Accuracy and Robustness of Analyses Based on Numbers of Genes in Observed Segments. In: Sankoff D, Nadeau JH, editors. Comparative Genomics. Dordrecht: Springer Netherlands; 2000. pp. 299-306. [DOI: 10.1007/978-94-011-4309-7_27]

Analysis of gene order evolution beyond single-copy genes

The purpose of this chapter is to provide a comprehensive review of the field of genome rearrangement, i.e., comparative genomics, based on the representation of genomes as ordered sequences of signed genes. We specifically focus on the "hard part" of genome rearrangement, how to handle duplicated genes. The main questions are: how have present-day genomes evolved from a common ancestor? What are the most realistic evolutionary scenarios explaining the observed gene orders? What was the content and structure of ancestral genomes? We aim to provide a concise but complete overview of the field, starting with the practical problem of finding an appropriate representation of a genome as a sequence of ordered genes or blocks, namely the problems of orthology, paralogy, and synteny block identification. We then consider three levels of gene organization: the gene family level (evolution by duplication, loss, and speciation), the cluster level (evolution by tandem duplications), and the genome level (all types of rearrangement events, including whole genome duplication).

Rearrangements and chromosomal evolution

Comparisons of the genome sequences of related species suggests varying patterns of chromosomal rearrangements in different evolutionary lineages. In this review, I focus on the quantitative characterization of rearrangement processes and discuss specific inventories that have been compiled to date. Of particular interest are the statistical distribution of the lengths of inverted or locally transposed chromosome fragments (notably very short ones), inhomogeneities in susceptibility to evolutionary breakpoints in chromosomal regions, the relative importance of genome doubling in the history of multicellular eukaryotes, and of lateral transfer versus gene gain and loss in prokaryotes. These developments provide challenges to computational biologists to refine, revise and scale up mathematical models and algorithms for analyzing genome rearrangements.