Identification of de novo copy number variants associated with human disorders of sexual development

Disorders of sexual development (DSD), ranging in severity from genital abnormalities to complete sex reversal, are among the most common human birth defects with incidence rates reaching almost 3%. Although causative alterations in key genes controlling gonad development have been identified, the majority of DSD cases remain unexplained. To improve the diagnosis, we screened 116 children born with idiopathic DSD using a clinically validated array-based comparative genomic hybridization platform. 8951 controls without urogenital defects were used to compare with our cohort of affected patients. Clinically relevant imbalances were found in 21.5% of the analyzed patients. Most anomalies (74.2%) evaded detection by the routinely ordered karyotype and were scattered across the genome in gene-enriched subtelomeric loci. Among these defects, confirmed de novo duplication and deletion events were noted on 1p36.33, 9p24.3 and 19q12-q13.11 for ambiguous genitalia, 10p14 and Xq28 for cryptorchidism and 12p13 and 16p11.2 for hypospadias. These variants were significantly associated with genitourinary defects (P = 6.08×10⁻¹²). The causality of defects observed in 5p15.3, 9p24.3, 22q12.1 and Xq28 was supported by the presence of overlapping chromosomal rearrangements in several unrelated patients. In addition to known gonad determining genes including SRY and DMRT1, novel candidate genes such as FGFR2, KANK1, ADCY2 and ZEB2 were encompassed. The identification of risk germline rearrangements for urogenital birth defects may impact diagnosis and genetic counseling and contribute to the elucidation of the molecular mechanisms underlying the pathogenesis of human sexual development.     

Identification of copy number variants from exome sequence data

Background

With advances in next generation sequencing technologies and genomic capture techniques, exome sequencing has become a cost-effective approach for mutation detection in genetic diseases. However, computational prediction of copy number variants (CNVs) from exome sequence data is a challenging task. Whilst numerous programs are available, they have different sensitivities, and have low sensitivity to detect smaller CNVs (1–4 exons). Additionally, exonic CNV discovery using standard aCGH has limitations due to the low probe density over exonic regions. The goal of our study was to develop a protocol to detect exonic CNVs (including shorter CNVs that cover 1–4 exons), combining computational prediction algorithms and a high-resolution custom CGH array.

Results

We used six published CNV prediction programs (ExomeCNV, CONTRA, ExomeCopy, ExomeDepth, CoNIFER, XHMM) and an in-house modification to ExomeCopy and ExomeDepth (ExCopyDepth) for computational CNV prediction on 30 exomes from the 1000 genomes project and 9 exomes from primary immunodeficiency patients. CNV predictions were tested using a custom CGH array designed to capture all exons (exaCGH). After this validation, we next evaluated the computational prediction of shorter CNVs. ExomeCopy and the in-house modified algorithm, ExCopyDepth, showed the highest capability in detecting shorter CNVs. Finally, the performance of each computational program was assessed by calculating the sensitivity and false positive rate.

Conclusions

In this paper, we assessed the ability of 6 computational programs to predict CNVs, focussing on short (1–4 exon) CNVs. We also tested these predictions using a custom array targeting exons. Based on these results, we propose a protocol to identify and confirm shorter exonic CNVs combining computational prediction algorithms and custom aCGH experiments.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-661) contains supplementary material, which is available to authorized users.     

The coalescent with selection on copy number variants

We develop a coalescent-based simulation tool to generate patterns of single nucleotide polymorphisms (SNPs) in a wide region encompassing both the original and duplicated genes. Selection on the new duplicated copy and interlocus gene conversion between the two copies are incorporated. This simulation enables us to explore how selection on duplicated copies affects the pattern of SNPs. The fixation of an advantageous duplicated copy causes a strong reduction in polymorphism not only in the duplicated copy but also in its flanking regions, which is a typical signature of a selective sweep by positive selection. After fixation, polymorphism gradually increases by accumulating neutral mutations and eventually reaches the equilibrium value if there is no gene conversion. When gene conversion is active, the number of SNPs in the duplicated copy quickly increases by transferring SNPs from the original copy; therefore, the time when we can recognize the signature of selection is decreased. Because this effect of gene conversion is restricted only to the duplicated region, more power to detect selection is expected if a flanking region to the duplicated copy is used.     

On the frequency of copy number variants

MOTIVATION: Estimating the frequency distribution of copy number variants (CNVs) is an important aspect of the effort to characterize this new type of genetic variation. Currently, most studies report a strong skew toward low-frequency CNVs. In this article, our goal is to investigate the frequencies of CNVs. We employ a two-step procedure for the CNV frequency estimation process. We use family information a posteriori to select only the most reliable CNV regions, i.e. those showing high rates of Mendelian transmission. RESULTS: Our results suggest that the current skew toward low-frequency CNVs may not be representative of the true frequency distribution, but may be due, among other reasons, to the non-negligible false negative rates that characterize CNV detection methods. Moreover, false positives are also likely, as low-frequency CNVs are hard to detect with small sample sizes and technologies that are not ideally suited for their detection. Without appropriate validation methods, such as incorporation of biologically relevant information (for example, in our case, the transmission of heritable CNVs from parents to offspring), it is difficult to assess the validity of specific CNVs, and even harder to obtain reliable frequency estimates.     

Identification of copy number variants on human chromosome 22 in patients with a variety of clinical findings

The aims of this study were to create a copy number variant (CNV) profile of human chromosome 22 and to establish a genotype-phenotype correlation for patients with genomic abnormalities on chromosome 22. Thus, 1,654 consecutive pediatric patients with a diversity of clinical findings were evaluated by high-resolution chromosomal microarray analysis (CMA). We identified 25 individuals with abnormal CNVs on chromosome 22, representing 1.5% of the cases analyzed in this cohort. Meanwhile, we detected 1,298 benign CNVs on this chromosome in these individuals. Twenty-one of the 25 abnormal CNVs and the majority of the benign CNVs occurred through involvement of the 8 unstable genomic regions enriched with low copy repeats (LCR22A-H). The highly dynamic status of LCR22s within the 22q11 region facilitates the formation of diverse genomic abnormalities. This CNV profile provides a general perspective of the spectrum of chromosome 22 genomic imbalances and subsequently improves the CNV-phenotype correlations.     

Genetic copy number variants in sib pairs both affected with schizophrenia

Background  

Schizophrenia is a complex disorder with involvement of multiple genes.     

Analysis of copy number variants in the cattle genome

Copy number variation (CNV) is likely to be an important component of heritable variation in livestock. To characterise CNVs in cattle, we performed a genome wide survey to determine the number, location and gene content of these genomic features. A tiling oligonucleotide array with ~385,000 probes was used for comparative genomic hybridisation of both taurine and zebu cattle. Using a conservative set of calling criteria, a total of 51 CNV were detected that collectively spanned approximately half of one percent of the bovine genome. The size of the average CNV within each animal ranged from 213 kb up to 335 kb. Half of the CNV were detected in a single animal only, whilst the remainder was independently identified in multiple individuals. Analysis was performed to determine the gene content for each CNV region. This revealed that the majority of CNV (82%) spanned at least one gene, with a number of CNV containing genes which are known to control aspects of phenotypic variation in cattle. Whilst additional studies are required to determine the impact of individual CNV, this study confirmed them as an important class of genomic variation in cattle.     

Identification of copy number variants in children and adolescents with autism spectrum disorder: a study from Turkey

Molecular Biology Reports - Copy number variants (CNVs) play a key role in the etiology of autism spectrum disorder (ASD). Therefore, recent guidelines recommend chromosomal microarrays (CMAs) as...     

Read count approach for DNA copy number variants detection

MOTIVATION: The advent of high-throughput sequencing technologies is revolutionizing our ability in discovering and genotyping DNA copy number variants (CNVs). Read count-based approaches are able to detect CNV regions with an unprecedented resolution. Although this computational strategy has been recently introduced in literature, much work has been already done for the preparation, normalization and analysis of this kind of data. RESULTS: Here we face the many aspects that cover the detection of CNVs by using read count approach. We first study the characteristics and systematic biases of read count distributions, focusing on the normalization methods designed for removing these biases. Subsequently, we compare the algorithms designed to detect the boundaries of CNVs and we investigate the ability of read count data to predict the exact number of DNA copy. Finally, we review the tools publicly available for analysing read count data. To better understand the state of the art of read count approaches, we compare the performance of the three most widely used sequencing technologies (Illumina Genome Analyzer, Roche 454 and Life Technologies SOLiD) in all the analyses that we perform.     

Clinical interpretation of copy number variants in the human genome

Molecular methods, by which copy number variants (CNVs) detection is available, have been gradually introduced into routine diagnostics over the last 15 years. Despite this, some CNVs continue to be a huge challenge when it comes to clinical interpretation. CNVs are an important source of normal and pathogenic variants, but, in many cases, their impact on human health depends on factors that are not yet known. Therefore, perception of their clinical consequences can change over time, as our knowledge grows. This review summarises guidelines that facilitate correct classification of identified changes and discusses difficulties with the interpretation of rare, small CNVs.     

Exploring the role of copy number variants in human adaptation

Over the past decade, the ubiquity of copy number variants (CNVs, the gain or loss of genomic material) in the genomes of healthy humans has become apparent. Although some of these variants are associated with disorders, a handful of studies documented an adaptive advantage conferred by CNVs. In this review, we propose that CNVs are substrates for human evolution and adaptation. We discuss the possible mechanisms and evolutionary processes in which CNVs are selected, outline the current challenges in identifying these loci, and highlight that copy number variable regions allow for the creation of novel genes that may diversify the repertoire of such genes in response to rapidly changing environments. We expect that many more adaptive CNVs will be discovered in the coming years, and we believe that these new findings will contribute to our understanding of human-specific phenotypes.     

Genome-wide analysis of copy number variants in age-related macular degeneration

Age-related macular degeneration (AMD) is a complex genetic disease, with many loci demonstrating appreciable attributable disease risk. Despite significant progress toward understanding the genetic and environmental etiology of AMD, identification of additional risk factors is necessary to fully appreciate and treat AMD pathology. In this study, we investigated copy number variants (CNVs) as potential AMD risk variants in a cohort of 400 AMD patients and 500 AMD-free controls ascertained at the University of Iowa. We used three publicly available copy number programs to analyze signal intensity data from Affymetrix GeneChip SNP Microarrays. CNVs were ranked based on prevalence in the disease cohort and absence from the control group; high interest CNVs were subsequently confirmed by qPCR. While we did not observe a single-locus "risk CNV" that could account for a major fraction of AMD, we identified several rare and overlapping CNVs containing or flanking compelling candidate genes such as NPHP1 and EFEMP1. These and other candidate genes highlighted by this study deserve further scrutiny as sources of genetic risk for AMD.     

EXCAVATOR: detecting copy number variants from whole-exome sequencing data

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/.     

Cytogenetically balanced translocations are associated with focal copy number alterations

Current cytogenetic methods (e.g., G-banding and multicolor chromosomal painting) allow detection of translocation events but lack the resolution to (a) locate the breakpoints precisely at the chromosome band level or (b) discriminate balanced translocations from translocations with copy number alterations not previously reported, or imperfectly balanced translocations. In this study, we demonstrate that cytogenetically balanced translocations are in fact frequently associated with segmental gain or loss of DNA. The recent development of a whole genome tiling path BAC array has enabled tiling resolution analysis of genomic segmental copy number status. Combining tiling resolution BAC array comparative genomic hybridization (array CGH) with G-Banding analysis and multicolor chromosomal painting approaches such as spectral karyotyping (SKY) facilitates high-resolution mapping of genomic alterations associated with imperfectly balanced translocations. Using a refined version of our CGH array we have deduced the copy number status throughout the genomes of three cytogenetically well-characterized prostate cancer cell lines (PC3, DU145, LNCaP) to determine whether translocations are associated with focal gains and losses of DNA. At 78 kb tiling resolution we identified the boundaries of 170, 80, and 34 known and novel copy number alterations (CNA) in these cell line genomes, respectively. Thirty-three of the 36 known translocations (92%, P < 0.001) in DU145 were associated with segmental CNA. Likewise, 80% (P < 0.001) of the known translocations showed association in LNCaP. Although many translocation breakpoints exhibit segmental alteration in PC3, the pattern of chromosomal rearrangements is too complex for use in comprehensive association with CNA boundaries. Our results reveal that imperfectly balanced translocations in tumor genomes are a phenomenon that occurs at frequencies much higher than previously demonstrated. Electronic supplementary material Supplementary material is available in the online version of this article at and is accessible for authorized users.     

Impact of whole genome amplification on analysis of copy number variants

Large-scale copy number variants (CNVs) have recently been recognized to play a role in human genome variation and disease. Approaches for analysis of CNVs in small samples such as microdissected tissues can be confounded by limited amounts of material. To facilitate analyses of such samples, whole genome amplification (WGA) techniques were developed. In this study, we explored the impact of Phi29 multiple-strand displacement amplification on detection of CNVs using oligonucleotide arrays. We extracted DNA from fresh frozen lymph node samples and used this for amplification and analysis on the Affymetrix Mapping 500k SNP array platform. We demonstrated that the WGA procedure introduces hundreds of potentially confounding CNV artifacts that can obscure detection of bona fide variants. Our analysis indicates that many artifacts are reproducible, and may correlate with proximity to chromosome ends and GC content. Pair-wise comparison of amplified products considerably reduced the number of apparent artifacts and partially restored the ability to detect real CNVs. Our results suggest WGA material may be appropriate for copy number analysis when amplified samples are compared to similarly amplified samples and that only the CNVs with the greatest significance values detected by such comparisons are likely to be representative of the unamplified samples.