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

Hybridization modeling of oligonucleotide SNP arrays for accurate DNA copy number estimation

Affymetrix SNP arrays have been widely used for single-nucleotide polymorphism (SNP) genotype calling and DNA copy number variation inference. Although numerous methods have achieved high accuracy in these fields, most studies have paid little attention to the modeling of hybridization of probes to off-target allele sequences, which can affect the accuracy greatly. In this study, we address this issue and demonstrate that hybridization with mismatch nucleotides (HWMMN) occurs in all SNP probe-sets and has a critical effect on the estimation of allelic concentrations (ACs). We study sequence binding through binding free energy and then binding affinity, and develop a probe intensity composite representation (PICR) model. The PICR model allows the estimation of ACs at a given SNP through statistical regression. Furthermore, we demonstrate with cell-line data of known true copy numbers that the PICR model can achieve reasonable accuracy in copy number estimation at a single SNP locus, by using the ratio of the estimated AC of each sample to that of the reference sample, and can reveal subtle genotype structure of SNPs at abnormal loci. We also demonstrate with HapMap data that the PICR model yields accurate SNP genotype calls consistently across samples, laboratories and even across array platforms.

The genetic contribution to non-syndromic human obesity

The last few years have seen major advances in common non-syndromic obesity research, much of it the result of genetic studies. This Review outlines the competing hypotheses about the mechanisms underlying the genetic and physiological basis of obesity, and then examines the recent explosion of genetic association studies that have yielded insights into obesity, both at the candidate gene level and the genome-wide level. With obesity genetics now entering the post-genome-wide association scan era, the obvious question is how to improve the results obtained so far using single nucleotide polymorphism markers and how to move successfully into the other areas of genomic variation that may be associated with common obesity.

Integrated study of copy number states and genotype calls using high-density SNP arrays

We propose a statistical framework, named genoCN, to simultaneously dissect copy number states and genotypes using high-density SNP (single nucleotide polymorphism) arrays. There are at least two types of genomic DNA copy number differences: copy number variations (CNVs) and copy number aberrations (CNAs). While CNVs are naturally occurring and inheritable, CNAs are acquired somatic alterations most often observed in tumor tissues only. CNVs tend to be short and more sparsely located in the genome compared with CNAs. GenoCN consists of two components, genoCNV and genoCNA, designed for CNV and CNA studies, respectively. In contrast to most existing methods, genoCN is more flexible in that the model parameters are estimated from the data instead of being decided a priori. GenoCNA also incorporates two important strategies for CNA studies. First, the effects of tissue contamination are explicitly modeled. Second, if SNP arrays are performed for both tumor and normal tissues of one individual, the genotype calls from normal tissue are used to study CNAs in tumor tissue. We evaluated genoCN by applications to 162 HapMap individuals and a brain tumor (glioblastoma) dataset and showed that our method can successfully identify both types of copy number differences and produce high-quality genotype calls.

Combining microarray-based genomic selection (MGS) with the Illumina Genome Analyzer platform to sequence diploid target regions

Novel methods of targeted sequencing of unique regions from complex eukaryotic genomes have generated a great deal of excitement, but critical demonstrations of these methods efficacy with respect to diploid genotype calling and experimental variation are lacking. To address this issue, we optimized microarray-based genomic selection (MGS) for use with the Illumina Genome Analyzer (IGA). A set of 202 fragments (304 kb total) contained within a 1.7 Mb genomic region on human chromosome X were MGS/IGA sequenced in ten female HapMap samples generating a total of 2.4 GB of DNA sequence. At a minimum coverage threshold of 5X, 93.9% of all bases and 94.9% of segregating sites were called, while 57.7% of bases (57.4% of segregating sites) were called at a 50X threshold. Data accuracy at known segregating sites was 98.9% at 5X coverage, rising to 99.6% at 50X coverage. Accuracy at homozygous sites was 98.7% at 5X sequence coverage and 99.5% at 50X coverage. Although accuracy at heterozygous sites was modestly lower, it was still over 92% at 5X coverage and increased to nearly 97% at 50X coverage. These data provide the first demonstration that MGS/IGA sequencing can generate the very high quality sequence data necessary for human genetics research. All sequences generated in this study have been deposited in NCBI Short Read Archive (http://www.ncbi.nlm.nih.gov/Traces/sra, Accession # SRA007913).

Copy-number variation: the end of the human genome?

Copy-number variation (CNV)--the presence of additional or missing segments of chromosomes in some individuals--has been found to be abundant in humans and adds another dimension of variation to the genome. Copy-number variants have already been associated with some diseases and disease susceptibilities and are likely to prove as significant as sequence polymorphisms in this respect. Changes in copy number of parts of the genome are known to be a feature of many cancers, and their analysis is expected to reveal genes involved in carcinogenesis. This article will present a somewhat biased and occasionally speculative discussion of the current and future significance of CNV with a particular focus on the potential of molecular copy-number counting in the analysis of small, damaged or heterogeneous samples.

Single nucleotide polymorphism arrays: a decade of biological, computational and technological advances

Array manufacturers originally designed single nucleotide polymorphism (SNP) arrays to genotype human DNA at thousands of SNPs across the genome simultaneously. In the decade since their initial development, the platform's applications have expanded to include the detection and characterization of copy number variation—whether somatic, inherited, or de novo—as well as loss-of-heterozygosity in cancer cells. The technology's impressive contributions to insights in population and molecular genetics have been fueled by advances in computational methodology, and indeed these insights and methodologies have spurred developments in the arrays themselves. This review describes the most commonly used SNP array platforms, surveys the computational methodologies used to convert the raw data into inferences at the DNA level, and details the broad range of applications. Although the long-term future of SNP arrays is unclear, cost considerations ensure their relevance for at least the next several years. Even as emerging technologies seem poised to take over for at least some applications, researchers working with these new sources of data are adopting the computational approaches originally developed for SNP arrays.

Forging links between human mental retardation-associated CNVs and mouse gene knockout models

Rare copy number variants (CNVs) are frequently associated with common neurological disorders such as mental retardation (MR; learning disability), autism, and schizophrenia. CNV screening in clinical practice is limited because pathological CNVs cannot be distinguished routinely from benign CNVs, and because genes underlying patients' phenotypes remain largely unknown. Here, we present a novel, statistically robust approach that forges links between 148 MR–associated CNVs and phenotypes from ∼5,000 mouse gene knockout experiments. These CNVs were found to be significantly enriched in two classes of genes, those whose mouse orthologues, when disrupted, result in either abnormal axon or dopaminergic neuron morphologies. Additional enrichments highlighted correspondences between relevant mouse phenotypes and secondary presentations such as brain abnormality, cleft palate, and seizures. The strength of these phenotype enrichments (>100% increases) greatly exceeded molecular annotations (<30% increases) and allowed the identification of 78 genes that may contribute to MR and associated phenotypes. This study is the first to demonstrate how the power of mouse knockout data can be systematically exploited to better understand genetically heterogeneous neurological disorders.

Mental retardation (MR; also known as learning disability) affects 1%–3% of people and is often associated with the presence of genomic copy number variations (CNVs) such as deletions and duplications. Most of these CNVs are rare and they often involve tens, sometimes hundreds, of genes. Pinpointing exactly which particular gene or genes are responsible for MR in an individual patient is therefore challenging and limits diagnostic applications. In this study, the functions of genes present within a large collection of MR–associated CNVs were investigated by comparing them to data from large-scale mouse knock-out experiments. We found that MR–associated CNVs contain greater than expected numbers of genes that give specific nervous system phenotypes when disrupted in the mouse. Not only does this study confirm that CNVs frequently cause MR, but it narrows down the list of genes whose changes lead to this disorder from thousands to several dozen. This reduced list of genes brings wide-spread genetic testing for MR one step closer. It also provides a better understanding of the biology behind MR that could, eventually, yield medical treatments.

Complex human chromosomal and genomic rearrangements

Copy number variation (CNV) is a major source of genetic variation among humans. In addition to existing as benign polymorphisms, CNVs can also convey clinical phenotypes, including genomic disorders, sporadic diseases and complex human traits. CNV results from genomic rearrangements that can represent simple deletion or duplication of a genomic segment, or be more complex. Complex chromosomal rearrangements (CCRs) have been known for some time but their mechanisms have remained elusive. Recent technology advances and high-resolution human genome analyses have revealed that complex genomic rearrangements can account for a large fraction of non-recurrent rearrangements at a given locus. Various mechanisms, most of which are DNA-replication-based, for example fork stalling and template switching (FoSTeS) and microhomology-mediated break-induced replication (MMBIR), have been proposed for generating such complex genomic rearrangements and are probably responsible for CCR.

Gene copy number and malaria biology

Alteration in gene copy number provides a simple way to change expression levels and alter phenotype. This was fully appreciated by bacteriologists more than 25 years ago, but the extent and implications of copy number polymorphism (CNP) have only recently become apparent in other organisms. New methods demonstrate the ubiquity of CNPs in eukaryotes and their medical importance in humans. CNP is also widespread in the Plasmodium falciparum genome and has an important and underappreciated role in determining phenotype. In this review, we summarize the distribution of CNP, its evolutionary dynamics within populations, its functional importance and its mode of evolution.

A novel method, digital genome scanning detects KRAS gene amplification in gastric cancers: involvement of overexpressed wild-type KRAS in downstream signaling and cancer cell growth

Background

Gastric cancer is the third most common malignancy affecting the general population worldwide. Aberrant activation of KRAS is a key factor in the development of many types of tumor, however, oncogenic mutations of KRAS are infrequent in gastric cancer. We have developed a novel quantitative method of analysis of DNA copy number, termed digital genome scanning (DGS), which is based on the enumeration of short restriction fragments, and does not involve PCR or hybridization. In the current study, we used DGS to survey copy-number alterations in gastric cancer cells.

Methods

DGS of gastric cancer cell lines was performed using the sequences of 5000 to 15000 restriction fragments. We screened 20 gastric cancer cell lines and 86 primary gastric tumors for KRAS amplification by quantitative PCR, and investigated KRAS amplification at the DNA, mRNA and protein levels by mutational analysis, real-time PCR, immunoblot analysis, GTP-RAS pull-down assay and immunohistochemical analysis. The effect of KRAS knock-down on the activation of p44/42 MAP kinase and AKT and on cell growth were examined by immunoblot and colorimetric assay, respectively.

Results

DGS analysis of the HSC45 gastric cancer cell line revealed the amplification of a 500-kb region on chromosome 12p12.1, which contains the KRAS gene locus. Amplification of the KRAS locus was detected in 15% (3/20) of gastric cancer cell lines (8–18-fold amplification) and 4.7% (4/86) of primary gastric tumors (8–50-fold amplification). KRAS mutations were identified in two of the three cell lines in which KRAS was amplified, but were not detected in any of the primary tumors. Overexpression of KRAS protein correlated directly with increased KRAS copy number. The level of GTP-bound KRAS was elevated following serum stimulation in cells with amplified wild-type KRAS, but not in cells with amplified mutant KRAS. Knock-down of KRAS in gastric cancer cells that carried amplified wild-type KRAS resulted in the inhibition of cell growth and suppression of p44/42 MAP kinase and AKT activity.

Conclusion

Our study highlights the utility of DGS for identification of copy-number alterations. Using DGS, we identified KRAS as a gene that is amplified in human gastric cancer. We demonstrated that gene amplification likely forms the molecular basis of overactivation of KRAS in gastric cancer. Additional studies using a larger cohort of gastric cancer specimens are required to determine the diagnostic and therapeutic implications of KRAS amplification and overexpression.

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

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

Validating, augmenting and refining genome-wide association signals

Studies using genome-wide platforms have yielded an unprecedented number of promising signals of association between genomic variants and human traits. This Review addresses the steps required to validate, augment and refine such signals to identify underlying causal variants for well-defined phenotypes. These steps include: large-scale exact replication across both similar and diverse populations; fine mapping and resequencing; determination of the most informative markers and multiple independent informative loci; incorporation of functional information; and improved phenotype mapping of the implicated genetic effects. Even in cases for which replication proves that an effect exists, confident localization of the causal variant often remains elusive.

Copy-number variation in BMPR2 is not associated with the pathogenesis of pulmonary arterial hypertension

Background

Copy-number variations (CNVs) are structural variations in the genome involving 1 kb to 3 mb of DNA. CNV has been reported within intron 1 of the BMPR2 gene. We propose that CNV could affect phenotype in familial and/or sporadic pulmonary arterial hypertension (PAH) by altering gene expression.

Methods

97 human DNA samples were obtained which included 24 patients with familial PAH, 18 obligate carriers (BMPR2 mutation positive), 20 sporadic PAH patients, and 35 controls. Two sets of primers were designed within the CNV, and two sets of control primers were designed outside the CNV. Quantitative PCR was performed to quantify genomic copies of CNV and control sequences.

Results

A CNV in BMPR2 was present in one African American negative control subject.

Conclusion

We conclude that the CNV in intron 1 in BMPR2 is unlikely to play a role in the pathogenesis of either familial or sporadic PAH.

Trial Registration

NIH NCT00091546.

Copy number variations and cancer

DNA copy number variations (CNVs) are an important component of genetic variation, affecting a greater fraction of the genome than single nucleotide polymorphisms (SNPs). The advent of high-resolution SNP arrays has made it possible to identify CNVs. Characterization of widespread constitutional (germline) CNVs has provided insight into their role in susceptibility to a wide spectrum of diseases, and somatic CNVs can be used to identify regions of the genome involved in disease phenotypes. The role of CNVs as risk factors for cancer is currently underappreciated. However, the genomic instability and structural dynamism that characterize cancer cells would seem to make this form of genetic variation particularly intriguing to study in cancer. Here, we provide a detailed overview of the current understanding of the CNVs that arise in the human genome and explore the emerging literature that reveals associations of both constitutional and somatic CNVs with a wide variety of human cancers.

Copy number variations and cancer

DNA copy number variations (CNVs) are an important component of genetic variation, affecting a greater fraction of the genome than single nucleotide polymorphisms (SNPs). The advent of high-resolution SNP arrays has made it possible to identify CNVs. Characterization of widespread constitutional (germline) CNVs has provided insight into their role in susceptibility to a wide spectrum of diseases, and somatic CNVs can be used to identify regions of the genome involved in disease phenotypes. The role of CNVs as risk factors for cancer is currently underappreciated. However, the genomic instability and structural dynamism that characterize cancer cells would seem to make this form of genetic variation particularly intriguing to study in cancer. Here, we provide a detailed overview of the current understanding of the CNVs that arise in the human genome and explore the emerging literature that reveals associations of both constitutional and somatic CNVs with a wide variety of human cancers.

Genetics of psychosis; insights from views across the genome

The major psychotic illnesses, schizophrenia and bipolar disorder (BD), are among the most heritable common disorders, but finding specific susceptibility genes for them has not been straightforward. The reasons are widely assumed to include lack of valid phenotypic definition, absence of good theories of pathophysiology for candidate gene studies, and the involvement of many genes, each making small contributions to population risk. Within the last year or so, a number of genome wide association (GWAS) of schizophrenia and BD have been published. These have produced stronger evidence for association to specific risk loci than have earlier studies, specifically for the zinc finger binding protein 804A (ZNF804A) locus in schizophrenia and for the calcium channel, voltage-dependent, L type, alpha 1C subunit (CACNA1C) and ankyrin 3, node of Ranvier (ANK3) loci in bipolar disorder. The ZNF804A and CACNA1C loci appear to influence risk for both disorders, a finding that supports the hypothesis that schizophrenia and BD are not aetiologically distinct. In the case of schizophrenia, a number of rare copy number variants have also been detected that have fairly large effect sizes on disease risk, and that additionally influence risk of autism, mental retardation, and other neurodevelopmental disorders. The existing findings point to some likely pathophysiological mechanisms but also challenge current concepts of disease classification. They also provide grounds for optimism that larger studies will reveal more about the origins of these disorders, although currently, very little of the genetic risk of either disorder is explained.

Common variation in KITLG and at 5q31.3 predisposes to testicular germ cell cancer

Testicular germ cell tumors (TGCT) have been expected to have a strong underlying genetic component. We conducted a genome-wide scan among 277 TGCT cases and 919 controls and found that seven markers at 12p22 within KITLG (c-KIT ligand) reached genome-wide significance (P < 5.0 x 10(-8) in discovery). In independent replication, TGCT risk was increased threefold per copy of the major allele at rs3782179 and rs4474514 (OR = 3.08, 95% CI = 2.29-4.13; OR = 3.07, 95% CI = 2.29-4.13, respectively). We found associations with rs4324715 and rs6897876 at 5q31.3 near SPRY4 (sprouty 4; P < 5.0 x 10(-6) in discovery). In independent replication, risk of TGCT was increased nearly 40% per copy of the major allele (OR = 1.37, 95% CI = 1.14-1.64; OR = 1.39, 95% CI = 1.16-1.66, respectively). All of the genotypes were associated with both seminoma and nonseminoma TGCT subtypes. These results demonstrate that common genetic variants affect TGCT risk and implicate KITLG and SPRY4 as genes involved in TGCT susceptibility.

Mobile elements create structural variation: analysis of a complete human genome

Structural variants (SVs) are common in the human genome. Because approximately half of the human genome consists of repetitive, transposable DNA sequences, it is plausible that these elements play an important role in generating SVs in humans. Sequencing of the diploid genome of one individual human (HuRef) affords us the opportunity to assess, for the first time, the impact of mobile elements on SVs in an individual in a thorough and unbiased fashion. In this study, we systematically evaluated more than 8000 SVs to identify mobile element-associated SVs as small as 100 bp and specific to the HuRef genome. Combining computational and experimental analyses, we identified and validated 706 mobile element insertion events (including Alu, L1, SVA elements, and nonclassical insertions), which added more than 305 kb of new DNA sequence to the HuRef genome compared with the Human Genome Project (HGP) reference sequence (hg18). We also identified 140 mobile element-associated deletions, which removed approximately 126 kb of sequence from the HuRef genome. Overall, approximately 10% of the HuRef-specific indels larger than 100 bp are caused by mobile element-associated events. More than one-third of the insertion/deletion events occurred in genic regions, and new Alu insertions occurred in exons of three human genes. Based on the number of insertions and the estimated time to the most recent common ancestor of HuRef and the HGP reference genome, we estimated the Alu, L1, and SVA retrotransposition rates to be one in 21 births, 212 births, and 916 births, respectively. This study presents the first comprehensive analysis of mobile element-related structural variants in the complete DNA sequence of an individual and demonstrates that mobile elements play an important role in generating inter-individual structural variation.

Linkage disequilibrium between two high-frequency deletion polymorphisms: implications for association studies involving the glutathione-S transferase (GST) genes

Copy number variations (CNVs) represent a large source of genetic variation in humans and have been increasingly studied for disease association. A deletion polymorphism of the gene encoding the cytosolic detoxification enzyme glutathione S-transferase theta 1 (GSTT1) has been extensively studied for cancer susceptibility (919 studies, from HuGE navigator, http://www.hugenavigator.net/). However, clear conclusions have not been reached. Since the GSTT1 gene is located within a genomic region of segmental duplications (SD), there may be a confounding effect from another, yet-uncharacterized CNV at the same locus. Here we describe a previously uncharacterized 38-kilo-base (kb) long deletion polymorphism of GSTT2B located within a 61-kb DNA inverted repeat. GSTT2B is a duplicated copy of GSTT2, the only paralogue of GSTT1 in humans. A newly developed PCR assay revealed that a microhomology-mediated breakpoint appears to be shared among individuals at high frequency. The GSTT2B deletion polymorphism was in strong linkage disequilibrium (LD) (D′ = 0.841) with the neighboring GSTT1 deletion polymorphism in the Caucasian population. Alleles harboring a single deletion were significantly overrepresented (p = 2.22×10⁻¹⁶), suggesting a selection against alleles with both deletions. The deletion alleles are almost certainly the derived ones, because the GSTT2B-GSTT2-GSTT1 genes were strictly retained in chimpanzees. Extremely low GSTT2 mRNA expression was associated with the GSTT2B deletion, suggesting an influence of the deletion on the flanking region and loss of GSTT2 function. Genome-wide LD analysis between deletion polymorphisms further points to the uniqueness of two deletions, because strong LD between deletion polymorphisms might be very rare in humans. These results show a complex genomic organization and unexpected biological functions of CNVs within segmental duplications and emphasize the importance of detailed structural characterization for disease association studies.

Common diseases such as cancer are caused by interactions between multiple genetic and environmental factors. Glutathione S-transferases (GST) are key enzymes in eliminating carcinogens and harmful macromolecules from cells. Based on the assumption that individuals who do not have a particular type of GST genes are susceptible to cancers, a number of studies have been conducted to find a link between GST genotypes and cancer. However such associations remain inconclusive to date. Because GST genes are clustered in repetitive, complex regions in the genome, other previously uncharacterized variations/polymorphisms may have had an impact on the data. We describe here such a genotype, a 37-kb deletion of GSTT2B gene that is found very frequently among humans. The neighboring GSTT2 gene expression is greatly impaired by the GSTT2B deletion, conferring a potentially null allele at GSTT2. The GSTT2B deletion is non-randomly associated with another high frequency deletion of the GSTT1 gene. Therefore, a detailed characterization of this complex region of the genome revealed unexpected genetic and biological interactions of large deletion polymorphisms; this is essential to consider in future disease association studies.

Genetic architecture of quantitative traits in mice, flies, and humans

We compare and contrast the genetic architecture of quantitative phenotypes in two genetically well-characterized model organisms, the laboratory mouse, Mus musculus, and the fruit fly, Drosophila melanogaster, with that found in our own species from recent successes in genome-wide association studies. We show that the current model of large numbers of loci, each of small effect, is true for all species examined, and that discrepancies can be largely explained by differences in the experimental designs used. We argue that the distribution of effect size of common variants is the same for all phenotypes regardless of species, and we discuss the importance of epistasis, pleiotropy, and gene by environment interactions. Despite substantial advances in mapping quantitative trait loci, the identification of the quantitative trait genes and ultimately the sequence variants has proved more difficult, so that our information on the molecular basis of quantitative variation remains limited. Nevertheless, available data indicate that many variants lie outside genes, presumably in regulatory regions of the genome, where they act by altering gene expression. As yet there are very few instances where homologous quantitative trait loci, or quantitative trait genes, have been identified in multiple species, but the availability of high-resolution mapping data will soon make it possible to test the degree of overlap between species.

A Bayesian segmentation approach to ascertain copy number variations at the population level

MOTIVATION

Efficient and accurate ascertainment of copy number variations (CNVs) at the population level is essential to understand the evolutionary process and population genetics, and to apply CNVs in population-based genome-wide association studies for complex human diseases. We propose a novel Bayesian segmentation approach to identify CNVs in a defined population of any size. It is computationally efficient and provides statistical evidence for the detected CNVs through the Bayes factor. This approach has the unique feature of carrying out segmentation and assigning copy number status simultaneously-a desirable property that current segmentation methods do not share.

RESULTS

In comparisons with popular two-step segmentation methods for a single individual using benchmark simulation studies, we find the new approach to perform competitively with respect to false discovery rate and sensitivity in breakpoint detection. In a simulation study of multiple samples with recurrent copy numbers, the new approach outperforms two leading single sample methods. We further demonstrate the effectiveness of our approach in population-level analysis of previously published HapMap data. We also apply our approach in studying population genetics of CNVs.

AVAILABILITY

R programs are available at http://www.mshri.on.ca/mitacs/software/SOFTWARE.HTML

Characterization of six human disease-associated inversion polymorphisms

The human genome is a highly dynamic structure that shows a wide range of genetic polymorphic variation. Unlike other types of structural variation, little is known about inversion variants within normal individuals because such events are typically balanced and are difficult to detect and analyze by standard molecular approaches. Using sequence-based, cytogenetic and genotyping approaches, we characterized six large inversion polymorphisms that map to regions associated with genomic disorders with complex segmental duplications mapping at the breakpoints. We developed a metaphase FISH-based assay to genotype inversions and analyzed the chromosomes of 27 individuals from three HapMap populations. In this subset, we find that these inversions are less frequent or absent in Asians when compared with European and Yoruban populations. Analyzing multiple individuals from outgroup species of great apes, we show that most of these large inversion polymorphisms are specific to the human lineage with two exceptions, 17q21.31 and 8p23 inversions, which are found to be similarly polymorphic in other great ape species and where the inverted allele represents the ancestral state. Investigating linkage disequilibrium relationships with genotyped SNPs, we provide evidence that most of these inversions appear to have arisen on at least two different haplotype backgrounds. In these cases, discovery and genotyping methods based on SNPs may be confounded and molecular cytogenetics remains the only method to genotype these inversions.

Human genetic variation and its contribution to complex traits

The last few years have seen extensive efforts to catalogue human genetic variation and correlate it with phenotypic differences. Most common SNPs have now been assessed in genome-wide studies for statistical associations with many complex traits, including many important common diseases. Although these studies have provided new biological insights, only a limited amount of the heritable component of any complex trait has been identified and it remains a challenge to elucidate the functional link between associated variants and phenotypic traits. Technological advances, such as the ability to detect rare and structural variants, and a clear understanding of the challenges in linking different types of variation with phenotype, will be essential for future progress.

Androgen receptor copy number variation and androgenetic alopecia: a case-control study

Background

The functional polymorphism that explains the established association of the androgen receptor (AR) with androgenetic alopecia (AGA) remains unidentified, but Copy Number Variation (CNV) might be relevant. CNV involves changes in copy number of large segments of DNA, leading to the altered dosage of gene regulators or genes themselves. Two recent reports indicate regions of CNV in and around AR, and these have not been studied in relation to AGA. The aim of this preliminary case-control study was to determine if AR CNV is associated with AGA, with the hypothesis that CNV is the functional AR variant contributing to this condition.

Methodology/Principal Findings

Multiplex Ligation-dependent Probe Amplification was used to screen for CNV in five AR exons and a conserved, non-coding region upstream of AR in 85 men carefully selected as cases and controls for maximal phenotypic contrast. There was no evidence of CNV in AR in any of the cases or controls, and thus no evidence of significant association between AGA and AR CNV.

Conclusions/Significance

The results suggest this form of genomic variation at the AR locus is unlikely to predispose to AGA.

Schizophrenia genetics: advancing on two fronts

Recent studies have supported the hypothesis that the high heritability of schizophrenia reflects a combination of relatively common alleles of small effect and some rare alleles with relatively large effects. Genome-wide association studies have identified at least one common allele of small effect at ZNF804a, which encodes a putative zinc finger binding protein, as well as possible roles for other loci. The genome-wide studies of at least one class of relatively uncommon variant, submicroscopic chromosomal abnormalities often referred to as copy number variations (CNVs), suggest that these confer high risk of schizophrenia. There is evidence both for an increased burden of CNVs in schizophrenia and that risk is conferred by specific large deletions at 1q21.1 and at 15q13.2 and by deletions of NRXN1 which encodes the synaptic scaffolding protein neurexin 1.

Microarray-Based Genomic DNA Profiling Technologies in Clinical Molecular Diagnostics

Background: Microarray-based genomic DNA profiling (MGDP) technologies are rapidly moving from translational research to clinical diagnostics and have revolutionized medical practices. Such technologies have shown great advantages in detecting genomic imbalances associated with genomic disorders and single-gene diseases.

Content: We discuss the development and applications of the major array platforms that are being used in both academic and commercial laboratories. Although no standardized platform is expected to emerge soon, comprehensive oligonucleotide microarray platforms—both comparative genomic hybridization arrays and genotyping hybrid arrays—are rapidly becoming the methods of choice for their demonstrated analytical validity in detecting genomic imbalances, for their flexibility in incorporating customized designs and updates, and for the advantage of being easily manufactured. Copy number variants (CNVs), the form of genomic deletions/duplications detected through MGDP, are a common etiology for a variety of clinical phenotypes. The widespread distribution of CNVs poses great challenges in interpretation. A broad survey of CNVs in the healthy population, combined with the data accumulated from the patient population in clinical laboratories, will provide a better understanding of the nature of CNVs and enhance the power of identifying genetic risk factors for medical conditions.

Summary: MGDP technologies for molecular diagnostics are still at an early stage but are rapidly evolving. We are in the process of extensive clinical validation and utility evaluation of different array designs and technical platforms. CNVs of currently unknown importance will be a rich source of novel discoveries.

Genome-wide association studies in type 2 diabetes

Despite numerous candidate gene and linkage studies, the field of type 2 diabetes (T2D) genetics had until recently succeeded in identifying few genuine disease-susceptibility loci. The advent of genome-wide association (GWA) scans has transformed the situation, leading to an expansion in the number of established, robustly replicating T2D loci to almost 20. These novel findings offer unique insights into the pathogenesis of T2D and in the main point toward the etiologic importance of disorders of beta-cell development and function. All associated variants have common allele frequencies in the discovery populations, and exert modest to small effects on the risk of disease, characteristics that limit their prognostic and diagnostic potential. However, ongoing studies focusing on the role of copy number variation and targeting low-frequency polymorphisms should identify additional T2D susceptibility loci, some of which may have larger effect sizes and offer better individual prediction of disease risk.

Singleton deletions throughout the genome increase risk of bipolar disorder

An overall burden of rare structural genomic variants has not been reported in bipolar disorder (BD), although there have been reports of cases with microduplication and microdeletion. Here, we present a genome-wide copy number variant (CNV) survey of 1001 cases and 1034 controls using the Affymetrix single nucleotide polymorphism (SNP) 6.0 SNP and CNV platform. Singleton deletions (deletions that appear only once in the dataset) more than 100 kb in length are present in 16.2% of BD cases in contrast to 12.3% of controls (permutation P=0.007). This effect was more pronounced for age at onset of mania <or=18 years old. Our results strongly suggest that BD can result from the effects of multiple rare structural variants.

Molecular genetics of autism

The increasing autism incidence estimates are generating strong interest in identifying its salient risk factors. Recognition of the importance of genes in this and other disorders has promulgated the development of valuable research tools. As this review indicates, application of these tools paints a portrait of a disorder that is more complex than anticipated.

SLC45A3-ELK4 is a novel and frequent erythroblast transformation-specific fusion transcript in prostate cancer

Chromosomal rearrangements account for all erythroblast transformation-specific (ETS) family member gene fusions that have been reported in prostate cancer and have clinical, diagnostic, and prognostic implications. Androgen-regulated genes account for the majority of the 5' genomic regulatory promoter elements fused with ETS genes. TMPRSS2-ERG, TMPRSS2-ETV1, and SLC45A3-ERG rearrangements account for roughly 90% of ETS fusion prostate cancer. ELK4, another ETS family member, is androgen regulated, involved in promoting cell growth, and highly expressed in a subset of prostate cancer, yet the mechanism of ELK4 overexpression is unknown. In this study, we identified a novel ETS family fusion transcript, SLC45A3-ELK4, and found it to be expressed in both benign prostate tissue and prostate cancer. We found high levels of SLC45A3-ELK4 mRNA restricted to a subset of prostate cancer samples. SLC45A3-ELK4 transcript can be detected at high levels in urine samples from men at risk for prostate cancer. Characterization of the fusion mRNA revealed a major variant in which SLC45A3 exon 1 is fused to ELK4 exon 2. Based on quantitative PCR analyses of DNA, unlike other ETS fusions described in prostate cancer, the expression of SLC45A3-ELK4 mRNA is not exclusive to cases harboring a chromosomal rearrangement. Treatment of LNCaP cancer cells with a synthetic androgen (R1881) revealed that SLC45A3-ELK4, and not endogenous ELK4, mRNA expression is androgen regulated. Altogether, our findings show that SLC45A3-ELK4 mRNA expression is heterogeneous, highly induced in a subset of prostate cancers, androgen regulated, and most commonly occurs through a mechanism other than chromosomal rearrangement (e.g., trans-splicing).

Joint estimation of copy number variation and reference intensities on multiple DNA arrays using GADA

MOTIVATION

The complexity of a large number of recently discovered copy number polymorphisms is much higher than initially thought, thus making it more difficult to detect them in the presence of significant measurement noise. In this scenario, separate normalization and segmentation is prone to lead to many false detections of changes in copy number. New approaches capable of jointly modeling the copy number and the non-copy number (noise) hybridization effects across multiple samples will potentially lead to more accurate results.

METHODS

In this article, the genome alteration detection analysis (GADA) approach introduced in our previous work is extended to a multiple sample model. The copy number component is independent for each sample and uses a sparse Bayesian prior, while the reference hybridization level is not necessarily sparse but identical on all samples. The expectation maximization (EM) algorithm used to fit the model iteratively determines whether the observed hybridization levels are more likely due to a copy number variation or to a shared hybridization bias.

RESULTS

The new proposed approach is compared with the currently used strategy of separate normalization followed by independent segmentation of each array. Real microarray data obtained from HapMap samples are randomly partitioned to create different reference sets. Using the new approach, copy number and reference intensity estimates are significantly less variable if the reference set changes; and a higher consistency on copy numbers detected within HapMap family trios is obtained. Finally, the running time to fit the model grows linearly in the number samples and probes.

AVAILABILITY

http://biron.usc.edu/~piquereg/GADA.

Palindromic gene amplification--an evolutionarily conserved role for DNA inverted repeats in the genome

The clinical importance of gene amplification in the diagnosis and treatment of cancer has been widely recognized, as it is often evident in advanced stages of diseases. However, our knowledge of the underlying mechanisms is still limited. Gene amplification is an essential process in several organisms including the ciliate Tetrahymena thermophila, in which the initiating mechanism has been well characterized. Lessons from such simple eukaryotes may provide useful information regarding how gene amplification occurs in tumour cells.

Genome-wide association of early-onset myocardial infarction with single nucleotide polymorphisms and copy number variants

We conducted a genome-wide association study testing single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) for association with early-onset myocardial infarction in 2,967 cases and 3,075 controls. We carried out replication in an independent sample with an effective sample size of up to 19,492. SNPs at nine loci reached genome-wide significance: three are newly identified (21q22 near MRPS6-SLC5A3-KCNE2, 6p24 in PHACTR1 and 2q33 in WDR12) and six replicated prior observations (9p21, 1p13 near CELSR2-PSRC1-SORT1, 10q11 near CXCL12, 1q41 in MIA3, 19p13 near LDLR and 1p32 near PCSK9). We tested 554 common copy number polymorphisms (>1% allele frequency) and none met the pre-specified threshold for replication (P < 10(-3)). We identified 8,065 rare CNVs but did not detect a greater CNV burden in cases compared to controls, in genes compared to the genome as a whole, or at any individual locus. SNPs at nine loci were reproducibly associated with myocardial infarction, but tests of common and rare CNVs failed to identify additional associations with myocardial infarction risk.

Ultrasome: efficient aberration caller for copy number studies of ultra-high resolution

MOTIVATION

Multimillion-probe microarrays allow detection of gains and losses of chromosomal material at unprecedented resolution. However, the data generated by these arrays are several-fold larger than data from earlier platforms, creating a need for efficient analysis tools that scale robustly with data size.

RESULTS

We developed a new aberration caller, Ultrasome, that delineates genomic changes-of-interest with dramatically improved efficiency. Ultrasome shows near-linear computational complexity and processes latest generation copy number arrays about 10,000 times faster than standard methods with preserved analytic accuracy.

Copy number variation in the human genome and its implication in autoimmunity

The causes of autoimmune disease remain poorly defined. However, it is known that genetic factors contribute to disease susceptibility. Hitherto, studies have focused upon single nucleotide polymorphisms as both tools for mapping and as probable causal variants. Recent studies, using genome-wide analytical techniques, have revealed that, in the genome, segments of DNA ranging in size from kilobases to megabases can vary in copy number. These changes of DNA copy number represent an important element of genomic polymorphism in humans and in other species and may therefore make a substantial contribution to phenotypic variation and population differentiation. Furthermore, copy number variation (CNV) in genomic regions harbouring dosage-sensitive genes may cause or predispose to a variety of human genetic diseases. Several recent studies have reported an association between CNV and autoimmunity in humans such as systemic lupus, psoriasis, Crohn's disease, rheumatoid arthritis and type 1 diabetes. The use of novel analytical techniques facilitates the study of complex human genomic structures such as CNV, and allows new susceptibility loci for autoimmunity to be found that are not readily mappable by single nucleotide polymorphism-based association analyses alone.

A practical case-control association test for detecting a susceptibility allele at a copy number variation locus

The association between a copy number variant (CNV) and susceptibility to disease has drawn much attention. In this study, a case-control association test for a CNV locus with multiple alleles is proposed for detecting a single CNV allele associated with a disease. In the association test, CNV allele frequencies are estimated for cases and controls separately using an expectation-maximization (EM) algorithm, and the chi(2) values are calculated for each CNV allele to compare the estimated frequency between them. A permutation procedure is used to obtain an empirical P-value for each CNV allele and for controlling a global type I error rate. The statistical power of the present association test was evaluated by a computer simulation analysis with several parameter settings. The results revealed that the statistical power was markedly different among CNV alleles with different copy numbers, and a higher power could be achieved for a susceptible allele with the lowest or highest copy number in comparison with those with intermediate copy numbers.

Jean PL, Giegling I, Hartmann AM, Möller HJ, Ruppert A, Fraser G, Crombie C, Middleton LT, St. Clair D, Roses AD, Muglia P, Francks C, Rujescu D, Meltzer HY, Goldstein DB. A genome-wide investigation of SNPs and CNVs in schizophrenia

We report a genome-wide assessment of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) in schizophrenia. We investigated SNPs using 871 patients and 863 controls, following up the top hits in four independent cohorts comprising 1,460 patients and 12,995 controls, all of European origin. We found no genome-wide significant associations, nor could we provide support for any previously reported candidate gene or genome-wide associations. We went on to examine CNVs using a subset of 1,013 cases and 1,084 controls of European ancestry, and a further set of 60 cases and 64 controls of African ancestry. We found that eight cases and zero controls carried deletions greater than 2 Mb, of which two, at 8p22 and 16p13.11-p12.4, are newly reported here. A further evaluation of 1,378 controls identified no deletions greater than 2 Mb, suggesting a high prior probability of disease involvement when such deletions are observed in cases. We also provide further evidence for some smaller, previously reported, schizophrenia-associated CNVs, such as those in NRXN1 and APBA2. We could not provide strong support for the hypothesis that schizophrenia patients have a significantly greater "load" of large (>100 kb), rare CNVs, nor could we find common CNVs that associate with schizophrenia. Finally, we did not provide support for the suggestion that schizophrenia-associated CNVs may preferentially disrupt genes in neurodevelopmental pathways. Collectively, these analyses provide the first integrated study of SNPs and CNVs in schizophrenia and support the emerging view that rare deleterious variants may be more important in schizophrenia predisposition than common polymorphisms. While our analyses do not suggest that implicated CNVs impinge on particular key pathways, we do support the contribution of specific genomic regions in schizophrenia, presumably due to recurrent mutation. On balance, these data suggest that very few schizophrenia patients share identical genomic causation, potentially complicating efforts to personalize treatment regimens.

Population analysis of large copy number variants and hotspots of human genetic disease

Copy number variants (CNVs) contribute to human genetic and phenotypic diversity. However, the distribution of larger CNVs in the general population remains largely unexplored. We identify large variants in approximately 2500 individuals by using Illumina SNP data, with an emphasis on "hotspots" prone to recurrent mutations. We find variants larger than 500 kb in 5%-10% of individuals and variants greater than 1 Mb in 1%-2%. In contrast to previous studies, we find limited evidence for stratification of CNVs in geographically distinct human populations. Importantly, our sample size permits a robust distinction between truly rare and polymorphic but low-frequency copy number variation. We find that a significant fraction of individual CNVs larger than 100 kb are rare and that both gene density and size are strongly anticorrelated with allele frequency. Thus, although large CNVs commonly exist in normal individuals, which suggests that size alone can not be used as a predictor of pathogenicity, such variation is generally deleterious. Considering these observations, we combine our data with published CNVs from more than 12,000 individuals contrasting control and neurological disease collections. This analysis identifies known disease loci and highlights additional CNVs (e.g., 3q29, 16p12, and 15q25.2) for further investigation. This study provides one of the first analyses of large, rare (0.1%-1%) CNVs in the general population, with insights relevant to future analyses of genetic disease.

On the level: IRGM gene function is all about expression

Crohn disease is a complex, multigenic, chronic inflammatory bowel disease of uncertain etiology. Recent advances in genetics, including high-throughput single-nucleotide polymorphism typing platforms and deep sequencing technologies have begun to shed light upon disease predisposition and pathogenesis. Autophagy is emerging as a key player in both innate and adaptive immunity, as well as tissue homeostasis and development in the gut. Here we describe our recent studies into the Crohn disease-associated Immunity-Related GTPase family, M (IRGM) gene and our discovery of a large risk-conferring upstream deletion. We discuss the effects of this deletion upon expression levels of IRGM alleles and how tissue-specific expression might be affected by the promoter polymorphism. In addition, we comment upon the potential roles of IRGM in autophagy of intracellular pathogens, and the challenges ahead for further elucidating IRGM function.

New findings from genetic association studies of schizophrenia

In the past 20 years, association studies of schizophrenia have evolved from analyses in lesser than 100 subjects of one or two markers in candidate genes to systematic analyses of association at a genome-wide level in samples of thousands of subjects. During this process, much of the emergent literature has been difficult to interpret and definitive findings that have met with universal acceptance have been elusive, largely because studies have been underpowered for such conclusions to be drawn. Nevertheless, in the course of the past few years, a few promising candidate genes have been reported for which the evidence is positive across multiple studies, and more recently, genome-wide association studies have yielded findings of a compelling nature. It is clear that genetic studies in schizophrenia have borne fruit, a process that can be expected to accelerate in the next few years, and that these findings are providing new avenues for research into the pathophysiology of this poorly understood disorder.

Schizophrenia genetics: new insights from new approaches

INTRODUCTION

Schizophrenia is a debilitating psychiatric disorder that imposes a considerable burden on sufferers, their families and society. The prominent involvement of genes, combined with the complexity and relative inaccessibility of the brain has led many to suggest that the identification of specific risk loci offers the best chance of understanding pathogenesis.

SOURCES OF DATA

Recent genome-wide association studies (GWAS) and copy number variation (CNV) publications have been included in this review along with key papers from the fields of schizophrenia, functional psychoses and complex disease mapping.

AREAS OF AGREEMENT

Recent GWAS have now shown that both common alleles of small effect and rare alleles of moderate to large effect contribute to the high heritability of schizophrenia.

AREAS OF CONTROVERSY

It is well known that many schizophrenic patients suffer symptoms seen in patients with bipolar disease and vice versa. There is now considerable interest in using aetiologically relevant risk factors, including genes, to explore the validity of the contemporary system of classification.

GROWING POINTS

Rare CNVs have been shown to play a role in at least some cases of schizophrenia and it is highly predictable that this figure will rise with the use of technologies with higher resolution or that are better designed to assay common CNVs reliably.

AREAS TIMELY FOR DEVELOPING RESEARCH

The findings with common alleles thus far point to overlap in the genetic risk for schizophrenia and bipolar disorder, while the specific CNVs implicated in schizophrenia also increase susceptibility to a range of developmental disorders, including autism, mental retardation, attention deficit-hyperactivity disorder (ADHD) and epilepsy.

Copy number variation in human health, disease, and evolution

Copy number variation (CNV) is a source of genetic diversity in humans. Numerous CNVs are being identified with various genome analysis platforms, including array comparative genomic hybridization (aCGH), single nucleotide polymorphism (SNP) genotyping platforms, and next-generation sequencing. CNV formation occurs by both recombination-based and replication-based mechanisms and de novo locus-specific mutation rates appear much higher for CNVs than for SNPs. By various molecular mechanisms, including gene dosage, gene disruption, gene fusion, position effects, etc., CNVs can cause Mendelian or sporadic traits, or be associated with complex diseases. However, CNV can also represent benign polymorphic variants. CNVs, especially gene duplication and exon shuffling, can be a predominant mechanism driving gene and genome evolution.

Six new loci associated with body mass index highlight a neuronal influence on body weight regulation

Common variants at only two loci, FTO and MC4R, have been reproducibly associated with body mass index (BMI) in humans. To identify additional loci, we conducted meta-analysis of 15 genome-wide association studies for BMI (n > 32,000) and followed up top signals in 14 additional cohorts (n > 59,000). We strongly confirm FTO and MC4R and identify six additional loci (P < 5 x 10(-8)): TMEM18, KCTD15, GNPDA2, SH2B1, MTCH2 and NEGR1 (where a 45-kb deletion polymorphism is a candidate causal variant). Several of the likely causal genes are highly expressed or known to act in the central nervous system (CNS), emphasizing, as in rare monogenic forms of obesity, the role of the CNS in predisposition to obesity.

In silico investigations on functional and haplotype tag SNPs associated with congenital long QT syndromes (LQTSs)

Single-nucleotide polymorphisms (SNPs) play a major role in the understanding of the genetic basis of many complex human diseases. It is still a major challenge to identify the functional SNPs in disease-related genes. In this review, the genetic variation that can alter the expression and the function of the genes, namely KCNQ1, KCNH2, SCN5A, KCNE1 and KCNE2, with the potential role for the development of congenital long QT syndrome (LQTS) was analyzed. Of the total of 3,309 SNPs in all five genes, 27 non-synonymous SNPs (nsSNPs) in the coding region and 44 SNPs in the 5' and 3' un-translated regions (UTR) were identified as functionally significant. SIFT and PolyPhen programs were used to analyze the nsSNPs and FastSNP; UTR scan programs were used to compute SNPs in the 5' and 3' untranslated regions. Of the five selected genes, KCNQ1 has the highest number of 26 haplotype blocks and 6 tag SNPs with a complete linkage disequilibrium value. The gene SCN5A has ten haplotype blocks and four tag SNPs. Both KCNE1 and KCNE2 genes have only one haplotype block and four tag SNPs. Four haplotype blocks and two tag SNPs were obtained for KCNH2 gene. Also, this review reports the copy number variations (CNVs), expressed sequence tags (ESTs) and genome survey sequences (GSS) of the selected genes. These computational methods are in good agreement with experimental works reported earlier concerning LQTS.