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Removal of unwanted variation reveals novel patterns of gene expression linked to sleep homeostasis in murine cortex

Overview of attention for article published in BMC Genomics, October 2016
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  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

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Title
Removal of unwanted variation reveals novel patterns of gene expression linked to sleep homeostasis in murine cortex
Published in
BMC Genomics, October 2016
DOI 10.1186/s12864-016-3065-8
Pubmed ID
Authors

Jason R. Gerstner, John N. Koberstein, Adam J. Watson, Nikolai Zapero, Davide Risso, Terence P. Speed, Marcos G. Frank, Lucia Peixoto

Abstract

Why we sleep is still one of the most perplexing mysteries in biology. Strong evidence indicates that sleep is necessary for normal brain function and that sleep need is a tightly regulated process. Surprisingly, molecular mechanisms that determine sleep need are incompletely described. Moreover, very little is known about transcriptional changes that specifically accompany the accumulation and discharge of sleep need. Several studies have characterized differential gene expression changes following sleep deprivation. Much less is known, however, about changes in gene expression during the compensatory response to sleep deprivation (i.e. recovery sleep). In this study we present a comprehensive analysis of the effects of sleep deprivation and subsequent recovery sleep on gene expression in the mouse cortex. We used a non-traditional analytical method for normalization of genome-wide gene expression data, Removal of Unwanted Variation (RUV). RUV improves detection of differential gene expression following sleep deprivation. We also show that RUV normalization is crucial to the discovery of differentially expressed genes associated with recovery sleep. Our analysis indicates that the majority of transcripts upregulated by sleep deprivation require 6 h of recovery sleep to return to baseline levels, while the majority of downregulated transcripts return to baseline levels within 1-3 h. We also find that transcripts that change rapidly during recovery (i.e. within 3 h) do so on average with a time constant that is similar to the time constant for the discharge of sleep need. We demonstrate that proper data normalization is essential to identify changes in gene expression that are specifically linked to sleep deprivation and recovery sleep. Our results provide the first evidence that recovery sleep is comprised of two waves of transcriptional regulation that occur at different times and affect functionally distinct classes of genes.

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X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 24%
Student > Bachelor 4 11%
Researcher 4 11%
Student > Postgraduate 3 8%
Student > Master 3 8%
Other 5 14%
Unknown 9 24%
Readers by discipline Count As %
Neuroscience 7 19%
Biochemistry, Genetics and Molecular Biology 7 19%
Agricultural and Biological Sciences 3 8%
Medicine and Dentistry 3 8%
Computer Science 2 5%
Other 4 11%
Unknown 11 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 September 2019.
All research outputs
#6,128,258
of 22,899,952 outputs
Outputs from BMC Genomics
#2,603
of 10,673 outputs
Outputs of similar age
#93,496
of 313,872 outputs
Outputs of similar age from BMC Genomics
#49
of 223 outputs
Altmetric has tracked 22,899,952 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 10,673 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 75% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 313,872 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 223 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.