ArticleBMC genetics2018
Genomic prediction of crown rust resistance in Lolium perenne.
Article in BMC genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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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.
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Who cites it
18 citing papers in PubMed, 40 citations in OpenAlex.
- GWAS and genomic prediction of crown rust resistance in the southern US elite oat (Avena sativa L.) germplasm.The plant genome · 2026Article
- Genomic selection shows improved expected genetic gain over phenotypic selection of agronomic traits in allotetraploid white clover.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Estimation of ryegrass (Frontiers in plant science · 2025Article
- Machine learning solutions for integrating partially overlapping genetic datasets and modelling host-endophyte effects in ryegrass (Frontiers in plant science · 2025Article
- Genomic evaluation for breeding and genetic management in Cordia africana, a multipurpose tropical tree species.BMC genomics · 2024Article
- Including marker x environment interactions improves genomic prediction in red clover (Frontiers in plant science · 2024Article
- Developing an integrated genomic selection approach beyond biomass for varietal protection and nutritive traits in perennial ryegrass (Lolium perenne L.).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023Article
- Genomic Prediction of Complex Traits in Forage Plants Species: Perennial Grasses Case.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Climate change conditions the selection of rust-resistant candidate wild lentil populations forFrontiers in plant science · 2022Article
- Prediction of heterosis in the recent rapeseed (Brassica napus) polyploid by pairing parental nucleotide sequences.PLoS genetics · 2021Article
- Article
- Effects of Different Strategies for Exploiting Genomic Selection in Perennial Ryegrass Breeding Programs.G3 (Bethesda, Md.) · 2020Article
- Mapping crown rust resistance at multiple time points in elite oat germplasm.The plant genome · 2020Article
- Genomic Predictive Ability for Foliar Nutritive Traits in Perennial Ryegrass.G3 (Bethesda, Md.) · 2020Article
- Genomic Predictions Using Low-Density SNP Markers, Pedigree and GWAS Information: A Case Study with the Non-Model SpeciesPlants (Basel, Switzerland) · 2020Article
- Multi-Trait Genomic Prediction Improves Predictive Ability for Dry Matter Yield and Water-Soluble Carbohydrates in Perennial Ryegrass.Frontiers in plant science · 2020Article
- Article
- Evaluation of Genomic Prediction for Pasmo Resistance in Flax.International journal of molecular sciences · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGenomic selection (GS) can accelerate genetic gains in breeding programmes by reducing the time it takes to complete a cycle of selection. Puccinia coronata f. sp lolli (crown rust) is one of the most widespread diseases of perennial ryegrass and can lead to reductions in yield, persistency and nutritional value. Here, we used a large perennial ryegrass population to assess the accuracy of using genome wide markers to predict crown rust resistance and to investigate the factors affecting predictive ability.
resultsUsing these data, predictive ability for crown rust resistance in the complete population reached a maximum of 0.52. Much of the predictive ability resulted from the ability of markers to capture genetic relationships among families within the training set, and reducing the marker density had little impact on predictive ability. Using permutation based variable importance measure and genome wide association studies (GWAS) to identify and rank markers enabled the identification of a small subset of SNPs that could achieve predictive abilities close to those achieved using the complete marker set.
conclusionUsing a GWAS to identify and rank markers enabled a small panel of markers to be identified that could achieve higher predictive ability than the same number of randomly selected markers, and predictive abilities close to those achieved with the entire marker set. This was particularly evident in a sub-population characterised by having on-average higher genome-wide linkage disequilibirum (LD). Higher predictive abilities with selected markers over random markers suggests they are in LD with QTL. Accuracy due to genetic relationships will decay rapidly over generations whereas accuracy due to LD will persist, which is advantageous for practical breeding applications.
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Registered trials
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.