Copy Number Variation in Thai Population

Copy number variation (CNV) is a major genetic polymorphism contributing to genetic diversity and human evolution. Clinical application of CNVs for diagnostic purposes largely depends on sufficient population CNV data for accurate interpretation. CNVs from general population in currently available databases help classify CNVs of uncertain clinical significance, and benign CNVs. Earlier studies of CNV distribution in several populations worldwide showed that a significant fraction of CNVs are population specific. In this study, we characterized and analyzed CNVs in 3,017 unrelated Thai individuals genotyped with the Illumina Human610, Illumina HumanOmniexpress, or Illumina HapMap550v3 platform. We employed hidden Markov model and circular binary segmentation methods to identify CNVs, extracted 23,458 CNVs consistently identified by both algorithms, and cataloged these high confident CNVs into our publicly available Thai CNV database. Analysis of CNVs in the Thai population identified a median of eight autosomal CNVs per individual. Most CNVs (96.73%) did not overlap with any known chromosomal imbalance syndromes documented in the DECIPHER database. When compared with CNVs in the 11 HapMap3 populations, CNVs found in the Thai population shared several characteristics with CNVs characterized in HapMap3. Common CNVs in Thais had similar frequencies to those in the HapMap3 populations, and all high frequency CNVs (>20%) found in Thai individuals could also be identified in HapMap3. The majorities of CNVs discovered in the Thai population, however, were of low frequency, or uniquely identified in Thais. When performing hierarchical clustering using CNV frequencies, the CNV data were clustered into Africans, Europeans, and Asians, in line with the clustering performed with single nucleotide polymorphism (SNP) data. As CNV data are specific to origin of population, our population-specific reference database will serve as a valuable addition to the existing resources for the investigation of clinical significance of CNVs in Thais and related ethnicities.     

拷贝数变异与疾病的关系及其在动物抗病育种中的应用前景

摘要: 拷贝数变异(Copy number variations, CNVs)主要指大于1 kb以上的DNA片段的缺失、插入、重复等。CNVs广泛存在于人类和其他哺乳动物的基因组中。文章主要介绍了CNVs对人类疾病的影响及其检测技术, 并对CNVs在动物抗病育种中的应用前景进行了展望。由于拷贝数变异对抗病性和易感性的影响至关重要, 因此采用生物技术手段有望将其运用于家畜标记辅助选择、QTL精细定位以及动物优良抗病品种培育当中。     

A study of CNVs as trait-associated polymorphisms and as expression quantitative trait loci

We conducted a comprehensive study of copy number variants (CNVs) well-tagged by SNPs (r(2)≥ 0.8) by analyzing their effect on gene expression and their association with disease susceptibility and other complex human traits. We tested whether these CNVs were more likely to be functional than frequency-matched SNPs as trait-associated loci or as expression quantitative trait loci (eQTLs) influencing phenotype by altering gene regulation. Our study found that CNV-tagging SNPs are significantly enriched for cis eQTLs; furthermore, we observed that trait associations from the NHGRI catalog show an overrepresentation of SNPs tagging CNVs relative to frequency-matched SNPs. We found that these SNPs tagging CNVs are more likely to affect multiple expression traits than frequency-matched variants. Given these findings on the functional relevance of CNVs, we created an online resource of expression-associated CNVs (eCNVs) using the most comprehensive population-based map of CNVs to inform future studies of complex traits. Although previous studies of common CNVs that can be typed on existing platforms and/or interrogated by SNPs in genome-wide association studies concluded that such CNVs appear unlikely to have a major role in the genetic basis of several complex diseases examined, our findings indicate that it would be premature to dismiss the possibility that even common CNVs may contribute to complex phenotypes and at least some common diseases.     

Common copy number variations in fifty radiosensitive cell lines

Hypersensitivity to radiation exposure is a major challenge to radiotherapy in the treatment of cancer patients. Copy number variations (CNVs) are believed to identify genomic regions of functional significance for radiosensitivity (RS) but have yet to be systematically investigated. We used Affymetrix 6.0 SNP arrays to survey common CNVs in a cohort of 50 radiosensitive lymphoblastoid cell lines (RS-LCLs) derived from patients with undiagnosed diseases. A total of 317 CNVs that were present in at least 10% of the studied cell lines were identified. Three hundred and eight CNVs overlapped with polymorphic CNVs, 13 of which were significantly enriched in the RS-LCLs compared to the reference. The remaining 9 CNVs were novel. The majority of these enriched and novel CNVs were chromosomal gains. The dominance of the chromosomal gains over losses is inconsistent with the traditional concept of molecular basis of RS and suggests more complex genetic mechanisms for RS.     

Copy Number Variants in German Patients with Schizophrenia

Large rare copy number variants (CNVs) have been recognized as significant genetic risk factors for the development of schizophrenia (SCZ). However, due to their low frequency (1∶150 to 1∶1000) among patients, large sample sizes are needed to detect an association between specific CNVs and SCZ. So far, the majority of genome-wide CNV analyses have focused on reporting only CNVs that reached a significant P-value within the study cohort and merely confirmed the frequency of already-established risk-carrying CNVs. As a result, CNVs with a very low frequency that might be relevant for SCZ susceptibility are lost for secondary analyses. In this study, we provide a concise collection of high-quality CNVs in a large German sample consisting of 1,637 patients with SCZ or schizoaffective disorder and 1,627 controls. All individuals were genotyped on Illumina''s BeadChips and putative CNVs were identified using QuantiSNP and PennCNV. Only those CNVs that were detected by both programs and spanned ≥30 consecutive SNPs were included in the data collection and downstream analyses (2,366 CNVs, 0.73 CNVs per individual). The genome-wide analysis did not reveal a specific association between a previously unknown CNV and SCZ. However, the group of CNVs previously reported to be associated with SCZ was more frequent in our patients than in the controls. The publication of our dataset will serve as a unique, easily accessible, high-quality CNV data collection for other research groups. The dataset could be useful for the identification of new disease-relevant CNVs that are currently overlooked due to their very low frequency and lack of power for their detection in individual studies.     

Copy number variation and disease resistance in plants

Plant genome diversity varies from single nucleotide polymorphisms to large-scale deletions, insertions, duplications, or re-arrangements. These re-arrangements of sequences resulting from duplication, gains or losses of DNA segments are termed copy number variations (CNVs). During the last decade, numerous studies have emphasized the importance of CNVs as a factor affecting human phenotype; in particular, CNVs have been associated with risks for several severe diseases. In plants, the exploration of the extent and role of CNVs in resistance against pathogens and pests is just beginning. Since CNVs are likely to be associated with disease resistance in plants, an understanding of the distribution of CNVs could assist in the identification of novel plant disease-resistance genes. In this paper, we review existing information about CNVs; their importance, role and function, as well as their association with disease resistance in plants.     

Copy number variations identified in the chicken using a 60K SNP BeadChip

Copy number variation (CNV) is considered an important genetic variation, contributing to many economically important traits in the chicken. Although CNVs can be detected using a comparative genomic hybridization array, the high‐density SNP array has provided an alternative way to identify CNVs in the chicken. In the current study, a chicken 60K SNP BeadChip was used to identify CNVs in two distinct chicken genetic lines (White Leghorn and dwarf) using the penncnv program. A total of 209 CNV regions were identified, distributing on chromosomes 1–22 and 24–28 and encompassing 13.55 Mb (1.42%) of chicken autosomal genome area. Three of seven selected CNVs (73.2% individuals) were completely validated by quantitative PCR. To our knowledge, this is the first report in the chicken identifying CNVs using a SNP array. Identification of 190 new identified CNVs illustrates the feasibility of the chicken 60K SNP BeadChip to detect CNVs in the chicken, which lays a solid foundation for future analyses of associations of CNVs with economically important phenotypes in chickens.     

Gene copy number variations in adaptive evolution: The genomic distribution of gene copy number variations revealed by genetic mapping and their adaptive role in an undomesticated species,white spruce (Picea glauca)

Gene copy number variation (CNV) has been associated with phenotypic variability in animals and plants, but a genomewide understanding of their impacts on phenotypes is largely restricted to human and agricultural systems. As such, CNVs have rarely been considered in investigations of the genomic architecture of adaptation in wild species. Here, we report on the genetic mapping of gene CNVs in white spruce, which lacks a contiguous assembly of its large genome (~20 Gb), and their relationships with adaptive phenotypic variation. We detected 3,911 gene CNVs including de novo structural variations using comparative genome hybridization on arrays (aCGH) in a large progeny set. We inferred the heterozygosity at CNV loci within parents by comparing haploid and diploid tissues and genetically mapped 82 gene CNVs. Our analysis showed that CNVs were distributed over 10 linkage groups and identified four CNV hotspots that we predict to occur in other species of the Pinaceae. Significant relationships were found between 29 of the gene CNVs and adaptive traits based on regression analyses with timings of bud set and bud flush, and height growth, suggesting a role for CNVs in climate adaptation. The importance of CNVs in adaptive evolution of white spruce was also indicated by functional gene annotations and the clustering of 31% of the mapped adaptive gene CNVs in CNV hotspots. Taken together, these results illustrate the feasibility of studying CNVs in undomesticated species and represent a major step towards a better understanding of the roles of CNVs in adaptive evolution.     

Accurate in silico confirmation of rare copy number variant calls from exome sequencing data using transfer learning

Exome sequencing is widely used in genetic studies of human diseases and clinical genetic diagnosis. Accurate detection of copy number variants (CNVs) is important to fully utilize exome sequencing data. However, exome data are noisy. None of the existing methods alone can achieve both high precision and recall rate. A common practice is to perform heuristic filtration followed by manual inspection of read depth of putative CNVs. This approach does not scale in large studies. To address this issue, we developed a transfer learning method, CNV-espresso, for in silico confirming rare CNVs from exome sequencing data. CNV-espresso encodes candidate CNVs from exome data as images and uses pretrained convolutional neural network models to classify copy number states. We trained CNV-espresso using an offspring–parents trio exome sequencing dataset, with inherited CNVs as positives and CNVs with Mendelian errors as negatives. We evaluated the performance using additional samples that have both exome and whole-genome sequencing (WGS) data. Assuming the CNVs detected from WGS data as a proxy of ground truth, CNV-espresso significantly improves precision while keeping recall almost intact, especially for CNVs that span a small number of exons. CNV-espresso can effectively replace manual inspection of CNVs in large-scale exome sequencing studies.     

Identification of copy number variation of CAPN10 in Thais with type 2 diabetes by multiplex PCR and denaturing high performance liquid chromatography (DHPLC)

Copy number variations (CNVs) have been shown to be associated with several diseases. They can cause deviation of genotypes from Hardy-Weinberg Equilibrium (HWE). Genetic case-control association studies in Thais revealed that genotype distribution of CAPN10 Indel19 was deviated from HWE after correction of genotyping error. Therefore, we aim to identify CNVs within CAPN10 Indel19 region. The semi-quantitative denaturating high performance liquid chromatography (DHPLC) method was used to detect CNVs in the region of CAPN10 Indel19 marker in cohort of 305 patients with type 2 diabetes and 250 control subjects without diabetes. CNVs in the region of CAPN10 Indel19 was successfully detected by DHPLC. After correction of genotype calling based on the status of identified CNVs, CAPN10 Indel19 genotypes were well-fitted for HWE (p>0.05). However, we did not find association between CNV genotypes and risk of type 2 diabetes in our population. CNVs in CAPN10 have been identified in Thais. These CNVs lead to deviation from HWE of CAPN10 Indel19 genotypes. After excluding identified CNVs from the analysis, CAPN10 Indel19 was associated with type 2 diabetes. The information obtained from our study would be helpful for genotyping accuracies of SNPs residing in the CNVs region.     

Replication stress and mechanisms of CNV formation

Copy number variants (CNVs) are widely distributed throughout the human genome, where they contribute to genetic variation and phenotypic diversity. De novo CNVs are also a major cause of numerous genetic and developmental disorders. However, unlike many other types of mutations, little is known about the genetic and environmental risk factors for new and deleterious CNVs. DNA replication errors have been implicated in the generation of a major class of CNVs, the nonrecurrent CNVs. We have found that agents that perturb normal replication and create conditions of replication stress, including hydroxyurea and aphidicolin, are potent inducers of nonrecurrent CNVs in cultured human cells. These findings have broad implications for identifying CNV risk factors and for hydroxyurea-related therapies in humans.     

Copy number variants in pharmacogenetic genes

Variation in drug efficacy and toxicity remains an important clinical concern. Presently, single nucleotide polymorphisms (SNPs) only explain a portion of this problem, even in situations where the pharmacological trait is clearly heritable. The Human CNV Project identified copy number variations (CNVs) across approximately 12% of the human genome, and these CNVs were considered causes of diseases. Although the contribution of CNVs to the pathogenesis of many common diseases is questionable, CNVs play a clear role in drug-related genes by altering drug metabolizing and drug response. In this review, we provide a comprehensive evaluation of the clinical relevance of CNVs to drug efficacy, toxicity, and disease prevalence in world populations, and discuss the implication of using CNVs as a diagnostic tool in clinical intervention.     

Accuracy of CNV Detection from GWAS Data

Several computer programs are available for detecting copy number variants (CNVs) using genome-wide SNP arrays. We evaluated the performance of four CNV detection software suites--Birdsuite, Partek, HelixTree, and PennCNV-Affy--in the identification of both rare and common CNVs. Each program's performance was assessed in two ways. The first was its recovery rate, i.e., its ability to call 893 CNVs previously identified in eight HapMap samples by paired-end sequencing of whole-genome fosmid clones, and 51,440 CNVs identified by array Comparative Genome Hybridization (aCGH) followed by validation procedures, in 90 HapMap CEU samples. The second evaluation was program performance calling rare and common CNVs in the Bipolar Genome Study (BiGS) data set (1001 bipolar cases and 1033 controls, all of European ancestry) as measured by the Affymetrix SNP 6.0 array. Accuracy in calling rare CNVs was assessed by positive predictive value, based on the proportion of rare CNVs validated by quantitative real-time PCR (qPCR), while accuracy in calling common CNVs was assessed by false positive/false negative rates based on qPCR validation results from a subset of common CNVs. Birdsuite recovered the highest percentages of known HapMap CNVs containing >20 markers in two reference CNV datasets. The recovery rate increased with decreased CNV frequency. In the tested rare CNV data, Birdsuite and Partek had higher positive predictive values than the other software suites. In a test of three common CNVs in the BiGS dataset, Birdsuite's call was 98.8% consistent with qPCR quantification in one CNV region, but the other two regions showed an unacceptable degree of accuracy. We found relatively poor consistency between the two "gold standards," the sequence data of Kidd et al., and aCGH data of Conrad et al. Algorithms for calling CNVs especially common ones need substantial improvement, and a "gold standard" for detection of CNVs remains to be established.     

Accurate Distinction of Pathogenic from Benign CNVs in Mental Retardation

Copy number variants (CNVs) have recently been recognized as a common form of genomic variation in humans. Hundreds of CNVs can be detected in any individual genome using genomic microarrays or whole genome sequencing technology, but their phenotypic consequences are still poorly understood. Rare CNVs have been reported as a frequent cause of neurological disorders such as mental retardation (MR), schizophrenia and autism, prompting widespread implementation of CNV screening in diagnostics. In previous studies we have shown that, in contrast to benign CNVs, MR-associated CNVs are significantly enriched in genes whose mouse orthologues, when disrupted, result in a nervous system phenotype. In this study we developed and validated a novel computational method for differentiating between benign and MR-associated CNVs using structural and functional genomic features to annotate each CNV. In total 13 genomic features were included in the final version of a Naïve Bayesian Tree classifier, with LINE density and mouse knock-out phenotypes contributing most to the classifier''s accuracy. After demonstrating that our method (called GECCO) perfectly classifies CNVs causing known MR-associated syndromes, we show that it achieves high accuracy (94%) and negative predictive value (99%) on a blinded test set of more than 1,200 CNVs from a large cohort of individuals with MR. These results indicate that this classification method will be of value for objectively prioritizing CNVs in clinical research and diagnostics.     

Identification of Rare Recurrent Copy Number Variants in High-Risk Autism Families and Their Prevalence in a Large ASD Population

Structural variation is thought to play a major etiological role in the development of autism spectrum disorders (ASDs), and numerous studies documenting the relevance of copy number variants (CNVs) in ASD have been published since 2006. To determine if large ASD families harbor high-impact CNVs that may have broader impact in the general ASD population, we used the Affymetrix genome-wide human SNP array 6.0 to identify 153 putative autism-specific CNVs present in 55 individuals with ASD from 9 multiplex ASD pedigrees. To evaluate the actual prevalence of these CNVs as well as 185 CNVs reportedly associated with ASD from published studies many of which are insufficiently powered, we designed a custom Illumina array and used it to interrogate these CNVs in 3,000 ASD cases and 6,000 controls. Additional single nucleotide variants (SNVs) on the array identified 25 CNVs that we did not detect in our family studies at the standard SNP array resolution. After molecular validation, our results demonstrated that 15 CNVs identified in high-risk ASD families also were found in two or more ASD cases with odds ratios greater than 2.0, strengthening their support as ASD risk variants. In addition, of the 25 CNVs identified using SNV probes on our custom array, 9 also had odds ratios greater than 2.0, suggesting that these CNVs also are ASD risk variants. Eighteen of the validated CNVs have not been reported previously in individuals with ASD and three have only been observed once. Finally, we confirmed the association of 31 of 185 published ASD-associated CNVs in our dataset with odds ratios greater than 2.0, suggesting they may be of clinical relevance in the evaluation of children with ASDs. Taken together, these data provide strong support for the existence and application of high-impact CNVs in the clinical genetic evaluation of children with ASD.     

Origins and breakpoint analyses of copy number variations: up close and personal

Array-based methods have enabled the detection of many genomic gains and losses. These are stated as copy number variants (CNVs) and comprise up to 13% of the human genome. Based on their breakpoints and modes of formation CNVs are termed recurrent or nonrecurrent. Recurrent CNVs are flanked by low copy repeats and are of a fixed size. They arise as a result of misalignment during meiosis by a mechanism named nonallelic homologous recombination. Several of such recurrent CNVs have been linked to human diseases. Nonrecurrent CNVs, which are not flanked by low copy repeats, are of variable size and may arise via mechanisms like nonhomologous end joining and replication-based mechanisms described by the fork stalling and template switching and microhomology-mediated break-induced replication models. It is becoming clear that most disease-causing CNVs are nonrecurrent and generally arise via replication-based mechanisms. Furthermore, it is now appreciated that genomic features other than low copy repeats play a role in the formation of nonrecurrent CNVs. This review will discuss the different mechanisms of CNV formation and how high resolution analyses of CNV breakpoints have added to our knowledge of their precise structure.     

基因拷贝数异常的研究进展

基因拷贝数异常(copy number variations,CNVs)是广泛存在于人体基因组的一种结构变异现象,主要包括拷贝数的缺失、插入、重组以及多位点的复杂变异等。最初是在病人的基因组中发现,后来的研究表明在正常人体中也普遍存在。有关CNVs的研究将随机个体之间的基因组差异估计值大大提高,极大的改变了人们的认识。目前,关于CNVs的研究多处在初步探索阶段,CNVs如何导致疾病,以及如何引起基因等的改变而诱发疾病的机理也需更进一步的研究加以验证和证实。该文主要就近年来关于CNVs的研究进展作一综述。     

Epigenetic silencing of genomic structural variations

A great amount of copy number variations (CNVs) are identified in the human genome. Most of them are neutral; nevertheless, the role of CNVs in the pathogenesis of hereditary diseases is still significant. Especially, this is important for neuropsychiatric disorders, such as intellectual disability and autism. When analyzing the CNV-associated diseases, the controversial question is to distinguish the pathogenic CNVs among common polymorphic variants and to predict the disease risk in other children of the family. Unfortunately, the mechanisms of phenotypic expression and incomplete penetrance of CNVs remain largely unknown. Currently, incomplete penetrance and variable expressivity of CNVs are attributed mainly to allelic interaction of different genetic variations. However, epigenetic mechanisms of gene expression regulation in the context of structural variation of the genome are poorly explored. It is possible that epigenetic modifications of the genome regions with CNVs may underlie the understanding of ways of phenotypic manifestations of structural variations in the human genome.     

High frequencies of de novo CNVs in bipolar disorder and schizophrenia

While it is known that rare copy-number variants (CNVs) contribute to risk for some neuropsychiatric disorders, the role of CNVs in bipolar disorder is unclear. Here, we reasoned that a contribution of CNVs to mood disorders might be most evident for de novo mutations. We performed a genome-wide analysis of de novo CNVs in a cohort of 788 trios. Diagnoses of offspring included bipolar disorder (n?= 185), schizophrenia (n?= 177), and healthy controls (n?= 426). Frequencies of de novo CNVs were significantly higher in bipolar disorder as compared with controls (OR?= 4.8 [1.4,16.0], p?= 0.009). De novo CNVs were particularly enriched among cases with an age at onset younger than 18 (OR?= 6.3 [1.7,22.6], p?= 0.006). We also confirmed a significant enrichment of de novo CNVs in schizophrenia (OR?= 5.0 [1.5,16.8], p?= 0.007). Our results suggest that rare spontaneous mutations are an important contributor to risk for bipolar disorder and other major neuropsychiatric diseases.