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The disparity mutagenesis model predicts rescue of living things from catastrophic errors

Overview of attention for article published in Frontiers in Genetics, December 2014
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Title
The disparity mutagenesis model predicts rescue of living things from catastrophic errors
Published in
Frontiers in Genetics, December 2014
DOI 10.3389/fgene.2014.00421
Pubmed ID
Authors

Mitsuru Furusawa

Abstract

In animals including humans, mutation rates per generation exceed a perceived threshold, and excess mutations increase genetic load. Despite this, animals have survived without extinction. This is a perplexing problem for animal and human genetics, arising at the end of the last century, and to date still does not have a fully satisfactory explanation. Shortly after we proposed the disparity theory of evolution in 1992, the disparity mutagenesis model was proposed, which forms the basis for an explanation for an acceleration of evolution and species survival. This model predicts a significant increase of the mutation threshold values if the fidelity difference in replication between the lagging and leading strands is high enough. When applied to biological evolution, the model predicts that living things, including humans, might overcome the lethal effect of accumulated deleterious mutations and be able to survive. Artificially derived mutator strains of microorganisms, in which an enhanced lagging-strand-biased mutagenesis was introduced, showed unexpectedly high adaptability to severe environments. The implications of the striking behaviors shown by these disparity mutators will be discussed in relation to how living things with high mutation rates can avoid the self-defeating risk of excess mutations.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 9%
Unknown 10 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 27%
Student > Bachelor 2 18%
Professor 1 9%
Other 1 9%
Unknown 4 36%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 36%
Biochemistry, Genetics and Molecular Biology 2 18%
Chemistry 1 9%
Unknown 4 36%
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 27 July 2020.
All research outputs
#15,311,799
of 22,772,779 outputs
Outputs from Frontiers in Genetics
#5,418
of 11,759 outputs
Outputs of similar age
#213,581
of 360,768 outputs
Outputs of similar age from Frontiers in Genetics
#82
of 115 outputs
Altmetric has tracked 22,772,779 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,759 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 48th percentile – i.e., 48% of its peers scored the same or lower than it.
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We're also able to compare this research output to 115 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.