• Genomics & Informatics
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• v.8 no.3
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• pp.122-130
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• 2010

Abnormal hematological values are associated with various disorders including cancer and cardiovascular, metabolic, infectious, and immune diseases. We report the copy number variations (CNVs) in clinically relevant hematological parameters, including hemoglobin level, red and white blood cell counts, platelet counts, and red blood cell (RBC) volume. We describe CNVs in several loci associated with these hematological parameters in 8,842 samples from Korean population-based studies. The data that we evaluated included four RBC parameters, one platelet parameter, and one associated with total white blood cell (WBC) count, exceeding the genome-wide significance. We show that CNVs in hematological parameters are associated with some loci, different from previously associated loci reported in single nucleotide polymorphism (SNP) association studies.

• Genomics & Informatics
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• v.14 no.4
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• pp.216-221
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• 2016

Osteoporotic fractures (OFs) are critical hard outcomes of osteoporosis and are characterized by decreased bone strength induced by low bone density and microarchitectural deterioration in bone tissue. Most OFs cause acute pain, hospitalization, immobilization, and slow recovery in patients and are associated with increased mortality. A variety of genetic studies have suggested associations of genetic variants with the risk of OF. Genome-wide association studies have reported various single-nucleotide polymorphisms and copy number variations (CNVs) in European and Asian populations. To identify CNV regions associated with OF risk, we conducted a genome-wide CNV study in a Korean population. We performed logistic regression analyses in 1,537 Korean subjects (299 OF cases and 1,238 healthy controls) and identified a total of 8 CNV regions significantly associated with OF (p < 0.05). Then, one CNV region located on chromosome 20q13.12 was selected for experimental validation. The selected CNV region was experimentally validated by quantitative polymerase chain reaction. The CNV region of chromosome 20q13.12 is positioned upstream of a family of long non-coding RNAs, LINC01260. Our findings could provide new information on the genetic factors associated with the risk of OF.

• Genomics & Informatics
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• v.12 no.1
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• pp.42-47
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• 2014

Asian populations contain a variety of ethnic groups that have ethnically specific genetic differences. Ethnic variants may be highly relevant in disease and human differentiation studies. Here, we identified ethnically specific variants and then investigated their distribution across Asian ethnic groups. We obtained 58,960 Pan-Asian single nucleotide polymorphisms of 1,953 individuals from 72 ethnic groups of 11 Asian countries. We selected 9,306 ethnic variant single nucleotide polymorphisms (ESNPs) and 5,167 ethnic variant copy number polymorphisms (ECNPs) using the nearest shrunken centroid method. We analyzed ESNPs and ECNPs in 3 hierarchical levels: superpopulation, subpopulation, and ethnic population. We also identified ESNP- and ECNP-related genes and their features. This study represents the first attempt to identify Asian ESNP and ECNP markers, which can be used to identify genetic differences and predict disease susceptibility and drug effectiveness in Asian ethnic populations.

• 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.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.4
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• pp.1851-1855
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• 2016

Tamoxifen is a pharmacological estrogen inhibitor that binds to the estrogen receptor (ER) in breast cells. However, it shows an estrogenic effect in other organs, which causes adverse drug reactions (ADRs). The sulfotransferase 1A1 (SULT1A1) enzyme encoded by the SULT1A1 gene is involved in estrogen metabolism. Previous research has suggested that the SULT1A1 copy number is linked with the plasma estradiol (E2) concentration. Here, a total of 34 premenopausal breast cancer patients, selected from the Thai Tamoxifen (TTAM) Project, were screened for their SULT1A1 copy number, plasma E2 concentration and ADRs. The mean age was $44.3{\pm}11.1years$, and they were subtyped as ER+/progesterone receptor (PR)+ (28 patients), ER+/PR- (5 patients) and ER-/PR- (1 patient). Three patients reported ADRs, which were irregular menstruation (2 patients) and vaginal discharge (1 patient). Most (33) patients had two SULT1A1 copies, with one patient having three copies. The median plasma E2 concentration was 1,575.6 (IQR 865.4) pg/ml. Patients with ADRs had significantly higher plasma E2 concentrations than those patients without ADRs (p = 0.014). The plasma E2 concentration was numerically higher in the patient with three SULT1A1 copies, but this lacked statistical significance.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.19-21
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• 2012

모든 암 세포는 체세포 변이를 동반한다. 따라서 암 유전체 변이 분석에 의하여 암을 발생시키는 유전자 및 진단/치료법을 찾아낼 수 있다. 본 연구에서는 차세대 시퀀싱 데이터를 이용하여 암 특이적 단이 반복 변이(copy number variation, CNV) 유형을 밝히는 새로운 알고리즘을 제안한다. 제안하는 방식은 암 환자의 정상 세포와 암세포로부터 얻어진 정상 유전체와 암 유전체를 동시 분석하여 각각 CNV 후보 영역을 추출하며, 통계적 유의성 분석을 통하여 암 특이적 CNV 후보 영역을 선별하고, 다음 후처리 과정에서 참조 표준 서열(reference sequence)에 존재하는 오류 영역 보정 작업을 수행하여 정확한 암 특이적 CNV 영역을 추출해 낸다. 또한 다수의 대용량 유전체 데이터 동시 분석을 위하여 맵리듀스(MapReduce) 기법을 기반으로 하는 병렬 수행 알고리즘을 제안한다.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.30 no.2
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• pp.205-212
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• 2008

Genetic variation in the human genome occurs on various levels; from the single nucleotide polymorphism to large, microscopically visible chromosome anomalies. It can be present in many forms, including variable number of tandem repeat (VNTRs; e.g., mini- and microsatellites), presence/absence of transposable elements (e.g., Alu elements), single nucleotide polymorphisms, and structural alterations (e.g., copy number variation, segmental duplication, inversion, translocation). Until recently SNPs were thought to be the main source of genetic and phenotypic human variation. However, the use of methods such as array comparative genomic hybridization (array CGH) and fluorescence in situ hybridization (FISH) have revealed the presence of copy number variations(CNVs) ranging from kilobases (kb) to megabases (Mb) in the human genome. There is great interest in the possibility that CNVs playa role in the etiology of common disease such as HIV-1/AIDS, diabetes, autoimmune disease, heart disease and cancer. The discovery of widespread copy number variation in human provides insights into genetic variability among populations and provides a foundation for studies of the contribution of CNVs to evolution and disease.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.12
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• pp.1809-1815
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• 2019

Objective: Copy number variations (CNVs) are a major source of genetic diversity complementary to single nucleotide polymorphism (SNP) in animals. The aim of the study was to perform a comprehensive genomic analysis of CNVs based on high density whole-genome SNP markers in Chinese Dongxiang spotted pigs. Methods: We used customized Affymetrix Axiom Pig1.4M array plates containing 1.4 million SNPs and the PennCNV algorithm to identify porcine CNVs on autosomes in Chinese Dongxiang spotted pigs. Then, the next generation sequence data was used to confirm the detected CNVs. Next, functional analysis was performed for gene contents in copy number variation regions (CNVRs). In addition, we compared the identified CNVRs with those reported ones and quantitative trait loci (QTL) in the pig QTL database. Results: We identified 871 putative CNVs belonging to 2,221 CNVRs on 17 autosomes. We further discarded CNVRs that were detected only in one individual, leaving us 166 CNVRs in total. The 166 CNVRs ranged from 2.89 kb to 617.53 kb with a mean value of 93.65 kb and a genome coverage of 15.55 Mb, corresponding to 0.58% of the pig genome. A total of 119 (71.69%) of the identified CNVRs were confirmed by next generation sequence data. Moreover, functional annotation showed that these CNVRs are involved in a variety of molecular functions. More than half (56.63%) of the CNVRs (n = 94) have been reported in previous studies, while 72 CNVRs are reported for the first time. In addition, 162 (97.59%) CNVRs were found to overlap with 2,765 previously reported QTLs affecting 378 phenotypic traits. Conclusion: The findings improve the catalog of pig CNVs and provide insights and novel molecular markers for further genetic analyses of Chinese indigenous pigs.

• Journal of KIISE:Databases
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• v.41 no.4
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• pp.249-255
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• 2014

Copy number variations(CNVs) are a recently recognized class of human structural variations and are associated with a variety of human diseases, including cancer. To find important cancer genes, researchers identify novel CNVs in patients with a particular cancer and analyze large amounts of genomic and clinical data. We present a tool called CNVDAT which is able to detect CNVs from NGS data and systematically analyze the genomic and clinical data associated with variations. CNVDAT consists of two modules, CNV Detection Engine and Sequence Analyser. CNV Detection Engine extracts CNVs by using the multi-resolution system of scale-space filtering, enabling the detection of the types and the exact locations of CNVs of all sizes even when the coverage level of read data is low. Sequence Analyser is a user-friendly program to view and compare variation regions between tumor and matched normal samples. It also provides a complete analysis function of refGene and OMIM data and makes it possible to discover CNV-gene-phenotype relationships. CNVDAT source code is freely available from http://dblab.hallym.ac.kr/CNVDAT/.

• Genomics & Informatics
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• v.10 no.2
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• pp.81-87
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• 2012

Large-scale copy number variants (CNVs) in the human provide the raw material for delineating population differences, as natural selection may have affected at least some of the CNVs thus far discovered. Although the examination of relatively large numbers of specific ethnic groups has recently started in regard to inter-ethnic group differences in CNVs, identifying and understanding particular instances of natural selection have not been performed. The traditional $F_{ST}$ measure, obtained from differences in allele frequencies between populations, has been used to identify CNVs loci subject to geographically varying selection. Here, we review advances and the application of multinomial-Dirichlet likelihood methods of inference for identifying genome regions that have been subject to natural selection with the $F_{ST}$ estimates. The contents of presentation are not new; however, this review clarifies how the application of the methods to CNV data, which remains largely unexplored, is possible. A hierarchical Bayesian method, which is implemented via Markov Chain Monte Carlo, estimates locus-specific $F_{ST}$ and can identify outlying CNVs loci with large values of FST. By applying this Bayesian method to the publicly available CNV data, we identified the CNV loci that show signals of natural selection, which may elucidate the genetic basis of human disease and diversity.