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Negative Epistasis in Experimental RNA Fitness Landscapes

Overview of attention for article published in Journal of Molecular Evolution, November 2017
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Title
Negative Epistasis in Experimental RNA Fitness Landscapes
Published in
Journal of Molecular Evolution, November 2017
DOI 10.1007/s00239-017-9817-5
Pubmed ID
Authors

Devin P. Bendixsen, Bjørn Østman, Eric J. Hayden

Abstract

Mutations and their effects on fitness are a fundamental component of evolution. The effects of some mutations change in the presence of other mutations, and this is referred to as epistasis. Epistasis can occur between mutations in different genes or within the same gene. A systematic study of epistasis requires the analysis of numerous mutations and their combinations, which has recently become feasible with advancements in DNA synthesis and sequencing. Here we review the mutational effects and epistatic interactions within RNA molecules revealed by several recent high-throughput mutational studies involving two ribozymes studied in vitro, as well as a tRNA and a snoRNA studied in yeast. The data allow an analysis of the distribution of fitness effects of individual mutations as well as combinations of two or more mutations. Two different approaches to measuring epistasis in the data both reveal a predominance of negative epistasis, such that higher combinations of two or more mutations are typically lower in fitness than expected from the effect of each individual mutation. These data are in contrast to past studies of epistasis that used computationally predicted secondary structures of RNA that revealed a predominance of positive epistasis. The RNA data reviewed here are more similar to that found from mutational experiments on individual protein enzymes, suggesting that a common thermodynamic framework may explain negative epistasis between mutations within macromolecules.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 24%
Student > Ph. D. Student 9 20%
Student > Master 7 15%
Student > Bachelor 3 7%
Student > Doctoral Student 2 4%
Other 5 11%
Unknown 9 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 17 37%
Agricultural and Biological Sciences 13 28%
Unspecified 1 2%
Computer Science 1 2%
Medicine and Dentistry 1 2%
Other 2 4%
Unknown 11 24%
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 02 March 2018.
All research outputs
#18,349,015
of 23,577,761 outputs
Outputs from Journal of Molecular Evolution
#1,256
of 1,464 outputs
Outputs of similar age
#236,851
of 329,561 outputs
Outputs of similar age from Journal of Molecular Evolution
#11
of 12 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,464 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one is in the 12th percentile – i.e., 12% of its peers scored the same or lower than it.
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We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.