Poster: Education

Abs # 24: Integration of microarray analysis of gene expression into undergraduate laboratory courses

Presenter:	Ewing, Nicholas N., nnewing@csus.edu
Authors	Ewing, Nicholas N. (A)   Youngblom, James J. (B)   Youngblom, Janey H. (B)   Horton, Robert M. (C)
Affiliations:	(A): California State University, Sacramento (B): California State University, Stanislaus (C): Attotron Biosensor Corporation
Web Site:	http://www.csus.edu/indiv/e/ewingn/index.htm

A major challenge for institutions that focus primarily on undergraduate education is to provide students exposure to leading technologies that require expensive instrumentation. The Genome Consortium for Active Teaching (GCAT; www.bio.davidson.edu/biology/gcat) was developed to overcome this obstacle and enable faculty nationwide (40 currently) to introduce students to microarray technology. Through its centralized facility GCAT provides faculty with microarrays representing a variety of species and provides scanning of these slides at affordable cost. GCAT also makes available teaching arrays with a reduced number of spotted cDNAs. The raw data and analyzed results from all successful exercises conducted by the users are contributed to a central database for pedagogical use and all GCAT members participate in a coordinated assessment program. Since data analysis has been identified as one of the most problematic and challenging aspects of microarray technology, we have developed data analysis exercises designed to facilitate student training. These exercises and the ongoing assessment of them will be made publicly available. The exercises utilize simulated array images that are "reverse engineered" from measured expression data. They provide advantages over actual experimental images in an educational setting as the images can be generated for various array designs, including those used in the GCAT labs, and allow the instructor the option of changing a number of variables, including statistical variation in pixel intensity, feature (spot) placement and shape and background signal. We will present examples of GCAT exercises and our data analysis exercises along with an assessment of the contribution of these to student understanding of functional genomics.