• The Korean Journal of Applied Statistics
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• v.18 no.3
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• pp.533-541
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• 2005

We identify the correct chromosome and locate the corresponding markers close to the QTL in the linkage analysis of a quantitative trait by using the SSVS method. We consider several markers linked to the QTL, as well as to each oyher and thus the i.b.d. values at these loci generate collinear predictors to be evaluated when using the SSVS approach. The results on considering only closely linked markers to two QTL simultaneously showed clear evidence in favor of the closest marker to the QTL considered over other markers. The results of the analysis of collinear markers with SSVS showeed high concordance to those obtained using traditional multiple regression. We conclude based on this simulation study that the SSVS is quite useful to identify linkage with multiple linked markers simultaneously for a complex quantitative trait.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.6
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• pp.784-788
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• 2008

Studies to detect genes responsible for economic traits in farm animals have been performed using parametric linear models. A non-parametric, model-free approach using the 'expanded multifactor-dimensionality reduction (MDR) method' considering high dimensionalities of interaction effects between multiple single nucleotide polymorphisms (SNPs), was applied to identify interaction effects of SNPs responsible for carcass traits in a Hanwoo beef cattle population. Data were obtained from the Hanwoo Improvement Center, National Agricultural Cooperation Federation, Korea, and comprised 299 steers from 16 paternal half-sib proven sires that were delivered in Namwon or Daegwanryong livestock testing stations between spring of 2002 and fall of 2003. For each steer at approximately 722 days of age, the Longssimus dorsi muscle area (LMA) was measured after slaughter. Three functional SNPs (19_1, 18_4, 28_2) near the microsatellite marker ILSTS035 on BTA6, around which the QTL for meat quality were previously detected, were assessed. Application of the expanded MDR method revealed the best model with an interaction effect between the SNPs 19_1 and 28_2, while only one main effect of SNP19_1 was statistically significant for LMA (p<0.01) under a general linear mixed model. Our results suggest that the expanded MDR method better identifies interaction effects between multiple genes that are related to polygenic traits, and that the method is an alternative to the current model choices to find associations of multiple functional SNPs and/or their interaction effects with economic traits in livestock populations.

• 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.

• Korean Journal of Poultry Science
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• v.27 no.1
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• pp.51-61
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• 2000

This study was conducted to estimate the general production performance, heritabilities, and genetic phenotypic correlations on several economic traits by multiple trait animal model in Korean native chicken. The data were collected from the records of 5,192 pullets produced from 2,029 dams and 250 sires in Daejon Branch, National Livestock Research Institute from April 10. 1994 to February 10. 1997. Body weights of Red Brown (RB), Yellow Brown (YB), Grey Brown (GB) and Black (B) strains were 1,649.9, 1,439.6, 1,455.6 and 1,575.3g at age of 150 days and 1,923.5, 1,689.6, 1,812.4 and 1,924.0g at age of 270 days, respectively. The ranges of coefficient of variation for body weight were 11.52 to 14.02 at age of 150 days and 12.82 to 14.59% at age of 270 days, respectively. The first eggs of RB, YB, GB and B strains were produced at 147.4, 146.5, 151.1 and 152.1 days, respectively and the coefficients of variation were 7.80 to 8.41%. Egg weight at 270 days were 49.7, 47.6, 48.8 and 48.7 g for RB, YB, GB nd B strains, and coefficients of variation were 6.99 to 7.94% . The number of eggs at age of 270days were 75.8, 78.0, 76.7 and 68.8 for RB, YB, GB and B strains, respectively, and coefficient of variations were 23.87 to 29.89%. On heritability estimates in RB, YB, GB and strains body weight were 0.40, 0.10, 0.09 and 0.57 for RB, YB, GB and B strains at age of 150 days, and 0.23, 0.09, 0.38 and 0.24 at age of 270 days were 0.39, 0.47, 0.60 and 0.62, and egg weights at 270 days and age at 1st egg were 0.36, 0.12, 0.38 and 0.26, number of egg production at 270 days were 0.44, 0.36, 0.58 and 0.49, respectively. The genetic correlation coefficients of body weight with the age of first egg, egg weight and number of egg production at 270days were -0.07∼0.67, -0.24∼0.70 and 0.12∼0.41, respectively ; age of first egg with number of egg production at 270days and egg weight were -0.75∼0.91 and 0.34∼0.97 ; and egg weight with number of egg production at 270days were 0.18∼0.68. The phenotypic correlation coefficients of body weight with at age of first egg, egg weight and number of egg production at 270days were -0.01∼0.74, -0.04∼0.72 and 0.25∼0.57 ; age of first egg with number of egg production at 270days and egg weight were 0.26∼0.52 and 0.52∼0.92, respectively ; and egg weight with number of egg production at 270days were 0.34∼0.91.

• Journal of Animal Science and Technology
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• v.65 no.6
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• pp.1194-1204
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• 2023

Meat quality comprises a set of key traits such as pH, meat color, water-holding capacity, tenderness and marbling. These traits are complex because they are affected by multiple genetic and environmental factors. The aim of this study was to investigate the molecular genetic basis underlying nine meat quality-related traits in a Yorkshire pig population using a genome-wide association study (GWAS) and subsequent biological pathway analysis. In total, 45,926 single nucleotide polymorphism (SNP) markers from 543 pigs were selected for the GWAS after quality control. Data were analyzed using a genome-wide efficient mixed model association (GEMMA) method. This linear mixed model-based approach identified two quantitative trait loci (QTLs) for meat color (b^*) on chromosome 2 (SSC2) and one QTL for shear force on chromosome 8 (SSC8). These QTLs acted additively on the two phenotypes and explained 3.92%-4.57% of the phenotypic variance of the traits of interest. The genes encoding HAUS8 on SSC2 and an lncRNA on SSC8 were identified as positional candidate genes for these QTLs. The results of the biological pathway analysis revealed that positional candidate genes for meat color (b^*) were enriched in pathways related to muscle development, muscle growth, intramuscular adipocyte differentiation, and lipid accumulation in muscle, whereas positional candidate genes for shear force were overrepresented in pathways related to cell growth, cell differentiation, and fatty acids synthesis. Further verification of these identified SNPs and genes in other independent populations could provide valuable information for understanding the variations in pork quality-related traits.

• 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.13 no.2
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• pp.149-154
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• 2000

The objectives of this study of Hanwoo (Korean Cattle) were 1) to estimate genetic parameters for direct and maternal genetic effects for birth weight, weaning weight, and six months weight which can be used for genetic evaluations and 2) to compare models with and without grandmatemal effects. Data were obtained from the National Livestock Research Institute in Rural Development Administration (RDA) of Korea and were used to estimate genetic parameters for birth weight (BW, n=10,889), weaning weight at 120-d (WW, n=8,637), and six month weight (W6, n=8,478) in Hanwoo. Total number of animals in pedigrees was 14,949. A single-trait animal model was initially used to obtain starting values for multiple-trait animal models. Estimates of genetic parameters were obtained with MTDFREML using animal models and derivative-free REML (Boldman et al., 1995). Estimates of direct heritability for BW, WW, and W6 analyzed as single-traits were 0.09, 0.03, and 0.02 from Model 3 which included direct and maternal genetic, maternal permanental environmental effects, and effects due to sire ${\times}$ region ${\times}$ year-season interaction, respectively. Ignoring sire ${\times}$ region ${\times}$ year-season interaction effect in the model (Model 2) resulted in larger estimates for direct heritability than for Model 3. Estimates of maternal heritability for BW, WW and W6 were 0.04, 0.05, and 0.07 from Model 3, respectively. The estimates of direct-maternal genetic correlation were positive for BW, WW, and W6 with Model 3 but were negative with Model 2 for WW and W6. Estimates of direct genetic correlations between BW and WW, BW and W6, and WW and W6 were large: 0.52, 0.45, and 0.90, respectively. Genetic correlations were also large and positive for maternal effects for BW with maternal effects for WW and W6 (0.69 and 0.74), and even larger for WW with W6 (0.97). The log likelihood values were the same for models including grandmatemal effects as for models including maternal effects for all traits. These results indicate that grandmatemal effects are not important for these traits for Hanwoo or that the data structure was not adequate for estimating parameters for a grandmatemal model.

• Journal of Animal Science and Technology
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• v.44 no.6
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• pp.685-692
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• 2002

This study was carried out to estimate the genetic correlations for the carcass and growth traits of Hanwoo bulls measured at 12 and 18 months of age on the basis of the data form 1,823 heads of Hanwoo bulls raised at the Livestock Improvement Main Center from 1991 to 1998. Genetic correlations were estimated with multiple trait animal model using MTDFREML. The genetic correlations of the body weight at 12 months with average daily gain during 6${\sim}$12 months and with the body length were 0.76 and 0.79, respectively. The genetic correlations of the body weight at 18 months with average daily gain during 6${\sim}$18 months and with the body length were 0.86 and 0.82, respectively. The genetic correlations of the carcass weight with dressing percent, eye muscle area, backfat thickness and carcass length were 0.39, 0.37, 0.44 and 0.63, respectively. And estimate of 0.36 was obtained for the genetic correlation between backfat thickness and marbling score. The high and positive genetic correlations of 0.71 and 0.96 were estimated for the carcass weight with the body weights at 12 and 18 months. The genetic correlations of the carcass weight with body lengths at 12 and 18 months were 0.63 and 0.75, respectively. Positive genetic correlations were estimated for the dressing percentage with the body weight, average daily gain, body length, thurls width and chest girth. Low genetic correlations were estimated between eye muscle area and the growth traits ranging from -0.07 to 0.32. Dressing percentage was low correlated genetically with the growth traits except for the chest girth at 18 months. The genetic correlation between marbling score and chest girth at 18 months estimated was 0.25.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.5
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• pp.636-642
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• 2018

Objective: The objective of this study was to estimate genetic parameters of milk, fat, and protein yields within and across lactations in Tunisian Holsteins using a random regression test-day (TD) model. Methods: A random regression multiple trait multiple lactation TD model was used to estimate genetic parameters in the Tunisian dairy cattle population. Data were TD yields of milk, fat, and protein from the first three lactations. Random regressions were modeled with third-order Legendre polynomials for the additive genetic, and permanent environment effects. Heritabilities, and genetic correlations were estimated by Bayesian techniques using the Gibbs sampler. Results: All variance components tended to be high in the beginning and the end of lactations. Additive genetic variances for milk, fat, and protein yields were the lowest and were the least variable compared to permanent variances. Heritability values tended to increase with parity. Estimates of heritabilities for 305-d yield-traits were low to moderate, 0.14 to 0.2, 0.12 to 0.17, and 0.13 to 0.18 for milk, fat, and protein yields, respectively. Within-parity, genetic correlations among traits were up to 0.74. Genetic correlations among lactations for the yield traits were relatively high and ranged from $0.78{\pm}0.01$ to $0.82{\pm}0.03$, between the first and second parities, from $0.73{\pm}0.03$ to $0.8{\pm}0.04$ between the first and third parities, and from $0.82{\pm}0.02$ to $0.84{\pm}0.04$ between the second and third parities. Conclusion: These results are comparable to previously reported estimates on the same population, indicating that the adoption of a random regression TD model as the official genetic evaluation for production traits in Tunisia, as developed by most Interbull countries, is possible in the Tunisian Holsteins.

• Asian-Australasian Journal of Animal Sciences
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• v.10 no.6
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• pp.567-570
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• 1997

A multiple trait animal model having milk yield and lactation length was used to estimate genetic parameters using data from four institutional herds and four field recording centers. Response to selection for milk yield alone and in combination with lactation length was estimated by using principles of genetic theory. Lactation records (n = 2,353) adjusted for age at calving to 60 months were utilized. Milk yield was 17% heritable with repeatability of 0.44. Lactation length had a low heritability of 0.06 with repeatability of 0.16. Genetic correlation between the two traits was 0.70. Selection response in milk yield can be improved slightly (103.8 vs 102.8 kg) when information on covariance with lactation length is used together with the information on milk yield.