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Functional Characterization of Human Genes from Exon Expression and RNA Interference Results

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Book cover Bioinformatics and Drug Discovery

Part of the book series: Methods in Molecular Biology ((MIMB,volume 910))

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Abstract

Complex biological systems comprise a large number of interacting molecules. The identification and detailed characterization of the functions of the involved genes and proteins are crucial for modeling and understanding such systems. To interrogate the various cellular processes, high-throughput techniques such as the Affymetrix Exon Array or RNA interference (RNAi) screens are powerful experimental approaches for functional genomics. However, they typically yield long gene lists that require computational methods to further analyze and functionally annotate the experimental results and to gain more insight into important molecular interactions. Here, we focus on bioinformatics software tools for the functional interpretation of exon expression data to discover alternative splicing events and their impact on gene and protein architecture, molecular networks, and pathways. We additionally demonstrate how to explore large lists of candidate genes as they also result from RNAi screens. In particular, our exemplary application studies show how to analyze the function of human genes that play a major role in human stem cells or viral infections.

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References

  1. Sultan M, Schulz MH, Richard H, Magen A, Klingenhoff A, Scherf M, Seifert M, Borodina T, Soldatov A, Parkhomchuk D et al (2008) A global view of gene activity and alternative splicing by deep sequencing of the human transcriptome. Science 321:956–960

    Article  PubMed  CAS  Google Scholar 

  2. Tang F, Barbacioru C, Wang Y, Nordman E, Lee C, Xu N, Wang X, Bodeau J, Tuch BB, Siddiqui A et al (2009) mRNA-Seq whole-transcriptome analysis of a single cell. Nat Methods 6:377–382

    Article  PubMed  CAS  Google Scholar 

  3. Clark TA, Schweitzer AC, Chen TX, Staples MK, Lu G, Wang H, Williams A, Blume JE (2007) Discovery of tissue-specific exons using comprehensive human exon microarrays. Genome Biol 8:R64

    Article  PubMed  Google Scholar 

  4. Resch A, Xing Y, Modrek B, Gorlick M, Riley R, Lee C (2004) Assessing the impact of alternative splicing on domain interactions in the human proteome. J Proteome Res 3:76–83

    Article  PubMed  CAS  Google Scholar 

  5. Stamm S, Ben-Ari S, Rafalska I, Tang Y, Zhang Z, Toiber D, Thanaraj TA, Soreq H (2005) Function of alternative splicing. Gene 344:1–20

    Article  PubMed  CAS  Google Scholar 

  6. Duursma AM, Kedde M, Schrier M, le Sage C, Agami R (2008) miR-148 targets human DNMT3b protein coding region. RNA 14:872–877

    Article  PubMed  CAS  Google Scholar 

  7. McGlincy NJ, Smith CW (2008) Alternative splicing resulting in nonsense-mediated mRNA decay: what is the meaning of nonsense? Trends Biochem Sci 33:385–393

    Article  PubMed  CAS  Google Scholar 

  8. Leeman JR, Gilmore TD (2008) Alternative splicing in the NF-kappaB signaling pathway. Gene 423:97–107

    Article  PubMed  CAS  Google Scholar 

  9. Orengo JP, Cooper TA (2007) Alternative splicing in disease. Adv Exp Med Biol 623:212–223

    Article  PubMed  Google Scholar 

  10. Gardina PJ, Clark TA, Shimada B, Staples MK, Yang Q, Veitch J, Schweitzer A, Awad T, Sugnet C, Dee S et al (2006) Alternative splicing and differential gene expression in colon cancer detected by a whole genome exon array. BMC Genomics 7:325

    Article  PubMed  Google Scholar 

  11. Purdom E, Simpson KM, Robinson MD, Conboy JG, Lapuk AV, Speed TP (2008) FIRMA: a method for detection of alternative splicing from exon array data. Bioinformatics 24:1707–1714

    Article  PubMed  CAS  Google Scholar 

  12. Xing Y, Stoilov P, Kapur K, Han A, Jiang H, Shen S, Black DL, Wong WH (2008) MADS: a new and improved method for analysis of differential alternative splicing by exon-tiling microarrays. RNA 14:1470–1479

    Article  PubMed  CAS  Google Scholar 

  13. Yates T, Okoniewski MJ, Miller CJ (2008) X:Map: annotation and visualization of genome structure for Affymetrix exon array analysis. Nucleic Acids Res 36:D780–786

    Article  PubMed  CAS  Google Scholar 

  14. Elbashir SM, Harborth J, Lendeckel W, Yalcin A, Weber K, Tuschl T (2001) Duplexes of 21-nucleotide RNAs mediate RNA interference in cultured mammalian cells. Nature 411:494–498

    Article  PubMed  CAS  Google Scholar 

  15. Fire A, Xu S, Montgomery MK, Kostas SA, Driver SE, Mello CC (1998) Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans. Nature 391: 806–811

    Article  PubMed  CAS  Google Scholar 

  16. Bushman FD, Malani N, Fernandes J, D’Orso I, Cagney G, Diamond TL, Zhou H, Hazuda DJ, Espeseth AS, Konig R et al (2009) Host cell factors in HIV replication: meta-analysis of genome-wide studies. PLoS Pathog 5:e1000437

    Article  PubMed  Google Scholar 

  17. Brass AL, Dykxhoorn DM, Benita Y, Yan N, Engelman A, Xavier RJ, Lieberman J, Elledge SJ (2008) Identification of host proteins required for HIV infection through a functional genomic screen. Science 319:921–926

    Article  PubMed  CAS  Google Scholar 

  18. Georgel P, Schuster C, Zeisel MB, Stoll-Keller F, Berg T, Bahram S, Baumert TF (2010) Virus-host interactions in hepatitis C virus infection: implications for molecular pathogenesis and antiviral strategies. Trends Mol Med 16:277–286

    Article  PubMed  CAS  Google Scholar 

  19. Kuritzkes DR (2009) HIV-1 entry inhibitors: an overview. Curr Opin HIV AIDS 4:82–87

    Article  PubMed  Google Scholar 

  20. Cherry S (2009) What have RNAi screens taught us about viral–host interactions? Curr Opin Microbiol 12:446–452

    Article  PubMed  CAS  Google Scholar 

  21. Sharma S, Rao A (2009) RNAi screening: tips and techniques. Nat Immunol 10:799–804

    Article  PubMed  CAS  Google Scholar 

  22. Blencowe BJ (2006) Alternative splicing: new insights from global analyses. Cell 126:37–47

    Article  PubMed  CAS  Google Scholar 

  23. Fagnani M, Barash Y, Ip JY, Misquitta C, Pan Q, Saltzman AL, Shai O, Lee L, Rozenhek A, Mohammad N et al (2007) Functional coordination of alternative splicing in the mammalian central nervous system. Genome Biol 8:R108

    Article  PubMed  Google Scholar 

  24. Sammeth M, Foissac S, Guigo R (2008) A general definition and nomenclature for alternative splicing events. PLoS Comput Biol 4:e1000147

    Article  PubMed  Google Scholar 

  25. Emig D, Salomonis N, Baumbach J, Lengauer T, Conklin BR, Albrecht M (2010) AltAnalyze and DomainGraph: analyzing and visualizing exon expression data. Nucleic Acids Res 38:W755–762

    Article  PubMed  CAS  Google Scholar 

  26. Cline MS, Smoot M, Cerami E, Kuchinsky A, Landys N, Workman C, Christmas R, Avila-Campilo I, Creech M, Gross B et al (2007) Integration of biological networks and gene expression data using Cytoscape. Nat Protoc 2:2366–2382

    Article  PubMed  CAS  Google Scholar 

  27. Salomonis N, Nelson B, Vranizan K, Pico AR, Hanspers K, Kuchinsky A, Ta L, Mercola M, Conklin BR (2009) Alternative splicing in the differentiation of human embryonic stem cells into cardiac precursors. PLoS Comput Biol 5:e1000553

    Article  PubMed  Google Scholar 

  28. Flicek P, Amode MR, Barrell D, Beal K, Brent S, Chen Y, Clapham P, Coates G, Fairley S, Fitzgerald S et al (2011) Ensembl. Nucleic Acids Res 39:D800–D806

    Article  PubMed  Google Scholar 

  29. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT et al (2000) Gene Ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25:25–29

    Article  PubMed  CAS  Google Scholar 

  30. Finn RD, Marshall M, Bateman A (2005) iPfam: visualization of protein–protein interactions in PDB at domain and amino acid resolutions. Bioinformatics 21:410–412

    Article  PubMed  CAS  Google Scholar 

  31. Stein A, Russell RB, Aloy P (2005) 3did: interacting protein domains of known three-dimensional structure. Nucleic Acids Res 33:D413–417

    Article  PubMed  CAS  Google Scholar 

  32. Ng SK, Zhang Z, Tan SH, Lin K (2003) InterDom: a database of putative interacting protein domains for validating predicted protein interactions and complexes. Nucleic Acids Res 31:251–254

    Article  PubMed  CAS  Google Scholar 

  33. Liu Y, Liu N, Zhao H (2005) Inferring protein–protein interactions through high-throughput interaction data from diverse organisms. Bioinformatics 21:3279–3285

    Article  PubMed  CAS  Google Scholar 

  34. Riley R, Lee C, Sabatti C, Eisenberg D (2005) Inferring protein domain interactions from databases of interacting proteins. Genome Biol 6:R89

    Article  PubMed  Google Scholar 

  35. Pagel P, Oesterheld M, Tovstukhina O, Strack N, Stumpflen V, Frishman D (2008) DIMA 2.0–predicted and known domain interactions. Nucleic Acids Res 36:D651–655

    Article  PubMed  CAS  Google Scholar 

  36. Lee H, Deng M, Sun F, Chen T (2006) An integrated approach to the prediction of domain-domain interactions. BMC Bioinformatics 7:269

    Article  PubMed  Google Scholar 

  37. Chen XW, Liu M (2005) Prediction of protein–protein interactions using random decision forest framework. Bioinformatics 21:4394–4400

    Article  PubMed  CAS  Google Scholar 

  38. Schelhorn SE, Lengauer T, Albrecht M (2008) An integrative approach for predicting interactions of protein regions. Bioinformatics 24:i35–41

    Article  PubMed  Google Scholar 

  39. Deane CM, Salwinski L, Xenarios I, Eisenberg D (2002) Protein interactions: two methods for assessment of the reliability of high throughput observations. Mol Cell Proteomics 1:349–356

    Article  PubMed  CAS  Google Scholar 

  40. Erfle H, Neumann B, Liebel U, Rogers P, Held M, Walter T, Ellenberg J, Pepperkok R (2007) Reverse transfection on cell arrays for high content screening microscopy. Nat Protoc 2:392–399

    Article  PubMed  CAS  Google Scholar 

  41. Jackson AL, Linsley PS (2010) Recognizing and avoiding siRNA off-target effects for target identification and therapeutic application. Nat Rev Drug Discov 9:57–67

    Article  PubMed  CAS  Google Scholar 

  42. Matula P, Kumar A, Worz I, Erfle H, Bartenschlager R, Eils R, Rohr K (2009) Single-cell-based image analysis of high-throughput cell array screens for quantification of viral infection. Cytometry A 75:309–318

    PubMed  Google Scholar 

  43. Reiss S, Rebhan I, Backes P, Romero-Brey I, Erfle H, Matula P, Kaderali L, Poenisch M, Blankenburg H, Hiet MS et al (2011) Recruitment and activation of a lipid kinase by hepatitis C virus NS5A is essential for integrity of the membranous replication compartment. Cell Host Microbe 9:32–45

    Article  PubMed  CAS  Google Scholar 

  44. Boutros M, Bras LP, Huber W (2006) Analysis of cell-based RNAi screens. Genome Biol 7:R66

    Article  PubMed  Google Scholar 

  45. Rieber N, Knapp B, Eils R, Kaderali L (2009) RNAither, an automated pipeline for the statistical analysis of high-throughput RNAi screens. Bioinformatics 25:678–679

    Article  PubMed  CAS  Google Scholar 

  46. Birmingham A, Selfors LM, Forster T, Wrobel D, Kennedy CJ, Shanks E, Santoyo-Lopez J, Dunican DJ, Long A, Kelleher D et al (2009) Statistical methods for analysis of high-throughput RNA interference screens. Nat Methods 6:569–575

    Article  PubMed  CAS  Google Scholar 

  47. Ramírez F, Lawyer G, Albrecht M (2012) Novel search method for the discovery of functional relationships. Bioinformatics 28:269–276

    Article  CAS  Google Scholar 

  48. da Huang W, Sherman BT, Lempicki RA (2009) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4:44–57

    Article  CAS  Google Scholar 

  49. Rivals I, Personnaz L, Taing L, Potier MC (2007) Enrichment or depletion of a GO category within a class of genes: which test? Bioinformatics 23:401–407

    Article  PubMed  CAS  Google Scholar 

  50. Dyer MD, Murali TM, Sobral BW (2008) The landscape of human proteins interacting with viruses and other pathogens. PLoS Pathog 4:e32

    Article  PubMed  Google Scholar 

  51. Jaeger S, Ertaylan G, van Dijk D, Leser U, Sloot P (2010) Inference of surface membrane factors of HIV-1 infection through functional interaction networks. PLoS One 5:e13139

    Article  PubMed  Google Scholar 

  52. Stein A, Aloy P (2010) Novel peptide-mediated interactions derived from high-resolution 3-dimensional structures. PLoS Comput Biol 6:e1000789

    Article  PubMed  Google Scholar 

  53. Blom N, Gammeltoft S, Brunak S (1999) Sequence and structure-based prediction of eukaryotic protein phosphorylation sites. J Mol Biol 294:1351–1362

    Article  PubMed  CAS  Google Scholar 

  54. Puntervoll P, Linding R, Gemund C, Chabanis-Davidson S, Mattingsdal M, Cameron S, Martin DM, Ausiello G, Brannetti B, Costantini A et al (2003) ELM server: a new resource for investigating short functional sites in modular eukaryotic proteins. Nucleic Acids Res 31:3625–3630

    Article  PubMed  CAS  Google Scholar 

  55. Li Q, Brass AL, Ng A, Hu Z, Xavier RJ, Liang TJ, Elledge SJ (2009) A genome-wide genetic screen for host factors required for hepatitis C virus propagation. Proc Natl Acad Sci USA 106:16410–16415

    Article  PubMed  CAS  Google Scholar 

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Acknowledgements

Part of this study was financially supported by the German National Genome Research Network (NGFN) and by the German Research Foundation (DFG), contract number KFO 129/1-2. The work was also conducted in the context of the DFG-funded Cluster of Excellence for Multimodal Computing and Interaction.

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Correspondence to Mario Albrecht .

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Emig, D., Blankenburg, H., Ramírez, F., Albrecht, M. (2012). Functional Characterization of Human Genes from Exon Expression and RNA Interference Results. In: Larson, R. (eds) Bioinformatics and Drug Discovery. Methods in Molecular Biology, vol 910. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-61779-965-5_3

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  • DOI: https://doi.org/10.1007/978-1-61779-965-5_3

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  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-61779-964-8

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