Theory of microbial genome evolution

TYPEStatistical & Bio Seminar
Speaker:Dr. Itama Sela
Affiliation:Computational Biology Branch, National Institutes of Health
Time:10:30 - 11:30
Location:Lidow Nathan Rosen (300)

The rapid accumulation of genome sequences from diverse organisms presents an opportunity and a challenge for theoretical research: is it possible to derive quantitative laws of genome evolution and an underlying theory? Microbes have small genomes with tightly packed protein-coding genes, and the different functional classes of genes (such as information processing, metabolism, or regulation) show distinct scaling exponents with the genome size. The compactness of microbial genomes is traditionally explained by genome streamlining under selection for high replication rate but so far, there has been no general theoretical model to account for the observed universal laws of genome content scaling. We developed a model for microbial genome evolution within the framework of population genetics and tested it against extensive data from multiple genome comparisons. The analyses indicate that the evolution of genome size is not governed by streamlining but rather, reflects the balance between the benefit of additional genes and the intrinsic preference for DNA deletion over acquisition. These results explain the observation that, contrary to the common belief, microbes with large genomes are subject to stronger selection than small genomes. Employing this model to recover the differential scaling of functional gene classes in bacterial genomes allowed us to identify the underlying factors that govern the evolution of the genome content. A key factor that we termed genome plasticity, shapes genome evolution and provides a simple mathematical representation of evolvability, a central but elusive concept in evolutionary biology. These findings demonstrate that key aspects of genome evolution can be captured by general population genetics models, and pave the way for further theoretical analyses of fundamental evolutionary mechanisms.