The human genome puzzle - the role of copy number variation in somatic mosaicism

The discovery of copy number variations (CNV) in the human genome opened new perspectives in the study of the genetic causes of inherited disorders and the etiology of common diseases. Differently patterned instances of somatic mosaicism in CNV regions have been shown to be present in monozygotic twins and throughout different tissues within an individual. A single-cell-level investigation of CNV in different human cell types led us to uncover mitotically derived genomic mosaicism, which is stable in different cell types of one individual. A unique study of immortalized B-lymphoblastoid cell lines obtained with 20 year interval from the same two subjects shows that mitotic changes in CNV regions may happen early during embryonic development and seem to occur only once, as levels of mosaicism remained stable. This finding has the potential to change our concept of dynamic human genome variation. We propose that further genomic studies should focus on the single-cell level, to understand better the etiology and physiology of aging and diseases mediated by somatic variations.     

Copy number variants (CNVs) in primate species using array-based comparative genomic hybridization

A substantial amount of genomic variation is now known to exist in humans and other primate species. Single nucleotide polymorphisms (SNPs) are thought to represent the vast majority of genomic differences among individuals in a given primate species and comprise about 0.1% of the genomes of two humans. However, recent studies have now shown that structural variation msay account for as much as 0.7% of the genomic differences in humans, of which copy number variants (CNVs) are the largest component. CNVs are segments of DNA that can range in size from hundreds of bases to millions of base pairs in length and have different number of copies between individuals. Recent technological advancements in array technologies led to genome-wide identification of CNVs and consequently revealed thousands of variable loci in humans, comprising as much as 12% of the human genome [A.J. Iafrate, L. Feuk, M.N. Rivera, M.L. Listewnik, P.K. Donahoe, Y. Qi, S.W. Scherer, C. Lee, Nat. Genet. 36 (2004) 949–951, [3]]. CNVs in humans have already been associated with susceptibility to certain complex diseases, dietary adaptation, and several neurological conditions. In addition, recent studies have shown that CNVs can be successfully implemented in population genetics research, providing important insights into human genetic variation. Nevertheless, the important role of CNVs in primate evolution and genetic diversity is still largely unknown. This article aims to outline the strengths and weaknesses of current comparative genomic hybridization array technologies that have been employed to detect CNV variation and the applications of these techniques to primate genetic research.     

Allele-specific amplification in cancer revealed by SNP array analysis

Amplification, deletion, and loss of heterozygosity of genomic DNA are hallmarks of cancer. In recent years a variety of studies have emerged measuring total chromosomal copy number at increasingly high resolution. Similarly, loss-of-heterozygosity events have been finely mapped using high-throughput genotyping technologies. We have developed a probe-level allele-specific quantitation procedure that extracts both copy number and allelotype information from single nucleotide polymorphism (SNP) array data to arrive at allele-specific copy number across the genome. Our approach applies an expectation-maximization algorithm to a model derived from a novel classification of SNP array probes. This method is the first to our knowledge that is able to (a) determine the generalized genotype of aberrant samples at each SNP site (e.g., CCCCT at an amplified site), and (b) infer the copy number of each parental chromosome across the genome. With this method, we are able to determine not just where amplifications and deletions occur, but also the haplotype of the region being amplified or deleted. The merit of our model and general approach is demonstrated by very precise genotyping of normal samples, and our allele-specific copy number inferences are validated using PCR experiments. Applying our method to a collection of lung cancer samples, we are able to conclude that amplification is essentially monoallelic, as would be expected under the mechanisms currently believed responsible for gene amplification. This suggests that a specific parental chromosome may be targeted for amplification, whether because of germ line or somatic variation. An R software package containing the methods described in this paper is freely available at http://genome.dfci.harvard.edu/~tlaframb/PLASQ.     

Germ-line DNA copy number variation frequencies in a large North American population

Genomic copy number variation (CNV) is a recently identified form of global genetic variation in the human genome. The Affymetrix GeneChip 100 and 500 K SNP genotyping platforms were used to perform a large-scale population-based study of CNV frequency. We constructed a genomic map of 578 CNV regions, covering approximately 220 Mb (7.3%) of the human genome, identifying 183 previously unknown intervals. Copy number changes were observed to occur infrequently (<1%) in the majority (>93%) of these genomic regions, but encompass hundreds of genes and disease loci. This North American population-based map will be a useful resource for future genetic studies. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Copy number variants and genetic traits: closer to the resolution of phenotypic to genotypic variability

A considerable and unanticipated plasticity of the human genome, manifested as inter-individual copy number variation, has been discovered. These structural changes constitute a major source of inter-individual genetic variation that could explain variable penetrance of inherited (Mendelian and polygenic) diseases and variation in the phenotypic expression of aneuploidies and sporadic traits, and might represent a major factor in the aetiology of complex, multifactorial traits. For these reasons, an effort should be made to discover all common and rare copy number variants (CNVs) in the human population. This will also enable systematic exploration of both SNPs and CNVs in association studies to identify the genomic contributors to the common disorders and complex traits.     

Whole Genome Distribution and Ethnic Differentiation of Copy Number Variation in Caucasian and Asian Populations

Although copy number variation (CNV) has recently received much attention as a form of structure variation within the human genome, knowledge is still inadequate on fundamental CNV characteristics such as occurrence rate, genomic distribution and ethnic differentiation. In the present study, we used the Affymetrix GeneChip® Mapping 500K Array to discover and characterize CNVs in the human genome and to study ethnic differences of CNVs between Caucasians and Asians. Three thousand and nineteen CNVs, including 2381 CNVs in autosomes and 638 CNVs in X chromosome, from 985 Caucasian and 692 Asian individuals were identified, with a mean length of 296 kb. Among these CNVs, 190 had frequencies greater than 1% in at least one ethnic group, and 109 showed significant ethnic differences in frequencies (p<0.01). After merging overlapping CNVs, 1135 copy number variation regions (CNVRs), covering approximately 439 Mb (14.3%) of the human genome, were obtained. Our findings of ethnic differentiation of CNVs, along with the newly constructed CNV genomic map, extend our knowledge on the structural variation in the human genome and may furnish a basis for understanding the genomic differentiation of complex traits across ethnic groups.     

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.     

Reconstructing DNA copy number by joint segmentation of multiple sequences

ABSTRACT: BACKGROUND: Variations in DNA copy number carry information on the modalities of genome evolution and mis-regulation of DNA replication in cancer cells. Their study can help localize tumor suppressor genes, distinguish different populations of cancerous cells, and identify genomic variations responsible for disease phenotypes. A number of different high throughput technologies can be used to identify copy number variable sites, and the literature documents multiple effective algorithms. We focus here on the specific problem of detecting regions where variation in copy number is relatively common in the sample at hand. This problem encompasses the cases of copy number polymorphisms, related samples, technical replicates, and cancerous sub-populations from the same individual. RESULTS: We present a segmentation method named generalized fused lasso (GFL) to reconstruct copy number variant regions, that is based on penalized estimation and is capable of processing multiple signals jointly. Our approach is computationally very attractive and leads to sensitivity and specificity levels comparable to those of state-of-the-art specialized methodologies. We illustrate its applicability with simulated and real data sets. CONCLUSIONS: The flexibility of our framework makes it applicable to data obtained with a wide range of technology. Its versatility and speed make GFL particularly useful in the initial screening stages of large data sets.     

Analysis of copy number variation in the normal human population within a region containing complex segmental duplications on 22q11 using high-resolution array-CGH

A previously detected copy number polymorphism (Ep CNP) in patients affected with neuroectodermal tumors led us to investigate its frequency and length in the normal population. For this purpose, a program called Sequence Allocator was developed and applied for the construction of an array that consisted of unique and duplicated fragments, allowing the assessment of copy number variation within regions of segmental duplications. The average resolution of this array was 11 kb and we determined the size of the Ep CNP to be 290 kb. Analysis of normal controls identified 7.7 and 7.1% gains in peripheral blood and lymphoblastoid cell line (LCL) DNA, respectively, while deletions were found only in the LCL group (7.1%). This array platform allows the detection of DNA copy number variation within regions of pronounced genomic complexity, which constitutes an improvement over available technologies.     

Divergent selection and heterogeneous genomic divergence

Levels of genetic differentiation between populations can be highly variable across the genome, with divergent selection contributing to such heterogeneous genomic divergence. For example, loci under divergent selection and those tightly physically linked to them may exhibit stronger differentiation than neutral regions with weak or no linkage to such loci. Divergent selection can also increase genome‐wide neutral differentiation by reducing gene flow (e.g. by causing ecological speciation), thus promoting divergence via the stochastic effects of genetic drift. These consequences of divergent selection are being reported in recently accumulating studies that identify: (i) ‘outlier loci’ with higher levels of divergence than expected under neutrality, and (ii) a positive association between the degree of adaptive phenotypic divergence and levels of molecular genetic differentiation across population pairs [‘isolation by adaptation’ (IBA)]. The latter pattern arises because as adaptive divergence increases, gene flow is reduced (thereby promoting drift) and genetic hitchhiking increased. Here, we review and integrate these previously disconnected concepts and literatures. We find that studies generally report 5–10% of loci to be outliers. These selected regions were often dispersed across the genome, commonly exhibited replicated divergence across different population pairs, and could sometimes be associated with specific ecological variables. IBA was not infrequently observed, even at neutral loci putatively unlinked to those under divergent selection. Overall, we conclude that divergent selection makes diverse contributions to heterogeneous genomic divergence. Nonetheless, the number, size, and distribution of genomic regions affected by selection varied substantially among studies, leading us to discuss the potential role of divergent selection in the growth of regions of differentiation (i.e. genomic islands of divergence), a topic in need of future investigation.     

Identification of large-scale human-specific copy number differences by inter-species array comparative genomic hybridization

Copy number differences (CNDs), and the concomitant differences in gene number, have contributed significantly to the genomic divergence between humans and other primates. To assess its relative importance, the genomes of human, common chimpanzee, bonobo, gorilla, orangutan and macaque were compared by comparative genomic hybridization using a high-resolution human BAC array (aCGH). In an attempt to avoid potential interference from frequent intra-species polymorphism, pooled DNA samples were used from each species. A total of 322 sites of large-scale inter-species CND were identified. Most CNDs were lineage-specific but frequencies differed considerably between the lineages; the highest CND frequency among hominoids was observed in gorilla. The conserved nature of the orangutan genome has already been noted by karyotypic studies and our findings suggest that this degree of conservation may extend to the sub-microscopic level. Of the 322 CND sites identified, 14 human lineage-specific gains were observed. Most of these human-specific copy number gains span regions previously identified as segmental duplications (SDs) and our study demonstrates that SDs are major sites of CND between the genomes of humans and other primates. Four of the human-specific CNDs detected by aCGH map close to the breakpoints of human-specific karyotypic changes [e.g., the human-specific inversion of chromosome 1 and the polymorphic inversion inv(2)(p11.2q13)], suggesting that human-specific duplications may have predisposed to chromosomal rearrangement. The association of human-specific copy number gains with chromosomal breakpoints emphasizes their potential importance in mediating karyotypic evolution as well as in promoting human genomic diversity. Electronic Supplementary Material Supplementary material is available for this article at and is accessible for authorized users.     

QuantiSNP: an Objective Bayes Hidden-Markov Model to detect and accurately map copy number variation using SNP genotyping data

Array-based technologies have been used to detect chromosomal copy number changes (aneuploidies) in the human genome. Recent studies identified numerous copy number variants (CNV) and some are common polymorphisms that may contribute to disease susceptibility. We developed, and experimentally validated, a novel computational framework (QuantiSNP) for detecting regions of copy number variation from BeadArray SNP genotyping data using an Objective Bayes Hidden-Markov Model (OB-HMM). Objective Bayes measures are used to set certain hyperparameters in the priors using a novel re-sampling framework to calibrate the model to a fixed Type I (false positive) error rate. Other parameters are set via maximum marginal likelihood to prior training data of known structure. QuantiSNP provides probabilistic quantification of state classifications and significantly improves the accuracy of segmental aneuploidy identification and mapping, relative to existing analytical tools (Beadstudio, Illumina), as demonstrated by validation of breakpoint boundaries. QuantiSNP identified both novel and validated CNVs. QuantiSNP was developed using BeadArray SNP data but it can be adapted to other platforms and we believe that the OB-HMM framework has widespread applicability in genomic research. In conclusion, QuantiSNP is a novel algorithm for high-resolution CNV/aneuploidy detection with application to clinical genetics, cancer and disease association studies.     

Large Genomic Region Free of GWAS-Based Common Variants Contains Fertility-Related Genes

DNA variants, such as single nucleotide polymorphisms (SNPs) and copy number variants (CNVs), are unevenly distributed across the human genome. Currently, dbSNP contains more than 6 million human SNPs, and whole-genome genotyping arrays can assay more than 4 million of them simultaneously. In our study, we first questioned whether published genome-wide association studies (GWASs) assays cover all regions well in the genome. Using dbSNP build 135 data, we identified 50 genomic regions longer than 100 Kb that do not contain any common SNPs, i.e., those with minor allele frequency (MAF)≥1%. Secondly, because conserved regions are generally of functional importance, we tested genes in those large genomic regions without common SNPs. We found 97 genes and were enriched for reproduction function. In addition, we further filtered out regions with CNVs listed in the Database of Genomic Variants (DGV), segmental duplications from Human Genome Project and common variants identified by personal genome sequencing (UCSC). No region survived after those filtering. Our analysis suggests that, while there may not be many large genomic regions free of common variants, there are still some “holes” in the current human genomic map for common SNPs. Because GWAS only focused on common SNPs, interpretation of GWAS results should take this limitation into account. Particularly, two recent GWAS of fertility may be incomplete due to the map deficit. Additional SNP discovery efforts should pay close attention to these regions.     

Early Embryonic Chromosome Instability Results in Stable Mosaic Pattern in Human Tissues

The discovery of copy number variations (CNV) in the human genome opened new perspectives on the study of the genetic causes of inherited disorders and the aetiology of common diseases. Here, a single-cell-level investigation of CNV in different human tissues led us to uncover the phenomenon of mitotically derived genomic mosaicism, which is stable in different cell types of one individual. The CNV mosaic ratios were different between the 10 individuals studied. However, they were stable in the T lymphocytes, immortalized B lymphoblastoid cells, and skin fibroblasts analyzed in each individual. Because these cell types have a common origin in the connective tissues, we suggest that mitotic changes in CNV regions may happen early during embryonic development and occur only once, after which the stable mosaic ratio is maintained throughout the differentiated tissues. This concept is further supported by a unique study of immortalized B lymphoblastoid cell lines obtained with 20 year difference from two subjects. We provide the first evidence of somatic mosaicism for CNV, with stable variation ratios in different cell types of one individual leading to the hypothesis of early embryonic chromosome instability resulting in stable mosaic pattern in human tissues. This concept has the potential to open new perspectives in personalized genetic diagnostics and can explain genetic phenomena like diminished penetrance in autosomal dominant diseases. We propose that further genomic studies should focus on the single-cell level, to better understand the aetiology of aging and diseases mediated by somatic mutations.     

Copy Number Variation in Transcriptionally Active Regions of Sexual and Apomictic Boechera Demonstrates Independently Derived Apomictic Lineages

In asexual (apomictic) plants, the absence of meiosis and sex is expected to lead to mutation accumulation. To compare mutation accumulation in the transcribed genomic regions of sexual and apomictic plants, we performed a double-validated analysis of copy number variation (CNV) on 10 biological replicates each of diploid sexual and diploid apomictic Boechera, using a high-density (>700 K) custom microarray. The Boechera genome demonstrated higher levels of depleted CNV, compared with enriched CNV, irrespective of reproductive mode. Genome-wide patterns of CNV revealed four divergent lineages, three of which contain both sexual and apomictic genotypes. Hence genome-wide CNV reflects at least three independent origins (i.e., expression) of apomixis from different sexual genetic backgrounds. CNV distributions for different families of transposable elements were lineage specific, and the enrichment of LINE/L1 and long term repeat/Copia elements in lineage 3 apomicts is consistent with sex and meiosis being mechanisms for purging genomic parasites. We hypothesize that significant overrepresentation of specific gene ontology classes (e.g., pollen–pistil interaction) in apomicts implies that gene enrichment could be an adaptive mechanism for genome stability in diploid apomicts by providing a polyploid-like system for buffering the effects of deleterious mutations.     

Copy number variation in the genome; the human DMD gene as an example

Recent developments have yielded new technologies that have greatly simplified the detection of deletions and duplications, i.e., copy number variants (CNVs). These technologies can be used to screen for CNVs in and around specific genomic regions, as well as genome-wide. Several genome-wide studies have demonstrated that CNV in the human genome is widespread and may include millions of nucleotides. One of the questions that emerge is which sequences, structures and/or processes are involved in their generation. Using as an example the human DMD gene, mutations in which cause Duchenne and Becker muscular dystrophy, we review the current data, determine the deletion and duplication profile across the gene and summarize the information that has been collected regarding their origin. In addition we discuss the methods most frequently used for their detection, in particular MAPH and MLPA.     

Variation of CNV distribution in five different ethnic populations

Recent studies have revealed a new type of variation in the human genome encompassing relatively large genomic segments ( approximately 100 kb-2.5 Mb), commonly referred to as copy number variation (CNV). The full nature and extent of CNV and its frequency in different ethnic populations is still largely unknown. In this study we surveyed a set of 12 CNVs previously detected by array-CGH. More than 300 individuals from five different ethnic populations, including three distinct European, one Asian and one African population, were tested for the occurrence of CNV using multiplex ligation-dependent probe amplification (MLPA). Seven of these loci indeed showed CNV, i.e., showed copy numbers that deviated from the population median. More precise estimations of the actual genomic copy numbers for (part of) the NSF gene locus, revealed copy numbers ranging from two to at least seven. Additionally, significant inter-population differences in the distribution of these copy numbers were observed. These data suggest that insight into absolute DNA copy numbers for loci exhibiting CNV is required to determine their potential contribution to normal phenotypic variation and, in addition, disease susceptibility.     

Clinical significance of germline copy number variation in susceptibility of human diseases

Germline copy number variation (CNV) is considered to be an important form of human genetic polymorphisms. Previous studies have identified amounts of CNVs in human genome by advanced technologies, such as comparative genomic hybridization, single nucleotide genotyping, and high-throughput sequencing. CNV is speculated to be derived from multiple mechanisms, such as nonallelic homologous recombination (NAHR) and nonhomologous end-joining (NHEJ). CNVs cover a much larger genome scale than single nucleotide polymorphisms (SNPs), and may alter gene expression levels by means of gene dosage, gene fusion, gene disruption, and long-range regulation effects, thus affecting individual phenotypes and playing crucial roles in human pathogenesis. The number of studies linking CNVs with common complex diseases has increased dramatically in recent years. Here, we provide a comprehensive review of the current understanding of germline CNVs, and summarize the association of germline CNVs with the susceptibility to a wide variety of human diseases that were identified in recent years. We also propose potential issues that should be addressed in future studies.     

Identification and functional characterization of copy number variations in diverse chicken breeds

Background

The detection and functional characterization of genomic structural variations are important for understanding the landscape of genetic variation in the chicken. A recently recognized aspect of genomic structural variation, called copy number variation (CNV), is gaining interest in chicken genomic studies. The aim of the present study was to investigate the pattern and functional characterization of CNVs in five characteristic chicken breeds, which will be important for future studies associating phenotype with chicken genome architecture.

Results

Using a commercial 385 K array-based comparative genomic hybridization (aCGH) genome array, we performed CNV discovery using 10 chicken samples from four local Chinese breeds and the French breed Houdan chicken. The female Anka broiler was used as a reference. A total of 281 copy number variation regions (CNVR) were identified, covering 12.8 Mb of polymorphic sequences or 1.07% of the entire chicken genome. The functional annotation of CNVRs indicated that these regions completely or partially overlapped with 231 genes and 1032 quantitative traits loci, suggesting these CNVs have important functions and might be promising resources for exploring differences among various breeds. In addition, we employed quantitative PCR (qPCR) to further validate several copy number variable genes, such as prolactin receptor, endothelin 3 (EDN3), suppressor of cytokine signaling 2, CD8a molecule, with important functions, and the results suggested that EDN3 might be a molecular marker for the selection of dark skin color in poultry production. Moreover, we also identified a new CNVR (chr24: 3484617–3512275), encoding the sortilin-related receptor gene, with copy number changes in only black-bone chicken.

Conclusions

Here, we report a genome-wide analysis of the CNVs in five chicken breeds using aCGH. The association between EDN3 and melanoblast proliferation was further confirmed using qPCR. These results provide additional information for understanding genomic variation and related phenotypic characteristics.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-934) contains supplementary material, which is available to authorized users.