• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.141-141
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• 2017

The ubiquitin-proteasome pathway is the major regulatory mechanism in a number of cellular processes for selective degradation of proteins and involves three steps: (1) ATP dependent activation of ubiquitin by E1 enzyme, (2) transfer of activated ubiquitin to E2 and (3) transfer of ubiquitin to the protein to be degraded by E3 complex. F-box proteins are subunit of SCF complex and involved in specificity for a target substrate to be degraded. F-box proteins regulate many important biological processes such as embryogenesis, floral development, plant growth and development, biotic and abiotic stress, hormonal responses and senescence. However, little is known about the F-box genes in wheat. The draft genome sequence of wheat (IWGSC Reference Sequence v1.0 assembly) used to analysis a genome-wide survey of the F-box gene family in wheat. The Hidden Markov Model (HMM) profiles of F-box (PF00646), F-box-like (PF12937), F-box-like 2 (PF13013), FBA (PF04300), FBA_1 (PF07734), FBA_2 (PF07735), FBA_3 (PF08268) and FBD (PF08387) domains were downloaded from Pfam database were searched against IWGSC Reference Sequence v1.0 assembly. RNA-seq paired-end libraries from different stages of wheat, such as stages of seedling, tillering, booting, day after flowering (DAF) 1, DAF 10, DAF 20, and DAF 30 were conducted and sequenced by Illumina HiSeq2000 for expression analysis of F-box protein genes. Basic analysis including Hisat, HTseq, DEseq, gene ontology analysis and KEGG mapping were conducted for differentially expressed gene analysis and their annotation mappings of DEGs from various stages. About 950 F-box domain proteins identified by Pfam were mapped to wheat reference genome sequence by blastX (e-value < 0.05). Among them, more than 140 putative F-box protein genes were selected by fold changes cut-offs of > 2, significance p-value < 0.01, and FDR<0.01. Expression profiling of selected F-box protein genes were shown by heatmap analysis, and average linkage and squared Euclidean distance of putative 144 F-box protein genes by expression patterns were calculated for clustering analysis. This work may provide valuable and basic information for further investigation of protein degradation mechanism by ubiquitin proteasome system using F-box proteins during wheat development stages.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.11
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• pp.1529-1539
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• 2012

A whole genome association (WGA) study was performed to detect significant polymorphisms for meat quality traits in an $F_2$ cross population (N = 478) that were generated with Korean native pig sires and Landrace dams in National Livestock Research Institute, Songwhan, Korea. The animals were genotyped using Illumina porcine 60k SNP beadchips, in which a set of 46,865 SNPs were available for the WGA analyses on ten carcass quality traits; live weight, crude protein, crude lipids, crude ash, water holding capacity, drip loss, shear force, CIE L, CIE a and CIE b. Phenotypes were regressed on additive and dominance effects for each SNP using a simple linear regression model, after adjusting for sex, sire and slaughter stage as fixed effects. With the significant SNPs for each trait (p<0.001), a stepwise regression procedure was applied to determine the best set of SNPs with the additive and/or dominance effects. A total of 106 SNPs, or quantitative trait loci (QTL) were detected, and about 32 to 66% of the total phenotypic variation was explained by the significant SNPs for each trait. The QTL were identified in most porcine chromosomes (SSCs), in which majority of the QTL were detected in SSCs 1, 2, 12, 13, 14 and 16. Several QTL clusters were identified on SSCs 12, 16 and 17, and a cluster of QTL influencing crude protein, crude lipid, drip loss, shear force, CIE a and CIE b were located between 20 and 29 Mb of SSC12. A pleiotropic QTL for drip loss, CIE L and CIE b was also detected on SSC16. These QTL need to be validated in commercial pig populations for genetic improvement in meat quality via marker-assisted selection.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.9
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• pp.1464-1473
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• 2018

Objective: To describe in-depth sequencing, the bacterial community diversity and its succession during ensiling of whole-plant maize and subsequent exposure to air. Methods: The microbial community dynamics of fermented whole-plant maize for 60 days (sampled on day 5, 10, 20, 40, 60) and subsequent aerobic exposure (sampled on day 63 after exposure to air for 3 days) were explored using Illumina Miseq sequence platform. Results: A total of 227,220 effective reads were obtained. At the genus level, there were 12 genera with relative abundance >1%, Lactobacillus, Klebsiella, Sporolactobacillus, Norank-c-cyanobacteria, Pantoea, Pediococcus, Rahnella, Sphingomonas, Serratia, Chryseobacterium, Sphingobacterium, and Lactococcus. Lactobacillus consistently dominated the bacterial communities with relative abundance from 49.56% to 64.17% during the ensiling process. Klebsiella was also an important succession bacterium with a decrease tendency from 15.20% to 6.41% during the ensiling process. The genus Sporolactobacillus appeared in late-ensiling stages with 7.70% abundance on day 40 and 5.32% on day 60. After aerobic exposure, the Lactobacillus decreased its abundance from 63.2% on day 60 to 45.03% on d 63, and Klebsiella from 5.51% to 5.64%, while Sporolactobacillus greatly increased its abundance to 28.15%. These bacterial genera belong to 5 phyla: Firmicutes (relative abundance: 56.38% to 78.43%) was dominant, others were Proteobacteria, Bacteroidetes, Cyanobacteria, and Actinobacteria. The bacterial communities clearly clustered into early-ensiling (d 5), medium-ensiling (d 10, d 20), late-ensiling (d 40, d 60), and aerobic exposure (d 63) clusters, with early- and late-ensiling communities more like each other than to the aerobic exposure communities. Conclusion: High-throughput sequencing based on 16S rRNA genes proved to be a useful method to explore bacterial communities of silage. The results indicated that the bacterial communities varied during fermentation and more dramatically during aerobic exposure. The study is valuable for understanding the mechanism of population change and the relationship between bacteria and ensilage characteristics.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.3
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• pp.322-329
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• 2011

A whole genome association (WGA) study was conducted to identify quantitative trait loci (QTL) for body conformation traits in Hanwoo cattle. The phenotypes of 497 steers were recorded from the Hanwoo Improvement Center of National Agricultural Cooperative Federation, Seosan, Korea, and analyzed using the Illumina Bovine 50 k SNP chip. A set of 35,987 SNPs that were available in the Hanwoo population was selected from the chip. After adjustments for the effects of year-season of birth, region and sire, phenotypes were regressed on each SNP using a linear regression model. Three hundred nineteen SNPs were detected for the ten conformation traits (p<0.003). For the significant SNPs, stepwise regression procedures were applied to determine best sets of markers. A total of 72 SNPs were selected (p<0.001), for which the sets of 5, 9, 10, 9, 8, 11, 4, 6, 3 and 7 SNPs were determined for height at withers, rump height, body length, chest depth, chest width, rump length, hip width, thurl width, pinbone width and heart girth, respectively. About 7-26% of the total phenotypic variation was explained by the set of SNPs for each trait. QTL for the conformation traits were harbored on most bovine chromosomes (BTAs). Four SNPs with pleiotropic effects on height at withers and rump height were detected on BTAs 3, 4, 6 and 16. A SNP with pleiotropic effects on chest width and rump length was also detected on BTA10. Two QTL regions, i.e. between 87 and 97 Mb in BTA3 and between 41 and 44 Mb in BTA7, were found, in which SNPs were detected for the five and three conformation traits, respectively. The detected SNPs need to be validated in other Hanwoo populations for commercial application to the genetic improvement of conformation characteristics in Hanwoo via marker-assisted selection (MAS).

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.4
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• pp.473-479
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• 2018

Objective: The study was designed to perform a genome-wide association (GWA) and partitioning of genome using Illumina's PorcineSNP60 Beadchip in order to identify variants and determine the explained heritability for the total number of teats in Yorkshire pig. Methods: After screening with the following criteria: minor allele frequency, $MAF{\leq}0.01$; Hardy-Weinberg equilibrium, $HWE{\leq}0.000001$, a pair-wise genomic relationship matrix was produced using 42,953 single nucleotide polymorphisms (SNPs). A genome-wide mixed linear model-based association analysis (MLMA) was conducted. And for estimating the explained heritability with genome- or chromosome-wide SNPs the genetic relatedness estimation through maximum likelihood approach was used in our study. Results: The MLMA analysis and false discovery rate p-values identified three significant SNPs on two different chromosomes (rs81476910 and rs81405825 on SSC8; rs81332615 on SSC13) for total number of teats. Besides, we estimated that 30% of variance could be explained by all of the common SNPs on the autosomal chromosomes for the trait. The maximum amount of heritability obtained by partitioning the genome were $0.22{\pm}0.05$, $0.16{\pm}0.05$, $0.10{\pm}0.03$ and $0.08{\pm}0.03$ on SSC7, SSC13, SSC1, and SSC8, respectively. Of them, SSC7 explained the amount of estimated heritability along with a SNP (rs80805264) identified by genome-wide association studies at the empirical p value significance level of 2.35E-05 in our study. Interestingly, rs80805264 was found in a nearby quantitative trait loci (QTL) on SSC7 for the teat number trait as identified in a recent study. Moreover, all other significant SNPs were found within and/or close to some QTLs related to ovary weight, total number of born alive and age at puberty in pigs. Conclusion: The SNPs we identified unquestionably represent some of the important QTL regions as well as genes of interest in the genome for various physiological functions responsible for reproduction in pigs.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.11
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• pp.1643-1650
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• 2017

Objective: The control of psychrotrophic bacteria causing milk spoilage and illness due to toxic compounds is an important issue in the dairy industry. In South Korea, Gangwon-do province is one of the coldest terrains in which eighty percent of the area is mountainous regions, and mainly plays an important role in the agriculture and dairy industries. The purposes of this study were to analyze the indigenous microbiota of raw milk in Gangwon-do and accurately investigate a putative microbial group causing deterioration in milk quality. Methods: We collected raw milk from the bulk tank of 18 dairy farms in the Hoengseong and Pyeongchang regions of Gangwon-do. Milk components were analyzed and the number of viable bacteria was confirmed. The V3 and V4 regions of 16S rRNA gene were amplified and sequenced on an Illumina Miseq platform. Sequences were then assigned to operational taxonomic units, followed by the selection of representative sequences using the QIIME software package. Results: The milk samples from Pyeongchang were higher in fat, protein, lactose, total solid, and solid non-fat, and bacterial cell counts were observed only for the Hoengseong samples. The phylum Proteobacteria was detected most frequently in both the Hoengseong and Pyeongchang samples, followed by the phyla Firmicutes and Actinobacteria. Notably, Corynebacterium, Pediococcus, Macrococcus, and Acinetobacter were significantly different from two regions. Conclusion: Although the predominant phylum in raw milk is same, the abundances of major genera in milk samples were different between Hoengseong and Pyeongchang. We assumed that these differences are caused by regional dissimilar farming environments such as soil, forage, and dairy farming equipment so that the quality of milk raw milk from Pyeongchang is higher than that of Hoengseong. These results could provide the crucial information for identifying the microbiota in raw milk of South Korea.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.11
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• pp.1691-1699
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• 2018

Objective: In Korea, there are three main cattle breeds, which are distinguished by coat color: Brown Hanwoo (BH), Brindle Hanwoo (BRH), and Jeju Black (JB). In this study, we sought to compare the genetic diversity and divergence among there Korean cattle breeds using a BovineHD chip genotyping array. Methods: Sample data were collected from 168 cattle in three populations of BH (48 cattle), BRH (96 cattle), and JB (24 cattle). The single-nucleotide polymorphism (SNP) genotyping was performed using the Illumina BovineHD SNP 777K Bead chip. Results: Heterozygosity, used as a measure of within-breed genetic diversity, was higher in BH (0.293) and BRH (0.296) than in JB (0.266). Linkage disequilibrium decay was more rapid in BH and BRH than in JB, reaching an average $r^2$ value of 0.2 before 26 kb in BH and BRH, whereas the corresponding value was reached before 32 kb in JB. Intra-population, interpopulation, and Fst analyses were used to identify candidate signatures of positive selection in the genome of a domestic Korean cattle population and 48, 11, and 11 loci were detected in the genomic region of the BRH breed, respectively. A Neighbor-Joining phylogenetic tree showed two main groups: a group comprising BH and BRH on one side and a group containing JB on the other. The runs of homozygosity analysis between Korean breeds indicated that the BRH and JB breeds have high inbreeding within breeds compared with BH. An analysis of differentiation based on a high-density SNP chip showed differences between Korean cattle breeds and the closeness of breeds corresponding to the geographic regions where they are evolving. Conclusion: Our results indicate that although the Korean cattle breeds have common features, they also show reliable breed diversity.

• Journal of Animal Science and Technology
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• v.52 no.5
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• pp.357-366
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• 2010

The emergence of next-generation sequencing technologies has lead to application of new computational and statistical methodologies that allow incorporating genetic information from entire genomes of many individuals composing the population. For example, using single-nucleotide polymorphisms (SNP) obtained from whole genome amplification platforms such as the Ilummina BovineSNP50 chip, many researchers are actively engaged in the genetic evaluation of cattle livestock using whole genome relationship analyses. In this study, we estimated the genomic relationship matrix (GRM) and compared it with one computed using a pedigree relationship matrix (PRM) using a population of Hanwoo. This project is a preliminary study that will eventually include future work on genomic selection and prediction. Data used in this study were obtained from 187 blood samples consisting of the progeny of 20 young bulls collected after parentage testing from the Hanwoo improvement center, National Agriculture Cooperative Federation as well as 103 blood samples from the progeny of 12 proven bulls collected from farms around the Kyong-buk area in South Korea. The data set was divided into two cases for analysis. In the first case missing genotypes were included. In the second case missing genotypes were excluded. The effect of missing genotypes on the accuracy of genomic relationship estimation was investigated. Estimation of relationships using genomic information was also carried out chromosome by chromosome for whole genomic SNP markers based on the regression method using allele frequencies across loci. The average correlation coefficient and standard deviation between relationships using pedigree information and chromosomal genomic information using data which was verified using a parentage test andeliminated missing genotypes was $0.81{\pm}0.04$ and their correlation coefficient when using whole genomic information was 0.98, which was higher. Variation in relationships between non-inbred half sibs was $0.22{\pm}0.17$ on chromosomal and $0.22{\pm}0.04$ on whole genomic SNP markers. The variations were larger and unusual values were observed when non-parentage test data were included. So, relationship matrix by genomic information can be useful for genetic evaluation of animal breeding.

• Molecules and Cells
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• v.38 no.5
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• pp.466-473
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• 2015

Over the last 30 years, Hanwoo has been selectively bred to improve economically important traits. Hanwoo is currently the representative Korean native beef cattle breed, and it is believed that it shared an ancestor with a Chinese breed, Yanbian cattle, until the last century. However, these two breeds have experienced different selection pressures during recent decades. Here, we whole-genome sequenced 10 animals each of Hanwoo and Yanbian cattle (20 total) using the Illumina HiSeq 2000 sequencer. A total of approximately 3.12 and 3.07 billion sequence reads were mapped to the bovine reference sequence assembly (UMD 3.1) at an average of approximately 10.71- and 10.53-fold coverage for Hanwoo and Yanbian cattle, respectively. A total of 17,936,399 single nucleotide polymorphisms (SNPs) were yielded, of which 22.3% were found to be novel. By annotating the SNPs, we further retrieved numerous nonsynonymous SNPs that may be associated with traits of interest in cattle. Furthermore, we performed whole-genome screening to detect signatures of selection throughout the genome. We located several promising selective sweeps that are potentially responsible for economically important traits in cattle; the PPP1R12A gene is an example of a gene that potentially affects intramuscular fat content. These discoveries provide valuable genomic information regarding potential genomic markers that could predict traits of interest for breeding programs of these cattle breeds.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.7
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• pp.920-929
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• 2017

Objective: The bursa of Fabricius (BF) is a central humoral immune organ belonging specifically to avians. Recent studies had suggested that miRNAs were active regulators involved in the immune processes. This study was to investigate the possible differences of the BF at miRNA level between two genetically disparate duck breeds. Methods: Using Illumina next-generation sequencing, the miRNAs libraries of ducks were established. Results: The results showed that there were 66 differentially expressed miRNAs and 28 novel miRNAs in bursa. A set of abundant miRNAs (i.e., let-7, miR-146a-5p, miR-21-5p, miR-17~92) which are involved in immunity and disease were detected and the predicted target genes of the novel miRNAs were associated with duck high anti-adversity ability. By gene ontology analysis and enriching KEGG pathway, the targets of differential expressed miRNAs were mainly involved in immunity and disease, supporting that there were differences in the BF immune functions between the two duck breeds. In addition, the metabolic pathway had the maximum enriched target genes and some enriched pathways that were related to cell cycle, protein synthesis, cell proliferation and apoptosis. It indicted that the difference of metabolism may be one of the reasons leading the immune difference between the BF of two duck breeds. Conclusion: This data lists the main differences in the BF at miRNAs level between two genetically disparate duck breeds and lays a foundation to carry out molecular assisted breeding of poultry in the future.