Identifying Novel Copy Number Variants in Azoospermia Factor Regions and Evaluating Their Effects on Spermatogenic Impairment.
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ABSTRACT:
SUBMITTER: Zhou R
PROVIDER: S-EPMC6514098 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Bipolar disorder is a complex psychiatric disorder with high heritability, but its genetic determinants are still largely unknown. Copy number variation (CNV) is one of the sources to explain part of the heritability. However, it is a challenge to estimate discrete values of the copy numbers using continuous signals calling from a set of markers, and to simultaneously perform association testing between CNVs and phenotypic outcomes. The goal of the present study is to perform a series of data filtering and analysis procedures using a DNA pooling strategy to identify potential CNV regions that are related to bipolar disorder. A total of 200 normal controls and 200 clinically diagnosed bipolar patients were recruited in this study, and were randomly divided into eight control and eight case pools. Genome-wide genotyping was employed using Illumina Human Omni1-Quad array with approximately one million markers for CNV calling. We aimed at setting a series of criteria to filter out the signal noise of marker data and to reduce the chance of false-positive findings for CNV regions. We first defined CNV regions for each pool. Potential CNV regions were reported based on the different patterns of CNV status between cases and controls. Genes that were mapped into the potential CNV regions were examined with association testing, Gene Ontology enrichment analysis, and checked with existing literature for their associations with bipolar disorder. We reported several CNV regions that are related to bipolar disorder. Two CNV regions on chromosome 11 and 22 showed significant signal differences between cases and controls (p < 0.05). Another five CNV regions on chromosome 6, 9, and 19 were overlapped with results in previous CNV studies. Experimental validation of two CNV regions lent some support to our reported findings. Further experimental and replication studies could be designed for these selected regions.
| S-EPMC5003455 | biostudies-literature
Project description:Copy number variants (CNVs) are known to affect a large portion of the human genome and have been implicated in many diseases. Although whole-genome sequencing (WGS) can help identify CNVs, most analytical methods suffer from limited sensitivity and specificity, especially in regions of low mappability. To address this, we use PopSV, a CNV caller that relies on multiple samples to control for technical variation. We demonstrate that our calls are stable across different types of repeat-rich regions and validate the accuracy of our predictions using orthogonal approaches. Applying PopSV to 640 human genomes, we find that low-mappability regions are approximately 5 times more likely to harbor germline CNVs, in stark contrast to the nearly uniform distribution observed for somatic CNVs in 95 cancer genomes. In addition to known enrichments in segmental duplication and near centromeres and telomeres, we also report that CNVs are enriched in specific types of satellite and in some of the most recent families of transposable elements. Finally, using this comprehensive approach, we identify 3455 regions with recurrent CNVs that were missing from existing catalogs. In particular, we identify 347 genes with a novel exonic CNV in low-mappability regions, including 29 genes previously associated with disease.
| S-EPMC6101599 | biostudies-other
Project description:BACKGROUND: Algorithms and software for CNV detection have been developed, but they detect the CNV regions sample-by-sample with individual-specific breakpoints, while common CNV regions are likely to occur at the same genomic locations across different individuals in a homogenous population. Current algorithms to detect common CNV regions do not account for the varying reliability of the individual CNVs, typically reported as confidence scores by SNP-based CNV detection algorithms. General methodologies for identifying these recurrent regions, especially those directed at SNP arrays, are still needed. RESULTS: In this paper, we describe two new approaches for identifying common CNV regions based on (i) the frequency of occurrence of reliable CNVs, where reliability is determined by high confidence scores, and (ii) a weighted frequency of occurrence of CNVs, where the weights are determined by the confidence scores. In addition, motivated by the fact that we often observe partially overlapping CNV regions as a mixture of two or more distinct subregions, regions identified using the two approaches can be fine-tuned to smaller sub-regions using a clustering algorithm. We compared the performance of the methods with sequencing-based results in terms of discordance rates, rates of departure from Hardy-Weinberg equilibrium (HWE) and average frequency and size of the identified regions. The discordance rates as well as the rates of departure from HWE decrease when we select CNVs with higher confidence scores. We also performed comparisons with two previously published methods, STAC and GISTIC, and showed that the methods we consider are better at identifying low-frequency but high-confidence CNV regions. CONCLUSIONS: The proposed methods for identifying common CNV regions in multiple individuals perform well compared to existing methods. The identified common regions can be used for downstream analyses such as group comparisons in association studies.
| S-EPMC2851607 | biostudies-literature
Project description:Copy number variants (CNVs) are among the largest genetic variants, yet CNVs have not been effectively ascertained in most genetic association studies. Here we ascertained protein-altering CNVs from UK Biobank whole-exome sequencing data (n = 468,570) using haplotype-informed methods capable of detecting subexonic CNVs and variation within segmental duplications. Incorporating CNVs into analyses of rare variants predicted to cause gene loss of function (LOF) identified 100 associations of predicted LOF variants with 41 quantitative traits. A low-frequency partial deletion of RGL3 exon 6 conferred one of the strongest protective effects of gene LOF on hypertension risk (odds ratio = 0.86 (0.82-0.90)). Protein-coding variation in rapidly evolving gene families within segmental duplications-previously invisible to most analysis methods-generated some of the human genome's largest contributions to variation in type 2 diabetes risk, chronotype and blood cell traits. These results illustrate the potential for new genetic insights from genomic variation that has escaped large-scale analysis to date.
| S-EPMC11018521 | 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:BackgroundRecent findings demonstrate that single nucleotide variants can cause non-obstructive azoospermia (NOA). In contrast, copy number variants (CNVs) were only analysed in few studies in infertile men. Some have reported a higher prevalence of CNVs in infertile versus fertile men.ObjectivesThis study aimed to elucidate if CNVs are associated with NOA.Materials and methodsWe performed array-based comparative genomic hybridisation (aCGH) in 37 men with meiotic arrest, 194 men with Sertoli cell-only phenotype, and 21 control men. We filtered our data for deletions affecting genes and prioritised the affected genes according to the literature search. Prevalence of CNVs was compared between all groups. Exome data of 2,030 men were screened to detect further genetic variants in prioritised genes. Modelling was performed for the protein encoded by the novel candidate gene TEKT5 and we stained for TEKT5 in human testicular tissue.ResultsWe determined the cause of infertility in two individuals with homozygous deletions of SYCE1 and in one individual with a heterozygous deletion of SYCE1 combined with a likely pathogenic missense variant on the second allele. We detected heterozygous deletions affecting MLH3, EIF2B2, SLX4, CLPP and TEKT5, in one subject each. CNVs were not detected more frequently in infertile men compared with controls.DiscussionWhile SYCE1 and MLH3 encode known meiosis-specific proteins, much less is known about the proteins encoded by the other identified candidate genes, warranting further analyses. We were able to identify the cause of infertility in one out of the 231 infertile men by aCGH and in two men by using exome sequencing data.ConclusionAs aCGH and exome sequencing are both expensive methods, combining both in a clinical routine is not an effective strategy. Instead, using CNV calling from exome data has recently become more precise, potentially making aCGH dispensable.
| S-EPMC9605881 | biostudies-literature
Project description:Copy number variants (CNV) can be called from SNP-arrays; however, few studies have attempted to combine both CNV and SNP calls to test for association with complex diseases. Even when SNPs are located within CNVs, two separate association analyses are necessary, to compare the distribution of bi-allelic genotypes in cases and controls (referred to as SNP-only strategy) and the number of copies of a region (referred to as CNV-only strategy). However, when disease susceptibility is actually associated with allele specific copy-number states, the two strategies may not yield comparable results, raising a series of questions about the optimal analytical approach. We performed simulations of the performance of association testing under different scenarios that varied genotype frequencies and inheritance models. We show that the SNP-only strategy lacks power under most scenarios when the SNP is located within a CNV; frequently it is excluded from analysis as it does not pass quality control metrics either because of an increased rate of missing calls or a departure from fitness for Hardy-Weinberg proportion. The CNV-only strategy also lacks power because the association testing depends on the allele which copy number varies. The combined strategy performs well in most of the scenarios. Hence, we advocate the use of this combined strategy when testing for association with SNPs located within CNVs.
| S-EPMC3769257 | biostudies-literature
Project description:An exploratory genome-wide copy number variant (CNV) study was performed in 127 independent cases with specific language impairment (SLI), their first-degree relatives (385 individuals) and 269 population controls. Language-impaired cases showed an increased CNV burden in terms of the average number of events (11.28 vs 10.01, empirical P=0.003), the total length of CNVs (717 vs 513?Kb, empirical P=0.0001), the average CNV size (63.75 vs 51.6?Kb, empirical P=0.0005) and the number of genes spanned (14.29 vs 10.34, empirical P=0.0007) when compared with population controls, suggesting that CNVs may contribute to SLI risk. A similar trend was observed in first-degree relatives regardless of affection status. The increased burden found in our study was not driven by large or de novo events, which have been described as causative in other neurodevelopmental disorders. Nevertheless, de novo CNVs might be important on a case-by-case basis, as indicated by identification of events affecting relevant genes, such as ACTR2 and CSNK1A1, and small events within known micro-deletion/-duplication syndrome regions, such as chr8p23.1. Pathway analysis of the genes present within the CNVs of the independent cases identified significant overrepresentation of acetylcholine binding, cyclic-nucleotide phosphodiesterase activity and MHC proteins as compared with controls. Taken together, our data suggest that the majority of the risk conferred by CNVs in SLI is via common, inherited events within a 'common disorder-common variant' model. Therefore the risk conferred by CNVs will depend upon the combination of events inherited (both CNVs and SNPs), the genetic background of the individual and the environmental factors.
| S-EPMC4592089 | biostudies-literature
Project description:BackgroundNon-obstructive azoospermia (NOA) is the most severe disease in male infertility, but the genetic causes for majority of NOA remain unknown.MethodsTwo Chinese NOA-affected patients were recruited to identify the genetic causal factor of infertility. Whole-exome sequencing (WES) was conducted in the two patients with NOA. Sanger sequencing and CNV array were used to ascertain the WES results. Hematoxylin and eosin (H&E) staining and immunofluorescence (IF) were carried out to evaluate the stage of spermatogenesis arrested in the affected cases.ResultsNovel heterozygous deletion (LOH) within SYCE1 (seq[GRCh37] del(10)(10q26.3)chr10:g.135111754_135427143del) and heterozygous loss of function (LoF) variant in SYCE1 (NM_001143763: c.689_690 del:p.F230fs) were identified in one NOA-affected patient. While homozygous deletion within SYCE1 (seq[GRCh37] del(10)(10q26.3)chr10:g.135340247_135379115del) was detected in the other patient with meiotic arrest. H&E and IF staining demonstrated that the spermatogenesis was arrested at pachytene stage in the two patients with NOA, suggesting these two novel CNVs within SYCE1 could lead to meiotic defect and NOA.ConclusionsWe identified that two novel CNVs within SYCE1 are associated with meiotic arrest and male infertility. Thus, our study expands the knowledge of variants in SYCE1 and provides a new insight to understand the genetic etiologies of NOA.
| S-EPMC9208180 | biostudies-literature
Project description:BackgroundConsidering the essential roles that genetic factors play in azoospermia and oligospermia, this study aims to identify abnormal chromosomes using karyotyping and CNVs and elucidate the associated genes in patients.MethodsA total of 1157 azoospermia and oligospermia patients were recruited, of whom, 769 and 674 underwent next-generation sequencing (NGS) to identify CNVs and routine G-band karyotyping, respectively.ResultsFirst, 286 patients were co-analyzed using CNV sequencing (CNV-seq) and karyotyping. Of the 725 and 432 patients with azoospermia and oligospermia, 33.8% and 48.9% had abnormal karyotypes and CNVs, respectively. In particular, 47,XXY accounted for 44.18% and 26.33% of abnormal karyotypes and CNVs, respectively, representing the most frequent genetic aberration in azoospermia and oligospermia patients. Nevertheless, big Y and small Y accounted for 7.46% and 16.67% of abnormal karyotypes, respectively. We also identified high-frequency CNVs-loci, such as Xp22.31 and 2p24.3, in azoospermia and oligospermia patients.ConclusionSex chromosome and autosomal CNV loci, such as Xp22.31 and 2p24.3, as well as the associated genes, such as VCX and NACAP9, could be candidate spermatogenesis genes. The high-frequency abnormal karyotypes, CNV loci, and hot genes represent new targets for future research.
| S-EPMC10485952 | biostudies-literature