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Objective: The improvement of carcass traits is essential for the Hanwoo industry because of the Hanwoo grade determination system, and genome-wide association study (GWAS) analysis is an instrumental tool for identifying the genetic factors that impact these traits. While GWAS analysis utilizing family data offers advantages in minimizing genetic bias, research on family-based GWAS in Hanwoo is currently lacking. Methods: This study classified Group A using both parental and offspring genetic information, and Group B based solely on offspring genetic information, to compare GWAS analysis results of Hanwoo carcass traits. Results: A total of 16 significant single nucleotide polymorphism (SNP) markers were identified in Group A, comprising 7 for carcass weight (CWT), 3 for back fat thickness (BFT), and 6 for marbling score (MS). In Group B, 7 significant SNP markers were identified, including 3 for CWT, 1 for eye muscle area, 1 for BFT, and 2 for MS. Functional annotation analysis revealed only one common function related to carcass traits between the groups, while protein-protein interaction analysis indicated more gene interactions in Group A. The reliability of estimated values for common SNP markers identified between the groups was higher in Group A. Conclusion: GWAS analysis utilizing parental genetic information holds greater potential for application, owing to its higher reliability of estimated values and the ability to explore numerous candidate genes. [ABSTRACT FROM AUTHOR]

Genetic association studies of child health outcomes often employ family-based study designs. One of the most popular family-based designs is the case-parent trio design that considers the smallest possible nuclear family consisting of two parents and their affected child. This trio design is particularly advantageous for studying relatively rare disorders because it is less prone to type 1 error inflation due to population stratification compared to population-based study designs (e.g., case-control studies). However, obtaining genetic data from both parents is difficult, from a practical perspective, and many large studies predominantly measure genetic variants in mother-child dyads. While some statistical methods for analyzing parent-child dyad data (most commonly involving mother-child pairs) exist, it is not clear if they provide the same advantage as trio methods in protecting against population stratification, or if a specific dyad design (e.g., case-mother dyads vs. case-mother/control-mother dyads) is more advantageous. In this article, we review existing statistical methods for analyzing genome-wide marker data on dyads and perform extensive simulation experiments to benchmark their type I errors and statistical power under different scenarios. We extend our evaluation to existing methods for analyzing a combination of case-parent trios and dyads together. We apply these methods on genotyped and imputed data from multiethnic mother-child pairs only, case-parent trios only or combinations of both dyads and trios from the Gene, Environment Association Studies consortium (GENEVA), where each family was ascertained through a child affected by nonsyndromic cleft lip with or without cleft palate. Results from the GENEVA study corroborate the findings from our simulation experiments. Finally, we provide recommendations for using statistical genetic association methods for dyads., (© 2022 The Authors. Genetic Epidemiology published by Wiley Periodicals LLC.)