Eyal Privman

GUIDANCE: a web server for assessing alignment confidence scores

Evaluating the accuracy of multiple sequence alignment (MSA) is critical for virtually every comparative sequence analysis that uses an MSA as input. Here we present the GUIDANCE web-server, a user-friendly, open access tool for the identification of unreliable alignment regions. The web-server accepts as input a set of unaligned sequences. The server aligns the sequences and provides a simple graphic visualization of the confidence score of each column, residue and sequence of an alignment, using a color-coding scheme. The method is generic and the user is allowed to choose the alignment algorithm (ClustalW, MAFFT and PRANK are supported) as well as any type of molecular sequences (nucleotide, protein or codon sequences). The server implements two different algorithms for evaluating confidence scores: (i) the heads-or-tails (HoT) method, which measures alignment uncertainty due to co-optimal solutions; (ii) the GUIDANCE method, which measures the robustness of the alignment to guide-tree uncertainty. The server projects the confidence scores onto the MSA and points to columns and sequences that are unreliably aligned. These can be automatically removed in preparation for downstream analyses. GUIDANCE is freely available for use at http://guidance.tau.ac.il.

Improving the Performance of Positive Selection Inference by Filtering Unreliable Alignment Regions

Errors in the inferred multiple sequence alignment may lead to false prediction of positive selection. Recently, methods for detecting unreliable alignment regions were developed and were shown to accurately identify incorrectly aligned regions. While removing unreliable alignment regions is expected to increase the accuracy of positive selection inference, such filtering may also significantly decrease the power of the test, as positively selected regions are fast evolving, and those same regions are often those that are difficult to align. Here, we used realistic simulations that mimic sequence evolution of HIV-1 genes to test the hypothesis that the performance of positive selection inference using codon models can be improved by removing unreliable alignment regions. Our study shows that the benefit of removing unreliable regions exceeds the loss of power due to the removal of some of the true positively selected sites.

Patterns of Positive Selection in Seven Ant Genomes

The evolution of ants is marked by remarkable adaptations that allowed the development of very complex social systems. To identify how ant-specific adaptations are associated with patterns of molecular evolution, we searched for signs of positive selection on amino-acid changes in proteins. We identified 24 functional categories of genes which were enriched for positively selected genes in the ant lineage. We also reanalyzed genome-wide data sets in bees and flies with the same methodology to check whether positive selection was specific to ants or also present in other insects. Notably, genes implicated in immunity were enriched for positively selected genes in the three lineages, ruling out the hypothesis that the evolution of hygienic behaviors in social insects caused a major relaxation of selective pressure on immune genes. Our scan also indicated that genes implicated in neurogenesis and olfaction started to undergo increased positive selection before the evolution of sociality in Hymenoptera. Finally, the comparison between these three lineages allowed us to pinpoint molecular evolution patterns that were specific to the ant lineage. In particular, there was ant-specific recurrent positive selection on genes with mitochondrial functions, suggesting that mitochondrial activity was improved during the evolution of this lineage. This might have been an important step toward the evolution of extreme lifespan that is a hallmark of ants.

Evolution of the metazoan protein phosphatase 2C superfamily.

Members of the protein phosphatase 2C (PP2C) superfamily are Mg2+/Mn2+-dependent serine/threonine phosphatases, which are essential for regulation of cell cycle and stress signaling pathways in cells. In this study, a comprehensive genomic analysis of all available metazoan PP2C sequences was conducted. The phylogeny of PP2C was reconstructed, revealing the existence of 15 vertebrate families which arose following a series of gene duplication events. Relative dating of these duplications showed that they occurred in two active periods: before the divergence of bilaterians and before vertebrate diversification. PP2C families which duplicated during the first period take part in different signaling pathways, whereas PP2C families which diverged in the second period display tissue expression differences yet participate in similar signaling pathways. These differences were found to involve variation of expression in tissues which show higher complexity in vertebrates, such as skeletal muscle and the nervous system. Further analysis was performed with the aim of identifying the functional domains of PP2C. The conservation pattern across the entire PP2C superfamily revealed an extensive domain of more than 50 amino acids which is highly conserved throughout all PP2C members. Several insertion or deletion events were found which may have led to the specialization of each PP2C family.

Deep Panning: Steps towards Probing the IgOme

Background Polyclonal serum consists of vast collections of antibodies, products of differentiated B-cells. The spectrum of antibody specificities is dynamic and varies with age, physiology, and exposure to pathological insults. The complete repertoire of antibody specificities in blood, the IgOme, is therefore an extraordinarily rich source of information–a molecular record of previous encounters as well as a status report of current immune activity. The ability to profile antibody specificities of polyclonal serum at exceptionally high resolution has been an important and serious challenge which can now be overcome. Methodology/Principal Findings Here we illustrate the application of Deep Panning, a method that combines the flexibility of combinatorial phage display of random peptides with the power of high-throughput deep sequencing. Deep Panning is first applied to evaluate the quality and diversity of naïve random peptide libraries. The production of very large data sets, hundreds of thousands of peptides, has revealed unexpected properties of combinatorial random peptide libraries and indicates correctives to ensure the quality of the libraries generated. Next, Deep Panning is used to analyze a model monoclonal antibody in addition to allowing one to follow the dynamics of biopanning and peptide selection. Finally Deep Panning is applied to profile polyclonal sera derived from HIV infected individuals. Conclusions/Significance The ability to generate and characterize hundreds of thousands of affinity-selected peptides creates an effective means towards the interrogation of the IgOme and understanding of the humoral response to disease. Deep Panning should open the door to new possibilities for serological diagnostics, vaccine design and the discovery of the correlates of immunity to emerging infectious agents.

Native homing endonucleases can target conserved genes in humans and in animal models

In recent years, both homing endonucleases (HEases) and zinc-finger nucleases (ZFNs) have been engineered and selected for the targeting of desired human loci for gene therapy. However, enzyme engineering is lengthy and expensive and the off-target effect of the manufactured endonucleases is difficult to predict. Moreover, enzymes selected to cleave a human DNA locus may not cleave the homologous locus in the genome of animal models because of sequence divergence, thus hampering attempts to assess the in vivo efficacy and safety of any engineered enzyme prior to its application in human trials. Here, we show that naturally occurring HEases can be found, that cleave desirable human targets. Some of these enzymes are also shown to cleave the homologous sequence in the genome of animal models. In addition, the distribution of off-target effects may be more predictable for native HEases. Based on our experimental observations, we present the HomeBase algorithm, database and web server that allow a high-throughput computational search and assignment of HEases for the targeting of specific loci in the human and other genomes. We validate experimentally the predicted target specificity of candidate fungal, bacterial and archaeal HEases using cell free, yeast and archaeal assays.

Homing endonucleases residing within inteins: evolutionary puzzles awaiting genetic solutions

Inteins are selfish genetic elements that disrupt the sequence of protein-coding genes and are excised post-translationally. Most inteins also contain a HEN (homing endonuclease) domain, which is important for their horizontal transmission. The present review focuses on the evolution of inteins and their nested HENs, and highlights several unsolved questions that could benefit from molecular genetic approaches. Such approaches can be well carried out in halophilic archaea, which are naturally intein-rich and have highly developed genetic tools for their study. In particular, the fitness effects of harbouring an intein/HEN can be tested in direct competition assays, providing additional insights that will improve current evolutionary models.

Oral transfer of chemical cues, growth proteins and hormones in social insects.

Social insects frequently engage in oral fluid exchange – trophallaxis – between adults, and between adults and larvae. Although trophallaxis is widely considered a food-sharing mechanism, we hypothesized that endogenous components of this fluid might underlie a novel means of chemical communication between colony members. Through protein and small-molecule mass spectrometry and RNA sequencing, we found that trophallactic fluid in the ant Camponotus floridanus contains a set of specific digestion- and non-digestion related proteins, as well as hydrocarbons, microRNAs, and a key developmental regulator, juvenile hormone. When C. floridanus workers’ food was supplemented with this hormone, the larvae they reared via trophallaxis were twice as likely to complete metamorphosis and became larger workers. Comparison of trophallactic fluid proteins across social insect species revealed that many are regulators of growth, development and behavioral maturation. These results suggest that trophallaxis plays previously unsuspected roles in communication and enables communal control of colony phenotypes.

Duplication and concerted evolution in a master sex determiner under balancing selection

The transformer (tra) gene is a key regulator in the signalling hierarchy controlling all aspects of somatic sexual differentiation in Drosophila and other insects. Here, we show that six of the seven sequenced ants have two copies of tra. Surprisingly, the two paralogues are always more similar within species than among species. Comparative sequence analyses indicate that this pattern is owing to the ongoing concerted evolution after an ancestral duplication rather than independent duplications in each of the six species. In particular, there was strong support for inter-locus recombination between the paralogues of the ant Atta cephalotes. In the five species where the location of paralogues is known, they are adjacent to each other in four cases and separated by only few genes in the fifth case. Because there have been extensive genomic rearrangements in these lineages, this suggests selection acting to conserve their synteny. In three species, we also find a signature of positive selection in one of the paralogues. In three bee species where information is available, the tra gene is also duplicated, the copies are adjacent and in at least one species there was recombination between paralogues. These results suggest that concerted evolution plays an adaptive role in the evolution of this gene family.

Phylogeny reconstruction: increasing the accuracy of pairwise distance estimation using Bayesian inference of evolutionary rates

Distance-based methods for phylogeny reconstruction are the fastest and easiest to use, and their popularity is accordingly high. They are also the only known methods that can cope with huge datasets of thousands of sequences. These methods rely on evolutionary distance estimation and are sensitive to errors in such estimations. In this study, a novel Bayesian method for estimation of evolutionary distances is developed. The proposed method enables the use of a sophisticated evolutionary model that better accounts for among-site rate variation (ASRV), thereby improving the accuracy of distance estimation. Rate variations are estimated within a Bayesian framework by extracting information from the entire dataset of sequences, unlike standard methods that can only use one pair of sequences at a time. We compare the accuracy of a cascade of distance estimation methods, starting from commonly used methods and moving towards the more sophisticated novel method. Simulation studies show significant improvements in the accuracy of distance estimation by the novel method over the commonly used ones. We demonstrate the effect of the improved accuracy on tree reconstruction using both real and simulated protein sequence alignments. An implementation of this method is available as part of the SEMPHY package.