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Multiple genome alignment remains a challenging problem. Effects ofrecombination including rearrangement, segmental duplication, gain, and losscan create a mosaic pattern of homology even among closely related organisms.We describe a method to align two or more genomes that have undergonelarge-scale recombination, particularly genomes that have undergone substantialamounts of gene gain and loss (gene flux). The method utilizes a novelalignment objective score, referred to as a sum-of-pairs breakpoint score. Wealso apply a probabilistic alignment filtering method to remove erroneousalignments of unrelated sequences, which are commonly observed in other genomealignment methods. We describe new metrics for quantifying genome alignmentaccuracy which measure the quality of rearrangement breakpoint predictions andindel predictions. The progressive genome alignment algorithm demonstratesmarkedly improved accuracy over previous approaches in situations where genomeshave undergone realistic amounts of genome rearrangement, gene gain, loss, andduplication. We apply the progressive genome alignment algorithm to a set of 23completely sequenced genomes from the genera Escherichia, Shigella, andSalmonella. The 23 enterobacteria have an estimated 2.46Mbp of genomic contentconserved among all taxa and total unique content of 15.2Mbp. We documentsubstantial population-level variability among these organisms driven byhomologous recombination, gene gain, and gene loss. Free, open-source softwareimplementing the described genome alignment approach is available fromhttp://gel.ahabs.wisc.edu/mauve .

Progressive Mauve: Multiple alignment of genomes with gene flux and rearrangement