Kim, Yong-Min;Cho, Eun-Seok;Cho, Kyu-Ho;Sa, Soo-Jin;Jeong, Yong-Dae;Woo, Jae-Seok;Lee, Il-Joo;Hong, Joon-Ki
Korean Journal of Agricultural Science
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v.43
no.4
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pp.595-602
/
2016
In pigs, individuals in the same pen may show aggressive behavior toward each other, such as tail biting. Such social interactions among pen mates may considerably affect their welfare and performance, both in negative and positive ways. The present study was conducted to investigate social genetic effects on days to 90 kg using data from 12,208 Duroc and Yorkshire pigs that were born between 2008 and 2012. Heritability was estimated using the five following animal models: a basic model with direct heritable effects only (Model 1), a social model with direct and social heritable effects (Model 2), a model accounting for covariance between direct and social heritable effects (Model 3), and two models considering a dilution factor with direct and social heritable effects (Models 4 and 5). The optimal model to represent Duroc pigs was Model 1 which only uses direct heritable effects. Direct heritability (0.21) was higher than total heritability (0.09) and covariance was negative. Model 2 was evaluated as the optimum model for Yorkshire pigs. Yorkshire data showed that total heritability (0.5) was twice as high as direct heritability (0.25) and covariance was positive. Our results suggest that the efficiency of social effects differed among breeding lines. Further research on social effects related to breeds by group size would clarify which is the most efficient selection method that accounts for social genetic effects.
Objective: The growth, carcass and retail cut yield records on 1,428 Hanwoo steers obtained through progeny testing were analyzed in this study, and their heritability and genetic relationships among the traits were estimated using animal models. Methods: Two different models were compared in this study. Each model was fitted for different fixed class effects, date of slaughter for carcass traits and batch of progeny test live measurement traits, and a choice of covariates (carcass weight in Model 1 or backfat thickness in Model 2) for carcass traits. Results: The differences in body composition among individuals were deemed being unaffected by their age at slaughter, except for carcass weight and backfat thickness. Heritability estimates of body size measurements were 0.21 to 0.36. Heritability estimates of retail cut percentage were high (0.56 from Model 1 and 0.47 from Model 2). And the heritability estimates for loin muscle percentage were 0.36 from Model 1 and 0.42 from Model 2, which were high enough to consider direct selection on carcass cutability traits as effective. The genetic correlations between body size measurements and retail cut ratio (RCR) were close to zero. But, some negative genetic correlations were found with chest girths measured at yearling (Model 1) or at 24 months of age or with chest widths. Loin muscle ratio (LMR) was genetically negatively correlated with body weights or body size measurements, in general in Model 1. These relationships were low close to zero but positive in Model 2. Phenotypic correlation between cutability traits (RCR, LMR) and live body size measurements were moderate and negative in Model 1 while those in Model 2 were all close to zero. Conclusion: Therefore, the body weights or linear body measurements at an earlier age may not be the most desirable selection traits for exploitation of correlated responses to improve loin muscle or lean meat yield.
This study was conducted to estimate the genetic parameters for pork belly traits and muscles in Yorkshire pigs. Each pork belly was cut into nine parts perpendicular to the thoracic vertebrae (6th to 14th). Traits of belly muscles including the deep pectoral, latissimus dorsi, cutaneous trunci, rectus abdominis, external and internal abdominal oblique from 382 purebred pigs were recorded and analyzed using SAS Package (9.1) and Derivative-free restricted maximum likelihood methods. Heritability estimates for belly traits ranged from 0.27 to 0.49, while they were 0.12 to 0.66 for belly muscles. Moderate to high heritability estimates were noted in belly weight (0.33), belly length (0.28), and belly width (0.49). In belly muscles, the latissimus dorsi and deep pectoral, which are located only in the 6th to 9th vertebrae sections, were found to have heritability estimates ranging from 0.21 to 0.29 and 0.23 to 0.35, respectively. Strong heritability estimates were observed in the 7th to 13th sections of cutaneous trunci muscle ranging from 0.42 to 0.66. Genetic correlations of latissimus dorsi m. with belly length were positive (0.50), while cutaneous trunci m. with belly weight also revealed a positive relationship that ranged from 0.35 to 0.47. The estimated genetic parameters indicate that belly weight can be improved by genetic selection. Differences in the levels of heritability occurred among various parameters of Yorkshire pork belly, which should be considered when performing selection to improve pork belly quality. Moreover, these results can provide valuable information that can be used as the basis for further investigations to improve pork belly.
The missing heritability has been a major problem in the analysis of best linear unbiased prediction (BLUP). We introduced the traditional genome-wide association study (GWAS) into the BLUP to improve the heritability estimation. We analyzed eight pork quality traits of the Berkshire breeds using GWAS and BLUP. GWAS detects the putative quantitative trait loci regions given traits. The single nucleotide polymorphisms (SNPs) were obtained using GWAS results with p value <0.01. BLUP analyzed with significant SNPs was much more accurate than that with total genotyped SNPs in terms of narrow-sense heritability. It implies that genomic estimated breeding values (GEBVs) of pork quality traits can be calculated by BLUP via GWAS. The GWAS model was the linear regression using PLINK and BLUP model was the G-BLUP and SNP-GBLUP. The SNP-GBLUP uses SNP-SNP relationship matrix. The BLUP analysis using preprocessing of GWAS can be one of the possible alternatives of solving the missing heritability problem and it can provide alternative BLUP method which can find more accurate GEBVs.
Journal of the Korean Data and Information Science Society
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v.27
no.3
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pp.741-747
/
2016
The aim of study was to estimate genetic parameter of carcass traits in commercial Hanwoo steer using national animal model for selection of superior bull. Analyzed data (n=5,843) on carcass traits was collected from 107,020 Hanwoo steer. The animal model was used to estimate heritability and genetic correlations. The estimated heritability of carcass traits were 0.19, 0.17, 0.20 and 0.23 for carcass weight, eye muscle area, backfat thickness and marbling score, respectively. The estimated heritability for carcass traits in commercial Hanwoo are low than estimated heritability of national progeny test population for selection of superior bull because breeding environment, genetic performance of cow and feeding day was different. Therefore, we suggests that animal model can include practical genetic variable based on national animal model to improve genetic performance in commercial Hanwoo.
Nwogwugwu, Chiemela Peter;Kim, Yeongkuk;Choi, Hyunji;Lee, Jun Heon;Lee, Seung-Hwan
Asian-Australasian Journal of Animal Sciences
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v.33
no.12
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pp.1912-1921
/
2020
Objective: This study assessed genomic prediction accuracies based on different selection methods, evaluation procedures, training population (TP) sizes, heritability (h2) levels, marker densities and pedigree error (PE) rates in a simulated Korean beef cattle population. Methods: A simulation was performed using two different selection methods, phenotypic and estimated breeding value (EBV), with an h2 of 0.1, 0.3, or 0.5 and marker densities of 10, 50, or 777K. A total of 275 males and 2,475 females were randomly selected from the last generation to simulate ten recent generations. The simulation of the PE dataset was modified using only the EBV method of selection with a marker density of 50K and a heritability of 0.3. The proportions of errors substituted were 10%, 20%, 30%, and 40%, respectively. Genetic evaluations were performed using genomic best linear unbiased prediction (GBLUP) and single-step GBLUP (ssGBLUP) with different weighted values. The accuracies of the predictions were determined. Results: Compared with phenotypic selection, the results revealed that the prediction accuracies obtained using GBLUP and ssGBLUP increased across heritability levels and TP sizes during EBV selection. However, an increase in the marker density did not yield higher accuracy in either method except when the h2 was 0.3 under the EBV selection method. Based on EBV selection with a heritability of 0.1 and a marker density of 10K, GBLUP and ssGBLUP_0.95 prediction accuracy was higher than that obtained by phenotypic selection. The prediction accuracies from ssGBLUP_0.95 outperformed those from the GBLUP method across all scenarios. When errors were introduced into the pedigree dataset, the prediction accuracies were only minimally influenced across all scenarios. Conclusion: Our study suggests that the use of ssGBLUP_0.95, EBV selection, and low marker density could help improve genetic gains in beef cattle.
Thiruvenkadan, A.K.;Karunanithi, K.;Muralidharan, J.;Babu, R. Narendra
Asian-Australasian Journal of Animal Sciences
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v.24
no.8
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pp.1041-1047
/
2011
Data on 2,365 Mecheri sheep (1,201 males and 1,164 females), maintained at the Mecheri Sheep Research Station, Pottaneri, India, and recorded between 1979 and 2006, were analysed to study the growth related traits and their genetic control. The body weights at different ages (i.e. at birth, weaning (3 months), 6, 9 and 12 months) were recorded and collected from the birth and growth registers maintained in the farm. The average weights of Mecheri sheep at birth, and at 12 months of age were $2.24{\pm}0.01$ and $16.81{\pm}0.15$ kg respectively. The pre- and post-weaning average daily weight gains were $63.84{\pm}0.75$ and $29.52{\pm}0.43$ g respectively. Study revealed a significant difference with the period of lambing on body weight, weight gain and efficiency in weight gain at different stages of growth. Males were heavier and had a higher weight gain than females at almost all stages of growth and the differences tended to increase with age. The direct heritability estimates increased from birth to six months of age and then decreased. The direct heritabilities of all body weights at different stages of growth were low to moderate in magnitude and the values at birth, weaning, six, nine and 12 months of age were 0.08, 0.17, 0.21, 0.13 and 0.10 respectively. For the estimation of heritability at birth and three months body weights, the direct additive genetic and maternal additive genetic effects have to be taken into account and for the estimation of six months weight, the direct additive genetic and maternal permanent environmental effects have to be included in the model. The estimates of heritability, phenotypic and genetic correlations among the different body weights indicated that the selection for improving the body weights at different traits should be done on the basis of three or six months weight because of higher heritability estimates and having higher genetic correlations with other traits.
Previous studies in Holstein have shown 35% to 51.8% heritability in milk production traits, such as milk yield, fat, and protein, using pedigree data. Other studies in complex human traits could be captured by common single-nucleotide polymorphisms (SNPs), and their genetic variations, attributed to chromosomes, are in proportion to their length. Using genome-wide estimation and partitioning approaches, we analyzed three quantitative Holstein traits relevant to milk production in Korean Holstein data harvested from 462 individuals genotyped for 54,609 SNPs. For all three traits (milk yield, fat, and protein), we estimated a nominally significant (p = 0.1) proportion of variance explained by all SNPs on the Illumina BovineSNP50 Beadchip ($h^2_G$). These common SNPs explained approximately most of the narrow-sense heritability. Longer genomic regions tended to provide more phenotypic variation information, with a correlation of 0.46~0.53 between the estimate of variance explained by individual chromosomes and their physical length. These results suggested that polygenicity was ubiquitous for Holstein milk production traits. These results will expand our knowledge on recent animal breeding, such as genomic selection in Holstein.
In Sasang constitutional medicine, both disease susceptibility and drug response are considered to be related to the characteristics of an individual's physiology and psychology: a theory which is central to traditional Korean medicine. Based on such observable characteristics, Sasang constitutional medicine classifies people into four constitutional types. Genetic studies of Sasang constitution would help reveal the inheritance patterns and models of the typological traits and, moreover, help with traditional medical diagnosis and treatment. To investigate the heritable aspect of Sasang constitution, we collected various pedigrees from South Korea. The study population has 101 pedigrees composed of 593 individuals. The determination of the Sasang constitution type of each individual was performed by doctors who diagnose the Sasang constitutional type of individuals as part of their professional practice. We calculated estimates of familial correlation and heritability. Parent-Offspring pairs showed the strongest familial correlation of Sasang constitutional type, with the correlation values of 0.21 and 0.28, followed by sibling pairs with the value ranging between 0.14 and 0.25. From the heritability analysis conducted with the Variance-Component method, the heritability of TE (Tae-Eum) type, SY (So-Yang) type, and SE (So-Eum) type were 55%, 41%, and 47%, respectively. This pattern of heritability was consistent with different set of analyses, which suggest the robustness of our result. Our result clearly shows that the Sasang constitution type is heritable, and further genetic analysis based on our result will shed light on the biological mechanism of Sasang constitution.
Rodrigues, Francelino Neiva;Sarmento, Jose Lindenberg Rocha;Leal, Tania Maria;de Araujo, Adriana Mello;Filho, Luiz Antonio Silva Figueiredo
Animal Bioscience
/
v.34
no.2
/
pp.185-191
/
2021
Objective: The objective of this study was to estimate the genetic parameters for worm resistance (WR) and associated characteristics, using the linear-threshold animal model via Bayesian inference in single- and multiple-trait analyses. Methods: Data were collected from a herd of Santa Inês breed sheep. All information was collected with animals submitted to natural contamination conditions. All data (number of eggs per gram of feces [FEC], Famacha score [FS], body condition score [BCS], and hematocrit [HCT]) were collected on the same day. The animals were weighed individually on the day after collection (after 12-h fasting). The WR trait was defined by the multivariate cluster analysis, using the FEC, HCT, BCS, and FS of material collected from naturally infected sheep of the Santa Inês breed. The variance components and genetic parameters for the WR, FEC, HCT, BCS, and FS traits were estimated using the Bayesian inference under the linear and threshold animal model. Results: A low magnitude was obtained for repeatability of worm-related traits. The mean values estimated for heritability were of low-to-high (0.05 to 0.88) magnitude. The FEC, HCT, BCS, FS, and body weight traits showed higher heritability (although low magnitude) in the multiple-trait model due to increased information about traits. All WR characters showed a significant genetic correlation, and heritability estimates ranged from low (0.44; single-trait model) to high (0.88; multiple-trait model). Conclusion: Therefore, we suggest that FS be included as a criterion of ovine genetic selection for endoparasite resistance using the trait defined by multivariate cluster analysis, as it will provide greater genetic gains when compared to any single trait. In addition, its measurement is easy and inexpensive, exhibiting greater heritability and repeatability and a high genetic correlation with the trait of resistance to worms.
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