A retrospective analysis of conception per embryo transfer in dairy cattle in South Korea.

The bovine embryo production industry has seen significant growth over the past two decades, particularly in the production of in vitro produced embryos. This growth, driven by advancements in cryopreservation, in vitro culture mediums, ovum pick-up (OPU) procedures, ultrasonography devices, and embryo transfer (ET) has been notable. Particularly, ET is crucial for disseminating high genetic merit and amplifying foreign breeds by importing frozen embryos. This retrospective study aimed to assess factors affecting conception per embryo transfer (CPET) in Holstein-Friesian cattle in South Korea from October 2008 to July 2022. We evaluated type of embryo breed, type of embryo production (fresh and frozen; in vitro and in vivo production), recipient conditions including estrus type, corpus luteum quality, parity (nulliparous heifers, primiparous, and multiparous cows), and the daily mean temperature-humidity index (THI) as an index for heat stress. Type of embryo breed and estrus had no significant impact on CPET. However, we observed higher CPET in recipients with good quality corpus luteum, nulliparous heifers, and surrogates receiving fresh in vitro and frozen in vivo embryos. Importantly, CPET was not adversely affected by mild heat stress conditions (up to daily mean THI 76), indicating that using frozen in vivo embryos produced by multiple ovulation embryo transfer and fresh in vitro embryos by OPU-ET can help alleviate the subfertility issues in dairy cattle caused by global warming in Korea.

Genomic evaluation of carcass traits of Korean beef cattle Hanwoo using a single-step marker effect model.

Hanwoo beef cattle are well known for the flavor and tenderness of their meat. Genetic improvement programs have been extremely successful over the last 40 yr. Recently, genomic selection was initiated in Hanwoo to enhance genetic progress. Routine genomic evaluation based on the single-step breeding value model was implemented in 2020 for all economically important traits. In this study, we tested a single-step marker effect model for the genomic evaluation of four carcass traits, namely, carcass weight (CW), eye muscle area, backfat thickness, and marbling score. In total, 8,023,666 animals with carcass records were jointly evaluated, including 29,965 genotyped animals. To assess the prediction stability of the single-step model, carcass data from the last 4 yr were removed in a forward validation study. The estimated genomic breeding values (GEBV) of the validation animals and other animals were compared between the truncated and full evaluations. A parallel conventional best linear unbiased prediction (BLUP) evaluation with either the full or the truncated dataset was also conducted for comparison with the single-step model. The estimates of the marker effect from the truncated evaluation were highly correlated with those from the full evaluation, ranging from 0.88 to 0.92. The regression coefficients of the estimates of the marker effect for the full and truncated evaluations were close to their expected value of 1, indicating unbiased estimates for all carcass traits. Estimates of the marker effect revealed three chromosomal regions (chromosomes 4, 6, and 14) harboring the major genes for CW in Hanwoo. For validation of cows or steers, the single-step model had a much higher R2 value for the linear regression model than the conventional BLUP model. Based on the regression intercept and slope of the validation, the single-step evaluation was neither inflated nor deflated. For genotyped animals, the estimated GEBV from the full and truncated evaluations were more correlated than the estimated breeding values from the two conventional BLUP evaluations. The single-step model provided a more accurate and stable evaluation over time.

Hanwoo beef cattle are well known for the flavor and tenderness of their meat. Genetic improvement programs have been successful over the last 40 yr. Recently, genomic selection was initiated in Hanwoo to enhance genetic progress. A routine genomic evaluation based on the single-step breeding value model was implemented in 2020 for all economically important traits. In this study, we tested a single-step marker effect model for the genomic evaluation of four carcass traits. In total, 8,023,666 cows or steers with carcass records were jointly evaluated, including 29,965 genotyped animals. To assess the prediction accuracy of the single-step model, carcass data from the last 4 yr were removed in a forward validation study. Estimated genomic breeding values (GEBV) of validation animals were compared between truncated and full evaluations. A parallel conventional best linear unbiased prediction (BLUP) evaluation with either the full or truncated dataset was conducted for comparison with the single-step model. Plots of the estimates of the marker effect showed three chromosomal regions harboring the major genes for carcass weight in Hanwoo. The single-step model yielded a more accurate and stable evaluation over time than the conventional BLUP model.

Case Study: Improving the Quality of Dairy Cow Reconstruction with a Deep Learning-Based Framework.

Three-dimensional point cloud generation systems from scanning data of a moving camera provide extra information about an object in addition to color. They give access to various prospective study fields for researchers. With applications in animal husbandry, we can analyze the characteristics of the body parts of a dairy cow to improve its fertility and milk production efficiency. However, in the depth image generation from stereo data, previous solutions using traditional stereo matching algorithms have several drawbacks, such as poor-quality depth images and missing information in overexposed regions. Additionally, the use of one camera to reconstruct a comprehensive 3D point cloud of the dairy cow has several challenges. One of these issues is point cloud misalignment when combining two adjacent point clouds with the small overlapping area between them. In addition, another drawback is the difficulty of point cloud generation from objects which have little motion. Therefore, we proposed an integrated system using two cameras to overcome the above disadvantages. Specifically, our framework includes two main parts: data recording part applies state-of-the-art convolutional neural networks to improve the depth image quality, and dairy cow 3D reconstruction part utilizes the simultaneous localization and calibration framework in order to reduce drift and provide a better-quality reconstruction. The experimental results showed that our approach improved the quality of the generated point cloud to some extent. This work provides the input data for dairy cow characteristics analysis with a deep learning approach.

The Estimation of Genetic Parameters for Longevity According to Lactation Period Using a Multiple Trait Animal Model in Korean Holstein Cows.

Longevity is closely related to the survival rate of dairy cattle and refers to the period during which the cow has economic value, from first calving to culling. The purpose of this study was to analyze the culling patterns and survival rates of Korean Holstein cows and evaluate genetic characteristics related to parity and longevity of each lactation by using the test day milk yield collected in South Korea. The performance data of the dairy cattle were collected from 2004 to 2019 by the Nonghyup Dairy Cattle Improvement Center. The collected 1,702,304 records were used as pedigree data through the Korea Animal Improvement Association. The lactation period was divided into early-lactation (0-90 days: L1.1, L2.1, and L3.1), mid-lactation (91-299 days: L1.2, L2.2, and L3.2), and late-lactation (300 days-next parity: L1.3, L2.3, and L3.3). The heritability of longevity for the first, second, and third parity was 0.020, 0.028, and 0.039, respectively. In all parities, the heritability in late-lactation was higher than that in early- and mid-lactation. Most genetic correlations for survival in the first parity were higher than those in the second and third parities. The results of this study may serve as a basis for developing a more accurate model for evaluating longevity traits in South Korea.

Genetic Analysis of Major Production and Reproduction Traits of Korean Duroc, Landrace and Yorkshire Pigs.

The study aimed to investigate the genetic parameters of the production and reproduction traits of Korean Duroc, Landrace, and Yorkshire pigs. Three production traits, namely average daily gain (ADG), age at 105 kg body weight (DAYS105) and backfat thickness (BFT), and three reproduction traits, namely age at first farrowing (AFF), total number of piglets born (TNB) and number of piglets born alive (NBA), were analyzed. The reproduction dataset was based on first-parity gilts only. However, the production dataset comprised pigs of both sexes. Genetic parameters were estimated from individual datasets using a multiple-trait animal model in AIREMLF90 software. The heritability values of ADG, DAYS105 and BFT were 0.34-0.36, 0.41-0.44 and 0.38-0.48, respectively, across breeds. Heritability values for AFF, TNB and NBA were 0.07-0.14, 0.09-0.11 and 0.09-0.10, respectively. Strong genetic correlations existed between ADG and DAYS105 (-0.97) and between TNB and NBA (0.90 to 0.96). In line with breeding goals, all productive traits in Duroc pigs, and all reproduction traits except AFF in Landrace and Yorkshire pigs, also showed noticeable improvements in recent years. In conclusion, we believe that our findings on economic traits would greatly assist future pig breeding decisions in Korea.

Genomic Prediction Using Alternative Strategies of Weighted Single-Step Genomic BLUP for Yearling Weight and Carcass Traits in Hanwoo Beef Cattle.

The weighted single-step genomic best linear unbiased prediction (GBLUP) method has been proposed to exploit information from genotyped and non-genotyped relatives, allowing the use of weights for single-nucleotide polymorphism in the construction of the genomic relationship matrix. The purpose of this study was to investigate the accuracy of genetic prediction using the following single-trait best linear unbiased prediction methods in Hanwoo beef cattle: pedigree-based (PBLUP), un-weighted (ssGBLUP), and weighted (WssGBLUP) single-step genomic methods. We also assessed the impact of alternative single and window weighting methods according to their effects on the traits of interest. The data was comprised of 15,796 phenotypic records for yearling weight (YW) and 5622 records for carcass traits (backfat thickness: BFT, carcass weight: CW, eye muscle area: EMA, and marbling score: MS). Also, the genotypic data included 6616 animals for YW and 5134 for carcass traits on the 43,950 single-nucleotide polymorphisms. The ssGBLUP showed significant improvement in genomic prediction accuracy for carcass traits (71%) and yearling weight (99%) compared to the pedigree-based method. The window weighting procedures performed better than single SNP weighting for CW (11%), EMA (11%), MS (3%), and YW (6%), whereas no gain in accuracy was observed for BFT. Besides, the improvement in accuracy between window WssGBLUP and the un-weighted method was low for BFT and MS, while for CW, EMA, and YW resulted in a gain of 22%, 15%, and 20%, respectively, which indicates the presence of relevant quantitative trait loci for these traits. These findings indicate that WssGBLUP is an appropriate method for traits with a large quantitative trait loci effect.

Identification of Monoallelically Expressed Genes Associated with Economic Traits in Hanwoo (Korean Native Cattle).

Hanwoo, an indigenous Korean cattle breed, has been genetically improved by selecting superior sires called Korean-proven bulls. However, cows still contribute half of the genetic stock of their offspring, and allelic-specific expressed genes have potential, as selective targets of cows, to enhance genetic gain. The aim of this study is to identify genes that have MAEs based on both the genome and transcriptome and to estimate their effects on breeding values (BVs) for economically important traits in Hanwoo. We generated resequencing data for the parents and RNA-sequencing data for the muscle, fat, and brain tissues of the offspring. A total of 3801 heterozygous single nucleotide polymorphisms (SNPs) in offspring were identified and they were located in 1569 genes. Only 14 genes showed MAE (seven expressing maternal alleles and seven expressing paternal alleles). Tissue-specific MAE was observed, and LANCL1 showed maternal allele expression across all tissues. MAE genes were enriched for the biological process of cell death and angiogenesis, which included ACKR3 and PDCL3 genes, whose SNPs were significantly associated with BVs of lean meat production-related traits, such as weight at 12 months of age, carcass weight, and loin eye area. In the current study, monoallelically expressed genes were identified in various adult tissues and these genes were associated with genetic capacity in Hanwoo.

Genome-wide investigation of a Korean synthetic breed, Woori-Heukdon using the Illumina PorcineSNP60K BeadChip.

BACKGROUND: Woori-Heukdon (KWH) is a Korean synthetic pig breed generated using Chookjin-Duroc (KCD), Chookjin-Chamdon (KCC), and their crossbreds. Currently, there is a severe lack of studies investigating the Korean breed populations including wild boars (KWB) throughout the genome. OBJECTIVE: This study was performed to investigate the genetic characteristics of Korean pig populations at the genome-wide level. METHODS: Using the SNP dataset derived from genotyped and downloaded datasets using the Illumina PorcineSNP60K BeadChip, we compared the genomes of 532 individuals derived from 23 pig breeds to assess the genetic diversity, inbreeding coefficient, genetic differentiation, and population structure. RESULTS: KWB showed the lowest average expected heterozygosity (HE = 0.1904), while KWH showed the highest genetic diversity (HE = 0.02859) among Korean populations. We verified that the genetic composition of KWH, showing USD of 74.8% and KCC of 25.2% in ADMIXTURE analysis. In population structure analyses, KCC was consistently shown to be separated from other pig populations. In addition, we observed gene flow from Western pigs to a part of Chinese populations. CONCLUSION: This study showed that Korean native pigs, KCC have genetic differences in comparison with Chinese and Western pigs; despite some historical records and recent genetic studies, we could not find any clear evidence that KCC was significantly influenced by Chinese or Western breeds in this study. We also verified the theoretical genomic composition of KWH at the molecular level in structure analyses. To our knowledge, this is the first genomic study to investigate the genomic characteristics of KWH and KCC.

Genomic Analysis Using Bayesian Methods under Different Genotyping Platforms in Korean Duroc Pigs.

Genomic evaluation has been widely applied to several species using commercial single nucleotide polymorphism (SNP) genotyping platforms. This study investigated the informative genomic regions and the efficiency of genomic prediction by using two Bayesian approaches (BayesB and BayesC) under two moderate-density SNP genotyping panels in Korean Duroc pigs. Growth and production records of 1026 individuals were genotyped using two medium-density, SNP genotyping platforms: Illumina60K and GeneSeek80K. These platforms consisted of 61,565 and 68,528 SNP markers, respectively. The deregressed estimated breeding values (DEBVs) derived from estimated breeding values (EBVs) and their reliabilities were taken as response variables. Two Bayesian approaches were implemented to perform the genome-wide association study (GWAS) and genomic prediction. Multiple significant regions for days to 90 kg (DAYS), lean muscle area (LMA), and lean percent (PCL) were detected. The most significant SNP marker, located near the MC4R gene, was detected using GeneSeek80K. Accuracy of genomic predictions was higher using the GeneSeek80K SNP panel for DAYS (Δ2%) and LMA (Δ2-3%) with two response variables, with no gains in accuracy by the Bayesian approaches in four growth and production-related traits. Genomic prediction is best derived from DEBVs including parental information as a response variable between two DEBVs regardless of the genotyping platform and the Bayesian method for genomic prediction accuracy in Korean Duroc pig breeding.

Genomic partitioning of growth traits using a high-density single nucleotide polymorphism array in Hanwoo (Korean cattle).

OBJECTIVE: The objective of this study was to characterize the number of loci affecting growth traits and the distribution of single nucleotide polymorphism (SNP) effects on growth traits, and to understand the genetic architecture for growth traits in Hanwoo (Korean cattle) using genome-wide association study (GWAS), genomic partitioning, and hierarchical Bayesian mixture models. METHODS: GWAS: A single-marker regression-based mixed model was used to test the association between SNPs and causal variants. A genotype relationship matrix was fitted as a random effect in this linear mixed model to correct the genetic structure of a sire family. Genomic restricted maximum likelihood and BayesR: A priori information included setting the fixed additive genetic variance to a pre-specified value; the first mixture component was set to zero, the second to 0.0001×σ_g^2, the third 0.001 × σ_g^2, d the fourth to 0.01 × σ_g^2. BayesR fixed a priori information was not more than 1% of the genetic variance for each of the SNPs affecting the mixed distribution. RESULTS: The GWAS revealed common genomic regions of 2 Mb on bovine chromosome 14 (BTA14) and 3 had a moderate effect that may contain causal variants for body weight at 6, 12, 18, and 24 months. This genomic region explained approximately 10% of the variance against total additive genetic variance and body weight heritability at 12, 18, and 24 months. BayesR identified the exact genomic region containing causal SNPs on BTA14, 3, and 22. However, the genetic variance explained by each chromosome or SNP was estimated to be very small compared to the total additive genetic variance. Causal SNPs for growth trait on BTA14 explained only 0.04% to 0.5% of the genetic variance. CONCLUSION: Segregating mutations have a moderate effect on BTA14, 3, and 19; many other loci with small effects on growth traits at different ages were also identified.

Comparison of genomic predictions for carcass and reproduction traits in Berkshire, Duroc and Yorkshire populations in Korea.

OBJECTIVE: A genome-based best linear unbiased prediction (GBLUP) method was applied to evaluate accuracies of genomic estimated breeding value (GEBV) of carcass and reproductive traits in Berkshire, Duroc and Yorkshire populations in Korean swine breeding farms. METHODS: The data comprised a total of 1,870, 696, and 1,723 genotyped pigs belonging to Berkshire, Duroc and Yorkshire breeds, respectively. Reference populations for carcass traits consisted of 888 Berkshire, 466 Duroc, and 1,208 Yorkshire pigs, and those for reproductive traits comprised 210, 154, and 890 dams for the respective breeds. The carcass traits analyzed were backfat thickness (BFT) and carcass weight (CWT), and the reproductive traits were total number born (TNB) and number born alive (NBA). For each trait, GEBV accuracies were evaluated with a GEBV BLUP model and realized GEBVs. RESULTS: The accuracies under the GBLUP model for BFT and CWT ranged from 0.33-0.72 and 0.33-0.63, respectively. For NBA and TNB, the model accuracies ranged 0.32 to 0.54 and 0.39 to 0.56, respectively. The realized accuracy estimates for BFT and CWT ranged 0.30 to 0.46 and 0.09 to 0.27, respectively, and 0.50 to 0.70 and 0.70 to 0.87 for NBA and TNB, respectively. For the carcass traits, the GEBV accuracies under the GBLUP model were higher than the realized GEBV accuracies across the breed populations, while for reproductive traits the realized accuracies were higher than the model based GEBV accuracies. CONCLUSION: The genomic prediction accuracy increased with reference population size and heritability of the trait. The GEBV accuracies were also influenced by GEBV estimation method, such that careful selection of animals based on the estimated GEBVs is needed. GEBV accuracy will increase with a larger sized reference population, which would be more beneficial for traits with low heritability such as reproductive traits.

Digestibility of phosphorous in cereals and co-products for animal feed.

Feed ingredients used in swine diets contain various levels and availabilities of nutrients. Nutritional precision evaluation of each ingredient is necessary for formulating diets of pigs. Especially, phosphorous (P) is one of important nutrients for metabolism. However, current data of P digestibility were most apparent digestibility. Therefore, this study was aimed to estimate the coefficient of total tract standardized digestibility (CTTSD) of P in cereals and various co-products used in pig diet. Twelve barrows (initial BW ±â€¯SD, 46.70 ±â€¯3.21 kg) were used in this experiment. The experimental design was a 12 × 8 incomplete Latin square with 12 diets and 8 periods. Experimental diets were consisted of barley, wheat, lupine kernel (LK), soybean meal (SBM), almond meal (AM), corn gluten meal (CGM), corn gluten feed from China (CGF-C), corn gluten feed from Korea (CGF-C), wheat bran (WB), rice bran (RB), lupine hull (LH) and P-free diet. The CTTAD of Ca was higher in AM than RB and CGF-K. The LK and CGM showed greater CTTSD of P than RB and LH. In conclusion, our results indicated that the cereals and co-products as P sources were the ideally used as an ingredient in mixed diets of the growing-finishing pigs.

Production of human tissue-type plasminogen activator (htPA) using in vitro cultured transgenic pig mammary gland cells.

Tissue plasminogen activator (tPA) is a protein involved in the breakdown of blood clots. We have previously produced a human tPA (htPA)-overexpressing transgenic pig using a mammary gland-specific promoter. In this study, we have established a transgenic pig mammary gland cell line that produces recombinant htPA. The mammary gland cells grew well and retained their character over long periods of culture. There was no difference in the extent of apoptosis in transgenic cells compared to wild-type mammary gland cells. In addition, the transgenic mammary gland cells expressed and secreted htPA into the conditioned media at a concentration similar to that in milk. This transgenic cell line represents a simple and ethical method for recombinant htPA production.

Social behavior and group growth of finishing pigs with divergent social breeding values / Comportamiento social y crecimiento grupal de cerdos en etapa de finalización con valores divergentes de crianza sociales / Comportamento social e crescimento grupal de porcos de engorda com valores divergentes de criação social

Abstract Background: Behavioral traits of pigs have been shown to be partly under genetic control, which raises the possibility that behavior might be altered by genetic selection, resulting in pigs with better growth performance. Objective: To evaluate the behavior and growth of finishing pigs and investigate pigs selected for high or low social breeding value (SBV) in relation to social behavior and group growth. Methods: Thirty-five females and 35 boars from five positive and five negative SBV groups of finishing pigs were grown from 30 to 90 kg and housed in 10 test pens (3.0 × 3.3 m, 7 pigs/pen). Pigs were recorded with video technology for nine consecutive hours on days 1, 15, and 30 after mixing. Pigs were weighed at approximately 90 kg body weight and the number of days to reach 90 kg was then calculated. Results: The frequency and duration of behaviors were present in the positive and negative SBV groups after mixing. On day 1 after mixing, agonistic behavior was significantly higher (p=0.027) for the -SBV group compared with the +SBV group. Feeding and feeding-together behaviors were significantly higher (p<0.003) in the +SBV group on days 1 and 30 after mixing. Moreover, growth performance to reach 90 kg body weight was significantly faster (p<0.002) in the +SBV group than in the -SBV group. Conclusion: Social interactions, such as feeding-together behavior, among pen mates might affect their growth rate and feed intake. Selection for SBV could be used as an indirect technique for improving growth performance of pigs.

Resumen Antecedentes: Se ha demostrado que los rasgos conductuales de los cerdos están parcialmente bajo control genético, lo que plantea la posibilidad de que el comportamiento pueda ser alterado vía selección genética y resulte en cerdos con mejores rendimientos de crecimiento. Objetivo: Evaluar el comportamiento y crecimiento de los cerdos en etapa de finalización e investigar cerdos seleccionados por un valor alto o bajo de crianza social (SBV) en relación al comportamiento social y al crecimiento grupal. Métodos: Treinta y cinco hembras y 35 verracos, pertenecientes a cinco grupos positivos y cinco grupos negativos de SBV de cerdos en etapa de finalización, llevados hasta los 90, desde 30 kg de peso, alojados en 10 corrales de prueba (3,0 x 3,3 m, 7 cerdos/corral). Los cerdos fueron observados con la ayuda de tecnología de vídeo por nueve horas consecutivas en los días 1, 15 y 30 luego de ser mezclados. Además, los cerdos se pesaron a los 90 kg de peso aproximadamente y se calculó el número de días para alcanzar dicho peso. Resultados: La frecuencia y duración de los comportamientos de los cerdos en la etapa de finalización se presentaron en los grupos de SBV negativos y positivos luego de ser mezclados. El día 1 luego de la mezcla, el comportamiento agonístico fue significativamente mayor (p=0,027) en el grupo -SBV que en el grupo +SBV. Los comportamientos de consumo de alimento y de consumo en compañía fueron significativamente mayores (p<0,003) en el grupo +SBV en los días 1 y 30 luego de la mezcla. Además, el crecimiento para alcanzar 90 kg de peso corporal fue significativamente más rápido (p=0,002) en el grupo +SBV que el grupo -SBV. Conclusiones: Las interacciones sociales, tales como el comportamiento de consumo de alimento en compañía, entre los compañeros de corral, pueden afectar la tasa de crecimiento y consumo de alimento. La selección por SBV podría usarse como técnica indirecta para mejorar el rendimiento de crecimiento en cerdos.

Resumo Antecedentes: Os traços comportamentais dos porcos demonstraram estar parcialmente sob controle genético, o que aumenta a possibilidade de que o comportamento possa ser alterado pela seleção genética e resulte em porcos com melhor comportamento de crescimento. Objetivo: Avaliar o comportamento e o crescimento dos porcos de engorda e investigar os porcos selecionados para alto ou baixo valor de reprodução social (SBV) em relação ao comportamento social e crescimento do grupo. Métodos: Trinta e cinco fêmeas e 35 machos, pertencentes a cinco grupos de SBV positivos e cinco negativos de porcos de engorda, foram engordados até 90 de 30 kg e alojados em 10 currais de teste (3,0 × 3,3 m, 7 porcos/curral). Os porcos foram observados com o auxílio de tecnologia de vídeo durante nove horas consecutivas nos dias 1, 15 e 30 após a mistura. Além disso, os porcos foram sopesados em aproximadamente 90 kg de peso corporal e o número de dias para atingir 90 kg foi então calculado. Resultados: A frequência e a duração dos comportamentos dos porcos de engorda foram apresentadas com grupos de SBV positivo e negativo após a mistura. No dia 1 após a mistura, o comportamento agonístico foi significativamente maior (p=0,027) no grupo -SBV do que no grupo +SBV. Os comportamentos de alimentação e alimentação conjunta foram significativamente maiores (p<0,003) no grupo +SBV nos dias 1 e 30 após a mistura. Além disso, o comportamento de crescimento do grupo para atingir 90 kg de peso corporal foi significativamente mais rápido (p<0,002) no grupo +SBV do que no grupo -SBV. Conclusão: As interações sociais, como o comportamento de alimentação conjunta, entre companheiros de curral podem afetar a taxa de crescimento e a ingestão alimentar. A seleção para SBV pode ser uma técnica indireta para melhorar o comportamento de crescimento dos porcos.

Artificial selection increased body weight but induced increase of runs of homozygosity in Hanwoo cattle.

Artificial selection has been demonstrated to have a rapid and significant effect on the phenotype and genome of an organism. However, most previous studies on artificial selection have focused solely on genomic sequences modified by artificial selection or genomic sequences associated with a specific trait. In this study, we generated whole genome sequencing data of 126 cattle under artificial selection, and 24,973,862 single nucleotide variants to investigate the relationship among artificial selection, genomic sequences and trait. Using runs of homozygosity detected by the variants, we showed increase of inbreeding for decades, and at the same time demonstrated a little influence of recent inbreeding on body weight. Also, we could identify ~0.2 Mb runs of homozygosity segment which may be created by recent artificial selection. This approach may aid in development of genetic markers directly influenced by artificial selection, and provide insight into the process of artificial selection.

Accuracy of genomic breeding value prediction for intramuscular fat using different genomic relationship matrices in Hanwoo (Korean cattle).

OBJECTIVE: Intramuscular fat is one of the meat quality traits that is considered in the selection strategies for Hanwoo (Korean cattle). Different methods are used to estimate the breeding value of selection candidates. In the present work we focused on accuracy of different genotype relationship matrices as described by forni and pedigree based relationship matrix. METHODS: The data set included a total of 778 animals that were genotyped for BovineSNP50 BeadChip. Among these 778 animals, 72 animals were sires for 706 reference animals and were used as a validation dataset. Single trait animal model (best linear unbiased prediction and genomic best linear unbiased prediction) was used to estimate the breeding values from genomic and pedigree information. RESULTS: The diagonal elements for the pedigree based coefficients were slightly higher for the genomic relationship matrices (GRM) based coefficients while off diagonal elements were considerably low for GRM based coefficients. The accuracy of breeding value for the pedigree based relationship matrix (A) was 13% while for GRM (GOF, G05, and Yang) it was 0.37, 0.45, and 0.38, respectively. CONCLUSION: Accuracy of GRM was 1.5 times higher than A in this study. Therefore, genomic information will be more beneficial than pedigree information in the Hanwoo breeding program.

Hanwoo cattle: origin, domestication, breeding strategies and genomic selection.

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.

The effect of age at first calving and calving interval on productive life and lifetime profit in korean holsteins.

This study was performed to estimate the effect of age at first calving and first two calving intervals on productive life and life time profit in Korean Holsteins. Reproduction data of Korean Holsteins born from 1998 to 2004 and lactation data from 276,573 cows with birth and last dry date that calved between 2000 and 2010 were used for the analysis. Lifetime profit increased with the days of life span. Regression of Life Span on Lifetime profit indicated that there was an increase of 3,800 Won (approximately $3.45) of lifetime profit per day increase in life span. This is evidence that care of each cow is necessary to improve net return and important for farms maintaining profitable cows. The estimates of heritability of age at first calving, first two calving intervals, days in milk for lifetime, lifespan, milk income and lifetime profit were 0.111, 0.088, 0.142, 0.140, 0.143, 0.123, and 0.102, respectively. The low heritabilities indicated that the productive life and economical traits include reproductive and productive characteristics. Age at first calving and interval between first and second calving had negative genetic correlation with lifetime profit (-0.080 and -0.265, respectively). Reducing age at first calving and first calving interval had a positive effect on lifetime profit. Lifetime profit increased to approximately 2,600,000 (2,363.6) from 800,000 Won ($727.3) when age at first calving decreased to (22.3 month) from (32.8 month). Results suggested that reproductive traits such as age at first calving and calving interval might affect various economical traits and consequently influenced productive life and profitability of cows. In conclusion, regard of the age at first calving must be taken with the optimum age at first calving for maximum lifetime profit being 22.5 to 23.5 months. Moreover, considering the negative genetic correlation of first calving interval with lifetime profit, it should be reduced against the present trend of increase.