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Enhancer reprogramming in mammalian genomes

Overview of attention for article published in BMC Bioinformatics, September 2018
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Title
Enhancer reprogramming in mammalian genomes
Published in
BMC Bioinformatics, September 2018
DOI 10.1186/s12859-018-2343-7
Pubmed ID
Authors

Mario A. Flores, Ivan Ovcharenko

Abstract

Transcription factor binding site (TFBS) loss, gain, and reshuffling within the sequence of a regulatory element could alter the function of that regulatory element. Some of the changes will be detrimental to the fitness of the species and will result in gradual removal from a population, while other changes would be either beneficial or just a part of genetic drift and end up being fixed in a population. This "reprogramming" of regulatory elements results in modification of the gene regulatory landscape during evolution. We identified reprogrammed enhancers (RPEs) by comparing the distribution of tissue-specific enhancers in the human and mouse genomes. We observed that around 30% of mammalian enhancers have been reprogrammed after the human-mouse speciation. In 79% of cases, the reprogramming of an enhancer resulted in a quantifiably different expression of a flanking gene. In the case of the Thy-1 cell surface antigen gene, for example, enhancer reprogramming is associated with cortex to thymus change in gene expression. To understand the mechanisms of enhancer reprogramming, we profiled the evolutionary changes in the TFBS enhancer content and found that enhancer reprogramming took place through the acquisition of new TFBSs in 72% of reprogramming events. Our results suggest that enhancer reprogramming takes place within well-established regulatory loci with RPEs contributing additively to fine-tuning of the gene regulatory program in mammals. We also found evidence for acquisition of novel gene function through enhancer reprogramming, which allows expansion of gene regulatory landscapes into new regulatory domains.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 29 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 24%
Student > Ph. D. Student 6 21%
Other 4 14%
Student > Postgraduate 3 10%
Student > Doctoral Student 2 7%
Other 6 21%
Unknown 1 3%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 12 41%
Agricultural and Biological Sciences 6 21%
Medicine and Dentistry 3 10%
Environmental Science 1 3%
Nursing and Health Professions 1 3%
Other 4 14%
Unknown 2 7%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 08 December 2018.
All research outputs
#14,574,276
of 23,344,526 outputs
Outputs from BMC Bioinformatics
#4,835
of 7,387 outputs
Outputs of similar age
#190,104
of 337,913 outputs
Outputs of similar age from BMC Bioinformatics
#66
of 104 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,387 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
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We're also able to compare this research output to 104 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.