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Record W3102923913 · doi:10.1101/368324

Parallel genetic evolution and speciation from standing variation

2018· preprint· en· W3102923913 on OpenAlexafffund
Ken Thompson, Matthew M. Osmond, Dolph Schluter

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2018
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEvolution and Genetic Dynamics
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaKillam TrustsGenome British Columbia
KeywordsBiologySelection (genetic algorithm)Evolutionary biologyAdaptation (eye)TraitParallel evolutionNatural selectionGenetic variationStabilizing selectionDirectional selectionAlleleDisruptive selectionLocal adaptationGeneticsPopulationPhylogeneticsDemographyGeneComputer science

Abstract

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Abstract Adaptation often proceeds via the sorting of standing variation, and natural selection acting on pairs of populations is a quantitative continuum ranging from parallel to divergent. Yet, it is unclear how the extent of parallel genetic evolution during adaptation from standing variation is affected by the difference in the direction of selection between populations. Nor is it clear whether the availability of standing variation for adaptation affects progress toward speciation in a manner that depends on the difference in the direction of selection. We conducted a theoretical study investigating these questions and have two primary findings. First, the extent of parallel genetic evolution between two populations is expected to rapidly decline as the difference in their directions of selection increases from fully parallel toward divergent, and this decline occurs more rapidly in organisms with greater trait ‘dimensionality’. This rapid decline results because seemingly small differences in the direction of selection cause steep reductions in the fraction of alleles that are beneficial in both populations. For example, populations adapting to optima separated by an angle of 33° have only 50% of potentially beneficial alleles in common (for a case of five trait ‘dimensions’). Second, we find that adaptation from standing variation leads to higher ecologically-dependent hybrid fitness under parallel selection, relative to when adaptation is from new mutation only. This occurs because genetic parallelism based on standing variation reduces the phenotypic segregation variance in hybrids when parents adapt to similar environments. In contrast, under divergent selection, the pleiotropic effects of alternative alleles fixed from standing variation change the major axes of phenotypic variation in hybrids and reduce their fitness in parental habitats. We conclude that adaptation from standing genetic variation is expected to slow progress toward speciation via parallel natural selection and can facilitate progress toward speciation via divergent natural selection. Impact summary It is increasingly clear that much of adaptation, especially that which occurs rapidly, proceeds from the sorting of ancestral standing variation rather than complete reliance on de novo mutation. In addition, evolutionary biologists are increasingly embracing the fact that the difference in the direction of natural selection on pairs of populations is a quantitative continuum ranging from completely parallel to completely divergent. In this article, we ask two questions. First, how does the degree of genetic parallelism—here, adaptation using the same alleles in allopatric populations—depend on the differences in the direction of natural selection acting on two populations, from parallel (0°) to divergent (180°)? And second, how does adaptation from standing variation affect progress toward speciation, and does its effect depend on the direction of natural selection? We develop theory to address these questions. We first find that very small differences in the direction of selection (angle) can largely preclude genetic parallelism. Second, we find that adaptation from standing variation has implications for speciation that change along the continuum from parallel to divergent selection. Under parallel selection, high genetic parallelism causes inter-population hybrids to have high mean fitness when their parents adapt from standing variation. As selection tends toward divergent, adaptation from standing variation is less beneficial for hybrid fitness and under completely divergent selection causes inter-population hybrids to have lower mean fitness than when adaptation was from new mutation alone. In sum, our results provide general insight into patterns of genetic parallelism and speciation along the continuum of parallel to divergent natural selection when adaptation is from standing variation.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.209
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2018
Admission routes2
Has abstractyes

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