Skip to main content

Barcode Sequencing for Understanding Drug–Gene Interactions

  • Protocol
  • First Online:
Bioinformatics and Drug Discovery

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

Abstract

With the advent of next-generation sequencing (NGS) technology, methods previously developed for microarrays have been adapted for use by NGS. Here we describe in detail a protocol for Barcode analysis by sequencing (Bar-seq) to assess pooled competitive growth of individually barcoded yeast deletion mutants. This protocol has been optimized on two sequencing platforms: Illumina’s Genome Analyzer IIx/HiSeq2000 and Life Technologies SOLiD3/5500. In addition, we provide guidelines for assessment of human knockdown cells using short-hairpin RNAs (shRNA) and an Illumina sequencing readout.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 159.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. DiMasi JA, Hansen RW, Grabowski HG (2003) The price of innovation: new estimates of drug development costs. J Health Econ 22(2):151–185

    Article  PubMed  Google Scholar 

  2. Higgins MJ, Graham SJ (2009) Intellectual property. Balancing innovation and access: patent challenges tip the scales. Science 326(5951):370–371

    Article  PubMed  CAS  Google Scholar 

  3. Waller CL, Shah A, Nolte M (2007) Strategies to support drug discovery through integration of systems and data. Drug Discov Today 12(15–16):634–639

    Article  PubMed  CAS  Google Scholar 

  4. Hopkins AL (2008) Network pharmacology: the next paradigm in drug discovery. Nat Chem Biol 4(11):682–690

    Article  PubMed  CAS  Google Scholar 

  5. Hopkins AL (2009) Drug discovery: predicting promiscuity. Nature 462(7270):167–168

    Article  PubMed  CAS  Google Scholar 

  6. Munos B (2009) Lessons from 60 years of pharmaceutical innovation. Nat Rev Drug Discov 8(12):959–968

    Article  PubMed  CAS  Google Scholar 

  7. Szarenings K et al (2004) Fishing for targets: novel approaches using small molecule baits. Drug Discov Today 1(1):9–15

    Google Scholar 

  8. Roth BL, Sheffler DJ, Kroeze WK (2004) Magic shotguns versus magic bullets: selectively non-selective drugs for mood disorders and schizophrenia. Nature Rev Drug Discov 3(4):353–359

    Article  CAS  Google Scholar 

  9. Metz JT, Hajduk PJ (2010) Rational approaches to targeted polypharmacology: creating and navigating protein-ligand interaction networks. Curr Opin Chem Biol 14(4): 498–504

    Article  PubMed  CAS  Google Scholar 

  10. Hillenmeyer ME et al (2008) The chemical genomic potrait of yeast: uncovering a phenotype for all genes. Science 320(5874):362–365

    Article  PubMed  CAS  Google Scholar 

  11. Parsons AB et al (2006) Exploring the mode-of-action of bioactive compounds by chemical-genetic profiling in yeast. Cell 126(3): 611–625

    Article  PubMed  CAS  Google Scholar 

  12. Costanzo M et al (2010) The genetic landscape of a cell. Science 327(5964):425–431

    Article  PubMed  CAS  Google Scholar 

  13. Hughes TR et al (2000) Functional discovery via a compendium of expression profiles. Cell 102(1):109–126

    Article  PubMed  CAS  Google Scholar 

  14. Marton MJ et al (1998) Drug target validation and identification of secondary drug target effects using DNA microarrays. Nat Med 4(11):1293–1301

    Article  PubMed  CAS  Google Scholar 

  15. Parsons AB et al (2004) Integration of chemical-genetic and genetic interaction data links bioactive compounds to cellular target pathways. Nat Biotechnol 22(1):62–69

    Article  PubMed  CAS  Google Scholar 

  16. Giaever G et al (2004) Chemogenomic profiling: identifying the functional interactions of small molecules in yeast. Proc Natl Acad Sci USA 101(3):793–798

    Article  PubMed  CAS  Google Scholar 

  17. Giaever G et al (1999) Genomic profiling of drug sensitivities via induced haploinsufficiency. Nat Genet 21(3):278–283

    Article  PubMed  CAS  Google Scholar 

  18. Giaever G et al (2002) Functional profiling of the Saccharomyces cerevisiae genome. Nature 418(6896):387–391

    Article  PubMed  CAS  Google Scholar 

  19. Winzeler EA et al (1999) Functional ­characterization of the S. cerevisiae genome by gene deletion and parallel analysis. Science 285:901–906

    Article  PubMed  CAS  Google Scholar 

  20. Ho CH et al (2009) A molecular barcoded yeast ORF library enables mode-of-action analysis of bioactive compounds. Nat Biotechnol 27(4):369–377

    Article  PubMed  CAS  Google Scholar 

  21. Davierwala AP et al (2005) The synthetic genetic interaction spectrum of essential genes. Nat Genet 37:1147–1152

    Article  PubMed  CAS  Google Scholar 

  22. Mnaimneh S et al (2004) Exploration of essential gene functions via titratable promoter alleles. Cell 118(1):31–44

    Article  PubMed  CAS  Google Scholar 

  23. Sopko R et al (2006) Mapping pathways and phenotypes by systematic gene overexpression. Mol Cell 21(3):319–330

    Article  PubMed  CAS  Google Scholar 

  24. Tong AH et al (2001) Systematic genetic analysis with ordered arrays of yeast deletion mutants. Science 294(5550):2364–2368

    Article  PubMed  CAS  Google Scholar 

  25. Tong AH et al (2004) Global mapping of the yeast genetic interaction network. Science 303(5659):808–813

    Article  PubMed  CAS  Google Scholar 

  26. Pierce SE et al (2007) Genome-wide analysis of barcoded Saccharomyces cerevisiae gene-deletion mutants in pooled cultures. Nat Protoc 2(11):2958–2974

    Article  PubMed  CAS  Google Scholar 

  27. Pierce SE et al (2006) A unique and universal molecular barcode array. Nat Methods 3(8): 601–603

    Article  PubMed  CAS  Google Scholar 

  28. Lum PY et al (2004) Discovering modes of action for therapeutic compounds using a genome-wide screen of yeast heterozygotes. Cell 116(1):121–137

    Article  PubMed  CAS  Google Scholar 

  29. Hoon S et al (2008) An integrated platform of genomic assays reveals small-molecule bioactivities. Nat Chem Biol 4(8):498–506

    Article  PubMed  CAS  Google Scholar 

  30. Lee W et al (2005) Genome-wide requirements for resistance to functionally distinct DNA-damaging agents. PLoS Genet 1(2):e24

    Article  PubMed  Google Scholar 

  31. Oh J et al (2010) Gene annotation and drug target discovery in Candida albicans with a tagged transposon mutant collection. PLoS Pathog 6(10):e1001140

    Article  PubMed  Google Scholar 

  32. Xu D et al (2007) Genome-wide fitness test and mechanism-of-action studies of inhibitory compounds in Candida albicans. PLoS Pathog 3(6):e92

    Article  PubMed  Google Scholar 

  33. Xu D et al (2009) Chemical genetic profiling and characterization of small-molecule compounds that affect the biosynthesis of unsaturated fatty acids in Candida albicans. J Biol Chem 284(29):19754–19764

    Article  PubMed  CAS  Google Scholar 

  34. Dorer RK et al (2005) A small-molecule ­inhibitor of Mps1 blocks the spindle-­checkpoint response to a lack of tension on mitotic chromosomes. Curr Biol 15(11):1070–1076

    Article  PubMed  CAS  Google Scholar 

  35. Smith AM et al (2009) Quantitative phenotyping via deep barcode sequencing. Genome Res 19(10):1836–1842

    Article  PubMed  CAS  Google Scholar 

  36. St Onge RP et al (2007) Systematic pathway analysis using high-resolution fitness profiling of combinatorial gene deletions. Nat Genet 39(2):199–206

    Article  PubMed  CAS  Google Scholar 

  37. Yan Z et al (2008) Yeast Barcoders: a chemogenomic application of a universal donor-strain collection carrying bar-code identifiers. Nat Methods 5(8):719–725

    Article  PubMed  CAS  Google Scholar 

  38. Ericson E et al (2008) Off-target effects of psychoactive drugs revealed by genome-wide assays in yeast. PLoS Genet 4(8):e1000151

    Article  PubMed  Google Scholar 

  39. Rock FL et al (2007) An antifungal agent inhibits an aminoacyl-tRNA synthetase by trapping tRNA in the editing site. Science 316(5832):1759–1761

    Article  PubMed  CAS  Google Scholar 

  40. Yu H et al (2008) High-quality binary protein interaction map of the yeast interactome network. Science 322(5898):104–110

    Article  PubMed  CAS  Google Scholar 

  41. Goh KI et al (2007) The human disease network. Proc Natl Acad Sci USA 104(21): 8685–8690

    Article  PubMed  CAS  Google Scholar 

  42. Moffat J et al (2006) A lentiviral RNAi library for human and mouse genes applied to an arrayed viral high-content screen. Cell 124(6): 1283–1298

    Article  PubMed  CAS  Google Scholar 

  43. Silva JM et al (2005) Second-generation shRNA libraries covering the mouse and human genomes. Nat Genet 37(11): 1281–1288

    PubMed  CAS  Google Scholar 

  44. Schlabach MR et al (2008) Cancer proliferation gene discovery through functional genomics. Science 319(5863):620–624

    Article  PubMed  CAS  Google Scholar 

  45. Silva JM et al (2008) Profiling essential genes in human mammary cells by multiplex RNAi screening. Science 319(5863):617–620

    Article  PubMed  CAS  Google Scholar 

  46. Luo J et al (2009) A genome-wide RNAi screen identifies multiple synthetic lethal interactions with the Ras oncogene. Cell 137(5): 835–848

    Article  PubMed  CAS  Google Scholar 

  47. Scholl C et al (2009) Synthetic lethal interaction between oncogenic KRAS dependency and STK33 suppression in human cancer cells. Cell 137(5):821–834

    Article  PubMed  CAS  Google Scholar 

  48. Bentley DR et al (2008) Accurate whole human genome sequencing using reversible terminator chemistry. Nature 456(7218): 53–59

    Article  PubMed  CAS  Google Scholar 

  49. Mardis ER (2009) New strategies and emerging technologies for massively parallel sequencing: applications in medical research. Genome Med 1(4):40

    Article  PubMed  Google Scholar 

  50. Mardis ER et al (2009) Recurring mutations found by sequencing an acute myeloid leukemia genome. N Engl J Med 361(11): 1058–1066

    Article  PubMed  CAS  Google Scholar 

  51. Miller W et al (2008) Sequencing the nuclear genome of the extinct woolly mammoth. Nature 456(7220):387–390

    Article  PubMed  CAS  Google Scholar 

  52. Green RE et al (2010) A draft sequence of the Neandertal genome. Science 328(5979): 710–722

    Article  PubMed  CAS  Google Scholar 

  53. Nagalakshmi U et al (2008) The transcriptional landscape of the yeast genome defined by RNA sequencing. Science 320(5881): 1344–1349

    Article  PubMed  CAS  Google Scholar 

  54. Robertson G et al (2007) Genome-wide profiles of STAT1 DNA association using ­chromatin immunoprecipitation and massively parallel sequencing. Nat Methods 4(8):651–657

    Article  PubMed  CAS  Google Scholar 

  55. Ozsolak F et al (2009) Direct RNA sequencing. Nature 461(7265):814–818

    Article  PubMed  CAS  Google Scholar 

  56. Ozsolak F et al (2007) High-throughput mapping of the chromatin structure of human promoters. Nat Biotechnol 25(2):244–248

    Article  PubMed  CAS  Google Scholar 

  57. Cloonan N et al (2008) Stem cell transcriptome profiling via massive-scale mRNA sequencing. Nat Methods 5(7):613–619

    Article  PubMed  CAS  Google Scholar 

  58. Hillier LW et al (2008) Whole-genome sequencing and variant discovery in C. elegans. Nat Methods 5(2):183–188

    Article  PubMed  CAS  Google Scholar 

  59. Lefrancois P et al (2009) Efficient yeast ChIP-Seq using multiplex short-read DNA sequencing. BMC Genomics 10(1):37

    Article  PubMed  Google Scholar 

  60. Turner EH et al (2009) Massively parallel exon capture and library-free resequencing across 16 genomes. Nat Methods 6(5):315–316

    Article  PubMed  CAS  Google Scholar 

  61. van Opijnen T, Bodi KL, Camilli A (2009) Tn-seq: high-throughput parallel sequencing for fitness and genetic interaction studies in microorganisms. Nat Methods 6(10): 767–772

    Article  PubMed  Google Scholar 

  62. Durbin RM et al (2010) A map of human genome variation from population-scale sequencing. Nature 467(7319):1061–1073

    Article  CAS  Google Scholar 

  63. Gnirke A et al (2009) Solution hybrid selection with ultra-long oligonucleotides for ­massively parallel targeted sequencing. Nat Biotechnol 27(2):182–189

    Article  PubMed  CAS  Google Scholar 

  64. Smith AM et al (2010) Highly-multiplexed barcode sequencing: an efficient method for parallel analysis of pooled samples. Nucleic Acids Res 38:e142

    Article  PubMed  Google Scholar 

  65. Sambrook J, Russell DW, and Cold Spring Harbor Laboratory (2001) Molecular cloning: a laboratory manual, 3rd edn. Cold Spring Harbor Laboratory, Cold Spring Harbor, NY

    Google Scholar 

  66. Root DE et al (2006) Genome-scale loss-of-function screening with a lentiviral RNAi library. Nat Methods 3(9):715–719

    Article  PubMed  CAS  Google Scholar 

  67. Luo B et al (2008) Highly parallel identification of essential genes in cancer cells. Proc Natl Acad Sci USA 105(51):20380–20385

    Article  PubMed  CAS  Google Scholar 

  68. Cummings N et al (2010) Combining target enrichment with barcode multiplexing for high throughput SNP discovery. BMC Genomics 11:641

    Article  PubMed  Google Scholar 

  69. Daines B et al (2009) High-throughput multiplex sequencing to discover copy number variants in Drosophila. Genetics 182(4):935–941

    Article  PubMed  CAS  Google Scholar 

  70. Han TX et al (2010) Global fitness profiling of fission yeast deletion strains by barcode sequencing. Genome Biol 11(6):R60

    Article  PubMed  Google Scholar 

  71. Hamady M et al (2008) Error-correcting barcoded primers for pyrosequencing hundreds of samples in multiplex. Nat Methods 5(3): 235–237

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgements

A.M.S. is supported by a University of Toronto Open Fellowship. Research in the Giaever and Nislow laboratories is supported by the NHGRI and CIHR.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Corey Nislow .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer Science+Business Media New York

About this protocol

Cite this protocol

Smith, A.M., Durbic, T., Kittanakom, S., Giaever, G., Nislow, C. (2012). Barcode Sequencing for Understanding Drug–Gene Interactions. 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_4

Download citation

  • DOI: https://doi.org/10.1007/978-1-61779-965-5_4

  • Published:

  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-61779-964-8

  • Online ISBN: 978-1-61779-965-5

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics