ArticleFrontiers in genetics2025
Genomic-based genetic parameters and genome-wide association studies for productive and reproductive traits in Beef-on-Dairy crossbreds.
Article in Frontiers in genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Machine Learning-Based Genome-Wide Association Study Reveals Genetic Loci Associated with Body Measurement Traits in Yili Horses.Animals : an open access journal from MDPI · 2026Article
- Genomic-based genetic parameters and genome-wide association studies for productive and reproductive traits in Beef-on-Dairy crossbreds.Frontiers in genetics · 2025Article
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Abstract
Background: Beef on Dairy (BoD) calves are born from the crossing of dairy cows with beef breeds. The genetic architecture of these calves differs significantly from the parent breeds due to heterosis and other dominance effects. Identification of the genomic regions associated with traits in BoD calves and the inheritance pattern of these regions can assist in the selection process. We conducted a genome-wide association study (GWAS) for Belgian blue and Angus crossbreds born from a Holstein dam, incorporating additive and dominance effects to identify genomic regions associated with birth weight, calving difficulty, and gestation length. Additionally, a haplotype-based GWAS was performed to compare the effectiveness of these two different methodologies and to identify the parental origin of the haplotypes based on similar allelic patterns between crossbred and parental breeds. Results: The heritability estimates for birth weight, calving difficulty, and gestation length were 0.29 (±0.03), 0.36 (±0.04), and 0.09 (±0.03), respectively. Using SNP-based GWAS for birth weight, a genomic region containing the Conclusion: Based on this study, Haplotype GWAS was found to have superior statistical power in the identification of associated genomic regions in BoD crossbreds. However, for traits such as calving difficulty, SNP-based GWAS proved to be more effective. Both approaches are essential for the identification of genomic regions associated with traits of interest in BoD calves.
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