• Journal of agriculture & life science
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• v.50 no.3
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• pp.99-117
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• 2016

Data on primal cuts were collected from 1,829 steers of Hanwoo progeny testing programs, between 2010 and 2015 for the ssGWAS. SNP data were analyzed by using Illumina Bovine 50K Beadchip. The SNP data that matches with phenotype data was 674 animals. As a first step, the genomic estimated breeding value(GEBV) of the loin and rib cuts were estimated, which was used in the estimation of SNP marker effects and their variances related to the traits. Then, the estimated variance explained by each marker was expressed as a proportion to the total genetic variance. Finally, the SNP loci and their significance to any possible QTL were examined. Among the 20 best SNP loci explaining a larger proportion of SNP variance to the total genetic variance for tender loin yield, the region between 12,812,193 ~ 12,922,313bp on BTA 10 harbored a cluster of SNPs that explained about 7.32 to 7.34% of the total genetic variance. For strip loin yield, a peak for higher effects for multiple SNPs was found in BTA24, between 38,158,543 and 38,347,278bp distances, which explained about 8.36 to 8.56% of the observed variance for this trait. For loin yield had relatively smaller effects in terms of the total genetic variance. Therefore, loin yield might be affected by a few loci with moderate effects and many other loci with smaller effects across the genome.

• Clinical Nutrition Research
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• v.12 no.3
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• pp.199-217
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• 2023

People with higher genetic predisposition to obesity are more susceptible to cardiovascular diseases (CVDs) and healthy plant-based foods may be associated with reduced risks of obesity and other metabolic markers. We investigated whether healthy plant-foods-rich dietary patterns might have inverse associations with cardiometabolic risk factors in participants at genetically elevated risk of obesity. For this cross-sectional study, 377 obese and overweight women were chosen from health centers in Tehran, Iran. We calculated a healthy plant-based diet index (h-PDI) in which healthy plant foods received positive scores, and unhealthy plant and animal foods received reversed scores. A genetic risk score (GRS) was developed based on 3 polymorphisms. The interaction between GRS and h-PDI on cardiometabolic traits was analyzed using a generalized linear model (GLM). We found significant interactions between GRS and h-PDI on body mass index (BMI) (p = 0.02), body fat mass (p = 0.04), and waist circumference (p = 0.056). There were significant gene-diet interactions for healthful plant-derived diets and BMI-GRS on high-sensitivity C-reactive protein (p = 0.03), aspartate aminotransferase (p = 0.04), alanine transaminase (p = 0.05), insulin (p = 0.04), and plasminogen activator inhibitor 1 (p = 0.002). Adherence to h-PDI was more strongly related to decreased levels of the aforementioned markers among participants in the second or top tertile of GRS than those with low GRS. These results highlight that following a plant-based dietary pattern considering genetics appears to be a protective factor against the risks of cardiometabolic abnormalities.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.10
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• pp.1344-1349
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• 2004

Titin-cap (TCAP), one of the abundant transcripts in skeletal muscles, was nvestigated in this study in cattle because of its role in regulating the proliferation and differentiation of myoblasts by interacting with the myostatin gene. From the 5, and 3, RACE experiments, full-length TCAP coding sequence was identified, comprising 166 amino acids. The amino acid comparison showed high sequence similarities with previously identified human (95.8%) and mouse (95.2%) TCAP genes. The TCAP expression, addressed by northern blot, is limited in muscle tissues as indicated by Valle et al. (1997). The radiation hybrid analysis localized the gene on BTA19, where the comparative human and porcine counterparts are on HSA17 and SSC12. A few muscle-related genetic disorders were mapped on HSA17 and some growth-related QTLs were identified on SSC12. The bovine TCAP gene found in this study opens up new possibilities for the investigation of muscle-related genetic diseases as well as meat yield traits in cattle.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.12
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• pp.1691-1695
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• 2005

The bovine lymphocyte antigen (BoLA)-DRB3 gene encodes cell surface glycoproteins that initiate immune responses by presenting processed antigenic peptides to CD4 T helper cells. DRB3 is the most polymorphic bovine MHC class II gene which encodes the peptide-binding groove. Since different alleles favour the binding of different peptides, DRB3 has been extensively evaluated as a candidate marker for associations with various bovine diseases and immunological traits. For that reason, the genetic diversity of the bovine class II DRB3 locus was investigated by polymerase chain reaction-restriction fragment length polymorphism method (PCR-RFLP). This study describes genetic variability in the BoLA-DRB3 in Iranian Golpayegani Cattle. Iranian Golpayegani Cows (n = 50) were genotyped for bovine lymphocyte antigen (BoLA)-DRB3.2 allele by polymerase chain reaction and restriction fragment length polymorphism method. Bovine DNA was isolated from aliquots of whole blood. A two-step polymerase chain reaction followed by digestion with restriction endonucleases RsaI, HaeIII and BstYI was conducted on the DNA from Iranian Golpayegani Cattle. In the Iranian Golpayegani herd studied, we identified 19 alleles.DRB3.2${\times}$16 had the highest allelic frequency (14%), followed by DRB3.2${\times}$7 (11%). Six alleles (DRB3.2${\times}$25, ${\times}$24, ${\times}$22, ${\times}$20, ${\times}$15, ${\times}$3) had frequencies = 2%. Although additional studies are required to confirm the present findings, our results indicate that exon 2 of the BoLA-DRB3 gene is highly polymorphic in Iranian Golpayegani Cattle.

• Asian-Australasian Journal of Animal Sciences
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• v.11 no.4
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• pp.422-427
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• 1998

The gene and genotypic frequencies of ${\kappa}$-casein (${\kappa}$-CN), ${\beta}$-lactoglobulin (${\beta}$-LG), growth hormone (bGH) and prolactin (bPRL) loci in Korean cattle were investigated using PCR-RFLP analyses. Genomic DNA samples were obtained from 290 cows and 30 AI bulls. In both cows and bulls, the most predominant genotypes of ${\kappa}$-CN, ${\beta}$-LG, bGH and bPRL loci were AB, BB, AA and AA, respecitively. The frequencies of A and B alleles for ${\kappa}$-CN locus were .612 and .388 for cows and .567 and .433 for bulls. The respective frequencies of A and B alleles for ${\beta}$-LG locus were .153 and .847 in cows and .217 and .783 in bulls. The frequencies of A and B alleles for bGH locus were .769 and .231 in cows and .784 and .216 in bulls, respectively. The frequencies of A and B alleles for bPRL locus were .678 and .322 for cows and .767 and .233 for bulls. Differences in frequencies of these alleles were not significant between cows and bulls at all loci examined. If the DNA polymorphisms of these candidate genes are associated with economically important traits, they could serve as genetic markers for genetic improvement in future marker-assisted selection programs in Korean cattle.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.12
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• pp.1651-1659
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• 2011

This study was conducted to detect quantitative trait loci (QTL) for thirteen growth and meat quality traits in pigs by combing QTL experimental populations. Two F2 reference populations that were sired by Korea native pig (KNP) and dammed by Landrace (LN) or Yorkshire (YK) were generated to construct linkage maps using 123 genetic markers (mostly microsatellites) and to perform QTL analysis on porcine chromosomes (SSCs) 1, 2, 3, 6, 7, 8, 9, 11, 13, 14, and 15. A set of line-cross models was applied to detect QTL, and a series of lack-of-fit tests between the models was used to characterize inheritance mode of QTL. A total of 23, 11 and 19 QTL were detected at 5% chromosome-wise level for the data sets of KNP${\times}$LN, KNP${\times}$YK cross and joint sets of the two cross populations, respectively. With the joint data, two Mendelian expressed QTL for live weight and cooking loss were detected on SSC3 and SSC15 at 1% chromosome-wise level, respectively. Another Mendelian expressed QTL was detected for CIE a on SSC7 at 5% genome-wise level. Our results suggest that QTL analysis by combining data from two QTL populations increase power for QTL detection, which could provide more accurate genetic information in subsequent marker-assisted selection.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.12
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• pp.1644-1650
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• 2011

This study was conducted to detect quantitative trait loci (QTL) affecting meat quality in an $F_2$ reference population of Korean native pig and Landrace crossbreds. The three-generation mapping population was generated with 411 progeny from 38 $F_2$ full-sib families, and 133 genetic markers were used to produce a sex-average map of the 17 autosomes. The data set was analyzed using least squares Mendelian and parent-of-origin interval-mapping models. Lack-of-fit tests between models were used to characterize the QTL for mode of gene expressions. A total of 10 (32) QTL were detected at the 5% genome (chromosome)-wise level for the analyzed traits. Of the 42 QTL detected, 13 QTL were classified as Mendelian, 10 as paternal, 14 as maternal, and 5 as partial expressed QTL, respectively. Among the QTL detected at 5% genome-wise level, four QTL had Mendelian mode of inheritance on SSCs 5, 10, 12, and 13 for cooking loss, drip loss, crude lipid and crude protein, respectively; two QTL maternal inheritance for pH at 24-h and shear force on SSC11; three QTL paternal inheritance for CIE b and Hunter b on SSC9 and for cooking loss on SSC15; and one QTL partial expression for crude ash on SSC13, respectively. Most of the Mendelian QTL (9 of 13) had a dominant mode of gene action, suggesting potential utilization of heterosis for genetic improvement of meat quality within the cross population via marker-assisted selection.

• Horticultural Science & Technology
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• v.33 no.6
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• pp.869-876
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• 2015

Wild relative species of domesticated crops are useful genetic resources for improving agronomic traits. Cytogenetic investigations based on chromosome composition provide insight into basic genetic and genomic characteristics of a species that can be exploited in a breeding program. Here, we used FISH analysis to characterize the ploidy level, chromosome constitution, and genomic distribution o f 5S and 4 5S r ibosomal DNA (rDNA) in four wild Cucurbitaceae species, namely, Citrullus lanatus (Thunb.) Mansf. var. citroides L. H. Bailey (2n = 22), Melothria japonica Maxim. (2n = 22), Sicyos angulatus L. (2n = 24), and Trichosanthes kirilowii Maxim. (2n = 66, 88, 110 cytotypes), collected in different areas of Korea. All species were diploids, except for T. kirilowii, which included hexa-, octa-, and decaploid cytotypes (2n = 6x = 66, 8x = 88, and 10x = 110). All species have small metaphase chromosomes in the range of $2-5{\mu}m$. The 45S rDNA signals were localized distally compared to the 5S rDNA. C. lanatus var. citroides and M. japonica showed one and two loci of 45S and 5S rDNA, respectively, with co-localization of rDNA signals in one M. japonica chromosome. S. angulatus showed two co-localized signals of 5S and 45S rDNA loci. The hexaploid T. kirilowii cytotype showed five signals each for 45S and 5S rDNA, with three being co-localized. This is the first report of hexaploid and decaploid cytotypes in T. kirilowii. These results will be useful in future Cucurbitaceae breeding programs.

• Genomics & Informatics
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• v.17 no.4
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• pp.48.1-48.6
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• 2019

Over the last decade, genome-wide association studies (GWASs) have provided an unprecedented amount of genetic variations that are associated with various phenotypes. However, previous GWAS were mostly conducted in European populations, and these biased results for non-Europeans may result in a significant reduction in risk prediction for non-Europeans. An issue with the early GWAS was the winner's curse problem, which led to misleading results when constructing the polygenic risk scores (PRS). Therefore, more non-European population-based studies are needed to validate reported variants and improve genetic risk assessment across diverse populations. In this study, we validated 422 variants independently associated with glycemic indexes, liver enzymes, and type 2 diabetes in 125,872 samples from a Korean population, and further validated the results by assessing publicly available summary statistics from European GWAS (n = 898,130). Among the 422 independently associated variants, 284, 320, and 361 variants were replicated in Koreans, Europeans, and either one of the two populations. In addition, the effect sizes for Koreans and Europeans were moderately correlated (r = 0.33-0.68). However, 61 variants were not replicated in both Koreans and Europeans. Our findings provide valuable information on effect sizes and statistical significance, which is essential to improve the assessment of disease risk using PRS analysis.

• Horticultural Science & Technology
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• v.16 no.1
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• pp.18-20
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• 1998

The present research was conducted to study genetic relationship and cultivar identification in sweet potato (lpomoea batatas) using RAPD method. Thirteen cultivars of sweet potato in Korea were classified by UPGMA clustering method into three groups as follows; group I was corresponded to 'Choongsung100'; group II, 'Eunmi', 'Saengmi', 'Suwon147' and 'Yulmi'; group III, 'Hongmi', 'Jinmi', 'Kwandong95', 'Seonmi', 'Wonmi', 'Shinyulmi', 'Jeungmi', and 'Poongmi'. Identification using RAPD was generally consistent with breeding pedigree of those parents. However, inconsistent results may be caused by clonal variation. The results presented in this study suggest that RAPDs in sweetpotato are likely to be useful for cultivar identification and various procedures in breeding. The use of various DNA marker system assists selection programs for economically important trait, and may facilitate selection in earlier growing stage. This systems may enhance the prospects for improving sweet potato cultivar by accurate marking desirable traits at DNA level.