"GenotypeColour™": colour visualisation of SNPs and CNVs

<p>Abstract</p> <p>Background</p> <p>The volume of data available on genetic variations has increased considerably with the recent development of high-density, single-nucleotide polymorphism (SNP) arrays. Several software programs have been developed to assist researchers in the analysis of this huge amount of data, but few can rely upon a whole genome variability visualisation system that could help data interpretation.</p> <p>Results</p> <p>We have developed <it>GenotypeColour™ </it>as a rapid user-friendly tool able to upload, visualise and compare the huge amounts of data produced by Affymetrix Human Mapping GeneChips without losing the overall view of the data.</p> <p>Some features of <it>GenotypeColour™ </it>include visualising the entire genome variability in a single screenshot for one or more samples, the simultaneous display of the genotype and Copy Number state for thousands of SNPs, and the comparison of large amounts of samples by producing "consensus" images displaying regions of complete or partial identity. The software is also useful for genotype analysis of trios and to show regions of potential uniparental disomy (UPD). All information can then be exported in a tabular format for analysis with dedicated software. At present, the software can handle data from 10 K, 100 K, 250 K, 5.0 and 6.0 Affymetrix chips.</p> <p>Conclusion</p> <p>We have created a software that offers a new way of displaying and comparing SNP and CNV genomic data. The software is available free at <url>http://www.med.unibs.it/~barlati/GenotypeColour</url> and is especially useful for the analysis of multiple samples.</p

An enhanced method for targeted next generation sequencing copy number variant detection using ExomeDepth [version 1; peer review: 1 approved, 1 approved with reservations]

Copy number variants (CNV) are a major cause of disease, with over 30,000 reported in the DECIPHER database. To use read depth data from targeted Next Generation Sequencing (NGS) panels to identify CNVs with the highest degree of sensitivity, it is necessary to account for biases inherent in the data. GC content and ambiguous mapping due to repetitive sequence elements and pseudogenes are the principal components of technical variability. In addition, the algorithms used favour the detection of multi-exon CNVs, and rely on suitably matched normal dosage samples for comparison. We developed a calling strategy that subdivides target intervals, and uses pools of historical control samples to overcome these limitations in a clinical diagnostic laboratory. We compared our enhanced strategy with an unmodified pipeline using the R software package ExomeDepth, using a cohort of 109 heterozygous CNVs (91 deletions, 18 duplications in 26 genes), including 25 single exon CNVs. The unmodified pipeline detected 104/109 CNVs, giving a sensitivity of 89.62% to 98.49% at the 95% confidence interval. The detection of all 109 CNVs by our enhanced method demonstrates 95% confidence the sensitivity is ≥96.67%, allowing NGS read depth analysis to be used for CNV detection in a clinical diagnostic setting

ESTIMATING GENOME-WIDE COPY NUMBER USING ALLELE SPECIFIC MIXTURE MODELS

Genomic changes such as copy number alterations are thought to be one of the major underlying causes of human phenotypic variation among normal and disease subjects [23,11,25,26,5,4,7,18]. These include chromosomal regions with so-called copy number alterations: instead of the expected two copies, a section of the chromosome for a particular individual may have zero copies (homozygous deletion), one copy (hemizygous deletions), or more than two copies (amplifications). The canonical example is Down syndrome which is caused by an extra copy of chromosome 21. Identification of such abnormalities in smaller regions has been of great interest, because it is believed to be an underlying cause of cancer. More than one decade ago comparative genomic hybridization (CGH)technology was developed to detect copy number changes in a high-throughput fashion. However, this technology only provides a 10 MB resolution which limits the ability to detect copy number alterations spanning small regions. It is widely believed that a copy number alteration as small as one base can have significant downstream effects, thus microarray manufacturers have developed technologies that provide much higher resolution. Unfortunately, strong probe effects and variation introduced by sample preparation procedures have made single-point copy number estimates too imprecise to be useful. CGH arrays use a two-color hybridization, usually comparing a sample of interest to a reference sample, which to some degree removes the probe effect. However, the resolution is not nearly high enough to provide single-point copy number estimates. Various groups have proposed statistical procedures that pool data from neighboring locations to successfully improve precision. However, these procedure need to average across relatively large regions to work effectively thus greatly reducing the resolution. Recently, regression-type models that account for probe-effect have been proposed and appear to improve accuracy as well as precision. In this paper, we propose a mixture model solution specifically designed for single-point estimation, that provides various advantages over the existing methodology. We use a 314 sample database, constructed with public datasets, to motivate and fit models for the conditional distribution of the observed intensities given allele specific copy numbers. With the estimated models in place we can compute posterior probabilities that provide a useful prediction rule as well as a confidence measure for each call. Software to implement this procedure will be available in the Bioconductor oligo packagehttp://www.bioconductor.org)

An examination of the Apo-1/Fas promoter Mva I polymorphism in Japanese patients with multiple sclerosis

BACKGROUND: The Apo-1/Fas (CD95) molecule is an apoptosis-signaling cell surface receptor belonging to the tumor necrosis factor (TNF) receptor family. Both Fas and Fas ligand (FasL) are expressed in activated mature T cells, and prolonged cell activation induces susceptibility to Fas-mediated apoptosis. The Apo-1/Fas gene is located in a chromosomal region that shows linkage in multiple sclerosis (MS) genome screens, and studies indicate that there is aberrant expression of the Apo-1/Fas molecule in MS. METHODS: Mva I polymorphism on the Apo-1/Fas promoter gene was detected by PCR-RFLP from the DNA of 114 Japanese patients with conventional MS and 121 healthy controls. We investigated the association of the Mva I polymorphism in Japanese MS patients using a case-control association study design. RESULTS: We found no evidence that the polymorphism contributes to susceptibility to MS. Furthermore, there was no association between Apo-1/Fas gene polymorphisms and clinical course (relapsing-remitting course or secondary-progressive course). No significant association was observed between Apo-1/Fas gene polymorphisms and the age at disease onset. CONCLUSIONS: Overall, our findings suggest that Apo-1/Fas promoter gene polymorphisms are not conclusively related to susceptibility to MS or the clinical characteristics of Japanese patients with MS

Genome-Wide Association Study of Copy Number Variants Suggests LTBP1 and FGD4 Are Important for Alcohol Drinking

Alcohol dependence (AD) is a complex disorder characterized by psychiatric and physiological dependence on alcohol. AD is reflected by regular alcohol drinking, which is highly inheritable. In this study, to identify susceptibility genes associated with alcohol drinking, we performed a genome-wide association study of copy number variants (CNVs) in 2,286 Caucasian subjects with Affymetrix SNP6.0 genotyping array. We replicated our findings in 1,627 Chinese subjects with the same genotyping array. We identified two CNVs, CNV207 (combined p-value 1.91E-03) and CNV1836 (combined p-value 3.05E-03) that were associated with alcohol drinking. CNV207 and CNV1836 are located at the downstream of genes LTBP1 (870 kb) and FGD4 (400 kb), respectively. LTBP1, by interacting TGFB1, may down-regulate enzymes directly participating in alcohol metabolism. FGD4 plays a role in clustering and trafficking GABAA receptor and subsequently influence alcohol drinking through activating CDC42. Our results provide suggestive evidence that the newly identified CNV regions and relevant genes may contribute to the genetic mechanism of alcohol dependence

Identification of polymorphic inversions from genotypes

Background: Polymorphic inversions are a source of genetic variability with a direct impact on recombination frequencies. Given the difficulty of their experimental study, computational methods have been developed to infer their existence in a large number of individuals using genome-wide data of nucleotide variation. Methods based on haplotype tagging of known inversions attempt to classify individuals as having a normal or inverted allele. Other methods that measure differences between linkage disequilibrium attempt to identify regions with inversions but unable to classify subjects accurately, an essential requirement for association studies. Results: We present a novel method to both identify polymorphic inversions from genome-wide genotype data and classify individuals as containing a normal or inverted allele. Our method, a generalization of a published method for haplotype data [1], utilizes linkage between groups of SNPs to partition a set of individuals into normal and inverted subpopulations. We employ a sliding window scan to identify regions likely to have an inversion, and accumulation of evidence from neighboring SNPs is used to accurately determine the inversion status of each subject. Further, our approach detects inversions directly from genotype data, thus increasing its usability to current genome-wide association studies (GWAS). Conclusions: We demonstrate the accuracy of our method to detect inversions and classify individuals on principled-simulated genotypes, produced by the evolution of an inversion event within a coalescent model [2]. We applied our method to real genotype data from HapMap Phase III to characterize the inversion status of two known inversions within the regions 17q21 and 8p23 across 1184 individuals. Finally, we scan the full genomes of the European Origin (CEU) and Yoruba (YRI) HapMap samples. We find population-based evidence for 9 out of 15 well-established autosomic inversions, and for 52 regions previously predicted by independent experimental methods in ten (9+1) individuals [3,4]. We provide efficient implementations of both genotype and haplotype methods as a unified R package inveRsion

Copy-Number Variation: The Balance between Gene Dosage and Expression in Drosophila melanogaster

Copy-number variants (CNVs) reshape gene structure, modulate gene expression, and contribute to significant phenotypic variation. Previous studies have revealed CNV patterns in natural populations of Drosophila melanogaster and suggested that selection and mutational bias shape genomic patterns of CNV. Although previous CNV studies focused on heterogeneous strains, here, we established a number of second-chromosome substitution lines to uncover CNV characteristics when homozygous. The percentage of genes harboring CNVs is higher than found in previous studies. More CNVs are detected in homozygous than heterozygous substitution strains, suggesting the comparative genomic hybridization arrays underestimate CNV owing to heterozygous masking. We incorporated previous gene expression data collected from some of the same substitution lines to investigate relationships between CNV gene dosage and expression. Most genes present in CNVs show no evidence of increased or diminished transcription, and the fraction of such dosage-insensitive CNVs is greater in heterozygotes. More than 70% of the dosage-sensitive CNVs are recessive with undetectable effects on transcription in heterozygotes. A deficiency of singletons in recessive dosage-sensitive CNVs supports the hypothesis that most CNVs are subject to negative selection. On the other hand, relaxed purifying selection might account for the higher number of protein–protein interactions in dosage-insensitive CNVs than in dosage-sensitive CNVs. Dosage-sensitive CNVs that are upregulated and downregulated coincide with copy-number increases and decreases. Our results help clarify the relation between CNV dosage and gene expression in the D. melanogaster genome

How and Why Chromosome Inversions Evolve

Chromosome inversions are a major engine of genome evolution. New genomic and ecological data are beginning to reveal the evolutionary forces that drive the evolution of inversions

Reconstructing CNV genotypes using segregation analysis: combining pedigree information with CNV assay

<p>Abstract</p> <p>Background</p> <p>Repeated blocks of genome sequence have been shown to be associated with genetic diversity and disease risk in humans, and with phenotypic diversity in model organisms and domestic animals. Reliable tests are desirable to determine whether individuals are carriers of copy number variants associated with disease risk in humans and livestock, or associated with economically important traits in livestock. In some cases, copy number variants affect the phenotype through a dosage effect but in other cases, allele combinations have non-additive effects. In the latter cases, it has been difficult to develop tests because assays typically return an estimate of the sum of the copy number counts on the maternally and paternally inherited chromosome segments, and this sum does not uniquely determine the allele configuration. In this study, we show that there is an old solution to this new problem: segregation analysis, which has been used for many years to infer alleles in pedigreed populations.</p> <p>Methods</p> <p>Segregation analysis was used to estimate copy number alleles from assay data on simulated half-sib sheep populations. Copy number variation at the Agouti locus, known to be responsible for the recessive self-colour black phenotype, was used as a model for the simulation and an appropriate penetrance function was derived. The precision with which carriers and non-carriers of the undesirable single copy allele could be identified, was used to evaluate the method for various family sizes, assay strategies and assay accuracies.</p> <p>Results</p> <p>Using relationship data and segregation analysis, the probabilities of carrying the copy number alleles responsible for black or white fleece were estimated with much greater precision than by analyzing assay results for animals individually. The proportion of lambs correctly identified as non-carriers of the undesirable allele increased from 7% when the lambs were analysed alone to 80% when the lambs were analysed in half-sib families.</p> <p>Conclusions</p> <p>When a quantitative assay is used to estimate copy number alleles, segregation analysis of related individuals can greatly improve the precision of the estimates. Existing software for segregation analysis would require little if any change to accommodate the penetrance function for copy number assay data.</p