Background: In this study, we assessed the accuracy of genomic prediction for carcass weight (CWT), marbling score (MS), eye muscle area (EMA) and back fat thickness (BFT) in Hanwoo cattle when using genomic best linear unbiased prediction (GBLUP), weighted GBLUP (wGBLUP), and a BayesR model. For these models, we investigated the potential gain from using pre-selected single nucleotide polymorphisms (SNPs) from a genome-wide association study (GWAS) on imputed sequence data and from gene expression information. We used data on 13,717 animals with carcass phenotypes and imputed sequence genotypes that were split in an independent GWAS discovery set of varying size and a remaining set for validation of prediction. Expression data were used from a Hanwoo gene expression experiment based on 45 animals. Results: Using a larger number of animals in the reference set increased the accuracy of genomic prediction whereas a larger independent GWAS discovery dataset improved identification of predictive SNPs. Using pre-selected SNPs from GWAS in GBLUP improved accuracy of prediction by 0.02 for EMA and up to 0.05 for BFT, CWT, and MS, compared to a 50 k standard SNP array that gave accuracies of 0.50, 0.47, 0.58, and 0.47, respectively. Accuracy of prediction of BFT and CWT increased when BayesR was applied with the 50 k SNP array (0.02 and 0.03, respectively) and was further improved by combining the 50 k array with the top-SNPs (0.06 and 0.04, respectively). By contrast, using BayesR resulted in limited improvement for EMA and MS. wGBLUP did not improve accuracy but increased prediction bias. Based on the RNA-seq experiment, we identified informative expression quantitative trait loci, which, when used in GBLUP, improved the accuracy of prediction slightly, i.e. between 0.01 and 0.02. SNPs that were located in genes, the expression of which was associated with differences in trait phenotype, did not contribute to a higher prediction accuracy. Conclusions: Our results show that, in Hanwoo beef cattle, when SNPs are pre-selected from GWAS on imputed sequence data, the accuracy of prediction improves only slightly whereas the contribution of SNPs that are selected based on gene expression is not significant. The benefit of statistical models to prioritize selected SNPs for estimating genomic breeding values is trait-specific and depends on the genetic architecture of each trait.

Korean Hanwoo cattle are known for their high meat quality, especially their high intramuscular fat compared to most other cattle breeds. Different muscles have very different meat quality traits and a study of the myogenic process in satellite cells can help us better understand the genes and pathways that regulate this process and how muscles differentiate. Cell cultures of Longissimus dorsi muscle differentiated from myoblast into multinucleated myotubes faster than semimembranosus. Time-series RNA-seq identified a total of 13 differentially expressed genes between the two muscles during their development. These genes seem to be involved in determining muscle lineage development and appear to modulate the expression of myogenic regulatory factors (mainly MYOD and MYF5) during differentiation of satellite cells into multinucleate myotubes. Gene ontology enriched terms were consistent with the morphological changes observed in the histology. Most of the over-represented terms and genes expressed during myoblast differentiation were similar regardless of muscle type which indicates a highly conserved myogenic process albeit the rates of differentiation being different. There were more differences in the enriched GO terms during the end of proliferation compared to myoblast differentiation. The use of satellite cells from newborn Hanwoo calves appears to be a good model to study embryonic myogenesis in muscle. Our findings provide evidence that the differential expression of HOXB2, HOXB4, HOXB9, HOXC8, FOXD1, IGFN1, ZIC2, ZIC4, HOXA11, HOXC11, PITX1, SIM2 and TBX4 genes could be involved in the differentiation of Longissimus dorsi and Semimembranosus muscles. These genes seem to modulate the muscle fate of the satellite cells during myogenesis through a differential expression profile that also controls the expression of some myogenic regulatory factors (MYOD and MYF5). The number of differentially expressed genes across time was unsurprisingly large. In relation to the baseline day 0, there were 631, 155, 175, 519 and 586 DE genes in LD, while in SM we found 204, 0, 615, 761 and 1154 DE genes at days 1, 2, 4, 7 and 14 respectively.

Genome-wide association studies (GWAS) are extensively used to identify single nucleotide polymorphisms (SNP) underlying the genetic variation of complex traits. However, much uncertainly often still exists about the causal variants and genes at quantitative trait loci (QTL). The aim of this study was to identify QTL associated with residual feed intake (RFI) and genes in these regions whose expression is also associated with this trait. Angus cattle (2190 steers) with RFI records were genotyped and imputed to high density arrays (770 K) and used for a GWAS approach to identify QTL associated with RFI. RNA sequences from 126 Angus divergently selected for RFI were analyzed to identify the genes whose expression was significantly associated this trait with special attention to those genes residing in the QTL regions. The heritability for RFI estimated for this Angus population was 0.3. In a GWAS, we identified 78 SNPs associated with RFI on six QTL (on BTA1, BTA6, BTA14, BTA17, BTA20 and BTA26). The most significant SNP was found on chromosome BTA20 (rs42662073) and explained 4% of the genetic variance. The minor allele frequencies of significant SNPs ranged from 0.05 to 0.49. All regions, except on BTA17, showed a significant dominance effect. In 1 Mb windows surrounding the six significant QTL, we found 149 genes from which OAS2, STC2, SHOX, XKR4, and SGMS1 were the closest to the most significant QTL on BTA17, BTA20, BTA1, BTA14, and BTA26, respectively. In a 2 Mb windows around the six significant QTL, we identified 15 genes whose expression was significantly associated with RFI: BTA20) NEURL1B and CPEB4; BTA17) RITA1, CCDC42B, OAS2, RPL6, and ERP29; BTA26) A1CF, SGMS1, PAPSS2, and PTEN; BTA1) MFSD1 and RARRES1; BTA14) ATP6V1H and MRPL15. Our results showed six QTL regions associated with RFI in a beef Angus population where five of these QTL contained genes that have expression associated with this trait. Therefore, here we show that integrating information from gene expression and GWAS studies can help to better understand the genetic mechanisms that determine variation in complex traits.

Ram semen traits play a significant role in conception outcomes, which in turn may influence reproductive efficiency and the overall productivity and profitability of sheep enterprises. Since hundreds of ewes may be inseminated from a single ejaculate, it is important to evaluate semen quality prior to use in sheep breeding programs. Given that semen traits have been found to be heritable, genetic variation likely contributes to the variability observed in these traits. Identifying such genetic variants could provide novel insights into the molecular mechanisms underlying variability in semen traits. Therefore, this study aimed to identify quantitative trait loci (QTLs) associated with semen traits in Merino sheep. A genome-wide association study (GWAS) was undertaken using 4506 semen collection records from 246 Merino rams collected between January 2002 and May 2021. The R package RepeatABEL was used to perform a GWAS for semen volume, gross motility, concentration, and percent post-thaw motility. A total of 35 QTLs, located on 16 Ovis aries autosomes (OARs), were significantly associated with either of the four semen traits in this study. A total of 89, 95, 33, and 73 candidate genes were identified, via modified Bonferroni, within the QTLs significantly associated with volume, gross motility, concentration, and percent post-thaw motility, respectively. Among the candidate genes identified, SORD, SH2B1, and NT5E have been previously described to significantly influence spermatogenesis, spermatozoal motility, and high percent post-thaw motility, respectively. Several candidate genes identified could potentially influence ram semen traits based on existing evidence in the literature. As such, validation of these putative candidates may offer the potential to develop future strategies to improve sheep reproductive efficiency. Furthermore, Merino ram semen traits are lowly heritable (0.071–0.139), and thus may be improved by selective breeding.

The genomic best linear unbiased prediction (GBLUP) method has been widely used in routine genomic evaluation as it assumes a common variance for all single nucleotide polymorphism (SNP). However, this is unlikely in the case of traits influenced by major SNP. Hence, the present study aimed to improve the accuracy of GBLUP by using the weighted GBLUP (WGBLUP), which gives more weight to important markers for various carcass traits of Hanwoo cattle, such as backfat thickness (BFT), carcass weight (CWT), eye muscle area (EMA), and marbling score (MS). Linear and different nonlinearA SNP weighting procedures under WGBLUP were evaluated and compared with unweighted GBLUP and traditional pedigree-based methods (PBLUP). WGBLUP methods were assessed over ten iterations. Phenotypic data from 10,215 animals from different commercial herds that were slaughtered at approximately 30-month-old of age were used. All these animals were genotyped using Illumina Bovine 50k SNP chip and were divided into a training and a validation population by birth date on 1 November 2015. Genomic prediction accuracies obtained in the nonlinearA weighting methods were higher than those of the linear weighting for all traits. Moreover, unlike with linear methods, no sudden drops in the accuracy were noted after the peak was reached in nonlinearA methods. The average accuracies using PBLUP were 0.37, 0.49, 0.40, and 0.37, and 0.62, 0.74, 0.67, and 0.65 using GBLUP for BFT, CWT, EMA, and MS, respectively. Moreover, these accuracies of genomic prediction were further increased to 4.84% and 2.70% for BFT and CWT, respectively by using the nonlinearA method under the WGBLUP model. For EMA and MS, WGBLUP was as accurate as GBLUP. Our results indicate that the WGBLUP using a nonlinearA weighting method provides improved predictions for CWT and BFT, suggesting that the ability of WGBLUP over the other models by weighting selected SNPs appears to be trait-dependent.

It is well known that male and female broilers differ in their growth performance and that many physiological factors contribute to this difference. The aim of this experiment is to investigate if there are differences between male and female broilers in cecal microbiota and nutrient transporter gene expression and if these differences play a role in the growth performance of broilers. The possible effect of protein level and its interaction with sex on microbiota and expression of the nutrient transporters were also investigated. Samples were collected from male and female birds fed either standard crude protein (SCP) or reduced crude protein diets (RCP) at the age of d 35. The experiment was designed as a 2 × 2 factorial arrangement of treatments consisting of 448 Cobb 500 broilers assigned to 32-floor pens with 4 treatments, 8 replicates, and 14 birds per pen for performance measurements. The factors were sex (male or female) and dietary crude protein (CP) level (standard or reduced). Body weight gain (BWG), feed intake and feed conversion ratio were recorded for each pen. Sex had a significant effect on BWG and FCR (P < 0.001) where males had a significantly higher BWG and better FCR compared to females. There was a significant interaction between sex and protein level on feed intake (FI) (P < 0.05), where male birds had a higher FI compared to female birds only when the birds were fed SCP but not RCP diets. There was a significant interaction between CP level and sex on the expression of CAT2 (P = 0.02) and PEPT2 (P = 0.026) where the genes were significantly upregulated in females but only when the RCP diet was fed. The RCP diet upregulated the expression of B^oAT (P = 0.03) as a main effect. Female birds had significantly higher expression of the PepT-2 gene compared to the males. The alpha diversity of the cecal microbiota showed differences among the treatments. The Shannon diversity index was statistically higher (P = 0.036) for males fed the SCP diet and the Chao1 index for evenness was statistically higher (P = 0.027) in females fed the SCP diet. There was also a difference in the relative abundance of the 15 most common genera found in the cecal content of the broilers in this experiment and lastly, the differential composition of microbiota between the different treatments was also significantly different. This study suggests that chickens are able to compensate for a reduction in AA substrates when fed a low CP diet through the upregulation of certain AA transporters, females may adapt to low CP diets better by such upregulation compared to males, and lastly, sex has an effect on the cecal microbial population and these differences contribute towards the performance differences between male and female broilers.