• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.258-263
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• 2005

Haplotype-based analysis using high-density SNP markers have gained a great attention in evaluating genes in gene analysis and various clinical situations. However, there has been no research on disease diagnostic modeling based on SNPs analysis to our knowledge. The purpose of this study is to explore how knowledge discovery techniques are applied in medical informatics area and proposes a Case Based Reasoning (CBR) technique for diagnosis of gastric caner using Single Nucleotide Polymorphism(SNP).

• Journal of Plant Biotechnology
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• v.48 no.2
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• pp.71-76
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• 2021

Angelica is a perennial plant used widely for medicinal purposes. Information on the genetic diversity of Angelica populations is important for their conservation and germplasm utilization. Although Angelica is an important medicinal plant genus registered in South Korea, no molecular markers are currently available to distinguish individual species from other similar species in different countries, in particular, China and Japan. In this study, we developed single nucleotide polymorphism (SNP) markers derived from internal transcribed spacer regions of the nuclear ribosomal DNA to identify a distinct domestic species, Angelica gigas Nakai, via a high-resolution melting (HRM) curve analyses. We also performed HRM curve analysis of intentionally mixed genomic DNA samples from five Angelica species. Finally, we investigated A. gigas Nakai and A. sinensis using varying ratios of mixed genomic DNA templates. The SNP markers developed in this study are useful for rapidly identifying A. gigas species from different countries.

• Genomics & Informatics
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• v.8 no.3
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• pp.116-121
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• 2010

The association between adiponectin concentration and obesity have been reported and genetic variations of the ADIPOQ gene are known to influence the plasmatic concentration of adiponectin. Therefore, we investigated the effect of AIPOQ single nucleotide polymorphism (SNP) on obesity-related variables, and their modulation by dietary intakes in Korean women. The subjects consisted of 3,217 Korean women aged 40-59 years participating in the Korean Genome Epidemiology Study (KoGES). The general characteristics, anthropometric variables, serum blood profiles were measured. Dietary intake was analyzed using the Food Frequency Questionnaire. Subjects with the T allele of AIPOQ rs182052 showed significantly higher obesity-related variables such as weight (p=0.005), BMI (p<0.000), fat body mass (p=0.005), and waist-hip ratio (p=0.007) than those with the C allele. Moreover, the rs182052 T allele was associated with an increased risk of obesity prevalence (p=0.019). However, there were not any significant interactions observed between the genotype of ADIPOQ rs182052 and dietary intake on BMI and fat body mass. These findings suggest that the obesity-related variables may be more dominantly affected by the genotype of ADIPOQ rs182052 than dietary intake in middle aged Korean women.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.4
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• pp.508-518
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• 2019

Objective: This research aimed to determine biological pathways and protein-protein interaction (PPI) networks for 305-d milk yield (MY), 305-d fat yield (FY), and age at first calving (AFC) in the Thai multibreed dairy population. Methods: Genotypic information contained 75,776 imputed and actual single nucleotide polymorphisms (SNP) from 2,661 animals. Single-step genomic best linear unbiased predictions were utilized to estimate SNP genetic variances for MY, FY, and AFC. Fixed effects included herd-year-season, breed regression and heterosis regression effects. Random effects were animal additive genetic and residual. Individual SNP explaining at least 0.001% of the genetic variance for each trait were used to identify nearby genes in the National Center for Biotechnology Information database. Pathway enrichment analysis was performed. The PPI of genes were identified and visualized of the PPI network. Results: Identified genes were involved in 16 enriched pathways related to MY, FY, and AFC. Most genes had two or more connections with other genes in the PPI network. Genes associated with MY, FY, and AFC based on the biological pathways and PPI were primarily involved in cellular processes. The percent of the genetic variance explained by genes in enriched pathways (303) was 2.63% for MY, 2.59% for FY, and 2.49% for AFC. Genes in the PPI network (265) explained 2.28% of the genetic variance for MY, 2.26% for FY, and 2.12% for AFC. Conclusion: These sets of SNP associated with genes in the set enriched pathways and the PPI network could be used as genomic selection targets in the Thai multibreed dairy population. This study should be continued both in this and other populations subject to a variety of environmental conditions because predicted SNP values will likely differ across populations subject to different environmental conditions and changes over time.

• Journal of Apiculture
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• v.32 no.3
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• pp.147-154
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• 2017

Honeybees (Apis mellifera) are common pollinators and important insects studied in agriculture, ecology and basic research. Recently, RDA (Rural Development Administration) and YIRI (Yecheon-gun Industrial Insect Research Institute) have been breeding a triple crossbred honey bee named Jangwon, which have the ability to produce superior quality honey. In this study, we identified a single nucleotide polymorphism (SNP) marker in the genome of Jangwon honeybee, particularly, in the paternal line (D line). Initially, we performed Sequence-Based Genotyping (SBG) using the Illumina Hiseq 2500 in 5 honeybee inbred lines; A, C, D, E, and F; and obtained 1,029 SNPs. Seventeen SNPs for each inbred line were generated and selected after further filtering of the SNP dataset. The 17 SNP markers validated by performing TaqMan probe-based real-time PCR and genotyping analysis was conducted. Genotyping analysis of the 5 honeybee inbred lines and one hybrid line, $D{\times}F$, revealed that one set of SNP marker, AmD9, precisely discriminated the inbred line D from the others. Our results suggest that the identified SNP marker, AmD9, is successful in distinguishing the inbred honeybee lines D, and can be directly used for genotyping and breeding applications.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.6
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• pp.316-325
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• 2006

In diploid organisms like human, each chromosome consists of two copies. A haplotype is a SNP(single nucleotide polymorphism) sequence information from each copy. Finding the complete map of haplotypes in human population is one of the important issues in human genome. To obtain haplotypes via experimental methods is both time-consuming and expensive. Therefore, inference methods have been used to infer haplotyes from the genotype samples. In this paper, we propose a new approach using genetic algorithm to infer haplotypes, which is based on the model of finding the minimum number of haplotypes that explain the genotype samples. We show that by doing a computational experiment, our algorithm has the correctness similar to HAPAR[1] which is known to produce good results while the execution time of our algorithm is less than that of HAPAR as the input size is increased. The experimental result is also compared with the result by the recent method PTG[2].

• Asian-Australasian Journal of Animal Sciences
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• v.27 no.9
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• pp.1219-1227
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• 2014

A whole genome association (WGA) study was carried out to find quantitative trait loci (QTL) for sensory evaluation traits in Hanwoo. Carcass samples of 250 Hanwoo steers were collected from National Agricultural Cooperative Livestock Research Institute, Ansung, Gyeonggi province, Korea, between 2011 and 2012 and genotyped with the Affymetrix Bovine Axiom Array 640K single nucleotide polymorphism (SNP) chip. Among the SNPs in the chip, a total of 322,160 SNPs were chosen after quality control tests. After adjusting for the effects of age, slaughter-year-season, and polygenic effects using genome relationship matrix, the corrected phenotypes for the sensory evaluation measurements were regressed on each SNP using a simple linear regression additive based model. A total of 1,631 SNPs were detected for color, aroma, tenderness, juiciness and palatability at 0.1% comparison-wise level. Among the significant SNPs, the best set of 52 SNP markers were chosen using a forward regression procedure at 0.05 level, among which the sets of 8, 14, 11, 10, and 9 SNPs were determined for the respectively sensory evaluation traits. The sets of significant SNPs explained 18% to 31% of phenotypic variance. Three SNPs were pleiotropic, i.e. AX-26703353 and AX-26742891 that were located at 101 and 110 Mb of BTA6, respectively, influencing tenderness, juiciness and palatability, while AX-18624743 at 3 Mb of BTA10 affected tenderness and palatability. Our results suggest that some QTL for sensory measures are segregating in a Hanwoo steer population. Additional WGA studies on fatty acid and nutritional components as well as the sensory panels are in process to characterize genetic architecture of meat quality and palatability in Hanwoo.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.6
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• pp.2489-2493
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• 2015

Background: Loss of heterozygosity (LOH) on chromosomal regions is crucial in tumor progression and this study aimed to identify genome-wide LOH in pancreatic cancer. Materials and Methods: Single-nucleotide polymorphism (SNP) profiling data GSE32682 of human pancreatic samples snap-frozen during surgery were downloaded from Gene Expression Omnibus database. Genotype console software was used to perform data processing. Candidate genes with LOH were screened based on the genotype calls, SNP loci of LOH and dbSNP database. Gene annotation was performed to identify the functions of candidate genes using NCBI (the National Center for Biotechnology Information) database, followed by Gene Ontology, INTERPRO, PFAM and SMART annotation and UCSC Genome Browser track to the unannotated genes using DAVID (the Database for Annotation, Visualization and Integration Discovery). Results: The candidate genes with LOH identified in this study were MCU, MICU1 and OIT3 on chromosome 10. MCU was found to encode a calcium transporter and MICU1 could encode an essential regulator of mitochondrial $Ca^{2+}$ uptake. OIT3 possibly correlated with calcium binding revealed by the annotation analyses and was regulated by a large number of transcription factors including STAT, SOX9, CREB, NF-kB, PPARG and p53. Conclusions: Global genomic analysis of SNPs identified MICU1, MCU and OIT3 with LOH on chromosome 10, implying involvement of these genes in progression of pancreatic cancer.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.145-145
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• 2017

Foxglove aphid, Aulacorthum solani (Kaltenbach), is a Hemipteran insect that infected a wide variety of plants worldwide and caused serious yield losses in crops. The objective of this study was to identify the putative genes to foxglove aphid resistance in wild soybean, PI 366121 (Glycine soja Sieb. and Zucc.). One hundred and forty-one F4:8 recombinant inbred lines developed from a cross between susceptible variety, Williams 82 and foxglove aphid resistance wild soybean, PI 366121 were used. The two type of resistance response, antibiosis and antixenosis resistance were evaluated through choice and no-choice test, graded by the degree of total plant damage and primary infestation leaf damage; a genome-wide molecular linkage map was constructed with 29,898 single-nucleotide polymorphism markers utilizing a Axiom(R) 180K soyaSNP array. Using inclusive composite interval mapping analysis for foxglove aphid resistance, one major candidate QTL on chromosome 7 was identified. The major QTL on chromosome 7 showed both antixenosis and antibiosis resistance responses. The newly identified major QTL was consistent with previously reported QTL, Raso2, which showed around 5 times narrow down interval range with 8 candidate genes. Furthermore, total 1,115 soybean varieties including Glycine soja and Glycine max were exposed to germplasm screening, and 31 varieties, which showed significant antibiosis type foxglove aphid resistance were identified. This result could be useful in breeding for new foxglove aphid resistant soybean cultivars and developing novel insecticides.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.11
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• pp.1540-1549
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• 2017

Objective: Increasing food safety demands in the animal product market have created a need for a system to trace the food distribution process, from the manufacturer to the retailer, and genetic traceability is an effective method to trace the origin of animal products. In this study, we successfully achieved the farm tracing of 6,018 multi-breed pigs, using single nucleotide polymorphism (SNP) markers strictly selected through least absolute shrinkage and selection operator (LASSO) feature selection. Methods: We performed farm tracing of domesticated pig (Sus scrofa) from SNP markers and selected the most relevant features for accurate prediction. Considering multi-breed composition of our data, we performed feature selection using LASSO penalization on 4,002 SNPs that are shared between breeds, which also includes 179 SNPs with small between-breed difference. The 100 highest-scored features were extracted from iterative simulations and then evaluated using machine-leaning based classifiers. Results: We selected 1,341 SNPs from over 45,000 SNPs through iterative LASSO feature selection, to minimize between-breed differences. We subsequently selected 100 highest-scored SNPs from iterative scoring, and observed high statistical measures in classification of breeding farms by cross-validation only using these SNPs. Conclusion: The study represents a successful application of LASSO feature selection on multi-breed pig SNP data to trace the farm information, which provides a valuable method and possibility for further researches on genetic traceability.