Association of CNVs with methylation variation.
Ontology highlight
ABSTRACT:
SUBMITTER: Shi X
PROVIDER: S-EPMC7519119 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Introns can be extraordinarily large and they account for the majority of the DNA sequence in human genes. However, little is known about their population patterns of structural variation and their functional implication. By combining the most extensive maps of CNVs in human populations, we have found that intronic losses are the most frequent copy number variants (CNVs) in protein-coding genes in human, with 12,986 intronic deletions, affecting 4,147 genes (including 1,154 essential genes and 1,638 disease-related genes). This intronic length variation results in dozens of genes showing extreme population variability in size, with 40 genes with 10 or more different sizes and up to 150 allelic sizes. Intronic losses are frequent in evolutionarily ancient genes that are highly conserved at the protein sequence level. This result contrasts with losses overlapping exons, which are observed less often than expected by chance and almost exclusively affect primate-specific genes. An integrated analysis of CNVs and RNA-seq data showed that intronic loss can be associated with significant differences in gene expression levels in the population (CNV-eQTLs). These intronic CNV-eQTLs regions are enriched for intronic enhancers and can be associated with expression differences of other genes showing long distance intron-promoter 3D interactions. Our data suggests that intronic structural variation of protein-coding genes makes an important contribution to the variability of gene expression and splicing in human populations.
| S-EPMC6345438 | biostudies-literature
Project description:VTRNA2-1 is a metastable epiallele with accumulating evidence that methylation at this region is heritable, modifiable and associated with disease including risk and progression of cancer. This study investigated the influence of genetic variation and other factors such as age and adult lifestyle on blood DNA methylation in this region. We first sequenced the VTRNA2-1 gene region in multiple-case breast cancer families in which VTRNA2-1 methylation was identified as heritable and associated with breast cancer risk. Methylation quantitative trait loci (mQTL) were investigated using a prospective cohort study (4500 participants with genotyping and methylation data). The cis-mQTL analysis (334 variants ± 50 kb of the most heritable CpG site) identified 43 variants associated with VTRNA2-1 methylation (p < 1.5 × 10-4); however, these explained little of the methylation variation (R2 < 0.5% for each of these variants). No genetic variants elsewhere in the genome were found to strongly influence VTRNA2-1 methylation. SNP-based heritability estimates were consistent with the mQTL findings (h2 = 0, 95%CI: -0.14 to 0.14). We found no evidence that age, sex, country of birth, smoking, body mass index, alcohol consumption or diet influenced blood DNA methylation at VTRNA2-1. Genetic factors and adult lifestyle play a minimal role in explaining methylation variability at the heritable VTRNA2-1 cluster.
| S-EPMC7961504 | biostudies-literature
Project description:BackgroundAutism spectrum disorder (ASD) is a complex neurodevelopmental condition whose biological basis is yet to be elucidated. The Australian Autism Biobank (AAB) is an initiative of the Cooperative Research Centre for Living with Autism (Autism CRC) to establish an Australian resource of biospecimens, phenotypes and genomic data for research on autism.MethodsGenome-wide single-nucleotide polymorphism genotypes were available for 2,477 individuals (after quality control) from 546 families (436 complete), including 886 participants aged 2 to 17 years with diagnosed (n = 871) or suspected (n = 15) ASD, 218 siblings without ASD, 1,256 parents, and 117 unrelated children without an ASD diagnosis. The genetic data were used to confirm familial relationships and assign ancestry, which was majority European (n = 1,964 European individuals). We generated polygenic scores (PGS) for ASD, IQ, chronotype and height in the subset of Europeans, and in 3,490 unrelated ancestry-matched participants from the UK Biobank. We tested for group differences for each PGS, and performed prediction analyses for related phenotypes in the AAB. We called copy-number variants (CNVs) in all participants, and intersected these with high-confidence ASD- and intellectual disability (ID)-associated CNVs and genes from the public domain.ResultsThe ASD (p = 6.1e-13), sibling (p = 4.9e-3) and unrelated (p = 3.0e-3) groups had significantly higher ASD PGS than UK Biobank controls, whereas this was not the case for height-a control trait. The IQ PGS was a significant predictor of measured IQ in undiagnosed children (r = 0.24, p = 2.1e-3) and parents (r = 0.17, p = 8.0e-7; 4.0% of variance), but not the ASD group. Chronotype PGS predicted sleep disturbances within the ASD group (r = 0.13, p = 1.9e-3; 1.3% of variance). In the CNV analysis, we identified 13 individuals with CNVs overlapping ASD/ID-associated CNVs, and 12 with CNVs overlapping ASD/ID/developmental delay-associated genes identified on the basis of de novo variants.LimitationsThis dataset is modest in size, and the publicly-available genome-wide-association-study (GWAS) summary statistics used to calculate PGS for ASD and other traits are relatively underpowered.ConclusionsWe report on common genetic variation and rare CNVs within the AAB. Prediction analyses using currently available GWAS summary statistics are largely consistent with expected relationships based on published studies. As the size of publicly-available GWAS summary statistics grows, the phenotypic depth of the AAB dataset will provide many opportunities for analyses of autism profiles and co-occurring conditions, including when integrated with other omics datasets generated from AAB biospecimens (blood, urine, stool, hair).
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Project description: Not available
| S-EPMC2330071 | biostudies-literature
Project description:Single-nucleotide polymorphisms that have been associated with opioid dependence (OD) altogether account for only a small proportion of the known heritability. Most of the genetic risk factors are unknown. Some of the 'missing heritability' might be explained by copy number variations (CNVs) in the human genome. We used Illumina HumanOmni1 arrays to genotype 5152 African-American and European-American OD cases and screened controls and implemented combined CNV calling methods. After quality control measures were applied, a genome-wide association study (GWAS) of CNVs with OD was performed. For common CNVs, two deletions and one duplication were significantly associated with OD genome-wide (eg, P=2 × 10(-8) and OR (95% CI)=0.64 (0.54-0.74) for a chromosome 18q12.3 deletion). Several rare or unique CNVs showed suggestive or marginal significance with large effect sizes. This study is the first GWAS of OD using CNVs. Some identified CNVs harbor genes newly identified here to be of biological importance in addiction, whereas others affect genes previously known to contribute to substance dependence risk. Our findings augment our specific knowledge of the importance of genomic variation in addictive disorders, and provide an addiction CNV pool for further research. These findings require replication.
| S-EPMC4330517 | biostudies-literature
Project description:Sequence variants in genes functioning in folate-mediated one-carbon metabolism are hypothesized to lead to changes in levels of homocysteine and DNA methylation, which, in turn, are associated with risk of cardiovascular disease.330 SNPs in 52 genes were studied in relation to plasma homocysteine and global genomic DNA methylation. SNPs were selected based on functional effects and gene coverage, and assays were completed on the Illumina Goldengate platform. Age-, smoking-, and nutrient-adjusted genotype--phenotype associations were estimated in regression models.Using a nominal P ? 0.005 threshold for statistical significance, 20 SNPs were associated with plasma homocysteine, 8 with Alu methylation, and 1 with LINE-1 methylation. Using a more stringent false discovery rate threshold, SNPs in FTCD, SLC19A1, and SLC19A3 genes remained associated with plasma homocysteine. Gene by vitamin B-6 interactions were identified for both Alu and LINE-1 methylation, and epistatic interactions with the MTHFR rs1801133 SNP were identified for the plasma homocysteine phenotype. Pleiotropy involving the MTHFD1L and SARDH genes for both plasma homocysteine and Alu methylation phenotypes was identified.No single gene was associated with all three phenotypes, and the set of the most statistically significant SNPs predictive of homocysteine or Alu or LINE-1 methylation was unique to each phenotype. Genetic variation in folate-mediated one-carbon metabolism, other than the well-known effects of the MTHFR c.665C>T (known as c.677 C>T, rs1801133, p.Ala222Val), is predictive of cardiovascular disease biomarkers.
| S-EPMC3266217 | biostudies-literature
Project description:Copy number variation (CNV) is an important type of genetic variation contributing to phenotypic differences among mammals. Up to now, GWAS analysis using CNV called by array CGH is lacking in livestock like Holstein cattle. The objectives of this work are to identify CNVs using high-density aCGH data and explore functional CNVs which are associated with complex traits by GWAS method in Holstein cattle. In this study, we reported a systematic CNV association analysis of CNVs and 39 complex production traits in Holsteins. This research identified 1043 CNV regions (CNVRs) by array CGH data in 47 Holstein bulls. Using a genome-wide association analysis (GWAS) approach, we identified 79 significant CNVRs associated with at least one complex traits after false discovery rate (FDR) correction. Notably, 24 CNVRs were markedly related to daughter pregnancy rate (DPR). This study observed the pleiotropy phenomenon of 39 CNV loci which can simultaneously regulate at least 2 complex traits. In summary, the significant CNVs identified in this research could be utilized additional molecular markers for genetic improvement programs in Holsteins.
2019-02-16 | GSE122478 | GEO
Project description:Brazil is one of the largest beef producers and exporters in the world with the Nelore breed representing the vast majority of Brazilian cattle (Bos taurus indicus). Despite the great adaptability of the Nelore breed to tropical climate, meat tenderness (MT) remains to be improved. Several factors including genetic composition can influence MT. In this article, we report a genome-wide analysis of copy number variation (CNV) inferred from Illumina® High Density SNP-chip data for a Nelore population of 723 males. We detected >2,600 CNV regions (CNVRs) representing ≈6.5% of the genome. Comparing our results with previous studies revealed an overlap in ≈1400 CNVRs (>50%). A total of 1,155 CNVRs (43.6%) overlapped 2,750 genes. They were enriched for processes involving guanosine triphosphate (GTP), previously reported to influence skeletal muscle physiology and morphology. Nelore CNVRs also overlapped QTLs for MT reported in other breeds (8.9%, 236 CNVRs) and from a previous study with this population (4.1%, 109 CNVRs). Two CNVRs were also proximal to glutathione metabolism genes that were previously associated with MT. Genome-wide association study of CN state with estimated breeding values derived from meat shear force identified 6 regions, including a region on BTA3 that contains genes of the cAMP and cGMP pathway. Ten CNVRs that overlapped regions associated with MT were successfully validated by qPCR. Our results represent the first comprehensive CNV study in Bos taurus indicus cattle and identify regions in which copy number changes are potentially of importance for the MT phenotype.
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Project description: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 a hidden Markov model (HMM), and generates an integrated sequence and copy number genotype at every locus (for example, including genotypes such as A-null, AAB and BBB in addition to AA, AB and BB calls). Such genotypes more accurately depict the underlying sequence of each individual, reducing the rate of apparent mendelian inconsistencies. The Birdsuite software is applied here to data from the Affymetrix SNP 6.0 array. Additionally, we describe a method, implemented in PLINK, to utilize these combined SNP and CNV genotypes for association testing with a phenotype.
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Project description:Preterm delivery (PTD) is an adverse birth outcome associated with increased infant mortality and negative lifelong health consequences. PTD may be the result of interactions between genetics and maternal/fetal environmental factors including smoking exposure (SMK). A common deletion in the GSTT1 gene was previously reported to affect birth outcomes in smokers. In this study, we dissect the associations among SMK, birth outcomes, and copy number variations (CNVs) in the GSTT1/GSTT2 region. A preterm birth case-control dataset of 1937 mothers was part of the GENEVA preterm birth study, which included genome-wide genotyping used to identify CNVs. We examined the association of SMK with birth outcomes, detected CNVs within the GSTT1/GSTT2 region using PennCNV, and examined associations of the identified CNVs with preterm birth and with birth weight (BW) in full term birth controls, including interactions with SMK. Finally, we tested the association of CNVs in GSTT1/GSTT2 with SMK. We confirmed the association of smoking with low BW and PTD. We identified 2 CNVs in GSTT2 (GSTT2 (a) and GSTT2 (b) ), 1 CNV in GSTTP1 and 2 CNVs in GSTT1 (GSTT1 (a) and GSTT1 (b) ). The GSTT2 (a) deletion was associated with reduced BW (-284 g, p = 2.50E-7) in smokers, and was more common in smokers [odds ratio(OR) = 1.30, p = 0.04]. We found that the size of the reported common deletion CNV in GSTT1 was larger than previously shown. The GSTTP1 and GSTT1 (b) null genotypes were in high linkage disequilibrium (LD) (D' = 0.89) and less common in smokers (OR = 0.68, p = 0.019 and OR = 0.73, p = 0.055, respectively). These two deletions were in partial LD with GSTT2 (a) and GSTT2 (b) duplications. All 5 CNVs seem to be associated with increased risk of preterm birth before 35 completed weeks. CNVs in the GSTTT1/GSTT2 region appear associated with low BW and PTD outcomes, but LD complicated these CNVs in GSTT1/GSTT2. In genetic association studies of BW, multiple CNVs in this region need to be investigated instead of a single polymorphism.
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