• Genomics & Informatics
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• v.13 no.4
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• pp.146-151
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• 2015

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.

• Journal of Life Science
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• v.32 no.4
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• pp.279-284
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• 2022

This study was conducted to establish a genetic evaluation system applicable to general farms for improving cows raised on farms. The analysis used Best Linear Unbiased Prediction (BLUP) and Genomic Best Linear Unbiased Prediction (GBLUP) for 619 cows raised in Gyeonggi-do Province and compared and analyzed the accuracy of the estimated breeding value according to four traits (carcass weight, loineye muscle area, back fat thickness, and marbling). In the case of the GBLUP method, the size of the reference population was divided into different four groups and analyzed. The analysis results confirmed that the accuracy of the breeding value of each trait increased as the size of the GBLUP reference population increased. Comparing the accuracy of the breeding values estimated using the BLUP and GBLUP methods, it was confirmed that when the breeding values were estimated using the GBLUP method, they increased by 0.10, 0.09, 0.09, and 0.11 for carcass weight, eye muscle area, back fat thickness, and marbling scores, respectively. Applying the GBLUP method to the evaluation and selection of cows can enable precise and accurate individual selection, while increasing the size of the reference population can make even more accurate individual selection possible, thus increasing selection efficiency.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.59 no.2
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• pp.109-127
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• 2014

Maize is one of the most important food and feed crops in the world including Southeast Asia. In spite of numberous efforts with conventional breeding, the maize productions remain low and the loss of yields by drought and downy mildew are still severe in Asia. Genetic improvement of maize has been performed with molecular marker and genetic engineering. Because maize is one of the most widely studied crop for its own genome and has tremendous diversity and variant, maize is considered as a forefront crop in development and estimation of molecular markers for agricultural useful trait in genetics and breeding. Using QTL (Quantitative Trait Loci) and MAS (Marker Assisted Breeding), molecular breeders are able to accelerate the development of drought tolerance or downy mildew resistance maize genotype. The present paper overviews QTL/MAS approaches towards improvement of maize production against drought and downy mildew. We also discuss here the trends and importance of molecular marker and mapping population in maize breeding.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.45 no.6
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• pp.374-381
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• 2000

This study was conducted to select sesame varieties with high cultural stabilities by comparing several parameters of agronomic traits under the different cultural environments. Of the six areas, Iksan and Jinju areas which showed positively larger environment index values were relatively adequate cultural conditions for sesame. At the comparison of cultural stability of agronomic traits by Eberhart and Russell regression model among sesame breeding lines, Suwon 169 showed more stable regression coefficient values to the number of capsules per plant, number of seeds per capsule and seed weight per plant, and Iksan 12 showed more stable regression coefficient values to culm length and weight per plant. At the comparison of cultural stability of yield per 10a, Suwon 169 and Iksan 12 among sesame breeding lines showed more stable respectively, deviation values of 0.99, 0.98 respectively, and more less regression deviation values of 0.074, 0.167 respectively. Therefore those breeding lines are comparatively higher stabilities to yield determining agronomic traits under the different cultural environments, and it was concluded that those two breeding lines had the possibility to recommend promising breeding lines in the future.

• Asian-Australasian Journal of Animal Sciences
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• v.8 no.1
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• pp.29-35
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• 1995

A selection experiment with Romney Marsh sheep was used to evaluate correlated responses to selection. The selected flock was formed in 1979 by the Romney Group Breeders where selection was for prolificacy, defined as the number of live lambs born per ewe joined per year and a randomly selected control flock was established in 1982. Selection for prolificacy resulted in (i) increased ewe fertility, (ii) increased ewe ovulation rate, (iii) increased ewe litter size, (iv) decreased ewe body weight, (v) decreased lamb birth weight and (vi) decreased lamb 8-week weight. The rates of correlated responses per year respectively for ewe fertility, ewe ovulation rate, ewe litter size, ewe body weight, lamb birth weight and lamb 8-week weight were 0.033(0.002), 0.043(0.016), 0.019(0.005), -0.017(0.066), -0.055(0.025) and -0.150(0.057).

• Asian-Australasian Journal of Animal Sciences
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• v.8 no.1
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• pp.23-27
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• 1995

A selection experiment with Romney Marsh sheep was used to evaluate direct responses to selection. Two flocks were maintained; a) the selection line formed in 1979 by the Romney Group Breeders to select for high prolificacy, defined as the number of live lambs born per ewe joined per year and b) a control line, established in 1982, where flock replacements were chosen at random. Predicted responses per year of birth female group and per year respectively were 0.033 and 0.027 live lambs. The rate of predicted response per year was within the theoretical expected range from 0.01 to 0.03 of the mean. The rates of realized response in prolificacy per year of birth female group and per year respectively were 0.026 and 0.021. These estimates of realized responses represented between 0.01 and 0.02 of the control line mean per year.

• Current Research on Agriculture and Life Sciences
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• v.28
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• pp.17-23
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• 2010

Selection procedures for breeding genic male sterile lines for resistance to both Phytophthora blight caused by Phytophthora capsici and bacterial spot caused by Xanthomonas euvesicatoria were executed to $F_3$ and $F_4$ generations derived from a cross between a Phytophthora resistant genic male sterile (GMS) breeding line and a bacterial spot and Phytophthora resistant breeding line. Resistance to P. capsici was originally introduced from KC294(CM334) and KC263(AC2258), the well-known sources of resistance to P. capsici. Resistance to bacterial spot was introduced from KC47(PI244670). GMS lines with high resistance to P. capsici were obtained and the selected lines are expected to be quantitatively resistant also to bacterial spot.

• Animal Bioscience
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• v.34 no.9
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• pp.1451-1459
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• 2021

Objective: The objectives of the study were to evaluate reproductive performance and selection response through genetic trend of community-based breeding programs (CBBPs) of Bonga sheep. Methods: Reproduction traits data were collected between 2012 and 2018 from Bonga sheep CBBPs. Phenotypic performance was analyzed using the general linear model procedures of Statistical Analysis System. Genetic parameters were estimated by univariate animal model for age at first lambing (AFL) and repeatability models for lambing interval (LI), litter size (LS), and annual reproductive rate (ARR) traits using restricted maximum likelihood method of WOMBAT. For correlations bivariate animal model was used. Best model was chosen based on likelihood ratio test. The genetic trends were estimated by the weighted regression of the average breeding value of the animals on the year of birth/lambing. Results: The overall least squares mean±standard error of AFL, LI, LS, and ARR were 375±12.5, 284±9.9, 1.45±0.010, and 2.31±0.050, respectively. Direct heritability estimates for AFL, LI, LS, and ARR were 0.07±0.190, 0.06±0.120, 0.18±0.070, and 0.25±0.203, respectively. The low heritability for both AFL and LI showed that these traits respond little to selection programs but rather highly depend on animal management options. The annual genetic gains were -0.0281 days, -0.016 days, -0.0002 lambs and 0.0003 lambs for AFL, LI, LS, and ARR, respectively. Conclusion: Implications of the result to future improvement programs were improving management of animals, conservation of prolific flocks and out scaling the CBBP to get better results.

• Journal of Animal Reproduction and Biotechnology
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• v.38 no.1
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• pp.32-37
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• 2023

This study has evaluated the genomic estimated breeding value (GEBV) of the commercial Hanwoo population using the genomic best linear unbiased prediction (GBLUP) method and genomic information. Furthermore, it analyzed the accuracy and realized accuracy of the GEBV. 1,740 heads of the Hanwoo population which were analyzed using a single nucleotide polymorphism (SNP) Chip has selected as the test population. For carcass weight (CWT), eye muscle area (EMA), back fat thickness (BFT), and marbling score (MS), the mean GEBVs estimated using the GBLUP method were 3.819, 0.740, -0.248, and 0.041, respectively and the accuracy of each trait was 0.743, 0.728, 0.737, and 0.765, respectively. The accuracy of the breeding value was affected by heritability. The accuracy was estimated to be low in EMA with low heritability and high in MS with high heritability. Realized accuracy values of 0.522, 0.404, 0.444, and 0.539 for CWT, EMA, BFT, and MS, respectively, showing the same pattern as the accuracy value. The results of this study suggest that the breeding value of each individual can be estimated with higher accuracy by estimating the GEBV using the genomic information of 18,499 reference populations. If this method is used and applied to individual selection in a commercial Hanwoo population, more precise and economical individual selection is possible. In addition, continuous verification of the GBLUP model and establishment of a reference population suitable for commercial Hanwoo populations in Korea will enable a more accurate evaluation of individuals.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.11
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• pp.1540-1549
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• 2017

Objective: Increasing food safety demands in the animal product market have created a need for a system to trace the food distribution process, from the manufacturer to the retailer, and genetic traceability is an effective method to trace the origin of animal products. In this study, we successfully achieved the farm tracing of 6,018 multi-breed pigs, using single nucleotide polymorphism (SNP) markers strictly selected through least absolute shrinkage and selection operator (LASSO) feature selection. Methods: We performed farm tracing of domesticated pig (Sus scrofa) from SNP markers and selected the most relevant features for accurate prediction. Considering multi-breed composition of our data, we performed feature selection using LASSO penalization on 4,002 SNPs that are shared between breeds, which also includes 179 SNPs with small between-breed difference. The 100 highest-scored features were extracted from iterative simulations and then evaluated using machine-leaning based classifiers. Results: We selected 1,341 SNPs from over 45,000 SNPs through iterative LASSO feature selection, to minimize between-breed differences. We subsequently selected 100 highest-scored SNPs from iterative scoring, and observed high statistical measures in classification of breeding farms by cross-validation only using these SNPs. Conclusion: The study represents a successful application of LASSO feature selection on multi-breed pig SNP data to trace the farm information, which provides a valuable method and possibility for further researches on genetic traceability.