Many aspects of genome evolution are best captured by numerical quantities. Examples include genome size, eukaryotic intron density, and gene family size. I will describe computational methods tailored for the analysis of such numerical characters evolving along a known evolutionary tree. The presentation focuses on inferring general evolutionary trends, as well as information about ancestral states.
I will discuss numerical parsimony, as well as probabilistic frameworks applied to the evolutionary analysis of gene repertoire and exon-intron architecture. In particular, I will address likelihood methods for phylogenetic birth-and-death models that assume linear birth-death-immigration processes acting on tree edges.
Analyses of intron evolution point to intron-rich eukaryotic ancestors. Reconstructions of genome-wide gene repertoires among Archaea reveal the persistence of streamlining processes, punctuated with occasional surges of gene content that (presumably) demarcate episodes of rapid adaptations and population bottlenecks. Perhaps surprisingly, both cases thus illustrate the formative influence of loss in the history of contemporary genomes.
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