Probalign: multiple sequence alignment using partition function posterior probabilities

PnpProbs: a better multiple sequence alignment tool by better handling of guide trees

BACKGROUND

This paper describes a new MSA tool called PnpProbs, which constructs better multiple sequence alignments by better handling of guide trees. It classifies sequences into two types: normally related and distantly related. For normally related sequences, it uses an adaptive approach to construct the guide tree needed for progressive alignment; it first estimates the input's discrepancy by computing the standard deviation of their percent identities, and based on this estimate, it chooses the better method to construct the guide tree. For distantly related sequences, PnpProbs abandons the guide tree and uses instead some non-progressive alignment method to generate the alignment.

RESULTS

To evaluate PnpProbs, we have compared it with thirteen other popular MSA tools, and PnpProbs has the best alignment scores in all but one test. We have also used it for phylogenetic analysis, and found that the phylogenetic trees constructed from PnpProbs' alignments are closest to the model trees.

CONCLUSIONS

By combining the strength of the progressive and non-progressive alignment methods, we have developed an MSA tool called PnpProbs. We have compared PnpProbs with thirteen other popular MSA tools and our results showed that our tool usually constructed the best alignments.

Functional characterization of GmBZL2 (AtBZR1 like gene) reveals the conserved BR signaling regulation in Glycine max

Brassinosteroids (BRs) play key roles in plant growth and development, and regulate various agricultural traits. Enhanced BR signaling leads to increased seed number and yield in Arabidopsis bzr1-1D (AtBZR1(P234L), gain-of-function mutant of the important transcription factor in BR signaling/effects). BR signal transduction pathway is well elucidated in Arabidopsis but less known in other species. Soybean is an important dicot crop producing edible oil and protein. Phylogenetic analysis reveals AtBZR1-like genes are highly conserved in angiosperm and there are 4 orthologues in soybean (GmBZL1-4). We here report the functional characterization of GmBZL2 (relatively highly expresses in flowers). The P234 site in AtBZR1 is conserved in GmBZL2 (P216) and mutation of GmBZL2(P216L) leads to GmBZL2 accumulation. GmBZL2(P216L) (GmBZL2*) in Arabidopsis results in enhanced BR signaling; including increased seed number per silique. GmBZL2* partially rescued the defects of bri1-5, further demonstrating the conserved function of GmBZL2 with AtBZR1. BR treatment promotes the accumulation, nuclear localization and dephosphorylation/phosphorylation ratio of GmBZL2, revealing that GmBZL2 activity is regulated conservatively by BR signaling. Our studies not only indicate the conserved regulatory mechanism of GmBZL2 and BR signaling pathway in soybean, but also suggest the potential application of GmBZL2 in soybean seed yield.

Promiscuous Pathogenicity Islands and Phylogeny of Pathogenic Streptomyces spp

Approximately 10 Streptomyces species cause disease on underground plant structures. The most economically important of these is potato scab, and the most studied of these pathogens is Streptomyces scabiei (syn. S. scabies). The main pathogenicity determinant of scab-causing Streptomyces species is a nitrated diketopiperazine, known as thaxtomin A (ThxA). In the pathogenic species Streptomyces turgidiscabies, ThxA biosynthetic genes reside on a mobile pathogenicity island (PAI). However, the mobilization of PAIs in other Streptomyces species remains uncharacterized. Here, we investigated the mobilization of the PAI of S. scabiei 87-22. Based on whole genome sequences, we inferred the evolutionary relationships of pathogenic Streptomyces species and discovered that Streptomyces sp. strain 96-12, a novel pathogenic species isolated from potatoes in Egypt, was phylogenetically grouped with nonpathogenic species rather than with known pathogenic species. We also found that Streptomyces sp. strain 96-12 contains a PAI that is almost identical to the PAI in S. scabiei 87-22, despite significant differences in their genome sequences. This suggested direct or indirect in vivo mobilization of the PAI between S. scabiei and nonpathogenic Streptomyces species. To test whether the S. scabiei 87-22 PAI could, indeed, be mobilized, S. scabiei 87-22 deletion mutants containing antibiotic resistance markers in the PAI were mated with Streptomyces diastatochromogenes, a nonpathogenic species. The PAI of S. scabiei was site-specifically inserted into the aviX1 gene of S. diastatochromogenes and conferred pathogenicity in radish seedling assays. Our results demonstrated that S. scabiei, the earliest described Streptomyces pathogen, could be the source of a PAI responsible for the emergence of novel pathogenic species.

Characterization of multiple sequence alignment errors using complete-likelihood score and position-shift map

BACKGROUND

Reconstruction of multiple sequence alignments (MSAs) is a crucial step in most homology-based sequence analyses, which constitute an integral part of computational biology. To improve the accuracy of this crucial step, it is essential to better characterize errors that state-of-the-art aligners typically make. For this purpose, we here introduce two tools: the complete-likelihood score and the position-shift map.

RESULTS

The logarithm of the total probability of a MSA under a stochastic model of sequence evolution along a time axis via substitutions, insertions and deletions (called the "complete-likelihood score" here) can serve as an ideal score of the MSA. A position-shift map, which maps the difference in each residue's position between two MSAs onto one of them, can clearly visualize where and how MSA errors occurred and help disentangle composite errors. To characterize MSA errors using these tools, we constructed three sets of simulated MSAs of selectively neutral mammalian DNA sequences, with small, moderate and large divergences, under a stochastic evolutionary model with an empirically common power-law insertion/deletion length distribution. Then, we reconstructed MSAs using MAFFT and Prank as representative state-of-the-art single-optimum-search aligners. About 40-99% of the hundreds of thousands of gapped segments were involved in alignment errors. In a substantial fraction, from about 1/4 to over 3/4, of erroneously reconstructed segments, reconstructed MSAs by each aligner showed complete-likelihood scores not lower than those of the true MSAs. Out of the remaining errors, a majority by an iterative option of MAFFT showed discrepancies between the aligner-specific score and the complete-likelihood score, and a majority by Prank seemed due to inadequate exploration of the MSA space. Analyses by position-shift maps indicated that true MSAs are in considerable neighborhoods of reconstructed MSAs in about 80-99% of the erroneous segments for small and moderate divergences, but in only a minority for large divergences.

CONCLUSIONS

The results of this study suggest that measures to further improve the accuracy of reconstructed MSAs would substantially differ depending on the types of aligners. They also re-emphasize the importance of obtaining a probability distribution of fairly likely MSAs, instead of just searching for a single optimum MSA.

Experimental Approach Reveals the Role of alx1 in the Evolution of the Echinoderm Larval Skeleton

Over the course of evolution, the acquisition of novel structures has ultimately led to wide variation in morphology among extant multicellular organisms. Thus, the origins of genetic systems for new morphological structures are a subject of great interest in evolutionary biology. The larval skeleton is a novel structure acquired in some echinoderm lineages via the activation of the adult skeletogenic machinery. Previously, VEGF signaling was suggested to have played an important role in the acquisition of the larval skeleton. In the present study, we compared expression patterns of Alx genes among echinoderm classes to further explore the factors involved in the acquisition of a larval skeleton. We found that the alx1 gene, originally described as crucial for sea urchin skeletogenesis, may have also played an essential role in the evolution of the larval skeleton. Unlike those echinoderms that have a larval skeleton, we found that alx1 of starfish was barely expressed in early larvae that have no skeleton. When alx1 overexpression was induced via injection of alx1 mRNA into starfish eggs, the expression patterns of certain genes, including those possibly involved in skeletogenesis, were altered. This suggested that a portion of the skeletogenic program was induced solely by alx1. However, we observed no obvious external phenotype or skeleton. We concluded that alx1 was necessary but not sufficient for the acquisition of the larval skeleton, which, in fact, requires several genetic events. Based on these results, we discuss how the larval expression of alx1 contributed to the acquisition of the larval skeleton in the putative ancestral lineage of echinoderms.

Genome Content and Phylogenomics Reveal both Ancestral and Lateral Evolutionary Pathways in Plant-Pathogenic Streptomyces Species

Streptomyces spp. are highly differentiated actinomycetes with large, linear chromosomes that encode an arsenal of biologically active molecules and catabolic enzymes. Members of this genus are well equipped for life in nutrient-limited environments and are common soil saprophytes. Out of the hundreds of species in the genus Streptomyces, a small group has evolved the ability to infect plants. The recent availability of Streptomyces genome sequences, including four genomes of pathogenic species, provided an opportunity to characterize the gene content specific to these pathogens and to study phylogenetic relationships among them. Genome sequencing, comparative genomics, and phylogenetic analysis enabled us to discriminate pathogenic from saprophytic Streptomyces strains; moreover, we calculated that the pathogen-specific genome contains 4,662 orthologs. Phylogenetic reconstruction suggested that Streptomyces scabies and S. ipomoeae share an ancestor but that their biosynthetic clusters encoding the required virulence factor thaxtomin have diverged. In contrast, S. turgidiscabies and S. acidiscabies, two relatively unrelated pathogens, possess highly similar thaxtomin biosynthesis clusters, which suggests that the acquisition of these genes was through lateral gene transfer.

Prevalent Exon-Intron Structural Changes in the APETALA1/FRUITFULL, SEPALLATA, AGAMOUS-LIKE6, and FLOWERING LOCUS C MADS-Box Gene Subfamilies Provide New Insights into Their Evolution

AP1/FUL, SEP, AGL6, and FLC subfamily genes play important roles in flower development. The phylogenetic relationships among them, however, have been controversial, which impedes our understanding of the origin and functional divergence of these genes. One possible reason for the controversy may be the problems caused by changes in the exon-intron structure of genes, which, according to recent studies, may generate non-homologous sites and hamper the homology-based sequence alignment. In this study, we first performed exon-by-exon alignments of these and three outgroup subfamilies (SOC1, AG, and STK). Phylogenetic trees reconstructed based on these matrices show improved resolution and better congruence with species phylogeny. In the context of these phylogenies, we traced evolutionary changes of exon-intron structures in each subfamily. We found that structural changes have occurred frequently following gene duplication and speciation events. Notably, exons 7 and 8 (if present) suffered more structural changes than others. With the knowledge of exon-intron structural changes, we generated more reasonable alignments containing all the focal subfamilies. The resulting trees showed that the SEP subfamily is sister to the monophyletic group formed by AP1/FUL and FLC subfamily genes and that the AGL6 subfamily forms a sister group to the three abovementioned subfamilies. Based on this topology, we inferred the evolutionary history of exon-intron structural changes among different subfamilies. Particularly, we found that the eighth exon originated before the divergence of AP1/FUL, FLC, SEP, and AGL6 subfamilies and degenerated in the ancestral FLC-like gene. These results provide new insights into the origin and evolution of the AP1/FUL, FLC, SEP, and AGL6 subfamilies.

Non-canonical structure, function and phylogeny of the Bsister MADS-box gene OsMADS30 of rice (Oryza sativa)

Bsister MADS-box genes play key roles in female reproductive organ and seed development throughout seed plants. This view is supported by their high conservation in terms of sequence, expression and function. In grasses, there are three subclades of Bsister genes: the OsMADS29-, the OsMADS30- and the OsMADS31-like genes. Here, we report on the evolution of the OsMADS30-like genes. Our analyses indicate that these genes evolved under relaxed purifying selection and are rather weakly expressed. OsMADS30, the representative of the OsMADS30-like genes from rice (Oryza sativa), shows strong sequence deviations in its 3' region when compared to orthologues from other grass species. We show that this is due to a 2.4-kbp insertion, possibly of a hitherto unknown helitron, which confers a heterologous C-terminal domain to OsMADS30. This putative helitron is not present in the OsMADS30 orthologues from closely related wild rice species, pointing to a relatively recent insertion event. Unlike other Bsister mutants O. sativa plants carrying a T-DNA insertion in the OsMADS30 gene do not show aberrant seed phenotypes, indicating that OsMADS30 likely does not have a canonical 'Bsister function'. However, imaging-based phenotyping of the T-DNA carrying plants revealed alterations in shoot size and architecture. We hypothesize that sequence deviations that accumulated during a period of relaxed selection in the gene lineage that led to OsMADS30 and the alteration of the C-terminal domain might have been a precondition for a potential neo-functionalization of OsMADS30 in O. sativa.

MSAIndelFR: a scheme for multiple protein sequence alignment using information on indel flanking regions

Background

The alignment of multiple protein sequences is one of the most commonly performed tasks in bioinformatics. In spite of considerable research and efforts that have been recently deployed for improving the performance of multiple sequence alignment (MSA) algorithms, finding a highly accurate alignment between multiple protein sequences is still a challenging problem.

Results

We propose a novel and efficient algorithm called, MSAIndelFR, for multiple sequence alignment using the information on the predicted locations of IndelFRs and the computed average log–loss values obtained from IndelFR predictors, each of which is designed for a different protein fold. We demonstrate that the introduction of a new variable gap penalty function based on the predicted locations of the IndelFRs and the computed average log–loss values into the proposed algorithm substantially improves the protein alignment accuracy. This is illustrated by evaluating the performance of the algorithm in aligning sequences belonging to the protein folds for which the IndelFR predictors already exist and by using the reference alignments of the four popular benchmarks, BAliBASE 3.0, OXBENCH, PREFAB 4.0, and SABRE (SABmark 1.65).

Conclusions

We have proposed a novel and efficient algorithm, the MSAIndelFR algorithm, for multiple protein sequence alignment incorporating a new variable gap penalty function. It is shown that the performance of the proposed algorithm is superior to that of the most–widely used alignment algorithms, Clustal W2, Clustal Omega, Kalign2, MSAProbs, MAFFT, MUSCLE, ProbCons and Probalign, in terms of both the sum–of–pairs and total column metrics.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0826-3) contains supplementary material, which is available to authorized users.

Phylogenomic analysis of the genus Ralstonia based on 686 single-copy genes

The genus Ralstonia contains species that are devastating plant pathogens, opportunistic human pathogens, and/or important degraders of xenobiotic and recalcitrant compounds. However, significant nomenclature problems exist, especially for the Ralstonia solanacearum species complex which consists of four phylotypes. Phylogenomics of the Ralstonia genus was investigated via a comprehensive analysis of 39 Ralstonia genomes as well as four genomes of Cupriavidus necator (more commonly known by its previous name Ralstonia eutropha). These data revealed 686 single-copy orthologs that could be extracted from the Ralstonia core-genome and used to reconstruct the phylogeny of the genus Ralstonia. The generated tree has strong bootstrap support for almost all branches. We also estimated the in silico DNA-DNA hybridization (isDDH) and the average nucleotide identity (ANI) values between each genome. Our data confirmed that whole genome sequence data provides a powerful tool to resolve the complex taxonomic questions of the genus Ralstonia, e.g. strains of Ralstonia solanacearum phylotype IIA and IIB may represent two subspecies of R. solanacearum, and strains of R. solanacearum phylotype I and III may be classified into two subspecies of Ralstonia pseudosolanacearum. Recently, strains of R. solanacearum phylotype IV were proposed to be reclassified into different subspecies of Ralstonia syzygii; our study, however, showed that phylotype IV strains had high isDDH values (83.8-96.1 %), indicating it may be not appropriate to classify these closely related strains into different subspecies. We also evaluated the performance of six chromosomal housekeeping genes (gdhA, mutS, adk, leuS, rplB and gyrB) used in Ralstonia phylogenetic inference. The multilocus sequence analysis of these six marker genes was able to reliably infer the phylogenetic relationships of the genus Ralstonia.

Examining phylogenetic relationships of Erwinia and Pantoea species using whole genome sequence data

The genera Erwinia and Pantoea contain species that are devastating plant pathogens, non-pathogen epiphytes, and opportunistic human pathogens. However, some controversies persist in the taxonomic classification of these two closely related genera. The phylogenomic analysis of these two genera was investigated via a comprehensive analysis of 25 Erwinia genomes and 23 Pantoea genomes. Single-copy orthologs could be extracted from the Erwinia/Pantoea core-genome to reconstruct the Erwinia/Pantoea phylogeny. This tree has strong bootstrap support for almost all branches. We also estimated the in silico DNA-DNA hybridization (isDDH) and the average nucleotide identity (ANI) values between each genome; strains from the same species showed ANI values ≥96% and isDDH values >70%. These data confirm that whole genome sequence data provides a powerful tool to resolve the complex taxonomic questions of Erwinia/Pantoea, e.g. Pantoea agglomerans 299R was not clustered into a single group with other P. agglomerans strains, and the ANI values and isDDH values between them were <91% and around 43.8%, respectively. These data indicate P. agglomerans 299R should not be classified into the P. agglomerans species. In addition, another strain (Pantoea sp. At_9b) was identified that may represent a novel Pantoea species. We also evaluated the performance of six commonly used housekeeping genes (atpD, carA, gyrB, infB, recA, and rpoB) in phylogenetic inference. A single gene was not enough to obtain a reliable species tree, and it was necessary to use the multilocus sequence analysis of the six marker genes to recover the Erwinia/Pantoea phylogeny.

Efficient representation of uncertainty in multiple sequence alignments using directed acyclic graphs

BACKGROUND

A standard procedure in many areas of bioinformatics is to use a single multiple sequence alignment (MSA) as the basis for various types of analysis. However, downstream results may be highly sensitive to the alignment used, and neglecting the uncertainty in the alignment can lead to significant bias in the resulting inference. In recent years, a number of approaches have been developed for probabilistic sampling of alignments, rather than simply generating a single optimum. However, this type of probabilistic information is currently not widely used in the context of downstream inference, since most existing algorithms are set up to make use of a single alignment.

RESULTS

In this work we present a framework for representing a set of sampled alignments as a directed acyclic graph (DAG) whose nodes are alignment columns; each path through this DAG then represents a valid alignment. Since the probabilities of individual columns can be estimated from empirical frequencies, this approach enables sample-based estimation of posterior alignment probabilities. Moreover, due to conditional independencies between columns, the graph structure encodes a much larger set of alignments than the original set of sampled MSAs, such that the effective sample size is greatly increased.

CONCLUSIONS

The alignment DAG provides a natural way to represent a distribution in the space of MSAs, and allows for existing algorithms to be efficiently scaled up to operate on large sets of alignments. As an example, we show how this can be used to compute marginal probabilities for tree topologies, averaging over a very large number of MSAs. This framework can also be used to generate a statistically meaningful summary alignment; example applications show that this summary alignment is consistently more accurate than the majority of the alignment samples, leading to improvements in downstream tree inference. Implementations of the methods described in this article are available at http://statalign.github.io/WeaveAlign .

Genome based phylogeny and comparative genomic analysis of intra-mammary pathogenic Escherichia coli

Escherichia coli is an important cause of bovine mastitis and can cause both severe inflammation with a short-term transient infection, as well as less severe, but more chronic inflammation and infection persistence. E. coli is a highly diverse organism that has been classified into a number of different pathotypes or pathovars, and mammary pathogenic E. coli (MPEC) has been proposed as a new such pathotype. The purpose of this study was to use genome sequence data derived from both transient and persistent MPEC isolates (two isolates of each phenotype) to construct a genome-based phylogeny that places MPEC in its phylogenetic context with other E. coli pathovars. A subsidiary goal was to conduct comparative genomic analyses of these MPEC isolates with other E. coli pathovars to provide a preliminary perspective on loci that might be correlated with the MPEC phenotype. Both concatenated and consensus tree phylogenies did not support MPEC monophyly or the monophyly of either transient or persistent phenotypes. Three of the MPEC isolates (ECA-727, ECC-Z, and ECA-O157) originated from within the predominately commensal clade of E. coli, referred to as phylogroup A. The fourth MPEC isolate, of the persistent phenotype (ECC-1470), was sister group to an isolate of ETEC, falling within the E. coli B1 clade. This suggests that the MPEC phenotype has arisen on numerous independent occasions and that this has often, although not invariably, occurred from commensal ancestry. Examination of the genes present in the MPEC strains relative to the commensal strains identified a consistent presence of the type VI secretion system (T6SS) in the MPEC strains, with only occasional representation in commensal strains, suggesting that T6SS may be associated with MPEC pathogenesis and/or as an inter-bacterial competitive attribute and therefore could represent a useful target to explore for the development of MPEC specific inhibitors.

Improving multiple sequence alignment by using better guide trees

Progressive sequence alignment is one of the most commonly used method for multiple sequence alignment. Roughly speaking, the method first builds a guide tree, and then aligns the sequences progressively according to the topology of the tree. It is believed that guide trees are very important to progressive alignment; a better guide tree will give an alignment with higher accuracy. Recently, we have proposed an adaptive method for constructing guide trees. This paper studies the quality of the guide trees constructed by such method. Our study showed that our adaptive method can be used to improve the accuracy of many different progressive MSA tools. In fact, we give evidences showing that the guide trees constructed by the adaptive method are among the best.

Phylogenomics and the dynamic genome evolution of the genus Streptococcus

The genus Streptococcus comprises important pathogens that have a severe impact on human health and are responsible for substantial economic losses to agriculture. Here, we utilize 46 Streptococcus genome sequences (44 species), including eight species sequenced here, to provide the first genomic level insight into the evolutionary history and genetic basis underlying the functional diversity of all major groups of this genus. Gene gain/loss analysis revealed a dynamic pattern of genome evolution characterized by an initial period of gene gain followed by a period of loss, as the major groups within the genus diversified. This was followed by a period of genome expansion associated with the origins of the present extant species. The pattern is concordant with an emerging view that genomes evolve through a dynamic process of expansion and streamlining. A large proportion of the pan-genome has experienced lateral gene transfer (LGT) with causative factors, such as relatedness and shared environment, operating over different evolutionary scales. Multiple gene ontology terms were significantly enriched for each group, and mapping terms onto the phylogeny showed that those corresponding to genes born on branches leading to the major groups represented approximately one-fifth of those enriched. Furthermore, despite the extensive LGT, several biochemical characteristics have been retained since group formation, suggesting genomic cohesiveness through time, and that these characteristics may be fundamental to each group. For example, proteolysis: mitis group; urea metabolism: salivarius group; carbohydrate metabolism: pyogenic group; and transcription regulation: bovis group.

Effective alignment of RNA pseudoknot structures using partition function posterior log-odds scores

Background

RNA pseudoknots play important roles in many biological processes. Previous methods for comparative pseudoknot analysis mainly focus on simultaneous folding and alignment of RNA sequences. Little work has been done to align two known RNA secondary structures with pseudoknots taking into account both sequence and structure information of the two RNAs.

Results

In this article we present a novel method for aligning two known RNA secondary structures with pseudoknots. We adopt the partition function methodology to calculate the posterior log-odds scores of the alignments between bases or base pairs of the two RNAs with a dynamic programming algorithm. The posterior log-odds scores are then used to calculate the expected accuracy of an alignment between the RNAs. The goal is to find an optimal alignment with the maximum expected accuracy. We present a heuristic to achieve this goal. The performance of our method is investigated and compared with existing tools for RNA structure alignment. An extension of the method to multiple alignment of pseudoknot structures is also discussed.

Conclusions

The method described here has been implemented in a tool named RKalign, which is freely accessible on the Internet. As more and more pseudoknots are revealed, collected and stored in public databases, we anticipate a tool like RKalign will play a significant role in data comparison, annotation, analysis, and retrieval in these databases.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0464-9) contains supplementary material, which is available to authorized users.

Accurate multiple network alignment through context-sensitive random walk

Background

Comparative network analysis can provide an effective means of analyzing large-scale biological networks and gaining novel insights into their structure and organization. Global network alignment aims to predict the best overall mapping between a given set of biological networks, thereby identifying important similarities as well as differences among the networks. It has been shown that network alignment methods can be used to detect pathways or network modules that are conserved across different networks. Until now, a number of network alignment algorithms have been proposed based on different formulations and approaches, many of them focusing on pairwise alignment.

Results

In this work, we propose a novel multiple network alignment algorithm based on a context-sensitive random walk model. The random walker employed in the proposed algorithm switches between two different modes, namely, an individual walk on a single network and a simultaneous walk on two networks. The switching decision is made in a context-sensitive manner by examining the current neighborhood, which is effective for quantitatively estimating the degree of correspondence between nodes that belong to different networks, in a manner that sensibly integrates node similarity and topological similarity. The resulting node correspondence scores are then used to predict the maximum expected accuracy (MEA) alignment of the given networks.

Conclusions

Performance evaluation based on synthetic networks as well as real protein-protein interaction networks shows that the proposed algorithm can construct more accurate multiple network alignments compared to other leading methods.

GLProbs: Aligning Multiple Sequences Adaptively

This paper introduces a simple and effective approach to improve the accuracy of multiple sequence alignment. We use a natural measure to estimate the similarity of the input sequences, and based on this measure, we align the input sequences differently. For example, for inputs with high similarity, we consider the whole sequences and align them globally, while for those with moderately low similarity, we may ignore the flank regions and align them locally. To test the effectiveness of this approach, we have implemented a multiple sequence alignment tool called GLProbs and compared its performance with about one dozen leading alignment tools on three benchmark alignment databases, and GLProbs's alignments have the best scores in almost all testings. We have also evaluated the practicability of the alignments of GLProbs by applying the tool to three biological applications, namely phylogenetic trees construction, protein secondary structure prediction and the detection of high risk members for cervical cancer in the HPV-E6 family, and the results are very encouraging.

Inflammation-associated adherent-invasive Escherichia coli are enriched in pathways for use of propanediol and iron and M-cell translocation

BACKGROUND

Perturbations of the intestinal microbiome, termed dysbiosis, are linked to intestinal inflammation. Isolation of adherent-invasive Escherichia coli (AIEC) from intestines of patients with Crohn's disease (CD), dogs with granulomatous colitis, and mice with acute ileitis suggests these bacteria share pathoadaptive virulence factors that promote inflammation.

METHODS

To identify genes associated with AIEC, we sequenced the genomes of phylogenetically diverse AIEC strains isolated from people with CD (4), dogs with granulomatous colitis (2), and mice with ileitis (2) and 1 non-AIEC strain from CD ileum and compared them with 38 genome sequences of E. coli and Shigella. We then determined the prevalence of AIEC-associated genes in 49 E. coli strains from patients with CD and controls and correlated genotype with invasion of intestinal epithelial cells, persistence within macrophages, AIEC pathotype, and growth in standardized conditions.

RESULTS

Genes encoding propanediol utilization (pdu operon) and iron acquisition (yersiniabactin, chu operon) were overrepresented in AIEC relative to nonpathogenic E. coli. PduC (propanediol dehydratase) was enriched in CD-derived AIEC, correlated with increased cellular invasion, and persistence in vitro and was increasingly expressed in fucose-containing media. Growth of AIEC required iron, and the presence of chuA (heme acquisition) correlated with persistence in macrophages. CD-associated AIEC with lpfA 154 (long polar fimbriae) demonstrated increased invasion of epithelial cells and translocation across M cells.

CONCLUSIONS

Our findings provide novel insights into the genetic basis of the AIEC pathotype, supporting the concept that AIEC are equipped to exploit and promote intestinal inflammation and reveal potential targets for intervention against AIEC and inflammation-associated dysbiosis.

MADS goes genomic in conifers: towards determining the ancestral set of MADS-box genes in seed plants

BACKGROUND AND AIMS

MADS-box genes comprise a gene family coding for transcription factors. This gene family expanded greatly during land plant evolution such that the number of MADS-box genes ranges from one or two in green algae to around 100 in angiosperms. Given the crucial functions of MADS-box genes for nearly all aspects of plant development, the expansion of this gene family probably contributed to the increasing complexity of plants. However, the expansion of MADS-box genes during one important step of land plant evolution, namely the origin of seed plants, remains poorly understood due to the previous lack of whole-genome data for gymnosperms.

METHODS

The newly available genome sequences of Picea abies, Picea glauca and Pinus taeda were used to identify the complete set of MADS-box genes in these conifers. In addition, MADS-box genes were identified in the growing number of transcriptomes available for gymnosperms. With these datasets, phylogenies were constructed to determine the ancestral set of MADS-box genes of seed plants and to infer the ancestral functions of these genes.

KEY RESULTS

Type I MADS-box genes are under-represented in gymnosperms and only a minimum of two Type I MADS-box genes have been present in the most recent common ancestor (MRCA) of seed plants. In contrast, a large number of Type II MADS-box genes were found in gymnosperms. The MRCA of extant seed plants probably possessed at least 11-14 Type II MADS-box genes. In gymnosperms two duplications of Type II MADS-box genes were found, such that the MRCA of extant gymnosperms had at least 14-16 Type II MADS-box genes.

CONCLUSIONS

The implied ancestral set of MADS-box genes for seed plants shows simplicity for Type I MADS-box genes and remarkable complexity for Type II MADS-box genes in terms of phylogeny and putative functions. The analysis of transcriptome data reveals that gymnosperm MADS-box genes are expressed in a great variety of tissues, indicating diverse roles of MADS-box genes for the development of gymnosperms. This study is the first that provides a comprehensive overview of MADS-box genes in conifers and thus will provide a framework for future work on MADS-box genes in seed plants.

Horizontal gene transfer and functional diversification of plant cell wall degrading polygalacturonases: Key events in the evolution of herbivory in beetles

Plant cell walls are the largest reservoir of organic carbon on earth. To breach and utilize this carbohydrate-rich protective barrier, microbes secrete plant cell wall degrading enzymes (PCWDEs) targeting pectin, cellulose and hemicelluloses. There is a growing body of evidence that genomes of some herbivorous insects also encode PCWDEs, raising questions about their evolutionary origins and functions. Among herbivorous beetles, pectin-degrading polygalacturonases (PGs) are found in the diverse superfamilies Chrysomeloidea (leaf beetles, long-horn beetles) and Curculionoidea (weevils). Here our aim was to test whether these arose from a common ancestor of beetles or via horizontal gene transfer (HGT), and whether PGs kept their ancestral function in degrading pectin or evolved novel functions. Transcriptome data derived from 10 beetle species were screened for PG-encoding sequences and used for phylogenetic comparisons with their bacterial, fungal and plant counterparts. These analyses revealed a large family of PG-encoding genes of Chrysomeloidea and Curculionoidea sharing a common ancestor, most similar to PG genes of ascomycete fungi. In addition, 50 PGs from beetle digestive systems were heterologously expressed and functionally characterized, showing a set of lineage-specific consecutively pectin-degrading enzymes, as well as conserved but enzymatically inactive PG proteins. The evidence indicates that a PG gene was horizontally transferred ∼200 million years ago from an ascomycete fungus to a common ancestor of Chrysomeloidea and Curculionoidea. This has been followed by independent duplications in these two lineages, as well as independent replacement in two sublineages of Chrysomeloidea by two other subsequent HGTs. This origin, leading to subsequent functional diversification of the PG gene family within its new hosts, was a key event promoting the evolution of herbivory in these beetles.

MSARC: Multiple sequence alignment by residue clustering

Background

Progressive methods offer efficient and reasonably good solutions to the multiple sequence alignment problem. However, resulting alignments are biased by guide-trees, especially for relatively distant sequences.

Results

We propose MSARC, a new graph-clustering based algorithm that aligns sequence sets without guide-trees. Experiments on the BAliBASE dataset show that MSARC achieves alignment quality similar to the best progressive methods.

Furthermore, MSARC outperforms them on sequence sets whose evolutionary distances are difficult to represent by a phylogenetic tree. These datasets are most exposed to the guide-tree bias of alignments.

Availability

MSARC is available at http://bioputer.mimuw.edu.pl/msarc

TCS: a new multiple sequence alignment reliability measure to estimate alignment accuracy and improve phylogenetic tree reconstruction

Multiple sequence alignment (MSA) is a key modeling procedure when analyzing biological sequences. Homology and evolutionary modeling are the most common applications of MSAs. Both are known to be sensitive to the underlying MSA accuracy. In this work, we show how this problem can be partly overcome using the transitive consistency score (TCS), an extended version of the T-Coffee scoring scheme. Using this local evaluation function, we show that one can identify the most reliable portions of an MSA, as judged from BAliBASE and PREFAB structure-based reference alignments. We also show how this measure can be used to improve phylogenetic tree reconstruction using both an established simulated data set and a novel empirical yeast data set. For this purpose, we describe a novel lossless alternative to site filtering that involves overweighting the trustworthy columns. Our approach relies on the T-Coffee framework; it uses libraries of pairwise alignments to evaluate any third party MSA. Pairwise projections can be produced using fast or slow methods, thus allowing a trade-off between speed and accuracy. We compared TCS with Heads-or-Tails, GUIDANCE, Gblocks, and trimAl and found it to lead to significantly better estimates of structural accuracy and more accurate phylogenetic trees. The software is available from www.tcoffee.org/Projects/tcs.

Assessing the efficiency of multiple sequence alignment programs

Background

Multiple sequence alignment (MSA) is an extremely useful tool for molecular and evolutionary biology and there are several programs and algorithms available for this purpose. Although previous studies have compared the alignment accuracy of different MSA programs, their computational time and memory usage have not been systematically evaluated. Given the unprecedented amount of data produced by next generation deep sequencing platforms, and increasing demand for large-scale data analysis, it is imperative to optimize the application of software. Therefore, a balance between alignment accuracy and computational cost has become a critical indicator of the most suitable MSA program. We compared both accuracy and cost of nine popular MSA programs, namely CLUSTALW, CLUSTAL OMEGA, DIALIGN-TX, MAFFT, MUSCLE, POA, Probalign, Probcons and T-Coffee, against the benchmark alignment dataset BAliBASE and discuss the relevance of some implementations embedded in each program’s algorithm. Accuracy of alignment was calculated with the two standard scoring functions provided by BAliBASE, the sum-of-pairs and total-column scores, and computational costs were determined by collecting peak memory usage and time of execution.

Results

Our results indicate that mostly the consistency-based programs Probcons, T-Coffee, Probalign and MAFFT outperformed the other programs in accuracy. Whenever sequences with large N/C terminal extensions were present in the BAliBASE suite, Probalign, MAFFT and also CLUSTAL OMEGA outperformed Probcons and T-Coffee. The drawback of these programs is that they are more memory-greedy and slower than POA, CLUSTALW, DIALIGN-TX, and MUSCLE. CLUSTALW and MUSCLE were the fastest programs, being CLUSTALW the least RAM memory demanding program.

Conclusions

Based on the results presented herein, all four programs Probcons, T-Coffee, Probalign and MAFFT are well recommended for better accuracy of multiple sequence alignments. T-Coffee and recent versions of MAFFT can deliver faster and reliable alignments, which are specially suited for larger datasets than those encountered in the BAliBASE suite, if multi-core computers are available. In fact, parallelization of alignments for multi-core computers should probably be addressed by more programs in a near future, which will certainly improve performance significantly.

QuickProbs--a fast multiple sequence alignment algorithm designed for graphics processors

Multiple sequence alignment is a crucial task in a number of biological analyses like secondary structure prediction, domain searching, phylogeny, etc. MSAProbs is currently the most accurate alignment algorithm, but its effectiveness is obtained at the expense of computational time. In the paper we present QuickProbs, the variant of MSAProbs customised for graphics processors. We selected the two most time consuming stages of MSAProbs to be redesigned for GPU execution: the posterior matrices calculation and the consistency transformation. Experiments on three popular benchmarks (BAliBASE, PREFAB, OXBench-X) on quad-core PC equipped with high-end graphics card show QuickProbs to be 5.7 to 9.7 times faster than original CPU-parallel MSAProbs. Additional tests performed on several protein families from Pfam database give overall speed-up of 6.7. Compared to other algorithms like MAFFT, MUSCLE, or ClustalW, QuickProbs proved to be much more accurate at similar speed. Additionally we introduce a tuned variant of QuickProbs which is significantly more accurate on sets of distantly related sequences than MSAProbs without exceeding its computation time. The GPU part of QuickProbs was implemented in OpenCL, thus the package is suitable for graphics processors produced by all major vendors.

Multiple sequence alignment using Probcons and Probalign

Sequence alignment remains a fundamental task in bioinformatics. The literature contains programs that employ a host of exact and heuristic strategies available in computer science. Probcons was the first program to construct maximum expected accuracy sequence alignments with hidden Markov models and at the time of its publication achieved the highest accuracies on standard protein multiple alignment benchmarks. Probalign followed this strategy except that it used a partition function approach instead of hidden Markov models. Several programs employing both strategies have been published since then. In this chapter we describe Probcons and Probalign.

MAFFT: iterative refinement and additional methods

This chapter outlines several methods implemented in the MAFFT package. MAFFT is a popular multiple sequence alignment (MSA) program with various options for the progressive method, the iterative refinement method and other methods. We first outline basic usage of MAFFT and then describe recent practical extensions, such as dot plot and adjustment of direction in DNA alignment. We also refer to MUSCLE, another high-performance MSA program.

PicXAA: a probabilistic scheme for finding the maximum expected accuracy alignment of multiple biological sequences

PicXAA is a probabilistic nonprogressive alignment algorithm that finds protein (or DNA) multiple sequence alignments with maximum expected accuracy. PicXAA greedily builds up the alignment from sequence regions with high local similarity, thereby yielding an accurate global alignment that effectively captures the local similarities across sequences. PicXAA constantly yields accurate alignment results on a wide range of reference sets that have different characteristics, with especially remarkable improvements over other leading algorithms on sequence sets with high local similarities. In this chapter, we describe the overall alignment strategy used in PicXAA and discuss several important considerations for effective deployment of the algorithm.

Putative sugar transporters of the mustard leaf beetle Phaedon cochleariae: their phylogeny and role for nutrient supply in larval defensive glands

Background

Phytophagous insects have emerged successfully on the planet also because of the development of diverse and often astonishing defensive strategies against their enemies. The larvae of the mustard leaf beetle Phaedon cochleariae, for example, secrete deterrents from specialized defensive glands on their back. The secretion process involves ATP-binding cassette transporters. Therefore, sugar as one of the major energy sources to fuel the ATP synthesis for the cellular metabolism and transport processes, has to be present in the defensive glands. However, the role of sugar transporters for the production of defensive secretions was not addressed until now.

Results

To identify sugar transporters in P. cochleariae, a transcript catalogue was created by Illumina sequencing of cDNA libraries. A total of 68,667 transcripts were identified and 68 proteins were annotated as either members of the solute carrier 2 (SLC2) family or trehalose transporters. Phylogenetic analyses revealed an extension of the mammalian GLUT6/8 class in insects as well as one group of transporters exhibiting distinctive conserved motifs only present in the insect order Coleoptera. RNA-seq data of samples derived from the defensive glands revealed six transcripts encoding sugar transporters with more than 3,000 counts. Two of them are exclusively expressed in the glandular tissue. Reduction in secretions production was accomplished by silencing two of four selected transporters. RNA-seq experiments of transporter-silenced larvae showed the down-regulation of the silenced transporter but concurrently the up-regulation of other SLC2 transporters suggesting an adaptive system to maintain sugar homeostasis in the defensive glands.

Conclusion

We provide the first comprehensive phylogenetic study of the SLC2 family in a phytophagous beetle species. RNAi and RNA-seq experiments underline the importance of SLC2 transporters in defensive glands to achieve a chemical defense for successful competitive interaction in natural ecosystems.

PSAR-align: improving multiple sequence alignment using probabilistic sampling

SUMMARY

We developed PSAR-Align, a multiple sequence realignment tool that can refine a given multiple sequence alignment based on suboptimal alignments generated by probabilistic sampling. Our evaluation demonstrated that PSAR-Align is able to improve the results from various multiple sequence alignment tools.

AVAILABILITY AND IMPLEMENTATION

The PSAR-Align source code (implemented mainly in C++) is freely available for download at http://bioen-compbio.bioen.illinois.edu/PSAR-Align.

Heuristic alignment methods

Computation of multiple sequence alignment (MSA) is usually formulated as a combinatory optimization problem of an objective function. Solving the problem for virtually all sensible objective functions is known to be NP-complete implying that some heuristics must be adopted. Several general strategies have been proven effective to obtain accurate MSAs in reasonable computational costs. This chapter is devoted to a brief summary of most successful heuristic approaches.

Characterization of the heart transcriptome of the white shark (Carcharodon carcharias)

BACKGROUND

The white shark (Carcharodon carcharias) is a globally distributed, apex predator possessing physical, physiological, and behavioral traits that have garnered it significant public attention. In addition to interest in the genetic basis of its form and function, as a representative of the oldest extant jawed vertebrate lineage, white sharks are also of conservation concern due to their small population size and threat from overfishing. Despite this, surprisingly little is known about the biology of white sharks, and genomic resources are unavailable. To address this deficit, we combined Roche-454 and Illumina sequencing technologies to characterize the first transciptome of any tissue for this species.

RESULTS

From white shark heart cDNA we generated 665,399 Roche 454 reads (median length 387-bp) that were assembled into 141,626 contigs (mean length 503-bp). We also generated 78,566,588 Illumina reads, which we aligned to the 454 contigs producing 105,014 454/Illumina consensus sequences. To these, we added 3,432 non-singleton 454 contigs. By comparing these sequences to the UniProtKB/Swiss-Prot database we were able to annotate 21,019 translated open reading frames (ORFs) of ≥ 20 amino acids. Of these, 19,277 were additionally assigned Gene Ontology (GO) functional annotations. While acknowledging the limitations of our single tissue transcriptome, Fisher tests showed the white shark transcriptome to be significantly enriched for numerous metabolic GO terms compared to the zebra fish and human transcriptomes, with white shark showing more similarity to human than to zebra fish (i.e. fewer terms were significantly different). We also compared the transcriptome to other available elasmobranch sequences, for signatures of positive selection and identified several genes of putative adaptive significance on the white shark lineage. The white shark transcriptome also contained 8,404 microsatellites (dinucleotide, trinucleotide, or tetranucleotide motifs ≥ five perfect repeats). Detailed characterization of these microsatellites showed that ORFs with trinucleotide repeats, were significantly enriched for transcription regulatory roles and that trinucleotide frequency within ORFs was lower than for a wide range of taxonomic groups including other vertebrates.

CONCLUSION

The white shark heart transcriptome represents a valuable resource for future elasmobranch functional and comparative genomic studies, as well as for population and other biological studies vital for effective conservation of this globally vulnerable species.

The evolution of small insertions and deletions in the coding genes of Drosophila melanogaster

Studies of protein evolution have focused on amino acid substitutions with much less systematic analysis on insertion and deletions (indels) in protein coding genes. We hence surveyed 7,500 genes between Drosophila melanogaster and D. simulans, using D. yakuba as an outgroup for this purpose. The evolutionary rate of coding indels is indeed low, at only 3% of that of nonsynonymous substitutions. As coding indels follow a geometric distribution in size and tend to fall in low-complexity regions of proteins, it is unclear whether selection or mutation underlies this low rate. To resolve the issue, we collected genomic sequences from an isogenic African line of D. melanogaster (ZS30) at a high coverage of 70× and analyzed indel polymorphism between ZS30 and the reference genome. In comparing polymorphism and divergence, we found that the divergence to polymorphism ratio (i.e., fixation index) for smaller indels (size ≤ 10 bp) is very similar to that for synonymous changes, suggesting that most of the within-species polymorphism and between-species divergence for indels are selectively neutral. Interestingly, deletions of larger sizes (size ≥ 11 bp and ≤ 30 bp) have a much higher fixation index than synonymous mutations and 44.4% of fixed middle-sized deletions are estimated to be adaptive. To our surprise, this pattern is not found for insertions. Protein indel evolution appear to be in a dynamic flux of neutrally driven expansion (insertions) together with adaptive-driven contraction (deletions), and these observations provide important insights for understanding the fitness of new mutations as well as the evolutionary driving forces for genomic evolution in Drosophila species.

Adaptive radiation of chemosymbiotic deep-sea mussels

Adaptive radiations present fascinating opportunities for studying the evolutionary process. Most cases come from isolated lakes or islands, where unoccupied ecological space is filled through novel adaptations. Here, we describe an unusual example of an adaptive radiation: symbiotic mussels that colonized island-like chemosynthetic environments such as hydrothermal vents, cold seeps and sunken organic substrates on the vast deep-sea floor. Our time-calibrated molecular phylogeny suggests that the group originated and acquired sulfur-oxidizing symbionts in the Late Cretaceous, possibly while inhabiting organic substrates and long before its major radiation in the Middle Eocene to Early Oligocene. The first appearance of intracellular and methanotrophic symbionts was detected only after this major radiation. Thus, contrary to expectations, the major radiation may have not been triggered by the evolution of novel types of symbioses. We hypothesize that environmental factors, such as increased habitat availability and/or increased dispersal capabilities, sparked the radiation. Intracellular and methanotrophic symbionts were acquired in several independent lineages and marked the onset of a second wave of diversification at vents and seeps. Changes in habitat type resulted in adaptive trends in shell lengths (related to the availability of space and energy, and physiological trade-offs) and in the successive colonization of greater water depths.

An Overview of Multiple Sequence Alignments and Cloud Computing in Bioinformatics

Multiple sequence alignment (MSA) of DNA, RNA, and protein sequences is one of the most essential techniques in the fields of molecular biology, computational biology, and bioinformatics. Next-generation sequencing technologies are changing the biology landscape, flooding the databases with massive amounts of raw sequence data. MSA of ever-increasing sequence data sets is becoming a significant bottleneck. In order to realise the promise of MSA for large-scale sequence data sets, it is necessary for existing MSA algorithms to be run in a parallelised fashion with the sequence data distributed over a computing cluster or server farm. Combining MSA algorithms with cloud computing technologies is therefore likely to improve the speed, quality, and capability for MSA to handle large numbers of sequences. In this review, multiple sequence alignments are discussed, with a specific focus on the ClustalW and Clustal Omega algorithms. Cloud computing technologies and concepts are outlined, and the next generation of cloud base MSA algorithms is introduced.

Using tertiary structure for the computation of highly accurate multiple RNA alignments with the SARA-Coffee package

MOTIVATION

Aligning RNAs is useful to search for homologous genes, study evolutionary relationships, detect conserved regions and identify any patterns that may be of biological relevance. Poor levels of conservation among homologs, however, make it difficult to compare RNA sequences, even when considering closely evolutionary related sequences.

RESULTS

We describe SARA-Coffee, a tertiary structure-based multiple RNA aligner, which has been validated using BRAliDARTS, a new benchmark framework designed for evaluating tertiary structure-based multiple RNA aligners. We provide two methods to measure the capacity of alignments to match corresponding secondary and tertiary structure features. On this benchmark, SARA-Coffee outperforms both regular aligners and those using secondary structure information. Furthermore, we show that on sequences in which <60% of the nucleotides form base pairs, primary sequence methods usually perform better than secondary-structure aware aligners.

AVAILABILITY AND IMPLEMENTATION

The package and the datasets are available from http://www.tcoffee.org/Projects/saracoffee and http://structure.biofold.org/sara/.

Convergent evolution of heat-inducibility during subfunctionalization of the Hsp70 gene family

BACKGROUND

Heat-shock proteins of the 70 kDa family (Hsp70s) are essential chaperones required for key cellular functions. In eukaryotes, four subfamilies can be distinguished according to their function and localisation in different cellular compartments: cytosol, endoplasmic reticulum, mitochondria and chloroplasts. Generally, multiple cytosol-type Hsp70s can be found in metazoans that show either constitutive expression and/or stress-inducibility, arguing for the evolution of different tasks and functions. Information about the hsp70 copy number and diversity in microbial eukaryotes is, however, scarce, and detailed knowledge about the differential gene expression in most protists is lacking. Therefore, we have characterised the Hsp70 gene family of Paramecium caudatum to gain insight into the evolution and differential heat stress response of the distinct family members in protists and to investigate the diversification of eukaryotic hsp70s focusing on the evolution of heat-inducibility.

RESULTS

Eleven putative hsp70 genes could be detected in P. caudatum comprising homologs of three major Hsp70-subfamilies. Phylogenetic analyses revealed five evolutionarily distinct Hsp70-groups, each with a closer relationship to orthologous sequences of Paramecium tetraurelia than to another P. caudatum Hsp70-group. These highly diverse, paralogous groups resulted from duplications preceding Paramecium speciation, underwent divergent evolution and were subject to purifying selection. Heat-shock treatments were performed to test for differential expression patterns among the five Hsp70-groups as well as for a functional conservation within Paramecium. These treatments induced exceptionally high mRNA up-regulations in one cytosolic group with a low basal expression, indicative for the major heat inducible hsp70s. All other groups showed comparatively high basal expression levels and moderate heat-inducibility, signifying constitutively expressed genes. Comparative EST analyses for P. tetraurelia hsp70s unveiled a corresponding expression pattern, which supports a functionally conserved evolution of the Hsp70 gene family in Paramecium.

CONCLUSIONS

Our analyses suggest an independent evolution of the heat-inducible cytosol-type hsp70s in Paramecium and in its close relative Tetrahymena, as well as within higher eukaryotes. This result indicates convergent evolution during hsp70 subfunctionalization and implies that heat-inducibility evolved several times during the course of eukaryotic evolution.

Making automated multiple alignments of very large numbers of protein sequences

MOTIVATION

Recent developments in sequence alignment software have made possible multiple sequence alignments (MSAs) of >100 000 sequences in reasonable times. At present, there are no systematic analyses concerning the scalability of the alignment quality as the number of aligned sequences is increased.

RESULTS

We benchmarked a wide range of widely used MSA packages using a selection of protein families with some known structures and found that the accuracy of such alignments decreases markedly as the number of sequences grows. This is more or less true of all packages and protein families. The phenomenon is mostly due to the accumulation of alignment errors, rather than problems in guide-tree construction. This is partly alleviated by using iterative refinement or selectively adding sequences. The average accuracy of progressive methods by comparison with structure-based benchmarks can be improved by incorporating information derived from high-quality structural alignments of sequences with solved structures. This suggests that the availability of high quality curated alignments will have to complement algorithmic and/or software developments in the long-term.

AVAILABILITY AND IMPLEMENTATION

Benchmark data used in this study are available at http://www.clustal.org/omega/homfam-20110613-25.tar.gz and http://www.clustal.org/omega/bali3fam-26.tar.gz.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A data parallel strategy for aligning multiple biological sequences on multi-core computers

In this paper, we address the large-scale biological sequence alignment problem, which has an increasing demand in computational biology. We employ data parallelism paradigm that is suitable for handling large-scale processing on multi-core computers to achieve a high degree of parallelism. Using the data parallelism paradigm, we propose a general strategy which can be used to speed up any multiple sequence alignment method. We applied five different clustering algorithms in our strategy and implemented rigorous tests on an 8-core computer using four traditional benchmarks and artificially generated sequences. The results show that our multi-core-based implementations can achieve up to 151-fold improvements in execution time while losing 2.19% accuracy on average. The source code of the proposed strategy, together with the test sets used in our analysis, is available on request.

Iteratively refined guide trees help improving alignment and phylogenetic inference in the mushroom family Bolbitiaceae

Reconciling traditional classifications, morphology, and the phylogenetic relationships of brown-spored agaric mushrooms has proven difficult in many groups, due to extensive convergence in morphological features. Here, we address the monophyly of the Bolbitiaceae, a family with over 700 described species and examine the higher-level relationships within the family using a newly constructed multilocus dataset (ITS, nrLSU rDNA and EF1-alpha). We tested whether the fast-evolving Internal Transcribed Spacer (ITS) sequences can be accurately aligned across the family, by comparing the outcome of two iterative alignment refining approaches (an automated and a manual) and various indel-treatment strategies. We used PRANK to align sequences in both cases. Our results suggest that--although PRANK successfully evades overmatching of gapped sites, referred previously to as alignment overmatching--it infers an unrealistically high number of indel events with natively generated guide-trees. This 'alignment undermatching' could be avoided by using more rigorous (e.g. ML) guide trees. The trees inferred in this study support the monophyly of the core Bolbitiaceae, with the exclusion of Panaeolus, Agrocybe, and some of the genera formerly placed in the family. Bolbitius and Conocybe were found monophyletic, however, Pholiotina and Galerella require redefinition. The phylogeny revealed that stipe coverage type is a poor predictor of phylogenetic relationships, indicating the need for a revision of the intrageneric relationships within Conocybe.

A NEW GENETIC ALGORITHM FOR MULTIPLE SEQUENCE ALIGNMENT

Multiple sequence alignment (MSA) is one of the basic and important problems in molecular biology. MSA can be used for different purposes including finding the conserved motifs and structurally important regions in protein sequences and determine evolutionary distance between sequences. Aligning several sequences cannot be done in polynomial time and therefore heuristic methods such as genetic algorithms can be used to find approximate solutions of MSA problems. Several algorithms based on genetic algorithms have been developed for this problem in recent years. Most of these algorithms use very complicated, problem specific and time consuming mutation operators. In this paper, we propose a new algorithm that uses a new way of population initialization and simple mutation and recombination operators. The strength of the proposed GA is using simple mutation operators and also a special recombination operator that does not have problems of similar recombination operators in other GAs. The experimental results show that the proposed algorithm is capable of finding good MSAs in contrast to existing methods, while it uses simple operators with low computational complexity.

Comparative characterization of the virulence gene clusters (lipooligosaccharide [LOS] and capsular polysaccharide [CPS]) for Campylobacter coli, Campylobacter jejuni subsp. jejuni and related Campylobacter species

Campylobacter jejuni subsp. jejuni and Campylobacter coli are leading causes of gastroenteritis, with virulence linked to cell surface carbohydrate diversity. Although the associated gene clusters are well studied for C. jejuni subsp. jejuni, C. coli has been largely neglected. Here we provide comparative analysis of the lipooligosaccharide (LOS) and capsular polysaccharide (CPS) gene clusters, using genome and cluster sequence data for 36 C. coli strains, 67 C. jejuni subsp. jejuni strains and ten additional Campylobacter species. Similar to C. jejuni subsp. jejuni, C. coli showed high LOS/CPS gene diversity, with each cluster delineated into eight gene content classes. This diversity was predominantly due to extensive gene gain/loss, with the lateral transfer of genes likely occurring both within and between species and also between the LOS and CPS. Additional mechanisms responsible for LOS/CPS diversity included phase-variable homopolymeric repeats, gene duplication/inactivation, and possibly host environment selection pressure. Analyses also showed that (i) strains of C. coli and Campylobacter upsaliensis possessed genes homologous to the sialic acid genes implicated in the neurological disorder Guillain-Barré syndrome (GBS), and (ii) C. coli LOS classes were differentiated between bovine and poultry hosts, potentially aiding post infection source tracking.

Re-mind the gap! Insertion - deletion data reveal neglected phylogenetic potential of the nuclear ribosomal internal transcribed spacer (ITS) of fungi

Rapidly evolving, indel-rich phylogenetic markers play a pivotal role in our understanding of the relationships at multiple levels of the tree of life. There is extensive evidence that indels provide conserved phylogenetic signal, however, the range of phylogenetic depths for which gaps retain tree signal has not been investigated in detail. Here we address this question using the fungal internal transcribed spacer (ITS), which is central in many phylogenetic studies, molecular ecology, detection and identification of pathogenic and non-pathogenic species. ITS is repeatedly criticized for indel-induced alignment problems and the lack of phylogenetic resolution above species level, although these have not been critically investigated. In this study, we examined whether the inclusion of gap characters in the analyses shifts the phylogenetic utility of ITS alignments towards earlier divergences. By re-analyzing 115 published fungal ITS alignments, we found that indels are slightly more conserved than nucleotide substitutions, and when included in phylogenetic analyses, improved the resolution and branch support of phylogenies across an array of taxonomic ranges and extended the resolving power of ITS towards earlier nodes of phylogenetic trees. Our results reconcile previous contradicting evidence for the effects of data exclusion: in the case of more sophisticated indel placement, the exclusion of indel-rich regions from the analyses results in a loss of tree resolution, whereas in the case of simpler alignment methods, the exclusion of gapped sites improves it. Although the empirical datasets do not provide to measure alignment accuracy objectively, our results for the ITS region are consistent with previous simulations studies alignment algorithms. We suggest that sophisticated alignment algorithms and the inclusion of indels make the ITS region and potentially other rapidly evolving indel-rich loci valuable sources of phylogenetic information, which can be exploited at multiple taxonomic levels.

Class of multiple sequence alignment algorithm affects genomic analysis

Multiple sequence alignment (MSA) is the heart of comparative sequence analysis. Recent studies demonstrate that MSA algorithms can produce different outcomes when analyzing genomes, including phylogenetic tree inference and the detection of adaptive evolution. These studies also suggest that the difference between MSA algorithms is of a similar order to the uncertainty within an algorithm and suggest integrating across this uncertainty. In this study, we examine further the problem of disagreements between MSA algorithms and how they affect downstream analyses. We also investigate whether integrating across alignment uncertainty affects downstream analyses. We address these questions by analyzing 200 chordate gene families, with properties reflecting those used in large-scale genomic analyses. We find that newly developed distance metrics reveal two significantly different classes of MSA methods (MSAMs). The similarity-based class includes progressive aligners and consistency aligners, representing many methodological innovations for sequence alignment, whereas the evolution-based class includes phylogenetically aware alignment and statistical alignment. We proceed to show that the class of an MSAM has a substantial impact on downstream analyses. For phylogenetic inference, tree estimates and their branch lengths appear highly dependent on the class of aligner used. The number of families, and the sites within those families, inferred to have undergone adaptive evolution depend on the class of aligner used. Similarity-based aligners tend to identify more adaptive evolution. We also develop and test methods for incorporating MSA uncertainty when detecting adaptive evolution but find that although accounting for MSA uncertainty does affect downstream analyses, it appears less important than the class of aligner chosen. Our results demonstrate the critical role that MSA methodology has on downstream analysis, highlighting that the class of aligner chosen in an analysis has a demonstrable effect on its outcome.