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Advanced Center for Genome Technology ACGT

Advanced Center for Genome Technology ACGT. The UNIVERSITY of OKLAHOMA. T. C. A. G. Orphans & Orthologes. Fares Z. Najar, Sandra W. Clifton, Tyrell Conway, and Bruce A. Roe. Project Goals.

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Advanced Center for Genome Technology ACGT

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  1. Advanced Center for Genome Technology ACGT TheUNIVERSITY ofOKLAHOMA T C A G Orphans & Orthologes Fares Z. Najar, Sandra W. Clifton, Tyrell Conway, and Bruce A. Roe

  2. Project Goals • To define stucture and function of Predicted Hypothetical ORFs (orhtologoes and orphans) in genetically established microbial models. • To generate a database of indexed clones of Predicted Hypothetical ORFs (available for the scientific community). • Train all-level students (high school, undergraduate, and graduate) on bioinformatics and molecular tools.

  3. ACGT profile • Part of the Human Chromosome 22 project. • Home to the Bioinformatics Core Facility (BCF) that houses the E. coli Community’s Gene Expression Database (GenExpDB). • Computational genomics facility for analysis of both DNA and gene expression. • Large scale DNA sequencing using both 454 massively parallel automated DNA sequencing and capillary sequencers (ABI 3730). • Robotic methods for DNA isolation and analysis. • Partnered with several departments at OU and other educational institutions within the state.

  4. Eukaryotic Projects Bacterial Genomes Meta-’omics Human Chimp Streptococcus oligofermentas Mouse Staph. aureus Costarican Forest Tall grass Priare N. gonorrhoeae Rat A. actinomycetemcomitans Desulfogleba alkanexidens Oil Strep. Pyogenes Mouse Gut Medicago Tylorella equigenitalis. Cow Rumen Cotton Soil Xanthomonas vasicola Soy Vellionella atypica Tomato Manduca Leptospira interrogans pomona Leptospira interrogans Grippo Screw worm Spiroplasma kunkelii Tick ACGT profile

  5. Characterization of the “PREDICTOMES” • Rationale: • About 30-40% of predicted proteins are “Hypotheticals Orthologes”. • About 5-20% orphan proteins that have no matches in the database (Hypothetical Orphans). • These putative ORFs represent a fertile ground for basic research and a great opportunity as an educational tool for the next generation scientist. • Goals: • Functional charcerization of the predictome. • Creating a clone library of predicted ORFs. • Train the next generation of scientists at all levels by creating student-specific tailored and balanced regimen of bioinformatics and wet-lab experiments. • Approach: • Define Criteria: • Hypothetical Orthologes in established genetic systems (e-value<=10-5.) • Hypothetical Orphans in established genetic systems. • Clone in E. coli. • Expression & Purification. • Generate mutant strains. • Crystallization. 23% 67% 4% 73% 100% 25% 8% 90% 80% • Meta-transcriptom Hypothetical Orphans Hypothetical Orthologes 70% Functional prediction 60% 50% 40% 30% 20% 10% 0% microbial Genomes

  6. Life Sciences Knowledge Sequence data Coding Non-coding Enzymes Non-enzymatic Hypothetical Orthologes Structural Regulatory Hypothetical Orphans Cell Biology Virology Molecular Biology Anatomy Microbiology Biochemistry Predictions (pathways, regulatory network….etc.) Generating Hypothesis Neuroscience Anthropology Physiology Genetics Botany Zoology Testing Hypothesis -- Generating new knowledge

  7. Generating an Indexed Gene library of “predicted” proteins in Bacteria with Established Genetic System Hypothetical Orphans Hypothetical Orthologoes Functional Hypotheticals BLAST COG KEGG GO PSORT PROSPECT Cloning Expression Hypotheses Purification Mutations Metabolomic Crystal-lization

  8. Preliminary Flowchart for Functional Genomics ORF Bioinformatics pipeline Are there biological predictions? Yes No Is the gene lethal ? • PCR • Clone in E. coli. Yes Store Data • Hypotheses • PCR • Clone in E. coli. No • Express • Purify • Crystallize • Deletion mutations

  9. Dynamics of Systems Biology’s Family Professor Student Postdocs Research scientists Technicians

  10. Dynamics of Systems Biology’s Family Research scientists Professor Professor Technicians Student Postdocs Postdocs Research scientists Technicians

  11. Dynamics of Systems Biology’s Family

  12. A map of Science: How Scientific paradigms relate • Bioinformatics • Molecular Biology • Biochemistry • Microbiology Nature (Dec. 2006, 444: 985)

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