Integrated detection and population-genetic analysis of SNPs and copy number variation

Kernel-Based Aggregation of Marker-Level Genetic Association Tests Involving Copy-Number Variation

Genetic association tests involving copy-number variants (CNVs) are complicated by the fact that CNVs span multiple markers at which measurements are taken. The power of an association test at a single marker is typically low, and it is desirable to pool information across the markers spanned by the CNV. However, CNV boundaries are not known in advance, and the best way to proceed with this pooling is unclear. In this article, we propose a kernel-based method for aggregation of marker-level tests and explore several aspects of its implementation. In addition, we explore some of the theoretical aspects of marker-level test aggregation, proposing a permutation-based approach that preserves the family-wise error rate of the testing procedure, while demonstrating that several simpler alternatives fail to do so. The empirical power of the approach is studied in a number of simulations constructed from real data involving a pharmacogenomic study of gemcitabine and compares favorably with several competing approaches.

Role of non-HLA gene polymorphisms in graft-versus-host disease

A large number of reports have associated various non-HLA gene polymorphisms with the risk and severity of graft-versus-host disease (GVHD). To date, candidate gene studies and genome-wide association studies have been performed to investigate such non-HLA gene polymorphisms in relation to GVHD. Candidate gene studies are hypothesis-driven and cost-effective, whereas genome-wide association studies have the potential to discover new gene polymorphisms, including possible biomarkers and therapeutic targets. Some gene polymorphisms have the potential to affect protein function or gene expression, or to encode minor histocompatibility antigens. Non-HLA genotyping for genes influencing GVHD prior to transplantation should provide useful information that will facilitate choosing the donor, type of graft, conditioning treatment, and GVHD prophylaxis. However, attention should be paid to the need for validation studies and ethical issues.

Ionizing radiation and genetic risks. XVII. Formation mechanisms underlying naturally occurring DNA deletions in the human genome and their potential relevance for bridging the gap between induced DNA double-strand breaks and deletions in irradiated germ cells

While much is known about radiation-induced DNA double-strand breaks (DSBs) and their repair, the question of how deletions of different sizes arise as a result of the processing of DSBs by the cell's repair systems has not been fully answered. In order to bridge this gap between DSBs and deletions, we critically reviewed published data on mechanisms pertaining to: (a) repair of DNA DSBs (from basic studies in this area); (b) formation of naturally occurring structural variation (SV) - especially of deletions - in the human genome (from genomic studies) and (c) radiation-induced mutations and structural chromosomal aberrations in mammalian somatic cells (from radiation mutagenesis and radiation cytogenetic studies). The specific aim was to assess the relative importance of the postulated mechanisms in generating deletions in the human genome and examine whether empirical data on radiation-induced deletions in mouse germ cells are consistent with predictions of these mechanisms. The mechanisms include (a) NHEJ, a DSB repair process that does not require any homology and which functions in all stages of the cell cycle (and is of particular relevance in G0/G1); (b) MMEJ, also a DSB repair process but which requires microhomology and which presumably functions in all cell cycle stages; (c) NAHR, a recombination-based DSB repair mechanism which operates in prophase I of meiosis in germ cells; (d) MMBIR, a microhomology-mediated, replication-based mechanism which operates in the S phase of the cell cycle, and (e) strand slippage during replication (involved in the origin of small insertions and deletions (INDELs). Our analysis permits the inference that, between them, these five mechanisms can explain nearly all naturally occurring deletions of different sizes identified in the human genome, NAHR and MMBIR being potentially more versatile in this regard. With respect to radiation-induced deletions, the basic studies suggest that those arising as a result of the operation of NHEJ/MMEJ processes, as currently formulated, are expected to be relatively small. However, data on induced mutations in mouse spermatogonial stem cells (irradiation in G0/G1 phase of the cell cycle and DSB repair presumed to be via NHEJ predominantly) show that most are associated with deletions of different sizes, some in the megabase range. There is thus a 'discrepancy' between what the basic studies suggest and the empirical observations in mutagenesis studies. This discrepancy, however, is only an apparent but not a real one. It can be resolved by considering the issue of deletions in the broader context of and in conjunction with the organization of chromatin in chromosomes and nuclear architecture, the conceptual framework for which already exists in studies carried out during the past fifteen years or so. In this paper, we specifically hypothesize that repair of DSBs induced in chromatin loops may offer a basis to explain the induction of deletions of different sizes and suggest an approach to test the hypothesis. We emphasize that the bridging of the gap between induced DSB and resulting deletions of different sizes is critical for current efforts in computational modeling of genetic risks.

Identification of null alleles and deletions from SNP genotypes for an intercross between domestic and wild chickens

We analyzed genotypes from ~10K single-nucleotide polymorphisms (SNPs) in two families of an F₂ intercross between Red Junglefowl and White Leghorn chickens. Possible null alleles were found by patterns of incompatible and missing genotypes. We estimated that 2.6% of SNPs had null alleles compared with 2.3% with genotyping errors and that 40% of SNPs in which a parent and offspring were genotyped as different homozygotes had null alleles. Putative deletions were identified by null alleles at adjacent markers. We found two candidate deletions that were supported by fluorescence intensity data from a 60K SNP chip. One of the candidate deletions was from the Red Junglefowl, and one was present in both the Red Junglefowl and White Leghorn. Both candidate deletions spanned protein-coding regions and were close to a previously detected quantitative trait locus affecting body weight in this population. This study demonstrates that the ~50K SNP genotyping arrays now available for several agricultural species can be used to identify null alleles and deletions in data from large families. We suggest that our approach could be a useful complement to linkage analysis in experimental crosses.

Comparison of genotyping using pooled DNA samples (allelotyping) and individual genotyping using the affymetrix genome-wide human SNP array 6.0

Background

Genome-wide association studies (GWAS) using array-based genotyping technology are widely used to identify genetic loci associated with complex diseases or other phenotypes. The costs of GWAS projects based on individual genotyping are still comparatively high and increase with the size of study populations. Genotyping using pooled DNA samples, as also being referred as to allelotyping approach, offers an alternative at affordable costs. In the present study, data from 100 DNA samples individually genotyped with the Affymetrix Genome-Wide Human SNP Array 6.0 were used to estimate the error of the pooling approach by comparing the results with those obtained using the same array type but DNA pools each composed of 50 of the same samples. Newly developed and established methods for signal intensity correction were applied. Furthermore, the relative allele intensity signals (RAS) obtained by allelotyping were compared to the corresponding values derived from individual genotyping. Similarly, differences in RAS values between pools were determined and compared.

Results

Regardless of the intensity correction method applied, the pooling-specific error of the pool intensity values was larger for single pools than for the comparison of the intensity values of two pools, which reflects the scenario of a case–control study. Using 50 pooled samples and analyzing 10,000 SNPs with a minor allele frequency of >1% and applying the best correction method for the corresponding type of comparison, the 90% quantile (median) of the pooling-specific absolute error of the RAS values for single sub-pools and the SNP-specific difference in allele frequency comparing two pools was 0.064 (0.026) and 0.056 (0.021), respectively.

Conclusions

Correction of the RAS values reduced the error of the RAS values when analyzing single pool intensities. We developed a new correction method with high accuracy but low computational costs. Correction of RAS, however, only marginally reduced the error of true differences between two sample groups and those obtained by allelotyping. Exclusion of SNPs with a minor allele frequency of ≤1% notably reduced the pooling-specific error. Our findings allow for improving the estimation of the pooling-specific error and may help in designing allelotyping studies using the Affymetrix Genome-Wide Human SNP Array 6.0.

Evolutionary dynamics of copy number variation in pig genomes in the context of adaptation and domestication

Background

Copy number variable regions (CNVRs) can result in drastic phenotypic differences and may therefore be subject to selection during domestication. Studying copy number variation in relation to domestication is highly relevant in pigs because of their very rich natural and domestication history that resulted in many different phenotypes. To investigate the evolutionary dynamic of CNVRs, we applied read depth method on next generation sequence data from 16 individuals, comprising wild boars and domestic pigs from Europe and Asia.

Results

We identified 3,118 CNVRs with an average size of 13 kilobases comprising a total of 39.2 megabases of the pig genome and 545 overlapping genes. Functional analyses revealed that CNVRs are enriched with genes related to sensory perception, neurological process and response to stimulus, suggesting their contribution to adaptation in the wild and behavioral changes during domestication. Variations of copy number (CN) of antimicrobial related genes suggest an ongoing process of evolution of these genes to combat food-borne pathogens. Likewise, some genes related to the omnivorous lifestyle of pigs, like genes involved in detoxification, were observed to be CN variable. A small portion of CNVRs was unique to domestic pigs and may have been selected during domestication. The majority of CNVRs, however, is shared between wild and domesticated individuals, indicating that domestication had minor effect on the overall diversity of CNVRs. Also, the excess of CNVRs in non-genic regions implies that a major part of these variations is likely to be (nearly) neutral. Comparison between different populations showed that larger populations have more CNVRs, highlighting that CNVRs are, like other genetic variation such as SNPs and microsatellites, reflecting demographic history rather than phenotypic diversity.

Conclusion

CNVRs in pigs are enriched for genes related to sensory perception, neurological process, and response to stimulus. The majority of CNVRs ascertained in domestic pigs are also variable in wild boars, suggesting that the domestication of the pig did not result in a change in CNVRs in domesticated pigs. The majority of variable regions were found to reflect demographic patterns rather than phenotypic.

GStream: improving SNP and CNV coverage on genome-wide association studies

We present GStream, a method that combines genome-wide SNP and CNV genotyping in the Illumina microarray platform with unprecedented accuracy. This new method outperforms previous well-established SNP genotyping software. More importantly, the CNV calling algorithm of GStream dramatically improves the results obtained by previous state-of-the-art methods and yields an accuracy that is close to that obtained by purely CNV-oriented technologies like Comparative Genomic Hybridization (CGH). We demonstrate the superior performance of GStream using microarray data generated from HapMap samples. Using the reference CNV calls generated by the 1000 Genomes Project (1KGP) and well-known studies on whole genome CNV characterization based either on CGH or genotyping microarray technologies, we show that GStream can increase the number of reliably detected variants up to 25% compared to previously developed methods. Furthermore, the increased genome coverage provided by GStream allows the discovery of CNVs in close linkage disequilibrium with SNPs, previously associated with disease risk in published Genome-Wide Association Studies (GWAS). These results could provide important insights into the biological mechanism underlying the detected disease risk association. With GStream, large-scale GWAS will not only benefit from the combined genotyping of SNPs and CNVs at an unprecedented accuracy, but will also take advantage of the computational efficiency of the method.

The unexpected role of copy number variations in juvenile myoclonic epilepsy

Structural genomic variants or copy number variants (CNVs) comprise submicroscopic deletions and duplications of chromosomal material, including both rearrangements at genomic hotspots as well as duplications and deletions with unique breakpoints. Copy number variants have increasingly been recognized in the Idiopathic/Genetic Generalized Epilepsies (IGE/GGE) including juvenile myoclonic epilepsy (JME). Microdeletions at 15q13.3, 15q11.2, and 16p13.11 are genetic risk factors that can be identified in 3% of patients with IGE including JME. These microdeletions, however, also represent genetic risk factors to a broad range of other neurodevelopmental disorders. Additionally, 6% of patients with GGE carry other, potentially pathogenic structural genomic variants. While family studies largely support the channelopathy concept of the idiopathic epilepsies, the results of studies investigating copy number variations suggest that JME genetically overlaps with a broad range of other neurodevelopmental disorders. In addition, the particular genetic properties of structural genomic variations as rare genetic variants highlight the complexity of the genetic architecture of human disease.

Comparative Analysis of CNV Calling Algorithms: Literature Survey and a Case Study Using Bovine High-Density SNP Data

Copy number variations (CNVs) are gains and losses of genomic sequence between two individuals of a species when compared to a reference genome. The data from single nucleotide polymorphism (SNP) microarrays are now routinely used for genotyping, but they also can be utilized for copy number detection. Substantial progress has been made in array design and CNV calling algorithms and at least 10 comparison studies in humans have been published to assess them. In this review, we first survey the literature on existing microarray platforms and CNV calling algorithms. We then examine a number of CNV calling tools to evaluate their impacts using bovine high-density SNP data. Large incongruities in the results from different CNV calling tools highlight the need for standardizing array data collection, quality assessment and experimental validation. Only after careful experimental design and rigorous data filtering can the impacts of CNVs on both normal phenotypic variability and disease susceptibility be fully revealed.

The genetic basis for interindividual immune response variation to measles vaccine: new understanding and new vaccine approaches

The live-attenuated measles vaccine is effective, but measles outbreaks still occur in vaccinated populations. This warrants elucidation of the determinants of measles vaccine-induced protective immunity. Interindividual variability in markers of measles vaccine-induced immunity, including neutralizing antibody levels, is regulated in part by host genetic factor variations. This review summarizes recent advances in our understanding of measles vaccine immunogenetics relative to the perspective of developing better measles vaccines. Important genetic regulators of measles vaccine-induced immunity, such as HLA class I and HLA class II genotypes, single nucleotide polymorphisms in cytokine/cytokine receptor genes (IL12B, IL12RB1, IL2, IL10) and the cell surface measles virus receptor CD46 gene, have been identified and independently replicated. New technologies present many opportunities for identification of novel genetic signatures and genetic architectures. These findings help explain a variety of immune response-related phenotypes and promote a new paradigm of 'vaccinomics' for novel vaccine development.

The Growing Importance of CNVs: New Insights for Detection and Clinical Interpretation

Differences between genomes can be due to single nucleotide variants, translocations, inversions, and copy number variants (CNVs, gain or loss of DNA). The latter can range from sub-microscopic events to complete chromosomal aneuploidies. Small CNVs are often benign but those larger than 500 kb are strongly associated with morbid consequences such as developmental disorders and cancer. Detecting CNVs within and between populations is essential to better understand the plasticity of our genome and to elucidate its possible contribution to disease. Hence there is a need for better-tailored and more robust tools for the detection and genome-wide analyses of CNVs. While a link between a given CNV and a disease may have often been established, the relative CNV contribution to disease progression and impact on drug response is not necessarily understood. In this review we discuss the progress, challenges, and limitations that occur at different stages of CNV analysis from the detection (using DNA microarrays and next-generation sequencing) and identification of recurrent CNVs to the association with phenotypes. We emphasize the importance of germline CNVs and propose strategies to aid clinicians to better interpret structural variations and assess their clinical implications.

Genome-wide linkage analysis of congenital heart defects using MOD score analysis identifies two novel loci

Background

Congenital heart defects (CHD) is the most common cause of death from a congenital structure abnormality in newborns and is often associated with fetal loss. There are many types of CHD. Human genetic studies have identified genes that are responsible for the inheritance of a particular type of CHD and for some types of CHD previously thought to be sporadic. However, occasionally different members of the same family might have anatomically distinct defects — for instance, one member with atrial septal defect, one with tetralogy of Fallot, and one with ventricular septal defect. Our objective is to identify susceptibility loci for CHD in families affected by distinct defects. The occurrence of these apparently discordant clinical phenotypes within one family might hint at a genetic framework common to most types of CHD.

Results

We performed a genome-wide linkage analysis using MOD score analysis in families with diverse CHD. Significant linkage was obtained in two regions, at chromosome 15 (15q26.3, P_empirical = 0.0004) and at chromosome 18 (18q21.2, P_empirical = 0.0005).

Conclusions

In these two novel regions four candidate genes are located: SELS, SNRPA1, and PCSK6 on 15q26.3, and TCF4 on 18q21.2. The new loci reported here have not previously been described in connection with CHD. Although further studies in other cohorts are needed to confirm these findings, the results presented here together with recent insight into how the heart normally develops will improve the understanding of CHD.

CNVrd, a read-depth algorithm for assigning copy-number at the FCGR locus: population-specific tagging of copy number variation at FCGR3B

The extent of contribution from common gene copy number (CN) variants in human disease is currently unresolved. Part of the reason for this is the technical difficulty in directly measuring CN variation (CNV) using molecular methods, and the lack of single nucleotide polymorphisms (SNPs) that can tag complex CNV that has arisen multiple times on different SNP haplotypes. One CNV locus implicated in human disease is FCGR. Here we aimed to use next-generation sequencing (NGS) data from the 1000 Genomes Project to assign CN at FCGR3A and FCGR3B and to comprehensively assess the ability of SNPs to tag specific CN variants. A read-depth algorithm was developed (CNVrd) and validated on a subset of HapMap samples using CN assignments that had previously been determined using molecular and microarray methods. At 7 out of 9 other complex loci there was >90% concordance with microarray data. However, given that some prior knowledge of CN is required, the generalizability of CNVrd is limited and should be applied to other complex CNV loci with caution. Subsequently, CN was assigned et FCGR3B using CNVrd in a total of 952 samples from the 1000 Genomes Project, using three classes and SNPs that correlated with duplication were identified. The best tag SNP was observed in the Mexican-American sample set for duplication at FCGR3B. This SNP (rs117435514, r² = 0.79) also tagged similar duplication in Chinese and Japanese (r² = 0.35–0.60), but not in Caucasian or African. No tag SNP for duplication at FCGR3A or deletion at FCGR3B was identified in any population. We conclude that it is possible to tag CNV at the FCGR locus, but CN and SNPs have to be characterized and correlated on a population-specific basis.

Male-biased autosomal effect of 16p13.11 copy number variation in neurodevelopmental disorders

Copy number variants (CNVs) at chromosome 16p13.11 have been associated with a range of neurodevelopmental disorders including autism, ADHD, intellectual disability and schizophrenia. Significant sex differences in prevalence, course and severity have been described for a number of these conditions but the biological and environmental factors underlying such sex-specific features remain unclear. We tested the burden and the possible sex-biased effect of CNVs at 16p13.11 in a sample of 10,397 individuals with a range of neurodevelopmental conditions, clinically referred for array comparative genomic hybridisation (aCGH); cases were compared with 11,277 controls. In order to identify candidate phenotype-associated genes, we performed an interval-based analysis and investigated the presence of ohnologs at 16p13.11; finally, we searched the DECIPHER database for previously identified 16p13.11 copy number variants. In the clinical referral series, we identified 46 cases with CNVs of variable size at 16p13.11, including 28 duplications and 18 deletions. Patients were referred for various phenotypes, including developmental delay, autism, speech delay, learning difficulties, behavioural problems, epilepsy, microcephaly and physical dysmorphisms. CNVs at 16p13.11 were also present in 17 controls. Association analysis revealed an excess of CNVs in cases compared with controls (OR = 2.59; p = 0.0005), and a sex-biased effect, with a significant enrichment of CNVs only in the male subgroup of cases (OR = 5.62; p = 0.0002), but not in females (OR = 1.19, p = 0.673). The same pattern of results was also observed in the DECIPHER sample. Interval-based analysis showed a significant enrichment of case CNVs containing interval II (OR = 2.59; p = 0.0005), located in the 0.83 Mb genomic region between 15.49-16.32 Mb, and encompassing the four ohnologs NDE1, MYH11, ABCC1 and ABCC6. Our data confirm that duplications and deletions at 16p13.11 represent incompletely penetrant pathogenic mutations that predispose to a range of neurodevelopmental disorders, and suggest a sex-limited effect on the penetrance of the pathological phenotypes at the 16p13.11 locus.

A 680 kb duplication at the FTO locus in a kindred with obesity and a distinct body fat distribution

Common intronic SNPs in the human fat mass and obesity associated (FTO) gene are strongly associated with body mass index (BMI). In mouse models, inactivation of the Fto gene results in a lean phenotype, whereas overexpression of Fto leads to increased food intake and obesity. The latter finding suggests that copy number variants at the FTO locus might be associated with extremes of adiposity. To address this question, we searched for rare, private or de novo copy number variation in a cohort of 985 obese and 869 lean subjects of European ancestry drawn from the extremes of the BMI distribution, genotyped on Affymetrix 6.0 arrays. A ∼680 kb duplication, confirmed by real-time PCR and G-to-FISH analyses, was observed between ∼rs11859825 and rs9932411 in a 68-year-old male with severe obesity. The duplicated region on chromosome 16 spans the entire genome-wide association studies risk locus for obesity, and further encompasses RBL2, AKTIP, RPGRIP1L and all but the last exon of the FTO gene. Affected family members exhibit a unique obesity phenotype, characterized by increased fat distribution in the shoulders and neck with a significantly increased neck circumference. This phenotype was accompanied by increased peripheral blood expression of RBL2 with no alteration in expression of FTO or other genes in the region. No other duplications or deletions in this region were identified in the cohort of obese and lean individuals or in a further survey of 4778 individuals, suggesting that large rare copy number variants surrounding the FTO gene are not a frequent cause of obesity.

A common deletion in the APOBEC3 genes and breast cancer risk

BACKGROUND

Genome-wide association studies (GWASs) have identified multiple genetic susceptibility loci for breast cancer. However, these loci explain only a small fraction of the heritability. Very few studies have evaluated copy number variation (CNV), another important source of human genetic variation, in relation to breast cancer risk.

METHODS

We conducted a CNV GWAS in 2623 breast cancer patients and 1946 control subjects using data from Affymetrix SNP Array 6.0 (stage 1). We then replicated the most promising CNV using real-time quantitative polymerase chain reaction (qPCR) in an independent set of 4254 case patients and 4387 control subjects (stage 2). All subjects were recruited from population-based studies conducted among Chinese women in Shanghai.

RESULTS

Of the 268 common CNVs (minor allele frequency ≥ 5%) investigated in stage 1, the strongest association was found for a common deletion in the APOBEC3 genes (P = 1.1×10(-4)) and was replicated in stage 2 (odds ratio =1.35, 95% confidence interval [CI] = 1.27 to 1.44; P = 9.6×10(-22)). Analyses of all samples from both stages using qPCR data produced odds ratios of 1.31 (95% CI = 1.21 to 1.42) for a one-copy deletion and 1.76 (95% CI = 1.57 to 1.97) for a two-copy deletion (P = 2.0×10(-24)).

CONCLUSIONS

We provide convincing evidence for a novel breast cancer locus at the APOBEC3 genes. This CNV is one of the strongest common genetic risk variants identified so far for breast cancer.

Worldwide population distribution of the common LCE3C-LCE3B deletion associated with psoriasis and other autoimmune disorders

Background

There is increasing evidence of the importance of copy number variants (CNV) in genetic diversity among individuals and populations, as well as in some common genetic diseases. We previously characterized a common 32-kb insertion/deletion variant of the PSORS4 locus at chromosome 1q21 that harbours the LCE3C and LCE3B genes. This variant allele (LCE3C_LCE3B-del) is common in patients with psoriasis and other autoimmune disorders from certain ethnic groups.

Results

Using array-CGH (Agilent 244 K) in samples from the HapMap and Human Genome Diversity Panel (HGDP) collections, we identified 54 regions showing population differences in comparison to Africans. We provided here a comprehensive population-genetic analysis of one of these regions, which involves the 32-kb deletion of the PSORS4 locus. By a PCR-based genotyping assay we characterised the profiles of the LCE3C_LCE3B-del and the linkage disequilibrium (LD) pattern between the variant allele and the tag SNP rs4112788. Our results show that most populations tend to have a higher frequency of the deleted allele than Sub-Saharan Africans. Furthermore, we found strong LD between rs4112788G and LCE3C_LCE3B-del in most non-African populations (r2 >0.8), in contrast to the low concordance between loci (r2 <0.3) in the African populations.

Conclusions

These results are another example of population variability in terms of biomedical interesting CNV. The frequency distribution of the LCE3C_LCE3B-del allele and the LD pattern across populations suggest that the differences between ethnic groups might not be due to natural selection, but the consequence of genetic drift caused by the strong bottleneck that occurred during “out of Africa” expansion.

Increased CNV-region deletions in mild cognitive impairment (MCI) and Alzheimer's disease (AD) subjects in the ADNI sample

We investigated the genome-wide distribution of CNVs in the Alzheimer's disease (AD) Neuroimaging Initiative (ADNI) sample (146 with AD, 313 with Mild Cognitive Impairment (MCI), and 181 controls). Comparison of single CNVs between cases (MCI and AD) and controls shows overrepresentation of large heterozygous deletions in cases (p-value<0.0001). The analysis of CNV-Regions identifies 44 copy number variable loci of heterozygous deletions, with more CNV-Regions among affected than controls (p=0.005). Seven of the 44 CNV-Regions are nominally significant for association with cognitive impairment. We validated and confirmed our main findings with genome re-sequencing of selected patients and controls. The functional pathway analysis of the genes putatively affected by deletions of CNV-Regions reveals enrichment of genes implicated in axonal guidance, cell-cell adhesion, neuronal morphogenesis and differentiation. Our findings support the role of CNVs in AD, and suggest an association between large deletions and the development of cognitive impairment.

Analysis of copy number variations in the sheep genome using 50K SNP BeadChip array

Background

In recent years, genome-wide association studies have successfully uncovered single-nucleotide polymorphisms (SNPs) associated with complex traits such as diseases and quantitative phenotypes. These variations account for a small proportion of heritability. With the development of high throughput techniques, abundant submicroscopic structural variations have been found in organisms, of which the main variations are copy number variations (CNVs). Therefore, CNVs are increasingly recognized as an important and abundant source of genetic variation and phenotypic diversity.

Results

Analyses of CNVs in the genomes of three sheep breeds were performed using the Ovine SNP50 BeadChip array. A total of 238 CNV regions (CNVRs) were identified, including 219 losses, 13 gains, and six with both events (losses and gains), which cover 60.35 Mb of the sheep genomic sequence and correspond to 2.27% of the autosomal genome sequence. The length of the CNVRs on autosomes range from 13.66 kb to 1.30 Mb with a mean size of 253.57 kb, and 75 CNVRs events had a frequency > 3%. Among these CNVRs, 47 CNVRs identified by the PennCNV overlapped with the CNVpartition. Functional analysis indicated that most genes in the CNVRs were significantly enriched for involvement in the environmental response. Furthermore, 10 CNVRs were selected for validation and 6 CNVRs were further experimentally confirmed by qPCR. In addition, there were 57 CNVRs overlapped in our new dataset and other published ruminant CNV studies.

Conclusions

In this study, we firstly constructed a sheep CNV map based on the Ovine SNP50 array. Our results demonstrated the differences of two detection tools and integration of multiple algorithms can enhance the detection of sheep genomic structure variations. Furthermore, our findings would be of help for understanding the sheep genome and provide preliminary foundation for carrying out the CNVs association studies with economically important phenotypes of sheep in the future.

Bivariate genome-wide association analyses identified genes with pleiotropic effects for femoral neck bone geometry and age at menarche

Femoral neck geometric parameters (FNGPs), which include cortical thickness (CT), periosteal diameter (W), buckling ratio (BR), cross-sectional area (CSA), and section modulus (Z), contribute to bone strength and may predict hip fracture risk. Age at menarche (AAM) is an important risk factor for osteoporosis and bone fractures in women. Some FNGPs are genetically correlated with AAM. In this study, we performed a bivariate genome-wide association study (GWAS) to identify new candidate genes responsible for both FNGPs and AAM. In the discovery stage, we tested 760,794 SNPs in 1,728 unrelated Caucasian subject, followed by replication analyses in independent samples of US Caucasians (with 501 subjects) and Chinese (with 826 subjects). We found six SNPs that were associated with FNGPs and AAM. These SNPs are located in three genes (i.e. NRCAM, IDS and LOC148145), suggesting these three genes may co-regulate FNGPs and AAM. Our findings may help improve the understanding of genetic architecture and pathophysiological mechanisms underlying both osteoporosis and AAM.

Complete haplotype sequence of the human immunoglobulin heavy-chain variable, diversity, and joining genes and characterization of allelic and copy-number variation

The immunoglobulin heavy-chain locus (IGH) encodes variable (IGHV), diversity (IGHD), joining (IGHJ), and constant (IGHC) genes and is responsible for antibody heavy-chain biosynthesis, which is vital to the adaptive immune response. Programmed V-(D)-J somatic rearrangement and the complex duplicated nature of the locus have impeded attempts to reconcile its genomic organization based on traditional B-lymphocyte derived genetic material. As a result, sequence descriptions of germline variation within IGHV are lacking, haplotype inference using traditional linkage disequilibrium methods has been difficult, and the human genome reference assembly is missing several expressed IGHV genes. By using a hydatidiform mole BAC clone resource, we present the most complete haplotype of IGHV, IGHD, and IGHJ gene regions derived from a single chromosome, representing an alternate assembly of ∼1 Mbp of high-quality finished sequence. From this we add 101 kbp of previously uncharacterized sequence, including functional IGHV genes, and characterize four large germline copy-number variants (CNVs). In addition to this germline reference, we identify and characterize eight CNV-containing haplotypes from a panel of nine diploid genomes of diverse ethnic origin, discovering previously unmapped IGHV genes and an additional 121 kbp of insertion sequence. We genotype four of these CNVs by using PCR in 425 individuals from nine human populations. We find that all four are highly polymorphic and show considerable evidence of stratification (Fst = 0.3-0.5), with the greatest differences observed between African and Asian populations. These CNVs exhibit weak linkage disequilibrium with SNPs from two commercial arrays in most of the populations tested.

Copy number variation prevalence in known asthma genes and their impact on asthma susceptibility

BACKGROUND

Genetic studies have identified numerous genes reproducibly associated with asthma, yet these studies have focussed almost entirely on single nucleotide polymorphisms (SNPs), and virtually ignored another highly prevalent form of genetic variation: Copy Number Variants (CNVs).

OBJECTIVE

To survey the prevalence of CNVs in genes previously associated with asthma, and to assess whether CNVs represent the functional asthma-susceptibility variants at these loci.

METHODS

We genotyped 383 asthmatic trios participating in the Childhood Asthma Management Program (CAMP) using a competitive genomic hybridization (CGH) array designed to interrogate 20 092 CNVs. To ensure comprehensive assessment of all potential asthma candidate genes, we purposely used liberal asthma gene inclusion criteria, resulting in consideration of 270 candidate genes previously implicated in asthma. We performed statistical testing using FBAT-CNV.

RESULTS

Copy number variation in asthma candidate genes was prevalent, with 21% of tested genes residing near or within one of 69 CNVs. In six instances, the complete candidate gene sequence resides within the CNV boundaries. On average, asthmatic probands carried six asthma-candidate CNVs (range 1-29). However, the vast majority of identified CNVs were of rare frequency (< 5%) and were not statistically associated with asthma. Modest evidence for association with asthma was observed for 2 CNVs near NOS1 and SERPINA3. Linkage disequilibrium analysis suggests that CNV effects are unlikely to explain previously detected SNP associations with asthma.

CONCLUSIONS AND CLINICAL RELEVANCE

Although a substantial proportion of asthma-susceptibility genes harbour polymorphic CNVs, the majority of these variants do not confer increased asthma risk. The lack of linkage disequilibrium (LD) between CNVs and asthma-associated SNPs suggests that these CNVs are unlikely to represent the functional variant responsible for most known asthma associations.

TIARA genome database: update 2013

The Total Integrated Archive of short-Read and Array (TIARA; http://tiara.gmi.ac.kr) database stores and integrates human genome data generated from multiple technologies including next-generation sequencing and high-resolution comparative genomic hybridization array. The TIARA genome browser is a powerful tool for the analysis of personal genomic information by exploring genomic variants such as SNPs, indels and structural variants simultaneously. As of September 2012, the TIARA database provides raw data and variant information for 13 sequenced whole genomes, 16 sequenced transcriptomes and 33 high resolution array assays. Sequencing reads are available at a depth of ~30× for whole genomes and 50× for transcriptomes. Information on genomic variants includes a total of ~9.56 million SNPs, 23 025 of which are non-synonymous SNPs, and ~1.19 million indels. In this update, by adding high coverage sequencing of additional human individuals, the TIARA genome database now provides an extensive record of rare variants in humans. Following TIARA's fundamentally integrative approach, new transcriptome sequencing data are matched with whole-genome sequencing data in the genome browser. Users can here observe, for example, the expression levels of human genes with allele-specific quantification. Improvements to the TIARA genome browser include the intuitive display of new complex and large-scale data sets.

Microhomology-mediated mechanisms underlie non-recurrent disease-causing microdeletions of the FOXL2 gene or its regulatory domain

Genomic disorders are often caused by recurrent copy number variations (CNVs), with nonallelic homologous recombination (NAHR) as the underlying mechanism. Recently, several microhomology-mediated repair mechanisms—such as microhomology-mediated end-joining (MMEJ), fork stalling and template switching (FoSTeS), microhomology-mediated break-induced replication (MMBIR), serial replication slippage (SRS), and break-induced SRS (BISRS)—were described in the etiology of non-recurrent CNVs in human disease. In addition, their formation may be stimulated by genomic architectural features. It is, however, largely unexplored to what extent these mechanisms contribute to rare, locus-specific pathogenic CNVs. Here, fine-mapping of 42 microdeletions of the FOXL2 locus, encompassing FOXL2 (32) or its regulatory domain (10), serves as a model for rare, locus-specific CNVs implicated in genetic disease. These deletions lead to blepharophimosis syndrome (BPES), a developmental condition affecting the eyelids and the ovary. For breakpoint mapping we used targeted array-based comparative genomic hybridization (aCGH), quantitative PCR (qPCR), long-range PCR, and Sanger sequencing of the junction products. Microhomology, ranging from 1 bp to 66 bp, was found in 91.7% of 24 characterized breakpoint junctions, being significantly enriched in comparison with a random control sample. Our results show that microhomology-mediated repair mechanisms underlie at least 50% of these microdeletions. Moreover, genomic architectural features, like sequence motifs, non-B DNA conformations, and repetitive elements, were found in all breakpoint regions. In conclusion, the majority of these microdeletions result from microhomology-mediated mechanisms like MMEJ, FoSTeS, MMBIR, SRS, or BISRS. Moreover, we hypothesize that the genomic architecture might drive their formation by increasing the susceptibility for DNA breakage or promote replication fork stalling. Finally, our locus-centered study, elucidating the etiology of a large set of rare microdeletions involved in a monogenic disorder, can serve as a model for other clustered, non-recurrent microdeletions in genetic disease.

Genomic disorder is a general term describing conditions caused by genomic aberrations leading to a copy number change of one or more genes. Copy number changes with the same length and clustered breakpoints for a group of patients with the same disorder are named recurrent rearrangements. These originate mostly from a well-studied mechanism, namely nonallelic homologous recombination (NAHR). In contrast, non-recurrent rearrangements vary in size, have scattered breakpoints, and can originate from several different mechanisms that are not fully understood. Here we tried to gain further insight into the extent to which these mechanisms contribute to non-recurrent rearrangements and into the possible role of the surrounding genomic architecture. To this end, we investigated a unique group of patients with non-recurrent deletions of the FOXL2 region causing blepharophimosis syndrome. We observed that the majority of these deletions can result from several mechanisms mediated by microhomology. Furthermore, our data suggest that rare pathogenic microdeletions do not occur at random genome sequences, but are possibly guided by the surrounding genomic architecture. Finally, our study, elucidating the etiology of a unique cohort of locus-specific microdeletions implicated in genetic disease, can serve as a model for the formation of genomic aberrations in other genetic disorders.

Germline and somatic KLLN alterations in breast cancer dysregulate G2 arrest

PTEN is a well-described predisposition gene for Cowden syndrome (CS), a familial cancer syndrome characterized by a high risk of breast and other cancers. KLLN, which shares a bidirectional promoter with PTEN, causes cell cycle arrest and apoptosis. We previously identified germline hypermethylation of the KLLN promoter in 37% of PTEN mutation-negative CS/CS-like (CSL) patients. Patients with germline KLLN hypermethylation have an increased prevalence of breast and renal cancers when compared with PTEN mutation carriers. We have consequently sought to identify and characterize germline KLLN variants/mutations in CS/CSL and in apparently sporadic breast cancer patients. KLLN variants in CS/CSL patients are rare (1 of 136, 0.007%). Interestingly, among 438 breast cancer patients, 13 (3%) have germline KLLN variants when compared with none in 128 controls (P = 0.049). Patients with KLLN variants have a family history of breast cancer when compared with those without (P = 0.02). We demonstrate that germline KLLN variants dysregulate the cell cycle at G2. Of 24 breast carcinomas analyzed, 3 (13%) have somatic KLLN hemizygous deletions, with somatic loss of the wild-type allele in a patient with germline KLLN p.Leu119Leu. Of 452 breast carcinomas in The Cancer Genome Atlas project, 93 (21%) have KLLN hemizygous or homozygous deletions. This is the first study to associate germline KLLN variants with sporadic breast cancer and to recognize somatic KLLN deletions in breast carcinomas. Our observations suggest that KLLN may be a low penetrance susceptibility factor for apparently sporadic breast cancer.

A computational method for detecting copy number variations using scale-space filtering

Background

As next-generation sequencing technology made rapid and cost-effective sequencing available, the importance of computational approaches in finding and analyzing copy number variations (CNVs) has been amplified. Furthermore, most genome projects need to accurately analyze sequences with fairly low-coverage read data. It is urgently needed to develop a method to detect the exact types and locations of CNVs from low coverage read data.

Results

Here, we propose a new CNV detection method, CNV_SS, which uses scale-space filtering. The scale-space filtering is evaluated by applying to the read coverage data the Gaussian convolution for various scales according to a given scaling parameter. Next, by differentiating twice and finding zero-crossing points, inflection points of scale-space filtered read coverage data are calculated per scale. Then, the types and the exact locations of CNVs are obtained by analyzing the finger print map, the contours of zero-crossing points for various scales.

Conclusions

The performance of CNV_SS showed that FNR and FPR stay in the range of 1.27% to 2.43% and 1.14% to 2.44%, respectively, even at a relatively low coverage (0.5x ≤C ≤2x). CNV_SS gave also much more effective results than the conventional methods in the evaluation of FNR, at 3.82% at least and 76.97% at most even when the coverage level of read data is low. CNV_SS source code is freely available from http://dblab.hallym.ac.kr/CNV SS/.

Contribution of copy number variants involving nonsense-mediated mRNA decay pathway genes to neuro-developmental disorders

The nonsense-mediated mRNA decay (NMD) pathway functions not only to degrade transcripts containing premature termination codons (PTC), but also to regulate the transcriptome. UPF3B and RBM8A, important components of NMD, have been implicated in various forms of intellectual disability (ID) and Thrombocytopenia with Absent Radius (TAR) syndrome, which is also associated with ID. To gauge the contribution of other NMD factors to ID, we performed a comprehensive search for copy number variants (CNVs) of 18 NMD genes among individuals with ID and/or congenital anomalies. We identified 11 cases with heterozygous deletions of the genomic region encompassing UPF2, which encodes for a direct interacting protein of UPF3B. Using RNA-Seq, we showed that the genome-wide consequence of reduced expression of UPF2 is similar to that seen in patients with UPF3B mutations. Out of the 1009 genes found deregulated in patients with UPF2 deletions by at least 2-fold, majority (95%) were deregulated similarly in patients with UPF3B mutations. This supports the major role of deletion of UPF2 in ID. Furthermore, we found that four other NMD genes, UPF3A, SMG6, EIF4A3 and RNPS1 are frequently deleted and/or duplicated in the patients. We postulate that dosage imbalances of these NMD genes are likely to be the causes or act as predisposing factors for neuro-developmental disorders. Our findings further emphasize the importance of NMD pathway(s) in learning and memory.

No effect of genome-wide copy number variation on measures of intelligence in a New Zealand birth cohort

Variation in human intelligence is approximately 50% heritable, but understanding of the genes involved is limited. Several forms of genetic variation remain under-studied in relation to intelligence, one of which is copy number variation (CNV). Using single-nucleotide polymorphism (SNP) -based microarrays, we genotyped CNVs genome-wide in a birth cohort of 723 New Zealanders, and correlated them with four intelligence-related phenotypes. We found no significant association for any common CNV after false discovery correction, which is consistent with previous work. In contrast to a previous study, however, we found no effect on any cognitive measure of rare CNV burden, defined as total number of bases inserted or deleted in CNVs rarer than 5%. We discuss possible reasons for this failure to replicate, including interaction between CNV and aging in determining the effects of rare CNVs. While our results suggest that no CNV assayable by SNP chips contributes more than a very small amount to variation in human intelligence, it remains possible that common CNVs in segmental duplication arrays, which are not well covered by SNP chips, are important contributors.

Development of a physical model-based algorithm for the detection of single-nucleotide substitutions by using tiling microarrays

High-density DNA microarrays are useful tools for analyzing sequence changes in DNA samples. Although microarray analysis provides informative signals from a large number of probes, the analysis and interpretation of these signals have certain inherent limitations, namely, complex dependency of signals on the probe sequences and the existence of false signals arising from non-specific binding between probe and target. In this study, we have developed a novel algorithm to detect the single-base substitutions by using microarray data based on a thermodynamic model of hybridization. We modified the thermodynamic model by introducing a penalty for mismatches that represent the effects of substitutions on hybridization affinity. This penalty results in significantly higher detection accuracy than other methods, indicating that the incorporation of hybridization free energy can improve the analysis of sequence variants by using microarray data.

Gene copy-number polymorphism caused by retrotransposition in humans

The era of whole-genome sequencing has revealed that gene copy-number changes caused by duplication and deletion events have important evolutionary, functional, and phenotypic consequences. Recent studies have therefore focused on revealing the extent of variation in copy-number within natural populations of humans and other species. These studies have found a large number of copy-number variants (CNVs) in humans, many of which have been shown to have clinical or evolutionary importance. For the most part, these studies have failed to detect an important class of gene copy-number polymorphism: gene duplications caused by retrotransposition, which result in a new intron-less copy of the parental gene being inserted into a random location in the genome. Here we describe a computational approach leveraging next-generation sequence data to detect gene copy-number variants caused by retrotransposition (retroCNVs), and we report the first genome-wide analysis of these variants in humans. We find that retroCNVs account for a substantial fraction of gene copy-number differences between any two individuals. Moreover, we show that these variants may often result in expressed chimeric transcripts, underscoring their potential for the evolution of novel gene functions. By locating the insertion sites of these duplicates, we are able to show that retroCNVs have had an important role in recent human adaptation, and we also uncover evidence that positive selection may currently be driving multiple retroCNVs toward fixation. Together these findings imply that retroCNVs are an especially important class of polymorphism, and that future studies of copy-number variation should search for these variants in order to illuminate their potential evolutionary and functional relevance.

Recent studies of human genetic variation have revealed that, in addition to differing at single nucleotide polymorphisms, individuals differ in copy-number at many regions of the genome. These copy-number variants (CNVs) are caused by duplication or deletion events and often affect functional sequences such as genes. Efforts to reveal the functional impact of CNVs have identified many variants increasing the risk of various disorders, and some that are adaptive. However, these studies mostly fail to detect gene duplications caused by retrotransposition, in which an mRNA transcript is reverse-transcribed and reinserted into the genome, yielding a new intron-less gene copy. Here we describe a method leveraging next-generation sequence data to accurately detect gene copy-number variants caused by retrotransposition, or retroCNVs, and apply this method to hundreds of whole-genome sequences from three different human subpopulations. We find that these variants account for a substantial number of gene copy-number differences between individuals, and that gene retrotransposition may often result in both deleterious and beneficial mutations. Indeed, we present evidence that two of these new gene duplications may be adaptive. These results imply that retroCNVs are an especially important class of CNV and should be included in future studies of human copy-number variation.

Impact of constitutional copy number variants on biological pathway evolution

Background

Inherited Copy Number Variants (CNVs) can modulate the expression levels of individual genes. However, little is known about how CNVs alter biological pathways and how this varies across different populations. To trace potential evolutionary changes of well-described biological pathways, we jointly queried the genomes and the transcriptomes of a collection of individuals with Caucasian, Asian or Yoruban descent combining high-resolution array and sequencing data.

Results

We implemented an enrichment analysis of pathways accounting for CNVs and genes sizes and detected significant enrichment not only in signal transduction and extracellular biological processes, but also in metabolism pathways. Upon the estimation of CNV population differentiation (CNVs with different polymorphism frequencies across populations), we evaluated that 22% of the pathways contain at least one gene that is proximal to a CNV (CNV-gene pair) that shows significant population differentiation. The majority of these CNV-gene pairs belong to signal transduction pathways and 6% of the CNV-gene pairs show statistical association between the copy number states and the transcript levels.

Conclusions

The analysis suggested possible examples of positive selection within individual populations including NF-kB, MAPK signaling pathways, and Alu/L1 retrotransposition factors. Altogether, our results suggest that constitutional CNVs may modulate subtle pathway changes through specific pathway enzymes, which may become fixed in some populations.

Child development and structural variation in the human genome

Structural variation of the human genome sequence is the insertion, deletion, or rearrangement of stretches of DNA sequence sized from around 1,000 to millions of base pairs. Over the past few years, structural variation has been shown to be far more common in human genomes than previously thought. Very little is currently known about the effects of structural variation on normal child development, but such effects could be of considerable significance. This review provides an overview of the phenomenon of structural variation in the human genome sequence, describing the novel genomics technologies that are revolutionizing the way structural variation is studied and giving examples of genomic structural variations that affect child development.

ParseCNV integrative copy number variation association software with quality tracking

A number of copy number variation (CNV) calling algorithms exist; however, comprehensive software tools for CNV association studies are lacking. We describe ParseCNV, unique software that takes CNV calls and creates probe-based statistics for CNV occurrence in both case–control design and in family based studies addressing both de novo and inheritance events, which are then summarized based on CNV regions (CNVRs). CNVRs are defined in a dynamic manner to allow for a complex CNV overlap while maintaining precise association region. Using this approach, we avoid failure to converge and non-monotonic curve fitting weaknesses of programs, such as CNVtools and CNVassoc, and although Plink is easy to use, it only provides combined CNV state probe-based statistics, not state-specific CNVRs. Existing CNV association methods do not provide any quality tracking information to filter confident associations, a key issue which is fully addressed by ParseCNV. In addition, uncertainty in CNV calls underlying CNV associations is evaluated to verify significant results, including CNV overlap profiles, genomic context, number of probes supporting the CNV and single-probe intensities. When optimal quality control parameters are followed using ParseCNV, 90% of CNVs validate by polymerase chain reaction, an often problematic stage because of inadequate significant association review. ParseCNV is freely available at http://parsecnv.sourceforge.net.

The Role of Copy Number Variation in African Americans with Type 2 Diabetes-Associated End Stage Renal Disease

This study investigated the association of copy number variants (CNVs) in type 2 diabetes (T2D) and T2D-associated end-stage renal disease (ESRD) in African Americans. Using the Affymetrix 6.0 array, >900,000 CNV probes spanning the genome were interrogated in 965 African Americans with T2D-ESRD and 1029 non-diabetic African American controls. Previously identified and novel CNVs were separately analyzed and were evaluated for insertion/deletion status and then used as predictors in a logistic regression model to test for association. One common CNV insertion on chromosome 1 was significantly associated with T2D-ESRD (p=6.17×10^-5, OR=1.63) after multiple comparison correction. This CNV region encompasses the genes AMY2A and AMY2B, which encode amylase isoenzymes produced by the pancreas. Additional common and novel CNVs approaching significance with disease were also detected. These exploratory results require further replication but suggest the involvement of the AMY2A/AMY2B CNV in T2D and/or T2D-ESRD, and indicate that CNVs may contribute to susceptibility for these diseases.

Genome-wide association studies

A host of data on genetic variation from the Human Genome and International HapMap projects, and advances in high-throughput genotyping technologies, have made genome-wide association (GWA) studies technically feasible. GWA studies help in the discovery and quantification of the genetic components of disease risks, many of which have not been unveiled before and have opened a new avenue to understanding disease, treatment, and prevention. This chapter presents an overview of GWA, an important tool for discovering regions of the genome that harbor common genetic variants to confer susceptibility for various diseases or health outcomes in the post-Human Genome Project era. A tutorial on how to conduct a GWA study and some practical challenges specifically related to the GWA design is presented, followed by a detailed GWA case study involving the identification of loci associated with glioma as an example and an illustration of current technologies.

Copy number variation on chromosome 10q26.3 for obesity identified by a genome-wide study

BACKGROUND

Obesity is a highly heritable disease defined by high body mass index (BMI). However, a large proportion of the heritability of obesity remains unexplained. Copy number variations (CNVs) might contribute to the missing heritability of obesity.

METHODS

We conducted genome-wide CNV analyses on obesity phenotypes, including BMI and body fat mass in a discovery sample of 2215 unrelated white subjects. After quality control, 314 CNVs were used for association tests. For significant CNVs identified, follow-up replication analyses were performed in three independent samples, including an unrelated sample of 1000 white subjects (OM sample), a family-based sample of 8385 white subjects (FHS sample), and an African-American sample of 1479 obesity cases and 1575 lean controls (AA sample).

RESULTS

Genome-wide CNV analyses detected that a CNV located at 10q26.3, which, even after multiple testing corrections, showed a strong association with both BMI (P = 2.30 × 10(-4), β = 2.164) and body fat mass (P = 6.76 × 10(-5), β = 4.126). This CNV was successfully replicated in the three replication samples (OM sample: P = 0.0465 for BMI, 0.0435 for fat mass; FHS sample: P = 0.0038 for BMI; AA sample: P = 0.0023 for obesity). Quantitative PCR validated this CNV, which covers a gene, CYP2E1. The protein encoded by CYP2E1 involves the synthesis of cholesterol, steroids and other lipids, which may have a potential impact on obesity.

CONCLUSION

Our findings suggest the significant contribution of CNV10q26.3 to the pathogenesis of obesity.

CGH protocols: chronic lymphocytic leukemia

Array-based comparative genomic hybridization (aCGH) is a powerful assay to identify copy number abnormalities underlying the pathogenesis of cancer. aCGH has become the gold standard for whole genome copy number analysis in medium and large cohorts in clinical and research laboratories. Identifying the best workflow is critical to achieving the optimal performance for this assay. Here we describe the aCGH protocol used by our group in the study of B-chronic lymphocytic leukemia (CLL). We also describe some initial applications of aCGH in association with clinical outcome for CLL.

A pilot study on collective effects of 22q13.31 deletions on gray matter concentration in schizophrenia

The association of copy number variation (CNV) with schizophrenia has been reported with evidence of increased frequency of both rare and large CNVs. Yet, little is known about the impact of CNVs in brain structure. In this pilot study, we explored collective effects of all CNVs in each cytogenetic band on the risk of schizophrenia and gray matter variation measured in structural magnetic resonance imaging. With 324 participants' CNV profiles (151 schizophrenia patients and 173 healthy controls), we first extracted specific CNV features that differ between patients and controls using a two sample t-test, and then tested their associations with gray matter concentration using a linear regression model in a subset of 301 participants. Our data first provided evidence of population structure in CNV features where elevated rare CNV burden in schizophrenia patients was confounded by the levels associated with African American subjects. We considered this ethnic group difference in the following cytoband analyses. Deletions in one cytoband 22q13.31 were observed significantly (p<0.05) more in patients than controls from all samples after controlling ethnicity, and the deletion load was also significantly (p = 1.44×10⁻⁴) associated with reduced gray matter concentration of a brain network mainly comprised of the cingulate gyrus and insula. Since 80% deletion carriers were patients, patients with deletions also showed reduced gray matter concentration compared with patients without deletions (p = 3.36×10⁻⁴). Our findings indicate that regional CNVs at 22q13.31, no matter the size, may influence the risk of schizophrenia with a remarkably increased mutation rate and with reduced gray matter concentration in the peri-limbic cortex. This proof-of-concept study suggests that the CNVs occurring at some 'hotspots' may in fact cause biological downstream effects and larger studies are important for confirming our initial results.

Improving detection of copy-number variation by simultaneous bias correction and read-depth segmentation

Structural variation is an important class of genetic variation in mammals. High-throughput sequencing (HTS) technologies promise to revolutionize copy-number variation (CNV) detection but present substantial analytic challenges. Converging evidence suggests that multiple types of CNV-informative data (e.g. read-depth, read-pair, split-read) need be considered, and that sophisticated methods are needed for more accurate CNV detection. We observed that various sources of experimental biases in HTS confound read-depth estimation, and note that bias correction has not been adequately addressed by existing methods. We present a novel read-depth-based method, GENSENG, which uses a hidden Markov model and negative binomial regression framework to identify regions of discrete copy-number changes while simultaneously accounting for the effects of multiple confounders. Based on extensive calibration using multiple HTS data sets, we conclude that our method outperforms existing read-depth-based CNV detection algorithms. The concept of simultaneous bias correction and CNV detection can serve as a basis for combining read-depth with other types of information such as read-pair or split-read in a single analysis. A user-friendly and computationally efficient implementation of our method is freely available.

Copy number variation signature to predict human ancestry

BACKGROUND

Copy number variations (CNVs) are genomic structural variants that are found in healthy populations and have been observed to be associated with disease susceptibility. Existing methods for CNV detection are often performed on a sample-by-sample basis, which is not ideal for large datasets where common CNVs must be estimated by comparing the frequency of CNVs in the individual samples. Here we describe a simple and novel approach to locate genome-wide CNVs common to a specific population, using human ancestry as the phenotype.

RESULTS

We utilized our previously published Genome Alteration Detection Analysis (GADA) algorithm to identify common ancestry CNVs (caCNVs) and built a caCNV model to predict population structure. We identified a 73 caCNV signature using a training set of 225 healthy individuals from European, Asian, and African ancestry. The signature was validated on an independent test set of 300 individuals with similar ancestral background. The error rate in predicting ancestry in this test set was 2% using the 73 caCNV signature. Among the caCNVs identified, several were previously confirmed experimentally to vary by ancestry. Our signature also contains a caCNV region with a single microRNA (MIR270), which represents the first reported variation of microRNA by ancestry.

CONCLUSIONS

We developed a new methodology to identify common CNVs and demonstrated its performance by building a caCNV signature to predict human ancestry with high accuracy. The utility of our approach could be extended to large case-control studies to identify CNV signatures for other phenotypes such as disease susceptibility and drug response.

Genetic copy number variation and general cognitive ability

Differences in genomic structure between individuals are ubiquitous features of human genetic variation. Specific copy number variants (CNVs) have been associated with susceptibility to numerous complex psychiatric disorders, including attention-deficit-hyperactivity disorder, autism-spectrum disorders and schizophrenia. These disorders often display co-morbidity with low intelligence. Rare chromosomal deletions and duplications are associated with these disorders, so it has been suggested that these deletions or duplications may be associated with differences in intelligence. Here we investigate associations between large (≥500kb), rare (<1% population frequency) CNVs and both fluid and crystallized intelligence in community-dwelling older people. We observe no significant associations between intelligence and total CNV load. Examining individual CNV regions previously implicated in neuropsychological disorders, we find suggestive evidence that CNV regions around SHANK3 are associated with fluid intelligence as derived from a battery of cognitive tests. This is the first study to examine the effects of rare CNVs as called by multiple algorithms on cognition in a large non-clinical sample, and finds no effects of such variants on general cognitive ability.

Identification of genome-wide copy number variations among diverse pig breeds by array CGH

Background

Recent studies have shown that copy number variation (CNV) in mammalian genomes contributes to phenotypic diversity, including health and disease status. In domestic pigs, CNV has been catalogued by several reports, but the extent of CNV and the phenotypic effects are far from clear. The goal of this study was to identify CNV regions (CNVRs) in pigs based on array comparative genome hybridization (aCGH).

Results

Here a custom-made tiling oligo-nucleotide array was used with a median probe spacing of 2506 bp for screening 12 pigs including 3 Chinese native pigs (one Chinese Erhualian, one Tongcheng and one Yangxin pig), 5 European pigs (one Large White, one Pietrain, one White Duroc and two Landrace pigs), 2 synthetic pigs (Chinese new line DIV pigs) and 2 crossbred pigs (Landrace × DIV pigs) with a Duroc pig as the reference. Two hundred and fifty-nine CNVRs across chromosomes 1–18 and X were identified, with an average size of 65.07 kb and a median size of 98.74 kb, covering 16.85 Mb or 0.74% of the whole genome. Concerning copy number status, 93 (35.91%) CNVRs were called as gains, 140 (54.05%) were called as losses and the remaining 26 (10.04%) were called as both gains and losses. Of all detected CNVRs, 171 (66.02%) and 34 (13.13%) CNVRs directly overlapped with Sus scrofa duplicated sequences and pig QTLs, respectively. The CNVRs encompassed 372 full length Ensembl transcripts. Two CNVRs identified by aCGH were validated using real-time quantitative PCR (qPCR).

Conclusions

Using 720 K array CGH (aCGH) we described a map of porcine CNVs which facilitated the identification of structural variations for important phenotypes and the assessment of the genetic diversity of pigs.

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.

Discovering gene-environment interactions in glioblastoma through a comprehensive data integration bioinformatics method

Glioblastoma multiforme (GBM) is the most common and aggressive type of human brain tumor. Although considerable efforts to delineate the underlying pathophysiological pathways have been made during the last decades, only very limited progress on treatment have been achieved because molecular pathways that drive the aggressive nature of GBM are largely unknown. Recent studies have emphasized the importance of environmental factors and the role of gene-environment interactions (GEI) in the development of GBM. Factors such as small sample sizes and study costs have limited the conduct of GEI studies in brain tumors however. Additionally, advances in high-throughput microarrays have produced a wealth of information concerning molecular biology of glioma. In particular, microarrays have been used to obtain genetic and epigenetic changes between normal non-tumor tissue and glioma tissue. Due to the relative rarity of gliomas, microarray data for these tumors is often the product of small studies, and thus pooling this data becomes desirable. To address the challenge of small sample sizes and GEI study difficulties, we introduce a comprehensive bioinformatics method using genetic variations (copy number variations and small-scale variations) and environmental data integration that links with glioblastoma (GEG) to identify: (1) genes that interact with chemicals and have genetic variants linked to the development of GBM, (2) important pathways that may be influenced by environmental exposures (or endogenous chemicals), and (3) genes with variants in GBM that have been understudied in relation to GBM development. The first step in our GEG method identified genes responsive to environmental exposures using the Environmental Genome Project, Comparative Toxicology, and Seattle SNPs databases. These environmentally responsive genes were then compared to a curated list of genes containing copy number variation and/or mutations in GBM. This comparison produced a list of genes responsive to the environment and important to GBM that was then further analyzed using gene networking tools such as RSpider, Cytoscape, and DAVID. Using this GEG bioinformatics method we were able to identify 173 genes with the potential to be involved in GEI that may be important to the development of GBM. Sixty five of these environmentally responsive genes have not been reported as important to GBM development, despite several of them having substantial potential for response to chemicals and subsequent disease related actions. The main biological functions of these 173 genes include signaling by nerve growth factor, DNA repair, integrin cell surface interactions, biological oxidations, apoptosis, synaptic transmission, cell cycle checkpoints, and arachidonic acid metabolism. Importantly, some of these functions have been implicated in the development of several cancers, including glioma. In summary, our GEG bioinformatics approach revealed potential gene-environment interactions, and generated new data for hypothesis generation, in GBM.