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The evolution of strand preference in simulated RNA replicators with strand displacement: Implications for the origin of transcription

Overview of attention for article published in Biology Direct, August 2008
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Title
The evolution of strand preference in simulated RNA replicators with strand displacement: Implications for the origin of transcription
Published in
Biology Direct, August 2008
DOI 10.1186/1745-6150-3-33
Pubmed ID
Authors

Nobuto Takeuchi, Laura Salazar, Anthony M Poole, Paulien Hogeweg

Abstract

The simplest conceivable example of evolving systems is RNA molecules that can replicate themselves. Since replication produces a new RNA strand complementary to a template, all templates would eventually become double-stranded and, hence, become unavailable for replication. Thus the problem of how to separate the two strands is considered a major issue for the early evolution of self-replicating RNA. One biologically plausible way to copy a double-stranded RNA is to displace a preexisting strand by a newly synthesized strand. Such copying can in principle be initiated from either the (+) or (-) strand of a double-stranded RNA. Assuming that only one of them, say (+), can act as replicase when single-stranded, strand displacement produces a new replicase if the (-) strand is the template. If, however, the (+) strand is the template, it produces a new template (but no replicase). Modern transcription exhibits extreme strand preference wherein anti-sense strands are always the template. Likewise, replication by strand displacement seems optimal if it also exhibits extreme strand preference wherein (-) strands are always the template, favoring replicase production. Here we investigate whether such strand preference can evolve in a simple RNA replicator system with strand displacement.

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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 %
Hungary 1 3%
Brazil 1 3%
Unknown 29 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 23%
Student > Ph. D. Student 6 19%
Student > Bachelor 4 13%
Student > Master 3 10%
Professor > Associate Professor 2 6%
Other 5 16%
Unknown 4 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 55%
Physics and Astronomy 3 10%
Biochemistry, Genetics and Molecular Biology 3 10%
Chemistry 2 6%
Computer Science 1 3%
Other 1 3%
Unknown 4 13%
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 06 March 2023.
All research outputs
#19,982,923
of 25,420,980 outputs
Outputs from Biology Direct
#429
of 537 outputs
Outputs of similar age
#93,351
of 101,398 outputs
Outputs of similar age from Biology Direct
#6
of 6 outputs
Altmetric has tracked 25,420,980 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 537 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one is in the 17th percentile – i.e., 17% 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 101,398 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.
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