Copy number variations and cancer

DNA copy number variations (CNVs) are an important component of genetic variation, affecting a greater fraction of the genome than single nucleotide polymorphisms (SNPs). The advent of high-resolution SNP arrays has made it possible to identify CNVs. Characterization of widespread constitutional (germline) CNVs has provided insight into their role in susceptibility to a wide spectrum of diseases, and somatic CNVs can be used to identify regions of the genome involved in disease phenotypes. The role of CNVs as risk factors for cancer is currently underappreciated. However, the genomic instability and structural dynamism that characterize cancer cells would seem to make this form of genetic variation particularly intriguing to study in cancer. Here, we provide a detailed overview of the current understanding of the CNVs that arise in the human genome and explore the emerging literature that reveals associations of both constitutional and somatic CNVs with a wide variety of human cancers

New Copy Number Variations in Schizophrenia

Genome-wide screenings for copy number variations (CNVs) in patients with schizophrenia have demonstrated the presence of several CNVs that increase the risk of developing the disease and a growing number of large rare CNVs; the contribution of these rare CNVs to schizophrenia remains unknown. Using Affymetrix 6.0 arrays, we undertook a systematic search for CNVs in 172 patients with schizophrenia and 160 healthy controls, all of Italian origin, with the aim of confirming previously identified loci and identifying novel schizophrenia susceptibility genes. We found five patients with a CNV occurring in one of the regions most convincingly implicated as risk factors for schizophrenia: NRXN1 and the 16p13.1 regions were found to be deleted in single patients and 15q11.2 in 2 patients, whereas the 15q13.3 region was duplicated in one patient. Furthermore, we found three distinct patients with CNVs in 2q12.2, 3q29 and 17p12 loci, respectively. These loci were previously reported to be deleted or duplicated in patients with schizophrenia but were never formally associated with the disease. We found 5 large CNVs (>900 kb) in 4q32, 5q14.3, 8q23.3, 11q25 and 17q12 in five different patients that could include some new candidate schizophrenia susceptibility genes. In conclusion, the identification of previously reported CNVs and of new, rare, large CNVs further supports a model of schizophrenia that includes the effect of multiple, rare, highly penetrant variants

Copy number variations and constitutional chromothripsis (Review)

Both copy number variations (CNVs) and chromothripsis are phenomena that involve complex genomic rearrangements. Chromothripsis results in CNVs and other structural changes. CNVs are frequently observed in the human genome. Studies on CNVs have been increasing exponentially; the Database of Genomic Variants shows an increase in the number of data published on structural variations added to the database in the last 15 years. CNVs may be a result of replicative and non-replicative mechanisms, and are hypothesized to serve important roles in human health and disease. Chromothripsis is a phenomena of chromosomal rearrangement following chromosomal breaks at multiple locations and involves impaired DNA repair. In 2011, Stephens et al coined the term chromothripsis for this type of fragmenting event. Several proposed mechanisms have been suggested to underlie chromothripsis, such as p53 inactivation, micronuclei formation, abortive apoptosis and telomere fusions in telomere crisis. Chromothripsis gives rise to normal or abnormal phenotypes. In this review, constitutional chromothripsis, which may coexist with multiple de novo CNVs are described and discussed. This reviews aims to summarize recent advances in our understanding of CNVs and chromothripsis, and describe the effects of these phenomena on human health and birth defects.publishersversionpublishe

Clinical Interpretation of Novel Copy Number Variations

Copy Number Variations: CNVs) are a significant source of human genetic diversity and are believed to be responsible for a wide variety of phenotypic variation. Recent advances in microarray-based genomic hybridization techniques have facilitated CNV analysis as a viable diagnostic technique in the clinic, and several public databases of well-characterized CNVs are being compiled, but a standard for interpreting uncharacterized CNVs has yet to emerge. This thesis examines the clinical interpretation of uncharacterized CNVs as a multiple instance binary classification problem. We analyze the current state of clinical techniques, then present and test several novel statistical approaches to the problem

Genomic characteristics of cattle copy number variations

<p>Abstract</p> <p>Background</p> <p>Copy number variation (CNV) represents another important source of genetic variation complementary to single nucleotide polymorphism (SNP). High-density SNP array data have been routinely used to detect human CNVs, many of which have significant functional effects on gene expression and human diseases. In the dairy industry, a large quantity of SNP genotyping results are becoming available and can be used for CNV discovery to understand and accelerate genetic improvement for complex traits.</p> <p>Results</p> <p>We performed a systematic analysis of CNV using the Bovine HapMap SNP genotyping data, including 539 animals of 21 modern cattle breeds and 6 outgroups. After correcting genomic waves and considering the pedigree information, we identified 682 candidate CNV regions, which represent 139.8 megabases (~4.60%) of the genome. Selected CNVs were further experimentally validated and we found that copy number "gain" CNVs were predominantly clustered in tandem rather than existing as interspersed duplications. Many CNV regions (~56%) overlap with cattle genes (1,263), which are significantly enriched for immunity, lactation, reproduction and rumination. The overlap of this new dataset and other published CNV studies was less than 40%; however, our discovery of large, high frequency (> 5% of animals surveyed) CNV regions showed 90% agreement with other studies. These results highlight the differences and commonalities between technical platforms.</p> <p>Conclusions</p> <p>We present a comprehensive genomic analysis of cattle CNVs derived from SNP data which will be a valuable genomic variation resource. Combined with SNP detection assays, gene-containing CNV regions may help identify genes undergoing artificial selection in domesticated animals.</p