CONAN: copy number variation analysis software for genome-wide association studies

Background  

Genome-wide association studies (GWAS) based on single nucleotide polymorphisms (SNPs) revolutionized our perception of the genetic regulation of complex traits and diseases. Copy number variations (CNVs) promise to shed additional light on the genetic basis of monogenic as well as complex diseases and phenotypes. Indeed, the number of detected associations between CNVs and certain phenotypes are constantly increasing. However, while several software packages support the determination of CNVs from SNP chip data, the downstream statistical inference of CNV-phenotype associations is still subject to complicated and inefficient in-house solutions, thus strongly limiting the performance of GWAS based on CNVs.     

Single-cell copy number variation detection

Detection of chromosomal aberrations from a single cell by array comparative genomic hybridization (single-cell array CGH), instead of from a population of cells, is an emerging technique. However, such detection is challenging because of the genome artifacts and the DNA amplification process inherent to the single cell approach. Current normalization algorithms result in inaccurate aberration detection for single-cell data. We propose a normalization method based on channel, genome composition and recurrent genome artifact corrections. We demonstrate that the proposed channel clone normalization significantly improves the copy number variation detection in both simulated and real single-cell array CGH data.     

The impact of errors in copy number variation detection algorithms on association results

The inaccuracy of copy number variation (CNV) detection on single nucleotide polymorphism (SNP) arrays has recently been brought to attention. Such high error rates will undoubtedly have ramifications on downstream association testing. We examined this effect for a wide range of scenarios and found a noticeable decrease in power for error rates typical of CNV calling algorithms. We compared power using CNV calls to the log relative ratio and found the latter to be superior when error rates are moderate to large or when the CNV size is small. It is our recommendation that CNV researchers use intensity measurements as an alternative to CNV calls in these scenarios.     

cnvHiTSeq: integrative models for high-resolution copy number variation detection and genotyping using population sequencing data

Recent advances in sequencing technologies provide the means for identifying copy number variation (CNV) at an unprecedented resolution. A single next-generation sequencing experiment offers several features that can be used to detect CNV, yet current methods do not incorporate all available signatures into a unified model. cnvHiTSeq is an integrative probabilistic method for CNV discovery and genotyping that jointly analyzes multiple features at the population level. By combining evidence from complementary sources, cnvHiTSeq achieves high genotyping accuracy and a substantial improvement in CNV detection sensitivity over existing methods, while maintaining a low false discovery rate. cnvHiTSeq is available at http://sourceforge.net/projects/cnvhitseq     

Genomic copy number variation in Mus musculus

Background

Copy number variation is an important dimension of genetic diversity and has implications in development and disease. As an important model organism, the mouse is a prime candidate for copy number variant (CNV) characterization, but this has yet to be completed for a large sample size. Here we report CNV analysis of publicly available, high-density microarray data files for 351 mouse tail samples, including 290 mice that had not been characterized for CNVs previously.

Results

We found 9634 putative autosomal CNVs across the samples affecting 6.87 % of the mouse reference genome. We find significant differences in the degree of CNV uniqueness (single sample occurrence) and the nature of CNV-gene overlap between wild-caught mice and classical laboratory strains. CNV-gene overlap was associated with lipid metabolism, pheromone response and olfaction compared to immunity, carbohydrate metabolism and amino-acid metabolism for wild-caught mice and classical laboratory strains, respectively. Using two subspecies of wild-caught Mus musculus, we identified putative CNVs unique to those subspecies and show this diversity is better captured by wild-derived laboratory strains than by the classical laboratory strains. A total of 9 genic copy number variable regions (CNVRs) were selected for experimental confirmation by droplet digital PCR (ddPCR).

Conclusion

The analysis we present is a comprehensive, genome-wide analysis of CNVs in Mus musculus, which increases the number of known variants in the species and will accelerate the identification of novel variants in future studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1713-z) contains supplementary material, which is available to authorized users.     

What a difference copy number variation makes

DNA copy number variation (CNV) represents a considerable source of human genetic diversity. Recently,1 a global map of copy number variation in the human genome has been drawn up which reveals not only the ubiquity but also the complexity of this type of variation. Thus, two human genomes may differ by more than 20 Mb and it is likely that the full extent of CNV still remains to be discovered. Nearly 3000 genes are associated with CNV. This high degree of variability with regard to gene copy number between two individuals challenges definitions of normality. Many CNVs are located in regions of complex genomic structure and this currently limits the extent to which these variants can be genotyped by using tagging SNPs. However, some CNVs are already amenable to genome-wide association studies so that their influence on human phenotypic diversity and disease susceptibility may soon be determined.     

tRNA gene copy number variation in humans

The human tRNAome consists of more than 500 interspersed tRNA genes comprising 51 anticodon families of largely unequal copy number. We examined tRNA gene copy number variation (tgCNV) in six individuals; two kindreds of two parents and a child, using high coverage whole genome sequence data. Such differences may be important because translation of some mRNAs is sensitive to the relative amounts of tRNAs and because tRNA competition determines translational efficiency vs. fidelity and production of native vs. misfolded proteins. We identified several tRNA gene clusters with CNV, which in some cases were part of larger iterations. In addition there was an isolated tRNALysCUU gene that was absent as a homozygous deletion in one of the parents. When assessed by semiquantitative PCR in 98 DNA samples representing a wide variety of ethnicities, this allele was found deleted in hetero- or homozygosity in all groups at ~ 50% frequency. This is the first report of copy number variation of human tRNA genes. We conclude that tgCNV exists at significant levels among individual humans and discuss the results in terms of genetic diversity and prior genome wide association studies (GWAS) that suggest the importance of the ratio of tRNALys isoacceptors in Type-2 diabetes.     

SCNVSim: somatic copy number variation and structure variation simulator

Background

Somatically acquired structure variations (SVs) and copy number variations (CNVs) can induce genetic changes that are directly related to tumor genesis. Somatic SV/CNV detection using next-generation sequencing (NGS) data still faces major challenges introduced by tumor sample characteristics, such as ploidy, heterogeneity, and purity. A simulated cancer genome with known SVs and CNVs can serve as a benchmark for evaluating the performance of existing somatic SV/CNV detection tools and developing new methods.

Results

SCNVSim is a tool for simulating somatic CNVs and structure variations SVs. Other than multiple types of SV and CNV events, the tool is capable of simulating important features related to tumor samples including aneuploidy, heterogeneity and purity.

Conclusions

SCNVSim generates the genomes of a cancer cell population with detailed information of copy number status, loss of heterozygosity (LOH), and event break points, which is essential for developing and evaluating somatic CNV and SV detection methods in cancer genomics studies.     

Human gene copy number variation and infectious disease

Variability in the susceptibility to infectious disease and its clinical manifestation can be determined by variation in the environment and by genetic variation in the pathogen and the host. Despite several successes based on candidate gene studies, defining the host variation affecting infectious disease has not been as successful as for other multifactorial diseases. Both single nucleotide variation and copy number variation (CNV) of the host contribute to the host’s susceptibility to infectious disease. In this review we focus on CNV, particularly on complex multiallelic CNV that is often not well characterised either directly by hybridisation methods or indirectly by analysis of genotypes and flanking single nucleotide variants. We summarise the well-known examples, such as α-globin deletion and susceptibility to severe malaria, as well as more recent controversies, such as the extensive CNV of the chemokine gene CCL3L1 and HIV infection. We discuss the potential biological mechanisms that could underly any genetic association and reflect on the extensive complexity and functional variation generated by a combination of CNV and sequence variation, as illustrated by the Fc gamma receptor genes FCGR3A, FCGR3B and FCGR2C. We also highlight some understudied areas that might prove fruitful areas for further research.     

拷贝数变异的全基因组关联分析

基因组拷贝数变异(copy number variations,CNVs)是指与基因组参考序列相比,基因组中≥1 kb的DNA片段插入、缺失和/或扩增,及其互相组合衍生出的复杂变异．由于其具有分布范围广、可遗传、相对稳定和高度异质性等特点,目前认为,CNVs是一种新的可以作为疾病易感标志的基因组DNA多态性,其变异引起的基因剂量改变可以导致表型改变．最近,一种基于CNVs的新的疾病易感基因鉴定策略——CNV全基因组关联分析开始出现,这一策略和传统的基于单核苷酸多态性的关联分析具有互补性,通过认识基因组结构变异可以认识复杂疾病的分子机制和遗传基础．     

Implications of copy number variation in people with chromosomal abnormalities: potential for greater variation in copy number state may contribute to variability of phenotype

Copy number variation is common in the human genome with many regions, overlapping thousands of genes, now known to be deleted or amplified. Aneuploidies and other forms of chromosomal imbalance have a wide range of adverse phenotypes and are a common cause of birth defects resulting in significant morbidity and mortality. “Normal” copy number variants (CNVs) embedded within the regions of chromosome imbalance may affect the clinical outcomes by altering the local copy number of important genes or regulatory regions: this could alleviate or exacerbate certain phenotypes. In this way CNVs may contribute to the clinical variability seen in many disorders caused by chromosomal abnormalities, such as the congenital heart defects (CHD) seen in ~40% of Down’s syndrome (DS) patients. Investigation of CNVs may therefore help to pinpoint critical genes or regulatory elements, elucidating the molecular mechanisms underlying these conditions, also shedding light on the aetiology of such phenotypes in people without major chromosome imbalances, and ultimately leading to their improved detection and treatment.     

Rare copy number deletions predict individual variation in intelligence

Phenotypic variation in human intellectual functioning shows substantial heritability, as demonstrated by a long history of behavior genetic studies. Many recent molecular genetic studies have attempted to uncover specific genetic variations responsible for this heritability, but identified effects capture little variance and have proven difficult to replicate. The present study, motivated an interest in “mutation load” emerging from evolutionary perspectives, examined the importance of the number of rare (or infrequent) copy number variations (CNVs), and the total number of base pairs included in such deletions, for psychometric intelligence. Genetic data was collected using the Illumina 1MDuoBeadChip Array from a sample of 202 adult individuals with alcohol dependence, and a subset of these (N = 77) had been administered the Wechsler Abbreviated Scale of Intelligence (WASI). After removing CNV outliers, the impact of rare genetic deletions on psychometric intelligence was investigated in 74 individuals. The total length of the rare deletions significantly and negatively predicted intelligence (r = −.30, p = .01). As prior studies have indicated greater heritability in individuals with relatively higher parental socioeconomic status (SES), we also examined the impact of ethnicity (Anglo/White vs. Other), as a proxy measure of SES; these groups did not differ on any genetic variable. This categorical variable significantly moderated the effect of length of deletions on intelligence, with larger effects being noted in the Anglo/White group. Overall, these results suggest that rare deletions (between 5% and 1% population frequency or less) adversely affect intellectual functioning, and that pleotropic effects might partly account for the association of intelligence with health and mental health status. Significant limitations of this research, including issues of generalizability and CNV measurement, are discussed.     

Retrotransposon distribution and copy number variation in gymnosperm genomes

Retrotransposable elements (REs) and related sequences form a large proportion of conifer genomes. During genome evolution, some RE sequences are degraded or eliminated, but some are evolutionarily stable, and can be identified even in distantly related species. Use of genome sequence information from loblolly pine (Pinus taeda) enables investigation of divergent non-coding RE sequences in other pine and conifer species, including Scots pine (Pinus sylvestris). Non-specific inter-retrotransposon amplified polymorphism technique (IRAP) as well as the amplification polymorphism of 12 RE families were investigated in 80 gymnosperm species. The obtained results were compared with phylogenetic relationships among gymnosperms. Investigation of distantly related gymnosperm species reveals persistent RE sequences, such as IFG and Pineywoods, distributed among a wide range of plant lineages. RE sequence divergence was observed, reflecting periods of inactivity and degradation during speciation of pine lineages, as demonstrated by the delineation of the main pine subgenera. Intraspecific variation of 10 RE copy numbers (CN) between Scots pine individuals ranged from 8.9 to 26.6% of the overall mean estimates. CN analyses were performed in 16 additional gymnosperm species. The analysed pine species contained a similar complement of RE families; however, CN and genome occupation proportions differ. A decrease in RE CN estimates can reflect sequence divergence, associated with independent transposition events. Transposition of some REs can be induced by stress conditions; therefore, even distantly related species inhabiting extreme environments could have similar patterns or distribution of these elements.     

A preliminary study of copy number variation in tibetans

Genetic features of Tibetans have been broadly investigated, but the properties of copy number variation (CNV) have not been well examined. To get a preliminary view of CNV in Tibetans, we scanned 29 Tibetan genomes with the Illumina Human-1 M high-resolution genotyping microarray and identified 139 putative copy number variable regions (CNVRs), consisting of 70 deletions, 61 duplications, and 8 multi-allelic loci. Thirty-four of the 139 CNVRs showed differential allele frequencies versus other East-Asian populations, with P values <0.0001. These results indicated a distinct pattern of CNVR allele frequency distribution in Tibetans. The Tibetan CNVRs are enriched for genes in the disease class of human reproduction (such as genes from the DAZ, BPY2, CDY, and HLA-DQ and -DR gene clusters) and biological process categories of "response to DNA damage stimulus" and "DNA repair" (such as RAD51, RAD52, and MRE11A). These genes are related to the adaptive traits of high infant birth weight and darker skin tone of Tibetans, and may be attributed to recent local adaptation. Our results provide a different view of genetic diversity in Tibetans and new insights into their high-altitude adaptation.     

Microarray analysis of copy number variation in single cells

We present a protocol for reliably detecting DNA copy number aberrations in a single human cell. Multiple displacement-amplified DNAs of a cell are hybridized to a 3,000-bacterial artificial chromosome (BAC) array and to an Affymetrix 250,000 (250K)-SNP array. Subsequent copy number calling is based on the integration of BAC probe-specific copy number probabilities that are estimated by comparing probe intensities with a single-cell whole-genome amplification (WGA) reference model for diploid chromosomes, as well as SNP copy number and loss-of-heterozygosity states estimated by hidden Markov models (HMM). All methods for detecting DNA copy number aberrations in single human cells have difficulty in confidently discriminating WGA artifacts from true genetic variants. Furthermore, some methods lack thorough validation for segmental DNA imbalance detection. Our protocol minimizes false-positive variant calling and enables uniparental isodisomy detection in single cells. Additionally, it provides quality assessment, allowing the exclusion of uninterpretable single-cell WGA samples. The protocol takes 5-7 d.     

Identification of copy number variation hotspots in human populations

Copy number variants (CNVs) in the human genome contribute to both Mendelian and complex traits as well as to genomic plasticity in evolution. The investigation of mutational rates of CNVs is critical to understanding genomic instability and the etiology of the copy number variation (CNV)-related traits. However, the evaluation of the CNV mutation rate at the genome level poses an insurmountable practical challenge that requires large samples and accurate typing. In this study, we show that an approximate estimation of the CNV mutation rate could be achieved by using the phylogeny information of flanking SNPs. This allows a genome-wide comparison of mutation rates between CNVs with the use of vast, readily available data of SNP genotyping. A total of 4187 CNV regions (CNVRs) previously identified in HapMap populations were investigated in this study. We showed that the mutation rates for the majority of these CNVRs are at the order of 10⁻⁵ per generation, consistent with experimental observations at individual loci. Notably, the mutation rates of 104 (2.5%) CNVRs were estimated at the order of 10⁻³ per generation; therefore, they were identified as potential hotspots. Additional analyses revealed that genome architecture at CNV loci has a potential role in inciting mutational hotspots in the human genome. Interestingly, 49 (47%) CNV hotspots include human genes, some of which are known to be functional CNV loci (e.g., CNVs of C4 and β-defensin causing autoimmune diseases and CNVs of HYDIN with implication in control of cerebral cortex size), implicating the important role of CNV in human health and evolution, especially in common and complex diseases.     

A hierarchical clustering method for estimating copy number variation

Microarray technologies allow for simultaneous measurement of DNA copy number at thousands of positions in a genome. Gains and losses of DNA sequences reveal themselves through characteristic patterns of hybridization intensity. To identify change points along the chromosomes, we develop a marker clustering method which consists of 2 parts. First, a "circular clustering tree test statistic" attaches a statistic to each marker that measures the likelihood that it is a change point. Then construction of the marker statistics is followed by outlier detection approaches. The method provides a new way to build up a binary tree that can accurately capture change-point signals and is easy to perform. A simulation study shows good performance in change-point detection, and cancer cell line data are used to illustrate performance when regions of true copy number changes are known.     

Rare copy number variation in extremely impulsively violent males

The genetic correlates of extreme impulsive violence are poorly understood, and there have been no studies that have systematically characterized a large group of affected individuals both clinically and genetically. We performed a genome‐wide rare copy number variant (CNV) analysis in 281 males from four Czech prisons who met strict clinical criteria for extreme impulsive violence. Inclusion criteria included age ≥ 18 years, an ICD‐10 diagnosis of Dissocial Personality Disorder, and the absence of an organic brain disorder. Participants underwent a structured psychiatric assessment to diagnose extreme impulsive violence and then provided a blood sample for genetic analysis. DNA was genotyped and CNVs were identified using Illumina HumanOmni2.5 single‐nucleotide polymorphism array platform. Comparing with 10851 external population controls, we identified 828 rare CNVs (frequency ≤ 0.1% among control samples) in 264 participants. The CNVs impacted 754 genes, with 124 genes impacted more than once (2‐25 times). Many of these genes are associated with autosomal dominant or X‐linked disorders affecting adult behavior, cognition, learning, intelligence, specifically expressed in the brain and relevant to synapses, neurodevelopment, neurodegeneration, obesity and neuropsychiatric phenotypes. Specifically, we identified 31 CNVs of clinical relevance in 31 individuals, 59 likely clinically relevant CNVs in 49 individuals, and 17 recurrent CNVs in 65 individuals. Thus, 123 of 281 (44%) individuals had one to several rare CNVs that were indirectly or directly relevant to impulsive violence. Extreme impulsive violence is genetically heterogeneous and genomic analysis is likely required to identify, further research and specifically treat the causes in affected individuals.