Biological relevance of CNV calling methods using familial relatedness including monozygotic twins

Abstract

BackgroundStudies involving the analysis of structural variation including Copy Number Variation (CNV) have recently exploded in the literature. Furthermore, CNVs have been associated with a number of complex diseases and neurodevelopmental disorders. Common methods for CNV detection use SNP, CNV, or CGH arrays, where the signal intensities of consecutive probes are used to define the number of copies associated with a given genomic region. These practices pose a number of challenges that interfere with the ability of available methods to accurately call CNVs. It has, therefore, become necessary to develop experimental protocols to test the reliability of CNV calling methods from microarray data so that researchers can properly discriminate biologically relevant data from noise.ResultsWe have developed a workflow for the integration of data from multiple CNV calling algorithms using the same array results. It uses four CNV calling programs: PennCNV (PC), Affymetrix® Genotyping Console™ (AGC), Partek® Genomics Suite™ (PGS) and Golden Helix SVS™ (GH) to analyze CEL files from the Affymetrix® Human SNP 6.0 Array™. To assess the relative suitability of each program, we used individuals of known genetic relationships. We found significant differences in CNV calls obtained by different CNV calling programs.ConclusionsAlthough the programs showed variable patterns of CNVs in the same individuals, their distribution in individuals of different degrees of genetic relatedness has allowed us to offer two suggestions. The first involves the use of multiple algorithms for the detection of the largest possible number of CNVs, and the second suggests the use of PennCNV over all other methods when the use of only one software program is desirable.

Clinical interpretation of CNVs with cross-species phenotype data

“…The number of CNVs per individual is estimated between 20 and 100 1 2. We performed a benchmark test, where we chose a pathogenic CNV together with the associated HPO terms according to the criteria described below.…”

“…Methods such as array comparative genomic hybridisation, SNP genotyping array and genome sequencing enable the genome-wide detection of structural variants. The typical landscape of CNVs in a patient shows from 20 to over 100 duplications and deletions,1 2 most of which are relatively small in size, while a few CNVs cover longer regions of the genome. Each CNV can either represent neutral polymorphic variation or convey clinical phenotypes by inducing gene dosage effects or dysregulation of genes 3.…”

A Genome-Wide Association Study to Identify Potential Germline Copy Number Variants for Sporadic Breast Cancer Susceptibility

“…However, we refrained from such assumptions, and as such many of the identified CNVs in our study or their potential concordances may have been underestimated in our analysis. This is true of any algorithm comparisons implemented thus far for CNV association analysis, as acknowledged by others [Grayson and Aune, 2011;Lin et al, 2011;Zhang et al, 2011;Cantsilieris et al, 2014;Castellani et al, 2014].…”

“…We therefore made a systematic effort to compare signatures based on criteria of concordances of CNV calls between algorithms (described above). Previous investigators used an arbitrary cut-off of 25-50% of overlap of the sequence as a criterion for concordance [Lin et al, 2011;Zhang et al, 2011;Castellani et al, 2014]. However, we defined concordance as 100% overlap of CNV regions to be on the more stringent side to accommodate the mismatch of default parameters for segmentation by individual algorithms.…”

Detecção de microdeleções do cromossomo Y em pacientes inférteis, comparando os resultados obtidos pelas técnicas de PCR e MLPA

“…Em algumas vezes, por efeito de posição, podem predispor à ocorrência de alterações deletérias. Por isso, estão sendo bastante estudadas na busca das causas de diversas patologias (Castellani et al, 2014 A MLPA pode ser utilizada para a detecção de microdeleções no cromossomo Y atualmente apenas em pesquisa. Ela detecta além das deleções, as duplicações e rearranjos complexos (Saito et al, 2015).…”