A bioinformatics simulation of a mutant workup from a model genetic organism

1. A bioinformatics simulation of a mutant workup from a model genetic organism Christopher J. Harendza – Montgomery County Community College

2. Importance • Students are losing the appreciation for the power of traditional “forward genetic” approaches and a situation is arising where most everything is mass “stare and compare” informatics and reverse genetics • While the new approaches are very powerful, full scale mutant screens have and should continue to be important

3. Example • Nusslein Volhard, who did a full scale saturation mutagenesis to identify developmentally important genes in Drosophila, is now doing similar work with Zebrafish • “Genetics (mutant analysis) is the window to the unknown” -Christopher Harendza, not a famous person. Ha ha

4. Objective • Introduce students to the power of traditional genetic analysis of mutants and extrapolate this to bioinformatics tools on the web

5. Target Audience: • Students in a sophomore genetics class • Advanced freshman biology majors

6. Overview • Give students model data on a real mutant using, Drosophila, C. elegans, etc. • This data could parallel a wet lab, or series of wet labs, where students learn the techniques, but can then do concordant studies with informatics tools • Flow chart 

7. Flow chart of the project Give students a collection of mutants ↓ Allow groups to choose a mutant of interest ↓ Groups perform a series of crosses to establish linkage -use Virtual Fly to obtain real data ↓ Students design appropriate 3 point cross to map the gene

8. Go over strategies to clone the gene (here is where corners would have to be cut) e.g. positional cloning e.g. P-element cloning by complementation etc. ↓ Instructor provides the DNA sequence data ↓ Students do bioinformatic analysis

9. Informatics phase

10. cDNA and application • The gene of interest would likely be eukaryotic and therefore possess introns • Therefore obtaining the cDNA is vital • Use the cDNA to identify open reading frames and translation tools to infer the amino acid sequence of the protein

11. Blast applications

12. BLAST • Use the sequence to find orthologs in other organisms • Ask questions regarding conservation of function • Work up to human, if applicable, to find cognate genes

13. Clustal Analysis • Once orthologs are obtained, students could establish a database and compare related gene products • Discuss evolution of function

14. Protein analysis • Go to Protein Data Bank to find orthologs or a protein (s) in the same gene family • If someone has solved the structure of this or some related protein, structural analysis could be performed

15. OMIM Application • Human applications would be the ultimate “hook” to draw in the interest • Students could then analyze the orthologous human gene • At this point they would have access to a tremendous wealth of information

16. Discussion of future applications • Reverse genetic approaches in mouse models (knock outs, knock ins) • Biotech applications • Gene therapy

17. Summary • This activity will expose students to an authentic research simulation while preserving the traditional discussion of genetics • Curriculum evolution

18. Wishes • It would’ve been nice if others at the workshop had interest in this project and I could stay for the last session; lack of interest makes me think it may not be such a good idea! • A trial run this term with my newfound tools will allow assessment of its efficacy