Extensive copy-number variation of the human olfactory receptor gene family

As much as a quarter of the human genome has been reported to vary in copy number between individuals, including regions containing about half of the members of the olfactory receptor (OR) gene family. We have undertaken a detailed study of copy-number variation of ORs to elucidate the selective and mechanistic forces acting on this gene family and the true impact of copy-number variation on human OR repertoires. We argue that the properties of copy-number variants (CNVs) and other sets of large genomic regions violate the assumptions of statistical methods that are commonly used in the assessment of gene enrichment. Using more appropriate methods, we provide evidence that OR enrichment in CNVs is not due to positive selection but is because of OR preponderance in segmentally duplicated regions, which are known to be frequently copy-number variable, and because purifying selection against CNVs is lower in OR-containing regions than in regions containing essential genes. We also combine multiplex ligation-dependent probe amplification (MLPA) and PCR to assay the copy numbers of 37 candidate CNV ORs in a panel of ~50 human individuals. We confirm copy-number variation of 18 ORs but find no variation in this human-diversity panel for 16 other ORs, highlighting the caveat that reported intervals often overrepresent true CNVs. The copy-number variation we describe is likely to underpin significant variation in olfactory abilities among human individuals. Finally, we show that both homology-based and homology-independent processes have played a recent role in remodeling the OR family.     

Next-Generation Sequencing of Duplication CNVs Reveals that Most Are Tandem and Some Create Fusion Genes at Breakpoints

Interpreting the genomic and phenotypic consequences of copy-number variation (CNV) is essential to understanding the etiology of genetic disorders. Whereas deletion CNVs lead obviously to haploinsufficiency, duplications might cause disease through triplosensitivity, gene disruption, or gene fusion at breakpoints. The mutational spectrum of duplications has been studied at certain loci, and in some cases these copy-number gains are complex chromosome rearrangements involving triplications and/or inversions. However, the organization of clinically relevant duplications throughout the genome has yet to be investigated on a large scale. Here we fine-mapped 184 germline duplications (14.7 kb–25.3 Mb; median 532 kb) ascertained from individuals referred for diagnostic cytogenetics testing. We performed next-generation sequencing (NGS) and whole-genome sequencing (WGS) to sequence 130 breakpoints from 112 subjects with 119 CNVs and found that most (83%) were tandem duplications in direct orientation. The remainder were triplications embedded within duplications (8.4%), adjacent duplications (4.2%), insertional translocations (2.5%), or other complex rearrangements (1.7%). Moreover, we predicted six in-frame fusion genes at sequenced duplication breakpoints; four gene fusions were formed by tandem duplications, one by two interconnected duplications, and one by duplication inserted at another locus. These unique fusion genes could be related to clinical phenotypes and warrant further study. Although most duplications are positioned head-to-tail adjacent to the original locus, those that are inverted, triplicated, or inserted can disrupt or fuse genes in a manner that might not be predicted by conventional copy-number assays. Therefore, interpreting the genetic consequences of duplication CNVs requires breakpoint-level analysis.     

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.     

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.     

Origins and Long-Term Patterns of Copy-Number Variation in Rhesus Macaques

Mutations play a key role in the development of disease in an individual and the evolution of traits within species. Recent work in humans and other primates has clarified the origins and patterns of single-nucleotide variants, showing that most arise in the father’s germline during spermatogenesis. It remains unknown whether larger mutations, such as deletions and duplications of hundreds or thousands of nucleotides, follow similar patterns. Such mutations lead to copy-number variation (CNV) within and between species, and can have profound effects by deleting or duplicating genes. Here, we analyze patterns of CNV mutations in 32 rhesus macaque individuals from 14 parent–offspring trios. We find the rate of CNV mutations per generation is low (less than one per genome) and we observe no correlation between parental age and the number of CNVs that are passed on to offspring. We also examine segregating CNVs within the rhesus macaque sample and compare them to a similar data set from humans, finding that both species have far more segregating deletions than duplications. We contrast this with long-term patterns of gene copy-number evolution between 17 mammals, where the proportion of deletions that become fixed along the macaque lineage is much smaller than the proportion of segregating deletions. These results suggest purifying selection acting on deletions, such that the majority of them are removed from the population over time. Rhesus macaques are an important biomedical model organism, so these results will aid in our understanding of this species and the disease models it supports.     

Systematic inference of copy-number genotypes from personal genome sequencing data reveals extensive olfactory receptor gene content diversity

Copy-number variations (CNVs) are widespread in the human genome, but comprehensive assignments of integer locus copy-numbers (i.e., copy-number genotypes) that, for example, enable discrimination of homozygous from heterozygous CNVs, have remained challenging. Here we present CopySeq, a novel computational approach with an underlying statistical framework that analyzes the depth-of-coverage of high-throughput DNA sequencing reads, and can incorporate paired-end and breakpoint junction analysis based CNV-analysis approaches, to infer locus copy-number genotypes. We benchmarked CopySeq by genotyping 500 chromosome 1 CNV regions in 150 personal genomes sequenced at low-coverage. The assessed copy-number genotypes were highly concordant with our performed qPCR experiments (Pearson correlation coefficient 0.94), and with the published results of two microarray platforms (95-99% concordance). We further demonstrated the utility of CopySeq for analyzing gene regions enriched for segmental duplications by comprehensively inferring copy-number genotypes in the CNV-enriched >800 olfactory receptor (OR) human gene and pseudogene loci. CopySeq revealed that OR loci display an extensive range of locus copy-numbers across individuals, with zero to two copies in some OR loci, and two to nine copies in others. Among genetic variants affecting OR loci we identified deleterious variants including CNVs and SNPs affecting ~15% and ~20% of the human OR gene repertoire, respectively, implying that genetic variants with a possible impact on smell perception are widespread. Finally, we found that for several OR loci the reference genome appears to represent a minor-frequency variant, implying a necessary revision of the OR repertoire for future functional studies. CopySeq can ascertain genomic structural variation in specific gene families as well as at a genome-wide scale, where it may enable the quantitative evaluation of CNVs in genome-wide association studies involving high-throughput sequencing.     

Global copy number analyses by next generation sequencing provide insight into pig genome variation

Background

Copy number variations (CNVs) confer significant effects on genetic innovation and phenotypic variation. Previous CNV studies in swine seldom focused on in-depth characterization of global CNVs.

Results

Using whole-genome assembly comparison (WGAC) and whole-genome shotgun sequence detection (WSSD) approaches by next generation sequencing (NGS), we probed formation signatures of both segmental duplications (SDs) and individualized CNVs in an integrated fashion, building the finest resolution CNV and SD maps of pigs so far. We obtained copy number estimates of all protein-coding genes with copy number variation carried by individuals, and further confirmed two genes with high copy numbers in Meishan pigs through an enlarged population. We determined genome-wide CNV hotspots, which were significantly enriched in SD regions, suggesting evolution of CNV hotspots may be affected by ancestral SDs. Through systematically enrichment analyses based on simulations and bioinformatics analyses, we revealed CNV-related genes undergo a different selective constraint from those CNV-unrelated regions, and CNVs may be associated with or affect pig health and production performance under recent selection.

Conclusions

Our studies lay out one way for characterization of CNVs in the pig genome, provide insight into the pig genome variation and prompt CNV mechanisms studies when using pigs as biomedical models for human diseases.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-593) contains supplementary material, which is available to authorized users.     

Multiple recurrent de novo CNVs, including duplications of the 7q11.23 Williams syndrome region, are strongly associated with autism

We have undertaken a genome-wide analysis of rare copy-number variation (CNV) in 1124 autism spectrum disorder (ASD) families, each comprised of a single proband, unaffected parents, and, in most kindreds, an unaffected sibling. We find significant association of ASD with de novo duplications of 7q11.23, where the reciprocal deletion causes Williams-Beuren syndrome, characterized by a highly social personality. We identify rare recurrent de novo CNVs at five additional regions, including 16p13.2 (encompassing genes USP7 and C16orf72) and Cadherin 13, and implement a rigorous approach to evaluating the statistical significance of these observations. Overall, large de novo CNVs, particularly those encompassing multiple genes, confer substantial risks (OR = 5.6; CI = 2.6-12.0, p = 2.4 × 10(-7)). We estimate there are 130-234 ASD-related CNV regions in the human genome and present compelling evidence, based on cumulative data, for association of rare de novo events at 7q11.23, 15q11.2-13.1, 16p11.2, and Neurexin 1.     

Allelic genome structural variations in maize detected by array comparative genome hybridization

DNA polymorphisms such as insertion/deletions and duplications affecting genome segments larger than 1 kb are known as copy-number variations (CNVs) or structural variations (SVs). They have been recently studied in animals and humans by using array-comparative genome hybridization (aCGH), and have been associated with several human diseases. Their presence and phenotypic effects in plants have not been investigated on a genomic scale, although individual structural variations affecting traits have been described. We used aCGH to investigate the presence of CNVs in maize by comparing the genome of 13 maize inbred lines to B73. Analysis of hybridization signal ratios of 60,472 60-mer oligonucleotide probes between inbreds in relation to their location in the reference genome (B73) allowed us to identify clusters of probes that deviated from the ratio expected for equal copy-numbers. We found CNVs distributed along the maize genome in all chromosome arms. They occur with appreciable frequency in different germplasm subgroups, suggesting ancient origin. Validation of several CNV regions showed both insertion/deletions and copy-number differences. The nature of CNVs detected suggests CNVs might have a considerable impact on plant phenotypes, including disease response and heterosis.     

Microarray-based maps of copy-number variant regions in European and sub-Saharan populations

The genetic basis of phenotypic variation can be partially explained by the presence of copy-number variations (CNVs). Currently available methods for CNV assessment include high-density single-nucleotide polymorphism (SNP) microarrays that have become an indispensable tool in genome-wide association studies (GWAS). However, insufficient concordance rates between different CNV assessment methods call for cautious interpretation of results from CNV-based genetic association studies. Here we provide a cross-population, microarray-based map of copy-number variant regions (CNVRs) to enable reliable interpretation of CNV association findings. We used the Affymetrix Genome-Wide Human SNP Array 6.0 to scan the genomes of 1167 individuals from two ethnically distinct populations (Europe, N=717; Rwanda, N=450). Three different CNV-finding algorithms were tested and compared for sensitivity, specificity, and feasibility. Two algorithms were subsequently used to construct CNVR maps, which were also validated by processing subsamples with additional microarray platforms (Illumina 1M-Duo BeadChip, Nimblegen 385K aCGH array) and by comparing our data with publicly available information. Both algorithms detected a total of 42669 CNVs, 74% of which clustered in 385 CNVRs of a cross-population map. These CNVRs overlap with 862 annotated genes and account for approximately 3.3% of the haploid human genome.We created comprehensive cross-populational CNVR-maps. They represent an extendable framework that can leverage the detection of common CNVs and additionally assist in interpreting CNV-based association studies.     

The current excitement about copy-number variation: how it relates to gene duplications and protein families

Following recent technological advances there has been an increasing interest in genome structural variants (SVs), in particular copy-number variants (CNVs)--large-scale duplications and deletions. Although not immediately evident, CNV surveys make a conceptual connection between the fields of population genetics and protein families, in particular with regard to the stability and expandability of families. The mechanisms giving rise to CNVs can be considered as fundamental processes underlying gene duplication and loss; duplicated genes being the results of 'successful' copies, fixed and maintained in the population. Conversely, many 'unsuccessful' duplicates remain in the genome as pseudogenes. Here, we survey studies on CNVs, highlighting issues related to protein families. In particular, CNVs tend to affect specific gene functional categories, such as those associated with environmental response, and are depleted in genes related to basic cellular processes. Furthermore, CNVs occur more often at the periphery of the protein interaction network. In comparison, protein families associated with successful and unsuccessful duplicates are associated with similar functional categories but are differentially placed in the interaction network. These trends are likely reflective of CNV formation biases and natural selection, both of which differentially influence distinct protein families.     

Refinement of primate copy number variation hotspots identifies candidate genomic regions evolving under positive selection

Background

Copy number variants (CNVs), defined as losses and gains of segments of genomic DNA, are a major source of genomic variation.

Results

In this study, we identified over 2,000 human CNVs that overlap with orthologous chimpanzee or orthologous macaque CNVs. Of these, 170 CNVs overlap with both chimpanzee and macaque CNVs, and these were collapsed into 34 hotspot regions of CNV formation. Many of these hotspot regions of CNV formation are functionally relevant, with a bias toward genes involved in immune function, some of which were previously shown to evolve under balancing selection in humans. The genes in these primate CNV formation hotspots have significant differential expression levels between species and show evidence for positive selection, indicating that they have evolved under species-specific, directional selection.

Conclusions

These hotspots of primate CNV formation provide a novel perspective on divergence and selective pressures acting on these genomic regions.     

Buffering and the evolution of chromosome-wide gene regulation

Copy number variation (CNV) in terms of aneuploidies of both entire chromosomes and chromosomal segments is an important evolutionary driving force, but it is inevitably accompanied by potentially problematic variations in gene doses and genomic instability. Thus, a delicate balance must be maintained between mechanisms that compensate for variations in gene doses (and thus allow such genomic variability) and selection against destabilizing CNVs. In Drosophila, three known compensatory mechanisms have evolved: a general segmental aneuploidy-buffering system and two chromosome-specific systems. The two chromosome-specific systems are the male-specific lethal complex, which is important for dosage compensation of the male X chromosome, and Painting of fourth, which stimulates expression of the fourth chromosome. In this review, we discuss the origin and function of buffering and compensation using Drosophila as a model.     

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.     

Discovery and Statistical Genotyping of Copy-Number Variation from Whole-Exome Sequencing Depth

Sequencing of gene-coding regions (the exome) is increasingly used for studying human disease, for which copy-number variants (CNVs) are a critical genetic component. However, detecting copy number from exome sequencing is challenging because of the noncontiguous nature of the captured exons. This is compounded by the complex relationship between read depth and copy number; this results from biases in targeted genomic hybridization, sequence factors such as GC content, and batching of samples during collection and sequencing. We present a statistical tool (exome hidden Markov model [XHMM]) that uses principal-component analysis (PCA) to normalize exome read depth and a hidden Markov model (HMM) to discover exon-resolution CNV and genotype variation across samples. We evaluate performance on 90 schizophrenia trios and 1,017 case-control samples. XHMM detects a median of two rare (<1%) CNVs per individual (one deletion and one duplication) and has 79% sensitivity to similarly rare CNVs overlapping three or more exons discovered with microarrays. With sensitivity similar to state-of-the-art methods, XHMM achieves higher specificity by assigning quality metrics to the CNV calls to filter out bad ones, as well as to statistically genotype the discovered CNV in all individuals, yielding a trio call set with Mendelian-inheritance properties highly consistent with expectation. We also show that XHMM breakpoint quality scores enable researchers to explicitly search for novel classes of structural variation. For example, we apply XHMM to extract those CNVs that are highly likely to disrupt (delete or duplicate) only a portion of a gene.     

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

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

Copy number variation in Fayoumi and Leghorn chickens analyzed using array comparative genomic hybridization

Copy number variation refers to regions along chromosomes that harbor a type of structural variation, such as duplications or deletions. Copy number variants (CNVs) play a role in many important traits as well as in genetic diversity. Previous analyses of chickens using array comparative genomic hybridizations or single‐nucleotide polymorphism chip assays have been performed on various breeds and genetic lines to discover CNVs. In this study, we assessed individuals from two highly inbred (inbreeding coefficiency > 99.99%) lines, Leghorn G‐B2 and Fayoumi M15.2, to discover novel CNVs in chickens. These lines have been previously studied for disease resistance, and to our knowledge, this represents the first global assessment of CNVs in the Fayoumi breed. Genomic DNA from individuals was examined using the Agilent chicken 244 K comparative genomic hybridization array and quantitative PCR. We identified a total of 273 CNVs overall, with 112 CNVs being novel and not previously reported. Quantitative PCR using the standard curve method validated a subset of our array data. Through enrichment analysis of genes within CNV regions, we observed multiple chromosomes, terms and pathways that were significantly enriched, largely dealing with the major histocompatibility complex and immune responsiveness. Using an additional round of computational and statistical analysis with a different bioinformatic pipeline, we identified 43 CNVs among these as high‐confidence regions, 14 of which were found to be novel. We further compared and contrasted individuals of the two inbred lines to discover regions that have a significant difference in copy number between lines. A total of 40 regions had significant deletions or duplications between the lines. Gene Ontology analysis of genomic regions containing CNVs between lines also was performed. This between‐line candidate CNV list will be useful in studies with these two unique genetic lines, which may harbor variations that underlie quantitative trait loci for disease resistance and other important traits. Through the global discovery of novel CNVs in chicken, these data also provide resources for further genetic and functional genomics studies.     

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.     

Enhancer Chip: Detecting Human Copy Number Variations in Regulatory Elements

Critical functional properties are embedded in the non-coding portion of the human genome. Recent successful studies have shown that variations in distant-acting gene enhancer sequences can contribute to disease. In fact, various disorders, such as thalassaemias, preaxial polydactyly or susceptibility to Hirschsprung’s disease, may be the result of rearrangements of enhancer elements. We have analyzed the distribution of enhancer loci in the genome and compared their localization to that of previously described copy-number variations (CNVs). These data suggest a negative selection of copy number variable enhancers. To identify CNVs covering enhancer elements, we have developed a simple and cost-effective test. Here we describe the gene selection, design strategy and experimental validation of a customized oligonucleotide Array-Based Comparative Genomic Hybridization (aCGH), designated Enhancer Chip. It has been designed to investigate CNVs, allowing the analysis of all the genome with a 300 Kb resolution and specific disease regions (telomeres, centromeres and selected disease loci) at a tenfold higher resolution. Moreover, this is the first aCGH able to test over 1,250 enhancers, in order to investigate their potential pathogenic role. Validation experiments have demonstrated that Enhancer Chip efficiently detects duplications and deletions covering enhancer loci, demonstrating that it is a powerful instrument to detect and characterize copy number variable enhancers.