• Asian-Australasian Journal of Animal Sciences
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• v.28 no.9
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• pp.1226-1234
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• 2015

The development of effective genetic evaluations and selection of sires requires accurate estimates of genetic parameters for all economically important traits in the breeding goal. The main objective of this study was to assess the relative performance of the traditional lactation average model (LAM) against the random regression test-day model (RRM) in the estimation of genetic parameters and prediction of breeding values for Holstein Friesian herds in Ethiopia. The data used consisted of 6,500 test-day (TD) records from 800 first-lactation Holstein Friesian cows that calved between 1997 and 2013. Co-variance components were estimated using the average information restricted maximum likelihood method under single trait animal model. The estimate of heritability for first-lactation milk yield was 0.30 from LAM whilst estimates from the RRM model ranged from 0.17 to 0.29 for the different stages of lactation. Genetic correlations between different TDs in first-lactation Holstein Friesian ranged from 0.37 to 0.99. The observed genetic correlation was less than unity between milk yields at different TDs, which indicated that the assumption of LAM may not be optimal for accurate evaluation of the genetic merit of animals. A close look at estimated breeding values from both models showed that RRM had higher standard deviation compared to LAM indicating that the TD model makes efficient utilization of TD information. Correlations of breeding values between models ranged from 0.90 to 0.96 for different group of sires and cows and marked re-rankings were observed in top sires and cows in moving from the traditional LAM to RRM evaluations.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.8
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• pp.1081-1085
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• 2017

Objective: Previously, we reported quantitative trait loci (QTLs) affecting backfat thickness (BFT) traits on pig chromosome 5 (SW1482-SW963) in an F2 intercross population between Landrace and Korean native pigs. The aim of this study was to evaluate glutamate receptor-interacting protein 1 (GRIP1) as a positional candidate gene underlying the QTL affecting BFT traits. Methods: Genotype and phenotype analyses were performed using the 1,105 $F_2$ progeny. A mixed-effect linear model was used to access association between these single nucleotide polymorphism (SNP) markers and the BFT traits in the $F_2$ intercross population. Results: Highly significant associations of two informative SNPs (c.2442 T>C, c.3316 C>G [R1106G]) in GRIP1 with BFT traits were detected. In addition, the two SNPs were used to construct haplotypes that were also highly associated with the BFT traits. Conclusion: The SNPs and haplotypes of the GRIP1 gene determined in this study can contribute to understand the genetic structure of BFT traits in pigs.

• Asian-Australasian Journal of Animal Sciences
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• v.22 no.7
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• pp.923-930
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• 2009

This study was conducted to compare three models: two random regression models with and without considering heterogeneity in the residual variances and a lactation model (LM) for evaluating the genetic ability of Holstein cows in Korea. Two datasets were prepared for this study. To apply the test-day random regression model, 94,390 test-day records were prepared from 15,263 cows. The second data set consisted of 14,704 lactation records covering milk production over 305 days. Raw milk yield and composition data were collected from 1998 to 2002 by the National Agricultural Cooperative Federation' dairy cattle improvement center by way of its milk testing program, which is nationally based. The pedigree information for this analysis was collected by the Korean Animal Improvement Association. The random regression models (RRMs) are single-trait animal models that consider each lactation record as an independent trait. Estimates of covariance were assumed to be different ones. In order to consider heterogeneity of residual variance in the analysis, test-days were classified into 29 classes. By considering heterogeneity of residual variance, variation for lactation performance in the early lactation classes was higher than during the middle classes and variance was lower in the late lactation classes than in the other two classes. This may be due to feeding management system and physiological properties of Holstein cows in Korea. Over classes e6 to e26 (covering 61 to 270 DIM), there was little change in residual variance, suggesting that a model with homogeneity of variance be used restricting the data to these days only. Estimates of heritability for milk yield ranged from 0.154 to 0.455, for which the estimates were variable depending on different lactation periods. Most of the heritabilities for milk yield using the RRM were higher than in the lactation model, and the estimate of genetic variance of milk yield was lower in the late lactation period than in the early or middle periods.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.9
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• pp.1234-1238
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• 2017

Objective: The vertebral number is associated with body length and carcass traits, which represents an economically important trait in farm animals. The variation of vertebral number has been observed in a few mammalian species. However, the variation of vertebral number and quantitative trait loci in sheep breeds have not been well addressed. Methods: In our investigation, the information including gender, age, carcass weight, carcass length and the number of thoracic and lumbar vertebrae from 624 China Kazakh sheep was collected. The effect of vertebral number variation on carcass weight and carcass length was estimated by general linear model. Further, the polymorphic sites of Vertnin (VRTN) gene were identified by sequencing, and the association of the genotype and vertebral number variation was analyzed by the one-way analysis of variance model. Results: The variation of thoracolumbar vertebrae number in Kazakh sheep (18 to 20) was smaller than that in Texel sheep (17 to 21). The individuals with 19 thoracolumbar vertebrae (T13L6) were dominant in Kazakh sheep (79.2%). The association study showed that the numbers of thoracolumbar vertebrae were positively correlated with the carcass length and carcass weight, statistically significant with carcass length. To investigate the association of thoracolumbar vertebrae number with VRTN gene, we genotyped the VRTN gene. A total of 9 polymorphic sites were detected and only a single nucleotide polymorphism (SNP) (rs426367238) was suggested to associate with thoracic vertebral number statistically. Conclusion: The variation of thoracolumbar vertebrae number positively associated with the carcass length and carcass weight, especially with the carcass length. VRTN gene polymorphism of the SNP (rs426367238) with significant effect on thoracic vertebral number could be as a candidate marker to further evaluate its role in influence of thoracolumbar vertebral number.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.11
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• pp.1551-1557
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• 2015

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.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.12
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• pp.1675-1681
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• 2016

The aim of this study was to detect positional candidate genes located within the support interval (SI) regions based on the results of red blood cell, mean corpuscular volume (MCV), and mean corpuscular hemoglobin quantitative trait locus (QTL) in Sus scrofa chromosome 13, and to verify the correlation between specific single-nucleotide polymorphisms (SNPs) located in the exonic region of the positional candidate gene and the three genetic traits. The flanking markers of the three QTL SI regions are SW38 and S0215. Within the QTL SI regions, 44 genes were located, and runt-related transcription factor 1, dual-specificity tyrosine-(Y)-phosphorylation regulated kinase 1A (DYRK1A), and potassium inwardly-rectifying channel, subfamily J, member 15 KCNJ15-which are reported to be related to the hematological traits and clinical features of Down syndrome-were selected as positional candidate genes. The ten SNPs located in the exonic region of the three genes were detected by next generation sequencing. A total of 1,232 pigs of an $F_2$ resource population between Landrace and Korean native pigs were genotyped. To investigate the effects of the three genes on each genotype, a mixed-effect model which is the considering family structure model was used to evaluate the associations between the SNPs and three genetic traits in the $F_2$ intercross population. Among them, the MCV level was highly significant (nominal $p=9.8{\times}10^{-9}$) in association with the DYRK1A-SNP1 (c.2989 G$F_2$ intercross, our approach has limited power to distinguish one particular positional candidate gene from a QTL region.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.10
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• pp.1395-1403
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• 2008

The objective of the present study was to estimate genetic parameters for economic traits in Markhoz goats. Data collected from 1993 to 2006 by the Markhoz goat Performance Testing Station in Sanandaj, Iran, were analyzed. The traits recorded as body weight performance at birth (BW), weaning (WW), six month (6MW), nine month (9MW), yearling (YW) and yearling fleece weight (YFW) were investigated. Least square analyses were used for estimation of environmental effects. Genetic parameters were estimated with single and multi trait analysis using restricted maximum likelihood (REML) procedures, under animal models. By ignoring or including maternal additive genetic effects and maternal permanent environmental effects, five different models were fitted for each trait. The effects of sex, type of birth, age of dam and year of birth on the all body weights were significant (p<0.01), but had no effects on YFW except year of birth. Age of kids had significant influences on WW and 6MW (p<0.01). A log likelihood ratio test was carried out for choosing the most suitable model for each trait. Total heritability estimates for YFW and growth traits varied from 0.16 for YFW and WW to 0.41 for YW. For all traits, maternal heritability was lower than direct heritability, ranging from 0.06 for BW to 0.01 for 6MW and 9MW. The magnitude of $c^2$ was more substantial for BW than the others, and relative importance was reduced from 0.12 for BW to 0.04 for 9MW. The direct additive genetic correlations estimates were positive and varied from 0.21 between BW-YW to 0.96 between WW-6MW. Direct additive genetic correlations between YFW and body weight traits were positive and ranged from 0.14 between BW-YFW to 0.67 between 6MW-YFW. For all traits, the corresponding estimates for phenotypic correlation were positive and lower than genetic correlations. The maternal additive genetic correlations between various traits were varied and ranged from -0.19 between 9MW-YFW to 0.96 between 6MW-9MW. The estimates of the maternal permanent environmental correlations between various traits were positive and ranged from 0.33 between WW-YFW to 0.93 between WW-6MW. Also, the environmental correlations between various traits ranged from 0.01 between BW-YFW and WW-YFW to 0.70 between 9MW-YW. Estimates of genetic parameters for various traits in this study confirm that selection should be applied on WW for genetic improvement in Markhoz goats.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.10
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• pp.1558-1565
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• 2020

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×σ²_g, the third 0.001×σ²_g, and the fourth to 0.01×σ²_g. 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.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.7
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• pp.936-942
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• 2015

The purpose of this study was to characterize genetic architecture of behavior patterns in Sapsaree dogs. The breed population (n=8,256) has been constructed since 1990 over 12 generations and managed at the Sapsaree Breeding Research Institute, Gyeongsan, Korea. Seven behavioral traits were investigated for 882 individuals. The traits were classified as a quantitative or a categorical group, and heritabilities ($h^2$) and variance components were estimated under the Animal model using ASREML 2.0 software program. In general, the $h^2$ estimates of the traits ranged between 0.00 and 0.16. Strong genetic ($r_G$) and phenotypic ($r_P$) correlations were observed between nerve stability, affability and adaptability, i.e. 0.9 to 0.94 and 0.46 to 0.68, respectively. To detect significant single nucleotide polymorphism (SNP) for the behavioral traits, a total of 134 and 60 samples were genotyped using the Illumina 22K CanineSNP20 and 170K CanineHD bead chips, respectively. Two datasets comprising 60 (Sap60) and 183 (Sap183) samples were analyzed, respectively, of which the latter was based on the SNPs that were embedded on both the 22K and 170K chips. To perform genome-wide association analysis, each SNP was considered with the residuals of each phenotype that were adjusted for sex and year of birth as fixed effects. A least squares based single marker regression analysis was followed by a stepwise regression procedure for the significant SNPs (p<0.01), to determine a best set of SNPs for each trait. A total of 41 SNPs were detected with the Sap183 samples for the behavior traits. The significant SNPs need to be verified using other samples, so as to be utilized to improve behavior traits via marker-assisted selection in the Sapsaree population.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.10
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• pp.1542-1549
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• 2018

Objective: Because lactation periods in dairy cows lengthen with increasing total milk production, it is important to predict individual productivities after 305 days in milk (DIM) to determine the optimal lactation period. We therefore examined whether the random regression (RR) coefficient from 306 to 450 DIM (M2) can be predicted from those during the first 305 DIM (M1) by using a RR model. Methods: We analyzed test-day milk records from 85,690 Holstein cows in their first lactations and 131,727 cows in their later (second to fifth) lactations. Data in M1 and M2 were analyzed separately by using different single-trait RR animal models. We then performed a multiple regression analysis of the RR coefficients of M2 on those of M1 during the first and later lactations. Results: The first-order Legendre polynomials were practical covariates of RR for the milk yields of M2. All RR coefficients for the additive genetic (AG) effect and the intercept for the permanent environmental (PE) effect of M2 had moderate to strong correlations with the intercept for the AG effect of M1. The coefficients of determination for multiple regression of the combined intercepts for the AG and PE effects of M2 on the coefficients for the AG effect of M1 were moderate to high. The daily milk yields of M2 predicted by using the RR coefficients for the AG effect of M1 were highly correlated with those obtained by using the coefficients of M2. Conclusion: Milk production after 305 DIM can be predicted by using the RR coefficient estimates of the AG effect during the first 305 DIM.