• Journal of Veterinary Science
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• v.25 no.4
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• pp.42.1-42.12
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• 2024

Importance: Bovine mastitis, predominantly associated with gram-positive Staphylococcus aureus, poses a significant threat to dairy cows, leading to a decline in milk quality and volume with substantial economic implications. Objective: This study investigated the incidence, virulence, and antibiotic resistance of S. aureus associated with mastitis in dairy cows. Methods: Fifty milk-productive cows underwent a subclinical mastitis diagnosis, and the S. aureus strains were isolated. Genomic DNA extraction, sequencing, and bioinformatic analysis were performed, supplemented by including 124 S. aureus genomes from cows with subclinical mastitis to enhance the overall analysis. Results: The results revealed a 42% prevalence of subclinical mastitis among the cows tested. Genomic analysis identified 26 sequence types (STs) for all isolates, with Mexican STs belonging primarily to CC1 and CC97. The analyzed genomes exhibited multidrug resistance to phenicol, fluoroquinolone, tetracycline, and cephalosporine, which are commonly used as the first line of treatment. Furthermore, a similar genomic virulence repertoire was observed across the genomes, encompassing the genes related to invasion, survival, pathogenesis, and iron uptake. In particular, the toxic shock syndrome toxin (tss-1) was found predominantly in the genomes isolated in this study, posing potential health risks, particularly in children. Conclusion and Relevance: These findings underscore the broad capacity for antibiotic resistance and pathogenicity by S. aureus, compromising the integrity of milk and dairy products. The study emphasizes the need to evaluate the effectiveness of antibiotics in combating S. aureus infections.

• Genomics & Informatics
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• v.15 no.1
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• pp.19-27
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• 2017

Understanding complex relationships among heterogeneous biological data is one of the fundamental goals in biology. In most cases, diverse biological data are stored in relational databases, such as MySQL and Oracle, which store data in multiple tables and then infer relationships by multiple-join statements. Recently, a new type of database, called the graph-based database, was developed to natively represent various kinds of complex relationships, and it is widely used among computer science communities and IT industries. Here, we demonstrate the feasibility of using a graph-based database for complex biological relationships by comparing the performance between MySQL and Neo4j, one of the most widely used graph databases. We collected various biological data (protein-protein interaction, drug-target, gene-disease, etc.) from several existing sources, removed duplicate and redundant data, and finally constructed a graph database containing 114,550 nodes and 82,674,321 relationships. When we tested the query execution performance of MySQL versus Neo4j, we found that Neo4j outperformed MySQL in all cases. While Neo4j exhibited a very fast response for various queries, MySQL exhibited latent or unfinished responses for complex queries with multiple-join statements. These results show that using graph-based databases, such as Neo4j, is an efficient way to store complex biological relationships. Moreover, querying a graph database in diverse ways has the potential to reveal novel relationships among heterogeneous biological data.

• Journal of Crop Science and Biotechnology
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• v.10 no.3
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• pp.175-184
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• 2007

Two subspecies, japonica and indica, have been reported in rice, which differ in several ecotypic traits. However, reproductive barriers in hybrid progenies between subspecies have been major obstacles in breeding programs using inter-subspecific hybridization. As the first step to elucidate the reproductive barriers, we developed subspecies-specific(SS) STS markers in this study. A total of 765 STS primers were designed through comparing DNA sequences at every $2{\sim}3$cM interval between japonica and indica rices, which are available at Web DBs such as IRGSP, NCBI, TIGR, and GRAMENE, and tested for subspecies-specificity using 15 indica and 15 japonica varieties of diverse origin. Of them, 67 STS markers were identified as SS STS markers and their subspecies-specificity scores were estimated. The SS markers were dispersed throughout the genome along chromosomes. Of them, 64 SS markers were mapped on an RIL population derived from a Dasanbyeo(indica)/TR22183(japonica) cross. Genomic inclination of RILs was evaluated based on the genotyping with different types of markers. Association test between markers and segregation distortion revealed that segregation distortion might not be the cause of generating SS markers. The SS markers will be applicable to estimate the genomic inclination of varieties or lines and to study the differentiation of indica and japonica, and ultimately to breed true hybrid rice varieties in which desirable characters from both subspecies are recombined.

• The Journal of Korean Medicine
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• v.27 no.2 s.66
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• pp.225-231
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• 2006

Objectives : This study was performed to determine if unknown species of antler samples could be identified by genetic distance methods. Methods : The DNAs of 4 antler samples were extracted, amplified by PCR, and sequenced. The DNAs of antlers were identified by genetic distance. Genetic distance method was made using MEGA software (Molecular Evolutionary Genetics Analysis, 3.1). Results : By genetic distance methods, all 4 antler samples were closest to Cervus elaphus nelsoni among Cervus species. Conclusion : These results suggest that genetic distance methods might be used as a tool for the identification of Cervus species.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2001.10a
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• pp.1-9
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• 2001

scale genomic and postgenomic data means that many of the challenges in biomedical research are now challenges in computational sciences and information technology. The informatics revolutions both in clinical informatics and bioinformatics will change the current paradigm of biomedical sciences and practice of clinical medicine, including diagnostics, therapeutics, and prognostics. Postgenome informatics, powered by high throughput technologies and genomic-scale databases, is likely to transform our biomedical understanding forever much the same way that biochemistry did a generation ago. In this talk, 1 will describe how these technologies will in pact biomedical research and clinical care, emphasizing recent advances in biochip-based functional genomics. Basic data preprocessing with normalization and filtering, primary pattern analysis, and machine teaming algorithms will be presented. Issues of integrated biochip informatics technologies including multivariate data projection, gene-metabolic pathway mapping, automated biomolecular annotation, text mining of factual and literature databases, and integrated management of biomolecular databases will be discussed. Each step will be given with real examples from ongoing research activities in the context of clinical relevance. Issues of linking molecular genotype and clinical phenotype information will be discussed.

• Proceedings of the KSAR Conference
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• 2001.10a
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• pp.25-31
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• 2001

During early development, a dramatic reduction in methylation levels occurs in mouse (Monk et al., 1987). The process of epigenetic reprogramming in early embryos erases gamete-specific methylation patterns inherited from the parents (Howlett ＆ Reik 1991, Monk et al., 1987, Oswald et al., 2000, Sanford et al., 1984). This genome-wide demethylation process may be a prerequisite for the formation of pluripotent stem cells that are important for the later development (Reik ＆ Surani 1997). During post-implantation development, a wave of de novo methylation takes place; most of the genomic DNA is methylated at defined developmental timepoints, whereas tissue-specific genes undergo demethylation in their tissues of expression (Kafri et al., 1992, Razin ＆ Kafri 1994). Another demethylation-remethylation cycle of epigenetic reprogramming takes place during gametogenesis and is necessary for resetting of genomic imprinting (Solter 1988). The dynamic epigenetic reprogramming events appear to be basic and are probably conserved in eutherian mammals (see below). (omitted)

• Fisheries and Aquatic Sciences
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• v.16 no.4
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• pp.303-309
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• 2013

Microsatellite markers are important for gene mapping and for marker-assisted selection. Sixty-five polymorphic microsatellite markers were developed with an enriched partial genomic library from olive flounder Paralichthys olivaceus an important commercial fish species in Korea. The variability of these markers was tested in 30 individuals collected from the East Sea (Korea). The number of alleles for each locus ranged from 2 to 33 (mean, 17.1). Observed and expected heterozygosity as well as polymorphism information content varied from 0.313 to 1.000 (mean, 0.788), from 0.323 to 0.977 (mean, 0.820), and from 0.277 to 0.960 (mean, 0.787), respectively. Nine loci showed significant deviation from the Hardy-Weinberg equilibrium after sequential Bonferroni correction. Analysis with MICROCHECKER suggested the presence of null alleles at five of these loci with estimated null allele frequencies of 0.126-0.285. These new microsatellite markers from genomic libraries will be useful for constructing a P. olivaceus linkage map.

• Korean Journal of Microbiology
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• v.38 no.4
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• pp.270-270
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• 2002

Pathogenic Salmonella typhimurium can invade the intestinal epithelium and cause a wide range of diseases including gastroenteritis and bacteremia in human and animals. To identify the genes involved in the infection, the invasion determinant was obtained from S. typhimurium 82/6915 and was subcloned into pGEM-7Z. A subclone DHl (pSV6235) invaded HEp-2 and Chinese hamster ovary epithelial cells and contained a 4.4 kb fragment of S. typhimurium genomic region. Compared with the host strain E. coli DHl, the subclone DHl (pSV6235) invaded cultured HEp-2 and Chinese hamster ovary cells at least 75- and 68-fold higher, respectively. The invasion rate of E. coli DHl for the cells significantly increased by harbouring the genomic region derived from pathogenic S. typhimurium 82/6915.

• Journal of Microbiology
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• v.41 no.1
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• pp.46-51
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• 2003

RAD6 in yeast mediates postreplication DNA repair and is responsible for DNA-damage induced mutations. RAD6 encodes ubiquitin-conjugating enzyme that is well conserved among eukaryotic organisms. However, the molecular targets and consequences of their ubiquitination by Rad6 have remained elusive. In Aspergillus nidulans, a RAD6 homolog has been isolated and shown to be an allele of uvs). We screened a CDNA library to isolate UVSJ-interacting proteins by the yeast two-hybrid system. JIPA was identified as an interactor of UVSJ. Their interaction was confirmed in vitro by a GST-pull down assay. JIPA was also able to interact with mutant UVSJ proteins, UVSJl and the active site cysteine mutant UVSJ-C88A. The N- and the C-terminal regions of UVSJ required for the interaction with UVSH, a RAD18 homolog of yeast which physically interacts with Rad6, were not necessary for the JIPA and UVSJ interactions. About 1.4 kb jipA transcript was detected in Northern analysis and its amount was not significantly increased in response to DNA-damaging agents. A genomic DNA clone of the jipA gene was isolated from a chromosome I specific genomic library by PCR-sib selection. Sequence determination of genomic and cDNA of jipA revealed an ORF of 893 bp interrupted by 2 introns, encoding a putative polypeptide of 262 amino acids. JIPA has 33% amino acid sequence identity to TIP41 of Saccharomyces cerevisiae which negatively regulates the TOR signaling pathway.

• Genomics & Informatics
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• v.18 no.1
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• pp.8.1-8.10
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• 2020

The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www. bioexpress.re.kr/.