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Ataxia and oculomotor apraxia caused by a large-scale deletion in the senataxin gene.

Senataxin, an RNA/DNA helicase, is a key protein providing genome stability and one of the best characterized R-loop-binding factors playing an important role in transcription and DNA repair processes. Pathogenic SETX gene variants cause autosomal recessive spinocerebellar ataxia with axonal neuropathy (AOA2, MIM #606002) and autosomal dominant juvenile amyotrophic lateral sclerosis (ALS4, MIM #602433), rare neurodegenerative disorders characterized by juvenile onset of progressive cerebellar ataxia, axonal sensorimotor peripheral neuropathy, combined upper and lower motor neuron symptoms, and increased serum alpha-fetoprotein (AFP; specific for AOA2). We report two cases of adult patients presenting with cerebellar syndrome, scanned speech, and exercise intolerance which started in the second/third decade of life and were followed by muscle weakness and impaired gait coordination. Whole exome sequencing (WES) was performed to analyze single nucleotide and copy number variants. A decreased coverage of a genomic region of around 16 kb on chromosome 9 (chr9:132,295,852-132,311,876), suggesting a deletion encompassing 5 exons of the SETX gene (exons 11-15, NM_015046.7) was observed. This homozygous SETX (9q34.13) deletion leads to a frame shift and consequently truncation of the helicase domain in the protein. Loss-of-function variants in the SETX gene are known to be pathogenic. Statistical analysis of NGS data from the Polish population identified a few heterozygous carriers, suggesting its region-specific origin.

Humans↗

Computational strategies for copy number variation detection, disease association, and beyond.

Copy number variations (CNVs) are key structural variations that contribute to human genetic diversity, evolution, and disease susceptibility. Advances in sequencing technologies and computational methods have improved CNV detection, yet association studies remain challenged by methodological limitations and a lack of standardisation. This review provides an overview of computational strategies for germline CNV detection and disease association. We highlight the value of CNV analysis for uncovering genetic contributions to complex traits and disease risk and outline an analysis workflow including key benchmarking methods. We also discuss current challenges and future directions for advancing CNV detection and association analysis.

Humans↗

Genetic analysis of partial duplication of the long arm of chromosome 16.

BACKGROUND: Pure partial trisomy 16q12.1q22.1 is a rare chromosome copy number variant (CNV). The primary clinical phenotypes associated with this syndrome include abnormal facial morphology, global developmental delay (GDD), short stature, and reported predisposing factors for atypical behavior, autism, the development of learning disabilities, and neuropsychiatric disorders. The dosage-sensitive genes associated with partial trisomy are not disclosed preventing to establish a genotype-phenotype correlation. METHODS: We report a case of a Chinese patient diagnosed with GDD and an abnormal facial shape, who was found to have partial trisomy 16 through karyotyping and high-throughput sequencing analysis. Karyotype and CNV tracing analyses were also conducted on the biological parents of the patient to assess for any chromosomal structural abnormalities. Additionally, we included 29 patients with pure partial trisomy 16q, reported in the DECIPHER database and the literature. We and performed a genotype-phenotype correlation analysis. RESULTS: The proband, a 2-year-old female, was found to have a de novo 21.96 Mb duplication located between 16q12.1q22.1, with no other deletions observed on other chromosomes, indicating a pure partial trisomy of 16q. Through genotype and phenotype analysis of 29 individuals, we found that patients with the duplicated region located at the distal region of 16q may exhibit more severe symptoms than those with duplication at the proximal region; however, no relationship was identified between phenotype and the size of the duplicated segment. CONCLUSION: We report, for the first time, a patient with partial trisomy 16q validated by multiple genetic tests, including CNV-seq, whole exome sequencing (WES), and karyotyping. It is speculated that partial trisomy of 16q may be associated with continuous gene duplication. However, functional studies are necessary to identify the causative gene or critical region linked to duplication syndrome of chromosome 16q.

Child, Preschool↗

Contribution of copy number variations to education, socioeconomic status and cognition from a genome-wide study of 305,401 subjects.

Educational attainment (EA), socioeconomic status (SES) and cognition are phenotypically and genetically linked to health outcomes. However, the role of copy number variations (CNVs) in influencing EA/SES/cognition remains unclear. Using a large-scale (n = 305,401) genome-wide CNV-level association analysis, we discovered 33 CNV loci significantly associated with EA/SES/cognition, 20 of which were novel (deletions at 2p22.2, 2p16.2, 2p12, 3p25.3, 4p15.2, 5p15.33, 5q21.1, 8p21.3, 9p21.1, 11p14.3, 13q12.13, 17q21.31, and 20q13.33, as well as duplications at 3q12.2, 3q23, 7p22.3, 8p23.1, 8p23.2, 17q12 (105 kb), and 19q13.32). The genes identified in gene-level tests were enriched in biological pathways such as neurodegeneration, telomere maintenance and axon guidance. Phenome-wide association studies further identified novel associations of EA/SES/cognition-associated CNVs with mental and physical diseases, such as 6q27 duplication with upper respiratory disease and 17q12 (105 kb) duplication with mood disorders. Our findings provide a genome-wide CNV profile for EA/SES/cognition and bridge their connections to health. The expanded candidate CNVs database and the residing genes would be a valuable resource for future studies aimed at uncovering the biological mechanisms underlying cognitive function and related clinical phenotypes.

Humans↗

Complex patterns of copy number variation at sites of segmental duplications: an important category of structural variation in the human genome.

The structural diversity of the human genome is much higher than previously assumed although its full extent remains unknown. To investigate the association between segmental duplications that display constitutive copy number differences (CNDs) between humans and the great apes and those which exhibit polymorphic copy number variations (CNVs) between humans, we analysed a BAC array enriched with segmental duplications displaying such CNDs. This study documents for the first time that in addition to human-specific gains common to all humans, these duplication clusters (DCs) also exhibit polymorphic CNVs > 40 kb. Segmental duplication is known to have been a frequent event during human genome evolution. Importantly, among the CNV-associated genes identified here, those involved in transcriptional regulation were found to be significantly overrepresented. Complex patterns of variation were evident at sites of DCs, manifesting as inter-individual differentially sized copy number alterations at the same genomic loci. Thus, CNVs associated with segmental duplications do not simply represent insertion/deletion polymorphisms, but rather constitute a wide variety of rearrangements involving differential amplification and partial gains and losses with high inter-individual variability. Although the number of CNVs was not found to differ between Africans and Caucasians/Asians, the average number of variant patterns per locus was significantly lower in Africans. Thus, complex variation patterns characterizing segmental duplications result from relatively recent genomic rearrangements. The high number of these rearrangements, some of which are potentially recurrent, together with differences in population size and expansion dynamics, may account for the greater diversity of CNV in Caucasians/Asians as compared with Africans.

Animals↗

Common genetic variants associated with urinary phthalate levels in children: A genome-wide study.

INTRODUCTION: Phthalates, or dieters of phthalic acid, are a ubiquitous type of plasticizer used in a variety of common consumer and industrial products. They act as endocrine disruptors and are associated with increased risk for several diseases. Once in the body, phthalates are metabolized through partially known mechanisms, involving phase I and phase II enzymes. OBJECTIVE: In this study we aimed to identify common single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) associated with the metabolism of phthalate compounds in children through genome-wide association studies (GWAS). METHODS: The study used data from 1,044 children with European ancestry from the Human Early Life Exposome (HELIX) cohort. Ten phthalate metabolites were assessed in a two-void pooled urine collected at the mean age of 8&#xa0;years. Six ratios between secondary and primary phthalate metabolites were calculated. Genome-wide genotyping was done with the Infinium Global Screening Array (GSA) and imputation with the Haplotype Reference Consortium (HRC) panel. PennCNV was used to estimate copy number variants (CNVs) and CNVRanger to identify consensus regions. GWAS of SNPs and CNVs were conducted using PLINK and SNPassoc, respectively. Subsequently, functional annotation of suggestive SNPs (p-value&#xa0;<&#xa0;1E-05) was done with the FUMA web-tool. RESULTS: We identified four genome-wide significant (p-value&#xa0;<&#xa0;5E-08) loci at chromosome (chr) 3 (FECHP1 for oxo-MiNP_oh-MiNP ratio), chr6 (SLC17A1 for MECPP_MEHHP ratio), chr9 (RAPGEF1 for MBzP), and chr10 (CYP2C9 for MECPP_MEHHP ratio). Moreover, 115 additional loci were found at suggestive significance (p-value&#xa0;<&#xa0;1E-05). Two CNVs located at chr11 (MRGPRX1 for oh-MiNP and SLC35F2 for MEP) were also identified. Functional annotation pointed to genes involved in phase I and phase II detoxification, molecular transfer across membranes, and renal excretion. CONCLUSION: Through genome-wide screenings we identified known and novel loci implicated in phthalate metabolism in children. Genes annotated to these loci participate in detoxification, transmembrane transfer, and renal excretion.

Humans↗

Hotspots for copy number variation in chimpanzees and humans.

Copy number variation is surprisingly common among humans and can be involved in phenotypic diversity and variable susceptibility to complex diseases, but little is known of the extent of copy number variation in nonhuman primates. We have used two array-based comparative genomic hybridization platforms to identify a total of 355 copy number variants (CNVs) in the genomes of 20 wild-born chimpanzees (Pan troglodytes) and have compared the identified chimpanzee CNVs to known human CNVs from previous studies. Many CNVs were observed in the corresponding regions in both chimpanzees and humans; especially those CNVs of higher frequency. Strikingly, these loci are enriched 20-fold for ancestral segmental duplications, which may facilitate CNV formation through nonallelic homologous recombination mechanisms. Therefore, some of these regions may be unstable "hotspots" for the genesis of copy number variation, with recurrent duplications and deletions occurring across and within species.

Animals↗

Genome-wide association study of copy number variations in Parkinson's disease.

OBJECTIVE: To investigate the impact of copy number variations (CNVs) on Parkinson's disease (PD) pathogenesis using genome-wide data and explore their role in sporadic PD. METHODS: We analyzed CNV data from 11,035 PD patients (including 2,731 early-onset PD (EOPD)) and 8,901 controls from the COURAGE-PD consortium using a sliding window CNV-GWAS and genome-wide burden analysis. The independent dataset from the Global Parkinson Genetics Program (GP2) consisted of 23,089 cases and 18,824 controls were used to validate our initial findings. RESULTS: The exploratory dataset identifies multiple CNV regions associated with PD risk. The nominated CNV loci were not confirmed in an independent dataset, except that only a deletion in the PRKN gene, a well-established EOPD locus, remained genome-wide significant and robustly supported. CNV burden analysis showed a higher prevalence of CNVs in PD-related genes in patients compared to controls (OR=1.56 [1.18-2.09], p=0.0013), with PRKN showing the highest burden (OR=1.47 [1.10-1.98], p=0.026). Patients with CNVs in PRKN had an earlier disease onset. Burden analysis with controls and EOPD patients showed similar results. INTERPRETATION: The largest CNV-based GWAS on PD highlights both the promise and pitfalls of array-based CNV detection in PD and underscores the relevance of whole-genome sequencing approaches in resolving the role of CNV in PD. The array-based findings are prone towards false positive findings that might arise either from platform limitations and/or cohort biases. Future studies require improved genotyping resolution and rigorous cross-cohort validation to reliably assess CNV contributions to PD risk.

Journal Article↗

Copy number variant scan in more than four thousand Holstein cows bred in Lombardy, Italy.

Copy Number Variants (CNV) are modifications affecting the genome sequence of DNA, for instance, they can be duplications or deletions of a considerable number of base pairs (i.e., greater than 1000 bp and up to millions of bp). Their impact on the variation of the phenotypic traits has been widely demonstrated. In addition, CNVs are a class of markers useful to identify the genetic biodiversity among populations related to adaptation to the environment. The aim of this study was to detect CNVs in more than four thousand Holstein cows, using information derived by a genotyping done with the GGP (GeneSeek Genomic Profiler) bovine 100K SNP chip. To detect CNV the SVS 8.9 software was used, then CNV regions (CNVRs) were detected. A total of 123,814 CNVs (4,150 non redundant) were called and aggregated into 1,397 CNVRs. The PCA results obtained using the CNVs information, showed that there is some variability among animals. For many genes annotated within the CNVRs, the role in immune response is well known, as well as their association with important and economic traits object of selection in Holstein, such as milk production and quality, udder conformation and body morphology. Comparison with reference revealed unique CNVRs of the Holstein breed, and others in common with Jersey and Brown. The information regarding CNVs represents a valuable resource to understand how this class of markers may improve the accuracy in prediction of genomic value, nowadays solely based on SNPs markers.

Cattle↗

MarkerMatch: a proximity-based probe-matching algorithm for joint analysis of copy-number variants from different genotyping arrays.

MOTIVATION: Copy-number variants (CNVs) are a form of genetic structural variation with increasing importance in complex human disorders. Both DNA sequencing and microarray data can be used to detect CNVs, which can be used in genetic association tests. Unlike genotypes, CNV detection in microarrays requires the use of observed intensity signals at each probe, which limits the imputability for analyses that span multiple array types. Thus far, a consensus set of probes (those present on all arrays) has been used to circumvent the problem of differing array-specific sensitivities. This has led to excessive reduction in overall sensitivity since arrays can have an undesirably low probe overlap. To overcome this limitation, we developed MarkerMatch, a proximity-based algorithm that matches probes across different genotyping microarrays to maximize the number of probes considered in the CNV calling algorithm, thereby increasing the resolution and sensitivity while preserving precision. RESULTS: By analyzing CNV calls from 4906 individuals genotyped across three different arrays, we show that the MarkerMatch approach improves sensitivity by increasing the density of probes available for CNV calling while maintaining precision or improving it relative to the current practice (e.g. use of consensus probes only). We further demonstrate that MarkerMatch matches the CNV detection from current practice in terms of F1 score and PPV for larger CNVs. We also optimize MarkerMatch parameters, DMAX and Method, and find an optimal DMAX setting at 10&#x2009;kb, with no clear optimal candidate based on Method, indicating that parameters for this metric should be determined on a use case basis. AVAILABILITY: The R package for MarkerMatch is available at: https://github.com/FranjoIM/MarkerMatch. The code used for analysis and implementation is available at: https://doi.org/10.5281/zenodo.18460979. The live notebook is available at https://fivankovic.notion.site/2026-markermatch.

DNA Copy Number Variations↗

Deep clinical and genetic analysis of 17p13.3 region: 38 pediatric patients diagnosed using next-generation sequencing and literature review.

BACKGROUND: Chromosome 17p13.3 is a region of genomic instability associated with different neurodevelopmental diseases. The malformation spectrum of 17p13.3 microdeletions ranges from an isolated lissencephaly sequence to Miller-Dieker syndrome, while 17p13.3 microduplications result in autism, learning disabilities, microcephaly and other brain malformations. This study aims to provide a more comprehensive delineation of the clinical and genetic characteristics associated with 17p13.3 alterations. METHODS: We retrospectively analyzed the next-generation sequencing (NGS) data of more than 40 thousand patients from January 2016 to December 2021 and identified 38 pediatric patients with copy-number variations (CNVs) or single-nucleotide variations (SNVs) in 17p13.3 region. Published patients with CNVs in the 17p13.3 region were also collected and we performed a Chi-square test to compare the phenotype spectrum of microdeletions and microduplications. RESULTS: Among the 27 CNV patients, 20 patients with microdeletions and 7 patients with microduplications were found. PAFAH1B1 was the most frequently deleted gene and CRK was the most frequently duplicated gene. Affected genes in 11 SNV patients included PAFAH1B1 and PRPF8. Developmental delay was the most common abnormality detected in the 38 patients (29/38, 76.3%). Of note, Case 10 presented omphalocele and Case 23 presented scoliosis, webbed neck and bone cyst, all of which were unusual variant phenotypes in this region. The Chi-square test revealed that epilepsy, lissencephaly and short stature were statistically significant with microdeletions, while behavioral abnormalities and hand and foot abnormalities were significant with microduplications (p&#x2009;<&#x2009;0.01). CONCLUSIONS: While PAFAH1B1, YWHAE and CRK are associated with major phenotypes of 17p13.3, RTN4RL1 may be involved in white matter changes and HIC1 might contribute to the occurrence of omphalocele. This study provided a comprehensive understanding of genetic information and phenotype spectrum of the 17p13.3 region.

Humans↗

Phenotypic Impact of Rare Potentially Damaging Copy Number Variation in Obsessive-Compulsive Disorder and Chronic Tic Disorders.

BACKGROUND: Recent studies report an important-and previously underestimated-role of rare variation in risk of obsessive-compulsive disorder (OCD) and chronic tic disorders (CTD). Using data from a large epidemiological study, we evaluate the distribution of potentially damaging copy number variation (pdCNV) in OCD and CTD, examining associations between pdCNV and the phenotypes of probands, including a consideration of early- vs. late-diagnoses. METHOD: The Obsessive-Compulsive Inventory-Revised (OCI-R) questionnaire was used to ascertain psychometric profiles of OCD probands. CNV were identified genome-wide using chromosomal microarray data. RESULTS: For 993 OCD cases, 86 (9%) were identified as pdCNV carriers. The most frequent pdCNV found was at the 16p13.11 region. There was no significant association between pdCNV and the OCI-R total score. However, pdCNV was associated with Obsessing and Checking subscores. There was no significant difference in pdCNV frequency between early- vs. late-diagnosed OCD probands. Of the 217 CTD cases, 18 (8%) were identified as pdCNV carriers. CTD probands with pdCNV were significantly more likely to have co-occurring autism spectrum disorder (ASD). CONCLUSIONS: pdCNV represents part of the risk architecture for OCD and CTD. If replicated, our findings suggest pdCNV impact some OCD symptoms. Genes within the 16p13.11 region are potential OCD risk genes.

Humans↗

A high-resolution map of segmental DNA copy number variation in the mouse genome.

Submicroscopic (less than 2 Mb) segmental DNA copy number changes are a recently recognized source of genetic variability between individuals. The biological consequences of copy number variants (CNVs) are largely undefined. In some cases, CNVs that cause gene dosage effects have been implicated in phenotypic variation. CNVs have been detected in diverse species, including mice and humans. Published studies in mice have been limited by resolution and strain selection. We chose to study 21 well-characterized inbred mouse strains that are the focus of an international effort to measure, catalog, and disseminate phenotype data. We performed comparative genomic hybridization using long oligomer arrays to characterize CNVs in these strains. This technique increased the resolution of CNV detection by more than an order of magnitude over previous methodologies. The CNVs range in size from 21 to 2,002 kb. Clustering strains by CNV profile recapitulates aspects of the known ancestry of these strains. Most of the CNVs (77.5%) contain annotated genes, and many (47.5%) colocalize with previously mapped segmental duplications in the mouse genome. We demonstrate that this technique can identify copy number differences associated with known polymorphic traits. The phenotype of previously uncharacterized strains can be predicted based on their copy number at these loci. Annotation of CNVs in the mouse genome combined with sequence-based analysis provides an important resource that will help define the genetic basis of complex traits.

Animals↗

Absolute copy number aware CNV calling of sub-megabase segments in ultra-low coverage single-cell DNA sequencing data.

Recent advances in ultra-low coverage whole-genome sequencing (WGS) of single cells have enabled detailed analysis of copy number variation at a throughput approaching that of single-cell RNA sequencing. However, downstream computational methods have not seen comparable advances and are largely adaptations of deep sequencing methodology with reduced precision. Here, we present ASCENT, a computational method built to take full advantage of modern direct tagmentation-based WGS at ultra-low depth. Using joint segmentation with high-resolution bins, we accurately detect small segments, achieving accurate copy number profiles even at 100 000 reads per cell. ASCENT implements true absolute copy state inference for single cells, based on statistical modeling of coverage rather than comparison to a reference, while taking variable segment copy state into account. Further, ASCENT implements per-segment copy-neutral loss of heterozygosity (LOH) calling without the need for non-tumor or bulk WGS reference. When applied to a pediatric B-ALL sample, ASCENT finds copy-neutral LOH in a small segment and a minor subclone defined by breakpoints missed in bulk WGS. Thus, by applying appropriate computational methods, single-cell WGS provides clear advantages over bulk, even at a relatively low cell number and sequencing depth.

DNA Copy Number Variations↗

Genomic Profiling of Anophthalmia/Microphthalmia-Associated CNVs Reveals Complex Genotype-Phenotype Correlations and Incomplete Penetrance.

BACKGROUND: Anophthalmia/microphthalmia (A/M) is a severe congenital ocular malformation characterized by the complete absence or small size of the eye bulb. Interpreting copy number variations (CNVs) in A/M is challenged by variable genotype-phenotype correlations and reduced penetrance. This study investigated the genetic etiology of A/M-associated CNVs. METHODS: Genomic profiling was performed on four unrelated families presenting with ocular anomalies or harboring A/M-susceptible CNVs. Variants were evaluated by integrating American College of Medical Genetics and Genomics (ACMG) guidelines with clinical phenotypes and familial segregation. RESULTS: An inherited 8.13&#x2009;Mb deletion (8p23.3p23.1) in Patient 1 was excluded due to genotype-phenotype mismatch. Patients 2 and 3 harbored de novo pathogenic deletions involving OTX2 (14q22.3) and SOX2 (3q26.33), causing typical A/M. Case 4 revealed a 14q22.2q23.1 deletion encompassing OTX2 in a fetus and mother without ocular anomalies, consistent with the incomplete penetrance of OTX2-related microphthalmia. Thus, CNV-induced haploinsufficiency causes A/M with high phenotypic variability. CONCLUSION: Accurate CNV interpretation requires robust genotype-phenotype correlation and careful assessment of incomplete penetrance to prevent diagnostic pitfalls and improve genetic counseling.

Female↗

Genomic Analysis of Circulating Tumor Cells at the Single-Cell Level.

Circulating tumor cells (CTCs) have a great potential for noninvasive diagnosis and real-time monitoring of cancer. A comprehensive evaluation of four whole genome amplification (WGA)/next-generation sequencing workflows for genomic analysis of single CTCs, including PCR-based (GenomePlex and Ampli1), multiple displacement amplification (Repli-g), and hybrid PCR- and multiple displacement amplification-based [multiple annealing and loop-based amplification cycling (MALBAC)] is reported herein. To demonstrate clinical utilities, copy number variations (CNVs) in single CTCs isolated from four patients with squamous non-small-cell lung cancer were profiled. Results indicate that MALBAC and Repli-g WGA have significantly broader genomic coverage compared with GenomePlex and Ampli1. Furthermore, MALBAC coupled with low-pass whole genome sequencing has better coverage breadth, uniformity, and reproducibility and is superior to Repli-g for genome-wide CNV profiling and detecting focal oncogenic amplifications. For mutation analysis, none of the WGA methods were found to achieve sufficient sensitivity and specificity by whole exome sequencing. Finally, profiling of single CTCs from patients with non-small-cell lung cancer revealed potentially clinically relevant CNVs. In conclusion, MALBAC WGA coupled with low-pass whole genome sequencing is a robust workflow for genome-wide CNV profiling at single-cell level and has great potential to be applied in clinical investigations. Nevertheless, data suggest that none of the evaluated single-cell sequencing workflows can reach sufficient sensitivity or specificity for mutation detection required for clinical applications.

Carcinoma, Non-Small-Cell Lung↗

Genome-wide detection of human copy number variations using high-density DNA oligonucleotide arrays.

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.

Algorithms↗

Copy number variation in the genome; the human DMD gene as an example.

Recent developments have yielded new technologies that have greatly simplified the detection of deletions and duplications, i.e., copy number variants (CNVs). These technologies can be used to screen for CNVs in and around specific genomic regions, as well as genome-wide. Several genome-wide studies have demonstrated that CNV in the human genome is widespread and may include millions of nucleotides. One of the questions that emerge is which sequences, structures and/or processes are involved in their generation. Using as an example the human DMD gene, mutations in which cause Duchenne and Becker muscular dystrophy, we review the current data, determine the deletion and duplication profile across the gene and summarize the information that has been collected regarding their origin. In addition we discuss the methods most frequently used for their detection, in particular MAPH and MLPA.

Alleles↗