Advanced Center for Genome Technology ACGT

1. Advanced Center for Genome Technology ACGT T C A G Fares Z. Najar & Sandra W. Clifton

2. 1000000 900 300000 800bp 100000 800 100000 30000 10000 700 10000 600bp 600bp 600 500bp 1000 500 1000 500 Mbase/run (Log scale) 100 Read length (bp) 100 350bp 30 400 10 250bp 300 200bp 1 1 200 100bp 0.2 75bp 0.1 35bp 26bp 100 0.04 0.01 0 FLX FLX-Ti FLX+ SoliD GS20 ABI370 Helicose ABI3700 ABI3730 Illumina polonator Sequencer platform A Brief History of Long Read Automated DNA Sequencing Instruments at OU Other Next- Generation Platforms 2 0 0 5 - Present 1994-2004

3. Advanced Center for Genome Technology ACGT • Human Chromosome 22 • Home to the Bioinformatics Core Facility • Large scale DNA sequencing • Partnered with several departments at OU and other educational institutions within the state • Maintain and inplements both 454 massively parallel automated DNA sequencing and capillary sequencers • Robotic methods for DNA isolation and analysis • Computational genomics facility for analysis of both DNA and gene expression

5. Characterizatino of Predicted ORFs. • Goals • The immediate goal of this project is to train the next generation of scientists at all levels by creating a student-specific tailored and balanced regiment of bioinformatics and wet-lab experiments. • Rationale: • from all sequencing data available that an average of 30-40% of the predicted proteins are hypotheticals that match other hypothetical proteins with about 15-20% orphan proteins that have no matches in the database. • But it also represents a very fertile ground for basic research and a great opportunity as an educational tool for the next generation scientist. • Approach: • To focus the effort, we will be looking at genes that have orthologes in prokaryotes with established genetic systems . • interrogate the genes individually using standard molecular biology techniques such as generating specific deletions and observation of resulting phenotypes and/or change in the transcription pattern • Putative orphan proteins will be cloned, validated, and made available for the scientific community.

6. Life Sciences Knowledge Sequence data Proteins Non-protein Enzymes Non-enzymatic Unknowns Structural Regulatory 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 Orphan Genes Unknowns/Hypotheticals Predicted functional ORF BLASTP/y COG No Results Developing Testable Hypothesis KEGG GO PSORT PROSPECT • Clonning • Expression • Deletion • Clonning • Expression Protein isolation Protein Crystallization

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 Generate Hypothesis Store Data Are there orthologesin genetically-established bacterium? No No Yes • Express • Purify • Crystallize Other tests? Generate Deletion mutation

9. Dynamics of system biology’s family Student / Professor Generating Hypothesis Student / Professor / Postdocs and research scientists Experimental approach Student / Professor(s) / Postdocs and research scientists / Technicians

10. Dynamics of system biology’s family

11. Nature (vol. 444, p. 985)