Genome-wide SNP assay reveals structural genomic variation, extended homozygosity and cell-line induced alterations in normal individuals

Genomic investigation of alpha-synuclein multiplication and parkinsonism

OBJECTIVE

Copy number variation is a common polymorphic phenomenon within the human genome. Although the majority of these events are non-deleterious they can also be highly pathogenic. Herein we characterize five families with parkinsonism that have been identified to harbor multiplication of the chromosomal 4q21 locus containing the alpha-synuclein gene (SNCA).

METHODS

A methodological approach using fluorescent in situ hybridization and Affymetrix (Santa Clara, CA) 250K SNP microarrays was used to characterize the multiplication in each family and to identify the genes encoded within the region. The telomeric and centromeric breakpoints of each family were further narrowed using semiquantitative polymerase chain reaction with microsatellite markers and then screened for transposable repeat elements.

RESULTS

The severity of clinical presentation is correlated with SNCA dosage and does not appear to be overtly affected by the presence of other genes in the multiplicated region. With the exception of the Lister kindred, in each family the multiplication event appears de novo. The type and position of Alu/LINE repeats are also different at each breakpoint. Microsatellite analysis demonstrates two genomic mechanisms are responsible for chromosome 4q21 multiplications, including both SNCA duplication and recombination.

INTERPRETATION

SNCA dosage is responsible for parkinsonism, autonomic dysfunction, and dementia observed within each family. We hypothesize dysregulated expression of wild-type alpha-synuclein results in parkinsonism and may explain the recent association of common SNCA variants in sporadic Parkinson's disease. SNCA genomic duplication results from intraallelic (segmental duplication) or interallelic recombination with unequal crossing over, whereas both mechanisms appear to be required for genomic SNCA triplication.

Detection, imputation, and association analysis of small deletions and null alleles on oligonucleotide arrays

Copy-number variation (CNV) is a major contributor to human genetic variation. Recently, CNV associations with human disease have been reported. Many genome-wide association (GWA) studies in complex diseases have been performed with sets of biallelic single-nucleotide polymorphisms (SNPs), but the available CNV methods are still limited. We present a new method (TriTyper) that can infer genotypes in case-control data sets for deletion CNVs, or SNPs with an extra, untyped allele at a high-resolution single SNP level. By accounting for linkage disequilibrium (LD), as well as intensity data, calling accuracy is improved. Analysis of 3102 unrelated individuals with European descent, genotyped with Illumina Infinium BeadChips, resulted in the identification of 1880 SNPs with a common untyped allele, and these SNPs are in strong LD with neighboring biallelic SNPs. Simulations indicate our method has superior power to detect associations compared to biallelic SNPs that are in LD with these SNPs, yet without increasing type I errors, as shown in a GWA analysis in celiac disease. Genotypes for 1204 triallelic SNPs could be fully imputed, with only biallelic-genotype calls, permitting association analysis of these SNPs in many published data sets. We estimate that 682 of the 1655 unique loci reflect deletions; this is on average 99 deletions per individual, four times greater than those detected by other methods. Whereas the identified loci are strongly enriched for known deletions, 61% have not been reported before. Genes overlapping with these loci more often have paralogs (p = 0.006) and biologically interact with fewer genes than expected (p = 0.004).

Structural genomic variation in ischemic stroke

Technological advances in molecular genetics allow rapid and sensitive identification of genomic copy number variants (CNVs). This, in turn, has sparked interest in the function such variation may play in disease. While a role for copy number mutations as a cause of Mendelian disorders is well established, it is unclear whether CNVs may affect risk for common complex disorders. We sought to investigate whether CNVs may modulate risk for ischemic stroke (IS) and to provide a catalog of CNVs in patients with this disorder by analyzing copy number metrics produced as a part of our previous genome-wide single-nucleotide polymorphism (SNP)-based association study of ischemic stroke in a North American white population. We examined CNVs in 263 patients with ischemic stroke (IS). Each identified CNV was compared with changes identified in 275 neurologically normal controls. Our analysis identified 247 CNVs, corresponding to 187 insertions (76%; 135 heterozygous; 25 homozygous duplications or triplications; 2 heterosomic) and 60 deletions (24%; 40 heterozygous deletions; 3 homozygous deletions; 14 heterosomic deletions). Most alterations (81%) were the same as, or overlapped with, previously reported CNVs. We report here the first genome-wide analysis of CNVs in IS patients. In summary, our study did not detect any common genomic structural variation unequivocally linked to IS, although we cannot exclude that smaller CNVs or CNVs in genomic regions poorly covered by this methodology may confer risk for IS. The application of genome-wide SNP arrays now facilitates the evaluation of structural changes through the entire genome as part of a genome-wide genetic association study.

SNP arrays in heterogeneous tissue: highly accurate collection of both germline and somatic genetic information from unpaired single tumor samples

SNP arrays provide reliable genotypes and can detect chromosomal aberrations at a high resolution. However, tissue heterogeneity is currently a major limitation for somatic tissue analysis. We have developed SOMATICs, an original program for accurate analysis of heterogeneous tissue samples. Fifty-four samples (42 tumors and 12 normal tissues) were processed through Illumina Beadarrays and then analyzed with SOMATICs. We demonstrate that tissue heterogeneity-related limitations not only can be overcome but can also be turned into an advantage. First, admixture of normal cells with tumor can be used as an internal reference, thereby enabling highly sensitive detection of somatic deletions without having corresponding normal tissue. Second, the presence of normal cells allows for discrimination of somatic from germline aberrations, and the proportion of cells in the tissue sample that are harboring the somatic events can be assessed. Third, relatively early versus late somatic events can also be distinguished, assuming that late events occur only in subsets of cancer cells. Finally, admixture by normal cells allows inference of germline genotypes from a cancer sample. All this information can be obtained from any cancer sample containing a proportion of 40-75% of cancer cells. SOMATICs is a ready-to-use open-source program that integrates all of these features into a simple format, comprehensively describing each chromosomal event.

Improved detection of global copy number variation using high density, non-polymorphic oligonucleotide probes

Background

DNA sequence diversity within the human genome may be more greatly affected by copy number variations (CNVs) than single nucleotide polymorphisms (SNPs). Although the importance of CNVs in genome wide association studies (GWAS) is becoming widely accepted, the optimal methods for identifying these variants are still under evaluation. We have previously reported a comprehensive view of CNVs in the HapMap DNA collection using high density 500 K EA (Early Access) SNP genotyping arrays which revealed greater than 1,000 CNVs ranging in size from 1 kb to over 3 Mb. Although the arrays used most commonly for GWAS predominantly interrogate SNPs, CNV identification and detection does not necessarily require the use of DNA probes centered on polymorphic nucleotides and may even be hindered by the dependence on a successful SNP genotyping assay.

Results

In this study, we have designed and evaluated a high density array predicated on the use of non-polymorphic oligonucleotide probes for CNV detection. This approach effectively uncouples copy number detection from SNP genotyping and thus has the potential to significantly improve probe coverage for genome-wide CNV identification. This array, in conjunction with PCR-based, complexity-reduced DNA target, queries over 1.3 M independent NspI restriction enzyme fragments in the 200 bp to 1100 bp size range, which is a several fold increase in marker density as compared to the 500 K EA array. In addition, a novel algorithm was developed and validated to extract CNV regions and boundaries.

Conclusion

Using a well-characterized pair of DNA samples, close to 200 CNVs were identified, of which nearly 50% appear novel yet were independently validated using quantitative PCR. The results indicate that non-polymorphic probes provide a robust approach for CNV identification, and the increasing precision of CNV boundary delineation should allow a more complete analysis of their genomic organization.

Copy-number variation in sporadic amyotrophic lateral sclerosis: a genome-wide screen

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterised by the selective death of motor neurons in the brain and spinal cord. Genetic risk factors have been implicated in susceptibility to ALS. Like single nucleotide polymorphisms (SNPs), copy-number variants (CNVs) are a source of genetic variation that have important effects on gene expression and disease phenotypes, and our aim was to identify CNVs that predispose to sporadic ALS.

METHODS

We did a genome-wide screen for CNVs by analysis of Illumina 317K SNP arrays for 406 patients with sporadic ALS and 404 controls. We examined CNVs for association with ALS, and used the Kyoto Encyclopedia of Genes and Genomes database and the Gene Ontology database to investigate the functionality of genes that were deleted exclusively in patients with ALS.

FINDINGS

We detected 2328 CNVs in 810 individuals. No CNV locus was significantly associated with sporadic ALS. 406 genes were duplicated or deleted exclusively in patients with ALS and have not been reported in previous studies of CNVs. Of the 390 genes heterozygously deleted in patients with sporadic ALS, 155 (40%) deletions were recorded exclusively in patients. By contrast, of the 323 genes heterozygously deleted in control participants, only 51 (16%) were exclusive to the controls (p=2.15 x 10(-12) for difference between groups). Products of the genes deleted specifically in patients with sporadic ALS include proteins involved in oxidative phosphorylation, regulation of the actin cytoskeleton, and interactions between cytokines and their receptors.

INTERPRETATION

Common CNVs in the regions of the genome represented on the SNP array are unlikely to be associated with sporadic ALS. However, the high number of genes deleted specifically in patients with ALS strongly suggests that multiple rare deletions might have an important role in ALS pathogenesis.

A recurrent 15q13.3 microdeletion syndrome associated with mental retardation and seizures

We report a recurrent microdeletion syndrome causing mental retardation, epilepsy and variable facial and digital dysmorphisms. We describe nine affected individuals, including six probands: two with de novo deletions, two who inherited the deletion from an affected parent and two with unknown inheritance. The proximal breakpoint of the largest deletion is contiguous with breakpoint 3 (BP3) of the Prader-Willi and Angelman syndrome region, extending 3.95 Mb distally to BP5. A smaller 1.5-Mb deletion has a proximal breakpoint within the larger deletion (BP4) and shares the same distal BP5. This recurrent 1.5-Mb deletion contains six genes, including a candidate gene for epilepsy (CHRNA7) that is probably responsible for the observed seizure phenotype. The BP4-BP5 region undergoes frequent inversion, suggesting a possible link between this inversion polymorphism and recurrent deletion. The frequency of these microdeletions in mental retardation cases is approximately 0.3% (6/2,082 tested), a prevalence comparable to that of Williams, Angelman and Prader-Willi syndromes.

Study of regions of extended homozygosity provides a powerful method to explore haplotype structure of human populations

Previous investigations have reported linkage disequilibrium occurring between nearby polymorphisms, a block-like structure for such relationships, some instances where surprisingly few haplotypes are found and regions of extended homozygosity which are especially marked around centromeres and which are especially common on the X chromosome. We investigated the distribution and nature of regions of extended homozygosity in a sample of 1411 subjects included in a genome wide association study. Regions of extended homozygosity over 1Mb are common, with an average of 35.9 occurring per subject, and containing on average 73 homozygous markers. They have a markedly non-random distribution. They are relatively common on the X chromosome and are seen at centromeres but are also concentrated at other chromosomal regions where presumably recombination is rare. They seem to be a consequence of some haplotypes being very common in the population and although sometimes this reflects the effect of a very common haplotype we also note that there are examples of two or three common haplotypes, each very different from each other, underlying this effect. Regions of extended homozygosity are commoner than previously appreciated. They result from the presence of extended haplotypes with high population frequency. Such regions concentrate in particular locations. The haplotypes involved are sometimes markedly disparate from each other. These regions offer a valuable opportunity for further investigation, in particular with regard to their ancestral history.

Genomewide SNP assay reveals mutations underlying Parkinson disease

Technologies that allow genotyping of more than 100,000 polymorphisms in a single assay enable the execution of genomewide SNP (GWSNP) association studies to identify common genetic variants underlying traits. Less appreciated is the ability of GWSNP assays to map and directly identify rare mutations that cause disease. Here we show the use of this approach in identifying rare structural mutations involved in disease using a large cohort of Parkinson disease (PD) patients and neurologically normal controls by examination of genotype data and copy number metrics. This approach revealed a patient with homozygous mutation at the PARK2 locus. In addition, two heterozygous deletion mutations and five heterozygous duplication mutations within PARK2 were identified in PD subjects and controls. All mutations were confirmed by independent gene dosage experiments. These data demonstrate the utility of this approach in the direct detection of mutations that underlie disease.

Copy number variants and common disorders: filling the gaps and exploring complexity in genome-wide association studies

Genome-wide association scans (GWASs) using single nucleotide polymorphisms (SNPs) have been completed successfully for several common disorders and have detected over 30 new associations. Considering the large sample sizes and genome-wide SNP coverage of the scans, one might have expected many of the common variants underpinning the genetic component of various disorders to have been identified by now. However, these studies have not evaluated the contribution of other forms of genetic variation, such as structural variation, mainly in the form of copy number variants (CNVs). Known CNVs account for over 15% of the assembled human genome sequence. Since CNVs are not easily tagged by SNPs, might have a wide range of copy number variability, and often fall in genomic regions not well covered by whole-genome arrays or not genotyped by the HapMap project, current GWASs have largely missed the contribution of CNVs to complex disorders. In fact, some CNVs have already been reported to show association with several complex disorders using candidate gene/region approaches, underpinning the importance of regions not investigated in current GWASs. This reveals the need for new generation arrays (some already in the market) and the use of tailored approaches to explore the full dimension of genome variability beyond the single nucleotide scale.

Runs of homozygosity reveal highly penetrant recessive loci in schizophrenia

Evolutionarily significant selective sweeps may result in long stretches of homozygous polymorphisms in individuals from outbred populations. We developed whole-genome homozygosity association (WGHA) methodology to characterize this phenomenon in healthy individuals and to use this genomic feature to identify genetic risk loci for schizophrenia (SCZ). Applying WGHA to 178 SCZ cases and 144 healthy controls genotyped at 500,000 markers, we found that runs of homozygosity (ROHs), ranging in size from 200 kb to 15 mb, were common in unrelated Caucasians. Properties of common ROHs in healthy subjects, including chromosomal location and presence of nonancestral haplotypes, converged with prior reports identifying regions under selective pressure. This interpretation was further supported by analysis of multiethnic HapMap samples genotyped with the same markers. ROHs were significantly more common in SCZ cases, and a set of nine ROHs significantly differentiated cases from controls. Four of these 9 "risk ROHs" contained or neighbored genes associated with SCZ (NOS1AP, ATF2, NSF, and PIK3C3). Several of these risk ROHs were very rare in healthy subjects, suggesting that recessive effects of relatively high penetrance may explain a proportion of the genetic liability for SCZ. Other risk ROHs feature haplotypes that are also common in healthy individuals, possibly indicating a source of balancing selection.

Amyotrophic lateral sclerosis: an emerging era of collaborative gene discovery

Amyotrophic lateral sclerosis (ALS) is the most common form of motor neuron disease (MND). It is currently incurable and treatment is largely limited to supportive care. Family history is associated with an increased risk of ALS, and many Mendelian causes have been discovered. However, most forms of the disease are not obviously familial. Recent advances in human genetics have enabled genome-wide analyses of single nucleotide polymorphisms (SNPs) that make it possible to study complex genetic contributions to human disease. Genome-wide SNP analyses require a large sample size and thus depend upon collaborative efforts to collect and manage the biological samples and corresponding data. Public availability of biological samples (such as DNA), phenotypic and genotypic data further enhances research endeavors. Here we discuss a large collaboration among academic investigators, government, and non-government organizations which has created a public repository of human DNA, immortalized cell lines, and clinical data to further gene discovery in ALS. This resource currently maintains samples and associated phenotypic data from 2332 MND subjects and 4692 controls. This resource should facilitate genetic discoveries which we anticipate will ultimately provide a better understanding of the biological mechanisms of neurodegeneration in ALS.

Visualization of uniparental inheritance, Mendelian inconsistencies, deletions, and parent of origin effects in single nucleotide polymorphism trio data with SNPtrio

A variety of alterations occur in chromosomal DNA, many of which can be detected using high density single nucleotide polymorphism (SNP) microarrays. These include deletions and duplications (assessed by observing changes in copy number) and regions of homozygosity. The analysis of SNP data from trios can provide an additional category of information about the nature and origin of inheritance patterns, including uniparental disomy (UPD), loss of transmitted allele (LTA), and nonparental relationship. The main purpose of SNPtrio is to locate regions of uniparental inheritance (UPI) and Mendelian inconsistency (MI), identify the type (paternal vs. maternal, iso- vs. hetero-), and assess the associated statistical probability of occurrence by chance. SNPtrio's schema permits the identification of hemizygous or homozygous deletions as well as UPD. We validated the performance of SNPtrio on three platforms (Affymetrix 10 K and 100 K arrays and Illumina 550 K arrays) using SNP data obtained from DNA samples of patients known to have UPD and diagnosed with Prader-Willi syndrome, Angelman syndrome, Beckwith-Wiedemann syndrome, pseudohypoparathyroidism, and a complex chromosome 2 abnormality. We further validated SNPtrio using DNA from patients previously shown to have microdeletions that were verified by fluorescence in situ hybridization (FISH). SNPtrio successfully identified previously known UPD and deletion regions, and generated associated probability values. SNPtrio analysis of trisomy 21 (Down syndrome) cases and their parents permitted identification of the parent of origin of the extra chromosomal copy. SNPtrio is freely accessible at http://pevsnerlab.kennedykrieger.org/SNPtrio.htm (Last accessed: 20 June 2007).

Discerning the ancestry of European Americans in genetic association studies

European Americans are often treated as a homogeneous group, but in fact form a structured population due to historical immigration of diverse source populations. Discerning the ancestry of European Americans genotyped in association studies is important in order to prevent false-positive or false-negative associations due to population stratification and to identify genetic variants whose contribution to disease risk differs across European ancestries. Here, we investigate empirical patterns of population structure in European Americans, analyzing 4,198 samples from four genome-wide association studies to show that components roughly corresponding to northwest European, southeast European, and Ashkenazi Jewish ancestry are the main sources of European American population structure. Building on this insight, we constructed a panel of 300 validated markers that are highly informative for distinguishing these ancestries. We demonstrate that this panel of markers can be used to correct for stratification in association studies that do not generate dense genotype data.

Haplotype-based association analysis via variance-components score test

Haplotypes provide a more informative format of polymorphisms for genetic association analysis than do individual single-nucleotide polymorphisms. However, the practical efficacy of haplotype-based association analysis is challenged by a trade-off between the benefits of modeling abundant variation and the cost of the extra degrees of freedom. To reduce the degrees of freedom, several strategies have been considered in the literature. They include (1) clustering evolutionarily close haplotypes, (2) modeling the level of haplotype sharing, and (3) smoothing haplotype effects by introducing a correlation structure for haplotype effects and studying the variance components (VC) for association. Although the first two strategies enjoy a fair extent of power gain, empirical evidence showed that VC methods may exhibit only similar or less power than the standard haplotype regression method, even in cases of many haplotypes. In this study, we report possible reasons that cause the underpowered phenomenon and show how the power of the VC strategy can be improved. We construct a score test based on the restricted maximum likelihood or the marginal likelihood function of the VC and identify its nontypical limiting distribution. Through simulation, we demonstrate the validity of the test and investigate the power performance of the VC approach and that of the standard haplotype regression approach. With suitable choices for the correlation structure, the proposed method can be directly applied to unphased genotypic data. Our method is applicable to a wide-ranging class of models and is computationally efficient and easy to implement. The broad coverage and the fast and easy implementation of this method make the VC strategy an effective tool for haplotype analysis, even in modern genomewide association studies.

PennCNV: an integrated hidden Markov model designed for high-resolution copy number variation detection in whole-genome SNP genotyping data

Comprehensive identification and cataloging of copy number variations (CNVs) is required to provide a complete view of human genetic variation. The resolution of CNV detection in previous experimental designs has been limited to tens or hundreds of kilobases. Here we present PennCNV, a hidden Markov model (HMM) based approach, for kilobase-resolution detection of CNVs from Illumina high-density SNP genotyping data. This algorithm incorporates multiple sources of information, including total signal intensity and allelic intensity ratio at each SNP marker, the distance between neighboring SNPs, the allele frequency of SNPs, and the pedigree information where available. We applied PennCNV to genotyping data generated for 112 HapMap individuals; on average, we detected approximately 27 CNVs for each individual with a median size of approximately 12 kb. Excluding common rearrangements in lymphoblastoid cell lines, the fraction of CNVs in offspring not detected in parents (CNV-NDPs) was 3.3%. Our results demonstrate the feasibility of whole-genome fine-mapping of CNVs via high-density SNP genotyping.

Extended homozygosity is not usually due to cytogenetic abnormality

Background

Previous studies have reported frequent stretches of homozygosity in human subjects but have failed to clarify whether these are due to cytogenetic abnormalities or to autozygosity.

Methods

Trios which had been typed for closely spaced SNPs spanning the genome were studied. Stretches of extended homozygosity were identified in the child members, as were occasions on which the child had been genotyped as not inheriting one parental allele. The number of times such transmission errors occurred within regions of extended homozygosity was compared with the chance expectation.

Results

Transmission errors occurred more rarely in regions of extended homozygosity than would be expected by chance.

Discussion

Regions of extended homozygosity are not generally due to cytogenetic abnormalities such as uniparental isodisomy. They reflect the Mendelian inheritance of haplotypes from a common ancestor. This may have implications for mapping disease genes.

Molecular karyotyping in patients with mental retardation using 100K single-nucleotide polymorphism arrays

BACKGROUND

Using array techniques, it was recently shown that about 10% of patients with mental retardation of unknown origin harbour cryptic chromosomal aneusomies. However, data analysis is currently not standardised and little is known about its sensitivity and specificity.

METHODS

We have developed an electronic data analysis tool for gene-mapping SNP arrays, a software tool that we call Copy Number Variation Finder (CNVF). Using CNVF, we analysed 104 unselected patients with mental retardation of unknown origin with a genechip mapping 100K SNP array and established an optimised set of analysis parameters.

RESULTS

We detected deletions as small as 20 kb when covered by at least three single-nucleotide polymorphisms (SNPs) and duplications as small as 150 kb when covered by at least six SNPs, with only one false-positive signal in six patients. In 9.1% of patients, we detected apparently disease-causing or de novo aberrations ranging in size from 0.4 to 14 Mb. Morphological anomalies in patients with de novo aberrations were equal to that of unselected patients when measured with de Vries score.

CONCLUSION

Our standardised CNVF data analysis tool is easy to use and has high sensitivity and specificity. As some genomic regions are covered more densely than others, the genome-wide resolution of the 100K array is about 400-500 kb for deletions and 900-1000 kb for duplications. The detection rate of about 10% of de novo aberrations is independent of selection of patients for particular features. The incidental finding in two patients of heterozygosity for the 250 kb recurrent deletion at the NPH1 locus, associated with autosomal recessive juvenile nephronophthisis, which was inherited from a healthy parent, highlights the fact that inherited aberrations might be disease-related even though not causal for mental retardation.

Simultaneous discovery and testing of deletions for disease association in SNP genotyping studies

Copy-number variation (CNV), and deletions in particular, can play a crucial, causative role in rare disorders. The extent to which CNV contributes to common, complex disease etiology, however, is largely unknown. Current techniques to detect CNV are relatively expensive and time consuming, making it difficult to conduct the necessary large-scale genetic studies. SNP genotyping technologies, on the other hand, are relatively cheap, thereby facilitating large study designs. We have developed a computational tool capable of harnessing the information in SNP genotype data to detect deletions. Our approach not only detects deletions with high power but also returns accurate estimates of both the population frequency and the transmission frequency. This tool, therefore, lends itself to the discovery of deletions in large familial SNP genotype data sets and to simultaneous testing of the discovered deletion for association, with the use of both frequency-based and transmission/disequilibrium test-based designs. We demonstrate the effectiveness of our computer program (microdel), available for download at no cost, with both simulated and real data. Here, we report 693 deletions in the HapMap 16c collection, with each deletion assigned a population frequency.

High-resolution genomic microarrays for X-linked mental retardation

Developments in genomic microarray technology have revolutionized the study of human genomic copy number variation. This has significantly affected many areas in human genetics, including the field of X-linked mental retardation (XLMR). Chromosome X-specific bacterial artificial chromosomes microarrays have been developed to specifically test this chromosome with a resolution of approximately 100 kilobases. Application of these microarrays in X-linked mental retardation studies has resulted in the identification of novel X-linked mental retardation genes, copy number variation at known X-linked mental retardation genes, and copy number variations harboring as yet unidentified X-linked mental retardation genes. Further enhancements in genomic microarray analysis will soon allow the reliable analysis of all copy number variations throughout this chromosome at the kilobase or single exon resolution. In this review, we describe the developments in this field and specifically highlight the impact of these microarray studies in the field of X-linked mental retardation.

Challenges and standards in integrating surveys of structural variation

There has been an explosion of data describing newly recognized structural variants in the human genome. In the flurry of reporting, there has been no standard approach to collecting the data, assessing its quality or describing identified features. This risks becoming a rampant problem, in particular with respect to surveys of copy number variation and their application to disease studies. Here, we consider the challenges in characterizing and documenting genomic structural variants. From this, we derive recommendations for standards to be adopted, with the aim of ensuring the accurate presentation of this form of genetic variation to facilitate ongoing research.

The C20orf133 gene is disrupted in a patient with Kabuki syndrome

BACKGROUND

Kabuki syndrome (KS) is a rare, clinically recognisable, congenital mental retardation syndrome. The aetiology of KS remains unknown.

METHODS

Four carefully selected patients with KS were screened for chromosomal imbalances using array comparative genomic hybridisation at 1 Mb resolution.

RESULTS

In one patient, a 250 kb de novo microdeletion at 20p12.1 was detected, deleting exon 5 of C20orf133. The function of this gene is unknown. In situ hybridisation with the mouse orthologue of C20orf133 showed expression mainly in brain, but also in kidney, eye, inner ear, ganglia of the peripheral nervous system and lung.

CONCLUSION

The de novo nature of the deletion, the expression data and the fact that C20orf133 carries a macro domain, suggesting a role for the gene in chromatin biology, make the gene a likely candidate to cause the phenotype in this patient with KS. Both the finding of different of chromosomal rearrangements in patients with KS features and the absence of C20orf133 mutations in 19 additional patients with KS suggest that KS is genetically heterogeneous.

Common genetic variation in eight genes of the GH/IGF1 axis does not contribute to adult height variation

Stature (adult height) is one of the most heritable human traits, yet few genes, if any, have been convincingly associated with adult height variation in the general population. Here, we selected 150 tag SNPs from eight candidate genes in the growth hormone (GH)/insulin-like growth factor-1 (IGF1) axis (GHR, GHRH, GHRHR, IGF1, IGFALS, IGFBP3, JAK2, STAT5B), and genotyped them in approximately 2,200 individuals ascertained for short or tall stature. Nominally significant tag SNPs were then tested in three additional replication cohorts, including a family-based panel to rule out spurious associations owing to population stratification. Across the four height cohorts (N = 6,075 individuals), we did not observe any consistent associations between stature and common variants (> or =5% minor allele frequency) in these eight genes, including a common deletion of the growth hormone receptor gene exon 3. Tests of epistatic interactions between these genes did not yield any results beyond those expected by chance. Although we have not tested all genes in the GH/IGF1 axis, our results indicate that common variation in these GH/IGF1 axis genes is not a major determinant of stature, and suggest that if common variation contributes to adult height variation in the general population, the variants are in other, possibly unanticipated genes.

Deletion at ITPR1 underlies ataxia in mice and spinocerebellar ataxia 15 in humans

We observed a severe autosomal recessive movement disorder in mice used within our laboratory. We pursued a series of experiments to define the genetic lesion underlying this disorder and to identify a cognate disease in humans with mutation at the same locus. Through linkage and sequence analysis we show here that this disorder is caused by a homozygous in-frame 18-bp deletion in Itpr1 (Itpr1(Delta18/Delta18)), encoding inositol 1,4,5-triphosphate receptor 1. A previously reported spontaneous Itpr1 mutation in mice causes a phenotype identical to that observed here. In both models in-frame deletion within Itpr1 leads to a decrease in the normally high level of Itpr1 expression in cerebellar Purkinje cells. Spinocerebellar ataxia 15 (SCA15), a human autosomal dominant disorder, maps to the genomic region containing ITPR1; however, to date no causal mutations had been identified. Because ataxia is a prominent feature in Itpr1 mutant mice, we performed a series of experiments to test the hypothesis that mutation at ITPR1 may be the cause of SCA15. We show here that heterozygous deletion of the 5' part of the ITPR1 gene, encompassing exons 1-10, 1-40, and 1-44 in three studied families, underlies SCA15 in humans.

A genome-wide genotyping study in patients with ischaemic stroke: initial analysis and data release

BACKGROUND

Despite evidence of a genetic role in stroke, the identification of common genetic risk factors for this devastating disorder remains problematic. We aimed to identify any common genetic variability exerting a moderate to large effect on risk of ischaemic stroke, and to generate publicly available genome-wide genotype data to facilitate others doing the same.

METHODS

We applied a genome-wide high-density single-nucleotide-polymorphism (SNP) genotyping approach to a cohort of samples with and without ischaemic stroke (n=278 and 275, respectively), and did an association analysis adjusted for known confounders in a final cohort of 249 cases and 268 controls. More than 400,000 unique SNPs were assayed.

FINDINGS

We produced more than 200 million genotypes in 553 unique participants. The raw genotypes of all the controls have been posted publicly in a previous study of Parkinson's disease. From this effort, results of genotype and allele association tests have been publicly posted for 88% of stroke patients who provided proper consent for public release. Preliminary analysis of these data did not reveal any single locus conferring a large effect on risk for ischaemic stroke.

INTERPRETATION

The data generated here comprise the first phase of a genome-wide association analysis in patients with stroke. Release of phase I results generated in these publicly available samples from each consenting individual makes this dataset a valuable resource for data-mining and augmentation.

Genome-wide genotyping in amyotrophic lateral sclerosis and neurologically normal controls: first stage analysis and public release of data

BACKGROUND

The cause of sporadic ALS is currently unknown. Despite evidence for a role for genetics, no common genetic variants have been unequivocally linked to sporadic ALS. We sought to identify genetic variants associated with an increased or decreased risk for developing ALS in a cohort of American sporadic cases.

METHODS

We undertook a genome-wide association study using publicly available samples from 276 patients with sporadic ALS and 271 neurologically normal controls. 555 352 unique SNPs were assayed in each sample using the Illumina Infinium II HumanHap550 SNP chip.

FINDINGS

More than 300 million genotypes were produced in 547 participants. These raw genotype data are freely available on the internet and represent the first publicly accessible SNP data for ALS cases. 34 SNPs with a p value less than 0.0001 (two degrees of freedom) were found, although none of these reached significance after Bonferroni correction.

INTERPRETATION

We generated publicly available genotype data for sporadic ALS patients and controls. No single locus was definitively associated with increased risk of developing disease, although potentially associated candidate SNPs were identified.