Evidence map›Paper›PMID 35538786›Full record

ArticleProceedings. Biological sciences2022

Using genomic prediction to detect microevolutionary change of a quantitative trait.

D C Hunter, B Ashraf, C Bérénos, P A Ellis, S E Johnston, A J Wilson, J G Pilkington, J M Pemberton, J Slate

Abstract read
In one paragraph

Article in Proceedings. Biological sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Unmeasured prior viability selection resolves the paradox of stasis for body size in wild Soay sheep.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  4. Article
  5. Article
  6. Joining forces to push past paradoxes: Combining quantitative genetics and genomics shows evolution hiding in plain sight.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  7. Caprine and Ovine Genomic Selection-Progress and Application.Animals : an open access journal from MDPI · 2024
    Review
  8. Microevolutionary change in wild stickleback: Using integrative time-series data to infer responses to selection.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  9. Review
  10. Article
  11. Review
  12. Article
  13. Taking quantitative genomics into the wild.Proceedings. Biological sciences · 2022
    Article
  14. Article
  15. Article
  16. Article
  17. 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

9 authors.

D C HunterSchool of Biosciences, University of Sheffield, Sheffield S10 2TN, UK.
B AshrafSchool of Biosciences, University of Sheffield, Sheffield S10 2TN, UK.
C BérénosInstitute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3FL, UK.
P A EllisInstitute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3FL, UK.
S E JohnstonInstitute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3FL, UK.
A J WilsonCentre of Ecology and Conservation, College of Life and Environmental Sciences, University of Exeter, Penryn TR10 9FE, UK.
J G PilkingtonInstitute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3FL, UK.
J M PembertonInstitute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3FL, UK.
J SlateSchool of Biosciences, University of Sheffield, Sheffield S10 2TN, UK.ORCID 0000-0003-3356-5123

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Detecting microevolutionary responses to natural selection by observing temporal changes in individual breeding values is challenging. The collection of suitable datasets can take many years and disentangling the contributions of the environment and genetics to phenotypic change is not trivial. Furthermore, pedigree-based methods of obtaining individual breeding values have known biases. Here, we apply a genomic prediction approach to estimate breeding values of adult weight in a 35-year dataset of Soay sheep (

Indexed as

GenomeGenomicsAnimalsBody WeightGenotypeModels, GeneticPedigreePhenotypeSheepcryptic evolutiongenomic estimated breeding valuegenomic predictionmicroevolutionsoay sheep

Identifiers

PMID35538786
PMCPMC9091855

What OpenQuestion holds

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LicenceCC BY
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.