2017
DOI: 10.1101/207787
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Transcription factor activity rhythms and tissue-specific chromatin interactions explain circadian gene expression across organs

Abstract: Temporal control of physiology requires the interplay between gene networks involved in daily timekeeping and tissue function across different organs. How the circadian clock interweaves with tissue-specific transcriptional programs is poorly understood. Here we dissected temporal and tissue-specific regulation at multiple gene regulatory layers by examining mouse tissues with an intact or disrupted clock over time. Integrated analysis uncovered two distinct regulatory modes underlying tissue-specific rhythms:… Show more

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Cited by 8 publications
(10 citation statements)
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“…30 Noteworthy, such rhythmic enhancer-promoter interactions are tissue specific. 31,32 The resulting core clock autoregulatory feedback loop lasts about 24 hours, and its molecular composition is identical for central and peripheral oscillators ( Figure 1C). In fact, circadian oscillators function in a cell-autonomous and self-sustained manner in nearly all cells of the body, thereby establishing a complex network that is regulated at the cellular, organ and organismal levels.…”
Section: Of 14 |mentioning
confidence: 99%
“…30 Noteworthy, such rhythmic enhancer-promoter interactions are tissue specific. 31,32 The resulting core clock autoregulatory feedback loop lasts about 24 hours, and its molecular composition is identical for central and peripheral oscillators ( Figure 1C). In fact, circadian oscillators function in a cell-autonomous and self-sustained manner in nearly all cells of the body, thereby establishing a complex network that is regulated at the cellular, organ and organismal levels.…”
Section: Of 14 |mentioning
confidence: 99%
“…The widespread lack of correspondence between promoter and transcription dynamics hint at a model where transcription happens from an accessible promoter under the regulation of a distal element mediated by transcription factors (TF). A TF motif activity analysis (40,41) taking advantage of our paired RNA-seq and ATACseq data predicted the SRF (serum response factor) motif to be by far the most statistically significant candidate in the entire temporal gene expression dataset (i.e.…”
Section: Gene Expression Correlates With Chromatin Accessibility At Dmentioning
confidence: 99%
“…binding site predictions and the temporal mRNA abundance, using a penalized regression model (MARA) as previously described (40,41) and using an L 2 norm penalty for regularization (ridge regression). Prior to the regression, we meancentered the input matrix of temporal mRNA abundances, standardized the columns of the site count matrix (each motif across genes), and excluded genes that were assigned to the flat model (F).…”
Section: Prediction Of Transcription Factor (Tf) Binding Site (Tfbs) mentioning
confidence: 99%
“…During macrophage differentiation, extensive changes are observed to gene expression, the enhancer landscape, and chromatin interactions linking them [73]; however IMR90 cells show extensive changes in enhancer activity and gene expression in response to TNFa treatment yet virtually no differences in DNA looping are observed [74]. Studies on circadian effects in mouse liver have shown selective interactions between circadian oscillating genes and oscillating enhancers, but did not directly show a related rhythmicity of 3D interactions (either no observed differences [75], or the comparison was not made [76]). Based on the sensitivity of distally-regulated genes to cohesin depletion, we predict that looping from distal sex-biased enhancers would be more responsive to alterations of the plasma growth hormone pattern.…”
Section: Matthews and Waxman -Pagementioning
confidence: 99%