Evidence map›Paper›PMID 27335010›Full record

ArticleGenetics, selection, evolution : GSE2016

Effect of manipulating recombination rates on response to selection in livestock breeding programs.

Mara Battagin, Gregor Gorjanc, Anne-Michelle Faux, Susan E Johnston, John M Hickey

Abstract read
In one paragraph

Article in Genetics, selection, evolution : GSE, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. Article
  2. Article
  3. Recent population history in Swedish cattle breeds.Genetics, selection, evolution : GSE · 2026
    Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. Review
  10. Article
  11. Review
  12. Article
  13. Exploring impact of recombination landscapes on breeding outcomes.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Review
  14. Article
  15. Article
  16. Article
  17. Fourth Report on Chicken Genes and Chromosomes 2022.Cytogenetic and genome research · 2022
    Review
  18. Genetic variation in recombination rate in the pig.Genetics, selection, evolution : GSE · 2021
    Article
  19. Emerging issues in genomic selection.Journal of animal science · 2021
    Article
  20. 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

5 authors.

Mara BattaginThe Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush, Midlothian, Scotland, UK.
Gregor GorjancThe Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush, Midlothian, Scotland, UK.
Anne-Michelle FauxThe Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush, Midlothian, Scotland, UK.
Susan E JohnstonInstitute of Evolutionary Biology, University of Edinburgh, Charlotte Auerbach Road, Edinburgh, EH9 3FL, UK.
John M HickeyThe Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush, Midlothian, Scotland, UK. john.hickey@roslin.ed.ac.uk.

Funding

Biotechnology and Biological Sciences Research Council BBS/E/D/20211553Biotechnology and Biological Sciences Research Council BBS/E/D/20211554Medical Research Council MR/M000370/1
6 · The paper itself

Abstract

backgroundIn this work, we performed simulations to explore the potential of manipulating recombination rates to increase response to selection in livestock breeding programs.

methodsWe carried out ten replicates of several scenarios that followed a common overall structure but differed in the average rate of recombination along the genome (expressed as the length of a chromosome in Morgan), the genetic architecture of the trait under selection, and the selection intensity under truncation selection (expressed as the proportion of males selected). Recombination rates were defined by simulating nine different chromosome lengths: 0.10, 0.25, 0.50, 1, 2, 5, 10, 15 and 20 Morgan, respectively. One Morgan was considered to be the typical chromosome length for current livestock species. The genetic architecture was defined by the number of quantitative trait variants (QTV) that affected the trait under selection. Either a large (10,000) or a small (1000 or 500) number of QTV was simulated. Finally, the proportions of males selected under truncation selection as sires for the next generation were equal to 1.2, 2.4, 5, or 10 %.

resultsIncreasing recombination rate increased the overall response to selection and decreased the loss of genetic variance. The difference in cumulative response between low and high recombination rates increased over generations. At low recombination rates, cumulative response to selection tended to asymptote sooner and the genetic variance was completely eroded. If the trait under selection was affected by few QTV, differences between low and high recombination rates still existed, but the selection limit was reached at all rates of recombination.

conclusionsHigher recombination rates can enhance the efficiency of breeding programs to turn genetic variation into response to selection. However, to increase response to selection significantly, the recombination rate would need to be increased 10- or 20-fold. The biological feasibility and consequences of such large increases in recombination rates are unknown.

Indexed as

Models, GeneticQuantitative Trait LociAnimalsComputer SimulationFemaleGenetic VariationLivestockMalePhenotypeRecombination, GeneticSelective Breeding

Identifiers

PMID27335010
PMCPMC4917950

What OpenQuestion holds

Textmetadata
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.