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1.  Irreconcilable differences: divorcing geographic mutation and recombination rates within a global MRSA clone 
Genome Biology  2012;13(12):181.
A growing resource of methicillin-resistant Staphylococcus aureus (MRSA) genomes uncovers intriguing phylogeographic and recombination patterns and highlights challenges in identifying the source of these phenomena.
doi:10.1186/gb-2012-13-12-181
PMCID: PMC3580406  PMID: 23270611
2.  Repetitive DNA and next-generation sequencing: computational challenges and solutions 
Nature Reviews. Genetics  2011;13(1):36-46.
Repetitive DNA sequences are abundant in a broad range of species, from bacteria to mammals, and they cover nearly half of the human genome. Repeats have always presented technical challenges for sequence alignment and assembly programs. Next-generation sequencing projects, with their short read lengths and high data volumes, have made these challenges more difficult. From a computational perspective, repeats create ambiguities in alignment and assembly, which, in turn, can produce biases and errors when interpreting results. Simply ignoring repeats is not an option, as this creates problems of its own and may mean that important biological phenomena are missed. We discuss the computational problems surrounding repeats and describe strategies used by current bioinformatics systems to solve them.
doi:10.1038/nrg3117
PMCID: PMC3324860  PMID: 22124482
3.  Bambus 2: scaffolding metagenomes 
Bioinformatics  2011;27(21):2964-2971.
Motivation: Sequencing projects increasingly target samples from non-clonal sources. In particular, metagenomics has enabled scientists to begin to characterize the structure of microbial communities. The software tools developed for assembling and analyzing sequencing data for clonal organisms are, however, unable to adequately process data derived from non-clonal sources.
Results: We present a new scaffolder, Bambus 2, to address some of the challenges encountered when analyzing metagenomes. Our approach relies on a combination of a novel method for detecting genomic repeats and algorithms that analyze assembly graphs to identify biologically meaningful genomic variants. We compare our software to current assemblers using simulated and real data. We demonstrate that the repeat detection algorithms have higher sensitivity than current approaches without sacrificing specificity. In metagenomic datasets, the scaffolder avoids false joins between distantly related organisms while obtaining long-range contiguity. Bambus 2 represents a first step toward automated metagenomic assembly.
Availability: Bambus 2 is open source and available from http://amos.sf.net.
Contact: mpop@umiacs.umd.edu
Supplementary Information: Supplementary data are available at Bioinformatics online.
doi:10.1093/bioinformatics/btr520
PMCID: PMC3198580  PMID: 21926123
4.  Next Generation Sequence Assembly with AMOS 
A Modular Open-Source Assembler (AMOS) was designed to offer a modular approach to genome assembly. AMOS includes a wide range of tools for assembly, including lightweight de novo assemblers Minimus and Minimo, and Bambus 2, a robust scaffolder able to handle metagenomic and polymorphic data. This protocol describes how to configure and use AMOS for the assembly of Next Generation sequence data. Additionally, we provide three tutorial examples that include bacterial, viral, and metagenomic datasets with specific tips for improving assembly quality.
doi:10.1002/0471250953.bi1108s33
PMCID: PMC3072823  PMID: 21400694
Next-generation sequencing; genome assembly; Open-Source
6.  Horizontal Transfer, Not Duplication, Drives the Expansion of Protein Families in Prokaryotes 
PLoS Genetics  2011;7(1):e1001284.
Gene duplication followed by neo- or sub-functionalization deeply impacts the evolution of protein families and is regarded as the main source of adaptive functional novelty in eukaryotes. While there is ample evidence of adaptive gene duplication in prokaryotes, it is not clear whether duplication outweighs the contribution of horizontal gene transfer in the expansion of protein families. We analyzed closely related prokaryote strains or species with small genomes (Helicobacter, Neisseria, Streptococcus, Sulfolobus), average-sized genomes (Bacillus, Enterobacteriaceae), and large genomes (Pseudomonas, Bradyrhizobiaceae) to untangle the effects of duplication and horizontal transfer. After removing the effects of transposable elements and phages, we show that the vast majority of expansions of protein families are due to transfer, even among large genomes. Transferred genes—xenologs—persist longer in prokaryotic lineages possibly due to a higher/longer adaptive role. On the other hand, duplicated genes—paralogs—are expressed more, and, when persistent, they evolve slower. This suggests that gene transfer and gene duplication have very different roles in shaping the evolution of biological systems: transfer allows the acquisition of new functions and duplication leads to higher gene dosage. Accordingly, we show that paralogs share most protein–protein interactions and genetic regulators, whereas xenologs share very few of them. Prokaryotes invented most of life's biochemical diversity. Therefore, the study of the evolution of biology systems should explicitly account for the predominant role of horizontal gene transfer in the diversification of protein families.
Author Summary
Prokaryotes can be found in the most diverse and severe ecological niches of the planet. Their rapid adaptation is, in part, the result of the ability to acquire genetic information horizontally. This means that prokaryotes utilize two major paths to expand their repertoire of protein families: they can duplicate a pre-existing gene or acquire it by horizontal transfer. In this study, we track family expansions among closely related strains of prokaryotic species. We find that the majority of gene expansions arrive via transfer not via duplication. Additionally, we find that duplicate genes tend be more transient and evolve slower than transferred ones, highlighting different roles with respect to adaptation and evolution. These results suggest that prevailing theories aimed at understanding the evolution of biological systems grounded on gene duplication might be poorly fit to explain the evolution of prokaryotic systems, which include the vast majority of life's biochemical diversity.
doi:10.1371/journal.pgen.1001284
PMCID: PMC3029252  PMID: 21298028
7.  The impact of the neisserial DNA uptake sequences on genome evolution and stability 
Genome Biology  2008;9(3):R60.
A study of the origin and distribution of the abundant short DNA uptake sequence (DUS) in six genomes of Neisseria suggests that transformation and recombination are tightly linked in evolution and that recombination has a key role in the establishment of DUS.
Background
Efficient natural transformation in Neisseria requires the presence of short DNA uptake sequences (DUSs). Doubts remain whether DUSs propagate by pure selfish molecular drive or are selected for 'safe sex' among conspecifics.
Results
Six neisserial genomes were aligned to identify gene conversion fragments, DUS distribution, spacing, and conservation. We found a strong link between recombination and DUS: DUS spacing matches the size of conversion fragments; genomes with shorter conversion fragments have more DUSs and more conserved DUSs; and conversion fragments are enriched in DUSs. Many recent and singly occurring DUSs exhibit too high divergence with homologous sequences in other genomes to have arisen by point mutation, suggesting their appearance by recombination. DUSs are over-represented in the core genome, under-represented in regions under diversification, and absent in both recently acquired genes and recently lost core genes. This suggests that DUSs are implicated in genome stability rather than in generating adaptive variation. DUS elements are most frequent in the permissive locations of the core genome but are themselves highly conserved, undergoing mutation selection balance and/or molecular drive. Similar preliminary results were found for the functionally analogous uptake signal sequence in Pasteurellaceae.
Conclusion
As do many other pathogens, Neisseria and Pasteurellaceae have hyperdynamic genomes that generate deleterious mutations by intrachromosomal recombination and by transient hypermutation. The results presented here suggest that transformation in Neisseria and Pasteurellaceae allows them to counteract the deleterious effects of genome instability in the core genome. Thus, rather than promoting hypervariation, bacterial sex could be regenerative.
doi:10.1186/gb-2008-9-3-r60
PMCID: PMC2397512  PMID: 18366792
8.  M-GCAT: interactively and efficiently constructing large-scale multiple genome comparison frameworks in closely related species 
BMC Bioinformatics  2006;7:433.
Background
Due to recent advances in whole genome shotgun sequencing and assembly technologies, the financial cost of decoding an organism's DNA has been drastically reduced, resulting in a recent explosion of genomic sequencing projects. This increase in related genomic data will allow for in depth studies of evolution in closely related species through multiple whole genome comparisons.
Results
To facilitate such comparisons, we present an interactive multiple genome comparison and alignment tool, M-GCAT, that can efficiently construct multiple genome comparison frameworks in closely related species. M-GCAT is able to compare and identify highly conserved regions in up to 20 closely related bacterial species in minutes on a standard computer, and as many as 90 (containing 75 cloned genomes from a set of 15 published enterobacterial genomes) in an hour. M-GCAT also incorporates a novel comparative genomics data visualization interface allowing the user to globally and locally examine and inspect the conserved regions and gene annotations.
Conclusion
M-GCAT is an interactive comparative genomics tool well suited for quickly generating multiple genome comparisons frameworks and alignments among closely related species. M-GCAT is freely available for download for academic and non-commercial use at: .
doi:10.1186/1471-2105-7-433
PMCID: PMC1629028  PMID: 17022809
9.  Deep Sequencing of the Oral Microbiome Reveals Signatures of Periodontal Disease 
PLoS ONE  2012;7(6):e37919.
The oral microbiome, the complex ecosystem of microbes inhabiting the human mouth, harbors several thousands of bacterial types. The proliferation of pathogenic bacteria within the mouth gives rise to periodontitis, an inflammatory disease known to also constitute a risk factor for cardiovascular disease. While much is known about individual species associated with pathogenesis, the system-level mechanisms underlying the transition from health to disease are still poorly understood. Through the sequencing of the 16S rRNA gene and of whole community DNA we provide a glimpse at the global genetic, metabolic, and ecological changes associated with periodontitis in 15 subgingival plaque samples, four from each of two periodontitis patients, and the remaining samples from three healthy individuals. We also demonstrate the power of whole-metagenome sequencing approaches in characterizing the genomes of key players in the oral microbiome, including an unculturable TM7 organism. We reveal the disease microbiome to be enriched in virulence factors, and adapted to a parasitic lifestyle that takes advantage of the disrupted host homeostasis. Furthermore, diseased samples share a common structure that was not found in completely healthy samples, suggesting that the disease state may occupy a narrow region within the space of possible configurations of the oral microbiome. Our pilot study demonstrates the power of high-throughput sequencing as a tool for understanding the role of the oral microbiome in periodontal disease. Despite a modest level of sequencing (∼2 lanes Illumina 76 bp PE) and high human DNA contamination (up to ∼90%) we were able to partially reconstruct several oral microbes and to preliminarily characterize some systems-level differences between the healthy and diseased oral microbiomes.
doi:10.1371/journal.pone.0037919
PMCID: PMC3366996  PMID: 22675498

Results 1-9 (9)