ArticleBMC genetics2019
Increasing accuracy of genomic selection in presence of high density marker panels through the prioritization of relevant polymorphisms.
Article in BMC genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Development of a Medium-Density Genotyping Platform to Accelerate Genetic Gain in Fresh Edible Maize.Plants (Basel, Switzerland) · 2026Article
- Genomic analysis for cattle breeding improvement, progress and future perspectives in Peru: a review.Animal biotechnology · 2025Review
- Genetic parameters estimation and optimization of genomic selection in mud crab (Scylla paramamosain): a case study for growth-related traits.BMC genomics · 2025Article
- Role of multi-omics in aquaculture genetics and breeding: current status and future perspective.Science China. Life sciences · 2025Review
- Variable selection strategies for genomic prediction of growth and carcass related traits in experimental Nellore cattle herds under different selection criteria.Scientific reports · 2025Article
- FGenes · 2025Article
- The prediction accuracies of linear-type traits in Czech Holstein cattle when using ssGBLUP or wssGBLUP.Journal of animal science · 2022Article
- Marker density and statistical model designs to increase accuracy of genomic selection for wool traits in Angora rabbits.Frontiers in genetics · 2022Article
- Applications of Omics Technology for Livestock Selection and Improvement.Frontiers in genetics · 2022Review
- Dissection of the impact of prioritized QTL-linked and -unlinked SNP markers on the accuracy of genomic selectionBMC genomic data · 2021Article
- Genetic diversity, viability and conservation value of the global captive population of the Moroccan Royal lions.PloS one · 2021Article
- Sequencing depth and genotype quality: accuracy and breeding operation considerations for genomic selection applications in autopolyploid crops.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2020Article
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundIt becomes clear that the increase in the density of marker panels and even the use of sequence data didn't result in any meaningful increase in the accuracy of genomic selection (GS) using either regression (RM) or variance component (VC) approaches. This is in part due to the limitations of current methods. Association model are well over-parameterized and suffer from severe co-linearity and lack of statistical power. Even when the variant effects are not directly estimated using VC based approaches, the genomic relationships didn't improve after the marker density exceeded a certain threshold. SNP prioritization-based fixation index (F
resultsTwo populations with average LD between adjacent markers of 0.3 (P1) and 0.7 (P2) were simulated. In both populations, the genomic data consisted of 400 K SNP markers distributed on 10 chromosomes. The density of simulated genomic data mimics roughly 1.2 million SNP markers in the bovine genome. The genomic relationship matrix (G) was calculated for each set of selected SNPs based on their F
conclusionsGenomic similarity could be maximized by the decrease in the number of selected SNPs, but it also leads to a decrease in the percentage of genetic variation explained by the selected markers. Finding the balance between these two parameters could optimize the accuracy of GS in the presence of high density marker panels.
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