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Whole-genome sequence (WGS) data was used to estimate genomic breeding values for growth and carcass traits in Australian Angus cattle. The study aimed to compare the accuracy and bias of genomic predictions with three marker densities, including 50K, high-density (HD) and WGS. The dataset used in this study consisted of animals born between 2013 and 2022. Body weight traits included birthweight, weight at 400 days and weight at 600 days of age. The carcass traits were carcass weight, carcass intramuscular fat and carcass marbling score. The accuracy and bias of prediction were assessed using the cross-validation. Further, for the growth traits, animals in the validation group were subdivided into two subgroups, which were moderately or highly related to the reference. Genomic best linear unbiased prediction (GBLUP) was used to compare genomic predictions with the three marker densities. The prediction accuracies were generally similar across the marker densities, ranging between 0.61 and 0.68 for the body weight traits and between 0.40 and 0.52 for the carcass traits. However, the accuracies marginally decreased as the marker density increased for all the traits studied. A similar lack of difference was found when considering the accuracy by the relatedness subgroups. The results indicated that no meaningful difference in prediction accuracy was estimated when comparing the three marker densities due to the population structure. In conclusion, there was no substantial improvement in genomic prediction when using the WGS in this study., (© 2024 Wiley‐VCH GmbH. Published by John Wiley & Sons Ltd.)

This study reports the molecular epidemiology and genetic characterization of human respiratory syncytial virus (RSV) samples collected in Thailand from January 2010 to December 2011. In total, 1,315 clinical samples were collected from Bangkok and Khon Kaen provinces and were screened by semi-nested PCR for RSV infection. We found 74 samples (27.7 %) and 71 samples (6.8 %) to be RSV positive for Bangkok and Khon Kaen, respectively, and we sequenced 122 of these samples. Phylogenetic analysis revealed that 100 of the RSV-A-positive samples clustered into either genotype NA1 or the recently discovered genotype ON1 strain, which has a 72-nucleotide duplication in the second variable region of its G protein. Moreover, 22 of the RSV-B-positive samples clustered into four genotypes; BA4, BA9, BA10 and genotype THB, first described here. The NA1 genotype was found to be the predominant strain in 2010 and 2011. The ON1 strain detected in this study first emerged in 2011 and is genetically similar to ON1 strains characterized in other counties. We also describe the THB genotype, which was first identified in 2005 and is genetically similar to the GB2 genotype. In conclusion, this study indicates the importance of molecular epidemiology and characterization of RSV in Thailand in order to better understand this virus. Further studies should be conducted to bolster the development of antiviral agents and a vaccine.