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Effect of Combining Multiple CNV Defining Algorithms on the Reliability of CNV Calls from SNP Genotyping Data.

ABSTRACT: In addition to single-nucleotide polymorphisms (SNP), copy number variation (CNV) is a major component of human genetic diversity. Among many whole-genome analysis platforms, SNP arrays have been commonly used for genomewide CNV discovery. Recently, a number of CNV defining algorithms from SNP genotyping data have been developed; however, due to the fundamental limitation of SNP genotyping data for the measurement of signal intensity, there are still concerns regarding the possibility of false discovery or low sensitivity for detecting CNVs. In this study, we aimed to verify the effect of combining multiple CNV calling algorithms and set up the most reliable pipeline for CNV calling with Affymetrix Genomewide SNP 5.0 data. For this purpose, we selected the 3 most commonly used algorithms for CNV segmentation from SNP genotyping data, PennCNV, QuantiSNP; and BirdSuite. After defining the CNV loci using the 3 different algorithms, we assessed how many of them overlapped with each other, and we also validated the CNVs by genomic quantitative PCR. Through this analysis, we proposed that for reliable CNV-based genomewide association study using SNP array data, CNV calls must be performed with at least 3 different algorithms and that the CNVs consistently called from more than 2 algorithms must be used for association analysis, because they are more reliable than the CNVs called from a single algorithm. Our result will be helpful to set up the CNV analysis protocols for Affymetrix Genomewide SNP 5.0 genotyping data.

SUBMITTER: Kim SY

PROVIDER: S-EPMC3492655 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature

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Effect of Combining Multiple CNV Defining Algorithms on the Reliability of CNV Calls from SNP Genotyping Data.

Kim Soon-Young SY Kim Ji-Hong JH Chung Yeun-Jun YJ

Genomics & informatics 20120928 3

In addition to single-nucleotide polymorphisms (SNP), copy number variation (CNV) is a major component of human genetic diversity. Among many whole-genome analysis platforms, SNP arrays have been commonly used for genomewide CNV discovery. Recently, a number of CNV defining algorithms from SNP genotyping data have been developed; however, due to the fundamental limitation of SNP genotyping data for the measurement of signal intensity, there are still concerns regarding the possibility of false d ...[more]

PMID: 23166530

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Project description:Gene expression analysis was performed on 30 Neuroblastomas to identify genes whose transcription is significantly altered by recurrent chromosomal alterations. Genomic copy number losses and gains had been delineated in the tumours using FISH and SNP arrays. We have identified genes significantly altered by 7 recurrent alterations: 1p, 3p, 4p, 10q and 11q loss, 2p and 17q gain, and genes co-amplified and over-expressed as a result of MYCN amplification. Subsequently, correlation of microarray data with survival and expression within rodent neuroblastomas were used to identify genes likely to be involved in the disease progression, and identified a significant excess of differentially expressed genes which correlated with survival within the minimally altered regions on 17q and 4p; Identifying genes whose expression is consistently altered by chromosomal gains or losses is an important step in defining genes of biological relevance in a wide variety of tumour types. However, additional criteria are needed to discriminate further among the large number of candidate genes identified. This is particularly true for neuroblastoma, where multiple genomic copy number changes of proven prognostic value exist. We have used Affymetrix microarrays and a combination of fluorescent in-situ hybridisation and single nucleotide polymorphism (SNP) microarrays to establish expression profiles and delineate copy number alterations in 30 primary neuroblastomas. Correlation of microarray data with patient survival and analysis of expression within rodent neuroblastoma cell lines were then used to further define genes likely to be involved in the disease process. Using this approach we identify >1000 genes within 8 recurrent genomic alterations (loss of 1p, 3p, 4p, 10q and 11q, 2p gain, 17q gain, and the MYCN amplicon) whose expression is consistently altered by copy number change. Of these, 84 correlate with patient survival, with the minimal regions of 17q gain and 4p loss being significantly enriched for such genes. Orthologues of all but one of these genes on 17q are overexpressed in rodent neuroblastoma cell lines. A significant excess of SNPs whose copy number correlates with survival is also observed on proximal 4p in stage 4 tumours, and we find that deletion of 4p is associated with improved outcome in an extended cohort of tumours. These results define the major impact of genomic copy number alterations upon transcription within neuroblastoma, and highlight genes on distal 17q and proximal 4p for downstream analyses. They also suggest that integration of discriminators such as survival and comparative gene expression with microarray data may be useful in the identification of critical genes within regions of loss or gain in many human cancers. Experiment Overall Design: Chromosomal gains and losses were delineated in Stage 4 neuroblastomas to facilitate, in combination with expression array data, the identification of genes within regions of gain and loss whose expression is significantly altered by copy number change.

Dataset Information

Effect of Combining Multiple CNV Defining Algorithms on the Reliability of CNV Calls from SNP Genotyping Data.

Publications

Effect of Combining Multiple CNV Defining Algorithms on the Reliability of CNV Calls from SNP Genotyping Data.

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