Evolution. Uniting alignments and trees

Omics Analysis of Odorant-Binding Proteins and Cuticle-Enriched SfruOBP18 Confers Multi-Insecticide Tolerance in Spodoptera frugiperda

Spodoptera frugiperda is a notorious pest that develops a high resistance to many insecticides. Recently, insect odorant-binding proteins (OBPs) have been proven to participate in insecticide resistance. However, the functional evidence supporting the cross-link between OBPs and insecticide resistance remains unexplored. Here, we identified 50 SfruOBPs from the larval transcriptome and genome. Notably, SfruOBP18 was highly expressed in the larval cuticle and could be induced to upregulate its expression by multi-insecticides. Ligand-binding assays revealed that SfruOBP18 bound strongly with four insecticides; RNAi and insecticide bioassay demonstrated that the knockdown of SfruOBP18 did not affect larval survival and development. However, it can significantly increase the larval susceptibility to multi-insecticides, suggesting an uncommon role of SfruOBP18 in multi-insecticide susceptibility. Our study provides a comprehensive understanding of SfruOBPs and furthermore proves that a larval cuticle-enriched OBP can bind with and confer larval tolerance to multi-insecticides. SfruOBP18 could be a new insecticidal target for controlling Lepidoptera pests.

Neofunctionalization driven by positive selection led to the retention of the loqs2 gene encoding an Aedes specific dsRNA binding protein

BACKGROUND

Mosquito borne viruses, such as dengue, Zika, yellow fever and Chikungunya, cause millions of infections every year. These viruses are mostly transmitted by two urban-adapted mosquito species, Aedes aegypti and Aedes albopictus. Although mechanistic understanding remains largely unknown, Aedes mosquitoes may have unique adaptations that lower the impact of viral infection. Recently, we reported the identification of an Aedes specific double-stranded RNA binding protein (dsRBP), named Loqs2, that is involved in the control of infection by dengue and Zika viruses in mosquitoes. Preliminary analyses suggested that the loqs2 gene is a paralog of loquacious (loqs) and r2d2, two co-factors of the RNA interference (RNAi) pathway, a major antiviral mechanism in insects.

RESULTS

Here we analyzed the origin and evolution of loqs2. Our data suggest that loqs2 originated from two independent duplications of the first double-stranded RNA binding domain of loqs that occurred before the origin of the Aedes Stegomyia subgenus, around 31 million years ago. We show that the loqs2 gene is evolving under relaxed purifying selection at a faster pace than loqs, with evidence of neofunctionalization driven by positive selection. Accordingly, we observed that Loqs2 is localized mainly in the nucleus, different from R2D2 and both isoforms of Loqs that are cytoplasmic. In contrast to r2d2 and loqs, loqs2 expression is stage- and tissue-specific, restricted mostly to reproductive tissues in adult Ae. aegypti and Ae. albopictus. Transgenic mosquitoes engineered to express loqs2 ubiquitously undergo developmental arrest at larval stages that correlates with massive dysregulation of gene expression without major effects on microRNAs or other endogenous small RNAs, classically associated with RNA interference.

CONCLUSIONS

Our results uncover the peculiar origin and neofunctionalization of loqs2 driven by positive selection. This study shows an example of unique adaptations in Aedes mosquitoes that could ultimately help explain their effectiveness as virus vectors.

Incorporating alignment uncertainty into Felsenstein's phylogenetic bootstrap to improve its reliability

Motivation

Most evolutionary analyses are based on pre-estimated multiple sequence alignment. Wong et al. established the existence of an uncertainty induced by multiple sequence alignment when reconstructing phylogenies. They were able to show that in many cases different aligners produce different phylogenies, with no simple objective criterion sufficient to distinguish among these alternatives.

Results

We demonstrate that incorporating MSA induced uncertainty into bootstrap sampling can significantly increase correlation between clade correctness and its corresponding bootstrap value. Our procedure involves concatenating several alternative multiple sequence alignments of the same sequences, produced using different commonly used aligners. We then draw bootstrap replicates while favoring columns of the more unique aligner among the concatenated aligners. We named this concatenation and bootstrapping method, Weighted Partial Super Bootstrap (wpSBOOT). We show on three simulated datasets of 16, 32 and 64 tips that our method improves the predictive power of bootstrap values. We also used as a benchmark an empirical collection of 853 1-to-1 orthologous genes from seven yeast species and found wpSBOOT to significantly improve discrimination capacity between topologically correct and incorrect trees. Bootstrap values of wpSBOOT are comparable to similar readouts estimated using a single method. However, for reduced trees by 50% and 95% bootstrap thresholds, wpSBOOT comes out the lowest Type I error (less FP).

Availability

The automated generation of replicates has been implemented in the T-Coffee package, which is available as open source freeware available from www.tcoffee.org.

Supplementary information

Supplementary data are available at Bioinformatics online.

A biologist's guide to Bayesian phylogenetic analysis

Bayesian methods have become very popular in molecular phylogenetics due to the availability of user-friendly software implementing sophisticated models of evolution. However, Bayesian phylogenetic models are complex, and analyses are often carried out using default settings, which may not be appropriate. Here, we summarize the major features of Bayesian phylogenetic inference and discuss Bayesian computation using Markov chain Monte Carlo (MCMC), the diagnosis of an MCMC run, and ways of summarising the MCMC sample. We discuss the specification of the prior, the choice of the substitution model, and partitioning of the data. Finally, we provide a list of common Bayesian phylogenetic software and provide recommendations as to their use.

Detecting Horizontal Gene Transfer between Closely Related Taxa

Horizontal gene transfer (HGT), the transfer of genetic material between organisms, is crucial for genetic innovation and the evolution of genome architecture. Existing HGT detection algorithms rely on a strong phylogenetic signal distinguishing the transferred sequence from ancestral (vertically derived) genes in its recipient genome. Detecting HGT between closely related species or strains is challenging, as the phylogenetic signal is usually weak and the nucleotide composition is normally nearly identical. Nevertheless, there is a great importance in detecting HGT between congeneric species or strains, especially in clinical microbiology, where understanding the emergence of new virulent and drug-resistant strains is crucial, and often time-sensitive.

We developed a novel, self-contained technique named Near HGT, based on the synteny index, to measure the divergence of a gene from its native genomic environment and used it to identify candidate HGT events between closely related strains. The method confirms candidate transferred genes based on the constant relative mutability (CRM). Using CRM, the algorithm assigns a confidence score based on “unusual” sequence divergence. A gene exhibiting exceptional deviations according to both synteny and mutability criteria, is considered a validated HGT product. We first employed the technique to a set of three E. coli strains and detected several highly probable horizontally acquired genes. We then compared the method to existing HGT detection tools using a larger strain data set.

When combined with additional approaches our new algorithm provides richer picture and brings us closer to the goal of detecting all newly acquired genes in a particular strain.

The transfer of genetic material between organisms, usually denoted as horizontal (or lateral) gene transfer (HGT or LGT), is a prime mechanism in microbial evolution and responsible for genetic innovation and the evolution of genome architecture. Detecting HGT between closely related species or strains is imperative as drug-resistant pathogenic strains most often acquire their virulence from closely related bacteria. The proposed method combines two evolutionary signals that were not employed in the past for this task. One is the synteny index (SI), measuring the loss of synteny in an organism, and the other is a novel concept—constant relative mutability (CRM), maintaining that genes preserve their relative evolution rate along linages (although the latter ones may each change).

We show both in simulation and real biological data that the method is sound and, in the cases examined, provides stronger sensitivity than existing methods. We therefore believe this novel approach represents a significant advance, for the first time enabling the detection of previously ignored HGT events that will bring us closer to the goal of detecting all newly acquired genes in a particular strain.

Availability: The method is publicly available at http://research.haifa.ac.il/~ssagi/software/nearHGT.zip

Farinin: characterization of a novel wheat endosperm protein belonging to the prolamin superfamily

Starch granule surface-associated proteins were separated by HPLC and identified by direct protein sequencing. Among the proteins identified was one that consisted of two polypeptide chains of 11 and 19 kDa linked by disulfide bonds. Sequencing of tryptic peptides from each of the polypeptides revealed similarities between some of the peptides and avenin-like b proteins encoded by partial cDNAs in NCBI. To identify a contiguous sequence that matched all of the peptides, contigs encoding three avenin-like b proteins were constructed from ESTs of the cultivar Butte 86. All peptide sequences were found in a protein encoded by one of these contigs that had not been identified previously. Protein and DNA sequences indicated that the two polypeptide chains were derived from a parent protein that had been cleaved at the C-terminal position of an asparagine residue. The name farinin is suggested for this protein and other avenin-like b proteins. Evolutionary relationships of the protein are discussed and a simple computer molecular model was constructed. On the basis of its sequence, the new protein was likely to be allergenic but unlikely to be active in celiac disease.

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.

Incorrect handling of calibration information in divergence time inference: an example from volcanic islands

Divergence time studies rely on calibration information from several sources. The age of volcanic islands is one of the standard references to obtain chronological data to estimate the absolute times of lineage diversifications. This strategy assumes that cladogenesis is necessarily associated with island formation, and punctual calibrations are commonly used to date the splits of endemic island species. Here, we re-examined three studies that inferred divergence times for different Hawaiian lineages assuming fixed calibration points. We show that, by permitting probabilistic calibrations, some divergences are estimated to be significantly younger or older than the age of the island formation, thus yielding distinct ecological scenarios for the speciation process. The results highlight the importance of using calibration information correctly, as well as the possibility of incorporating volcanic island studies into a formal, biogeographical hypothesis-testing framework.

The interface of protein structure, protein biophysics, and molecular evolution

Abstract The interface of protein structural biology, protein biophysics, molecular evolution, and molecular population genetics forms the foundations for a mechanistic understanding of many aspects of protein biochemistry. Current efforts in interdisciplinary protein modeling are in their infancy and the state-of-the art of such models is described. Beyond the relationship between amino acid substitution and static protein structure, protein function, and corresponding organismal fitness, other considerations are also discussed. More complex mutational processes such as insertion and deletion and domain rearrangements and even circular permutations should be evaluated. The role of intrinsically disordered proteins is still controversial, but may be increasingly important to consider. Protein geometry and protein dynamics as a deviation from static considerations of protein structure are also important. Protein expression level is known to be a major determinant of evolutionary rate and several considerations including selection at the mRNA level and the role of interaction specificity are discussed. Lastly, the relationship between modeling and needed high-throughput experimental data as well as experimental examination of protein evolution using ancestral sequence resurrection and in vitro biochemistry are presented, towards an aim of ultimately generating better models for biological inference and prediction.

Accurate extension of multiple sequence alignments using a phylogeny-aware graph algorithm

MOTIVATION

Accurate alignment of large numbers of sequences is demanding and the computational burden is further increased by downstream analyses depending on these alignments. With the abundance of sequence data, an integrative approach of adding new sequences to existing alignments without their full re-computation and maintaining the relative matching of existing sequences is an attractive option. Another current challenge is the extension of reference alignments with fragmented sequences, as those coming from next-generation metagenomics, that contain relatively little information. Widely used methods for alignment extension are based on profile representation of reference sequences. These do not incorporate and use phylogenetic information and are affected by the composition of the reference alignment and the phylogenetic positions of query sequences.

RESULTS

We have developed a method for phylogeny-aware alignment of partial-order sequence graphs and apply it here to the extension of alignments with new data. Our new method, called PAGAN, infers ancestral sequences for the reference alignment and adds new sequences in their phylogenetic context, either to predefined positions or by finding the best placement for sequences of unknown origin. Unlike profile-based alternatives, PAGAN considers the phylogenetic relatedness of the sequences and is not affected by inclusion of more diverged sequences in the reference set. Our analyses show that PAGAN outperforms alternative methods for alignment extension and provides superior accuracy for both DNA and protein data, the improvement being especially large for fragmented sequences. Moreover, PAGAN-generated alignments of noisy next-generation sequencing (NGS) sequences are accurate enough for the use of RNA-seq data in evolutionary analyses.

AVAILABILITY

PAGAN is written in C++, licensed under the GPL and its source code is available at http://code.google.com/p/pagan-msa.

Phylo: a citizen science approach for improving multiple sequence alignment

Background

Comparative genomics, or the study of the relationships of genome structure and function across different species, offers a powerful tool for studying evolution, annotating genomes, and understanding the causes of various genetic disorders. However, aligning multiple sequences of DNA, an essential intermediate step for most types of analyses, is a difficult computational task. In parallel, citizen science, an approach that takes advantage of the fact that the human brain is exquisitely tuned to solving specific types of problems, is becoming increasingly popular. There, instances of hard computational problems are dispatched to a crowd of non-expert human game players and solutions are sent back to a central server.

Methodology/Principal Findings

We introduce Phylo, a human-based computing framework applying “crowd sourcing” techniques to solve the Multiple Sequence Alignment (MSA) problem. The key idea of Phylo is to convert the MSA problem into a casual game that can be played by ordinary web users with a minimal prior knowledge of the biological context. We applied this strategy to improve the alignment of the promoters of disease-related genes from up to 44 vertebrate species. Since the launch in November 2010, we received more than 350,000 solutions submitted from more than 12,000 registered users. Our results show that solutions submitted contributed to improving the accuracy of up to 70% of the alignment blocks considered.

Conclusions/Significance

We demonstrate that, combined with classical algorithms, crowd computing techniques can be successfully used to help improving the accuracy of MSA. More importantly, we show that an NP-hard computational problem can be embedded in casual game that can be easily played by people without significant scientific training. This suggests that citizen science approaches can be used to exploit the billions of “human-brain peta-flops” of computation that are spent every day playing games. Phylo is available at: http://phylo.cs.mcgill.ca.

Looking for the Last Universal Common Ancestor (LUCA)

Genomic sequences across diverse species seem to align towards a common ancestry, eventually implying that eons ago some universal antecedent organism would have lived on the face of Earth. However, when evolution is understood not only as a biological process but as a general thermodynamic process, it becomes apparent that the quest for the last universal common ancestor is unattainable. Ambiguities in alignments are unavoidable because the driving forces and paths of evolution cannot be separated from each other. Thus tracking down life’s origin is by its nature a non-computable task. The thermodynamic tenet clarifies that evolution is a path-dependent process of least-time consumption of free energy. The natural process is without a demarcation line between animate and inanimate.

Alignment methods: strategies, challenges, benchmarking, and comparative overview

Comparative evolutionary analyses of molecular sequences are solely based on the identities and differences detected between homologous characters. Errors in this homology statement, that is errors in the alignment of the sequences, are likely to lead to errors in the downstream analyses. Sequence alignment and phylogenetic inference are tightly connected and many popular alignment programs use the phylogeny to divide the alignment problem into smaller tasks. They then neglect the phylogenetic tree, however, and produce alignments that are not evolutionarily meaningful. The use of phylogeny-aware methods reduces the error but the resulting alignments, with evolutionarily correct representation of homology, can challenge the existing practices and methods for viewing and visualising the sequences. The inter-dependency of alignment and phylogeny can be resolved by joint estimation of the two; methods based on statistical models allow for inferring the alignment parameters from the data and correctly take into account the uncertainty of the solution but remain computationally challenging. Widely used alignment methods are based on heuristic algorithms and unlikely to find globally optimal solutions. The whole concept of one correct alignment for the sequences is questionable, however, as there typically exist vast numbers of alternative, roughly equally good alignments that should also be considered. This uncertainty is hidden by many popular alignment programs and is rarely correctly taken into account in the downstream analyses. The quest for finding and improving the alignment solution is complicated by the lack of suitable measures of alignment goodness. The difficulty of comparing alternative solutions also affects benchmarks of alignment methods and the results strongly depend on the measure used. As the effects of alignment error cannot be predicted, comparing the alignments' performance in downstream analyses is recommended.

Tasting soil fungal diversity with earth tongues: phylogenetic test of SATé alignments for environmental ITS data

An abundance of novel fungal lineages have been indicated by DNA sequencing of the nuclear ribosomal ITS region from environmental samples such as soil and wood. Although phylogenetic analysis of these novel lineages is a key component of unveiling the structure and diversity of complex communities, such analyses are rare for environmental ITS data due to the difficulties of aligning this locus across significantly divergent taxa. One potential approach to this issue is simultaneous alignment and tree estimation. We targeted divergent ITS sequences of the earth tongue fungi (Geoglossomycetes), a basal class in the Ascomycota, to assess the performance of SATé, recent software that combines progressive alignment and tree building. We found that SATé performed well in generating high-quality alignments and in accurately estimating the phylogeny of earth tongue fungi. Drawing from a data set of 300 sequences of earth tongues and progressively more distant fungal lineages, 30 insufficiently identified ITS sequences from the public sequence databases were assigned to the Geoglossomycetes. The association between earth tongues and plants has been hypothesized for a long time, but hard evidence is yet to be collected. The ITS phylogeny showed that four ectomycorrhizal isolates shared a clade with Geoglossum but not with Trichoglossum earth tongues, pointing to the significant potential inherent to ecological data mining of environmental samples. Environmental sampling holds the key to many focal questions in mycology, and simultaneous alignment and tree estimation, as performed by SATé, can be a highly efficient companion in that pursuit.

PhyloSim - Monte Carlo simulation of sequence evolution in the R statistical computing environment

BACKGROUND

The Monte Carlo simulation of sequence evolution is routinely used to assess the performance of phylogenetic inference methods and sequence alignment algorithms. Progress in the field of molecular evolution fuels the need for more realistic and hence more complex simulations, adapted to particular situations, yet current software makes unreasonable assumptions such as homogeneous substitution dynamics or a uniform distribution of indels across the simulated sequences. This calls for an extensible simulation framework written in a high-level functional language, offering new functionality and making it easy to incorporate further complexity.

RESULTS

PhyloSim is an extensible framework for the Monte Carlo simulation of sequence evolution, written in R, using the Gillespie algorithm to integrate the actions of many concurrent processes such as substitutions, insertions and deletions. Uniquely among sequence simulation tools, PhyloSim can simulate arbitrarily complex patterns of rate variation and multiple indel processes, and allows for the incorporation of selective constraints on indel events. User-defined complex patterns of mutation and selection can be easily integrated into simulations, allowing PhyloSim to be adapted to specific needs.

CONCLUSIONS

Close integration with R and the wide range of features implemented offer unmatched flexibility, making it possible to simulate sequence evolution under a wide range of realistic settings. We believe that PhyloSim will be useful to future studies involving simulated alignments.

Use of phylogenetics in the molecular epidemiology and evolutionary studies of viral infections

Since DNA sequencing techniques first became available almost 30 years ago, the amount of nucleic acid sequence data has increased enormously. Phylogenetics, which is widely applied to compare and analyze such data, is particularly useful for the analysis of genes from rapidly evolving viruses. It has been used extensively to describe the molecular epidemiology and transmission of the human immunodeficiency virus (HIV), the origins and subsequent evolution of the severe acute respiratory syndrome (SARS)-associated coronavirus (SCoV), and, more recently, the evolving epidemiology of avian influenza as well as seasonal and pandemic human influenza viruses. Recent advances in phylogenetic methods can infer more in-depth information about the patterns of virus emergence, adding to the conventional approaches in viral epidemiology. Examples of this information include estimations (with confidence limits) of the actual time of the origin of a new viral strain or its emergence in a new species, viral recombination and reassortment events, the rate of population size change in a viral epidemic, and how the virus spreads and evolves within a specific population and geographical region. Such sequence-derived information obtained from the phylogenetic tree can assist in the design and implementation of public health and therapeutic interventions. However, application of many of these advanced phylogenetic methods are currently limited to specialized phylogeneticists and statisticians, mainly because of their mathematical basis and their dependence on the use of a large number of computer programs. This review attempts to bridge this gap by presenting conceptual, technical, and practical aspects of applying phylogenetic methods in studies of influenza, HIV, and SCoV. It aims to provide, with minimal mathematics and statistics, a practical overview of how phylogenetic methods can be incorporated into virological studies by clinical and laboratory specialists.