Sign up for email alerts to receive notifications of new articles published in Evolutionary Bioinformatics
Evolutionary changes in gene expression account for most phenotypic differences between species. Advances in microarray technology have made the systematic study of gene expression evolution possible. In this study, gene expression patterns were compared between human and mouse genomes using two published methods. Specifically, we studied how gene expression evolution was related to GO terms and tried to decode the relationship between promoter evolution and gene expression evolution. The results showed that (1) the significant enrichment of biological processes in orthologs of expression conservation reveals functional significance of gene expression conservation. The more conserved gene expression in some biological processes than is expected in a purely neutral model reveals negative selection on gene expression. However, fast evolving genes mainly support the neutrality of gene expression evolution, and (2) gene expression conservation is positively but only slightly correlated with promoter conservation based on a motif-count score of the promoter alignment. Our results suggest a neutral model with negative selection for gene expression evolution between humans and mice, and promoter evolution could have some effects on gene expression evolution.
PDF (581.43 KB PDF FORMAT)
RIS citation (ENDNOTE, REFERENCE MANAGER, PROCITE, REFWORKS)
BibTex citation (BIBDESK, LATEX)
Having just published in a Libertas Academica journal (Evolutionary Bioinformatics) for the first time, I can attest that I was impressed by the process. Every stage from submission to typesetting and correspondence on matters relating to publishing was simple and efficient. In addition to this, regular updates of the status of the manuscript (with clear explanation of the status) enabled the process to be transparent and informative. I would not hesitate to use Libertas Academica ...