Yangmo Koo

Dr. Yangmo Koo

Genetics & Breeding Dept., Korea Animal Improvement Association, Seoul, Republic of Korea
orcid

Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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30 July 2023 in Journal of Animal Science and Technology
Verified
Journal Article
Open access
PDF file
HLHyo Sang Lee
Hyo Sang Lee
YKYeong Kuk Kim
Yeong Kuk Kim
DLDoo Ho Lee
Doo Ho Lee
DSDongwon Seo
Dongwon Seo
DLDong Jae Lee
Dong Jae Lee
YKYangmo Koo
Yangmo Koo
Journal of Animal Science and Technology (JAST) is a peer-reviewed, open access journal publishing original research, review articles and notes in all fields of animal science. Topics covered by the journal include: genetics and breeding, physiology, nutrition of monogastric animals, nutrition of ruminants, animal products (milk, meat, eggs and their by-products) and their processing, grasslands and roughages, livestock environment, animal biotechnology, animal behavior and welfare.

29 March 2024 in Animals
Verified
Journal Article
Open access
PDF file
JLJungjae Lee
Jungjae Lee
HMHyosik Mun
Hyosik Mun
YKYangmo Koo
Yangmo Koo
SPSangchul Park
Sangchul Park
JKJunsoo Kim
Junsoo Kim
JPJun Park
Jun Park
The Holstein breed is the mainstay of dairy production in Korea. In this study, we evaluated the genomic prediction accuracy for body conformation traits in Korean Holstein cattle, using a range of π levels (0.75, 0.90, 0.99, and 0.995) in Bayesian methods (BayesB and BayesC). Focusing on 24 traits, we analyzed the impact of different π levels on prediction accuracy. We observed a general increase in accuracy at higher levels for specific traits, with variations depending on the Bayesian method applied. Notably, the highest accuracy was achieved for rear teat angle when using deregressed estimated breeding values including parent average as a response variable. We further demonstrated that incorporating parent average into deregressed estimated breeding values enhances genomic prediction accuracy, showcasing the effectiveness of the model in integrating both offspring and parental genetic information. Additionally, we identified 18 significant window regions through genome-wide association studies, which are crucial for future fine mapping and discovery of causal mutations. These findings provide valuable insights into the efficiency of genomic selection for body conformation traits in Korean Holstein cattle and highlight the potential for advancements in the prediction accuracy using larger datasets and more sophisticated genomic models.

1 January 2023 in Journal of Animal Science
Verified
Journal Article
Open access
PDF file
YKYangmo Koo
Yangmo Koo
HAHatem Alkhoder
Hatem Alkhoder
TCTae Jeong Choi
Tae Jeong Choi
ZLZengting Liu
Zengting Liu
RRReinhard Reents
Reinhard Reents
Hanwoo beef cattle are well known for the flavor and tenderness of their meat. Genetic improvement programs have been extremely successful over the last 40 yr. Recently, genomic selection was initiated in Hanwoo to enhance genetic progress. Routine genomic evaluation based on the single-step breeding value model was implemented in 2020 for all economically important traits. In this study, we tested a single-step marker effect model for the genomic evaluation of four carcass traits, namely, carcass weight (CW), eye muscle area, backfat thickness, and marbling score. In total, 8,023,666 animals with carcass records were jointly evaluated, including 29,965 genotyped animals. To assess the prediction stability of the single-step model, carcass data from the last 4 yr were removed in a forward validation study. The estimated genomic breeding values (GEBV) of the validation animals and other animals were compared between the truncated and full evaluations. A parallel conventional best linear unbiased prediction (BLUP) evaluation with either the full or the truncated dataset was also conducted for comparison with the single-step model. The estimates of the marker effect from the truncated evaluation were highly correlated with those from the full evaluation, ranging from 0.88 to 0.92. The regression coefficients of the estimates of the marker effect for the full and truncated evaluations were close to their expected value of 1, indicating unbiased estimates for all carcass traits. Estimates of the marker effect revealed three chromosomal regions (chromosomes 4, 6, and 14) harboring the major genes for CW in Hanwoo. For validation of cows or steers, the single-step model had a much higher R2 value for the linear regression model than the conventional BLUP model. Based on the regression intercept and slope of the validation, the single-step evaluation was neither inflated nor deflated. For genotyped animals, the estimated GEBV from the full and truncated evaluations were more correlated than the estimated breeding values from the two conventional BLUP evaluations. The single-step model provided a more accurate and stable evaluation over time. Hanwoo beef cattle are well known for the flavor and tenderness of their meat. Genetic improvement programs have been successful over the last 40 yr. Recently, genomic selection was initiated in Hanwoo to enhance genetic progress. A routine genomic evaluation based on the single-step breeding value model was implemented in 2020 for all economically important traits. In this study, we tested a single-step marker effect model for the genomic evaluation of four carcass traits. In total, 8,023,666 cows or steers with carcass records were jointly evaluated, including 29,965 genotyped animals. To assess the prediction accuracy of the single-step model, carcass data from the last 4 yr were removed in a forward validation study. Estimated genomic breeding values (GEBV) of validation animals were compared between truncated and full evaluations. A parallel conventional best linear unbiased prediction (BLUP) evaluation with either the full or truncated dataset was conducted for comparison with the single-step model. Plots of the estimates of the marker effect showed three chromosomal regions harboring the major genes for carcass weight in Hanwoo. The single-step model yielded a more accurate and stable evaluation over time than the conventional BLUP model.

20 December 2023 in Genes
Verified
Journal Article
Open access
PDF file
SYSeungyeon Youk
Seungyeon Youk
MKMingue Kang
Mingue Kang
BAByeongyong Ahn
Byeongyong Ahn
YKYangmo Koo
Yangmo Koo
CPchankyu Park
chankyu Park
Comparative analyses of MHC gene diversity and evolution across different species could offer valuable insights into the evolution of MHC genes. Intra- and inter-species sequence diversity and conservation of 12 classical major histocompatibility complex (MHC) class I genes from cattle, chimpanzees, pigs, and humans was analyzed using 20 representative allelic groups for each gene. The combined analysis of paralogous loci for each species revealed that intra-locus amino-acid sequence variations in the peptide-binding region (PBR) of MHC I genes did not differ significantly between species, ranging from 8.44% for SLA to 10.75% for BoLA class I genes. In contrast, intraspecies differences in the non-PBRs of these paralogous genes were more pronounced, varying from 4.59% for SLA to 16.89% for HLA. Interestingly, the Shannon diversity index and rate of nonsynonymous substitutions for PBR were significantly higher in SLA and BoLA than those in Patr and HLA. Analysis of peptide-binding pockets across all analyzed MHC class I genes of the four species indicated that pockets A and E showed the lowest and highest diversity, respectively. The estimated divergence times suggest that primate and artiodactyl MHC class I genes diverged 60.41 Mya, and BoLA and SLA genes diverged 35.34 Mya. These results offer new insights into the conservation and diversity of MHC class I genes in various mammalian species.

30 August 2016 in Journal of Agriculture & Life Science
Verified
Journal Article
Closed access
JKJun-Sik Kong
Jun-Sik Kong
TCTae-Jeong Choi
Tae-Jeong Choi
JKJeong-Il Kim
Jeong-Il Kim
KLKi-Hwan Lee
Ki-Hwan Lee
JNJae-Kwang Noh
Jae-Kwang Noh
YKYangmo Koo
Yangmo Koo

31 December 2020 in Journal of Agriculture & Life Science
Verified
Journal Article
Closed access
JSJi-Hyun Son
Ji-Hyun Son
YKYangmo Koo
Yangmo Koo
YJYeoung-Ho Jeoung
Yeoung-Ho Jeoung
DCDae-Hyeop Cha
Dae-Hyeop Cha
SKSeong-Jin Kim
Seong-Jin Kim
JLJi-Hong Lee
Ji-Hong Lee