Bias of selection on human copy-number variants

Although large-scale copy-number variation is an important contributor to conspecific genomic diversity, whether these variants frequently contribute to human phenotype differences remains unknown. If they have few functional consequences, then copy-number variants (CNVs) might be expected both to be distributed uniformly throughout the human genome and to encode genes that are characteristic of the genome as a whole. We find that human CNVs are significantly overrepresented close to telomeres and centromeres and in simple tandem repeat sequences. Additionally, human CNVs were observed to be unusually enriched in those protein-coding genes that have experienced significantly elevated synonymous and nonsynonymous nucleotide substitution rates, estimated between single human and mouse orthologues. CNV genes encode disproportionately large numbers of secreted, olfactory, and immunity proteins, although they contain fewer than expected genes associated with Mendelian disease. Despite mouse CNVs also exhibiting a significant elevation in synonymous substitution rates, in most other respects they do not differ significantly from the genomic background. Nevertheless, they encode proteins that are depleted in olfactory function, and they exhibit significantly decreased amino acid sequence divergence. Natural selection appears to have acted discriminately among human CNV genes. The significant overabundance, within human CNVs, of genes associated with olfaction, immunity, protein secretion, and elevated coding sequence divergence, indicates that a subset may have been retained in the human population due to the adaptive benefit of increased gene dosage. By contrast, the functional characteristics of mouse CNVs either suggest that advantageous gene copies have been depleted during recent selective breeding of laboratory mouse strains or suggest that they were preferentially fixed as a consequence of the larger effective population size of wild mice. It thus appears that CNV differences among mouse strains do not provide an appropriate model for large-scale sequence variations in the human population.     

Copy number polymorphism in plant genomes

Copy number variants (CNVs) are genomic rearrangements resulting from gains or losses of DNA segments. Typically, the term refers to rearrangements of sequences larger than 1 kb. This type of polymorphism has recently been shown to be a key contributor to intra-species genetic variation, along with single-nucleotide polymorphisms and short insertion-deletion polymorphisms. Over the last decade, a growing number of studies have highlighted the importance of copy number variation (CNV) as a factor affecting human phenotype and individual CNVs have been linked to risks for severe diseases. In plants, the exploration of the extent and role of CNV is still just beginning. Initial genomic analyses indicate that CNVs are prevalent in plants and have greatly affected plant genome evolution. Many CNV events have been observed in outcrossing and autogamous species. CNVs are usually found on all chromosomes, with CNV hotspots interspersed with regions of very low genetic variation. Although CNV is mainly associated with intergenic regions, many CNVs encompass protein-coding genes. The collected data suggest that CNV mainly affects the members of large families of functionally redundant genes. Thus, the effects of individual CNV events on phenotype are usually modest. Nevertheless, there are many cases in which CNVs for specific genes have been linked to important traits such as flowering time, plant height and resistance to biotic and abiotic stress. Recent reports suggest that CNVs may form rapidly in response to stress.     

Extensive Copy-Number Variation of Young Genes across Stickleback Populations

Duplicate genes emerge as copy-number variations (CNVs) at the population level, and remain copy-number polymorphic until they are fixed or lost. The successful establishment of such structural polymorphisms in the genome plays an important role in evolution by promoting genetic diversity, complexity and innovation. To characterize the early evolutionary stages of duplicate genes and their potential adaptive benefits, we combine comparative genomics with population genomics analyses to evaluate the distribution and impact of CNVs across natural populations of an eco-genomic model, the three-spined stickleback. With whole genome sequences of 66 individuals from populations inhabiting three distinct habitats, we find that CNVs generally occur at low frequencies and are often only found in one of the 11 populations surveyed. A subset of CNVs, however, displays copy-number differentiation between populations, showing elevated within-population frequencies consistent with local adaptation. By comparing teleost genomes to identify lineage-specific genes and duplications in sticklebacks, we highlight rampant gene content differences among individuals in which over 30% of young duplicate genes are CNVs. These CNV genes are evolving rapidly at the molecular level and are enriched with functional categories associated with environmental interactions, depicting the dynamic early copy-number polymorphic stage of genes during population differentiation.     

Copy Number Variations in Tilapia Genomes

Discovering the nature and pattern of genome variation is fundamental in understanding phenotypic diversity among populations. Although several millions of single nucleotide polymorphisms (SNPs) have been discovered in tilapia, the genome-wide characterization of larger structural variants, such as copy number variation (CNV) regions has not been carried out yet. We conducted a genome-wide scan for CNVs in 47 individuals from three tilapia populations. Based on 254 Gb of high-quality paired-end sequencing reads, we identified 4642 distinct high-confidence CNVs. These CNVs account for 1.9% (12.411 Mb) of the used Nile tilapia reference genome. A total of 1100 predicted CNVs were found overlapping with exon regions of protein genes. Further association analysis based on linear model regression found 85 CNVs ranging between 300 and 27,000 base pairs significantly associated to population types (R ² > 0.9 and P > 0.001). Our study sheds first insights on genome-wide CNVs in tilapia. These CNVs among and within tilapia populations may have functional effects on phenotypes and specific adaptation to particular environments.     

Novel origins of copy number variation in the dog genome

ABSTRACT: BACKGROUND: Copy number variants (CNVs) account for substantial variation between genomes and are a major source of normal and pathogenic phenotypic differences. The dog is an ideal model to investigate mutational mechanisms that generate CNVs as its genome lacks a functional ortholog of the PRDM9 gene implicated in recombination and CNV formation in humans. Here we comprehensively assay CNVs using high-density array comparative genomic hybridization in 50 dogs from 17 dog breeds and 3 gray wolves. RESULTS: We use a stringent new method to identify a total of 430 high-confidence CNV loci, that range in size from 9 kb to 1.6 Mb and span 26.4 Mb, or 1.08%, of the assayed dog genome, overlapping 413 annotated genes. 98% of CNVs observed in each breed are also observed in multiple breeds. CNVs predicted to disrupt gene function are significantly less common than expected by chance. We identify a significant overrepresentation of peaks of GC content, previously shown to be enriched in dog recombination hotspots, in the vicinity of CNV breakpoints. CONCLUSIONS: A number of the CNVs identified by this study are candidates for generating breed-specific phenotypes. Purifying selection seems to be a major factor shaping structural variation in the dog genome, suggesting that many CNVs are deleterious. Localized peaks of GC content appear to be novel sites of CNV formation in the dog genome by non-allelic homologous recombination, potentially activated by the loss of PRDM9. These sequence features may have driven genome instability and chromosomal rearrangements throughout canid evolution.     

Outlier-Based Identification of Copy Number Variations Using Targeted Resequencing in a Small Cohort of Patients with Tetralogy of Fallot

Copy number variations (CNVs) are one of the main sources of variability in the human genome. Many CNVs are associated with various diseases including cardiovascular disease. In addition to hybridization-based methods, next-generation sequencing (NGS) technologies are increasingly used for CNV discovery. However, respective computational methods applicable to NGS data are still limited. We developed a novel CNV calling method based on outlier detection applicable to small cohorts, which is of particular interest for the discovery of individual CNVs within families, de novo CNVs in trios and/or small cohorts of specific phenotypes like rare diseases. Approximately 7,000 rare diseases are currently known, which collectively affect ∼6% of the population. For our method, we applied the Dixon’s Q test to detect outliers and used a Hidden Markov Model for their assessment. The method can be used for data obtained by exome and targeted resequencing. We evaluated our outlier- based method in comparison to the CNV calling tool CoNIFER using eight HapMap exome samples and subsequently applied both methods to targeted resequencing data of patients with Tetralogy of Fallot (TOF), the most common cyanotic congenital heart disease. In both the HapMap samples and the TOF cases, our method is superior to CoNIFER, such that it identifies more true positive CNVs. Called CNVs in TOF cases were validated by qPCR and HapMap CNVs were confirmed with available array-CGH data. In the TOF patients, we found four copy number gains affecting three genes, of which two are important regulators of heart development (NOTCH1, ISL1) and one is located in a region associated with cardiac malformations (PRODH at 22q11). In summary, we present a novel CNV calling method based on outlier detection, which will be of particular interest for the analysis of de novo or individual CNVs in trios or cohorts up to 30 individuals, respectively.     

An algorithm for inferring complex haplotypes in a region of copy-number variation

Recent studies have extensively examined the large-scale genetic variants in the human genome known as copy-number variations (CNVs), and the universality of CNVs in normal individuals, along with their functional importance, has been increasingly recognized. However, the absence of a method to accurately infer alleles or haplotypes within a CNV region from high-throughput experimental data hampers the finer analyses of CNV properties and applications to disease-association studies. Here we developed an algorithm to infer complex haplotypes within a CNV region by using data obtained from high-throughput experimental platforms. We applied this algorithm to experimental data and estimated the population frequencies of haplotypes that can yield information on both sequences and numbers of DNA copies. These results suggested that the analysis of such complex haplotypes is essential for accurately detecting genetic differences within a CNV region between population groups.     

Haplotype Phasing and Inheritance of Copy Number Variants in Nuclear Families

DNA copy number variants (CNVs) that alter the copy number of a particular DNA segment in the genome play an important role in human phenotypic variability and disease susceptibility. A number of CNVs overlapping with genes have been shown to confer risk to a variety of human diseases thus highlighting the relevance of addressing the variability of CNVs at a higher resolution. So far, it has not been possible to deterministically infer the allelic composition of different haplotypes present within the CNV regions. We have developed a novel computational method, called PiCNV, which enables to resolve the haplotype sequence composition within CNV regions in nuclear families based on SNP genotyping microarray data. The algorithm allows to i) phase normal and CNV-carrying haplotypes in the copy number variable regions, ii) resolve the allelic copies of rearranged DNA sequence within the haplotypes and iii) infer the heritability of identified haplotypes in trios or larger nuclear families. To our knowledge this is the first program available that can deterministically phase null, mono-, di-, tri- and tetraploid genotypes in CNV loci. We applied our method to study the composition and inheritance of haplotypes in CNV regions of 30 HapMap Yoruban trios and 34 Estonian families. For 93.6% of the CNV loci, PiCNV enabled to unambiguously phase normal and CNV-carrying haplotypes and follow their transmission in the corresponding families. Furthermore, allelic composition analysis identified the co-occurrence of alternative allelic copies within 66.7% of haplotypes carrying copy number gains. We also observed less frequent transmission of CNV-carrying haplotypes from parents to children compared to normal haplotypes and identified an emergence of several de novo deletions and duplications in the offspring.     

Copy number variants in a highly inbred Iberian porcine strain

We carried out a comprehensive genomic analysis of porcine copy number variants (CNVs) based on whole‐genome SNP genotyping data and provided new measures of genomic diversity (number, length and distribution of CNV events) for a highly inbred strain (the Guadyerbas strain). This strain represents one of the most ancient surviving populations of the Iberian breed, and it is currently in serious danger of extinction. CNV detection was conducted on the complete Guadyerbas population, adjusted for genomic waves, and used strict quality criteria, pedigree information and the latest porcine genome annotation. The analysis led to the detection of 65 CNV regions (CNVRs). These regions cover 0.33% of the autosomal genome of this particular strain. Twenty‐nine of these CNVRs were identified here for the first time. The relatively low number of detected CNVRs is in line with the low variability and high inbreeding estimated previously for this Iberian strain using pedigree, microsatellite or SNP data. A comparison across different porcine studies has revealed that more than half of these regions overlap with previously identified CNVRs or multicopy regions. Also, a preliminary analysis of CNV detection using whole‐genome sequence data for four Guadyerbas pigs showed overlapping for 16 of the CNVRs, supporting their reliability. Some of the identified CNVRs contain relevant functional genes (e.g., the SCD and USP15 genes), which are worth being further investigated because of their importance in determining the quality of Iberian pig products. The CNVR data generated could be useful for improving the porcine genome annotation.     

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.     

The application of gene co-expression network reconstruction based on CNVs and gene expression microarray data in breast cancer

Copy number variations (CNVs) are one type of the human genetic variations and are pervasive in the human genome. It has been confirmed that they can play a causal role in complex diseases. Previous studies of CNVs focused more on identifying the disease-specific CNV regions or candidate genes on these CNV regions, but less on the synergistic actions between genes on CNV regions and other genes. Our research combined the CNVs with related gene co-expression to reconstruct gene co-expression network by using single nucleotide polymorphism microarray datasets and gene microarray datasets of breast cancer, and then extracted the modules which connected densely inside and analyzed the functions of modules. Interestingly, all of these modules’ functions were related to breast cancer according to our enrichment analysis, and most of the genes in these modules have been reported to be involved in breast cancer. Our findings suggested that integrating CNVs and gene co-expressed relations was an available way to analyze the roles of CNV genes and their synergistic genes in breast cancer, and provided a novel insight into the pathological mechanism of breast cancer.     

Genome-Wide Identification of Copy Number Variations in Chinese Holstein

Recent studies of mammalian genomes have uncovered the vast extent of copy number variations (CNVs) that contribute to phenotypic diversity. Compared to SNP, a CNV can cover a wider chromosome region, which may potentially incur substantial sequence changes and induce more significant effects on phenotypes. CNV has been becoming an alternative promising genetic marker in the field of genetic analyses. Here we firstly report an account of CNV regions in the cattle genome in Chinese Holstein population. The Illumina Bovine SNP50K Beadchips were used for screening 2047 Holstein individuals. Three different programes (PennCNV, cnvPartition and GADA) were implemented to detect potential CNVs. After a strict CNV calling pipeline, a total of 99 CNV regions were identified in cattle genome. These CNV regions cover 23.24 Mb in total with an average size of 151.69 Kb. 52 out of these CNV regions have frequencies of above 1%. 51 out of these CNV regions completely or partially overlap with 138 cattle genes, which are significantly enriched for specific biological functions, such as signaling pathway, sensory perception response and cellular processes. The results provide valuable information for constructing a more comprehensive CNV map in the cattle genome and offer an important resource for investigation of genome structure and genomic variation underlying traits of interest in cattle.     

Spectrum of large copy number variations in 26 diverse Indian populations: potential involvement in phenotypic diversity

Copy number variations (CNVs) have provided a dynamic aspect to the apparently static human genome. We have analyzed CNVs larger than 100 kb in 477 healthy individuals from 26 diverse Indian populations of different linguistic, ethnic and geographic backgrounds. These CNVRs were identified using the Affymetrix 50K Xba 240 Array. We observed 1,425 and 1,337 CNVRs in the deletion and amplification sets, respectively, after pooling data from all the populations. More than 50% of the genes encompassed entirely in CNVs had both deletions and amplifications. There was wide variability across populations not only with respect to CNV extent (ranging from 0.04–1.14% of genome under deletion and 0.11–0.86% under amplification) but also in terms of functional enrichments of processes like keratinization, serine proteases and their inhibitors, cadherins, homeobox, olfactory receptors etc. These did not correlate with linguistic, ethnic, geographic backgrounds and size of populations. Certain processes were near exclusive to deletion (serine proteases, keratinization, olfactory receptors, GPCRs) or duplication (homeobox, serine protease inhibitors, embryonic limb morphogenesis) datasets. Populations having same enriched processes were observed to contain genes from different genomic loci. Comparison of polymorphic CNVRs (5% or more) with those cataloged in Database of Genomic Variants revealed that 78% (2473) of the genes in CNVRs in Indian populations are novel. Validation of CNVs using Sequenom MassARRAY revealed extensive heterogeneity in CNV boundaries. Exploration of CNV profiles in such diverse populations would provide a widely valuable resource for understanding diversity in phenotypes and disease.     

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.     

The fine-scale and complex architecture of human copy-number variation

Despite considerable excitement over the potential functional significance of copy-number variants (CNVs), we still lack knowledge of the fine-scale architecture of the large majority of CNV regions in the human genome. In this study, we used a high-resolution array-based comparative genomic hybridization (aCGH) platform that targeted known CNV regions of the human genome at approximately 1 kb resolution to interrogate the genomic DNAs of 30 individuals from four HapMap populations. Our results revealed that 1020 of 1153 CNV loci (88%) were actually smaller in size than what is recorded in the Database of Genomic Variants based on previously published studies. A reduction in size of more than 50% was observed for 876 CNV regions (76%). We conclude that the total genomic content of currently known common human CNVs is likely smaller than previously thought. In addition, approximately 8% of the CNV regions observed in multiple individuals exhibited genomic architectural complexity in the form of smaller CNVs within larger ones and CNVs with interindividual variation in breakpoints. Future association studies that aim to capture the potential influences of CNVs on disease phenotypes will need to consider how to best ascertain this previously uncharacterized complexity.     

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.     

Genomic regions showing copy number variations associate with resistance or susceptibility to gastrointestinal nematodes in Angus cattle

Genomic structural variation is an important and abundant source of genetic and phenotypic variation. We previously reported an initial analysis of copy number variations (CNVs) in Angus cattle selected for resistance or susceptibility to gastrointestinal nematodes. In this study, we performed a large-scale analysis of CNVs using SNP genotyping data from 472 animals of the same population. We detected 811 candidate CNV regions, which represent 141.8 Mb (~4.7%) of the genome. To investigate the functional impacts of CNVs, we created 2 groups of 100 individual animals with extremely low or high estimated breeding values of eggs per gram of feces and referred to these groups as parasite resistant (PR) or parasite susceptible (PS), respectively. We identified 297 (~51 Mb) and 282 (~48 Mb) CNV regions from PR and PS groups, respectively. Approximately 60% of the CNV regions were specific to the PS group or PR group of animals. Selected PR- or PS-specific CNVs were further experimentally validated by quantitative PCR. A total of 297 PR CNV regions overlapped with 437 Ensembl genes enriched in immunity and defense, like WC1 gene which uniquely expresses on gamma/delta T cells in cattle. Network analyses indicated that the PR-specific genes were predominantly involved in gastrointestinal disease, immunological disease, inflammatory response, cell-to-cell signaling and interaction, lymphoid tissue development, and cell death. By contrast, the 282 PS CNV regions contained 473 Ensembl genes which are overrepresented in environmental interactions. Network analyses indicated that the PS-specific genes were particularly enriched for inflammatory response, immune cell trafficking, metabolic disease, cell cycle, and cellular organization and movement.     

High-resolution copy-number variation map reflects human olfactory receptor diversity and evolution

Olfactory receptors (ORs), which are involved in odorant recognition, form the largest mammalian protein superfamily. The genomic content of OR genes is considerably reduced in humans, as reflected by the relatively small repertoire size and the high fraction ( approximately 55%) of human pseudogenes. Since several recent low-resolution surveys suggested that OR genomic loci are frequently affected by copy-number variants (CNVs), we hypothesized that CNVs may play an important role in the evolution of the human olfactory repertoire. We used high-resolution oligonucleotide tiling microarrays to detect CNVs across 851 OR gene and pseudogene loci. Examining genomic DNA from 25 individuals with ancestry from three populations, we identified 93 OR gene loci and 151 pseudogene loci affected by CNVs, generating a mosaic of OR dosages across persons. Our data suggest that approximately 50% of the CNVs involve more than one OR, with the largest CNV spanning 11 loci. In contrast to earlier reports, we observe that CNVs are more frequent among OR pseudogenes than among intact genes, presumably due to both selective constraints and CNV formation biases. Furthermore, our results show an enrichment of CNVs among ORs with a close human paralog or lacking a one-to-one ortholog in chimpanzee. Interestingly, among the latter we observed an enrichment in CNV losses over gains, a finding potentially related to the known diminution of the human OR repertoire. Quantitative PCR experiments performed for 122 sampled ORs agreed well with the microarray results and uncovered 23 additional CNVs. Importantly, these experiments allowed us to uncover nine common deletion alleles that affect 15 OR genes and five pseudogenes. Comparison to the chimpanzee reference genome revealed that all of the deletion alleles are human derived, therefore indicating a profound effect of human-specific deletions on the individual OR gene content. Furthermore, these deletion alleles may be used in future genetic association studies of olfactory inter-individual differences.     

The influence of copy number polymorphism on the human phenotype

The variability of human populations in a large part is determined by two complementary factors: environment and genetic information. Genetic variation is caused by different genetic variants (polymorphisms and mutations) present in the human genome. Until recently it was thought that most of these variants are small changes of one or several nucleotides (SNPs) which in their millions are present in the human genome. However, it was recently shown that there are also polymorphisms that extend over hundreds of thousands of DNA base pairs in the human genome. Such alternations called copy number variation (CNV) often include genes and other functional genetic elements. In this article we present the general characteristics of copy number polymorphism and we discuss some examples of CNVs that influence human phenotypes.