• Journal of Animal Science and Technology
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• v.50 no.5
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• pp.613-620
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• 2008

The genetic parameters used in National Hanwoo Genetic Evaluation(NHGE) were needed to be monitored and updated periodically for accounting any possible changes in population parameters due to selection and environmental changes. Genetic parameters were estimated with single and two-trait models with MTDFREML package using 2,791 carcass records of steers collected from Hanwoo Progeny Test Program(HPTP). Single and two-trait models gave similar parameter estimates for all traits. The heritability estimates from single and two-trait models for carcass weight(CW), dressing percentage(DP), eye muscle area(EMA), back fat thickness(BFT) and marbling score(MS) were 0.30, 0.30, 0.37, 0.44 and 0.44, respectively. The heritability estimates for all the traits except BFT were slightly lower than those used in NHGE but seemed to be within the acceptable ranges. However, further monitoring is needed because the data might not have fully reflected the changes such as carcass grading standards in performance testing program. In order to shift statistical model of NHGE from single trait model to multiple-trait model, the genetic correlations between carcass traits were estimated with pairwise two-trait models. The genetic correlation coefficients between CW and DP, between CW and EMA, between CW and BFT and between CW and MS were 0.44, 0.63, 0.17 and 0.06, respectively. Those between DP and EMA, between DP and BFT and between DP and MS were 0.29, 0.40 and 0.20. Those between EMA and BFT and between EMA and MS were －0.24 and 0.15, respectively. The genetic correlation coefficient between BFT and MS was 0.03.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.12
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• pp.1674-1680
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• 2012

The purpose of this study was to detect significant SNPs for blood components that were related to immunity using high single nucleotide polymorphism (SNP) density panels in a Korean native pig (KNP)${\times}$Yorkshire (YK) cross population. A reciprocal design of KNP${\times}$YK produced 249 $F_2$ individuals that were genotyped for a total of 46,865 available SNPs in the Illumina porcine 60K beadchip. To perform whole genome association analysis (WGA), phenotypes were regressed on each SNP under a simple linear regression model after adjustment for sex and slaughter age. To set up a significance threshold, 0.1% point-wise p value from F distribution was used for each SNP test. Among the significant SNPs for a trait, the best set of SNP markers were determined using a stepwise regression procedure with the rates of inclusion and exclusion of each SNP out of the model at 0.001 level. A total of 54 SNPs were detected; 10, 6, 4, 4, 5, 4, 5, 10, and 6 SNPs for neutrophil, lymphocyte, monocyte, eosinophil, basophil, atypical lymph, immuno-globulin, insulin, and insulin-like growth factor-I, respectively. Each set of significant SNPs per trait explained 24 to 42% of phenotypic variance. Several pleiotropic SNPs were detected on SSCs 4, 13, 14 and 15.

• Asian-Australasian Journal of Animal Sciences
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• v.23 no.4
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• pp.417-424
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• 2010

The purpose of this study was to detect significant SNPs for carcass quality traits using DNA chips of high SNP density in Hanwoo populations. Carcass data of two hundred and eighty nine steers sired by 30 Korean proven sires were collected from two regions; the Hanwoo Improvement Center of National Agricultural Cooperative Federation in Seosan, Chungnam province and the commercial farms in Gyeongbuk province. The steers in Seosan were born between spring and fall of 2006 and those in Gyeonbuk between falls of 2004 and 2005. The former steers were slaughtered at approximately 24 months, while the latter steers were fed six months longer before slaughter. Among the 55,074 SNPs in the Illumina bovine 50K chip, a total of 32,756 available SNPs were selected for whole genome association study. After adjusting for the effects of sire, region and slaughter age, phenotypes were regressed on each SNP using a simple linear regression model. For the significance threshold, 0.1% point-wise p value from F distribution was used for each SNP test. Among the significant SNPs for a trait, the best set of SNP markers were selected using a stepwise regression procedure, and inclusion and exclusion of each SNP out of the model was determined at the p<0.001 level. A total of 118 SNPs were detected; 15, 20, 22, 28, 20, and 13 SNPs for final weight before slaughter, carcass weight, backfat thickness, weight index, longissimus dorsi muscle area, and marbling score, respectively. Among the significant SNPs, the best set of 44 SNPs was determined by stepwise regression procedures with 7, 9, 6, 9, 7, and 6 SNPs for the respective traits. Each set of SNPs per trait explained 20-40% of phenotypic variance. The number of detected SNPs per trait was not great in whole genome association tests, suggesting additional phenotype and genotype data are required to get more power to detect the trait-related SNPs with high accuracy for estimation of the SNP effect. These SNP markers could be applied to commercial Hanwoo populations via marker-assisted selection to verify the SNP effects and to improve genetic potentials in successive generations of the Hanwoo populations.

• Asian-Australasian Journal of Animal Sciences
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• v.10 no.5
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• pp.505-509
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• 1997

Data were from four institutional herds and four field data collection centers involved in a progeny testing program for Nili-Ravi buffaloes in Pakistan. The REML with a single trait animal model, employed on 2,353 lactations, from 901 daughters of 66 sires, gave a heritability estimate of 0.18 for milk yield with repeatability (between lactations) of 0.43. Estimated milk yield was highest at 65 months of age for the first parity and 81 months for later parities. Correction factors for age at calving, standardized to 60 months in the second and later parities, were developed.

• Animal Bioscience
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• v.35 no.7
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• pp.955-963
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• 2022

Objective: The aim of this study was to estimate genetic parameters for 305-day cumulative milk yield and components, growth, and reproductive traits in Guzerá cattle. Methods: The evaluated traits were 305-day first-lactation cumulative yields (kg) of milk (MY305), fat (FY305), protein (PY305), lactose (LY305), and total solids (SY305); age at first calving (AFC) in days; adjusted scrotal perimeter (cm) at the ages of 365 (SP365) and 450 (SP450) days; and adjusted body weight (kg) at the ages of 210 (W210), 365 (W365), and 450 (W450) days. The (co)variance components were estimated using the restricted maximum likelihood method for single-trait, bi-trait and tri-trait analyses. Contemporary groups and additive genetic effects were included in the general mixed model. Maternal genetic and permanent environmental effects were also included for W210. Results: The direct heritability estimates ranged from 0.16 (W210) to 0.32 (MY305). The maternal heritability estimate for W210 was 0.03. Genetic correlation estimates among milk production traits and growth traits ranged from 0.92 to 0.99 and from 0.92 to 0.99, respectively. For milk production and growth traits, the genetic correlations ranged from 0.33 to 0.56. The genetic correlations among AFC and all other traits were negative (-0.43 to -0.27). Scrotal perimeter traits and body weights showed genetic correlations ranging from 0.41 to 0.46, and scrotal perimeter and milk production traits showed genetic correlations ranging from 0.11 to 0.30. The phenotypic correlations were similar in direction (same sign) and lower than the corresponding genetic correlations. Conclusion: These results suggest the viability and potential of joint selection for dairy and beef traits in Guzerá cattle, taking into account reproductive traits.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.7
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• pp.926-935
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• 2015

The efficiency of genome-wide association analysis (GWAS) depends on power of detection for quantitative trait loci (QTL) and precision for QTL mapping. In this study, three different strategies for GWAS were applied to detect QTL for carcass quality traits in the Korean cattle, Hanwoo; a linkage disequilibrium single locus regression method (LDRM), a combined linkage and linkage disequilibrium analysis (LDLA) and a $BayesC{\pi}$ approach. The phenotypes of 486 steers were collected for weaning weight (WWT), yearling weight (YWT), carcass weight (CWT), backfat thickness (BFT), longissimus dorsi muscle area, and marbling score (Marb). Also the genotype data for the steers and their sires were scored with the Illumina bovine 50K single nucleotide polymorphism (SNP) chips. For the two former GWAS methods, threshold values were set at false discovery rate <0.01 on a chromosome-wide level, while a cut-off threshold value was set in the latter model, such that the top five windows, each of which comprised 10 adjacent SNPs, were chosen with significant variation for the phenotype. Four major additive QTL from these three methods had high concordance found in 64.1 to 64.9Mb for Bos taurus autosome (BTA) 7 for WWT, 24.3 to 25.4Mb for BTA14 for CWT, 0.5 to 1.5Mb for BTA6 for BFT and 26.3 to 33.4Mb for BTA29 for BFT. Several candidate genes (i.e. glutamate receptor, ionotropic, ampa 1 [GRIA1], family with sequence similarity 110, member B [FAM110B], and thymocyte selection-associated high mobility group box [TOX]) may be identified close to these QTL. Our result suggests that the use of different linkage disequilibrium mapping approaches can provide more reliable chromosome regions to further pinpoint DNA makers or causative genes in these regions.

• Asian-Australasian Journal of Animal Sciences
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• v.16 no.8
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• pp.1087-1092
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• 2003

As an experimental reference population, crosses between Korean native pig and Landraces were established and information on growth traits was recorded. Animals were genotyped for 24 microsatellite markers covering chromosomes 2, 6, and 7 for partial-genome scan to identify chromosomal regions that have effects on growth traits. quantitative trait loci (QTL) effects were estimated using interval mapping by the regression method under the line cross models with a test for imprinting effects. For test of presence of QTL, chromosome-wide and single position significance thresholds were estimated by permutation test and normal significance threshold for the imprinting test were derived. For tests against the Mendelian model, additive and dominance coefficients were permuted within individuals. Thresholds (5% chromosome-wide) against the no-QTL model for the analyzed traits ranged from 4.57 to 4.99 for the Mendelian model and from 4.14 to 4.67 for the imprinting model, respectively. Partial-genome scan revealed significant evidence for 4 QTL affecting growth traits, and 2 out of the 4 QTLs were imprinted. This study demonstrated that testing for imprinting should become a standard procedure to unravel the genetic control of multi-factorial traits. The models and tests developed in this study allowed the detection and evaluation of imprinted QTL.

• Journal of Animal Science and Technology
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• v.55 no.2
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• pp.81-85
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• 2013

This experiment was conducted to investigate the effects of lactation records in Holstein dairy cattle on the selection rates using a total of 341,436 test records from 113, 812 heads of cattle from first to third lactation. Heritabilities for milk, fat, and protein yields were highest at first lactation (0.28, 0.24, and 0.27, respectively), and decreased to 0.14, 0.15, and 0.13 at third lactation. For the milk yields, phenotypic correlations between first and second lactation, first and third lactation, and second and third lactation were low (0.49, 0.39, and 0.47, respectively), while genetic correlations among consecutive lactations and between second and third were above 0.8 and 0.9. In Model I, of the 1,138 heads the top 1% were selected based on first lactation records, only 32.4% (396 heads) were re-selected when the second lactation records were included and the 67.6% (769 heads) were newly selected animals. While in Model II, 85.1% (1,138 heads) of the animals which were selected as the top 1% on the basis of first and second lactation records were included. A multiple trait evaluation method using multiple lactation records is more desirable than a single trait evaluation method using first lactation records only.

• Journal of Animal Science and Technology
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• v.55 no.1
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• pp.1-6
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• 2013

This study was aimed to solve the problems of current national genetic evaluation systems in Korea and its development to pass the verification processes as required by International Bull Evaluation Service (Interbull). This will enable Korea to participate in international genetic evaluation program. A total of 1,416,589 test-day milk records with calving dates used in this study were collected by National Agricultural Cooperative Federation from 2001 to 2009. Parity was limited up to fifth calving and milk production records were adjusted to cumulative 305 day lactation. The pedigree consisted of 2,279,741 animals where 2,467 bulls had 535,409 parents. A newly developed multiple trait model was used in calculation of breeding values for milk yield, milk fat, and protein yield. Data were edited with SAS (version 9.2) and R programs, and genetic parameters were estimated using VCE 6.0. Results showed a continuous increase in genetic potentials, in general, and no remarkable differences were found between performances by parity. Except fat yield, potentials in milk yield and protein yield were well calculated. We found an increased number of daughters per each top ranked 1,000 bulls in recent years of calf births compared to the cases of previous evaluations. Of the bulls ranked top 100 by our new models (multiple-trait models) we found that increased numbers of bulls were included. Of twenty eight bulls born in 2006, twenty bulls born in 2007 and eight bulls born in 2008 that were listed by new models, only 23, 12, and 2 bulls born in respective years were represented on top 100 by old single-trait models. Re-ranking of the daughters or sires by multiple-trait models suggest that this new multiple trait approach should be used for dairy cattle genetic evaluation and seed-stock selection in the future to increase the accuracy of multiple trait selection. Breeding values for these traits should also be calculated by new method for international genetic evaluation.

• Asian-Australasian Journal of Animal Sciences
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• v.23 no.5
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• pp.543-555
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• 2010

The objectives of this research were the estimation of genetic parameters and trends for weaning-to-first service interval (WSI), and litter traits in a commercial swine population composed of Landrace (L), Large White (T), LT, and TL animals in Chiang Mai, Northern Thailand. The dataset contained 4,399 records of WSI, number of piglets born alive (NBA), litter weight of live piglets at birth (LBW), number of piglets at weaning (NPW), and litter weight at weaning (LWW). Variance and covariance components were estimated with REML using 2-trait analyses. An animal model was used for WSI and a sire-dam model for litter traits. Fixed effects were farrowing year-season, breed group of sow, breed group of boar (litter traits), parity, heterosis (litter traits), sow age, and lactation length (NPW and LWW). Random effects were boar (litter traits), sow, permanent environment, and residual. Heritabilities for direct genetic effects were low for WSI (0.04${\pm}$0.02) and litter traits (0.05${\pm}$0.02 to 0.06${\pm}$0.02). Most heritabilities for maternal litter trait effects were 20% to 50% lower than their direct counterparts. Repeatability for WSI was similar to its heritability. Repeatabilities for litter traits ranged from 0.15${\pm}$0.02 to 0.18${\pm}$F0.02. Direct genetic, permanent environment, and phenotypic correlations between WSI and litter traits were near zero. Direct genetic correlations among litter traits ranged from 0.56${\pm}$0.20 to 0.95${\pm}$0.05, except for near zero estimates between NBA and LWW, and LBW and LWW. Maternal, permanent environment, and phenotypic correlations among litter traits had similar patterns of values to direct genetic correlations. Boar genetic trends were small and significant only for NBA (-0.015${\pm}$0.005 piglets/yr, p<0.004). Sow genetic trends were small, negative, and significant (-0.036${\pm}$0.013 d/yr, p<0.01 for WSI; -0.017${\pm}$0.005 piglets/yr, p<0.007, for NBA; -0.015${\pm}$0.005 kg/yr, p<0.01, for LBW; -0.019${\pm}$0.008 piglets/yr, p<0.02, for NPW; and -0.022${\pm}$0.006 kg/yr, p<0.003, for LWW). Permanent environmental correlations were small, negative, and significant only for WSI (-0.028${\pm}$0.011 d/yr, p<0.02). Environmental trends were positive and significant only for litter traits (p<0.01 to p<0.0003). Selection based on predicted genetic values rather than phenotypes could be advantageous in this population. A single trait analysis could be used for WSI and a multiple trait analysis could be implemented for litter traits.