• Asian-Australasian Journal of Animal Sciences
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• v.16 no.9
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• pp.1239-1241
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• 2003

Korean cattle breeders have shown interest in genetic improvement of milking ability because poor milking ability and short suckling period of Korean cattle is a hindrance to growth of calves. In this study, daily milk yields by period in Korean cattle were analyzed with an animal model. The milk yields were actually measured at sequential intervals from 1 to 4 months after calving: daily milk yields from delivery to 1 month (DMY1), from 1 to 2 months (DMY2), from 2 to 3 months (DMY3), and from 3 to 4 months (DMY4). Genetic variance estimates gradually increased by the periods while environmental variance estimates gradually decreased. This resulted in a dramatic increase in the heritability by periods: 0.02 for DMY1, 0.11 for DMY2, 0.16 for DMY3, and 0.42 for DMY4. In multi-trait analyses with daily milk yield and body weight of calf, genetic correlation estimates between milk yield and body weight were quite small (-0.08 to 0.02 for birth weight and -0.10 to 0.00 for weaning weight). The trends of the heritability estimated in this study showed that the genetic effects were more influential when the milking period was longer, suggesting genetic evaluations with daily milk yield collected at a longer period.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.1
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• pp.7-12
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• 2004

Real time ultrasonic measurements for 13th rib fat thickness (LBF), longissimus muscle area (LEMA) and marbling score (LMS) of live animal at pre-harvest and subsequent carcass measurements for fat thickness (BF), longissimus muscle area (EMA), marbling score (MS) as well as body weight of live animal, carcass weight (CW), dressing percentage (DP), and total merit index (TMI) on 755 Korean beef steers were analyzed to estimate genetic parameters. Data were analyzed using multivariate animal models with an EM-REML algorithm. Models included fixed effects for year-season of birth, location of birth, test station, age of dam, linear and quadratic covariates for age or body weight at slaughter and random animal and residual effects. The heritability estimates for LEMA, LBF and LMS on RTU scans were 0.17, 0.41 and 0.55 in the age-adjusted model (Model 1) and 0.20, 0.52 and 0.55 in the weight-adjusted model (Model 2), respectively. The Heritability estimates for subsequent traits on carcass measures were 0.20, 0.38 and 0.54 in Model 1 and 0.23, 0.46 and 0.55 in Model 2, respectively. Genetic correlation estimate between LEMA and EMA was 0.81 and 0.79 in Model 1 and Model 2, respectively. Genetic correlation estimate between LBF and BF were high as 0.97 in Model 1 and 0.98 in Model 2. Real time ultrasonic marbling score were highly genetically correlated to carcass MS of 0.89 in Model 1 and 0.92 in Model 2. These results indicate that RTU scans would be alterative to carcass measurement for genetic evaluation of meat quality in a designed progeny-testing program in Korean beef cattle.

• Journal of Forest and Environmental Science
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• v.29 no.3
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• pp.200-210
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• 2013

Biochemical characteristics of 24 Pongamia pinnata genotypes (candidate plus trees) from three agroclimatic zones were estimated and molecular characterization through RAPD markers was done. Various biochemical characters viz. seed oil, total carbohydrates, protein, acid value and Iodine number recorded significant variation among different genotypes. The highest seed oil content was 41.87% while seeds of 14 genotypes recorded above average (32.11%) for the trait. Seed oil and protein content exhibited a significant positive correlation and moderate heritability. Out of the initially selected twenty-five random primers, twenty-two RAPD primers were found to be highly reproducible and produced a total of 183 loci of which 147 (80.32%) loci were polymorphic. Percentage of polymorphism varied from 44% to 100% with an average of 80.62%. High level of genetic variation was found among different genotypes of P. pinnata. Both molecular and oil content (biochemical) markers appeared useful in analyzing the extent of genetic diversity in Pongamia and the result of these analyses will help to better understand the genetic diversity and relationship among populations. Overall, the Pongamia genotypes included in the study showed a correlation with their geographical origins such that genotypes from the same region tend to have higher genetic similarity as compared to those from different regions. However, in UPGMA based Nei's analysis, some genotypes were found not to be grouped based on geographical origins possibly due to the exchange of germplasm over time between farmers across the regions. The results from oil content analyses showed that several genotypes in 'Central and Western Plateau' agroclimatic zone of Jharkhand displayed a good potential for high oil content. The study provides insight about P. pinnata populations in Jharkhand (India) and constitutes a set of useful background information that can be used as a basis for future breeding strategy and improvement of the species.

• Animal Bioscience
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• v.34 no.4
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• pp.516-524
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• 2021

Objective: The genetic evaluation of Santa Inês sheep was performed for resistance to gastrointestinal nematode infection (RGNI) and body size using different relationship matrices to assess the efficiency of including genomic information in the analyses. Methods: There were 1,637 animals in the pedigree and 500, 980, and 980 records of RGNI, thoracic depth (TD), and rump height (RH), respectively. The genomic data consisted of 42,748 SNPs and 388 samples genotyped with the OvineSNP50 BeadChip. The (co)variance components were estimated in single- and multi-trait analyses using the numerator relationship matrix (A) and the hybrid matrix H, which blends A with the genomic relationship matrix (G). The BLUP and single-step genomic BLUP methods were used. The accuracies of estimated breeding values and Spearman rank correlation were also used to assess the feasibility of incorporating genomic information in the analyses. Results: The heritability estimates ranged from 0.11±0.07, for TD (in single-trait analysis using the A matrix), to 0.38±0.08, for RH (using the H matrix in multi-trait analysis). The estimates of genetic correlation ranged from -0.65±0.31 to 0.59±0.19, using A, and from -0.42±0.30 to 0.57±0.16 using H. The gains in accuracy of estimated breeding values ranged from 2.22% to 75.00% with the inclusion of genomic information in the analyses. Conclusion: The inclusion of genomic information will benefit the direct selection for the traits in this study, especially RGNI and TD. More information is necessary to improve the understanding on the genetic relationship between resistance to nematode infection and body size in Santa Inês sheep. The genetic evaluation for the evaluated traits was more efficient when genomic information was included in the analyses.

• Journal of Korean Neurosurgical Society
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• v.63 no.5
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• pp.550-558
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• 2020

To perform a systematic review of the data collected from case-control studies conducted earlier to investigate the correlation between E-selectin S128R polymorphism and ischemic stroke (IS) risk among the Chinese population. The PubMed, Web of Science, Chinese biomedical literature database (CBM), Chinese databases China National Knowledge Infrastructure (CNKI), WanfangData knowledge service platform (Wanfang Data), and information resource integration service platform (VIP) Databases were searched to retrieve case-control studies on the correlation between E-selectin gene S128R polymorphism and IS from the inception of the database till June 2019. The literature was screened, data were extracted, the risk of bias was reviewed, and the studies included were assessed independently by two reviewers. Stata ver. 12.0 software (Stata Corp LLC, College Station, TX, USA) was used to perform the meta-analysis. A total of 2907 cases from eight case-control studies involving 1478 IS patients and 1429 controls were included in this study. The R allele and RS genotype in E-selectin were found to be associated with the risk of IS as per the results of the meta-analysis (R vs. S : odds ratio [OR], 2.75; 95% confidence interval [CI], 2.15-3.51; p<0.00001; RS vs. SS : OR, 2.50; 95% CI, 1.95-3.19; p<0.00001; RR+RS vs. SS : OR, 2.85, 95% CI, 2.21-3.67; p<0.00001). The E-selectin gene S128R polymorphism is likely related to IS based on the results of a meta-analysis in the Chinese population, and the R allele and RS genotype of E-selectin may be IS risk factors.

• Korean Journal of Poultry Science
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• v.9 no.1
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• pp.35-42
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• 1982

Data pertaining to the first generation of a Synthetic White Leghorn flock were used to estimate the heritabilities of and genetic correlation between partial egg production(egg number or percentage) or diversely segmented part records and other traits such as age at sexual maturity, residual and annual egg production, and to compare the expected genetic gain from selection on partial egg number or partial percent production with correlated response in other traits. The estimated heritabilites for six measures of egg Production were ranged from 29 to 35, while heritability for age at sexual maturity (SM) was intermediate (48). Genetic correlations between partial egg number (P) and annual egg number. (A), and partial percent production (P') and annual percent production (A') were 51 and 72, respectively. Genetic correlation between P and SM was estimated largely negative (-.64), while correlation bettween P' and SM was positively intermediate(34). In comparing direct response from selection on partial production (P or P') with another response in correlated trait, selection on P would be 25% more efficient than selection of P' for improving A, while selection of P' would be 94% more efficient than selection P for improving A' For shortening SM selection of P would be 98% more efficient than selection on P'.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.48 no.5
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• pp.413-418
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• 2003

Genetic diversity and soybean sprout-related traits were evaluated in a total of 72 soybean accessions (60 Glycine max, 7 Glycine soja, and 5 Glycine gracilis). 100-seed weight (SW) was greatly varied and ranged from 3.2g to 32.3g in 72 soybean accessions. Positive correlation was observed between GR and hypocotyl length (HL), whereas negative correlation was observed between SW and hypocotyl diameter (HD). Re-evaluation by discarding two soybean genotypes characterized with low GR indicated that much higher correlation of sprout yield (SY) with HD and SW. Based on the principal component analysis (PCA) for sprout-related traits, 57 accessions were classified. Soybean genotypes with better traits for sprout, such as small size of seeds and high SY, were characterized with high PCA 1 and PCA 2 values. The seed size in second is small but showed low GR and SY, whereas the third has large seed, high GR and more than 400% SY. In genetic similarity analysis using 60 SSR marker genotyping, 72 accessions were classified into three major and several minor groups. Nine of twelve accessions that were identified as the representatives of soybean for sprout based on PCA were in a group by the SSR marker analysis, indicating the SSR marker selection of parental genotypes for soybean sprout improvement program.

• Animal Bioscience
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• v.37 no.4
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• pp.622-630
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• 2024

Objective: Pig breeders cannot obtain phenotypic information at the time of selection for sow lifetime productivity (SLP). They would benefit from obtaining genetic information of candidate sows. Genomic data interpreted using deep learning (DL) techniques could contribute to the genetic improvement of SLP to maximize farm profitability because DL models capture nonlinear genetic effects such as dominance and epistasis more efficiently than conventional genomic prediction methods based on linear models. This study aimed to investigate the usefulness of DL for the genomic prediction of two SLP-related traits; lifetime number of litters (LNL) and lifetime pig production (LPP). Methods: Two bivariate DL models, convolutional neural network (CNN) and local convolutional neural network (LCNN), were compared with conventional bivariate linear models (i.e., genomic best linear unbiased prediction, Bayesian ridge regression, Bayes A, and Bayes B). Phenotype and pedigree data were collected from 40,011 sows that had husbandry records. Among these, 3,652 pigs were genotyped using the PorcineSNP60K BeadChip. Results: The best predictive correlation for LNL was obtained with CNN (0.28), followed by LCNN (0.26) and conventional linear models (approximately 0.21). For LPP, the best predictive correlation was also obtained with CNN (0.29), followed by LCNN (0.27) and conventional linear models (approximately 0.25). A similar trend was observed with the mean squared error of prediction for the SLP traits. Conclusion: This study provides an example of a CNN that can outperform against the linear model-based genomic prediction approaches when the nonlinear interaction components are important because LNL and LPP exhibited strong epistatic interaction components. Additionally, our results suggest that applying bivariate DL models could also contribute to the prediction accuracy by utilizing the genetic correlation between LNL and LPP.

• Clinical and Experimental Pediatrics
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• v.62 no.11
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• pp.412-413
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• 2019

• Asian-Australasian Journal of Animal Sciences
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• v.10 no.4
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• pp.422-427
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• 1997

Breeding efficiency was investigated to reveal crucial factors for constructing effective breeding system with subdivided populations under equal genetic level. Simulation study of selection experiment was performed for 20 generations with 20 replications each, comparing average breeding values and inbreeding coefficients between the two breeding systems; single population scheme and two population scheme, each of which had the same genetic parameters. Genetic correlations (-0.5 to 0.5) were assumed to be caused only by pleiotropic effect of a gene. Phenotypes of the two traits generated by polygenic effect with additive 36 loci and residuals distributed normally were selected by two traits selection index procedure. Comparing between the single population scheme and the two population scheme, the single population scheme showed higher genetic gain with lower inbreeding coefficient. This result was confirmed particularly for the situation of high selection intensity, high heritability and high degree of unevenness for economic weight. Genetic correlations in the single population scheme were significantly lower than the two population scheme when initial genetic correlation was negative. When terminal crossbreeding for the two population scheme is taken into account, superiority of the two population scheme was suggested. The terminal crossbreeding was effective under the situation of long term selection, existence of moderate inbreeding depression and use of less extreme economic weight.