Improving sequence-based fold recognition by using 3D model quality assessment

Motivation: The ability of a simple method (MODCHECK) to determine the sequence–structure compatibility of a set of structural models generated by fold recognition is tested in a thorough benchmark analysis. Four Model Quality Assessment Programs (MQAPs) were tested on 188 targets from the latest LiveBench-9 automated structure evaluation experiment. We systematically test and evaluate whether the MQAP methods can successfully detect native-likemodels. Results: We show that compared with the other three methods tested MODCHECK is the most reliable method for consistently performing the best top model selection and for ranking the models. In addition, we show that the choice of model similarity score used to assess a model's similarity to the experimental structure can influence the overall performance of these tools. Although these MQAP methods fail to improve the model selection performance for methods that already incorporate protein three dimension (3D) structural information, an improvement is observed for methods that are purely sequence-based, including the best profile–profile methods. This suggests that even the best sequence-based fold recognition methods can still be improved by taking into account the 3D structural information.

Navigating the labyrinth: a guide to sequence-based, community ecology of arbuscular mycorrhizal fungi

Data generated from next generation sequencing (NGS) will soon comprise the majority of information about arbuscular mycorrhizal fungal (AMF) communities. Although these approaches give deeper insight, analysing NGS data involves decisions that can significantly affect results and conclusions. This is particularly true for AMF community studies, because much remains to be known about their basic biology and genetics. During a workshop in 2013, representatives from seven research groups using NGS for AMF community ecology gathered to discuss common challenges and directions for future research. Our goal was to improve the quality and accessibility of NGS data for the AMF research community. Discussions spanned sampling design, sample preservation, sequencing, bioinformatics and data archiving. With concrete examples we demonstrated how different approaches can significantly alter analysis outcomes. Failure to consider the consequences of these decisions may compound bias introduced at each step along the workflow. The products of these discussions have been summarized in this paper in order to serve as a guide for any researcher undertaking NGS sequencing of AMF communities.

A SNP-based consensus genetic map for synteny-based trait targeting in faba bean (Vicia faba L.)

Faba bean (Vicia faba L.) is a globally important nitrogen-fixing legume, which is widely grown in a diverse range of environments. In this work, we mine and validate a set of 845 SNPs from the aligned transcriptomes of two contrasting inbred lines. Each V. faba SNP is assigned by BLAST analysis to a single Medicago orthologue. This set of syntenically anchored polymorphisms were then validated as individual KASP assays, classified according to their informativeness and performance on a panel of 37 inbred lines, and the best performing 757 markers used to genotype six mapping populations. The six resulting linkage maps were merged into a single consensus map on which 687 SNPs were placed on six linkage groups, each presumed to correspond to one of the six V. faba chromosomes. This sequence-based consensus map was used to explore synteny with the most closely-related crop species, lentil, and the most closely related fully sequenced genome, Medicago. Large tracts of uninterrupted colinearity were found between faba bean and Medicago, making it relatively straightforward to predict gene content and order in mapped genetic interval. As a demonstration of this, we mapped a flower colour gene to a 2 cM interval of Vf chromosome 2 which was highly collinear with Mt3. The obvious candidate gene from 77 gene models in the collinear Medicago chromosome segment was the previously characterized MtWD40-1 gene (Mt3g092830, Mt3g092840) controlling anthocyanin production in Medicago and re-sequencing of the Vf orthologue showed a putative causative deletion of the entire 5’ end of the gene.

A hierarchical Bayesian model for predicting the functional consequences of amino-acid polymorphisms

Genetic polymorphisms in deoxyribonucleic acid coding regions may have a phenotypic effect on the carrier, e.g. by influencing susceptibility to disease. Detection of deleterious mutations via association studies is hampered by the large number of candidate sites; therefore methods are needed to narrow down the search to the most promising sites. For this, a possible approach is to use structural and sequence-based information of the encoded protein to predict whether a mutation at a particular site is likely to disrupt the functionality of the protein itself. We propose a hierarchical Bayesian multivariate adaptive regression spline (BMARS) model for supervised learning in this context and assess its predictive performance by using data from mutagenesis experiments on lac repressor and lysozyme proteins. In these experiments, about 12 amino-acid substitutions were performed at each native amino-acid position and the effect on protein functionality was assessed. The training data thus consist of repeated observations at each position, which the hierarchical framework is needed to account for. The model is trained on the lac repressor data and tested on the lysozyme mutations and vice versa. In particular, we show that the hierarchical BMARS model, by allowing for the clustered nature of the data, yields lower out-of-sample misclassification rates compared with both a BMARS and a frequen-tist MARS model, a support vector machine classifier and an optimally pruned classification tree.

Improved channel estimation in TDMA by reproduction with applications in GSM/GPRS under co-channel interference

Finding an estimate of the channel impulse response (CIR) by correlating a received known (training) sequence with the sent training sequence is commonplace. Where required, it is also common to truncate the longer correlation to a sub-set of correlation coefficients by finding the set of N sequential correlation coefficients with the maximum power. This paper presents a new approach to selecting the optimal set of N CIR coefficients from the correlation rather than relying on power. The algorithm reconstructs a set of predicted symbols using the training sequence and various sub-sets of the correlation to find the sub-set that results in the minimum mean squared error between the actual received symbols and the reconstructed symbols. The application of the algorithm is presented in the context of the TDMA based GSM/GPRS system to demonstrate an improvement in the system performance with the new algorithm and the results are presented in the paper. However, the application lends itself to any training sequence based communication system often found within wireless consumer electronic device(1).

Autonomous ship collision free trajectory navigation and control algorithms

A new autonomous ship collision free (ASCF) trajectory navigation and control system has been introduced with a new recursive navigation algorithm based on analytic geometry and convex set theory for ship collision free guidance. The underlying assumption is that the geometric information of ship environment is available in the form of a polygon shaped free space, which may be easily generated from a 2D image or plots relating to physical hazards or other constraints such as collision avoidance regulations. The navigation command is given as a heading command sequence based on generating a way point which falls within a small neighborhood of the current position, and the sequence of the way points along the trajectory are guaranteed to lie within a bounded obstacle free region using convex set theory. A neurofuzzy network predictor which in practice uses only observed input/output data generated by on board sensors or external sensors (or a sensor fusion algorithm), based on using rudder deflection angle for the control of ship heading angle, is utilised in the simulation of an ESSO 190000 dwt tanker model to demonstrate the effectiveness of the system.

Pseudomonas syringae pv. coryli, the causal agent of bacterial twig dieback of Corylus avellana

Thirty-eight bacterial strains isolated from hazelnut (Corylus avellana) cv. Tonda Gentile delle Langhe showing a twig dieback in Piedmont and Sardinia, Italy, were studied by a polyphasic approach. All strains were assessed by fatty acids analysis and repetitive sequence-based polymerase chain reaction (PCR) fingerprinting using BOX and ERIC primer sets. Representative strains also were assessed by sequencing the 16S rDNA and hrpL genes, determining the presence of the syrB gene, testing their biochemical and nutritional characteristics, and determining their pathogenicity to hazelnut and other plants species or plant organs. Moreover, they were compared with reference strains of other phytopathogenic pseudomonads. The strains from hazelnut belong to Pseudomonas syringae (sensu latu), LOPAT group Ia. Both fatty acids and repetitive-sequence-based PCR clearly discriminate such strains from other Pseudomonas spp., including P. avellanae and other P. syringae pathovars as well as P. syringae pv. syringae strains from hazelnut. Also, the sequencing of 16S rDNA and hrpL genes differentiated them from P. avellanae and from P. syringae pv. syringae. They did not possess the syrB gene. Some nutritional tests also differentiated them from related P. syringae pathovars. Upon artificial inoculation, these strains incited severe twig diebacks only on hazelnut. Our results justify the creation of a new pathovar because the strains from hazelnut constitute a homogeneous group and a discrete phenon. The name of P. syringae pv. coryli is proposed and criteria for routine identification are presented.

Detecting recombination in 4-taxa DNA sequence alignments with Bayesian hidden Markov models and Markov chain Monte Carlo

This article presents a statistical method for detecting recombination in DNA sequence alignments, which is based on combining two probabilistic graphical models: (1) a taxon graph (phylogenetic tree) representing the relationship between the taxa, and (2) a site graph (hidden Markov model) representing interactions between different sites in the DNA sequence alignments. We adopt a Bayesian approach and sample the parameters of the model from the posterior distribution with Markov chain Monte Carlo, using a Metropolis-Hastings and Gibbs-within-Gibbs scheme. The proposed method is tested on various synthetic and real-world DNA sequence alignments, and we compare its performance with the established detection methods RECPARS, PLATO, and TOPAL, as well as with two alternative parameter estimation schemes.

A phylogenetic reappraisal of the Peltophorum group (Caesalpinieae: Leguminosae) based on the chloroplast trnL-F, rbcL and rps16 sequence data

The monophyly of the Peltophorum group, one of nine informal groups recognized by Polhill in the Caesalpinieae, was tested using sequence data from the trnL-F, rbcL, and rps16 regions of the chloroplast genome. Exemplars were included from all 16 genera of the Peltophorum group, and from 15 genera representing seven of the other eight informal groups in the tribe. The data were analyzed separately and in combined analyses using parsimony and Bayesian methods. The analysis method had little effect on the topology of well-supported relationships. The molecular data recovered a generally well-supported phylogeny with many intergeneric relationships resolved. Results show that the Peltophorum group as currently delimited is polyphyletic, but that eight genera plus one undescribed genus form a core Peltophorum group, which is referred to here as the Peltophorum group sensu stricto. These genera are Bussea, Conzattia, Colvillea, Delonix, Heteroflorum (inedit.), Lemuropisum, Parkinsonia, Peltophorum, and Schizolobium. The remaining eight genera of the Peltophorum group s.l. are distributed across the Caesalpinieae. Morphological support for the redelimited Peltophorum group and the other recovered clades was assessed, and no unique synapomorphy was found for the Peltophorum group s.s. A proposal for the reclassification of the Peltophorum group s.l. is presented.

Phylogenomics of eukaryotes: Impact of missing data on large alignments

Resolving the relationships between Metazoa and other eukaryotic groups as well as between metazoan phyla is central to the understanding of the origin and evolution of animals. The current view is based on limited data sets, either a single gene with many species (e.g., ribosomal RNA) or many genes but with only a few species. Because a reliable phylogenetic inference simultaneously requires numerous genes and numerous species, we assembled a very large data set containing 129 orthologous proteins (similar to30,000 aligned amino acid positions) for 36 eukaryotic species. Included in the alignments are data from the choanoflagellate Monosiga ovata, obtained through the sequencing of about 1,000 cDNAs. We provide conclusive support for choanoflagellates as the closest relative of animals and for fungi as the second closest. The monophyly of Plantae and chromalveolates was recovered but without strong statistical support. Within animals, in contrast to the monophyly of Coelomata observed in several recent large-scale analyses, we recovered a paraphyletic Coelamata, with nematodes and platyhelminths nested within. To include a diverse sample of organisms, data from EST projects were used for several species, resulting in a large amount of missing data in our alignment (about 25%). By using different approaches, we verify that the inferred phylogeny is not sensitive to these missing data. Therefore, this large data set provides a reliable phylogenetic framework for studying eukaryotic and animal evolution and will be easily extendable when large amounts of sequence information become available from a broader taxonomic range.

Phylogenetic systematics of Sternbergia (Amaryllidaceae) based on plastid and ITS sequence data

The phylogenetics of Sternbergia (Amaryllidaceae) were studied using DNA sequences of the plastid ndhF and matK genes and nuclear internal transcribed spacer (ITS) ribosomal region for 38, 37 and 32 ingroup and outgroup accessions, respectively. All members of Sternbergia were represented by at least one accession, except S. minoica and S. schubertii, with additional taxa from Narcissus and Pancratium serving as principal outgroups. Sternbergia was resolved and supported as sister to Narcissus and composed of two primary subclades: S. colchiciflora sister to S. vernalis, S. candida and S. clusiana, with this clade in turn sister to S. lutea and its allies in both Bayesian and bootstrap analyses. A clear relationship between the two vernal flowering members of the genus was recovered, supporting the hypothesis of a single origin of vernal flowering in Sternbergia. However, in the S. lutea complex, the DNA markers examined did not offer sufficient resolving power to separate taxa, providing some support for the idea that S. sicula and S. greuteriana are conspecific with S. lutea

Reversible thermal transition of polydiacetylene based on KTTKS collagen sequence

Here we explore the physico-chemical properties of a peptide amphiphile obtained by chemical conjugation of the collagenstimulating peptide KTTKS with 10,12-pentacosadiynoic acid which photopolymerizes as a stable and extended polydiacetylene. We investigate the self-assembly of this new polymer and rationalize its peculiar behavior in terms of a thermal conformational transition. Surprisingly, this polymer shows a thermal transition associated with a non-cooperative increase in b-sheet content at high temperature.

Conformation and self-association of peptide amphiphiles based on the KTTKS collagen sequence

Studying peptide amphiphiles (PAs), we investigate the influence of alkyl chain length on the aggregation behavior of the collagen-derived peptide KTTKS with applications ranging from antiwrinkle cosmetic creams to potential uses in regenerative medicine. We have studied synthetic peptides amphiphiles C14− KTTKS (myristoyl Lys-Thr-Thr-Lys-Ser) and C18−KTTKS(stearoyl-Lys-Thr Thr-Lys-Ser) to investigate in detail their physicochemical properties. It is presumed that the hydrophobic chain in these self-assembling peptide amphiphiles enhances peptide permeation across the skin compared to KTTKS alone. Subsequently Cn−KTTKS should act as a prodrug and release the peptide by enzymatic cleavage. Our results should be useful in the further development of molecules with collagen-stimulating activity.

A Filter for Visual Tracking Based on a Stochastic Model for Driver Behaviour

A driver controls a car by turning the steering wheel or by pressing on the accelerator or the brake. These actions are modelled by Gaussian processes, leading to a stochastic model for the motion of the car. The stochastic model is the basis of a new filter for tracking and predicting the motion of the car, using measurements obtained by fitting a rigid 3D model to a monocular sequence of video images. Experiments show that the filter easily outperforms traditional filters.