MirSNP, a database of polymorphisms altering miRNA target sites, identifies miRNA-related SNPs in GWAS SNPs and eQTLs
© Liu et al.; licensee BioMed Central Ltd. 2012
Received: 23 July 2012
Accepted: 17 October 2012
Published: 23 November 2012
Numerous single nucleotide polymorphisms (SNPs) associated with complex diseases have been identified by genome-wide association studies (GWAS) and expression quantitative trait loci (eQTLs) studies. However, few of these SNPs have explicit biological functions. Recent studies indicated that the SNPs within the 3’UTR regions of susceptibility genes could affect complex traits/diseases by affecting the function of miRNAs. These 3’UTR SNPs are functional candidates and therefore of interest to GWAS and eQTL researchers.
We developed a publicly available online database, MirSNP (http://cmbi.bjmu.edu.cn/mirsnp), which is a collection of human SNPs in predicted miRNA-mRNA binding sites. We identified 414,510 SNPs that might affect miRNA-mRNA binding. Annotations were added to these SNPs to predict whether a SNP within the target site would decrease/break or enhance/create an miRNA-mRNA binding site. By applying MirSNP database to three brain eQTL data sets, we identified four unreported SNPs (rs3087822, rs13042, rs1058381, and rs1058398), which might affect miRNA binding and thus affect the expression of their host genes in the brain. We also applied the MirSNP database to our GWAS for schizophrenia: seven predicted miRNA-related SNPs (p < 0.0001) were found in the schizophrenia GWAS. Our findings identified the possible functions of these SNP loci, and provide the basis for subsequent functional research.
MirSNP could identify the putative miRNA-related SNPs from GWAS and eQTLs researches and provide the direction for subsequent functional researches.
KeywordsmicroRNA Single nucleotide polymorphism (SNP) Genome-wide association study (GWAS) Expression quantitative trait loci (eQTLs) MirSNP
MicroRNAs (miRNAs) are small non-coding RNA molecules of ~22 nucleotides that primarily mediate post-transcriptional gene silencing processes in animals [1, 2]. MiRNAs inactivate specific mRNAs and interfere with the translation of target proteins . In mammals, miRNAs are predicted to control the activities of ~50% of all protein-coding genes . As key post-transcriptional regulators, miRNAs have an important role in a wide range of biological processes, including cell proliferation, differentiation, apoptosis and metabolism [2, 3]. Evidence indicates that miRNAs are also involved in the pathogenesis of complex diseases, such as cancer and mental disorders [4, 5].
Complementarity to bases 2-8 of the miRNA (the seed site) is important in miRNA-mRNA binding [6, 7]. MiRNAs are key regulators of gene expression; therefore, SNPs in the seed sites of miRNA targets may create, as well as destroy, miRNA binding sites, and further affect phenotypes and disease susceptibility . Identifying these seed-site SNPs could help in the further exploration of the molecular mechanism of gene dysregulation. In addition, genetic variants in miRNA genes may also have important roles by affecting miRNA maturation, which may affect disease susceptibility . Certain polymorphisms in miRNA genes have been found to be associated with various complex diseases, including cancers, mental diseases, cardiomyopathy, and asthma (Additional file 1: Table S1).
GWAS and eQTLs are powerful methods for identifying genetic variants contributing to disease risk and gene expression. In a GWAS of schizophrenia (SCZ), Ripke et al. found the most significant SNP (p < 1.6 × 10-11) within an intron of a putative primary transcript for hsa-mir-137 and found four other SNPs achieving genome-wide significance that were located in predicted target sites of hsa-mir-137 . It was estimated that more than 50% of the protein-coding genes are regulated by miRNAs, and each miRNA may regulate hundreds of potential targets [10, 11]. Taking into account large scale of biological significance shown by miRNAs, miRNA-related SNPs could be important variations leading to traits and diseases. Identifying allele-specific miRNA-mRNA interactions may indicate the functional roles of the SNPs from GWAS and eQTLs that presently lack obvious known function.
To help identifying putative miRNA-related SNPs from researchers’ own GWAS and cis-acting eQTLs data set, we have developed a freely available database, named “MirSNP”, which provides SNPs located in predicted miRNA target sites. This database has minor allele frequency (MAF) and linkage disequilibrium (LD) information for the SNPs and has annotations concerning their creative or disruptive effects on putative target sites. The MirSNP database comprises over 414,510 predicted miRNA-related SNPs, enabling users to identify potential miRNA-related SNPs from their own GWAS or eQTLs data. In this work, we applied MirSNP to our schizophrenia GWAS data and several brain eQTLs data as examples.
Construction and content
To store the mRNA sequences, miRNA data and SNPs, a local Structured Query Language (SQL) database was built using MySQL software. Human miRNAs were downloaded from miRBase18.0 . For SNP catalogs, four tables from dbSNP135  were used (see URLs). To maximize the consistency between different databases, mRNA sequence files were obtained from NCBI (see URLs) rather than from the UCSC genome browser. In total, 42,733 mRNA sequences and 513,249 SNPs located in the 3’UTRs of mRNA were eligible for subsequent analysis.
Identifying polymorphisms in pre-miRNA genes
Identifying polymorphisms in miRNA target sites
Although there are examples that imperfect 7-nt seed site pairing can be functional, there is overwhelming evidence to support the hypothesis that Watson-Crick pairing to the miRNA seed site is the most important feature for miRNA prediction and function [6, 7]. Therefore, we adopted the 7-nt seed region in the miRNA as the major criterion in the miRanda algorithm . In detail, to predict miRNA binding sites, we applied miRanda v3.3a with the default pairing score cutoff of “≥140” and “–strick” command, which only considered stringent 7-nt seed pairing (requiring an uninterrupted match of at least seven nucleotides from the 5’-end of the miRNA).
Additional information about MirSNP
A requirement for perfect 7-nt seed site pairing improves the reliability of miRNA target prediction, particularly when seed motif is conserved in the UTR regions of whole-genome alignments [16, 17]. We downloaded the conservative information of whole-genome alignments (phastCons 46way vertebrates from UCSC ftp site, see URLs)  and then added the average value of conservative scores of 7-nt seed motif to our database. The score of mirSVR methodology, a machine learning method for ranking miRNA target sites , were also added to the MirSNP database as annotation. However, the data of MirSNP are not identical to that of the mirSVR. Imperfect overlap may traced back to SNPs (the mirSVR methodology didn’t consider the impact of SNPs on miRNA-mRNA bindings), the use of different UTR database and miRNA information. Therefore, not all results in MirSNP should have the score of mirSVR.
SNPs become more important if they have a high frequency or are undergoing positive selection. Therefore, we have added MAF information from dbSNP135 (see URLs) for the SNPs into MirSNP. Based on this information, the results of MirSNP filtered by MAF could be displayed. Analysis of the MAF data revealed that there were 32,822 SNPs located in miRNA-mRNA binding sites with MAFs greater than 0.01 in the four populations. In addition, 122 SNPs in pre-miRNA genes had MAF data and the remaining 1,818 SNPs lacked MAF data.
LD information was obtained for each SNP from the HapMap project . The Phase2 HapMap fileset (see URLs) was downloaded for the four populations and the linkage of the SNPs was calculated using a threshold of r 2 greater than 0.8 using the PLINK software . LD and MAF information of SNPs were stored into separate tables in download page (see URLs).
All the useful data were stored in a local MySQL database. We used Django, a web application framework written in Python, to build a user-friendly online website (http://cmbi.bjmu.edu.cn/mirsnp).
The use of MirSNP for brain eQTL data sets
Brain eQTLs found in predicted miRNA-mRNA binding sites
p-value (Myers, A.J. et al)b
p-value (Colantuoni, C. et al)c
p-value (Gibbs, J.R. et al)d
hsa-miR-200a-3p, hsa-miR-26b-3p, hsa-miR-29b-1-5p, hsa-miR-335-3p
hsa-miR-202-5p, hsa-miR-362-5p, hsa-miR-500b, hsa-miR-1914-5p
hsa-miR-134, hsa-miR-3118, hsa-miR-943, hsa-miR-192-3p, hsa-miR-5002-3p
The use of MirSNP for a schizophrenia GWAS data set
Putative miRNA-related SNPs associated with schizophrenia
hsa-miR-145-3p, hsa-miR-3680-3p, hsa-miR-5689, hsa-miR-1294
hsa-miR-1193, hsa-miR-335-3p, hsa-miR-29b-2-5p
hsa-miR-516a-3p, hsa-miR-376a-5p, hsa-miR-1287, hsa-miR-145-3p, hsa-miR-5191, hsa-miR-516b-3p
hsa-miR-30b-5p, hsa-miR-3686, hsa-miR-30c-5p, hsa-miR-4773, hsa-miR-2278, hsa-miR-589-3p
hsa-miR-3689b-5p, hsa-miR-3177-5p, hsa-miR-3689a-5p, hsa-miR-3689f, hsa-miR-190b, hsa-miR-3689e, hsa-miR-190a
hsa-miR-4305, hsa-miR-331-3p, hsa-miR-4638-3p, hsa-miR-4705, hsa-miR-3690, hsa-miR-5195-5p, hsa-miR-4308
hsa-miR-16-2-3p, hsa-miR-195-3p, hsa-miR-3942-5p, hsa-miR-4703-5p, hsa-miR-4766-3p
hsa-miR-1267, hsa-miR-501-5p, hsa-miR-3613-3p, hsa-miR-653
We also overlapped the SNPs around microRNA genes in our GWAS data of schizophrenia. A subset of 108 SNPs around miRNA genes was identified. We found one SNP (rs10173558), which is only 5 bp away from the start site of “hsa-mir-1302-4”, having a statistical significance lower than 0.001. Yuan et al. reported that the highest expression level of miR-1302’ target genes was in the nervous system and the genes were enriched in both synapses and intracellular membrane-bounded organelles . This finding implied a potential relevance of miR-1304 to psychiatric disorders.
In recent years, increasing numbers of databases have been published to aid researchers to explore the impact of SNPs on miRNA targets [27–33]. Some researchers, such as Richardson  and Ziebarth , have provided links between SNPs in miRNA target sites, cis-acting eQTLs and the results of GWAS. Previous works summarized the characteristics of miRNA-related SNPs and showed the potential of applying such databases in GWAS and eQTL researches. However, these databases may not be suitable for a single GWAS or eQTL data set. Some databases cannot perform batch search for numbers of SNPs and some cannot provide effective miRNA-related information for strongly- associated loci. MirSNP was developed to identify putative miRNA-related SNPs from single data sets of GWAS or eQTL, especially from newly published data sets. First, our analysis covered 513,249 known 3’UTR SNPs based on dbSNP135 and we used highly consistent data sources to avoid data loss while integrating different data. Furthermore, sequence alignments between surrounding DNA sequences of SNPs and the corresponding mRNA sequences were used to map variants into their mRNA sequences. Finally, our web site was designed to directly use GWAS or eQTL data sets in a batch query, particularly considering the linked SNPs in different populations.
Comparison among four databases
miRNA-related SNPs with MAF > 0.01
Involved mature miRNAs
Records (SNPs with MAF > 0.01)
Overlap with MirSNP
Number of SNPs (MAF > 0.01) coinciding with MirSNP
Experimentally validated miRNA-related SNPs found in MirSNP
Reported associated disease
Squamous cell carcinoma of the head and neck
Small-cell lung cancer
Diarrhea predominant irritable bowel syndrome
Hum. Mol. Genet
Arson or property damage
Am. J. Hum. Genet
Am. J. Hum. Genet
Am. J. Hum. Genet
MiRNAs can downregulate gene expression by two posttranscriptional mechanisms: mRNA cleavage or translational repression. In animals, miRNA is thought to have a repressive effect that influences protein expression, not the mRNA levels. However, it has been estimated that over 80 percent of miRNAs acted to lower mRNA levels, which shows that mRNA destabilization is the primary action mode of miRNAs on target mRNAs . In addition, studies have shown that SNPs in seed-sites region can significantly change the expression of the target mRNA and protein [36–40]. eQTL analysis is an experimental method for exploring the relationship between SNPs and mRNA expression at a high throughput. Genetic variants that create or destroy an miRNA binding site may be the casual cis-acting eQTLs. The combination of our MirSNP database and eQTL data will provide possible explanations for the eQTLs. We have already identified four SNPs in prediected miRNA target sites that were proven to be brain eQTLs in three independent studies. Further experiments are needed to prove that these eQTLs affect gene expression through an miRNA mechanism. On the other hand, using GWAS, enormous numbers of associations between SNPs and diseases have been reported. There are many disease-associated SNPs that function by miRNA regulation. Overlapping miRNA-related SNPs and the existing GWAS data could identify possible biological mechanisms for these disease-associated variations and provide the in silico basis for further studies.
Our aim was to merge the MirSNP database with high throughput SNP experimental data. We identified many SNPs in predicted miRNA targets and indicated their potential functions based on sequence algorithms. Unfortunately, the expression information of miRNAs and mRNAs are not supplied in our database. We considered the possibility of an miRNA and mRNA combining, but under the complex mechanism of spatial and temporal expression, we had no idea if the two molecules would encounter each other in vivo. Combining MirSNP with additional databases containing expression information, such as miRGator , would improve the functionality of the database.
MirSNP is a database of SNPs in predicted miRNA target sites, based on information from dbSNP135 and mirBASE18. MirSNP is highly sensitive and covers most experiments confirmed SNPs that affect miRNA function. The results suggest that our prediction and data processing are full-scale. MirSNP may be combined with researchers’ own GWAS or eQTL positive data sets to identify the putative miRNA-related SNPs from traits/diseases associated variants. We aim to update the MirSNP database as new versions of mirBASE and dbSNP database become available.
Availability and requirements
MirSNP is publicly available on the internet at http://cmbi.bjmu.edu.cn/mirsnp.
mRNA sequence file (ftp://ftp.ncbi.nih.gov//refseq/H_sapiens/mRNA_Prot/human.rna.fna.gz, released November 15, 2011)
HapMap fileset (http://pngu.mgh.harvard.edu/~purcell/plink/res.shtml)
3’ untranslated region
Samples of Utah residents with Northern and Western European ancestry from the CEPH collection
Samples of Han Chinese in Beijing
Samples of Japanese in Tokyo
Samples of Yoruba people in Ibadan
Expression quantitative trait locus
Genome-wide association study
Minor allele frequency
Single nucleotide polymorphism
Structured Query Language.
We extend our gratitude to all the subjects who participated in this study. This work was supported by grants from the National Natural Science Foundation of China (81071087, 81071088), the International Science & Technology Cooperation Program of China (2010DFB30820), the National High Technology Research and Development Program of China (2009AA022702).
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