Search

Due to genetic variation in the ancestor of two populations or two species, the divergence time for DNA sequences from two populations is variable along the genome. Within genomic segments all bases will share the same divergence—because they share a most recent common ancestor—when no recombination event has occurred to split them apart. The size of these segments of constant divergence depends on the recombination rate, but also on the speciation time, the effective population size of the ancestral population, as well as demographic effects and selection. Thus, inference of these parameters may be possible if we can decode the divergence times along a genomic alignment. Here, we present a new hidden Markov model that infers the changing divergence (coalescence) times along the genome alignment using a coalescent framework, in order to estimate the speciation time, the recombination rate, and the ancestral effective population size. The model is efficient enough to allow inference on whole-genome data sets. We first investigate the power and consistency of the model with coalescent simulations and then apply it to the whole-genome sequences of the two orangutan sub-species, Bornean (P. p. pygmaeus) and Sumatran (P. p. abelii) orangutans from the Orangutan Genome Project. We estimate the speciation time between the two sub-species to be thousand years ago and the effective population size of the ancestral orangutan species to be , consistent with recent results based on smaller data sets. We also report a negative correlation between chromosome size and ancestral effective population size, which we interpret as a signature of recombination increasing the efficacy of selection., Author Summary We present a hidden Markov model that uses variation in coalescence times between two distantly related populations, or closely related species, to infer population genetics parameters in ancestral population or species. The model infers the divergence times in segments along the alignment. Using coalescent simulations, we show that the model accurately estimates the divergence time between the two populations and the effective population size of the ancestral population. We apply the model to the recently sequenced orangutan sub-species and estimate their divergence time and the effective population size of their ancestor population.

Despite highly active antiretroviral therapy (HAART), AIDS related lymphoma (ARL) occurs at a significantly higher rate in patients infected with the Human Immunodeficiency Virus (HIV) than in the general population. HIV-infected macrophages are a known viral reservoir and have been shown to have lymphomagenic potential in SCID mice; therefore, there is an interest in determining if a viral component to lymphomagenesis also exists. We sequenced HIV-1 envelope gp120 clones obtained post mortem from several tumor and non-tumor tissues of two patients who died with AIDS-related Non-Hodgkin's lymphoma (ARL-NH). Similar results were found in both patients: 1) high-resolution phylogenetic analysis showed a significant degree of compartmentalization between lymphoma and non-lymphoma viral sub-populations while viral sub-populations from lymph nodes appeared to be intermixed within sequences from tumor and non-tumor tissues, 2) a 100-fold increase in the effective HIV population size in tumor versus non-tumor tissues was associated with the emergence of lymphadenopathy and aggressive metastatic ARL, and 3) HIV gene flow among lymph nodes, normal and metastatic tissues was non-random. The different population dynamics between the viruses found in tumors versus the non-tumor associated viruses suggest that there is a significant relationship between HIV evolution and lymphoma pathogenesis. Moreover, the study indicates that HIV could be used as an effective marker to study the origin and dissemination of lymphomas in vivo.

In recent years the functions that the p53 tumor suppressor plays in human biology have been greatly extended beyond “guardian of the genome.” Our studies of promoter response element sequences targeted by the p53 master regulatory transcription factor suggest a general role for this DNA damage and stress-responsive regulator in the control of human Toll-like receptor (TLR) gene expression. The TLR gene family mediates innate immunity to a wide variety of pathogenic threats through recognition of conserved pathogen-associated molecular motifs. Using primary human immune cells, we have examined expression of the entire TLR gene family following exposure to anti-cancer agents that induce the p53 network. Expression of all TLR genes, TLR1 to TLR10, in blood lymphocytes and alveolar macrophages from healthy volunteers can be induced by DNA metabolic stressors. However, there is considerable inter-individual variability. Most of the TLR genes respond to p53 via canonical as well as noncanonical promoter binding sites. Importantly, the integration of the TLR gene family into the p53 network is unique to primates, a recurrent theme raised for other gene families in our previous studies. Furthermore, a polymorphism in a TLR8 response element provides the first human example of a p53 target sequence specifically responsible for endogenous gene induction. These findings—demonstrating that the human innate immune system, including downstream induction of cytokines, can be modulated by DNA metabolic stress—have many implications for health and disease, as well as for understanding the evolution of damage and p53 responsive networks., Author Summary Among the most prominently studied regulators of gene function is the p53 tumor suppressor, which has many roles in human biology. The transcriptional master regulator p53 directly targets expression of >200 genes. Previously, we sought to define the p53 network in terms of functionality, specifically the ability of target response element sequences (REs) to support p53 transactivation. Here we identify p53 target canonical and noncanonical REs in the family of Toll-like Receptor (TLR) innate immune response genes and establish p53 regulation of most TLR genes. We address p53 responsiveness in primary human lymphocytes and alveolar macrophages collected from healthy volunteers. Notably, all TLR genes show responses to DNA damage, and most are p53-mediated. However, there is considerable variability between individuals, suggesting that DNA and p53 metabolic stresses can markedly differ in impact on the innate immune system as well as downstream appearance of cytokines. Indeed, we report a SNP in a p53 RE within the TLR8 promoter that alters p53 responsiveness in primary human cells. Furthermore, the p53-mediated expression of TLRs is unique to primates. Overall, these findings identify a new, pivotal role for the well-known human tumor suppressor p53, namely, integration of DNA damage and innate immune responses.

In the quest to reconstruct the Tree of Life, researchers have increasingly turned to phylogenomics, the inference of phylogenetic relationships using genome-scale data (Box 1). Mesmerized by the sustained increase in sequencing throughput, many phylogeneticists entertained the hope that the incongruence frequently observed in studies using single or a few genes [1] would come to an end with the generation of large multigene datasets. Yet, as so often happens, reality has turned out to be far more complex, as three recent large-scale analyses, one published in PLoS Biology [2]–[4], make clear. The studies, which deal with the early diversification of animals, produced highly incongruent (Box 2) findings despite the use of considerable sequence data (see Figure 1). Clearly, merely adding more sequences is not enough to resolve the inconsistencies.

13 páginas, 6 figuras, 4 tablas. Artículo OpenAccess, This paper proposes a new method to identify communities in generally weighted complex networks and apply it to phylogenetic analysis. In this case, weights correspond to the similarity indexes among protein sequences, which can be used for network construction so that the network structure can be analyzed to recover phylogenetically useful information from its properties. The analyses discussed here are mainly based on the modular character of protein similarity networks, explored through the Newman-Girvan algorithm, with the help of the neighborhood matrix . The most relevant networks are found when the network topology changes abruptly revealing distinct modules related to the sets of organisms to which the proteins belong. Sound biological information can be retrieved by the computational routines used in the network approach, without using biological assumptions other than those incorporated by BLAST. Usually, all the main bacterial phyla and, in some cases, also some bacterial classes corresponded totally (100%) or to a great extent (>70%) to the modules. We checked for internal consistency in the obtained results, and we scored close to 84% of matches for community pertinence when comparisons between the results were performed. To illustrate how to use the network-based method, we employed data for enzymes involved in the chitin metabolic pathway that are present in more than 100 organisms from an original data set containing 1,695 organisms, downloaded from GenBank on May 19, 2007. A preliminary comparison between the outcomes of the network-based method and the results of methods based on Bayesian, distance, likelihood, and parsimony criteria suggests that the former is as reliable as these commonly used methods. We conclude that the network-based method can be used as a powerful tool for retrieving modularity information from weighted networks, which is useful for phylogenetic analysis., National Council for Scientific and Technological Development (CNPq), Brasil (no. 306052/2007-5, no. 307140/2009-1, no. 304831/2007-7, no. 305176/2009-9 and no. 301259/2010-0). Beca JAE Predoctoral del Consejo Superior de Investigaciones Cientificas (CSIC), España.

Background Autism spectrum disorders (ASDs) are frequently occurring disorders diagnosed by deficits in three core functional areas: social skills, communication, and behaviours and/or interests. Mental retardation frequently accompanies the most severe forms of ASDs, while overall ASDs are more commonly diagnosed in males. Most ASDs have a genetic origin and one gene recently implicated in the etiology of autism is the Deleted-In-Autism-1 (DIA1) gene. Methodology/Principal Findings Using a bioinformatics-based approach, we have identified a human gene closely related to DIA1, we term DIA1R (DIA1-Related). While DIA1 is autosomal (chromosome 3, position 3q24), DIA1R localizes to the X chromosome at position Xp11.3 and is known to escape X-inactivation. The gene products are of similar size, with DIA1 encoding 430, and DIA1R 433, residues. At the amino acid level, DIA1 and DIA1R are 62% similar overall (28% identical), and both encode signal peptides for targeting to the secretory pathway. Both genes are ubiquitously expressed, including in fetal and adult brain tissue. Conclusions/Significance Examination of published literature revealed point mutations in DIA1R are associated with X-linked mental retardation (XLMR) and DIA1R deletion is associated with syndromes with ASD-like traits and/or XLMR. Together, these results support a model where the DIA1 and DIA1R gene products regulate molecular traffic through the cellular secretory pathway or affect the function of secreted factors, and functional deficits cause disorders with ASD-like symptoms and/or mental retardation.

When avian influenza viruses (AIVs) are transmitted from their reservoir hosts (wild waterfowl and shorebirds) to domestic bird species, they undergo genetic changes that have been linked to higher virulence and broader host range. Common genetic AIV modifications in viral proteins of poultry isolates are deletions in the stalk region of the neuraminidase (NA) and additions of glycosylation sites on the hemagglutinin (HA). Even though these NA deletion mutations occur in several AIV subtypes, they have not been analyzed comprehensively. In this study, 4,920 NA nucleotide sequences, 5,596 HA nucleotide and 4,702 HA amino acid sequences were analyzed to elucidate the widespread emergence of NA stalk deletions in gallinaceous hosts, the genetic polymorphism of the deletion patterns and association between the stalk deletions in NA and amino acid variants in HA. Forty-seven different NA stalk deletion patterns were identified in six NA subtypes, N1–N3 and N5–N7. An analysis that controlled for phylogenetic dependence due to shared ancestry showed that NA stalk deletions are statistically correlated with gallinaceous hosts and certain amino acid features on the HA protein. Those HA features included five glycosylation sites, one insertion and one deletion. The correlations between NA stalk deletions and HA features are HA-NA-subtype-specific. Our results demonstrate that stalk deletions in the NA proteins of AIV are relatively common. Understanding the NA stalk deletion and related HA features may be important for vaccine and drug development and could be useful in establishing effective early detection and warning systems for the poultry industry.

Large-scale parallel pyrosequencing produces unprecedented quantities of sequence data. However, when generated from viral populations current mapping software is inadequate for dealing with the high levels of variation present, resulting in the potential for biased data loss. In order to apply the 454 Life Sciences' pyrosequencing system to the study of viral populations, we have developed software for the processing of highly variable sequence data. Here we demonstrate our software by analyzing two temporally sampled HIV-1 intra-patient datasets from a clinical study of maraviroc. This drug binds the CCR5 coreceptor, thus preventing HIV-1 infection of the cell. The objective is to determine viral tropism (CCR5 versus CXCR4 usage) and track the evolution of minority CXCR4-using variants that may limit the response to a maraviroc-containing treatment regimen. Five time points (two prior to treatment) were available from each patient. We first quantify the effects of divergence on initial read k-mer mapping and demonstrate the importance of utilizing population-specific template sequences in relation to the analysis of next-generation sequence data. Then, in conjunction with coreceptor prediction algorithms that infer HIV tropism, our software was used to quantify the viral population structure pre- and post-treatment. In both cases, low frequency CXCR4-using variants (2.5–15%) were detected prior to treatment. Following phylogenetic inference, these variants were observed to exist as distinct lineages that were maintained through time. Our analysis, thus confirms the role of pre-existing CXCR4-using virus in the emergence of maraviroc-insensitive HIV. The software will have utility for the study of intra-host viral diversity and evolution of other fast evolving viruses, and is available from http://www.bioinf.manchester.ac.uk/segminator/., Author Summary Due to high data volumes, error rates, and short sequence lengths, new sequencing technologies present a new challenge for computational biology. In addition, high-depth (or ultra-deep) datasets, for example from pathogens, contain exceptionally large amounts of variation over short genomes or genomic regions. Here we present software for the processing and downstream analysis of such short-read viral sequence data. We apply the software to the analysis of two HIV-1 infected individuals who did not respond optimally to the drug maraviroc. For each patient, pyrosequence data was available for five time points. In both cases we detect distinct clusters of low-frequency drug-insensitive variants that were present prior to maraviroc treatment and effectively unmasked by the removal of the drug-sensitive HIV.

The computational detection of regulatory elements in DNA is a difficult but important problem impacting our progress in understanding the complex nature of eukaryotic gene regulation. Attempts to utilize cross-species conservation for this task have been hampered both by evolutionary changes of functional sites and poor performance of general-purpose alignment programs when applied to non-coding sequence. We describe a new and flexible framework for modeling binding site evolution in multiple related genomes, based on phylogenetic pair hidden Markov models which explicitly model the gain and loss of binding sites along a phylogeny. We demonstrate the value of this framework for both the alignment of regulatory regions and the inference of precise binding-site locations within those regions. As the underlying formalism is a stochastic, generative model, it can also be used to simulate the evolution of regulatory elements. Our implementation is scalable in terms of numbers of species and sequence lengths and can produce alignments and binding-site predictions with accuracy rivaling or exceeding current systems that specialize in only alignment or only binding-site prediction. We demonstrate the validity and power of various model components on extensive simulations of realistic sequence data and apply a specific model to study Drosophila enhancers in as many as ten related genomes and in the presence of gain and loss of binding sites. Different models and modeling assumptions can be easily specified, thus providing an invaluable tool for the exploration of biological hypotheses that can drive improvements in our understanding of the mechanisms and evolution of gene regulation., Author Summary The computational detection of regulatory elements in DNA is a difficult but important problem for decoding eukaryotic gene regulation. Increasing sequence data has made it possible to utilize related genomes, but this is not as straightforward as it may seem, as the evolution of noncoding regulatory regions is relatively poorly understood. In this work we describe a modeling framework and software implementation for aligning multiple DNA sequences to each other while simultaneously predicting functional regions in that DNA (such as the locations where proteins bind to the DNA for the purpose of regulating genes). Those functional regions may or may not be evolutionarily conserved across the sequences. Our framework allows for explicit modeling of evolutionary change across sequences in both the individual nucleotides making up the sequences and in the functional significance of the sequences (functional versus nonfunctional). While most competing frameworks and implementations are limited to a maximum number of sequences and their lengths, ours is scalable. We demonstrate the value of our system by using it to align a set of complex regulatory regions across ten Drosophila species and to predict protein-binding sites in those sequences.

Although overall pollinator populations have declined over the last couple of decades, the honey bee (Apis mellifera) malady, colony collapse disorder (CCD), has caused major concern in the agricultural community. Among honey bee pathogens, RNA viruses are emerging as a serious threat and are suspected as major contributors to CCD. Recent detection of these viral species in bumble bees suggests a possible wider environmental spread of these viruses with potential broader impact. It is therefore vital to study the ecology and epidemiology of these viruses in the hymenopteran pollinator community as a whole. We studied the viral distribution in honey bees, in their pollen loads, and in other non-Apis hymenopteran pollinators collected from flowering plants in Pennsylvania, New York, and Illinois in the United States. Viruses in the samples were detected using reverse transcriptase-PCR and confirmed by sequencing. For the first time, we report the molecular detection of picorna-like RNA viruses (deformed wing virus, sacbrood virus and black queen cell virus) in pollen pellets collected directly from forager bees. Pollen pellets from several uninfected forager bees were detected with virus, indicating that pollen itself may harbor viruses. The viruses in the pollen and honey stored in the hive were demonstrated to be infective, with the queen becoming infected and laying infected eggs after these virus-contaminated foods were given to virus-free colonies. These viruses were detected in eleven other non-Apis hymenopteran species, ranging from many solitary bees to bumble bees and wasps. This finding further expands the viral host range and implies a possible deeper impact on the health of our ecosystem. Phylogenetic analyses support that these viruses are disseminating freely among the pollinators via the flower pollen itself. Notably, in cases where honey bee apiaries affected by CCD harbored honey bees with Israeli Acute Paralysis virus (IAPV), nearby non-Apis hymenopteran pollinators also had IAPV, while those near apiaries without IAPV did not. In containment greenhouse experiments, IAPV moved from infected honey bees to bumble bees and from infected bumble bees to honey bees within a week, demonstrating that the viruses could be transmitted from one species to another. This study adds to our present understanding of virus epidemiology and may help explain bee disease patterns and pollinator population decline in general.

BackgroundHepatitis E virus (HEV) is an enterically transmitted hepatropic virus. It segregates as four genotypes. All genotypes infect humans while only genotypes 3 and 4 also infect several animal species. It has been suggested that hepatitis E is zoonotic, but no study has analyzed the evolutionary history of HEV. We present here an analysis of the evolutionary history of HEV.Methods and findingsThe times to the most recent common ancestors for all four genotypes of HEV were calculated using BEAST to conduct a Bayesian analysis of HEV. The population dynamics for genotypes 1, 3 and 4 were analyzed using skyline plots. Bayesian analysis showed that the most recent common ancestor for modern HEV existed between 536 and 1344 years ago. The progenitor of HEV appears to have given rise to anthropotropic and enzootic forms of HEV, which evolved into genotypes 1 and 2 and genotypes 3 and 4, respectively. Population dynamics suggest that genotypes 1, 3 and 4 experienced a population expansion during the 20(th) century. Genotype 1 has increased in infected population size ∼30-35 years ago. Genotype 3 and 4 have experienced an increase in population size starting late in the 19(th) century until ca.1940-45, with genotype 3 having undergone additional rapid expansion until ca.1960. The effective population size for both genotype 3 and 4 rapidly declined to pre-expansion levels starting in ca.1990. Genotype 4 was further examined as Chinese and Japanese sequences, which exhibited different population dynamics, suggesting that this genotype experienced different evolutionary history in these two countries.ConclusionsHEV appears to have evolved through a series of steps, in which the ancestors of HEV may have adapted to a succession of animal hosts leading to humans. Analysis of the population dynamics of HEV suggests a substantial temporal variation in the rate of transmission among HEV genotypes in different geographic regions late in the 20(th) Century.

Background In the process of protein evolution, sequence variations within protein families can cause changes in protein structures and functions. However, structures tend to be more conserved than sequences and functions. This leads to an intriguing question: what is the evolutionary mechanism by which sequence variations produce structural changes? To investigate this question, we focused on the most common types of sequence variations: amino acid substitutions and insertions/deletions (indels). Here their combined effects on protein structure evolution within protein families are studied. Results Sequence-structure correlation analysis on 75 homologous structure families (from SCOP) that contain 20 or more non-redundant structures shows that in most of these families there is, statistically, a bilinear correlation between the amount of substitutions and indels versus the degree of structure variations. Bilinear regression of percent sequence non-identity (PNI) and standardized number of gaps (SNG) versus RMSD was performed. The coefficients from the regression analysis could be used to estimate the structure changes caused by each unit of substitution (structural substitution sensitivity, SSS) and by each unit of indel (structural indel sensitivity, SIDS). An analysis on 52 families with high bilinear fitting multiple correlation coefficients and statistically significant regression coefficients showed that SSS is mainly constrained by disulfide bonds, which almost have no effects on SIDS. Conclusions Structural changes in homologous protein families could be rationally explained by a bilinear model combining amino acid substitutions and indels. These results may further improve our understanding of the evolutionary mechanisms of protein structures.

Computational methods attempting to identify instances of cis-regulatory modules (CRMs) in the genome face a challenging problem of searching for potentially interacting transcription factor binding sites while knowledge of the specific interactions involved remains limited. Without a comprehensive comparison of their performance, the reliability and accuracy of these tools remains unclear. Faced with a large number of different tools that address this problem, we summarized and categorized them based on search strategy and input data requirements. Twelve representative methods were chosen and applied to predict CRMs from the Drosophila CRM database REDfly, and across the human ENCODE regions. Our results show that the optimal choice of method varies depending on species and composition of the sequences in question. When discriminating CRMs from non-coding regions, those methods considering evolutionary conservation have a stronger predictive power than methods designed to be run on a single genome. Different CRM representations and search strategies rely on different CRM properties, and different methods can complement one another. For example, some favour homotypical clusters of binding sites, while others perform best on short CRMs. Furthermore, most methods appear to be sensitive to the composition and structure of the genome to which they are applied. We analyze the principal features that distinguish the methods that performed well, identify weaknesses leading to poor performance, and provide a guide for users. We also propose key considerations for the development and evaluation of future CRM-prediction methods., Author Summary Transcriptional regulation involves multiple transcription factors binding to DNA sequences. A limited repertoire of transcription factors performs this complex regulatory step through various spatial and temporal interactions between themselves and their binding sites. These transcription factor binding interactions are clustered as distinct modules: cis-regulatory modules (CRMs). Computational methods attempting to identify instances of CRMs in the genome face a challenging problem because a majority of these interactions between transcription factors remain unknown. To investigate the reliability and accuracy of these methods, we chose twelve representative methods and applied them to predict CRMs on both the fly and human genomes. Our results show that the optimal choice of method varies depending on species and composition of the sequences in question. Different CRM representations and search strategies rely on different CRM properties, and different methods can complement one another. We provide a guide for users and key considerations for developers. We also expect that, along with new technology generating new types of genomic data, future CRM prediction methods will be able to reveal transcription binding interactions in three-dimensional space.

BackgroundA fraction of the Neanderthal mitochondrial genome sequence has a similarity with a 5,839-bp nuclear DNA sequence of mitochondrial origin (numt) on the human chromosome 1. This fact has never been interpreted. Although this phenomenon may be attributed to contamination and mosaic assembly of Neanderthal mtDNA from short sequencing reads, we explain the mysterious similarity by integration of this numt (mtAncestor-1) into the nuclear genome of the common ancestor of Neanderthals and modern humans not long before their reproductive split.Principal findingsExploiting bioinformatics, we uncovered an additional numt (mtAncestor-2) with a high similarity to the Neanderthal mtDNA and indicated that both numts represent almost identical replicas of the mtDNA sequences ancestral to the mitochondrial genomes of Neanderthals and modern humans. In the proteins, encoded by mtDNA, the majority of amino acids distinguishing chimpanzees from humans and Neanderthals were acquired by the ancestral hominins. The overall rate of nonsynonymous evolution in Neanderthal mitochondrial protein-coding genes is not higher than in other lineages. The model incorporating the ancestral hominin mtDNA sequences estimates the average divergence age of the mtDNAs of Neanderthals and modern humans to be 450,000-485,000 years. The mtAncestor-1 and mtAncestor-2 sequences were incorporated into the nuclear genome approximately 620,000 years and 2,885,000 years ago, respectively.ConclusionsThis study provides the first insight into the evolution of the mitochondrial DNA in hominins ancestral to Neanderthals and humans. We hypothesize that mtAncestor-1 and mtAncestor-2 are likely to be molecular fossils of the mtDNAs of Homo heidelbergensis and a stem Homo lineage. The d(N)/d(S) dynamics suggests that the effective population size of extinct hominins was low. However, the hominin lineage ancestral to humans, Neanderthals and H. heidelbergensis, had a larger effective population size and possessed genetic diversity comparable with those of chimpanzee and gorilla.

The phylogeny and taxonomy of mammalian species were originally based upon shared or derived morphological characteristics. However, genetic analyses have more recently played an increasingly important role in confirming existing or establishing often radically different mammalian groupings and phylogenies. The two most commonly used genetic loci in species identification are the cytochrome oxidase I gene (COI) and the cytochrome b gene (cyt b). For the first time this study provides a detailed comparison of the effectiveness of these two loci in reconstructing the phylogeny of mammals at different levels of the taxonomic hierarchy in order to provide a basis for standardizing methodologies in the future. Interspecific and intraspecific variation is assessed and for the first time, to our knowledge, statistical confidence is applied to sequence comparisons. Comparison of the DNA sequences of 217 mammalian species reveals that cyt b more accurately reconstructs their phylogeny and known relationships between species based on other molecular and morphological analyses at Super Order, Order, Family and generic levels. Cyt b correctly assigned 95.85% of mammal species to Super Order, 94.31% to Order and 98.16% to Family compared to 78.34%, 93.36% and 96.93% respectively for COI. Cyt b also gives better resolution when separating species based on sequence data. Using a Kimura 2-parameter p-distance (x100) threshold of 1.5–2.5, cyt b gives a better resolution for separating species with a lower false positive rate and higher positive predictive value than those of COI.

Background: Phylogenetic study of protein sequences provides unique and valuable insights into the molecular and genetic basis of important medical and epidemiological problems as well as insights about the origins and development of physiological features in present day organisms. Consensus phylogenies based on the bootstrap and other resampling methods play a crucial part in analyzing the robustness of the trees produced for these analyses. Methodology: Our focus was to increase the number of bootstrap replications that can be performed on large protein datasets using the maximum parsimony, distance matrix, and maximum likelihood methods. We have modified the PHYLIP package using MPI to enable large-scale phylogenetic study of protein sequences, using a statistically robust number of bootstrapped datasets, to be performed in a moderate amount of time. This paper discusses the methodology used to parallelize the PHYLIP programs and reports the performance of the parallel PHYLIP programs that are relevant to the study of protein evolution on several protein datasets. Conclusions: Calculations that currently take a few days on a state of the art desktop workstation are reduced to calculations that can be performed over lunchtime on a modern parallel computer. Of the three protein methods tested, the maximum likelihood method scales the best, followed by the distance method, and then the maximum parsimony method. However, the maximum likelihood method requires significant memory resources, which limits its application to more moderately sized protein datasets.

The frequent dispensability of duplicated genes in budding yeast is heralded as a hallmark of genetic robustness contributed by genetic redundancy. However, theoretical predictions suggest such backup by redundancy is evolutionarily unstable, and the extent of genetic robustness contributed from redundancy remains controversial. It is anticipated that, to achieve mutual buffering, the duplicated paralogs must at least share some functional overlap. However, counter-intuitively, several recent studies reported little functional redundancy between these buffering duplicates. The large yeast genetic interactions released recently allowed us to address these issues on a genome-wide scale. We herein characterized the synthetic genetic interactions for ∼500 pairs of yeast duplicated genes originated from either whole-genome duplication (WGD) or small-scale duplication (SSD) events. We established that functional redundancy between duplicates is a pre-requisite and thus is highly predictive of their backup capacity. This observation was particularly pronounced with the use of a newly introduced metric in scoring functional overlap between paralogs on the basis of gene ontology annotations. Even though mutual buffering was observed to be prevalent among duplicated genes, we showed that the observed backup capacity is largely an evolutionarily transient state. The loss of backup capacity generally follows a neutral mode, with the buffering strength decreasing in proportion to divergence time, and the vast majority of the paralogs have already lost their backup capacity. These observations validated previous theoretic predictions about instability of genetic redundancy. However, departing from the general neutral mode, intriguingly, our analysis revealed the presence of natural selection in stabilizing functional overlap between SSD pairs. These selected pairs, both WGD and SSD, tend to have decelerated functional evolution, have higher propensities of co-clustering into the same protein complexes, and share common interacting partners. Our study revealed the general principles for the long-term retention of genetic redundancy., Author Summary Eukaryotic cells show remarkable robustness against external perturbations, which has been thought to be attributed, at least in part, to the extensive gene duplication events in eukaryotic genomes. By duplication, genes are likely to gain redundant copies for backup purposes, however, this notion contradicts the population genetic theory that genetic redundancy is evolutionarily unstable. In this study, we used yeast as a model organism to delineate the evolutionary trajectory of genetic robustness by gene duplication, utilizing the comprehensively characterized synthetic genetic interaction data in the yeast genome. We showed that the evolution of genetic robustness by duplication follows a neutral mode, with the loss of backup capacity proportional to the divergence time. However, natural selection was also acting on a few pairs to maintain their long-term backup capacity; and these pairs are slowly evolving, are co-clustered in the same protein complexes, and tend to interact with the similar partners. This study unravels the general principles underlying the evolution of the cellular robustness arising from genetic redundancy.

Two bursts of gene gains occurred on the mammalian X chromosome contribute to an age-dependent chromosomal distribution of male-biased genes., Mammalian X chromosomes evolved under various mechanisms including sexual antagonism, the faster-X process, and meiotic sex chromosome inactivation (MSCI). These forces may contribute to nonrandom chromosomal distribution of sex-biased genes. In order to understand the evolution of gene content on the X chromosome and autosome under these forces, we dated human and mouse protein-coding genes and miRNA genes on the vertebrate phylogenetic tree. We found that the X chromosome recently acquired a burst of young male-biased genes, which is consistent with fixation of recessive male-beneficial alleles by sexual antagonism. For genes originating earlier, however, this pattern diminishes and finally reverses with an overrepresentation of the oldest male-biased genes on autosomes. MSCI contributes to this dynamic since it silences X-linked old genes but not X-linked young genes. This demasculinization process seems to be associated with feminization of the X chromosome with more X-linked old genes expressed in ovaries. Moreover, we detected another burst of gene originations after the split of eutherian mammals and opossum, and these genes were quickly incorporated into transcriptional networks of multiple tissues. Preexisting X-linked genes also show significantly higher protein-level evolution during this period compared to autosomal genes, suggesting positive selection accompanied the early evolution of mammalian X chromosomes. These two findings cast new light on the evolutionary history of the mammalian X chromosome in terms of gene gain, sequence, and expressional evolution., Author Summary Some evolutionary theories predict that the X chromosome will be enriched for genes with male functions. However, recent studies showed there had been gene traffic in which autosomal male-biased genes were retroposed from X-linked parental genes. A question remains about whether this pattern also holds for all types of new genes. Herein, using comparative genomic analysis, we dated all human and mouse genes to the vertebrate phylogenetic tree. We found that the X chromosome evolved with two bursts of gene origination events. The recent burst includes mainly male-biased genes in contrast to older X-linked genes that are often female-biased in expression. Meiotic sex chromosome inactivation contributes to this dynamic since it silences the older but not the younger X-linked genes. The older burst was after the split of eutherian mammals and the marsupial opossum, and the genes from this burst were quickly incorporated into transcriptional networks of multiple tissues, especially in the brain. The transcriptional expansion, together with the rapid protein evolution of the preexisting old X-linked genes, suggests that positive selection was acting in the early evolution of the mammalian X chromosome. These two lines of findings revealed extensive gene evolution in the mammalian X chromosome.

Neutralizing antibodies (NAb) able to react to heterologous viruses are generated during natural HIV-1 infection in some individuals. Further knowledge is required in order to understand the factors contributing to induction of cross-reactive NAb responses. Here a well-established model of experimental pathogenic infection in cynomolgus macaques, which reproduces long-lasting HIV-1 infection, was used to study the NAb response as well as the viral evolution of the highly neutralization-resistant SIVmac239. Twelve animals were infected intravenously with SIVmac239. Antiretroviral therapy (ART) was initiated ten days post-inoculation and administered daily for four months. Viral load, CD4+ T-cell counts, total IgG levels, and breadth as well as strength of NAb in plasma were compared simultaneously over 14 months. In addition, envs from plasma samples were sequenced at three time points in all animals in order to assess viral evolution. We report here that seven of the 12 animals controlled viremia to below 104 copies/ml of plasma after discontinuation of ART and that this control was associated with a low level of evolutionary divergence. Macaques that controlled viral load developed broader NAb responses early on. Furthermore, escape mutations, such as V67M and R751G, were identified in virus sequenced from all animals with uncontrolled viremia. Bayesian estimation of ancestral population genetic diversity (PGD) showed an increase in this value in non-controlling or transient-controlling animals during the first 5.5 months of infection, in contrast to virus-controlling animals. Similarly, non- or transient controllers displayed more positively-selected amino-acid substitutions. An early increase in PGD, resulting in the generation of positively-selected amino-acid substitutions, greater divergence and relative high viral load after ART withdrawal, may have contributed to the generation of potent NAb in several animals after SIVmac239 infection. However, early broad NAb responses correlated with relatively preserved CD4+ T-cell numbers, low viral load and limited viral divergence., Author Summary In a longitudinal study of clinical and evolutionary responses to transient treatment in 12 experimentally-infected macaques, subjects show clear stratification into two groups based on viral load, immunological response, and evolutionary factors. Subjects that controlled viremia following withdrawal of treatment developed broadly neutralizing antibody responses earlier than subjects with no or transient control of viremia. Moreover, this latter group of macaques with higher viral loads showed greater divergence of SIV sequences, greater numbers of positively-selected amino-acid substitutions and a stronger neutralizing antibody response. The increase in viral genetic diversity started at an early stage of infection. The authors propose that this early phase of evolution is principally responsible for the later failure to control viremia and resulted in the development of potent neutralizing capacity.

Malaria, caused by the apicomplexan parasite Plasmodium, threatens 40% of the world's population. Transmission between vertebrate and insect hosts depends on the sexual stages of the life-cycle. The male gamete of Plasmodium parasite is the only developmental stage that possesses a flagellum. Very little is known about the identity or function of proteins in the parasite's flagellar biology. Here, we characterise a Plasmodium PF16 homologue using reverse genetics in the mouse malaria parasite Plasmodium berghei. PF16 is a conserved Armadillo-repeat protein that regulates flagellar structure and motility in organisms as diverse as green algae and mice. We show that P. berghei PF16 is expressed in the male gamete flagellum, where it plays a crucial role maintaining the correct microtubule structure in the central apparatus of the axoneme as studied by electron microscopy. Disruption of the PF16 gene results in abnormal flagellar movement and reduced fertility, but does not lead to complete sterility, unlike pf16 mutations in other organisms. Using homology modelling, bioinformatics analysis and complementation studies in Chlamydomonas, we show that some regions of the PF16 protein are highly conserved across all eukaryotes, whereas other regions may have species-specific functions. PF16 is the first ARM-repeat protein characterised in the malaria parasite genus Plasmodium and this study opens up a novel model for analysis of Plasmodium flagellar biology that may provide unique insights into an ancient organelle and suggest novel intervention strategies to control the malaria parasite.

The functional structure of all biologically active molecules is dependent on intra- and inter-molecular interactions. This is especially evident for RNA molecules whose functionality, maturation, and regulation require formation of correct secondary structure through encoded base-pairing interactions. Unfortunately, intra- and inter-molecular base-pairing information is lacking for most RNAs. Here, we marry classical nuclease-based structure mapping techniques with high-throughput sequencing technology to interrogate all base-paired RNA in Arabidopsis thaliana and identify ∼200 new small (sm)RNA–producing substrates of RNA–DEPENDENT RNA POLYMERASE6. Our comprehensive analysis of paired RNAs reveals conserved functionality within introns and both 5′ and 3′ untranslated regions (UTRs) of mRNAs, as well as a novel population of functional RNAs, many of which are the precursors of smRNAs. Finally, we identify intra-molecular base-pairing interactions to produce a genome-wide collection of RNA secondary structure models. Although our methodology reveals the pairing status of RNA molecules in the absence of cellular proteins, previous studies have demonstrated that structural information obtained for RNAs in solution accurately reflects their structure in ribonucleoprotein complexes. Furthermore, our identification of RNA–DEPENDENT RNA POLYMERASE6 substrates and conserved functional RNA domains within introns and both 5′ and 3′ untranslated regions (UTRs) of mRNAs using this approach strongly suggests that RNA molecules are correctly folded into their secondary structure in solution. Overall, our findings highlight the importance of base-paired RNAs in eukaryotes and present an approach that should be widely applicable for the analysis of this key structural feature of RNA., Author Summary At the heart of RNA functionality, maturation, and regulation is the formation of intricate secondary structures that are dependent on specific nucleotide base-pairing interactions encoded within their sequences. These interactions can either be within (intra-molecular) or between (inter-molecular (heteroduplex)) RNA molecules. Although it is clear that secondary structure is abundantly important for the functionality and regulation of RNAs, comprehensive base-pairing interaction data are completely lacking for the majority of these molecules. To address this, we have developed a new approach for studying the base-pairing interactions of RNA molecules by marrying classical nuclease-based structure mapping techniques with high-throughput sequencing technology. We have used this approach to identify known and novel substrates of the base-paired RNA producing enzyme RNA–DEPENDENT RNA POLYMERASE6, reveal conserved functionality within introns and both 5′ and 3′ untranslated regions (UTRs) of mRNAs, uncover a novel population of functional RNAs, and produce a genome-wide collection of RNA secondary structure models by identifying the base-pairing interactions within each RNA molecule. Our findings demonstrate that our methodology should be widely applicable for the identification and analysis of base-paired RNAs in all biological organisms.

Herbivores can gain indirect access to recalcitrant carbon present in plant cell walls through symbiotic associations with lignocellulolytic microbes. A paradigmatic example is the leaf-cutter ant (Tribe: Attini), which uses fresh leaves to cultivate a fungus for food in specialized gardens. Using a combination of sugar composition analyses, metagenomics, and whole-genome sequencing, we reveal that the fungus garden microbiome of leaf-cutter ants is composed of a diverse community of bacteria with high plant biomass-degrading capacity. Comparison of this microbiome's predicted carbohydrate-degrading enzyme profile with other metagenomes shows closest similarity to the bovine rumen, indicating evolutionary convergence of plant biomass degrading potential between two important herbivorous animals. Genomic and physiological characterization of two dominant bacteria in the fungus garden microbiome provides evidence of their capacity to degrade cellulose. Given the recent interest in cellulosic biofuels, understanding how large-scale and rapid plant biomass degradation occurs in a highly evolved insect herbivore is of particular relevance for bioenergy., Author Summary Leaf-cutter ants form massive subterranean colonies containing millions of workers that harvest hundreds of kilograms of leaves each year. They use these leaves to grow a mutualistic fungus that serves as the colony's primary food source. By farming fungus in specialized garden chambers, these dominant Neotropical herbivores facilitate rapid large-scale plant biomass conversion. Our understanding of this degradation process, and the responsible microbial community, is limited. In this study, we track the degradation of plant polymers in leaf-cutter ant fungus gardens and characterize the microbial community potentially mediating this process. We show that cellulose and hemicelluloses are degraded in the fungus gardens and that a previously unknown microbial community containing a diversity of bacteria is present. Metagenomic analysis of this community's genetic content revealed many genes predicted to encode enzymes capable of degrading plant cell walls. The ability of leaf-cutter ants to maintain an external microbial community with high plant biomass-degrading capacity likely represents a key step in the establishment of these ants as widespread, dominant insect herbivores in the Neotropics. This system is an important model for understanding how microbial communities degrade plant biomass in natural systems and has direct relevancy for bioenergy, given recent interest in cellulosic biofuels.

Background Arthropod cuticle is composed predominantly of a self-assembling matrix of chitin and protein. Genes encoding structural cuticular proteins are remarkably abundant in arthropod genomes, yet there has been no systematic survey of conserved motifs across cuticular protein families. Methodology/Principal Findings Two short sequence motifs with conserved tyrosines were identified in Drosophila cuticular proteins that were similar to the GYR and YLP Interpro domains. These motifs were found in members of the CPR, Tweedle, CPF/CPFL, and (in Anopheles gambiae) CPLCG cuticular protein families, and the Dusky/Miniature family of cuticle-associated proteins. Tweedle proteins have a characteristic motif architecture that is shared with the Drosophila protein GCR1 and its orthologs in other species, suggesting that GCR1 is also cuticular. A resilin repeat, which has been shown to confer elasticity, matched one of the motifs; a number of other Drosophila proteins of unknown function exhibit a motif architecture similar to that of resilin. The motifs were also present in some proteins of the peritrophic matrix and the eggshell, suggesting molecular convergence among distinct extracellular matrices. More surprisingly, gene regulation, development, and proteolysis were statistically over-represented ontology terms for all non-cuticular matches in Drosophila. Searches against other arthropod genomes indicate that the motifs are taxonomically widespread. Conclusions This survey suggests a more general definition for GYR and YLP motifs and reveals their contribution to several types of extracellular matrix. They may define sites of protein interaction with DNA or other proteins, based on ontology analysis. These results can help guide experimental studies on the biochemistry of cuticle assembly.

Mutation is the engine that drives evolution and adaptation forward in that it generates the variation on which natural selection acts. Mutation is a random process that nevertheless occurs according to certain biases. Elucidating mutational biases and the way they vary across species and within genomes is crucial to understanding evolution and adaptation. Here we demonstrate that clonal pathogens that evolve under severely relaxed selection are uniquely suitable for studying mutational biases in bacteria. We estimate mutational patterns using sequence datasets from five such clonal pathogens belonging to four diverse bacterial clades that span most of the range of genomic nucleotide content. We demonstrate that across different types of sites and in all four clades mutation is consistently biased towards AT. This is true even in clades that have high genomic GC content. In all studied cases the mutational bias towards AT is primarily due to the high rate of C/G to T/A transitions. These results suggest that bacterial mutational biases are far less variable than previously thought. They further demonstrate that variation in nucleotide content cannot stem entirely from variation in mutational biases and that natural selection and/or a natural selection-like process such as biased gene conversion strongly affect nucleotide content., Author Summary Natural selection sorts through the variability generated by mutation and biases evolution toward fitter outcomes. However, because mutation is itself not entirely random it can also bias the direction of evolution independently of selection. For instance, it is often assumed that the extreme variation observed in nucleotide content among bacteria (from ∼20% to ∼80% GC) is predominantly driven by extreme differences in mutational biases towards or away from GC. Here, we show that bacterial lineages that recently developed clonal, pathogenic lifestyles evolve under weak selection and that polymorphisms in these bacteria can be used as a fair proxy for mutational spectra. We analyze large sequence datasets from five clonal pathogens in four diverse bacterial clades spanning most of the range of genomic nucleotide content. We find that, surprisingly, mutation is AT-biased in every case to a very similar degree and in each case it is dominated by transitions from C/G to T/A. This demonstrates that mutational biases are far les variable than previously assumed and that variation in bacterial nucleotide content is not due entirely to mutational biases. Rather natural selection or a selection like process such as biased gene conversion strongly affect nucleotide content in bacteria.

Background Despite high potential for HIV-1 genetic variation, the emergence of some mutations is constrained by fitness costs, and may be associated with compensatory amino acid (AA) co-variation. To characterize the interplay between Cytotoxic T Lymphocyte (CTL)-mediated pressure and HIV-1 evolutionary pathways, we investigated AA co-variation in Gag sequences obtained from 449 South African individuals chronically infected with HIV-1 subtype C. Methodology/Principal Findings Individuals with CTL responses biased toward Gag presented lower viral loads than individuals with under-represented Gag-specific CTL responses. Using methods that account for founder effects and HLA linkage disequilibrium, we identified 35 AA sites under Human Leukocyte Antigen (HLA)-restricted CTL selection pressure and 534 AA-to-AA interactions. Analysis of two-dimensional distances between co-varying residues revealed local stabilization mechanisms since 40% of associations involved neighboring residues. Key features of our co-variation analysis included sites with a high number of co-varying partners, such as HLA-associated sites, which had on average 55% more connections than other co-varying sites. Conclusions/Significance Clusters of co-varying AA around HLA-associated sites (especially at typically conserved sites) suggested that cooperative interactions act to preserve the local structural stability and protein function when CTL escape mutations occur. These results expose HLA-imprinted HIV-1 polymorphisms and their interlinked mutational paths in Gag that are likely due to opposite selective pressures from host CTL-mediated responses and viral fitness constraints., Bill & Melinda Gates Foundation (#43437), American Foundation for AIDS Research (#107005-43-RFNT), Center for AIDS Research (CFAR), United States. Public Health Service (AI057005)

BackgroundWe sequenced four plasmids of the genus Listeria, including two novel plasmids from L. monocytogenes serotype 1/2c and 7 strains as well as one from the species L. grayi. A comparative analysis in conjunction with 10 published Listeria plasmids revealed a common evolutionary background.Principal findingsAll analysed plasmids share a common replicon-type related to theta-replicating plasmid pAMbeta1. Nonetheless plasmids could be broadly divided into two distinct groups based on replicon diversity and the genetic content of the respective plasmid groups. Listeria plasmids are characterized by the presence of a large number of diverse mobile genetic elements and a commonly occurring translesion DNA polymerase both of which have probably contributed to the evolution of these plasmids. We detected small non-coding RNAs on some plasmids that were homologous to those present on the chromosome of L. monocytogenes EGD-e. Multiple genes involved in heavy metal resistance (cadmium, copper, arsenite) as well as multidrug efflux (MDR, SMR, MATE) were detected on all listerial plasmids. These factors promote bacterial growth and survival in the environment and may have been acquired as a result of selective pressure due to the use of disinfectants in food processing environments. MDR efflux pumps have also recently been shown to promote transport of cyclic diadenosine monophosphate (c-di-AMP) as a secreted molecule able to trigger a cytosolic host immune response following infection.ConclusionsThe comparative analysis of 14 plasmids of genus Listeria implied the existence of a common ancestor. Ubiquitously-occurring MDR genes on plasmids and their role in listerial infection now deserve further attention.

The South American phorusrhacid bird radiation comprised at least 18 species of small to gigantic terrestrial predators for which there are no close modern analogs. Here we perform functional analyses of the skull of the medium-sized (,40 kg) patagornithine phorusrhacid Andalgalornis steulleti (upper Miocene-lower Pliocene, Andalgalá Formation, Catamarca, Argentina) to assess its mechanical performance in a comparative context. Based on computed tomographic (CT) scanning and morphological analysis, the skull of Andalgalornis steulleti is interpreted as showing features reflecting loss of intracranial immobility. Discrete anatomical attributes permitting such cranial kinesis are widespread phorusrhacids outgroups, but this is the first clear evidence of loss of cranial kinesis in a gruiform bird and may be among the best documented cases among all birds. This apomorphic loss is interpreted as an adaptation for enhanced craniofacial rigidity, particularly with regard to sagittal loading. We apply a Finite Element approach to a three-dimensional (3D) model of the skull. Based on regression analysis we estimate the bite force of Andalgalornis at the bill tip to be 133 N. Relative to results obtained from Finite Element Analysis of one of its closest living relatives (seriema) and a large predatory bird (eagle), the phorusrhacid's skull shows relatively high stress under lateral loadings, but low stress where force is applied dorsoventrally (sagittally) and in ''pullback'' simulations. Given the relative weakness of the skull mediolaterally, it seems unlikely that Andalgalornis engaged in potentially risky behaviors that involved subduing large, struggling prey with its beak. We suggest that it either consumed smaller prey that could be killed and consumed more safely (e.g., swallowed whole) or that it used multiple well-targeted sagittal strikes with the beak in a repetitive attack-and-retreat strategy., Facultad de Ciencias Naturales y Museo

Positive selection is known to occur when the environment that an organism inhabits is suddenly altered, as is the case across recent human history. Genome-wide association studies (GWASs) have successfully illuminated disease-associated variation. However, whether human evolution is heading towards or away from disease susceptibility in general remains an open question. The genetic-basis of common complex disease may partially be caused by positive selection events, which simultaneously increased fitness and susceptibility to disease. We analyze seven diseases studied by the Wellcome Trust Case Control Consortium to compare evidence for selection at every locus associated with disease. We take a large set of the most strongly associated SNPs in each GWA study in order to capture more hidden associations at the cost of introducing false positives into our analysis. We then search for signs of positive selection in this inclusive set of SNPs. There are striking differences between the seven studied diseases. We find alleles increasing susceptibility to Type 1 Diabetes (T1D), Rheumatoid Arthritis (RA), and Crohn's Disease (CD) underwent recent positive selection. There is more selection in alleles increasing, rather than decreasing, susceptibility to T1D. In the 80 SNPs most associated with T1D (p-value

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.

Autism spectrum disorders (ASDs) are a group of commonly occurring, highly-heritable developmental disabilities. Human genes c3orf58 or Deleted In Autism-1 (DIA1) and cXorf36 or Deleted in Autism-1 Related (DIA1R) are implicated in ASD and mental retardation. Both gene products encode signal peptides for targeting to the secretory pathway. As evolutionary medicine has emerged as a key tool for understanding increasing numbers of human diseases, we have used an evolutionary approach to study DIA1 and DIA1R. We found DIA1 conserved from cnidarians to humans, indicating DIA1 evolution coincided with the development of the first primitive synapses. Nematodes lack a DIA1 homologue, indicating Caenorhabditis elegans is not suitable for studying all aspects of ASD etiology, while zebrafish encode two DIA1 paralogues. By contrast to DIA1, DIA1R was found exclusively in vertebrates, with an origin coinciding with the whole-genome duplication events occurring early in the vertebrate lineage, and the evolution of the more complex vertebrate nervous system. Strikingly, DIA1R was present in schooling fish but absent in fish that have adopted a more solitary lifestyle. An additional DIA1-related gene we named DIA1-Like (DIA1L), lacks a signal peptide and is restricted to the genomes of the echinoderm Strongylocentrotus purpuratus and cephalochordate Branchiostoma floridae. Evidence for remarkable DIA1L gene expansion was found in B. floridae. Amino acid alignments of DIA1 family gene products revealed a potential Golgi-retention motif and a number of conserved motifs with unknown function. Furthermore, a glycine and three cysteine residues were absolutely conserved in all DIA1-family proteins, indicating a critical role in protein structure and/or function. We have therefore identified a new metazoan protein family, the DIA1-family, and understanding the biological roles of DIA1-family members will have implications for our understanding of autism and mental retardation.

Assessing conservation/divergence of gene expression across species is important for the understanding of gene regulation evolution. Although advances in microarray technology have provided massive high-dimensional gene expression data, the analysis of such data is still challenging. To date, assessing cross-species conservation of gene expression using microarray data has been mainly based on comparison of expression patterns across corresponding tissues, or comparison of co-expression of a gene with a reference set of genes. Because direct and reliable high-throughput experimental data on conservation of gene expression are often unavailable, the assessment of these two computational models is very challenging and has not been reported yet. In this study, we compared one corresponding tissue based method and three co-expression based methods for assessing conservation of gene expression, in terms of their pair-wise agreements, using a frequently used human-mouse tissue expression dataset. We find that 1) the co-expression based methods are only moderately correlated with the corresponding tissue based methods, 2) the reliability of co-expression based methods is affected by the size of the reference ortholog set, and 3) the corresponding tissue based methods may lose some information for assessing conservation of gene expression. We suggest that the use of either of these two computational models to study the evolution of a gene's expression may be subject to great uncertainty, and the investigation of changes in both gene expression patterns over corresponding tissues and co-expression of the gene with other genes is necessary.

BackgroundDuring typical microRNA (miRNA) biogenesis, one strand of a approximately 22 nt RNA duplex is preferentially selected for entry into a silencing complex, whereas the other strand, known as the passenger strand or miRNA* strand, is degraded. Recently, some miRNA* sequences were reported as guide miRNAs with abundant expression. Here, we intended to discover evolutionary implication of the fate of miRNA* strand by analyzing miRNA/miRNA* sequences across vertebrates.Principal findingsMature miRNAs based on gene families were well conserved especially for their seed sequences across vertebrates, while their passenger strands always showed various divergence patterns. The divergence mainly resulted from divergence of different animal species, homologous miRNA genes and multicopy miRNA hairpin precursors. Some miRNA* sequences were phylogenetically conserved in seed and anchor sequences similar to mature miRNAs, while others revealed high levels of nucleotide divergence despite some of their partners were highly conserved. Most of those miRNA precursors that could generate abundant miRNAs from both strands always were well conserved in sequences of miR-#-5p and miR-#-3p, especially for their seed sequences.ConclusionsThe final fate of miRNA* strand, either degraded as merely carrier strand or expressed abundantly as potential functional guide miRNA, may be destined across evolution. Well-conserved miRNA* strands, particularly conservation in seed sequences, maybe afford potential opportunities for contributing to regulation network. The study will broaden our understanding of potential functional miRNA* species.

The prediction of functional RNA structures has attracted increased interest, as it allows us to study the potential functional roles of many genes. RNA structure prediction methods, however, assume that there is a unique functional RNA structure and also do not predict functional features required for in vivo folding. In order to understand how functional RNA structures form in vivo, we require sophisticated experiments or reliable prediction methods. So far, there exist only a few, experimentally validated transient RNA structures. On the computational side, there exist several computer programs which aim to predict the co-transcriptional folding pathway in vivo, but these make a range of simplifying assumptions and do not capture all features known to influence RNA folding in vivo. We want to investigate if evolutionarily related RNA genes fold in a similar way in vivo. To this end, we have developed a new computational method, Transat, which detects conserved helices of high statistical significance. We introduce the method, present a comprehensive performance evaluation and show that Transat is able to predict the structural features of known reference structures including pseudo-knotted ones as well as those of known alternative structural configurations. Transat can also identify unstructured sub-sequences bound by other molecules and provides evidence for new helices which may define folding pathways, supporting the notion that homologous RNA sequence not only assume a similar reference RNA structure, but also fold similarly. Finally, we show that the structural features predicted by Transat differ from those assuming thermodynamic equilibrium. Unlike the existing methods for predicting folding pathways, our method works in a comparative way. This has the disadvantage of not being able to predict features as function of time, but has the considerable advantage of highlighting conserved features and of not requiring a detailed knowledge of the cellular environment., Author Summary Many non-coding genes exert their function via an RNA structure which starts emerging while the RNA sequence is being transcribed from the genome. The resulting folding pathway is known to depend on a variety of features such as the transcription speed, the concentration of various ions and the binding of proteins and other molecules. Not all of these influences can be adequately captured by the existing computational methods which try to replicate what happens in vivo. So far, it has been challenging to experimentally investigate co-transcriptional folding pathways in vivo and only little data from in vitro experiments exists. In order to investigate if functionally similar RNA sequences from different organisms fold in a similar way, we have developed a new computational method, called Transat, which does not require the detailed computational modeling of the cellular environment. We show in a comprehensive analysis that our method is capable of detecting known structural features and provide evidence that structural features of the in vivo folding pathways have been conserved for several biologically interesting classes of RNA sequences.

Despite its economical, cultural, and biological importance, there has not been a large scale sequencing project to date for Camelus dromedarius. With the goal of sequencing complete DNA of the organism, we first established and sequenced camel EST libraries, generating 70,272 reads. Following trimming, chimera check, repeat masking, cluster and assembly, we obtained 23,602 putative gene sequences, out of which over 4,500 potentially novel or fast evolving gene sequences do not carry any homology to other available genomes. Functional annotation of sequences with similarities in nucleotide and protein databases has been obtained using Gene Ontology classification. Comparison to available full length cDNA sequences and Open Reading Frame (ORF) analysis of camel sequences that exhibit homology to known genes show more than 80% of the contigs with an ORF>300 bp and approximately 40% hits extending to the start codons of full length cDNAs suggesting successful characterization of camel genes. Similarity analyses are done separately for different organisms including human, mouse, bovine, and rat. Accompanying web portal, CAGBASE (http://camel.kacst.edu.sa/), hosts a relational database containing annotated EST sequences and analysis tools with possibility to add sequences from public domain. We anticipate our results to provide a home base for genomic studies of camel and other comparative studies enabling a starting point for whole genome sequencing of the organism.

The understanding of selective constraints affecting genes is a major issue in biology. It is well established that gene expression level is a major determinant of the rate of protein evolution, but the reasons for this relationship remain highly debated. Here we demonstrate that gene expression is also a major determinant of the evolution of gene dosage: the rate of gene losses after whole genome duplications in the Paramecium lineage is negatively correlated to the level of gene expression, and this relationship is not a byproduct of other factors known to affect the fate of gene duplicates. This indicates that changes in gene dosage are generally more deleterious for highly expressed genes. This rule also holds for other taxa: in yeast, we find a clear relationship between gene expression level and the fitness impact of reduction in gene dosage. To explain these observations, we propose a model based on the fact that the optimal expression level of a gene corresponds to a trade-off between the benefit and cost of its expression. This COSTEX model predicts that selective pressure against mutations changing gene expression level or affecting the encoded protein should on average be stronger in highly expressed genes and hence that both the frequency of gene loss and the rate of protein evolution should correlate negatively with gene expression. Thus, the COSTEX model provides a simple and common explanation for the general relationship observed between the level of gene expression and the different facets of gene evolution., Author Summary The analysis of gene evolution is a powerful approach to recognize the genetic features that contribute to the fitness of organisms. It was shown previously that selective constraints on protein sequences increase with expression level. This observation was surprising because there is a priori no reason why lowly expressed genes should be less important than highly expressed genes for the proper function of an organism. Here we show that selective pressure on the evolution of gene dosage, which is another important aspect of gene evolution, is also directly dependent on gene expression level. To explain these observations, we propose a model based on the fact that gene expression is a costly process (notably protein synthesis), so that there is an optimal expression level for each gene corresponding to a trade-off between the benefit and the cost of its expression. This model predicts that selective pressure on gene expression level or on the encoded protein should on average be stronger in highly expressed genes, providing a simple and common explanation for the general relationship observed between gene expression and the different facets of gene evolution.

The equine-associated obligate pathogen Burkholderia mallei was developed by reductive evolution involving a substantial portion of the genome from Burkholderia pseudomallei, a free-living opportunistic pathogen. With its short history of divergence (∼3.5 myr), B. mallei provides an excellent resource to study the early steps in bacterial genome reductive evolution in the host. By examining 20 genomes of B. mallei and B. pseudomallei, we found that stepwise massive expansion of IS (insertion sequence) elements ISBma1, ISBma2, and IS407A occurred during the evolution of B. mallei. Each element proliferated through the sites where its target selection preference was met. Then, ISBma1 and ISBma2 contributed to the further spread of IS407A by providing secondary insertion sites. This spread increased genomic deletions and rearrangements, which were predominantly mediated by IS407A. There were also nucleotide-level disruptions in a large number of genes. However, no significant signs of erosion were yet noted in these genes. Intriguingly, all these genomic modifications did not seriously alter the gene expression patterns inherited from B. pseudomallei. This efficient and elaborate genomic transition was enabled largely through the formation of the highly flexible IS-blended genome and the guidance by selective forces in the host. The detailed IS intervention, unveiled for the first time in this study, may represent the key component of a general mechanism for early bacterial evolution in the host., Author Summary It has been known for some time that bacteria undergo genome-reduction when they transition from a free-living state to a constantly host-restricted state. High levels of IS element expansion were also found in these bacteria, and the IS elements were suggested to play a role in genome reductive evolution. Here we provide evidence for stepwise IS actions as the exclusive mechanism that mediates bacterial genomic changes during the early stage of constant host-bacterial association, by unveiling the processes that resulted in the development of B. mallei genome. We show the details of the multi-level interplay of IS elements, which facilitate the wide spread of the IS copies, and the overall mechanics in genome reduction and rearrangement. These processes appeared to operate as chain reactions mediating elaborate genomic transition, without seriously affecting the original gene expression patterns. The absence of differential gene expression in the resulting genome suggests that changes in transcriptional regulation that are often observed in other old bacterial genomes may take place subsequent to the IS-mediated steps, along with gradual nucleotide-level changes.

Background It has been long appreciated that speciation involves changes in body plans and establishes genetic, reproductive, developmental and behavioral incompatibilities between populations. However, little is still known about the genetic components involved in these changes or the sequence and scale of events that lead to the differentiation of species. Principal Findings In this paper, we investigated the genetic changes in three closely related species of Drosophila by making pair-wise comparisons of their genomes. We focused our analysis on the modern relatives of the alleles likely to be segregating in pre-historic populations at the time or after the ancestor of D. simulans became separated from the ancestor of D. melanogaster. Some of these genes were previously implicated in the genetics of reproduction and behavior while the biological functions of others are not yet clear. Conclusions Together these results identify different classes of genes that might have participated in the beginning of segregation of these species millions of years ago in Africa.

Histopathological classification of human tumors relies in part on the degree of differentiation of the tumor sample. To date, there is no objective systematic method to categorize tumor subtypes by maturation. In this paper, we introduce a novel computational algorithm to rank tumor subtypes according to the dissimilarity of their gene expression from that of stem cells and fully differentiated tissue, and thereby construct a phylogenetic tree of cancer. We validate our methodology with expression data of leukemia, breast cancer and liposarcoma subtypes and then apply it to a broader group of sarcomas. This ranking of tumor subtypes resulting from the application of our methodology allows the identification of genes correlated with differentiation and may help to identify novel therapeutic targets. Our algorithm represents the first phylogeny-based tool to analyze the differentiation status of human tumors., Author Summary Gene expression profiling of malignancies is often held to demonstrate genes that are “up-regulated” or “down-regulated”, but the appropriate frame of reference against which observations should be compared has not been determined. Fully differentiated somatic cells arise from stem cells, with changes in gene expression that can be experimentally determined. If cancers arise as the result of an abruption of the differentiation process, then poorly differentiated cancers would have a gene expression more similar to stem cells than to normal differentiated tissue, and well differentiated cancers would have a gene expression more similar to fully differentiated cells than to stem cells. In this paper, we describe a novel computational algorithm that allows orientation of cancer gene expression between the poles of the gene expression of stem cells and of fully differentiated tissue. Our methodology allows the construction of a multi-branched phylogeny of human malignancies and can be used to identify genes related to differentiation as well as novel therapeutic targets.

selection pressure on a gene, revealed from its evolutionary history, is determined by the role played by the gene, i.e., its biological function. The known conservation of a gene’s sequence coupled with the knowledge of the timing/dating of evolutionary events provides clues about the gene’s function. If a gene is preserved in all species with high sequence similarity and there are only a few duplication events along its evolutionary history, we have high confidence that its orthologs have the same function in different species. On the other hand, a large number of duplications and/or deletions along a gene’s evolutionary history could indicate neofunctionalization and/or nonorthologous gene displacement [3], and consequently, orthologs in different genomes may have different functions. These facts highlight the significance of functionoriented ortholog identification. In this article, we will review the general procedures to identify orthologs and make ortholog groups. We will focus on the functional analyses of orthologs, review previous work to assess functional consistency of orthologs, and make suggestions to construct better ortholog groups. Lastly, because orthologs can only be identified when the whole gene inventories from all the involved species are examined, the distribution of identified orthologs among species is an immediate result of looking into the composition of ortholog groups. Composition of ortholog groups, which bears important information for downstream research and applications, will also be briefly discussed.

Codon models of evolution have facilitated the interpretation of selective forces operating on genomes. These models, however, assume a single rate of non-synonymous substitution irrespective of the nature of amino acids being exchanged. Recent developments have shown that models which allow for amino acid pairs to have independent rates of substitution offer improved fit over single rate models. However, these approaches have been limited by the necessity for large alignments in their estimation. An alternative approach is to assume that substitution rates between amino acid pairs can be subdivided into rate classes, dependent on the information content of the alignment. However, given the combinatorially large number of such models, an efficient model search strategy is needed. Here we develop a Genetic Algorithm (GA) method for the estimation of such models. A GA is used to assign amino acid substitution pairs to a series of rate classes, where is estimated from the alignment. Other parameters of the phylogenetic Markov model, including substitution rates, character frequencies and branch lengths are estimated using standard maximum likelihood optimization procedures. We apply the GA to empirical alignments and show improved model fit over existing models of codon evolution. Our results suggest that current models are poor approximations of protein evolution and thus gene and organism specific multi-rate models that incorporate amino acid substitution biases are preferred. We further anticipate that the clustering of amino acid substitution rates into classes will be biologically informative, such that genes with similar functions exhibit similar clustering, and hence this clustering will be useful for the evolutionary fingerprinting of genes., Author Summary Evolution in protein-coding DNA sequences can be modeled at three levels: nucleotides, amino acids or codons that encode the amino acids. Codon models incorporate nucleotide and amino acid information, and allow the estimation of the rate at which amino acids are replaced () versus the rate at which they are preserved (). The ratio has been used in thousands of studies to detect molecular footprints of natural selection. A serious limitation of most codon models is the unrealistic assumption that all non-synonymous substitutions occur at the same rate. Indeed, amino acid models have consistently demonstrated that different residues are exchanged more or less frequently, depending on incompletely understood factors. We derive and validate a computational approach for inferring codon models which combine the power to investigate natural selection with data-driven amino acid substitution biases from alignments. The addition of amino acid properties can lead to more powerful and accurate methods for studying natural selection and the evolutionary history of protein-coding sequences. The pattern of amino acid substitutions specific to a given alignment can be used to compare and contrast the evolutionary properties of different genes, providing an evolutionary analog to protein family comparisons.

Background: Molecular biology is currently facing the challenging task of functionally characterizing the proteome. The large number of possible protein-protein interactions and complexes, the variety of environmental conditions and cellular states in which these interactions can be reorganized, and the multiple ways in which a protein can influence the function of others, requires the development of experimental and computational approaches to analyze and predict functional associations between proteins as part of their activity in the interactome. Methodology/Principal Findings: We have studied the possibility of constructing a classifier in order to combine the output of the several protein interaction prediction methods. The AODE (Averaged One-Dependence Estimators) machine learning algorithm is a suitable choice in this case and it provides better results than the individual prediction methods, and it has better performances than other tested alternative methods in this experimental set up. To illustrate the potential use of this new AODE-based Predictor of Protein InterActions (APPIA), when analyzing high-throughput experimental data, we show how it helps to filter the results of published High-Throughput proteomic studies, ranking in a significant way functionally related pairs. Availability: All the predictions of the individual methods and of the combined APPIA predictor, together with the used datasets of functional associations are available at http://ecid.bioinfo.cnio.es/. Conclusions: We propose a strategy that integrates the main current computational techniques used to predict functional associations into a unified classifier system, specifically focusing on the evaluation of poorly characterized protein pairs. We selected the AODE classifier as the appropriate tool to perform this task. AODE is particularly useful to extract valuable information from large unbalanced and heterogeneous data sets. The combination of the information provided by five prediction interaction prediction methods with some simple sequence features in APPIA is useful in establishing reliability values and helpful to prioritize functional interactions that can be further experimentally characterized. This work was funded by the BioSapiens (grant number LSHG-CT-2003-503265) and the Experimental Network for Functional Integration (ENFIN) Networks of Excellence (contract number LSHG-CT-2005-518254), by Consolider BSC (grant number CSD2007-00050) and by the project “Functions for gene sets” from the Spanish Ministry of Education and Science (BIO2007-66855). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Background The role of long non-coding RNAs (lncRNAs) in controlling gene expression has garnered increased interest in recent years. Sequencing projects, such as Fantom3 for mouse and H-InvDB for human, have generated abundant data on transcribed components of mammalian cells, the majority of which appear not to be protein-coding. However, much of the non-protein-coding transcriptome could merely be a consequence of ‘transcription noise’. It is therefore essential to use bioinformatic approaches to identify the likely functional candidates in a high throughput manner. Principal Findings We derived a scheme for classifying and annotating likely functional lncRNAs in mammals. Using the available experimental full-length cDNA data sets for human and mouse, we identified 78 lncRNAs that are either syntenically conserved between human and mouse, or that originate from the same protein-coding genes. Of these, 11 have significant sequence homology. We found that these lncRNAs exhibit: (i) patterns of codon substitution typical of non-coding transcripts; (ii) preservation of sequences in distant mammals such as dog and cow, (iii) significant sequence conservation relative to their corresponding flanking regions (in 50% cases, flanking regions do not have homology at all; and in the remaining, the degree of conservation is significantly less); (iv) existence mostly as single-exon forms (8/11); and, (v) presence of conserved and stable secondary structure motifs within them. We further identified orthologous protein-coding genes that are contributing to the pool of lncRNAs; of which, genes implicated in carcinogenesis are significantly over-represented. Conclusion Our comparative mammalian genomics approach coupled with evolutionary analysis identified a small population of conserved long non-protein-coding RNAs (lncRNAs) that are potentially functional across Mammalia. Additionally, our analysis indicates that amongst the orthologous protein-coding genes that produce lncRNAs, those implicated in cancer pathogenesis are significantly over-represented, suggesting that these lncRNAs could play an important role in cancer pathomechanisms.

Dosage sensitivity is an important evolutionary force which impacts on gene dispensability and duplicability. The newly available data on human copy-number variation (CNV) allow an analysis of the most recent and ongoing evolution. Provided that heterozygous gene deletions and duplications actually change gene dosage, we expect to observe negative selection against CNVs encompassing dosage sensitive genes. In this study, we make use of several sources of population genetic data to identify selection on structural variations of dosage sensitive genes. We show that CNVs can directly affect expression levels of contained genes. We find that genes encoding members of protein complexes exhibit limited expression variation and overlap significantly with a manually derived set of dosage sensitive genes. We show that complexes and other dosage sensitive genes are underrepresented in CNV regions, with a particular bias against frequent variations and duplications. These results suggest that dosage sensitivity is a significant force of negative selection on regions of copy-number variation.

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.

We recently used computational phylogenetic methods on lexical data to test between two scenarios for the peopling of the Pacific. Our analyses of lexical data supported a pulse-pause scenario of Pacific settlement in which the Austronesian speakers originated in Taiwan around 5,200 years ago and rapidly spread through the Pacific in a series of expansion pulses and settlement pauses. We claimed that there was high congruence between traditional language subgroups and those observed in the language phylogenies, and that the estimated age of the Austronesian expansion at 5,200 years ago was consistent with the archaeological evidence. However, the congruence between the language phylogenies and the evidence from historical linguistics was not quantitatively assessed using tree comparison metrics. The robustness of the divergence time estimates to different calibration points was also not investigated exhaustively. Here we address these limitations by using a systematic tree comparison metric to calculate the similarity between the Bayesian phylogenetic trees and the subgroups proposed by historical linguistics, and by re-estimating the age of the Austronesian expansion using only the most robust calibrations. The results show that the Austronesian language phylogenies are highly congruent with the traditional subgroupings, and the date estimates are robust even when calculated using a restricted set of historical calibrations.

Regulation of Pak2 activity involves at least two mechanisms: (i) phosphorylation of the conserved Thr(402) in the activation loop and (ii) interaction of the autoinhibitory domain (AID) with the catalytic domain. We collected 482 human protein kinase sequences from the kinome database and globally mapped the evolutionary interactions of the residues in the catalytic domain with Thr(402) by sequence-based statistical coupling analysis (SCA). Perturbation of Thr(402) (34.6%) suggests a communication pathway between Thr(402) in the activation loop, and Phe(387) (DeltaDeltaE(387F,402T) = 2.80) in the magnesium positioning loop, Trp(427) (DeltaDeltaE(427W,402T) = 3.12) in the F-helix, and Val(404) (DeltaDeltaE(404V,402T) = 4.43) and Gly(405) (DeltaDeltaE(405G,402T) = 2.95) in the peptide positioning loop. When compared to the cAMP-dependent protein kinase (PKA) and Src, the perturbation pattern of threonine phosphorylation in the activation loop of Pak2 is similar to that of PKA, and different from the tyrosine phosphorylation pattern of Src. Reciprocal coupling analysis by SCA showed the residues perturbed by Thr(402) and the reciprocal coupling pairs formed a network centered at Trp(427) in the F-helix. Nine pairs of reciprocal coupling residues crucial for enzymatic activity and structural stabilization were identified. Pak2, PKA and Src share four pairs. Reciprocal coupling residues exposed to the solvent line up as an activation groove. This is the inhibitor (PKI) binding region in PKA and the activation groove for Pak2. This indicates these evolutionary conserved residues are crucial for the catalytic activity of PKA and Pak2.

BACKGROUND: Norovirus GII.4 is the predominant genotype circulating worldwide over the last decade causing 80% of all norovirus outbreaks with new GII.4 variants reported in parallel with periodic epidemic waves of norovirus outbreaks. The circulating new GII.4 variants and the epidemiology of norovirus outbreaks in Alberta, Canada have not been described. Our hypothesis is that the periodic epidemic norovirus outbreak activity in Alberta was driven by new GII.4 variants evolving by genetic drift. METHODOLOGY/PRINCIPAL FINDINGS: The Alberta Provincial Public Health Laboratory performed norovirus testing using RT-PCR for suspected norovirus outbreaks in the province and the northern Territories between 2000 and 2008. At least one norovirus strain from 707 out of 1,057 (66.9%) confirmed norovirus outbreaks were successfully sequenced. Phylogenetic analysis was performed using BioNumerics and 617 (91.1%) outbreaks were characterized as caused by GII.4 with 598 assigned as novel variants including: GII.4-1996, GII.4-2002, GII.4-2004, GII.4-2006a, GII.4-2006b, GII.4-2008a and GII.4-2008b. Defining July to June of the following year as the yearly observation period, there was clear biannual pattern of low and high outbreak activity in Alberta. Within this biannual pattern, high outbreak activity followed the emergence of novel GII.4 variants. The two variants that emerged in 2006 had wider geographic distribution and resulted in higher outbreak activity compared to other variants. The outbreak settings were analyzed. Community-based group residence was the most common for both GII.4 variants and non-GII.4 variants. GII.4 variants were more commonly associated with outbreaks in acute care hospitals while outbreaks associated non-GII.4 variants were more commonly seen in school and community social events settings (p

MYH9 was recently identified as renal susceptibility gene (OR 3-8, p < 10(-8)) for major forms of kidney disease disproportionately affecting individuals of African descent. The risk haplotype (E-1) occurs at much higher frequencies in African Americans (> or = 60%) than in European Americans (< 4%), revealing a genetic basis for a major health disparity. The population distributions of MYH9 risk alleles and the E-1 risk haplotype and the demographic and selective forces acting on the MYH9 region are not well explored. We reconstructed MYH9 haplotypes from 4 tagging single nucleotide polymorphisms (SNPs) spanning introns 12-23 using available data from HapMap Phase II, and by genotyping 938 DNAs from the Human Genome Diversity Panel (HGDP). The E-1 risk haplotype followed a cline, being most frequent within sub-Saharan African populations (range 50-80%), less frequent in populations from the Middle East (9-27%) and Europe (0-9%), and rare or absent in Asia, the Americas, and Oceania. The fixation indexes (F(ST)) for pairwise comparisons between the risk haplotypes for continental populations were calculated for MYH9 haplotypes; F(ST) ranged from 0.27-0.40 for Africa compared to other continental populations, possibly due to selection. Uniquely in Africa, the Yoruba population showed high frequency extended haplotype length around the core risk allele (C) compared to the alternative allele (T) at the same locus (rs4821481, iHs = 2.67), as well as high population differentiation (F(ST(CEU vs. YRI)) = 0.51) in HapMap Phase II data, also observable only in the Yoruba population from HGDP (F(ST) = 0.49), pointing to an instance of recent selection in the genomic region. The population-specific divergence in MYH9 risk allele frequencies among the world's populations may prove important in risk assessment and public health policies to mitigate the burden of kidney disease in vulnerable populations.

Large, recently-available genomic databases cover a wide range of life forms, suggesting opportunity for insights into genetic structure of biodiversity. In this study we refine our recently-described technique using indicator vectors to analyze and visualize nucleotide sequences. The indicator vector approach generates correlation matrices, dubbed Klee diagrams, which represent a novel way of assembling and viewing large genomic datasets. To explore its potential utility, here we apply the improved algorithm to a collection of almost 17,000 DNA barcode sequences covering 12 widely-separated animal taxa, demonstrating that indicator vectors for classification gave correct assignment in all 11,000 test cases. Indicator vector analysis revealed discontinuities corresponding to species- and higher-level taxonomic divisions, suggesting an efficient approach to classification of organisms from poorly-studied groups. As compared to standard distance metrics, indicator vectors preserve diagnostic character probabilities, enable automated classification of test sequences, and generate high-information density single-page displays. These results support application of indicator vectors for comparative analysis of large nucleotide data sets and raise prospect of gaining insight into broad-scale patterns in the genetic structure of biodiversity.