Dataset Information

Comparison of sequencing based CNV discovery methods using monozygotic twin quartets.

ABSTRACT:

Background

The advent of high throughput sequencing methods breeds an important amount of technical challenges. Among those is the one raised by the discovery of copy-number variations (CNVs) using whole-genome sequencing data. CNVs are genomic structural variations defined as a variation in the number of copies of a large genomic fragment, usually more than one kilobase. Here, we aim to compare different CNV calling methods in order to assess their ability to consistently identify CNVs by comparison of the calls in 9 quartets of identical twin pairs. The use of monozygotic twins provides a means of estimating the error rate of each algorithm by observing CNVs that are inconsistently called when considering the rules of Mendelian inheritance and the assumption of an identical genome between twins. The similarity between the calls from the different tools and the advantage of combining call sets were also considered.

Results

ERDS and CNVnator obtained the best performance when considering the inherited CNV rate with a mean of 0.74 and 0.70, respectively. Venn diagrams were generated to show the agreement between the different algorithms, before and after filtering out familial inconsistencies. This filtering revealed a high number of false positives for CNVer and Breakdancer. A low overall agreement between the methods suggested a high complementarity of the different tools when calling CNVs. The breakpoint sensitivity analysis indicated that CNVnator and ERDS achieved better resolution of CNV borders than the other tools. The highest inherited CNV rate was achieved through the intersection of these two tools (81%).

Conclusions

This study showed that ERDS and CNVnator provide good performance on whole genome sequencing data with respect to CNV consistency across families, CNV breakpoint resolution and CNV call specificity. The intersection of the calls from the two tools would be valuable for CNV genotyping pipelines.

SUBMITTER: Legault MA

PROVIDER: S-EPMC4374778 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Publications

Comparison of sequencing based CNV discovery methods using monozygotic twin quartets.

Legault Marc-André MA Girard Simon S Lemieux Perreault Louis-Philippe LP Rouleau Guy A GA Dubé Marie-Pierre MP

PloS one 20150326 3

<h4>Background</h4>The advent of high throughput sequencing methods breeds an important amount of technical challenges. Among those is the one raised by the discovery of copy-number variations (CNVs) using whole-genome sequencing data. CNVs are genomic structural variations defined as a variation in the number of copies of a large genomic fragment, usually more than one kilobase. Here, we aim to compare different CNV calling methods in order to assess their ability to consistently identify CNVs ...[more]

PMID: 25812131

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Project description:Objective:We used data from twins and their families to probe the genetic factors contributing to microtia-atresia, in particular, early post-twinning variations that potentially account for the discordant phenotypes of monozygotic twin pairs. Methods:Six families of monozygotic twins discordant for congenital microtia-atresia were recruited for study. The six patients shared a consistent clinical phenotype of unilateral microtia-atresia. Whole-exome sequencing (WES) was performed for all six twin pairs and their parents. Family segregation and multiple bioinformatics methods were applied to identify suspicious mutations in all families. Recurring mutations commonly detected in at least two families were highlighted. All variants were validated via Sanger sequencing. Gene Ontology (GO) analysis was performed to identify candidate gene sets and related pathways. Copy number variation (CNV), linkage analysis, association analysis and machine learning methods were additionally applied to isolate candidate mutations, and comparative genomics and structural modeling tools used to evaluate their potential roles in onset of microtia-atresia. Results:Our analyses revealed 61 genes with suspected mutations associated with microtia-atresia. Five (HOXA4, MUC6, CHST15, TBX10, and AMER1) contained 7 de novo mutations that appeared in at least two families, which have been previously reported as pathogenic for other diseases. Among these, HOXA4 (c.920A>C, p.H307P) was determined as the most likely pathogenic variant for microtia-atresia. GO analysis revealed four gene sets involving 11 pathways potentially related to underlying pathogenesis of the disease. CNVs in three genes (UGT2B17, OVOS, and KATNAL2) were detected in at least two families. Linkage analysis disclosed 13 extra markers for the disease, of which two (FGFR1 and EYA1) were validated via machine learning analysis as plausible candidate genes for the disease. Conclusion:Based on comprehensive genetic and bioinformatic analyses of WES data from six families of discordant monozygotic twins with microtia-atresia, we identified multiple candidate genes that may function in post-twinning onset of the disease. The collective findings provide novel insights into the pathogenesis of congenital microtia-atresia.

Dataset Information

Comparison of sequencing based CNV discovery methods using monozygotic twin quartets.

Background

Results

Conclusions

Publications

Comparison of sequencing based CNV discovery methods using monozygotic twin quartets.

Similar Datasets

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