Lateral gene transfer (LGT) is the process by which prokaryotes acquire DNA across wide taxonomic boundaries and incorporate it into their genome. Accumulating evidence shows that LGT plays a major role in prokaryote evolution. The biological and evolutionary significance of lateral gene transfer has broad implications for our understanding of microbial biology, not only in terms of evolution, but also in terms of human health.Mechanisms of lateral gene transfer include: transformation, transduction, conjugation, and gene transfer agents. Each of these transfer mechanisms leaves distinct and recognizable molecular footprints in genome sequences. The molecular details of these footprints betray the workings of the corresponding mechanisms in nature, but their relative contributions to the evolution of sequenced genomes have so far not been investigated. By identifying these footprints one can specify and quantify the relative contribution of the different LGT mechanisms during prokaryote genome evolution and thereby uncover more of the biology underlying prokaryote evolution in nature. The goal of this proposal is to quantify those contributions and to bring forth a general computer-based model of prokaryote genome evolution that approximates the underlying evolutionary process far more realistically than phylogenetic trees alone possibly can.Here I propose to apply directed networks to the study of prokaryotic genome evolution in an evolutionary model that allows both for vertical inheritance and for lateral gene transfer events. With methods to identify gene donors, all recent LGTs can be described in a single directed network. This is a fundamentally new, biologically more realistic and evolutionarily more accurate, general computational model of prokaryote genome evolution. Such a model will substantially enrich our ability to understand the process of prokaryote evolution as it is recorded in genomic and metagenomic data.