Genetically determined partial complement C4 deficiency states are not independent risk factors for SLE in UK and Spanish populations

Systemic lupus erythematosus (SLE) is a chronic, multisystem autoimmune disease. Complete deficiency of complement component C4 confers strong genetic risk for SLE. Partial C4 deficiency states have also shown association with SLE, but despite much effort over the last 30 years, it has not been established whether this association is primarily causal or secondary to long-range linkage disequilibrium. The complement C4 locus, located in the major histocompatibility complex (MHC) class III region, exhibits copy-number variation (CNV) and C4 itself exists as two paralogs, C4A and C4B. In order to determine whether partial C4 deficiency is an independent genetic risk factor for SLE, we investigated C4 CNV in the context of HLA-DRB1 and MHC region SNP polymorphism in the largest and most comprehensive complement C4 study to date. Specifically, we genotyped 2,207 subjects of northern and southern European ancestry (1,028 SLE cases and 1,179 controls) for total C4, C4A, and C4B gene copy numbers, and the loss-of-function C4 exon 29 CT indel. We used multiple logistic regression to determine the independence of C4 CNV from known SNP and HLA-DRB1 associations. We clearly demonstrate that genetically determined partial C4 deficiency states are not independent risk factors for SLE in UK and Spanish populations. These results are further corroborated by the lack of association shown by the C4A exon 29 CT insertion in either cohort. Thus, although complete homozygous deficiency of complement C4 is one of the strongest genetic risk factors for SLE, partial C4 deficiency states do not independently predispose to the disease.     

Genetic Variation of the Fc Gamma Receptor 3B Gene and Association with Rheumatoid Arthritis

Background

Fc gamma receptors (FcγRs) play a crucial role in immunity by linking IgG antibody-mediated responses with cellular effector and regulatory functions. Genetic variants in these receptors have been previously identified as risk factors for several chronic inflammatory conditions. The present study aimed to investigate the presence of copy number variations (CNVs) in the FCGR3B gene and its potential association with the autoimmune disease rheumatoid arthritis (RA).

Methodology/Principal Findings

CNV of the FCGR3B gene was studied using Multiplex Ligation Dependent Probe Amplification (MLPA) in 518 Dutch RA patients and 304 healthy controls. Surprisingly, three independent MLPA probes targeting the FCGR3B promoter measured different CNV frequencies, with probe#1 and #2 measuring 0 to 5 gene copies and probe#3 showing little evidence of CNV. Quantitative-PCR correlated with the copy number results from MLPA probe#2, which detected low copy number (1 copy) in 6.7% and high copy number (≥3 copies) in 9.4% of the control population. No significant difference was observed between RA patients and the healthy controls, neither in the low copy nor the high copy number groups (p-values = 0.36 and 0.71, respectively). Sequencing of the FCGR3B promoter region revealed an insertion/deletion (indel) that explained the disparate CNV results of MLPA probe#1. Finally, a non-significant trend was found between the novel -256A>TG indel and RA (40.7% in healthy controls versus 35.9% in RA patients; P = 0.08).

Conclusions/Significance

The current study highlights the complexity and poor characterization of the FCGR3B gene sequence, indicating that the design and interpretation of genotyping assays based on specific probe sequences must be performed with caution. Nonetheless, we confirmed the presence of CNV and identified novel polymorphisms in the FCGR3B gene in the Dutch population. Although no association was found between RA and FCGR3B CNV, the possible protective effect of the -256A>TG indel polymorphism must be addressed in larger studies.     

MOCSphaser: a haplotype inference tool from a mixture of copy number variation and single nucleotide polymorphism data

Detailed analyses of the population-genetic nature of copy number variations (CNVs) and the linkage disequilibrium between CNV and single nucleotide polymorphism (SNP) loci from high-throughput experimental data require a computational tool to accurately infer alleles of CNVs and haplotypes composed of both CNV alleles and SNP alleles. Here we developed a new tool to infer population frequencies of such alleles and haplotypes from observed copy numbers and SNP genotypes, using the expectation-maximization algorithm. This tool can also handle copy numbers ambiguously determined, such as 2 or 3 copies, due to experimental noise. AVAILABILITY: http://emu.src.riken.jp/MOCSphaser/MOCSphaser.zip.     

Copy number analysis of complement C4A, C4B and C4A silencing mutation by real-time quantitative polymerase chain reaction

Low protein levels and copy number variation (CNV) of the fourth component of human complement (C4A and C4B) have been associated with various diseases. High-throughput methods for analysing C4 CNV are available, but they commonly do not detect the most common C4A mutation, a silencing CT insertion (CTins) leading to low protein levels. We developed a SYBR? Green labelled real-time quantitative polymerase chain reaction (qPCR) with a novel concentration range approach to address C4 CNV and deficiencies due to CTins. This method was validated in three sample sets and applied to over 1600 patient samples. CTins caused C4A deficiency in more than 70% (76/105) of the carriers. Twenty per cent (76/381) of patients with a C4A deficiency would have been erroneously recorded as having none, if the CTins had not been assessed. C4A deficiency was more common in patients than a healthy reference population, (OR?=?1.60, 95%CI?=?1.02-2.52, p?=?0.039). The number of functional C4 genes can be straightforwardly analyzed by real-time qPCR, also with SYBR? Green labelling. Determination of CTins increases the frequency of C4A deficiency and thus helps to elucidate the genotypic versus phenotypic disease associations.     

Large-scale Genotyping and Genetic Mapping in Plasmodium Parasites

The completion of many malaria parasite genomes provides great opportunities for genomewide characterization of gene expression and high-throughput genotyping. Substantial progress in malaria genomics and genotyping has been made recently, particularly the development of various microarray platforms for large-scale characterization of the Plasmodium falciparum genome. Microarray has been used for gene expression analysis, detection of single nucleotide polymorphism (SNP) and copy number variation (CNV), characterization of chromatin modifications, and other applications. Here we discuss some recent advances in genetic mapping and genomic studies of malaria parasites, focusing on the use of high-throughput arrays for the detection of SNP and CNV in the P. falciparum genome. Strategies for genetic mapping of malaria traits are also discussed.     

Studying copy number variations using a nanofluidic platform

Copy number variations (CNVs) in the human genome are conventionally detected using high-throughput scanning technologies, such as comparative genomic hybridization and high-density single nucleotide polymorphism (SNP) microarrays, or relatively low-throughput techniques, such as quantitative polymerase chain reaction (PCR). All these approaches are limited in resolution and can at best distinguish a twofold (or 50%) difference in copy number. We have developed a new technology to study copy numbers using a platform known as the digital array, a nanofluidic biochip capable of accurately quantitating genes of interest in DNA samples. We have evaluated the digital array's performance using a model system, to show that this technology is exquisitely sensitive, capable of differentiating as little as a 15% difference in gene copy number (or between 6 and 7 copies of a target gene). We have also analyzed commercial DNA samples for their CYP2D6 copy numbers and confirmed that our results were consistent with those obtained independently using conventional techniques. In a screening experiment with breast cancer and normal DNA samples, the ERBB2 gene was found to be amplified in about 35% of breast cancer samples. The use of the digital array enables accurate measurement of gene copy numbers and is of significant value in CNV studies.     

What a difference copy number variation makes

DNA copy number variation (CNV) represents a considerable source of human genetic diversity. Recently,1 a global map of copy number variation in the human genome has been drawn up which reveals not only the ubiquity but also the complexity of this type of variation. Thus, two human genomes may differ by more than 20 Mb and it is likely that the full extent of CNV still remains to be discovered. Nearly 3000 genes are associated with CNV. This high degree of variability with regard to gene copy number between two individuals challenges definitions of normality. Many CNVs are located in regions of complex genomic structure and this currently limits the extent to which these variants can be genotyped by using tagging SNPs. However, some CNVs are already amenable to genome-wide association studies so that their influence on human phenotypic diversity and disease susceptibility may soon be determined.     

The impact of errors in copy number variation detection algorithms on association results

The inaccuracy of copy number variation (CNV) detection on single nucleotide polymorphism (SNP) arrays has recently been brought to attention. Such high error rates will undoubtedly have ramifications on downstream association testing. We examined this effect for a wide range of scenarios and found a noticeable decrease in power for error rates typical of CNV calling algorithms. We compared power using CNV calls to the log relative ratio and found the latter to be superior when error rates are moderate to large or when the CNV size is small. It is our recommendation that CNV researchers use intensity measurements as an alternative to CNV calls in these scenarios.     

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

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

Variation of CNV distribution in five different ethnic populations

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

Determination of beta-defensin genomic copy number in different populations: a comparison of three methods

Background

There have been conflicting reports in the literature on association of gene copy number with disease, including CCL3L1 and HIV susceptibility, and β-defensins and Crohn''s disease. Quantification of precise gene copy numbers is important in order to define any association of gene copy number with disease. At present, real-time quantitative PCR (QPCR) is the most commonly used method to determine gene copy number, however the Paralogue Ratio Test (PRT) is being used in more and more laboratories.

Findings

In this study we compare a Pyrosequencing-based Paralogue Ratio Test (PPRT) for determining beta-defensin gene copy number with two currently used methods for gene copy number determination, QPCR and triplex PRT by typing five different cohorts (UK, Danish, Portuguese, Ghanaian and Czech) of DNA from a total of 576 healthy individuals. We found a systematic measurement bias between DNA cohorts revealed by QPCR, but not by the PRT-based methods. Using PRT, copy number ranged from 2 to 9 copies, with a modal copy number of 4 in all populations.

Conclusions

QPCR is very sensitive to quality of the template DNA, generating systematic biases that could produce false-positive or negative disease associations. Both triplex PRT and PPRT do not show this systematic bias, and type copy number within the correct range, although triplex PRT appears to be a more precise and accurate method to type beta-defensin copy number.     

Array-based comparative genomic hybridization and copy number variation in cancer research

Array-based comparative genomic hybridization (aCGH) is a molecular cytogenetic technique used in detecting and mapping DNA copy number alterations. aCGH is able to interrogate the entire genome at a previously unattainable, high resolution and has directly led to the recent appreciation of a novel class of genomic variation: copy number variation (CNV) in mammalian genomes. All forms of DNA variation/polymorphism are important for studying the basis of phenotypic diversity among individuals. CNV research is still at its infancy, requiring careful collation and annotation of accumulating CNV data that will undoubtedly be useful for accurate interpretation of genomic imbalances identified during cancer research.     

Contributions of Mamu-A*01 Status and TRIM5 Allele Expression,But Not CCL3L Copy Number Variation,to the Control of SIVmac251 Replication in Indian-Origin Rhesus Monkeys

CCL3 is a ligand for the HIV-1 co-receptor CCR5. There have recently been conflicting reports in the literature concerning whether CCL3-like gene (CCL3L) copy number variation (CNV) is associated with resistance to HIV-1 acquisition and with both viral load and disease progression following infection with HIV-1. An association has also been reported between CCL3L CNV and clinical sequelae of the simian immunodeficiency virus (SIV) infection in vivo in rhesus monkeys. The present study was initiated to explore the possibility of an association of CCL3L CNV with the control of virus replication and AIDS progression in a carefully defined cohort of SIVmac251-infected, Indian-origin rhesus monkeys. Although we demonstrated extensive variation in copy number of CCL3L in this cohort of monkeys, CCL3L CNV was not significantly associated with either peak or set-point plasma SIV RNA levels in these monkeys when MHC class I allele Mamu-A*01 was included in the models or progression to AIDS in these monkeys. With 66 monkeys in the study, there was adequate power for these tests if the correlation of CCL3L and either peak or set-point plasma SIV RNA levels was 0.34 or 0.36, respectively. These findings call into question the premise that CCL3L CNV is important in HIV/SIV pathogenesis.     

A chromosome 8 gene-cluster polymorphism with low human beta-defensin 2 gene copy number predisposes to Crohn disease of the colon

Defensins are endogenous antimicrobial peptides that protect the intestinal mucosa against bacterial invasion. It has been suggested that deficient defensin expression may underlie the chronic inflammation of Crohn disease (CD). The DNA copy number of the beta-defensin gene cluster on chromosome 8p23.1 is highly polymorphic within the healthy population, which suggests that the defective beta-defensin induction in colonic CD could be due to low beta-defensin-gene copy number. Here, we tested this hypothesis, using genomewide DNA copy number profiling by array-based comparative genomic hybridization and quantitative polymerase-chain-reaction analysis of the human beta-defensin 2 (HBD-2) gene. We showed that healthy individuals, as well as patients with ulcerative colitis, have a median of 4 (range 2-10) HBD-2 gene copies per genome. In a surgical cohort with ileal or colonic CD and in a second large cohort with inflammatory bowel diseases, those with ileal resections/disease exhibited a normal median HBD-2 copy number of 4, whereas those with colonic CD had a median of only 3 copies per genome (P=.008 for the surgical cohort; P=.032 for the second cohort). Overall, the copy number distribution in colonic CD was shifted to lower numbers compared with controls (P=.002 for both the surgical cohort and the cohort with inflammatory bowel diseases). Individuals with < or = 3 copies have a significantly higher risk of developing colonic CD than did individuals with > or = 4 copies (odds ratio 3.06; 95% confidence interval 1.46-6.45). An HBD-2 gene copy number of < 4 was associated with diminished mucosal HBD-2 mRNA expression (P=.033). In conclusion, a lower HBD-2 gene copy number in the beta-defensin locus predisposes to colonic CD, most likely through diminished beta-defensin expression.     

An efficient method for measuring copy number variation applied to improvement of nematode resistance in soybean

Copy number variation (CNV) is implicated in important traits in multiple crop plants, but can be challenging to genotype using conventional methods. The Rhg1 locus of soybean, which confers resistance to soybean cyst nematode (SCN), is a CNV of multiple 31.2‐kb genomic units each containing four genes. Reliable, high‐throughput methods to quantify Rhg1 and other CNVs for selective breeding were developed. The CNV genotyping assay described here uses a homeologous gene copy within the paleopolyploid soybean genome to provide the internal control for a single‐tube TaqMan copy number assay. Using this assay, CNV in breeding populations can be tracked with high precision. We also show that extensive CNV exists within Fayette, a released, inbred SCN‐resistant soybean cultivar with a high copy number at Rhg1 derived from a single donor parent. Copy number at Rhg1 is therefore unstable within a released variety over a relatively small number of generations. Using this assay to select for individuals with altered copy number, plants were obtained with both increased copy number and increased SCN resistance relative to control plants. Thus, CNV genotyping technologies can be used as a new type of marker‐assisted selection to select for desirable traits in breeding populations, and to control for undesirable variation within cultivars.     

Copy number variations of CBF genes at the Fr‐A2 locus are essential components of winter hardiness in wheat

Winter hardiness is important for the adaptation of wheat to the harsh winter conditions in temperate regions and is thus also an important breeding goal. Here, we employed a panel of 407 European winter wheat cultivars to dissect the genetic architecture of winter hardiness. We show that copy number variation (CNV) of CBF (C‐repeat Binding Factor) genes at the Fr‐A2 locus is the essential component for winter survival, with CBF‐A14 CNV being the most likely causal polymorphism, accounting for 24.3% of the genotypic variance. Genome‐wide association mapping identified several markers in the Fr‐A2 chromosomal region, which even after accounting for the effects of CBF‐A14 copy number explained approximately 15% of the genotypic variance. This suggests that additional, as yet undiscovered, polymorphisms are present at the Fr‐A2 locus. Furthermore, CNV of Vrn‐A1 explained an additional 3.0% of the genotypic variance. The allele frequencies of all loci associated with winter hardiness were found to show geographic patterns consistent with their role in adaptation. Collectively, our results from the candidate gene analysis, association mapping and genome‐wide prediction show that winter hardiness in wheat is a quantitative trait, but with a major contribution of the Fr‐A2 locus.     

CNVassoc: Association analysis of CNV data using R

Background

Copy number variants (CNV) are a potentially important component of the genetic contribution to risk of common complex diseases. Analysis of the association between CNVs and disease requires that uncertainty in CNV copy-number calls, which can be substantial, be taken into account; failure to consider this uncertainty can lead to biased results. Therefore, there is a need to develop and use appropriate statistical tools. To address this issue, we have developed CNVassoc, an R package for carrying out association analysis of common copy number variants in population-based studies. This package includes functions for testing for association with different classes of response variables (e.g. class status, censored data, counts) under a series of study designs (case-control, cohort, etc) and inheritance models, adjusting for covariates. The package includes functions for inferring copy number (CNV genotype calling), but can also accept copy number data generated by other algorithms (e.g. CANARY, CGHcall, IMPUTE).

Results

Here we present a new R package, CNVassoc, that can deal with different types of CNV arising from different platforms such as MLPA o aCGH. Through a real data example we illustrate that our method is able to incorporate uncertainty in the association process. We also show how our package can also be useful when analyzing imputed data when analyzing imputed SNPs. Through a simulation study we show that CNVassoc outperforms CNVtools in terms of computing time as well as in convergence failure rate.

Conclusions

We provide a package that outperforms the existing ones in terms of modelling flexibility, power, convergence rate, ease of covariate adjustment, and requirements for sample size and signal quality. Therefore, we offer CNVassoc as a method for routine use in CNV association studies.     

Gene-based copy number variation study reveals a microdeletion at 12q24 that influences height in the Korean population

Height is a classic polygenic trait with high heritability (h² = 0.8). Recent genome-wide association studies have revealed many independent loci associated with human height. In addition, although many studies have reported an association between copy number variation (CNV) and complex diseases, few have explored the relationship between CNV and height. Recent studies reported that single nucleotide polymorphisms (SNPs) are highly correlated with common CNVs, suggesting that it is warranted to survey CNVs to identify additional genetic factors affecting heritable traits such as height.This study tested the hypothesis that there would be CNV regions (CNVRs) associated with height nearby genes from the GWASs known to affect height. We identified regions containing > 1% copy number deletion frequency from 3667 population-based cohort samples using the Illumina HumanOmni1-Quad BeadChip. Among the identified CNVRs, we selected 15 candidate regions that were located within 1 Mb of 283 previously reported genes. To assess the effect of these CNVRs on height, statistical analyses were conducted with samples from a case group of 370 taller (upper 10%) individuals and a control group of 1828 individuals (lower 50%).We found that a newly identified 17.7 kb deletion at chromosomal position 12q24.33, approximately 171.6 kb downstream of GPR133, significantly correlated with height; this finding was validated using quantitative PCR. These results suggest that CNVs are potentially important in determining height and may contribute to height variation in human populations.     

Complement component 4 copy number variation and CYP21A2 genotype associations in patients with congenital adrenal hyperplasia due to 21-hydroxylase deficiency

Congenital adrenal hyperplasia (CAH) due to 21-hydroxylase deficiency (21-OHD) is an autosomal recessive disorder of cortisol biosynthesis caused by CYP21A2 mutations. An increase in gene copy number variation (CNV) exists at the CYP21A2 locus. CNV of C4, a neighboring gene that encodes complement component 4, is associated with autoimmune disease susceptibility. In this study, we performed comprehensive genetic analysis of the RP-C4-CYP21-TNX (RCCX) region in 127 unrelated 21-OHD patients (100 classic, 27 nonclassic). C4 copy number was determined by Southern blot. C4 CNV and serum C4 levels were evaluated in relation to CYP21A2 mutations and relevant phenotypes. We found that the most common CYP21A2 mutation associated with the nonclassic form of CAH, V281L, was associated with high C4 copy number (p?=?7.13?×?10^?16). Large CYP21A2 deletion, a common mutation associated with the classic form of CAH, was associated with low C4 copy number (p?=?1.61?×?10^?14). Monomodular RCCX with a short C4 gene, a risk factor for autoimmune disease, was significantly less frequent in CAH patients compared to population estimates (2.8 vs. 10.6?%; p?=?1.08?×?10^?4). In conclusion, CAH patients have increased C4 CNV, with mutation-specific associations that may be protective for autoimmune disease. The study of CYP21A2 in relation to neighboring genes provides insight into the genetics of CNV hotspots, an important determinant of human health.     

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.