Involving Undergraduates in the Annotation and Analysis of Global Gene Expression Studies: Creation of a Maize Shoot Apical Meristem Expression Database

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ABSTRACT

Through a multi-university and interdisciplinary project we have involved undergraduate biology and computer science research students in the functional annotation of maize genes and the analysis of their microarray expression patterns. We have created a database to house the results of our functional annotation of >4400 genes identified as being differentially regulated in the maize shoot apical meristem (SAM). This database is located at http://sam.truman.edu and is now available for public use. The undergraduate students involved in constructing this unique SAM database received hands-on training in an intellectually challenging environment, which has prepared them for graduate and professional careers in biological sciences. We describe our experiences with this project as a model for effective research-based teaching of undergraduate biology and computer science students, as well as for a rich professional development experience for faculty at predominantly undergraduate institutions.

ONE essential component of the success of genomics research has been the development of the field of bioinformatics, which can be defined as the use of information technology for the collection, storage, retrieval, and analysis of genomic data. Collaborations of biologists, computer scientists, and statisticians have become more robust in recent years; current graduate students in genetics commonly receive at least some formal training in computational biology. In addition, bioinformatics graduate degrees are now being offered by several institutions (ZATZ 2002). However, it remains a challenge to involve undergraduate biology students, particularly freshmen and sophomores, in genomics and bioinformatics research. Moreover, establishing undergraduate genomics research can be particularly difficult at undergraduate institutions where collaborations between biologists and computer scientists have been slower to develop, or where there historically has not been a strong culture of research.

Many undergraduate biology programs introduce cell biology and genetics during freshman introductory courses and require additional courses in cell biology and genetics later in the curriculum (LEDBETTER and CAMPBELL 2005). Thus, the beginning biology student's view of biology is largely a cellular and molecular genetics one. Too often students are taken to the brink of understanding the networks and circuitry involved in cell function, but are unable to utilize and develop this knowledge in a research environment. Furthermore, while undergraduates are Internet savvy, few realize that most bioinformatics tools are readily accessible and user friendly.Thus, when undergraduates do engage in genetics research, they are likely to seek out "wet-lab" experiences rather than bioinformatics or wet-lab/bioinformatics combinations (DYER and LEBLANC 2002).

With appropriate training and nurturing, properly prepared undergraduate students can make meaningful contributions to the functional annotation and analysis of microarray hybridization data. In addition, students develop a true sense of biophilia while performing this type of research. The ever-increasing publicly available genomic sequence and microarray data provide an unprecedented opportunity for undergraduate students and their mentors to contribute to advances in genomics. Furthermore, bioinformatics research is relatively inexpensive to perform and can be integrated into existing laboratory exercises.

A vital component of developing an undergraduate bioinformatics research project is to establish a collaboration between biology and computer science faculty. Computer scientists are essential to the design, execution, and maintenance of a bioinformatic database. Also, collaboration between computer scientists and biologists will foster the creation of interdisciplinary courses that are desirable for students considering postgraduate study in bioinformatics (BECK et al. …