• Asian-Australasian Journal of Animal Sciences
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• v.27 no.10
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• pp.1394-1398
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• 2014

Indigenous (native) breeds of livestock have higher disease resistance and adaptation to the environment due to high genetic diversity. Even though their extinction rate is accelerated due to the increase of commercial breeds, natural disaster, and civil war, there is a lack of well-established databases for the native breeds. Thus, we constructed the native pig and chicken breed database (NPCDB) which integrates available information on the breeds from around the world. It is a nonprofit public database aimed to provide information on the genetic resources of indigenous pig and chicken breeds for their conservation. The NPCDB (http://npcdb.snu.ac.kr/) provides the phenotypic information and population size of each breed as well as its specific habitat. In addition, it provides information on the distribution of genetic resources across the country. The database will contribute to understanding of the breed's characteristics such as disease resistance and adaptation to environmental changes as well as the conservation of indigenous genetic resources.

• BMB Reports
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• v.46 no.8
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• pp.416-421
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• 2013

Genome-wide association studies (GWAS) have become popular as an approach for the identification of large numbers of phenotype-associated variants. However, differences in genetic architecture and environmental factors mean that the effect of variants can vary across populations. Understanding population genetic diversity is valuable for the investigation of possible population specific and independent effects of variants. EvoSNP-DB aims to provide information regarding genetic diversity among East Asian populations, including Chinese, Japanese, and Korean. Non-redundant SNPs (1.6 million) were genotyped in 54 Korean trios (162 samples) and were compared with 4 million SNPs from HapMap phase II populations. EvoSNP-DB provides two user interfaces for data query and visualization, and integrates scores of genetic diversity (Fst and VarLD) at the level of SNPs, genes, and chromosome regions. EvoSNP-DB is a web-based application that allows users to navigate and visualize measurements of population genetic differences in an interactive manner, and is available online at [http://biomi.cdc.go.kr/EvoSNP/].

• Genomics & Informatics
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• v.5 no.4
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• pp.152-160
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• 2007

Most common diseases are caused by multiple genetic and environmental factors. Among the genetic factors, single nucleotide polymorphisms (SNPs) are common DNA sequence variations in individuals and can serve as important genetic markers. Recently, investigations of gene-based and whole genome-based SNPs have been applied to association studies for marker discovery. However, SNPs are so population-specific that the association needs to be verified. Fifty-five genes and 384 SNPs were selected based on association with disease. Genotypes of 337 SNPs in candidate genes were determined using Illumina Sentrix Array Matrix (SAM) chips by an allele-specific extension method in 364 unrelated Korean individuals. Allelic frequencies of SNPs were compared with those of other populations obtained from the International HapMap database. Minor allele frequencies, linkage disequilibrium blocks, tagSNPs, and haplotypes of functional candidate SNPs in 55 genetic disease-associated genes were provided. Our data may provide useful information for the selection of genetic markers for gene-based genetic disease-association studies of the Korean population.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.2
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• pp.290-296
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• 2019

Objective: Pigs share many physiological, anatomical and genomic similarities with humans, which make them suitable models for biomedical researches. Understanding the genetic status of Yucatan miniature pigs (YMPs) and their association with human diseases will help to assess their potential as biomedical model animals. This study was performed to identify non-synonymous single nucleotide polymorphisms (nsSNPs) in selective sweep regions of the genome of YMPs and present the genetic nsSNP distributions that are potentially associated with disease occurrence in humans. Methods: nsSNPs in whole genome resequencing data from 12 YMPs were identified and annotated to predict their possible effects on protein function. Sorting intolerant from tolerant (SIFT) and polymorphism phenotyping v2 analyses were used, and gene ontology (GO) network and Kyoto encyclopedia of genes and genomes (KEGG) pathway analyses were performed. Results: The results showed that 8,462 genes, encompassing 72,067 nsSNPs were identified, and 118 nsSNPs in 46 genes were predicted as deleterious. GO network analysis classified 13 genes into 5 GO terms (p<0.05) that were associated with kidney development and metabolic processes. Seven genes encompassing nsSNPs were classified into the term associated with Alzheimer's disease by referencing the genetic association database. The KEGG pathway analysis identified only one significantly enriched pathway (p<0.05), hsa04080: Neuroactive ligand-receptor interaction, among the transcripts. Conclusion: The number of deleterious nsSNPs in YMPs was identified and then these variants-containing genes in YMPs data were adopted as the putative human diseases-related genes. The results revealed that many genes encompassing nsSNPs in YMPs were related to the various human genes which are potentially associated with kidney development and metabolic processes as well as human disease occurrence.

• The Journal of the Korea Contents Association
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• v.5 no.5
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• pp.152-158
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• 2005

By using a combination of different feature sets extracted from input character patterns, we can improve the character recognition system performance. To reduce the dimensionality of the combined feature vector, we conduct the feature selection. This paper proposes a general framework for the feature combination and selection for character recognition problems. It also presents a specific design for the handwritten numeral recognition. Tn the design, DDD and AGD feature sets are extracted from handwritten numeral patterns, and a genetic algorithm is used for the feature selection. Experimental result showed a significant accuracy improvement by about 0.7% for the CENPARMI handwrittennumeral database.

• Genomics & Informatics
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• v.6 no.3
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• pp.153-156
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• 2008

Complex diseases such as stroke and cancer have two or more genetic loci and are affected by environmental factors that contribute to the diseases. Due to the complex characteristics of these diseases, identifying candidate genes requires a system-level analysis of the following: gene ontology, pathway, and interactions. A database and user interface, termed StrokeBase, was developed; StrokeBase provides queries that search for pathways, candidate genes, candidate SNPs, and gene networks. The database was developed by using in silico data mining of HGNC, ENSEMBL, STRING, RefSeq, UCSC, GO, HPRD, KEGG, GAD, and OMIM. Forty candidate genes that are associated with cerebrovascular disease were selected by human experts and public databases. The networked cerebrovascular disease gene maps also were developed; these maps describe genegene interactions and biological pathways. We identified 1127 genes, related indirectly to cerebrovascular disease but directly to the etiology of cerebrovascular disease. We found that a protein-protein interaction (PPI) network that was associated with cerebrovascular disease follows the power-law degree distribution that is evident in other biological networks. Not only was in silico data mining utilized, but also 250K Affymetrix SNP chips were utilized in the 320 control/disease association study to generate associated markers that were pertinent to the cerebrovascular disease as a genome-wide search. The associated genes and the genes that were retrieved from the in silico data mining system were compared and analyzed. We developed a well-curated cerebrovascular disease-associated gene network and provided bioinformatic resources to cerebrovascular disease researchers. This cerebrovascular disease network can be used as a frame of systematic genomic research, applicable to other complex diseases. Therefore, the ongoing database efficiently supports medical and genetic research in order to overcome cerebrovascular disease.

• Journal of Korean Neurosurgical Society
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• v.57 no.6
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• pp.422-427
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• 2015

Moyamoya disease (MMD) is a chronic, progressive, cerebrovascular occlusive disorder that displays various clinical features and results in cerebral infarct or hemorrhagic stroke. Specific genes associated with the disease have not yet been identified, making identification of at-risk patients difficult before clinical manifestation. Familial MMD is not uncommon, with as many as 15% of MMD patients having a family history of the disease, suggesting a genetic etiology. Studies of single nucleotide polymorphisms (SNPs) in MMD have mostly focused on mechanical stress on vessels, endothelium, and the relationship to atherosclerosis. In this review, we discuss SNPs studies targeting the genetic etiology of MMD. Genetic analyses in familial MMD and genome-wide association studies represent promising strategies for elucidating the pathophysiology of this condition. This review also discusses future research directions, not only to offer new insights into the origin of MMD, but also to enhance our understanding of the genetic aspects of MMD. There have been several SNP studies of MMD. Current SNP studies suggest a genetic contribution to MMD, but further reliable and replicable data are needed. A large cohort or family-based design would be important. Modern SNP studies of MMD depend on novel genetic, experimental, and database methods that will hopefully hasten the arrival of a consensus conclusion.

• Genomics & Informatics
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• v.21 no.3
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• pp.31.1-31.8
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• 2023

Multiple myeloma (MM) is a hematological malignancy. It is widely believed that genetic factors play a significant role in the development of MM, as investigated in numerous studies. However, the application of genomic information for clinical purposes, including diagnostic and prognostic biomarkers, remains largely confined to research. In this study, we utilized genetic information from the Genomic-Driven Clinical Implementation for Multiple Myeloma database, which is dedicated to clinical trial studies on MM. This genetic information was sourced from the genome-wide association studies catalog database. We prioritized genes with the potential to cause MM based on established annotations, as well as biological risk genes for MM, as potential drug target candidates. The DrugBank database was employed to identify drug candidates targeting these genes. Our research led to the discovery of 14 MM biological risk genes and the identification of 10 drugs that target three of these genes. Notably, only one of these 10 drugs, panobinostat, has been approved for use in MM. The two most promising genes, calcium signal-modulating cyclophilin ligand (CAMLG) and histone deacetylase 2 (HDAC2), were targeted by four drugs (cyclosporine, belinostat, vorinostat, and romidepsin), all of which have clinical evidence supporting their use in the treatment of MM. Interestingly, five of the 10 drugs have been approved for other indications than MM, but they may also be effective in treating MM. Therefore, this study aimed to clarify the genomic variants involved in the pathogenesis of MM and highlight the potential benefits of these genomic variants in drug discovery.

• The KIPS Transactions:PartD
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• v.18D no.2
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• pp.89-100
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• 2011

The CNV (Copy Number Variation) which is one of the genetic structural variations in human genome is closely related with the function of gene. In particular, the genome-wide association studies for genetic diseased persons have been researched. However, there have been few studies which infer the genetic function of CNV with normal human. In this paper, we propose the analysis method to reveal the functional relationship between common CNV and genes without considering their genomic loci. To achieve that, we propose the data integration method for heterogeneity biological data and novel measurement which can calculate the correlation between common CNV and genes. To verify the significance of proposed method, we has experimented several verification tests with GO database. The result showed that the novel measurement had enough significance compared with random test and the proposed method could systematically produce the candidates of genetic function which have strong correlation with common CNV.

• Animal Bioscience
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• v.34 no.4
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• pp.499-505
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• 2021

Objective: The objective of this study was to evaluate the genetic behavior of a population of Holstein cattle in response to the variation of environmental temperature by analyzing the effects of genotype by environment interaction (GEI) through reaction norms for the somatic cell score (SCS). Methods: Data was collected for 67,206 primiparous cows from the database of the Paraná Holstein Breeders Association in Brazil, with the aim of evaluating the temperature effect, considered as an environmental variable, distinguished under six gradients, with the variation range found being 17℃ to 19.5℃, over the region. A reaction norm model was adopted utilizing the fourth order under the Legendre polynomials, using the mixed models of analysis by the restricted maximum likelihood method by the WOMBAT software. Additionally, the genetic behavior of the 15 most representative bulls was assessed, in response to the changes in the temperature gradient. Results: A mean score of 2.66 and a heritability variation from 0.17 to 0.23 was found in the regional temperature increase. The correlation between the environmental gradients proved to be higher than 0.80. Distinctive genetic behaviors were observed according to the increase in regional temperature, with an observed increase of up to 0.258 in the breeding values of some animals, as well as a reduction in the breeding of up to 0.793, with occasional reclassifications being observed as the temperature increased. Conclusion: Non-relevant GEI for SCS were observed in Holstein cattle herds of southern Brazil. Thus, the inclusion of the temperature effect in the model of genetic evaluation of SCS for the southern Brazilian Holstein breed is not required.