engleski

Large-scale inference of gene gain and loss dynamics following gene duplication

Gene turnover (gene gain and loss) is ever occurring process in genomes of both eukaryotes and prokaryotes. Forms of gene gain are: duplication of an existing gene in a genome, de novo evolution from noncoding regions of a genome or horizontal gene transfer from one genome to another. Uncovering gene gain and loss events in genomes’ histories is usually done by comparing gene trees with species trees, that is, tree reconciliation. A caveat in the existing reconciliation algorithms is that their resulting inference largely depends on the input parameters set by the user which can by themselves be very error-prone. Therefore, in this thesis, we developed a simple parameter-free algorithm for inferring duplication events, mapping them on the branches a rooted species tree and inferring losses that followed the inferred duplication event. Our algorithm only assumes a rooted species tree and rooted gene trees. Developed algorithm was used to analyze genome evolution in prokaryotes and eukaryotes. Obtained results suggest differences in horizontal gene transfer rates between prokaryotic genomes evolution and eukaryotic genomes evolution and overall prevalence of duplication and loss processes.

: phylogenomics, tree reconciliation, eukaryotes, prokaryotes, genome evolution, horizontal gene transfer

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