We developed a novel software tool, EXCAVATOR, for the detection of copy number variants (CNVs) from whole-exome sequencing data. EXCAVATOR combines a three-step normalization procedure with a novel heterogeneous hidden Markov model algorithm and a calling method that classifies genomic regions into five copy number states. We validate EXCAVATOR on three datasets and compare the results with three other methods. These analyses show that EXCAVATOR outperforms the other methods and is therefore a valuable tool for the investigation of CNVs in largescale projects, as well as in clinical research and diagnostics. EXCAVATOR is freely available at http://sourceforge.net/projects/excavatortool/.
Structural variants are genomic rearrangements larger than 50 bp accounting for around 1% of the variation among human genomes. They impact on phenotypic diversity and play a role in various diseases including neurological/neurocognitive disorders and cancer development and progression. Dissecting structural variants from next-generation sequencing data presents several challenges and a number of approaches have been proposed in the literature. In this mini review, we describe and summarize the latest tools – and their underlying algorithms – designed for the analysis of whole-genome sequencing, whole-exome sequencing, custom captures, and amplicon sequencing data, pointing out the major advantages/drawbacks. We also report a summary of the most recent applications of third-generation sequencing platforms. This assessment provides a guided indication – with particular emphasis on human genetics and copy number variants – for researchers involved in the investigation of these genomic events.
Copy Number Variants (CNVs) are structural rearrangements contributing to phenotypic variation that have been proved to be associated with many disease states. Over the last years, the identification of CNVs from whole-exome sequencing (WES) data has become a common practice for research and clinical purpose and, consequently, the demand for more and more efficient and accurate methods has increased. In this paper, we demonstrate that more than 30% of WES data map outside the targeted regions and that these reads, usually discarded, can be exploited to enhance the identification of CNVs from WES experiments. Here, we present EXCAVATOR2, the first read count based tool that exploits all the reads produced by WES experiments to detect CNVs with a genome-wide resolution. To evaluate the performance of our novel tool we use it for analysing two WES data sets, a population data set sequenced by the 1000 Genomes Project and a tumor data set made of bladder cancer samples. The results obtained from these analyses demonstrate that EXCAVATOR2 outperforms other four state-of-the-art methods and that our combined approach enlarge the spectrum of detectable CNVs from WES data with an unprecedented resolution. EXCAVATOR2 is freely available at http://sourceforge.net/projects/excavator2tool/.
SUMMARYBackgroundBilateral perisylvian polymicrogyria (BPP), the most common form of regional polymicrogyria, causes the congenital bilateral perisylvian syndrome, featuring oromotor dysfunction, cognitive impairment and epilepsy. BPP is etiologically heterogeneous, but only a few genetic causes have been reported. The aim of this study was to identify additional genetic etiologies of BPP and delineate their frequency in this patient population.MethodsWe performed child-parent (trio)-based whole exome sequencing (WES) on eight children with BPP. Following the identification of mosaic PIK3R2 mutations in two of these eight children, we performed targeted screening of PIK3R2 in a cohort of 118 children with BPP who were ascertained from 1980 until 2015 using two methods. First, we performed targeted sequencing of the entire PIK3R2 gene by single molecule molecular inversion probes (smMIPs) on 38 patients with BPP with normal-large head size. Second, we performed amplicon sequencing of the recurrent PIK3R2 mutation (p.Gly373Arg) on 80 children with various types of polymicrogyria including BPP. One additional patient underwent clinical WES independently, and was included in this study given the phenotypic similarity to our cohort. All patients included in this study were children (< 18 years of age) with polymicrogyria enrolled in our research program.FindingsUsing WES, we identified a mosaic mutation (p.Gly373Arg) in the regulatory subunit of the PI3K-AKT-MTOR pathway, PIK3R2, in two children with BPP. Of the 38 patients with BPP and normal-large head size who underwent targeted next generation sequencing by smMIPs, we identified constitutional and mosaic PIK3R2 mutations in 17 additional children. In parallel, one patient was found to have the recurrent PIK3R2 mutation by clinical WES. Seven patients had BPP alone, and 13 had BPP in association with features of the megalencephaly-polymicrogyria-polydactyly-hydrocephalus syndrome (MPPH). Nineteen patients had the same mutation (Gly373Arg), and one had a nearby missense mutation (p.Lys376Glu). Across the entire cohort, mutations were constitutional in 12 and mosaic in eight patients. Among mosaic patients, we observed substantial variation in alternate (mutant) allele levels ranging from 2·5% (10/377) to 36·7% (39/106) of reads, equivalent to 5–73·4% of cells analyzed. Levels of mosaicism varied from undetectable to 17·1% (37/216) of reads in blood-derived compared to 29·4% (2030/6889) to 43·3% (275/634) in saliva-derived DNA.InterpretationConstitutional and mosaic mutations in the PIK3R2 gene are associated with a spectrum of developmental brain disorders ranging from BPP with a normal head size to the megalencephaly-polymicrogyria-polydactyly-hydrocephalus syndrome. The phenotypic variability and low-level mosaicism challenging conventional molecular methods have important implications for genetic testing and counseling.
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