Single nucleotide polymorphisms affect miRNA target prediction in bovine.
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ABSTRACT:
SUBMITTER: Sousa MAP
PROVIDER: S-EPMC8059806 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The class IV alcohol dehydrogenase (ADH7, ?-ADH, ?-ADH) is important in the metabolism of ethanol and retinol. ADH7 is the only ADH not expressed in liver, instead being expressed mainly in the upper gastrointestinal tract. Genome-wide studies have identified significant associations between single-nucleotide polymorphisms in ADH7 and alcoholism and cancer, but the causative variants have not been identified.In vitro studies of gene expression by transient transfection into cell lines that express endogenous ADH7 (CP-A cells) and that do not (HepG2 cells).We have identified transcriptional regulatory elements of ADH7 and observed differences in the effects of variants on gene expression in CP-A cells and HepG2 cells. Two haplotypes of the proximal promoter that differ in a single nucleotide at rs2851028, A7P-G and A7P-A, have different transcriptional activities. There is an interaction between variants farther upstream and these proximal variants: Upstream regulatory sequences generally showed a greater increase or smaller reduction in activity when combined with the A7P-A promoter than with the A7P-G promoter. A sequence located 12.5-kb upstream (7P10) can function as an enhancer. In CP-A cells, both haplotypes of 7P10 increased A7P-A activity by 2.5-fold while having only 1.2-fold effect on A7P-G. In HepG2 cells, the 7P10-TTT haplotype had no effect on the A7P-A promoter but decreased A7P-G promoter activity by 50%, whereas the CTT haplotype increased A7P-A activity by 50%, but had no effect on A7P-G.These complex interactions indicate that the effects of variants in the ADH7 regulatory elements depend on both sequence and cellular context and should be considered in interpretation of the association of variants with alcoholism and cancer.
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Project description:Human EBV-transformed B lymphocyte cell lines (LCLs) were used to measure the apoptotic response of individuals to gamma radiation. The responses form a normal distribution around a median of 35.5% apoptosis with a range of 12-58%. This heterogeneous response has a genetic basis. LCLs from Caucasian donors and African American donors form distinct distributions of apoptotic response; all of the 11 LCLs comprising the lowest responding group (exhibiting between 12-20% apoptosis) are from Caucasian donors. The assay is capable of detecting significant effects of SNPs in two genes, MDM2 and AKT1, whose products are involved in controlling the p53 pathway and cellular response to DNA damage, suggesting that these data and this assay can be used to identify novel SNPs in other genes whose products impact the cellular response to radiation. Finally, the LCLs in the lowest apoptotic response group have the highest concentration of AKT1 protein and all harbor a haplotype in AKT1 that is present in Caucasians but absent in African Americans.
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Project description:Background/aimMicroRNAs (miRNAs) are non-coding RNA molecules that exert post-transcriptional gene expression regulation in response to cellular or environmental changes. Genetic variation affects their synthesis and cellular actions, and single nucleotide polymorphisms (SNPs) are one example of genetic variants studied in relation to various diseases. Literature indicates that the differentially expressed miRNA-145 in patients' serum is an essential biomarker for abdominal aortic aneurysm (AAA). However, the correlation between specific miR-145 genetic polymorphisms with AAA susceptibility is inadequately studied.Materials and methodsEighty-seven AAA patients and 122 healthy controls were recruited. Peripheral blood samples were genotyped for miRNA-145 SNPs; rs55945735, rs73798217 and rs353291.ResultsThe GG genotype of the rs55945735 polymorphism (p=0.047) and the AG genotype of the rs353291 polymorphism (p=0.036) were overrepresented in AAA patients compared to healthy individuals, revealing an association with susceptibility to AAA development.ConclusionSNPs rs55945735 and rs353291 are associated with AAA susceptibility.
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Project description:A growing body of evidence suggests that microRNAs (miRNAs) are involved in Alzheimer's disease (AD) and that some disease-associated genetic variants are located within miRNA binding sites. In the present study, we sought to characterize functional polymorphisms in miRNA target sites within the loci defined in earlier genome-wide association studies (GWAS). The main objectives of this study were to (1) facilitate the identification of the gene or genes responsible for the GWAS signal within a locus of interest and (2) determine how functional polymorphisms might be involved in the AD process (e.g., by affecting miRNA-mediated variations in gene expression).Stringent in silico analyses were developed to select potential polymorphisms susceptible to impairment of miRNA-mediated repression, and subsequent functional assays were performed in HeLa and HEK293 cells.Two polymorphisms were identified and further analyzed in vitro. The AD-associated rs7143400-T allele (located in 3' untranslated region [3'-UTR] of FERMT2) cotransfected with miR-4504 resulted in lower protein levels relative to the rs7143400-G allele cotransfected with the same miRNA. The AD-associated rs9909-C allele in the 3'-UTR of NUP160 abolished the miR-1185-1-3p-regulated expression observed for the rs9909-G allele.When considered in conjunction with the findings of previous association studies, our results suggest that decreased expression of FERMT2 might be a risk factor in the etiopathology of AD, whereas increased expression of NUP160 might protect against the disease. Our data therefore provide new insights into AD by highlighting two new proteins putatively involved in the disease process.
| S-EPMC4878064 | biostudies-literature
Project description:Single-nucleotide polymorphisms (SNP) associated with polygenetic disorders, such as breast cancer (BC), can create, destroy, or modify microRNA (miRNA) binding sites; however, the extent to which SNPs interfere with miRNA gene regulation and affect cancer susceptibility remains largely unknown. We hypothesize that disruption of miRNA target binding by SNPs is a widespread mechanism relevant to cancer susceptibility. To test this, we analyzed SNPs known to be associated with BC risk, in silico and in vitro, for their ability to modify miRNA binding sites and miRNA gene regulation and referred to these as target SNPs. We identified rs1982073-TGFB1 and rs1799782-XRCC1 as target SNPs, whose alleles could modulate gene expression by differential interaction with miR-187 and miR-138, respectively. Genome-wide bioinformatics analysis predicted approximately 64% of transcribed SNPs as target SNPs that can modify (increase/decrease) the binding energy of putative miRNA::mRNA duplexes by >90%. To assess whether target SNPs are implicated in BC susceptibility, we conducted a case-control population study and observed that germline occurrence of rs799917-BRCA1 and rs334348-TGFR1 significantly varies among populations with different risks of developing BC. Luciferase activity of target SNPs, allelic variants, and protein levels in cancer cell lines with different genotypes showed differential regulation of target genes following overexpression of the two interacting miRNAs (miR-638 and miR-628-5p). Therefore, we propose that transcribed target SNPs alter miRNA gene regulation and, consequently, protein expression, contributing to the likelihood of cancer susceptibility, by a novel mechanism of subtle gene regulation.
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Project description:Background:DNA prediction of eye color represent one application of the externally visible characteristics (EVC), which attained growing interest in the field of DNA forensic phenotyping. This is mainly due to its ability to narrow the pool of suspects without the need to compare any retrieved DNA material from the crime scene to a reference DNA. Several methods and multiplex genetic panel were proposed with variable prediction accuracy between different populations. However, such panel was not previously tested in the Saudi population, nor any populations of the Middle East and North Africa origin. Method:A panel of eleven single nucleotide polymorphisms (SNPs) was tested for their association with three eye colors (brown, hazel, and intermediate) in 80 volunteer Saudi individuals. SNPs and haplotype association test with eye colors were performed to identify the top significant SNPs with the three eye colors. Also, multinomial logistic regression was used to construct the prediction model using a training set of 60 subjects, and a validation set of 20 subjects. The goodness of fit parameter of the model to correctly predicts each eye color as compared to the other was performed. Results:Eye color was significantly associated with rs12913832, rs7170852, and rs916977 that are located within HERC2. SNP rs12913832 was the top significant SNP (p-value?=?1.78E-15) that accounted for the association in this region, as the other SNPs were not significant after adjusting for rs12913832. A prediction model containing five SNPs showed high prediction accuracy with Area Under the receiver operating characteristic Curves (AUC) equals to 0.95 and 0.83 for brown and intermediate eye colors, respectively. However, the model's performance was very low for predicting the hazel eye color with AUC equals 0.75. Discussion:Despite the small sample size of our study, we reported very significant SNP associations with eye color. Our model to predict eye colors based on DNA material showed high accuracy for brown and intermediate eye colors. The eye color prediction-model underperformed for the hazel eye colors, suggesting that larger sample size, as well as more comprehensive set of SNPs, could improve the model-prediction accuracy.
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Project description:Wolfram syndrome (WS) is a rare, progressive, neurodegenerative disorder that has an autosomal recessive pattern of inheritance. The gene for WS, wolfram syndrome 1 gene (WFS1), is located on human chromosome 4p16.1 and encodes a transmembrane protein. To date, approximately 230 mutations in WFS1 have been confirmed, in which nonsynonymous single nucleotide polymorphisms (nsSNPs) are the most common forms of genetic variation. Nonetheless, there is poor knowledge on the relationship between SNP genotype and phenotype in other nsSNPs of the WFS1 gene. Here, we analysed 395 nsSNPs associated with the WFS1 gene using different computational methods and identified 20 nsSNPs to be potentially pathogenic. Furthermore, to identify the amino acid distributions and significances of pathogenic nsSNPs in the protein of WFS1, its transmembrane domain was constructed by the TMHMM server, which suggested that mutations outside of the TMhelix could have more effects on protein function. The predicted pathogenic mutations for the nsSNPs of the WFS1 gene provide an excellent guide for screening pathogenic mutations.
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Project description:BackgroundMiRNAs are key regulators in the miRNA-mediated regulatory networks. Single nucleotide polymorphisms (SNPs) that occur at miRNA-related regions may cause serious phenotype changes. To gain new insights into the evolution of miRNAs after SNP variation, we performed a genome-wide scan of miRNA-related SNPs, and analyzed their effects on the stability of miRNAs structure and the alteration of target spectrum in rice.ResultsWe find that the SNP density in pre-miRNAs is significantly higher than that in the flanking regions, owing to the rapid evolution of a large number of species-specific miRNAs in rice. In contrast, it is obvious that deeply conserved miRNAs are under strong purifying selection during evolution. In most cases, the SNPs in stem regions may result in the miRNA hairpin structures changing from stable to unstable status; And SNPs in mature miRNAs have great potential to have either newly created or disrupted the miRNA-target interactions. However, the total number of gained targets is over 2.5 times greater than that are lost after mutation. Notably, 12 putative domestication-related miRNAs have been identified, where the SNP density is significantly lower.ConclusionsThe present study provides the first outline of SNP variations occurred in rice pre-miRNAs at the whole genome-wide level. These analyses may deepen our understanding on the effects of SNPs on the evolution of miRNAs in the rice genome.
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Project description:Breast cancer (BC), a heterogeneous, aggressive illness with high mortality, is essentially a genomic disease. While the high-penetrance genes BRCA1 and BRCA2 play important roles in tumorigenesis, moderate- and low-penetrance genes are also involved. Single-nucleotide polymorphisms (SNPs) in microRNA (miRNA) genes have recently been identified as BC risk factors. miRNA genes are currently classified as low-penetrance. SNPs are the most common variations in the human genome. While the role of miRNA SNPs in BC susceptibility has been studied extensively, results have been inconsistent. This review analyzes the results of association studies between miRNA SNPs and BC risk from countries around the world. We conclude that: (a) By continent, the largest proportion of studies to date were conducted in Asia (65.0 %) and the smallest proportion in Africa (1.8 %); (b) Association studies have been completed for 67 different SNPs; (c) 146a, 196a2, 499, 27a, and 423 are the most-studied miRNAs; (d) The SNPs rs2910164 (miRNA-146a), rs11614913 (miRNA-196a2), rs3746444 (miRNA-499) and rs6505162 (miRNA-423) were the most widely associated with increased BC risk; (e) The majority of studies had small samples, which may affect the precision and power of the results; and (f) The effect of an SNP on BC risk depends on the ethnicity of the population. This review also discusses potential explanations for controversial findings.
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Project description:Smoking is a complex behavior with a heritability as high as 50%. Given such a large genetic contribution, it provides an opportunity to prevent those individuals who are susceptible to smoking dependence from ever starting to smoke by predicting their inherited predisposition with their genomic profiles. Although previous studies have identified many susceptibility variants for smoking, they have limited power to predict smoking behavior. We applied the support vector machine (SVM) and random forest (RF) methods to build prediction models for smoking behavior. We first used 1,431 smokers and 1,503 non-smokers of African origin for model building with a 10-fold cross-validation and then tested the prediction models on an independent dataset consisting of 213 smokers and 224 non-smokers. The SVM model with 500 top single nucleotide polymorphisms (SNPs) selected using logistic regression (p<0.01) as the feature selection method achieved an area under the curve (AUC) of 0.691, 0.721, and 0.720 for the training, test, and independent test samples, respectively. The RF model with 500 top SNPs selected using logistic regression (p<0.01) achieved AUCs of 0.671, 0.665, and 0.667 for the training, test, and independent test samples, respectively. Finally, we used the combined logistic (p<0.01) and LASSO (λ=10-3) regression to select features and the SVM algorithm for model building. The SVM model with 500 top SNPs achieved AUCs of 0.756, 0.776, and 0.897 for the training, test, and independent test samples, respectively. We conclude that machine learning methods are promising means to build predictive models for smoking.
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