An update of miRNASNP database for better SNP selection by GWAS data, miRNA expression and online tools

Identification and analysis of inflammation-related biomarkers in tetralogy of Fallot

Background

Studies have revealed that inflammatory response is relevant to the tetralogy of Fallot (TOF). However, there are no studies to systematically explore the role of the inflammation-related genes (IRGs) in TOF. Therefore, based on bioinformatics, we explored the biomarkers related to inflammation in TOF, laying a theoretical foundation for its in-depth study.

Methods

TOF-related datasets (GSE36761 and GSE35776) were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between TOF and control groups were identified in GSE36761. And DEGs between TOF and control groups were intersected with IRGs to obtain differentially expressed IRGs (DE-IRGs). Afterwards, the least absolute shrinkage and selection operator (LASSO) and random forest (RF) were utilized to identify the biomarkers. Next, immune analysis was carried out. The transcription factor (TF)-mRNA, lncRNA-miRNA-mRNA, and miRNA-single nucleotide polymorphism (SNP)-mRNA networks were created. Finally, the potential drugs targeting the biomarkers were predicted.

Results

There were 971 DEGs between TOF and control groups, and 29 DE-IRGs were gained through the intersection between DEGs and IRGs. Next, a total of five biomarkers (MARCO, CXCL6, F3, SLC7A2, and SLC7A1) were acquired via two machine learning algorithms. Infiltrating abundance of 18 immune cells was significantly different between TOF and control groups, such as activated B cells, neutrophil, CD56dim natural killer cells, etc. The TF-mRNA network contained 4 mRNAs, 31 TFs, and 33 edges, for instance, ELF1-CXCL6, CBX8-SLC7A2, ZNF423-SLC7A1, ZNF71-F3. The lncRNA-miRNA-mRNA network was created, containing 4 mRNAs, 4 miRNAs, and 228 lncRNAs. Afterwards, nine SNPs locations were identified in the miRNA-SNP-mRNA network. A total of 21 drugs were predicted, such as ornithine, lysine, arginine, etc.

Conclusions

Our findings detected five inflammation-related biomarkers (MARCO, CXCL6, F3, SLC7A2, and SLC7A1) for TOF, providing a scientific reference for further studies of TOF.

Genetic variations in IKZF3, LET7-a2, and CDKN2B-AS1: Exploring associations with metabolic syndrome susceptibility and clinical manifestations

BACKGROUND AND AIM

Metabolic syndrome (MetS) increases the risk of atherosclerosis and diabetes, but there are no approved predictive markers. This study assessed the role of specific genetic variations in MetS susceptibility and their impact on clinical manifestations.

METHOD

In this study, a genotype-phenotype assessment was performed for IKZF3 (rs907091), microRNA-let-7a-2 (rs1143770), and lncRNA-CDKN2B-AS1 (rs1333045).

RESULTS

Analyses indicate that while rs907091 and rs1143770 may have potential associations with MetS susceptibility and an increased risk of atherosclerosis and diabetes, there is an observed trend suggesting that the rs1333045 CC genotype may be associated with a decreased risk of MetS. The genotypes and allele frequencies of rs1333045 were significantly different between studied groups (OR = 0.56, 95% CI 0.38-0.81, p = 0.002, and OR = 0.71, 95% CI 0.55-0.92, p = 0.008), with the CC genotype displaying increased levels of HDL. Furthermore, the rs907091 TT genotype was associated with increased triglyceride, cholesterol, and HOMA index in MetS patients. Subjects with the CC genotype for rs1143770 had higher HbA1c and BMI. In silico analyses illustrated that rs907091 C remarkably influences the secondary structure and the target site of a broad spectrum of microRNAs, especially hsa-miR-4497. Moreover, rs1333045 creates a binding site for seven different microRNAs.

CONCLUSION

Further studies on other populations may help confirm these SNPs as useful predictive markers in assessing the MetS risk.

Phenome-wide association study on miRNA-related sequence variants: the UK Biobank

BACKGROUND

Genetic variants in the coding region could directly affect the structure and expression levels of genes and proteins. However, the importance of variants in the non-coding region, such as microRNAs (miRNAs), remain to be elucidated. Genetic variants in miRNA-related sequences could affect their biogenesis or functionality and ultimately affect disease risk. Yet, their implications and pleiotropic effects on many clinical conditions remain unknown.

METHODS

Here, we utilised genotyping and hospital records data in the UK Biobank (N = 423,419) to investigate associations between 346 genetic variants in miRNA-related sequences and a wide range of clinical diagnoses through phenome-wide association studies. Further, we tested whether changes in blood miRNA expression levels could affect disease risk through colocalisation and Mendelian randomisation analysis.

RESULTS

We identified 122 associations for six variants in the seed region of miRNAs, nine variants in the mature region of miRNAs, and 27 variants in the precursor miRNAs. These included associations with hypertension, dyslipidaemia, immune-related disorders, and others. Nineteen miRNAs were associated with multiple diagnoses, with six of them associated with multiple disease categories. The strongest association was reported between rs4285314 in the precursor of miR-3135b and celiac disease risk (odds ratio (OR) per effect allele increase = 0.37, P = 1.8 × 10-162). Colocalisation and Mendelian randomisation analysis highlighted potential causal role of miR-6891-3p in dyslipidaemia.

CONCLUSIONS

Our study demonstrates the pleiotropic effect of miRNAs and offers insights to their possible clinical importance.

MicroRNA-Related Polymorphism and Their Association with Fibromyalgia

MicroRNAs are tissue-specific expressed short RNAs that serve post-transcriptional gene regulation. A specific microRNA can bind to mRNAs of different genes and thereby suppress their protein production. In the context of the complex phenotype of fibromyalgia, we used the Axiom miRNA Target Site Genotyping Array to search genome-wide for DNA variations in microRNA genes, their regulatory regions, and in the 3'UTR of protein-coding genes. To identify disease-relevant DNA polymorphisms, a cohort of 176 female fibromyalgia patients was studied in comparison to a cohort of 162 healthy women. The association between 48,329 markers and fibromyalgia was investigated using logistic regression adjusted for population stratification. Results show that 29 markers had p-values < 1 × 10^-3, and the strongest association was observed for rs758459 (p-value of 0.0001), located in the Neurogenin 1 gene which is targeted by hsa-miR-130a-3p. Furthermore, variant rs2295963 is predicted to affect binding of hsa-miR-1-3p. Both microRNAs were previously reported to be differentially expressed in fibromyalgia patients. Despite its limited statistical power, this study reports two microRNA-related polymorphisms which may play a functional role in the pathogenesis of fibromyalgia. For a better understanding of the disease pattern, further functional analyses on the biological significance of microRNAs and microRNA-related polymorphisms are required.

The Association of pre-miR27a Gene Polymorphism and Clinicopathological Data in Thai Breast Cancer Patients

BACKGROUND

MiR27a plays an important role in carcinogenesis, cell proliferation, apoptosis, invasion, migration and angiogenesis. Several studies have identified an important role of pre-miR27a (rs895819) A>G polymorphism in several types of cancer. This research aims to investigate the association of pre-miR27a (rs895819) A>G and breast cancer susceptibility, clinicopathological data and survival. Blood DNA samples of 143 Thai breast cancer patients and 100 healthy Thai women were studied for pre-miR27a (rs895819) A>G polymorphism using polymerase chain reaction-restriction fragment-length polymorphism (PCR-RFLP).

RESULTS

The results revealed that the frequency of pre-miR27a (rs895819) A>G genotypes was not statistically significant different between breast cancer patient and normal control subjects. The rs895819 A>G genotype was significantly associated with clinicopathological parameter of grade III differentiation (P = 0.006), progesterone receptor (P = 0.011) and triple negative (P = 0.031) in breast cancer patients, but not with breast cancer susceptibility.

CONCLUSION

The pre-miR27a (rs895819) A>G genotype was significantly associated with poorly differentiated, progesterone receptor and triple-negative in breast cancer patients. Therefore, pre-miR27a (rs895819) A>G may be used as a biomarker for poor prognosis.

Insights into Online microRNA Bioinformatics Tools

MicroRNAs (miRNAs) are members of the small non-coding RNA family regulating gene expression at the post-transcriptional level. MiRNAs have been found to have critical roles in various biological and pathological processes. Research in this field has significantly progressed, with increased recognition of the importance of miRNA regulation. As a result of the vast data and information available regarding miRNAs, numerous online tools have emerged to address various biological questions related to their function and influence across essential cellular processes. This review includes a brief introduction to available resources for an investigation covering aspects such as miRNA sequences, target prediction/validation, miRNAs associated with disease, pathway analysis and genetic variants within miRNAs.

The association between microRNA polymorphisms and the risk of childhood acute lymphoblastic leukemia: A meta-analysis

The aim of this meta-analysis was to determine the relationship between microRNA polymorphisms and the risk of childhood acute lymphoblastic leukemia comprehensively. PubMed, EMBASE, Scopus, Web of Science, the Cochrane Library, Global Index Medicus, Clinicaltrials.gov, ProQuest, and Open Grey databases were used to find relevant papers. Using the STATA 16.0 and CMA 3.0 software, the significance of relationships between microRNA polymorphisms and childhood acute lymphoblastic leukemia risk was evaluated using odds ratios (ORs) and 95 % confidence intervals (95 % CIs) for five genetic models. The results of the meta-analysis showed that there was no significant association between the polymorphism of miR-146a rs2910164 and childhood acute lymphoblastic leukemia risk in different genetic models. Also, in the sensitivity analysis, removing Xue's study from the analysis indicated that both the homozygote and recessive models are significantly affected. Additionally, there was a statistically significant relationship between the polymorphisms of pri-miR-34b/c rs4938723 (in the homozygote and recessive models) and miR-612 rs12803915 (in the allele and dominant models) and childhood acute lymphoblastic leukemia risk. These findings suggest that the rs4938723 and rs12803915 polymorphisms may have a role in the development of childhood acute lymphoblastic leukemia.

Pharmacogenomics deliberations of 2-deoxy-d-glucose in the treatment of COVID-19 disease: an in silico approach

The outbreak of COVID-19 caused by the coronavirus (SARS-CoV-2) prompted number of computational and laboratory efforts to discover molecules against the virus entry or replication. Simultaneously, due to the availability of clinical information, drug-repurposing efforts led to the discovery of 2-deoxy-d-glucose (2-DG) for treating COVID-19 infection. 2-DG critically accumulates in the infected cells to prevent energy production and viral replication. As there is no clarity on the impact of genetic variations on the efficacy and adverse effects of 2-DG in treating COVID-19 using in silico approaches, we attempted to extract the genes associated with the 2-DG pathway using the Comparative Toxicogenomics Database. The interaction between selected genes was assessed using ClueGO, to identify the susceptible gene loci for SARS-CoV infections. Further, SNPs that were residing in the distinct genomic regions were retrieved from the Ensembl genome browser and characterized. A total of 80 SNPs were retrieved using diverse bioinformatics resources after assessing their (a) detrimental influence on the protein stability using Swiss-model, (b) miRNA regulation employing miRNASNP3, PolymiRTS, MirSNP databases, (c) binding of transcription factors by SNP2TFBS, SNPInspector, and (d) enhancers regulation using EnhancerDB and HaploReg reported A2M rs201769751, PARP1 rs193238922 destabilizes protein, six polymorphisms of XIAP effecting microRNA binding sites, EGFR rs712829 generates 15 TFBS, BECN1 rs60221525, CASP9 rs4645980, SLC2A2 rs5393 impairs 14 TFBS, STK11 rs3795063 altered 19 regulatory motifs. These data may provide the relationship between genetic variations and drug effects of 2-DG which may further assist in assigning the right individuals to benefit from the treatment.

Polymorphisms of microRNAs are associated with salt sensitivity in a Han Chinese population: the EpiSS study

The majority of single-nucleotide polymorphism (SNP) association studies of salt sensitivity (SS) have focused on SNPs in protein-coding genes rather than on SNPs in noncoding RNAs. This study attempted to identify the association between whole blood microRNA (miRNA)-related SNPs and the risk of SS in a Han Chinese population. A case-control study of 762 individuals was performed. A modified Sullivan's acute oral saline load and diuresis shrinkage test was used to assess SS. All SNPs were analysed by RT-PCR on a Sequenom Mass ARRAY Platform (Sequenom, San Diego, CA, USA). A genetic risk score (GRS) was used to evaluate the joint genetic effect. In total, 24 miRNA-related SNPs were genotyped, four of which (miR-1307-5p/rs11191676, miR-1307-5p/rs2292807, miR-145/rs41291957 and miR-4638-3p/rs6601178) were associated with both SS and salt sensitivity of blood pressure (SSBP) (p ≤ 0.05). MiR-382-5p/rs4906032 and miR-15b-5/rs10936201 were associated with SSBP. Weighted GRS showed that participants in the second, third and fourth quartiles had 1.760-fold (95% CI: 1.068-2.903), 2.450-fold (95% CI: 1.470-4.083) and 2.774-fold (95% CI: 1.680-4.582) increased risk of SS, respectively. Bioinformatics analysis indicated that these four SNP risk alleles may affect transcription factor binding and influence promoter activity. A total of six miRNA-related SNPs were found to be associated with SS or SSBP, and the presence of multiple risk alleles resulted in increased risk level.

MicroRNA Variants and HLA-miRNA Interactions are Novel Rheumatoid Arthritis Susceptibility Factors

Genome-wide association studies have identified >100 genetic risk factors for rheumatoid arthritis. However, the reported genetic variants could only explain less than 40% heritability of rheumatoid arthritis. The majority of the heritability is still missing and needs to be identified with more studies with different approaches and populations. In order to identify novel function SNPs to explain missing heritability and reveal novel mechanism pathogenesis of rheumatoid arthritis, 4 HLA SNPs (HLA-DRB1, HLA-DRB9, HLA-DQB1, and TNFAIP3) and 225 common SNPs located in miRNA, which might influence the miRNA target binding or pre-miRNA stability, were genotyped in 1,607 rheumatoid arthritis and 1,580 matched normal individuals. We identified 2 novel SNPs as significantly associated with rheumatoid arthritis including rs1414273 (miR-548ac, OR = 0.84, p = 8.26 × 10^-4) and rs2620381 (miR-627, OR = 0.77, p = 2.55 × 10^-3). We also identified that rs5997893 (miR-3928) showed significant epistasis effect with rs4947332 (HLA-DRB1, OR = 4.23, p = 0.04) and rs2967897 (miR-5695) with rs7752903 (TNFAIP3, OR = 4.43, p = 0.03). In addition, we found that individuals who carried 8 risk alleles showed 15.38 (95%CI: 4.69-50.49, p < 1.0 × 10^-6) times more risk of being affected by RA. Finally, we demonstrated that the targets of the significant miRNAs showed enrichment in immune related genes (p = 2.0 × 10^-5) and FDA approved drug target genes (p = 0.014). Overall, 6 novel miRNA SNPs including rs1414273 (miR-548ac, p = 8.26 × 10^-4), rs2620381 (miR-627, p = 2.55 × 10^-3), rs4285314 (miR-3135b, p = 1.10 × 10^-13), rs28477407 (miR-4308, p = 3.44 × 10^-5), rs5997893 (miR-3928, p = 5.9 × 10^-3) and rs45596840 (miR-4482, p = 6.6 × 10^-3) were confirmed to be significantly associated with RA in a Chinese population. Our study suggests that miRNAs might be interesting targets to accelerate understanding of the pathogenesis and drug development for rheumatoid arthritis.

Classical and noncanonical functions of miRNAs in cancers

Alterations in microRNAs (miRNAs) expression are causative in the initiation and progression of human cancers. The molecular events responsible for the widespread differential expression of miRNAs in malignancy are exemplified by their location in cancer-associated genomic regions, epigenetic mechanisms, transcriptional dysregulation, chemical modifications and editing, and alterations in miRNA biogenesis proteins. The classical miRNA function is synonymous with post-transcriptional repression of target protein genes. However, several studies have reported miRNAs functioning outside this paradigm and some of these novel modes of regulation of gene expression have been implicated in cancers. Here, we summarize key aspects of miRNA involvement in cancer, with a special focus on these lesser-studied mechanisms of action.

Integrative assessment of CIP2A overexpression and mutational effects in human malignancies identifies possible deleterious variants

KIAA1524 is the gene encoding the human cancerous inhibitor of PP2A (CIP2A) protein which is regarded as a novel target for cancer therapy. It is overexpressed in 65%-90% of tissues in almost all studied human cancers. CIP2A expression correlates with cancer progression, disease aggressivity in lung cancer besides poor survival and resistance to chemotherapy in breast cancer. Herein, a pan-cancer analysis of public gene expression datasets was conducted showing significant upregulation of CIP2A in cancerous and metastatic tissues. CIP2A overexpression also correlated with poor survival of cancer patients. To determine the non-coding variants associated with CIP2A overexpression, 5'UTR and 3'UTR variants were annotated and scored using RegulomeDB and Enformer deep learning model. The 5'UTR variants rs1239349555, rs1576326380, and rs1231839144 were predicted to be potential regulators of CIP2A overexpression scoring best on RegulomeDB annotations with a high "2a" rank of supporting experimental data. These variants also scored the highest on Enformer predictions. Analysis of the 3'UTR variants of CIP2A predicted rs56255137 and rs58758610 to alter binding sites of hsa-miR-500a-5 and (hsa-miR-3671, hsa-miR-5692a) respectively. Both variants were also found in linkage disequilibrium with rs11709183 and rs147863209 respectively at r² ≥ 0.8. The aforementioned variants were found to be eQTL hits significantly associated with CIP2A overexpression. Further, analysis of rs11709183 and rs147863209 revealed a high "2b" rank on RegulomeDB annotations indicating a probable effect on DNAse transcription factors binding. The MuTarget analysis indicated that somatic mutations in TP53 are significantly associated with upregulated CIP2A in human cancers. Analysis of missense SNPs on CIP2A solved structure predicted seven deleterious effects. Four of these variants were also predicted as structurally and functionally destabilizing to CIP2A including; rs375108755, rs147942716, rs368722879, and rs367941403. Variant rs1193091427 was predicted as a potential intronic splicing mutation that might be responsible for the novel CIP2A variant (NOCIVA) in multiple myeloma. Finally, Enrichment of the Wnt/β-catenin pathway within the CIP2A regulatory gene network suggested potential of therapeutic combinations between FTY720 with Wnt/β-catenin, Plk1 and/or HDAC inhibitors to downregulate CIP2A which has been shown to be essential for the survival of different cancer cell lines.

EpiHNet: Detecting epistasis by heterogeneous molecule network

Epistasis between single nucleotide polymorphisms (SNPs) plays an important role in elucidating the missing heritability of complex diseases. Diverse approaches have been invented for detecting SNP interactions, but they canonically neglect the important and useful connections between SNPs and other bio-molecules (i.e., miRNAs and lncRNAs). To comprehensively model these disease related molecules, a heterogeneous bio-molecular network based solution EpiHNet is introduced for high-order SNP interactions detection. EpiHNet firstly uses case/control data to construct an SNP statistical network, and meta-path based similarity on the heterogeneous network composed with SNPs, genes, lncRNAs, miRNAs and diseases to define another SNP relational network. The SNP relational network can explore and exploit different associations between molecules and diseases to complement the SNP statistical network and search the significantly associated SNPs. Next, EpiHNet integrates these two networks into a composite network, applies the modularity based clustering with fast search strategy to divide SNP nodes into different clusters. After that, it detects SNP interactions based on SNP combinations derived from each cluster. Synthetic experiments on diverse two-locus and three-locus disease models manifest that EpiHNet outperforms competitive baselines, even without the heterogeneous network. For real WTCCC breast cancer data, EpiHNet also demonstrates expressive results on detecting high-order SNP interactions.

Emerging Role of isomiRs in Cancer: State of the Art and Recent Advances

The advent of Next Generation Sequencing technologies brought with it the discovery of several microRNA (miRNA) variants of heterogeneous lengths and/or sequences. Initially ascribed to sequencing errors/artifacts, these isoforms, named isomiRs, are now considered non-canonical variants that originate from physiological processes affecting the canonical miRNA biogenesis. To date, accurate IsomiRs abundance, biological activity, and functions are not completely understood; however, the study of isomiR biology is an area of great interest due to their high frequency in the human miRNome, their putative functions in cooperating with the canonical miRNAs, and potential for exhibiting novel functional roles. The discovery of isomiRs highlighted the complexity of the small RNA transcriptional landscape in several diseases, including cancer. In this field, the study of isomiRs could provide further insights into the miRNA biology and its implication in oncogenesis, possibly providing putative new cancer diagnostic, prognostic, and predictive biomarkers as well. In this review, a comprehensive overview of the state of research on isomiRs in different cancer types, including the most common tumors such as breast cancer, colorectal cancer, melanoma, and prostate cancer, as well as in the less frequent tumors, as for example brain tumors and hematological malignancies, will be summarized and discussed.

Association of Genetic Variants Affecting microRNAs and Pancreatic Cancer Risk

Genetic factors play an important role in the susceptibility to pancreatic cancer (PC). However, established loci explain a small proportion of genetic heritability for PC; therefore, more progress is needed to find the missing ones. We aimed at identifying single nucleotide polymorphisms (SNPs) affecting PC risk through effects on micro-RNA (miRNA) function. We searched in silico the genome for SNPs in miRNA seed sequences or 3 prime untranslated regions (3'UTRs) of miRNA target genes. Genome-wide association data of PC cases and controls from the Pancreatic Cancer Cohort (PanScan) Consortium and the Pancreatic Cancer Case-Control (PanC4) Consortium were re-analyzed for discovery, and genotyping data from two additional consortia (PanGenEU and PANDoRA) were used for replication, for a total of 14,062 cases and 11,261 controls. None of the SNPs reached genome-wide significance in the meta-analysis, but for three of them the associations were in the same direction in all the study populations and showed lower value of p in the meta-analyses than in the discovery phase. Specifically, rs7985480 was consistently associated with PC risk (OR = 1.12, 95% CI 1.07-1.17, p = 3.03 × 10-6 in the meta-analysis). This SNP is in linkage disequilibrium (LD) with rs2274048, which modulates binding of various miRNAs to the 3'UTR of UCHL3, a gene involved in PC progression. In conclusion, our results expand the knowledge of the genetic PC risk through miRNA-related SNPs and show the usefulness of functional prioritization to identify genetic polymorphisms associated with PC risk.

Recent development of bioinformatics tools for microRNA target prediction

MicroRNAs (miRNAs) are central players that regulate the post-transcriptional processes of gene expression. Binding of miRNAs to target mRNAs can repress their translation by inducing the degradation or by inhibiting the translation of the target mRNAs. High-throughput experimental approaches for miRNA target identification are costly and time-consuming, depending on various factors. It is vitally important to develop the bioinformatics methods for accurately predicting miRNA targets. With the increase of RNA sequences in the post-genomic era, bioinformatics methods are being developed for miRNA studies specially for miRNA target prediction. This review summarizes the current development of state-of-the-art bioinformatics tools for miRNA target prediction, points out the progress and limitations of the available miRNA databases, and their working principles. Finally, we discuss the caveat and perspectives of the next-generation algorithms for the prediction of miRNA targets.

Conceptualization of functional single nucleotide polymorphisms of polycystic ovarian syndrome genes: an in silico approach

PURPOSE

Polycystic ovarian syndrome (PCOS) is a multi-faceted endocrinopathy frequently observed in reproductive-aged females, causing infertility. Cumulative evidence revealed that genetic and epigenetic variations, along with environmental factors, were linked with PCOS. Deciphering the molecular pathways of PCOS is quite complicated due to the availability of limited molecular information. Hence, to explore the influence of genetic variations in PCOS, we mapped the GWAS genes and performed a computational analysis to identify the SNPs and their impact on the coding and non-coding sequences.

METHODS

The causative genes of PCOS were searched using the GWAS catalog, and pathway analysis was performed using ClueGO. SNPs were extracted using an Ensembl genome browser, and missense variants were shortlisted. Further, the native and mutant forms of the deleterious SNPs were modeled using I-TASSER, Swiss-PdbViewer, and PyMOL. MirSNP, PolymiRTS, miRNASNP3, and SNP2TFBS, SNPInspector databases were used to find SNPs in the miRNA binding site and transcription factor binding site (TFBS), respectively. EnhancerDB and HaploReg were used to characterize enhancer SNPs. Linkage Disequilibrium (LD) analysis was performed using LDlink.

RESULTS

25 PCOS genes showed interaction with 18 pathways. 7 SNPs were predicted to be deleterious using different pathogenicity predictions. 4 SNPs were found in the miRNA target site, TFBS, and enhancer sites and were in LD with reported PCOS GWAS SNPs.

CONCLUSION

Computational analysis of SNPs residing in PCOS genes may provide insight into complex molecular interactions among genes involved in PCOS pathophysiology. It may also aid in determining the causal variants and consequently contributing to predicting disease strategies.

Role of SNPs in the Biogenesis of Mature miRNAs

Single nucleotide polymorphisms (SNPs) play a significant role in microRNA (miRNA) generation, processing, and function and contribute to multiple phenotypes and diseases. Therefore, whole-genome analysis of how SNPs affect miRNA maturation mechanisms is important for precision medicine. The present study established an SNP-associated pre-miRNA (SNP-pre-miRNA) database, named miRSNPBase, and constructed SNP-pre-miRNA sequences. We also identified phenotypes and disease biomarker-associated isoform miRNA (isomiR) based on miRFind, which was developed in our previous study. We identified functional SNPs and isomiRs. We analyzed the biological characteristics of functional SNPs and isomiRs and studied their distribution in different ethnic groups using whole-genome analysis. Notably, we used individuals from Great Britain (GBR) as examples and identified isomiRs and isomiR-associated SNPs (iso-SNPs). We performed sequence alignments of isomiRs and miRNA sequencing data to verify the identified isomiRs and further revealed GBR ethnographic epigenetic dominant biomarkers. The SNP-pre-miRNA database consisted of 886 pre-miRNAs and 2640 SNPs. We analyzed the effects of SNP type, SNP location, and SNP-mediated free energy change during mature miRNA biogenesis and found that these factors were closely associated to mature miRNA biogenesis. Remarkably, 158 isomiRs were verified in the miRNA sequencing data for the 18 GBR samples. Our results indicated that SNPs affected the mature miRNA processing mechanism and contributed to the production of isomiRs. This mechanism may have important significance for epigenetic changes and diseases.

Family-based association study identifies SNAP25 as a susceptibility gene for autism in the Han Chinese population

Autism is a neurodevelopmental disorder with high heritability. Synaptosome associated protein 25 (SNAP25) encodes a presynaptic membrane-binding protein. It plays a crucial role in neurotransmission and may be involved in the pathogenesis of autism. However, the association between SNAP25 and autism in the Han Chinese population remains unclear. To investigate whether single nucleotide polymorphisms (SNPs) in SNAP25 contribute to the risk of autism, we performed a family-based association study of 14 tagSNPs in SNAP25 in 640 Han Chinese autism trios. Our results demonstrated that rs363018 in SNAP25 was significantly associated with autism under both additive (A > G, Z = 3.144, P = .0017) and recessive models (A > G, Z = 3.055, P = .0023) after Bonferroni correction (P < .0036). An additional SNP, rs8636, was nominally associated with autism under the recessive model (C > T, Z = 1.972, P = .0487). Haplotype-based association test revealed that haplotypes A-T (Z = 2.038, P = .0415) and G-T (Z = -3.114, P = .0018) of rs363018-rs362582 were significantly associated with autism after the permutation test (P = .0158). These findings suggest that SNAP25 may represent a susceptibility gene for autism in the Han Chinese population.

Functional correlations between CXCL10/IP10 gene polymorphisms and risk of Kawasaki disease

BACKGROUND

Kawasaki disease (KD) is an acute systemic vasculitis syndrome with unknown pathogen. The immune system has been suggested to involve in the pathogenesis in KD. IP10 is a chemoattractant for initiating T-cell activation. The aim of this study was to investigate the association between genetic polymorphisms of IP10 and KD.

METHODS

A total of 354 KD patients and 1,709 control subjects (709 subjects in cohort 1 and 1,000 subjects in cohort 2) were enrolled in this study. Four tagging single nucleotide polymorphisms (rs3921, rs4256246, rs4508917, and rs4386624) were chosen for genotyping.

RESULTS

Our results indicated that CC genotype of rs3921 and GG genotype of rs4386624 had higher frequency in KD patients compared to control. In addition, higher plasma IP10 level was observed in CC genotype of rs3921 than CG genotype and GG genotype. C/G haplotype carriers of rs3921/rs4386624 had 5.48-fold risk for KD compared to G/C haplotype carriers. Two-locus analysis further showed the combinatorial effects of rs3921 and rs4386624 in KD susceptibility.

CONCLUSIONS

This study indicated the close correlation between IP10 and the risk of Kawasaki disease.

miRNASNP-v3: a comprehensive database for SNPs and disease-related variations in miRNAs and miRNA targets

MicroRNAs (miRNAs) related single-nucleotide variations (SNVs), including single-nucleotide polymorphisms (SNPs) and disease-related variations (DRVs) in miRNAs and miRNA-target binding sites, can affect miRNA functions and/or biogenesis, thus to impact on phenotypes. miRNASNP is a widely used database for miRNA-related SNPs and their effects. Here, we updated it to miRNASNP-v3 (http://bioinfo.life.hust.edu.cn/miRNASNP/) with tremendous number of SNVs and new features, especially the DRVs data. We analyzed the effects of 7 161 741 SNPs and 505 417 DRVs on 1897 pre-miRNAs (2630 mature miRNAs) and 3'UTRs of 18 152 genes. miRNASNP-v3 provides a one-stop resource for miRNA-related SNVs research with the following functions: (i) explore associations between miRNA-related SNPs/DRVs and diseases; (ii) browse the effects of SNPs/DRVs on miRNA-target binding; (iii) functional enrichment analysis of miRNA target gain/loss caused by SNPs/DRVs; (iv) investigate correlations between drug sensitivity and miRNA expression; (v) inquire expression profiles of miRNAs and their targets in cancers; (vi) browse the effects of SNPs/DRVs on pre-miRNA secondary structure changes; and (vii) predict the effects of user-defined variations on miRNA-target binding or pre-miRNA secondary structure. miRNASNP-v3 is a valuable and long-term supported resource in functional variation screening and miRNA function studies.

Genetic variability in noncoding RNAs: involvement of miRNAs and long noncoding RNAs in osteoporosis pathogenesis

The pathogenesis of osteoporosis is multifactorial and is the consequence of genetic, hormonal and lifestyle factors. Epigenetics, including noncoding RNA (ncRNA) deregulation, represents a link between susceptibility to develop the disease and environmental influences. The majority of studies investigated the expression of ncRNAs in osteoporosis patients; however, very little information is available on their genetic variability. In this review, we focus on two classes of ncRNAs: miRNAs and long noncoding RNAs (lncRNAs). We summarize recent findings on how polymorphisms in miRNAs and lncRNAs can perturb the lncRNA/miRNA/mRNA axis and may be involved in osteoporosis clinical outcome. We also provide a general overview on databases and bioinformatic tools useful for associating miRNAs and lncRNAs variability with complex genetic diseases.

ncRNAVar: A Manually Curated Database for Identification of Noncoding RNA Variants Associated with Human Diseases

While variants of noncoding RNAs (ncRNAs) have been experimentally validated as a new class of biomarkers and drug targets, the discovery and interpretation of relationships between ncRNA variants and human diseases become important and challenging. Here we present ncRNAVar (http://www.liwzlab.cn/ncrnavar/), the first database that provides association data between validated ncRNA variants and human diseases through manual curation on 2650 publications and computational annotation. ncRNAVar contains 4565 associations between 711 human disease phenotypes and 3112 variants from 2597 ncRNAs. Each association was reviewed by professional curators, incorporated with valuable annotation and cross references, and designated with an association score by our refined score model. ncRNAVar offers web applications including association prioritization, network visualization, and relationship mapping. ncRNAVar, presenting a landscape of ncRNA variants in human diseases and a useful resource for subsequent software development, will improve our insight of relationships between ncRNA variants and human health.

Pan-cancer analysis of somatic mutations in miRNA genes

Background

miRNAs are considered important players in oncogenesis, serving either as oncomiRs or suppressormiRs. Although the accumulation of somatic alterations is an intrinsic aspect of cancer development and many important cancer-driving mutations have been identified in protein-coding genes, the area of functional somatic mutations in miRNA genes is heavily understudied.

Methods

Here, based on the analysis of large genomic datasets, mostly the whole-exome sequencing of over 10,000 cancer/normal sample pairs deposited within the TCGA repository, we undertook an analysis of somatic mutations in miRNA genes.

Findings

We identified and characterized over 10,000 somatic mutations and showed that some of the miRNA genes are overmutated in Pan-Cancer and/or specific cancers. Nonrandom occurrence of the identified mutations was confirmed by a strong association of overmutated miRNA genes with KEGG pathways, most of which were related to specific cancer types or cancer-related processes. Additionally, we showed that mutations in some of the overmutated genes correlate with miRNA expression, cancer staging, and patient survival.

Interpretation

Our study is the first comprehensive Pan-Cancer study of cancer somatic mutations in miRNA genes. It may help to understand the consequences of mutations in miRNA genes and the identification of miRNA functional mutations. The results may also be the first step (form the basis and provide the resources) in the development of computational and/or statistical approaches/tools dedicated to the identification of cancer-driver miRNA genes.

Funding

This work was supported by research grants from the Polish National Science Centre 2016/22/A/NZ2/00184 and 2015/17/N/NZ3/03629.

Annotation of susceptibility SNPs associated with atrial fibrillation

OBJECTIVE

Genome-wide association studies (GWAS) and the candidate gene based association studies have identified a panel of variants associated with atrial fibrillation (AF), however, most of the identified single nucleotide polymorphisms (SNPs) were found located within intergenic or intronic genomic regions, and whether the positive SNPs have a real biological function is unknown, and the real disease causing gene need to be studied.

RESULTS

The current results of the genetic studies including common variants identified by GWAS (338 index SNPs) and candidate gene based association studies (40 SNPs) were summarized.

CONCLUSION

Our study suggests the relationship between genetic variants and possible targeted genes, and provides insight into potential genetic pathways underlying AF incidence and development. The results may provide an encyclopedia of AF susceptibility SNPs and shed light on the functional mechanisms of AF variants identified through genetic studies.

METHODS

We summarized AF susceptibility SNPs identified by GWAS and candidate gene based association studies, and give a comprehensive functional annotation of all these AF susceptibility loci. by genomic annotation, microRNA binding prediction, promoter activity analysis, enhancer activity analysis, transcription factors binding activity prediction, expression quantitative trait loci (eQTL) analysis, long-range transcriptional regulatory function analysis, gene ontology and pathway enrichment analysis.

miR-499 rs3746444 and miR-196a-2 rs11614913 Are Associated with the Risk of Glioma, but Not the Prognosis

Previous studies of correlations of microRNA (miR)-499 rs3746444 and miR-196a-2 rs11614913 polymorphisms with glioma risk have yielded inconsistent results. In this study, relationships between these two polymorphisms and glioma risk and survival were evaluated. In total, 605 patients and 1,300 controls were genotyped. rs3746444 increased glioma risk in five genetic models (GA versus AA, odds ratio [OR], 95% confidence interval [CI] = 1.31 [1.05–1.66], p = 0.02; GG versus AA, OR [95% CI] = 10.70 [6.13–18.69], p < 0.0001; GA + GG versus AA, OR [95% CI] = 1.82 [1.47–2.24], p < 0.0001; GG versus AA + GA, OR [95% CI] = 9.99 [5.74–17.40], p < 0.0001; G versus A, OR [95% CI] = 2.18 [1.82–2.60], p < 0.0001). rs11614913 decreased glioma risk in a recessive model (OR [95% CI] = 0.79 [0.64–0.97], p = 0.03). No relationships between either SNP and survival were found. rs3746444 in the miR-499 seed region could affect target recognition. Bioinformatics analyses indicated that miR-499 rs3746444 is involved in various biological processes and pathways, including “cell adhesion molecule binding,” “positive regulation of catabolic process,” “NF-kappa B pathway,” and “PI3K-Akt pathway,” by targeting mRNAs. Our results suggested that miR-499 rs3746444 and miR-196a-2 rs11614913 have crucial roles in glioma susceptibility.

ncRPheno: a comprehensive database platform for identification and validation of disease related noncoding RNAs

Noncoding RNAs (ncRNAs) play critical roles in many critical biological processes and have become a novel class of potential targets and bio-markers for disease diagnosis, therapy, and prognosis. Annotating and analysing ncRNA-disease association data are essential but challenging. Current computational resources lack comprehensive database platforms to consistently interpret and prioritize ncRNA-disease association data for biomedical investigation and application. Here, we present the ncRPheno database platform (http://lilab2.sysu.edu.cn/ncrpheno), which comprehensively integrates and annotates ncRNA-disease association data and provides novel searches, visualizations, and utilities for association identification and validation. ncRPheno contains 482,751 non-redundant associations between 14,494 ncRNAs and 3,210 disease phenotypes across 11 species with supporting evidence in the literature. A scoring model was refined to prioritize the associations based on evidential metrics. Moreover, ncRPheno provides user-friendly web interfaces, novel visualizations, and programmatic access to enable easy exploration, analysis, and utilization of the association data. A case study through ncRPheno demonstrated a comprehensive landscape of ncRNAs dysregulation associated with 22 cancers and uncovered 821 cancer-associated common ncRNAs. As a unique database platform, ncRPheno outperforms the existing similar databases in terms of data coverage and utilities, and it will assist studies in encoding ncRNAs associated with phenotypes ranging from genetic disorders to complex diseases.

ABBREVIATIONS

APIs: application programming interfaces; circRNA: circular RNA; ECO: Evidence & Conclusion Ontology; EFO: Experimental Factor Ontology; FDR: false discovery rate; GO: Gene Ontology; GWAS: genome wide association studies; HPO: Human Phenotype Ontology; ICGC: International Cancer Genome Consortium; lncRNA: long noncoding RNA; miRNA: micro RNA; ncRNA: noncoding RNA; NGS: next generation sequencing; OMIM: Online Mendelian Inheritance in Man; piRNA: piwi-interacting RNA; snoRNA: small nucleolar RNA; TCGA: The Cancer Genome Atlas.

Pancan-meQTL: a database to systematically evaluate the effects of genetic variants on methylation in human cancer

DNA methylation is an important epigenetic mechanism for regulating gene expression. Aberrant DNA methylation has been observed in various human diseases, including cancer. Single-nucleotide polymorphisms can contribute to tumor initiation, progression and prognosis by influencing DNA methylation, and DNA methylation quantitative trait loci (meQTL) have been identified in physiological and pathological contexts. However, no database has been developed to systematically analyze meQTLs across multiple cancer types. Here, we present Pancan-meQTL, a database to comprehensively provide meQTLs across 23 cancer types from The Cancer Genome Atlas by integrating genome-wide genotype and DNA methylation data. In total, we identified 8 028 964 cis-meQTLs and 965 050 trans-meQTLs. Among these, 23 432 meQTLs are associated with patient overall survival times. Furthermore, we identified 2 214 458 meQTLs that overlap with known loci identified through genome-wide association studies. Pancan-meQTL provides a user-friendly web interface (http://bioinfo.life.hust.edu.cn/Pancan-meQTL/) that is convenient for browsing, searching and downloading data of interest. This database is a valuable resource for investigating the roles of genetics and epigenetics in cancer.

Mismatched and wobble base pairs govern primary microRNA processing by human Microprocessor

MicroRNAs (miRNAs) are small RNAs that regulate gene expression. miRNAs are produced from primary miRNAs (pri-miRNAs), which are cleaved by Microprocessor. Microprocessor, therefore, plays a crucial role in determining the efficiency and precision of miRNA production, and thus the function of the final miRNA product. Here, we conducted high-throughput enzymatic assays to investigate the catalytic mechanism of Microprocessor cleaving randomized pri-miRNAs. We identified multiple mismatches and wobble base pairs in the upper stem of pri-miRNAs, which influence the efficiency and accuracy of their processing. The existence of these RNA elements helps to explain the alternative cleavage of Microprocessor for some human pri-miRNAs. We also demonstrated that miRNA biogenesis can be altered via modification of the RNA elements by RNA-editing events or single nucleotide polymorphisms (SNPs). These findings improve our understanding of pri-miRNA processing mechanisms and provide a foundation for interpreting differential miRNA expression due to RNA modifications and SNPs.

MicroRNA genes are transcribed to long primary transcripts called primary microRNAs, which are cleaved by Microprocessor. Here the authors employ high-throughput sequencing and Microprocessor assay to show that mismatches and wobble base pairs in primary microRNAs affect the accuracy and efficiency of Microprocessor processing.

dbMTS: A comprehensive database of putative human microRNA target site SNVs and their functional predictions

MicroRNAs (miRNA) are short noncoding RNAs that can repress the expression of protein-coding messenger RNAs (mRNAs) by binding to the 3'-untranslated region (UTR) of the target. Genetic mutations such as single nucleotide variants (SNVs) in the 3'-UTR of the mRNAs can disrupt miRNA regulation. In this study, we presented dbMTS, a database for miRNA target site (MTS) SNVs and their functional annotations. This database can help studies easily identify putative SNVs that affect miRNA targeting and facilitate the prioritization of their functional importance. dbMTS is freely available for academic use at http://database.liulab.science/dbMTS as a web service or a downloadable attached database of dbNSFP.

A review of databases predicting the effects of SNPs in miRNA genes or miRNA-binding sites

Modern precision medicine comprises the knowledge and understanding of individual differences in the genomic sequence of patients to provide tailor-made treatments. Regularly, such variants are considered in coding regions only, and their effects are predicted based on their impact on the amino acid sequence of expressed proteins. However, assessing the effects of variants in noncoding elements, in particular microRNAs (miRNAs) and their binding sites, is important as well, as a single miRNA can influence the expression patterns of many genes at the same time. To analyze the effects of variants in miRNAs and their target sites, several databases storing variant impact predictions have been published. In this review, we will compare the core functionalities and features of these databases and discuss the importance of up-to-date data resources in the context of web applications. Finally, we will outline some recommendations for future developments in the field.

Prevalence and architecture of posttranscriptionally impaired synonymous mutations in 8,320 genomes across 22 cancer types

Somatic synonymous mutations are one of the most frequent genetic variants occurring in the coding region of cancer genomes, while their contributions to cancer development remain largely unknown. To assess whether synonymous mutations involved in post-transcriptional regulation contribute to the genetic etiology of cancers, we collected whole exome data from 8,320 patients across 22 cancer types. By employing our developed algorithm, PIVar, we identified a total of 22,948 posttranscriptionally impaired synonymous SNVs (pisSNVs) spanning 2,042 genes. In addition, 35 RNA binding proteins impacted by these identified pisSNVs were significantly enriched. Remarkably, we discovered markedly elevated ratio of somatic pisSNVs across all 22 cancer types, and a high pisSNV ratio was associated with worse patient survival in five cancer types. Intriguing, several well-established cancer genes, including PTEN, RB1 and PIK3CA, appeared to contribute to tumorigenesis at both protein function and posttranscriptional regulation levels, whereas some pisSNV-hosted genes, including UBR4, EP400 and INTS1, exerted their function during carcinogenesis mainly via posttranscriptional mechanisms. Moreover, we predicted three drugs associated with two pisSNVs, and numerous compounds associated with expression signature of pisSNV-hosted genes. Our study reveals the prevalence and clinical relevance of pisSNVs in cancers, and emphasizes the importance of considering posttranscriptional impaired synonymous mutations in cancer biology.

Investigating the role of microRNA-27a gene polymorphisms and its interactive effect with risk factors in gastrointestinal cancers

Gastrointestinal (GI) cancers are known to have a high incidence worldwide and require an early diagnosis to successfully treat them, providing higher survival rates and better quality of life for the patients. MicroRNA-27a is a well-known oncogene that plays a significant role in various GI cancers. It is known to upregulate the expression of numerous oncogenes leading to cancer progression. The miR-27a harbors two polymorphisms rs895819 and rs11671784 which alter the disease susceptibility by interfering with the maturation and expression of miR-27a. In the current study, we aimed to investigate the role played by these polymorphisms in cancers of the GI tract. We conducted a case-control study with 210 GI cancer cases and 210 cancer-free controls to analyze the effect of these polymorphisms. The rs895819 polymorphism was genotyped using PCR-RFLP, and rs11671784 was genotyped on a MassARRAY platform. The association analysis failed to bring out any significant association of the polymorphisms with GI cancer risk. However, genotype-phenotype interaction analysis revealed that the rs895819 was found to increase the risk GI cancers along with the presence of risk factors such as socioeconomic status, diabetes mellitus, hypertension, alcohol consumption, and tobacco chewing.

Clinical relevance of the lnc-HNF1B-3:1 genetic polymorphisms in Western Chinese tuberculosis patients

BACKGROUND

Tuberculosis remains a global public health problem. Genetic polymorphisms may affect the susceptibility, clinical characteristics, and adverse drug reactions of patients with TB. The present study aimed to examine the association of single nucleotide polymorphisms of lncRNA-HNF1B-3:1 with the clinical manifestation of TB in a Western Chinese population.

METHOD

A total of 526 tuberculosis patients and 561 healthy subjects were recruited in Western China. The correlation between lnc-HNF1B-3:1 polymorphism and tuberculosis susceptibility was investigated. Moreover, the influence on adverse drug reactions following treatment was explored. A total of 7 SNPs within the lnc-HNF1B-3:1 locus was genotyped by the improved multiplex ligation detection reaction method.

RESULTS

No significant associations were noted between TB susceptibility and the presence of all 7 SNPs of the lnc-HNF1B-3:1 as determined by single-locus analysis (All P > .05). The AA genotype of rs12939622 (in the dominant model) and the AA genotype of rs4262994 (in the recessive model) caused increased susceptibility of the subjects to fever (P < .001 and P = .008, respectively). The Rs2542670 G allele was associated with increased risk of thrombocytopenia, leukopenia, and chronic kidney damage following drug administration (P = .007, .029, .003, respectively).

CONCLUSION

The present study reported for the first time that the rs12939622, rs4262994 and rs2542670 genotypes in lnc-HNF1B-3:1 locus may influence the clinical manifestations of tuberculosis.

Evaluation of polymorphisms in microRNA-binding sites and pancreatic cancer risk in Chinese population

As promising biomarkers and therapy targets, microRNAs (miRNAs) are involved in various physiological and tumorigenic processes. Genetic variants in miRNA‐binding sites can lead to dysfunction of miRNAs and contribute to disease. However, systematic investigation of the miRNA‐related single nucleotide polymorphisms (SNPs) for pancreatic cancer (PC) risk remains elusive. We performed integrative bioinformatics analyses to select 31 SNPs located in miRNA‐target binding sites using the miRNASNP v2.0, a solid database providing miRNA‐related SNPs for genetic research, and investigated their associations with risk of PC in two large case‐control studies totally including 1847 cases and 5713 controls. We observed that the SNP rs3802266 is significantly associated with increased risk of PC (odds ratio (OR) = 1.21, 95% confidence intervals (CI) = 1.11‐1.31, P = 1.29E‐05). Following luciferase reporter gene assays show that rs3802266‐G creates a stronger binding site for miR‐181a‐2‐3p in 3′ untranslated region (3′UTR) of the gene ZHX2. Expression quantitative trait loci (eQTL) analysis suggests that ZHX2 expression is lower in individuals carrying rs3802266‐G with increased PC risk. In conclusion, our findings highlight the involvement of miRNA‐binding SNPs in PC susceptibility and provide new clues for PC carcinogenesis.

Computational resources associating diseases with genotypes, phenotypes and exposures

The causes of a disease and its therapies are not only related to genotypes, but also associated with other factors, including phenotypes, environmental exposures, drugs and chemical molecules. Distinguishing disease-related factors from many neutral factors is critical as well as difficult. Over the past two decades, bioinformaticians have developed many computational resources to integrate the omics data and discover associations among these factors. However, researchers and clinicians are experiencing difficulties in choosing appropriate resources from hundreds of relevant databases and software tools. Here, in order to assist the researchers and clinicians, we systematically review the public computational resources of human diseases related to genotypes, phenotypes, environment factors, drugs and chemical exposures. We briefly describe the development history of these computational resources, followed by the details of the relevant databases and software tools. We finally conclude with a discussion of current challenges and future opportunities as well as prospects on this topic.

MSDD: a manually curated database of experimentally supported associations among miRNAs, SNPs and human diseases

The MiRNA SNP Disease Database (MSDD, http://www.bio-bigdata.com/msdd/) is a manually curated database that provides comprehensive experimentally supported associations among microRNAs (miRNAs), single nucleotide polymorphisms (SNPs) and human diseases. SNPs in miRNA-related functional regions such as mature miRNAs, promoter regions, pri-miRNAs, pre-miRNAs and target gene 3′-UTRs, collectively called ‘miRSNPs’, represent a novel category of functional molecules. miRSNPs can lead to miRNA and its target gene dysregulation, and resulting in susceptibility to or onset of human diseases. A curated collection and summary of miRSNP-associated diseases is essential for a thorough understanding of the mechanisms and functions of miRSNPs. Here, we describe MSDD, which currently documents 525 associations among 182 human miRNAs, 197 SNPs, 153 genes and 164 human diseases through a review of more than 2000 published papers. Each association incorporates information on the miRNAs, SNPs, miRNA target genes and disease names, SNP locations and alleles, the miRNA dysfunctional pattern, experimental techniques, a brief functional description, the original reference and additional annotation. MSDD provides a user-friendly interface to conveniently browse, retrieve, download and submit novel data. MSDD will significantly improve our understanding of miRNA dysfunction in disease, and thus, MSDD has the potential to serve as a timely and valuable resource.

An Approach to Identify Individual Functional Single Nucleotide Polymorphisms and Isoform MicroRNAs

MicroRNAs (miRNAs) and single nucleotide polymorphisms (SNPs) play important roles in disease risk and development, especially cancer. Importantly, when SNPs are located in pre-miRNAs, they affect their splicing mechanism and change the function of miRNAs. To improve disease risk assessment, we propose an approach and developed a software tool, IsomiR_Find, to identify disease/phenotype-related SNPs and isomiRs in individuals. Our approach is based on the individual's samples, with SNP information extracted from the 1000 Genomes Project. SNPs were mapped to pre-miRNAs based on whole-genome coordinates and then SNP-pre-miRNA sequences were constructed. Moreover, we developed matpred2, a software tool to identify the four splicing sites of mature miRNAs. Using matpred2, we identified isomiRs and then verified them by searching within individual miRNA sequencing data. Our approach yielded biomarkers for biological experiments, mined functions of miRNAs and SNPs, improved disease risk assessment, and provided a way to achieve individualized precision medicine.

3'-UTR Polymorphisms in the Vascular Endothelial Growth Factor Gene (VEGF) Contribute to Susceptibility to Recurrent Pregnancy Loss (RPL)

Numerous studies have examined the genetic association of vascular endothelial growth factor (VEGF) single nucleotide polymorphisms (SNPs) with recurrent pregnancy loss (RPL). However, of the four known SNPs in the 3′-untranslated region (3′-UTR) of VEGF, three SNPs—namely rs3025040 (1451C>T), rs10434 (1612G>A), and rs3025053 (1725G>A)—remain poorly characterized with regard to RPL. Herein, we evaluated the association between these three SNPs in the VEGF 3′-UTR and RPL susceptibility. We analyzed VEGF 3′-UTR gene variants in with and without RPL using TaqMan allelic discrimination. There were significant differences in the genotype frequencies of 1612G>A (GA: adjusted odds ratio (AOR), 0.652; 95% confidence interval (CI), 0.447–0.951; p = 0.026) and 1725G>A (GA: AOR, 0.503; 95% CI, 0.229–0.848; p = 0.010) in RPL patients vs. controls. Our results indicate that the 1612G>A and 1725G>A polymorphisms in the 3′-UTR of VEGF are associated with RPL susceptibility in Korean women. These data suggest that VEGF 3′-UTR polymorphisms may be utilized as biomarkers for the detection of RPL risk and prevention.

Association and in silico investigations of miR-302c insertion/deletion variant as a novel biomarker with susceptibility to gastric cancer

Gastric cancer (GC) is the fifth most prevalent malignant tumor and the third most frequent cause of cancer mortality worldwide. rs199971565 is an insertion/deletion (INDEL) located in microRNA-302c (miR-302c) seed site, which may affect its function and biogenesis. There is no genetic association study investigating this INDEL with any disease till now. Thus, the current study was conducted to investigate the association of rs199971565 with susceptibility to GC in an Iranian population. In addition, in silico studies were performed to reveal the possible functional significance of this INDEL. A total of 378 subjects were genotyped through amplification refractory mutation system PCR (ARMS-PCR) after DNA extraction from peripheral blood by the salting out procedure. Also, in silico analyses were performed through databases and web tools including MiRNASNP V2.0, miRWalk V2.0, miRTarBase, DAVID V6.8, RNAfold, PHDcleave, miRmap, and STarMir. Results revealed that there was an association between rs199971565 and the incidence risk of GC under a recessive (P = .04, odds ratio [OR] = 18.73; 95% confidence interval [CI] = 1.07-326.95) model of inheritance. Also, compared to the Ins allele, the Del allele significantly increased the risk of GC (P = .01, OR = 2.02; 95% CI = 1.11-3.66). Further analyses showed no significant association in age and sex between two study groups (P = .216 and P = .798, respectively). In conclusion, for the first time, this study indicated the association and in silico investigations of rs199971565 and suggested it as a novel INDEL biomarker located in the seed site of miR-302c, which may have crucial roles in the susceptibility to GC and its incidence risk.

MiR-21 binding site SNP within ITGAM associated with psoriasis susceptibility in women

BACKGROUND

Great progress has been made in the understanding of inflammatory processes in psoriasis. However, clarifying the role of genetic variability in processes regulating inflammation, including post-transcriptional regulation by microRNA (miRNA), remains a challenge.

OBJECTIVES

We therefore investigated single nucleotide polymorphisms (SNPs) with a predicted change in the miRNA/mRNA interaction of genes involved in the psoriasis inflammatory processes.

METHODS

Studied SNPs rs2910164 C/G-miR-146a, rs4597342 T/C-ITGAM, rs1368439 G/T-IL12B, rs1468488 C/T-IL17RA were selected using a bioinformatics analysis of psoriasis inflammation-associated genes. These SNPs were then genotyped using a large cohort of women with psoriasis (n = 241) and healthy controls (n = 516).

RESULTS

No significant association with psoriasis was observed for rs2910164, rs1368439, and rs1468488 genotypes. However, the major allele T of rs4597342 -ITGAM was associated with approximately 28% higher risk for psoriasis in comparison to the patients with the C allele (OR = 1.28, 95% CI 1.01-1.61, p = 0.037). In case of genotypes, the effect of the T allele indicates the dominant model of disease penetrance as the CT and TT genotypes increase the chance of psoriasis up to 42% in comparison to CC homozygotes of rs4597342 (OR = 1.42, 95% CI = 1.05-1.94, p = 0.025).

CONCLUSION

SNP rs4597342 in 3'UTR of ITGAM influencing miR-21 binding may be considered a risk factor for psoriasis development. Upregulated miR-21 in psoriasis is likely to inhibit CD11b production in the case of the rs4597342 T allele which may lead to Mac-1 dysfunction, resulting in an aberrant function of innate immune cells and leading to the production of cytokines involved in psoriasis pathogenesis.

In silico genome-wide miRNA-QTL-SNPs analyses identify a functional SNP associated with mastitis in Holsteins

Background

Single-nucleotide polymorphisms (SNPs) in microRNAs (miRNAs) and their target binding sites affect miRNA function and are involved in biological processes and diseases, including bovine mastitis, a frequent inflammatory disease. Our previous study has shown that bta-miR-2899 is significantly upregulated in the mammary gland tissue of mastitis-infected cow than that of healthy cows.

Results

In the present study, we used a customized miRNAQTLsnp software and identified 5252 SNPs in 691 bovine pre-miRNAs, which are also located within the quantitative trait loci (QTLs) that are associated with mastitis and udder conformation-related traits. Using luciferase assay in the bovine mammary epithelial cells, we confirmed a candidate SNP (rs109462250, g. 42,198,087 G > A) in the seed region of bta-miR-2899 located in the somatic cell score (SCS)-related QTL (Chr.18: 33.9–43.9 Mbp), which affected the interaction of bta-miR-2899 and its putative target Spi-1 proto-oncogene (SPI1), a pivotal regulator in the innate and adaptive immune systems. Quantitative real-time polymerase chain reaction results showed that the relative expression of SPI1 in the mammary gland of AA genotype cows was significantly higher than that of GG genotype cows. The SNP genotypes were associated with SCS in Holstein cows.

Conclusions

Altogether, miRNA-related SNPs, which influence the susceptibility to mastitis, are one of the plausible mechanisms underlying mastitis via modulating the interaction of miRNAs and immune-related genes. These miRNA-QTL-SNPs, such as the SNP (rs109462250) of bta-miR-2899 may have implication for the mastitis resistance breeding program in Holstein cattle.

Electronic supplementary material

The online version of this article (10.1186/s12863-019-0749-5) contains supplementary material, which is available to authorized users.

Integrated mRNA and miRNA expression profile analyses reveal the potential roles of sex-biased miRNA-mRNA pairs in gonad tissues of the Chinese concave-eared torrent frog (Odorrana tormota)

The Chinese concave-eared torrent frog (Odorrana tormota) is typically sexually dimorphic. Females are significantly less common than males in the wild. Until now, the molecular mechanisms of reproduction and sex differentiation of frogs remain unclear. Here, we integrated mRNA and microRNA (miRNA) expression profiles to reveal the molecular mechanisms of reproduction and sex differentiation in O. tormota. We identified 234 differentially expressed miRNAs (DEMs) and 18,551 differentially expressed transcripts. Of these, 12,053 mRNAs and 64 miRNAs were upregulated in testes, and 6,498 mRNAs and 170 miRNAs were upregulated in ovaries. Integrated analysis of the miRNA and mRNA expression profiles predicted 75,602 potential miRNA-mRNA interaction sites, with 42,065 negative miRNA-mRNA interactions. We found 36 differentially expressed genes (DEGs) related to reproduction and sex differentiation, of which 15 DEGs formed 92 negative miRNA-mRNA interactions with 34 known DEMs. Thus, miRNAs may play other important roles in O. tormota. Furthermore, Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses showed reproductive-related processes, such as the gonadotropinreleasing hormone signaling pathway and ovarian steroidogenesis. Based on functional annotation and the literature, the retinoic acid signaling pathway, the SOX9-AMH pathway, and the process of spermatogenesis may be involved in the molecular mechanisms of reproduction and sex differentiation in O. tormota, and may be regulated by miRNAs. The miRNA-mRNA pairs described may provide further understanding of the regulatory mechanisms associated with reproduction and sex differentiation, and the molecular mechanism of reproduction in O. tormota.

The Role of Tertiary Structure in MicroRNA Target Recognition

Translational repression and degradation of transcripts by microRNAs (miRNAs) is mediated by a ribonucleoprotein complex called the miRNA-induced silencing complex (miRISC, or RISC). Advances in experimental determination of RISC structures have enabled detailed analysis and modeling of known miRNA targets, yet a full appreciation of the structural factors influencing target recognition remains a challenge, primarily because target recognition involves a combination of RNA-RNA and RNA-protein interactions that can vary greatly among different miRNA-target pairs. In this chapter, we review progress toward understanding the role of tertiary structure in miRNA target recognition using computational approaches to assemble RISC complexes at known targets and physics-based methods for computing target interactions. Using this framework to examine RISC structures and dynamics, we describe how the conformational flexibility of Argonautes plays an important role in accommodating the diversity of miRNA-target duplexes formed at canonical and noncanonical target sites. We then discuss applications of tertiary structure-based approaches to emerging topics, including the structural effects of SNPs in miRNA targets and cooperative interactions involving Argonaute-Argonaute complexes. We conclude by assessing the prospects for genome-scale modeling of RISC structures and modeling of higher-order Argonaute complexes associated with miRNA biogenesis, mRNA regulation, and other functions.

Noncoding RNAs Databases: Current Status and Trends

One of the most important resources for researchers of noncoding RNAs is the information available in public databases spread over the internet. However, the effective exploration of this data can represent a daunting task, given the large amount of databases available and the variety of stored data. This chapter describes a classification of databases based on information source, type of RNA, source organisms, data formats, and the mechanisms for information retrieval, detailing the relevance of each of these classifications and its usability by researchers. This classification is used to update a 2012 review, indexing now more than 229 public databases. This review will include an assessment of the new trends for ncRNA research based on the information that is being offered by the databases. Additionally, we will expand the previous analysis focusing on the usability and application of these databases in pathogen and disease research. Finally, this chapter will analyze how currently available database schemas can help the development of new and improved web resources.

Functional Analysis of Genetic Variants and Somatic Mutations Impacting MicroRNA-Target Recognition: Bioinformatics Resources

MicroRNAs are small noncoding RNA molecules with great importance in regulating a large number of diverse biological processes in health and disease. MicroRNAs can bind to both coding and noncoding RNAs and regulate their stability and expression. Genetic variants and somatic mutations may alter microRNA sequences and their target sites and therefore impact microRNA-target recognition. Aberrant microRNA-target interactions have been associated with many diseases. In recent years, computational resources have been developed for retrieving, annotating, and analyzing the impact of mutations on microRNA-target recognition. In this chapter, we provide an overview on the computational analysis of mutations impacting microRNA target recognition, followed by a detailed tutorial on how to use three major Web-based bioinformatics resources: PolymiRTS ( http://compbio.uthsc.edu/miRSNP ), a database of genetic variants impacting microRNA target recognition; SomamiR ( http://compbio.uthsc.edu/SomamiR ), a database of somatic mutations affecting the interactions between microRNAs and their targets in mRNAs and noncoding RNAs; and miR2GO ( http://compbio.uthsc.edu/miR2GO ), a computational tool for knowledge-based functional analysis of genetic variants and somatic mutations in microRNA seed regions.

microRNA-27a and microRNA-146a SNP in cerebral malaria

Background

During Plasmodium falciparum infection, microRNA expression alters in brain tissue of mice with cerebral malaria compared to noninfected controls. MicroRNA regulates gene expression post‐transcriptionally to influence biological processes. Cerebral malaria pathology caused mainly by the immunological disorder. We hypothesize that single‐nucleotide polymorphism in a microRNA influences microRNA biogenesis or target gene recognition and altering susceptibility to cerebral malaria.

Methods

We performed a literature search based on immunological mechanism and applied microRNA‐related single‐nucleotide polymorphisms database to examine candidate microRNA SNPs possibly responsible for cerebral malaria. MicroRNA‐27a and microRNA‐146a are supposed to involve in cerebral malaria pathology. To assess the relationship of microRNA SNP to cerebral malaria outcome, we performed TaqMan Genotyping Assays in 110 cerebral malaria and 207 uncomplicated malaria cases for three candidate microRNA SNPs (rs895819 of microRNA‐27a, rs57095329 and rs2910164 of microRNA‐146a).

Results

Our study detected no significant difference in genotype and allele frequency of individual microRNA SNPs as well as in haplotypes of microRNA‐146a between these two groups of malaria patients in Thailand. Hardy–Weinberg disequilibrium of rs57095329 in the cerebral malaria group showed a heterozygous excess which might be due to natural selection.

Conclusion

Our data supported that the candidate microRNA SNPs have no major role to develop cerebral malaria.