This study aimed to identify genetic associations with carcass traits in Hanwoo cattle using a genome-wide association study. A total of 9302 phenotypes were analyzed, and all animals were genotyped using the Illumina Bovine 50K v.3 SNP chip. Heritabilities for carcass weight (CWT), eye muscle area (EMA), backfat thickness (BF), and marbling score (MS) were estimated as 0.42, 0.36, 0.36, and 0.47, respectively, using the GBLUP model, and 0.47, 0.37, 0.36, and 0.42, respectively, using the Bayes B model. We identified 129 common SNPs using DGEBV and 118 common SNPs using GEBV on BTA6, BTA13, and BTA14, suggesting their potential association with the traits of interest. No common SNPs were found between the GBLUP and Bayes B methods when using residuals as a response variable in GWAS. The most promising candidate genes for CWT included SLIT2, PACRGL, KCNIP4, RP1, XKR4, LYN, RPS20, MOS, FAM110B, UBXN2B, CYP7A1, SDCBP, NSMAF, TOX, CA8, LAP3, FAM184B, and NCAPG. For EMA, the genes IBSP, LAP3, FAM184B, LCORL, NCAPG, SLC30A9, and BEND4 demonstrated significance. Similarly, CYP7B1, ARMC1, PDE7A, and CRH were associated with BF, while CTSZ, GNAS, VAPB, and RAB22A were associated with MS. This finding offers valuable insights into genomic regions and molecular mechanisms influencing Hanwoo carcass traits, aiding efficient breeding strategies.

Maternal overnutrition and targeted supplements during pregnancy strongly affect fetal development in beef cattle, influencing gene expression, tissue development, and productivity after birth. As modern feeding practices often result in cows receiving energy and protein above requirements, understanding the balance between adequate nutrition and overconditioning is critical for sustainable beef production. This review synthesizes findings from recent studies on maternal overnutrition and supplementation, focusing on macronutrients (energy, protein, methionine) and key micronutrients (e.g., selenium, zinc). It evaluates the timing and impact of supplementation during different gestational stages, with emphasis on fetal muscle and adipose tissue development, immune function, and metabolic programming. The role of epigenetic mechanisms, such as DNA methylation and non-coding RNAs, is also discussed in relation to maternal dietary inputs. Mid-gestation supplementation promotes muscle growth by activating muscle-specific genes, whereas late-gestation diets enhance marbling and carcass traits. However, maternal overnutrition may impair mitochondrial efficiency, encourage fat deposition over muscle, and promote collagen synthesis, reducing meat tenderness. Recent evidence highlights sex-specific fetal programming differences, the significant impact of maternal diets on offspring gut microbiomes, and breed-specific nutritional responses, and multi-OMICs integration reveals metabolic reprogramming mechanisms. Targeted trace mineral and methionine supplementation enhance antioxidant capacity, immune function, and reproductive performance. Precision feeding strategies aligned with gestational requirements improve feed efficiency and minimize overfeeding risks. Early interventions, including protein and vitamin supplementation, optimize placental function and fetal development, supporting stronger postnatal growth, immunity, and fertility. Balancing nutritional adequacy without excessive feeding supports animal welfare, profitability, and sustainability in beef cattle systems.

Hematological reference intervals must consider several parameters, including genotype, age, sex, management, and analytic process. Work is needed to evaluate hematological changes specifically in Hanwoo calves and according to calf sex. Therefore, in this study, we sought to confirm the complete blood cell count (CBC) reference intervals in Hanwoo calves, to monitor changes in hematologic values in Hanwoo calves from birth until 28 weeks of life, and to compare the hematologic values of male and female calves. A total of 35 male calves and 35 female calves was studied. Calf blood was sampled at multiple intervals from the time of birth until 28 weeks of age (including within 6 h of birth and at 2 days, 7 days, and 4 weeks and then at 4-week intervals through 28 weeks). In addition, blood samples were collected from 210 clinically healthy pregnant Hanwoo cows to establish CBC reference intervals for adult cattle. There were significant differences in the results of the cows and calves in all 14 parameters considered. The CBC reference intervals of the calves were wider than those of the cows in all parameters except mean corpuscular volume, mean corpuscular hemoglobin concentration, and mean platelet volume. We also identified differences from birth through 28 weeks between male and female calves at only some ages and some parameters. These results suggest that CBC reference intervals specific to Hanwoo calves are necessary for accurate diagnosis of calf diseases.

Background: Conducting genome-wide association studies (GWAS) for reproductive traits in Hanwoo cattle, including age at first calving (AFC), calving interval (CI), gestation length (GL), and number of artificial inseminations per conception (NAIPC), is of paramount significance. These analyses provided a thorough exploration of the genetic basis of these traits, facilitating the identification of key markers for targeted trait improvement. Breeders can optimize their selection strategies, leading to more efficient and sustainable breeding programs, by incorporating genetic insights. This impact extends beyond individual traits and contributes to the overall productivity and profitability of the Hanwoo beef cattle industry. Ultimately, GWAS is essential in ensuring the long-term genetic resilience and adaptability of Hanwoo cattle populations. The primary goal of this study was to identify significant single nucleotide polymorphisms (SNPs) or quantitative trait loci (QTLs) associated with the studied reproductive traits and subsequently map the underlying genes that hold promise for trait improvement. Results: A genome-wide association study of reproductive traits identified 68 significant single nucleotide polymorphisms (SNPs) distributed across 29 Bos taurus autosomes (BTA). Among them, BTA14 exhibited the highest number of identified SNPs (25), whereas BTA6, BTA7, BTA8, BTA10, BTA13, BTA17, and BTA20 exhibited 8, 5, 5, 3, 8, 2, and 12 significant SNPs, respectively. Annotation of candidate genes within a 500 kb region surrounding the significant SNPs led to the identification of ten candidate genes relevant to age at first calving. These genes were: FANCG, UNC13B, TESK1, TLN1, and CREB3 on BTA8; FAM110B, UBXN2B, SDCBP, and TOX on BTA14; and MAP3K1 on BTA20. Additionally, APBA3, TCF12, and ZFR2, located on BTA7 and BTA10, were associated with the calving interval; PAX1, SGCD, and HAND1, located on BTA7 and BTA13, were linked to gestation length; and RBM47, UBE2K, and GPX8, located on BTA6 and BTA20, were linked to the number of artificial inseminations per conception in Hanwoo cows. Conclusions: The findings of this study enhance our knowledge of the genetic factors that influence reproductive traits in Hanwoo cattle populations and provide a foundation for future breeding strategies focused on improving desirable traits in beef cattle. This research offers new evidence and insights into the genetic variants and genome regions associated with reproductive traits and contributes valuable information to guide future efforts in cattle breeding.

This study aimed to predict the accuracy of genomic estimated breeding values (GEBVs) for reproductive traits in Hanwoo cows using the GBLUP, BayesB, BayesLASSO, and BayesR methods. Accuracy estimates of GEBVs for reproductive traits were derived through fivefold cross-validation, analyzing a dataset comprising 11,348 animals and employing an Illumina Bovine 50K SNP chip. GBLUP showed an accuracy of 0.26 for AFC, while BayesB, BayesLASSO, and BayesR demonstrated values of 0.28, 0.29, and 0.29, respectively. For CI, GBLUP attained an accuracy of 0.19, whereas BayesB, BayesLASSO, and BayesR scored 0.21, 0.24, and 0.25, respectively. The accuracy for GL was uniform across GBLUP, BayesB, and BayesR at 0.31, whereas BayesLASSO showed a slightly higher accuracy of 0.33. For NAIPC, GBLUP showed an accuracy of 0.24, while BayesB, BayesLASSO, and BayesR recorded 0.22, 0.27, and 0.30, respectively. The variation in genomic prediction accuracy among methods indicated Bayesian approaches slightly outperformed GBLUP. The findings suggest that Bayesian methods, notably BayesLASSO and BayesR, offer improved predictive capabilities for reproductive traits. Future research may explore more advanced genomic approaches to enhance predictive accuracy and genetic gains in Hanwoo cattle breeding programs.