A genome-wide survey for SNPs altering microRNA seed sites identifies functional candidates in GWAS

BackgroundGene variants within regulatory regions are thought to be major contributors of the variation of complex traits/diseases. Genome wide association studies (GWAS), have identified scores of genetic variants that appear to contribute to human disease risk. However, most of these variants do not appear to be functional. Thus, the significance of the association may be brought up by still unknown mechanisms or by linkage disequilibrium (LD) with functional polymorphisms. In the present study, focused on functional variants related with the binding of microRNAs (miR), we utilized SNP data, including newly released 1000 Genomes Project data to perform a genome-wide scan of SNPs that abrogate or create miR recognition element (MRE) seed sites (MRESS).ResultsWe identified 2723 SNPs disrupting, and 22295 SNPs creating MRESSs. We estimated the percent of SNPs falling within both validated (5%) and predicted conserved MRESSs (3%). We determined 87 of these MRESS SNPs were listed in GWAS association studies, or in strong LD with a GWAS SNP, and may represent the functional variants of identified GWAS SNPs. Furthermore, 39 of these have evidence of co-expression of target mRNA and the predicted miR. We also gathered previously published eQTL data supporting a functional role for four of these SNPs shown to associate with disease phenotypes. Comparison of FST statistics (a measure of population subdivision) for predicted MRESS SNPs against non MRESS SNPs revealed a significantly higher (P = 0.0004) degree of subdivision among MRESS SNPs, suggesting a role for these SNPs in environmentally driven selection.ConclusionsWe have demonstrated the potential of publicly available resources to identify high priority candidate SNPs for functional studies and for disease risk prediction.

[1]  Simon C. Potter,et al.  The Architecture of Gene Regulatory Variation across Multiple Human Tissues: The MuTHER Study , 2011, PLoS genetics.

[2]  Henrik,et al.  Association analyses of 249,796 individuals reveal eighteen new loci associated with body mass index , 2012 .

[3]  Nicholas T. Ingolia,et al.  Mammalian microRNAs predominantly act to decrease target mRNA levels , 2010, Nature.

[4]  D. Bartel MicroRNAs: Target Recognition and Regulatory Functions , 2009, Cell.

[5]  N. Rajewsky,et al.  Natural selection on human microRNA binding sites inferred from SNP data , 2006, Nature Genetics.

[6]  William Ritchie,et al.  mimiRNA: a microRNA expression profiler and classification resource designed to identify functional correlations between microRNAs and their targets , 2010, Bioinform..

[7]  Timothy B Sackton,et al.  A Scan for Positively Selected Genes in the Genomes of Humans and Chimpanzees , 2005, PLoS biology.

[8]  Life Technologies,et al.  A map of human genome variation from population-scale sequencing , 2011 .

[9]  A. Verhoeven,et al.  Hepatic lipase promoter activity is reduced by the C-480T and G-216A substitutions present in the common LIPC gene variant, and is increased by Upstream Stimulatory Factor. , 2001, Atherosclerosis.

[10]  Wei Chen,et al.  SNP@Evolution: a hierarchical database of positive selection on the human genome , 2009, BMC Evolutionary Biology.

[11]  Wen-Hsiung Li,et al.  Human polymorphism at microRNAs and microRNA target sites , 2007, Proceedings of the National Academy of Sciences.

[12]  Praveen Sethupathy,et al.  MicroRNA target site polymorphisms and human disease. , 2008, Trends in genetics : TIG.

[13]  Tyson A. Clark,et al.  Evaluation of genetic variation contributing to differences in gene expression between populations. , 2008, American journal of human genetics.

[14]  R. Russell,et al.  Principles of MicroRNA–Target Recognition , 2005, PLoS biology.

[15]  J. Reif,et al.  Patterns of population differentiation of candidate genes for cardiovascular disease , 1997, BMC Genetics.

[16]  Julius Brennecke,et al.  Identification of Drosophila MicroRNA Targets , 2003, PLoS biology.

[17]  M. Stoneking,et al.  Worldwide population differentiation at disease-associated SNPs , 2008, BMC Medical Genomics.

[18]  F. Collins,et al.  Potential etiologic and functional implications of genome-wide association loci for human diseases and traits , 2009, Proceedings of the National Academy of Sciences.

[19]  K. Vickers,et al.  MicroRNAs are Transported in Plasma and Delivered to Recipient Cells by High-Density Lipoproteins , 2011, Nature Cell Biology.

[20]  M. Nóbrega,et al.  An 8q24 gene desert variant associated with prostate cancer risk confers differential in vivo activity to a MYC enhancer. , 2010, Genome research.

[21]  Doron Betel,et al.  The microRNA.org resource: targets and expression , 2007, Nucleic Acids Res..

[22]  Anjali J. Koppal,et al.  Supplementary data: Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites , 2010 .

[23]  C. Molony,et al.  Genetic analysis of genome-wide variation in human gene expression , 2004, Nature.

[24]  Christian Gieger,et al.  Genome-wide association analysis identifies three psoriasis susceptibility loci , 2010, Nature Genetics.

[25]  Timothy J. Durham,et al.  "Systematic" , 1966, Comput. J..

[26]  Philippe Rocca-Serra,et al.  Owner controlled data exchange in nutrigenomic collaborations: the NuGO information network , 2009, Genes & Nutrition.

[27]  Jack A. Taylor,et al.  SNPinfo: integrating GWAS and candidate gene information into functional SNP selection for genetic association studies , 2009, Nucleic Acids Res..

[28]  L. Liang,et al.  A genome-wide association study of global gene expression , 2007, Nature Genetics.

[29]  D. Altshuler,et al.  A map of human genome variation from population-scale sequencing , 2010, Nature.

[30]  C. Burge,et al.  Most mammalian mRNAs are conserved targets of microRNAs. , 2008, Genome research.

[31]  Ana Kozomara,et al.  miRBase: integrating microRNA annotation and deep-sequencing data , 2010, Nucleic Acids Res..

[32]  On beyond GWAS , 2010, Nature Genetics.

[33]  M. Lindsay,et al.  microRNAs and the immune response. , 2008, Trends in immunology.

[34]  Ryan D. Hernandez,et al.  Natural selection on protein-coding genes in the human genome , 2005, Nature.

[35]  N. Rajewsky microRNA target predictions in animals , 2006, Nature Genetics.

[36]  D. Haussler,et al.  Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes. , 2005, Genome research.

[37]  Tongbin Li,et al.  miRecords: an integrated resource for microRNA–target interactions , 2008, Nucleic Acids Res..

[38]  Tsun-Po Yang,et al.  Genevar: a database and Java application for the analysis and visualization of SNP-gene associations in eQTL studies , 2010, Bioinform..

[39]  D. Weinberger,et al.  MicroSNiPer: a web tool for prediction of SNP effects on putative microRNA targets , 2010, Human mutation.

[40]  J. Bertino,et al.  MicroRNA polymorphisms: the future of pharmacogenomics, molecular epidemiology and individualized medicine. , 2009, Pharmacogenomics.

[41]  Joshua T. Burdick,et al.  Common genetic variants account for differences in gene expression among ethnic groups , 2007, Nature Genetics.

[42]  Ligang Wu,et al.  PolymiRTS Database: linking polymorphisms in microRNA target sites with complex traits , 2006, Nucleic Acids Res..

[43]  C. Burge,et al.  Conserved Seed Pairing, Often Flanked by Adenosines, Indicates that Thousands of Human Genes are MicroRNA Targets , 2005, Cell.

[44]  A. Baranova,et al.  Differential expression of miRNAs in the visceral adipose tissue of patients with non‐alcoholic fatty liver disease , 2010, Alimentary pharmacology & therapeutics.

[45]  M. Shriver,et al.  Interrogating a high-density SNP map for signatures of natural selection. , 2002, Genome research.

[46]  M. Mihatsch,et al.  Lack of the Transcriptional Coactivator OBF-1 Prevents the Development of Systemic Lupus Erythematosus-Like Phenotypes in Aiolos Mutant Mice 1 , 2003, The Journal of Immunology.

[47]  P. Talmud,et al.  Determination of the Functionality of Common APOA5 Polymorphisms* , 2005, Journal of Biological Chemistry.

[48]  P. Deloukas,et al.  Common Regulatory Variation Impacts Gene Expression in a Cell Type–Dependent Manner , 2009, Science.

[49]  Jiuhong Kang,et al.  MicroRNA miR-326 regulates TH-17 differentiation and is associated with the pathogenesis of multiple sclerosis , 2009, Nature Immunology.

[50]  Laurence D. Parnell,et al.  The PLIN4 Variant rs8887 Modulates Obesity Related Phenotypes in Humans through Creation of a Novel miR-522 Seed Site , 2011, PloS one.

[51]  Tanya M. Teslovich,et al.  Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index , 2010 .

[52]  A. Visel,et al.  Genomic Views of Distant-Acting Enhancers , 2009, Nature.

[53]  F. Pereyra,et al.  Differential microRNA regulation of HLA-C expression and its association with HIV control , 2011, Nature.

[54]  Inês Barroso,et al.  Genetic Variants Influencing Circulating Lipid Levels and Risk of Coronary Artery Disease , 2010, Arteriosclerosis, thrombosis, and vascular biology.