•  
  •  
 

EFFECT OF THE NUMBER OF PHYSICAL INTERACTIONS ON DIVERGENT EVOLUTION BETWEEN INSULIN-SIGNALING PATHWAY GENES OF DROSOPHILA MELANOGASTER AND DROSOPHILA BIPECTINATA

Abstract

This study aimed to understand the relationship between divergent evolution and the number of physical interactions of gene products in the insulin-signaling pathway (ISP). The ISP is initiated by the binding of insulin and insulin-like peptides to membrane receptors. Insulin is an anabolic peptide hormone secreted by β cells of the pancreas. Insulin binds to various cells, including those of the liver, skeletal muscle, fat, and brain, to promote glucose uptake, glucose storage into glycogen, and growth. Mutations in the ISP can lead to several health conditions, including: type II diabetes, hypertension, obesity, atherosclerosis, cognitive disorders, and certain types of cancer. We examined the relationship between the number of physical interactions of ISP gene products and their evolutionary divergence between Drosophila melanogaster and Drosophila bipectinata. Specifically, we studied the divergence of Thor (84 interactions), Pi3K21B (97 interactions), and foxo (309 interactions). Previous studies have shown that a higher number of physical interactions constrain divergence, resulting in the genes evolving more slowly. Thus, this study hypothesized that foxo would evolve slowest and display the highest similarity between the two species, and Thor would have the lowest similarity. UCSC Genome Browser and BLAST were used to compare the genomic neighborhood and annotate the three genes in both species. Further, dots plots and protein alignments, obtained from the Genomics Education Partnership Gene Model Checker, were used to compare the protein sequences associated with the genes and examine their percent similarities and identities. The data did not support the initial hypothesis, as Thor had the highest percent identity (93.2%) for protein sequences between the two species, and Pi3K21B had the lowest (73.3%).

Acknowledgements

Genomics Education Partnership, CSU Department of Biology

This document is currently not available here.

Share

COinS