Integrated genotype calling and association analysis of SNPs, common copy number polymorphisms and rare CNVs.
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ABSTRACT:
SUBMITTER: Korn JM
PROVIDER: S-EPMC2756534 | biostudies-literature | 2008 Oct
REPOSITORIES: biostudies-literature
Publications
Integrated genotype calling and association analysis of SNPs, common copy number polymorphisms and rare CNVs.
Korn Joshua M JM Kuruvilla Finny G FG McCarroll Steven A SA Wysoker Alec A Nemesh James J Cawley Simon S Hubbell Earl E Veitch Jim J Collins Patrick J PJ Darvishi Katayoon K Lee Charles C Nizzari Marcia M MM Gabriel Stacey B SB Purcell Shaun S Daly Mark J MJ Altshuler David D
Nature genetics 20080907 10
Accurate and complete measurement of single nucleotide (SNP) and copy number (CNV) variants, both common and rare, will be required to understand the role of genetic variation in disease. We present Birdsuite, a four-stage analytical framework instantiated in software for deriving integrated and mutually consistent copy number and SNP genotypes. The method sequentially assigns copy number across regions of common copy number polymorphisms (CNPs), calls genotypes of SNPs, identifies rare CNVs via ...[more]
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Project description:ObjectiveBoth rare copy number variants (CNVs) and common single-nucleotide polymorphisms (SNPs) contribute to liability to schizophrenia, but their etiological relationship has not been fully elucidated. The authors evaluated an additive model whereby risk of schizophrenia requires less contribution from common SNPs in the presence of a rare CNV, and tested for interactions.MethodGenetic data from 21,094 case subjects with schizophrenia and 20,227 control subjects from the Psychiatric Genomics Consortium were examined. Three classes of rare CNVs were assessed: CNVs previously associated with schizophrenia, CNVs with large deletions ≥500 kb, and total CNV burden. The mean polygenic risk scores (PRSs) between study subjects with and without rare CNVs were compared, and joint effects of PRS and CNVs on schizophrenia liability were modeled by using logistic regression.ResultsSchizophrenia case subjects carrying risk CNVs had a lower polygenic risk than case subjects without risk CNVs but a higher risk than control subjects. For case subjects carrying known risk CNVs, the PRS was diminished in proportion to the effect size of the CNV. The strongly associated 22q11.2 deletion required little added PRS to produce schizophrenia. Large deletions and increased CNV burden were also associated with lower polygenic risk in schizophrenia case subjects but not in control subjects or after removal of known risk CNV carriers.ConclusionsThe authors found evidence for interactive effects of PRS and previously associated CNVs for risk for schizophrenia, and the results for large deletions and total CNV burden support an additive model. These findings offer insights into the genetic architecture of schizophrenia by illuminating how different established genetic risk factors act and interact to influence liability to schizophrenia.
| S-EPMC6408268 | biostudies-literature
Project description:MotivationSeveral algorithms exist for detecting copy number variants (CNVs) from human exome sequencing read depth, but previous tools have not been well suited for large population studies on the order of tens or hundreds of thousands of exomes. Their limitations include being difficult to integrate into automated variant-calling pipelines and being ill-suited for detecting common variants. To address these issues, we developed a new algorithm--Copy number estimation using Lattice-Aligned Mixture Models (CLAMMS)--which is highly scalable and suitable for detecting CNVs across the whole allele frequency spectrum.ResultsIn this note, we summarize the methods and intended use-case of CLAMMS, compare it to previous algorithms and briefly describe results of validation experiments. We evaluate the adherence of CNV calls from CLAMMS and four other algorithms to Mendelian inheritance patterns on a pedigree; we compare calls from CLAMMS and other algorithms to calls from SNP genotyping arrays for a set of 3164 samples; and we use TaqMan quantitative polymerase chain reaction to validate CNVs predicted by CLAMMS at 39 loci (95% of rare variants validate; across 19 common variant loci, the mean precision and recall are 99% and 94%, respectively). In the Supplementary Materials (available at the CLAMMS Github repository), we present our methods and validation results in greater detail.Availability and implementationhttps://github.com/rgcgithub/clamms (implemented in C).Contactjeffrey.reid@regeneron.comSupplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC4681995 | biostudies-literature
Project description:With the recent advance in genome-wide association studies (GWAS), disease-associated single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) have been extensively reported. Accordingly, the issue of incorrect identification of recombination events that can induce the distortion of multi-allelic or hemizygous variants has received more attention. However, the potential distorted calculation bias or significance of a detected association in a GWAS due to the coexistence of CNVs and SNPs in the same genomic region may remain under-recognized. Here we performed the association study within a congenital scoliosis (CS) cohort whose genetic etiology was recently elucidated as a compound inheritance model, including mostly one rare variant deletion CNV null allele and one common variant non-coding hypomorphic haplotype of the TBX6 gene. We demonstrated that the existence of a deletion in TBX6 led to an overestimation of the contribution of the SNPs on the hypomorphic allele. Furthermore, we generalized a model to explain the calculation bias, or distorted significance calculation for an association study, that can be 'induced' by CNVs at a locus. Meanwhile, overlapping between the disease-associated SNPs from published GWAS and common CNVs (overlap 10%) and pathogenic/likely pathogenic CNVs (overlap 99.69%) was significantly higher than the random distribution (p?<?1?×?10-6 and p?=?0.034, respectively), indicating that such co-existence of CNV and SNV alleles might generally influence data interpretation and potential outcomes of a GWAS. We also verified and assessed the influence of colocalizing CNVs to the detection sensitivity of disease-associated SNP variant alleles in another adolescent idiopathic scoliosis (AIS) genome-wide association study. We proposed that detecting co-existent CNVs when evaluating the association signals between SNPs and disease traits could improve genetic model analyses and better integrate GWAS with robust Mendelian principles.
| S-EPMC6200315 | biostudies-literature
Project description:BACKGROUND: Recently, the discovery of copy number variation (CNV) led researchers to think that there are more variations of genomic DNA than initially believed. Moreover, a certain CNV region has been found to be associated with the onset of diseases. Therefore, CNV is now known as an important genomic variation in biological mechanisms. However, most CNV studies have only involved the human genome. The study of CNV involving other animals, including cattle, is severely lacking. RESULTS: In our study of cattle, we used Illumina BovineSNP50 BeadChip (54,001 markers) to obtain each marker's signal intensity (Log R ratio) and allelic intensity (B allele frequency), which led to our discovery of 855 bovine CNVs from 265 cows. For these animals, the average number of CNVs was 3.2, average size was 149.8 kb, and median size was 171.5 kb. Taking into consideration some overlapping regions among the identified bovine CNVs, 368 unique CNV regions were detected. Among them, there were 76 common CNVRs with > 1% CNV frequency. Together, these CNVRs contained 538 genes. Heritability errors of 156 bovine pedigrees and comparative pairwise analyses were analyzed to detect 448 common deletion polymorphisms. Identified variations in this study were successfully validated using visual examination of the genoplot image, Mendelian inconsistency, another CNV identification program, and quantitative PCR. CONCLUSIONS: In this study, we describe a map of bovine CNVs and provide important resources for future bovine genome research. This result will contribute to animal breeding and protection from diseases with the aid of genomic information.
| S-EPMC2859865 | biostudies-other
Project description:BackgroundCopy-number variations (CNVs) have been associated with rare and debilitating genomic disorders (GDs) but their impact on health later in life in the general population remains poorly described.MethodsAssessing four modes of CNV action, we performed genome-wide association scans (GWASs) between the copy-number of CNV-proxy probes and 60 curated ICD-10 based clinical diagnoses in 331,522 unrelated white British UK Biobank (UKBB) participants with replication in the Estonian Biobank.ResultsWe identified 73 signals involving 40 diseases, all of which indicating that CNVs increased disease risk and caused earlier onset. We estimated that 16% of these associations are indirect, acting by increasing body mass index (BMI). Signals mapped to 45 unique, non-overlapping regions, nine of which being linked to known GDs. Number and identity of genes affected by CNVs modulated their pathogenicity, with many associations being supported by colocalization with both common and rare single-nucleotide variant association signals. Dissection of association signals provided insights into the epidemiology of known gene-disease pairs (e.g., deletions in BRCA1 and LDLR increased risk for ovarian cancer and ischemic heart disease, respectively), clarified dosage mechanisms of action (e.g., both increased and decreased dosage of 17q12 impacted renal health), and identified putative causal genes (e.g., ABCC6 for kidney stones). Characterization of the pleiotropic pathological consequences of recurrent CNVs at 15q13, 16p13.11, 16p12.2, and 22q11.2 in adulthood indicated variable expressivity of these regions and the involvement of multiple genes. Finally, we show that while the total burden of rare CNVs-and especially deletions-strongly associated with disease risk, it only accounted for ~ 0.02% of the UKBB disease burden. These associations are mainly driven by CNVs at known GD CNV regions, whose pleiotropic effect on common diseases was broader than anticipated by our CNV-GWAS.ConclusionsOur results shed light on the prominent role of rare CNVs in determining common disease susceptibility within the general population and provide actionable insights for anticipating later-onset comorbidities in carriers of recurrent CNVs.
| S-EPMC10773105 | biostudies-literature
Project description:BackgroundCopy number variations (CNVs) are deletions, insertions, duplications, and more complex variations ranging from 1 kb to sub-microscopic sizes. Recent advances in array technologies have enabled researchers to identify a number of CNVs from normal individuals. However, the identification of new CNVs has not yet reached saturation, and more CNVs from diverse populations remain to be discovered.ResultsWe identified 65 copy number variation regions (CNVRs) in 116 normal Korean individuals by analyzing Affymetrix 250 K Nsp whole-genome SNP data. Ten of these CNVRs were novel and not present in the Database of Genomic Variants (DGV). To increase the specificity of CNV detection, three algorithms, CNAG, dChip and GEMCA, were applied to the data set, and only those regions recognized at least by two algorithms were identified as CNVs. Most CNVRs identified in the Korean population were rare (<1%), occurring just once among the 116 individuals. When CNVs from the Korean population were compared with CNVs from the three HapMap ethnic groups, African, European, and Asian; our Korean population showed the highest degree of overlap with the Asian population, as expected. However, the overlap was less than 40%, implying that more CNVs remain to be discovered from the Asian population as well as from other populations. Genes in the novel CNVRs from the Korean population were enriched for genes involved in regulation and development processes.ConclusionCNVs are recently-recognized structural variations among individuals, and more CNVs need to be identified from diverse populations. Until now, CNVs from Asian populations have been studied less than those from European or American populations. In this regard, our study of CNVs from the Korean population will contribute to the full cataloguing of structural variation among diverse human populations.
| S-EPMC2576253 | biostudies-literature
Project description:Human growth has an estimated heritability of about 80%-90%. Nevertheless, the underlying cause of shortness of stature remains unknown in the majority of individuals. Genome-wide association studies (GWAS) showed that both common single nucleotide polymorphisms and copy number variants (CNVs) contribute to height variation under a polygenic model, although explaining only a small fraction of overall genetic variability in the general population. Under the hypothesis that severe forms of growth retardation might also be caused by major gene effects, we searched for rare CNVs in 200 families, 92 sporadic and 108 familial, with idiopathic short stature compared to 820 control individuals. Although similar in number, patients had overall significantly larger CNVs (p-value<1×10(-7)). In a gene-based analysis of all non-polymorphic CNVs>50 kb for gene function, tissue expression, and murine knock-out phenotypes, we identified 10 duplications and 10 deletions ranging in size from 109 kb to 14 Mb, of which 7 were de novo (p<0.03) and 13 inherited from the likewise affected parent but absent in controls. Patients with these likely disease causing 20 CNVs were smaller than the remaining group (p<0.01). Eleven (55%) of these CNVs either overlapped with known microaberration syndromes associated with short stature or contained GWAS loci for height. Haploinsufficiency (HI) score and further expression profiling suggested dosage sensitivity of major growth-related genes at these loci. Overall 10% of patients carried a disease-causing CNV indicating that, like in neurodevelopmental disorders, rare CNVs are a frequent cause of severe growth retardation.
| S-EPMC3597495 | biostudies-literature
Project description:BACKGROUND: The Li-Fraumeni syndrome (LFS), an inherited rare cancer predisposition syndrome characterized by a variety of early-onset tumors, is caused by different highly penetrant germline mutations in the TP53 gene; each separate mutation has dissimilar functional and phenotypic effects, which partially clarifies the reported heterogeneity between LFS families. Increases in copy number variation (CNV) have been reported in TP53 mutated individuals, and are also postulated to contribute to LFS phenotypic variability. The Brazilian p.R337H TP53 mutation has particular functional and regulatory properties that differ from most other common LFS TP53 mutations, by conferring a strikingly milder phenotype. METHODS: We compared the CNV profiles of controls, and LFS individuals carrying either p.R337H or DNA binding domain (DBD) TP53 mutations by high resolution array-CGH. RESULTS: Although we did not find any significant difference in the frequency of CNVs between LFS patients and controls, our data indicated an increased proportion of rare CNVs per genome in patients carrying DBD mutations compared to both controls (p=0.0002***) and p.R337H (0.0156*) mutants. CONCLUSIONS: The larger accumulation of rare CNVs in DBD mutants may contribute to the reported anticipation and severity of the syndrome; likewise the fact that p.R337H individuals do not present the same magnitude of rare CNV accumulation may also explain the maintenance of this mutation at relatively high frequency in some populations.
| S-EPMC3558401 | biostudies-literature
Project description:Children with autism have an elevated frequency of large, rare copy number variants (CNVs). However, the global load of deletions or duplications, per se, and their size, location and relationship to clinical manifestations of autism have not been documented. We examined CNV data from 516 individuals with autism or typical development from the population-based Childhood Autism Risks from Genetics and Environment (CHARGE) study. We interrogated 120 regions flanked by segmental duplications (genomic hotspots) for events >50 kbp and the entire genomic backbone for variants >300 kbp using a custom targeted DNA microarray. This analysis was complemented by a separate study of five highly dynamic hotspots associated with autism or developmental delay syndromes, using a finely tiled array platform (>1 kbp) in 142 children matched for gender and ethnicity. In both studies, a significant increase in the number of base pairs of duplication, but not deletion, was associated with autism. Significantly elevated levels of CNV load remained after the removal of rare and likely pathogenic events. Further, the entire CNV load detected with the finely tiled array was contributed by common variants. The impact of this variation was assessed by examining the correlation of clinical outcomes with CNV load. The level of personal and social skills, measured by Vineland Adaptive Behavior Scales, negatively correlated (Spearman's r = -0.13, P = 0.034) with the duplication CNV load for the affected children; the strongest association was found for communication (P = 0.048) and socialization (P = 0.022) scores. We propose that CNV load, predominantly increased genomic base pairs of duplication, predisposes to autism.
| S-EPMC3690969 | biostudies-literature
Project description: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.
| S-EPMC2935461 | biostudies-literature