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

Assessing copy number alterations in targeted, amplicon-based next-generation sequencing data

Changes in gene copy number are important in the setting of precision medicine. Recent studies have established that copy number alterations (CNAs) can be detected in sequencing libraries prepared by hybridization-capture, but there has been comparatively little attention given to CNA assessment in amplicon-based libraries prepared by PCR. In this study, we developed an algorithm for detecting CNAs in amplicon-based sequencing data. CNAs determined from the algorithm mirrored those from a hybridization-capture library. In addition, analysis of 14 pairs of matched normal and breast carcinoma tissues revealed that sequence data pooled from normal samples could be substituted for a matched normal tissue without affecting the detection of clinically relevant CNAs (>|2| copies). Comparison of CNAs identified by array comparative genomic hybridization and amplicon-based libraries across 10 breast carcinoma samples showed an excellent correlation. The CNA algorithm also compared favorably with fluorescence in situ hybridization, with agreement in 33 of 38 assessments across four different genes. Factors that influenced the detection of CNAs included the number of amplicons per gene, the average read depth, and, most important, the proportion of tumor within the sample. Our results show that CNAs can be identified in amplicon-based targeted sequencing data, and that their detection can be optimized by ensuring adequate tumor content and read coverage.

BAT2 and BAT3 polymorphisms as novel genetic risk factors for rejection after HLA-related SCT

The genetic background of donor and recipient is an important factor determining the outcome of allogeneic hematopoietic SCT (allo-HSCT). We applied whole-genome analysis to investigate genetic variants-other than HLA class I and II-associated with negative outcome after HLA-identical sibling allo-HSCT in a cohort of 110 β-Thalassemic patients. We identified two single-nucleotide polymorphisms (SNPs) in BAT2 (A/G) and BAT3 (T/C) genes, SNP rs11538264 and SNP rs10484558, both located in the HLA class III region, in strong linkage disequilibrium between each other (R(2)=0.92). When considered as single SNP, none of them reached a significant association with graft rejection (nominal P<0.00001 for BAT2 SNP rs11538264, and P<0.0001 for BAT3 SNP rs10484558), whereas the BAT2/BAT3 A/C haplotype was present at significantly higher frequency in patients who rejected as compared to those with functional graft (30.0% vs 2.6%, nominal P=1.15 × 10(-8); and adjusted P=0.0071). The BAT2/BAT3 polymorphisms and specifically the A/C haplotype may represent a novel immunogenetic factor associated with graft rejection in patients undergoing allo-HSCT.

DNA methylation modifies urine biomarker levels in 1,6-hexamethylene diisocyanate exposed workers: a pilot study

DNA methylation may mediate inter-individual responses to chemical exposure and, thus, modify biomarker levels of exposure and effects. We analyzed inter-individual differences in inhalation and skin exposure to 1,6-hexamethylene diisocyanate (HDI) and urine biomarker 1,6-hexamethylene diamine (HDA) levels in 20 automotive spray-painters. Genome-wide 5-methyl cytosine (CpG) DNA methylation was assessed in each individual's peripheral blood mononuclear cells (PBMC) DNA using the Illumina 450K CpG array. Mediation analysis using linear regression models adjusted for age, ethnicity, and smoking was conducted to identify and assess the association between HDI exposure, CpG methylation, and urine HDA biomarker levels. We did not identify any CpGs common to HDI exposure and biomarker level suggesting that CpG methylation is a mediator that only partially explains the phenotype. Functional significance of genic- and intergenic-CpG methylation status was tested using protein-protein or protein-DNA interactions and gene-ontology enrichment to infer networks. Combined, the results suggest that methylation has the potential to affect HDI mass transport, permeation, and HDI metabolism. We demonstrate the potential use of PBMC methylation along with quantitative exposure and biomarker data to guide further investigation into the mediators of occupational exposure and biomarkers and its role in risk assessment.

Abnormal dosage of ultraconserved elements is highly disfavored in healthy cells but not cancer cells

Ultraconserved elements (UCEs) are strongly depleted from segmental duplications and copy number variations (CNVs) in the human genome, suggesting that deletion or duplication of a UCE can be deleterious to the mammalian cell. Here we address the process by which CNVs become depleted of UCEs. We begin by showing that depletion for UCEs characterizes the most recent large-scale human CNV datasets and then find that even newly formed de novo CNVs, which have passed through meiosis at most once, are significantly depleted for UCEs. In striking contrast, CNVs arising specifically in cancer cells are, as a rule, not depleted for UCEs and can even become significantly enriched. This observation raises the possibility that CNVs that arise somatically and are relatively newly formed are less likely to have established a CNV profile that is depleted for UCEs. Alternatively, lack of depletion for UCEs from cancer CNVs may reflect the diseased state. In support of this latter explanation, somatic CNVs that are not associated with disease are depleted for UCEs. Finally, we show that it is possible to observe the CNVs of induced pluripotent stem (iPS) cells become depleted of UCEs over time, suggesting that depletion may be established through selection against UCE-disrupting CNVs without the requirement for meiotic divisions.

Whole-genome haplotyping approaches and genomic medicine

Genomic information reported as haplotypes rather than genotypes will be increasingly important for personalized medicine. Current technologies generate diploid sequence data that is rarely resolved into its constituent haplotypes. Furthermore, paradigms for thinking about genomic information are based on interpreting genotypes rather than haplotypes. Nevertheless, haplotypes have historically been useful in contexts ranging from population genetics to disease-gene mapping efforts. The main approaches for phasing genomic sequence data are molecular haplotyping, genetic haplotyping, and population-based inference. Long-read sequencing technologies are enabling longer molecular haplotypes, and decreases in the cost of whole-genome sequencing are enabling the sequencing of whole-chromosome genetic haplotypes. Hybrid approaches combining high-throughput short-read assembly with strategic approaches that enable physical or virtual binning of reads into haplotypes are enabling multi-gene haplotypes to be generated from single individuals. These techniques can be further combined with genetic and population approaches. Here, we review advances in whole-genome haplotyping approaches and discuss the importance of haplotypes for genomic medicine. Clinical applications include diagnosis by recognition of compound heterozygosity and by phasing regulatory variation to coding variation. Haplotypes, which are more specific than less complex variants such as single nucleotide variants, also have applications in prognostics and diagnostics, in the analysis of tumors, and in typing tissue for transplantation. Future advances will include technological innovations, the application of standard metrics for evaluating haplotype quality, and the development of databases that link haplotypes to disease.

EXCAVATOR: detecting copy number variants from whole-exome sequencing data

We developed a novel software tool, EXCAVATOR, for the detection of copy number variants (CNVs) from whole-exome sequencing data. EXCAVATOR combines a three-step normalization procedure with a novel heterogeneous hidden Markov model algorithm and a calling method that classifies genomic regions into five copy number states. We validate EXCAVATOR on three datasets and compare the results with three other methods. These analyses show that EXCAVATOR outperforms the other methods and is therefore a valuable tool for the investigation of CNVs in largescale projects, as well as in clinical research and diagnostics. EXCAVATOR is freely available at http://sourceforge.net/projects/excavatortool/.

Advances in Genetic Discovery and Implications for Counseling of Patients and Families with Autism Spectrum Disorders

The prevalence of autism spectrum disorders (ASD) continues to increase. Genetic factors play an important role in the etiology of ASD, although specific genetic causes are identified in only a minority of cases. Recent advances have accelerated the discovery of genes implicated in ASD through convergent genomic analysis of genome-wide association studies, chromosomal microarray, exome sequencing, genome sequencing, and gene networks. Hundreds of candidate genes for ASD have been reported, yet only a handful have proven causative. Symptoms are complex and highly variable, and most cases are likely due to cumulative genetic factors, the interactions among them, as well as environmental factors. Here we summarize recent findings in genomic research regarding discovery of candidate genes, describe the major molecular processes in neural development that may be disrupted in ASD, and discuss the implication of research findings in clinical genetic diagnostic testing and counseling. Continued advances in genetic research will eventually translate into innovative approaches to prevention and treatment of ASD.

Exome sequence read depth methods for identifying copy number changes

Copy number variants (CNVs) play important roles in a number of human diseases and in pharmacogenetics. Powerful methods exist for CNV detection in whole genome sequencing (WGS) data, but such data are costly to obtain. Many disease causal CNVs span or are found in genome coding regions (exons), which makes CNV detection using whole exome sequencing (WES) data attractive. If reliably validated against WGS-based CNVs, exome-derived CNVs have potential applications in a clinical setting. Several algorithms have been developed to exploit exome data for CNV detection and comparisons made to find the most suitable methods for particular data samples. The results are not consistent across studies. Here, we review some of the exome CNV detection methods based on depth of coverage profiles and examine their performance to identify problems contributing to discrepancies in published results. We also present a streamlined strategy that uses a single metric, the likelihood ratio, to compare exome methods, and we demonstrated its utility using the VarScan 2 and eXome Hidden Markov Model (XHMM) programs using paired normal and tumour exome data from chronic lymphocytic leukaemia patients. We use array-based somatic CNV (SCNV) calls as a reference standard to compute prevalence-independent statistics, such as sensitivity, specificity and likelihood ratio, for validation of the exome-derived SCNVs. We also account for factors known to influence the performance of exome read depth methods, such as CNV size and frequency, while comparing our findings with published results.

Whole-genome sequencing of individuals from a founder population identifies candidate genes for asthma

Asthma is a complex genetic disease caused by a combination of genetic and environmental risk factors. We sought to test classes of genetic variants largely missed by genome-wide association studies (GWAS), including copy number variants (CNVs) and low-frequency variants, by performing whole-genome sequencing (WGS) on 16 individuals from asthma-enriched and asthma-depleted families. The samples were obtained from an extended 13-generation Hutterite pedigree with reduced genetic heterogeneity due to a small founding gene pool and reduced environmental heterogeneity as a result of a communal lifestyle. We sequenced each individual to an average depth of 13-fold, generated a comprehensive catalog of genetic variants, and tested the most severe mutations for association with asthma. We identified and validated 1960 CNVs, 19 nonsense or splice-site single nucleotide variants (SNVs), and 18 insertions or deletions that were out of frame. As follow-up, we performed targeted sequencing of 16 genes in 837 cases and 540 controls of Puerto Rican ancestry and found that controls carry a significantly higher burden of mutations in IL27RA (2.0% of controls; 0.23% of cases; nominal p = 0.004; Bonferroni p = 0.21). We also genotyped 593 CNVs in 1199 Hutterite individuals. We identified a nominally significant association (p = 0.03; Odds ratio (OR) = 3.13) between a 6 kbp deletion in an intron of NEDD4L and increased risk of asthma. We genotyped this deletion in an additional 4787 non-Hutterite individuals (nominal p = 0.056; OR = 1.69). NEDD4L is expressed in bronchial epithelial cells, and conditional knockout of this gene in the lung in mice leads to severe inflammation and mucus accumulation. Our study represents one of the early instances of applying WGS to complex disease with a large environmental component and demonstrates how WGS can identify risk variants, including CNVs and low-frequency variants, largely untested in GWAS.

BAT2 and BAT3 polymorphisms as novel genetic risk factors for rejection after HLA-related SCT

The genetic background of donor and recipient is an important factor determining the outcome of allogeneic hematopoietic SCT (allo-HSCT). We applied whole-genome analysis to investigate genetic variants-other than HLA class I and II-associated with negative outcome after HLA-identical sibling allo-HSCT in a cohort of 110 β-Thalassemic patients. We identified two single-nucleotide polymorphisms (SNPs) in BAT2 (A/G) and BAT3 (T/C) genes, SNP rs11538264 and SNP rs10484558, both located in the HLA class III region, in strong linkage disequilibrium between each other (R(2)=0.92). When considered as single SNP, none of them reached a significant association with graft rejection (nominal P<0.00001 for BAT2 SNP rs11538264, and P<0.0001 for BAT3 SNP rs10484558), whereas the BAT2/BAT3 A/C haplotype was present at significantly higher frequency in patients who rejected as compared to those with functional graft (30.0% vs 2.6%, nominal P=1.15 × 10(-8); and adjusted P=0.0071). The BAT2/BAT3 polymorphisms and specifically the A/C haplotype may represent a novel immunogenetic factor associated with graft rejection in patients undergoing allo-HSCT.

Use of Copy Number Deletion Polymorphisms to Assess DNA Chimerism

BACKGROUND

We describe a novel approach that harnesses the ubiquity of copy number deletion polymorphisms in human genomes to definitively detect and quantify chimeric DNA in clinical samples. Unlike other molecular approaches to chimerism analysis, the copy number deletion (CND) method targets genomic loci (&gt;50 base pairs in length) that are wholly absent from wild-type (i.e., self) background DNA sequences in a sex-independent manner.

METHODS

Bespoke quantitative PCR (qPCR) CND assays were developed and validated using a series of DNA standards and chimeric plasma DNA samples collected from 2 allogeneic kidney transplant recipients and 12 pregnant women. Assay performance and informativeness were assessed using appropriate statistical methods.

RESULTS

The CND qPCR assays showed high sensitivity, precision, and reliability for linear quantification of DNA chimerism down to 16 genomic equivalents (i.e., 106 pg). Fetal fraction (%) in 12 singleton male pregnancies was calculated using the CND qPCR approach, which showed closer agreement with single-nucleotide polymorphism–based massively parallel sequencing than the SRY (sex determining region Y) (Y chromosome) qPCR assay. The latter consistently underestimated the fetal fraction relative to the other methods. We also were able to measure biological changes in plasma nonself DNA concentrations in 2 renal transplant recipients.

CONCLUSIONS

The CND qPCR technique is suitable for measurement of chimerism for monitoring of rejection in allogeneic organ transplantation and quantification of the cell-free fetal DNA fraction in maternal plasma samples used for noninvasive prenatal genetic testing.

Molecular and cytogenetic analysis in stillbirth: results from 481 consecutive cases

INTRODUCTION

The underlying causes of stillbirth are heterogeneous and in many cases unexplained. Our aim was to conclude clinical results from karyotype and quantitative fluorescence-polymerase chain reaction (QF-PCR) analysis of all stillbirths occurring in Stockholm County between 2008 and 2012. By screening a subset of cases, we aimed to study the possible benefits of chromosomal microarray (CMA) in the analysis of the etiology of stillbirth.

METHODS

During 2008-2012, 481 stillbirths in Stockholm County were investigated according to a clinical protocol including karyotype or QF-PCR analysis. CMA screening was performed on a subset of 90 cases, corresponding to all stillbirths from 2010 without a genetic diagnosis.

RESULTS

Chromosomal aberrations were detected by karyotype or QF-PCR analysis in 7.5% of the stillbirths. CMA analysis additionally identified two known syndromes, one aberration disrupting a known disease gene, and 26 variants of unknown significance. Furthermore, CMA had a significantly higher success rate than karyotyping (100 vs. 80%, p < 0.001).

DISCUSSION

In the analysis of stillbirth, conventional karyotyping is prone to failure, and QF-PCR is a useful complement. We show that CMA has a higher success rate and aberration detection frequency than these methods, and conclude that CMA is a valuable tool for identification of chromosomal aberrations in stillbirth.

Copy number polymorphisms near SLC2A9 are associated with serum uric acid concentrations

Background

Hyperuricemia is associated with multiple diseases, including gout, cardiovascular disease, and renal disease. Serum urate is highly heritable, yet association studies of single nucleotide polymorphisms (SNPs) and serum uric acid explain a small fraction of the heritability. Whether copy number polymorphisms (CNPs) contribute to uric acid levels is unknown.

Results

We assessed copy number on a genome-wide scale among 8,411 individuals of European ancestry (EA) who participated in the Atherosclerosis Risk in Communities (ARIC) study. CNPs upstream of the urate transporter SLC2A9 on chromosome 4p16.1 are associated with uric acid (χ2df2=3545, p=3.19×10^-23). Effect sizes, expressed as the percentage change in uric acid per deleted copy, are most pronounced among women (_3.974.93_5.87 [ _2.550_97.5 denoting percentiles], p=4.57×10^-23) and independent of previously reported SNPs in SLC2A9 as assessed by SNP and CNP regression models and the phasing SNP and CNP haplotypes (χ2df2=3190,p=7.23×10-08). Our finding is replicated in the Framingham Heart Study (FHS), where the effect size estimated from 4,089 women is comparable to ARIC in direction and magnitude (_1.414.70_7.88, p=5.46×10^-03).

Conclusions

This is the first study to characterize CNPs in ARIC and the first genome-wide analysis of CNPs and uric acid. Our findings suggests a novel, non-coding regulatory mechanism for SLC2A9-mediated modulation of serum uric acid, and detail a bioinformatic approach for assessing the contribution of CNPs to heritable traits in large population-based studies where technical sources of variation are substantial.

DNA methylome profiling of maternal peripheral blood and placentas reveal potential fetal DNA markers for non-invasive prenatal testing

Utilizing epigenetic (DNA methylation) differences to differentiate between maternal peripheral blood (PBL) and fetal (placental) DNA has been a promising strategy for non-invasive prenatal testing (NIPT). However, the differentially methylated regions (DMRs) have yet to be fully ascertained. In the present study, we performed genome-wide comparative methylome analysis between maternal PBL and placental DNA from pregnancies of first trimester by methylated DNA immunoprecipitation-sequencing (MeDIP-Seq) and Infinium HumanMethylation450 BeadChip assays. A total of 36 931 DMRs and 45 804 differentially methylated sites (DMSs) covering the whole genome, exclusive of the Y chromosome, were identified via MeDIP-Seq and Infinium 450k array, respectively, of which 3759 sites in 2188 regions were confirmed by both methods. Not only did we find the previously reported potential fetal DNA markers in our identified DMRs/DMSs but also we verified fully the identified DMRs/DMSs in the validation round by MassARRAY EpiTYPER. The screened potential fetal DNA markers may be used for NIPT on aneuploidies and other chromosomal diseases, such as cri du chat syndrome and velo-cardio-facial syndrome. In addition, these potential markers may have application in the early diagnosis of placental dysfunction, such as pre-eclampsia.

Large germline copy number variations as predisposing factor in childhood neoplasms

ABSTRACT: 

Aims: Constitutive genetic factors are believed to predispose to cancer in children. This study investigated the role of rare germline copy number variations (CNVs) in pediatric cancer predisposition. Patients & methods: A total of 54 patients who developed cancer in infancy were screened by array-CGH for germline CNVs. Results: In total, 12 rare CNVs were detected, including a Xq27.2 triplication, and two >1.8 Mb deletions: one of them at 13q31, containing only RNA genes, and another at 3q26.33–q27.1, in a patient with congenital malformations. Detected rare CNVs are significantly larger than those identified in controls, and encompass genes never implicated in cancer predisposition. Conclusion: Our results suggest that constitutive CNVs contribute to the etiology of pediatric neoplasms, revealing new candidate genes for tumorigenesis.

Copy number variation in schizophrenia in Sweden

Schizophrenia (SCZ) is a highly heritable neuropsychiatric disorder of complex genetic etiology. Previous genome-wide surveys have revealed a greater burden of large, rare copy number variations (CNVs) in SCZ cases and identified multiple rare recurrent CNVs that increase risk of SCZ although with incomplete penetrance and pleiotropic effects. Identification of additional recurrent CNVs and biological pathways enriched for SCZ CNVs requires greater sample sizes. We conducted a genome-wide survey for CNVs associated with SCZ using a Swedish national sample (4719 cases and 5917 controls). High-confidence CNV calls were generated using genotyping array intensity data, and their effect on risk of SCZ was measured. Our data confirm increased burden of large, rare CNVs in SCZ cases as well as significant associations for recurrent 16p11.2 duplications, 22q11.2 deletions and 3q29 deletions. We report a novel association for 17q12 duplications (odds ratio=4.16, P=0.018), previously associated with autism and mental retardation but not SCZ. Intriguingly, gene set association analyses implicate biological pathways previously associated with SCZ through common variation and exome sequencing (calcium channel signaling and binding partners of the fragile X mental retardation protein). We found significantly increased burden of the largest CNVs (>500 kb) in genes present in the postsynaptic density, in genomic regions implicated via SCZ genome-wide association studies and in gene products localized to mitochondria and cytoplasm. Our findings suggest that multiple lines of genomic inquiry--genome-wide screens for CNVs, common variation and exonic variation--are converging on similar sets of pathways and/or genes.

Structural genomic variation as risk factor for idiopathic recurrent miscarriage

Recurrent miscarriage (RM) is a multifactorial disorder with acknowledged genetic heritability that affects ∼3% of couples aiming at childbirth. As copy number variants (CNVs) have been shown to contribute to reproductive disease susceptibility, we aimed to describe genome-wide profile of CNVs and identify common rearrangements modulating risk to RM. Genome-wide screening of Estonian RM patients and fertile controls identified excessive cumulative burden of CNVs (5.4 and 6.1 Mb per genome) in two RM cases possibly increasing their individual disease risk. Functional profiling of all rearranged genes within RM study group revealed significant enrichment of loci related to innate immunity and immunoregulatory pathways essential for immune tolerance at fetomaternal interface. As a major finding, we report a multicopy duplication (61.6 kb) at 5p13.3 conferring increased maternal risk to RM in Estonia and Denmark (meta-analysis, n = 309/205, odds ratio = 4.82, P = 0.012). Comparison to Estonian population-based cohort (total, n = 1000) confirmed the risk for Estonian female cases (P = 7.9 × 10(-4) ). Datasets of four cohorts from the Database of Genomic Variants (total, n = 5,846 subjects) exhibited similar low duplication prevalence worldwide (0.7%-1.2%) compared to RM cases of this study (6.6%-7.5%). The CNV disrupts PDZD2 and GOLPH3 genes predominantly expressed in placenta and it may represent a novel risk factor for pregnancy complications.

An MLPA-based approach for high-resolution genotyping of disease-related multi-allelic CNVs

Copy number variation has recently been recognized as an important type of genetic variation that modifies human phenotypes. Copy number variants (CNVs) are being increasingly associated with various human phenotypes and diseases. However, the lack of an appropriate method that allows fast, inexpensive and, most importantly, accurate CNVs genotyping significantly hampers CNV analysis. This limitation especially affects the analysis of multi-allelic CNVs that frequently modify various phenotypes. Recently, we developed a multiplex ligation-dependent probe amplification (MLPA)-based strategy for multiplex copy number genotyping and the validation of candidate CNV-miRNAs. Here we present the adaptation and optimization of this recently developed method for high-resolution genotyping of individual disease-related multi-allelic CNVs. We developed appropriate assays for three well-known and extensively studied CNVs: CNV-CCL3L1, CNV-DEFB, and CNV-UGT2B17, which have been associated with various human phenotypes including inflammation-related and infectious diseases. With the use of these assays we identified several general factors that allow to increase the resolution of the copy number genotyping. Performed experiments confirmed the high reproducibility and accuracy of the obtained genotyping results. The reliability of the results and relatively low per-genotype cost makes this strategy an attractive method for large-scale experiments such as genotype-phenotype association studies.

A genome-wide assessment of the role of untagged copy number variants in type 1 diabetes

Genome-wide association studies (GWAS) for type 1 diabetes (T1D) have successfully identified more than 40 independent T1D associated tagging single nucleotide polymorphisms (SNPs). However, owing to technical limitations of copy number variants (CNVs) genotyping assays, the assessment of the role of CNVs has been limited to the subset of these in high linkage disequilibrium with tag SNPs. The contribution of untagged CNVs, often multi-allelic and difficult to genotype using existing assays, to the heritability of T1D remains an open question. To investigate this issue, we designed a custom comparative genetic hybridization array (aCGH) specifically designed to assay untagged CNV loci identified from a variety of sources. To overcome the technical limitations of the case control design for this class of CNVs, we genotyped the Type 1 Diabetes Genetics Consortium (T1DGC) family resource (representing 3,903 transmissions from parents to affected offspring) and used an association testing strategy that does not necessitate obtaining discrete genotypes. Our design targeted 4,309 CNVs, of which 3,410 passed stringent quality control filters. As a positive control, the scan confirmed the known T1D association at the INS locus by direct typing of the 5′ variable number of tandem repeat (VNTR) locus. Our results clarify the fact that the disease association is indistinguishable from the two main polymorphic allele classes of the INS VNTR, class I-and class III. We also identified novel technical artifacts resulting into spurious associations at the somatically rearranging loci, T cell receptor, TCRA/TCRD and TCRB, and Immunoglobulin heavy chain, IGH, loci on chromosomes 14q11.2, 7q34 and 14q32.33, respectively. However, our data did not identify novel T1D loci. Our results do not support a major role of untagged CNVs in T1D heritability.

For many complex traits, and in particular type 1 diabetes (T1D), the genome-wide association study (GWAS) design has been successful at detecting a large number of loci that contribute disease risk. However, in the case of T1D as well as almost all other traits, the sum of these loci does not fully explain the heritability estimated from familial studies. This observation raises the possibility that additional variants exist but have not yet been found because they have not effectively been targeted by the GWAS design. Here, we focus on a specific class of large deletions/duplications called copy number variants (CNVs), and more precisely to the subset of these loci that mutate rapidly, which are highly polymorphic. A consequence of this high level of polymorphism is that these variants have typically not been captured by previous GWAS studies. We use a family based design that is optimized to capture these previously untested variants. We then perform a genome-wide scan to assess their contribution to T1D. Our scan was technically successful but did not identify novel associations. This suggests that little was missed by the GWAS strategy, and that the remaining heritability of T1D is most likely driven by a large number of variants, either rare of common, but with a small individual contribution to disease risk.

HaplotypeCN: copy number haplotype inference with Hidden Markov Model and localized haplotype clustering

Copy number variation (CNV) has been reported to be associated with disease and various cancers. Hence, identifying the accurate position and the type of CNV is currently a critical issue. There are many tools targeting on detecting CNV regions, constructing haplotype phases on CNV regions, or estimating the numerical copy numbers. However, none of them can do all of the three tasks at the same time. This paper presents a method based on Hidden Markov Model to detect parent specific copy number change on both chromosomes with signals from SNP arrays. A haplotype tree is constructed with dynamic branch merging to model the transition of the copy number status of the two alleles assessed at each SNP locus. The emission models are constructed for the genotypes formed with the two haplotypes. The proposed method can provide the segmentation points of the CNV regions as well as the haplotype phasing for the allelic status on each chromosome. The estimated copy numbers are provided as fractional numbers, which can accommodate the somatic mutation in cancer specimens that usually consist of heterogeneous cell populations. The algorithm is evaluated on simulated data and the previously published regions of CNV of the 270 HapMap individuals. The results were compared with five popular methods: PennCNV, genoCN, COKGEN, QuantiSNP and cnvHap. The application on oral cancer samples demonstrates how the proposed method can facilitate clinical association studies. The proposed algorithm exhibits comparable sensitivity of the CNV regions to the best algorithm in our genome-wide study and demonstrates the highest detection rate in SNP dense regions. In addition, we provide better haplotype phasing accuracy than similar approaches. The clinical association carried out with our fractional estimate of copy numbers in the cancer samples provides better detection power than that with integer copy number states.

Linkage disequilibrium and signatures of positive selection around LINE-1 retrotransposons in the human genome

Insertions of the human-specific subfamily of LINE-1 (L1) retrotransposon are highly polymorphic across individuals and can critically influence the human transcriptome. We hypothesized that L1 insertions could represent genetic variants determining important human phenotypic traits, and performed an integrated analysis of L1 elements and single nucleotide polymorphisms (SNPs) in several human populations. We found that a large fraction of L1s were in high linkage disequilibrium with their surrounding genomic regions and that they were well tagged by SNPs. However, L1 variants were only partially captured by SNPs on standard SNP arrays, so that their potential phenotypic impact would be frequently missed by SNP array-based genome-wide association studies. We next identified potential phenotypic effects of L1s by looking for signatures of natural selection linked to L1 insertions; significant extended haplotype homozygosity was detected around several L1 insertions. This finding suggests that some of these L1 insertions may have been the target of recent positive selection.

A genome-wide association study on copy-number variation identifies a 11q11 loss as a candidate susceptibility variant for colorectal cancer

Colorectal cancer (CRC) is a complex disease, and therefore its development is determined by the combination of both environmental factors and genetic variants. Although genome-wide association studies (GWAS) of SNP variation have conveniently identified 20 genetic variants so far, a significant proportion of the observed heritability is yet to be explained. Common copy-number variants (CNVs) are one of the most important genomic sources of variability, and hence a potential source to explain part of this missing genetic fraction. Therefore, we have performed a GWAS on CNVs to explore the relationship between common structural variation and CRC development. Phase 1 of the GWAS consisted of 881 cases and 667 controls from a Spanish cohort. Copy-number status was validated by quantitative PCR for each of those common CNVs potentially associated with CRC in phase I. Subsequently, SNPs were chosen as proxies for the validated CNVs for phase II replication (1,342 Spanish cases and 1,874 Spanish controls). Four common CNVs were found to be associated with CRC and were further replicated in Phase II. Finally, we found that SNP rs1944682, tagging a 11q11 CNV, was nominally associated with CRC susceptibility (p value = 0.039; OR = 1.122). This locus has been previously related to extreme obesity phenotypes, which could suggest a relationship between body weight and CRC susceptibility.

Compilation of copy number variants identified in phenotypically normal and parous Japanese women

With increasing public concern about infertility and the frequent involvement of chromosomal anomalies in miscarriage, analyses of copy number variations (CNVs) have been used to identify the genomic regions responsible for each process of childbearing. Although associations between CNVs and diseases have been reported, many CNVs have also been identified in healthy individuals. Like other types of mutations, phenotypically indefinite CNVs may have been retained and accumulated during anthropogenesis. Therefore to distinguish causative variants from other variants is a formidable task. Furthermore, because previous studies have predominantly focused on European and African populations, comprehensive detection of common Asian CNVs is eagerly awaited. Here, using a high-resolution genotyping array and samples from 411 Japanese women with normal parity without significant complications, we have compiled 1043 copy number variable regions. In total, the collected regions cover 164 Mb, or up to 0.5% of the genome. The copy number differences in these regions may be irrelevant not only to infertility but also to a wide range of diseases. The utility of this resource in reducing the candidate pathogenetic variants, especially in Japanese subjects, is also demonstrated.

An evaluation of copy number variation detection tools from whole-exome sequencing data

Copy number variation (CNV) has been found to play an important role in human disease. Next-generation sequencing technology, including whole-genome sequencing (WGS) and whole-exome sequencing (WES), has become a primary strategy for studying the genetic basis of human disease. Several CNV calling tools have recently been developed on the basis of WES data. However, the comparative performance of these tools using real data remains unclear. An objective evaluation study of these tools in practical research situations would be beneficial. Here, we evaluated four well-known WES-based CNV detection tools (XHMM, CoNIFER, ExomeDepth, and CONTRA) using real data generated in house. After evaluation using six metrics, we found that the sensitive and accurate detection of CNVs in WES data remains challenging despite the many algorithms available. Each algorithm has its own strengths and weaknesses. None of the exome-based CNV calling methods performed well in all situations; in particular, compared with CNVs identified from high coverage WGS data from the same samples, all tools suffered from limited power. Our evaluation provides a comprehensive and objective comparison of several well-known detection tools designed for WES data, which will assist researchers in choosing the most suitable tools for their research needs.

Copy number variations among silkworms

Background

Copy number variations (CNVs), which are important source for genetic and phenotypic variation, have been shown to be associated with disease as well as important QTLs, especially in domesticated animals. However, little is known about the CNVs in silkworm.

Results

In this study, we have constructed the first CNVs map based on genome-wide analysis of CNVs in domesticated silkworm. Using next-generation sequencing as well as quantitative PCR (qPCR), we identified ~319 CNVs in total and almost half of them (~ 49%) were distributed on uncharacterized chromosome. The CNVs covered 10.8 Mb, which is about 2.3% of the entire silkworm genome. Furthermore, approximately 61% of CNVs directly overlapped with SDs in silkworm. The genes in CNVs are mainly related to reproduction, immunity, detoxification and signal recognition, which is consistent with the observations in mammals.

Conclusions

An initial CNVs map for silkworm has been described in this study. And this map provides new information for genetic variations in silkworm. Furthermore, the silkworm CNVs may play important roles in reproduction, immunity, detoxification and signal recognition. This study provided insight into the evolution of the silkworm genome and an invaluable resource for insect genomics research.

Low copy number of the salivary amylase gene predisposes to obesity

Common multi-allelic copy number variants (CNVs) appear enriched for phenotypic associations compared to their biallelic counterparts. Here we investigated the influence of gene dosage effects on adiposity through a CNV association study of gene expression levels in adipose tissue. We identified significant association of a multi-allelic CNV encompassing the salivary amylase gene (AMY1) with body mass index (BMI) and obesity, and we replicated this finding in 6,200 subjects. Increased AMY1 copy number was positively associated with both amylase gene expression (P = 2.31 × 10(-14)) and serum enzyme levels (P < 2.20 × 10(-16)), whereas reduced AMY1 copy number was associated with increased BMI (change in BMI per estimated copy = -0.15 (0.02) kg/m(2); P = 6.93 × 10(-10)) and obesity risk (odds ratio (OR) per estimated copy = 1.19, 95% confidence interval (CI) = 1.13-1.26; P = 1.46 × 10(-10)). The OR value of 1.19 per copy of AMY1 translates into about an eightfold difference in risk of obesity between subjects in the top (copy number > 9) and bottom (copy number < 4) 10% of the copy number distribution. Our study provides a first genetic link between carbohydrate metabolism and BMI and demonstrates the power of integrated genomic approaches beyond genome-wide association studies.

Haplotype differences for copy number variants in the 22q11.23 region among human populations: a pigmentation-based model for selective pressure

Two gene clusters are tightly linked in a narrow region of chromosome 22q11.23: the macrophage migration inhibitory factor (MIF) gene family and the glutathione S-transferase theta class. Within 120 kb in this region, two 30-kb deletions reach high frequencies in human populations. This gives rise to four haplotypic arrangements, which modulate the number of genes in both families. The variable patterns of linkage disequilibrium (LD) between these copy number variants (CNVs) in diverse human populations remain poorly understood. We analyzed 2469 individuals belonging to 27 human populations with different ethnic origins. Then we correlated the genetic variability of 22q11.23 CNVs with environmental variables. We confirmed an increasing strength of LD from Africa to Asia and to Europe. Further, we highlighted strongly significant correlations between the frequency of one of the haplotypes and pigmentation-related variables: skin color (R(2)=0.675, P<0.001), distance from the equator (R(2)=0.454, P<0.001), UVA radiation (R(2)=0.439, P<0.001), and UVB radiation (R(2)=0.313, P=0.002). The fact that all MIF-related genes are retained on this haplotype and the evidences gleaned from experimental systems seem to agree with the role of MIF-related genes in melanogenesis. As such, we propose a model that explains the geographic and ethnic distribution of 22q11.23 CNVs among human populations, assuming that MIF-related gene dosage could be associated with adaptation to low UV radiation.

Genome-wide association study identified copy number variants important for appendicular lean mass

Skeletal muscle is a major component of the human body. Age-related loss of muscle mass and function contributes to some public health problems such as sarcopenia and osteoporosis. Skeletal muscle, mainly composed of appendicular lean mass (ALM), is a heritable trait. Copy number variation (CNV) is a common type of human genome variant which may play an important role in the etiology of many human diseases. In this study, we performed genome-wide association analyses of CNV for ALM in 2,286 Caucasian subjects. We then replicated the major findings in 1,627 Chinese subjects. Two CNVs, CNV1191 and CNV2580, were detected to be associated with ALM (p = 2.26×10⁻² and 3.34×10⁻³, respectively). In the Chinese replication sample, the two CNVs achieved p-values of 3.26×10⁻² and 0.107, respectively. CNV1191 covers a gene, GTPase of the immunity-associated protein family (GIMAP1), which is important for skeletal muscle cell survival/death in humans. CNV2580 is located in the Serine hydrolase-like protein (SERHL) gene, which plays an important role in normal peroxisome function and skeletal muscle growth in response to mechanical stimuli. In summary, our study suggested two novel CNVs and the related genes that may contribute to variation in ALM.

Genetic aspects of autism spectrum disorders: insights from animal models

Autism spectrum disorders (ASDs) are a complex neurodevelopmental disorder that display a triad of core behavioral deficits including restricted interests, often accompanied by repetitive behavior, deficits in language and communication, and an inability to engage in reciprocal social interactions. ASD is among the most heritable disorders but is not a simple disorder with a singular pathology and has a rather complex etiology. It is interesting to note that perturbations in synaptic growth, development, and stability underlie a variety of neuropsychiatric disorders, including ASD, schizophrenia, epilepsy, and intellectual disability. Biological characterization of an increasing repertoire of synaptic mutants in various model organisms indicates synaptic dysfunction as causal in the pathophysiology of ASD. Our understanding of the genes and genetic pathways that contribute toward the formation, stabilization, and maintenance of functional synapses coupled with an in-depth phenotypic analysis of the cellular and behavioral characteristics is therefore essential to unraveling the pathogenesis of these disorders. In this review, we discuss the genetic aspects of ASD emphasizing on the well conserved set of genes and genetic pathways implicated in this disorder, many of which contribute to synapse assembly and maintenance across species. We also review how fundamental research using animal models is providing key insights into the various facets of human ASD.

The challenges and importance of structural variation detection in livestock

Recent studies in humans and other model organisms have demonstrated that structural variants (SVs) comprise a substantial proportion of variation among individuals of each species. Many of these variants have been linked to debilitating diseases in humans, thereby cementing the importance of refining methods for their detection. Despite progress in the field, reliable detection of SVs still remains a problem even for human subjects. Many of the underlying problems that make SVs difficult to detect in humans are amplified in livestock species, whose lower quality genome assemblies and incomplete gene annotation can often give rise to false positive SV discoveries. Regardless of the challenges, SV detection is just as important for livestock researchers as it is for human researchers, given that several productive traits and diseases have been linked to copy number variations (CNVs) in cattle, sheep, and pig. Already, there is evidence that many beneficial SVs have been artificially selected in livestock such as a duplication of the agouti signaling protein gene that causes white coat color in sheep. In this review, we will list current SV and CNV discoveries in livestock and discuss the problems that hinder routine discovery and tracking of these polymorphisms. We will also discuss the impacts of selective breeding on CNV and SV frequencies and mention how SV genotyping could be used in the future to improve genetic selection.

A genome-wide association study identifies common variants influencing serum uric acid concentrations in a Chinese population

BACKGROUND

Uric acid (UA) is a complex phenotype influenced by both genetic and environmental factors as well as their interactions. Current genome-wide association studies (GWASs) have identified a variety of genetic determinants of UA in Europeans; however, such studies in Asians, especially in Chinese populations remain limited.

METHODS

A two-stage GWAS was performed to identify single nucleotide polymorphisms (SNPs) that were associated with serum uric acid (UA) in a Chinese population of 12,281 participants (GWAS discovery stage included 1452 participants from the Dongfeng-Tongji cohort (DFTJ-cohort) and 1999 participants from the Fangchenggang Area Male Health and Examination Survey (FAMHES). The validation stage included another independent 8830 individuals from the DFTJ-cohort). Affymetrix Genome-Wide Human SNP Array 6.0 chips and Illumina Omni-Express platform were used for genotyping for DFTJ-cohort and FAMHES, respectively. Gene-environment interactions on serum UA levels were further explored in 10,282 participants from the DFTJ-cohort.

RESULTS

Briefly, we identified two previously reported UA loci of SLC2A9 (rs11722228, combined P = 8.98 × 10-31) and ABCG2 (rs2231142, combined P = 3.34 × 10-42). The two independent SNPs rs11722228 and rs2231142 explained 1.03% and 1.09% of the total variation of UA levels, respectively. Heterogeneity was observed across different populations. More importantly, both independent SNPs rs11722228 and rs2231142 were nominally significantly interacted with gender on serum UA levels (P for interaction = 4.0 × 10-2 and 2.0 × 10-2, respectively). The minor allele (T) for rs11722228 in SLC2A9 has greater influence in elevating serum UA levels in females compared to males and the minor allele (T) of rs2231142 in ABCG2 had stronger effects on serum UA levels in males than that in females.

CONCLUSIONS

Two genetic loci (SLC2A9 and ABCG2) were confirmed to be associated with serum UA concentration. These findings strongly support the evidence that SLC2A9 and ABCG2 function in UA metabolism across human populations. Furthermore, we observed these associations are modified by gender.

A Single-Array-Based Method for Detecting Copy Number Variants Using Affymetrix High Density SNP Arrays and its Application to Breast Cancer

Cumulative evidence has shown that structural variations, due to insertions, deletions, and inversions of DNA, may contribute considerably to the development of complex human diseases, such as breast cancer. High-throughput genotyping technologies, such as Affymetrix high density single-nucleotide polymorphism (SNP) arrays, have produced large amounts of genetic data for genome-wide SNP genotype calling and copy number estimation. Meanwhile, there is a great need for accurate and efficient statistical methods to detect copy number variants. In this article, we introduce a hidden-Markov-model (HMM)-based method, referred to as the PICR-CNV, for copy number inference. The proposed method first estimates copy number abundance for each single SNP on a single array based on the raw fluorescence values, and then standardizes the estimated copy number abundance to achieve equal footing among multiple arrays. This method requires no between-array normalization, and thus, maintains data integrity and independence of samples among individual subjects. In addition to our efforts to apply new statistical technology to raw fluorescence values, the HMM has been applied to the standardized copy number abundance in order to reduce experimental noise. Through simulations, we show our refined method is able to infer copy number variants accurately. Application of the proposed method to a breast cancer dataset helps to identify genomic regions significantly associated with the disease.

Characterizing multi-omic data in systems biology

In today's biology, studies have shifted to analyzing systems over discrete biochemical reactions and pathways. These studies depend on combining the results from scores of experimental methods that analyze DNA; mRNA; noncoding RNAs, DNA, RNA, and protein interactions; and the nucleotide modifications that form the epigenome into global datasets that represent a diverse array of "omics" data (transcriptional, epigenetic, proteomic, metabolomic). The methods used to collect these data consist of high-throughput data generation platforms that include high-content screening, imaging, flow cytometry, mass spectrometry, and nucleic acid sequencing. Of these, the next-generation DNA sequencing platforms predominate because they provide an inexpensive and scalable way to quickly interrogate the molecular changes at the genetic, epigenetic, and transcriptional level. Furthermore, existing and developing single-molecule sequencing platforms will likely make direct RNA and protein measurements possible, thus increasing the specificity of current assays and making it possible to better characterize "epi-alterations" that occur in the epigenome and epitranscriptome. These diverse data types present us with the largest challenge: how do we develop software systems and algorithms that can integrate these datasets and begin to support a more democratic model where individuals can capture and track their own medical information through biometric devices and personal genome sequencing? Such systems will need to provide the necessary user interactions to work with the trillions of data points needed to make scientific discoveries. Here, we describe novel approaches in the genesis and processing of such data, models to integrate these data, and the increasing ubiquity of self-reporting and self-measured genomics and health data.

Chromosome microarrays in diagnostic testing: interpreting the genomic data

DNA-based Chromosome MicroArrays (CMAs) are now well established as diagnostic tools in clinical genetics laboratories. Over the last decade, the primary application of CMAs has been the genome-wide detection of a particular class of mutation known as copy number variants (CNVs). Since 2010, CMA testing has been recommended as a first-tier test for detection of CNVs associated with intellectual disability, autism spectrum disorders, and/or multiple congenital anomalies…in the post-natal setting. CNVs are now regarded as pathogenic in 14-18 % of patients referred for these (and related) disorders.Through consideration of clinical examples, and several microarray platforms, we attempt to provide an appreciation of microarray diagnostics, from the initial inspection of the microarray data, to the composing of the patient report. In CMA data interpretation, a major challenge comes from the high frequency of clinically irrelevant CNVs observed within "patient" and "normal" populations. As might be predicted, the more common and clinically insignificant CNVs tend to be the smaller ones <100 kb in length, involving few or no known genes. However, this relationship is not at all straightforward: CNV length and gene content are only very imperfect indicators of CNV pathogenicity. Presently, there are no reliable means of separating, a priori, the benign from the pathological CNV classes.This chapter also considers sources of technical "noise" within CMA data sets. Some level of noise is inevitable in diagnostic genomics, given the very large number of data points generated in any one test. Noise further limits CMA resolution, and some miscalling of CNVs is unavoidable. In this, there is no ideal solution, but various strategies for handling noise are available. Even without solutions, consideration of these diagnostic problems per se is informative, as they afford critical insights into the biological and technical underpinnings of CNV discovery. These are indispensable to any clinician or scientist practising within the field of genome diagnostics.

The somatic genomic landscape of glioblastoma

We describe the landscape of somatic genomic alterations based on multidimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors, including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer.

Copy number variation at 6q13 is associated with lung cancer risk in a Han Chinese population

Copy number variations (CNVs), a major source of human genetic polymorphism, have been suggested to have an important role in genetic susceptibility to common diseases such as cancer, immune diseases, and neurological disorders. Lung cancer is a multifactorial tumor closely associated with genetic background. Previous genome-wide association studies have identified single nucleotide polymorphisms (SNPs) that are associated with lung cancer susceptibility. This study examined the CNVR2966.1 at 6q13 and its association with lung cancer susceptibility. The CNVR2966.1 was found to be a 10,379 bp nucleotides deletion/insertion within the uniform boundaries chromosome 6: 74,648,791-74,659,169. The risk of lung cancer observed in 503 cases and 623 controls was significantly associated with copy number of CNVR2966.1, with the odds ratio (OR) being 1.38 [95% confidence interval (CI) = 1.05-1.79; P = .007] for one copy genotype compared with two copies genotype. These results suggest that CNVR2966.1 is associated with lung cancer risk.

Copy Number Studies in Noisy Samples

System noise was analyzed in 77 Affymetrix 6.0 samples from a previous clinical study of copy number variation (CNV). Twenty-three samples were classified as eligible for CNV detection, 29 samples as ineligible and 25 were classified as being of intermediate quality. New software (“noise-free-cnv”) was developed to visualize the data and reduce system noise. Fresh DNA preparations were more likely to yield eligible samples (p < 0.001). Eligible samples had higher rates of successfully genotyped SNPs (p < 0.001) and lower variance of signal intensities (p < 0.001), yielded fewer CNV findings after Birdview analysis (p < 0.001), and showed a tendency to yield fewer PennCNV calls (p = 0.053). The noise-free-cnv software visualized trend patterns of noise in the signal intensities across the ordered SNPs, including a wave pattern of noise, being co-linear with the banding pattern of metaphase chromosomes, as well as system deviations of individual probe sets (per-SNP noise). Wave noise and per-SNP noise occurred independently and could be separately removed from the samples. We recommend a two-step procedure of CNV validation, including noise reduction and visual inspection of all CNV calls, prior to molecular validation of a selected number of putative CNVs.

An integer programming formulation of the parsimonious loss of heterozygosity problem

A loss of heterozygosity (LOH) event occurs when, by the laws of Mendelian inheritance, an individual should be heterozygote at a given site but, due to a deletion polymorphism, is not. Deletions play an important role in human disease and their detection could provide fundamental insights for the development of new diagnostics and treatments. In this paper, we investigate the parsimonious loss of heterozygosity problem (PLOHP), i.e., the problem of partitioning suspected polymorphisms from a set of individuals into a minimum number of deletion areas. Specifically, we generalize Halldórsson et al.'s work by providing a more general formulation of the PLOHP and by showing how one can incorporate different recombination rates and prior knowledge about the locations of deletions. Moreover, we show that the PLOHP can be formulated as a specific version of the clique partition problem in a particular class of graphs called undirected catch-point interval graphs and we prove its general $({\cal NP})$-hardness. Finally, we provide a state-of-the-art integer programming (IP) formulation and strengthening valid inequalities to exactly solve real instances of the PLOHP containing up to 9,000 individuals and 3,000 SNPs. Our results give perspectives on the mathematics of the PLOHP and suggest new directions on the development of future efficient exact solution approaches.

Multiplex ligase-based genotyping methods combined with CE

In this genomic era, the ability to assay multiple genomic hot spots that have strong clinical implications is greatly desired. Conventional PCR-based methods suffer from frequent false-positive detections, particularly when a multiplex analysis is desirable. As an alternative to the error-prone conventional methods, multiplex ligase-based genotyping methods combined with CE have a strong potential. In this review, both previously developed methods and emerging methods are described to reveal the specificity, sensitivity, and simplicity of the ligase-based methods. For each step (ligation, amplification, and separation), the principles of several alternative methods are discussed along with their applications to explore the future development of ligase-based diagnostic methods.

Genome-wide analysis associates familial colorectal cancer with increases in copy number variations and a rare structural variation at 12p12.3

Colorectal cancer (CRC) is one of the most common cancer worldwide. However, a large number of genetic risk factors involved in CRC have not been understood. Copy number variations (CNVs) might partly contribute to the 'missing heritability' of CRC. An increased overall burden of CNV has been identified in several complex diseases, whereas the association between the overall CNV burden and CRC risk is largely unknown. We performed a genome-wide investigation of CNVs on genomic DNA from 384 familial CRC cases and 1285 healthy controls by the Affymetrix 6.0 array. An increase of overall CNV burden was observed in familial CRC patients compared with healthy controls, especially for CNVs larger than 50kb (case/control ratio = 1.66, P = 0.025). In addition, we discovered for the first time a novel structural variation at 12p12.3 and determined the breakpoints by strategic PCR and sequencing. This 12p12.3 structural variation was found in four of 2862 CRC cases but not in 6243 healthy controls (P = 0.0098). RERGL gene (RERG/RAS-like), the only gene influenced by the 12p12.3 structural variation, sharing most of the conserved regions with its close family member RERG tumor suppressor gene (RAS-like, estrogen-regulated, growth inhibitor), might be a novel CRC-related gene. In conclusion, this is the first study to reveal the contribution of the overall burden of CNVs to familial CRC risk and identify a novel rare structural variation at 12p12.3 containing RERGL gene to be associated with CRC.

Direct visualization of the highly polymorphic RNU2 locus in proximity to the BRCA1 gene

Although the breast cancer susceptibility gene BRCA1 is one of the most extensively characterized genetic loci, much less is known about its upstream variable number tandem repeat element, the RNU2 locus. RNU2 encodes the U2 small nuclear RNA, an essential splicing element, but this locus is missing from the human genome assembly due to the inherent difficulty in the assembly of repetitive sequences. To fill the gap between RNU2 and BRCA1, we have reconstructed the physical map of this region by re-examining genomic clone sequences of public databases, which allowed us to precisely localize the RNU2 array 124 kb telomeric to BRCA1. We measured by performing FISH analyses on combed DNA for the first time the exact number of repeats carried by each of the two alleles in 41 individuals and found a range of 6-82 copies and a level of heterozygosity of 98%. The precise localisation of the RNU2 locus in the genome reference assembly and the implementation of a new technical tool to study it will make the detailed exploration of this locus possible. This recently neglected macrosatellite could be valuable for evaluating the potential role of structural variations in disease due to its location next to a major cancer susceptibility gene.

A genome-wide investigation of copy number variation in patients with sporadic brain arteriovenous malformation

BACKGROUND

Brain arteriovenous malformations (BAVM) are clusters of abnormal blood vessels, with shunting of blood from the arterial to venous circulation and a high risk of rupture and intracranial hemorrhage. Most BAVMs are sporadic, but also occur in patients with Hereditary Hemorrhagic Telangiectasia, a Mendelian disorder caused by mutations in genes in the transforming growth factor beta (TGFβ) signaling pathway.

METHODS

To investigate whether copy number variations (CNVs) contribute to risk of sporadic BAVM, we performed a genome-wide association study in 371 sporadic BAVM cases and 563 healthy controls, all Caucasian. Cases and controls were genotyped using the Affymetrix 6.0 array. CNVs were called using the PennCNV and Birdsuite algorithms and analyzed via segment-based and gene-based approaches. Common and rare CNVs were evaluated for association with BAVM.

RESULTS

A CNV region on 1p36.13, containing the neuroblastoma breakpoint family, member 1 gene (NBPF1), was significantly enriched with duplications in BAVM cases compared to controls (P = 2.2×10(-9)); NBPF1 was also significantly associated with BAVM in gene-based analysis using both PennCNV and Birdsuite. We experimentally validated the 1p36.13 duplication; however, the association did not replicate in an independent cohort of 184 sporadic BAVM cases and 182 controls (OR = 0.81, P = 0.8). Rare CNV analysis did not identify genes significantly associated with BAVM.

CONCLUSION

We did not identify common CNVs associated with sporadic BAVM that replicated in an independent cohort. Replication in larger cohorts is required to elucidate the possible role of common or rare CNVs in BAVM pathogenesis.

Insights on the functional interactions between miRNAs and copy number variations in the aging brain

MicroRNAs (miRNAs) are regulatory genetic elements that coordinate the expression of thousands of genes and play important roles in brain aging and neurodegeneration. DNA polymorphisms affecting miRNA biogenesis, dosage, and gene targeting may represent potentially functional variants. The consequences of single nucleotide polymorphisms affecting miRNA function were previously demonstrated by both experimental and computational methods. However, little is known about how copy number variations (CNVs) influence miRNA metabolism and regulatory networks. We discuss potential mechanisms of CNVs-mediated effects on miRNA function and regulation that might have consequences for brain aging. We argue that CNVs, which potentially can alter miRNA expression, regulation or target gene recognition, are possible functional variants and should be considered high priority candidates in genotype–phenotype mapping studies of brain-related disorders.

Use of autocorrelation scanning in DNA copy number analysis

MOTIVATION

Data quality is a critical issue in the analyses of DNA copy number alterations obtained from microarrays. It is commonly assumed that copy number alteration data can be modeled as piecewise constant and the measurement errors of different probes are independent. However, these assumptions do not always hold in practice. In some published datasets, we find that measurement errors are highly correlated between probes that interrogate nearby genomic loci, and the piecewise-constant model does not fit the data well. The correlated errors cause problems in downstream analysis, leading to a large number of DNA segments falsely identified as having copy number gains and losses.

METHOD

We developed a simple tool, called autocorrelation scanning profile, to assess the dependence of measurement error between neighboring probes.

RESULTS

Autocorrelation scanning profile can be used to check data quality and refine the analysis of DNA copy number data, which we demonstrate in some typical datasets.

CONTACT

lzhangli@mdanderson.org.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.