A latent variable model for chemogenomic profiling

MOTIVATION In haploinsufficiency profiling data, pleiotropic genes are often misclassified by clustering algorithms that impose the constraint that a gene or experiment belong to only one cluster. We have developed a general probabilistic model that clusters genes and experiments without requiring that a given gene or drug only appear in one cluster. The model also incorporates the functional annotation of known genes to guide the clustering procedure. RESULTS We applied our model to the clustering of 79 chemogenomic experiments in yeast. Known pleiotropic genes PDR5 and MAL11 are more accurately represented by the model than by a clustering procedure that requires genes to belong to a single cluster. Drugs such as miconazole and fenpropimorph that have different targets but similar off-target genes are clustered more accurately by the model-based framework. We show that this model is useful for summarizing the relationship among treatments and genes affected by those treatments in a compendium of microarray profiles. AVAILABILITY Supplementary information and computer code at http://genomics.lbl.gov/llda.

[1]  Ronald W. Davis,et al.  Functional profiling of the Saccharomyces cerevisiae genome , 2002, Nature.

[2]  K L Gould,et al.  The Arp2/3 complex: a multifunctional actin organizer. , 1999, Current opinion in cell biology.

[3]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[4]  T. Furuchi,et al.  Two nuclear proteins, Cin5 and Ydr259c, confer resistance to cisplatin in Saccharomyces cerevisiae. , 2001, Molecular pharmacology.

[5]  N. Morin,et al.  The Saccharomyces cerevisiae FKS1 (ETG1) gene encodes an integral membrane protein which is a subunit of 1,3-beta-D-glucan synthase. , 1994, Proceedings of the National Academy of Sciences of the United States of America.

[6]  Elizabeth A. Winzeler,et al.  Genomic profiling of drug sensitivities via induced haploinsufficiency , 1999, Nature Genetics.

[7]  Leif E. Peterson.  Partitioning large-sample microarray-based gene expression profiles using principal components analysis , 2003, Comput. Methods Programs Biomed..

[8]  M. Goebl,et al.  The identification of a gene family in the Saccharomyces cerevisiae ergosterol biosynthesis pathway. , 1994, Gene.

[9]  Alnawaz Rehemtulla,et al.  Regional delivery and selective expression of a high-activity yeast cytosine deaminase in an intrahepatic colon cancer model. , 2003, Cancer research.

[10]  Jasper Rine,et al.  Upc2p and Ecm22p, Dual Regulators of Sterol Biosynthesis in Saccharomyces cerevisiae , 2001, Molecular and Cellular Biology.

[11]  P. Johnston,et al.  5-Fluorouracil: mechanisms of action and clinical strategies , 2003, Nature Reviews Cancer.

[12]  D. Botstein,et al.  Singular value decomposition for genome-wide expression data processing and modeling. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[13]  P. Calabresi,et al.  Chemotherapy of neoplastic diseases. , 1962, Annual review of medicine.

[14]  Daphne Koller,et al.  Decomposing Gene Expression into Cellular Processes , 2002, Pacific Symposium on Biocomputing.

[15]  S. Rafii,et al.  Splitting vessels: Keeping lymph apart from blood , 2003, Nature Medicine.

[16]  Roded Sharan,et al.  Discovering statistically significant biclusters in gene expression data , 2002, ISMB.

[17]  J. C. Hinshaw,et al.  Discovering Modes of Action for Therapeutic Compounds Using a Genome-Wide Screen of Yeast Heterozygotes , 2004, Cell.

[18]  M. Basson,et al.  Saccharomyces cerevisiae contains two functional genes encoding 3-hydroxy-3-methylglutaryl-coenzyme A reductase. , 1986, Proceedings of the National Academy of Sciences of the United States of America.

[19]  Yudong D. He,et al.  Functional Discovery via a Compendium of Expression Profiles , 2000, Cell.

[20]  E J Walaszek,et al.  The Pharmacological Basis of Therapeutics (ed. 3) , 1966 .

[21]  F. Karst,et al.  In vivo effects of fenpropimorph on the yeast Saccharomyces cerevisiae and determination of the molecular basis of the antifungal property , 1990, Antimicrobial Agents and Chemotherapy.

[22]  A. Mitchell,et al.  Identification of the FKS1 gene of Candida albicans as the essential target of 1,3-beta-D-glucan synthase inhibitors , 1997, Antimicrobial agents and chemotherapy.

[23]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[24]  M. Gerstein,et al.  A Bayesian Networks Approach for Predicting Protein-Protein Interactions from Genomic Data , 2003, Science.

[25]  Sven Bergmann,et al.  Iterative signature algorithm for the analysis of large-scale gene expression data. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[26]  A. Goffeau,et al.  PDR16 and PDR17, Two Homologous Genes ofSaccharomyces cerevisiae, Affect Lipid Biosynthesis and Resistance to Multiple Drugs* , 1999, The Journal of Biological Chemistry.

[27]  Michael I. Jordan.  Learning in Graphical Models , 1999, NATO ASI Series.

[28]  Michael I. Jordan.  Graphical Models , 1998 .

[29]  L. Goodman,et al.  The Pharmacological Basis of Therapeutics , 1941 .

[30]  Bin Yu,et al.  Model Selection and the Principle of Minimum Description Length , 2001 .

[31]  Thomas Hofmann,et al.  Statistical Models for Co-occurrence Data , 1998 .

[32]  Yoshikazu Ohya,et al.  Movement of yeast 1,3‐β‐glucan synthase is essential for uniform cell wall synthesis , 2002, Genes to cells : devoted to molecular & cellular mechanisms.

[33]  P. A. Rea,et al.  Transport of methotrexate (MTX) and folates by multidrug resistance protein (MRP) 3 and MRP1: effect of polyglutamylation on MTX transport. , 2001, Cancer research.

[34]  D. Pe’er,et al.  Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data , 2003, Nature Genetics.

[35]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[36]  D. Botstein,et al.  A gene expression database for the molecular pharmacology of cancer , 2000, Nature Genetics.

[37]  Michael I. Jordan,et al.  Chemogenomic profiling: identifying the functional interactions of small molecules in yeast. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[38]  L. Lazzeroni.  Plaid models for gene expression data , 2000 .

[39]  B. Katzung.  Basic and Clinical Pharmacology , 1982 .

[40]  John Finn,et al.  The identification of quality antibacterial drug discovery targets: a case study with aminoacyl-tRNA synthetases , 2000 .

[41]  Matthew R. Redinbo,et al.  New potential targets for antifungal development , 2000 .

[42]  Brian C. Baldwin,et al.  Inhibition of ergosterol biosynthesis in Saccharomyces cerevisiae and Ustilago maydis by tridemorph, fenpropimorph and fenpropidin , 1984 .

[43]  George M. Church,et al.  Biclustering of Expression Data , 2000, ISMB.

[44]  Michael I. Jordan,et al.  Variational Probabilistic Inference and the QMR-DT Network , 2011, J. Artif. Intell. Res..

[45]  L. Pachter,et al.  SLAM: cross-species gene finding and alignment with a generalized pair hidden Markov model. , 2003, Genome research.

[46]  Dmitrij Frishman,et al.  MIPS: a database for genomes and protein sequences , 2000, Nucleic Acids Res..

[47]  D. Botstein,et al.  Cluster analysis and display of genome-wide expression patterns. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[48]  Raoul Herbrecht,et al.  Caspofungin: the first representative of a new antifungal class. , 2003, The Journal of antimicrobial chemotherapy.

[49]  D. Karnofsky,et al.  Chemotherapy of neoplastic diseases. , 1950, The Medical clinics of North America.

[50]  L Bueno,et al.  Rectal antinociceptive properties of alverine citrate are linked to antagonism at the 5‐HT1A receptor subtype , 2001, The Journal of pharmacy and pharmacology.