Transcript A bioinformatics simulation of a mutant workup from a

A bioinformatics simulation of
a mutant workup from a model
genetic organism
Christopher J. Harendza – Montgomery County Community College
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
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
Objective

Introduce students to the power of traditional
genetic analysis of mutants and extrapolate
this to bioinformatics tools on the web
Target Audience:

Students in a sophomore genetics class

Advanced freshman biology majors
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 
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
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
Informatics phase
DNA SEQUENCE
Find homologs in fly cDNA
library database
BLAST
Generate restriction enzyme map
(do this backwards)
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
Blast applications
BLAST
Find orthologs
Go to OMIM to find information on
human ortholog
Do Clustal analysis to compare to
known proteins
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
Clustal Analysis

Once orthologs are obtained, students could
establish a database and compare related
gene products

Discuss evolution of function
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
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
Discussion of future applications

Reverse genetic approaches in mouse
models (knock outs, knock ins)

Biotech applications

Gene therapy
Summary

This activity will expose students to an
authentic research simulation while
preserving the traditional discussion of
genetics

Curriculum evolution
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