ArticleGenetics, selection, evolution : GSE2017
Whole-genome sequence-based genomic prediction in laying chickens with different genomic relationship matrices to account for genetic architecture.
Article in Genetics, selection, evolution : GSE, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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35 citing papers in PubMed.
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- Claudin and Rab proteins are key molecular components involved in coccidiosis resistance in Portuguese Merino sheep.Genetics, selection, evolution : GSE · 2025Article
- A Deep Autoencoder Compression-Based Genomic Prediction Method for Whole-Genome Sequencing Data.Biology · 2025Article
- Genomic Selection for Economic Traits in Inner Mongolia Cashmere Goats by Integrating GWAS Prior Information.Veterinary sciences · 2025Article
- Effect of using preselected markers from imputed whole-genome sequence for genomic prediction in Angus cattle.Genetics, selection, evolution : GSE · 2025Article
- Increased Accuracy of Genomic Prediction Using Preselected SNPs from GWAS with Imputed Whole-Genome Sequence Data in Pigs.Animals : an open access journal from MDPI · 2023Article
- Improving the accuracy of genomic prediction for meat quality traits using whole genome sequence data in pigs.Journal of animal science and biotechnology · 2023Article
- Utilizing Variants Identified with Multiple Genome-Wide Association Study Methods Optimizes Genomic Selection for Growth Traits in Pigs.Animals : an open access journal from MDPI · 2023Article
- Haplotype blocks for genomic prediction: a comparative evaluation in multiple crop datasets.Frontiers in plant science · 2023Article
- Genomic selection in tropical perennial crops and plantation trees: a review.Molecular breeding : new strategies in plant improvement · 2022Review
- Genomic Selection in Chinese Holsteins Using Regularized Regression Models for Feature Selection of Whole Genome Sequencing Data.Animals : an open access journal from MDPI · 2022Article
- Development and validation of a horse reference panel for genotype imputation.Genetics, selection, evolution : GSE · 2022Article
- Genomics applied to livestock and aquaculture breeding.Evolutionary applications · 2022Review
- Increased accuracy of genomic predictions for growth under chronic thermal stress in rainbow trout by prioritizing variants from GWAS using imputed sequence data.Evolutionary applications · 2022Article
- Genetic parameters and genome-wide association for milk production traits and somatic cell score in different lactation stages of Shanghai Holstein population.Frontiers in genetics · 2022Article
- Haplotype genomic prediction of phenotypic values based on chromosome distance and gene boundaries using low-coverage sequencing in Duroc pigs.Genetics, selection, evolution : GSE · 2021Article
- Investigating the Effect of Imputed Structural Variants from Whole-Genome Sequence on Genome-Wide Association and Genomic Prediction in Dairy Cattle.Animals : an open access journal from MDPI · 2021Article
- The Genetic Basis of Tomato Aroma.Genes · 2021Review
- Comparison of Genotype Imputation for SNP Array and Low-Coverage Whole-Genome Sequencing Data.Frontiers in genetics · 2021Article
- A Comprehensive Comparison of Haplotype-Based Single-Step Genomic Predictions in Livestock Populations With Different Genetic Diversity Levels: A Simulation Study.Frontiers in genetics · 2021Article
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5 authors.
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Abstract
backgroundWith the availability of next-generation sequencing technologies, genomic prediction based on whole-genome sequencing (WGS) data is now feasible in animal breeding schemes and was expected to lead to higher predictive ability, since such data may contain all genomic variants including causal mutations. Our objective was to compare prediction ability with high-density (HD) array data and WGS data in a commercial brown layer line with genomic best linear unbiased prediction (GBLUP) models using various approaches to weight single nucleotide polymorphisms (SNPs).
methodsA total of 892 chickens from a commercial brown layer line were genotyped with 336 K segregating SNPs (array data) that included 157 K genic SNPs (i.e. SNPs in or around a gene). For these individuals, genome-wide sequence information was imputed based on data from re-sequencing runs of 25 individuals, leading to 5.2 million (M) imputed SNPs (WGS data), including 2.6 M genic SNPs. De-regressed proofs (DRP) for eggshell strength, feed intake and laying rate were used as quasi-phenotypic data in genomic prediction analyses. Four weighting factors for building a trait-specific genomic relationship matrix were investigated: identical weights, -(log
resultsAveraged over the three traits, the highest predictive ability (0.366 ± 0.075) was obtained when only genic SNPs from WGS data were used. Predictive abilities with genic SNPs and all SNPs from HD array data were 0.361 ± 0.072 and 0.353 ± 0.074, respectively. Prediction with -(log
conclusionsOur results show that little or no benefit was gained when using all imputed WGS data to perform genomic prediction compared to using HD array data regardless of the weighting factors tested. However, using only genic SNPs from WGS data had a positive effect on prediction ability.
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