Statistical Analysis of Fitness Data Determined by TAG Hybridization on Microarrays

  • Brian D. Peyser
  • Rafael Irizarry
  • Forrest A. Spencer
Part of the Methods in Molecular Biology™ book series (MIMB, volume 416)

Abstract

TAG, or bar-code, microarrays allow measurement of the oligonucleotide sequences (TAGs) that mark each strain of deletion mutants in the Saccharomyces cerevisiae yeast knockout (YKO) collection. Comparison of genomic DNA from pooled YKO samples allows estimation of relative abundance of TAGs marking each deletion strain. Features of TAG hybridizations create unique challenges for analysis. Analysis is complicated by the presence of two TAGs in most YKO strains and the hybridization behavior of TAGs that may differ in sequence from array probes. The oligonucleotide size of labeled TAGs also results in difficulty with contaminating sequences that cause reduced specificity. We present methods for analysis that approach these unique features of TAG hybridizations.

Key Words

bar code deletion knockout microarray Saccharomyces cerevisiae TAG yeast 

References

  1. 1.
    Shoemaker, D. D., Lashkari, D. A., Morris, D., Mittmann, M., and Davis, R. W. (1996) Quantitative phenotypic analysis of yeast deletion mutants using a highly parallel molecular bar-coding strategy. Nat. Genet. 14, 450–456.CrossRefPubMedGoogle Scholar
  2. 2.
    Giaever, G., Chu, A. M., Ni, L., Connelly, C., Riles, L., Veronneau, S., et al. (2002) Functional profiling of the Saccharomyces cerevisiae genome. Nature 418, 387–391.CrossRefPubMedGoogle Scholar
  3. 3.
    Pan, X., Yuan, D. S., Xiang, D., Wang, X., Sookhai-Mahadeo, S., Bader, J. S., et al. (2004) A robust toolkit for functional profiling of the yeast genome. Mol. Cell 16, 487–496.CrossRefPubMedGoogle Scholar
  4. 4.
    Winzeler, E. A., Castillo-Davis, C. I., Oshiro, G., Liang, D., Richards, D. R., Zhou, Y., and Hartl, D. L. (2003) Genetic diversity in yeast assessed with whole-genome oligonucleotide arrays. Genetics 163, 79–89.PubMedGoogle Scholar
  5. 5.
    Warren, C. D., Eckley, D. M., Lee, M. S., Hanna, J. S., Hughes, A., Peyser, B., et al. (2004) S-phase checkpoint genes safeguard high-fidelity sister chromatid cohesion. Mol. Biol. Cell 15, 1724–1735.CrossRefPubMedGoogle Scholar
  6. 6.
    Ooi, S. L., Pan, X., Peyser, B. D., Ye, P., Meluh, P. B., Yuan, D. S., et al. (2006) Global synthetic-lethality analysis and yeast functional profiling. Trends Genet. 22, 56–63.CrossRefPubMedGoogle Scholar
  7. 7.
    Winzeler, E. A., Lee, B., McCusker, J. H., and Davis, R. W. (1999) Whole genome genetic-typing in yeast using high-density oligonucleotide arrays. Parasitology 118(Suppl), S73–80.CrossRefPubMedGoogle Scholar
  8. 8.
    Giaever, G., Shoemaker, D. D., Jones, T. W., Liang, H., Winzeler, E. A., Astromoff, A., and Davis, R. W. (1999) Genomic profiling of drug sensitivities via induced haploinsufficiency. Nat. Genet. 21, 278–283.CrossRefPubMedGoogle Scholar
  9. 9.
    Giaever, G. (2003) A chemical genomics approach to understanding drug action. Trends Pharmacol. Sci. 24, 444–446.CrossRefPubMedGoogle Scholar
  10. 10.
    Giaever, G., Flaherty, P., Kumm, J., Proctor, M., Nislow, C., Jaramillo, D. F., et al. (2004) Chemogenomic profiling: identifying the functional interactions of small molecules in yeast. Proc. Natl. Acad. Sci. U.S.A. 101, 793–798.CrossRefPubMedGoogle Scholar
  11. 11.
    Lum, P. Y., Armour, C. D., Stepaniants, S. B., Cavet, G., Wolf, M. K., Butler, J. S., et al. (2004) Discovering modes of action for therapeutic compounds using a genome-wide screen of yeast heterozygotes. Cell 116, 121–137.CrossRefPubMedGoogle Scholar
  12. 12.
    Dunn, C. D., Lee, M. S., Spencer, F. A., and Jensen, R. E. (2006) A genomewide screen for petite-negative yeast strains yields a new subunit of the i-AAA protease complex. Mol. Biol. Cell 17, 213–226.CrossRefPubMedGoogle Scholar
  13. 13.
    Arevalo-Rodriguez, M., Pan, X., Boeke, J. D., and Heitman, J. (2004) FKBP12 controls aspartate pathway flux in Saccharomyces cerevisiae to prevent toxic intermediate accumulation. Eukaryot. Cell 3, 1287–1296.CrossRefPubMedGoogle Scholar
  14. 14.
    Deutschbauer, A. M., Jaramillo, D. F., Proctor, M., Kumm, J., Hillenmeyer, M. E., Davis, R. W., et al. (2005) Mechanisms of haploinsufficiency revealed by genome-wide profiling in yeast. Genetics 169, 1915–1925.CrossRefPubMedGoogle Scholar
  15. 15.
    Ooi, S. L., Shoemaker, D. D., and Boeke, J. D. (2003) DNA helicase interaction network defined using synthetic lethality analyzed by microarray. Nat. Genet. 35, 277–286.CrossRefPubMedGoogle Scholar
  16. 16.
    Lee, M. S., and Spencer, F. A. (2004) Bipolar orientation of chromosomes in Saccharomyces cerevisiae is monitored by Mad1 and Mad2, but not by Mad3. Proc. Natl Acad. Sci. U.S.A. 101, 10655–10660.CrossRefPubMedGoogle Scholar
  17. 17.
    Pan, X., Ye, P., Yuan, D. S., Wang, X., Bader, J. S., and Boeke, J. D. (2006) A DNA integrity network in the yeast Saccharomyces cerevisiae. Cell 124, 1069–1081.CrossRefPubMedGoogle Scholar
  18. 18.
    Eason, R. G., Pourmand, N., Tongprasit, W., Herman, Z. S., Anthony, K., Jejelowo, O., et al. (2004) Characterization of synthetic DNA bar codes in Saccharomyces cerevisiae gene-deletion strains. Proc. Natl. Acad. Sci. U.S.A. 101, 11046–11051.CrossRefPubMedGoogle Scholar
  19. 19.
    Yuan, D. S., Pan, X., Ooi, S. L., Peyser, B. D., Spencer, F. A., Irizarry, R. A., and Boeke, J. D. (2005) Improved microarray methods for profiling the Yeast Knockout strain collection. Nucleic Acids Res. 33, e103.CrossRefPubMedGoogle Scholar
  20. 20.
    Huber, W., von Heydebreck, A., Sueltmann, H., Poustka, A., and Vingron, M. (2003) Parameter estimation for the calibration and variance stabilization of microarray data. Stat. Appl. Genet. Mol. Biol. 2, article 3.Google Scholar
  21. 21.
    Durbin, B. P., Hardin, J. S., Hawkins, D. M., and Rocke, D. M. (2002) A variance-stabilizing transformation for gene-expression microarray data. Bioinformatics 18(Suppl 1), S105–110.PubMedGoogle Scholar
  22. 22.
    Durbin, B. P., and Rocke, D. M. (2004) Variance-stabilizing transformations for two-color microarrays. Bioinformatics 20, 660–667.CrossRefPubMedGoogle Scholar
  23. 23.
    Dudoit, S., Yang, Y. H., Callow, M. J., and Speed, T. P. (2002) Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments. Statistica Sinica 12, 111–139.Google Scholar
  24. 24.
    Wu, Z., Irizarry, R. A., Gentleman, R., Martinez-Murillo, F., and Spencer, F. (2004) A model-based background adjustment for oligonucleotide expression Arrays. J. Am. Statist. Assoc. 99, 909–917.CrossRefGoogle Scholar
  25. 25.
    Smyth, G. K. (2005) Limma: linear models for microarray data. In: Gentleman, R., Carey, V., Dudoit, S., Irizarry, R., and Huber, W., eds. Bioinformatics and Computational Biology Solutions using R and Bioconductor. New York: Springer, pp.390–420.Google Scholar
  26. 26.
    Huber, W., von Heydebreck, A., Sultmann, H., Poustka, A., and Vingron, M. (2002) Variance stablization applied to microarray data calibration and to quantification of differential expression. Bioinformatics 18(Suppl 1), S96–104.PubMedGoogle Scholar
  27. 27.
    Irizarry, R. A., Hobbs, B., Collin, F., Beazer-Barclay, Y. D., Antonellis, K. J., Scherf, U., and Speed, T. P. (2003) Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 4, 249–264.CrossRefPubMedGoogle Scholar
  28. 28.
    Yuan, D. S., and Irizarry, R. A. (2006) High-resolution spatial normalization for micro-arrays containing embedded technical replicates. Bioinformatics 22, 3054–3060.CrossRefPubMedGoogle Scholar
  29. 29.
    Colantuoni, C., Henry, G., Zeger, S., and Pevsner, J. (2002) SNOMAD (Standardization and Normalization of MicroArray Data): WEB-accessible gene expression data analysis. Bioinformatics 18, 1540–1541.CrossRefPubMedGoogle Scholar
  30. 30.
    Yang, Y. H., Dudoit, S., Luu, P., Lin, D. M., Peng, V., Ngai, J., and Speed, T. P. (2002) Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. Nucleic Acids Res. 30, e15.CrossRefPubMedGoogle Scholar
  31. 31.
    Cleveland, W. S. (1979) Robust locally weighted regression and smoothing scatterplots. J. Am. Statist. Assoc. 74, 829–836.CrossRefGoogle Scholar
  32. 32.
    Peyser, B. D., Irizarry, R. A., Tiffany, C. W., Chen, O., Yuan, D. S., Boeke, J. D., and Spencer, F. A. (2005) Improved statistical analysis of budding yeast TAG microarrays revealed by defined spike-in pools. Nucleic Acids Res. 33, e140.CrossRefPubMedGoogle Scholar
  33. 33.
    Bolstad, B. M., Irizarry, R. A., Astrand, M., and Speed, T. P. (2003) A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 19, 185–193.CrossRefPubMedGoogle Scholar

Copyright information

© Humana Press Inc., a part of Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Brian D. Peyser
    • 1
  • Rafael Irizarry
    • 2
  • Forrest A. Spencer
    • 3
  1. 1.United States Army Medical Research Institute of Infectious Diseases, Fort DetrickFrederick
  2. 2.Department of Biostatistics, Bloomberg School of Public HealthJohns Hopkins UniversityBaltimore
  3. 3.Department of Molecular Biology and Genetics, McKusick-Nathans Institute of Genetic MedicineThe Johns Hopkins University School of MedicineBaltimore

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