Joon Ki Hong

Dr. Joon Ki Hong

National Institute of Animal Science, Wanju, Republic of Korea
orcid

Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

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

Representative Publications

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31 May 2020 in Journal of Animal Science and Technology
Verified
Journal Article
Open access
PDF file
JKJeong A Kim
Jeong A Kim
ECEun Seok Cho
Eun Seok Cho
YJYong Dae Jeong
Yong Dae Jeong
YCYohan Choi
Yohan Choi
YKYoung Sin Kim
Young Sin Kim
SSSoo Jin Sa
Soo Jin Sa
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.

1 December 2015 in Meat Science
Verified
Journal Article
Closed access
JHJoon Ki Hong
Joon Ki Hong
DKDuwan Kim
Duwan Kim
KCKyuho Cho
Kyuho Cho
SSSoojin Sa
Soojin Sa
SCSunho Choi
Sunho Choi
HCHoyoung Chung
Hoyoung Chung

25 April 2020 in Animals
Verified
Journal Article
Open access
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JLJungjae Lee
Jungjae Lee
YKYong Min Kim
Yong Min Kim
ECEun Seok Cho
Eun Seok Cho
KCKyuho Cho
Kyuho Cho
SSSoo Jin Sa
Soo Jin Sa
TCTae Jeong Choi
Tae Jeong Choi
Genomic evaluation has been widely applied to several species using commercial single nucleotide polymorphism (SNP) genotyping platforms. This study investigated the informative genomic regions and the efficiency of genomic prediction by using two Bayesian approaches (BayesB and BayesC) under two moderate-density SNP genotyping panels in Korean Duroc pigs. Growth and production records of 1026 individuals were genotyped using two medium-density, SNP genotyping platforms: Illumina60K and GeneSeek80K. These platforms consisted of 61,565 and 68,528 SNP markers, respectively. The deregressed estimated breeding values (DEBVs) derived from estimated breeding values (EBVs) and their reliabilities were taken as response variables. Two Bayesian approaches were implemented to perform the genome-wide association study (GWAS) and genomic prediction. Multiple significant regions for days to 90 kg (DAYS), lean muscle area (LMA), and lean percent (PCL) were detected. The most significant SNP marker, located near the MC4R gene, was detected using GeneSeek80K. Accuracy of genomic predictions was higher using the GeneSeek80K SNP panel for DAYS (Δ2%) and LMA (Δ2–3%) with two response variables, with no gains in accuracy by the Bayesian approaches in four growth and production-related traits. Genomic prediction is best derived from DEBVs including parental information as a response variable between two DEBVs regardless of the genotyping platform and the Bayesian method for genomic prediction accuracy in Korean Duroc pig breeding.

1 June 2018 in Asian-Australasian Journal of Animal Sciences
Verified
Journal Article
Open access
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JHJoon Ki Hong
Joon Ki Hong
YJYong Dae Jeong
Yong Dae Jeong
ECEun Seok Cho
Eun Seok Cho
TCTae Jeong Choi
Tae Jeong Choi
YKYong Min Kim
Yong Min Kim
DLDeukmin Lee
Deukmin Lee
The genetic effects of an individual on the phenotypes of its social partners, such as its pen mates, are known as social genetic effects. This study aims to identify the candidate genes for social (pen-mates') average daily gain (ADG) in pigs by using the genome-wide association approach. Social ADG (sADG) was the average ADG of unrelated pen-mates (strangers). We used the phenotype data (16,802 records) after correcting for batch (week), sex, pen, number of strangers (1 to 7 pigs) in the pen, full-sib rate (0% to 80%) within pen, and age at the end of the test. A total of 1,041 pigs from Landrace breeds were genotyped using the Illumina PorcineSNP60 v2 BeadChip panel, which comprised 61,565 single nucleotide polymorphism (SNP) markers. After quality control, 909 individuals and 39,837 markers remained for sADG in genome-wide association study. We detected five new SNPs, all on chromosome 6, which have not been associated with social ADG or other growth traits to date. One SNP was inside the prostaglandin F2α receptor (PTGFR) gene, another SNP was located 22 kb upstream of gene interferon-induced protein 44 (IFI44), and the last three SNPs were between 161 kb and 191 kb upstream of the EGF latrophilin and seven transmembrane domain-containing protein 1 (ELTD1) gene. PTGFR, IFI44, and ELTD1 were never associated with social interaction and social genetic effects in any of the previous studies. The identification of several genomic regions, and candidate genes associated with social genetic effects reported here, could contribute to a better understanding of the genetic basis of interaction traits for ADG. In conclusion, we suggest that the PTGFR, IFI44, and ELTD1 may be used as a molecular marker for sADG, although their functional effect was not defined yet. Thus, it will be of interest to execute association studies in those genes.

27 April 2020 in Animals
Verified
Journal Article
Open access
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SLSoohyun Lee
Soohyun Lee
DSDongwon Seo
Dongwon Seo
ECEun Seok Cho
Eun Seok Cho
BCBong Hwan Choi
Bong Hwan Choi
YKYong Min Kim
Yong Min Kim
SLSeung-Hwan Lee
Seung-Hwan Lee
The Korean native pig (KNP; Sus scrofa coreanus) is an indigenous porcine breed in South Korea considered as a valuable but dwindling genetic resource. Studies using diverse methodologies and genetic markers suggest that this population originated from the Manchu province of Northeastern China and migrated approximately 3000 years ago into the Korean peninsula. This study aimed to verify those findings by performing diversity and ancestral analyses using the 60K single-nucleotide polymorphism (SNP) BeadChip on 891 pigs of 47 breeds worldwide. We also performed principal component analysis (PCA), ancestry analyses, phylogenetic tree analysis using SNPhylo, and linkage disequilibrium analysis. Furthermore, we generated heatmap, obtained Nei’s genetic distance and FST values, and explored the heterozygosity of commercial and native Korean pigs. The results demonstrated that KNP pigs are more closely related to European breeds than to Chinese breeds. In addition, as previous studies have suggested, our admixture analyses indicated that KNP pigs showed distinguishable genetic structure.

1 June 2021 in Animal Bioscience
Verified
Journal Article
Open access
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JHJoon Ki Hong
Joon Ki Hong
KCKyu Ho Cho
Kyu Ho Cho
YKYoung Sin Kim
Young Sin Kim
HCHakjae Chung
Hakjae Chung
SBSun Young Baek
Sun Young Baek
SSSoo Jin Sa
Soo Jin Sa
Objective: The objective of this study was to estimate the genetic correlation (rpc) of growth performance between purebred (Duroc and Korean native) and synthetic (WooriHeukDon) pigs using a single-step method.Methods: Phenotypes of 15,902 pigs with genotyped data from 1,792 pigs from a nucleus farm were used for this study. We estimated the rpc of several performance traits between WooriHeukDon and purebred pigs: day of target weight (DAY), backfat thickness (BF), feed conversion rate (FCR), and residual feed intake (RFI). The variances and covariances of the studied traits were estimated by an animal multi-trait model that applied the Bayesian inference.Results: rpc within traits was lower than 0.1 for DAY and BF, but high for FCR and RFI; in particular, rpc for RFI between Duroc and WooriHeukDon pigs was nearly 1. Comparison between different traits revealed that RFI in Duroc pigs was associated with different traits in WooriHeukDon pigs. However, the most of rpc between different traits were estimated with low or with high standard deviation.Conclusion: The results indicated that there were substantial differences in rpc of traits in the synthetic WooriHeukDon pigs, which could be caused by these pigs having a more complex origin than other crossbred pigs. RFI was strongly correlated between Duroc and WooriHeukDon pigs, and these breeds might have similar single nucleotide polymorphism effects that control RFI. RFI is more essential for metabolism than other growth traits and these metabolic characteristics in purebred pigs, such as nutrient utilization, could significantly affect those in synthetic pigs. The findings of this study can be used to elucidate the genetic architecture of crossbred pigs and help develop new breeds with target traits.