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Dive into the research topics where Chae-Kyoung Yoo is active.

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Featured researches published by Chae-Kyoung Yoo.


Animal Genetics | 2011

QTL analysis of white blood cell, platelet and red blood cell-related traits in an F2 intercross between Landrace and Korean native pigs

In-Cheol Cho; Hee-Bok Park; Chae-Kyoung Yoo; G. J. Lee; Hyun-Tae Lim; Jonguk Lee; Eun-Ji Jung; Moon-Suck Ko; Jun-Heon Lee; Jin-Tae Jeon

Haematological traits play important roles in disease resistance and defence functions. The objective of this study was to locate quantitative trait loci (QTL) and the associated positional candidate genes influencing haematological traits in an F(2) intercross between Landrace and Korean native pigs. Eight blood-related traits (six erythrocyte traits, one leucocyte trait and one platelet trait) were measured in 816 F(2) progeny. All experimental animals were genotyped with 173 informative microsatellite markers located throughout the pig genome. We report that nine chromosomes harboured QTL for the baseline blood parameters: genomic regions on SSC 1, 4, 5, 6, 8, 9, 11, 13 and 17. Eight of twenty identified QTL reached genome-wide significance. In addition, we evaluated the KIT locus, an obvious candidate gene locus affecting variation in blood-related traits. Using dense single nucleotide polymorphism marker data on SSC 8 and the marker-assisted association test, the strong association of the KIT locus with blood phenotypes was confirmed. In conclusion, our study identified both previously reported and novel QTL affecting baseline haematological parameters in pigs. Additionally, the positional candidate genes identified here could play an important role in elucidating the genetic architecture of haematological phenotype variation in swine and in humans.


Molecules and Cells | 2009

The robust phylogeny of Korean wild boar (Sus scrofa coreanus) using partial D-loop sequence of mtDNA.

In-Cheol Cho; Sang-Hyun Han; Meiying Fang; Sung-Soo Lee; Moon-Suck Ko; Hang Lee; Hyun-Tae Lim; Chae-Kyoung Yoo; Jun-Heon Lee; Jin-Tae Jeon

In order to elucidate the precise phylogenetic relationships of Korean wild boar (Sus scrofa coreanus), a partial mtDNA D-loop region (1,274 bp, NC_000845 nucleotide positions 16576-1236) was sequenced among 56 Korean wild boars. In total, 25 haplotypes were identified and classified into four distinct subgroups (K1 to K4) based on Bayesian phylogenetic analysis using Markov chain Monte Carlo methods. An extended analysis, adding 139 wild boars sampled worldwide, confirmed that Korean wild boars clearly belong to the Asian wild boar cluster. Unexpectedly, the Myanmarese/Thai wild boar population was detected on the same branch as Korean wild boar subgroups K3 and K4. A parsimonious median-joining network analysis including all Asian wild boar haplotypes again revealed four maternal lineages of Korean wild boars, which corresponded to the four Korean wild boar subgroups identified previously. In an additional analysis, we supplemented the Asian wild boar network with 34 Korean and Chinese domestic pig haplotypes. We found only one haplotype, C31, that was shared by Chinese wild, Chinese domestic and Korean domestic pigs. In contrast to our expectation that Korean wild boars contributed to the gene pool of Korean native pigs, these data clearly suggest that Korean native pigs would be introduced from China after domestication from Chinese wild boars.


Journal of Animal Science and Technology | 2009

Establishment of a Microsatellite Marker Set for Individual, Pork Brand and Product Origin Identification in Pigs

Hyun-Tae Lim; B.Y. Seo; Eun-Ji Jung; Chae-Kyoung Yoo; Tao Zhong; In-Cheol Cho; Duhak Yoon; Jung-Gyu Lee; Jin-Tae Jeon

Hyun-Tae Lim*, Bo-Yeong Seo*, Eun-Ji Jung*, Chae-Kyoung Yoo*, Tao Zhong*, In-Cheol Cho**, Duhak Yoon**, Jung-Gyu Lee* and Jin-Tae Jeon*Division of Applied Life Science (BK21 program) Graduate School of Gyeongsang National University*,National Institute of Animal Science, R. D. A.**ABSTRACTSeventeen porcine microsatellite(MS) markers recommended by the EID+DNA Tracing EU project, ISAG and Roslin institute were selected for the use in porcine individual and brand identification. The MSA, CERVUS, FSTAT, GENEPOP and API-CALC programs were applied for calculating heterozygosity indices. By considering the hetreozygosity value and PCR product size of each marker, we established a MS marker set composed of 13 MS markers(SW936, SW951, SW787, S00090, S0026, SW122, SW857, S0005, SW72, S0155, S0225, SW24 and SW632) and two sexing markers. The expected probability of identity among genotypes of random individuals(PI), probability of identity among genotypes from random half sibs(PI


Animal Genetics | 2014

QTL analysis of body weight and carcass body length traits in an F2 intercross between Landrace and Korean native pigs

Chae-Kyoung Yoo; Hee-Bok Park; Jonguk Lee; Eun-Ji Jung; Byeong-Woo Kim; H. I. Kim; S. J. Ahn; Moon-Suck Ko; In-Cheol Cho; Hyun-Tae Lim

Growth traits, such as body weight and carcass body length, directly affect productivity and economic efficiency in the livestock industry. We performed a genome-wide linkage analysis to detect the quantitative trait loci (QTL) that affect body weight, growth curve parameters and carcass body length in an F2 intercross between Landrace and Korean native pigs. Eight phenotypes related to growth were measured in approximately 1000 F2 progeny. All experimental animals were subjected to genotypic analysis using 173 microsatellite markers located throughout the pig genome. The least squares regression approach was used to conduct the QTL analysis. For body weight traits, we mapped 16 genome-wide significant QTL on SSC1, 3, 5, 6, 8, 9 and 12 as well as 22 suggestive QTL on SSC2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 16 and 17. On SSC12, we identified a major QTL affecting body weight at 140 days of age that accounted for 4.3% of the phenotypic variance, which was the highest test statistic (F-ratio = 45.6 under the additive model, nominal P = 2.4 × 10(-11) ) observed in this study. We also showed that there were significant QTL on SSC2, 5, 7, 8, 9 and 12 affecting carcass body length and growth curve parameters. Interestingly, the QTL on SSC2, 3, 5, 6, 8, 9, 10, 12 and 17 influencing the growth-related traits showed an obvious trend for co-localization. In conclusion, the identified QTL may play an important role in investigating the genetic structure underlying the phenotypic variation of growth in pigs.


Genes & Genomics | 2011

Whole-genome association study for the roan coat color in an intercrossed pig population between Landrace and Korean native pig

In-Cheol Cho; Tao Zhong; Bo-Young Seo; Eun-Ji Jung; Chae-Kyoung Yoo; Jae-Hwan Kim; Jae-Bong Lee; Hyun-Tae Lim; Byoung-Woo Kim; Jun-Heon Lee; Moon-Suck Ko; Jin-Tae Jeon

The roan coat color is characterized by white hairs intermingled with colored hairs. Candidate genes based on comparative phenotypes in horses and cattle involve the KIT and KIT ligand (MGF) genes. Here, we report the result of the whole genome scanning to detect genomic regions responsible for the roan coat color, using a three-generation pedigree of 62 pigs in an intercross between Landrace and Korean native pig. These pigs were genotyped using the PorcineSNP 60 BeadChip (Illumina, USA). The whole genome scan indicated that three genomic regions, 35∼36 Mb, 38∼39 Mb, and 58∼59 Mb on SSC8, were commonly and highly associated/linked with the roan phenotype in the case/control, sib-pair, and linkage test, respectively. The porcine KIT was selected as a candidate gene, because it is located in one of the three significant regions and its function is related to coat color formation. SNPs and Indels within coding sequence (CDS), promoter, and 3′-UTR of KIT were surveyed. Twenty-two SNPs in the CDS reported previously, as well as nine variations in promoter (2 SNPs) and 3′-UTR (5 SNPs and 2 Indels) were detected. Although no causative mutations were identified, these results will help to elucidate the genetic mechanisms involved in the expression of the roan phenotype and will aid in identifying key mutations responsible for the roan phenotype in further studies.


Physiological Genomics | 2012

QTL analysis of clinical-chemical traits in an F2 intercross between Landrace and Korean native pigs

Chae-Kyoung Yoo; In-Cheol Cho; Jae-Bong Lee; Eun-Ji Jung; Hyun-Tae Lim; Sang-Hyun Han; Sung-Soo Lee; Moon-Suck Ko; Tae-Young Kang; Joon-Ho Hwang; Yong Sang Park; Hee-Bok Park

Clinical-chemical traits are essential when examining the health status of individuals. The aim of this study was to identify quantitative trait loci (QTL) and the associated positional candidate genes affecting clinical-chemical traits in a reciprocal F(2) intercross between Landrace and Korean native pigs. Following an overnight fast, 25 serum phenotypes related to clinical-chemical traits (e.g., hepatic function parameters, renal function parameters, electrolyte, lipids) were measured in >970 F(2) progeny. All experimental samples were subjected to genotyping analysis using 165 microsatellite markers located across the genome. We identified eleven genome-wide significant QTL in six chromosomal regions (SSC 2, 7, 8, 13, 14, and 15) and 59 suggestive QTL in 17 chromosomal regions (SSC 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 17, and 18). We also observed significant effects of reciprocal crosses on some of the traits, which would seem to result from maternal effect, QTL on sex chromosomes, imprinted genes, or genetic difference in mitochondrial DNA. The role of genomic imprinting in clinical-chemical traits also was investigated. Genome-wide analysis revealed a significant evidence for an imprinted QTL in SSC4 affecting serum amylase levels. Additionally, a series of bivariate linkage analysis provided strong evidence that QTL in SSC 2, 13, 15, and 18 have a pleiotropic effect on clinical-chemical traits. In conclusion, our study detected both novel and previously reported QTL influencing clinical-chemical traits in pigs. The identified QTL together with the positional candidate genes identified here could play an important role in elucidating the genetic structure of clinical-chemical phenotype variation in humans and swine.


Animal Genetics | 2014

Genome‐wide association analysis identifies quantitative trait loci for growth in a Landrace purebred population

Eun-Ji Jung; Hee-Bok Park; Jonguk Lee; Chae-Kyoung Yoo; Byeong-Woo Kim; H. I. Kim; B. W. Kim; Hyun-Tae Lim

Growth-related traits are complex and economically important in the livestock industry. The aim of this study was to identify quantitative trait loci (QTL) and the associated positional candidate genes affecting growth in pigs. A genome-wide association study (GWAS) was performed using the porcine single-nucleotide polymorphism (SNP) 60K bead chip. A mixed-effects model and linear regression approach were used for the GWAS. The data used in the study included 490 purebred Landrace pigs. All experimental animals were genotyped with 39 438 SNPs located throughout the pig autosomes. We identified a strong association between a SNP marker on chromosome 16 and body weight at 71 days of age (ALGA0092396, P = 5.35 × 10(-9) , Bonferroni adjusted P < 0.05). The SNP marker was located near the genomic region containing IRX4, which encodes iroquois homeobox 4. This SNP marker could be useful in the selective breeding program after validating its effect on other populations.


Genetics Selection Evolution | 2015

Genome-wide QTL analysis of meat quality-related traits in a large F2 intercross between Landrace and Korean native pigs

In-Cheol Cho; Chae-Kyoung Yoo; Jae-Bong Lee; Eun-Ji Jung; Sang-Hyun Han; Sung-Soo Lee; Moon-Suck Ko; Hyun-Tae Lim; Hee-Bok Park

BackgroundWe conducted a genome-wide linkage analysis to identify quantitative trait loci (QTL) that influence meat quality-related traits in a large F2 intercross between Landrace and Korean native pigs. Thirteen meat quality-related traits of the m. longissimus lumborum et thoracis were measured in more than 830 F2 progeny. All these animals were genotyped with 173 microsatellite markers located throughout the pig genome, and the GridQTL program based on the least squares regression model was used to perform the QTL analysis.ResultsWe identified 23 genome-wide significant QTL in eight chromosome regions (SSC1, 2, 6, 7, 9, 12, 13, and 16) (SSC for Sus Scrofa) and detected 51 suggestive QTL in the 17 chromosome regions. QTL that affect 10 meat quality traits were detected on SSC12 and were highly significant at the genome-wide level. In particular, the QTL with the largest effect affected crude fat percentage and explained 22.5% of the phenotypic variance (F-ratio = 278.0 under the additive model, nominal P = 5.5 × 10−55). Interestingly, the QTL on SSC12 that influenced meat quality traits showed an obvious trend for co-localization.ConclusionsOur results confirm several previously reported QTL. In addition, we identified novel QTL for meat quality traits, which together with the associated positional candidate genes improve the knowledge on the genetic structure that underlies genetic variation for meat quality traits in pigs.


Animal Genetics | 2014

Genome‐wide association study identifies quantitative trait loci affecting hematological traits in an F2 intercross between Landrace and Korean native pigs

Eun-Ji Jung; Hee-Bok Park; Jonguk Lee; Chae-Kyoung Yoo; Byeong-Woo Kim; H. I. Kim; In-Sook Cho; Hyun-Tae Lim

Changes affecting the status of health and robustness can bring about physiological alterations including hematological parameters in swine. To identify quantitative trait loci (QTL) associated with eight hematological traits (one leukocyte trait, six erythrocyte traits and one platelet trait), we conducted a genome-wide association study using the PorcineSNP60K BeadChip in a resource population derived from an intercross between Landrace and Korean native pigs. A total of 36 740 SNPs from 816 F2 progeny were analyzed for each blood-related trait after filtering for quality control. Data were analyzed by the genome-wide rapid association using mixed model and regression (GRAMMAR) approach. A total of 257 significant SNPs (P < 1.36 × 10(-6) ) on SSC3, 6, 8, 13 and 17 were identified for blood-related traits in this study. Interestingly, the genomic region between 17.9 and 130 Mb on SSC8 was found to be significantly associated with red blood cell, mean corpuscular volume and mean corpuscular hemoglobin. Our results include the identification of five significant SNPs within five candidate genes (KIT, IL15, TXK, ARAP2 and ERG) for hematopoiesis. Further validation of these identified SNPs could give valuable information for understanding the variation of hematological traits in pigs.


Journal of Life Science | 2013

Association between Numerical Variations of Vertebrae and Carcass Traits in Jeju Native Black Pigs, Landrace Pigs, and Crossbred F 2 Population

In-Cheol Cho; Sang-Keum Kim; Yoo-Kyung Kim; Sung-Nyun Yang; Yong-Sang Park; Won-Mo Cho; Sang-Rae Cho; Nam-Young Kim; Hyun-Seok Chae; Pil-Nam Seong; Beom-Young Park; Jun-Heon Lee; Jae-Bong Lee; Chae-Kyoung Yoo; Sang-Hyun Han; Moon-Suck Ko

The number of thoracic and lumbar vertebrae is known to be an unfixed trait among mammals. This study focused on the relationship between numerical variations of cervical (CER), thoracic (THO), and lumbar (LUM) vertebrae and the total number of vertebrae (TNV) and carcass traits in Jejunative black pigs (JBPs), Landrace pigs, and their intercrossed population. There were no numerical variations in CER vertebrae. On the other hand, the numbers of THO and LUM vertebrae and the TNV varied in all three populations. Of the traits investigated in the three populations, only the meansSE of the LUM vertebrae did not show statistical significance (p>0.05). The carcass weights (CW), meat color (MC), marbling score (MS), backfat thickness (BFT), carcass length (CLE), THO vertebrae, and TNV all showed statistical significance (p population had 14-17 THO vertebrae, 5-7 LUM vertebrae, and 27-30 TNV. In the F2 population, increased numbers of THO vertebrae and TNV were associated with a significant increase in the CW, CLE, and BFT (pThe number of thoracic and lumbar vertebrae is known to be an unfixed trait among mammals. This study focused on the relationship between numerical variations of cervical (CER), thoracic (THO), and lumbar (LUM) vertebrae and the total number of vertebrae (TNV) and carcass traits in Jejunative black pigs (JBPs), Landrace pigs, and their intercrossed F 2 population. There were no numerical variations in CER vertebrae. On the other hand, the numbers of THO and LUM vertebrae and the TNV varied in all three populations. Of the traits investigated in the three populations, only the means±SE of the LUM vertebrae did not show statistical significance (p>0.05). The carcass weights (CW), meat color (MC), marbling score (MS), backfat thickness (BFT), carcass length (CLE), THO vertebrae, and TNV all showed statistical significance (p 2 population had 14-17 THO vertebrae, 5-7 LUM vertebrae, and 27-30 TNV. In the F 2 population, increased numbers of THO vertebrae and TNV were associated with a significant increase in the CW, CLE, and BFT (p<0.05). In particular, the increase in the TNV was caused by an increase in the number of THO rather than LUM vertebrae. Although the animals with a greater number of THO and TNV had thicker backfat, they had a longer CLE and a heavier CW. Both these traits are economically more important than the level of backfat when determining the productivity level. These results suggest that genetic selection to increase the number of vertebrae, especially in Landrace pigs, JBPs, and their related populations, may be an excellent strategy for improving productivity.

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Hyun-Tae Lim

Gyeongsang National University

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In-Cheol Cho

Rural Development Administration

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Hee-Bok Park

Gyeongsang National University

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Jae-Bong Lee

Gyeongsang National University

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Eun-Ji Jung

Gyeongsang National University

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Moon-Suck Ko

Rural Development Administration

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Jin-Tae Jeon

Gyeongsang National University

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Sang-Hyun Han

Rural Development Administration

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Byeong-Woo Kim

Gyeongsang National University

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Jun-Heon Lee

Chungnam National University

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