Incomplete Sequences Research Articles

Order classification of river watershed divides based on processing digital elevation models

The principles and the algorithm of order classification of river watershed divides are outlined. It is shown that a formal application of any available order classification procedures for river watershed divides is not theoretically grounded as well as being impractical, because the physical mechanisms for formation of watershed divide network are different from those operating in the river network. We have formulated the basic principle of determining the watershed divides order on the basis of a serial sequence of sections constituting the travel path of an arbitrary water drop from the watershed divide to the outlet section of the basin. It is suggested that the order N should be assigned to the section of the watershed divide belonging to the full divide line of the N-order basin only if the travel path from it to the N-order stream is “full” in the topological sense, i.e. includes sections of all orders, from 1 to N. Also, we present a variant of determining the order on the basis of so-called higher-order triplets, incomplete sequences of sections of three neighboring orders along the travel path, with the higher of them determining the watershed divide order. The use of triplets is a subjective procedure of generalization that eliminates the influence of recent random erosional incisions on the forms of stable high-order watersheds. We outline the variants of the technique for identifying the network of watershed divides and calculating their orders, based on processing the digital elevation models (DEM) through the use of standard GIS ArcMap tools. Results are obtained in the form of a correlated classification of river and watershed networks which are rationally interpreted and hold promise for investigating the structure, functioning and evolution of river systems. The study revealed the existence of formation “cores” of river systems, i.e. regions within which the system reaches a higher stream order and which are bounded by watersheds of the same order.

Sequence Prediction of Driving Behavior Using Double Articulation Analyzer

A sequence prediction method for driving behavior data is proposed in this paper. The proposed method can predict a longer latent state sequence of driving behavior data than conventional sequence prediction methods. The proposed method is derived by focusing on the double articulation structure latently embedded in driving behavior data. The double articulation structure is a two-layer hierarchical structure originally found in spoken language, i.e., a sentence is a sequence of words and a word is a sequence of letters. Analogously, we assume that driving behavior data comprise a sequence of driving words and a driving word is a sequence of driving letters. The sequence prediction method is obtained by extending a nonparametric Bayesian unsupervised morphological analyzer using a nested Pitman-Yor language model (NPYLM), which was originally proposed in the natural language processing field. This extension allows the proposed method to analyze incomplete sequences of latent states of driving behavior and to predict subsequent latent states on the basis of a maximum a posteriori criterion. The extension requires a marginalization technique over an infinite number of possible driving words. We derived such a technique on the basis of several characteristics of the NPYLM. We evaluated this proposed sequence prediction method using three types of data: 1) synthetic data; 2) data from test drives around a driving course at a factory; and 3) data from drives on a public thoroughfare. The results showed that the proposed method made better long-term predictions than did the previous methods.

GRASPx: efficient homolog-search of short peptide metagenome database through simultaneous alignment and assembly.

BackgroundMetagenomics is a cultivation-independent approach that enables the study of the genomic composition of microbes present in an environment. Metagenomic samples are routinely sequenced using next-generation sequencing technologies that generate short nucleotide reads. Proteins identified from these reads are mostly of partial length. On the other hand, de novo assembly of a large metagenomic dataset is computationally demanding and the assembled contigs are often fragmented, resulting in the identification of protein sequences that are also of partial length and incomplete. Annotation of an incomplete protein sequence often proceeds by identifying its homologs in a database of reference sequences. Identifying the homologs of incomplete sequences is a challenge and can result in substandard annotation of proteins from metagenomic datasets. To address this problem, we recently developed a homology detection algorithm named GRASP (Guided Reference-based Assembly of Short Peptides) that identifies the homologs of a given reference protein sequence in a database of short peptide metagenomic sequences. GRASP was developed to implement a simultaneous alignment and assembly algorithm for annotation of short peptides identified on metagenomic reads. The program achieves significantly improved recall rate at the cost of computational efficiency. In this article, we adopted three techniques to speed up the original version of GRASP, including the pre-construction of extension links, local assembly of individual seeds, and the implementation of query-level parallelism.ResultsThe resulting new program, GRASPx, achieves >30X speedup compared to its predecessor GRASP. At the same time, we show that the performance of GRASPx is consistent with that of GRASP, and that both of them significantly outperform other popular homology-search tools including the BLAST and FASTA suites. GRASPx was also applied to a human saliva metagenome dataset and shows superior performance for both recall and precision rates.ConclusionsIn this article we present GRASPx, a fast and accurate homology-search program implementing a simultaneous alignment and assembly framework. GRASPx can be used for more comprehensive and accurate annotation of short peptides. GRASPx is freely available at http://graspx.sourceforge.net/.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1119-1) contains supplementary material, which is available to authorized users.

HCV1b genome evolution under selective pressure of the cyclophilin inhibitor alisporivir during the DEB-025-HCV-203 phase II clinical trial

Major advances have revolutionized the HCV antiviral treatment field, with interferon-free combinations of direct-acting antivirals (DAAs) resulting into success rates of >90% for all HCV genotypes. Nevertheless, viral eradication at a global level stills remains challenging, stimulating the continued search for new affordable pan-genotypic drugs. To overcome selection of drug resistant variants, targeting host proteins can be an attractive mechanism of action. Alisporivir (Debio 025) is a potent pan-genotypic host-targeting antiviral agent, acting on cyclophilin A, which is necessary for HCV replication. The efficacy and safety of three different oral doses of alisporivir in combination with pegylated interferon-α2a given over a period of four weeks, was investigated in a randomized, double-blind and placebo-controlled phase IIa clinical trial, in 90 treatment-naïve subjects infected with chronic hepatitis C, wherefrom 58 HCV1b samples were selected for genetic sequencing purposes. Sequencing results were used to study the HCV genome for amino acid changes potentially related with selective pressure and resistance to alisporivir. By comparing baseline and on-treatment sequences, a large variation in proportion of amino acid changes was detected in all treatment arms. The NS5A variant D320E, which was previously identified during in vitro resistance selection and resulted in 3.6-fold reduced alisporivir susceptibility, emerged in two subjects in the alisporivir monotherapy arm. However, emergence of D320E appeared to be associated only with concurrent viral load rebound in one subject with 0.8log10IU/ml increase in HCV RNA. In general, for all datasets, low numbers of positions under positive selective pressure were observed, with no significant differences between naïve and treated sequences. Additionally, incomplete sequence information for some of the 22 patients and the low number of individuals per treatment arm, is limiting the power to assess the association of alisporivir or interferon treatment with the observed amino acid changes.

Top-down venomics of the East African green mamba, Dendroaspis angusticeps, and the black mamba, Dendroaspis polylepis, highlight the complexity of their toxin arsenals

We report the characterization, by combination of high-resolution on-line molecular mass and disulfide bond profiling and top-down MS/MS analysis, of the venom proteomes of two congeneric African snake species of medical importance, Dendroaspis angusticeps (green mamba) and D. polylepis (black mamba). Each of these mamba venoms comprised more than two-hundred polypeptides belonging to just a few toxin families. Both venom proteomes are overwhelmingly composed of post-synaptically-acting short- and long-chain neurotoxins that potently inhibit muscle- and neuronal-type nicotinic acetylcholine receptors; muscarinic cardiotoxins; and dendrotoxins, that block some of the Kv1, n-class of K+ channels. However, the identity of the major proteins and their relative abundances exhibit marked interspecific variation. In addition, the greater resolution of the top-down venomic analytical approach revealed previously undetected protein species, isoforms and proteoforms, including the identification and precise location of modified lysine residues in a number of proteins in both venoms, but particularly in green mamba toxins. This comparative top-down venomic analysis unveiled the untapped complexity of Dendroaspis venoms and lays the foundations for rationalizing the notably different potency of green and black mamba lethal arsenals at locus resolution. Significance paragraphDendroaspis angusticeps (eastern green mamba) and D. polylepis (black mamba) are African snake species of medical concern. Their venoms comprise a high diversity of pharmacologically active peptides, including extremely rapid-acting neurotoxins. Studies on the venoms of D. polylepis and D. angusticeps have focused on the biochemical and pharmacological characterization of their most relevant toxins to rationalize the common neurological and neuromuscular symptoms of envenomings caused by these species. Only very recently an overview of the composition of the venom of a Dendroaspis species, D. polylepis, has been reported through a bottom-up venomics strategy. Peptide-centric approaches provide incomplete sequence coverage, and in general do not allow to distinguish between different proteoforms or closely related toxin isoforms. To overcome this shortcoming we have now applied top-down venomics to unveil the complexity of the toxin arsenals of the black mamba and the eastern green mamba at locus resolution. Our data show that the green and the black mamba venom contain, respectively, ≥232 and ≥268 protein species, highlighting that D. angusticeps and D. polylepis venom comprise a much higher complexity than the 20 and the 27 toxin sequences available, respectively for these snake species, in the non-redundant NCBI database. On the other hand, 36 (D. angusticeps) and 3 (D. polylepis) minor venom proteins showed mass shifts of +42Da modifications, suggesting the presence of monoacetyl lysine residues. Noteworthy, although both venoms have highly similar global molecular compositions, the identity of the major proteins and their relative abundances vary between D. angusticeps and D. polylepis. Our data lay the foundation for rationalizing the notably different venom toxicity profiles of the green and the black mamba.

Provenance and depositional setting of Lower Silurian siliciclastic rocks on Hainan Island, South China: Implications for a passive margin environment of South China in Gondwana

Diverse models have been proposed for interpreting the early Paleozoic tectonic setting of the Cathaysia Block in South China. However, few of them undertook a comprehensive study of clastic sedimentary rocks in the Cathaysia Block. This study reports the petrography and sedimentary facies, the whole-rock geochemistry and Sm–Nd isotopic data, and the LA-ICP-MS U–Pb ages of detrital zircon from the Lower Silurian meta-siliciclastics on Hainan Island in order to constrain the early Paleozoic tectonic setting. The source rocks for the Lower Silurian meta-siliciclastics have suffered moderate to intense weathering, indicated by the weathering indices, like Chemical Index of Alteration (CIA), Plagioclase Index of Alteration (PIA) and Weathering Index (W index). The Lower Silurian rocks have high Th/Sc (generally between 1.1 and 2.0) and Th/U (generally between 4 and 6) ratios, LREE-enriched REE patterns with negative Eu anomalies (avg. 0.55), and low εNd(t) values (−16.2 to −8.5), suggesting a continental margin basin receiving detritus mostly derived from a recycled-orogen or cratonic provenance. This Early Silurian turbiditic succession with rhythmic flysch and incomplete Bouma sequences also reveals a neritic to abyssal facies, continental shelf to continental slope depositional setting. The geochemical features like the pattern of REEs, the ratios of trace elements (e.g., Th/Sc, Th/Co, La/Sc, Cr/Th, La/Th), and the binary plots and ternary diagrams (e.g., A–CN–K and FMW diagram), demonstrate that the source-areas are dominated by felsic rocks. Together with the two-stage Nd depleted mantle model age (TDM-2) (ca. 2.3Ga), the detrital zircon U–Pb age populations with peaks mainly at ca. 1635Ma confirm that the source rocks are dominated by the Paleo- to Mesoproterozoic Baoban Group and ca. 1430Ma granitoids on Hainan Island. Linked to the early Paleozoic tectonic development of South China, the Lower Silurian siliciclastic rocks on Hainan Island can be interpreted as depositing in a passive continent margin.

Completion of HLA protein sequences by automated homology-based nearest-neighbor extrapolation of HLA database sequences

The IMGT/HLA database contains every publicly available HLA sequence. However, most of these HLA protein sequences are restricted to the alpha-1/alpha-2 domain for HLA class-I and alpha-1/beta-1 domain for HLA class-II. Nevertheless, also polymorphism outside these domains may play a role in alloreactivity after transplantation. Several computational algorithms that aim for predicting alloreactivity after transplantation, HLAMatchmaker and the PIRCHE algorithm, require a major or the whole part of the HLA protein sequence as input for their prediction. In this study we describe an automated homology-based nearest-neighbor method to extrapolate incomplete HLA protein sequences. To get insight in the reliability of our extrapolation method, we performed a 10-fold cross-validation. The majority of the amino acid positions of the individual HLA class-I and -II proteins were correctly predicted. Eplets as defined by HLAMatchmaker were located both at correctly predicted as well as at lower reliably predicted amino acid positions. Moreover, six out of seven completely sequenced HLA alleles with previously unknown exons sequences were in agreement with the extrapolated amino acid sequences. In conclusion, incomplete HLA sequences can be completed by a homology-based nearest-neighbor principle. Since this method is automated, future submitted incomplete HLA sequences can easily be extrapolated.

Ecological, topographic and successional patterns across wetlands in a rugged land uplift coast in Nyby, northern Finland

We studied 45 mid-boreal wetlands in a rugged land uplift coast with a thin cover of till. Wetlands ranged from 1 to 53 m a.s.l. and were of highly various sizes. Our aims were to examine, if vegetation types are valid in comparing wetlands, what kind of ecological major pattern the vegetation type composition of wetlands shows and how vegetation types distribute across altitudes. On those ground we discuss the wetland succession of the study area. We used the Finnish mire site types as vegetation types. Mire site types could be used for an ecological classification and ordination of the wetlands. As was expected, the major gradient consisted of the transition from mire margin (swamp) to expanse. The distribution of the Major Vegetational Wetland Groups (MVWG) responded to a general water-flow pattern in the landscape. Partly different peatland succession sequences occur in areas with small mire basins and in areas with larger mire basins with evolving mire complexes. Sequences of small wetlands and those of mire complexes follow the same trajectory only as far as the major gradient is considered while they differ with regard to the vegetation type composition of locally rare vegetation types and with regard to peatland morphology. Trajectories of mire complexes at catchment divides differ from those at catchment centers where the waters in the landscape tend to gather. Peatland forms of aapa mires experience a change reaching altitudes of 30–50 m a.s.l. Small bog complexes at catchment divides reach a stage of an unpatterned Sphagnum fuscum bog in the study area. Mature mixed complexes with aapa-mire parts and patterned sloping-bog parts only occur at altitudes higher than 60 m a.s.l. Peculiarities in the succession of the wetlands of Nyby, which include the presence of separate incomplete successional sequences in the same area, are mainly caused by the peculiar topography with various sub-areas and with an abundance of rock outcrops.

불완전 시계열 데이터를 위한 이산 HMM 학습 알고리듬

Hidden Markov Model is one of the most successful and popular tools for modeling real world sequential data. Real world signals come in a variety of shapes and variabilities, among which temporal and spectral ones are the prime targets that the HMM aims at. A new problem that is gaining increasing attention is characterizing missing observations in incomplete data sequences. They are incomplete in that there are holes or omitted measurements. The standard HMM algorithms have been developed for complete data with a measurements at each regular point in time. This paper presents a modified algorithm for a discrete HMM that allows substantial amount of omissions in the input sequence. Basically it is a variant of Baum-Welch which explicitly considers the case of isolated or a number of omissions in succession. The algorithm has been tested on online handwriting samples expressed in direction codes. An extensive set of experiments show that the HMM so modeled are highly flexible showing a consistent and robust performance regardless of the amount of omissions.

Contourite vs gravity-flow deposits of the Pleistocene Faro Drift (Gulf of Cadiz): Sedimentological and mineralogical approaches

Pleistocene succession at Sites U1386 and U1387 (IODP 339) from palaeo-moat and drift domains of the Faro Drift has been examined to characterize the lithofacies and to identify the most useful criteria for distinguishing between contourite and gravity-flow deposits. Three lithofacies, A, B, and C, are defined based on a combination of sedimentological and mineralogical analyses. The dominant lithofacies A corresponds to contourite deposits; lithofacies B and C comprise turbidites and debrites respectively. Three main criteria have been utilized to distinguish between these deposits: (i) the vertical trend of the grain-size and the sedimentary structures. The contourites show complete sequences (C1 to C5 divisions) and truncate sequences (basecut-out divisions, e.g., C3–C2–C1, and C3). The turbidites display mainly Td–Te divisions, although Tc division is also present to a lesser extent. The debrites display deformational and shearing structures; (ii) the modal frequency distribution. The contourite sequences show similar mode grain-size values in different textures suggesting that the steady conditions of supply are maintained over time. In contrast, turbidite and debrite sequences display different modes, primarily conditioned by mixing of components from allochthonous sources and their downslope gravitational transport; (iii) the sediment composition (clay mineral, bulk mineral and sand fraction) and provenance that reflect long- and short-distance transport modes. Most of the terrigenous components of the contourites come from the Guadalquivir drainage basin, whereas for the turbidites and debrites these are sourced from the neighbouring fluvial drainage basins (Guadiana, Tinto-Odiel). The biogenic components in the latter indicate shallow depositional environments prior to seafloor failure. The spatial and temporal distributions of the lithofacies reflect the different (palaeo) environments of the Faro Drift. Debrite and incomplete turbidite sequences characterize the palaeo-moat domain during the Early Pleistocene. Complete contourite sequences (C1 to C5) and basecut-out sequences (C3–C4–C5, and C3) characterize the proximal palaeo-drift domain during the Early and Middle Pleistocene and the complete contourite sequences represent the distal drift domain during the Late Pleistocene.

Polymorphisms and resistance mutations of hepatitis C virus on sequences in the European hepatitis C virus database.

AIMTo evaluate the occurrence of resistant mutations in treatment-naïve hepatitis C virus (HCV) sequences deposited in the European hepatitis C virus database (euHCVdb).METHODSThe sequences were downloaded from the euHCVdb (https://euhcvdb.ibcp.fr/euHCVdb/). The search was performed for full-length NS3 protease, NS5A and NS5B polymerase sequences of HCV, separated by genotypes 1a, 1b, 2a, 2b and 3a, and resulted in 798 NS3, 708 NS5A and 535 NS5B sequences from HCV genotypes 1a, 1b, 2a, 2b and 3a, after the exclusion of sequences containing errors and/or gaps or incomplete sequences, and sequences from patients previously treated with direct antiviral agents (DAA). The sequence alignment was performed with MEGA 6.06 MAC and the resulting protein sequences were then analyzed using the BioEdit 7.2.5. for mutations associated with resistance. Only positions that have been described as being associated with failure in treatment in in vivo studies, and/or as conferring a more than 2-fold change in replication in comparison to the wildtype reference strain in in vitro phenotypic assays were included in the analysis.RESULTSThe Q80K variant in the NS3 gene was the most prevalent mutation, being found in 44.66% of subtype 1a and 0.25% of subtype 1b. Other frequent mutations observed in more than 2% of the NS3 sequences were: I170V (3.21%) in genotype 1a, and Y56F (15.93%), V132I (23.28%) and I170V (65.20%) in genotype 1b. For the NS5A, 2.21% of the genotype 1a sequences have the P58S mutation, 5.95% of genotype 1b sequences have the R30Q mutation, 15.79% of subtypes 2a sequences have the Q30R mutation, 23.08% of subtype 2b sequences have a L31M mutation, and in subtype 3a sequences, 23.08% have the M31L resistant variants. For the NS5B, the V321L RAV was identified in 0.60% of genotype 1a and in 0.32% of genotype 1b sequences, and the N142T variant was observed in 0.32% of subtype 1b sequences. The C316Y, S556G, D559N RAV were identified in 0.33%, 7.82% and 0.32% of genotype 1b sequences, respectively, and were not observed in other genotypes.CONCLUSIONHCV mutants resistant to DAAs are found in low frequency, nevertheless they could be selected and therapy could fail due resistance substitutions in HCV genome.

Draft mitochondrial genomes of Hirudo medicinalis and Hirudo verbana (Annelida, Hirudinea).

Here we present two incomplete mitochondrial genome sequences of Hirudo medicinalis and Hirudo verbana (Annelida, Hirudinea). The corresponding sequences are 14,729 and 14,604 base pairs in length. They contain all mitochondrial genes (13 protein-coding genes, 22 tRNAs and two rRNAs) but lack the non-coding region. Nevertheless, the robust reconstruction of their phylogenetic relationships presented here reveals distinct separation of both leeches from other annelids and at the same time relatively high dissimilarity between each other.

Intelligent Decision Support System for Dementia Care Through Smart Home

As per the statistics of WHO (World Health Organization), major percentages of aged society across the globe are affected with memory related disease - dementia. The percentage of dement people would be doubled in future and hence assistive health care systems have become predominant. Smart home, an ubiquitous environment offers ambient assisted living to its occupant through activity recognition and decision making process. This research work proposes an assistive dementia care environment through smart home that aid mentally disabled people with many different types of assistance during emergency. The proposed system models “Intelligent Decision Support System” that identifies deviation of the occupant from their regular activities of daily routines and decides on appropriate alerts to handle these situations. Significant criterion to model dementia care is to handle incomplete event sequences (produced due to memory loss) and to model occupant specific knowledge (provided by the care taker / doctors). Markov Logic Network (MLN), an approach of statistical relational learning models uncertain data and domain knowledge within a single framework. Thus, the proposed approach of decision support system for dementia care effectively utilizes MLN for its modeling. The experimental study made with smart home dataset showcased the competence of MLN approach of decision making has higher F-measure than existing approaches.

The calcified eggshell matrix proteome of a songbird, the zebra finch (Taeniopygia guttata).

BackgroundThe proteins of avian eggshell organic matrices are thought to control the mineralization of the eggshell in the shell gland (uterus). Proteomic analysis of such matrices identified many candidates for such a role. However, all matrices analyzed to date come from species of one avian family, the Phasianidae. To analyze the conservation of such proteins throughout the entire class Aves and to possibly identify a common protein toolkit enabling eggshell mineralization, it is important to analyze eggshell matrices from other avian families. Because mass spectrometry-based in-depth proteomic analysis still depends on sequence databases as comprehensive and accurate as possible, the obvious choice for a first such comparative study was the eggshell matrix of zebra finch, the genome sequence of which is the only songbird genome published to date.ResultsThe zebra finch eggshell matrix comprised 475 accepted protein identifications. Most of these proteins (84 %) were previously identified in species of the Phasianidae family (chicken, turkey, quail). This also included most of the so-called eggshell-specific proteins, the ovocleidins and ovocalyxins. Ovocleidin-116 was the second most abundant protein in the zebra finch eggshell matrix. Major proteins also included ovocalyxin-32 and -36. The sequence of ovocleidin-17 was not contained in the sequence database, but a presumptive homolog was tentatively identified by N-terminal sequence analysis of a prominent 17 kDa band. The major proteins also included three proteins similar to ovalbumin, the most abundant of which was identified as ovalbumin with the aid of two characteristic phosphorylation sites. Several other proteins identified in Phasianidae eggshell matrices were not identified. When the zebra finch sequence database contained a sequence similar to a missing phasianid protein it may be assumed that the protein is missing from the matrix. This applied to ovocalyxin-21/gastrokine-1, a major protein of the chicken eggshell matrix, to EDIL3 and to lactadherin. In other cases failure to identify a particular protein may be due to the absence of this protein from the sequence database, highlighting the importance of better, more comprehensive sequence databases.ConclusionsThe results indicate that ovocleidin-116, ovocleidin-17, ovocalyxin-36 and ovocalyxin-32 may be universal avian eggshell-mineralizing proteins. All the more important it is to elucidate the role of these proteins at the molecular level. This cannot be achieved by proteomic studies but will need application of other methods, such as atomic force microscopy or gene knockouts. However, it will also be important to analyze more eggshell matrices of different avian families to unequivocally identify other mineralization toolkit proteins apart from ovocleidins and ovocalyxins. Progress in this respect will depend critically on the availability of more, and more comprehensive, sequence databases. The development of faster and cheaper nucleotide sequencing methods has considerably accelerated genome and transcriptome sequencing, but this seems to concur with frequent publication of incomplete and fragmented sequence databases.Electronic supplementary materialThe online version of this article (doi:10.1186/s12953-015-0086-1) contains supplementary material, which is available to authorized users.

A Systematic Bayesian Integration of Epidemiological and Genetic Data

Genetic sequence data on pathogens have great potential to inform inference of their transmission dynamics ultimately leading to better disease control. Where genetic change and disease transmission occur on comparable timescales additional information can be inferred via the joint analysis of such genetic sequence data and epidemiological observations based on clinical symptoms and diagnostic tests. Although recently introduced approaches represent substantial progress, for computational reasons they approximate genuine joint inference of disease dynamics and genetic change in the pathogen population, capturing partially the joint epidemiological-evolutionary dynamics. Improved methods are needed to fully integrate such genetic data with epidemiological observations, for achieving a more robust inference of the transmission tree and other key epidemiological parameters such as latent periods. Here, building on current literature, a novel Bayesian framework is proposed that infers simultaneously and explicitly the transmission tree and unobserved transmitted pathogen sequences. Our framework facilitates the use of realistic likelihood functions and enables systematic and genuine joint inference of the epidemiological-evolutionary process from partially observed outbreaks. Using simulated data it is shown that this approach is able to infer accurately joint epidemiological-evolutionary dynamics, even when pathogen sequences and epidemiological data are incomplete, and when sequences are available for only a fraction of exposures. These results also characterise and quantify the value of incomplete and partial sequence data, which has important implications for sampling design, and demonstrate the abilities of the introduced method to identify multiple clusters within an outbreak. The framework is used to analyse an outbreak of foot-and-mouth disease in the UK, enhancing current understanding of its transmission dynamics and evolutionary process.

Lysosomal localization of Japanese medaka (Oryzias latipes) Neu1 sialidase and its highly conserved enzymatic profiles with human

Desialylation in the lysosome is a crucial step for glycoprotein degradation. The abnormality of lysosomal desialylation by NEU1 sialidase is involved in diseases of mammals such as sialidosis and galactosialidosis. Mammalian Neu1 sialidase is also localized at plasma membrane where it regulates several signaling pathways through glycoprotein desialylation. In fish, on the other hand, the mechanism of desialylation in the lysosome and functions of Neu1 sialidase are still unclear. Here, to understand the significance of fish Neu1 sialidase, neu1 gene was cloned from medaka brain and the profiles of its polypeptides were analyzed. Open reading frame of medaka neu1 consisted 1,182bp and the similarity of its deduced amino acids with human NEU1 was 57%. As this recombinant polypeptide did not show significant sialidase activity, medaka cathepsin A, known in mammals as protective protein activating Neu1, was cloned and then co-expressed with medaka Neu1 to examine whether medaka cathepsin A activates Neu1 activity. As a result, Neu1/cathepsin A showed a drastic increase of sialidase activity toward MU-NANA. Major substrate of medaka Neu1 was 3-sialyllactose and its optimal pH was 4.0. With immunofluorescence analysis, signal of overexpressed medaka Neu1 was found to coincide with Lysotracker signals (organelle marker of lysosome) and co-localized with medaka cathepsin A in fish hepatic Hepa-T1 cells. Furthermore, part of medaka Neu1 was also detected at plasma membrane. Medaka Neu1 possessed signal peptide sequence at N-terminal and incomplete lysosomal targeting sequence at C-terminus. Medaka neu1 gene was ubiquitously expressed in various medaka tissues, and its expression level was significantly higher than other sialidase genes such as neu3a, neu3b and neu4. The present study revealed the profiles of fish Neu1 sialidase and indicated its high conservation with human NEU1 for the first time, suggesting the presence of similar desialylation system in the medaka lysosome to human. Moreover, the present study showed the possibility of medaka as a model animal of human NEU1 sialidase.

Accurate identification of mass peaks for tandem mass spectra using MCMC model

In proteomics, many methods for the identification of proteins have been developed. However, because of limited known genome sequences, noisy data, incomplete ion sequences, and the accuracy of protein identification,it is challenging to identify peptides using tandem mass spectral data. Noise filtering and removing thus play a key role in accurate peptide identification from tandem mass spectra. In this paper, we employ a Bayesian model to identify proteins based on the prior information of bond cleavages. A Markov Chain Monte Carlo(MCMC)algorithm is used to simulate candidate peptides from the posterior distribution and to estimate the parameters for the Bayesian model. Our simulation and computational experimental results show that the model can identify peptide with a higher accuracy.

Full-length HLA-DRB1 coding sequences generated by a hemizygous RNA-SBT approach.

Currently 1582 HLA-DRB1 alleles have been identified in the IMGT/HLA database (v3.18). Among those alleles, more than 90% have incomplete allele sequences, which complicates the analysis of the functional relevance of polymorphism beyond exon 2. The polymorphic index of each individual exon of the currently known allele sequences, shows that polymorphism is present in all exons, albeit not equally abundant. Full-length HLA-DRB1 RNA sequencing identifies polymorphism of the complete coding region. Here we describe a hemizygous full-length RNA sequence-based typing (SBT) approach based on group-specific HLA-DRB1 amplification and subsequent sequencing. RNA full-length sequences can easily be accessed because of the short amplicon length (801 bp). The RNA-SBT approach was successfully validated on a panel of DRB1 alleles having fully known coding sequences according to the IMGT/HLA database, and cover all serological equivalents. Subsequently, the approach was applied on a panel of 54 alleles with incomplete allele sequences, resulting in full-length coding sequences and the identification of one new and one corrected allele. This study shows the universal applicability of the RNA-based sequencing approach to identify full-length coding sequences and to define the polymorphic content of HLA-DRB1 alleles.

Genomic variability and protein species — Improving sequence coverage for proteogenomics

Protein heterogeneity may result from many factors often closely related to the regulation of biological mechanisms. This review addresses one source of protein heterogeneity, the translation of genetic variability and transcriptional modulation to the protein level. We provide an overview how customized protein sequence databases generated using genomic and transcriptomic sequence information in conjunction with approaches to increase protein sequence coverage can aid in gaining a deeper insight into variability at the protein level. Modern approaches of DNA/RNA sequencing open the possibility to obtain detailed sequence information from individual genomes and transcriptomes at single nucleotide resolution. Further studies tried to correlate genetic variability with important biological consequences such as the risk for developing a disease or defining a personalized approach towards therapy (also called “personalized or precision medicine”). Linking genomic and transcriptomic information to complex biological mechanisms has, however, remained elusive due to the fact that there is no direct cause and effect relationship between changes at the DNA/RNA level and downstream consequences. In this review we give an overview of the challenges of integrating genomics and transcriptomics data with proteomics data and link variability at the DNA/RNA level to protein variability and protein species. Biological significanceThe manuscript focuses on a recent trend in proteomics, namely the integration of genomic and proteomic data. Genetic and transcriptomic variability accounts for a considerable part of protein variability and is at the basis of many protein species, many of which not yet described at the protein level but many also identified as proteins or peptides with unknown function. The review highlights the challenges of current proteomics methodology, notably incomplete sequence coverage, which make it difficult to appreciate the full complexity of any proteome and leads to the fact that much variability at the DNA/RNA level is not captured at the protein level. We outline a few strategies to ameliorate this situation.

Using next generation sequencing to characterize potential HLA class I novel alleles

Aim We explored the impact of using next generation sequencing (NGS) of the entire gene in 300 samples carrying potential new or rare HLA class I alleles. Methods Samples had been previously typed for exons 2 + 3 by SBT sequence based typing (Sanger) and/or by (SSO) sequence specific oligoprobes. Targeted class I loci were amplified using locus-specific PCR primers described by Hozomichi et al. Sonication was used to obtain 400 base pair fragments; an Illumina True Seq Nano kit was used for end repair and adaptor/index ligation. Libraries were pooled and paired end sequences were obtained with a MiSeq. AssignTM MPS software (Connexio, Genomics) was used for analysis. Results Of the 600 alleles sequenced, 69 (11.5%) novel alleles (HLA-A: 27, B: 31, C: 11) differed in the antigen recognition domain (ARD)-encoding exons 2 and/or 3. Ten additional alleles (1.7 %) carried previously unobserved differences in non-ARD-encoding exons (exon 1:2, exon 4:5, exon 5:2, exon 7:1). Thirty three alleles (5.5%) appeared to exhibit novel sequences only in introns. At HLA-A∗03:01:01:01 a novel insertion of 19 bp was observed in intron 2 in two different cells. One hundred and fifty seven (26%) alleles had incomplete sequences in the IMGT/HLA data base, of which most of these (121) had intron sequences identical to the closest related allele. The remaining 331 alleles were primarily common and well documented alleles. Conclusion NGS provided complete, unambiguous, high resolution allele assignments. In this more comprehensive analysis, there was less variation from the IMGT reference database than expected. Most of the introns of alleles with incomplete sequences were conserved when compared to their putative ancestral allele. L. Hou: Other (Identify); Company/Organization; Intellectual property. B. Tu: Other (Identify); Company/Organization; Intellectual property. C. Masaberg: Other (Identify); Company/Organization; Intellectual property. B. Beduhn: Employee; Company/Organization; National Marrow Donor Program. D. Goodridge: Employee; Company/Organization; Connexio Genomics. J. Ng: Other (Identify); Company/Organization; Intellectual property. C.K. Hurley: Other (Identify); Company/Organization; Intellectual property.