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Project description:Detection of genomic copy number variations induced by multiple DNA breaks
| PRJNA354382 | ENA
Project description:BackgroundCopy 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.ResultsWe 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.ConclusionsWe 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.
| S-EPMC3053260 | biostudies-literature
Project description:BackgroundCopy number variations (CNVs) can create new genes, change gene dosage, reshape gene structures, and modify elements regulating gene expression. As with all types of genetic variation, CNVs may influence phenotypic variation and gene expression. CNVs are thus considered major sources of genetic variation. Little is known, however, about their contribution to genetic variation in rice.ResultsTo detect CNVs, we used a set of NimbleGen whole-genome comparative genomic hybridization arrays containing 718,256 oligonucleotide probes with a median probe spacing of 500 bp. We compiled a high-resolution map of CNVs in the rice genome, showing 641 CNVs between the genomes of the rice cultivars 'Nipponbare' (from O. sativa ssp. japonica) and 'Guang-lu-ai 4' (from O. sativa ssp. indica). The CNVs identified vary in size from 1.1 kb to 180.7 kb, and encompass approximately 7.6 Mb of the rice genome. The largest regions showing copy gain and loss are of 37.4 kb on chromosome 4, and 180.7 kb on chromosome 8. In addition, 85 DNA segments were identified, including some genic sequences. Contracted genes greatly outnumbered duplicated ones. Many of the contracted genes corresponded to either the same genes or genes involved in the same biological processes; this was also the case for genes involved in disease and defense.ConclusionWe detected CNVs in rice by array-based comparative genomic hybridization. These CNVs contain known genes. Further discussion of CNVs is important, as they are linked to variation among rice varieties, and are likely to contribute to subspecific characteristics.
| S-EPMC3156786 | biostudies-literature
Project description:Genomic copy number variations (CNVs) are considered as a significant source of genetic diversity and widely involved in gene expression and regulatory mechanism, genetic disorders and disease risk, susceptibility to certain diseases and conditions, and resistance to medical drugs. Many studies have targeted the identification, profiling, analysis, and associations of genetic CNVs. We propose herein two new fuzzy methods, taht is, one based on the fuzzy inference from the pre-processed input, and another based on fuzzy C-means clustering. Our solutions present a higher true positive rate and a lower false negative with no false positive, efficient performance and consumption of least resources.
| S-EPMC7714972 | biostudies-literature
Project description:Human genome contains many variations, often called mutations, which are difficult to detect and have remained a challenge for years. A substantial part of the genome encompasses repeats and when such repeats are in the coding region they may lead to change in the gene expression profile followed by pathological conditions. Structural variants are alterations which change one or more sequence feature in the chromosome such as change in the copy number, rearrangements, and translocations of a sequence and can be balanced or unbalanced. Copy number variants (CNVs) may increase or decrease the copies of a given region and have a pivotal role in the onset of many diseases including cardiovascular disorders. Cardiovascular disorders have a magnitude of well-established risk factors and etiology, but their correlation with CNVs is still being studied. In this article, we have discussed history of CNVs and a summary on the diseases associated with CNVs. To detect such variations, we shed light on the number of techniques introduced so far and their limitations. The lack of studies on cardiovascular diseases to determine the frequency of such variants needs clinical studies with larger cohorts. This review is a compilation of articles suggesting the importance of CNVs in multitude of cardiovascular anomalies. Finally, future perspectives for better understanding of CNVs and cardiovascular disorders have also been discussed.
| S-EPMC6291864 | biostudies-other
Project description:Copy Number Variations in Genomic Disorders
| PRJNA75521 | ENA
Project description:Copy number variations (CNVs) can create new genes, change gene dosage, reshape gene structures, and modify elements regulating gene expression. As with all types of genetic variation, CNVs may influence phenotypic variation and gene expression. CNVs are thus considered major sources of genetic variation. Little is known, however, about their contribution to genetic variation in rice. To detect CNVs, we used a set of NimbleGen whole-genome comparative genomic hybridization arrays containing 715,851 oligonucleotide probes with a median probe spacing of 500 bp. We compiled a high-resolution map of CNVs in the rice genome, showing 641 CNVs between the genomes of the rice cultivars ‘Nipponbare’ (from O. sativa ssp. japonica) and ‘Guang-lu-ai 4’ (from O. sativa ssp. indica). These CNVs contain some known genes. They are linked to variation among rice varieties, and are likely to contribute to subspecific characteristics.
2012-07-01 | GSE30542 | GEO
Project description:Recent reports indicate that copy number variations (CNVs) within the human genome contribute to nucleotide diversity to a larger extent than single nucleotide polymorphisms (SNPs). In addition, the contribution of CNVs to human disease susceptibility may be greater than previously expected, although a complete understanding of the phenotypic consequences of CNVs is incomplete. We have recently reported a comprehensive view of CNVs among 270 HapMap samples using high-density SNP genotyping arrays and BAC array CGH. In this report, we describe a novel algorithm using Affymetrix GeneChip Human Mapping 500K Early Access (500K EA) arrays that identified 1203 CNVs ranging in size from 960 bp to 3.4 Mb. The algorithm consists of three steps: (1) Intensity pre-processing to improve the resolution between pairwise comparisons by directly estimating the allele-specific affinity as well as to reduce signal noise by incorporating probe and target sequence characteristics via an improved version of the Genomic Imbalance Map (GIM) algorithm; (2) CNV extraction using an adapted SW-ARRAY procedure to automatically and robustly detect candidate CNV regions; and (3) copy number inference in which all pairwise comparisons are summarized to more precisely define CNV boundaries and accurately estimate CNV copy number. Independent testing of a subset of CNVs by quantitative PCR and mass spectrometry demonstrated a >90% verification rate. The use of high-resolution oligonucleotide arrays relative to other methods may allow more precise boundary information to be extracted, thereby enabling a more accurate analysis of the relationship between CNVs and other genomic features.
| S-EPMC1665641 | biostudies-literature
Project description:BackgroundChanges in genomic copy number occur in many human diseases including cancer. Characterization of these changes is important for both basic understanding and diagnosis of these diseases. Microarrays have recently become the standard technique and are commercially available. However, it is useful to have an affordable technique to complement them.ResultsWe describe a novel polymerase chain reaction (PCR)-based technique, termed competitive genomic PCR (CGP). The main characteristic of CGP is that different adaptors are added to the sample and control genomic DNAs after appropriate restriction enzyme digestion. These adaptor-supplemented DNAs are subjected to competitive PCR using an adaptor-primer and a locus-specific primer. The amplified products are then separated according to size differences between the adaptors. CGP eliminates the tedious steps inherent in quantitative PCR and achieves moderate throughput. Assays with different X chromosome numbers showed that it can provide accurate quantification. High-resolution analysis of neuroblastoma cell lines around the MYCN locus revealed novel junctions for amplification, which were not detected by a commercial array.ConclusionCGP is a moderate throughput technique for analyzing changes in genomic copy numbers. Because CGP can measure any genomic locus using PCR primers, it is especially useful for detailed analysis of a genomic region of interest.
| S-EPMC1920520 | biostudies-literature
Project description:BackgroundApproximately 1% of normal tension glaucoma (NTG) cases are caused by TANK-binding kinase 1 (TBK1) gene duplications and triplications. However, the precise borders and orientation of these TBK1 gene copy number variations (CNVs) on chromosome 12 are unknown.MethodsWe determined the exact borders of TBK1 CNVs and the orientation of duplicated or triplicated DNA segments in 5 NTG patients with different TBK1 mutations using whole-genome sequencing.ResultsTandemly duplicated chromosome segments spanning the TBK1 gene were detected in 4 NTG patients, each with unique borders. Four of 5 CNVs had borders located within interspersed repetitive DNA sequences (Alu and long interspersed nuclear element-L1 elements), suggesting that mismatched homologous recombinations likely generated these CNVs. A fifth NTG patient had a complex rearrangement including triplication of a chromosome segment spanning the TBK1 gene.ConclusionsNo specific mutation hotspots for TBK1 CNVs were detected, however, interspersed repetitive sequences (ie, Alu elements) were identified at the borders of TBK1 CNVs, which suggest that mismatch of these elements during meiosis may be the mechanism that generated TBK1 gene dosage mutations.
| S-EPMC5716909 | biostudies-literature