Evidence map›Paper›PMID 38816340›Full record

ArticleThe plant genome2024

Evolutionary computing to assemble standing genetic diversity and achieve long-term genetic gain.

Kira Villiers, Kai P Voss-Fels, Eric Dinglasan, Bertus Jacobs, Lee Hickey, Ben J Hayes

Abstract read
In one paragraph

Article in The plant genome, 2024. 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. Review
  2. Article
  3. Article
  4. Article
  5. Restructuring breeding programs 1: Integration of diversity.Genetics, selection, evolution : GSE · 2026
    Article
  6. Article
  7. Article
  8. Exploring intra-varietal variation for complex traits in grapevine (Vitis vinifera L.).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
    Article
  9. Haplotype stacking to improve stability of stripe rust resistance in wheat.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
    Article
  10. Optimising parent selection in plant breeding: comparing metaheuristic algorithms for genotype building.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
    Article
  11. Article
  12. Article
  13. Review
  14. Stacking beneficial haplotypes from the Vavilov wheat collection to accelerate breeding for multiple disease resistance.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024
    Article
  15. Review
  16. Genome-wide atlas of rust resistance loci in wheat.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024
    Review
  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

6 authors.

Kira VilliersQueensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, Queensland, Australia.ORCID https://orcid.org/0000-0002-6410-3477
Kai P Voss-FelsQueensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, Queensland, Australia.ORCID https://orcid.org/0000-0003-0782-366X
Eric DinglasanQueensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, Queensland, Australia.
Bertus JacobsLongReach Plant Breeders Management Pty Ltd, Lonsdale, South Australia, Australia.
Lee HickeyQueensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, Queensland, Australia.
Ben J HayesQueensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, Queensland, Australia.

Funding

Australian Research Council LP170100317
6 · The paper itself

Abstract

Loss of genetic diversity in elite crop breeding pools can severely limit long-term genetic gains and limit ability to make gains in new traits, like heat tolerance, that are becoming important as the climate changes. Here, we investigate and propose potential breeding program applications of optimal haplotype stacking (OHS), a selection method that retains useful diversity in the population. OHS selects sets of candidates containing, between them, haplotype segments with very high segment breeding values for the target trait. We compared the performance of OHS, a similar method called optimal population value (OPV), truncation selection on genomic estimated breeding values (GEBVs), and optimal contribution selection (OCS) in stochastic simulations of recurrent selection on founder wheat genotypes. After 100 generations of intercrossing and selection, OCS and truncation selection had exhausted the genetic diversity, while considerable diversity remained in the OHS population. Gain under OHS in these simulations ultimately exceeded that from truncation selection or OCS. OHS achieved faster gains when the population size was small, with many progeny per cross. A promising hybrid strategy, involving a single cycle of OHS in the first generation followed by recurrent truncation selection, substantially improved long-term gain compared with truncation selection and performed similarly to OCS. The results of this study provide initial insights into where OHS could be incorporated into breeding programs.

Indexed as

Genetic VariationPlant BreedingTriticumComputer SimulationHaplotypesModels, GeneticSelection, Genetic

Identifiers

PMID38816340
PMCPMC12807084

What OpenQuestion holds

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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.