This genome-wide association study (GWAS) was conducted to identify major loci that are significantly associated with carcass weight, and their effects, in order to provide increased understanding of the genetic architecture of carcass weight in Hanwoo. This genome-wide association study identified one major chromosome region ranging from 23 Mb to 25 Mb on chromosome 14 as being associated with carcass weight in Hanwoo. Significant Bonferroni-corrected genome-wide associations (P<1.52×10−6) were detected for 6 Single Nucleotide Polymorphic (SNP) loci for carcass weight on chromosome 14. The most significant SNP was BTB-01280026 (P = 4.02×10−11), located in the 25 Mb region on Bos taurus autosome 14 (BTA14). The other 5 significant SNPs were Hapmap27934-BTC-065223 (P = 4.04×10−11) in 25.2 Mb, BTB-01143580 (P = 6.35×10−11) in 24.3 Mb, Hapmap30932-BTC-011225 (P = 5.92×10−10) in 24.8 Mb, Hapmap27112-BTC-063342 (P = 5.18×10−9) in 25.4 Mb, and Hapmap24414-BTC-073009 (P = 7.38×10−8) in 25.4 Mb, all on BTA 14. One SNP (BTB-01143580; P = 6.35×10−11) lies independently from the other 5 SNPs. The 5 SNPs that lie together showed a large Linkage disequilibrium (LD) block (block size of 553 kb) with LD coefficients ranging from 0.53 to 0.89 within the block. The most significant SNPs accounted for 6.73% to 10.55% of additive genetic variance, which is quite a large proportion of the total additive genetic variance. The most significant SNP (BTB-01280026; P = 4.02×10−11) had 16.96 kg of allele substitution effect, and the second most significant SNP (Hapmap27934-BTC-065223; P = 4.04×10−11) had 18.06 kg of effect on carcass weight, which correspond to 44% and 47%, respectively, of the phenotypic standard deviation for carcass weight in Hanwoo cattle. Our results demonstrated that carcass weight was affected by a major Quantitative Trait Locus (QTL) with a large effect and by many SNPs with small effects that are normally distributed.

Hanwoo (Korean cattle) is the native, taurine type of cattle breed of Korea and its history as a draft animal dates back to 5000 Years. In earlier times Hanwoo was used extensively for farming, transportation. Over the period of time, Hanwoo has changed to be meat type cattle. Full-scale production of Hanwoo as meat-type cattle has occurred since 1960s with the rapid growth of the Korean economy. Hanwoo is one of the most economically important species in Korea as it is a significant source of nutrition to the Korean people. Hanwoo beef is the most cherished food of Korea. One of the main goals of researchers is to increase the meat quality, quantity and taste of the beef. In this review we describe the origin, domestication of Hanwoo cattle and breeding program initiated from 1980’s. Moreover the advent of technological advancement had provided us a platform to perform genome wide selection on economic traits and its implementation into traditional breeding programs.

Undoubtedly livestock is one of the major contributors to the economy of any country. The economic value of livestock includes meat, dairy products, fiber, fertilizer etc. Understanding and identifying the associations of quantitative trait loci (QTL) with the economically important traits is believed to substantially benefit the livestock industry. The past two decades have seen a flurry of interest in mapping the QTL associated with traits of economic importance on the genome. With the availability of single nucleotide polymorphism chip of various densities it is possible to identify regions, QTL and genes on the genome that explain the association and its effect on the phenotype under consideration. Remarkable advancement has been seen in genome wide association studies (GWAS) since its inception till the present day. In this review we describe the progress and challenges of GWAS in various livestock species.

Holstein is one among the dairy cattle which provide higher milk yields than most other cattle breeds. Lack of high-accuracy, reliable methods for early detection of cattle pregnancy reduces overall productivity and constitutes a high economic burden to the dairy industry. The circulating microRNAs (miRNAs) in exosomes could provide information and serve as potential biomarkers for livestock health and disease. However, the complexity of miRNA in response to cattle early pregnancy remains unknown. Hence, we collected blood samples of three healthy dairy cows of normal and 30 days of pregnancy, in order to further characterize the miRNA transcriptome profile. A high-throughput RNA-Seq approach detected 794 known and 2154 novel circulating miRNAs in six libraries. A total of 29 miRNAs in the 30 days of pregnancy group showed significant differences compared to the normal group. Further, bta-miR-450b, bta-miR-146b, bta-miR-26b and bta-miR-27b were up-regulated which shown to be involved in preeclampsia, immune response and mammary gland development. GO enrichment analysis showed these target genes were involved in the metabolic process, signal transducer activity, and membrane etc., while KEGG analysis showed that these genes were enriched in membrane trafficking, chromosome and associated proteins, exosome and G protein-coupled receptors pathways. These results provide an experimental basis to reveal the potential role of miRNAs as biomarkers in early diagnosis of pregnancy and other molecular functions.

Significant SNPs associated with Warner-Bratzler (WB) shear force and sensory traits were confirmed for Hanwoo beef (Korean cattle). A Bonferroni-corrected genome-wide significant association (p<1.3×10−6) was detected with only one single nucleotide polymorphism (SNP) on chromosome 5 for WB shear force. A slightly higher number of SNPs was significantly (p<0.001) associated with WB shear force than with other sensory traits. Further, 50, 25, 29, and 34 SNPs were significantly associated with WB shear force, tenderness, juiciness, and flavor likeness, respectively. The SNPs between p = 0.001 and p = 0.0001 thresholds explained 3% to 9% of the phenotypic variance, while the most significant SNPs accounted for 7% to 12% of the phenotypic variance. In conclusion, because WB shear force and sensory evaluation were moderately affected by a few loci and minimally affected by other loci, further studies are required by using a large sample size and high marker density.

This study was conducted to estimate genetic parameters for ultrasound and carcass traits in Hanwoo. Heritabilities and genetic and phenotypic correlations were estimated for carcass and ultrasound measurements collected from Hanwoo cows (n=312) born at Hanwoo experiment station. Traits evaluated were eye muscle area (EMA), backfat thickness (BF), marbling score (MS) from carcass, and ultrasound eye muscle area (UEMA), ultrasound backfat (UBF), and ultrasound marbling score (UMS). Parameters were estimated using multi-trait animal models byderivative-free restricted maximum likelihood procedures. Estimated heritabilities for UBF, UEMA and UMS were 0.43, 0.23 and 0.32, while heritabilities for BF, EMA and MS were 0.33, 0.13 and 0.33 in fattened cows, respectively. Genetic correlations between ultrasound and carcass measurements were estimated to -0.19, -0.61, and -0.36 for UBF: UEMA, UBF: UMS, and UEMA: UMS in fattened cows, respectively. Phenotypic correlations between ultrasound and carcass measurements were 0.03, 0.13 and 0.26 for UBF: UEMA, UBF: UMS, and UEMA: UMS in fattened cows, respectively. As for the steer, genetic correlations between ultrasound and carcass measurements were 0.36, -0.80 and 0.27 for UBF: UEMA, UBF: UMS, and UEMA: UMS in steers, respectively. Phenotypic correlations between ultrasound and carcass measurements were 0.13, 0.07 and 0.41 for UBF: UEMA, UBF: UMS, and UEMA: UMS in steers, respectively. In conclusion, this finding would be very useful to implement into Hanwoo breeding program.

:The objective of this study was to establish genetic evaluation systems with carcass data collected by 68 individual farms from 2007 to 2011 in Pyeongchang area of Kangwon province. All the possible of environment effects were corrected by analysis of variance (ANOVA) to estimate more accurate genetic parameters. Heritabilities and genetic correlations were estimated from carcass data collected from Hanwoo steers(n=10,441) born in Pyeongchang region from 2005 to 2008. Traits evaluated included carcass weight (CWT), eye muscle area (EMA), back fat thickness (BF) and marbling score (MS). As for the mean value and standard deviation for carcass traits, CWT, EMA, BF and MS were 424.5, 92, 13.7 and 5.7. Parameters were estimated using a multiple trait animal model and derivative-free restricted maximum likelihood procedures. Estimated heritabilities for CWT, EMA, BF and MS were 0.30, 0.21, 0.42 and 0.42, respectively. Genetic correlation of CWT with EMA, BF and MS were estimated to 0.24, 0.36 and 0.07, respectively. Genetic correlation of EMA with BF and MS was -0.27 and 0.61, respectively.

Objective The objectives of this study were to compare identified informative regions through two genome-wide association study (GWAS) approaches and determine the accuracy and bias of the direct genomic value (DGV) for milk production traits in Korean Holstein cattle, using two genomic prediction approaches: single-step genomic best linear unbiased prediction (ss-GBLUP) and Bayesian Bayes-B. Methods Records on production traits such as adjusted 305-day milk (MY305), fat (FY305), and protein (PY305) yields were collected from 265,271 first parity cows. After quality control, 50,765 single-nucleotide polymorphic genotypes were available for analysis. In GWAS for ss-GBLUP (ssGWAS) and Bayes-B (BayesGWAS), the proportion of genetic variance for each 1-Mb genomic window was calculated and used to identify informative genomic regions. Accuracy of the DGV was estimated by a five-fold cross-validation with random clustering. As a measure of accuracy for DGV, we also assessed the correlation between DGV and deregressed-estimated breeding value (DEBV). The bias of DGV for each method was obtained by determining regression coefficients. Results A total of nine and five significant windows (1 Mb) were identified for MY305 using ssGWAS and BayesGWAS, respectively. Using ssGWAS and BayesGWAS, we also detected multiple significant regions for FY305 (12 and 7) and PY305 (14 and 2), respectively. Both single-step DGV and Bayes DGV also showed somewhat moderate accuracy ranges for MY305 (0.32 to 0.34), FY305 (0.37 to 0.39), and PY305 (0.35 to 0.36) traits, respectively. The mean biases of DGVs determined using the single-step and Bayesian methods were 1.50±0.21 and 1.18±0.26 for MY305, 1.75±0.33 and 1.14±0.20 for FY305, and 1.59±0.20 and 1.14±0.15 for PY305, respectively. Conclusion From the bias perspective, we believe that genomic selection based on the application of Bayesian approaches would be more suitable than application of ss-GBLUP in Korean Holstein populations.