Linking genes to diseases: It's all in the data

Genome Medicine

Volumn 1, Issue 8, 2009, Pages

  Tiffin, Nicki T ^a   Andrade Navarro, Miguel A ^b   Perez Iratxeta, Carolina ^c  

^a UNIVERSITY OF THE WESTERN CAPE   (South Africa)

^b MAX DELBRÜCK CENTER FOR MOLECULAR MEDICINE   (Germany)

^c OTTAWA HOSPITAL RESEARCH INSTITUTE   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

MESSENGER RNA; PROTEIN KINASE; TRANSCRIPTION FACTOR;

3' UNTRANSLATED REGION; AUTISM; COMPLEX FORMATION; DISEASE PREDISPOSITION; GENE EXPRESSION; GENE FUNCTION; GENE MUTATION; GENE NUMBER; GENE REGULATORY NETWORK; GENE STRUCTURE; GENETIC ASSOCIATION; GENETIC LINKAGE; GENETIC SIMILARITY; GENETIC VARIABILITY; HUMAN; MALIGNANT NEOPLASTIC DISEASE; MATHEMATICAL ANALYSIS; METABOLIC SYNDROME X; NON INSULIN DEPENDENT DIABETES MELLITUS; OBESITY; PHYLOGENY; PRIORITY JOURNAL; PROTEIN PROTEIN INTERACTION; QUANTITATIVE TRAIT LOCUS; REVIEW; RNA EDITING;

EID: 77953403446     PISSN: None     EISSN: 1756994X     Source Type: Journal    
DOI: 10.1186/gm77     Document Type: Review

References (69)

1. Zeggini E, Ioannidis JP: Meta-analysis in genome-wide association studies. Pharmacogenomics 2009, 10:191-201.
2. Iles MM: What can genome-wide association studies tell us about the genetics of common disease? PLoS Genet 2008, 4: e33.
3. Altshuler D, Daly M: Guilt beyond a reasonable doubt. Nat Genet 2007, 39:813-815.
4. Marchini J, Howie B, Myers S, McVean G, Donnelly P: A new multipoint method for genome-wide association studies by imputation of genotypes. Nat Genet 2007, 39:906-913.
5. Farber CR, Lusis AJ: Integrating global gene expression analysis and genetics. Adv Genet 2008, 60:571-601.
6. Hene L, Sreenu VB, Vuong MT, Abidi SH, Sutton JK, Rowland-Jones SL, Davis SJ, Evans EJ: Deep analysis of cellular transcriptomes - LongSAGE versus classic MPSS. BMC Genomics 2007, 8:333.
7. de Hoon M, Hayashizaki Y: Deep cap analysis gene expression (CAGE): genome-wide identification of promoters, quantification of their expression, and network inference. Biotechniques 2008, 44:627-628, 630, 632.
8. Mardis ER: The impact of next-generation sequencing technology on genetics. Trends Genet 2008, 24:133-141.
9. Perez-Iratxeta C, Bork P, Andrade MA: Association of genes to genetically inherited diseases using data mining. Nat Genet 2002, 31:316-319.
10. Risch NJ: Searching for genetic determinants in the new millennium. Nature 2000, 405:847-856.
11. Flicek P, Aken BL, Beal K, Ballester B, Caccamo M, Chen Y, Clarke L, Coates G, Cunningham F, Cutts T, Down T, Dyer SC, Eyre T, Fitzgerald S, Fernandez-Banet J, Gräf S, Haider S, Hammond M, Holland R, Howe KL, Howe K, Johnson N, Jenkinson A, Kähäri A, Keefe D, Kokocinski F, Kulesha E, Lawson D, Longden I, Megy K, et al.: Ensembl 2008. Nucleic Acids Res 2008, 36:D707-D714.
12. Wheeler DL, Barrett T, Benson DA, Bryant SH, Canese K, Chetvernin V, Church DM, Dicuccio M, Edgar R, Federhen S, Feolo M, Geer LY, Helmberg W, Kapustin Y, Khovayko O, Landsman D, Lipman DJ, Madden TL, Maglott DR, Miller V, Ostell J, Pruitt KD, Schuler GD, Shumway M, Sequeira E, Sherry ST, Sirotkin K, Souvorov A, Starchenko G, et al.:Database resources of the National Center for Biotechnology Information. Nucleic Acids Res 2008, 36:D13-D21.
13. Kuhn RM, Karolchik D, Zweig AS, Wang T, Smith KE, Rosenbloom KR, Rhead B, Raney BJ, Pohl A, Pheasant M, Meyer L, Hsu F, Hinrichs AS, Harte RA, Giardine B, Fujita P, Diekhans M, Dreszer T, Clawson H, Barber GP, Haussler D, Kent WJ: The UCSC Genome Browser Database: update 2009. Nucleic Acids Res 2009, 37:D755-D761.
14. Barrett T, Troup DB, Wilhite SE, Ledoux P, Rudnev D, Evangelista C, Kim IF, Soboleva A, Tomashevsky M, Marshall KA, Phillippy KH, Sherman PM, Muertter RN, Edgar R: NCBI GEO: archive for high-throughput functional genomic data. Nucleic Acids Res 2009, 37:D885-D890.
15. International HapMap Consortium, Frazer KA, Ballinger DG, Cox DR, Hinds DA, Stuve LL, Gibbs RA, Belmont JW, Boudreau A, Hardenbol P, Leal SM, Pasternak S, Wheeler DA, Willis TD, Yu F, Yang H, Zeng C, Gao Y, Hu H, Hu W, Li C, Lin W, Liu S, Pan H, Tang X, Wang J, Wang W, Yu J, Zhang B, Zhang Q, et al.: A second generation human haplotype map of over 3.1 million SNPs. Nature 2007, 449:851-861.
16. Kanehisa M, Araki M, Goto S, Hattori M, Hirakawa M, Itoh M, Katayama T, Kawashima S, Okuda S, Tokimatsu T, Yamanishi Y: KEGG for linking genomes to life and the environment. Nucleic Acids Res 2008, 36:D480-D484.
17. Matthews L, Gopinath G, Gillespie M, Caudy M, Croft D, de Bono B, Garapati P, Hemish J, Hermjakob H, Jassal B, Kanapin A, Lewis S, Mahajan S, May B, Schmidt E, Vastrik I, Wu G, Birney E, Stein L, D'Eustachio P: Reactome knowledgebase of human biological pathways and processes. Nucleic Acids Res 2009, 37:D619-D622.
18. Oti M, Brunner HG: The modular nature of genetic diseases. Clin Genet 2007, 71:1-11.
19. Lopez-Bigas N, Ouzounis CA: Genome-wide identification of genes likely to be involved in human genetic disease. Nucleic Acids Res 2004, 32:3108-3114.
20. Adie EA, Adams RR, Evans KL, Porteous DJ, Pickard BS: Speeding disease gene discovery by sequence based candidate prioritization. BMC Bioinformatics 2005, 6:55.
21. Oti M, Snel B, Huynen MA, Brunner HG: Predicting disease genes using protein-protein interactions. J Med Genet 2006, 43:691-698.
22. United States National Library of Medicine, National Institutes of Health, Medical Subject Headings [http://www. nlm.nih.gov/mesh/meshhome.html]
23. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G: Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 2000, 25:25-29.
24. Turner FS, Clutterbuck DR, Semple CA: POCUS: mining genomic sequence annotation to predict disease genes. Genome Biol 2003, 4:R75.
25. Tranchevent LC, Barriot R, Yu S, Van Vooren S, Van Loo P, Coessens B, De Moor B, Aerts S, Moreau Y: ENDEAVOUR update: a web resource for gene prioritization in multiple species. Nucleic Acids Res 2008, 36:W377-W384.
26. Masotti D, Nardini C, Rossi S, Bonora E, Romeo G, Volinia S, Benini L: TOM: enhancement and extension of a tool suite for in silico approaches to multigenic hereditary disorders. Bioinformatics 2008, 24:428-429.
27. Perez-Iratxeta C, Palidwor G, Andrade-Navarro MA: Towards completion of the Earth's proteome. EMBO Rep 2007, 8: 1135-1141.
28. Camon E, Magrane M, Barrell D, Lee V, Dimmer E, Maslen J, Binns D, Harte N, Lopez R, Apweiler R: The Gene Ontology Annotation (GOA) Database: sharing knowledge in Uniprot with Gene Ontology. Nucleic Acids Res 2004, 32:D262-D266
29. Jensen LJ, Kuhn M, Stark M, Chaffron S, Creevey C, Muller J, Doerks T, Julien P, Roth A, Simonovic M, Bork P, von Mering C: STRING 8 - a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res 2009, 37: D412-D416.
30. Chaurasia G, Malhotra S, Russ J, Schnoegl S, Hanig C, Wanker EE, Futschik ME: UniHI 4: new tools for query, analysis and visualization of the human protein-protein interactome. Nucleic Acids Res 2009, 37:D657-D660.
31. Wingender E: The TRANSFAC project as an example of framework technology that supports the analysis of genomic regulation. Brief Bioinform 2008, 9:326-332.
32. Duggan DJ, Hoffman EP: Autosomal recessive muscular dystrophy and mutations of the sarcoglycan complex. Neuromuscul Disord 1996, 6:475-482.
33. Perez-Iratxeta C, Bork P, Andrade-Navarro MA: Update of the G2D tool for prioritization of gene candidates to inherited diseases. Nucleic Acids Res 2007, 35:W212-W216.
34. Lage K, Karlberg EO, Storling ZM, Olason PI, Pedersen AG, Rigina O, Hinsby AM, Tumer Z, Pociot F, Tommerup N, Moreau Y, Brunak S: A human phenome-interactome network of protein complexes implicated in genetic disorders. Nat Biotechnol 2007, 25:309-316.
35. van Driel MA, Cuelenaere K, Kemmeren PP, Leunissen JA, Brunner HG, Vriend G: GeneSeeker: extraction and integration of human disease-related information from web-based genetic databases. Nucleic Acids Res 2005, 33:W758-W761.
36. Firth HV, Richards SM, Bevan AP, Clayton S, Corpas M, Rajan D, Van Vooren S, Moreau Y, Pettett RM, Carter NP: DECIPHER: Database of Chromosomal Imbalance and Phenotype in Humans Using Ensembl Resources. Am J Hum Genet 2009, 84:524-533.
37. Chen J, Xu H, Aronow BJ, Jegga AG: Improved human disease candidate gene prioritization using mouse phenotype. BMC Bioinformatics 2007, 8:392.
38. Fraser HB, Plotkin JB: Using protein complexes to predict phenotypic effects of gene mutation. Genome Biol 2007, 8: R252.
39. Tiffin N, Kelso JF, Powell AR, Pan H, Bajic VB, Hide WA: Integration of text- and data-mining using ontologies successfully selects disease gene candidates. Nucleic Acids Res 2005, 33:1544-1552.
40. Masseroli M, Galati O, Pinciroli F: GFINDer: genetic disease and phenotype location statistical analysis and mining of dynamically annotated gene lists. Nucleic Acids Res 2005, 33: W717-W723.
41. Sam LT, Mendonca EA, Li J, Blake J, Friedman C, Lussier YA: PhenoGO: an integrated resource for the multiscale mining of clinical and biological data. BMC Bioinformatics 2009, 10 (Suppl 2):S8.
42. Robinson PN, Kohler S, Bauer S, Seelow D, Horn D, Mundlos S: The Human Phenotype Ontology: a tool for annotating and analyzing human hereditary disease. Am J Hum Genet 2008, 83:610-615.
43. Smith CL, Goldsmith CA, Eppig JT: The Mammalian Phenotype Ontology as a tool for annotating, analyzing and comparing phenotypic information. Genome Biol 2005, 6: R7.
44. Bult CJ, Eppig JT, Kadin JA, Richardson JE, Blake JA: The Mouse Genome Database (MGD): mouse biology and model systems. Nucleic Acids Res 2008, 36:D724-D728.
45. Twigger SN, Shimoyama M, Bromberg S, Kwitek AE, Jacob HJ: The Rat Genome Database, update 2007 - easing the path from disease to data and back again. Nucleic Acids Res 2007, 35:D658-D662
46. Valdar W, Solberg LC, Gauguier D, Burnett S, Klenerman P, Cookson WO, Taylor MS, Rawlins JN, Mott R, Flint J: Genomewide genetic association of complex traits in heterogeneous stock mice. Nat Genet 2006, 38:879-887.
47. Auwerx J, Avner P, Baldock R, Ballabio A, Balling R, Barbacid M, Berns A, Bradley A, Brown S, Carmeliet P, Chambon P, Cox R, Davidson D, Davies K, Duboule D, Forejt J, Granucci F, Hastie N, de Angelis MH, Jackson I, Kioussis D, Kollias G, Lathrop M, Lendahl U, Malumbres M, von Melchner H, Müller W, Partanen J, Ricciardi-Castagnoli P, Rigby P, et al: TheEuropean dimension for the mouse genome mutagenesis program. Nat Genet 2004, 36:925-927.
48. Collins FS, Rossant J, Wurst W: A mouse for all reasons. Cell2007, 128:9-13.
49. Phenotypic Quality Ontology, PATO [http://obofoundry.org/ wiki/index.php/PATO:Main_Page]
50. Thiel CT, Horn D, Zabel B, Ekici AB, Salinas K, Gebhart E, Rüschendorf F, Sticht H, Spranger J, Müller D, Zweier C, Schmitt ME, Reis A, Rauch A: Severely incapacitating mutations in patients with extreme short stature identify RNAprocessing endoribonuclease RMRP as an essential cell growth regulator. Am J Hum Genet 2005, 77:795-806.
51. Tremblay K, Lemire M, Potvin C, Tremblay A, Hunninghake GM, Raby BA, Hudson TJ, Perez-Iratxeta C, Andrade-Navarro MA, Laprise C: Genes to diseases (G2D) computational method to identify asthma candidate genes. PLoS One 2008, 3:e2907.
52. Tiffin N, Okpechi I, Perez-Iratxeta C, Andrade-Navarro MA, Ramesar R: Prioritization of candidate disease genes for metabolic syndrome by computational analysis of its defining phenotypes. Physiol Genomics 2008, 35:55-64.
53. Tiffin N, Adie E, Turner F, Brunner HG, van Driel MA, Oti M, Lopez-Bigas N, Ouzounis C, Perez-Iratxeta C, Andrade-Navarro MA, Adeyemo A, Patti ME, Semple CA, Hide W: Computational disease gene identification: a concert of methods prioritizes type 2 diabetes and obesity candidate genes. Nucleic Acids Res 2006, 34:3067-3081.
54. Cho YS, Go MJ, Han HR, Cha SH, Kim HT, Min H, Shin HD, Park C, Han BG, Cho NH, Shin C, Kimm K, Oh B: Association of lipoprotein lipase (LPL) single nucleotide polymorphisms with type 2 diabetes mellitus. Exp Mol Med 2008, 40: 523-532.
55. Huang QY, Li GH, Cheung WM, Song YQ, Kung AW: Prediction of osteoporosis candidate genes by computational disease-gene identification strategy. J Hum Genet 2008, 53:644-655.
56. Lombard Z, Tiffin N, Hofmann O, Bajic VB, Hide W, Ramsay M: Computational selection and prioritization of candidate genes for fetal alcohol syndrome. BMC Genomics 2007, 8: 389.
57. van der Zwaag B, Franke L, Poot M, Hochstenbach R, Spierenburg HA, Vorstman JA, van Daalen E, de Jonge MV, Verbeek NE, Brilstra EH, van 't Slot R, Ophoff RA, van Es MA, Blauw HM, Veldink JH, Buizer-Voskamp JE, Beemer FA, van den Berg LH, Wijmenga C, van Amstel HK, van Engeland H, Burbach JP, Staal WG: Gene-network analysis identifies susceptibility genes related to glycobiology in autism. PLoS ONE 2009, 4:e5324.
58. Li JB, Levanon EY, Yoon JK, Aach J, Xie B, Leproust E, Zhang K, Gao Y, Church GM: Genome-wide identification of human RNA editing sites by parallel DNA capturing and sequencing. Science 2009, 324:1210-1213.
59. Mercer TR, Dinger ME, Mattick JS: Long non-coding RNAs: insights into functions. Nat Rev Genet 2009, 10:155-159.
60. Sabherwal N, Bangs F, Roth R, Weiss B, Jantz K, Tiecke E, Hinkel GK, Spaich C, Hauffa BP, van der Kamp H, Kapeller J, Tickle C, Rappold G: Long-range conserved non-coding SHOX sequences regulate expression in developing chicken limb and are associated with short stature phenotypes in human patients. Hum Mol Genet 2007, 16:210-222.
61. Clark SJ: Action at a distance: epigenetic silencing of large chromosomal regions in carcinogenesis. Hum Mol Genet 2007, 16(Spec 1):R88-R95.
62. Lavorgna G, Dahary D, Lehner B, Sorek R, Sanderson CM, Casari G: In search of antisense. Trends Biochem Sci 2004, 29: 88-94.
63. Danko CG, Pertsov AM: Identification of gene co-regulatory modules and associated cis-elements involved in degenerative heart disease. BMC Med Genomics 2009, 2:31.
64. Nam S, Li M, Choi K, Balch C, Kim S, Nephew KP: MicroRNA and mRNA integrated analysis (MMIA): a web tool for examining biological functions of microRNA expression. Nucleic Acids Res 2009, 37:W356-W362.
65. Adeyemo A, Rotimi C: Genetic variants associated with complex human diseases show wide variation across multiple populations. Public Health Genomics 2009, doi: 10.1159/ 000218711.
66. Lopez-Bigas N, Blencowe BJ, Ouzounis CA: Highly consistent patterns for inherited human diseases at the molecular level. Bioinformatics 2006, 22:269-277.
67. Freudenberg J, Propping P: A similarity-based method for genome-wide prediction of disease-relevant human genes. Bioinformatics 2002, 18(Suppl 2):S110-S115.
68. van Driel MA, Bruggeman J, Vriend G, Brunner HG, Leunissen JA: A text-mining analysis of the human phenome. Eur J Hum Genet 2006, 14:535-542.
69. Yang Q, Khoury MJ, Botto L, Friedman JM, Flanders WD: Improving the prediction of complex diseases by testing for multiple disease-susceptibility genes. Am J Hum Genet 2003, 72:636-649.