Exploration of Novel Methods to Visualize Genome Evolution

Applications

http://gogarten.uconn.edu/AISRP NASA AISRP 2004-07

Keywords: Self Organizing Maps, Local Linear Embedding, Molecular Phylogeny, Early Evolution of Life, Astrobiology, Comparative Genome Analysis

J. Peter GogartenUniversity of Connecticutgogarten@uconn.edu

Lutz HammelUniversity of Rhode Island

Maria PoptsovaUniversity of Connecticut

Neha NaharUniversity of Rhode Island

Reconstruction of the early history of life on Earth, including the order in which metabolic pathways were assembled.

Project Summary Last Year’s Highlights

Plans for Next Year

• Development of the new algorithm to select gene families http://bioinformatics.org/branchclust/

• Creation of software tool for the

visualization of genome mosaicism from SOM maps.

• Apply the SOM algorithm for embedded quartets.

• Explore Principle Component Analysis (PCA) and Local Linear Embedding (LLE) algorithms.

Apply the analyses to different selection of genomes, with emphasis on those groups that might allow correlation to the fossil and geological records

The developed tools facilitate the analysis of microbial genomes, especially with respect to the early evolution of life and the evolution of metabolic pathways. The work addresses questions central to NASA’s astrobiology program: “Understand how past life on Earth interacted with its changing planetary and Solar System environment” and “Understand the evolutionary mechanisms and environmental limits of life”.