↓ Skip to main content

Under-Dominance Constrains the Evolution of Negative Autoregulation in Diploids

Overview of attention for article published in PLoS Computational Biology, March 2013
Altmetric Badge

Mentioned by

twitter
2 X users

Citations

dimensions_citation
19 Dimensions

Readers on

mendeley
31 Mendeley
citeulike
1 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Under-Dominance Constrains the Evolution of Negative Autoregulation in Diploids
Published in
PLoS Computational Biology, March 2013
DOI 10.1371/journal.pcbi.1002992
Pubmed ID
Authors

Alexander J. Stewart, Robert M. Seymour, Andrew Pomiankowski, Max Reuter

Abstract

Regulatory networks have evolved to allow gene expression to rapidly track changes in the environment as well as to buffer perturbations and maintain cellular homeostasis in the absence of change. Theoretical work and empirical investigation in Escherichia coli have shown that negative autoregulation confers both rapid response times and reduced intrinsic noise, which is reflected in the fact that almost half of Escherichia coli transcription factors are negatively autoregulated. However, negative autoregulation is rare amongst the transcription factors of Saccharomyces cerevisiae. This difference is surprising because E. coli and S. cerevisiae otherwise have similar profiles of network motifs. In this study we investigate regulatory interactions amongst the transcription factors of Drosophila melanogaster and humans, and show that they have a similar dearth of negative autoregulation to that seen in S. cerevisiae. We then present a model demonstrating that this striking difference in the noise reduction strategies used amongst species can be explained by constraints on the evolution of negative autoregulation in diploids. We show that regulatory interactions between pairs of homologous genes within the same cell can lead to under-dominance--mutations which result in stronger autoregulation, and decrease noise in homozygotes, paradoxically can cause increased noise in heterozygotes. This severely limits a diploid's ability to evolve negative autoregulation as a noise reduction mechanism. Our work offers a simple and general explanation for a previously unexplained difference between the regulatory architectures of E. coli and yeast, Drosophila and humans. It also demonstrates that the effects of diploidy in gene networks can have counter-intuitive consequences that may profoundly influence the course of evolution.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 6%
Netherlands 1 3%
Switzerland 1 3%
Unknown 27 87%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 48%
Student > Ph. D. Student 3 10%
Student > Bachelor 2 6%
Professor > Associate Professor 2 6%
Student > Master 2 6%
Other 2 6%
Unknown 5 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 42%
Biochemistry, Genetics and Molecular Biology 8 26%
Environmental Science 1 3%
Computer Science 1 3%
Physics and Astronomy 1 3%
Other 2 6%
Unknown 5 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 22 March 2013.
All research outputs
#17,295,853
of 25,385,509 outputs
Outputs from PLoS Computational Biology
#7,479
of 8,961 outputs
Outputs of similar age
#135,327
of 210,427 outputs
Outputs of similar age from PLoS Computational Biology
#112
of 152 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,961 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 11th percentile – i.e., 11% of its peers scored the same or lower than it.
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 210,427 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 152 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.