Are microRNAs located in genomic regions associated with cancer?
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ABSTRACT:
SUBMITTER: Lamy P
PROVIDER: S-EPMC2360608 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:MicroRNAs (miRNAs) are a widespread class of regulatory noncoding RNAs with key roles in physiology and development, conferring robustness to noise in regulatory networks. Consistent with this buffering function, it was recently suggested that human miRNAs coevolve with genes in copy number regions (copy number variation [CNV] genes) to reduce dosage imbalance. Here, I compare miRNA regulation between CNV and non-CNV genes in four model organisms. miRNA regulation of CNV genes is elevated in human and fly but reduced in nematode and zebrafish. By analyzing 31 human CNV data sets, careful analysis of human and chimpanzee orthologs, resampling genes within species and comparing structural variant types, I show that the apparent coevolution between CNV genes and miRNAs is due to the strong dependency between 3'-untranslated region length and miRNA target prediction. Deciphering the interplay between CNVs and miRNAs will likely require a deeper understanding of how miRNAs are embedded in regulatory circuits.
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Project description:Genetic variants in regulatory regions of some miRNAs might be associated with lung cancer risk and survival. We performed a case-control study including 1341 non-small cell lung cancer (NSCLC) cases and 1982 controls to evaluate the associations of 7 potentially functional polymorphisms in several differently expressed miRNAs with NSCLC risk. Each SNP was also tested for the association with overall survival of 1001 NSCLC patients. We identified that rs9660710 in miR-200b/200a/429 cluster and rs763354 in miR-30a were significantly associated with NSCLC risk [odds ratio (OR) = 1.17, 95% confidence interval (CI) = 1.06-1.30, P = 0.002; OR = 0.88, 95% CI = 0.80-0.98, P = 0.017; respectively]. However, no significant association between variants and NSCLC death risk was observed in survival analysis. Functional annotation showed that both rs9660710 and rs763354 were located in regulatory elements in lung cancer cells. Compared to normal tissues, miR-200a-3p, miR-200a-5p, miR-200b-3p, miR-200b-5p and miR-429 were significantly increased in The Cancer Genome Atlas (TCGA) Lung Adenocarcinoma (LUAD) tumors, whereas miR-30a-3p and miR-30a-5p were significantly decreased in tumors (all P < 0.05). Furthermore, we observed that rs9660710 is an expression quantitative trait locus (eQTL) or methylation eQTL for miR-429 expression in TCGA normal tissues. Our results indicated that rs9660710 in miR-200b/200a/429 cluster and rs763354 in miR-30a might modify the susceptibility to NSCLC.
| S-EPMC5216992 | biostudies-literature
Project description:A large number of tiny noncoding RNAs have been cloned and named microRNAs (miRs). Recently, we have reported that miR-15a and miR-16a, located at 13q14, are frequently deleted and/or down-regulated in patients with B cell chronic lymphocytic leukemia, a disorder characterized by increased survival. To further investigate the possible involvement of miRs in human cancers on a genome-wide basis, we have mapped 186 miRs and compared their location to the location of previous reported nonrandom genetic alterations. Here, we show that miR genes are frequently located at fragile sites, as well as in minimal regions of loss of heterozygosity, minimal regions of amplification (minimal amplicons), or common breakpoint regions. Overall, 98 of 186 (52.5%) of miR genes are in cancer-associated genomic regions or in fragile sites. Moreover, by Northern blotting, we have shown that several miRs located in deleted regions have low levels of expression in cancer samples. These data provide a catalog of miR genes that may have roles in cancer and argue that the full complement of miRs in a genome may be extensively involved in cancers.
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Project description:MiRNAs have been focused for their wide range of biological regulatory functions. Previous studies have suggested that individual miRNAs could influence tumorigenesis through their regulation of specific proto-oncogenes and tumor suppressor genes. This study was implemented to investigate the associations between SNPs in mature microRNAs (miRNAs) and development of lung cancer in a two-stage, case-control study, followed by some functional validations. First, 11 SNPs were analyzed in a case-control study of lung cancer, and the significant results were validated in an additional population. Our results showed that rs3746444 in mir-499 (allele C vs T: OR = 1.33; 95% CI = 1.15-1.54; P = 1.2 × 10-4) and rs4919510 in mir-608 (allele G vs C: OR = 1.27; 95% CI= 1.13-1.43; P = 5.1 × 10-5) were significantly associated with increased risk of lung cancer. Rs3746444 in mir-499 was also significantly associated with poor survival of lung cancer (HR, 1.35; 95% CI, 1.15-1.58; P = 0.0002). The expression levels of mir-499 and mir-608 were significantly lower than those of adjacent normal tissues (P < 0.0005), and the carriers of minor alleles have lower expression levels of mir-499 and mir-608 than those of major alleles (P < 0.001). These findings indicated that rs3746444 in mir-499 and rs4919510 in mir-608 might play a substantial role in the susceptibility to lung cancer.
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Project description:BackgroundA back curvature defect similar to kyphosis in humans has been observed in swine herds. The defect ranges from mild to severe curvature of the thoracic vertebrate in split carcasses and has an estimated heritability of 0.3. The objective of this study was to identify genomic regions that affect this trait.ResultsSingle nucleotide polymorphism (SNP) associations performed with 198 SNPs and microsatellite markers in a Duroc-Landrace-Yorkshire resource population (U.S. Meat Animal Research Center, USMARC resource population) of swine provided regions of association with this trait on 15 chromosomes. Positional candidate genes, especially those involved in human skeletal development pathways, were selected for SNP identification. SNPs in 16 candidate genes were genotyped in an F2 population (n = 371) and the USMARC resource herd (n = 1,257) with kyphosis scores. SNPs in KCNN2 on SSC2, RYR1 and PLOD1 on SSC6 and MYST4 on SSC14 were significantly associated with kyphosis in the resource population of swine (P ≤ 0.05). SNPs in CER1 and CDH7 on SSC1, PSMA5 on SSC4, HOXC6 and HOXC8 on SSC5, ADAMTS18 on SSC6 and SOX9 on SSC12 were significantly associated with the kyphosis trait in the F2 population of swine (P ≤ 0.05).ConclusionsThese data suggest that this kyphosis trait may be affected by several loci and that these may differ by population. Carcass value could be improved by effectively removing this undesirable trait from pig populations.
| S-EPMC3018398 | biostudies-literature
Project description:Genome-wide association studies (GWAS) have consistently identified specific lung cancer susceptibility regions. We evaluated the lung cancer-predictive performance of single-nucleotide polymorphisms (SNPs) in these regions.Lung cancer cases (N = 778) and controls (N = 1166) were genotyped for 77 SNPs located in GWAS-identified lung cancer susceptibility regions. Variable selection and model development used stepwise logistic regression and decision-tree analyses. In a subset nested in the Pittsburgh Lung Screening Study, change in area under the receiver operator characteristic curve and net reclassification improvement were used to compare predictions made by risk factor models with and without genetic variables.Variable selection and model development kept two SNPs in each of three GWAS regions, rs2736100 and rs7727912 in 5p15.33, rs805297 and rs1802127 in 6p21.33, and rs8034191 and rs12440014 in 15q25.1. The ratio of cases to controls was three times higher among subjects with a high-risk genotype in every one as opposed to none of the three GWAS regions (odds ratio, 3.14; 95% confidence interval, 2.02-4.88; adjusted for sex, age, and pack-years). Adding a three-level classified count of GWAS regions with high-risk genotypes to an age and smoking risk factor-only model improved lung cancer prediction by a small amount: area under the receiver operator characteristic curve, 0.725 versus 0.717 (p = 0.056); overall net reclassification improvement was 0.052 across low-, intermediate-, and high- 6-year lung cancer risk categories (<3.0%, 3.0%-4.9%, ? 5.0%).Specifying genotypes for SNPs in three GWAS-identified susceptibility regions improved lung cancer prediction, but probably by an extent too small to affect disease control practice.
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Project description:The majority of existing computational tools rely on sequence homology and/or structural similarity to identify novel microRNA (miRNA) genes. Recently supervised algorithms are utilized to address this problem, taking into account sequence, structure and comparative genomics information. In most of these studies miRNA gene predictions are rarely supported by experimental evidence and prediction accuracy remains uncertain. In this work we present a new computational tool (SSCprofiler) utilizing a probabilistic method based on Profile Hidden Markov Models to predict novel miRNA precursors. Via the simultaneous integration of biological features such as sequence, structure and conservation, SSCprofiler achieves a performance accuracy of 88.95% sensitivity and 84.16% specificity on a large set of human miRNA genes. The trained classifier is used to identify novel miRNA gene candidates located within cancer-associated genomic regions and rank the resulting predictions using expression information from a full genome tiling array. Finally, four of the top scoring predictions are verified experimentally using northern blot analysis. Our work combines both analytical and experimental techniques to show that SSCprofiler is a highly accurate tool which can be used to identify novel miRNA gene candidates in the human genome. SSCprofiler is freely available as a web service at http://www.imbb.forth.gr/SSCprofiler.html.
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Project description:A BRCA2 prostate cancer cluster region (PCCR) was recently proposed (c.7914 to 3') wherein pathogenic variants (PVs) are associated with higher prostate cancer (PCa) risk than PVs elsewhere in the BRCA2 gene. Using a prospective cohort study of 447 male BRCA2 PV carriers recruited in the UK and Ireland from 1998 to 2016, we estimated standardised incidence ratios (SIRs) compared with population incidences and assessed variation in risk by PV location. Carriers of PVs in the PCCR had a PCa SIR of 8.33 (95% confidence interval [CI] 4.46-15.6) and were at a higher risk of PCa than carriers of other BRCA2 PVs (SIR?=?3.31, 95% CI 1.97-5.57; hazard ratio?=?2.34, 95% CI 1.09-5.03). PCCR PV carriers had an estimated cumulative PCa risk of 44% (95% CI 23-72%) by the age of 75?yr and 78% (95% CI 54-94%) by the age of 85?yr. Our results corroborate the existence of a PCCR in BRCA2 in a prospective cohort. PATIENT SUMMARY: In this report, we investigated whether the risk of prostate cancer for men with a harmful mutation in the BRCA2 gene differs based on where in the gene the mutation is located. We found that men with mutations in one region of BRCA2 had a higher risk of prostate cancer than men with mutations elsewhere in the gene.
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Project description:Asperger disorder (ASP) is one of the autism spectrum disorders (ASD) and is differentiated from autism largely on the absence of clinically significant cognitive and language delays. Analysis of a homogenous subset of families with ASP may help to address the corresponding effect of genetic heterogeneity on identifying ASD genetic risk factors. To examine the hypothesis that common variation is important in ASD, we performed a genome-wide association study (GWAS) in 124 ASP families in a discovery data set and 110 ASP families in a validation data set. We prioritized the top 100 association results from both cohorts by employing a ranking strategy. Novel regions on 5q21.1 (P = 9.7 × 10(-7) ) and 15q22.1-q22.2 (P = 7.3 × 10(-6) ) were our most significant findings in the combined data set. Three chromosomal regions showing association, 3p14.2 (P = 3.6 × 10(-6) ), 3q25-26 (P = 6.0 × 10(-5) ) and 3p23 (P = 3.3 × 10(-4) ) overlapped linkage regions reported in Finnish ASP families, and eight association regions overlapped ASD linkage areas. Our findings suggest that ASP shares both ASD-related genetic risk factors, as well as has genetic risk factors unique to the ASP phenotype.
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Project description:Most transcription factors (TFs) belong to protein families that share a common DNA binding domain and have very similar DNA binding preferences. However, many paralogous TFs (i.e. members of the same TF family) perform different regulatory functions and interact with different genomic regions in the cell. A potential mechanism for achieving this differential in vivo specificity is through interactions with protein co-factors. Computational tools for studying the genomic binding profiles of paralogous TFs and identifying their putative co-factors are currently lacking. Here, we present an interactive web implementation of COUGER, a classification-based framework for identifying protein co-factors that might provide specificity to paralogous TFs. COUGER takes as input two sets of genomic regions bound by paralogous TFs, and it identifies a small set of putative co-factors that best distinguish the two sets of sequences. To achieve this task, COUGER uses a classification approach, with features that reflect the DNA-binding specificities of the putative co-factors. The identified co-factors are presented in a user-friendly output page, together with information that allows the user to understand and to explore the contributions of individual co-factor features. COUGER can be run as a stand-alone tool or through a web interface: http://couger.oit.duke.edu.
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