Bacterial microevolution and the Pangenome

The comparison of multiple genome sequences sampled from a bacterial population reveals considerable diversity in both the core and the accessory parts of the pangenome. This diversity can be analysed in terms of microevolutionary events that took place since the genomes shared a common ancestor, especially deletion, duplication, and recombination. We review the basic modelling ingredients used implicitly or explicitly when performing such a pangenome analysis. In particular, we describe a basic neutral phylogenetic framework of bacterial pangenome microevolution, which is not incompatible with evaluating the role of natural selection. We survey the different ways in which pangenome data is summarised in order to be included in microevolutionary models, as well as the main methodological approaches that have been proposed to reconstruct pangenome microevolutionary history

Who Watches the Watchmen? An Appraisal of Benchmarks for Multiple Sequence Alignment

Multiple sequence alignment (MSA) is a fundamental and ubiquitous technique in bioinformatics used to infer related residues among biological sequences. Thus alignment accuracy is crucial to a vast range of analyses, often in ways difficult to assess in those analyses. To compare the performance of different aligners and help detect systematic errors in alignments, a number of benchmarking strategies have been pursued. Here we present an overview of the main strategies--based on simulation, consistency, protein structure, and phylogeny--and discuss their different advantages and associated risks. We outline a set of desirable characteristics for effective benchmarking, and evaluate each strategy in light of them. We conclude that there is currently no universally applicable means of benchmarking MSA, and that developers and users of alignment tools should base their choice of benchmark depending on the context of application--with a keen awareness of the assumptions underlying each benchmarking strategy.Comment: Revie

estMOI: estimating multiplicity of infection using parasite deep sequencing data.

Individuals living in endemic areas generally harbour multiple parasite strains. Multiplicity of infection (MOI) can be an indicator of immune status and transmission intensity. It has a potentially confounding effect on a number of population genetic analyses, which often assume isolates are clonal. Polymerase chain reaction-based approaches to estimate MOI can lack sensitivity. For example, in the human malaria parasite Plasmodium falciparum, genotyping of the merozoite surface protein (MSP1/2) genes is a standard method for assessing MOI, despite the apparent problem of underestimation. The availability of deep coverage data from massively parallizable sequencing technologies means that MOI can be detected genome wide by considering the abundance of heterozygous genotypes. Here, we present a method to estimate MOI, which considers unique combinations of polymorphisms from sequence reads. The method is implemented within the estMOI software. When applied to clinical P.falciparum isolates from three continents, we find that multiple infections are common, especially in regions with high transmission

Accurate reconstruction of insertion-deletion histories by statistical phylogenetics

The Multiple Sequence Alignment (MSA) is a computational abstraction that represents a partial summary either of indel history, or of structural similarity. Taking the former view (indel history), it is possible to use formal automata theory to generalize the phylogenetic likelihood framework for finite substitution models (Dayhoff's probability matrices and Felsenstein's pruning algorithm) to arbitrary-length sequences. In this paper, we report results of a simulation-based benchmark of several methods for reconstruction of indel history. The methods tested include a relatively new algorithm for statistical marginalization of MSAs that sums over a stochastically-sampled ensemble of the most probable evolutionary histories. For mammalian evolutionary parameters on several different trees, the single most likely history sampled by our algorithm appears less biased than histories reconstructed by other MSA methods. The algorithm can also be used for alignment-free inference, where the MSA is explicitly summed out of the analysis. As an illustration of our method, we discuss reconstruction of the evolutionary histories of human protein-coding genes.Comment: 28 pages, 15 figures. arXiv admin note: text overlap with arXiv:1103.434

Local adaptation drives the diversification of effectors in the fungal wheat pathogen Parastagonospora nodorum in the United States

Filamentous fungi rapidly evolve in response to environmental selection pressures in part due to their genomic plasticity. Parastagonospora nodorum, a fungal pathogen of wheat and causal agent of septoria nodorum blotch, responds to selection pressure exerted by its host, influencing the gain, loss, or functional diversification of virulence determinants, known as effector genes. Whole genome resequencing of 197 P. nodorum isolates collected from spring, durum, and winter wheat production regions of the United States enabled the examination of effector diversity and genomic regions under selection specific to geographically discrete populations. 1,026,859 SNPs/InDels were used to identify novel loci, as well as SnToxA and SnTox3 as factors in disease. Genes displaying presence/absence variation, predicted effector genes, and genes localized on an accessory chromosome had significantly higher pN/pS ratios, indicating a higher rate of sequence evolution. Population structure analyses indicated two P. nodorum populations corresponding to the Upper Midwest (Population 1) and Southern/Eastern United States (Population 2). Prevalence of SnToxA varied greatly between the two populations which correlated with presence of the host sensitivity gene Tsn1 in the most prevalent cultivars in the corresponding regions. Additionally, 12 and 5 candidate effector genes were observed to be under diversifying selection among isolates from Population 1 and 2, respectively, but under purifying selection or neutrally evolving in the opposite population. Selective sweep analysis revealed 10 and 19 regions that had recently undergone positive selection in Population 1 and 2, respectively, involving 92 genes in total. When comparing genes with and without presence/absence variation, those genes exhibiting this variation were significantly closer to transposable elements. Taken together, these results indicate that P. nodorum is rapidly adapting to distinct selection pressures unique to spring and winter wheat production regions by rapid adaptive evolution and various routes of genomic diversification, potentially facilitated through transposable element activity