"Comparative Synteny Analysis of the Microtubule Star Gene in Drosophila obscura and Drosophila persimilis with Reference to Drosophila melanogaster"

Presenter

Hlaing Htoo

Group Members

Jeremy F. Vargas

Campus

Quinsigamond Community College

Sponsor

Jessica Crowley, Department of Biology, Quinsigamond Community College

Schedule

Session 3, 1:30 PM - 2:15 PM [Schedule by Time][Poster Grid for Time/Location]

Location

Poster Board C17, Poster Showcase Room (163), Row 2 (C11-C20) [Poster Location Map]

Abstract

Comparing the gene architecture of closely related species to Drosophila melanogaster is a fundamental approach to gaining insights into the evolution of genes in signaling pathways. Our research focuses on the microtubule star gene, which plays a crucial role in the insulin signaling pathway in Drosophila. We will analyze the gene structure of microtubule star in two closely related species, Drosophila obscura and Drosophila persimilis, in comparison to Drosophila melanogaster, to identify evolutionary differences. By annotating genetic features such as transcription start sites, intron/exon boundaries, protein coding regions, and 5’ and 3’ untranslated regions, using a variety of bioinformatic tools including the UCSC Genome Browser, NCBI BLAST, and custom tools developed by the Genomics Education Partnership (GEP), we aim to deepen our understanding of pathway gene structures and evolutionary relationships across species. Based on their placements on the phylogenetic tree, we anticipate that the microtubule star gene in Drosophila obscura will exhibit greater conservation with Drosophila melanogaster compared to Drosophila persimilis. This project is a significant part of the GEP Pathways Project, a collaborative initiative supported by the NSF/NIH involving over two hundred institutions in the U.S., dedicated to advancing undergraduate research in genomics and bioinformatics, which is crucial for furthering our understanding of complex biological processes.

Keywords

gene structure, comparative genomics, bioinformative analysis, signaling pathway evolution

Research Area

Genetics

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