Significant impact of miRNA-target gene networks on genetics of human complex traits

Scientific Reports

Volumn 6, Issue , 2016, Pages

  Okada, Yukinori ^a,b   Muramatsu, Tomoki ^a   Suita, Naomasa ^a,c   Kanai, Masahiro ^a   Kawakami, Eiryo ^b   Iotchkova, Valentina ^d,e   Soranzo, Nicole ^d,e   Inazawa, Johji ^a   Tanaka, Toshihiro ^a,b  

^a TOKYO MEDICAL AND DENTAL UNIVERSITY   (Japan)

^b Institute of Physical and Chemical Research   (Japan)

^c ONO PHARMACEUTICAL CO   (Japan)

^d WELLCOME TRUST SANGER INSTITUTE   (United Kingdom)

^e UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

HYDROLASE; MICRORNA; MIRN4728 MICRORNA, HUMAN; PROTEIN-ARGININE DEIMINASE;

ADULT; BODY HEIGHT; DOWN REGULATION; GENE REGULATORY NETWORK; GENETIC PREDISPOSITION; GENETICS; GENOME-WIDE ASSOCIATION STUDY; HUMAN; KIDNEY; MOLECULARLY TARGETED THERAPY; MULTIFACTORIAL INHERITANCE; PHYSIOLOGY; RHEUMATOID ARTHRITIS; RISK; SINGLE NUCLEOTIDE POLYMORPHISM;

ADULT; ARTHRITIS, RHEUMATOID; BODY HEIGHT; DOWN-REGULATION; GENE REGULATORY NETWORKS; GENETIC PREDISPOSITION TO DISEASE; GENOME-WIDE ASSOCIATION STUDY; HUMANS; HYDROLASES; KIDNEY; MICRORNAS; MOLECULAR TARGETED THERAPY; MULTIFACTORIAL INHERITANCE; POLYMORPHISM, SINGLE NUCLEOTIDE; RISK;

EID: 84959477574     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/srep22223     Document Type: Article

References (45)

1. Esteller, M. Non-coding RNAs in human disease. Nat Rev Genet 12, 861-874 (2011).
2. Takada, S. & Asahara, H. Current strategies for microRNA research. Mod Rheumatol 22, 645-653 (2012).
3. Kozomara, A. & Griffiths-Jones, S. miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res 42, D68-D73 (2014).
4. Londin, E. et al. Analysis of 13 cell types reveals evidence for the expression of numerous novel primate-and tissue-specific microRNAs. Proc Natl Acad Sci USA 112, E1106-E1115 (2015).
5. Geeleher, P. et al. The regulatory effect of miRNAs is a heritable genetic trait in humans. BMC Genomics 13, 383 (2012).
6. Liu, C. et al. MirSNP, a database of polymorphisms altering miRNA target sites, identifies miRNA-related SNPs in GWAS SNPs and eQTLs. BMC Genomics 13, 661 (2012).
7. Huan, T. et al. Genome-wide identification of microRNA expression quantitative trait loci. Nat Commun 6, 6601 (2015).
8. Brest, P. et al. A synonymous variant in IRGM alters a binding site for miR-196 and causes deregulation of IRGM-dependent xenophagy in Crohn's disease. Nat Genet 43, 242-245 (2011).
9. Witkos, T. M., Koscianska, E. & Krzyzosiak, W. J. Practical Aspects of microRNA Target Prediction. Curr Mol Med 11, 93-109 (2011).
10. Segre, A. V. et al. Common inherited variation in mitochondrial genes is not enriched for associations with type 2 diabetes or related glycemic traits. PLoS Genet 6, e1001058 (2010).
11. Wong, N. & Wang, X. miRDB: an online resource for microRNA target prediction and functional annotations. Nucleic Acids Res 43, D146-D152 (2015).
12. Vejnar, C. E. & Zdobnov, E. M. MiRmap: comprehensive prediction of microRNA target repression strength. Nucleic Acids Res 40, 11673-11683 (2012).
13. Kertesz, M. et al. The role of site accessibility in microRNA target recognition. Nat Genet 39, 1278-1284 (2007).
14. Lewis, B. P., Burge, C. B. & Bartel, D. P. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 120, 15-20 (2005).
15. Wood, A. R. et al. Defining the role of common variation in the genomic and biological architecture of adult human height. Nat Genet 46, 1173-1186 (2014).
16. Locke, A. E. et al. Genetic studies of body mass index yield new insights for obesity biology. Nature 518, 197-206 (2015).
17. Gieger, C. et al. New gene functions in megakaryopoiesis and platelet formation. Nature 480, 201-208 (2011).
18. van der Harst, P. et al. Seventy-five genetic loci influencing the human red blood cell. Nature 492, 369-375 (2012).
19. Willer, C. J. et al. Discovery and refinement of loci associated with lipid levels. Nat Genet 45, 1274-1283 (2013).
20. Köttgen, A. et al. New loci associated with kidney function and chronic kidney disease. Nat Genet 42, 376-384 (2010).
21. Ehret, G. B. et al. Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk. Nature 478, 103-109 (2011).
22. Estrada, K. et al. Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture. Nat Genet 44, 491-501 (2012).
23. Mahajan, A. et al. Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility. Nat Genet 46, 234-244 (2014).
24. Kottgen, A. et al. Genome-wide association analyses identify 18 new loci associated with serum urate concentrations. Nat Genet 45, 145-154 (2013).
25. Lambert, J. C. et al. Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease. Nat Genet 45, 1452-1458 (2013).
26. Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature 511, 421-427 (2014).
27. Fritsche, L. G. et al. Seven new loci associated with age-related macular degeneration. Nat Genet 45, 433-9, 439e1-2 (2013).
28. Okada, Y. et al. Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature 506, 376-381 (2014).
29. Perry, J. R. et al. Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche. Nature 514, 92-97 (2014).
30. Trionfini, P., Benigni, A. & Remuzzi, G. MicroRNAs in kidney physiology and disease. Nat Rev Nephrol 11, 23-33 (2015).
31. Nelson, M. R. et al. The support of human genetic evidence for approved drug indications. Nat Genet 47, 856-860 (2015).
32. Okada, Y. From the era of genome analysis to the era of genomic drug discovery: a pioneering example of rheumatoid arthritis. Clin Genet 86, 432-440 (2014).
33. Fisher, B. A. & Venables, P. J. Inhibiting citrullination in rheumatoid arthritis: taking fuel from the fire. Arthritis Res Ther 14, 108 (2012).
34. Chang, X. et al. PADI2 is significantly associated with rheumatoid arthritis. PLoS One 8, e81259 (2013).
35. GTEx Consortium. Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science 348, 648-660 (2015).
36. Wang, E. et al. Predictive genomics: a cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data. Semin Cancer Biol 30, 4-12 (2015).
37. Okada, Y. et al. Construction of a population-specific HLA imputation reference panel and its application to Graves' disease risk in Japanese. Nat Genet 47, 798-802 (2015).
38. Okada, Y. et al. Risk for ACPA-positive rheumatoid arthritis is driven by shared HLA amino acid polymorphisms in Asian and European populations. Hum Mol Genet 23, 6916-6926 (2014).
39. Okada, Y. et al. Fine mapping major histocompatibility complex associations in psoriasis and its clinical subtypes. Am J Hum Genet 95, 162-172 (2014).
40. Hecker, N. et al. SuperTarget goes quantitative: update on drug-target interactions. Nucleic Acids Res 40, D1113-D1117 (2012).
41. Knox, C. et al. DrugBank 3.0: a comprehensive resource for 'omics' research on drugs. Nucleic Acids Res 39, D1035-D1041 (2011).
42. Qin, C. et al. Therapeutic target database update 2014: a resource for targeted therapeutics. Nucleic Acids Res 42, D1118-D1123 (2014).
43. Muramatsu, T. et al. YAP is a candidate oncogene for esophageal squamous cell carcinoma. Carcinogenesis 32, 389-398 (2011).
44. Yang, J., Lee, S. H., Goddard, M. E. & Visscher, P. M. GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet 88, 76-82 (2011).
45. Krzywinski, M. et al. Circos: an information aesthetic for comparative genomics. Genome Res 19, 1639-1645 (2009).