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Das methodische Potenzial der neuen Sequenziertechnologien jenseits der Mutationssuche

Methodological potential of new sequencing technologies beyond the search for mutations

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medizinische genetik

Zusammenfassung

In diesem Beitrag wird eine Reihe wichtiger Anwendungen der neuen Sequenziertechnologien bzw. des Next Generation Sequencing (NGS) vorgestellt. An ausgewählten Beispielen werden für jede Methode die Anwendungsmöglichkeiten in der humangenetischen Forschung dargestellt, jeweils das prinzipielle Vorgehen beschrieben und mögliche Quellen für ausführliche Arbeitsanweisungen vorgestellt. Die beschriebenen Techniken umfassen im Einzelnen: RNA-Sequenzierung mittels NGS („RNA-Seq“), Chromatinimmunpräzipitation in Kombination mit NGS („ChIP-Seq“), „ribosome profiling“, Immunpräzipitation methylierter DNA-Segmente in Kombination mit NGS („methylated DNA immunoprecipitation“ bzw. „MeDIP-Seq“) und die HiC-Technik, eine Weiterentwicklung der Chromosome-Conformation-Capture(3c)-Methode.

Abstract

In this article, a number of important applications for next generation sequencing (NGS)-based techniques are presented. For each method the technical principles are introduced, the application options in human genetic research using selected examples are illustrated and possible sources for detailed protocols are indicated. The following methods are described: RNA sequencing using NGS (RNA-seq), chromatin immunoprecipitation in combination with NGS (ChIP-seq), ribosome profiling, methylated DNA immunoprecipitation in combination with NGS (MeDIP-seq) and the HiC technique, an extension of the chromosome confirmation capture (3c) method.

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Literatur

  1. Adomas AB, Grimm SA, Malone C et al (2014) Breast tumor specific mutation in GATA3 affects physiological mechanisms regulating transcription factor turnover. BMC Cancer 14:278

    Article  PubMed Central  PubMed  Google Scholar 

  2. Albuisson J, Isidor B, Giraud M et al (2011) Identification of two novel mutations in Shh long-range regulator associated with familial pre-axial polydactyly. Clin Genet 79:371–377

    Article  CAS  PubMed  Google Scholar 

  3. Anders S, Huber W (2010) Differential expression analysis for sequence count data. Genome Biol 11:R106

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  4. Bell CG, Wilson GA, Butcher LM et al (2012) Human-specific CpG „beacons“ identify loci associated with human-specific traits and disease. Epigenetics 7:1188–1199

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  5. Boycott KM, Vanstone MR, Bulman DE et al (2013) Rare-disease genetics in the era of next-generation sequencing: discovery to translation. Nat Rev Genet 14:681–691

    Article  CAS  PubMed  Google Scholar 

  6. Bullard JH, Purdom E, Hansen KD et al (2010) Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments. BMC Bioinformatics 11:94

    Article  PubMed Central  PubMed  Google Scholar 

  7. Cho I, Blaser MJ (2012) The human microbiome: at the interface of health and disease. Nat Rev Genet 13:260–270

    CAS  PubMed Central  PubMed  Google Scholar 

  8. Cui P, Lin Q, Ding F et al (2010) A comparison between ribo-minus RNA-sequencing and polyA-selected RNA-sequencing. Genomics 96:259–265

    Article  CAS  PubMed  Google Scholar 

  9. Dathe K, Kjaer KW, Brehm A et al (2009) Duplications involving a conserved regulatory element downstream of BMP2 are associated with brachydactyly type A2. Am J Hum Genet 84:483–492

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  10. Dekker J, Rippe K, Dekker M et al (2002) Capturing chromosome conformation. Science 295:1306–1311

    Article  CAS  PubMed  Google Scholar 

  11. Edgren H, Murumagi A, Kangaspeska S et al (2011) Identification of fusion genes in breast cancer by paired-end RNA-sequencing. Genome Biol 12:R6

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  12. Fu GK, Xu W, Wilhelmy J et al (2014) Molecular indexing enables quantitative targeted RNA sequencing and reveals poor efficiencies in standard library preparations. Proc Natl Acad Sci U S A 111:1891–1896

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  13. Gurtan AM, Sharp PA (2013) The role of miRNAs in regulating gene expression networks. J Mol Biol 425:3582–3600

    Article  CAS  PubMed  Google Scholar 

  14. Guttman M, Russell P, Ingolia NT et al (2013) Ribosome profiling provides evidence that large noncoding RNAs do not encode proteins. Cell 154:240–251

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  15. Hafner M, Renwick N, Farazi TA et al (2012) Barcoded cDNA library preparation for small RNA profiling by next-generation sequencing. Methods 58:164–170

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  16. Hansen KD, Brenner SE, Dudoit S (2010) Biases in Illumina transcriptome sequencing caused by random hexamer priming. Nucleic Acids Res 38:e131

    Article  PubMed Central  PubMed  Google Scholar 

  17. Ingolia NT, Brar GA, Rouskin S et al (2012) The ribosome profiling strategy for monitoring translation in vivo by deep sequencing of ribosome-protected mRNA fragments. Nat Protoc 7:1534–1550

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  18. Ingolia NT, Brar GA, Rouskin S et al (2013) Genome-wide annotation and quantitation of translation by ribosome profiling. Curr Protoc Mol Biol Chapter 4:Unit 4 18

    Google Scholar 

  19. Jensen LR, Bartenschlager H, Rujirabanjerd S et al (2010) A distinctive gene expression fingerprint in mentally retarded male patients reflects disease-causing defects in the histone demethylase KDM5C. Pathogenetics 3:2

    Article  PubMed Central  PubMed  Google Scholar 

  20. Li J, Jiang H, Wong WH (2010) Modeling non-uniformity in short-read rates in RNA-Seq data. Genome Biol 11:R50

    Article  PubMed Central  PubMed  Google Scholar 

  21. Lieberman-Aiden E, Berkum NL van, Williams L et al (2009) Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326:289–293

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  22. Markowitz VM, Korzeniewski F, Palaniappan K et al (2006) The integrated microbial genomes (IMG) system. Nucleic Acids Res 34:D344–D348

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  23. Michel AM, Choudhury KR, Firth AE et al (2012) Observation of dually decoded regions of the human genome using ribosome profiling data. Genome Res 22:2219–2229

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  24. Montgomery SB, Sammeth M, Gutierrez-Arcelus M et al (2010) Transcriptome genetics using second generation sequencing in a Caucasian population. Nature 464:773–777

    Article  CAS  PubMed  Google Scholar 

  25. Morlan JD, Qu K, Sinicropi DV (2012) Selective depletion of rRNA enables whole transcriptome profiling of archival fixed tissue. PLoS One 7:e42882

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  26. Nakagawa H (2013) Prostate cancer genomics by high-throughput technologies: genome-wide association study and sequencing analysis. Endocr Relat Cancer 20:R171–R181

    Article  CAS  PubMed  Google Scholar 

  27. Norton N, Sun Z, Asmann YW et al (2013) Gene expression, single nucleotide variant and fusion transcript discovery in archival material from breast tumors. PLoS One 8:e81925

    Article  PubMed Central  PubMed  Google Scholar 

  28. Parker BC, Engels M, Annala M et al (2014) Emergence of FGFR family gene fusions as therapeutic targets in a wide spectrum of solid tumours. J Pathol 232:4–15

    Article  CAS  PubMed  Google Scholar 

  29. Pickrell JK, Marioni JC, Pai AA et al (2010) Understanding mechanisms underlying human gene expression variation with RNA sequencing. Nature 464:768–772

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  30. Quinn EM, Cormican P, Kenny EM et al (2013) Development of strategies for SNP detection in RNA-seq data: application to lymphoblastoid cell lines and evaluation using 1000 genomes data. PLoS One 8:e58815

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  31. Roberts A, Trapnell C, Donaghey J et al (2011) Improving RNA-Seq expression estimates by correcting for fragment bias. Genome Biol 12:R22

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  32. Rooijers K, Loayza-Puch F, Nijtmans LG et al (2013) Ribosome profiling reveals features of normal and disease-associated mitochondrial translation. Nat Commun 4:2886

    Article  PubMed Central  PubMed  Google Scholar 

  33. Satoh J, Kawana N, Yamamoto Y (2013) Pathway analysis of ChIP-Seq-Based NRF1 target genes suggests a logical hypothesis of their involvement in the pathogenesis of neurodegenerative diseases. Gene Regul Syst Bio 7:139–152

    Article  PubMed Central  PubMed  Google Scholar 

  34. Siegel TN, Hekstra DR, Kemp LE et al (2009) Four histone variants mark the boundaries of polycistronic transcription units in Trypanosoma brucei. Genes Dev 23:1063–1076

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  35. Smits P, Mattijssen S, Morava E et al (2010) Functional consequences of mitochondrial tRNA Trp and tRNA Arg mutations causing combined OXPHOS defects. Eur J Hum Genet 18:324–329

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  36. Taiwo O, Wilson GA, Morris T et al (2012) Methylome analysis using MeDIP-seq with low DNA concentrations. Nat Protoc 7:617–636

    Article  CAS  PubMed  Google Scholar 

  37. Berkum NL van, Lieberman-Aiden E, Williams L et al (2010) Hi-C: a method to study the three-dimensional architecture of genomes. J Vis Exp 39:1869

    PubMed  Google Scholar 

  38. Dijk EL van, Jaszczyszyn Y, Thermes C (2014) Library preparation methods for next-generation sequencing: tone down the bias. Exp Cell Res 322:12–20

    Article  PubMed  Google Scholar 

  39. Watanabe K, Biesinger J, Salmans ML et al (2014) Integrative ChIP-seq/microarray analysis identifies a CTNNB1 target signature enriched in intestinal stem cells and colon cancer. PLoS One 9:e92317

    Article  PubMed Central  PubMed  Google Scholar 

  40. Xiao Y, Camarillo C, Ping Y et al (2014) The DNA methylome and transcriptome of different brain regions in schizophrenia and bipolar disorder. PLoS One 9:e95875

    Article  PubMed Central  PubMed  Google Scholar 

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Danksagung

Der Autor dankt Prof. U. Felbor für konstruktive Kommentare.

Einhaltung ethischer Richtlinien

Interessenkonflikt. A. W. Kuß gibt an, dass kein Interessenkonflikt besteht.

Dieser Beitrag beinhaltet keine Studien an Menschen oder Tieren.

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  1. Institut für Humangenetik, Universitätsmedizin Greifswald, und Interfakultäres Institut für Genetik und Funktionelle Genomforschung, Universität Greifswald, Fleischmannstr. 42–44, 17475, Greifswald, Deutschland

    A.W. Kuss

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Kuss, A. Das methodische Potenzial der neuen Sequenziertechnologien jenseits der Mutationssuche. medgen 26, 264–272 (2014). https://doi.org/10.1007/s11825-014-0449-5

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