Evidence map›Paper›PMID 29099079›Full record

ArticleLife (Basel, Switzerland)2017

Evolutionary Conflict Leads to Innovation: Symmetry Breaking in a Spatial Model of RNA-Like Replicators.

Samuel H A von der Dunk, Enrico Sandro Colizzi, Paulien Hogeweg

Abstract read
In one paragraph

Article in Life (Basel, Switzerland), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Kin Selection in the RNA World.Life (Basel, Switzerland) · 2017
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Samuel H A von der DunkTheoretical Biology and Bioinformatics, Utrecht University, 3584 CH Utrecht, The Netherlands. s.h.a.vonderdunk@uu.nl.ORCID 0000-0002-5741-7558
Enrico Sandro ColizziTheoretical Biology and Bioinformatics, Utrecht University, 3584 CH Utrecht, The Netherlands. istidina@gmail.com.
Paulien HogewegTheoretical Biology and Bioinformatics, Utrecht University, 3584 CH Utrecht, The Netherlands. p.hogeweg@uu.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecules that replicate in trans are vulnerable to evolutionary extinction because they decrease the catalysis of replication to become more available as a template for replication. This problem can be alleviated with higher-level selection that clusters molecules of the same phenotype, favouring those groups that contain more catalysis. Here, we study a simple replicator model with implicit higher-level selection through space. We ask whether the functionality of such system can be enhanced when molecules reproduce through complementary replication, representing RNA-like replicators. For high diffusion, symmetry breaking between complementary strands occurs: one strand becomes a specialised catalyst and the other a specialised template. In ensemble, such replicators can modulate their catalytic activity depending on their environment, thereby mitigating the conflict between levels of selection. In addition, these replicators are more evolvable, facilitating survival in extreme conditions (i.e., for higher diffusion rates). Our model highlights that evolution with implicit higher-level selection-i.e., as a result of local interactions and spatial patterning-is very flexible. For different diffusion rates, different solutions to the selective conflict arise. Our results support an RNA World by showing that complementary replicators may have various ways to evolve more complexity.

Indexed as

catalysisdivision of labourhigher-level selectionmultilevel evolutionRNA worldspatial modelsymmetry breaking

Identifiers

PMID29099079
PMCPMC5745556

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.