Detection of Copy Number Variants by Short Multiply Aggregated Sequence Homologies.
Ontology highlight
ABSTRACT:
SUBMITTER: Jobanputra V
PROVIDER: S-EPMC7722526 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:SummaryWe have developed an algorithm to detect copy number variants (CNVs) in homozygous organisms, such as inbred laboratory strains of mice, from short read sequence data. Our novel approach exploits the fact that inbred mice are homozygous at virtually every position in the genome to detect CNVs using a hidden Markov model (HMM). This HMM uses both the density of sequence reads mapped to the genome, and the rate of apparent heterozygous single nucleotide polymorphisms, to determine genomic copy number. We tested our algorithm on short read sequence data generated from re-sequencing chromosome 17 of the mouse strains A/J and CAST/EiJ with the Illumina platform. In total, we identified 118 copy number variants (43 for A/J and 75 for CAST/EiJ). We investigated the performance of our algorithm through comparison to CNVs previously identified by array-comparative genomic hybridization (array CGH). We performed quantitative-PCR validation on a subset of the calls that differed from the array CGH data sets.
| S-EPMC2820678 | biostudies-literature
Project description:Height is a highly heritable and classic polygenic trait. Recent genome-wide association studies (GWAS) have revealed that at least 180 genetic variants influence adult height. However, these variants explain only about 10% of the phenotypic variation in height. Genetic analysis of short individuals can lead to the discovery of novel rare gene defects with a large effect on growth. In an effort to identify novel genes associated with short stature, genome-wide analysis for copy number variants (CNVs), using single-nucleotide polymorphism arrays, in 162 patients (149 families) with short stature was performed. Segregation analysis was performed if possible, and genes in CNVs were compared with information from GWAS, gene expression in rodents' growth plates and published information. CNVs were detected in 40 families. In six families, a known cause of short stature was found (SHOX deletion or duplication, IGF1R deletion), in two combined with a de novo potentially pathogenic CNV. Thirty-three families had one or more potentially pathogenic CNVs (n=40). In 24 of these families, segregation analysis could be performed, identifying three de novo CNVs and nine CNVs segregating with short stature. Four were located near loci associated with height in GWAS (ADAMTS17, TULP4, PRKG2/BMP3 and PAPPA). Besides six CNVs known to be causative for short stature, 40 CNVs with possible pathogenicity were identified. Segregation studies and bioinformatics analysis suggested various potential candidate genes.
| S-EPMC3992565 | biostudies-literature
Project description:BackgroundCopy number variations (CNV) are a significant source of variation in the genome and are therefore essential to the understanding of genetic characterization. The aim of this study was to develop a fine-scaled copy number variation map for African goats. We used sequence data from multiple breeds and from multiple African countries.ResultsA total of 253,553 CNV (244,876 deletions and 8677 duplications) were identified, corresponding to an overall average of 1393 CNV per animal. The mean CNV length was 3.3 kb, with a median of 1.3 kb. There was substantial differentiation between the populations for some CNV, suggestive of the effect of population-specific selective pressures. A total of 6231 global CNV regions (CNVR) were found across all animals, representing 59.2 Mb (2.4%) of the goat genome. About 1.6% of the CNVR were present in all 34 breeds and 28.7% were present in all 5 geographical areas across Africa, where animals had been sampled. The CNVR had genes that were highly enriched in important biological functions, molecular functions, and cellular components including retrograde endocannabinoid signaling, glutamatergic synapse and circadian entrainment.ConclusionsThis study presents the first fine CNV map of African goat based on WGS data and adds to the growing body of knowledge on the genetic characterization of goats.
| S-EPMC8164248 | biostudies-literature
Project description:BACKGROUND: With advances in next generation sequencing technologies and genomic capture techniques, exome sequencing has become a cost-effective approach for mutation detection in genetic diseases. However, computational prediction of copy number variants (CNVs) from exome sequence data is a challenging task. Whilst numerous programs are available, they have different sensitivities, and have low sensitivity to detect smaller CNVs (1-4 exons). Additionally, exonic CNV discovery using standard aCGH has limitations due to the low probe density over exonic regions. The goal of our study was to develop a protocol to detect exonic CNVs (including shorter CNVs that cover 1-4 exons), combining computational prediction algorithms and a high-resolution custom CGH array. RESULTS: We used six published CNV prediction programs (ExomeCNV, CONTRA, ExomeCopy, ExomeDepth, CoNIFER, XHMM) and an in-house modification to ExomeCopy and ExomeDepth (ExCopyDepth) for computational CNV prediction on 30 exomes from the 1000 genomes project and 9 exomes from primary immunodeficiency patients. CNV predictions were tested using a custom CGH array designed to capture all exons (exaCGH). After this validation, we next evaluated the computational prediction of shorter CNVs. ExomeCopy and the in-house modified algorithm, ExCopyDepth, showed the highest capability in detecting shorter CNVs. Finally, the performance of each computational program was assessed by calculating the sensitivity and false positive rate. CONCLUSIONS: In this paper, we assessed the ability of 6 computational programs to predict CNVs, focussing on short (1-4 exon) CNVs. We also tested these predictions using a custom array targeting exons. Based on these results, we propose a protocol to identify and confirm shorter exonic CNVs combining computational prediction algorithms and custom aCGH experiments.
| S-EPMC4132917 | 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/aimsIn addition to genome-wide association studies (GWAS), height-associated genes may be uncovered by studying individuals with extreme short or tall stature.MethodsGenome-wide analysis for copy number variants (CNVs), using single nucleotide polymorphism (SNP) arrays, was performed in 49 index cases born small for gestational age with persistent short stature. Segregation analysis was performed, and genes in CNVs were compared with information from GWAS, gene expression in rodents' growth plates, and published information.ResultsCNVs were detected in 13 cases. In 5 children a known cause of short stature was found: UPD7, UPD14, a duplication of the SHOX enhancer region, an IGF1R deletion, and a 22q11.21 deletion. In the remaining 8 cases, potential pathogenic CNVs were detected, either de novo (n = 1), segregating (n = 2), or not segregating with short stature (n = 5). Bioinformatic analysis of the de novo and segregating CNVs suggested that HOXD4, AGPS, PDE11A, OSBPL6, PRKRA and PLEKHA3, and possibly DGKB and TNFRSF11B are potential candidate genes. A SERPINA7 or NRK defect may be associated with an X-linked form of short stature.ConclusionSNP arrays detected 5 known causes of short stature with prenatal onset and suggested several potential candidate genes.
| S-EPMC4236248 | biostudies-literature
Project description:Ebstein anomaly (EA) is a rare congenital defect characterized by apical displacement of the septal tricuspid leaflets and atrialization of the right ventricle. The etiology of EA is unclear; however, recurrence in families and the association of EA with genetic syndromes and copy number variants (CNVs) suggest a genetic component.We performed a population-based study to search for recurrent and novel CNVs in a previously unreported set of EA cases.We genotyped 60 EA cases identified from all live births (2,891,076) from selected California counties (1991-2010) using the Illumina HumanOmni2.5-8 array. We identified 38 candidate CNVs in 28 (46%) cases and prioritized and validated 11 CNVs based on the genes included.Five CNVs (41%) overlapped or were close to genes involved in early myocardial development, including NODAL, PDLIM5, SIX1, ASF1A and FGF12. We also replicated a previous association of EA with CNVs at 1p34.1 and AKAP12. Finally, we identified four CNVs overlapping or in close proximity to the transcription factors HES3, TRIM71, CUX1 and EIF4EBP2.This study supports the relationship of genetic factors to EA and demonstrates that defects in cardiomyocytes and myocardium differentiation may play a role. Abnormal differentiation of cardiomyocytes and how genetic factors contribute should be examined for their association with EA.
| S-EPMC5720705 | biostudies-other
Project description:While exome sequencing is readily amenable to single-nucleotide variant discovery, the sparse and nonuniform nature of the exome capture reaction has hindered exome-based detection and characterization of genic copy number variation. We developed a novel method using singular value decomposition (SVD) normalization to discover rare genic copy number variants (CNVs) as well as genotype copy number polymorphic (CNP) loci with high sensitivity and specificity from exome sequencing data. We estimate the precision of our algorithm using 122 trios (366 exomes) and show that this method can be used to reliably predict (94% overall precision) both de novo and inherited rare CNVs involving three or more consecutive exons. We demonstrate that exome-based genotyping of CNPs strongly correlates with whole-genome data (median r(2) = 0.91), especially for loci with fewer than eight copies, and can estimate the absolute copy number of multi-allelic genes with high accuracy (78% call level). The resulting user-friendly computational pipeline, CoNIFER (copy number inference from exome reads), can reliably be used to discover disruptive genic CNVs missed by standard approaches and should have broad application in human genetic studies of disease.
| S-EPMC3409265 | biostudies-literature
Project description:Current methods for detection of copy number variants (CNV) and aberrations (CNA) from targeted sequencing data are based on the depth of coverage of captured exons. Accurate CNA determination is complicated by uneven genomic distribution and non-uniform capture efficiency of targeted exons. Here we present CopywriteR, which eludes these problems by exploiting 'off-target' sequence reads. CopywriteR allows for extracting uniformly distributed copy number information, can be used without reference, and can be applied to sequencing data obtained from various techniques including chromatin immunoprecipitation and target enrichment on small gene panels. CopywriteR outperforms existing methods and constitutes a widely applicable alternative to available tools.
| S-EPMC4396974 | biostudies-literature
Project description:BackgroundThe short arm of chromosome 16 consists of several copy number variants (CNVs) that are crucial in neurodevelopmental disorders; however, incomplete penetrance and diverse phenotypes after birth aggravate the difficulty of prenatal genetic counseling.MethodsWe screened 15,051 pregnant women who underwent prenatal chromosomal microarray analysis between July 2012 and December 2017. Patients with positive array results were divided into four subgroups based on the type of mutation identified on screening (16p13.3, 16p13.11, 16p12.2, and 16p11.2), and the maternal characteristics, prenatal examinations, and postnatal outcomes of different cases were reviewed.ResultsChromosome 16 CNVs were identified in 34 fetuses, including four with 16p13.3 CNVs, 22 with 16p13.11 CNVs, two with 16p12.2 microdeletions, and six with 16p11.2 CNVs. Of the 34 fetuses, 17 delivered without early childhood neurodevelopmental disorders, three developed neurodevelopmental disorders during childhood, and 10 were terminated.ConclusionIncomplete penetrance and variable expressivity make prenatal counseling challenging. Most cases with inherited 16p13.11 microduplication were reported to have normal development in early childhood, and we also report a few cases of de novo 16p CNVs without further neurodevelopmental disorders.
| S-EPMC10337270 | biostudies-literature