• The KIPS Transactions:PartD
• /
• v.18D no.2
• /
• pp.89-100
• /
• 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-Australasian Journal of Animal Sciences
• /
• v.27 no.12
• /
• pp.1691-1694
• /
• 2014

Copy number variation (CNV) or single nucleotide phlyorphism (SNP) is useful genetic resource to aid in understanding complex phenotypes or deseases susceptibility. Although thousands of CNVs and SNPs are currently avaliable in the public databases, they are somewhat difficult to use for analyses without visualization tools. We developed a web-based tool called the VCS (visualization of CNV or SNP) to visualize the CNV or SNP detected. The VCS tool can assist to easily interpret a biological meaning from the numerical value of CNV and SNP. The VCS provides six visualization tools: i) the enrichment of genome contents in CNV; ii) the physical distribution of CNV or SNP on chromosomes; iii) the distribution of log2 ratio of CNVs with criteria of interested; iv) the number of CNV or SNP per binning unit; v) the distribution of homozygosity of SNP genotype; and vi) cytomap of genes within CNV or SNP region.

• Genomics & Informatics
• /
• v.12 no.4
• /
• pp.136-144
• /
• 2014

Besides single-nucleotide variants in the human genome, large-scale genomic variants, such as copy number variations (CNVs), are being increasingly discovered as a genetic source of human diversity and the pathogenic factors of diseases. Recent experimental findings have shed light on the links between different genome architectures and CNV mutagenesis. In this review, we summarize various genomic features and discuss their contributions to CNV formation. Genomic repeats, including both low-copy and high-copy repeats, play important roles in CNV instability, which was initially known as DNA recombination events. Furthermore, it has been found that human genomic repeats can also induce DNA replication errors and consequently result in CNV mutations. Some recent studies showed that DNA replication timing, which reflects the high-order information of genomic organization, is involved in human CNV mutations. Our review highlights that genome architecture, from DNA sequence to high-order genomic organization, is an important molecular factor in CNV mutagenesis and human genomic instability.

• Genomics & Informatics
• /
• v.6 no.1
• /
• pp.1-7
• /
• 2008

The widespread presence of large-scale genomic variations, termed copy number variation (CNVs), has been recently recognized in phenotypically normal individuals. Judging by the growing number of reports on CNVs, it is now evident that these variants contribute significantly to genetic diversity in the human genome. Like single nucleotide polymorphisms (SNPs), CNVs are expected to serve as potential biomarkers for disease susceptibility or drug responses. However, the technical and practical concerns still remain to be tackled. In this review, we examine the current status of CNV DBs and research, including the ongoing efforts of CNV screening in the human genome. We also discuss the characteristics of platforms that are available at the moment and suggest the potential of CNVs in clinical research and application.

• Communications for Statistical Applications and Methods
• /
• v.16 no.6
• /
• pp.1037-1046
• /
• 2009

Copy number variations(CNVs) are known as one of the most important factors in susceptibility to genetic disorders because they affect expression levels of genes. In previous studies, pyrosequencing, mini-sequencing real-time polymerase chain reaction(PCR), invader assays and other techniques have been used to detect CNVs. However, the higher the copy number in a genome, the more difficult it is to resolve the copies, so a more accurate method for measuring CNVs and assigning genotype is needed. PCR followed by a quantitative oligonucleotide ligation assay(qOLA) was developed for quantifying CNVs. The aim of this study was to compare the two methods for detecting and quantifying the CNVs of duplicated gene: the published pyrosequencing assay(pyro_CNV) and the newly developed qOLA_CNV. The accuracy and precision of the assay were evaluated for porcine KIT, which was selected as a model locus. Overall, the root mean squares(RMSs) of bias and standard deviation of qOLA_CNV were 2.09 and 0.45, respectively. These values are less than half of those of pyro CNV.

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

• The KIPS Transactions:PartD
• /
• v.16D no.5
• /
• pp.661-672
• /
• 2009

Recently it was found that various genetic structural variations such as CNV(copy number variation) exist in the human genome, and these variations are closely related with disease susceptibility, reaction to treatment, and genetic characteristics. In this paper we propose a new CNV detection algorithm using millions of short DNA sequences generated by giga-sequencing technology. Our method maps the DNA sequences onto the reference sequence, and obtains the occurrence frequency of each read in the reference sequence. And then it detects the statistically significant regions which are longer than 1Kbp as the candidate CNV regions by analyzing the distribution of the occurrence frequency. To select a proper read alignment method, several methods are employed in our algorithm, and the performances are compared. To verify the superiority of our approach, we performed extensive experiments. The result of simulation experiments (using a reference sequence, build 35 of NCBI) revealed that our approach successfully finds all the CNV regions that have various shapes and arbitrary length (small, intermediate, or large size).

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

• Journal of Genetic Medicine
• /
• v.20 no.2
• /
• pp.46-51
• /
• 2023

Exonic copy number variation (CNV), involving deletions and duplications at the gene's exon level, presents challenges in detection due to their variable impact on gene function. The study delves into the complexities of identifying large CNVs and investigates less familiar but recurrent exonic CNVs, notably enriched in East Asian populations. Examining specific cases like DRC1, STX16, LAMA2, and CFTR highlights the clinical implications and prevalence of exonic CNVs in diverse populations. The review addresses diagnostic challenges, particularly for single exon alterations, advocating for a strategic, multi-method approach. Diagnostic methods, including multiplex ligation-dependent probe amplification, droplet digital PCR, and CNV screening using next-generation sequencing data, are discussed, with whole genome sequencing emerging as a powerful tool. The study underscores the crucial role of ethnic considerations in understanding specific CNV prevalence and ongoing efforts to unravel subtle variations. The ultimate goal is to advance rare disease diagnosis and treatment through ethnically-specific therapeutic interventions.

• Asian-Australasian Journal of Animal Sciences
• /
• v.33 no.9
• /
• pp.1378-1386
• /
• 2020

Objective: Chinese indigenous sheep breeds can be classified into the following three categories by their tail morphology: fat-tailed, fat-rumped and thin-tailed sheep. The typical sheep breeds corresponding to fat-tailed, fat-rumped, and thin-tailed sheep are large-tailed Han, Altay, and Tibetan sheep, respectively. Detection of copy number variation (CNV) and selection signatures provides information on the genetic mechanisms underlying the phenotypic differences of the different sheep types. Methods: In this study, PennCNV software and F-statistics (F_ST) were implemented to detect CNV and selection signatures, respectively, on the X chromosome in three Chinese indigenous sheep breeds using ovine high-density 600K single nucleotide polymorphism arrays. Results: In large-tailed Han, Altay, and Tibetan sheep, respectively, a total of six, four and 22 CNV regions (CNVRs) with lengths of 1.23, 0.93, and 7.02 Mb were identified on the X chromosome. In addition, 49, 34, and 55 candidate selection regions with respective lengths of 27.49, 16.47, and 25.42 Mb were identified in large-tailed Han, Altay, and Tibetan sheep, respectively. The bioinformatics analysis results indicated several genes in these regions were associated with fat, including dehydrogenase/reductase X-linked, calcium voltage-gated channel subunit alpha1 F, and patatin like phospholipase domain containing 4. In addition, three other genes were identified from this analysis: the family with sequence similarity 58 member A gene was associated with energy metabolism, the serine/arginine-rich protein specific kinase 3 gene was associated with skeletal muscle development, and the interleukin 2 receptor subunit gamma gene was associated with the immune system. Conclusion: The results of this study indicated CNVRs and selection regions on the X chromosome of Chinese indigenous sheep contained several genes associated with various heritable traits.