Evidence map›Paper›PMID 31335870›Full record

ArticlePLoS computational biology2019

Biophysics and population size constrains speciation in an evolutionary model of developmental system drift.

Bhavin S Khatri, Richard A Goldstein

Abstract read
In one paragraph

Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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.

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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Understanding developmental system drift.Development (Cambridge, England) · 2024
    Review
  2. Fisher's Geometric Model as a Tool to Study Speciation.Cold Spring Harbor perspectives in biology · 2024
    Review
  3. Article
  4. Article
  5. A computational investigation of cis-gene regulation in evolution.Theory in biosciences = Theorie in den Biowissenschaften · 2023
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Multi-locus interactions and the build-up of reproductive isolation.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2020
    Review
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

2 authors.

Bhavin S KhatriThe Francis Crick Institute, London, United Kingdom.ORCID 0000-0002-0312-336X
Richard A GoldsteinDivision of Infection & Immunity, University College London, London, United Kingdom.

Funding

Biotechnology and Biological Sciences Research Council BB/P007562/1Cancer Research UKMedical Research Council MC_PC_13056Medical Research Council U117573805Wellcome Trust
6 · The paper itself

Abstract

Developmental system drift is a likely mechanism for the origin of hybrid incompatibilities between closely related species. We examine here the detailed mechanistic basis of hybrid incompatibilities between two allopatric lineages, for a genotype-phenotype map of developmental system drift under stabilising selection, where an organismal phenotype is conserved, but the underlying molecular phenotypes and genotype can drift. This leads to number of emergent phenomenon not obtainable by modelling genotype or phenotype alone. Our results show that: 1) speciation is more rapid at smaller population sizes with a characteristic, Orr-like, power law, but at large population sizes slow, characterised by a sub-diffusive growth law; 2) the molecular phenotypes under weakest selection contribute to the earliest incompatibilities; and 3) pair-wise incompatibilities dominate over higher order, contrary to previous predictions that the latter should dominate. The population size effect we find is consistent with previous results on allopatric divergence of transcription factor-DNA binding, where smaller populations have common ancestors with a larger drift load because genetic drift favours phenotypes which have a larger number of genotypes (higher sequence entropy) over more fit phenotypes which have far fewer genotypes; this means less substitutions are required in either lineage before incompatibilities arise. Overall, our results indicate that biophysics and population size provide a much stronger constraint to speciation than suggested by previous models, and point to a general mechanistic principle of how incompatibilities arise the under stabilising selection for an organismal phenotype.

Indexed as

Biological EvolutionGenetic SpeciationModels, GeneticAnimalsBiodiversityBiophysical PhenomenaComputational BiologyComputer SimulationEpistasis, GeneticFemaleGenetic Association StudiesGenetic DriftGenetic FitnessGenotypeMaleMonte Carlo Method

Identifiers

PMID31335870
PMCPMC6677325

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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.