Trends and Prospects in Functional Genomics and Bioinformatics

1. Trends and Prospects in Functional Genomics and Bioinformatics Helsinki, October 2000

2. The Genome Sequencing efforts (28 major centers world-wide) Sequences of genomes for over 600 organism can be found in current public databases (Entrez-Genomes) This includes over 100 completely sequenced genomes and those whose sequencing is still in progress. Viroids 20 Total number of species: 908 Plasmmids 34 Viruses 557 Eukaryotes 172 Bacteria 112 Archaea 13 All domains of life are represented ! Human genome nearly fully sequenced!

3. Challenges of the post-genomic era DATABASES Curation & management of the fast growing body of primary data Raw data -Gene assignment -Infer function by homology -Comparative genomics -Experimental analyses: * Transcriptome * Proteome Deciphering sequence information in terms of biological function Gaining understanding of cellular processes Analysing & simulating cellular processes

4. Challenges of the post-genomic era Making new & better drugs, diagnostics & cures for diseases Discovering: new drug targets, genes involved in diseases Huge incentives for Biotech & Pharma Industry

5. Till now: analysis of individual genes & proteins a b c d e Genes A B C D E Proteins Comparative analyses Pfam... SCOP CATH Sequence systematics 3D structure Systematics

6. Now: see the ‘big picture’: Map the physical and Functional Interactions In the Cell Living cell Genome t.f Protein 2 t.s. Protein 1 Biochemical pathway Physical interactions Functional interactions

7. Cellular systems: Huge networks of thousands of molecules interconnected via thousands of interactions Only a small fraction is chartered: known metabolic, regulatory & signal transduction pathways..

8. New and Old Approaches, the Jargon: Determine & annotate the sequence of whole genomes, Genomics Comparative genomics Use/compare information on genes, Proteins, Processes, from across genomes Functional genomics Assign gene function on genome scale... Determine 3D structure of all proteins in a genome or a process Structural proteomics (genomics) Genome scale analysis of protein expression patterns, protein-protein interactions... Proteomics

9. S.cerevisiae (yeast) genome All proteins: 6362 Known function: 3303 Strong similarity to known proteins:237 Similarity or weak similarity to proteins of known function:823 Similarity to unknown proteins:766 No similarity:785 Questionable ORF’s:448 31% 1/3 of the genes/proteins in yeast have unknown function

10. functional genomics expression of RNA biological activities and function genome sequence expression of proteins Protein 3D structures Bioinformatics

11. Functional Genomics : assigning gene function on genome scale Annotated sequences from other genomes By inference: New sequence Sequences function Is the new sequence similar to any known sequence? no yes unknown function Databases

12. DNA Microarray experiment Cell culture, tissue, ... Sample 2 Samples 1 yellowish not specific reddish sample 1 -specific greenish sample 2 - specific RNA RNA RNA extraction Synthesis of fluorescent cDNA cDNA cDNA • Brightness indicates quantity • Color indicates specificity DNA chip ORF’s amplified & printed on chip

13. Differential Protein Expression Patterns using 2D PAGE Proteins expressed under condition2 but not condition 1 PROTEOMICS mass spec aa sequence compare to genome sequence Condition 1, absence of compound x Condition 2, presence of compound x identified protein

14. Structural proteomics: determining protein 3D structure on genome scale HIV process

15. Structural proteomics: extending structure information to sequences Library of known folds New sequence Assign known fold from library Function Build detailed Atomic model

16. Sequence analysis: gene discovery seq.alignment profiles, HMM’s pattern analysis pattern discovery systematics & phylogeny .. Seq. Databases EMBL-data Library GenBank Swiss-prot ….. Bioinformatics Structure analysis structure comparison structure prediction homology modelling …. Analysis &display of data from experiments: DNA microarrays 2D PAGE Databases of: Gene expression patterns 2D PAGE gels Specialised databases -Genomes -Processes Kegg EcoCyc -Diseases -SNP’s Communication and integration of DB’s Annotation tools Analysis & simulation of cellular processes ….

17. Cell Biology …. Medicine …. Molecular Biology Genetic & protein engineering DNA micro arrays 2-hybrid; knockout Cellular function Biochemistry Math DNA sequencing Na/pep Synthesis, Mol. Function prot purification Statistics Graph theory Numerical analysis Differential geometry Bioinformatics Physics/ Biophysics Computer science & information technology Machine learning Logical programming Computer vision Comp. geometry X-ray diffraction NMR Light spectroscopy Microscopy DBMS GUI’s, WEB Networking

18. Trends of the “Post Genomic” era - research is becoming increasingly multi-disciplinary - increasing role of sophisticated technology, at all levels; cost is high, but will go down - research involves a large engineering component-> high throughout analyses - multi-team projects: national, world-wide.. - vaste opportunity for industrial applications, Biotech, agricultural, health, IT, etc..

19. Trends of the “Post Genomic” era -Investigation of cellular processes and their control -new tools for investigating how molecular activity is related to biological function -enormous thrust towards identifying genetic determinants of traits and pathologies -far reaching impact on all aspects of society!!

20. Bioinformatics: Different disciplines -> Tools & Methods for: *managing & analysing biological information *formulating hypotheses *scientific discovery

21. The various definitions of Bioinformatics “Bioinformatics is an integration of mathematical, statistical and computer methods to analyse biological, biochemical and biophysical data”(Georgia Inst of Tech., USA) “Bioinformatics is the study of biological information as is passes from its storage site in the genome to the various gene products in the cell. …it involves the creating and development of advanced information and computational technologies for problems in molecular biology…”(Stanford University, USA) “Bioinformatics specifically refers to the search and use of patterns and structure in biological data and the development of new methods for database access..” Computational biology is more frequently used to refer to physical and mathematical simulation of biological processes(Virginia Inst Tech., USA)