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Convergent evolution can explain similarity in morphology between species, due to selection on a fitness-enhancing phenotype in response to local environmental conditions. As selective pressures on body morphology may be strong, these have confounded our understanding of the evolutionary relationships between species. Within the speciose African radiation of lacertid lizards (Eremiadini), some species occupy a narrow habitat range (e.g. open habitat, cluttered habitat, strictly rupicolous, or strictly psammophilic), which may exert strong selective pressures on lizard body morphology. Here we show that the overall body plan is unrelated to shared ancestry in the African radiation of Eremiadini, but is instead coupled to habitat use. Comprehensive Bayesian and likelihood phylogenies using multiple representatives from all genera (2 nuclear, 2 mitochondrial markers) show that morphologically convergent species thought to represent sister taxa within the same genus are distantly related evolutionary lineages (Ichnotropis squamulosa and Ichnotropis spp.; Australolacerta rupicola and A. australis). Hierarchical clustering and multivariate analysis of morphological characters suggest that body, and head, width and height (stockiness), all of which are ecologically relevant with respect to movement through habitat, are similar between the genetically distant species. Our data show that convergence in morphology, due to adaptation to similar environments, has confounded the assignment of species leading to misidentification of the taxonomic position of I. squamulosa and the Australolacerta species. [ABSTRACT FROM AUTHOR]

Background: Several population-wide HIV-1 subtype distribution studies in Uganda have evaluated relatively healthy clinic patients. Given the differences in HIV-1 disease progression based on subtype, we examined HIV-1 subtype distribution and disease outcomes among hospitalized patients with severe sepsis. Methods: Patients with severe sepsis were enrolled at two hospitals in Uganda. Data collected included demographics, Karnofsky scores, highly active antiretroviral therapy (HAART) use, HIV-1 serostatus, CD4+ T cell concentration, whole blood lactate concentration, and blood cultures. HIV-1 subtypes were determined by sequencing parts of the gag and env genes, followed by phylogenetic analysis. Results: Of the 267 patients evaluated, 228 (85.4%) were HIV infected. The predominant HIV-1 subtypes were A (46%), D (17%), and AD recombinants (30%). HIV-1 subtypes B, C, and other recombinants were uncommon. Patients infected with HIV-1 subtypes A, D and AD viruses were similar in demographics, CD4+ T cell concentration, HAART use, Karnofsky scores, whole blood lactate concentration, and positive blood cultures. There was no difference in 30-day mortality from severe sepsis between the 3 groups (p = 0.99). Conclusion: A high proportion of HIV-1 subtypes A and AD recombinants was observed in this cohort of severely septic patients. The proportion of AD recombinants was higher in this cohort than in previous cohorts of Ugandan HIV-1 patients. No difference in baseline demographics, clinical factors or 30-day mortality was seen across HIV-subtypes. [ABSTRACT FROM AUTHOR]

Recent advancements of sequencing technology have opened up unprecedented opportunities in many application areas. Virus samples can now be sequenced efficiently with very deep coverage to infer the genetic diversity of the underlying virus populations. Several sequencing platforms with different underlying technologies and performance characteristics are available for viral diversity studies. Here, we investigate how the differences between two common platforms provided by 454/Roche and Illumina affect viral diversity estimation and the reconstruction of viral haplotypes. Using a mixture of ten HIV clones sequenced with both platforms and additional simulation experiments, we assessed the trade-off between sequencing coverage, read length, and error rate. For fixed costs, short Illumina reads can be generated at higher coverage and allow for detecting variants at lower frequencies. They can also be sufficient to assess the diversity of the sample if sequences are dissimilar enough, but, in general, assembly of full-length haplotypes is feasible only with the longer 454/Roche reads. The quantitative comparison highlights the advantages and disadvantages of both platforms and provides guidance for the design of viral diversity studies. [ABSTRACT FROM AUTHOR]

The evolution of drug resistance mutations in plasma samples is relatively well-characterized. However, the viral population and diversity in other body compartments such as peripheral blood mononuclear cells (PBMC) remains poorly understood. Previous studies have mostly focused on protease and reverse transcriptase drug resistance mutations (DRMs). In this study, we used 454 "deep" sequencing technology to observe and quantify longitudinally the prevalence of resistance mutations associated with the integrase inhibitor, raltegravir, in plasma versus PBMC samples from a San Francisco-based cohort. Four heavily treatment-experienced subjects were monitored in this study over a median of 1.2 years since the initiation of raltegravir-containing regimens. We observed a consistent discordance in the prevalence of DRMs, but not resistance pathway(s), in the plasma versus PBMC viral populations. In the final paired samples that were tested while the subjects were on a raltegravir-containing regimen, DRM prevalence reached 100% in plasma but remained 1% in PBMC on day 177 post-therapy in Subject 3180 (Q148H/G140S), 100% in plasma and 36% in PBMC on day 224 in Subject 3242 (N155H), 78% in plasma and 11-12% in PBMC on day 338 in Subject 3501 (Q148H/G140S), and 100% in plasma and 0% in PBMC on day 197 in Subject 3508 (Y143R). Furthermore, absolute sequence homology comparison between the two compartments revealed that 21% - 99% of PBMC sequences had no match in plasma, whereas 14% - 100% of plasma sequences had no match in PBMC. Overall, our observations suggested that plasma and PBMC hosted drastically different HIV-1 populations even after a prolonged exposure to raltegravir selection pressure. [ABSTRACT FROM AUTHOR]

One of the most common questions asked before starting a new population genetic study using microsatellite allele frequencies is "how many individuals do I need to sample from each population?" This question has previously been answered by addressing how many individuals are needed to detect all of the alleles present in a population (i.e. rarefaction based analyses). However, we argue that obtaining accurate allele frequencies and accurate estimates of diversity are much more important than detecting all of the alleles, given that very rare alleles (i.e. new mutations) are not very informative for assessing genetic diversity within a population or genetic structure among populations. Here we present a comparison of allele frequencies, expected heterozygosities and genetic distances between real and simulated populations by randomly subsampling 5-100 individuals from four empirical microsatellite genotype datasets (Formica lugubris, Sciurus vulgaris, Thalassarche melanophris, and Himantopus novaezelandia) to create 100 replicate datasets at each sample size. Despite differences in taxon (two birds, one mammal, one insect), population size, number of loci and polymorphism across loci, the degree of differences between simulated and empirical dataset allele frequencies, expected heterozygosities and pairwise FST values were almost identical among the four datasets at each sample size. Variability in allele frequency and expected heterozygosity among replicates decreased with increasing sample size, but these decreases were minimal above sample sizes of 25 to 30. Therefore, there appears to be little benefit in sampling more than 25 to 30 individuals per population for population genetic studies based on microsatellite allele frequencies. [ABSTRACT FROM AUTHOR]

Currently existing theories predict that because deleterious mutations accumulate at a higher rate, selfing populations suffer from more intense genetic degradation relative to outcrossing populations. This prediction may not always be true when we consider a potential difference in deleterious mutation rate between selfers and outcrossers. By analyzing the evolutionary stability of selfing and outcrossing in an infinite population, we found that the genome-wide deleterious mutation rate would be lower in selfing than in outcrossing organisms. When this difference in mutation rate was included in simulations, we found that in a small population, mutations accumulated more slowly under selfing rather than outcrossing. This result suggests that under frequent and intense bottlenecks, a selfing population may have a lower risk of genetic extinction than an outcrossing population. [ABSTRACT FROM AUTHOR]

Correlated mutation analysis has a long history of interesting applications, mostly in the detection of contact pairs in protein structures. Based on previous observations that, if properly assessed, amino acid correlation data can also provide insights about functional sub-classes in a protein family, we provide a complete framework devoted to this purpose. An amino acid specific correlation measure is proposed, which can be used to build networks summarizing all correlation and anti-correlation patterns in a protein family. These networks can be submitted to community structure detection algorithms, resulting in subsets of correlated amino acids which can be further assessed by specific parameters and procedures that provide insight into the relationship between different communities, the individual importance of community members and the adherence of a given amino acid sequence to a given community. By applying this framework to three protein families with contrasting characteristics (the Fe/Mn-superoxide dismutases, the peroxidase-catalase family and the C-type lysozyme/ a-lactalbumin family), we show how our method and the proposed parameters and procedures are related to biological characteristics observed in these protein families, highlighting their potential use in protein characterization and gene annotation. [ABSTRACT FROM AUTHOR]

Cytochrome c (cyt c) participates in two crucial cellular processes, energy production and apoptosis, and unsurprisingly is a highly conserved protein. However, previous studies have reported for the primate lineage (i) loss of the paralogous testis isoform, (ii) an acceleration and then a deceleration of the amino acid replacement rate of the cyt c somatic isoform, and (iii) atypical biochemical behavior of human cyt c. To gain insight into the cause of these major evolutionary events, we have retraced the history of cyt c loci among primates. For testis cyt c, all primate sequences examined carry the same nonsense mutation, which suggests that silencing occurred before the primates diversified. For somatic cyt c, maximum parsimony, maximum likelihood, and Bayesian phylogenetic analyses yielded the same tree topology. The evolutionary analyses show that a fast accumulation of non-synonymous mutations (suggesting positive selection) occurred specifically on the anthropoid lineage root and then continued in parallel on the early catarrhini and platyrrhini stems. Analysis of evolutionary changes using the 3D structure suggests they are focused on the respiratory chain rather than on apoptosis or other cyt c functions. In agreement with previous biochemical studies, our results suggest that silencing of the cyt c testis isoform could be linked with the decrease of primate reproduction rate. Finally, the evolution of cyt c in the two sister anthropoid groups leads us to propose that somatic cyt c evolution may be related both to COX evolution and to the convergent brain and body mass enlargement in these two anthropoid clades. [ABSTRACT FROM AUTHOR]

Human influenza A viruses undergo antigenic changes with gradual accumulation of amino acid substitutions on the hemagglutinin (HA) molecule. A strong antigenic mismatch between vaccine and epidemic strains often requires the replacement of influenza vaccines worldwide. To establish a practical model enabling us to predict the future direction of the influenza virus evolution, relative distances of amino acid sequences among past epidemic strains were analyzed by multidimensional scaling (MDS). We found that human influenza viruses have evolved along a gnarled evolutionary pathway with an approximately constant curvature in the MDS-constructed 3D space. The gnarled pathway indicated that evolution on the trunk favored multiple substitutions at the same amino acid positions on HA. The constant curvature was reasonably explained by assuming that the rate of amino acid substitutions varied from one position to another according to a gamma distribution. Furthermore, we utilized the estimated parameters of the gamma distribution to predict the amino acid substitutions on HA in subsequent years. Retrospective prediction tests for 12 years from 1997 to 2009 showed that 70% of actual amino acid substitutions were correctly predicted, and that 45% of predicted amino acid substitutions have been actually observed. Although it remains unsolved how to predict the exact timing of antigenic changes, the present results suggest that our model may have the potential to recognize emerging epidemic strains. [ABSTRACT FROM AUTHOR]

The heterogametic sex chromosomes (i.e. mammalian Y and avian W) do not usually recombine with the homogametic sex chromosomes which is known to lead into rapid degeneration of Y and W due to accumulation of deleterious mutations. On the other hand, some 96% of amphibian species have homomorphic, i.e. non-degenerate Y chromosomes. Nicolas Perrin's fountain-of-youth hypothesis states that this is a result of recombination between X and Y chromosomes in sex-reversed individuals. In this study, I model the consequences of such recombination for the dynamics of a deleterious mutation occurring in Y chromosomes. As expected, even relatively low levels of sex reversal help to purge deleterious mutations. However, the population-dynamic consequences of this depend on the type of selection that operates on the population undergoing sex reversal. Under fecundity selection, sex reversal can be beneficial for some parameter values, whereas under survival selection, it seems to be always harmful. [ABSTRACT FROM AUTHOR]

The relationship between mutation, protein stability and protein function plays a central role in molecular evolution. Mutations tend to be destabilizing, including those that would confer novel functions such as host-switching or antibiotic resistance. Elevated temperature may play an important role in preadapting a protein for such novel functions by selecting for stabilizing mutations. In this study, we test the stability change conferred by single mutations that arise in a G4-like bacteriophage adapting to elevated temperature. The vast majority of these mutations map to interfaces between viral coat proteins, suggesting they affect protein-protein interactions. We assess their effects by estimating thermodynamic stability using molecular dynamic simulations and measuring kinetic stability using experimental decay assays. The results indicate that most, though not all, of the observed mutations are stabilizing. [ABSTRACT FROM AUTHOR]

Microbial diseases are important selective agents in social insects and one major defense mechanism is the secretion of cuticular antimicrobial compounds. We hypothesized that given differences in group size, social complexity, and nest type the secretions of these antimicrobials will be under different selective pressures. To test this we extracted secretions from nine wasp species of varying social complexity and nesting habits and assayed their antimicrobial compounds against cultures of Staphylococcus aureus. These data were then combined with phylogenetic data to provide an evolutionary context. Social species showed significantly higher (18x) antimicrobial activity than solitary species and species with paper nests showed significantly higher (11x) antimicrobial activity than those which excavated burrows. Mud-nest species showed no antimicrobial activity. Solitary, burrow-provisioning wasps diverged at more basal nodes of the phylogenetic trees, while social wasps diverged from the most recent nodes. These data suggest that antimicrobial defences may have evolved in response to ground-dwelling pathogens but the most important variable leading to increased antimicrobial strength was increase in group size and social complexity. [ABSTRACT FROM AUTHOR]

Background: Human Papillomavirus type 16 (HPV16) causes over half of all cervical cancer and some HPV16 variants are more oncogenic than others. The genetic basis for the extraordinary oncogenic properties of HPV16 compared to other HPVs is unknown. In addition, we neither know which nucleotides vary across and within HPV types and lineages, nor which of the single nucleotide polymorphisms (SNPs) determine oncogenicity. Methods: A reference set of 62 HPV16 complete genome sequences was established and used to examine patterns of evolutionary relatedness amongst variants using a pairwise identity heatmap and HPV16 phylogeny. A BLAST-based algorithm was developed to impute complete genome data from partial sequence information using the reference database. To interrogate the oncogenic risk of determined and imputed HPV16 SNPs, odds-ratios for each SNP were calculated in a case-control viral genome-wide association study (VWAS) using biopsy confirmed high-grade cervix neoplasia and self-limited HPV16 infections from Guanacaste, Costa Rica. Results: HPV16 variants display evolutionarily stable lineages that contain conserved diagnostic SNPs. The imputation algorithm indicated that an average of 97.5±1.03% of SNPs could be accurately imputed. The VWAS revealed specific HPV16 viral SNPs associated with variant lineages and elevated odds ratios; however, individual causal SNPs could not be distinguished with certainty due to the nature of HPV evolution. Conclusions: Conserved and lineage-specific SNPs can be imputed with a high degree of accuracy from limited viral polymorphic data due to the lack of recombination and the stochastic mechanism of variation accumulation in the HPV genome. However, to determine the role of novel variants or non-lineage-specific SNPs by VWAS will require direct sequence analysis. The investigation of patterns of genetic variation and the identification of diagnostic SNPs for lineages of HPV16 variants provides a valuable resource for future studies of HPV16 pathogenicity. [ABSTRACT FROM AUTHOR]

Background: Bambusoideae is the only subfamily that contains woody members in the grass family, Poaceae. In phylogenetic analyses, Bambusoideae, Pooideae and Ehrhartoideae formed the BEP clade, yet the internal relationships of this clade are controversial. The distinctive life history (infrequent flowering and predominance of asexual reproduction) of woody bamboos makes them an interesting but taxonomically difficult group. Phylogenetic analyses based on large DNA fragments could only provide a moderate resolution of woody bamboo relationships, although a robust phylogenetic tree is needed to elucidate their evolutionary history. Phylogenomics is an alternative choice for resolving difficult phylogenies. Methodology/Principal Findings: Here we present the complete nucleotide sequences of six woody bamboo chloroplast (cp) genomes using Illumina sequencing. These genomes are similar to those of other grasses and rather conservative in evolution. We constructed a phylogeny of Poaceae from 24 complete cp genomes including 21 grass species. Within the BEP clade, we found strong support for a sister relationship between Bambusoideae and Pooideae. In a substantial improvement over prior studies, all six nodes within Bambusoideae were supported with ≥0.95 posterior probability from Bayesian inference and 5/6 nodes resolved with 100% bootstrap support in maximum parsimony and maximum likelihood analyses. We found that repeats in the cp genome could provide phylogenetic information, while caution is needed when using indels in phylogenetic analyses based on few selected genes. We also identified relatively rapidly evolving cp genome regions that have the potential to be used for further phylogenetic study in Bambusoideae. Conclusions/Significance: The cp genome of Bambusoideae evolved slowly, and phylogenomics based on whole cp genome could be used to resolve major relationships within the subfamily. The difficulty in resolving the diversification among three clades of temperate woody bamboos, even with complete cp genome sequences, suggests that these lineages may have diverged very rapidly. [ABSTRACT FROM AUTHOR]

Background: DNA barcoding and other DNA sequence-based techniques for investigating and estimating biodiversity require explicit methods for associating individual sequences with taxa, as it is at the taxon level that biodiversity is assessed. For many projects, the bioinformatic analyses required pose problems for laboratories whose prime expertise is not in bioinformatics. User-friendly tools are required for both clustering sequences into molecular operational taxonomic units (MOTU) and for associating these MOTU with known organismal taxonomies. Results: Here we present jMOTU, a Java program for the analysis of DNA barcode datasets that uses an explicit, determinate algorithm to define MOTU. We demonstrate its usefulness for both individual specimen-based Sanger sequencing surveys and bulk-environment metagenetic surveys using long-read next-generation sequencing data. jMOTU is driven through a graphical user interface, and can analyse tens of thousands of sequences in a short time on a desktop computer. A companion program, Taxonerator, that adds traditional taxonomic annotation to MOTU, is also presented. Clustering and taxonomic annotation data are stored in a relational database, and are thus amenable to subsequent data mining and web presentation. Conclusions: jMOTU efficiently and robustly identifies the molecular taxa present in survey datasets, and Taxonerator decorates the MOTU with putative identifications. jMOTU and Taxonerator are freely available from http://www.nematodes. org/. [ABSTRACT FROM AUTHOR]

The difference between regional rates of HIV-associated dementia (HAD) in patients infected with different subtypes of HIV suggests that genetic determinants exist within HIV that influence the ability of the virus to replicate in the central nervous system (in Uganda, Africa, subtype D HAD rate is 89%, while subtype A HAD rate is 24%). HIV-1 nef is a multifunctional protein with known toxic effects in the brain compartment. The goal of the current study was to identify if specific three-dimensional nef structures may be linked to patients who developed HAD. HIV-1 nef structures were computationally derived for consensus brain and non-brain sequences from a panel of patients infected with subtype B who died due to varied disease pathologies and consensus subtype A and subtype D sequences from Uganda. Site directed mutation analysis identified signatures in brain structures that appear to change binding potentials and could affect folding conformations of brain-associated structures. Despite the large sequence variation between HIV subtypes, structural alignments confirmed that viral structures derived from patients with HAD were more similar to subtype D structures than to structures derived from patient sequences without HAD. Furthermore, structures derived from brain sequences of patients with HAD were more similar to subtype D structures than they were to their own non-brain structures. The potential finding of a brain-specific nef structure indicates that HAD may result from genetic alterations that alter the folding or binding potential of the protein. [ABSTRACT FROM AUTHOR]

Whether HIV-1 evolution in infected individuals is dominated by deterministic or stochastic effects remains unclear because current estimates of the effective population size of HIV-1 in vivo, Ne, are widely varying. Models assuming HIV-1 evolution to be Neutral estimate Ne,10²-104, smaller than the inverse mutation rate of HIV-1 (∼105), implying the predominance of stochastic forces. In contrast, a model that includes selection estimates Ne>105, suggesting that deterministic forces would hold sway. The consequent uncertainty in the nature of HIV-1 evolution compromises our ability to describe disease progression and outcomes of therapy. We perform detailed bit-string simulations of viral evolution that consider large genome lengths and incorporate the key evolutionary processes underlying the genomic diversification of HIV-1 in infected individuals, namely, mutation, multiple infections of cells, recombination, selection, and epistatic interactions between multiple loci. Our simulations describe quantitatively the evolution of HIV-1 diversity and divergence in patients. From comparisons of our simulations with patient data, we estimate Ne∼10³-104, implying predominantly stochastic evolution. Interestingly, we find that Ne and the viral generation time are correlated with the disease progression time, presenting a route to a priori prediction of disease progression in patients. Further, we show that the previous estimate of Ne>105 reduces as the frequencies of multiple infections of cells and recombination assumed increase. Our simulations with Ne∼10³-104 may be employed to estimate markers of disease progression and outcomes of therapy that depend on the evolution of viral diversity and divergence. [ABSTRACT FROM AUTHOR]

Next-generation DNA sequencing is increasingly being utilized to probe microbial communities, such as gastrointestinal microbiomes, where it is important to be able to quantify measures of abundance and diversity. The fragmented nature of the 16S rRNA datasets obtained, coupled with their unprecedented size, has led to the recognition that the results of such analyses are potentially contaminated by a variety of artifacts, both experimental and computational. Here we quantify how multiple alignment and clustering errors contribute to overestimates of abundance and diversity, reflected by incorrect OTU assignment, corrupted phylogenies, inaccurate species diversity estimators, and rank abundance distribution functions. We show that straightforward procedural optimizations, combining preexisting tools, are effective in handling large (105—106) 16S rRNA datasets, and we describe metrics to measure the effectiveness and quality of the estimators obtained. We introduce two metrics to ascertain the quality of clustering of pyrosequenced rRNA data, and show that complete linkage clustering greatly outperforms other widely used methods. [ABSTRACT FROM AUTHOR]

Background: The accumulation of deleterious mutations can drastically reduce population mean fitness. Self-fertilization is thought to be an effective means of purging deleterious mutations. However, widespread linkage disequilibrium generated and maintained by self-fertilization is predicted to reduce the efficacy of purging when mutations are present at multiple loci. Methodology/Principal Findings: We tested the ability of self-fertilizing populations to purge deleterious mutations at multiple loci by exposing obligately self-fertilizing populations of Caenorhabditis elegans to a range of elevated mutation rates and found that mutations accumulated, as evidenced by a reduction in mean fitness, in each population. Therefore, purging in obligate selfing populations is overwhelmed by an increase in mutation rate. Surprisingly, we also found that obligate and predominantly self-fertilizing populations exposed to very high mutation rates exhibited consistently greater fitness than those subject to lesser increases in mutation rate, which contradicts the assumption that increases in mutation rate are negatively correlated with fitness. The high levels of genetic linkage inherent in self-fertilization could drive this fitness increase. Conclusions: Compensatory mutations can be more frequent under high mutation rates and may alleviate a portion of the fitness lost due to the accumulation of deleterious mutations through epistatic interactions with deleterious mutations. The prolonged maintenance of tightly linked compensatory and deleterious mutations facilitated by self-fertilization may be responsible for the fitness increase as linkage disequilibrium between the compensatory and deleterious mutations preserves their epistatic interaction. [ABSTRACT FROM AUTHOR]

Background: Although genotypic resistance testing (GRT) is recommended to guide combination antiretroviral therapy (cART), funding and/or facilities to perform GRT may not be available in low to middle income countries. Since treatment history (TH) impacts response to subsequent therapy, we investigated a set of statistical learning models to optimise cART in the absence of GRT information. Methods and Findings: The EuResist database was used to extract 8-week and 24-week treatment change episodes (TCE) with GRT and additional clinical, demographic and TH information. Random Forest (RF) classification was used to predict 8- and 24-week success, defined as undetectable HIV-1 RNA, comparing nested models including (i) GRT+TH and (ii) TH without GRT, using multiple cross-validation and area under the receiver operating characteristic curve (AUC). Virological success was achieved in 68.2% and 68.0% of TCE at 8- and 24-weeks (n = 2,831 and 2,579), respectively. RF (i) and (ii) showed comparable performances, with an average (st.dev.) AUC 0.77 (0.031) vs. 0.757 (0.035) at 8-weeks, 0.834 (0.027) vs. 0.821 (0.025) at 24-weeks. Sensitivity analyses, carried out on a data subset that included antiretroviral regimens commonly used in low to middle income countries, confirmed our findings. Training on subtype B and validation on non-B isolates resulted in a decline of performance for models (i) and (ii). Conclusions: Treatment history-based RF prediction models are comparable to GRT-based for classification of virological outcome. These results may be relevant for therapy optimisation in areas where availability of GRT is limited. Further investigations are required in order to account for different demographics, subtypes and different therapy switching strategies. [ABSTRACT FROM AUTHOR]

Background: Identifying causal relationships in phylogeographic and landscape genetic investigations is notoriously difficult, but can be facilitated by use of multispecies comparisons. Methodology/Principal Findings: We used data visualizations to identify common spatial patterns within single lineages of four taxa inhabiting Pacific Northwest forests (northern spotted owl: Strix occidentalis caurina; red tree vole: Arborimus longicaudus; southern torrent salamander: Rhyacotriton variegatus; and western white pine: Pinus monticola). Visualizations suggested that, despite occupying the same geographical region and habitats, species responded differently to prevailing historical processes. S. o. caurina and P. monticola demonstrated directional patterns of spatial genetic structure where genetic distances and diversity were greater in southern versus northern locales. A. longicaudus and R. variegatus displayed opposite patterns where genetic distances were greater in northern versus southern regions. Statistical analyses of directional patterns subsequently confirmed observations from visualizations. Based upon regional climatological history, we hypothesized that observed latitudinal patterns may have been produced by range expansions. Subsequent computer simulations confirmed that directional patterns can be produced by expansion events. Conclusions/Significance: We discuss phylogeographic hypotheses regarding historical processes that may have produced observed patterns. Inferential methods used here may become increasingly powerful as detailed simulations of organisms and historical scenarios become plausible. We further suggest that inter-specific comparisons of historical patterns take place prior to drawing conclusions regarding effects of current anthropogenic change within landscapes. [ABSTRACT FROM AUTHOR]

Background: Phylogenetic methods produce hierarchies of molecular species, inferring knowledge about taxonomy and evolution. However, there is not yet a consensus methodology that provides a crisp partition of taxa, desirable when considering the problem of intra/inter-patient quasispecies classification or infection transmission event identification. We introduce the threshold bootstrap clustering (TBC), a new methodology for partitioning molecular sequences, that does not require a phylogenetic tree estimation. Methodology/Principal Findings: The TBC is an incremental partition algorithm, inspired by the stochastic Chinese restaurant process, and takes advantage of resampling techniques and models of sequence evolution. TBC uses as input a multiple alignment of molecular sequences and its output is a crisp partition of the taxa into an automatically determined number of clusters. By varying initial conditions, the algorithm can produce different partitions. We describe a procedure that selects a prime partition among a set of candidate ones and calculates a measure of cluster reliability. TBC was successfully tested for the identification of type-1 human immunodeficiency and hepatitis C virus subtypes, and compared with previously established methodologies. It was also evaluated in the problem of HIV-1 intra-patient quasispecies clustering, and for transmission cluster identification, using a set of sequences from patients with known transmission event histories. Conclusion: TBC has been shown to be effective for the subtyping of HIV and HCV, and for identifying intra-patient quasispecies. To some extent, the algorithm was able also to infer clusters corresponding to events of infection transmission. The computational complexity of TBC is quadratic in the number of taxa, lower than other established methods; in addition, TBC has been enhanced with a measure of cluster reliability. The TBC can be useful to characterise molecular quasipecies in a broad context. [ABSTRACT FROM AUTHOR]

A major computational challenge in the genomic era is annotating structure/function to the vast quantities of sequence information that is now available. This problem is illustrated by the fact that most proteins lack comprehensive annotations, even when experimental evidence exists. We previously theorized that embedded-alignment profiles (simply "alignment profiles" hereafter) provide a quantitative method that is capable of relating the structural and functional properties of proteins, as well as their evolutionary relationships. A key feature of alignment profiles lies in the interoperability of data format (e.g., alignment information, physio-chemical information, genomic information, etc.). Indeed, we have demonstrated that the Position Specific Scoring Matrices (PSSMs) are an informative M-dimension that is scored by quantitatively measuring the embedded or unmodified sequence alignments. Moreover, the information obtained from these alignments is informative, and remains so even in the "twilight zone" of sequence similarity (<25% identity) [1-5]. Although our previous embedding strategy was powerful, it suffered from contaminating alignments (embedded AND unmodified) and high computational costs. Herein, we describe the logic and algorithmic process for a heuristic embedding strategy named "Adaptive GDDA-BLAST." Adaptive GDDA-BLAST is, on average, up to 19 times faster than, but has similar sensitivity to our previous method. Further, data are provided to demonstrate the benefits of embedded-alignment measurements in terms of detecting structural homology in highly divergent protein sequences and isolating secondary structural elements of transmembrane and ankyrin-repeat domains. Together, these advances allow further exploration of the embedded alignment data space within sufficiently large data sets to eventually induce relevant statistical inferences. We show that sequence embedding could serve as one of the vehicles for measurement of low-identity alignments and for incorporation thereof into high-performance PSSM-based alignment profiles. [ABSTRACT FROM AUTHOR]

Background: Many software packages have been developed to address the need for generating phylogenetic trees intended for print. With an increased use of the web to disseminate scientific literature, there is a need for phylogenetic trees to be viewable across many types of devices and feature some of the interactive elements that are integral to the browsing experience. We propose a novel approach for publishing interactive phylogenetic trees. Methods/Principal Findings: We present a javascript library, jsPhyloSVG, which facilitates constructing interactive phylogenetic trees from raw Newick or phyloXML formats directly within the browser in Scalable Vector Graphics (SVG) format. It is designed to work across all major browsers and renders an alternative format for those browsers that do not support SVG. The library provides tools for building rectangular and circular phylograms with integrated charting. Interactive features may be integrated and made to respond to events such as clicks on any element of the tree, including labels. Conclusions/Significance: jsPhyloSVG is an open-source solution for rendering dynamic phylogenetic trees. It is capable of generating complex and interactive phylogenetic trees across all major browsers without the need for plugins. It is novel in supporting the ability to interpret the tree inference formats directly, exposing the underlying markup to data-mining services. The library source code, extensive documentation and live examples are freely accessible at www.jsphylosvg.com. [ABSTRACT FROM AUTHOR]

Background: Due to the advances of high throughput technology and data-collection approaches, we are now in an unprecedented position to understand the evolution of organisms. Great efforts have characterized many individual genes responsible for the interspecies divergence, yet little is known about the genome-wide divergence at a higher level. Modules, serving as the building blocks and operational units of biological systems, provide more information than individual genes. Hence, the comparative analysis between species at the module level would shed more light on the mechanisms underlying the evolution of organisms than the traditional comparative genomics approaches. Results: We systematically identified the tissue-related modules using the iterative signature algorithm (ISA), and we detected 52 and 65 modules in the human and mouse genomes, respectively. The gene expression patterns indicate that all of these predicted modules have a high possibility of serving as real biological modules. In addition, we defined a novel quantity, "total constraint intensity," a proxy of multiple constraints (of co-regulated genes and tissues where the coregulation occurs) on the evolution of genes in module context. We demonstrate that the evolutionary rate of a gene is negatively correlated with its total constraint intensity. Furthermore, there are modules coding the same essential biological processes, while their gene contents have diverged extensively between human and mouse. Conclusions: Our results suggest that unlike the composition of module, which exhibits a great difference between human and mouse, the functional organization of the corresponding modules may evolve in a more conservative manner. Most importantly, our findings imply that similar biological processes can be carried out by different sets of genes from human and mouse, therefore, the functional data of individual genes from mouse may not apply to human in certain occasions. [ABSTRACT FROM AUTHOR]

The single rate codon model of non-synonymous substitution is ubiquitous in phylogenetic modeling. Indeed, the use of a non-synonymous to synonymous substitution rate ratio parameter has facilitated the interpretation of selection pressure on genomes. Although the single rate model has achieved wide acceptance, we argue that the assumption of a single rate of non-synonymous substitution is biologically unreasonable, given observed differences in substitution rates evident from empirical amino acid models. Some have attempted to incorporate amino acid substitution biases into models of codon evolution and have shown improved model performance versus the single rate model. Here, we show that the single rate model of non-synonymous substitution is easily outperformed by a model with multiple non-synonymous rate classes, yet in which amino acid substitution pairs are assigned randomly to these classes. We argue that, since the single rate model is so easy to improve upon, new codon models should not be validated entirely on the basis of improved model fit over this model. Rather, we should strive to both improve on the single rate model and to approximate the general time-reversible model of codon substitution, with as few parameters as possible, so as to reduce model over-fitting. We hint at how this can be achieved with a Genetic Algorithm approach in which rate classes are assigned on the basis of sequence information content. [ABSTRACT FROM AUTHOR]

In 1977, H1N1 influenza A virus reappeared after a 20-year absence. Genetic analysis indicated that this strain was missing decades of nucleotide sequence evolution, suggesting an accidental release of a frozen laboratory strain into the general population. Recently, this strain and its descendants were included in an analysis attempting to date the origin of pandemic influenza virus without accounting for the missing decades of evolution. Here, we investigated the effect of using viral isolates with biologically unrealistic sampling dates on estimates of divergence dates. Not accounting for missing sequence evolution produced biased results and increased the variance of date estimates of the most recent common ancestor of the re-emergent lineages and across the entire phylogeny. Reanalysis of the H1N1 sequences excluding isolates with unrealistic sampling dates indicates that the 1977 re-emergent lineage was circulating for approximately one year before detection, making it difficult to determine the geographic source of reintroduction. We suggest that a new method is needed to account for viral isolates with unrealistic sampling dates. [ABSTRACT FROM AUTHOR]

Background: Phenotypic differences among species have long been systematically itemized and described by biologists in the process of investigating phylogenetic relationships and trait evolution. Traditionally, these descriptions have been expressed in natural language within the context of individual journal publications or monographs. As such, this rich store of phenotype data has been largely unavailable for statistical and computational comparisons across studies or integration with other biological knowledge. Methodology/Principal Findings: Here we describe Phenex, a platform-independent desktop application designed to facilitate efficient and consistent annotation of phenotypic similarities and differences using Entity-Quality syntax, drawing on terms from community ontologies for anatomical entities, phenotypic qualities, and taxonomic names. Phenex can be configured to load only those ontologies pertinent to a taxonomic group of interest. The graphical user interface was optimized for evolutionary biologists accustomed to working with lists of taxa, characters, character states, and characterby- taxon matrices. Conclusions/Significance: Annotation of phenotypic data using ontologies and globally unique taxonomic identifiers will allow biologists to integrate phenotypic data from different organisms and studies, leveraging decades of work in systematics and comparative morphology. [ABSTRACT FROM AUTHOR]

Piscidins constitute a family of cationic antimicrobial peptides that are thought to play an important role in the innate immune response of teleosts. On the one hand they show a remarkable diversity, which indicates that they are shaped by positive selection, but on the other hand they are ancient and have specific targets, suggesting that they are constrained by purifying selection. Until now piscidins had only been found in fish species from the superorder Acanthopterygii but we have recently identified a piscidin gene in Atlantic cod (Gadus morhua), thus showing that these antimicrobial peptides are not restricted to evolutionarily modern teleosts. Nucleotide diversity was much higher in the regions of the piscidin gene that code for the mature peptide and its pro domain than in the signal peptide. Maximum likelihood analyses with different evolution models revealed that the piscidin gene is under positive selection. Charge or hydrophobicity-changing amino acid substitutions observed in positively selected sites within the mature peptide influence its amphipathic structure and can have a marked effect on its function. This diversification might be associated with adaptation to new habitats or rapidly evolving pathogens. [ABSTRACT FROM AUTHOR]

Background: We recently described FastTree, a tool for inferring phylogenies for alignments with up to hundreds of thousands of sequences. Here, we describe improvements to FastTree that improve its accuracy without sacrificing scalability. Methodology/Principal Findings: Where FastTree 1 used nearest-neighbor interchanges (NNIs) and the minimum-evolution criterion to improve the tree, FastTree 2 adds minimum-evolution subtree-pruning-regrafting (SPRs) and maximum-likelihood NNIs. FastTree 2 uses heuristics to restrict the search for better trees and estimates a rate of evolution for each site (the ''CAT'' approximation). Nevertheless, for both simulated and genuine alignments, FastTree 2 is slightly more accurate than a standard implementation of maximum-likelihood NNIs (PhyML 3 with default settings). Although FastTree 2 is not quite as accurate as methods that use maximum-likelihood SPRs, most of the splits that disagree are poorly supported, and for large alignments, FastTree 2 is 100-1,000 times faster. FastTree 2 inferred a topology and likelihood-based local support values for 237,882 distinct 16S ribosomal RNAs on a desktop computer in 22 hours and 5.8 gigabytes of memory. Conclusions/Significance: FastTree 2 allows the inference of maximum-likelihood phylogenies for huge alignments. FastTree 2 is freely available at http://www.microbesonline.org/fasttree. [ABSTRACT FROM AUTHOR]

Background: There is widespread concern that H5N1 avian influenza A viruses will emerge as a pandemic threat, if they become capable of human-to-human (H2H) transmission. Avian strains lack this capability, which suggests that it requires important adaptive mutations. We performed a large-scale comparative analysis of proteins from avian and human strains, to produce a catalogue of mutations associated with H2H transmissibility, and to detect their presence in avian isolates. Methodology/Principal Findings: We constructed a dataset of influenza A protein sequences from 92,343 public database records. Human and avian sequence subsets were compared, using a method based on mutual information, to identify characteristic sites where human isolates present conserved mutations. The resulting catalogue comprises 68 characteristic sites in eight internal proteins. Subtype variability prevented the identification of adaptive mutations in the hemagglutinin and neuraminidase proteins. The high number of sites in the ribonucleoprotein complex suggests interdependence between mutations in multiple proteins. Characteristic sites are often clustered within known functional regions, suggesting their functional roles in cellular processes. By isolating and concatenating characteristic site residues, we defined adaptation signatures, which summarize the adaptive potential of specific isolates. Most adaptive mutations emerged within three decades after the 1918 pandemic, and have remained remarkably stable thereafter. Two lineages with stable internal protein constellations have circulated among humans without reassorting. On the contrary, H5N1 avian and swine viruses reassort frequently, causing both gains and losses of adaptive mutations. Conclusions: Human host adaptation appears to be complex and systemic, involving nearly all influenza proteins. Adaptation signatures suggest that the ability of H5N1 strains to infect humans is related to the presence of an unusually high number of adaptive mutations. However, these mutations appear unstable, suggesting low pandemic potential of H5N1 in its current form. In addition, adaptation signatures indicate that pandemic H1N1/09 strain possesses multiple human-transmissibility mutations, though not an unusually high number with respect to swine strains that infected humans in the past. Adaptation signatures provide a novel tool for identifying zoonotic strains with the potential to infect humans. [ABSTRACT FROM AUTHOR]

The article focuses on a study on the haplotype distribution and evolutionary network of miR-17 and miR-124 families of microRNAs (miRNAs) across the animal kingdom. It states that miRNAs are non-protein-coding small RNAs that regulate mRNAs post-transcriptionally in animals and plants. The study found 31 haplotypes in the miR-17 family and only 9 haplotypes in the miR-124 family. The miR-17 family was found to be distributed in vertebrates, but the miR-124 family was shared by more animal species and had a wide distribution spectrum.

The article focuses on a study which describe a functional analogy to a common morphological process in human speech, affixation, in the alarm calls of free-ranging adult Campbell's monkeys. According to the results of the study, male alarm calls are composed of an acoustically variable stem, which can be followed by an acoustically invariable suffix. It is mentioned that the study concluded, non-human primates can generate meaningful acoustic variation during call production that is functionally equivalent to suffixation in human language.

In the more than twenty years since its discovery, both the phylogenetic origin and cellular function of the prion protein (PrP) have remained enigmatic. Insights into a possible function of PrP may be obtained through the characterization of its molecular neighborhood in cells. Quantitative interactome data demonstrated the spatial proximity of two metal ion transporters of the ZIP family, ZIP6 and ZIP10, to mammalian prion proteins in vivo. A subsequent bioinformatic analysis revealed the unexpected presence of a PrP-like amino acid sequence within the N-terminal, extracellular domain of a distinct sub-branch of the ZIP protein family that includes ZIP5, ZIP6 and ZIP10. Additional structural threading and orthologous sequence alignment analyses argued that the prion gene family is phylogenetically derived from a ZIP-like ancestral molecule. The level of sequence homology and the presence of prion protein genes in most chordate species place the split from the ZIP-like ancestor gene at the base of the chordate lineage. This relationship explains structural and functional features found within mammalian prion proteins as elements of an ancient involvement in the transmembrane transport of divalent cations. The phylogenetic and spatial connection to ZIP proteins is expected to open new avenues of research to elucidate the biology of the prion protein in health and disease. [ABSTRACT FROM AUTHOR]

Genetic structure due to ancestry has been well documented among many divergent human populations. However, the ability to associate ancestry with genetic substructure without using supervised clustering has not been explored in more presumably homogeneous and admixed US populations. The goal of this study was to determine if genetic structure could be detected in a United States population from a single state where the individuals have mixed European ancestry. Using Bayesian clustering with a set of 960 single nucleotide polymorphisms (SNPs) we found evidence of population stratification in 864 individuals from New Hampshire that can be used to differentiate the population into six distinct genetic subgroups. We then correlated self-reported ancestry of the individuals with the Bayesian clustering results. Finnish and Russian/Polish/ Lithuanian ancestries were most notably found to be associated with genetic substructure. The ancestral results were further explained and substantiated using New Hampshire census data from 1870 to 1930 when the largest waves of European immigrants came to the area. We also discerned distinct patterns of linkage disequilibrium (LD) between the genetic groups in the growth hormone receptor gene (GHR). To our knowledge, this is the first time such an investigation has uncovered a strong link between genetic structure and ancestry in what would otherwise be considered a homogenous US population. [ABSTRACT FROM AUTHOR]

Background: Often described as an extremely rare zoonosis, cowpox virus (CPXV) infections are on the increase in Germany. CPXV is rodent-borne with a broad host range and contains the largest and most complete genome of all poxviruses, including parts with high homology to variola virus (smallpox). So far, most CPXV cases have occurred individually in unvaccinated animals and humans and were caused by genetically distinguishable virus strains. Methodology/Principal Findings: Generalized CPXV infections in banded mongooses (Mungos mungo) and jaguarundis (Herpailurus yagouaroundi) at a Zoological Garden were observed with a prevalence of the affected animal group of 100% and a mortality of 30%. A subsequent serological investigation of other exotic animal species provided evidence of subclinical cases before the onset of the outbreak. Moreover, a time-delayed human cowpox virus infection caused by the identical virus strain occurred in a different geographical area indicating that handling/feeding food rats might be the common source of infection. Conclusions/Significance: Reports on the increased zoonotic transmission of orthopoxviruses have renewed interest in understanding interactions between these viruses and their hosts. The list of animals known to be susceptible to CPXV is still growing. Thus, the likely existence of unknown CPXV hosts and their distribution may present a risk for other exotic animals but also for the general public, as was shown in this outbreak. Animal breeders and suppliers of food rats represent potential multipliers and distributors of CPXV, in the context of increasingly pan-European trading. Taking the cessation of vaccination against smallpox into account, this situation contributes to the increased incidence of CPXV infections in man, particularly in younger age groups, with more complicated courses of clinical infections. [ABSTRACT FROM AUTHOR]

Background: Microsatellites have been used extensively in the field of comparative genomics. By studying microsatellites in coding regions we have a simple model of how genotypic changes undergo selection as they are directly expressed in the phenotype as altered proteins. The simplest of these tandem repeats in coding regions are the tri-nucleotide repeats which produce a repeat of a single amino acid when translated into proteins. Tri-nucleotide repeats are often disease associated, and are also known to be unstable to both expansion and contraction. This makes them sensitive markers for studying proteome evolution, in closely related species. Results: The evolutionary history of the family of malarial causing parasites Plasmodia is complex because of the life-cycle of the organism, where it interacts with a number of different hosts and goes through a series of tissue specific stages. This study shows that the divergence between the primate and rodent malarial parasites has resulted in a lineage specific change in the simple amino acid repeat distribution that is correlated to A-T content. The paper also shows that this altered use of amino acids in SAARs is consistent with the repeat distributions being under selective pressure. Conclusions: The study shows that simple amino acid repeat distributions can be used to group related species and to examine their phylogenetic relationships. This study also shows that an outgroup species with a similar A-T content can be distinguished based only on the amino acid usage in repeats, and suggest that this might be a useful feature for proteome clustering. The lineage specific use of amino acids in repeat regions suggests that comparative studies of SAAR distributions between proteomes gives an insight into the mechanisms of expansion and the selective pressures acting on the organism. [ABSTRACT FROM AUTHOR]

Despite the effectiveness of direct-acting antiviral agents in treating hepatitis C virus (HCV), cases of treatment failure have been associated with the emergence of resistance-associated substitutions. To better guide clinical decision-making, we developed and validated a near-whole-genome HCV genotype-independent next-generation sequencing strategy. HCV genotype 1–6 samples from direct-acting antiviral agent treatment-naïve and -treated HCV-infected individuals were included. Viral RNA was extracted using a NucliSens easyMAG and amplified using nested reverse transcription-polymerase chain reaction. Libraries were prepared using Nextera XT and sequenced on the Illumina MiSeq sequencing platform. Data were processed by an in-house pipeline (MiCall). Nucleotide consensus sequences were aligned to reference strain sequences for resistance-associated substitution identification and compared to NS3, NS5a, and NS5b sequence data obtained from a validated in-house assay optimized for HCV genotype 1. Sequencing success rates (defined as achieving >100-fold read coverage) approaching 90% were observed for most genotypes in samples with a viral load >5 log10 IU/mL. This genotype-independent sequencing method resulted in >99.8% nucleotide concordance with the genotype 1-optimized method, and 100% agreement in genotype assignment with paired line probe assay-based genotypes. The assay demonstrated high intra-run repeatability and inter-run reproducibility at detecting substitutions above 2% prevalence. This study highlights the performance of a freely available laboratory and bioinformatic approach for reliable HCV genotyping and resistance-associated substitution detection regardless of genotype. [ABSTRACT FROM AUTHOR]

The transmission fitness and pathogenesis of HIV-1 is disproportionately influenced by evolution in the five variable regions (V1–V5) of the surface envelope glycoprotein (gp120). Insertions and deletions (indels) are a significant source of evolutionary change in these regions. However, the rate and composition of indels has not yet been quantified through a large-scale comparative analysis of HIV-1 sequences. Here, we develop and report results from a phylogenetic method to estimate indel rates for the gp120 variable regions across five major subtypes and two circulating recombinant forms (CRFs) of HIV-1 group M. We processed over 26,000 published HIV-1 gp120 sequences, from which we extracted 6,605 sequences for phylogenetic analysis. We reconstructed time-scaled phylogenies by maximum likelihood and fit a binomial-Poisson model to the observed distribution of indels between closely related pairs of sequences in each tree (cherries). By focusing on cherries in each tree, we obtained phylogenetically independent indel reconstructions, and the shorter time scales in cherries reduced the bias due to purifying selection. Rate estimates ranged from 3.0 × 10 − 5 to 1.5 × 10 − 3 indels/nt/year and varied significantly among variable regions and subtypes. Indel rates were significantly lower in V3 relative to V1, and were also lower in HIV-1 subtype B relative to the 01_AE reference. We also found that V1, V2, and V4 tended to accumulate significantly longer indels. Furthermore, we observed that the nucleotide composition of indels was distinct from the flanking sequence, with higher frequencies of G and lower frequencies of T. Indels affected N-linked glycosylation sites more often in V1 and V2 than expected by chance, consistent with positive selection on glycosylation patterns within these regions. These results represent the first comprehensive measures of indel rates in HIV-1 gp120 across multiple subtypes and CRFs, and identifies novel and unexpected patterns for further research in the molecular evolution of HIV-1. [ABSTRACT FROM AUTHOR]

Background: Our understanding of HIV-1 and antiretroviral treatment (ART) is strongly biased towards subtype B, the predominant subtype in North America and western Europe. Efforts to characterize the response to first-line treatments in other HIV-1 subtypes have been hindered by the availability of large study cohorts in resource-limited settings. To maximize our statistical power, we combined HIV-1 sequence and clinical data from every available study population associated with the Joint Clinical Research Centre (JCRC) in Uganda. These records were combined with contemporaneous ART-naive records from Uganda in the Stanford HIVdb database. Methods: Treatment failures were defined by the presence of HIV genotype records with sample collection dates after the ART start dates in the JCRC database. Drug resistances were predicted by the Stanford HIVdb algorithm, and HIV subtype classification and recombination detection was performed with SCUEAL. We used Bayesian network analysis to evaluate associations between drug exposures and subtypes, and binomial regression for associations with recombination. Results: This is the largest database of first-line treatment failures ( n = 1724 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$n=1724$$\end{document}) in Uganda to date, with a predicted statistical power of 80% to detect subtype associations at an odds ratio of ≥ 1.2 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\ge 1.2$$\end{document}. In the subset where drug regimen data were available, we observed that use of 3TC was associated with a higher rate of first line treatment failure, whereas regimens containing AZT and TDF were associated with reduced rates of failure. In the complete database, we found limited evidence of associations between HIV-1 subtypes and treatment failure, with the exception of a significantly lower frequency of failures among A/D recombinants that comprised about 7% of the population. First-line treatment failure was significantly associated with reduced numbers of recombination breakpoints across subtypes. Conclusions: Expanding access to first-line ART should confer the anticipated public health benefits in Uganda, despite known differences in the pathogenesis of HIV-1 subtypes. Furthermore, the impact of ART may actually be enhanced by frequent inter-subtype recombination in this region. [ABSTRACT FROM AUTHOR]

Reconstructing the early dynamics of the HIV-1 pandemic can provide crucial insights into the socioeconomic drivers of emerging infectious diseases in human populations, including the roles of urbanization and transportation networks. Current evidence indicates that the global pandemic comprising almost entirely of HIV-1/M originated around the 1920s in central Africa. However, these estimates are based on molecular clock estimates that are assumed to apply uniformly across the virus genome. There is growing evidence that recombination has played a significant role in the early history of the HIV-1 pandemic, such that different regions of the HIV-1 genome have different evolutionary histories. In this study, we have conducted a dated-tip analysis of all near full-length HIV-1/M genome sequences that were published in the GenBank database. We used a sliding window approach similar to the 'bootscanning' method for detecting breakpoints in inter-subtype recombinant sequences. We found evidence of substantial variation in estimated root dates among windows, with an estimated mean time to the most recent common ancestor of 1922. Estimates were significantly autocorrelated, which was more consistent with an early recombination event than with stochastic error variation in phylogenetic reconstruction and dating analyses. A piecewise regression analysis supported the existence of at least one recombination breakpoint in the HIV-1/M genome with interval-specific means around 1929 and 1913, respectively. This analysis demonstrates that a sliding window approach can accommodate early recombination events outside the established nomenclature of HIV-1/M subtypes, although it is difficult to incorporate the earliest available samples due to their limited genome coverage. [ABSTRACT FROM AUTHOR]

Background: The ability of HIV-1 to integrate into the genomes of quiescent host immune cells, establishing a long-lived latent viral reservoir (LVR), is the primary obstacle to curing these infections. Quantitative viral outgrowth assays (QVOAs) are the gold standard for estimating the size of the replication-competent HIV-1 LVR, measured by the number of infectious units per million (IUPM) cells. QVOAs are time-consuming because they rely on culturing replicate wells to amplify the production of virus antigen or nucleic acid to reproducibly detectable levels. Sequence analysis can reduce the required number of culture wells because the virus genetic diversity within the LVR provides an internal replication and dilution series. Here we develop a Bayesian method to jointly estimate the IUPM and variant frequencies (a measure of clonality) from the sequence diversity of QVOAs. Results: Using simulation experiments, we find our Bayesian approach confers significantly greater accuracy over current methods to estimate the IUPM, particularly for reduced numbers of QVOA replicates and/or increasing actual IUPM. Furthermore, we determine that the improvement in accuracy is greater with increasing genetic diversity in the sample population. We contrast results of these different methods applied to new HIV-1 sequence data derived from QVOAs from two individuals with suppressed viral loads from the Rakai Health Sciences Program in Uganda. Conclusions: Utilizing sequence variation has the additional benefit of providing information on the contribution of clonality of the LVR, where high clonality (the predominance of a single genetic variant) suggests a role for cell division in the long-term persistence of the reservoir. In addition, our Bayesian approach can be adapted to other limiting dilution assays where positive outcomes can be partitioned by their genetic heterogeneity, such as immune cell populations and other viruses. [ABSTRACT FROM AUTHOR]

The table of contents for the March 2015 issue of "Journal of Infectious Diseases" is presented.

454 pyrosequencing, a massively parallel sequencing (MPS) technology, is often used to study HIV genetic variation. However, the substantial mismatch error rate of the PCR required to prepare HIV-containing samples for pyrosequencing has limited the detection of rare variants within viral populations to those present above ~1%. To improve detection of rare variants, we varied PCR enzymes and conditions to identify those that combined high sensitivity with a low error rate. Substitution errors were found to vary up to 3-fold between the different enzymes tested. The sensitivity of each enzyme, which impacts the number of templates amplified for pyrosequencing, was shown to vary, although not consistently across genes and different samples. We also describe an amplicon-based method to improve the consistency of read coverage over stretches of the HIV-1 genome. Twenty-two primers were designed to amplify 11 overlapping amplicons in the HIV-1 clade B gag-pol and env gp120 coding regions to encompass 4.7 kb of the viral genome per sample at sensitivities as low as 0.01-0.2%. [ABSTRACT FROM AUTHOR]

The table of contents for the June 2013 issue of "Clinical Infectious Diseases" is presented.