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

Multiple genome alignment remains a challenging problem. Effects of recombination including rearrangement, segmental duplication, gain, and loss can create a mosaic pattern of homology even among closely related organisms. We describe a method to align two or more genomes that have undergone large-scale recombination, particularly genomes that have undergone substantial amounts of gene gain and loss (gene flux). The method utilizes a novel alignment objective score, referred to as a sum-of-pairs breakpoint score. We also apply a probabilistic alignment filtering method to remove erroneous alignments of unrelated sequences, which are commonly observed in other genome alignment methods. We describe new metrics for quantifying genome alignment accuracy which measure the quality of rearrangement breakpoint predictions and indel predictions. The progressive genome alignment algorithm demonstrates markedly improved accuracy over previous approaches in situations where genomes have undergone realistic amounts of genome rearrangement, gene gain, loss, and duplication. We apply the progressive genome alignment algorithm to a set of 23 completely sequenced genomes from the genera Escherichia, Shigella, and Salmonella. The 23 enterobacteria have an estimated 2.46Mbp of genomic content conserved among all taxa and total unique content of 15.2Mbp. We document substantial population-level variability among these organisms driven by homologous recombination, gene gain, and gene loss. Free, open-source software implementing the described genome alignment approach is available from http://gel.ahabs.wisc.edu/mauve .Comment: Revision dated June 19, 200

The rise and fall of breakpoint reuse depending on genome resolution

<p>Abstract</p> <p>Background</p> <p>During evolution, large-scale genome rearrangements of chromosomes shuffle the order of homologous genome sequences ("synteny blocks") across species. Some years ago, a controversy erupted in genome rearrangement studies over whether rearrangements recur, causing breakpoints to be reused.</p> <p>Methods</p> <p>We investigate this controversial issue using the synteny block's for human-mouse-rat reported by Bourque <it>et al</it>. and a series of synteny blocks we generated using Mauve at resolutions ranging from coarse to very fine-scale. We conducted analyses to test how resolution affects the traditional measure of the breakpoint reuse rate<it>.</it></p> <p>Results</p> <p>We found that the inversion-based breakpoint reuse rate is low at fine-scale synteny block resolution and that it rises and eventually falls as synteny block resolution decreases. By analyzing the cycle structure of the breakpoint graph of human-mouse-rat synteny blocks for human-mouse and comparing with theoretically derived distributions for random genome rearrangements, we showed that the implied genome rearrangements at each level of resolution become more “random” as synteny block resolution diminishes. At highest synteny block resolutions the Hannenhalli-Pevzner inversion distance deviates from the Double Cut and Join distance, possibly due to small-scale transpositions or simply due to inclusion of erroneous synteny blocks. At synteny block resolutions as coarse as the Bourque <it>et al</it>. blocks, we show the breakpoint graph cycle structure has already converged to the pattern expected for a random distribution of synteny blocks.</p> <p>Conclusions</p> <p>The inferred breakpoint reuse rate depends on synteny block resolution in human-mouse genome comparisons. At fine-scale resolution, the cycle structure for the transformation appears less random compared to that for coarse resolution. Small synteny blocks may contain critical information for accurate reconstruction of genome rearrangement history and parameters.</p

Fidelity of Hyperbolic Space for Bayesian Phylogenetic Inference

Bayesian inference for phylogenetics is a gold standard for computing distributions of phylogenies. It faces the challenging problem of. moving throughout the high-dimensional space of trees. However, hyperbolic space offers a low dimensional representation of tree-like data. In this paper, we embed genomic sequences into hyperbolic space and perform hyperbolic Markov Chain Monte Carlo for Bayesian inference. The posterior probability is computed by decoding a neighbour joining tree from proposed embedding locations. We empirically demonstrate the fidelity of this method on eight data sets. The sampled posterior distribution recovers the splits and branch lengths to a high degree. We investigated the effects of curvature and embedding dimension on the Markov Chain's performance. Finally, we discuss the prospects for adapting this method to navigate tree space with gradients

Draft Genome Sequence of Curtobacterium flaccumfaciens Strain UCD-AKU (Phylum Actinobacteria).

Here we present the draft genome of an actinobacterium, Curtobacterium flaccumfaciens strain UCD-AKU, isolated from a residential carpet. The genome assembly contains 3,692,614 bp in 130 contigs. This is the first member of the Curtobacterium genus to be sequenced

Draft Genome Sequence of Kocuria sp. Strain UCD-OTCP (Phylum Actinobacteria).

Here, we present the draft genome of Kocuria sp. strain UCD-OTCP, a member of the phylum Actinobacteria, isolated from a restaurant chair cushion. The assembly contains 3,791,485 bp (G+C content of 73%) and is contained in 68 scaffolds

Draft Genome Sequence of Dietzia sp. Strain UCD-THP (Phylum Actinobacteria).

Here, we present the draft genome sequence of an actinobacterium, Dietzia sp. strain UCD-THP, isolated from a residential toilet handle. The assembly contains 3,915,613 bp. The genome sequences of only two other Dietzia species have been published, those of Dietzia alimentaria and Dietzia cinnamea