlated with the percentage of cycling genes. Of those, the correlation of Rorc in both relative amplitude and the average level was one of the strongest. In addition, the level of Per2AS, a novel non-coding transcript that is expressed at the Period 2 locus, was also linearly correlated, although with a much lesser degree compared to Rorc. Overall, our study provides insight into how the variation in the percentage of clock-controlled genes can be generated in mouse tissues and suggests that Rorc and potentially Per2AS are involved in regulating the amplitude of circadian transcriptome output.
format	article
author	Evan S. Littleton Madison L. Childress Michaela L. Gosting Ayana N. Jackson Shihoko Kojima
author_facet	Evan S. Littleton Madison L. Childress Michaela L. Gosting Ayana N. Jackson Shihoko Kojima
author_sort	Evan S. Littleton
title	Genome-wide correlation analysis to identify amplitude regulators of circadian transcriptome output
title_short	Genome-wide correlation analysis to identify amplitude regulators of circadian transcriptome output
title_full	Genome-wide correlation analysis to identify amplitude regulators of circadian transcriptome output
title_fullStr	Genome-wide correlation analysis to identify amplitude regulators of circadian transcriptome output
title_full_unstemmed	Genome-wide correlation analysis to identify amplitude regulators of circadian transcriptome output
title_sort	genome-wide correlation analysis to identify amplitude regulators of circadian transcriptome output
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/0c2d30fa82e44ea6bd4b258bf1673672
work_keys_str_mv	AT evanslittleton genomewidecorrelationanalysistoidentifyamplituderegulatorsofcircadiantranscriptomeoutput AT madisonlchildress genomewidecorrelationanalysistoidentifyamplituderegulatorsofcircadiantranscriptomeoutput AT michaelalgosting genomewidecorrelationanalysistoidentifyamplituderegulatorsofcircadiantranscriptomeoutput AT ayananjackson genomewidecorrelationanalysistoidentifyamplituderegulatorsofcircadiantranscriptomeoutput AT shihokokojima genomewidecorrelationanalysistoidentifyamplituderegulatorsofcircadiantranscriptomeoutput
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Genome-wide correlation analysis to identify amplitude regulators of circadian transcriptome output

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