Automated prediction of the clinical impact of structural copy number variations.
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ABSTRACT:
SUBMITTER: Gaziova M
PROVIDER: S-EPMC8752772 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Clinical interpretation of copy number variants (CNVs) is a complex process that requires skilled clinical professionals. General recommendations have been recently released to guide the CNV interpretation based on predefined criteria to uniform the decision process. Several semiautomatic computational methods have been proposed to recommend appropriate choices, relieving clinicians of tedious searching in vast genomic databases. We have developed and evaluated such a tool called MarCNV and tested it on CNV records collected from the ClinVar database. Alternatively, the emerging machine learning-based tools, such as the recently published ISV (Interpretation of Structural Variants), showed promising ways of even fully automated predictions using broader characterization of affected genomic elements. Such tools utilize features additional to ACMG criteria, thus providing supporting evidence and the potential to improve CNV classification. Since both approaches contribute to evaluation of CNVs clinical impact, we propose a combined solution in the form of a decision support tool based on automated ACMG guidelines (MarCNV) supplemented by a machine learning-based pathogenicity prediction (ISV) for the classification of CNVs. We provide evidence that such a combined approach is able to reduce the number of uncertain classifications and reveal potentially incorrect classifications using automated guidelines. CNV interpretation using MarCNV, ISV, and combined approach is available for non-commercial use at https://predict.genovisio.com/ .
| S-EPMC10310736 | biostudies-literature
Project description:Recent array-based studies have detected a wealth of copy number variations (CNVs) in patients with autism spectrum disorders (ASD). Since CNVs also occur in healthy individuals, their contributions to the patient's phenotype remain largely unclear. In a cohort of children with symptoms of ASD, diagnosis of the index patient using ADOS-G and ADI-R was performed, and the Social Responsiveness Scale (SRS) was administered to the index patients, both parents, and all available siblings. CNVs were identified using SNP arrays and confirmed by FISH or array CGH. To evaluate the clinical significance of CNVs, we analyzed three families with multiple affected children (multiplex) and six families with a single affected child (simplex) in which at least one child carried a CNV with a brain-transcribed gene. CNVs containing genes that participate in pathways previously implicated in ASD, such as the phosphoinositol signaling pathway (PIK3CA, GIRDIN), contactin-based networks of cell communication (CNTN6), and microcephalin (MCPH1) were found not to co-segregate with ASD phenotypes. In one family, a loss of CNTN5 co-segregated with disease. This indicates that most CNVs may by themselves not be sufficient to cause ASD, but still may contribute to the phenotype by additive or epistatic interactions with inherited (transmitted) mutations or non-genetic factors. Our study extends the scope of genome-wide CNV profiling beyond de novo CNVs in sporadic patients and may aid in uncovering missing heritability in genome-wide screening studies of complex psychiatric disorders.
| S-EPMC3215885 | biostudies-literature
Project description:Schizophrenia is a psychiatric disorder with onset in late adolescence and unclear etiology characterized by both positive and negative symptoms, as well as cognitive deficits. To identify copy number variations (CNVs) that increase the risk of schizophrenia, we performed a whole-genome CNV analysis on a cohort of 977 schizophrenia cases and 2,000 healthy adults of European ancestry who were genotyped with 1.7 million probes. Positive findings were evaluated in an independent cohort of 758 schizophrenia cases and 1,485 controls. The Gene Ontology synaptic transmission family of genes was notably enriched for CNVs in the cases (P = 1.5 x 10(-7)). Among these, CACNA1B and DOC2A, both calcium-signaling genes responsible for neuronal excitation, were deleted in 16 cases and duplicated in 10 cases, respectively. In addition, RET and RIT2, both ras-related genes important for neural crest development, were significantly affected by CNVs. RET deletion was exclusive to seven cases, and RIT2 deletions were overrepresented common variant CNVs in the schizophrenia cases. Our results suggest that novel variations involving the processes of synaptic transmission contribute to the genetic susceptibility of schizophrenia.
| S-EPMC2890845 | biostudies-literature
Project description:Copy-number variations (CNVs) are one of the widely dispersed forms of structural variations in mammalian genomes, and are present as deletions, insertions, or duplications. Only few studies have been conducted in goats on CNVs derived from SNP array data, and many local breeds still remain uncharacterized, e.g., the Sicilian goat dairy breeds. In this study, CNV detection was performed, starting from the genotypic data of 120 individuals, belonging to four local breeds (Argentata dell'Etna, Derivata di Siria, Girgentana, and Messinese), genotyped with the Illumina GoatSNP50 BeadChip array. Overall, 702 CNVs were identified in 107 individuals using PennCNV software based on the hidden Markov model algorithm. These were merged in 75 CNV regions (CNVRs), i.e., regions containing CNVs overlapped by at least 1 base pair, while 85 CNVs remained unique. The part of the genome covered by CNV events was 35.21 Mb (1.2% of the goat genome length). Functional annotation of the CNVRs allowed the identification of 139 genes/loci within the most frequent CNVRs that are involved in local adaptations, such as coat colour (ADAMTS20 and EDNRA), mild behaviour (NR3C2), immune response (EXOC3L4 and TNFAIP2), reproduction (GBP1 and GBP6), and olfactory receptors (OR7E24). This study provides insights into the genomic variations for these Sicilian dairy goat breeds and should be of value for future studies to identify the relationships between this type of genetic variation and phenotypic traits.
| S-EPMC7341319 | biostudies-literature
Project description:BackgroundGene copy number variations (CNVs) contribute to genetic diversity and disease prevalence across populations. Substantial efforts have been made to decipher the relationship between CNVs and pathogenesis but with limited success.ResultsWe have developed a novel computational framework X-CNV ( www.unimd.org/XCNV ), to predict the pathogenicity of CNVs by integrating more than 30 informative features such as allele frequency (AF), CNV length, CNV type, and some deleterious scores. Notably, over 14 million CNVs across various ethnic groups, covering nearly 93% of the human genome, were unified to calculate the AF. X-CNV, which yielded area under curve (AUC) values of 0.96 and 0.94 in training and validation sets, was demonstrated to outperform other available tools in terms of CNV pathogenicity prediction. A meta-voting prediction (MVP) score was developed to quantitively measure the pathogenic effect, which is based on the probabilistic value generated from the XGBoost algorithm. The proposed MVP score demonstrated a high discriminative power in determining pathogenetic CNVs for inherited traits/diseases in different ethnic groups.ConclusionsThe ability of the X-CNV framework to quantitatively prioritize functional, deleterious, and disease-causing CNV on a genome-wide basis outperformed current CNV-annotation tools and will have broad utility in population genetics, disease-association studies, and diagnostic screening.
| S-EPMC8375180 | biostudies-literature
Project description:Stroke is the third leading cause of death worldwide after heart disease and all forms of cancers. Monogenic disorders, genetic, and environmental risk factors contribute to damaging cerebral blood vessels and, consequently, cause stroke. Developments in genomic research led to the discovery of numerous copy number variants (CNVs) that have been recently identified as a new tool for understanding the genetic basis of many diseases. This review discusses the current understanding of the types of stroke, the existing knowledge on the involvement of specific CNVs in stroke as well as the limitations of the methods used for detecting CNVs like SNP-microarray. To confirm an unequivocally association between CNVs and stroke and extend the current findings, it would be desirable to use another methodology to detect smaller CNVs or CNVs in genomic regions poorly covered by this technique, for instance, CGH-array.
| S-EPMC5110597 | biostudies-literature
Project description:Copy number variation is a defining characteristic of human subtelomeres. Human subtelomeric segmental duplication regions ('Subtelomeric Repeats') comprise about 25% of the most distal 500 kb and 80% of the most distal 100 kb in human DNA. Huge allelic disparities seen in subtelomeric DNA sequence content and organization are postulated to have an impact on the dosage of transcripts embedded within the duplicated sequences, on the transcription of genes in adjacent single copy DNA regions, and on the chromatin structures mediating telomere functions including chromosome stability. In addition to the complex duplicon substructure and huge allelic variations in extended subtelomere regions, both copy number variation and alternative sequence organizations for DNA characterize the sequences immediately adjacent to terminal (TTAGGG)n tracts ('subterminal DNA'). The structural variation in subterminal DNA is likely to have important consequences for expression of subterminal transcripts such as a newly-discovered gene family encoding actin-interacting proteins and a non-coding telomeric repeat containing RNA (TERRA) transcript family critical for telomere integrity. Major immediate challenges include discovering the full extent and nature of subtelomeric structural and copy number variation in humans, and developing methods for tracking individual allelic variants in the context of total genomic DNA.
| S-EPMC2731494 | biostudies-literature
Project description:BackgroundCopy number variations (CNVs), which are important source for genetic and phenotypic variation, have been shown to be associated with disease as well as important QTLs, especially in domesticated animals. However, little is known about the CNVs in silkworm.ResultsIn this study, we have constructed the first CNVs map based on genome-wide analysis of CNVs in domesticated silkworm. Using next-generation sequencing as well as quantitative PCR (qPCR), we identified ~319 CNVs in total and almost half of them (~ 49%) were distributed on uncharacterized chromosome. The CNVs covered 10.8 Mb, which is about 2.3% of the entire silkworm genome. Furthermore, approximately 61% of CNVs directly overlapped with SDs in silkworm. The genes in CNVs are mainly related to reproduction, immunity, detoxification and signal recognition, which is consistent with the observations in mammals.ConclusionsAn initial CNVs map for silkworm has been described in this study. And this map provides new information for genetic variations in silkworm. Furthermore, the silkworm CNVs may play important roles in reproduction, immunity, detoxification and signal recognition. This study provided insight into the evolution of the silkworm genome and an invaluable resource for insect genomics research.
| S-EPMC3997817 | biostudies-literature
Project description:BackgroundCopy number variation (CNV), a complex genomic rearrangement, has been extensively studied in humans and other organisms. In plants, CNVs of several genes were found to be responsible for various important traits; however, the cause and consequence of CNVs remains largely unknown. Recently released next-generation sequencing (NGS) data provide an opportunity for a genome-wide study of CNVs in rice.ResultsHere, by an NGS-based approach, we generated a CNV map comprising 9,196 deletions compared to the reference genome 'Nipponbare'. Using Oryza glaberrima as the outgroup, 80% of the CNV events turned out to be insertions in Nipponbare. There were 2,806 annotated genes affected by these CNV events. We experimentally validated 28 functional CNV genes including OsMADS56, BPH14, OsDCL2b and OsMADS30, implying that CNVs might have contributed to phenotypic variations in rice. Most CNV genes were found to be located in non-co-linear positions by comparison to O. glaberrima. One of the origins of these non-co-linear genes was genomic duplications caused by transposon activity or double-strand break repair. Comprehensive analysis of mutation mechanisms suggested an abundance of CNVs formed by non-homologous end-joining and mobile element insertion.ConclusionsThis study showed the impact and origin of copy number variations in rice on a genomic scale.
| S-EPMC4812662 | biostudies-literature
Project description:Copy number variations (CNVs) are being used as genetic markers or functional candidates in gene-mapping studies. However, unlike single nucleotide polymorphism or microsatellite genotyping techniques, most CNV detection methods are limited to detecting total copy numbers, rather than copy number in each of the two homologous chromosomes. To address this issue, we developed a statistical framework for intensity-based CNV detection platforms using family data. Our algorithm identifies CNVs for a family simultaneously, thus avoiding the generation of calls with Mendelian inconsistency while maintaining the ability to detect de novo CNVs. Applications to simulated data and real data indicate that our method significantly improves both call rates and accuracy of boundary inference, compared to existing approaches. We further illustrate the use of Mendelian inheritance to infer SNP allele compositions in each of the two homologous chromosomes in CNV regions using real data. Finally, we applied our method to a set of families genotyped using both the Illumina HumanHap550 and Affymetrix genome-wide 5.0 arrays to demonstrate its performance on both inherited and de novo CNVs. In conclusion, our method produces accurate CNV calls, gives probabilistic estimates of CNV transmission and builds a solid foundation for the development of linkage and association tests utilizing CNVs.
| S-EPMC2588508 | biostudies-other