ArticleFrontiers in genetics2014
Changes in variance explained by top SNP windows over generations for three traits in broiler chicken.
Article in Frontiers in genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed.
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- Changes in allele frequencies and genetic architecture due to selection in two pig populations.Genetics, selection, evolution : GSE · 2024Article
- Marker effect p-values for single-step GWAS with the algorithm for proven and young in large genotyped populations.Genetics, selection, evolution : GSE · 2024Article
- Temporal dynamics of genetic parameters and SNP effects for performance and disorder traits in poultry undergoing genomic selection.Journal of animal science · 2024Article
- Reviewing the definition of mortality in broiler chickens and its implications in genomic evaluations.Journal of animal science · 2024Article
- Longitudinal genomic analyses of automatically-recorded vaginal temperature in lactating sows under heat stress conditions based on random regression models.Genetics, selection, evolution : GSE · 2023Article
- Single-Step GBLUP and GWAS Analyses Suggests Implementation of Unweighted Two Trait Approach for Heat Stress in Swine.Animals : an open access journal from MDPI · 2022Article
- Genome-wide association study identifies SNPs for growth performance and serum indicators in Valgus-varus deformity broilers (Gallus gallus) using ddGBS sequencing.BMC genomics · 2022Article
- Genotype-by-environment interactions for reproduction, body composition, and growth traits in maternal-line pigs based on single-step genomic reaction norms.Genetics, selection, evolution : GSE · 2021Article
- Identification of Major Loci and Candidate Genes for Meat Production-Related Traits in Broilers.Frontiers in genetics · 2021Article
- Genome-wide association study to identify genomic regions and positional candidate genes associated with male fertility in beef cattle.Scientific reports · 2020Article
- Current status of genomic evaluation.Journal of animal science · 2020Review
- A Genome-Wide Association Study for Calving Interval in Holstein Dairy Cows Using Weighted Single-Step Genomic BLUP Approach.Animals : an open access journal from MDPI · 2020Article
- Genome-Wide Association Study of Growth and Body-Shape-Related Traits in Large Yellow Croaker (Larimichthys crocea) Using ddRAD Sequencing.Marine biotechnology (New York, N.Y.) · 2019Article
- Whole-genome mapping of quantitative trait loci and accuracy of genomic predictions for resistance to columnaris disease in two rainbow trout breeding populations.Genetics, selection, evolution : GSE · 2019Article
- Genome-Wide Association Study for Milk Protein Composition Traits in a Chinese Holstein Population Using a Single-Step Approach.Frontiers in genetics · 2019Article
Corrections and comments
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Authors and funding
6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
The purpose of this study was to determine if the set of genomic regions inferred as accounting for the majority of genetic variation in quantitative traits remain stable over multiple generations of selection. The data set contained phenotypes for five generations of broiler chicken for body weight, breast meat, and leg score. The population consisted of 294,632 animals over five generations and also included genotypes of 41,036 single nucleotide polymorphism (SNP) for 4,866 animals, after quality control. The SNP effects were calculated by a GWAS type analysis using single step genomic BLUP approach for generations 1-3, 2-4, 3-5, and 1-5. Variances were calculated for windows of 20 SNP. The top ten windows for each trait that explained the largest fraction of the genetic variance across generations were examined. Across generations, the top 10 windows explained more than 0.5% but less than 1% of the total variance. Also, the pattern of the windows was not consistent across generations. The windows that explained the greatest variance changed greatly among the combinations of generations, with a few exceptions. In many cases, a window identified as top for one combination, explained less than 0.1% for the other combinations. We conclude that identification of top SNP windows for a population may have little predictive power for genetic selection in the following generations for the traits here evaluated.
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