Integrative analysis of prognostic long non-coding RNAs with copy number variation in bladder cancer / 浙江大学学报（英文版）（B辑：生物医学和生物技术）

Copy number variations (CNVs), which can affect the role of long non-coding RNAs (lncRNAs), are important genetic changes seen in some malignant tumors. We analyzed lncRNAs with CNV to explore the relationship between lncRNAs and prognosis in bladder cancer (BLCA). Messenger RNA (mRNA) expression levels, DNA methylation, and DNA copy number data of 408 BLCA patients were subjected to integrative bioinformatics analysis. Cluster analysis was performed to obtain different subtypes and differently expressed lncRNAs and coding genes. Weighted gene co-expression network analysis (WGCNA) was performed to identify the co-expression gene and lncRNA modules. CNV-associated lncRNA data and their influence on cancer prognosis were assessed with Kaplan-Meier survival curve. Multi-omics integration analysis revealed five prognostic lncRNAs with CNV, namely

A Genome-Wide Study of Moyamoya-Type Cerebrovascular Disease in the Korean Population

OBJECTIVE: Structural genetic variation, including copy-number variation (CNV), constitutes a substantial fraction of total genetic variability, and the importance of structural variants in modulating susceptibility is increasingly being recognized. CNV can change biological function and contribute to pathophysiological conditions of human disease. Its relationship with common, complex human disease in particular is not fully understood. Here, we searched the human genome to identify copy number variants that predispose to moya-moya type cerebrovascular disease. METHODS: We retrospectively analyzed patients who had unilateral or bilateral steno-occlusive lesions at the cerebral artery from March, 2007, to September, 2009. For the 20 subjects, including patients with moyamoya type pathologies and three normal healthy controls, we divided the subjects into 4 groups : typical moyamoya (n=6), unilateral moyamoya (n=9), progression unilateral to typical moyamoya (n=2) and non-moyamoya (n=3). Fragmented DNA was hybridized on Human610Quad v1.0 DNA analysis BeadChips (Illumina). Data analysis was performed with GenomeStudio v2009.1, Genotyping 1.1.9, cnvPartition_v2.3.4 software. Overall call rates were more than 99.8%. RESULTS: In total, 1258 CNVs were identified across the whole genome. The average number of CNV was 45.55 per subject (CNV region was 45.4). The gain/loss of CNV was 52/249, having 4.7 fold higher frequencies in loss calls. The total CNV size was 904,657,868, and average size was 993,038. The largest portion of CNVs (613 calls) were 1M-10M in length. Interestingly, significant association between unilateral moyamoya disease (MMD) and progression of unilateral to typical moyamoya was observed. CONCLUSION: Significant association between unilateral MMD and progression of unilateral to typical moyamoya was observed. The finding was confirmed again with clustering analysis. These data demonstrate that certain CNV associate with moyamoya-type cerebrovascular disease.

Comparison of the Affymetrix SNP Array 5.0 and Oligoarray Platforms for Defining CNV

Together with single nucleotide polymorphism (SNP), copy number variations (CNV) are recognized to be the major component of human genetic diversity and used as a genetic marker in many disease association studies. Affymetrix Genome-wide SNP 5.0 is one of the commonly used SNP array platforms for SNP-GWAS as well as CNV analysis. However, there has been no report that validated the accuracy and reproducibility of CNVs identified by Affymetrix SNP array 5.0. In this study, we compared the characteristics of CNVs from the same set of genomic DNAs detected by three different array platforms; Affymetrix SNP array 5.0, Agilent 2X244K CNV array and NimbleGen 2.1M CNV array. In our analysis, Affymetrix SNP array 5.0 seems to detect CNVs in a reliable manner, which can be applied for association studies. However, for the purpose of defining CNVs in detail, Affymetrix Genome-wide SNP 5.0 might be relatively less ideal than NimbleGen 2.1M CNV array and Agilent 2X244K CNV array, which outperform Affymetrix array for defining the small-sized single copy variants. This result will help researchers to select a suitable array platform for CNV analysis.

Understanding of epigenetics and dna methylation

CGHscape: A Software Framework for the Detection and Visualization of Copy Number Alterations

The robust identification and comprehensive profiling of copy number alterations (CNAs) is highly challenging. The amount of data obtained from high-throughput technologies such as array-based comparative genomic hybridization is often too large and it is required to develop a comprehensive and versatile tool for the detection and visualization of CNAs in a genome-wide scale. With this respective, we introduce a software framework, CGHscape that was originally developed to explore the CNAs for the study of copy number variation (CNV) or tumor biology. As a standalone program, CGHscape can be easily installed and run in Microsoft Windows platform. With a user-friendly interface, CGHscape provides a method for data smoothing to cope with the intrinsic noise of array data and CNA detection based on SW-ARRAY algorithm. The analysis results can be demonstrated as log2 plots for individual chromosomes or genomic distribution of identified CNAs. With extended applicability, CGHscape can be used for the initial screening and visualization of CNAs facilitating the cataloguing and characterizing chromosomal alterations of a cohort of samples.

Copy Number Variations in the Human Genome: Potential Source for Individual Diversity and Disease Association Studies

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.

Copy Number Variations in the Human Genome: Potential Source for Individual Diversity and Disease Association Studies

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.