Evidence map›Paper›PMID 31803197›Full record

ArticleFrontiers in plant science2019

Boosting Genetic Gain in Allogamous Crops

Abdulqader Jighly, Zibei Lin, Luke W Pembleton, Noel O I Cogan, German C Spangenberg, Ben J Hayes, Hans D Daetwyler

Open access · goldAbstract read
In one paragraph

Article in Frontiers in plant science, 2019. 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
5.7field-weighted citation impact, top 4% 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

28 citing papers in PubMed, 67 citations in OpenAlex.

  1. Article
  2. Review
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  4. Speed breeding enhances crop resilience and productivity in a changing climate.Molecular breeding : new strategies in plant improvement · 2025
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  11. Article
  12. Genetic gains in IRRI's rice salinity breeding and elite panel development as a future breeding resource.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024
    Article
  13. Article
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  15. Review
  16. Transposable element polymorphisms improve prediction of complex agronomic traits in rice.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022
    Article
  17. Review
  18. Article
  19. Article
  20. Review
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

7 authors at 4 institutions in 1 country.

Abdulqader JighlyAgriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora,VIC, Australia.
Zibei LinAgriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora,VIC, Australia.
Luke W PembletonAgriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora,VIC, Australia.
Noel O I CoganAgriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora,VIC, Australia.
German C SpangenbergAgriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora,VIC, Australia.
Ben J HayesAgriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora,VIC, Australia.
Hans D DaetwylerAgriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora,VIC, Australia.
AgriBio · AUAgriculture Victoria · AULa Trobe University · AUUniversity of Queensland · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breeding schemes that utilize modern breeding methods like genomic selection (GS) and speed breeding (SB) have the potential to accelerate genetic gain for different crops. We investigated through stochastic computer simulation the advantages and disadvantages of adopting both GS and SB (SpeedGS) into commercial breeding programs for allogamous crops. In addition, we studied the effect of omitting one or two selection stages from the conventional phenotypic scheme on GS accuracy, genetic gain, and inbreeding. As an example, we simulated GS and SB for five traits (heading date, forage yield, seed yield, persistency, and quality) with different genetic architectures and heritabilities (0.7, 0.3, 0.4, 0.1, and 0.3; respectively) for a tall fescue breeding program. We developed a new method to simulate correlated traits with complex architectures of which effects can be sampled from multiple distributions, e.g. to simulate the presence of both minor and major genes. The phenotypic selection scheme required 11 years, while the proposed SpeedGS schemes required four to nine years per cycle. Generally, SpeedGS schemes resulted in higher genetic gain per year for all traits especially for traits with low heritability such as persistency. Our results showed that running more SB rounds resulted in higher genetic gain per cycle when compared to phenotypic or GS only schemes and this increase was more pronounced per year when cycle time was shortened by omitting cycle stages. While GS accuracy declined with additional SB rounds, the decline was less in round three than in round two, and it stabilized after the fourth SB round. However, more SB rounds resulted in higher inbreeding rate, which could limit long-term genetic gain. The inbreeding rate was reduced by approximately 30% when generating the initial population for each cycle through random crosses instead of generating half-sib families. Our study demonstrated a large potential for additional genetic gain from combining GS and SB. Nevertheless, methods to mitigate inbreeding should be considered for optimal utilization of these highly accelerated breeding programs.

Indexed as

allogamous breedinggenomic selectioninbreedingsimulationspeed breeding

Identifiers

PMID31803197
PMCPMC6873660
OpenAlexW2985391041

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.