Comparative Analysis of Aerobic and Anaerobic Prokaryotes to Identify Correlation between Oxygen Requirement and Gene-Gene Functional Association Patterns

Yaming Lin (
Hongwei Wu (

School of Electrical and Computer Engineering, Georgia Institute of Technology 210 Technology Circle Savannah, Georgia, 31407, USA


Activities of prokaryotes are pivotal in shaping the environment, and are also greatly influenced by the environment. With the substantial progress in genome and metagenome sequencing and the about-to-be-standardized ecological context information, environment-centric comparative genomics will complement species-centric comparative genomics, illuminating how environments have shaped and maintained prokaryotic diversities. In this paper we report our preliminary studies on the association analysis of a particular duo of genomic and ecological traits of prokaryotes - gene-gene functional association patterns vs. oxygen requirement conditions. We first establish a stochastic model to describe gene arrangements on chromosomes, based on which the functional association between genes are quantified. The gene-gene functional association measures are validated using biological process ontology and KEGG pathway annotations. Student's t-tests are then performed on the aerobic and anaerobic organisms to identify those gene pairs that exhibit different functional association patterns in the two different oxygen requirement conditions. As it is difficult to design and conduct biological experiments to validate those genome-environment association relationships that have resulted from long-term accumulative genome-environment interactions, we finally conduct computational validations to determine whether the oxygen requirement condition of an organism is predictable based on gene-gene functional association patterns. The reported study demonstrates the existence and significance of the association relationships between certain gene-gene functional association patterns and oxygen requirement conditions of prokaryotes, as well as the effectiveness of the adopted methodology for such association analysis.

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Japanese Society for Bioinformatics