6 Subcellular Localization, Provides a simple goal for genome-scale functional prediction Determine how many of the ~6000 yeast proteins go into each compartment
7 Subcellular Localization, a standardized aspect of function CytoplasmNucleusMembraneERExtra- cellular [secreted]GolgiMitochondria
8 "Traditionally" subcellular localization is "predicted" by sequence patterns CytoplasmNLSNucleusMembraneTM-helixERHDELExtra- cellular [secreted]GolgiImport Sig.MitochondriaSig. Seq.
9 [Expression Level in Copies/Cell] Subcellular localization is associated with the level of gene expression[Expression Level in Copies/Cell]CytoplasmNucleusMembraneERExtra- cellular [secreted]GolgiMitochondria
10 [Expression Level in Copies/Cell] Combine Expression Information & Sequence Patterns to Predict Localization[Expression Level in Copies/Cell]CytoplasmNLSNucleusMembraneTM-helixERHDELExtra- cellular [secreted]GolgiImport Sig.MitochondriaSig. Seq.
11 The central dogma of molecular biology??? Major Objective: Discover a comprehensive theory of life’s organization at the molecular levelThe major actors of molecular biology: the nucleic acids, DeoxyriboNucleic Acid (DNA) and RiboNucleic Acids (RNA)The central dogma of molecular biology???EpigeneticsRNA editingPost-translational modificationTranslational regulationProteins are very complicated molecules with 20 different amino acids.
13 Higher Level Microarray data analysis Clustering and pattern detectionData mining and visualizationLinkage between gene expression data and gene sequence/function/metabolic pathways databasesDiscovery of common sequences in co-regulated genesMeta-studies using data from multiple experiments
14 Scatter plot of all genes in a simple comparison of two control (A) and two treatments (B: high vs. low glucose) showing changes in expression greater than 2.2 and 3 fold.
15 Types of Clustering Herarchical Self Organizing Maps (SOM) Link similar genes, build up to a tree of allSelf Organizing Maps (SOM)Split all genes into similar sub-groupsFinds its own groups (machine learning)
18 Public DatabasesGene Expression data is an essential aspect of annotating the genomePublication and data exchange for microarray experimentsData mining/Meta-studiesCommon data format - XMLMIAME (Minimal Information About a Microarray Experiment)
19 The 3 Gene Ontologies Molecular Function = elemental activity/task the tasks performed by individual gene products; examples are carbohydrate binding and ATPase activityBiological Process = biological goal or objectivebroad biological goals, such as mitosis or purine metabolism, that are accomplished by ordered assemblies of molecular functionsCellular Component = location or complexsubcellular structures, locations, and macromolecular complexes; examples include nucleus, telomere, and RNA polymerase II holoenzyme
20 One Last Note Microarrays are “cutting edge” technology You now have experience doing a technique that most Ph.D.s have never doneLooks great on a resume…