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

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

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.

Key words

Gene function Alternative splicing Exon expression RNA interference Functional annotation Molecular network Software tool Data integration Visual analytics 

Notes

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.

References

  1. 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 321:956–960PubMedCrossRefGoogle Scholar
  2. 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 6:377–382PubMedCrossRefGoogle Scholar
  3. 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:R64PubMedCrossRefGoogle Scholar
  4. 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 3:76–83PubMedCrossRefGoogle Scholar
  5. 5.
    Stamm S, Ben-Ari S, Rafalska I, Tang Y, Zhang Z, Toiber D, Thanaraj TA, Soreq H (2005) Function of alternative splicing. Gene 344:1–20PubMedCrossRefGoogle Scholar
  6. 6.
    Duursma AM, Kedde M, Schrier M, le Sage C, Agami R (2008) miR-148 targets human DNMT3b protein coding region. RNA 14:872–877PubMedCrossRefGoogle Scholar
  7. 7.
    McGlincy NJ, Smith CW (2008) Alternative splicing resulting in nonsense-mediated mRNA decay: what is the meaning of nonsense? Trends Biochem Sci 33:385–393PubMedCrossRefGoogle Scholar
  8. 8.
    Leeman JR, Gilmore TD (2008) Alternative splicing in the NF-kappaB signaling pathway. Gene 423:97–107PubMedCrossRefGoogle Scholar
  9. 9.
    Orengo JP, Cooper TA (2007) Alternative splicing in disease. Adv Exp Med Biol 623:212–223PubMedCrossRefGoogle Scholar
  10. 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 7:325PubMedCrossRefGoogle Scholar
  11. 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 24:1707–1714PubMedCrossRefGoogle Scholar
  12. 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 14:1470–1479PubMedCrossRefGoogle Scholar
  13. 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:D780–786PubMedCrossRefGoogle Scholar
  14. 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 411:494–498PubMedCrossRefGoogle Scholar
  15. 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: 806–811PubMedCrossRefGoogle Scholar
  16. 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:e1000437PubMedCrossRefGoogle Scholar
  17. 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 319:921–926PubMedCrossRefGoogle Scholar
  18. 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 16:277–286PubMedCrossRefGoogle Scholar
  19. 19.
    Kuritzkes DR (2009) HIV-1 entry inhibitors: an overview. Curr Opin HIV AIDS 4:82–87PubMedCrossRefGoogle Scholar
  20. 20.
    Cherry S (2009) What have RNAi screens taught us about viral–host interactions? Curr Opin Microbiol 12:446–452PubMedCrossRefGoogle Scholar
  21. 21.
    Sharma S, Rao A (2009) RNAi screening: tips and techniques. Nat Immunol 10:799–804PubMedCrossRefGoogle Scholar
  22. 22.
    Blencowe BJ (2006) Alternative splicing: new insights from global analyses. Cell 126:37–47PubMedCrossRefGoogle Scholar
  23. 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:R108PubMedCrossRefGoogle Scholar
  24. 24.
    Sammeth M, Foissac S, Guigo R (2008) A general definition and nomenclature for alternative splicing events. PLoS Comput Biol 4:e1000147PubMedCrossRefGoogle Scholar
  25. 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:W755–762PubMedCrossRefGoogle Scholar
  26. 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 2:2366–2382PubMedCrossRefGoogle Scholar
  27. 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:e1000553PubMedCrossRefGoogle Scholar
  28. 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–D806PubMedCrossRefGoogle Scholar
  29. 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 25:25–29PubMedCrossRefGoogle Scholar
  30. 30.
    Finn RD, Marshall M, Bateman A (2005) iPfam: visualization of protein–protein interactions in PDB at domain and amino acid resolutions. Bioinformatics 21:410–412PubMedCrossRefGoogle Scholar
  31. 31.
    Stein A, Russell RB, Aloy P (2005) 3did: interacting protein domains of known three-dimensional structure. Nucleic Acids Res 33:D413–417PubMedCrossRefGoogle Scholar
  32. 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 31:251–254PubMedCrossRefGoogle Scholar
  33. 33.
    Liu Y, Liu N, Zhao H (2005) Inferring protein–protein interactions through high-throughput interaction data from diverse organisms. Bioinformatics 21:3279–3285PubMedCrossRefGoogle Scholar
  34. 34.
    Riley R, Lee C, Sabatti C, Eisenberg D (2005) Inferring protein domain interactions from databases of interacting proteins. Genome Biol 6:R89PubMedCrossRefGoogle Scholar
  35. 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:D651–655PubMedCrossRefGoogle Scholar
  36. 36.
    Lee H, Deng M, Sun F, Chen T (2006) An integrated approach to the prediction of domain-domain interactions. BMC Bioinformatics 7:269PubMedCrossRefGoogle Scholar
  37. 37.
    Chen XW, Liu M (2005) Prediction of protein–protein interactions using random decision forest framework. Bioinformatics 21:4394–4400PubMedCrossRefGoogle Scholar
  38. 38.
    Schelhorn SE, Lengauer T, Albrecht M (2008) An integrative approach for predicting interactions of protein regions. Bioinformatics 24:i35–41PubMedCrossRefGoogle Scholar
  39. 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 1:349–356PubMedCrossRefGoogle Scholar
  40. 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 2:392–399PubMedCrossRefGoogle Scholar
  41. 41.
    Jackson AL, Linsley PS (2010) Recognizing and avoiding siRNA off-target effects for target identification and therapeutic application. Nat Rev Drug Discov 9:57–67PubMedCrossRefGoogle Scholar
  42. 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 75:309–318PubMedGoogle Scholar
  43. 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 9:32–45PubMedCrossRefGoogle Scholar
  44. 44.
    Boutros M, Bras LP, Huber W (2006) Analysis of cell-based RNAi screens. Genome Biol 7:R66PubMedCrossRefGoogle Scholar
  45. 45.
    Rieber N, Knapp B, Eils R, Kaderali L (2009) RNAither, an automated pipeline for the statistical analysis of high-throughput RNAi screens. Bioinformatics 25:678–679PubMedCrossRefGoogle Scholar
  46. 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 6:569–575PubMedCrossRefGoogle Scholar
  47. 47.
    Ramírez F, Lawyer G, Albrecht M (2012) Novel search method for the discovery of functional relationships. Bioinformatics 28:269–276CrossRefGoogle Scholar
  48. 48.
    da Huang W, Sherman BT, Lempicki RA (2009) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4:44–57CrossRefGoogle Scholar
  49. 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 23:401–407PubMedCrossRefGoogle Scholar
  50. 50.
    Dyer MD, Murali TM, Sobral BW (2008) The landscape of human proteins interacting with viruses and other pathogens. PLoS Pathog 4:e32PubMedCrossRefGoogle Scholar
  51. 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:e13139PubMedCrossRefGoogle Scholar
  52. 52.
    Stein A, Aloy P (2010) Novel peptide-mediated interactions derived from high-resolution 3-dimensional structures. PLoS Comput Biol 6:e1000789PubMedCrossRefGoogle Scholar
  53. 53.
    Blom N, Gammeltoft S, Brunak S (1999) Sequence and structure-based prediction of eukaryotic protein phosphorylation sites. J Mol Biol 294:1351–1362PubMedCrossRefGoogle Scholar
  54. 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 31:3625–3630PubMedCrossRefGoogle Scholar
  55. 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 106:16410–16415PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  1. 1.Max Planck Institute for InformaticsSaarbrückenGermany

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