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GEP Research Projects

The GEP introduces students to research in genomics by engaging them in projects for which careful annotation of genes from recently sequenced species provides important data. Many scientific questions can be addressed using comparative genomics, as evolution enables us to identify conserved features and important changes. With the advent of inexpensive DNA sequencing, many new genomes are being sequenced, but most are annotated only by computer tools. Analysis by humans can make a difference, and high quality gene annotation can provide the data sets needed for comparative analysis.

GEP students construct gene models using evidence tracks on a genome browser and other bioinformatics tools such as NCBI BLAST. The annotation process requires students to evaluate multiple lines of evidence (e.g., sequence similarity, gene predictions, RNA-Seq data, repeats), and resolve apparent differences among these evidence tracks in order to create defendable gene models.

For quality control, each project is completed by at least two students working independently and then reconciled by experienced students. The assembled data are used for meta-analysis, and the faculty and students who contributed data to the project are eligible to be co-authors on the resulting scientific publications.

GEP students are currently engaged in comparative gene annotations for three research projects—F Element, Parasitoid Wasps, and Pathways.

F Element

In this project, GEP students produce coding region and transcription start site annotations for F element genes in D. ananassae, D. bipectinata, D. kikkawai, and D. takahashii, as well as for genes in a euchromatic reference region derived from the Muller D element.

Parasitoid Wasps

In this GEP project, we annotate venom encoding genes from three species of parasitoid wasps that infect Drosophila melanogaster. The gene models generated in this project will allow us to investigate the evolution of venom proteins and to better characterize the proteins for follow up functional studies.


In this GEP project, we use network analysis approaches to better understand the evolution and function of biological pathways. The Pathways Project is currently focused on annotating genes within the insulin signaling pathway across the Drosophila genus.