Evidence map›Paper›PMID 24132087›Full record

ArticleBiology letters2013

Kin selection, genomics and caste-antagonistic pleiotropy.

David W Hall, Soojin V Yi, Michael A D Goodisman

Open access · bronzeAbstract read
In one paragraph

Article in Biology letters, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
4.0field-weighted citation impact, top 7% of its field
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

11 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Review
  3. Kin selection for cooperation in natural bacterial populations.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  4. Article
  5. Review
  6. Review
  7. Building a new research framework for social evolution: intralocus caste antagonism.Biological reviews of the Cambridge Philosophical Society · 2018
    Review
  8. Article
  9. Article
  10. Article
  11. 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 at 2 institutions in 1 country.

David W HallDepartment of Genetics, University of Georgia, , Athens, GA 30602, USA.
Soojin V Yi
Michael A D Goodisman
Georgia Institute of Technology · USUniversity of Georgia · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Kin selection is a fundamentally important process that affects the evolution of social behaviours. The genomics revolution now provides the opportunity to test kin selection theory using genomic data. In this commentary, we discuss previous studies that explored the link between kin selection and patterns of variation within the genome. We then present a new theory aimed at understanding the evolution of genes involved in the development of social insects. Specifically, we investigate caste-antagonistic pleiotropy, which occurs when the phenotypes of distinct castes are optimized by different genotypes at a single locus. We find that caste-antagonistic pleiotropy leads to narrow regions where polymorphism can be maintained. Furthermore, multiple mating by queens reduces the region in which worker-favoured alleles fix, which suggests that multiple mating impedes worker caste evolution. We conclude by discussing ways to test these and other facets of kin selection using newly emerging genomic data.

Indexed as

Social BehaviorAnimalsAntsBeesBiological EvolutionEvolution, MolecularGenetic VariationGenomeGenomicsGenotypeInsectaModels, GeneticPhenotypePolymorphism, GeneticReproductionSexual Behavior, Animalantagonistic selectioneusocial insect castemolecular evolutionsexual selectionsocial conflict

Identifiers

PMID24132087
PMCPMC3871331
OpenAlexW2129169924

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.