Evolution and Diversity of the Human Hepatitis D Virus Genome

PubMed Central

Huang, Chi-Ruei; Lo, Szecheng J.

2010-01-01

Human hepatitis delta virus (HDV) is the smallest RNA virus in genome. HDV genome is divided into a viroid-like sequence and a protein-coding sequence which could have originated from different resources and the HDV genome was eventually constituted through RNA recombination. The genome subsequently diversified through accumulation of mutations selected by interactions between the mutated RNA and proteins with host factors to successfully form the infectious virions. Therefore, we propose that the conservation of HDV nucleotide sequence is highly related with its functionality. Genome analysis of known HDV isolates shows that the C-terminal coding sequences of large delta antigen (LDAg) are the highest diversity than other regions of protein-coding sequences but they still retain biological functionality to interact with the heavy chain of clathrin can be selected and maintained. Since viruses interact with many host factors, including escaping the host immune response, how to design a program to predict RNA genome evolution is a great challenging work. PMID:20204073

SIFTER search: a web server for accurate phylogeny-based protein function prediction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sahraeian, Sayed M.; Luo, Kevin R.; Brenner, Steven E.

We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access tomore » precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. Lastly, the SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded.« less

SIFTER search: a web server for accurate phylogeny-based protein function prediction

DOE PAGES

Sahraeian, Sayed M.; Luo, Kevin R.; Brenner, Steven E.

2015-05-15

We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access tomore » precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. Lastly, the SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded.« less

Draft Genome Sequence of the Deinococcus-Thermus Bacterium Meiothermus ruber Strain A

DOE PAGES

Thiel, Vera; Tomsho, Lynn P.; Burhans, Richard; ...

2015-03-26

The draft genome sequence of the Deinococcus-Thermus group bacterium Meiothermus ruber strain A, isolated from a cyanobacterial enrichment culture obtained from Octopus Spring (Yellowstone National Park, WY), comprises 2,968,099 bp in 170 contigs. It is predicted to contain 2,895 protein-coding genes, 44 tRNA-coding genes, and 2 rRNA operons.

Identification of Putative Nuclear Receptors and Steroidogenic Enzymes in Murray-Darling Rainbowfish (Melanotaenia fluviatilis) Using RNA-Seq and De Novo Transcriptome Assembly.

PubMed

Bain, Peter A; Papanicolaou, Alexie; Kumar, Anupama

2015-01-01

Murray-Darling rainbowfish (Melanotaenia fluviatilis [Castelnau, 1878]; Atheriniformes: Melanotaeniidae) is a small-bodied teleost currently under development in Australasia as a test species for aquatic toxicological studies. To date, efforts towards the development of molecular biomarkers of contaminant exposure have been hindered by the lack of available sequence data. To address this, we sequenced messenger RNA from brain, liver and gonads of mature male and female fish and generated a high-quality draft transcriptome using a de novo assembly approach. 149,742 clusters of putative transcripts were obtained, encompassing 43,841 non-redundant protein-coding regions. Deduced amino acid sequences were annotated by functional inference based on similarity with sequences from manually curated protein sequence databases. The draft assembly contained protein-coding regions homologous to 95.7% of the complete cohort of predicted proteins from the taxonomically related species, Oryzias latipes (Japanese medaka). The mean length of rainbowfish protein-coding sequences relative to their medaka homologues was 92.1%, indicating that despite the limited number of tissues sampled a large proportion of the total expected number of protein-coding genes was captured in the study. Because of our interest in the effects of environmental contaminants on endocrine pathways, we manually curated subsets of coding regions for putative nuclear receptors and steroidogenic enzymes in the rainbowfish transcriptome, revealing 61 candidate nuclear receptors encompassing all known subfamilies, and 41 putative steroidogenic enzymes representing all major steroidogenic enzymes occurring in teleosts. The transcriptome presented here will be a valuable resource for researchers interested in biomarker development, protein structure and function, and contaminant-response genomics in Murray-Darling rainbowfish.

SinEx DB: a database for single exon coding sequences in mammalian genomes.

PubMed

Jorquera, Roddy; Ortiz, Rodrigo; Ossandon, F; Cárdenas, Juan Pablo; Sepúlveda, Rene; González, Carolina; Holmes, David S

2016-01-01

Eukaryotic genes are typically interrupted by intragenic, noncoding sequences termed introns. However, some genes lack introns in their coding sequence (CDS) and are generally known as 'single exon genes' (SEGs). In this work, a SEG is defined as a nuclear, protein-coding gene that lacks introns in its CDS. Whereas, many public databases of Eukaryotic multi-exon genes are available, there are only two specialized databases for SEGs. The present work addresses the need for a more extensive and diverse database by creating SinEx DB, a publicly available, searchable database of predicted SEGs from 10 completely sequenced mammalian genomes including human. SinEx DB houses the DNA and protein sequence information of these SEGs and includes their functional predictions (KOG) and the relative distribution of these functions within species. The information is stored in a relational database built with My SQL Server 5.1.33 and the complete dataset of SEG sequences and their functional predictions are available for downloading. SinEx DB can be interrogated by: (i) a browsable phylogenetic schema, (ii) carrying out BLAST searches to the in-house SinEx DB of SEGs and (iii) via an advanced search mode in which the database can be searched by key words and any combination of searches by species and predicted functions. SinEx DB provides a rich source of information for advancing our understanding of the evolution and function of SEGs.Database URL: www.sinex.cl. © The Author(s) 2016. Published by Oxford University Press.

SIBIS: a Bayesian model for inconsistent protein sequence estimation.

PubMed

Khenoussi, Walyd; Vanhoutrève, Renaud; Poch, Olivier; Thompson, Julie D

2014-09-01

The prediction of protein coding genes is a major challenge that depends on the quality of genome sequencing, the accuracy of the model used to elucidate the exonic structure of the genes and the complexity of the gene splicing process leading to different protein variants. As a consequence, today's protein databases contain a huge amount of inconsistency, due to both natural variants and sequence prediction errors. We have developed a new method, called SIBIS, to detect such inconsistencies based on the evolutionary information in multiple sequence alignments. A Bayesian framework, combined with Dirichlet mixture models, is used to estimate the probability of observing specific amino acids and to detect inconsistent or erroneous sequence segments. We evaluated the performance of SIBIS on a reference set of protein sequences with experimentally validated errors and showed that the sensitivity is significantly higher than previous methods, with only a small loss of specificity. We also assessed a large set of human sequences from the UniProt database and found evidence of inconsistency in 48% of the previously uncharacterized sequences. We conclude that the integration of quality control methods like SIBIS in automatic analysis pipelines will be critical for the robust inference of structural, functional and phylogenetic information from these sequences. Source code, implemented in C on a linux system, and the datasets of protein sequences are freely available for download at http://www.lbgi.fr/∼julie/SIBIS. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

SPRINT: ultrafast protein-protein interaction prediction of the entire human interactome.

PubMed

Li, Yiwei; Ilie, Lucian

2017-11-15

Proteins perform their functions usually by interacting with other proteins. Predicting which proteins interact is a fundamental problem. Experimental methods are slow, expensive, and have a high rate of error. Many computational methods have been proposed among which sequence-based ones are very promising. However, so far no such method is able to predict effectively the entire human interactome: they require too much time or memory. We present SPRINT (Scoring PRotein INTeractions), a new sequence-based algorithm and tool for predicting protein-protein interactions. We comprehensively compare SPRINT with state-of-the-art programs on seven most reliable human PPI datasets and show that it is more accurate while running orders of magnitude faster and using very little memory. SPRINT is the only sequence-based program that can effectively predict the entire human interactome: it requires between 15 and 100 min, depending on the dataset. Our goal is to transform the very challenging problem of predicting the entire human interactome into a routine task. The source code of SPRINT is freely available from https://github.com/lucian-ilie/SPRINT/ and the datasets and predicted PPIs from www.csd.uwo.ca/faculty/ilie/SPRINT/ .

Genomic analysis of organismal complexity in the multicellular green alga Volvox carteri

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prochnik, Simon E.; Umen, James; Nedelcu, Aurora

2010-07-01

Analysis of the Volvox carteri genome reveals that this green alga's increased organismal complexity and multicellularity are associated with modifications in protein families shared with its unicellular ancestor, and not with large-scale innovations in protein coding capacity. The multicellular green alga Volvox carteri and its morphologically diverse close relatives (the volvocine algae) are uniquely suited for investigating the evolution of multicellularity and development. We sequenced the 138 Mb genome of V. carteri and compared its {approx}14,500 predicted proteins to those of its unicellular relative, Chlamydomonas reinhardtii. Despite fundamental differences in organismal complexity and life history, the two species have similarmore » protein-coding potentials, and few species-specific protein-coding gene predictions. Interestingly, volvocine algal-specific proteins are enriched in Volvox, including those associated with an expanded and highly compartmentalized extracellular matrix. Our analysis shows that increases in organismal complexity can be associated with modifications of lineage-specific proteins rather than large-scale invention of protein-coding capacity.« less

Representation of DNA sequences in genetic codon context with applications in exon and intron prediction.

PubMed

Yin, Changchuan

2015-04-01

To apply digital signal processing (DSP) methods to analyze DNA sequences, the sequences first must be specially mapped into numerical sequences. Thus, effective numerical mappings of DNA sequences play key roles in the effectiveness of DSP-based methods such as exon prediction. Despite numerous mappings of symbolic DNA sequences to numerical series, the existing mapping methods do not include the genetic coding features of DNA sequences. We present a novel numerical representation of DNA sequences using genetic codon context (GCC) in which the numerical values are optimized by simulation annealing to maximize the 3-periodicity signal to noise ratio (SNR). The optimized GCC representation is then applied in exon and intron prediction by Short-Time Fourier Transform (STFT) approach. The results show the GCC method enhances the SNR values of exon sequences and thus increases the accuracy of predicting protein coding regions in genomes compared with the commonly used 4D binary representation. In addition, this study offers a novel way to reveal specific features of DNA sequences by optimizing numerical mappings of symbolic DNA sequences.

Draft Genome Sequence of Photorhabdus luminescens Strain DSPV002N Isolated from Santa Fe, Argentina

PubMed Central

Del Valle, Eleodoro E.; Frizzo, Laureano; Berry, Colin; Caballero, Primitivo

2016-01-01

Here, we report the draft genome sequence of Photorhabdus luminescens strain DSPV002N, which consists of 177 contig sequences accounting for 5,518,143 bp, with a G+C content of 42.3% and 4,701 predicted protein-coding genes (CDSs). From these, 27 CDSs exhibited significant similarity with insecticidal toxin proteins from Photorhabdus luminescens subsp. laumondii TT01. PMID:27469965

DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier.

PubMed

Kulmanov, Maxat; Khan, Mohammed Asif; Hoehndorf, Robert; Wren, Jonathan

2018-02-15

A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often only done rigorously for few selected model organisms. Computational function prediction approaches have been suggested to fill this gap. The functions of proteins are classified using the Gene Ontology (GO), which contains over 40 000 classes. Additionally, proteins have multiple functions, making function prediction a large-scale, multi-class, multi-label problem. We have developed a novel method to predict protein function from sequence. We use deep learning to learn features from protein sequences as well as a cross-species protein-protein interaction network. Our approach specifically outputs information in the structure of the GO and utilizes the dependencies between GO classes as background information to construct a deep learning model. We evaluate our method using the standards established by the Computational Assessment of Function Annotation (CAFA) and demonstrate a significant improvement over baseline methods such as BLAST, in particular for predicting cellular locations. Web server: http://deepgo.bio2vec.net, Source code: https://github.com/bio-ontology-research-group/deepgo. robert.hoehndorf@kaust.edu.sa. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Correlations of nucleotide substitution rates and base composition of mammalian coding sequences with protein structure.

PubMed

Chiusano, M L; D'Onofrio, G; Alvarez-Valin, F; Jabbari, K; Colonna, G; Bernardi, G

1999-09-30

We investigated the relationships between the nucleotide substitution rates and the predicted secondary structures in the three states representation (alpha-helix, beta-sheet, and coil). The analysis was carried out on 34 alignments, each of which comprised sequences belonging to at least four different mammalian orders. The rates of synonymous substitution were found to be significantly different in regions predicted to be alpha-helix, beta-sheet, or coil. Likewise, the nonsynonymous rates also differ, although expectedly at a lower extent, in the three types of secondary structure, suggesting that different selective constraints associated with the different structures are affecting in a similar way the synonymous and nonsynonymous rates. Moreover, the base composition of the third codon positions is different in coding sequence regions corresponding to different secondary structures of proteins.

Multi-level machine learning prediction of protein-protein interactions in Saccharomyces cerevisiae.

PubMed

Zubek, Julian; Tatjewski, Marcin; Boniecki, Adam; Mnich, Maciej; Basu, Subhadip; Plewczynski, Dariusz

2015-01-01

Accurate identification of protein-protein interactions (PPI) is the key step in understanding proteins' biological functions, which are typically context-dependent. Many existing PPI predictors rely on aggregated features from protein sequences, however only a few methods exploit local information about specific residue contacts. In this work we present a two-stage machine learning approach for prediction of protein-protein interactions. We start with the carefully filtered data on protein complexes available for Saccharomyces cerevisiae in the Protein Data Bank (PDB) database. First, we build linear descriptions of interacting and non-interacting sequence segment pairs based on their inter-residue distances. Secondly, we train machine learning classifiers to predict binary segment interactions for any two short sequence fragments. The final prediction of the protein-protein interaction is done using the 2D matrix representation of all-against-all possible interacting sequence segments of both analysed proteins. The level-I predictor achieves 0.88 AUC for micro-scale, i.e., residue-level prediction. The level-II predictor improves the results further by a more complex learning paradigm. We perform 30-fold macro-scale, i.e., protein-level cross-validation experiment. The level-II predictor using PSIPRED-predicted secondary structure reaches 0.70 precision, 0.68 recall, and 0.70 AUC, whereas other popular methods provide results below 0.6 threshold (recall, precision, AUC). Our results demonstrate that multi-scale sequence features aggregation procedure is able to improve the machine learning results by more than 10% as compared to other sequence representations. Prepared datasets and source code for our experimental pipeline are freely available for download from: http://zubekj.github.io/mlppi/ (open source Python implementation, OS independent).

Well-characterized sequence features of eukaryote genomes and implications for ab initio gene prediction.

PubMed

Huang, Ying; Chen, Shi-Yi; Deng, Feilong

2016-01-01

In silico analysis of DNA sequences is an important area of computational biology in the post-genomic era. Over the past two decades, computational approaches for ab initio prediction of gene structure from genome sequence alone have largely facilitated our understanding on a variety of biological questions. Although the computational prediction of protein-coding genes has already been well-established, we are also facing challenges to robustly find the non-coding RNA genes, such as miRNA and lncRNA. Two main aspects of ab initio gene prediction include the computed values for describing sequence features and used algorithm for training the discriminant function, and by which different combinations are employed into various bioinformatic tools. Herein, we briefly review these well-characterized sequence features in eukaryote genomes and applications to ab initio gene prediction. The main purpose of this article is to provide an overview to beginners who aim to develop the related bioinformatic tools.

Analysis of protein-coding genetic variation in 60,706 humans.

PubMed

Lek, Monkol; Karczewski, Konrad J; Minikel, Eric V; Samocha, Kaitlin E; Banks, Eric; Fennell, Timothy; O'Donnell-Luria, Anne H; Ware, James S; Hill, Andrew J; Cummings, Beryl B; Tukiainen, Taru; Birnbaum, Daniel P; Kosmicki, Jack A; Duncan, Laramie E; Estrada, Karol; Zhao, Fengmei; Zou, James; Pierce-Hoffman, Emma; Berghout, Joanne; Cooper, David N; Deflaux, Nicole; DePristo, Mark; Do, Ron; Flannick, Jason; Fromer, Menachem; Gauthier, Laura; Goldstein, Jackie; Gupta, Namrata; Howrigan, Daniel; Kiezun, Adam; Kurki, Mitja I; Moonshine, Ami Levy; Natarajan, Pradeep; Orozco, Lorena; Peloso, Gina M; Poplin, Ryan; Rivas, Manuel A; Ruano-Rubio, Valentin; Rose, Samuel A; Ruderfer, Douglas M; Shakir, Khalid; Stenson, Peter D; Stevens, Christine; Thomas, Brett P; Tiao, Grace; Tusie-Luna, Maria T; Weisburd, Ben; Won, Hong-Hee; Yu, Dongmei; Altshuler, David M; Ardissino, Diego; Boehnke, Michael; Danesh, John; Donnelly, Stacey; Elosua, Roberto; Florez, Jose C; Gabriel, Stacey B; Getz, Gad; Glatt, Stephen J; Hultman, Christina M; Kathiresan, Sekar; Laakso, Markku; McCarroll, Steven; McCarthy, Mark I; McGovern, Dermot; McPherson, Ruth; Neale, Benjamin M; Palotie, Aarno; Purcell, Shaun M; Saleheen, Danish; Scharf, Jeremiah M; Sklar, Pamela; Sullivan, Patrick F; Tuomilehto, Jaakko; Tsuang, Ming T; Watkins, Hugh C; Wilson, James G; Daly, Mark J; MacArthur, Daniel G

2016-08-18

Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.

Intrinsic and extrinsic approaches for detecting genes in a bacterial genome.

PubMed Central

Borodovsky, M; Rudd, K E; Koonin, E V

1994-01-01

The unannotated regions of the Escherichia coli genome DNA sequence from the EcoSeq6 database, totaling 1,278 'intergenic' sequences of the combined length of 359,279 basepairs, were analyzed using computer-assisted methods with the aim of identifying putative unknown genes. The proposed strategy for finding new genes includes two key elements: i) prediction of expressed open reading frames (ORFs) using the GeneMark method based on Markov chain models for coding and non-coding regions of Escherichia coli DNA, and ii) search for protein sequence similarities using programs based on the BLAST algorithm and programs for motif identification. A total of 354 putative expressed ORFs were predicted by GeneMark. Using the BLASTX and TBLASTN programs, it was shown that 208 ORFs located in the unannotated regions of the E. coli chromosome are significantly similar to other protein sequences. Identification of 182 ORFs as probable genes was supported by GeneMark and BLAST, comprising 51.4% of the GeneMark 'hits' and 87.5% of the BLAST 'hits'. 73 putative new genes, comprising 20.6% of the GeneMark predictions, belong to ancient conserved protein families that include both eubacterial and eukaryotic members. This value is close to the overall proportion of highly conserved sequences among eubacterial proteins, indicating that the majority of the putative expressed ORFs that are predicted by GeneMark, but have no significant BLAST hits, nevertheless are likely to be real genes. The majority of the putative genes identified by BLAST search have been described since the release of the EcoSeq6 database, but about 70 genes have not been detected so far. Among these new identifications are genes encoding proteins with a variety of predicted functions including dehydrogenases, kinases, several other metabolic enzymes, ATPases, rRNA methyltransferases, membrane proteins, and different types of regulatory proteins. Images PMID:7984428

A Graph-Centric Approach for Metagenome-Guided Peptide and Protein Identification in Metaproteomics

PubMed Central

Tang, Haixu; Li, Sujun; Ye, Yuzhen

2016-01-01

Metaproteomic studies adopt the common bottom-up proteomics approach to investigate the protein composition and the dynamics of protein expression in microbial communities. When matched metagenomic and/or metatranscriptomic data of the microbial communities are available, metaproteomic data analyses often employ a metagenome-guided approach, in which complete or fragmental protein-coding genes are first directly predicted from metagenomic (and/or metatranscriptomic) sequences or from their assemblies, and the resulting protein sequences are then used as the reference database for peptide/protein identification from MS/MS spectra. This approach is often limited because protein coding genes predicted from metagenomes are incomplete and fragmental. In this paper, we present a graph-centric approach to improving metagenome-guided peptide and protein identification in metaproteomics. Our method exploits the de Bruijn graph structure reported by metagenome assembly algorithms to generate a comprehensive database of protein sequences encoded in the community. We tested our method using several public metaproteomic datasets with matched metagenomic and metatranscriptomic sequencing data acquired from complex microbial communities in a biological wastewater treatment plant. The results showed that many more peptides and proteins can be identified when assembly graphs were utilized, improving the characterization of the proteins expressed in the microbial communities. The additional proteins we identified contribute to the characterization of important pathways such as those involved in degradation of chemical hazards. Our tools are released as open-source software on github at https://github.com/COL-IU/Graph2Pro. PMID:27918579

Predicted secondary structure similarity in the absence of primary amino acid sequence homology: hepatitis B virus open reading frames.

PubMed Central

Schaeffer, E; Sninsky, J J

1984-01-01

Proteins that are related evolutionarily may have diverged at the level of primary amino acid sequence while maintaining similar secondary structures. Computer analysis has been used to compare the open reading frames of the hepatitis B virus to those of the woodchuck hepatitis virus at the level of amino acid sequence, and to predict the relative hydrophilic character and the secondary structure of putative polypeptides. Similarity is seen at the levels of relative hydrophilicity and secondary structure, in the absence of sequence homology. These data reinforce the proposal that these open reading frames encode viral proteins. Computer analysis of this type can be more generally used to establish structural similarities between proteins that do not share obvious sequence homology as well as to assess whether an open reading frame is fortuitous or codes for a protein. PMID:6585835

Predicting protein subcellular locations using hierarchical ensemble of Bayesian classifiers based on Markov chains.

PubMed

Bulashevska, Alla; Eils, Roland

2006-06-14

The subcellular location of a protein is closely related to its function. It would be worthwhile to develop a method to predict the subcellular location for a given protein when only the amino acid sequence of the protein is known. Although many efforts have been made to predict subcellular location from sequence information only, there is the need for further research to improve the accuracy of prediction. A novel method called HensBC is introduced to predict protein subcellular location. HensBC is a recursive algorithm which constructs a hierarchical ensemble of classifiers. The classifiers used are Bayesian classifiers based on Markov chain models. We tested our method on six various datasets; among them are Gram-negative bacteria dataset, data for discriminating outer membrane proteins and apoptosis proteins dataset. We observed that our method can predict the subcellular location with high accuracy. Another advantage of the proposed method is that it can improve the accuracy of the prediction of some classes with few sequences in training and is therefore useful for datasets with imbalanced distribution of classes. This study introduces an algorithm which uses only the primary sequence of a protein to predict its subcellular location. The proposed recursive scheme represents an interesting methodology for learning and combining classifiers. The method is computationally efficient and competitive with the previously reported approaches in terms of prediction accuracies as empirical results indicate. The code for the software is available upon request.

Protein Sequence Annotation Tool (PSAT): A centralized web-based meta-server for high-throughput sequence annotations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leung, Elo; Huang, Amy; Cadag, Eithon

In this study, we introduce the Protein Sequence Annotation Tool (PSAT), a web-based, sequence annotation meta-server for performing integrated, high-throughput, genome-wide sequence analyses. Our goals in building PSAT were to (1) create an extensible platform for integration of multiple sequence-based bioinformatics tools, (2) enable functional annotations and enzyme predictions over large input protein fasta data sets, and (3) provide a web interface for convenient execution of the tools. In this paper, we demonstrate the utility of PSAT by annotating the predicted peptide gene products of Herbaspirillum sp. strain RV1423, importing the results of PSAT into EC2KEGG, and using the resultingmore » functional comparisons to identify a putative catabolic pathway, thereby distinguishing RV1423 from a well annotated Herbaspirillum species. This analysis demonstrates that high-throughput enzyme predictions, provided by PSAT processing, can be used to identify metabolic potential in an otherwise poorly annotated genome. Lastly, PSAT is a meta server that combines the results from several sequence-based annotation and function prediction codes, and is available at http://psat.llnl.gov/psat/. PSAT stands apart from other sequencebased genome annotation systems in providing a high-throughput platform for rapid de novo enzyme predictions and sequence annotations over large input protein sequence data sets in FASTA. PSAT is most appropriately applied in annotation of large protein FASTA sets that may or may not be associated with a single genome.« less

Protein Sequence Annotation Tool (PSAT): A centralized web-based meta-server for high-throughput sequence annotations

DOE PAGES

Leung, Elo; Huang, Amy; Cadag, Eithon; ...

2016-01-20

In this study, we introduce the Protein Sequence Annotation Tool (PSAT), a web-based, sequence annotation meta-server for performing integrated, high-throughput, genome-wide sequence analyses. Our goals in building PSAT were to (1) create an extensible platform for integration of multiple sequence-based bioinformatics tools, (2) enable functional annotations and enzyme predictions over large input protein fasta data sets, and (3) provide a web interface for convenient execution of the tools. In this paper, we demonstrate the utility of PSAT by annotating the predicted peptide gene products of Herbaspirillum sp. strain RV1423, importing the results of PSAT into EC2KEGG, and using the resultingmore » functional comparisons to identify a putative catabolic pathway, thereby distinguishing RV1423 from a well annotated Herbaspirillum species. This analysis demonstrates that high-throughput enzyme predictions, provided by PSAT processing, can be used to identify metabolic potential in an otherwise poorly annotated genome. Lastly, PSAT is a meta server that combines the results from several sequence-based annotation and function prediction codes, and is available at http://psat.llnl.gov/psat/. PSAT stands apart from other sequencebased genome annotation systems in providing a high-throughput platform for rapid de novo enzyme predictions and sequence annotations over large input protein sequence data sets in FASTA. PSAT is most appropriately applied in annotation of large protein FASTA sets that may or may not be associated with a single genome.« less

CaMELS: In silico prediction of calmodulin binding proteins and their binding sites.

PubMed

Abbasi, Wajid Arshad; Asif, Amina; Andleeb, Saiqa; Minhas, Fayyaz Ul Amir Afsar

2017-09-01

Due to Ca 2+ -dependent binding and the sequence diversity of Calmodulin (CaM) binding proteins, identifying CaM interactions and binding sites in the wet-lab is tedious and costly. Therefore, computational methods for this purpose are crucial to the design of such wet-lab experiments. We present an algorithm suite called CaMELS (CalModulin intEraction Learning System) for predicting proteins that interact with CaM as well as their binding sites using sequence information alone. CaMELS offers state of the art accuracy for both CaM interaction and binding site prediction and can aid biologists in studying CaM binding proteins. For CaM interaction prediction, CaMELS uses protein sequence features coupled with a large-margin classifier. CaMELS models the binding site prediction problem using multiple instance machine learning with a custom optimization algorithm which allows more effective learning over imprecisely annotated CaM-binding sites during training. CaMELS has been extensively benchmarked using a variety of data sets, mutagenic studies, proteome-wide Gene Ontology enrichment analyses and protein structures. Our experiments indicate that CaMELS outperforms simple motif-based search and other existing methods for interaction and binding site prediction. We have also found that the whole sequence of a protein, rather than just its binding site, is important for predicting its interaction with CaM. Using the machine learning model in CaMELS, we have identified important features of protein sequences for CaM interaction prediction as well as characteristic amino acid sub-sequences and their relative position for identifying CaM binding sites. Python code for training and evaluating CaMELS together with a webserver implementation is available at the URL: http://faculty.pieas.edu.pk/fayyaz/software.html#camels. © 2017 Wiley Periodicals, Inc.

TCOF1 gene encodes a putative nucleolar phosphoprotein that exhibits mutations in Treacher Collins Syndrome throughout its coding region.

PubMed

Wise, C A; Chiang, L C; Paznekas, W A; Sharma, M; Musy, M M; Ashley, J A; Lovett, M; Jabs, E W

1997-04-01

Treacher Collins Syndrome (TCS) is the most common of the human mandibulofacial dysostosis disorders. Recently, a partial TCOF1 cDNA was identified and shown to contain mutations in TCS families. Here we present the entire exon/intron genomic structure and the complete coding sequence of TCOF1. TCOF1 encodes a low complexity protein of 1,411 amino acids, whose predicted protein structure reveals repeated motifs that mirror the organization of its exons. These motifs are shared with nucleolar trafficking proteins in other species and are predicted to be highly phosphorylated by casein kinase. Consistent with this, the full-length TCOF1 protein sequence also contains putative nuclear and nucleolar localization signals. Throughout the open reading frame, we detected an additional eight mutations in TCS families and several polymorphisms. We postulate that TCS results from defects in a nucleolar trafficking protein that is critically required during human craniofacial development.

Computational prediction of over-annotated protein-coding genes in the genome of Agrobacterium tumefaciens strain C58

NASA Astrophysics Data System (ADS)

Yu, Jia-Feng; Sui, Tian-Xiang; Wang, Hong-Mei; Wang, Chun-Ling; Jing, Li; Wang, Ji-Hua

2015-12-01

Agrobacterium tumefaciens strain C58 is a type of pathogen that can cause tumors in some dicotyledonous plants. Ever since the genome of A. tumefaciens strain C58 was sequenced, the quality of annotation of its protein-coding genes has been queried continually, because the annotation varies greatly among different databases. In this paper, the questionable hypothetical genes were re-predicted by integrating the TN curve and Z curve methods. As a result, 30 genes originally annotated as “hypothetical” were discriminated as being non-coding sequences. By testing the re-prediction program 10 times on data sets composed of the function-known genes, the mean accuracy of 99.99% and mean Matthews correlation coefficient value of 0.9999 were obtained. Further sequence analysis and COG analysis showed that the re-annotation results were very reliable. This work can provide an efficient tool and data resources for future studies of A. tumefaciens strain C58. Project supported by the National Natural Science Foundation of China (Grant Nos. 61302186 and 61271378) and the Funding from the State Key Laboratory of Bioelectronics of Southeast University.

Genome Sequence of a Chromium-Reducing Strain, Bacillus cereus S612

DOE PAGES

Wang, Dongping; Boukhalfa, Hakim; Ware, Doug S.; ...

2015-12-10

We report here the genome sequence of an effective chromium-reducing bacterium,Bacillus cereusstrain S612. We found that the size of the draft genome sequence is approximately 5.4 Mb, with a G+C content of 35%, and it is predicted to contain 5,450 protein-coding genes.

Draft Genome Sequence of Saccharomyces cerevisiae Barra Grande (BG-1), a Brazilian Industrial Bioethanol-Producing Strain

PubMed Central

Coutouné, Natalia; Mulato, Aline Tieppo Nogueira

2017-01-01

ABSTRACT Here, we present the draft genome sequence of Saccharomyces cerevisiae BG-1, a Brazilian industrial strain widely used for bioethanol production from sugarcane. The 11.7-Mb genome sequence consists of 216 scaffolds and harbors 5,607 predicted protein-coding genes. PMID:28360170

ContEst16S: an algorithm that identifies contaminated prokaryotic genomes using 16S RNA gene sequences.

PubMed

Lee, Imchang; Chalita, Mauricio; Ha, Sung-Min; Na, Seong-In; Yoon, Seok-Hwan; Chun, Jongsik

2017-06-01

Thanks to the recent advancement of DNA sequencing technology, the cost and time of prokaryotic genome sequencing have been dramatically decreased. It has repeatedly been reported that genome sequencing using high-throughput next-generation sequencing is prone to contaminations due to its high depth of sequencing coverage. Although a few bioinformatics tools are available to detect potential contaminations, these have inherited limitations as they only use protein-coding genes. Here we introduce a new algorithm, called ContEst16S, to detect potential contaminations using 16S rRNA genes from genome assemblies. We screened 69 745 prokaryotic genomes from the NCBI Assembly Database using ContEst16S and found that 594 were contaminated by bacteria, human and plants. Of the predicted contaminated genomes, 8 % were not predicted by the existing protein-coding gene-based tool, implying that both methods can be complementary in the detection of contaminations. A web-based service of the algorithm is available at www.ezbiocloud.net/tools/contest16s.

The standard operating procedure of the DOE-JGI Metagenome Annotation Pipeline (MAP v.4)

DOE PAGES

Huntemann, Marcel; Ivanova, Natalia N.; Mavromatis, Konstantinos; ...

2016-02-24

The DOE-JGI Metagenome Annotation Pipeline (MAP v.4) performs structural and functional annotation for metagenomic sequences that are submitted to the Integrated Microbial Genomes with Microbiomes (IMG/M) system for comparative analysis. The pipeline runs on nucleotide sequences provide d via the IMG submission site. Users must first define their analysis projects in GOLD and then submit the associated sequence datasets consisting of scaffolds/contigs with optional coverage information and/or unassembled reads in fasta and fastq file formats. The MAP processing consists of feature prediction including identification of protein-coding genes, non-coding RNAs and regulatory RNAs, as well as CRISPR elements. Structural annotation ismore » followed by functional annotation including assignment of protein product names and connection to various protein family databases.« less

The standard operating procedure of the DOE-JGI Metagenome Annotation Pipeline (MAP v.4)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huntemann, Marcel; Ivanova, Natalia N.; Mavromatis, Konstantinos

The DOE-JGI Metagenome Annotation Pipeline (MAP v.4) performs structural and functional annotation for metagenomic sequences that are submitted to the Integrated Microbial Genomes with Microbiomes (IMG/M) system for comparative analysis. The pipeline runs on nucleotide sequences provide d via the IMG submission site. Users must first define their analysis projects in GOLD and then submit the associated sequence datasets consisting of scaffolds/contigs with optional coverage information and/or unassembled reads in fasta and fastq file formats. The MAP processing consists of feature prediction including identification of protein-coding genes, non-coding RNAs and regulatory RNAs, as well as CRISPR elements. Structural annotation ismore » followed by functional annotation including assignment of protein product names and connection to various protein family databases.« less

Cloud prediction of protein structure and function with PredictProtein for Debian.

PubMed

Kaján, László; Yachdav, Guy; Vicedo, Esmeralda; Steinegger, Martin; Mirdita, Milot; Angermüller, Christof; Böhm, Ariane; Domke, Simon; Ertl, Julia; Mertes, Christian; Reisinger, Eva; Staniewski, Cedric; Rost, Burkhard

2013-01-01

We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also present two case studies that successfully utilize PredictProtein packages for high performance computing in the cloud: the first analyzes protein disorder for whole organisms, and the second analyzes the effect of all possible single sequence variants in protein coding regions of the human genome.

Cloud Prediction of Protein Structure and Function with PredictProtein for Debian

PubMed Central

Kaján, László; Yachdav, Guy; Vicedo, Esmeralda; Steinegger, Martin; Mirdita, Milot; Angermüller, Christof; Böhm, Ariane; Domke, Simon; Ertl, Julia; Mertes, Christian; Reisinger, Eva; Rost, Burkhard

2013-01-01

We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also present two case studies that successfully utilize PredictProtein packages for high performance computing in the cloud: the first analyzes protein disorder for whole organisms, and the second analyzes the effect of all possible single sequence variants in protein coding regions of the human genome. PMID:23971032

Cloning and sequence analysis of Hemonchus contortus HC58cDNA.

PubMed

Muleke, Charles I; Ruofeng, Yan; Lixin, Xu; Xinwen, Bo; Xiangrui, Li

2007-06-01

The complete coding sequence of Hemonchus contortus HC58cDNA was generated by rapid amplification of cDNA ends and polymerase chain reaction using primers based on the 5' and 3' ends of the parasite mRNA, accession no. AF305964. The HC58cDNA gene was 851 bp long, with open reading frame of 717 bp, precursors to 239 amino acids coding for approximately 27 kDa protein. Analysis of amino acid sequence revealed conserved residues of cysteine, histidine, asparagine, occluding loop pattern, hemoglobinase motif and glutamine of the oxyanion hole characteristic of cathepsin B like proteases (CBL). Comparison of the predicted amino acid sequences showed the protein shared 33.5-58.7% identity to cathepsin B homologues in the papain clan CA family (family C1). Phylogenetic analysis revealed close evolutionary proximity of the protein sequence to counterpart sequences in the CBL, suggesting that HC58cDNA was a member of the papain family.

An exploration of the sequence of a 2.9-Mb region of the genome of Drosophila melanogaster: the Adh region.

PubMed Central

Ashburner, M; Misra, S; Roote, J; Lewis, S E; Blazej, R; Davis, T; Doyle, C; Galle, R; George, R; Harris, N; Hartzell, G; Harvey, D; Hong, L; Houston, K; Hoskins, R; Johnson, G; Martin, C; Moshrefi, A; Palazzolo, M; Reese, M G; Spradling, A; Tsang, G; Wan, K; Whitelaw, K; Celniker, S

1999-01-01

A contiguous sequence of nearly 3 Mb from the genome of Drosophila melanogaster has been sequenced from a series of overlapping P1 and BAC clones. This region covers 69 chromosome polytene bands on chromosome arm 2L, including the genetically well-characterized "Adh region." A computational analysis of the sequence predicts 218 protein-coding genes, 11 tRNAs, and 17 transposable element sequences. At least 38 of the protein-coding genes are arranged in clusters of from 2 to 6 closely related genes, suggesting extensive tandem duplication. The gene density is one protein-coding gene every 13 kb; the transposable element density is one element every 171 kb. Of 73 genes in this region identified by genetic analysis, 49 have been located on the sequence; P-element insertions have been mapped to 43 genes. Ninety-five (44%) of the known and predicted genes match a Drosophila EST, and 144 (66%) have clear similarities to proteins in other organisms. Genes known to have mutant phenotypes are more likely to be represented in cDNA libraries, and far more likely to have products similar to proteins of other organisms, than are genes with no known mutant phenotype. Over 650 chromosome aberration breakpoints map to this chromosome region, and their nonrandom distribution on the genetic map reflects variation in gene spacing on the DNA. This is the first large-scale analysis of the genome of D. melanogaster at the sequence level. In addition to the direct results obtained, this analysis has allowed us to develop and test methods that will be needed to interpret the complete sequence of the genome of this species.Before beginning a Hunt, it is wise to ask someone what you are looking for before you begin looking for it. Milne 1926 PMID:10471707

Tetrahymena thermophila acidic ribosomal protein L37 contains an archaebacterial type of C-terminus.

PubMed

Hansen, T S; Andreasen, P H; Dreisig, H; Højrup, P; Nielsen, H; Engberg, J; Kristiansen, K

1991-09-15

We have cloned and characterized a Tetrahymena thermophila macronuclear gene (L37) encoding the acidic ribosomal protein (A-protein) L37. The gene contains a single intron located in the 3'-part of the coding region. Two major and three minor transcription start points (tsp) were mapped 39 to 63 nucleotides upstream from the translational start codon. The uppermost tsp mapped to the first T in a putative T. thermophila RNA polymerase II initiator element, TATAA. The coding region of L37 predicts a protein of 109 amino acid (aa) residues. A substantial part of the deduced aa sequence was verified by protein sequencing. The T. thermophila L37 clearly belongs to the P1-type family of eukaryotic A-proteins, but the C-terminal region has the hallmarks of archaebacterial A-proteins.

Rare and Coding Region Genetic Variants Associated With Risk of Ischemic Stroke: The NHLBI Exome Sequence Project.

PubMed

Auer, Paul L; Nalls, Mike; Meschia, James F; Worrall, Bradford B; Longstreth, W T; Seshadri, Sudha; Kooperberg, Charles; Burger, Kathleen M; Carlson, Christopher S; Carty, Cara L; Chen, Wei-Min; Cupples, L Adrienne; DeStefano, Anita L; Fornage, Myriam; Hardy, John; Hsu, Li; Jackson, Rebecca D; Jarvik, Gail P; Kim, Daniel S; Lakshminarayan, Kamakshi; Lange, Leslie A; Manichaikul, Ani; Quinlan, Aaron R; Singleton, Andrew B; Thornton, Timothy A; Nickerson, Deborah A; Peters, Ulrike; Rich, Stephen S

2015-07-01

Stroke is the second leading cause of death and the third leading cause of years of life lost. Genetic factors contribute to stroke prevalence, and candidate gene and genome-wide association studies (GWAS) have identified variants associated with ischemic stroke risk. These variants often have small effects without obvious biological significance. Exome sequencing may discover predicted protein-altering variants with a potentially large effect on ischemic stroke risk. To investigate the contribution of rare and common genetic variants to ischemic stroke risk by targeting the protein-coding regions of the human genome. The National Heart, Lung, and Blood Institute (NHLBI) Exome Sequencing Project (ESP) analyzed approximately 6000 participants from numerous cohorts of European and African ancestry. For discovery, 365 cases of ischemic stroke (small-vessel and large-vessel subtypes) and 809 European ancestry controls were sequenced; for replication, 47 affected sibpairs concordant for stroke subtype and an African American case-control series were sequenced, with 1672 cases and 4509 European ancestry controls genotyped. The ESP's exome sequencing and genotyping started on January 1, 2010, and continued through June 30, 2012. Analyses were conducted on the full data set between July 12, 2012, and July 13, 2013. Discovery of new variants or genes contributing to ischemic stroke risk and subtype (primary analysis) and determination of support for protein-coding variants contributing to risk in previously published candidate genes (secondary analysis). We identified 2 novel genes associated with an increased risk of ischemic stroke: a protein-coding variant in PDE4DIP (rs1778155; odds ratio, 2.15; P = 2.63 × 10(-8)) with an intracellular signal transduction mechanism and in ACOT4 (rs35724886; odds ratio, 2.04; P = 1.24 × 10(-7)) with a fatty acid metabolism; confirmation of PDE4DIP was observed in affected sibpair families with large-vessel stroke subtype and in African Americans. Replication of protein-coding variants in candidate genes was observed for 2 previously reported GWAS associations: ZFHX3 (cardioembolic stroke) and ABCA1 (large-vessel stroke). Exome sequencing discovered 2 novel genes and mechanisms, PDE4DIP and ACOT4, associated with increased risk for ischemic stroke. In addition, ZFHX3 and ABCA1 were discovered to have protein-coding variants associated with ischemic stroke. These results suggest that genetic variation in novel pathways contributes to ischemic stroke risk and serves as a target for prediction, prevention, and therapy.

The standard operating procedure of the DOE-JGI Microbial Genome Annotation Pipeline (MGAP v.4).

PubMed

Huntemann, Marcel; Ivanova, Natalia N; Mavromatis, Konstantinos; Tripp, H James; Paez-Espino, David; Palaniappan, Krishnaveni; Szeto, Ernest; Pillay, Manoj; Chen, I-Min A; Pati, Amrita; Nielsen, Torben; Markowitz, Victor M; Kyrpides, Nikos C

2015-01-01

The DOE-JGI Microbial Genome Annotation Pipeline performs structural and functional annotation of microbial genomes that are further included into the Integrated Microbial Genome comparative analysis system. MGAP is applied to assembled nucleotide sequence datasets that are provided via the IMG submission site. Dataset submission for annotation first requires project and associated metadata description in GOLD. The MGAP sequence data processing consists of feature prediction including identification of protein-coding genes, non-coding RNAs and regulatory RNA features, as well as CRISPR elements. Structural annotation is followed by assignment of protein product names and functions.

Identifying functionally informative evolutionary sequence profiles.

PubMed

Gil, Nelson; Fiser, Andras

2018-04-15

Multiple sequence alignments (MSAs) can provide essential input to many bioinformatics applications, including protein structure prediction and functional annotation. However, the optimal selection of sequences to obtain biologically informative MSAs for such purposes is poorly explored, and has traditionally been performed manually. We present Selection of Alignment by Maximal Mutual Information (SAMMI), an automated, sequence-based approach to objectively select an optimal MSA from a large set of alternatives sampled from a general sequence database search. The hypothesis of this approach is that the mutual information among MSA columns will be maximal for those MSAs that contain the most diverse set possible of the most structurally and functionally homogeneous protein sequences. SAMMI was tested to select MSAs for functional site residue prediction by analysis of conservation patterns on a set of 435 proteins obtained from protein-ligand (peptides, nucleic acids and small substrates) and protein-protein interaction databases. Availability and implementation: A freely accessible program, including source code, implementing SAMMI is available at https://github.com/nelsongil92/SAMMI.git. andras.fiser@einstein.yu.edu. Supplementary data are available at Bioinformatics online.

Variability and transmission by Aphis glycines of North American and Asian Soybean mosaic virus isolates.

PubMed

Domier, L L; Latorre, I J; Steinlage, T A; McCoppin, N; Hartman, G L

2003-10-01

The variability of North American and Asian strains and isolates of Soybean mosaic virus was investigated. First, polymerase chain reaction (PCR) products representing the coat protein (CP)-coding regions of 38 SMVs were analyzed for restriction fragment length polymorphisms (RFLP). Second, the nucleotide and predicted amino acid sequence variability of the P1-coding region of 18 SMVs and the helper component/protease (HC/Pro) and CP-coding regions of 25 SMVs were assessed. The CP nucleotide and predicted amino acid sequences were the most similar and predicted phylogenetic relationships similar to those obtained from RFLP analysis. Neither RFLP nor sequence analyses of the CP-coding regions grouped the SMVs by geographical origin. The P1 and HC/Pro sequences were more variable and separated the North American and Asian SMV isolates into two groups similar to previously reported differences in pathogenic diversity of the two sets of SMV isolates. The P1 region was the most informative of the three regions analyzed. To assess the biological relevance of the sequence differences in the HC/Pro and CP coding regions, the transmissibility of 14 SMV isolates by Aphis glycines was tested. All field isolates of SMV were transmitted efficiently by A. glycines, but the laboratory isolates analyzed were transmitted poorly. The amino acid sequences from most, but not all, of the poorly transmitted isolates contained mutations in the aphid transmission-associated DAG and/or KLSC amino acid sequence motifs of CP and HC/Pro, respectively.

Cloning and expression of a cDNA coding for a human monocyte-derived plasminogen activator inhibitor.

PubMed

Antalis, T M; Clark, M A; Barnes, T; Lehrbach, P R; Devine, P L; Schevzov, G; Goss, N H; Stephens, R W; Tolstoshev, P

1988-02-01

Human monocyte-derived plasminogen activator inhibitor (mPAI-2) was purified to homogeneity from the U937 cell line and partially sequenced. Oligonucleotide probes derived from this sequence were used to screen a cDNA library prepared from U937 cells. One positive clone was sequenced and contained most of the coding sequence as well as a long incomplete 3' untranslated region (1112 base pairs). This cDNA sequence was shown to encode mPAI-2 by hybrid-select translation. A cDNA clone encoding the remainder of the mPAI-2 mRNA was obtained by primer extension of U937 poly(A)+ RNA using a probe complementary to the mPAI-2 coding region. The coding sequence for mPAI-2 was placed under the control of the lambda PL promoter, and the protein expressed in Escherichia coli formed a complex with urokinase that could be detected immunologically. By nucleotide sequence analysis, mPAI-2 cDNA encodes a protein containing 415 amino acids with a predicted unglycosylated Mr of 46,543. The predicted amino acid sequence of mPAI-2 is very similar to placental PAI-2 (3 amino acid differences) and shows extensive homology with members of the serine protease inhibitor (serpin) superfamily. mPAI-2 was found to be more homologous to ovalbumin (37%) than the endothelial plasminogen activator inhibitor, PAI-1 (26%). Like ovalbumin, mPAI-2 appears to have no typical amino-terminal signal sequence. The 3' untranslated region of the mPAI-2 cDNA contains a putative regulatory sequence that has been associated with the inflammatory mediators.

Cloning and expression of a cDNA coding for a human monocyte-derived plasminogen activator inhibitor.

PubMed Central

Antalis, T M; Clark, M A; Barnes, T; Lehrbach, P R; Devine, P L; Schevzov, G; Goss, N H; Stephens, R W; Tolstoshev, P

1988-01-01

Human monocyte-derived plasminogen activator inhibitor (mPAI-2) was purified to homogeneity from the U937 cell line and partially sequenced. Oligonucleotide probes derived from this sequence were used to screen a cDNA library prepared from U937 cells. One positive clone was sequenced and contained most of the coding sequence as well as a long incomplete 3' untranslated region (1112 base pairs). This cDNA sequence was shown to encode mPAI-2 by hybrid-select translation. A cDNA clone encoding the remainder of the mPAI-2 mRNA was obtained by primer extension of U937 poly(A)+ RNA using a probe complementary to the mPAI-2 coding region. The coding sequence for mPAI-2 was placed under the control of the lambda PL promoter, and the protein expressed in Escherichia coli formed a complex with urokinase that could be detected immunologically. By nucleotide sequence analysis, mPAI-2 cDNA encodes a protein containing 415 amino acids with a predicted unglycosylated Mr of 46,543. The predicted amino acid sequence of mPAI-2 is very similar to placental PAI-2 (3 amino acid differences) and shows extensive homology with members of the serine protease inhibitor (serpin) superfamily. mPAI-2 was found to be more homologous to ovalbumin (37%) than the endothelial plasminogen activator inhibitor, PAI-1 (26%). Like ovalbumin, mPAI-2 appears to have no typical amino-terminal signal sequence. The 3' untranslated region of the mPAI-2 cDNA contains a putative regulatory sequence that has been associated with the inflammatory mediators. Images PMID:3257578

Principles of protein folding--a perspective from simple exact models.

PubMed Central

Dill, K. A.; Bromberg, S.; Yue, K.; Fiebig, K. M.; Yee, D. P.; Thomas, P. D.; Chan, H. S.

1995-01-01

General principles of protein structure, stability, and folding kinetics have recently been explored in computer simulations of simple exact lattice models. These models represent protein chains at a rudimentary level, but they involve few parameters, approximations, or implicit biases, and they allow complete explorations of conformational and sequence spaces. Such simulations have resulted in testable predictions that are sometimes unanticipated: The folding code is mainly binary and delocalized throughout the amino acid sequence. The secondary and tertiary structures of a protein are specified mainly by the sequence of polar and nonpolar monomers. More specific interactions may refine the structure, rather than dominate the folding code. Simple exact models can account for the properties that characterize protein folding: two-state cooperativity, secondary and tertiary structures, and multistage folding kinetics--fast hydrophobic collapse followed by slower annealing. These studies suggest the possibility of creating "foldable" chain molecules other than proteins. The encoding of a unique compact chain conformation may not require amino acids; it may require only the ability to synthesize specific monomer sequences in which at least one monomer type is solvent-averse. PMID:7613459

CodingQuarry: highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts.

PubMed

Testa, Alison C; Hane, James K; Ellwood, Simon R; Oliver, Richard P

2015-03-11

The impact of gene annotation quality on functional and comparative genomics makes gene prediction an important process, particularly in non-model species, including many fungi. Sets of homologous protein sequences are rarely complete with respect to the fungal species of interest and are often small or unreliable, especially when closely related species have not been sequenced or annotated in detail. In these cases, protein homology-based evidence fails to correctly annotate many genes, or significantly improve ab initio predictions. Generalised hidden Markov models (GHMM) have proven to be invaluable tools in gene annotation and, recently, RNA-seq has emerged as a cost-effective means to significantly improve the quality of automated gene annotation. As these methods do not require sets of homologous proteins, improving gene prediction from these resources is of benefit to fungal researchers. While many pipelines now incorporate RNA-seq data in training GHMMs, there has been relatively little investigation into additionally combining RNA-seq data at the point of prediction, and room for improvement in this area motivates this study. CodingQuarry is a highly accurate, self-training GHMM fungal gene predictor designed to work with assembled, aligned RNA-seq transcripts. RNA-seq data informs annotations both during gene-model training and in prediction. Our approach capitalises on the high quality of fungal transcript assemblies by incorporating predictions made directly from transcript sequences. Correct predictions are made despite transcript assembly problems, including those caused by overlap between the transcripts of adjacent gene loci. Stringent benchmarking against high-confidence annotation subsets showed CodingQuarry predicted 91.3% of Schizosaccharomyces pombe genes and 90.4% of Saccharomyces cerevisiae genes perfectly. These results are 4-5% better than those of AUGUSTUS, the next best performing RNA-seq driven gene predictor tested. Comparisons against whole genome Sc. pombe and S. cerevisiae annotations further substantiate a 4-5% improvement in the number of correctly predicted genes. We demonstrate the success of a novel method of incorporating RNA-seq data into GHMM fungal gene prediction. This shows that a high quality annotation can be achieved without relying on protein homology or a training set of genes. CodingQuarry is freely available ( https://sourceforge.net/projects/codingquarry/ ), and suitable for incorporation into genome annotation pipelines.

DeepLoc: prediction of protein subcellular localization using deep learning.

PubMed

Almagro Armenteros, José Juan; Sønderby, Casper Kaae; Sønderby, Søren Kaae; Nielsen, Henrik; Winther, Ole

2017-11-01

The prediction of eukaryotic protein subcellular localization is a well-studied topic in bioinformatics due to its relevance in proteomics research. Many machine learning methods have been successfully applied in this task, but in most of them, predictions rely on annotation of homologues from knowledge databases. For novel proteins where no annotated homologues exist, and for predicting the effects of sequence variants, it is desirable to have methods for predicting protein properties from sequence information only. Here, we present a prediction algorithm using deep neural networks to predict protein subcellular localization relying only on sequence information. At its core, the prediction model uses a recurrent neural network that processes the entire protein sequence and an attention mechanism identifying protein regions important for the subcellular localization. The model was trained and tested on a protein dataset extracted from one of the latest UniProt releases, in which experimentally annotated proteins follow more stringent criteria than previously. We demonstrate that our model achieves a good accuracy (78% for 10 categories; 92% for membrane-bound or soluble), outperforming current state-of-the-art algorithms, including those relying on homology information. The method is available as a web server at http://www.cbs.dtu.dk/services/DeepLoc. Example code is available at https://github.com/JJAlmagro/subcellular_localization. The dataset is available at http://www.cbs.dtu.dk/services/DeepLoc/data.php. jjalma@dtu.dk. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Identification of Methanococcus Jannaschii Proteins in 2-D Gel Electrophoresis Patterns by Mass Spectrometry

DOE R&D Accomplishments Database

Liang, X.

1998-06-10

The genome of Methanococcus jannaschii has been sequenced completely and has been found to contain approximately 1,770 predicted protein-coding regions. When these coding regions are expressed and how their expression is regulated, however, remain open questions. In this work, mass spectrometry was combined with two-dimensional gel electrophoresis to identify which proteins the genes produce under different growth conditions, and thus investigate the regulation of genes responsible for functions characteristic of this thermophilic representative of the methanogenic Archaea.

Sequencing proteins with transverse ionic transport in nanochannels.

PubMed

Boynton, Paul; Di Ventra, Massimiliano

2016-05-03

De novo protein sequencing is essential for understanding cellular processes that govern the function of living organisms and all sequence modifications that occur after a protein has been constructed from its corresponding DNA code. By obtaining the order of the amino acids that compose a given protein one can then determine both its secondary and tertiary structures through structure prediction, which is used to create models for protein aggregation diseases such as Alzheimer's Disease. Here, we propose a new technique for de novo protein sequencing that involves translocating a polypeptide through a synthetic nanochannel and measuring the ionic current of each amino acid through an intersecting perpendicular nanochannel. We find that the distribution of ionic currents for each of the 20 proteinogenic amino acids encoded by eukaryotic genes is statistically distinct, showing this technique's potential for de novo protein sequencing.

Mutations that Cause Human Disease: A Computational/Experimental Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beernink, P; Barsky, D; Pesavento, B

International genome sequencing projects have produced billions of nucleotides (letters) of DNA sequence data, including the complete genome sequences of 74 organisms. These genome sequences have created many new scientific opportunities, including the ability to identify sequence variations among individuals within a species. These genetic differences, which are known as single nucleotide polymorphisms (SNPs), are particularly important in understanding the genetic basis for disease susceptibility. Since the report of the complete human genome sequence, over two million human SNPs have been identified, including a large-scale comparison of an entire chromosome from twenty individuals. Of the protein coding SNPs (cSNPs), approximatelymore » half leads to a single amino acid change in the encoded protein (non-synonymous coding SNPs). Most of these changes are functionally silent, while the remainder negatively impact the protein and sometimes cause human disease. To date, over 550 SNPs have been found to cause single locus (monogenic) diseases and many others have been associated with polygenic diseases. SNPs have been linked to specific human diseases, including late-onset Parkinson disease, autism, rheumatoid arthritis and cancer. The ability to predict accurately the effects of these SNPs on protein function would represent a major advance toward understanding these diseases. To date several attempts have been made toward predicting the effects of such mutations. The most successful of these is a computational approach called ''Sorting Intolerant From Tolerant'' (SIFT). This method uses sequence conservation among many similar proteins to predict which residues in a protein are functionally important. However, this method suffers from several limitations. First, a query sequence must have a sufficient number of relatives to infer sequence conservation. Second, this method does not make use of or provide any information on protein structure, which can be used to understand how an amino acid change affects the protein. The experimental methods that provide the most detailed structural information on proteins are X-ray crystallography and NMR spectroscopy. However, these methods are labor intensive and currently cannot be carried out on a genomic scale. Nonetheless, Structural Genomics projects are being pursued by more than a dozen groups and consortia worldwide and as a result the number of experimentally determined structures is rising exponentially. Based on the expectation that protein structures will continue to be determined at an ever-increasing rate, reliable structure prediction schemes will become increasingly valuable, leading to information on protein function and disease for many different proteins. Given known genetic variability and experimentally determined protein structures, can we accurately predict the effects of single amino acid substitutions? An objective assessment of this question would involve comparing predicted and experimentally determined structures, which thus far has not been rigorously performed. The completed research leveraged existing expertise at LLNL in computational and structural biology, as well as significant computing resources, to address this question.« less

Avoidance of truncated proteins from unintended ribosome binding sites within heterologous protein coding sequences.

PubMed

Whitaker, Weston R; Lee, Hanson; Arkin, Adam P; Dueber, John E

2015-03-20

Genetic sequences ported into non-native hosts for synthetic biology applications can gain unexpected properties. In this study, we explored sequences functioning as ribosome binding sites (RBSs) within protein coding DNA sequences (CDSs) that cause internal translation, resulting in truncated proteins. Genome-wide prediction of bacterial RBSs, based on biophysical calculations employed by the RBS calculator, suggests a selection against internal RBSs within CDSs in Escherichia coli, but not those in Saccharomyces cerevisiae. Based on these calculations, silent mutations aimed at removing internal RBSs can effectively reduce truncation products from internal translation. However, a solution for complete elimination of internal translation initiation is not always feasible due to constraints of available coding sequences. Fluorescence assays and Western blot analysis showed that in genes with internal RBSs, increasing the strength of the intended upstream RBS had little influence on the internal translation strength. Another strategy to minimize truncated products from an internal RBS is to increase the relative strength of the upstream RBS with a concomitant reduction in promoter strength to achieve the same protein expression level. Unfortunately, lower transcription levels result in increased noise at the single cell level due to stochasticity in gene expression. At the low expression regimes desired for many synthetic biology applications, this problem becomes particularly pronounced. We found that balancing promoter strengths and upstream RBS strengths to intermediate levels can achieve the target protein concentration while avoiding both excessive noise and truncated protein.

A versatile palindromic amphipathic repeat coding sequence horizontally distributed among diverse bacterial and eucaryotic microbes

PubMed Central

2010-01-01

Background Intragenic tandem repeats occur throughout all domains of life and impart functional and structural variability to diverse translation products. Repeat proteins confer distinctive surface phenotypes to many unicellular organisms, including those with minimal genomes such as the wall-less bacterial monoderms, Mollicutes. One such repeat pattern in this clade is distributed in a manner suggesting its exchange by horizontal gene transfer (HGT). Expanding genome sequence databases reveal the pattern in a widening range of bacteria, and recently among eucaryotic microbes. We examined the genomic flux and consequences of the motif by determining its distribution, predicted structural features and association with membrane-targeted proteins. Results Using a refined hidden Markov model, we document a 25-residue protein sequence motif tandemly arrayed in variable-number repeats in ORFs lacking assigned functions. It appears sporadically in unicellular microbes from disparate bacterial and eucaryotic clades, representing diverse lifestyles and ecological niches that include host parasitic, marine and extreme environments. Tracts of the repeats predict a malleable configuration of recurring domains, with conserved hydrophobic residues forming an amphipathic secondary structure in which hydrophilic residues endow extensive sequence variation. Many ORFs with these domains also have membrane-targeting sequences that predict assorted topologies; others may comprise reservoirs of sequence variants. We demonstrate expressed variants among surface lipoproteins that distinguish closely related animal pathogens belonging to a subgroup of the Mollicutes. DNA sequences encoding the tandem domains display dyad symmetry. Moreover, in some taxa the domains occur in ORFs selectively associated with mobile elements. These features, a punctate phylogenetic distribution, and different patterns of dispersal in genomes of related taxa, suggest that the repeat may be disseminated by HGT and intra-genomic shuffling. Conclusions We describe novel features of PARCELs (Palindromic Amphipathic Repeat Coding ELements), a set of widely distributed repeat protein domains and coding sequences that were likely acquired through HGT by diverse unicellular microbes, further mobilized and diversified within genomes, and co-opted for expression in the membrane proteome of some taxa. Disseminated by multiple gene-centric vehicles, ORFs harboring these elements enhance accessory gene pools as part of the "mobilome" connecting genomes of various clades, in taxa sharing common niches. PMID:20626840

Draft Genome Sequence of Lactobacillus panis DSM 6035T, First Isolated from Sourdough

PubMed Central

Zhu, Yixin; Fang, Daiqiong; Shi, Ding; Li, Ang; Lv, Longxian; Yan, Ren; Yao, Jian; Hua, Dasong; Hu, Xinjun; Guo, Feifei; Wu, Wenrui; Guo, Jing; Chen, Yanfei; Jiang, Xiawei; Chen, Xiaoxiao

2015-01-01

We report a draft genome sequence of Lactobacillus panis DSM 6035T, isolated from sourdough. The genome of this strain is 2,082,789 bp long, with 47.9% G+C content. A total of 2,047 protein-coding genes were predicted. PMID:26205855

Efficient analysis of mouse genome sequences reveal many nonsense variants

PubMed Central

Steeland, Sophie; Timmermans, Steven; Van Ryckeghem, Sara; Hulpiau, Paco; Saeys, Yvan; Van Montagu, Marc; Vandenbroucke, Roosmarijn E.; Libert, Claude

2016-01-01

Genetic polymorphisms in coding genes play an important role when using mouse inbred strains as research models. They have been shown to influence research results, explain phenotypical differences between inbred strains, and increase the amount of interesting gene variants present in the many available inbred lines. SPRET/Ei is an inbred strain derived from Mus spretus that has ∼1% sequence difference with the C57BL/6J reference genome. We obtained a listing of all SNPs and insertions/deletions (indels) present in SPRET/Ei from the Mouse Genomes Project (Wellcome Trust Sanger Institute) and processed these data to obtain an overview of all transcripts having nonsynonymous coding sequence variants. We identified 8,883 unique variants affecting 10,096 different transcripts from 6,328 protein-coding genes, which is about 28% of all coding genes. Because only a subset of these variants results in drastic changes in proteins, we focused on variations that are nonsense mutations that ultimately resulted in a gain of a stop codon. These genes were identified by in silico changing the C57BL/6J coding sequences to the SPRET/Ei sequences, converting them to amino acid (AA) sequences, and comparing the AA sequences. All variants and transcripts affected were also stored in a database, which can be browsed using a SPRET/Ei M. spretus variants web tool (www.spretus.org), including a manual. We validated the tool by demonstrating the loss of function of three proteins predicted to be severely truncated, namely Fas, IRAK2, and IFNγR1. PMID:27147605

Distribution of cold adaptation proteins in microbial mats in Lake Joyce, Antarctica: Analysis of metagenomic data by using two bioinformatics tools.

PubMed

Koo, Hyunmin; Hakim, Joseph A; Fisher, Phillip R E; Grueneberg, Alexander; Andersen, Dale T; Bej, Asim K

2016-01-01

In this study, we report the distribution and abundance of cold-adaptation proteins in microbial mat communities in the perennially ice-covered Lake Joyce, located in the McMurdo Dry Valleys, Antarctica. We have used MG-RAST and R code bioinformatics tools on Illumina HiSeq2000 shotgun metagenomic data and compared the filtering efficacy of these two methods on cold-adaptation proteins. Overall, the abundance of cold-shock DEAD-box protein A (CSDA), antifreeze proteins (AFPs), fatty acid desaturase (FAD), trehalose synthase (TS), and cold-shock family of proteins (CSPs) were present in all mat samples at high, moderate, or low levels, whereas the ice nucleation protein (INP) was present only in the ice and bulbous mat samples at insignificant levels. Considering the near homogeneous temperature profile of Lake Joyce (0.08-0.29 °C), the distribution and abundance of these proteins across various mat samples predictively correlated with known functional attributes necessary for microbial communities to thrive in this ecosystem. The comparison of the MG-RAST and the R code methods showed dissimilar occurrences of the cold-adaptation protein sequences, though with insignificant ANOSIM (R = 0.357; p-value = 0.012), ADONIS (R(2) = 0.274; p-value = 0.03) and STAMP (p-values = 0.521-0.984) statistical analyses. Furthermore, filtering targeted sequences using the R code accounted for taxonomic groups by avoiding sequence redundancies, whereas the MG-RAST provided total counts resulting in a higher sequence output. The results from this study revealed for the first time the distribution of cold-adaptation proteins in six different types of microbial mats in Lake Joyce, while suggesting a simpler and more manageable user-defined method of R code, as compared to a web-based MG-RAST pipeline.

SVM-Fold: a tool for discriminative multi-class protein fold and superfamily recognition

PubMed Central

Melvin, Iain; Ie, Eugene; Kuang, Rui; Weston, Jason; Stafford, William Noble; Leslie, Christina

2007-01-01

Background Predicting a protein's structural class from its amino acid sequence is a fundamental problem in computational biology. Much recent work has focused on developing new representations for protein sequences, called string kernels, for use with support vector machine (SVM) classifiers. However, while some of these approaches exhibit state-of-the-art performance at the binary protein classification problem, i.e. discriminating between a particular protein class and all other classes, few of these studies have addressed the real problem of multi-class superfamily or fold recognition. Moreover, there are only limited software tools and systems for SVM-based protein classification available to the bioinformatics community. Results We present a new multi-class SVM-based protein fold and superfamily recognition system and web server called SVM-Fold, which can be found at . Our system uses an efficient implementation of a state-of-the-art string kernel for sequence profiles, called the profile kernel, where the underlying feature representation is a histogram of inexact matching k-mer frequencies. We also employ a novel machine learning approach to solve the difficult multi-class problem of classifying a sequence of amino acids into one of many known protein structural classes. Binary one-vs-the-rest SVM classifiers that are trained to recognize individual structural classes yield prediction scores that are not comparable, so that standard "one-vs-all" classification fails to perform well. Moreover, SVMs for classes at different levels of the protein structural hierarchy may make useful predictions, but one-vs-all does not try to combine these multiple predictions. To deal with these problems, our method learns relative weights between one-vs-the-rest classifiers and encodes information about the protein structural hierarchy for multi-class prediction. In large-scale benchmark results based on the SCOP database, our code weighting approach significantly improves on the standard one-vs-all method for both the superfamily and fold prediction in the remote homology setting and on the fold recognition problem. Moreover, our code weight learning algorithm strongly outperforms nearest-neighbor methods based on PSI-BLAST in terms of prediction accuracy on every structure classification problem we consider. Conclusion By combining state-of-the-art SVM kernel methods with a novel multi-class algorithm, the SVM-Fold system delivers efficient and accurate protein fold and superfamily recognition. PMID:17570145

FrameD: A flexible program for quality check and gene prediction in prokaryotic genomes and noisy matured eukaryotic sequences.

PubMed

Schiex, Thomas; Gouzy, Jérôme; Moisan, Annick; de Oliveira, Yannick

2003-07-01

We describe FrameD, a program that predicts coding regions in prokaryotic and matured eukaryotic sequences. Initially targeted at gene prediction in bacterial GC rich genomes, the gene model used in FrameD also allows to predict genes in the presence of frameshifts and partially undetermined sequences which makes it also very suitable for gene prediction and frameshift correction in unfinished sequences such as EST and EST cluster sequences. Like recent eukaryotic gene prediction programs, FrameD also includes the ability to take into account protein similarity information both in its prediction and its graphical output. Its performances are evaluated on different bacterial genomes. The web site (http://genopole.toulouse.inra.fr/bioinfo/FrameD/FD) allows direct prediction, sequence correction and translation and the ability to learn new models for new organisms.

Characterization of the Lymantria dispar nucleopolyhedrovirus 25K FP gene

Treesearch

David S. Bischoff; James M. Slavicek

1996-01-01

The Lymantria dispar nucleopolyhedrovirus (LdMNPV) gene encoding the 25K FP protein has been cloned and sequenced. The 25KFP gene codes for a 217 amino acid protein with a predicted molecular mass of 24870 Da. Expression of the 25K FP protein in a rabbit reticulocyte system generated a 27 kDa protein, in close agreement with the...

The LINE-1 DNA sequences in four mammalian orders predict proteins that conserve homologies to retrovirus proteins.

PubMed Central

Fanning, T; Singer, M

1987-01-01

Recent work suggests that one or more members of the highly repeated LINE-1 (L1) DNA family found in all mammals may encode one or more proteins. Here we report the sequence of a portion of an L1 cloned from the domestic cat (Felis catus). These data permit comparison of the L1 sequences in four mammalian orders (Carnivore, Lagomorph, Rodent and Primate) and the comparison supports the suggested coding potential. In two separate, noncontiguous regions in the carboxy terminal half of the proteins predicted from the DNA sequences, there are several strongly conserved segments. In one region, these share homology with known or suspected reverse transcriptases, as described by others in rodents and primates. In the second region, closer to the carboxy terminus, the strongly conserved segments are over 90% homologous among the four orders. One of the latter segments is cysteine rich and resembles the putative metal binding domains of nucleic acid binding proteins, including those of TFIIIA and retroviruses. PMID:3562227

The standard operating procedure of the DOE-JGI Microbial Genome Annotation Pipeline (MGAP v.4)

DOE PAGES

Huntemann, Marcel; Ivanova, Natalia N.; Mavromatis, Konstantinos; ...

2015-10-26

The DOE-JGI Microbial Genome Annotation Pipeline performs structural and functional annotation of microbial genomes that are further included into the Integrated Microbial Genome comparative analysis system. MGAP is applied to assembled nucleotide sequence datasets that are provided via the IMG submission site. Dataset submission for annotation first requires project and associated metadata description in GOLD. The MGAP sequence data processing consists of feature prediction including identification of protein-coding genes, non-coding RNAs and regulatory RNA features, as well as CRISPR elements. In conclusion, structural annotation is followed by assignment of protein product names and functions.

The standard operating procedure of the DOE-JGI Microbial Genome Annotation Pipeline (MGAP v.4)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huntemann, Marcel; Ivanova, Natalia N.; Mavromatis, Konstantinos

The DOE-JGI Microbial Genome Annotation Pipeline performs structural and functional annotation of microbial genomes that are further included into the Integrated Microbial Genome comparative analysis system. MGAP is applied to assembled nucleotide sequence datasets that are provided via the IMG submission site. Dataset submission for annotation first requires project and associated metadata description in GOLD. The MGAP sequence data processing consists of feature prediction including identification of protein-coding genes, non-coding RNAs and regulatory RNA features, as well as CRISPR elements. In conclusion, structural annotation is followed by assignment of protein product names and functions.

Permanent Improved High-Quality Draft Genome Sequence of Nocardia casuarinae Strain BMG51109, an Endophyte of Actinorhizal Root Nodules of Casuarina glauca

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghodhbane-Gtari, Faten; Beauchemin, Nicholas; Louati, Moussa

Here, we report the first genome sequence of a Nocardia plant endophyte, N. casuarinae strain BMG51109, isolated from Casuarina glauca root nodules. The improved high-quality draft genome sequence contains 8,787,999 bp with a 68.90% GC content and 7,307 predicted protein-coding genes.

Permanent Improved High-Quality Draft Genome Sequence of Nocardia casuarinae Strain BMG51109, an Endophyte of Actinorhizal Root Nodules of Casuarina glauca

DOE PAGES

Ghodhbane-Gtari, Faten; Beauchemin, Nicholas; Louati, Moussa; ...

2016-08-04

Here, we report the first genome sequence of a Nocardia plant endophyte, N. casuarinae strain BMG51109, isolated from Casuarina glauca root nodules. The improved high-quality draft genome sequence contains 8,787,999 bp with a 68.90% GC content and 7,307 predicted protein-coding genes.

De novo assembly and characterization of the Trichuris trichiura adult worm transcriptome using Ion Torrent sequencing.

PubMed

Santos, Leonardo N; Silva, Eduardo S; Santos, André S; De Sá, Pablo H; Ramos, Rommel T; Silva, Artur; Cooper, Philip J; Barreto, Maurício L; Loureiro, Sebastião; Pinheiro, Carina S; Alcantara-Neves, Neuza M; Pacheco, Luis G C

2016-07-01

Infection with helminthic parasites, including the soil-transmitted helminth Trichuris trichiura (human whipworm), has been shown to modulate host immune responses and, consequently, to have an impact on the development and manifestation of chronic human inflammatory diseases. De novo derivation of helminth proteomes from sequencing of transcriptomes will provide valuable data to aid identification of parasite proteins that could be evaluated as potential immunotherapeutic molecules in near future. Herein, we characterized the transcriptome of the adult stage of the human whipworm T. trichiura, using next-generation sequencing technology and a de novo assembly strategy. Nearly 17.6 million high-quality clean reads were assembled into 6414 contiguous sequences, with an N50 of 1606bp. In total, 5673 protein-encoding sequences were confidentially identified in the T. trichiura adult worm transcriptome; of these, 1013 sequences represent potential newly discovered proteins for the species, most of which presenting orthologs already annotated in the related species T. suis. A number of transcripts representing probable novel non-coding transcripts for the species T. trichiura were also identified. Among the most abundant transcripts, we found sequences that code for proteins involved in lipid transport, such as vitellogenins, and several chitin-binding proteins. Through a cross-species expression analysis of gene orthologs shared by T. trichiura and the closely related parasites T. suis and T. muris it was possible to find twenty-six protein-encoding genes that are consistently highly expressed in the adult stages of the three helminth species. Additionally, twenty transcripts could be identified that code for proteins previously detected by mass spectrometry analysis of protein fractions of the whipworm somatic extract that present immunomodulatory activities. Five of these transcripts were amongst the most highly expressed protein-encoding sequences in the T. trichiura adult worm. Besides, orthologs of proteins demonstrated to have potent immunomodulatory properties in related parasitic helminths were also predicted from the T. trichiura de novo assembled transcriptome. Copyright © 2016. Published by Elsevier B.V.

Molecular modelling of the Norrie disease protein predicts a cystine knot growth factor tertiary structure.

PubMed

Meitinger, T; Meindl, A; Bork, P; Rost, B; Sander, C; Haasemann, M; Murken, J

1993-12-01

The X-lined gene for Norrie disease, which is characterized by blindness, deafness and mental retardation has been cloned recently. This gene has been thought to code for a putative extracellular factor; its predicted amino acid sequence is homologous to the C-terminal domain of diverse extracellular proteins. Sequence pattern searches and three-dimensional modelling now suggest that the Norrie disease protein (NDP) has a tertiary structure similar to that of transforming growth factor beta (TGF beta). Our model identifies NDP as a member of an emerging family of growth factors containing a cystine knot motif, with direct implications for the physiological role of NDP. The model also sheds light on sequence related domains such as the C-terminal domain of mucins and of von Willebrand factor.

Predicting the tolerated sequences for proteins and protein interfaces using RosettaBackrub flexible backbone design.

PubMed

Smith, Colin A; Kortemme, Tanja

2011-01-01

Predicting the set of sequences that are tolerated by a protein or protein interface, while maintaining a desired function, is useful for characterizing protein interaction specificity and for computationally designing sequence libraries to engineer proteins with new functions. Here we provide a general method, a detailed set of protocols, and several benchmarks and analyses for estimating tolerated sequences using flexible backbone protein design implemented in the Rosetta molecular modeling software suite. The input to the method is at least one experimentally determined three-dimensional protein structure or high-quality model. The starting structure(s) are expanded or refined into a conformational ensemble using Monte Carlo simulations consisting of backrub backbone and side chain moves in Rosetta. The method then uses a combination of simulated annealing and genetic algorithm optimization methods to enrich for low-energy sequences for the individual members of the ensemble. To emphasize certain functional requirements (e.g. forming a binding interface), interactions between and within parts of the structure (e.g. domains) can be reweighted in the scoring function. Results from each backbone structure are merged together to create a single estimate for the tolerated sequence space. We provide an extensive description of the protocol and its parameters, all source code, example analysis scripts and three tests applying this method to finding sequences predicted to stabilize proteins or protein interfaces. The generality of this method makes many other applications possible, for example stabilizing interactions with small molecules, DNA, or RNA. Through the use of within-domain reweighting and/or multistate design, it may also be possible to use this method to find sequences that stabilize particular protein conformations or binding interactions over others.

The Caenorhabditis elegans gene unc-89, required fpr muscle M-line assembly, encodes a giant modular protein composed of Ig and signal transduction domains

PubMed Central

1996-01-01

Mutations in the Caenorhabditis elegans gene unc-89 result in nematodes having disorganized muscle structure in which thick filaments are not organized into A-bands, and there are no M-lines. Beginning with a partial cDNA from the C. elegans sequencing project, we have cloned and sequenced the unc-89 gene. An unc-89 allele, st515, was found to contain an 84-bp deletion and a 10-bp duplication, resulting in an in- frame stop codon within predicted unc-89 coding sequence. Analysis of the complete coding sequence for unc-89 predicts a novel 6,632 amino acid polypeptide consisting of sequence motifs which have been implicated in protein-protein interactions. UNC-89 begins with 67 residues of unique sequences, SH3, dbl/CDC24, and PH domains, 7 immunoglobulins (Ig) domains, a putative KSP-containing multiphosphorylation domain, and ends with 46 Ig domains. A polyclonal antiserum raised to a portion of unc-89 encoded sequence reacts to a twitchin-sized polypeptide from wild type, but truncated polypeptides from st515 and from the amber allele e2338. By immunofluorescent microscopy, this antiserum localizes to the middle of A-bands, consistent with UNC-89 being a structural component of the M-line. Previous studies indicate that myofilament lattice assembly begins with positional cues laid down in the basement membrane and muscle cell membrane. We propose that the intracellular protein UNC-89 responds to these signals, localizes, and then participates in assembling an M-line. PMID:8603916

Characterization and prediction of residues determining protein functional specificity.

PubMed

Capra, John A; Singh, Mona

2008-07-01

Within a homologous protein family, proteins may be grouped into subtypes that share specific functions that are not common to the entire family. Often, the amino acids present in a small number of sequence positions determine each protein's particular functional specificity. Knowledge of these specificity determining positions (SDPs) aids in protein function prediction, drug design and experimental analysis. A number of sequence-based computational methods have been introduced for identifying SDPs; however, their further development and evaluation have been hindered by the limited number of known experimentally determined SDPs. We combine several bioinformatics resources to automate a process, typically undertaken manually, to build a dataset of SDPs. The resulting large dataset, which consists of SDPs in enzymes, enables us to characterize SDPs in terms of their physicochemical and evolutionary properties. It also facilitates the large-scale evaluation of sequence-based SDP prediction methods. We present a simple sequence-based SDP prediction method, GroupSim, and show that, surprisingly, it is competitive with a representative set of current methods. We also describe ConsWin, a heuristic that considers sequence conservation of neighboring amino acids, and demonstrate that it improves the performance of all methods tested on our large dataset of enzyme SDPs. Datasets and GroupSim code are available online at http://compbio.cs.princeton.edu/specificity/. Supplementary data are available at Bioinformatics online.

osFP: a web server for predicting the oligomeric states of fluorescent proteins.

PubMed

Simeon, Saw; Shoombuatong, Watshara; Anuwongcharoen, Nuttapat; Preeyanon, Likit; Prachayasittikul, Virapong; Wikberg, Jarl E S; Nantasenamat, Chanin

2016-01-01

Currently, monomeric fluorescent proteins (FP) are ideal markers for protein tagging. The prediction of oligomeric states is helpful for enhancing live biomedical imaging. Computational prediction of FP oligomeric states can accelerate the effort of protein engineering efforts of creating monomeric FPs. To the best of our knowledge, this study represents the first computational model for predicting and analyzing FP oligomerization directly from the amino acid sequence. After data curation, an exhaustive data set consisting of 397 non-redundant FP oligomeric states was compiled from the literature. Results from benchmarking of the protein descriptors revealed that the model built with amino acid composition descriptors was the top performing model with accuracy, sensitivity and specificity in excess of 80% and MCC greater than 0.6 for all three data subsets (e.g. training, tenfold cross-validation and external sets). The model provided insights on the important residues governing the oligomerization of FP. To maximize the benefit of the generated predictive model, it was implemented as a web server under the R programming environment. osFP affords a user-friendly interface that can be used to predict the oligomeric state of FP using the protein sequence. The advantage of osFP is that it is platform-independent meaning that it can be accessed via a web browser on any operating system and device. osFP is freely accessible at http://codes.bio/osfp/ while the source code and data set is provided on GitHub at https://github.com/chaninn/osFP/.Graphical Abstract.

Community and gene composition of a human dental plaque microbiota obtained by metagenomic sequencing

PubMed Central

Xie, G.; Chain, P.S.G.; Lo, C.; Liu, K-L.; Gans, J.; Merritt, J.; Qi, F.

2010-01-01

SUMMARY Human dental plaque is a complex microbial community containing an estimated 700 to 19,000 species/phylotypes. Despite numerous studies analysing species richness in healthy and diseased human subjects, the true genomic composition of the human dental plaque microbiota remains unknown. Here we report a metagenomic analysis of a healthy human plaque sample using a combination of second-generation sequencing platforms. A total of 860 million base pairs of non-human sequences were generated. Various analysis tools revealed the presence of 12 well-characterized phyla, members of the TM-7 and BRC1 clade, and sequences that could not be classified. Both pathogens and opportunistic pathogens were identified, supporting the ecological plaque hypothesis for oral diseases. Mapping the metagenomic reads to sequenced reference genomes demonstrated that 4% of the reads could be assigned to the sequenced species. Preliminary annotation identified genes belonging to all known functional categories. Interestingly, although 73% of the total assembled contig sequences were predicted to code for proteins, only 51% of them could be assigned a functional role. Furthermore, ~ 2.8% of the total predicted genes coded for proteins involved in resistance to antibiotics and toxic compounds, suggesting that the oral cavity is an important reservoir for antimicrobial resistance. PMID:21040513

Community and gene composition of a human dental plaque microbiota obtained by metagenomic sequencing.

PubMed

Xie, G; Chain, P S G; Lo, C-C; Liu, K-L; Gans, J; Merritt, J; Qi, F

2010-12-01

Human dental plaque is a complex microbial community containing an estimated 700 to 19,000 species/phylotypes. Despite numerous studies analysing species richness in healthy and diseased human subjects, the true genomic composition of the human dental plaque microbiota remains unknown. Here we report a metagenomic analysis of a healthy human plaque sample using a combination of second-generation sequencing platforms. A total of 860 million base pairs of non-human sequences were generated. Various analysis tools revealed the presence of 12 well-characterized phyla, members of the TM-7 and BRC1 clade, and sequences that could not be classified. Both pathogens and opportunistic pathogens were identified, supporting the ecological plaque hypothesis for oral diseases. Mapping the metagenomic reads to sequenced reference genomes demonstrated that 4% of the reads could be assigned to the sequenced species. Preliminary annotation identified genes belonging to all known functional categories. Interestingly, although 73% of the total assembled contig sequences were predicted to code for proteins, only 51% of them could be assigned a functional role. Furthermore, ~2.8% of the total predicted genes coded for proteins involved in resistance to antibiotics and toxic compounds, suggesting that the oral cavity is an important reservoir for antimicrobial resistance. © 2010 John Wiley & Sons A/S.

EST-PAC a web package for EST annotation and protein sequence prediction

PubMed Central

Strahm, Yvan; Powell, David; Lefèvre, Christophe

2006-01-01

With the decreasing cost of DNA sequencing technology and the vast diversity of biological resources, researchers increasingly face the basic challenge of annotating a larger number of expressed sequences tags (EST) from a variety of species. This typically consists of a series of repetitive tasks, which should be automated and easy to use. The results of these annotation tasks need to be stored and organized in a consistent way. All these operations should be self-installing, platform independent, easy to customize and amenable to using distributed bioinformatics resources available on the Internet. In order to address these issues, we present EST-PAC a web oriented multi-platform software package for expressed sequences tag (EST) annotation. EST-PAC provides a solution for the administration of EST and protein sequence annotations accessible through a web interface. Three aspects of EST annotation are automated: 1) searching local or remote biological databases for sequence similarities using Blast services, 2) predicting protein coding sequence from EST data and, 3) annotating predicted protein sequences with functional domain predictions. In practice, EST-PAC integrates the BLASTALL suite, EST-Scan2 and HMMER in a relational database system accessible through a simple web interface. EST-PAC also takes advantage of the relational database to allow consistent storage, powerful queries of results and, management of the annotation process. The system allows users to customize annotation strategies and provides an open-source data-management environment for research and education in bioinformatics. PMID:17147782

The structural genes for three Drosophila glue proteins reside at a single polytene chromosome puff locus.

PubMed Central

Crowley, T E; Bond, M W; Meyerowitz, E M

1983-01-01

The polytene chromosome puff at 68C on the Drosophila melanogaster third chromosome is thought from genetic experiments to contain the structural gene for one of the secreted salivary gland glue polypeptides, sgs-3. Previous work has demonstrated that the DNA included in this puff contains sequences that are transcribed to give three different polyadenylated RNAs that are abundant in third-larval-instar salivary glands. These have been called the group II, group III, and group IV RNAs. In the experiments reported here, we used the nucleotide sequence of the DNA coding for these RNAs to predict some of the physical and chemical properties expected of their protein products, including molecular weight, amino acid composition, and amino acid sequence. Salivary gland polypeptides with molecular weights similar to those expected for the 68C RNA translation products, and with the expected degree of incorporation of different radioactive amino acids, were purified. These proteins were shown by amino acid sequencing to correspond to the protein products of the 68C RNAs. It was further shown that each of these proteins is a part of the secreted salivary gland glue: the group IV RNA codes for the previously described sgs-3, whereas the group II and III RNAs code for the newly identified glue polypeptides sgs-8 and sgs-7. Images PMID:6406838

Polymerization of non-complementary RNA: systematic symmetric nucleotide exchanges mainly involving uracil produce mitochondrial RNA transcripts coding for cryptic overlapping genes.

PubMed

Seligmann, Hervé

2013-03-01

Usual DNA→RNA transcription exchanges T→U. Assuming different systematic symmetric nucleotide exchanges during translation, some GenBank RNAs match exactly human mitochondrial sequences (exchange rules listed in decreasing transcript frequencies): C↔U, A↔U, A↔U+C↔G (two nucleotide pairs exchanged), G↔U, A↔G, C↔G, none for A↔C, A↔G+C↔U, and A↔C+G↔U. Most unusual transcripts involve exchanging uracil. Independent measures of rates of rare replicational enzymatic DNA nucleotide misinsertions predict frequencies of RNA transcripts systematically exchanging the corresponding misinserted nucleotides. Exchange transcripts self-hybridize less than other gene regions, self-hybridization increases with length, suggesting endoribonuclease-limited elongation. Blast detects stop codon depleted putative protein coding overlapping genes within exchange-transcribed mitochondrial genes. These align with existing GenBank proteins (mainly metazoan origins, prokaryotic and viral origins underrepresented). These GenBank proteins frequently interact with RNA/DNA, are membrane transporters, or are typical of mitochondrial metabolism. Nucleotide exchange transcript frequencies increase with overlapping gene densities and stop densities, indicating finely tuned counterbalancing regulation of expression of systematic symmetric nucleotide exchange-encrypted proteins. Such expression necessitates combined activities of suppressor tRNAs matching stops, and nucleotide exchange transcription. Two independent properties confirm predicted exchanged overlap coding genes: discrepancy of third codon nucleotide contents from replicational deamination gradients, and codon usage according to circular code predictions. Predictions from both properties converge, especially for frequent nucleotide exchange types. Nucleotide exchanging transcription apparently increases coding densities of protein coding genes without lengthening genomes, revealing unsuspected functional DNA coding potential. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

UET: a database of evolutionarily-predicted functional determinants of protein sequences that cluster as functional sites in protein structures.

PubMed

Lua, Rhonald C; Wilson, Stephen J; Konecki, Daniel M; Wilkins, Angela D; Venner, Eric; Morgan, Daniel H; Lichtarge, Olivier

2016-01-04

The structure and function of proteins underlie most aspects of biology and their mutational perturbations often cause disease. To identify the molecular determinants of function as well as targets for drugs, it is central to characterize the important residues and how they cluster to form functional sites. The Evolutionary Trace (ET) achieves this by ranking the functional and structural importance of the protein sequence positions. ET uses evolutionary distances to estimate functional distances and correlates genotype variations with those in the fitness phenotype. Thus, ET ranks are worse for sequence positions that vary among evolutionarily closer homologs but better for positions that vary mostly among distant homologs. This approach identifies functional determinants, predicts function, guides the mutational redesign of functional and allosteric specificity, and interprets the action of coding sequence variations in proteins, people and populations. Now, the UET database offers pre-computed ET analyses for the protein structure databank, and on-the-fly analysis of any protein sequence. A web interface retrieves ET rankings of sequence positions and maps results to a structure to identify functionally important regions. This UET database integrates several ways of viewing the results on the protein sequence or structure and can be found at http://mammoth.bcm.tmc.edu/uet/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

The complete nucleotide sequence of RNA beta from the type strain of barley stripe mosaic virus.

PubMed Central

Gustafson, G; Armour, S L

1986-01-01

The complete nucleotide sequence of RNA beta from the type strain of barley stripe mosaic virus (BSMV) has been determined. The sequence is 3289 nucleotides in length and contains four open reading frames (ORFs) which code for proteins of Mr 22,147 (ORF1), Mr 58,098 (ORF2), Mr 17,378 (ORF3), and Mr 14,119 (ORF4). The predicted N-terminal amino acid sequence of the polypeptide encoded by the ORF nearest the 5'-end of the RNA (ORF1) is identical (after the initiator methionine) to the published N-terminal amino acid sequence of BSMV coat protein for 29 of the first 30 amino acids. ORF2 occupies the central portion of the coding region of RNA beta and ORF3 is located at the 3'-end. The ORF4 sequence overlaps the 3'-region of ORF2 and the 5'-region of ORF3 and differs in codon usage from the other three RNA beta ORFs. The coding region of RNA beta is followed by a poly(A) tract and a 238 nucleotide tRNA-like structure which are common to all three BSMV genomic RNAs. Images PMID:3754962

Draft genome sequence of Streptomyces vitaminophilus ATCC 31673, a producer of pyrrolomycin antibiotics, some of which contain a nitro group

DOE PAGES

Mahan, Kristina M.; Klingeman, Dawn Marie; Robert L. Hettich; ...

2016-01-21

Streptomyces vitaminophilus produces pyrrolomycins, which are halogenated polyketide antibiotics. Some of the pyrrolomycins contain a rare nitro group located on the pyrrole ring. In addition, the 6.5-Mbp genome encodes 5,941 predicted protein-coding sequences in 39 contigs with a 71.9% G+C content.

Draft Genome Sequence of Streptomyces vitaminophilus ATCC 31673, a Producer of Pyrrolomycin Antibiotics, Some of Which Contain a Nitro Group

PubMed Central

Klingeman, Dawn M.; Hettich, Robert L.; Parry, Ronald J.

2016-01-01

Streptomyces vitaminophilus produces pyrrolomycins, which are halogenated polyketide antibiotics. Some of the pyrrolomycins contain a rare nitro group located on the pyrrole ring. The 6.5-Mbp genome encodes 5,941 predicted protein-coding sequences in 39 contigs with a 71.9% G+C content. PMID:26798098

Draft genome sequence of Streptomyces vitaminophilus ATCC 31673, a producer of pyrrolomycin antibiotics, some of which contain a nitro group

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mahan, Kristina M.; Klingeman, Dawn Marie; Robert L. Hettich

Streptomyces vitaminophilus produces pyrrolomycins, which are halogenated polyketide antibiotics. Some of the pyrrolomycins contain a rare nitro group located on the pyrrole ring. In addition, the 6.5-Mbp genome encodes 5,941 predicted protein-coding sequences in 39 contigs with a 71.9% G+C content.

Computational Identification and Functional Predictions of Long Noncoding RNA in Zea mays

PubMed Central

Boerner, Susan; McGinnis, Karen M.

2012-01-01

Background Computational analysis of cDNA sequences from multiple organisms suggests that a large portion of transcribed DNA does not code for a functional protein. In mammals, noncoding transcription is abundant, and often results in functional RNA molecules that do not appear to encode proteins. Many long noncoding RNAs (lncRNAs) appear to have epigenetic regulatory function in humans, including HOTAIR and XIST. While epigenetic gene regulation is clearly an essential mechanism in plants, relatively little is known about the presence or function of lncRNAs in plants. Methodology/Principal Findings To explore the connection between lncRNA and epigenetic regulation of gene expression in plants, a computational pipeline using the programming language Python has been developed and applied to maize full length cDNA sequences to identify, classify, and localize potential lncRNAs. The pipeline was used in parallel with an SVM tool for identifying ncRNAs to identify the maximal number of ncRNAs in the dataset. Although the available library of sequences was small and potentially biased toward protein coding transcripts, 15% of the sequences were predicted to be noncoding. Approximately 60% of these sequences appear to act as precursors for small RNA molecules and may function to regulate gene expression via a small RNA dependent mechanism. ncRNAs were predicted to originate from both genic and intergenic loci. Of the lncRNAs that originated from genic loci, ∼20% were antisense to the host gene loci. Conclusions/Significance Consistent with similar studies in other organisms, noncoding transcription appears to be widespread in the maize genome. Computational predictions indicate that maize lncRNAs may function to regulate expression of other genes through multiple RNA mediated mechanisms. PMID:22916204

Identification and substrate prediction of new Fragaria x ananassa aquaporins and expression in different tissues and during strawberry fruit development.

PubMed

Merlaen, Britt; De Keyser, Ellen; Van Labeke, Marie-Christine

2018-01-01

The newly identified aquaporin coding sequences presented here pave the way for further insights into the plant-water relations in the commercial strawberry ( Fragaria x ananassa ). Aquaporins are water channel proteins that allow water to cross (intra)cellular membranes. In Fragaria x ananassa , few of them have been identified hitherto, hampering the exploration of the water transport regulation at cellular level. Here, we present new aquaporin coding sequences belonging to different subclasses: plasma membrane intrinsic proteins subtype 1 and subtype 2 (PIP1 and PIP2) and tonoplast intrinsic proteins (TIP). The classification is based on phylogenetic analysis and is confirmed by the presence of conserved residues. Substrate-specific signature sequences (SSSSs) and specificity-determining positions (SDPs) predict the substrate specificity of each new aquaporin. Expression profiling in leaves, petioles and developing fruits reveals distinct patterns, even within the same (sub)class. Expression profiles range from leaf-specific expression over constitutive expression to fruit-specific expression. Both upregulation and downregulation during fruit ripening occur. Substrate specificity and expression profiles suggest that functional specialization exists among aquaporins belonging to a different but also to the same (sub)class.

Tissue-specific Proteogenomic Analysis of Plutella xylostella Larval Midgut Using a Multialgorithm Pipeline*

PubMed Central

Zhu, Xun; Xie, Shangbo; Armengaud, Jean; Xie, Wen; Guo, Zhaojiang; Kang, Shi; Wu, Qingjun; Wang, Shaoli; Xia, Jixing; He, Rongjun; Zhang, Youjun

2016-01-01

The diamondback moth, Plutella xylostella (L.), is the major cosmopolitan pest of brassica and other cruciferous crops. Its larval midgut is a dynamic tissue that interfaces with a wide variety of toxicological and physiological processes. The draft sequence of the P. xylostella genome was recently released, but its annotation remains challenging because of the low sequence coverage of this branch of life and the poor description of exon/intron splicing rules for these insects. Peptide sequencing by computational assignment of tandem mass spectra to genome sequence information provides an experimental independent approach for confirming or refuting protein predictions, a concept that has been termed proteogenomics. In this study, we carried out an in-depth proteogenomic analysis to complement genome annotation of P. xylostella larval midgut based on shotgun HPLC-ESI-MS/MS data by means of a multialgorithm pipeline. A total of 876,341 tandem mass spectra were searched against the predicted P. xylostella protein sequences and a whole-genome six-frame translation database. Based on a data set comprising 2694 novel genome search specific peptides, we discovered 439 novel protein-coding genes and corrected 128 existing gene models. To get the most accurate data to seed further insect genome annotation, more than half of the novel protein-coding genes, i.e. 235 over 439, were further validated after RT-PCR amplification and sequencing of the corresponding transcripts. Furthermore, we validated 53 novel alternative splicings. Finally, a total of 6764 proteins were identified, resulting in one of the most comprehensive proteogenomic study of a nonmodel animal. As the first tissue-specific proteogenomics analysis of P. xylostella, this study provides the fundamental basis for high-throughput proteomics and functional genomics approaches aimed at deciphering the molecular mechanisms of resistance and controlling this pest. PMID:26902207

Plant MicroRNA Prediction by Supervised Machine Learning Using C5.0 Decision Trees.

PubMed

Williams, Philip H; Eyles, Rod; Weiller, Georg

2012-01-01

MicroRNAs (miRNAs) are nonprotein coding RNAs between 20 and 22 nucleotides long that attenuate protein production. Different types of sequence data are being investigated for novel miRNAs, including genomic and transcriptomic sequences. A variety of machine learning methods have successfully predicted miRNA precursors, mature miRNAs, and other nonprotein coding sequences. MirTools, mirDeep2, and miRanalyzer require "read count" to be included with the input sequences, which restricts their use to deep-sequencing data. Our aim was to train a predictor using a cross-section of different species to accurately predict miRNAs outside the training set. We wanted a system that did not require read-count for prediction and could therefore be applied to short sequences extracted from genomic, EST, or RNA-seq sources. A miRNA-predictive decision-tree model has been developed by supervised machine learning. It only requires that the corresponding genome or transcriptome is available within a sequence window that includes the precursor candidate so that the required sequence features can be collected. Some of the most critical features for training the predictor are the miRNA:miRNA(∗) duplex energy and the number of mismatches in the duplex. We present a cross-species plant miRNA predictor with 84.08% sensitivity and 98.53% specificity based on rigorous testing by leave-one-out validation.

Draft Genome Sequence of Algoriphagus sp. Strain NH1, a Multidrug-Resistant Bacterium Isolated from Coastal Sediments of the Northern Yellow Sea in China

PubMed Central

Mu, Dashuai; Zhao, Jinxin; Wang, Zongjie; Chen, Guanjun

2016-01-01

Algoriphagus sp. NH1 is a multidrug-resistant bacterium isolated from coastal sediments of the northern Yellow Sea in China. Here, we report the draft genome sequence of NH1, with a size of 6,131,579 bp, average G+C content of 42.68%, and 5,746 predicted protein-coding sequences. PMID:26769940

Draft Genome Sequence of Cellulolytic and Xylanolytic Cellulomonas sp. Strain B6 Isolated from Subtropical Forest Soil

PubMed Central

Piccinni, Florencia; Murua, Yanina; Ghio, Silvina; Talia, Paola; Rivarola, Máximo

2016-01-01

Cellulomonas sp. strain B6 was isolated from a subtropical forest soil sample and presented (hemi)cellulose-degrading activity. We report here its draft genome sequence, with an estimated genome size of 4 Mb, a G+C content of 75.1%, and 3,443 predicted protein-coding sequences, 92 of which are glycosyl hydrolases involved in polysaccharide degradation. PMID:27563050

Genome Sequence of Bacillus cereus Strain TG1-6, a Plant-Beneficial Rhizobacterium That Is Highly Salt Tolerant

PubMed Central

2018-01-01

ABSTRACT The complete genome sequence of Bacillus cereus strain TG1-6, which is a highly salt-tolerant rhizobacterium that enhances plant tolerance to drought stress, is reported here. The sequencing process was performed based on a combination of pyrosequencing and single-molecule sequencing. The complete genome is estimated to be approximately 5.42 Mb, containing a total of 5,610 predicted protein-coding DNA sequences (CDSs). PMID:29748401

Genome Sequence of Bacillus megaterium Strain YC4-R4, a Plant Growth-Promoting Rhizobacterium Isolated from a High-Salinity Environment.

PubMed

Vílchez, Juan Ignacio; Tang, Qiming; Kaushal, Richa; Wang, Wei; Lv, Suhui; He, Danxia; Chu, Zhaoqing; Zhang, Heng; Liu, Renyi; Zhang, Huiming

2018-06-21

Here, we report the complete genome sequence for Bacillus megaterium strain YC4-R4, a highly salt-tolerant rhizobacterium that promotes growth in plants. The sequencing process was performed by combining pyrosequencing and single-molecule sequencing techniques. The complete genome is estimated to be approximately 5.44 Mb, containing a total of 5,673 predicted protein-coding DNA sequences (CDSs). Copyright © 2018 Vílchez et al.

Human somatostatin I: sequence of the cDNA.

PubMed Central

Shen, L P; Pictet, R L; Rutter, W J

1982-01-01

RNA has been isolated from a human pancreatic somatostatinoma and used to prepare a cDNA library. After prescreening, clones containing somatostatin I sequences were identified by hybridization with an anglerfish somatostatin I-cloned cDNA probe. From the nucleotide sequence of two of these clones, we have deduced an essentially full-length mRNA sequence, including the preprosomatostatin coding region, 105 nucleotides from the 5' untranslated region and the complete 150-nucleotide 3' untranslated region. The coding region predicts a 116-amino acid precursor protein (Mr, 12.727) that contains somatostatin-14 and -28 at its COOH terminus. The predicted amino acid sequence of human somatostatin-28 is identical to that of somatostatin-28 isolated from the porcine and ovine species. A comparison of the amino acid sequences of human and anglerfish preprosomatostatin I indicated that the COOH-terminal region encoding somatostatin-14 and the adjacent 6 amino acids are highly conserved, whereas the remainder of the molecule, including the signal peptide region, is more divergent. However, many of the amino acid differences found in the pro region of the human and anglerfish proteins are conservative changes. This suggests that the propeptides have a similar secondary structure, which in turn may imply a biological function for this region of the molecule. Images PMID:6126875

A deep learning framework for improving long-range residue-residue contact prediction using a hierarchical strategy.

PubMed

Xiong, Dapeng; Zeng, Jianyang; Gong, Haipeng

2017-09-01

Residue-residue contacts are of great value for protein structure prediction, since contact information, especially from those long-range residue pairs, can significantly reduce the complexity of conformational sampling for protein structure prediction in practice. Despite progresses in the past decade on protein targets with abundant homologous sequences, accurate contact prediction for proteins with limited sequence information is still far from satisfaction. Methodologies for these hard targets still need further improvement. We presented a computational program DeepConPred, which includes a pipeline of two novel deep-learning-based methods (DeepCCon and DeepRCon) as well as a contact refinement step, to improve the prediction of long-range residue contacts from primary sequences. When compared with previous prediction approaches, our framework employed an effective scheme to identify optimal and important features for contact prediction, and was only trained with coevolutionary information derived from a limited number of homologous sequences to ensure robustness and usefulness for hard targets. Independent tests showed that 59.33%/49.97%, 64.39%/54.01% and 70.00%/59.81% of the top L/5, top L/10 and top 5 predictions were correct for CASP10/CASP11 proteins, respectively. In general, our algorithm ranked as one of the best methods for CASP targets. All source data and codes are available at http://166.111.152.91/Downloads.html . hgong@tsinghua.edu.cn or zengjy321@tsinghua.edu.cn. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Informational structure of genetic sequences and nature of gene splicing

NASA Astrophysics Data System (ADS)

Trifonov, E. N.

1991-10-01

Only about 1/20 of DNA of higher organisms codes for proteins, by means of classical triplet code. The rest of DNA sequences is largely silent, with unclear functions, if any. The triplet code is not the only code (message) carried by the sequences. There are three levels of molecular communication, where the same sequence ``talks'' to various bimolecules, while having, respectively, three different appearances: DNA, RNA and protein. Since the molecular structures and, hence, sequence specific preferences of these are substantially different, the original DNA sequence has to carry simultaneously three types of sequence patterns (codes, messages), thus, being a composite structure in which one had the same letter (nucleotide) is frequently involved in several overlapping codes of different nature. This multiplicity and overlapping of the codes is a unique feature of the Gnomic, language of genetic sequences. The coexisting codes have to be degenerate in various degrees to allow an optimal and concerted performance of all the encoded functions. There is an obvious conflict between the best possible performance of a given function and necessity to compromise the quality of a given sequence pattern in favor of other patterns. It appears that the major role of various changes in the sequences on their ``ontogenetic'' way from DNA to RNA to protein, like RNA editing and splicing, or protein post-translational modifications is to resolve such conflicts. New data are presented strongly indicating that the gene splicing is such a device to resolve the conflict between the code of DNA folding in chromatin and the triplet code for protein synthesis.

Signal sequence and keyword trap in silico for selection of full-length human cDNAs encoding secretion or membrane proteins from oligo-capped cDNA libraries.

PubMed

Otsuki, Tetsuji; Ota, Toshio; Nishikawa, Tetsuo; Hayashi, Koji; Suzuki, Yutaka; Yamamoto, Jun-ichi; Wakamatsu, Ai; Kimura, Kouichi; Sakamoto, Katsuhiko; Hatano, Naoto; Kawai, Yuri; Ishii, Shizuko; Saito, Kaoru; Kojima, Shin-ichi; Sugiyama, Tomoyasu; Ono, Tetsuyoshi; Okano, Kazunori; Yoshikawa, Yoko; Aotsuka, Satoshi; Sasaki, Naokazu; Hattori, Atsushi; Okumura, Koji; Nagai, Keiichi; Sugano, Sumio; Isogai, Takao

2005-01-01

We have developed an in silico method of selection of human full-length cDNAs encoding secretion or membrane proteins from oligo-capped cDNA libraries. Fullness rates were increased to about 80% by combination of the oligo-capping method and ATGpr, software for prediction of translation start point and the coding potential. Then, using 5'-end single-pass sequences, cDNAs having the signal sequence were selected by PSORT ('signal sequence trap'). We also applied 'secretion or membrane protein-related keyword trap' based on the result of BLAST search against the SWISS-PROT database for the cDNAs which could not be selected by PSORT. Using the above procedures, 789 cDNAs were primarily selected and subjected to full-length sequencing, and 334 of these cDNAs were finally selected as novel. Most of the cDNAs (295 cDNAs: 88.3%) were predicted to encode secretion or membrane proteins. In particular, 165(80.5%) of the 205 cDNAs selected by PSORT were predicted to have signal sequences, while 70 (54.2%) of the 129 cDNAs selected by 'keyword trap' preserved the secretion or membrane protein-related keywords. Many important cDNAs were obtained, including transporters, receptors, and ligands, involved in significant cellular functions. Thus, an efficient method of selecting secretion or membrane protein-encoding cDNAs was developed by combining the above four procedures.

Coarse-grained sequences for protein folding and design.

PubMed

Brown, Scott; Fawzi, Nicolas J; Head-Gordon, Teresa

2003-09-16

We present the results of sequence design on our off-lattice minimalist model in which no specification of native-state tertiary contacts is needed. We start with a sequence that adopts a target topology and build on it through sequence mutation to produce new sequences that comprise distinct members within a target fold class. In this work, we use the alpha/beta ubiquitin fold class and design two new sequences that, when characterized through folding simulations, reproduce the differences in folding mechanism seen experimentally for proteins L and G. The primary implication of this work is that patterning of hydrophobic and hydrophilic residues is the physical origin for the success of relative contact-order descriptions of folding, and that these physics-based potentials provide a predictive connection between free energy landscapes and amino acid sequence (the original protein folding problem). We present results of the sequence mapping from a 20- to the three-letter code for determining a sequence that folds into the WW domain topology to illustrate future extensions to protein design.

Coarse-grained sequences for protein folding and design

PubMed Central

Brown, Scott; Fawzi, Nicolas J.; Head-Gordon, Teresa

2003-01-01

We present the results of sequence design on our off-lattice minimalist model in which no specification of native-state tertiary contacts is needed. We start with a sequence that adopts a target topology and build on it through sequence mutation to produce new sequences that comprise distinct members within a target fold class. In this work, we use the α/β ubiquitin fold class and design two new sequences that, when characterized through folding simulations, reproduce the differences in folding mechanism seen experimentally for proteins L and G. The primary implication of this work is that patterning of hydrophobic and hydrophilic residues is the physical origin for the success of relative contact-order descriptions of folding, and that these physics-based potentials provide a predictive connection between free energy landscapes and amino acid sequence (the original protein folding problem). We present results of the sequence mapping from a 20- to the three-letter code for determining a sequence that folds into the WW domain topology to illustrate future extensions to protein design. PMID:12963815

A method for partitioning the information contained in a protein sequence between its structure and function.

PubMed

Possenti, Andrea; Vendruscolo, Michele; Camilloni, Carlo; Tiana, Guido

2018-05-23

Proteins employ the information stored in the genetic code and translated into their sequences to carry out well-defined functions in the cellular environment. The possibility to encode for such functions is controlled by the balance between the amount of information supplied by the sequence and that left after that the protein has folded into its structure. We study the amount of information necessary to specify the protein structure, providing an estimate that keeps into account the thermodynamic properties of protein folding. We thus show that the information remaining in the protein sequence after encoding for its structure (the 'information gap') is very close to what needed to encode for its function and interactions. Then, by predicting the information gap directly from the protein sequence, we show that it may be possible to use these insights from information theory to discriminate between ordered and disordered proteins, to identify unknown functions, and to optimize artificially-designed protein sequences. This article is protected by copyright. All rights reserved. © 2018 Wiley Periodicals, Inc.

Identification and characterization of an early gene in the Lymantria dispar multinucleocapsid nuclear polyhedrosis virus

Treesearch

David S. Bischoff; James M. Slavicek

1995-01-01

The Lymantria dispar multinucleocapsid nuclear polyhedrosis virus (LdMNPV) gene encoding G22 was cloned and sequenced. The G22 gene codes for a 191 amino acid protein with a predicted Mr of 22000. Expression of G22 in a rabbit reticulocyte system generated a protein with an M...

Experimental annotation of post-translational features and translated coding regions in the pathogen Salmonella Typhimurium

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ansong, Charles; Tolic, Nikola; Purvine, Samuel O.

Complete and accurate genome annotation is crucial for comprehensive and systematic studies of biological systems. For example systems biology-oriented genome scale modeling efforts greatly benefit from accurate annotation of protein-coding genes to develop proper functioning models. However, determining protein-coding genes for most new genomes is almost completely performed by inference, using computational predictions with significant documented error rates (> 15%). Furthermore, gene prediction programs provide no information on biologically important post-translational processing events critical for protein function. With the ability to directly measure peptides arising from expressed proteins, mass spectrometry-based proteomics approaches can be used to augment and verify codingmore » regions of a genomic sequence and importantly detect post-translational processing events. In this study we utilized “shotgun” proteomics to guide accurate primary genome annotation of the bacterial pathogen Salmonella Typhimurium 14028 to facilitate a systems-level understanding of Salmonella biology. The data provides protein-level experimental confirmation for 44% of predicted protein-coding genes, suggests revisions to 48 genes assigned incorrect translational start sites, and uncovers 13 non-annotated genes missed by gene prediction programs. We also present a comprehensive analysis of post-translational processing events in Salmonella, revealing a wide range of complex chemical modifications (70 distinct modifications) and confirming more than 130 signal peptide and N-terminal methionine cleavage events in Salmonella. This study highlights several ways in which proteomics data applied during the primary stages of annotation can improve the quality of genome annotations, especially with regards to the annotation of mature protein products.« less

Draft Genome Sequence of Streptomyces vitaminophilus ATCC 31673, a Producer of Pyrrolomycin Antibiotics, Some of Which Contain a Nitro Group.

PubMed

Mahan, Kristina M; Klingeman, Dawn M; Hettich, Robert L; Parry, Ronald J; Graham, David E

2016-01-21

Streptomyces vitaminophilus produces pyrrolomycins, which are halogenated polyketide antibiotics. Some of the pyrrolomycins contain a rare nitro group located on the pyrrole ring. The 6.5-Mbp genome encodes 5,941 predicted protein-coding sequences in 39 contigs with a 71.9% G+C content. Copyright © 2016 Mahan et al.

A novel Multi-Agent Ada-Boost algorithm for predicting protein structural class with the information of protein secondary structure.

PubMed

Fan, Ming; Zheng, Bin; Li, Lihua

2015-10-01

Knowledge of the structural class of a given protein is important for understanding its folding patterns. Although a lot of efforts have been made, it still remains a challenging problem for prediction of protein structural class solely from protein sequences. The feature extraction and classification of proteins are the main problems in prediction. In this research, we extended our earlier work regarding these two aspects. In protein feature extraction, we proposed a scheme by calculating the word frequency and word position from sequences of amino acid, reduced amino acid, and secondary structure. For an accurate classification of the structural class of protein, we developed a novel Multi-Agent Ada-Boost (MA-Ada) method by integrating the features of Multi-Agent system into Ada-Boost algorithm. Extensive experiments were taken to test and compare the proposed method using four benchmark datasets in low homology. The results showed classification accuracies of 88.5%, 96.0%, 88.4%, and 85.5%, respectively, which are much better compared with the existing methods. The source code and dataset are available on request.

DNA sequence-dependent mechanics and protein-assisted bending in repressor-mediated loop formation

PubMed Central

Boedicker, James Q.; Garcia, Hernan G.; Johnson, Stephanie; Phillips, Rob

2014-01-01

As the chief informational molecule of life, DNA is subject to extensive physical manipulations. The energy required to deform double-helical DNA depends on sequence, and this mechanical code of DNA influences gene regulation, such as through nucleosome positioning. Here we examine the sequence-dependent flexibility of DNA in bacterial transcription factor-mediated looping, a context for which the role of sequence remains poorly understood. Using a suite of synthetic constructs repressed by the Lac repressor and two well-known sequences that show large flexibility differences in vitro, we make precise statistical mechanical predictions as to how DNA sequence influences loop formation and test these predictions using in vivo transcription and in vitro single-molecule assays. Surprisingly, sequence-dependent flexibility does not affect in vivo gene regulation. By theoretically and experimentally quantifying the relative contributions of sequence and the DNA-bending protein HU to DNA mechanical properties, we reveal that bending by HU dominates DNA mechanics and masks intrinsic sequence-dependent flexibility. Such a quantitative understanding of how mechanical regulatory information is encoded in the genome will be a key step towards a predictive understanding of gene regulation at single-base pair resolution. PMID:24231252

Protein Solvent-Accessibility Prediction by a Stacked Deep Bidirectional Recurrent Neural Network.

PubMed

Zhang, Buzhong; Li, Linqing; Lü, Qiang

2018-05-25

Residue solvent accessibility is closely related to the spatial arrangement and packing of residues. Predicting the solvent accessibility of a protein is an important step to understand its structure and function. In this work, we present a deep learning method to predict residue solvent accessibility, which is based on a stacked deep bidirectional recurrent neural network applied to sequence profiles. To capture more long-range sequence information, a merging operator was proposed when bidirectional information from hidden nodes was merged for outputs. Three types of merging operators were used in our improved model, with a long short-term memory network performing as a hidden computing node. The trained database was constructed from 7361 proteins extracted from the PISCES server using a cut-off of 25% sequence identity. Sequence-derived features including position-specific scoring matrix, physical properties, physicochemical characteristics, conservation score and protein coding were used to represent a residue. Using this method, predictive values of continuous relative solvent-accessible area were obtained, and then, these values were transformed into binary states with predefined thresholds. Our experimental results showed that our deep learning method improved prediction quality relative to current methods, with mean absolute error and Pearson's correlation coefficient values of 8.8% and 74.8%, respectively, on the CB502 dataset and 8.2% and 78%, respectively, on the Manesh215 dataset.

Draft Genome Sequence of a Novel Chitinophaga sp. Strain, MD30, Isolated from a Biofilm in an Air Conditioner Condensate Pipe

PubMed Central

Darris, Maxwell

2017-01-01

ABSTRACT Most of the 24 known Chitinophaga species were originally isolated from soils. We report the draft genome sequence of a putatively novel Chitinophaga sp. from a biofilm in an air conditioner condensate pipe. The genome comprises 7,661,303 bp in one scaffold, 5,694 predicted protein-coding sequences, and a G+C content of 47.6%. PMID:29051259

Draft Genome Sequence of Cellulolytic and Xylanolytic Cellulomonas sp. Strain B6 Isolated from Subtropical Forest Soil.

PubMed

Piccinni, Florencia; Murua, Yanina; Ghio, Silvina; Talia, Paola; Rivarola, Máximo; Campos, Eleonora

2016-08-25

Cellulomonas sp. strain B6 was isolated from a subtropical forest soil sample and presented (hemi)cellulose-degrading activity. We report here its draft genome sequence, with an estimated genome size of 4 Mb, a G+C content of 75.1%, and 3,443 predicted protein-coding sequences, 92 of which are glycosyl hydrolases involved in polysaccharide degradation. Copyright © 2016 Piccinni et al.

Draft Genome Sequence of the Entomopathogenic Bacterium Bacillus pumilus 15.1, a Strain Highly Toxic to the Mediterranean Fruit Fly Ceratitis capitata

PubMed Central

García-Ramón, Diana C.; Palma, Leopoldo; Berry, Colin; Osuna, Antonio

2015-01-01

We present the draft whole-genome sequence of the entomopathogenic Bacillus pumilus 15.1 strain that consists of 3,795,691 bp and 3,776 predicted protein-coding genes. This genome sequence provides the basis for understanding the potential mechanism behind the toxicity and virulence of B. pumilus 15.1 against the Mediterranean fruit fly. PMID:26404596

An integrative strategy to identify the entire protein coding potential of prokaryotic genomes by proteogenomics.

PubMed

Omasits, Ulrich; Varadarajan, Adithi R; Schmid, Michael; Goetze, Sandra; Melidis, Damianos; Bourqui, Marc; Nikolayeva, Olga; Québatte, Maxime; Patrignani, Andrea; Dehio, Christoph; Frey, Juerg E; Robinson, Mark D; Wollscheid, Bernd; Ahrens, Christian H

2017-12-01

Accurate annotation of all protein-coding sequences (CDSs) is an essential prerequisite to fully exploit the rapidly growing repertoire of completely sequenced prokaryotic genomes. However, large discrepancies among the number of CDSs annotated by different resources, missed functional short open reading frames (sORFs), and overprediction of spurious ORFs represent serious limitations. Our strategy toward accurate and complete genome annotation consolidates CDSs from multiple reference annotation resources, ab initio gene prediction algorithms and in silico ORFs (a modified six-frame translation considering alternative start codons) in an integrated proteogenomics database (iPtgxDB) that covers the entire protein-coding potential of a prokaryotic genome. By extending the PeptideClassifier concept of unambiguous peptides for prokaryotes, close to 95% of the identifiable peptides imply one distinct protein, largely simplifying downstream analysis. Searching a comprehensive Bartonella henselae proteomics data set against such an iPtgxDB allowed us to unambiguously identify novel ORFs uniquely predicted by each resource, including lipoproteins, differentially expressed and membrane-localized proteins, novel start sites and wrongly annotated pseudogenes. Most novelties were confirmed by targeted, parallel reaction monitoring mass spectrometry, including unique ORFs and single amino acid variations (SAAVs) identified in a re-sequenced laboratory strain that are not present in its reference genome. We demonstrate the general applicability of our strategy for genomes with varying GC content and distinct taxonomic origin. We release iPtgxDBs for B. henselae , Bradyrhizobium diazoefficiens and Escherichia coli and the software to generate both proteogenomics search databases and integrated annotation files that can be viewed in a genome browser for any prokaryote. © 2017 Omasits et al.; Published by Cold Spring Harbor Laboratory Press.

CombAlign: a code for generating a one-to-many sequence alignment from a set of pairwise structure-based sequence alignments.

PubMed

Zhou, Carol L Ecale

2015-01-01

In order to better define regions of similarity among related protein structures, it is useful to identify the residue-residue correspondences among proteins. Few codes exist for constructing a one-to-many multiple sequence alignment derived from a set of structure or sequence alignments, and a need was evident for creating such a tool for combining pairwise structure alignments that would allow for insertion of gaps in the reference structure. This report describes a new Python code, CombAlign, which takes as input a set of pairwise sequence alignments (which may be structure based) and generates a one-to-many, gapped, multiple structure- or sequence-based sequence alignment (MSSA). The use and utility of CombAlign was demonstrated by generating gapped MSSAs using sets of pairwise structure-based sequence alignments between structure models of the matrix protein (VP40) and pre-small/secreted glycoprotein (sGP) of Reston Ebolavirus and the corresponding proteins of several other filoviruses. The gapped MSSAs revealed structure-based residue-residue correspondences, which enabled identification of structurally similar versus differing regions in the Reston proteins compared to each of the other corresponding proteins. CombAlign is a new Python code that generates a one-to-many, gapped, multiple structure- or sequence-based sequence alignment (MSSA) given a set of pairwise sequence alignments (which may be structure based). CombAlign has utility in assisting the user in distinguishing structurally conserved versus divergent regions on a reference protein structure relative to other closely related proteins. CombAlign was developed in Python 2.6, and the source code is available for download from the GitHub code repository.

Deciphering mRNA Sequence Determinants of Protein Production Rate

NASA Astrophysics Data System (ADS)

Szavits-Nossan, Juraj; Ciandrini, Luca; Romano, M. Carmen

2018-03-01

One of the greatest challenges in biophysical models of translation is to identify coding sequence features that affect the rate of translation and therefore the overall protein production in the cell. We propose an analytic method to solve a translation model based on the inhomogeneous totally asymmetric simple exclusion process, which allows us to unveil simple design principles of nucleotide sequences determining protein production rates. Our solution shows an excellent agreement when compared to numerical genome-wide simulations of S. cerevisiae transcript sequences and predicts that the first 10 codons, which is the ribosome footprint length on the mRNA, together with the value of the initiation rate, are the main determinants of protein production rate under physiological conditions. Finally, we interpret the obtained analytic results based on the evolutionary role of the codons' choice for regulating translation rates and ribosome densities.

Identification and characterization of a novel zebrafish (Danio rerio) pentraxin-carbonic anhydrase.

PubMed

Patrikainen, Maarit S; Tolvanen, Martti E E; Aspatwar, Ashok; Barker, Harlan R; Ortutay, Csaba; Jänis, Janne; Laitaoja, Mikko; Hytönen, Vesa P; Azizi, Latifeh; Manandhar, Prajwol; Jáger, Edit; Vullo, Daniela; Kukkurainen, Sampo; Hilvo, Mika; Supuran, Claudiu T; Parkkila, Seppo

2017-01-01

Carbonic anhydrases (CAs) are ubiquitous, essential enzymes which catalyze the conversion of carbon dioxide and water to bicarbonate and H + ions. Vertebrate genomes generally contain gene loci for 15-21 different CA isoforms, three of which are enzymatically inactive. CA VI is the only secretory protein of the enzymatically active isoforms. We discovered that non-mammalian CA VI contains a C-terminal pentraxin (PTX) domain, a novel combination for both CAs and PTXs. We isolated and sequenced zebrafish ( Danio rerio ) CA VI cDNA, complete with the sequence coding for the PTX domain, and produced the recombinant CA VI-PTX protein. Enzymatic activity and kinetic parameters were measured with a stopped-flow instrument. Mass spectrometry, analytical gel filtration and dynamic light scattering were used for biophysical characterization. Sequence analyses and Bayesian phylogenetics were used in generating hypotheses of protein structure and CA VI gene evolution. A CA VI-PTX antiserum was produced, and the expression of CA VI protein was studied by immunohistochemistry. A knock-down zebrafish model was constructed, and larvae were observed up to five days post-fertilization (dpf). The expression of ca6 mRNA was quantitated by qRT-PCR in different developmental times in morphant and wild-type larvae and in different adult fish tissues. Finally, the swimming behavior of the morphant fish was compared to that of wild-type fish. The recombinant enzyme has a very high carbonate dehydratase activity. Sequencing confirms a 530-residue protein identical to one of the predicted proteins in the Ensembl database (ensembl.org). The protein is pentameric in solution, as studied by gel filtration and light scattering, presumably joined by the PTX domains. Mass spectrometry confirms the predicted signal peptide cleavage and disulfides, and N-glycosylation in two of the four observed glycosylation motifs. Molecular modeling of the pentamer is consistent with the modifications observed in mass spectrometry. Phylogenetics and sequence analyses provide a consistent hypothesis of the evolutionary history of domains associated with CA VI in mammals and non-mammals. Briefly, the evidence suggests that ancestral CA VI was a transmembrane protein, the exon coding for the cytoplasmic domain was replaced by one coding for PTX domain, and finally, in the therian lineage, the PTX-coding exon was lost. We knocked down CA VI expression in zebrafish embryos with antisense morpholino oligonucleotides, resulting in phenotype features of decreased buoyancy and swim bladder deflation in 4 dpf larvae. These findings provide novel insights into the evolution, structure, and function of this unique CA form.

InterProScan 5: genome-scale protein function classification

PubMed Central

Jones, Philip; Binns, David; Chang, Hsin-Yu; Fraser, Matthew; Li, Weizhong; McAnulla, Craig; McWilliam, Hamish; Maslen, John; Mitchell, Alex; Nuka, Gift; Pesseat, Sebastien; Quinn, Antony F.; Sangrador-Vegas, Amaia; Scheremetjew, Maxim; Yong, Siew-Yit; Lopez, Rodrigo; Hunter, Sarah

2014-01-01

Motivation: Robust large-scale sequence analysis is a major challenge in modern genomic science, where biologists are frequently trying to characterize many millions of sequences. Here, we describe a new Java-based architecture for the widely used protein function prediction software package InterProScan. Developments include improvements and additions to the outputs of the software and the complete reimplementation of the software framework, resulting in a flexible and stable system that is able to use both multiprocessor machines and/or conventional clusters to achieve scalable distributed data analysis. InterProScan is freely available for download from the EMBl-EBI FTP site and the open source code is hosted at Google Code. Availability and implementation: InterProScan is distributed via FTP at ftp://ftp.ebi.ac.uk/pub/software/unix/iprscan/5/ and the source code is available from http://code.google.com/p/interproscan/. Contact: http://www.ebi.ac.uk/support or interhelp@ebi.ac.uk or mitchell@ebi.ac.uk PMID:24451626

Fast and Accurate Multivariate Gaussian Modeling of Protein Families: Predicting Residue Contacts and Protein-Interaction Partners

PubMed Central

Feinauer, Christoph; Procaccini, Andrea; Zecchina, Riccardo; Weigt, Martin; Pagnani, Andrea

2014-01-01

In the course of evolution, proteins show a remarkable conservation of their three-dimensional structure and their biological function, leading to strong evolutionary constraints on the sequence variability between homologous proteins. Our method aims at extracting such constraints from rapidly accumulating sequence data, and thereby at inferring protein structure and function from sequence information alone. Recently, global statistical inference methods (e.g. direct-coupling analysis, sparse inverse covariance estimation) have achieved a breakthrough towards this aim, and their predictions have been successfully implemented into tertiary and quaternary protein structure prediction methods. However, due to the discrete nature of the underlying variable (amino-acids), exact inference requires exponential time in the protein length, and efficient approximations are needed for practical applicability. Here we propose a very efficient multivariate Gaussian modeling approach as a variant of direct-coupling analysis: the discrete amino-acid variables are replaced by continuous Gaussian random variables. The resulting statistical inference problem is efficiently and exactly solvable. We show that the quality of inference is comparable or superior to the one achieved by mean-field approximations to inference with discrete variables, as done by direct-coupling analysis. This is true for (i) the prediction of residue-residue contacts in proteins, and (ii) the identification of protein-protein interaction partner in bacterial signal transduction. An implementation of our multivariate Gaussian approach is available at the website http://areeweb.polito.it/ricerca/cmp/code. PMID:24663061

Combining Structural Modeling with Ensemble Machine Learning to Accurately Predict Protein Fold Stability and Binding Affinity Effects upon Mutation

PubMed Central

Garcia Lopez, Sebastian; Kim, Philip M.

2014-01-01

Advances in sequencing have led to a rapid accumulation of mutations, some of which are associated with diseases. However, to draw mechanistic conclusions, a biochemical understanding of these mutations is necessary. For coding mutations, accurate prediction of significant changes in either the stability of proteins or their affinity to their binding partners is required. Traditional methods have used semi-empirical force fields, while newer methods employ machine learning of sequence and structural features. Here, we show how combining both of these approaches leads to a marked boost in accuracy. We introduce ELASPIC, a novel ensemble machine learning approach that is able to predict stability effects upon mutation in both, domain cores and domain-domain interfaces. We combine semi-empirical energy terms, sequence conservation, and a wide variety of molecular details with a Stochastic Gradient Boosting of Decision Trees (SGB-DT) algorithm. The accuracy of our predictions surpasses existing methods by a considerable margin, achieving correlation coefficients of 0.77 for stability, and 0.75 for affinity predictions. Notably, we integrated homology modeling to enable proteome-wide prediction and show that accurate prediction on modeled structures is possible. Lastly, ELASPIC showed significant differences between various types of disease-associated mutations, as well as between disease and common neutral mutations. Unlike pure sequence-based prediction methods that try to predict phenotypic effects of mutations, our predictions unravel the molecular details governing the protein instability, and help us better understand the molecular causes of diseases. PMID:25243403

Comparative genomics approach to detecting split-coding regions in a low-coverage genome: lessons from the chimaera Callorhinchus milii (Holocephali, Chondrichthyes).

PubMed

Dessimoz, Christophe; Zoller, Stefan; Manousaki, Tereza; Qiu, Huan; Meyer, Axel; Kuraku, Shigehiro

2011-09-01

Recent development of deep sequencing technologies has facilitated de novo genome sequencing projects, now conducted even by individual laboratories. However, this will yield more and more genome sequences that are not well assembled, and will hinder thorough annotation when no closely related reference genome is available. One of the challenging issues is the identification of protein-coding sequences split into multiple unassembled genomic segments, which can confound orthology assignment and various laboratory experiments requiring the identification of individual genes. In this study, using the genome of a cartilaginous fish, Callorhinchus milii, as test case, we performed gene prediction using a model specifically trained for this genome. We implemented an algorithm, designated ESPRIT, to identify possible linkages between multiple protein-coding portions derived from a single genomic locus split into multiple unassembled genomic segments. We developed a validation framework based on an artificially fragmented human genome, improvements between early and recent mouse genome assemblies, comparison with experimentally validated sequences from GenBank, and phylogenetic analyses. Our strategy provided insights into practical solutions for efficient annotation of only partially sequenced (low-coverage) genomes. To our knowledge, our study is the first formulation of a method to link unassembled genomic segments based on proteomes of relatively distantly related species as references.

Comparative genomics approach to detecting split-coding regions in a low-coverage genome: lessons from the chimaera Callorhinchus milii (Holocephali, Chondrichthyes)

PubMed Central

Zoller, Stefan; Manousaki, Tereza; Qiu, Huan; Meyer, Axel; Kuraku, Shigehiro

2011-01-01

Recent development of deep sequencing technologies has facilitated de novo genome sequencing projects, now conducted even by individual laboratories. However, this will yield more and more genome sequences that are not well assembled, and will hinder thorough annotation when no closely related reference genome is available. One of the challenging issues is the identification of protein-coding sequences split into multiple unassembled genomic segments, which can confound orthology assignment and various laboratory experiments requiring the identification of individual genes. In this study, using the genome of a cartilaginous fish, Callorhinchus milii, as test case, we performed gene prediction using a model specifically trained for this genome. We implemented an algorithm, designated ESPRIT, to identify possible linkages between multiple protein-coding portions derived from a single genomic locus split into multiple unassembled genomic segments. We developed a validation framework based on an artificially fragmented human genome, improvements between early and recent mouse genome assemblies, comparison with experimentally validated sequences from GenBank, and phylogenetic analyses. Our strategy provided insights into practical solutions for efficient annotation of only partially sequenced (low-coverage) genomes. To our knowledge, our study is the first formulation of a method to link unassembled genomic segments based on proteomes of relatively distantly related species as references. PMID:21712341

Coevolutionary modeling of protein sequences: Predicting structure, function, and mutational landscapes

NASA Astrophysics Data System (ADS)

Weigt, Martin

Over the last years, biological research has been revolutionized by experimental high-throughput techniques, in particular by next-generation sequencing technology. Unprecedented amounts of data are accumulating, and there is a growing request for computational methods unveiling the information hidden in raw data, thereby increasing our understanding of complex biological systems. Statistical-physics models based on the maximum-entropy principle have, in the last few years, played an important role in this context. To give a specific example, proteins and many non-coding RNA show a remarkable degree of structural and functional conservation in the course of evolution, despite a large variability in amino acid sequences. We have developed a statistical-mechanics inspired inference approach - called Direct-Coupling Analysis - to link this sequence variability (easy to observe in sequence alignments, which are available in public sequence databases) to bio-molecular structure and function. In my presentation I will show, how this methodology can be used (i) to infer contacts between residues and thus to guide tertiary and quaternary protein structure prediction and RNA structure prediction, (ii) to discriminate interacting from non-interacting protein families, and thus to infer conserved protein-protein interaction networks, and (iii) to reconstruct mutational landscapes and thus to predict the phenotypic effect of mutations. References [1] M. Figliuzzi, H. Jacquier, A. Schug, O. Tenaillon and M. Weigt ''Coevolutionary landscape inference and the context-dependence of mutations in beta-lactamase TEM-1'', Mol. Biol. Evol. (2015), doi: 10.1093/molbev/msv211 [2] E. De Leonardis, B. Lutz, S. Ratz, S. Cocco, R. Monasson, A. Schug, M. Weigt ''Direct-Coupling Analysis of nucleotide coevolution facilitates RNA secondary and tertiary structure prediction'', Nucleic Acids Research (2015), doi: 10.1093/nar/gkv932 [3] F. Morcos, A. Pagnani, B. Lunt, A. Bertolino, D. Marks, C. Sander, R. Zecchina, J.N. Onuchic, T. Hwa, M. Weigt, ''Direct-coupling analysis of residue co-evolution captures native contacts across many protein families'', Proc. Natl. Acad. Sci. 108, E1293-E1301 (2011).

Deep transcriptome annotation enables the discovery and functional characterization of cryptic small proteins

PubMed Central

Delcourt, Vivian; Lucier, Jean-François; Gagnon, Jules; Beaudoin, Maxime C; Vanderperre, Benoît; Breton, Marc-André; Motard, Julie; Jacques, Jean-François; Brunelle, Mylène; Gagnon-Arsenault, Isabelle; Fournier, Isabelle; Ouangraoua, Aida; Hunting, Darel J; Cohen, Alan A; Landry, Christian R; Scott, Michelle S

2017-01-01

Recent functional, proteomic and ribosome profiling studies in eukaryotes have concurrently demonstrated the translation of alternative open-reading frames (altORFs) in addition to annotated protein coding sequences (CDSs). We show that a large number of small proteins could in fact be coded by these altORFs. The putative alternative proteins translated from altORFs have orthologs in many species and contain functional domains. Evolutionary analyses indicate that altORFs often show more extreme conservation patterns than their CDSs. Thousands of alternative proteins are detected in proteomic datasets by reanalysis using a database containing predicted alternative proteins. This is illustrated with specific examples, including altMiD51, a 70 amino acid mitochondrial fission-promoting protein encoded in MiD51/Mief1/SMCR7L, a gene encoding an annotated protein promoting mitochondrial fission. Our results suggest that many genes are multicoding genes and code for a large protein and one or several small proteins. PMID:29083303

Using cellular automata to generate image representation for biological sequences.

PubMed

Xiao, X; Shao, S; Ding, Y; Huang, Z; Chen, X; Chou, K-C

2005-02-01

A novel approach to visualize biological sequences is developed based on cellular automata (Wolfram, S. Nature 1984, 311, 419-424), a set of discrete dynamical systems in which space and time are discrete. By transforming the symbolic sequence codes into the digital codes, and using some optimal space-time evolvement rules of cellular automata, a biological sequence can be represented by a unique image, the so-called cellular automata image. Many important features, which are originally hidden in a long and complicated biological sequence, can be clearly revealed thru its cellular automata image. With biological sequences entering into databanks rapidly increasing in the post-genomic era, it is anticipated that the cellular automata image will become a very useful vehicle for investigation into their key features, identification of their function, as well as revelation of their "fingerprint". It is anticipated that by using the concept of the pseudo amino acid composition (Chou, K.C. Proteins: Structure, Function, and Genetics, 2001, 43, 246-255), the cellular automata image approach can also be used to improve the quality of predicting protein attributes, such as structural class and subcellular location.

Contribution to the Prediction of the Fold Code: Application to Immunoglobulin and Flavodoxin Cases

PubMed Central

Banach, Mateusz; Prudhomme, Nicolas; Carpentier, Mathilde; Duprat, Elodie; Papandreou, Nikolaos; Kalinowska, Barbara; Chomilier, Jacques; Roterman, Irena

2015-01-01

Background Folding nucleus of globular proteins formation starts by the mutual interaction of a group of hydrophobic amino acids whose close contacts allow subsequent formation and stability of the 3D structure. These early steps can be predicted by simulation of the folding process through a Monte Carlo (MC) coarse grain model in a discrete space. We previously defined MIRs (Most Interacting Residues), as the set of residues presenting a large number of non-covalent neighbour interactions during such simulation. MIRs are good candidates to define the minimal number of residues giving rise to a given fold instead of another one, although their proportion is rather high, typically [15-20]% of the sequences. Having in mind experiments with two sequences of very high levels of sequence identity (up to 90%) but different folds, we combined the MIR method, which takes sequence as single input, with the “fuzzy oil drop” (FOD) model that requires a 3D structure, in order to estimate the residues coding for the fold. FOD assumes that a globular protein follows an idealised 3D Gaussian distribution of hydrophobicity density, with the maximum in the centre and minima at the surface of the “drop”. If the actual local density of hydrophobicity around a given amino acid is as high as the ideal one, then this amino acid is assigned to the core of the globular protein, and it is assumed to follow the FOD model. Therefore one obtains a distribution of the amino acids of a protein according to their agreement or rejection with the FOD model. Results We compared and combined MIR and FOD methods to define the minimal nucleus, or keystone, of two populated folds: immunoglobulin-like (Ig) and flavodoxins (Flav). The combination of these two approaches defines some positions both predicted as a MIR and assigned as accordant with the FOD model. It is shown here that for these two folds, the intersection of the predicted sets of residues significantly differs from random selection. It reduces the number of selected residues by each individual method and allows a reasonable agreement with experimentally determined key residues coding for the particular fold. In addition, the intersection of the two methods significantly increases the specificity of the prediction, providing a robust set of residues that constitute the folding nucleus. PMID:25915049

Analysis and recognition of 5′ UTR intron splice sites in human pre-mRNA

PubMed Central

Eden, E.; Brunak, S.

2004-01-01

Prediction of splice sites in non-coding regions of genes is one of the most challenging aspects of gene structure recognition. We perform a rigorous analysis of such splice sites embedded in human 5′ untranslated regions (UTRs), and investigate correlations between this class of splice sites and other features found in the adjacent exons and introns. By restricting the training of neural network algorithms to ‘pure’ UTRs (not extending partially into protein coding regions), we for the first time investigate the predictive power of the splicing signal proper, in contrast to conventional splice site prediction, which typically relies on the change in sequence at the transition from protein coding to non-coding. By doing so, the algorithms were able to pick up subtler splicing signals that were otherwise masked by ‘coding’ noise, thus enhancing significantly the prediction of 5′ UTR splice sites. For example, the non-coding splice site predicting networks pick up compositional and positional bias in the 3′ ends of non-coding exons and 5′ non-coding intron ends, where cytosine and guanine are over-represented. This compositional bias at the true UTR donor sites is also visible in the synaptic weights of the neural networks trained to identify UTR donor sites. Conventional splice site prediction methods perform poorly in UTRs because the reading frame pattern is absent. The NetUTR method presented here performs 2–3-fold better compared with NetGene2 and GenScan in 5′ UTRs. We also tested the 5′ UTR trained method on protein coding regions, and discovered, surprisingly, that it works quite well (although it cannot compete with NetGene2). This indicates that the local splicing pattern in UTRs and coding regions is largely the same. The NetUTR method is made publicly available at www.cbs.dtu.dk/services/NetUTR. PMID:14960723

Comparison of the Genome Sequence of the Poultry Pathogen Bordetella avium with Those of B. bronchiseptica, B. pertussis, and B. parapertussis Reveals Extensive Diversity in Surface Structures Associated with Host Interaction

PubMed Central

Sebaihia, Mohammed; Preston, Andrew; Maskell, Duncan J.; Kuzmiak, Holly; Connell, Terry D.; King, Natalie D.; Orndorff, Paul E.; Miyamoto, David M.; Thomson, Nicholas R.; Harris, David; Goble, Arlette; Lord, Angela; Murphy, Lee; Quail, Michael A.; Rutter, Simon; Squares, Robert; Squares, Steven; Woodward, John; Parkhill, Julian; Temple, Louise M.

2006-01-01

Bordetella avium is a pathogen of poultry and is phylogenetically distinct from Bordetella bronchiseptica, Bordetella pertussis, and Bordetella parapertussis, which are other species in the Bordetella genus that infect mammals. In order to understand the evolutionary relatedness of Bordetella species and further the understanding of pathogenesis, we obtained the complete genome sequence of B. avium strain 197N, a pathogenic strain that has been extensively studied. With 3,732,255 base pairs of DNA and 3,417 predicted coding sequences, it has the smallest genome and gene complement of the sequenced bordetellae. In this study, the presence or absence of previously reported virulence factors from B. avium was confirmed, and the genetic bases for growth characteristics were elucidated. Over 1,100 genes present in B. avium but not in B. bronchiseptica were identified, and most were predicted to encode surface or secreted proteins that are likely to define an organism adapted to the avian rather than the mammalian respiratory tracts. These include genes coding for the synthesis of a polysaccharide capsule, hemagglutinins, a type I secretion system adjacent to two very large genes for secreted proteins, and unique genes for both lipopolysaccharide and fimbrial biogenesis. Three apparently complete prophages are also present. The BvgAS virulence regulatory system appears to have polymorphisms at a poly(C) tract that is involved in phase variation in other bordetellae. A number of putative iron-regulated outer membrane proteins were predicted from the sequence, and this regulation was confirmed experimentally for five of these. PMID:16885469

Complete genome sequence of Cupriavidus basilensis 4G11, isolated from the Oak Ridge Field Research Center site

DOE PAGES

Ray, Jayashree; Waters, R. Jordan; Skerker, Jeffrey M.; ...

2015-05-14

Cupriavidus basilensis 4G11 was isolated from groundwater at the Oak Ridge Field Research Center (FRC) site. Here, we report the complete genome sequence and annotation of Cupriavidus basilensis 4G11. The genome contains 8,421,483 bp, 7,661 predicted protein-coding genes, and a total GC content of 64.4%.

Draft Genome Sequence of a Novel Chitinophaga sp. Strain, MD30, Isolated from a Biofilm in an Air Conditioner Condensate Pipe.

PubMed

Wan, Xuehua; Darris, Maxwell; Hou, Shaobin; Donachie, Stuart P

2017-10-19

Most of the 24 known Chitinophaga species were originally isolated from soils. We report the draft genome sequence of a putatively novel Chitinophaga sp. from a biofilm in an air conditioner condensate pipe. The genome comprises 7,661,303 bp in one scaffold, 5,694 predicted protein-coding sequences, and a G+C content of 47.6%. Copyright © 2017 Wan et al.

MINS2: revisiting the molecular code for transmembrane-helix recognition by the Sec61 translocon.

PubMed

Park, Yungki; Helms, Volkhard

2008-08-15

To be fully functional, membrane proteins should not only fold, but also get inserted into the membrane, which is mediated by the Sec61 translocon. Recent experimental studies have attempted to elucidate how the Sec61 translocon accomplishes this delicate task by measuring the translocon-mediated membrane insertion free energies of 357 systematically designed peptides. On the basis of this data set, we have developed MINS2, a novel sequence-based computational method for predicting the membrane insertion free energies of protein sequences. A benchmark analysis of MINS2 shows that MINS2 signi.cantly outperforms previously proposed methods. Importantly, the application of MINS2 to known membrane protein structures shows that a better prediction of membrane insertion free energies does not lead to a better prediction of transmembrane segments of polytopic membrane proteins. A web server for MINS2 is publicly available at http://service.bioinformatik.uni-saarland.de/mins. Supplementary data are available at Bioinformatics online.

RNAcode: Robust discrimination of coding and noncoding regions in comparative sequence data

PubMed Central

Washietl, Stefan; Findeiß, Sven; Müller, Stephan A.; Kalkhof, Stefan; von Bergen, Martin; Hofacker, Ivo L.; Stadler, Peter F.; Goldman, Nick

2011-01-01

With the availability of genome-wide transcription data and massive comparative sequencing, the discrimination of coding from noncoding RNAs and the assessment of coding potential in evolutionarily conserved regions arose as a core analysis task. Here we present RNAcode, a program to detect coding regions in multiple sequence alignments that is optimized for emerging applications not covered by current protein gene-finding software. Our algorithm combines information from nucleotide substitution and gap patterns in a unified framework and also deals with real-life issues such as alignment and sequencing errors. It uses an explicit statistical model with no machine learning component and can therefore be applied “out of the box,” without any training, to data from all domains of life. We describe the RNAcode method and apply it in combination with mass spectrometry experiments to predict and confirm seven novel short peptides in Escherichia coli and to analyze the coding potential of RNAs previously annotated as “noncoding.” RNAcode is open source software and available for all major platforms at http://wash.github.com/rnacode. PMID:21357752

RNAcode: robust discrimination of coding and noncoding regions in comparative sequence data.

PubMed

Washietl, Stefan; Findeiss, Sven; Müller, Stephan A; Kalkhof, Stefan; von Bergen, Martin; Hofacker, Ivo L; Stadler, Peter F; Goldman, Nick

2011-04-01

With the availability of genome-wide transcription data and massive comparative sequencing, the discrimination of coding from noncoding RNAs and the assessment of coding potential in evolutionarily conserved regions arose as a core analysis task. Here we present RNAcode, a program to detect coding regions in multiple sequence alignments that is optimized for emerging applications not covered by current protein gene-finding software. Our algorithm combines information from nucleotide substitution and gap patterns in a unified framework and also deals with real-life issues such as alignment and sequencing errors. It uses an explicit statistical model with no machine learning component and can therefore be applied "out of the box," without any training, to data from all domains of life. We describe the RNAcode method and apply it in combination with mass spectrometry experiments to predict and confirm seven novel short peptides in Escherichia coli and to analyze the coding potential of RNAs previously annotated as "noncoding." RNAcode is open source software and available for all major platforms at http://wash.github.com/rnacode.

N-terminal Proteomics Assisted Profiling of the Unexplored Translation Initiation Landscape in Arabidopsis thaliana *

PubMed Central

Ndah, Elvis; Jonckheere, Veronique

2017-01-01

Proteogenomics is an emerging research field yet lacking a uniform method of analysis. Proteogenomic studies in which N-terminal proteomics and ribosome profiling are combined, suggest that a high number of protein start sites are currently missing in genome annotations. We constructed a proteogenomic pipeline specific for the analysis of N-terminal proteomics data, with the aim of discovering novel translational start sites outside annotated protein coding regions. In summary, unidentified MS/MS spectra were matched to a specific N-terminal peptide library encompassing protein N termini encoded in the Arabidopsis thaliana genome. After a stringent false discovery rate filtering, 117 protein N termini compliant with N-terminal methionine excision specificity and indicative of translation initiation were found. These include N-terminal protein extensions and translation from transposable elements and pseudogenes. Gene prediction provided supporting protein-coding models for approximately half of the protein N termini. Besides the prediction of functional domains (partially) contained within the newly predicted ORFs, further supporting evidence of translation was found in the recently released Araport11 genome re-annotation of Arabidopsis and computational translations of sequences stored in public repositories. Most interestingly, complementary evidence by ribosome profiling was found for 23 protein N termini. Finally, by analyzing protein N-terminal peptides, an in silico analysis demonstrates the applicability of our N-terminal proteogenomics strategy in revealing protein-coding potential in species with well- and poorly-annotated genomes. PMID:28432195

N-terminal Proteomics Assisted Profiling of the Unexplored Translation Initiation Landscape in Arabidopsis thaliana.

PubMed

Willems, Patrick; Ndah, Elvis; Jonckheere, Veronique; Stael, Simon; Sticker, Adriaan; Martens, Lennart; Van Breusegem, Frank; Gevaert, Kris; Van Damme, Petra

2017-06-01

Proteogenomics is an emerging research field yet lacking a uniform method of analysis. Proteogenomic studies in which N-terminal proteomics and ribosome profiling are combined, suggest that a high number of protein start sites are currently missing in genome annotations. We constructed a proteogenomic pipeline specific for the analysis of N-terminal proteomics data, with the aim of discovering novel translational start sites outside annotated protein coding regions. In summary, unidentified MS/MS spectra were matched to a specific N-terminal peptide library encompassing protein N termini encoded in the Arabidopsis thaliana genome. After a stringent false discovery rate filtering, 117 protein N termini compliant with N-terminal methionine excision specificity and indicative of translation initiation were found. These include N-terminal protein extensions and translation from transposable elements and pseudogenes. Gene prediction provided supporting protein-coding models for approximately half of the protein N termini. Besides the prediction of functional domains (partially) contained within the newly predicted ORFs, further supporting evidence of translation was found in the recently released Araport11 genome re-annotation of Arabidopsis and computational translations of sequences stored in public repositories. Most interestingly, complementary evidence by ribosome profiling was found for 23 protein N termini. Finally, by analyzing protein N-terminal peptides, an in silico analysis demonstrates the applicability of our N-terminal proteogenomics strategy in revealing protein-coding potential in species with well- and poorly-annotated genomes. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Meta4: a web application for sharing and annotating metagenomic gene predictions using web services.

PubMed

Richardson, Emily J; Escalettes, Franck; Fotheringham, Ian; Wallace, Robert J; Watson, Mick

2013-01-01

Whole-genome shotgun metagenomics experiments produce DNA sequence data from entire ecosystems, and provide a huge amount of novel information. Gene discovery projects require up-to-date information about sequence homology and domain structure for millions of predicted proteins to be presented in a simple, easy-to-use system. There is a lack of simple, open, flexible tools that allow the rapid sharing of metagenomics datasets with collaborators in a format they can easily interrogate. We present Meta4, a flexible and extensible web application that can be used to share and annotate metagenomic gene predictions. Proteins and predicted domains are stored in a simple relational database, with a dynamic front-end which displays the results in an internet browser. Web services are used to provide up-to-date information about the proteins from homology searches against public databases. Information about Meta4 can be found on the project website, code is available on Github, a cloud image is available, and an example implementation can be seen at.

GuiTope: an application for mapping random-sequence peptides to protein sequences.

PubMed

Halperin, Rebecca F; Stafford, Phillip; Emery, Jack S; Navalkar, Krupa Arun; Johnston, Stephen Albert

2012-01-03

Random-sequence peptide libraries are a commonly used tool to identify novel ligands for binding antibodies, other proteins, and small molecules. It is often of interest to compare the selected peptide sequences to the natural protein binding partners to infer the exact binding site or the importance of particular residues. The ability to search a set of sequences for similarity to a set of peptides may sometimes enable the prediction of an antibody epitope or a novel binding partner. We have developed a software application designed specifically for this task. GuiTope provides a graphical user interface for aligning peptide sequences to protein sequences. All alignment parameters are accessible to the user including the ability to specify the amino acid frequency in the peptide library; these frequencies often differ significantly from those assumed by popular alignment programs. It also includes a novel feature to align di-peptide inversions, which we have found improves the accuracy of antibody epitope prediction from peptide microarray data and shows utility in analyzing phage display datasets. Finally, GuiTope can randomly select peptides from a given library to estimate a null distribution of scores and calculate statistical significance. GuiTope provides a convenient method for comparing selected peptide sequences to protein sequences, including flexible alignment parameters, novel alignment features, ability to search a database, and statistical significance of results. The software is available as an executable (for PC) at http://www.immunosignature.com/software and ongoing updates and source code will be available at sourceforge.net.

GenoMycDB: a database for comparative analysis of mycobacterial genes and genomes.

PubMed

Catanho, Marcos; Mascarenhas, Daniel; Degrave, Wim; Miranda, Antonio Basílio de

2006-03-31

Several databases and computational tools have been created with the aim of organizing, integrating and analyzing the wealth of information generated by large-scale sequencing projects of mycobacterial genomes and those of other organisms. However, with very few exceptions, these databases and tools do not allow for massive and/or dynamic comparison of these data. GenoMycDB (http://www.dbbm.fiocruz.br/GenoMycDB) is a relational database built for large-scale comparative analyses of completely sequenced mycobacterial genomes, based on their predicted protein content. Its central structure is composed of the results obtained after pair-wise sequence alignments among all the predicted proteins coded by the genomes of six mycobacteria: Mycobacterium tuberculosis (strains H37Rv and CDC1551), M. bovis AF2122/97, M. avium subsp. paratuberculosis K10, M. leprae TN, and M. smegmatis MC2 155. The database stores the computed similarity parameters of every aligned pair, providing for each protein sequence the predicted subcellular localization, the assigned cluster of orthologous groups, the features of the corresponding gene, and links to several important databases. Tables containing pairs or groups of potential homologs between selected species/strains can be produced dynamically by user-defined criteria, based on one or multiple sequence similarity parameters. In addition, searches can be restricted according to the predicted subcellular localization of the protein, the DNA strand of the corresponding gene and/or the description of the protein. Massive data search and/or retrieval are available, and different ways of exporting the result are offered. GenoMycDB provides an on-line resource for the functional classification of mycobacterial proteins as well as for the analysis of genome structure, organization, and evolution.

Complete mitochondrial genome of Taharana fasciana (Insecta, Hemiptera: Cicadellidae) and comparison with other Cicadellidae insects.

PubMed

Wang, Jiajia; Li, Hu; Dai, Renhuai

2017-12-01

Here, we describe the first complete mitochondrial genome (mitogenome) sequence of the leafhopper Taharana fasciana (Coelidiinae). The mitogenome sequence contains 15,161 bp with an A + T content of 77.9%. It includes 13 protein-coding genes, two ribosomal RNA genes, 22 transfer RNA genes, and one non-coding (A + T-rich) region; in addition, a repeat region is also present (GenBank accession no. KY886913). These genes/regions are in the same order as in the inferred insect ancestral mitogenome. All protein-coding genes have ATN as the start codon, and TAA or single T as the stop codons, except the gene ND3, which ends with TAG. Furthermore, we predicted the secondary structures of the rRNAs in T. fasciana. Six domains (domain III is absent in arthropods) and 41 helices were predicted for 16S rRNA, and 12S rRNA comprised three structural domains and 24 helices. Phylogenetic tree analysis confirmed that T. fasciana and other members of the Cicadellidae are clustered into a clade, and it identified the relationships among the subfamilies Deltocephalinae, Coelidiinae, Idiocerinae, Cicadellinae, and Typhlocybinae.

Identification and correction of abnormal, incomplete and mispredicted proteins in public databases.

PubMed

Nagy, Alinda; Hegyi, Hédi; Farkas, Krisztina; Tordai, Hedvig; Kozma, Evelin; Bányai, László; Patthy, László

2008-08-27

Despite significant improvements in computational annotation of genomes, sequences of abnormal, incomplete or incorrectly predicted genes and proteins remain abundant in public databases. Since the majority of incomplete, abnormal or mispredicted entries are not annotated as such, these errors seriously affect the reliability of these databases. Here we describe the MisPred approach that may provide an efficient means for the quality control of databases. The current version of the MisPred approach uses five distinct routines for identifying abnormal, incomplete or mispredicted entries based on the principle that a sequence is likely to be incorrect if some of its features conflict with our current knowledge about protein-coding genes and proteins: (i) conflict between the predicted subcellular localization of proteins and the absence of the corresponding sequence signals; (ii) presence of extracellular and cytoplasmic domains and the absence of transmembrane segments; (iii) co-occurrence of extracellular and nuclear domains; (iv) violation of domain integrity; (v) chimeras encoded by two or more genes located on different chromosomes. Analyses of predicted EnsEMBL protein sequences of nine deuterostome (Homo sapiens, Mus musculus, Rattus norvegicus, Monodelphis domestica, Gallus gallus, Xenopus tropicalis, Fugu rubripes, Danio rerio and Ciona intestinalis) and two protostome species (Caenorhabditis elegans and Drosophila melanogaster) have revealed that the absence of expected signal peptides and violation of domain integrity account for the majority of mispredictions. Analyses of sequences predicted by NCBI's GNOMON annotation pipeline show that the rates of mispredictions are comparable to those of EnsEMBL. Interestingly, even the manually curated UniProtKB/Swiss-Prot dataset is contaminated with mispredicted or abnormal proteins, although to a much lesser extent than UniProtKB/TrEMBL or the EnsEMBL or GNOMON-predicted entries. MisPred works efficiently in identifying errors in predictions generated by the most reliable gene prediction tools such as the EnsEMBL and NCBI's GNOMON pipelines and also guides the correction of errors. We suggest that application of the MisPred approach will significantly improve the quality of gene predictions and the associated databases.

Draft Genome Sequence of the Terrestrial Cyanobacterium Scytonema millei VB511283, Isolated from Eastern India

PubMed Central

Sen, Diya; Chandrababunaidu, Mathu Malar; Singh, Deeksha; Sanghi, Neha; Ghorai, Arpita; Mishra, Gyan Prakash; Madduluri, Madhavi

2015-01-01

We report here the draft genome sequence of Scytonema millei VB511283, a cyanobacterium isolated from biofilms on the exterior of stone monuments in Santiniketan, eastern India. The draft genome is 11,627,246 bp long (11.63 Mb), with 118 scaffolds. About 9,011 protein-coding genes, 117 tRNAs, and 12 rRNAs are predicted from this assembly. PMID:25744984

Genome Sequence of Legionella massiliensis, Isolated from a Cooling Tower Water Sample.

PubMed

Pagnier, Isabelle; Croce, Olivier; Robert, Catherine; Raoult, Didier; La Scola, Bernard

2014-10-16

We present the draft genome sequence of Legionella massiliensis strain LegA(T), recovered from a cooling tower water sample, using an amoebal coculture procedure. The strain described here is composed of 4,387,007 bp, with a G+C content of 41.19%, and its genome has 3,767 protein-coding genes and 60 predicted RNA genes. Copyright © 2014 Pagnier et al.

Position specific variation in the rate of evolution in transcription factor binding sites

PubMed Central

Moses, Alan M; Chiang, Derek Y; Kellis, Manolis; Lander, Eric S; Eisen, Michael B

2003-01-01

Background The binding sites of sequence specific transcription factors are an important and relatively well-understood class of functional non-coding DNAs. Although a wide variety of experimental and computational methods have been developed to characterize transcription factor binding sites, they remain difficult to identify. Comparison of non-coding DNA from related species has shown considerable promise in identifying these functional non-coding sequences, even though relatively little is known about their evolution. Results Here we analyse the genome sequences of the budding yeasts Saccharomyces cerevisiae, S. bayanus, S. paradoxus and S. mikatae to study the evolution of transcription factor binding sites. As expected, we find that both experimentally characterized and computationally predicted binding sites evolve slower than surrounding sequence, consistent with the hypothesis that they are under purifying selection. We also observe position-specific variation in the rate of evolution within binding sites. We find that the position-specific rate of evolution is positively correlated with degeneracy among binding sites within S. cerevisiae. We test theoretical predictions for the rate of evolution at positions where the base frequencies deviate from background due to purifying selection and find reasonable agreement with the observed rates of evolution. Finally, we show how the evolutionary characteristics of real binding motifs can be used to distinguish them from artefacts of computational motif finding algorithms. Conclusion As has been observed for protein sequences, the rate of evolution in transcription factor binding sites varies with position, suggesting that some regions are under stronger functional constraint than others. This variation likely reflects the varying importance of different positions in the formation of the protein-DNA complex. The characterization of the pattern of evolution in known binding sites will likely contribute to the effective use of comparative sequence data in the identification of transcription factor binding sites and is an important step toward understanding the evolution of functional non-coding DNA. PMID:12946282

Tissue-specific Proteogenomic Analysis of Plutella xylostella Larval Midgut Using a Multialgorithm Pipeline.

PubMed

Zhu, Xun; Xie, Shangbo; Armengaud, Jean; Xie, Wen; Guo, Zhaojiang; Kang, Shi; Wu, Qingjun; Wang, Shaoli; Xia, Jixing; He, Rongjun; Zhang, Youjun

2016-06-01

The diamondback moth, Plutella xylostella (L.), is the major cosmopolitan pest of brassica and other cruciferous crops. Its larval midgut is a dynamic tissue that interfaces with a wide variety of toxicological and physiological processes. The draft sequence of the P. xylostella genome was recently released, but its annotation remains challenging because of the low sequence coverage of this branch of life and the poor description of exon/intron splicing rules for these insects. Peptide sequencing by computational assignment of tandem mass spectra to genome sequence information provides an experimental independent approach for confirming or refuting protein predictions, a concept that has been termed proteogenomics. In this study, we carried out an in-depth proteogenomic analysis to complement genome annotation of P. xylostella larval midgut based on shotgun HPLC-ESI-MS/MS data by means of a multialgorithm pipeline. A total of 876,341 tandem mass spectra were searched against the predicted P. xylostella protein sequences and a whole-genome six-frame translation database. Based on a data set comprising 2694 novel genome search specific peptides, we discovered 439 novel protein-coding genes and corrected 128 existing gene models. To get the most accurate data to seed further insect genome annotation, more than half of the novel protein-coding genes, i.e. 235 over 439, were further validated after RT-PCR amplification and sequencing of the corresponding transcripts. Furthermore, we validated 53 novel alternative splicings. Finally, a total of 6764 proteins were identified, resulting in one of the most comprehensive proteogenomic study of a nonmodel animal. As the first tissue-specific proteogenomics analysis of P. xylostella, this study provides the fundamental basis for high-throughput proteomics and functional genomics approaches aimed at deciphering the molecular mechanisms of resistance and controlling this pest. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Protein functional features are reflected in the patterns of mRNA translation speed.

PubMed

López, Daniel; Pazos, Florencio

2015-07-09

The degeneracy of the genetic code makes it possible for the same amino acid string to be coded by different messenger RNA (mRNA) sequences. These "synonymous mRNAs" may differ largely in a number of aspects related to their overall translational efficiency, such as secondary structure content and availability of the encoded transfer RNAs (tRNAs). Consequently, they may render different yields of the translated polypeptides. These mRNA features related to translation efficiency are also playing a role locally, resulting in a non-uniform translation speed along the mRNA, which has been previously related to some protein structural features and also used to explain some dramatic effects of "silent" single-nucleotide-polymorphisms (SNPs). In this work we perform the first large scale analysis of the relationship between three experimental proxies of mRNA local translation efficiency and the local features of the corresponding encoded proteins. We found that a number of protein functional and structural features are reflected in the patterns of ribosome occupancy, secondary structure and tRNA availability along the mRNA. One or more of these proxies of translation speed have distinctive patterns around the mRNA regions coding for certain protein local features. In some cases the three patterns follow a similar trend. We also show specific examples where these patterns of translation speed point to the protein's important structural and functional features. This support the idea that the genome not only codes the protein functional features as sequences of amino acids, but also as subtle patterns of mRNA properties which, probably through local effects on the translation speed, have some consequence on the final polypeptide. These results open the possibility of predicting a protein's functional regions based on a single genomic sequence, and have implications for heterologous protein expression and fine-tuning protein function.

Chromosome preference of disease genes and vectorization for the prediction of non-coding disease genes.

PubMed

Peng, Hui; Lan, Chaowang; Liu, Yuansheng; Liu, Tao; Blumenstein, Michael; Li, Jinyan

2017-10-03

Disease-related protein-coding genes have been widely studied, but disease-related non-coding genes remain largely unknown. This work introduces a new vector to represent diseases, and applies the newly vectorized data for a positive-unlabeled learning algorithm to predict and rank disease-related long non-coding RNA (lncRNA) genes. This novel vector representation for diseases consists of two sub-vectors, one is composed of 45 elements, characterizing the information entropies of the disease genes distribution over 45 chromosome substructures. This idea is supported by our observation that some substructures (e.g., the chromosome 6 p-arm) are highly preferred by disease-related protein coding genes, while some (e.g., the 21 p-arm) are not favored at all. The second sub-vector is 30-dimensional, characterizing the distribution of disease gene enriched KEGG pathways in comparison with our manually created pathway groups. The second sub-vector complements with the first one to differentiate between various diseases. Our prediction method outperforms the state-of-the-art methods on benchmark datasets for prioritizing disease related lncRNA genes. The method also works well when only the sequence information of an lncRNA gene is known, or even when a given disease has no currently recognized long non-coding genes.

Chromosome preference of disease genes and vectorization for the prediction of non-coding disease genes

PubMed Central

Peng, Hui; Lan, Chaowang; Liu, Yuansheng; Liu, Tao; Blumenstein, Michael; Li, Jinyan

2017-01-01

Disease-related protein-coding genes have been widely studied, but disease-related non-coding genes remain largely unknown. This work introduces a new vector to represent diseases, and applies the newly vectorized data for a positive-unlabeled learning algorithm to predict and rank disease-related long non-coding RNA (lncRNA) genes. This novel vector representation for diseases consists of two sub-vectors, one is composed of 45 elements, characterizing the information entropies of the disease genes distribution over 45 chromosome substructures. This idea is supported by our observation that some substructures (e.g., the chromosome 6 p-arm) are highly preferred by disease-related protein coding genes, while some (e.g., the 21 p-arm) are not favored at all. The second sub-vector is 30-dimensional, characterizing the distribution of disease gene enriched KEGG pathways in comparison with our manually created pathway groups. The second sub-vector complements with the first one to differentiate between various diseases. Our prediction method outperforms the state-of-the-art methods on benchmark datasets for prioritizing disease related lncRNA genes. The method also works well when only the sequence information of an lncRNA gene is known, or even when a given disease has no currently recognized long non-coding genes. PMID:29108274

Different evolutionary patterns of SNPs between domains and unassigned regions in human protein-coding sequences.

PubMed

Pang, Erli; Wu, Xiaomei; Lin, Kui

2016-06-01

Protein evolution plays an important role in the evolution of each genome. Because of their functional nature, in general, most of their parts or sites are differently constrained selectively, particularly by purifying selection. Most previous studies on protein evolution considered individual proteins in their entirety or compared protein-coding sequences with non-coding sequences. Less attention has been paid to the evolution of different parts within each protein of a given genome. To this end, based on PfamA annotation of all human proteins, each protein sequence can be split into two parts: domains or unassigned regions. Using this rationale, single nucleotide polymorphisms (SNPs) in protein-coding sequences from the 1000 Genomes Project were mapped according to two classifications: SNPs occurring within protein domains and those within unassigned regions. With these classifications, we found: the density of synonymous SNPs within domains is significantly greater than that of synonymous SNPs within unassigned regions; however, the density of non-synonymous SNPs shows the opposite pattern. We also found there are signatures of purifying selection on both the domain and unassigned regions. Furthermore, the selective strength on domains is significantly greater than that on unassigned regions. In addition, among all of the human protein sequences, there are 117 PfamA domains in which no SNPs are found. Our results highlight an important aspect of protein domains and may contribute to our understanding of protein evolution.

The Number, Organization, and Size of Polymorphic Membrane Protein Coding Sequences as well as the Most Conserved Pmp Protein Differ within and across Chlamydia Species.

PubMed

Van Lent, Sarah; Creasy, Heather Huot; Myers, Garry S A; Vanrompay, Daisy

2016-01-01

Variation is a central trait of the polymorphic membrane protein (Pmp) family. The number of pmp coding sequences differs between Chlamydia species, but it is unknown whether the number of pmp coding sequences is constant within a Chlamydia species. The level of conservation of the Pmp proteins has previously only been determined for Chlamydia trachomatis. As different Pmp proteins might be indispensible for the pathogenesis of different Chlamydia species, this study investigated the conservation of Pmp proteins both within and across C. trachomatis,C. pneumoniae,C. abortus, and C. psittaci. The pmp coding sequences were annotated in 16 C. trachomatis, 6 C. pneumoniae, 2 C. abortus, and 16 C. psittaci genomes. The number and organization of polymorphic membrane coding sequences differed within and across the analyzed Chlamydia species. The length of coding sequences of pmpA,pmpB, and pmpH was conserved among all analyzed genomes, while the length of pmpE/F and pmpG, and remarkably also of the subtype pmpD, differed among the analyzed genomes. PmpD, PmpA, PmpH, and PmpA were the most conserved Pmp in C. trachomatis,C. pneumoniae,C. abortus, and C. psittaci, respectively. PmpB was the most conserved Pmp across the 4 analyzed Chlamydia species. © 2016 S. Karger AG, Basel.

Correlation approach to identify coding regions in DNA sequences

NASA Technical Reports Server (NTRS)

Ossadnik, S. M.; Buldyrev, S. V.; Goldberger, A. L.; Havlin, S.; Mantegna, R. N.; Peng, C. K.; Simons, M.; Stanley, H. E.

1994-01-01

Recently, it was observed that noncoding regions of DNA sequences possess long-range power-law correlations, whereas coding regions typically display only short-range correlations. We develop an algorithm based on this finding that enables investigators to perform a statistical analysis on long DNA sequences to locate possible coding regions. The algorithm is particularly successful in predicting the location of lengthy coding regions. For example, for the complete genome of yeast chromosome III (315,344 nucleotides), at least 82% of the predictions correspond to putative coding regions; the algorithm correctly identified all coding regions larger than 3000 nucleotides, 92% of coding regions between 2000 and 3000 nucleotides long, and 79% of coding regions between 1000 and 2000 nucleotides. The predictive ability of this new algorithm supports the claim that there is a fundamental difference in the correlation property between coding and noncoding sequences. This algorithm, which is not species-dependent, can be implemented with other techniques for rapidly and accurately locating relatively long coding regions in genomic sequences.

Genome-wide computational identification of microRNAs and their targets in the deep-branching eukaryote Giardia lamblia.

PubMed

Zhang, Yan-Qiong; Chen, Dong-Liang; Tian, Hai-Feng; Zhang, Bao-Hong; Wen, Jian-Fan

2009-10-01

Using a combined computational program, we identified 50 potential microRNAs (miRNAs) in Giardia lamblia, one of the most primitive unicellular eukaryotes. These miRNAs are unique to G. lamblia and no homologues have been found in other organisms; miRNAs, currently known in other species, were not found in G. lamblia. This suggests that miRNA biogenesis and miRNA-mediated gene regulation pathway may evolve independently, especially in evolutionarily distant lineages. A majority (43) of the predicted miRNAs are located at one single locus; however, some miRNAs have two or more copies in the genome. Among the 58 miRNA genes, 28 are located in the intergenic regions whereas 30 are present in the anti-sense strands of the protein-coding sequences. Five predicted miRNAs are expressed in G. lamblia trophozoite cells evidenced by expressed sequence tags or RT-PCR. Thirty-seven identified miRNAs may target 50 protein-coding genes, including seven variant-specific surface proteins (VSPs). Our findings provide a clue that miRNA-mediated gene regulation may exist in the early stage of eukaryotic evolution, suggesting that it is an important regulation system ubiquitous in eukaryotes.

lncRScan-SVM: A Tool for Predicting Long Non-Coding RNAs Using Support Vector Machine.

PubMed

Sun, Lei; Liu, Hui; Zhang, Lin; Meng, Jia

2015-01-01

Functional long non-coding RNAs (lncRNAs) have been bringing novel insight into biological study, however it is still not trivial to accurately distinguish the lncRNA transcripts (LNCTs) from the protein coding ones (PCTs). As various information and data about lncRNAs are preserved by previous studies, it is appealing to develop novel methods to identify the lncRNAs more accurately. Our method lncRScan-SVM aims at classifying PCTs and LNCTs using support vector machine (SVM). The gold-standard datasets for lncRScan-SVM model training, lncRNA prediction and method comparison were constructed according to the GENCODE gene annotations of human and mouse respectively. By integrating features derived from gene structure, transcript sequence, potential codon sequence and conservation, lncRScan-SVM outperforms other approaches, which is evaluated by several criteria such as sensitivity, specificity, accuracy, Matthews correlation coefficient (MCC) and area under curve (AUC). In addition, several known human lncRNA datasets were assessed using lncRScan-SVM. LncRScan-SVM is an efficient tool for predicting the lncRNAs, and it is quite useful for current lncRNA study.

TCOF1 gene encodes a putative nucleolar phosphoprotein that exhibits mutations in Treacher Collins Syndrome throughout its coding region

PubMed Central

Wise, Carol A.; Chiang, Lydia C.; Paznekas, William A.; Sharma, Mridula; Musy, Maurice M.; Ashley, Jennifer A.; Lovett, Michael; Jabs, Ethylin W.

1997-01-01

Treacher Collins Syndrome (TCS) is the most common of the human mandibulofacial dysostosis disorders. Recently, a partial TCOF1 cDNA was identified and shown to contain mutations in TCS families. Here we present the entire exon/intron genomic structure and the complete coding sequence of TCOF1. TCOF1 encodes a low complexity protein of 1,411 amino acids, whose predicted protein structure reveals repeated motifs that mirror the organization of its exons. These motifs are shared with nucleolar trafficking proteins in other species and are predicted to be highly phosphorylated by casein kinase. Consistent with this, the full-length TCOF1 protein sequence also contains putative nuclear and nucleolar localization signals. Throughout the open reading frame, we detected an additional eight mutations in TCS families and several polymorphisms. We postulate that TCS results from defects in a nucleolar trafficking protein that is critically required during human craniofacial development. PMID:9096354

Evaluating the protein coding potential of exonized transposable element sequences

PubMed Central

Piriyapongsa, Jittima; Rutledge, Mark T; Patel, Sanil; Borodovsky, Mark; Jordan, I King

2007-01-01

Background Transposable element (TE) sequences, once thought to be merely selfish or parasitic members of the genomic community, have been shown to contribute a wide variety of functional sequences to their host genomes. Analysis of complete genome sequences have turned up numerous cases where TE sequences have been incorporated as exons into mRNAs, and it is widely assumed that such 'exonized' TEs encode protein sequences. However, the extent to which TE-derived sequences actually encode proteins is unknown and a matter of some controversy. We have tried to address this outstanding issue from two perspectives: i-by evaluating ascertainment biases related to the search methods used to uncover TE-derived protein coding sequences (CDS) and ii-through a probabilistic codon-frequency based analysis of the protein coding potential of TE-derived exons. Results We compared the ability of three classes of sequence similarity search methods to detect TE-derived sequences among data sets of experimentally characterized proteins: 1-a profile-based hidden Markov model (HMM) approach, 2-BLAST methods and 3-RepeatMasker. Profile based methods are more sensitive and more selective than the other methods evaluated. However, the application of profile-based search methods to the detection of TE-derived sequences among well-curated experimentally characterized protein data sets did not turn up many more cases than had been previously detected and nowhere near as many cases as recent genome-wide searches have. We observed that the different search methods used were complementary in the sense that they yielded largely non-overlapping sets of hits and differed in their ability to recover known cases of TE-derived CDS. The probabilistic analysis of TE-derived exon sequences indicates that these sequences have low protein coding potential on average. In particular, non-autonomous TEs that do not encode protein sequences, such as Alu elements, are frequently exonized but unlikely to encode protein sequences. Conclusion The exaptation of the numerous TE sequences found in exons as bona fide protein coding sequences may prove to be far less common than has been suggested by the analysis of complete genomes. We hypothesize that many exonized TE sequences actually function as post-transcriptional regulators of gene expression, rather than coding sequences, which may act through a variety of double stranded RNA related regulatory pathways. Indeed, their relatively high copy numbers and similarity to sequences dispersed throughout the genome suggests that exonized TE sequences could serve as master regulators with a wide scope of regulatory influence. Reviewers: This article was reviewed by Itai Yanai, Kateryna D. Makova, Melissa Wilson (nominated by Kateryna D. Makova) and Cedric Feschotte (nominated by John M. Logsdon Jr.). PMID:18036258

Draft Genome Sequence of the Terrestrial Cyanobacterium Scytonema millei VB511283, Isolated from Eastern India.

PubMed

Sen, Diya; Chandrababunaidu, Mathu Malar; Singh, Deeksha; Sanghi, Neha; Ghorai, Arpita; Mishra, Gyan Prakash; Madduluri, Madhavi; Adhikary, Siba Prasad; Tripathy, Sucheta

2015-03-05

We report here the draft genome sequence of Scytonema millei VB511283, a cyanobacterium isolated from biofilms on the exterior of stone monuments in Santiniketan, eastern India. The draft genome is 11,627,246 bp long (11.63 Mb), with 118 scaffolds. About 9,011 protein-coding genes, 117 tRNAs, and 12 rRNAs are predicted from this assembly. Copyright © 2015 Sen et al.

From sequence to enzyme mechanism using multi-label machine learning.

PubMed

De Ferrari, Luna; Mitchell, John B O

2014-05-19

In this work we predict enzyme function at the level of chemical mechanism, providing a finer granularity of annotation than traditional Enzyme Commission (EC) classes. Hence we can predict not only whether a putative enzyme in a newly sequenced organism has the potential to perform a certain reaction, but how the reaction is performed, using which cofactors and with susceptibility to which drugs or inhibitors, details with important consequences for drug and enzyme design. Work that predicts enzyme catalytic activity based on 3D protein structure features limits the prediction of mechanism to proteins already having either a solved structure or a close relative suitable for homology modelling. In this study, we evaluate whether sequence identity, InterPro or Catalytic Site Atlas sequence signatures provide enough information for bulk prediction of enzyme mechanism. By splitting MACiE (Mechanism, Annotation and Classification in Enzymes database) mechanism labels to a finer granularity, which includes the role of the protein chain in the overall enzyme complex, the method can predict at 96% accuracy (and 96% micro-averaged precision, 99.9% macro-averaged recall) the MACiE mechanism definitions of 248 proteins available in the MACiE, EzCatDb (Database of Enzyme Catalytic Mechanisms) and SFLD (Structure Function Linkage Database) databases using an off-the-shelf K-Nearest Neighbours multi-label algorithm. We find that InterPro signatures are critical for accurate prediction of enzyme mechanism. We also find that incorporating Catalytic Site Atlas attributes does not seem to provide additional accuracy. The software code (ml2db), data and results are available online at http://sourceforge.net/projects/ml2db/ and as supplementary files.

Lineage-Specific Biology Revealed by a Finished Genome Assembly of the Mouse

PubMed Central

Hillier, LaDeana W.; Zody, Michael C.; Goldstein, Steve; She, Xinwe; Bult, Carol J.; Agarwala, Richa; Cherry, Joshua L.; DiCuccio, Michael; Hlavina, Wratko; Kapustin, Yuri; Meric, Peter; Maglott, Donna; Birtle, Zoë; Marques, Ana C.; Graves, Tina; Zhou, Shiguo; Teague, Brian; Potamousis, Konstantinos; Churas, Christopher; Place, Michael; Herschleb, Jill; Runnheim, Ron; Forrest, Daniel; Amos-Landgraf, James; Schwartz, David C.; Cheng, Ze; Lindblad-Toh, Kerstin; Eichler, Evan E.; Ponting, Chris P.

2009-01-01

The mouse (Mus musculus) is the premier animal model for understanding human disease and development. Here we show that a comprehensive understanding of mouse biology is only possible with the availability of a finished, high-quality genome assembly. The finished clone-based assembly of the mouse strain C57BL/6J reported here has over 175,000 fewer gaps and over 139 Mb more of novel sequence, compared with the earlier MGSCv3 draft genome assembly. In a comprehensive analysis of this revised genome sequence, we are now able to define 20,210 protein-coding genes, over a thousand more than predicted in the human genome (19,042 genes). In addition, we identified 439 long, non–protein-coding RNAs with evidence for transcribed orthologs in human. We analyzed the complex and repetitive landscape of 267 Mb of sequence that was missing or misassembled in the previously published assembly, and we provide insights into the reasons for its resistance to sequencing and assembly by whole-genome shotgun approaches. Duplicated regions within newly assembled sequence tend to be of more recent ancestry than duplicates in the published draft, correcting our initial understanding of recent evolution on the mouse lineage. These duplicates appear to be largely composed of sequence regions containing transposable elements and duplicated protein-coding genes; of these, some may be fixed in the mouse population, but at least 40% of segmentally duplicated sequences are copy number variable even among laboratory mouse strains. Mouse lineage-specific regions contain 3,767 genes drawn mainly from rapidly-changing gene families associated with reproductive functions. The finished mouse genome assembly, therefore, greatly improves our understanding of rodent-specific biology and allows the delineation of ancestral biological functions that are shared with human from derived functions that are not. PMID:19468303

PAR-CLIP data indicate that Nrd1-Nab3-dependent transcription termination regulates expression of hundreds of protein coding genes in yeast

PubMed Central

2014-01-01

Background Nrd1 and Nab3 are essential sequence-specific yeast RNA binding proteins that function as a heterodimer in the processing and degradation of diverse classes of RNAs. These proteins also regulate several mRNA coding genes; however, it remains unclear exactly what percentage of the mRNA component of the transcriptome these proteins control. To address this question, we used the pyCRAC software package developed in our laboratory to analyze CRAC and PAR-CLIP data for Nrd1-Nab3-RNA interactions. Results We generated high-resolution maps of Nrd1-Nab3-RNA interactions, from which we have uncovered hundreds of new Nrd1-Nab3 mRNA targets, representing between 20 and 30% of protein-coding transcripts. Although Nrd1 and Nab3 showed a preference for binding near 5′ ends of relatively short transcripts, they bound transcripts throughout coding sequences and 3′ UTRs. Moreover, our data for Nrd1-Nab3 binding to 3′ UTRs was consistent with a role for these proteins in the termination of transcription. Our data also support a tight integration of Nrd1-Nab3 with the nutrient response pathway. Finally, we provide experimental evidence for some of our predictions, using northern blot and RT-PCR assays. Conclusions Collectively, our data support the notion that Nrd1 and Nab3 function is tightly integrated with the nutrient response and indicate a role for these proteins in the regulation of many mRNA coding genes. Further, we provide evidence to support the hypothesis that Nrd1-Nab3 represents a failsafe termination mechanism in instances of readthrough transcription. PMID:24393166

Operon-mapper: A Web Server for Precise Operon Identification in Bacterial and Archaeal Genomes.

PubMed

Taboada, Blanca; Estrada, Karel; Ciria, Ricardo; Merino, Enrique

2018-06-19

Operon-mapper is a web server that accurately, easily, and directly predicts the operons of any bacterial or archaeal genome sequence. The operon predictions are based on the intergenic distance of neighboring genes as well as the functional relationships of their protein-coding products. To this end, Operon-mapper finds all the ORFs within a given nucleotide sequence, along with their genomic coordinates, orthology groups, and functional relationships. We believe that Operon-mapper, due to its accuracy, simplicity and speed, as well as the relevant information that it generates, will be a useful tool for annotating and characterizing genomic sequences. http://biocomputo.ibt.unam.mx/operon_mapper/.

Online interactive analysis of protein structure ensembles with Bio3D-web.

PubMed

Skjærven, Lars; Jariwala, Shashank; Yao, Xin-Qiu; Grant, Barry J

2016-11-15

Bio3D-web is an online application for analyzing the sequence, structure and conformational heterogeneity of protein families. Major functionality is provided for identifying protein structure sets for analysis, their alignment and refined structure superposition, sequence and structure conservation analysis, mapping and clustering of conformations and the quantitative comparison of their predicted structural dynamics. Bio3D-web is based on the Bio3D and Shiny R packages. All major browsers are supported and full source code is available under a GPL2 license from http://thegrantlab.org/bio3d-web CONTACT: bjgrant@umich.edu or lars.skjarven@uib.no. © The Author 2016. Published by Oxford University Press.

EGASP: the human ENCODE Genome Annotation Assessment Project

PubMed Central

Guigó, Roderic; Flicek, Paul; Abril, Josep F; Reymond, Alexandre; Lagarde, Julien; Denoeud, France; Antonarakis, Stylianos; Ashburner, Michael; Bajic, Vladimir B; Birney, Ewan; Castelo, Robert; Eyras, Eduardo; Ucla, Catherine; Gingeras, Thomas R; Harrow, Jennifer; Hubbard, Tim; Lewis, Suzanna E; Reese, Martin G

2006-01-01

Background We present the results of EGASP, a community experiment to assess the state-of-the-art in genome annotation within the ENCODE regions, which span 1% of the human genome sequence. The experiment had two major goals: the assessment of the accuracy of computational methods to predict protein coding genes; and the overall assessment of the completeness of the current human genome annotations as represented in the ENCODE regions. For the computational prediction assessment, eighteen groups contributed gene predictions. We evaluated these submissions against each other based on a 'reference set' of annotations generated as part of the GENCODE project. These annotations were not available to the prediction groups prior to the submission deadline, so that their predictions were blind and an external advisory committee could perform a fair assessment. Results The best methods had at least one gene transcript correctly predicted for close to 70% of the annotated genes. Nevertheless, the multiple transcript accuracy, taking into account alternative splicing, reached only approximately 40% to 50% accuracy. At the coding nucleotide level, the best programs reached an accuracy of 90% in both sensitivity and specificity. Programs relying on mRNA and protein sequences were the most accurate in reproducing the manually curated annotations. Experimental validation shows that only a very small percentage (3.2%) of the selected 221 computationally predicted exons outside of the existing annotation could be verified. Conclusion This is the first such experiment in human DNA, and we have followed the standards established in a similar experiment, GASP1, in Drosophila melanogaster. We believe the results presented here contribute to the value of ongoing large-scale annotation projects and should guide further experimental methods when being scaled up to the entire human genome sequence. PMID:16925836

Genetic diversity of tyrosine hydroxylase (TH) and dopamine β-hydroxylase (DBH) genes in cattle breeds

PubMed Central

Lourenco-Jaramillo, Diana Lelidett; Sifuentes-Rincón, Ana María; Parra-Bracamonte, Gaspar Manuel; de la Rosa-Reyna, Xochitl Fabiola; Segura-Cabrera, Aldo; Arellano-Vera, Williams

2012-01-01

DNA from four cattle breeds was used to re-sequence all of the exons and 56% of the introns of the bovine tyrosine hydroxylase (TH) gene and 97% and 13% of the bovine dopamine β-hydroxylase (DBH) coding and non-coding sequences, respectively. Two novel single nucleotide polymorphisms (SNPs) and a microsatellite motif were found in the TH sequences. The DBH sequences contained 62 nucleotide changes, including eight non-synonymous SNPs (nsSNPs) that are of particular interest because they may alter protein function and therefore affect the phenotype. These DBH nsSNPs resulted in amino acid substitutions that were predicted to destabilize the protein structure. Six SNPs (one from TH and five from DBH non-synonymous SNPs) were genotyped in 140 animals; all of them were polymorphic and had a minor allele frequency of > 9%. There were significant differences in the intra- and inter-population haplotype distributions. The haplotype differences between Brahman cattle and the three B. t. taurus breeds (Charolais, Holstein and Lidia) were interesting from a behavioural point of view because of the differences in temperament between these breeds. PMID:22888292

Fine tangled pili expressed by Haemophilus ducreyi are a novel class of pili.

PubMed Central

Brentjens, R J; Ketterer, M; Apicella, M A; Spinola, S M

1996-01-01

Haemophilus ducreyi synthesizes fine, tangled pili composed predominantly of a protein whose apparent molecular weight is 24,000 (24K). A hybridoma, 2D8, produced a monoclonal antibody (MAb) that bound to a 24K protein in H. ducreyi strains isolated from diverse geographic locations. A lambda gt11 H. ducreyi library was screened with MAb 2D8. A 3.5-kb chromosomal insert from one reactive plaque was amplified and ligated into the pCRII vector. The recombinant plasmid, designated pHD24, expressed a 24K protein in Escherichia coli INV alpha F that bound MAb 2D8. The coding sequence of the 24K gene was localized by exonuclease III digestion. The insert contained a 570-bp open reading frame, designated ftpA (fine, tangled pili). Translation of ftpA predicted a polypeptide with a molecular weight of 21.1K. The predicted N-terminal amino acid sequence of the polypeptide encoded by ftpA was identical to the N-terminal amino acid sequence of purified pilin and lacked a cleavable signal sequence. Primer extension analysis of ftpA confirmed the lack of a leader peptide. The predicted amino acid sequence lacked homology to known pilin sequences but shared homology with the sequences of E. coli Dps and Treponema pallidum antigen TpF1 or 4D, proteins which associate to form ordered rings. An isogenic pilin mutant, H. ducreyi 35000ftpA::mTn3(Cm), was constructed by shuttle mutagenesis and did not contain pili when examined by electron microscopy. We conclude that H. ducreyi synthesizes fine, tangled pili that are composed of a unique major subunit, which may be exported by a signal sequence independent mechanism. PMID:8550517

CDSbank: taxonomy-aware extraction, selection, renaming and formatting of protein-coding DNA or amino acid sequences.

PubMed

Hazes, Bart

2014-02-28

Protein-coding DNA sequences and their corresponding amino acid sequences are routinely used to study relationships between sequence, structure, function, and evolution. The rapidly growing size of sequence databases increases the power of such comparative analyses but it makes it more challenging to prepare high quality sequence data sets with control over redundancy, quality, completeness, formatting, and labeling. Software tools for some individual steps in this process exist but manual intervention remains a common and time consuming necessity. CDSbank is a database that stores both the protein-coding DNA sequence (CDS) and amino acid sequence for each protein annotated in Genbank. CDSbank also stores Genbank feature annotation, a flag to indicate incomplete 5' and 3' ends, full taxonomic data, and a heuristic to rank the scientific interest of each species. This rich information allows fully automated data set preparation with a level of sophistication that aims to meet or exceed manual processing. Defaults ensure ease of use for typical scenarios while allowing great flexibility when needed. Access is via a free web server at http://hazeslab.med.ualberta.ca/CDSbank/. CDSbank presents a user-friendly web server to download, filter, format, and name large sequence data sets. Common usage scenarios can be accessed via pre-programmed default choices, while optional sections give full control over the processing pipeline. Particular strengths are: extract protein-coding DNA sequences just as easily as amino acid sequences, full access to taxonomy for labeling and filtering, awareness of incomplete sequences, and the ability to take one protein sequence and extract all synonymous CDS or identical protein sequences in other species. Finally, CDSbank can also create labeled property files to, for instance, annotate or re-label phylogenetic trees.

Draft genome sequence of the docosahexaenoic acid producing thraustochytrid Aurantiochytrium sp. T66.

PubMed

Liu, Bin; Ertesvåg, Helga; Aasen, Inga Marie; Vadstein, Olav; Brautaset, Trygve; Heggeset, Tonje Marita Bjerkan

2016-06-01

Thraustochytrids are unicellular, marine protists, and there is a growing industrial interest in these organisms, particularly because some species, including strains belonging to the genus Aurantiochytrium, accumulate high levels of docosahexaenoic acid (DHA). Here, we report the draft genome sequence of Aurantiochytrium sp. T66 (ATCC PRA-276), with a size of 43 Mbp, and 11,683 predicted protein-coding sequences. The data has been deposited at DDBJ/EMBL/Genbank under the accession LNGJ00000000. The genome sequence will contribute new insight into DHA biosynthesis and regulation, providing a basis for metabolic engineering of thraustochytrids.

Draft Genome Sequence of Mycobacterium bohemicum Strain DSM 44277T.

PubMed

Asmar, Shady; Phelippeau, Michael; Robert, Catherine; Croce, Olivier; Drancourt, Michel

2015-08-06

The Mycobacterium bohemicum strain is a nontuberculosis species mainly responsible for pediatric cervical lymphadenitis. The draft genome of M. bohemicum DSM 44277(T) comprises 5,097,190 bp exhibiting a 68.64% G+C content, 4,840 protein-coding genes, and 75 predicted RNA genes. Copyright © 2015 Asmar et al.

The prediction of human exons by oligonucleotide composition and discriminant analysis of spliceable open reading frames

DOE Office of Scientific and Technical Information (OSTI.GOV)

Solovyev, V.V.; Salamov, A.A.; Lawrence, C.B.

1994-12-31

Discriminant analysis is applied to the problem of recognition 5`-, internal and 3`-exons in human DNA sequences. Specific recognition functions were developed for revealing exons of particular types. The method based on a splice site prediction algorithm that uses the linear Fisher discriminant to combine the information about significant triplet frequencies of various functional parts of splice site regions and preferences of oligonucleotide in protein coding and nation regions. The accuracy of our splice site recognition function is about 97%. A discriminant function for 5`-exon prediction includes hexanucleotide composition of upstream region, triplet composition around the ATG codon, ORF codingmore » potential, donor splice site potential and composition of downstream introit region. For internal exon prediction, we combine in a discriminant function the characteristics describing the 5`- intron region, donor splice site, coding region, acceptor splice site and Y-intron region for each open reading frame flanked by GT and AG base pairs. The accuracy of precise internal exon recognition on a test set of 451 exon and 246693 pseudoexon sequences is 77% with a specificity of 79% and a level of pseudoexon ORF prediction of 99.96%. The recognition quality computed at the level of individual nucleotides is 89%, for exon sequences and 98% for intron sequences. A discriminant function for 3`-exon prediction includes octanucleolide composition of upstream nation region, triplet composition around the stop codon, ORF coding potential, acceptor splice site potential and hexanucleotide composition of downstream region. We unite these three discriminant functions in exon predicting program FEX (find exons). FEX exactly predicts 70% of 1016 exons from the test of 181 complete genes with specificity 73%, and 89% exons are exactly or partially predicted. On the average, 85% of nucleotides were predicted accurately with specificity 91%.« less

Curated genome annotation of Oryza sativa ssp. japonica and comparative genome analysis with Arabidopsis thaliana

PubMed Central

Itoh, Takeshi; Tanaka, Tsuyoshi; Barrero, Roberto A.; Yamasaki, Chisato; Fujii, Yasuyuki; Hilton, Phillip B.; Antonio, Baltazar A.; Aono, Hideo; Apweiler, Rolf; Bruskiewich, Richard; Bureau, Thomas; Burr, Frances; Costa de Oliveira, Antonio; Fuks, Galina; Habara, Takuya; Haberer, Georg; Han, Bin; Harada, Erimi; Hiraki, Aiko T.; Hirochika, Hirohiko; Hoen, Douglas; Hokari, Hiroki; Hosokawa, Satomi; Hsing, Yue; Ikawa, Hiroshi; Ikeo, Kazuho; Imanishi, Tadashi; Ito, Yukiyo; Jaiswal, Pankaj; Kanno, Masako; Kawahara, Yoshihiro; Kawamura, Toshiyuki; Kawashima, Hiroaki; Khurana, Jitendra P.; Kikuchi, Shoshi; Komatsu, Setsuko; Koyanagi, Kanako O.; Kubooka, Hiromi; Lieberherr, Damien; Lin, Yao-Cheng; Lonsdale, David; Matsumoto, Takashi; Matsuya, Akihiro; McCombie, W. Richard; Messing, Joachim; Miyao, Akio; Mulder, Nicola; Nagamura, Yoshiaki; Nam, Jongmin; Namiki, Nobukazu; Numa, Hisataka; Nurimoto, Shin; O’Donovan, Claire; Ohyanagi, Hajime; Okido, Toshihisa; OOta, Satoshi; Osato, Naoki; Palmer, Lance E.; Quetier, Francis; Raghuvanshi, Saurabh; Saichi, Naomi; Sakai, Hiroaki; Sakai, Yasumichi; Sakata, Katsumi; Sakurai, Tetsuya; Sato, Fumihiko; Sato, Yoshiharu; Schoof, Heiko; Seki, Motoaki; Shibata, Michie; Shimizu, Yuji; Shinozaki, Kazuo; Shinso, Yuji; Singh, Nagendra K.; Smith-White, Brian; Takeda, Jun-ichi; Tanino, Motohiko; Tatusova, Tatiana; Thongjuea, Supat; Todokoro, Fusano; Tsugane, Mika; Tyagi, Akhilesh K.; Vanavichit, Apichart; Wang, Aihui; Wing, Rod A.; Yamaguchi, Kaori; Yamamoto, Mayu; Yamamoto, Naoyuki; Yu, Yeisoo; Zhang, Hao; Zhao, Qiang; Higo, Kenichi; Burr, Benjamin; Gojobori, Takashi; Sasaki, Takuji

2007-01-01

We present here the annotation of the complete genome of rice Oryza sativa L. ssp. japonica cultivar Nipponbare. All functional annotations for proteins and non-protein-coding RNA (npRNA) candidates were manually curated. Functions were identified or inferred in 19,969 (70%) of the proteins, and 131 possible npRNAs (including 58 antisense transcripts) were found. Almost 5000 annotated protein-coding genes were found to be disrupted in insertional mutant lines, which will accelerate future experimental validation of the annotations. The rice loci were determined by using cDNA sequences obtained from rice and other representative cereals. Our conservative estimate based on these loci and an extrapolation suggested that the gene number of rice is ∼32,000, which is smaller than previous estimates. We conducted comparative analyses between rice and Arabidopsis thaliana and found that both genomes possessed several lineage-specific genes, which might account for the observed differences between these species, while they had similar sets of predicted functional domains among the protein sequences. A system to control translational efficiency seems to be conserved across large evolutionary distances. Moreover, the evolutionary process of protein-coding genes was examined. Our results suggest that natural selection may have played a role for duplicated genes in both species, so that duplication was suppressed or favored in a manner that depended on the function of a gene. PMID:17210932

Permanent draft genome sequence of Comamonas testosteroni KF-1

PubMed Central

Weiss, Michael; Kesberg, Anna I.; LaButti, Kurt M.; Pitluck, Sam; Bruce, David; Hauser, Loren; Copeland, Alex; Woyke, Tanja; Lowry, Stephen; Lucas, Susan; Land, Miriam; Goodwin, Lynne; Kjelleberg, Staffan; Cook, Alasdair M.; Buhmann, Matthias; Thomas, Torsten; Schleheck, David

2013-01-01

Comamonas testosteroni KF-1 is a model organism for the elucidation of the novel biochemical degradation pathways for xenobiotic 4-sulfophenylcarboxylates (SPC) formed during biodegradation of synthetic 4-sulfophenylalkane surfactants (linear alkylbenzenesulfonates, LAS) by bacterial communities. Here we describe the features of this organism, together with the complete genome sequence and annotation. The 6,026,527 bp long chromosome (one sequencing gap) exhibits an average G+C content of 61.79% and is predicted to encode 5,492 protein-coding genes and 114 RNA genes. PMID:23991256

Purification, characterization and sequence analysis of Omp50,a new porin isolated from Campylobacter jejuni.

PubMed Central

Bolla, J M; Dé, E; Dorez, A; Pagès, J M

2000-01-01

A novel pore-forming protein identified in Campylobacter was purified by ion-exchange chromatography and named Omp50 according to both its molecular mass and its outer membrane localization. We observed a pore-forming ability of Omp50 after re-incorporation into artificial membranes. The protein induced cation-selective channels with major conductance values of 50-60 pS in 1 M NaCl. N-terminal sequencing allowed us to identify the predicted coding sequence Cj1170c from the Campylobacter jejuni genome database as the corresponding gene in the NCTC 11168 genome sequence. The gene, designated omp50, consists of a 1425 bp open reading frame encoding a deduced 453-amino acid protein with a calculated pI of 5.81 and a molecular mass of 51169.2 Da. The protein possessed a 20-amino acid leader sequence. No significant similarity was found between Omp50 and porin protein sequences already determined. Moreover, the protein showed only weak sequence identity with the major outer-membrane protein (MOMP) of Campylobacter, correlating with the absence of antigenic cross-reactivity between these two proteins. Omp50 is expressed in C. jejuni and Campylobacter lari but not in Campylobacter coli. The gene, however, was detected in all three species by PCR. According to its conformation and functional properties, the protein would belong to the family of outer-membrane monomeric porins. PMID:11104668

SMOQ: a tool for predicting the absolute residue-specific quality of a single protein model with support vector machines

PubMed Central

2014-01-01

Background It is important to predict the quality of a protein structural model before its native structure is known. The method that can predict the absolute local quality of individual residues in a single protein model is rare, yet particularly needed for using, ranking and refining protein models. Results We developed a machine learning tool (SMOQ) that can predict the distance deviation of each residue in a single protein model. SMOQ uses support vector machines (SVM) with protein sequence and structural features (i.e. basic feature set), including amino acid sequence, secondary structures, solvent accessibilities, and residue-residue contacts to make predictions. We also trained a SVM model with two new additional features (profiles and SOV scores) on 20 CASP8 targets and found that including them can only improve the performance when real deviations between native and model are higher than 5Å. The SMOQ tool finally released uses the basic feature set trained on 85 CASP8 targets. Moreover, SMOQ implemented a way to convert predicted local quality scores into a global quality score. SMOQ was tested on the 84 CASP9 single-domain targets. The average difference between the residue-specific distance deviation predicted by our method and the actual distance deviation on the test data is 2.637Å. The global quality prediction accuracy of the tool is comparable to other good tools on the same benchmark. Conclusion SMOQ is a useful tool for protein single model quality assessment. Its source code and executable are available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/. PMID:24776231

SMOQ: a tool for predicting the absolute residue-specific quality of a single protein model with support vector machines.

PubMed

Cao, Renzhi; Wang, Zheng; Wang, Yiheng; Cheng, Jianlin

2014-04-28

It is important to predict the quality of a protein structural model before its native structure is known. The method that can predict the absolute local quality of individual residues in a single protein model is rare, yet particularly needed for using, ranking and refining protein models. We developed a machine learning tool (SMOQ) that can predict the distance deviation of each residue in a single protein model. SMOQ uses support vector machines (SVM) with protein sequence and structural features (i.e. basic feature set), including amino acid sequence, secondary structures, solvent accessibilities, and residue-residue contacts to make predictions. We also trained a SVM model with two new additional features (profiles and SOV scores) on 20 CASP8 targets and found that including them can only improve the performance when real deviations between native and model are higher than 5Å. The SMOQ tool finally released uses the basic feature set trained on 85 CASP8 targets. Moreover, SMOQ implemented a way to convert predicted local quality scores into a global quality score. SMOQ was tested on the 84 CASP9 single-domain targets. The average difference between the residue-specific distance deviation predicted by our method and the actual distance deviation on the test data is 2.637Å. The global quality prediction accuracy of the tool is comparable to other good tools on the same benchmark. SMOQ is a useful tool for protein single model quality assessment. Its source code and executable are available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/.

Sequence and structural implications of a bovine corneal keratan sulfate proteoglycan core protein. Protein 37B represents bovine lumican and proteins 37A and 25 are unique

NASA Technical Reports Server (NTRS)

Funderburgh, J. L.; Funderburgh, M. L.; Brown, S. J.; Vergnes, J. P.; Hassell, J. R.; Mann, M. M.; Conrad, G. W.; Spooner, B. S. (Principal Investigator)

1993-01-01

Amino acid sequence from tryptic peptides of three different bovine corneal keratan sulfate proteoglycan (KSPG) core proteins (designated 37A, 37B, and 25) showed similarities to the sequence of a chicken KSPG core protein lumican. Bovine lumican cDNA was isolated from a bovine corneal expression library by screening with chicken lumican cDNA. The bovine cDNA codes for a 342-amino acid protein, M(r) 38,712, containing amino acid sequences identified in the 37B KSPG core protein. The bovine lumican is 68% identical to chicken lumican, with an 83% identity excluding the N-terminal 40 amino acids. Location of 6 cysteine and 4 consensus N-glycosylation sites in the bovine sequence were identical to those in chicken lumican. Bovine lumican had about 50% identity to bovine fibromodulin and 20% identity to bovine decorin and biglycan. About two-thirds of the lumican protein consists of a series of 10 amino acid leucine-rich repeats that occur in regions of calculated high beta-hydrophobic moment, suggesting that the leucine-rich repeats contribute to beta-sheet formation in these proteins. Sequences obtained from 37A and 25 core proteins were absent in bovine lumican, thus predicting a unique primary structure and separate mRNA for each of the three bovine KSPG core proteins.

Transmembrane protein topology prediction using support vector machines.

PubMed

Nugent, Timothy; Jones, David T

2009-05-26

Alpha-helical transmembrane (TM) proteins are involved in a wide range of important biological processes such as cell signaling, transport of membrane-impermeable molecules, cell-cell communication, cell recognition and cell adhesion. Many are also prime drug targets, and it has been estimated that more than half of all drugs currently on the market target membrane proteins. However, due to the experimental difficulties involved in obtaining high quality crystals, this class of protein is severely under-represented in structural databases. In the absence of structural data, sequence-based prediction methods allow TM protein topology to be investigated. We present a support vector machine-based (SVM) TM protein topology predictor that integrates both signal peptide and re-entrant helix prediction, benchmarked with full cross-validation on a novel data set of 131 sequences with known crystal structures. The method achieves topology prediction accuracy of 89%, while signal peptides and re-entrant helices are predicted with 93% and 44% accuracy respectively. An additional SVM trained to discriminate between globular and TM proteins detected zero false positives, with a low false negative rate of 0.4%. We present the results of applying these tools to a number of complete genomes. Source code, data sets and a web server are freely available from http://bioinf.cs.ucl.ac.uk/psipred/. The high accuracy of TM topology prediction which includes detection of both signal peptides and re-entrant helices, combined with the ability to effectively discriminate between TM and globular proteins, make this method ideally suited to whole genome annotation of alpha-helical transmembrane proteins.

Importing statistical measures into Artemis enhances gene identification in the Leishmania genome project.

PubMed

Aggarwal, Gautam; Worthey, E A; McDonagh, Paul D; Myler, Peter J

2003-06-07

Seattle Biomedical Research Institute (SBRI) as part of the Leishmania Genome Network (LGN) is sequencing chromosomes of the trypanosomatid protozoan species Leishmania major. At SBRI, chromosomal sequence is annotated using a combination of trained and untrained non-consensus gene-prediction algorithms with ARTEMIS, an annotation platform with rich and user-friendly interfaces. Here we describe a methodology used to import results from three different protein-coding gene-prediction algorithms (GLIMMER, TESTCODE and GENESCAN) into the ARTEMIS sequence viewer and annotation tool. Comparison of these methods, along with the CODONUSAGE algorithm built into ARTEMIS, shows the importance of combining methods to more accurately annotate the L. major genomic sequence. An improvised and powerful tool for gene prediction has been developed by importing data from widely-used algorithms into an existing annotation platform. This approach is especially fruitful in the Leishmania genome project where there is large proportion of novel genes requiring manual annotation.

Deep developmental transcriptome sequencing uncovers numerous new genes and enhances gene annotation in the sponge Amphimedon queenslandica.

PubMed

Fernandez-Valverde, Selene L; Calcino, Andrew D; Degnan, Bernard M

2015-05-15

The demosponge Amphimedon queenslandica is amongst the few early-branching metazoans with an assembled and annotated draft genome, making it an important species in the study of the origin and early evolution of animals. Current gene models in this species are largely based on in silico predictions and low coverage expressed sequence tag (EST) evidence. Amphimedon queenslandica protein-coding gene models are improved using deep RNA-Seq data from four developmental stages and CEL-Seq data from 82 developmental samples. Over 86% of previously predicted genes are retained in the new gene models, although 24% have additional exons; there is also a marked increase in the total number of annotated 3' and 5' untranslated regions (UTRs). Importantly, these new developmental transcriptome data reveal numerous previously unannotated protein-coding genes in the Amphimedon genome, increasing the total gene number by 25%, from 30,060 to 40,122. In general, Amphimedon genes have introns that are markedly smaller than those in other animals and most of the alternatively spliced genes in Amphimedon undergo intron-retention; exon-skipping is the least common mode of alternative splicing. Finally, in addition to canonical polyadenylation signal sequences, Amphimedon genes are enriched in a number of unique AT-rich motifs in their 3' UTRs. The inclusion of developmental transcriptome data has substantially improved the structure and composition of protein-coding gene models in Amphimedon queenslandica, providing a more accurate and comprehensive set of genes for functional and comparative studies. These improvements reveal the Amphimedon genome is comprised of a remarkably high number of tightly packed genes. These genes have small introns and there is pervasive intron retention amongst alternatively spliced transcripts. These aspects of the sponge genome are more similar unicellular opisthokont genomes than to other animal genomes.

CONFOLD2: improved contact-driven ab initio protein structure modeling.

PubMed

Adhikari, Badri; Cheng, Jianlin

2018-01-25

Contact-guided protein structure prediction methods are becoming more and more successful because of the latest advances in residue-residue contact prediction. To support contact-driven structure prediction, effective tools that can quickly build tertiary structural models of good quality from predicted contacts need to be developed. We develop an improved contact-driven protein modelling method, CONFOLD2, and study how it may be effectively used for ab initio protein structure prediction with predicted contacts as input. It builds models using various subsets of input contacts to explore the fold space under the guidance of a soft square energy function, and then clusters the models to obtain the top five models. CONFOLD2 obtains an average reconstruction accuracy of 0.57 TM-score for the 150 proteins in the PSICOV contact prediction dataset. When benchmarked on the CASP11 contacts predicted using CONSIP2 and CASP12 contacts predicted using Raptor-X, CONFOLD2 achieves a mean TM-score of 0.41 on both datasets. CONFOLD2 allows to quickly generate top five structural models for a protein sequence when its secondary structures and contacts predictions at hand. The source code of CONFOLD2 is publicly available at https://github.com/multicom-toolbox/CONFOLD2/ .

Accurate prediction of cellular co-translational folding indicates proteins can switch from post- to co-translational folding

PubMed Central

Nissley, Daniel A.; Sharma, Ajeet K.; Ahmed, Nabeel; Friedrich, Ulrike A.; Kramer, Günter; Bukau, Bernd; O'Brien, Edward P.

2016-01-01

The rates at which domains fold and codons are translated are important factors in determining whether a nascent protein will co-translationally fold and function or misfold and malfunction. Here we develop a chemical kinetic model that calculates a protein domain's co-translational folding curve during synthesis using only the domain's bulk folding and unfolding rates and codon translation rates. We show that this model accurately predicts the course of co-translational folding measured in vivo for four different protein molecules. We then make predictions for a number of different proteins in yeast and find that synonymous codon substitutions, which change translation-elongation rates, can switch some protein domains from folding post-translationally to folding co-translationally—a result consistent with previous experimental studies. Our approach explains essential features of co-translational folding curves and predicts how varying the translation rate at different codon positions along a transcript's coding sequence affects this self-assembly process. PMID:26887592

Effective gene prediction by high resolution frequency estimator based on least-norm solution technique

PubMed Central

2014-01-01

Linear algebraic concept of subspace plays a significant role in the recent techniques of spectrum estimation. In this article, the authors have utilized the noise subspace concept for finding hidden periodicities in DNA sequence. With the vast growth of genomic sequences, the demand to identify accurately the protein-coding regions in DNA is increasingly rising. Several techniques of DNA feature extraction which involves various cross fields have come up in the recent past, among which application of digital signal processing tools is of prime importance. It is known that coding segments have a 3-base periodicity, while non-coding regions do not have this unique feature. One of the most important spectrum analysis techniques based on the concept of subspace is the least-norm method. The least-norm estimator developed in this paper shows sharp period-3 peaks in coding regions completely eliminating background noise. Comparison of proposed method with existing sliding discrete Fourier transform (SDFT) method popularly known as modified periodogram method has been drawn on several genes from various organisms and the results show that the proposed method has better as well as an effective approach towards gene prediction. Resolution, quality factor, sensitivity, specificity, miss rate, and wrong rate are used to establish superiority of least-norm gene prediction method over existing method. PMID:24386895

Sequencing, annotation and comparative analysis of nine BACs of giant panda (Ailuropoda melanoleuca).

PubMed

Zheng, Yang; Cai, Jing; Li, JianWen; Li, Bo; Lin, Runmao; Tian, Feng; Wang, XiaoLing; Wang, Jun

2010-01-01

A 10-fold BAC library for giant panda was constructed and nine BACs were selected to generate finish sequences. These BACs could be used as a validation resource for the de novo assembly accuracy of the whole genome shotgun sequencing reads of giant panda newly generated by the Illumina GA sequencing technology. Complete sanger sequencing, assembly, annotation and comparative analysis were carried out on the selected BACs of a joint length 878 kb. Homologue search and de novo prediction methods were used to annotate genes and repeats. Twelve protein coding genes were predicted, seven of which could be functionally annotated. The seven genes have an average gene size of about 41 kb, an average coding size of about 1.2 kb and an average exon number of 6 per gene. Besides, seven tRNA genes were found. About 27 percent of the BAC sequence is composed of repeats. A phylogenetic tree was constructed using neighbor-join algorithm across five species, including giant panda, human, dog, cat and mouse, which reconfirms dog as the most related species to giant panda. Our results provide detailed sequence and structure information for new genes and repeats of giant panda, which will be helpful for further studies on the giant panda.

PANNZER2: a rapid functional annotation web server.

PubMed

Törönen, Petri; Medlar, Alan; Holm, Liisa

2018-05-08

The unprecedented growth of high-throughput sequencing has led to an ever-widening annotation gap in protein databases. While computational prediction methods are available to make up the shortfall, a majority of public web servers are hindered by practical limitations and poor performance. Here, we introduce PANNZER2 (Protein ANNotation with Z-scoRE), a fast functional annotation web server that provides both Gene Ontology (GO) annotations and free text description predictions. PANNZER2 uses SANSparallel to perform high-performance homology searches, making bulk annotation based on sequence similarity practical. PANNZER2 can output GO annotations from multiple scoring functions, enabling users to see which predictions are robust across predictors. Finally, PANNZER2 predictions scored within the top 10 methods for molecular function and biological process in the CAFA2 NK-full benchmark. The PANNZER2 web server is updated on a monthly schedule and is accessible at http://ekhidna2.biocenter.helsinki.fi/sanspanz/. The source code is available under the GNU Public Licence v3.

Plasmid-encoded hygromycin B resistance: the sequence of hygromycin B phosphotransferase gene and its expression in Escherichia coli and Saccharomyces cerevisiae.

PubMed

Gritz, L; Davies, J

1983-11-01

The plasmid-borne gene hph coding for hygromycin B phosphotransferase (HPH) in Escherichia coli has been identified and its nucleotide sequence determined. The hph gene is 1026 nucleotides long, coding for a protein with a predicted Mr of 39 000. The hph gene was placed in a shuttle plasmid vector, downstream from the promoter region of the cyc 1 gene of Saccharomyces cerevisiae, and an hph construction containing a single AUG in the 5' noncoding region allowed direct selection following transformation in yeast and in E. coli. Thus the hph gene can be used in cloning vectors for both pro- and eukaryotes.

aPPRove: An HMM-Based Method for Accurate Prediction of RNA-Pentatricopeptide Repeat Protein Binding Events

PubMed Central

Harrison, Thomas; Ruiz, Jaime; Sloan, Daniel B.; Ben-Hur, Asa; Boucher, Christina

2016-01-01

Pentatricopeptide repeat containing proteins (PPRs) bind to RNA transcripts originating from mitochondria and plastids. There are two classes of PPR proteins. The P class contains tandem P-type motif sequences, and the PLS class contains alternating P, L and S type sequences. In this paper, we describe a novel tool that predicts PPR-RNA interaction; specifically, our method, which we call aPPRove, determines where and how a PLS-class PPR protein will bind to RNA when given a PPR and one or more RNA transcripts by using a combinatorial binding code for site specificity proposed by Barkan et al. Our results demonstrate that aPPRove successfully locates how and where a PPR protein belonging to the PLS class can bind to RNA. For each binding event it outputs the binding site, the amino-acid-nucleotide interaction, and its statistical significance. Furthermore, we show that our method can be used to predict binding events for PLS-class proteins using a known edit site and the statistical significance of aligning the PPR protein to that site. In particular, we use our method to make a conjecture regarding an interaction between CLB19 and the second intronic region of ycf3. The aPPRove web server can be found at www.cs.colostate.edu/~approve. PMID:27560805

Are plant formins integral membrane proteins?

PubMed

Cvrcková, F

2000-01-01

The formin family of proteins has been implicated in signaling pathways of cellular morphogenesis in both animals and fungi; in the latter case, at least, they participate in communication between the actin cytoskeleton and the cell surface. Nevertheless, they appear to be cytoplasmic or nuclear proteins, and it is not clear whether they communicate with the plasma membrane, and if so, how. Because nothing is known about formin function in plants, I performed a systematic search for putative Arabidopsis thaliana formin homologs. I found eight putative formin-coding genes in the publicly available part of the Arabidopsis genome sequence and analyzed their predicted protein sequences. Surprisingly, some of them lack parts of the conserved formin-homology 2 (FH2) domain and the majority of them seem to have signal sequences and putative transmembrane segments that are not found in yeast or animals formins. Plant formins define a distinct subfamily. The presence in most Arabidopsis formins of sequence motifs typical or transmembrane proteins suggests a mechanism of membrane attachment that may be specific to plant formins, and indicates an unexpected evolutionary flexibility of the conserved formin domain.

Brain cDNA clone for human cholinesterase

DOE Office of Scientific and Technical Information (OSTI.GOV)

McTiernan, C.; Adkins, S.; Chatonnet, A.

1987-10-01

A cDNA library from human basal ganglia was screened with oligonucleotide probes corresponding to portions of the amino acid sequence of human serum cholinesterase. Five overlapping clones, representing 2.4 kilobases, were isolated. The sequenced cDNA contained 207 base pairs of coding sequence 5' to the amino terminus of the mature protein in which there were four ATG translation start sites in the same reading frame as the protein. Only the ATG coding for Met-(-28) lay within a favorable consensus sequence for functional initiators. There were 1722 base pairs of coding sequence corresponding to the protein found circulating in human serum.more » The amino acid sequence deduced from the cDNA exactly matched the 574 amino acid sequence of human serum cholinesterase, as previously determined by Edman degradation. Therefore, our clones represented cholinesterase rather than acetylcholinesterase. It was concluded that the amino acid sequences of cholinesterase from two different tissues, human brain and human serum, were identical. Hybridization of genomic DNA blots suggested that a single gene, or very few genes coded for cholinesterase.« less

Multi-Omics Driven Assembly and Annotation of the Sandalwood (Santalum album) Genome.

PubMed

Mahesh, Hirehally Basavarajegowda; Subba, Pratigya; Advani, Jayshree; Shirke, Meghana Deepak; Loganathan, Ramya Malarini; Chandana, Shankara Lingu; Shilpa, Siddappa; Chatterjee, Oishi; Pinto, Sneha Maria; Prasad, Thottethodi Subrahmanya Keshava; Gowda, Malali

2018-04-01

Indian sandalwood ( Santalum album ) is an important tropical evergreen tree known for its fragrant heartwood-derived essential oil and its valuable carving wood. Here, we applied an integrated genomic, transcriptomic, and proteomic approach to assemble and annotate the Indian sandalwood genome. Our genome sequencing resulted in the establishment of a draft map of the smallest genome for any woody tree species to date (221 Mb). The genome annotation predicted 38,119 protein-coding genes and 27.42% repetitive DNA elements. In-depth proteome analysis revealed the identities of 72,325 unique peptides, which confirmed 10,076 of the predicted genes. The addition of transcriptomic and proteogenomic approaches resulted in the identification of 53 novel proteins and 34 gene-correction events that were missed by genomic approaches. Proteogenomic analysis also helped in reassigning 1,348 potential noncoding RNAs as bona fide protein-coding messenger RNAs. Gene expression patterns at the RNA and protein levels indicated that peptide sequencing was useful in capturing proteins encoded by nuclear and organellar genomes alike. Mass spectrometry-based proteomic evidence provided an unbiased approach toward the identification of proteins encoded by organellar genomes. Such proteins are often missed in transcriptome data sets due to the enrichment of only messenger RNAs that contain poly(A) tails. Overall, the use of integrated omic approaches enhanced the quality of the assembly and annotation of this nonmodel plant genome. The availability of genomic, transcriptomic, and proteomic data will enhance genomics-assisted breeding, germplasm characterization, and conservation of sandalwood trees. © 2018 American Society of Plant Biologists. All Rights Reserved.

The Effect of α-Mating Factor Secretion Signal Mutations on Recombinant Protein Expression in Pichia pastoris

PubMed Central

Lin-Cereghino, Geoff P.; Stark, Carolyn M.; Kim, Daniel; Chang, Jennifer; Shaheen, Nadia; Poerwanto, Hansel; Agari, Kimiko; Moua, Pachai; Low, Lauren K.; Tran, Namphuong; Huang, Amy D.; Nattestad, Maria; Oshiro, Kristin T.; Chang, John William; Chavan, Archana; Tsai, Jerry W.; Lin-Cereghino, Joan

2013-01-01

The methylotrophic yeast, Pichia pastoris, has been genetically engineered to produce many heterologous proteins for industrial and research purposes. In order to secrete proteins for easier purification from the extracellular medium, the coding sequence of recombinant proteins are initially fused to the Saccharomyces cerevisiae α-mating factor secretion signal leader. Extensive site-directed mutagenesis of the prepro region of the α-mating factor secretion signal sequence was performed in order to determine the effects of various deletions and substitutions on expression. Though some mutations clearly dampened protein expression, deletion of amino acids 57-70, corresponding to the predicted 3rd alpha helix of α-mating factor secretion signal, increased secretion of reporter proteins horseradish peroxidase and lipase at least 50% in small-scale cultures. These findings raise the possibility that the secretory efficiency of the leader can be further enhanced in the future. PMID:23454485

Sialotranscriptomics of Rhipicephalus zambeziensis reveals intricate expression profiles of secretory proteins and suggests tight temporal transcriptional regulation during blood-feeding.

PubMed

de Castro, Minique Hilda; de Klerk, Daniel; Pienaar, Ronel; Rees, D Jasper G; Mans, Ben J

2017-08-10

Ticks secrete a diverse mixture of secretory proteins into the host to evade its immune response and facilitate blood-feeding, making secretory proteins attractive targets for the production of recombinant anti-tick vaccines. The largely neglected tick species, Rhipicephalus zambeziensis, is an efficient vector of Theileria parva in southern Africa but its available sequence information is limited. Next generation sequencing has advanced sequence availability for ticks in recent years and has assisted the characterisation of secretory proteins. This study focused on the de novo assembly and annotation of the salivary gland transcriptome of R. zambeziensis and the temporal expression of secretory protein transcripts in female and male ticks, before the onset of feeding and during early and late feeding. The sialotranscriptome of R. zambeziensis yielded 23,631 transcripts from which 13,584 non-redundant proteins were predicted. Eighty-six percent of these contained a predicted start and stop codon and were estimated to be putatively full-length proteins. A fifth (2569) of the predicted proteins were annotated as putative secretory proteins and explained 52% of the expression in the transcriptome. Expression analyses revealed that 2832 transcripts were differentially expressed among feeding time points and 1209 between the tick sexes. The expression analyses further indicated that 57% of the annotated secretory protein transcripts were differentially expressed. Dynamic expression profiles of secretory protein transcripts were observed during feeding of female ticks. Whereby a number of transcripts were upregulated during early feeding, presumably for feeding site establishment and then during late feeding, 52% of these were downregulated, indicating that transcripts were required at specific feeding stages. This suggested that secretory proteins are under stringent transcriptional regulation that fine-tunes their expression in salivary glands during feeding. No open reading frames were predicted for 7947 transcripts. This class represented 17% of the differentially expressed transcripts, suggesting a potential transcriptional regulatory function of long non-coding RNA in tick blood-feeding. The assembled sialotranscriptome greatly expands the sequence availability of R. zambeziensis, assists in our understanding of the transcription of secretory proteins during blood-feeding and will be a valuable resource for future vaccine candidate selection.

MetaPSICOV: combining coevolution methods for accurate prediction of contacts and long range hydrogen bonding in proteins.

PubMed

Jones, David T; Singh, Tanya; Kosciolek, Tomasz; Tetchner, Stuart

2015-04-01

Recent developments of statistical techniques to infer direct evolutionary couplings between residue pairs have rendered covariation-based contact prediction a viable means for accurate 3D modelling of proteins, with no information other than the sequence required. To extend the usefulness of contact prediction, we have designed a new meta-predictor (MetaPSICOV) which combines three distinct approaches for inferring covariation signals from multiple sequence alignments, considers a broad range of other sequence-derived features and, uniquely, a range of metrics which describe both the local and global quality of the input multiple sequence alignment. Finally, we use a two-stage predictor, where the second stage filters the output of the first stage. This two-stage predictor is additionally evaluated on its ability to accurately predict the long range network of hydrogen bonds, including correctly assigning the donor and acceptor residues. Using the original PSICOV benchmark set of 150 protein families, MetaPSICOV achieves a mean precision of 0.54 for top-L predicted long range contacts-around 60% higher than PSICOV, and around 40% better than CCMpred. In de novo protein structure prediction using FRAGFOLD, MetaPSICOV is able to improve the TM-scores of models by a median of 0.05 compared with PSICOV. Lastly, for predicting long range hydrogen bonding, MetaPSICOV-HB achieves a precision of 0.69 for the top-L/10 hydrogen bonds compared with just 0.26 for the baseline MetaPSICOV. MetaPSICOV is available as a freely available web server at http://bioinf.cs.ucl.ac.uk/MetaPSICOV. Raw data (predicted contact lists and 3D models) and source code can be downloaded from http://bioinf.cs.ucl.ac.uk/downloads/MetaPSICOV. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

Biophysics of protein evolution and evolutionary protein biophysics

PubMed Central

Sikosek, Tobias; Chan, Hue Sun

2014-01-01

The study of molecular evolution at the level of protein-coding genes often entails comparing large datasets of sequences to infer their evolutionary relationships. Despite the importance of a protein's structure and conformational dynamics to its function and thus its fitness, common phylogenetic methods embody minimal biophysical knowledge of proteins. To underscore the biophysical constraints on natural selection, we survey effects of protein mutations, highlighting the physical basis for marginal stability of natural globular proteins and how requirement for kinetic stability and avoidance of misfolding and misinteractions might have affected protein evolution. The biophysical underpinnings of these effects have been addressed by models with an explicit coarse-grained spatial representation of the polypeptide chain. Sequence–structure mappings based on such models are powerful conceptual tools that rationalize mutational robustness, evolvability, epistasis, promiscuous function performed by ‘hidden’ conformational states, resolution of adaptive conflicts and conformational switches in the evolution from one protein fold to another. Recently, protein biophysics has been applied to derive more accurate evolutionary accounts of sequence data. Methods have also been developed to exploit sequence-based evolutionary information to predict biophysical behaviours of proteins. The success of these approaches demonstrates a deep synergy between the fields of protein biophysics and protein evolution. PMID:25165599

A common class of transcripts with 5'-intron depletion, distinct early coding sequence features, and N1-methyladenosine modification.

PubMed

Cenik, Can; Chua, Hon Nian; Singh, Guramrit; Akef, Abdalla; Snyder, Michael P; Palazzo, Alexander F; Moore, Melissa J; Roth, Frederick P

2017-03-01

Introns are found in 5' untranslated regions (5'UTRs) for 35% of all human transcripts. These 5'UTR introns are not randomly distributed: Genes that encode secreted, membrane-bound and mitochondrial proteins are less likely to have them. Curiously, transcripts lacking 5'UTR introns tend to harbor specific RNA sequence elements in their early coding regions. To model and understand the connection between coding-region sequence and 5'UTR intron status, we developed a classifier that can predict 5'UTR intron status with >80% accuracy using only sequence features in the early coding region. Thus, the classifier identifies transcripts with 5 ' proximal- i ntron- m inus-like-coding regions ("5IM" transcripts). Unexpectedly, we found that the early coding sequence features defining 5IM transcripts are widespread, appearing in 21% of all human RefSeq transcripts. The 5IM class of transcripts is enriched for non-AUG start codons, more extensive secondary structure both preceding the start codon and near the 5' cap, greater dependence on eIF4E for translation, and association with ER-proximal ribosomes. 5IM transcripts are bound by the exon junction complex (EJC) at noncanonical 5' proximal positions. Finally, N 1 -methyladenosines are specifically enriched in the early coding regions of 5IM transcripts. Taken together, our analyses point to the existence of a distinct 5IM class comprising ∼20% of human transcripts. This class is defined by depletion of 5' proximal introns, presence of specific RNA sequence features associated with low translation efficiency, N 1 -methyladenosines in the early coding region, and enrichment for noncanonical binding by the EJC. © 2017 Cenik et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Complete genome sequence analysis of the fish pathogen Flavobacterium columnare provides insights into antibiotic resistance and pathogenicity related genes.

PubMed

Zhang, Yulei; Zhao, Lijuan; Chen, Wenjie; Huang, Yunmao; Yang, Ling; Sarathbabu, V; Wu, Zaohe; Li, Jun; Nie, Pin; Lin, Li

2017-10-01

We analyzed here the complete genome sequences of a highly virulent Flavobacterium columnare Pf1 strain isolated in our laboratory. The complete genome consists of a 3,171,081 bp circular DNA with 2784 predicted protein-coding genes. Among these, 286 genes were predicted as antibiotic resistance genes, including 32 RND-type efflux pump related genes which were associated with the export of aminoglycosides, indicating inducible aminoglycosides resistances in F. columnare. On the other hand, 328 genes were predicted as pathogenicity related genes which could be classified as virulence factors, gliding motility proteins, adhesins, and many putative secreted proteases. These genes were probably involved in the colonization, invasion and destruction of fish tissues during the infection of F. columnare. Apparently, our obtained complete genome sequences provide the basis for the explanation of the interactions between the F. columnare and the infected fish. The predicted antibiotic resistance and pathogenicity related genes will shed a new light on the development of more efficient preventional strategies against the infection of F. columnare, which is a major worldwide fish pathogen. Copyright © 2017 Elsevier Ltd. All rights reserved.

Prediction and identification of sequences coding for orphan enzymes using genomic and metagenomic neighbours

PubMed Central

Yamada, Takuji; Waller, Alison S; Raes, Jeroen; Zelezniak, Aleksej; Perchat, Nadia; Perret, Alain; Salanoubat, Marcel; Patil, Kiran R; Weissenbach, Jean; Bork, Peer

2012-01-01

Despite the current wealth of sequencing data, one-third of all biochemically characterized metabolic enzymes lack a corresponding gene or protein sequence, and as such can be considered orphan enzymes. They represent a major gap between our molecular and biochemical knowledge, and consequently are not amenable to modern systemic analyses. As 555 of these orphan enzymes have metabolic pathway neighbours, we developed a global framework that utilizes the pathway and (meta)genomic neighbour information to assign candidate sequences to orphan enzymes. For 131 orphan enzymes (37% of those for which (meta)genomic neighbours are available), we associate sequences to them using scoring parameters with an estimated accuracy of 70%, implying functional annotation of 16 345 gene sequences in numerous (meta)genomes. As a case in point, two of these candidate sequences were experimentally validated to encode the predicted activity. In addition, we augmented the currently available genome-scale metabolic models with these new sequence–function associations and were able to expand the models by on average 8%, with a considerable change in the flux connectivity patterns and improved essentiality prediction. PMID:22569339

High quality draft genome sequence of Olivibacter sitiensis type strain (AW-6T), a diphenol degrader with genes involved in the catechol pathway

PubMed Central

Ntougias, Spyridon; Lapidus, Alla; Han, James; Mavromatis, Konstantinos; Pati, Amrita; Chen, Amy; Klenk, Hans-Peter; Woyke, Tanja; Fasseas, Constantinos; Kyrpides, Nikos C.; Zervakis, Georgios I.

2014-01-01

Olivibacter sitiensis Ntougias et al. 2007 is a member of the family Sphingobacteriaceae, phylum Bacteroidetes. Members of the genus Olivibacter are phylogenetically diverse and of significant interest. They occur in diverse habitats, such as rhizosphere and contaminated soils, viscous wastes, composts, biofilter clean-up facilities on contaminated sites and cave environments, and they are involved in the degradation of complex and toxic compounds. Here we describe the features of O. sitiensis AW-6T, together with the permanent-draft genome sequence and annotation. The organism was sequenced under the Genomic Encyclopedia for Bacteria and Archaea (GEBA) project at the DOE Joint Genome Institute and is the first genome sequence of a species within the genus Olivibacter. The genome is 5,053,571 bp long and is comprised of 110 scaffolds with an average GC content of 44.61%. Of the 4,565 genes predicted, 4,501 were protein-coding genes and 64 were RNA genes. Most protein-coding genes (68.52%) were assigned to a putative function. The identification of 2-keto-4-pentenoate hydratase/2-oxohepta-3-ene-1,7-dioic acid hydratase-coding genes indicates involvement of this organism in the catechol catabolic pathway. In addition, genes encoding for β-1,4-xylanases and β-1,4-xylosidases reveal the xylanolytic action of O. sitiensis. PMID:25197463

Protein-RNA interface residue prediction using machine learning: an assessment of the state of the art.

PubMed

Walia, Rasna R; Caragea, Cornelia; Lewis, Benjamin A; Towfic, Fadi; Terribilini, Michael; El-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2012-05-10

RNA molecules play diverse functional and structural roles in cells. They function as messengers for transferring genetic information from DNA to proteins, as the primary genetic material in many viruses, as catalysts (ribozymes) important for protein synthesis and RNA processing, and as essential and ubiquitous regulators of gene expression in living organisms. Many of these functions depend on precisely orchestrated interactions between RNA molecules and specific proteins in cells. Understanding the molecular mechanisms by which proteins recognize and bind RNA is essential for comprehending the functional implications of these interactions, but the recognition 'code' that mediates interactions between proteins and RNA is not yet understood. Success in deciphering this code would dramatically impact the development of new therapeutic strategies for intervening in devastating diseases such as AIDS and cancer. Because of the high cost of experimental determination of protein-RNA interfaces, there is an increasing reliance on statistical machine learning methods for training predictors of RNA-binding residues in proteins. However, because of differences in the choice of datasets, performance measures, and data representations used, it has been difficult to obtain an accurate assessment of the current state of the art in protein-RNA interface prediction. We provide a review of published approaches for predicting RNA-binding residues in proteins and a systematic comparison and critical assessment of protein-RNA interface residue predictors trained using these approaches on three carefully curated non-redundant datasets. We directly compare two widely used machine learning algorithms (Naïve Bayes (NB) and Support Vector Machine (SVM)) using three different data representations in which features are encoded using either sequence- or structure-based windows. Our results show that (i) Sequence-based classifiers that use a position-specific scoring matrix (PSSM)-based representation (PSSMSeq) outperform those that use an amino acid identity based representation (IDSeq) or a smoothed PSSM (SmoPSSMSeq); (ii) Structure-based classifiers that use smoothed PSSM representation (SmoPSSMStr) outperform those that use PSSM (PSSMStr) as well as sequence identity based representation (IDStr). PSSMSeq classifiers, when tested on an independent test set of 44 proteins, achieve performance that is comparable to that of three state-of-the-art structure-based predictors (including those that exploit geometric features) in terms of Matthews Correlation Coefficient (MCC), although the structure-based methods achieve substantially higher Specificity (albeit at the expense of Sensitivity) compared to sequence-based methods. We also find that the expected performance of the classifiers on a residue level can be markedly different from that on a protein level. Our experiments show that the classifiers trained on three different non-redundant protein-RNA interface datasets achieve comparable cross-validation performance. However, we find that the results are significantly affected by differences in the distance threshold used to define interface residues. Our results demonstrate that protein-RNA interface residue predictors that use a PSSM-based encoding of sequence windows outperform classifiers that use other encodings of sequence windows. While structure-based methods that exploit geometric features can yield significant increases in the Specificity of protein-RNA interface residue predictions, such increases are offset by decreases in Sensitivity. These results underscore the importance of comparing alternative methods using rigorous statistical procedures, multiple performance measures, and datasets that are constructed based on several alternative definitions of interface residues and redundancy cutoffs as well as including evaluations on independent test sets into the comparisons.

Two fundamental questions about protein evolution.

PubMed

Penny, David; Zhong, Bojian

2015-12-01

Two basic questions are considered that approach protein evolution from different directions; the problems arising from using Markov models for the deeper divergences, and then the origin of proteins themselves. The real problem for the first question (going backwards in time) is that at deeper phylogenies the Markov models of sequence evolution must lose information exponentially at deeper divergences, and several testable methods are suggested that should help resolve these deeper divergences. For the second question (coming forwards in time) a problem is that most models for the origin of protein synthesis do not give a role for the very earliest stages of the process. From our knowledge of the importance of replication accuracy in limiting the length of a coding molecule, a testable hypothesis is proposed. The length of the code, the code itself, and tRNAs would all have prior roles in increasing the accuracy of RNA replication; thus proteins would have been formed only after the tRNAs and the length of the triplet code are already formed. Both questions lead to testable predictions. Copyright © 2014 Elsevier B.V. and Société Française de Biochimie et Biologie Moléculaire (SFBBM). All rights reserved.

AMS 4.0: consensus prediction of post-translational modifications in protein sequences.

PubMed

Plewczynski, Dariusz; Basu, Subhadip; Saha, Indrajit

2012-08-01

We present here the 2011 update of the AutoMotif Service (AMS 4.0) that predicts the wide selection of 88 different types of the single amino acid post-translational modifications (PTM) in protein sequences. The selection of experimentally confirmed modifications is acquired from the latest UniProt and Phospho.ELM databases for training. The sequence vicinity of each modified residue is represented using amino acids physico-chemical features encoded using high quality indices (HQI) obtaining by automatic clustering of known indices extracted from AAindex database. For each type of the numerical representation, the method builds the ensemble of Multi-Layer Perceptron (MLP) pattern classifiers, each optimising different objectives during the training (for example the recall, precision or area under the ROC curve (AUC)). The consensus is built using brainstorming technology, which combines multi-objective instances of machine learning algorithm, and the data fusion of different training objects representations, in order to boost the overall prediction accuracy of conserved short sequence motifs. The performance of AMS 4.0 is compared with the accuracy of previous versions, which were constructed using single machine learning methods (artificial neural networks, support vector machine). Our software improves the average AUC score of the earlier version by close to 7 % as calculated on the test datasets of all 88 PTM types. Moreover, for the selected most-difficult sequence motifs types it is able to improve the prediction performance by almost 32 %, when compared with previously used single machine learning methods. Summarising, the brainstorming consensus meta-learning methodology on the average boosts the AUC score up to around 89 %, averaged over all 88 PTM types. Detailed results for single machine learning methods and the consensus methodology are also provided, together with the comparison to previously published methods and state-of-the-art software tools. The source code and precompiled binaries of brainstorming tool are available at http://code.google.com/p/automotifserver/ under Apache 2.0 licensing.

Beyond the Triplet Code: Context Cues Transform Translation.

PubMed

Brar, Gloria A

2016-12-15

The elucidation of the genetic code remains among the most influential discoveries in biology. While innumerable studies have validated the general universality of the code and its value in predicting and analyzing protein coding sequences, established and emerging work has also suggested that full genome decryption may benefit from a greater consideration of a codon's neighborhood within an mRNA than has been broadly applied. This Review examines the evidence for context cues in translation, with a focus on several recent studies that reveal broad roles for mRNA context in programming translation start sites, the rate of translation elongation, and stop codon identity. Copyright © 2016 Elsevier Inc. All rights reserved.

Proteus: a random forest classifier to predict disorder-to-order transitioning binding regions in intrinsically disordered proteins

NASA Astrophysics Data System (ADS)

Basu, Sankar; Söderquist, Fredrik; Wallner, Björn

2017-05-01

The focus of the computational structural biology community has taken a dramatic shift over the past one-and-a-half decades from the classical protein structure prediction problem to the possible understanding of intrinsically disordered proteins (IDP) or proteins containing regions of disorder (IDPR). The current interest lies in the unraveling of a disorder-to-order transitioning code embedded in the amino acid sequences of IDPs/IDPRs. Disordered proteins are characterized by an enormous amount of structural plasticity which makes them promiscuous in binding to different partners, multi-functional in cellular activity and atypical in folding energy landscapes resembling partially folded molten globules. Also, their involvement in several deadly human diseases (e.g. cancer, cardiovascular and neurodegenerative diseases) makes them attractive drug targets, and important for a biochemical understanding of the disease(s). The study of the structural ensemble of IDPs is rather difficult, in particular for transient interactions. When bound to a structured partner, an IDPR adapts an ordered conformation in the complex. The residues that undergo this disorder-to-order transition are called protean residues, generally found in short contiguous stretches and the first step in understanding the modus operandi of an IDP/IDPR would be to predict these residues. There are a few available methods which predict these protean segments from their amino acid sequences; however, their performance reported in the literature leaves clear room for improvement. With this background, the current study presents `Proteus', a random forest classifier that predicts the likelihood of a residue undergoing a disorder-to-order transition upon binding to a potential partner protein. The prediction is based on features that can be calculated using the amino acid sequence alone. Proteus compares favorably with existing methods predicting twice as many true positives as the second best method (55 vs. 27%) with a much higher precision on an independent data set. The current study also sheds some light on a possible `disorder-to-order' transitioning consensus, untangled, yet embedded in the amino acid sequence of IDPs. Some guidelines have also been suggested for proceeding with a real-life structural modeling involving an IDPR using Proteus.

Molecular cloning and functional characterization of an antifungal PR-5 protein from Ocimum basilicum.

PubMed

Rather, Irshad Ahmad; Awasthi, Praveen; Mahajan, Vidushi; Bedi, Yashbir S; Vishwakarma, Ram A; Gandhi, Sumit G

2015-03-01

Pathogenesis-related (PR) proteins are involved in biotic and abiotic stress responses of plants and are grouped into 17 families (PR-1 to PR-17). PR-5 family includes proteins related to thaumatin and osmotin, with several members possessing antimicrobial properties. In this study, a PR-5 gene showing a high degree of homology with osmotin-like protein was isolated from sweet basil (Ocimum basilicum L.). A complete open reading frame consisting of 675 nucleotides, coding for a precursor protein, was obtained by PCR amplification. Based on sequence comparisons with tobacco osmotin and other osmotin-like proteins (OLPs), this protein was named ObOLP. The predicted mature protein is 225 amino acids in length and contains 16 cysteine residues that may potentially form eight disulfide bonds, a signature common to most PR-5 proteins. Among the various abiotic stress treatments tested, including high salt, mechanical wounding and exogenous phytohormone/elicitor treatments; methyl jasmonate (MeJA) and mechanical wounding significantly induced the expression of ObOLP gene. The coding sequence of ObOLP was cloned and expressed in a bacterial host resulting in a 25kDa recombinant-HIS tagged protein, displaying antifungal activity. The ObOLP protein sequence appears to contain an N-terminal signal peptide with signatures of secretory pathway. Further, our experimental data shows that ObOLP expression is regulated transcriptionally and in silico analysis suggests that it may be post-transcriptionally and post-translationally regulated through microRNAs and post-translational protein modifications, respectively. This study appears to be the first report of isolation and characterization of osmotin-like protein gene from O. basilicum. Copyright © 2014 Elsevier B.V. All rights reserved.

Protein structure and the sequential structure of mRNA: alpha-helix and beta-sheet signals at the nucleotide level.

PubMed

Brunak, S; Engelbrecht, J

1996-06-01

A direct comparison of experimentally determined protein structures and their corresponding protein coding mRNA sequences has been performed. We examine whether real world data support the hypothesis that clusters of rare codons correlate with the location of structural units in the resulting protein. The degeneracy of the genetic code allows for a biased selection of codons which may control the translational rate of the ribosome, and may thus in vivo have a catalyzing effect on the folding of the polypeptide chain. A complete search for GenBank nucleotide sequences coding for structural entries in the Brookhaven Protein Data Bank produced 719 protein chains with matching mRNA sequence, amino acid sequence, and secondary structure assignment. By neural network analysis, we found strong signals in mRNA sequence regions surrounding helices and sheets. These signals do not originate from the clustering of rare codons, but from the similarity of codons coding for very abundant amino acid residues at the N- and C-termini of helices and sheets. No correlation between the positioning of rare codons and the location of structural units was found. The mRNA signals were also compared with conserved nucleotide features of 16S-like ribosomal RNA sequences and related to mechanisms for maintaining the correct reading frame by the ribosome.

Nucleotide sequence of the gag gene and gag-pol junction of feline leukemia virus.

PubMed Central

Laprevotte, I; Hampe, A; Sherr, C J; Galibert, F

1984-01-01

The nucleotide sequence of the gag gene of feline leukemia virus and its flanking sequences were determined and compared with the corresponding sequences of two strains of feline sarcoma virus and with that of the Moloney strain of murine leukemia virus. A high degree of nucleotide sequence homology between the feline leukemia virus and murine leukemia virus gag genes was observed, suggesting that retroviruses of domestic cats and laboratory mice have a common, proximal evolutionary progenitor. The predicted structure of the complete feline leukemia virus gag gene precursor suggests that the translation of nonglycosylated and glycosylated gag gene polypeptides is initiated at two different AUG codons. These initiator codons fall in the same reading frame and are separated by a 222-base-pair segment which encodes an amino terminal signal peptide. The nucleotide sequence predicts the order of amino acids in each of the individual gag-coded proteins (p15, p12, p30, p10), all of which derive from the gag gene precursor. Stable stem-and-loop secondary structures are proposed for two regions of viral RNA. The first falls within sequences at the 5' end of the viral genome, together with adjacent palindromic sequences which may play a role in dimer linkage of RNA subunits. The second includes coding sequences at the gag-pol junction and is proposed to be involved in translation of the pol gene product. Sequence analysis of the latter region shows that the gag and pol genes are translated in different reading frames. Classical consensus splice donor and acceptor sequences could not be localized to regions which would permit synthesis of the expected gag-pol precursor protein. Alternatively, we suggest that the pol gene product (RNA-dependent DNA polymerase) could be translated by a frameshift suppressing mechanism which could involve cleavage modification of stems and loops in a manner similar to that observed in tRNA processing. PMID:6328019

Diverse RNA-binding proteins interact with functionally related sets of RNAs, suggesting an extensive regulatory system.

PubMed

Hogan, Daniel J; Riordan, Daniel P; Gerber, André P; Herschlag, Daniel; Brown, Patrick O

2008-10-28

RNA-binding proteins (RBPs) have roles in the regulation of many post-transcriptional steps in gene expression, but relatively few RBPs have been systematically studied. We searched for the RNA targets of 40 proteins in the yeast Saccharomyces cerevisiae: a selective sample of the approximately 600 annotated and predicted RBPs, as well as several proteins not annotated as RBPs. At least 33 of these 40 proteins, including three of the four proteins that were not previously known or predicted to be RBPs, were reproducibly associated with specific sets of a few to several hundred RNAs. Remarkably, many of the RBPs we studied bound mRNAs whose protein products share identifiable functional or cytotopic features. We identified specific sequences or predicted structures significantly enriched in target mRNAs of 16 RBPs. These potential RNA-recognition elements were diverse in sequence, structure, and location: some were found predominantly in 3'-untranslated regions, others in 5'-untranslated regions, some in coding sequences, and many in two or more of these features. Although this study only examined a small fraction of the universe of yeast RBPs, 70% of the mRNA transcriptome had significant associations with at least one of these RBPs, and on average, each distinct yeast mRNA interacted with three of the RBPs, suggesting the potential for a rich, multidimensional network of regulation. These results strongly suggest that combinatorial binding of RBPs to specific recognition elements in mRNAs is a pervasive mechanism for multi-dimensional regulation of their post-transcriptional fate.

Non-coding RNAs in lung cancer

PubMed Central

Ricciuti, Biagio; Mecca, Carmen; Crinò, Lucio; Baglivo, Sara; Cenci, Matteo; Metro, Giulio

2014-01-01

The discovery that protein-coding genes represent less than 2% of all human genome, and the evidence that more than 90% of it is actively transcribed, changed the classical point of view of the central dogma of molecular biology, which was always based on the assumption that RNA functions mainly as an intermediate bridge between DNA sequences and protein synthesis machinery. Accumulating data indicates that non-coding RNAs are involved in different physiological processes, providing for the maintenance of cellular homeostasis. They are important regulators of gene expression, cellular differentiation, proliferation, migration, apoptosis, and stem cell maintenance. Alterations and disruptions of their expression or activity have increasingly been associated with pathological changes of cancer cells, this evidence and the prospect of using these molecules as diagnostic markers and therapeutic targets, make currently non-coding RNAs among the most relevant molecules in cancer research. In this paper we will provide an overview of non-coding RNA function and disruption in lung cancer biology, also focusing on their potential as diagnostic, prognostic and predictive biomarkers. PMID:25593996

On the Origin of Protein Superfamilies and Superfolds

NASA Astrophysics Data System (ADS)

Magner, Abram; Szpankowski, Wojciech; Kihara, Daisuke

2015-02-01

Distributions of protein families and folds in genomes are highly skewed, having a small number of prevalent superfamiles/superfolds and a large number of families/folds of a small size. Why are the distributions of protein families and folds skewed? Why are there only a limited number of protein families? Here, we employ an information theoretic approach to investigate the protein sequence-structure relationship that leads to the skewed distributions. We consider that protein sequences and folds constitute an information theoretic channel and computed the most efficient distribution of sequences that code all protein folds. The identified distributions of sequences and folds are found to follow a power law, consistent with those observed for proteins in nature. Importantly, the skewed distributions of sequences and folds are suggested to have different origins: the skewed distribution of sequences is due to evolutionary pressure to achieve efficient coding of necessary folds, whereas that of folds is based on the thermodynamic stability of folds. The current study provides a new information theoretic framework for proteins that could be widely applied for understanding protein sequences, structures, functions, and interactions.

Translational resistivity/conductivity of coding sequences during exponential growth of Escherichia coli.

PubMed

Takai, Kazuyuki

2017-01-21

Codon adaptation index (CAI) has been widely used for prediction of expression of recombinant genes in Escherichia coli and other organisms. However, CAI has no mechanistic basis that rationalizes its application to estimation of translational efficiency. Here, I propose a model based on which we could consider how codon usage is related to the level of expression during exponential growth of bacteria. In this model, translation of a gene is considered as an analog of electric current, and an analog of electric resistance corresponding to each gene is considered. "Translational resistance" is dependent on the steady-state concentration and the sequence of the mRNA species, and "translational resistivity" is dependent only on the mRNA sequence. The latter is the sum of two parts: one is the resistivity for the elongation reaction (coding sequence resistivity), and the other comes from all of the other steps of the decoding reaction. This electric circuit model clearly shows that some conditions should be met for codon composition of a coding sequence to correlate well with its expression level. On the other hand, I calculated relative frequency of each of the 61 sense codon triplets translated during exponential growth of E. coli from a proteomic dataset covering over 2600 proteins. A tentative method for estimating relative coding sequence resistivity based on the data is presented. Copyright © 2016. Published by Elsevier Ltd.

Identification of new stress-induced microRNA and their targets in wheat using computational approach.

PubMed

Pandey, Bharati; Gupta, Om Prakash; Pandey, Dev Mani; Sharma, Indu; Sharma, Pradeep

2013-05-01

MicroRNAs (miRNAs) are a class of short endogenous non-coding small RNA molecules of about 18-22 nucleotides in length. Their main function is to downregulate gene expression in different manners like translational repression, mRNA cleavage and epigenetic modification. Computational predictions have raised the number of miRNAs in wheat significantly using an EST based approach. Hence, a combinatorial approach which is amalgamation of bioinformatics software and perl script was used to identify new miRNA to add to the growing database of wheat miRNA. Identification of miRNAs was initiated by mining the EST (Expressed Sequence Tags) database available at National Center for Biotechnology Information. In this investigation, 4677 mature microRNA sequences belonging to 50 miRNA families from different plant species were used to predict miRNA in wheat. A total of five abiotic stress-responsive new miRNAs were predicted and named Ta-miR5653, Ta-miR855, Ta-miR819k, Ta-miR3708 and Ta-miR5156. In addition, four previously identified miRNA, i.e., Ta-miR1122, miR1117, Ta-miR1134 and Ta-miR1133 were predicted in newly identified EST sequence and 14 potential target genes were subsequently predicted, most of which seems to encode ubiquitin carrier protein, serine/threonine protein kinase, 40S ribosomal protein, F-box/kelch-repeat protein, BTB/POZ domain-containing protein, transcription factors which are involved in growth, development, metabolism and stress response. Our result has increased the number of miRNAs in wheat, which should be useful for further investigation into the biological functions and evolution of miRNAs in wheat and other plant species.

Genome Sequence of Microbulbifer mangrovi DD-13T Reveals Its Versatility to Degrade Multiple Polysaccharides.

PubMed

Imran, Md; Pant, Poonam; Shanbhag, Yogini P; Sawant, Samir V; Ghadi, Sanjeev C

2017-02-01

Microbulbifer mangrovi strain DD-13 T is a novel-type species isolated from the mangroves of Goa, India. The draft genome sequence of strain DD-13 comprised 4,528,106 bp with G+C content of 57.15%. Out of 3479 open reading frames, functions for 3488 protein coding sequences were predicted on the basis of similarity with the cluster of orthologous groups. In addition to protein coding sequences, 34 tRNA genes and 3 rRNA genes were detected. Analysis of nucleotide sequence of predicted gene using a Carbohydrate-Active Enzymes (CAZymes) Analysis Toolkit indicates that strain DD-13 encodes a large set of CAZymes including 255 glycoside hydrolases, 76 carbohydrate esterases, 17 polysaccharide lyases, and 113 carbohydrate-binding modules (CBMs). Many genes from strain DD-13 were annotated as carbohydrases specific for degradation of agar, alginate, carrageenan, chitin, xylan, pullulan, cellulose, starch, β-glucan, pectin, etc. Some of polysaccharide-degrading genes were highly modular and were appended at least with one CBM indicating the versatility of strain DD-13 to degrade complex polysaccharides. The cell growth of strain DD-13 was validated using pure polysaccharides such as agarose or alginate as carbon source as well as by using red and brown seaweed powder as substrate. The homologous carbohydrase produced by strain DD-13 during growth degraded the polysaccharide, ensuring the production of metabolizable reducing sugars. Additionally, several other polysaccharides such as carrageenan, xylan, pullulan, pectin, starch, and carboxymethyl cellulose were also corroborated as growth substrate for strain DD-13 and were associated with concomitant production of homologous carbohydrase.

Molecular cloning, sequence characterization and recombinant expression of Nanog gene in goat fibroblast cells using lentiviral based expression system.

PubMed

Singhal, Dinesh K; Singhal, Raxita; Malik, Hruda N; Kumar, Surender; Kumar, Sudarshan; Mohanty, Ashok K; Kaushik, Jai K; Malakar, Dhruba

2014-01-01

Nanog is a homeodomain containing protein which plays important roles in regulation of signaling pathways for maintenance and induction of pluripotency in stem cells. Because of its unique expression in stem cells it is also regarded as pluripotency marker. In this study goat Nanog (gNanog) gene has been amplified, cloned and characterized at sequence level with successful over-expression in CHO-K1 cell line using a lentiviral based system. gNanog ORF is 903 bp long which codes for Nanog protein of size 300 amino acids (aas). Complete nucleotide sequence shows some evolutionary mutation in goat in comparision to other species. Protein sequence of goat is highly similar to other species. Overall, gNanog nucleotide sequence and predicted protein sequence showed high similarity and minimum divergence with cattle (96 % identity/4 % divergence) and buffalo (94/5 %) while low similarity and high divergence with pig (84/15 %), human (81/23 %) and mouse (69/40 %) indicating evolutionary closeness of gNanog to cattle and buffalo. gNanog lentiviral expression construct was prepared for over-expression of Nanog gene in adult goat fibroblast cells. Lentiviral expression construct of Nanog enabled continuous protein expression for induction and maintenance of pluripotency. Western blotting revealed the expression of Nanog gene at protein level which supported that the lentiviral expression system is highly promising for Nanog protein expression in differentiated goat cell.

A novel class of plant-specific zinc-dependent DNA-binding protein that binds to A/T-rich DNA sequences

PubMed Central

Nagano, Yukio; Furuhashi, Hirofumi; Inaba, Takehito; Sasaki, Yukiko

2001-01-01

Complementary DNA encoding a DNA-binding protein, designated PLATZ1 (plant AT-rich sequence- and zinc-binding protein 1), was isolated from peas. The amino acid sequence of the protein is similar to those of other uncharacterized proteins predicted from the genome sequences of higher plants. However, no paralogous sequences have been found outside the plant kingdom. Multiple alignments among these paralogous proteins show that several cysteine and histidine residues are invariant, suggesting that these proteins are a novel class of zinc-dependent DNA-binding proteins with two distantly located regions, C-x2-H-x11-C-x2-C-x(4–5)-C-x2-C-x(3–7)-H-x2-H and C-x2-C-x(10–11)-C-x3-C. In an electrophoretic mobility shift assay, the zinc chelator 1,10-o-phenanthroline inhibited DNA binding, and two distant zinc-binding regions were required for DNA binding. A protein blot with 65ZnCl2 showed that both regions are required for zinc-binding activity. The PLATZ1 protein non-specifically binds to A/T-rich sequences, including the upstream region of the pea GTPase pra2 and plastocyanin petE genes. Expression of the PLATZ1 repressed those of the reporter constructs containing the coding sequence of luciferase gene driven by the cauliflower mosaic virus (CaMV) 35S90 promoter fused to the tandem repeat of the A/T-rich sequences. These results indicate that PLATZ1 is a novel class of plant-specific zinc-dependent DNA-binding protein responsible for A/T-rich sequence-mediated transcriptional repression. PMID:11600698

Application of 2D graphic representation of protein sequence based on Huffman tree method.

PubMed

Qi, Zhao-Hui; Feng, Jun; Qi, Xiao-Qin; Li, Ling

2012-05-01

Based on Huffman tree method, we propose a new 2D graphic representation of protein sequence. This representation can completely avoid loss of information in the transfer of data from a protein sequence to its graphic representation. The method consists of two parts. One is about the 0-1 codes of 20 amino acids by Huffman tree with amino acid frequency. The amino acid frequency is defined as the statistical number of an amino acid in the analyzed protein sequences. The other is about the 2D graphic representation of protein sequence based on the 0-1 codes. Then the applications of the method on ten ND5 genes and seven Escherichia coli strains are presented in detail. The results show that the proposed model may provide us with some new sights to understand the evolution patterns determined from protein sequences and complete genomes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Draft Genome Sequence of Mycobacterium boenickei CIP 107829.

PubMed

Bouam, Amar; Robert, Catherine; Croce, Olivier; Levasseur, Anthony; Drancourt, Michel

2017-05-04

Mycobacterium boenickei is a rapidly growing mycobacterium isolated for the first time from a leg wound in the United States. Its 6,506,908-bp draft genome exhibits a 66.77% G+C content, 6,279 protein-coding genes, and 59 predicted RNA genes. In silico DNA-DNA hybridization confirms its assignment to the Mycobacterium fortuitum complex. Copyright © 2017 Bouam et al.

Prunus necrotic ringspot ilarvirus: nucleotide sequence of RNA3 and the relationship to other ilarviruses based on coat protein comparison.

PubMed

Guo, D; Maiss, E; Adam, G; Casper, R

1995-05-01

The RNA3 of prunus necrotic ringspot ilarvirus (PNRSV) has been cloned and its entire sequence determined. The RNA3 consists of 1943 nucleotides (nt) and possesses two large open reading frames (ORFs) separated by an intergenic region of 74 nt. The 5' proximal ORF is 855 nt in length and codes for a protein of molecular mass 31.4 kDa which has homologies with the putative movement protein of other members of the Bromoviridae. The 3' proximal ORF of 675 nt is the cistron for the coat protein (CP) and has a predicted molecular mass of 24.9 kDa. The sequence of the 3' non-coding region (NCR) of PNRSV RNA3 showed a high degree of similarity with those of tobacco streak virus (TSV), prune dwarf virus (PDV), apple mosaic virus (ApMV) and also alfalfa mosaic virus (AIMV). In addition it contained potential stem-loop structures with interspersed AUGC motifs characteristic for ilar- and alfamoviruses. This conserved primary and secondary structure in all 3' NCRs may be responsible for the interaction with homologous and heterologous CPs and subsequent activation of genome replication. The CP gene of an ApMV isolate (ApMV-G) of 657 nt has also been cloned and sequenced. Although ApMV and PNRSV have a distant serological relationship, the deduced amino acid sequences of their CPs have an identity of only 51.8%. The N termini of PNRSV and ApMV CPs have in common a zinc-finger motif and the potential to form an amphipathic helix.

Long Non-coding RNAs and Their Biological Roles in Plants

PubMed Central

Liu, Xue; Hao, Lili; Li, Dayong; Zhu, Lihuang; Hu, Songnian

2015-01-01

With the development of genomics and bioinformatics, especially the extensive applications of high-throughput sequencing technology, more transcriptional units with little or no protein-coding potential have been discovered. Such RNA molecules are called non-protein-coding RNAs (npcRNAs or ncRNAs). Among them, long npcRNAs or ncRNAs (lnpcRNAs or lncRNAs) represent diverse classes of transcripts longer than 200 nucleotides. In recent years, the lncRNAs have been considered as important regulators in many essential biological processes. In plants, although a large number of lncRNA transcripts have been predicted and identified in few species, our current knowledge of their biological functions is still limited. Here, we have summarized recent studies on their identification, characteristics, classification, bioinformatics, resources, and current exploration of their biological functions in plants. PMID:25936895

Bacillus anthracis genome organization in light of whole transcriptome sequencing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martin, Jeffrey; Zhu, Wenhan; Passalacqua, Karla D.

2010-03-22

Emerging knowledge of whole prokaryotic transcriptomes could validate a number of theoretical concepts introduced in the early days of genomics. What are the rules connecting gene expression levels with sequence determinants such as quantitative scores of promoters and terminators? Are translation efficiency measures, e.g. codon adaptation index and RBS score related to gene expression? We used the whole transcriptome shotgun sequencing of a bacterial pathogen Bacillus anthracis to assess correlation of gene expression level with promoter, terminator and RBS scores, codon adaptation index, as well as with a new measure of gene translational efficiency, average translation speed. We compared computationalmore » predictions of operon topologies with the transcript borders inferred from RNA-Seq reads. Transcriptome mapping may also improve existing gene annotation. Upon assessment of accuracy of current annotation of protein-coding genes in the B. anthracis genome we have shown that the transcriptome data indicate existence of more than a hundred genes missing in the annotation though predicted by an ab initio gene finder. Interestingly, we observed that many pseudogenes possess not only a sequence with detectable coding potential but also promoters that maintain transcriptional activity.« less

The Intolerance of Regulatory Sequence to Genetic Variation Predicts Gene Dosage Sensitivity

PubMed Central

Wang, Quanli; Halvorsen, Matt; Han, Yujun; Weir, William H.; Allen, Andrew S.; Goldstein, David B.

2015-01-01

Noncoding sequence contains pathogenic mutations. Yet, compared with mutations in protein-coding sequence, pathogenic regulatory mutations are notoriously difficult to recognize. Most fundamentally, we are not yet adept at recognizing the sequence stretches in the human genome that are most important in regulating the expression of genes. For this reason, it is difficult to apply to the regulatory regions the same kinds of analytical paradigms that are being successfully applied to identify mutations among protein-coding regions that influence risk. To determine whether dosage sensitive genes have distinct patterns among their noncoding sequence, we present two primary approaches that focus solely on a gene’s proximal noncoding regulatory sequence. The first approach is a regulatory sequence analogue of the recently introduced residual variation intolerance score (RVIS), termed noncoding RVIS, or ncRVIS. The ncRVIS compares observed and predicted levels of standing variation in the regulatory sequence of human genes. The second approach, termed ncGERP, reflects the phylogenetic conservation of a gene’s regulatory sequence using GERP++. We assess how well these two approaches correlate with four gene lists that use different ways to identify genes known or likely to cause disease through changes in expression: 1) genes that are known to cause disease through haploinsufficiency, 2) genes curated as dosage sensitive in ClinGen’s Genome Dosage Map, 3) genes judged likely to be under purifying selection for mutations that change expression levels because they are statistically depleted of loss-of-function variants in the general population, and 4) genes judged unlikely to cause disease based on the presence of copy number variants in the general population. We find that both noncoding scores are highly predictive of dosage sensitivity using any of these criteria. In a similar way to ncGERP, we assess two ensemble-based predictors of regional noncoding importance, ncCADD and ncGWAVA, and find both scores are significantly predictive of human dosage sensitive genes and appear to carry information beyond conservation, as assessed by ncGERP. These results highlight that the intolerance of noncoding sequence stretches in the human genome can provide a critical complementary tool to other genome annotation approaches to help identify the parts of the human genome increasingly likely to harbor mutations that influence risk of disease. PMID:26332131

The genome of obligately intracellular Ehrlichia canis revealsthemes of complex membrane structure and immune evasion strategies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mavromatis, K.; Kuyler Doyle, C.; Lykidis, A.

2005-09-01

Ehrlichia canis, a small obligately intracellular, tick-transmitted, gram-negative, a-proteobacterium is the primary etiologic agent of globally distributed canine monocytic ehrlichiosis. Complete genome sequencing revealed that the E. canis genome consists of a single circular chromosome of 1,315,030 bp predicted to encode 925 proteins, 40 stable RNA species, and 17 putative pseudogenes, and a substantial proportion of non-coding sequence (27 percent). Interesting genome features include a large set of proteins with transmembrane helices and/or signal sequences, and a unique serine-threonine bias associated with the potential for O-glycosylation that was prominent in proteins associated with pathogen-host interactions. Furthermore, two paralogous protein familiesmore » associated with immune evasion were identified, one of which contains poly G:C tracts, suggesting that they may play a role in phase variation and facilitation of persistent infections. Proteins associated with pathogen-host interactions were identified including a small group of proteins (12) with tandem repeats and another with eukaryotic-like ankyrin domains (7).« less

Molecular cloning of a cDNA coding for GTP cyclohydrolase I from Dictyostelium discoideum.

PubMed Central

Witter, K; Cahill, D J; Werner, T; Ziegler, I; Rödl, W; Bacher, A; Gütlich, M

1996-01-01

The GTP cyclohydrolase I (GTP-CH) gene of the cellular slime mould Dictyostelium discoideum has been cloned and sequenced. The 855 bp cDNA of this gene contains the open reading frame (ORF) encoding 232 amino acids with a predicted molecular mass of approx. 26 kDa. Southern blot analysis indicated the presence of a single gene for GTP-CH in Dictyostelium. PCR amplification of the ORF from chromosomal DNA and sequencing showed the existence of a 101 bp intron in the GTP-CH gene of Dictyostelium discoideum. The amino acid sequence has 47% and 49% positional identity to those of the human and yeast enzymes respectively. Most of the sequence variation between species is located in the N-terminal part of the protein. The overall identity with the E. coli protein is markedly lower. The enzyme was expressed in E. coli and purified as a 68 kDa fusion protein with the maltose-binding protein of E. coli. GTP-CH of Dictyostelium is heat-stable and showed maximal activity at 60 degrees C. The Km value for GTP is 50 microM. PMID:8870645

Improving the genome annotation of the acarbose producer Actinoplanes sp. SE50/110 by sequencing enriched 5'-ends of primary transcripts.

PubMed

Schwientek, Patrick; Neshat, Armin; Kalinowski, Jörn; Klein, Andreas; Rückert, Christian; Schneiker-Bekel, Susanne; Wendler, Sergej; Stoye, Jens; Pühler, Alfred

2014-11-20

Actinoplanes sp. SE50/110 is the producer of the alpha-glucosidase inhibitor acarbose, which is an economically relevant and potent drug in the treatment of type-2 diabetes mellitus. In this study, we present the detection of transcription start sites on this genome by sequencing enriched 5'-ends of primary transcripts. Altogether, 1427 putative transcription start sites were initially identified. With help of the annotated genome sequence, 661 transcription start sites were found to belong to the leader region of protein-coding genes with the surprising result that roughly 20% of these genes rank among the class of leaderless transcripts. Next, conserved promoter motifs were identified for protein-coding genes with and without leader sequences. The mapped transcription start sites were finally used to improve the annotation of the Actinoplanes sp. SE50/110 genome sequence. Concerning protein-coding genes, 41 translation start sites were corrected and 9 novel protein-coding genes could be identified. In addition to this, 122 previously undetermined non-coding RNA (ncRNA) genes of Actinoplanes sp. SE50/110 were defined. Focusing on antisense transcription start sites located within coding genes or their leader sequences, it was discovered that 96 of those ncRNA genes belong to the class of antisense RNA (asRNA) genes. The remaining 26 ncRNA genes were found outside of known protein-coding genes. Four chosen examples of prominent ncRNA genes, namely the transfer messenger RNA gene ssrA, the ribonuclease P class A RNA gene rnpB, the cobalamin riboswitch RNA gene cobRS, and the selenocysteine-specific tRNA gene selC, are presented in more detail. This study demonstrates that sequencing of enriched 5'-ends of primary transcripts and the identification of transcription start sites are valuable tools for advanced genome annotation of Actinoplanes sp. SE50/110 and most probably also for other bacteria. Copyright © 2014 Elsevier B.V. All rights reserved.

A multi-objective optimization approach accurately resolves protein domain architectures

PubMed Central

Bernardes, J.S.; Vieira, F.R.J.; Zaverucha, G.; Carbone, A.

2016-01-01

Motivation: Given a protein sequence and a number of potential domains matching it, what are the domain content and the most likely domain architecture for the sequence? This problem is of fundamental importance in protein annotation, constituting one of the main steps of all predictive annotation strategies. On the other hand, when potential domains are several and in conflict because of overlapping domain boundaries, finding a solution for the problem might become difficult. An accurate prediction of the domain architecture of a multi-domain protein provides important information for function prediction, comparative genomics and molecular evolution. Results: We developed DAMA (Domain Annotation by a Multi-objective Approach), a novel approach that identifies architectures through a multi-objective optimization algorithm combining scores of domain matches, previously observed multi-domain co-occurrence and domain overlapping. DAMA has been validated on a known benchmark dataset based on CATH structural domain assignments and on the set of Plasmodium falciparum proteins. When compared with existing tools on both datasets, it outperforms all of them. Availability and implementation: DAMA software is implemented in C++ and the source code can be found at http://www.lcqb.upmc.fr/DAMA. Contact: juliana.silva_bernardes@upmc.fr or alessandra.carbone@lip6.fr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26458889

Prediction and analysis of protein solubility using a novel scoring card method with dipeptide composition

PubMed Central

2012-01-01

Background Existing methods for predicting protein solubility on overexpression in Escherichia coli advance performance by using ensemble classifiers such as two-stage support vector machine (SVM) based classifiers and a number of feature types such as physicochemical properties, amino acid and dipeptide composition, accompanied with feature selection. It is desirable to develop a simple and easily interpretable method for predicting protein solubility, compared to existing complex SVM-based methods. Results This study proposes a novel scoring card method (SCM) by using dipeptide composition only to estimate solubility scores of sequences for predicting protein solubility. SCM calculates the propensities of 400 individual dipeptides to be soluble using statistic discrimination between soluble and insoluble proteins of a training data set. Consequently, the propensity scores of all dipeptides are further optimized using an intelligent genetic algorithm. The solubility score of a sequence is determined by the weighted sum of all propensity scores and dipeptide composition. To evaluate SCM by performance comparisons, four data sets with different sizes and variation degrees of experimental conditions were used. The results show that the simple method SCM with interpretable propensities of dipeptides has promising performance, compared with existing SVM-based ensemble methods with a number of feature types. Furthermore, the propensities of dipeptides and solubility scores of sequences can provide insights to protein solubility. For example, the analysis of dipeptide scores shows high propensity of α-helix structure and thermophilic proteins to be soluble. Conclusions The propensities of individual dipeptides to be soluble are varied for proteins under altered experimental conditions. For accurately predicting protein solubility using SCM, it is better to customize the score card of dipeptide propensities by using a training data set under the same specified experimental conditions. The proposed method SCM with solubility scores and dipeptide propensities can be easily applied to the protein function prediction problems that dipeptide composition features play an important role. Availability The used datasets, source codes of SCM, and supplementary files are available at http://iclab.life.nctu.edu.tw/SCM/. PMID:23282103

Validating a Coarse-Grained Potential Energy Function through Protein Loop Modelling

PubMed Central

MacDonald, James T.; Kelley, Lawrence A.; Freemont, Paul S.

2013-01-01

Coarse-grained (CG) methods for sampling protein conformational space have the potential to increase computational efficiency by reducing the degrees of freedom. The gain in computational efficiency of CG methods often comes at the expense of non-protein like local conformational features. This could cause problems when transitioning to full atom models in a hierarchical framework. Here, a CG potential energy function was validated by applying it to the problem of loop prediction. A novel method to sample the conformational space of backbone atoms was benchmarked using a standard test set consisting of 351 distinct loops. This method used a sequence-independent CG potential energy function representing the protein using -carbon positions only and sampling conformations with a Monte Carlo simulated annealing based protocol. Backbone atoms were added using a method previously described and then gradient minimised in the Rosetta force field. Despite the CG potential energy function being sequence-independent, the method performed similarly to methods that explicitly use either fragments of known protein backbones with similar sequences or residue-specific /-maps to restrict the search space. The method was also able to predict with sub-Angstrom accuracy two out of seven loops from recently solved crystal structures of proteins with low sequence and structure similarity to previously deposited structures in the PDB. The ability to sample realistic loop conformations directly from a potential energy function enables the incorporation of additional geometric restraints and the use of more advanced sampling methods in a way that is not possible to do easily with fragment replacement methods and also enable multi-scale simulations for protein design and protein structure prediction. These restraints could be derived from experimental data or could be design restraints in the case of computational protein design. C++ source code is available for download from http://www.sbg.bio.ic.ac.uk/phyre2/PD2/. PMID:23824634

Robust enzyme design: bioinformatic tools for improved protein stability.

PubMed

Suplatov, Dmitry; Voevodin, Vladimir; Švedas, Vytas

2015-03-01

The ability of proteins and enzymes to maintain a functionally active conformation under adverse environmental conditions is an important feature of biocatalysts, vaccines, and biopharmaceutical proteins. From an evolutionary perspective, robust stability of proteins improves their biological fitness and allows for further optimization. Viewed from an industrial perspective, enzyme stability is crucial for the practical application of enzymes under the required reaction conditions. In this review, we analyze bioinformatic-driven strategies that are used to predict structural changes that can be applied to wild type proteins in order to produce more stable variants. The most commonly employed techniques can be classified into stochastic approaches, empirical or systematic rational design strategies, and design of chimeric proteins. We conclude that bioinformatic analysis can be efficiently used to study large protein superfamilies systematically as well as to predict particular structural changes which increase enzyme stability. Evolution has created a diversity of protein properties that are encoded in genomic sequences and structural data. Bioinformatics has the power to uncover this evolutionary code and provide a reproducible selection of hotspots - key residues to be mutated in order to produce more stable and functionally diverse proteins and enzymes. Further development of systematic bioinformatic procedures is needed to organize and analyze sequences and structures of proteins within large superfamilies and to link them to function, as well as to provide knowledge-based predictions for experimental evaluation. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Structure-related statistical singularities along protein sequences: a correlation study.

PubMed

Colafranceschi, Mauro; Colosimo, Alfredo; Zbilut, Joseph P; Uversky, Vladimir N; Giuliani, Alessandro

2005-01-01

A data set composed of 1141 proteins representative of all eukaryotic protein sequences in the Swiss-Prot Protein Knowledge base was coded by seven physicochemical properties of amino acid residues. The resulting numerical profiles were submitted to correlation analysis after the application of a linear (simple mean) and a nonlinear (Recurrence Quantification Analysis, RQA) filter. The main RQA variables, Recurrence and Determinism, were subsequently analyzed by Principal Component Analysis. The RQA descriptors showed that (i) within protein sequences is embedded specific information neither present in the codes nor in the amino acid composition and (ii) the most sensitive code for detecting ordered recurrent (deterministic) patterns of residues in protein sequences is the Miyazawa-Jernigan hydrophobicity scale. The most deterministic proteins in terms of autocorrelation properties of primary structures were found (i) to be involved in protein-protein and protein-DNA interactions and (ii) to display a significantly higher proportion of structural disorder with respect to the average data set. A study of the scaling behavior of the average determinism with the setting parameters of RQA (embedding dimension and radius) allows for the identification of patterns of minimal length (six residues) as possible markers of zones specifically prone to inter- and intramolecular interactions.

Biosynthesis of riboflavin: an unusual riboflavin synthase of Methanobacterium thermoautotrophicum.

PubMed Central

Eberhardt, S; Korn, S; Lottspeich, F; Bacher, A

1997-01-01

Riboflavin synthase was purified by a factor of about 1,500 from cell extract of Methanobacterium thermoautotrophicum. The enzyme had a specific activity of about 2,700 nmol mg(-1) h(-1) at 65 degrees C, which is relatively low compared to those of riboflavin synthases of eubacteria and yeast. Amino acid sequences obtained after proteolytic cleavage had no similarity with known riboflavin synthases. The gene coding for riboflavin synthase (designated ribC) was subsequently cloned by marker rescue with a ribC mutant of Escherichia coli. The ribC gene of M. thermoautotrophicum specifies a protein of 153 amino acid residues. The predicted amino acid sequence agrees with the information gleaned from Edman degradation of the isolated protein and shows 67% identity with the sequence predicted for the unannotated reading frame MJ1184 of Methanococcus jannaschii. The ribC gene is adjacent to a cluster of four genes with similarity to the genes cbiMNQO of Salmonella typhimurium, which form part of the cob operon (this operon contains most of the genes involved in the biosynthesis of vitamin B12). The amino acid sequence predicted by the ribC gene of M. thermoautotrophicum shows no similarity whatsoever to the sequences of riboflavin synthases of eubacteria and yeast. Most notably, the M. thermoautotrophicum protein does not show the internal sequence homology characteristic of eubacterial and yeast riboflavin synthases. The protein of M. thermoautotrophicum can be expressed efficiently in a recombinant E. coli strain. The specific activity of the purified, recombinant protein is 1,900 nmol mg(-1) h(-1) at 65 degrees C. In contrast to riboflavin synthases from eubacteria and fungi, the methanobacterial enzyme has an absolute requirement for magnesium ions. The 5' phosphate of 6,7-dimethyl-8-ribityllumazine does not act as a substrate. The findings suggest that riboflavin synthase has evolved independently in eubacteria and methanobacteria. PMID:9139911

In Silico Pattern-Based Analysis of the Human Cytomegalovirus Genome

PubMed Central

Rigoutsos, Isidore; Novotny, Jiri; Huynh, Tien; Chin-Bow, Stephen T.; Parida, Laxmi; Platt, Daniel; Coleman, David; Shenk, Thomas

2003-01-01

More than 200 open reading frames (ORFs) from the human cytomegalovirus genome have been reported as potentially coding for proteins. We have used two pattern-based in silico approaches to analyze this set of putative viral genes. With the help of an objective annotation method that is based on the Bio-Dictionary, a comprehensive collection of amino acid patterns that describes the currently known natural sequence space of proteins, we have reannotated all of the previously reported putative genes of the human cytomegalovirus. Also, with the help of MUSCA, a pattern-based multiple sequence alignment algorithm, we have reexamined the original human cytomegalovirus gene family definitions. Our analysis of the genome shows that many of the coded proteins comprise amino acid combinations that are unique to either the human cytomegalovirus or the larger group of herpesviruses. We have confirmed that a surprisingly large portion of the analyzed ORFs encode membrane proteins, and we have discovered a significant number of previously uncharacterized proteins that are predicted to be G-protein-coupled receptor homologues. The analysis also indicates that many of the encoded proteins undergo posttranslational modifications such as hydroxylation, phosphorylation, and glycosylation. ORFs encoding proteins with similar functional behavior appear in neighboring regions of the human cytomegalovirus genome. All of the results of the present study can be found and interactively explored online (http://cbcsrv.watson.ibm.com/virus/). PMID:12634390

In silico pattern-based analysis of the human cytomegalovirus genome.

PubMed

Rigoutsos, Isidore; Novotny, Jiri; Huynh, Tien; Chin-Bow, Stephen T; Parida, Laxmi; Platt, Daniel; Coleman, David; Shenk, Thomas

2003-04-01

More than 200 open reading frames (ORFs) from the human cytomegalovirus genome have been reported as potentially coding for proteins. We have used two pattern-based in silico approaches to analyze this set of putative viral genes. With the help of an objective annotation method that is based on the Bio-Dictionary, a comprehensive collection of amino acid patterns that describes the currently known natural sequence space of proteins, we have reannotated all of the previously reported putative genes of the human cytomegalovirus. Also, with the help of MUSCA, a pattern-based multiple sequence alignment algorithm, we have reexamined the original human cytomegalovirus gene family definitions. Our analysis of the genome shows that many of the coded proteins comprise amino acid combinations that are unique to either the human cytomegalovirus or the larger group of herpesviruses. We have confirmed that a surprisingly large portion of the analyzed ORFs encode membrane proteins, and we have discovered a significant number of previously uncharacterized proteins that are predicted to be G-protein-coupled receptor homologues. The analysis also indicates that many of the encoded proteins undergo posttranslational modifications such as hydroxylation, phosphorylation, and glycosylation. ORFs encoding proteins with similar functional behavior appear in neighboring regions of the human cytomegalovirus genome. All of the results of the present study can be found and interactively explored online (http://cbcsrv.watson.ibm.com/virus/).

The Acheta domesticus Densovirus, Isolated from the European House Cricket, Has Evolved an Expression Strategy Unique among Parvoviruses▿†

PubMed Central

Liu, Kaiyu; Li, Yi; Jousset, Françoise-Xavière; Zadori, Zoltan; Szelei, Jozsef; Yu, Qian; Pham, Hanh Thi; Lépine, François; Bergoin, Max; Tijssen, Peter

2011-01-01

The Acheta domesticus densovirus (AdDNV), isolated from crickets, has been endemic in Europe for at least 35 years. Severe epizootics have also been observed in American commercial rearings since 2009 and 2010. The AdDNV genome was cloned and sequenced for this study. The transcription map showed that splicing occurred in both the nonstructural (NS) and capsid protein (VP) multicistronic RNAs. The splicing pattern of NS mRNA predicted 3 nonstructural proteins (NS1 [576 codons], NS2 [286 codons], and NS3 [213 codons]). The VP gene cassette contained two VP open reading frames (ORFs), of 597 (ORF-A) and 268 (ORF-B) codons. The VP2 sequence was shown by N-terminal Edman degradation and mass spectrometry to correspond with ORF-A. Mass spectrometry, sequencing, and Western blotting of baculovirus-expressed VPs versus native structural proteins demonstrated that the VP1 structural protein was generated by joining ORF-A and -B via splicing (splice II), eliminating the N terminus of VP2. This splice resulted in a nested set of VP1 (816 codons), VP3 (467 codons), and VP4 (429 codons) structural proteins. In contrast, the two splices within ORF-B (Ia and Ib) removed the donor site of intron II and resulted in VP2, VP3, and VP4 expression. ORF-B may also code for several nonstructural proteins, of 268, 233, and 158 codons. The small ORF-B contains the coding sequence for a phospholipase A2 motif found in VP1, which was shown previously to be critical for cellular uptake of the virus. These splicing features are unique among parvoviruses and define a new genus of ambisense densoviruses. PMID:21775445

Bioinformatic Analysis Reveals Archaeal tRNATyr and tRNATrp Identities in Bacteria

PubMed Central

Mukai, Takahito; Reynolds, Noah M.; Crnković, Ana; Söll, Dieter

2017-01-01

The tRNA identity elements for some amino acids are distinct between the bacterial and archaeal domains. Searching in recent genomic and metagenomic sequence data, we found some candidate phyla radiation (CPR) bacteria with archaeal tRNA identity for Tyr-tRNA and Trp-tRNA synthesis. These bacteria possess genes for tyrosyl-tRNA synthetase (TyrRS) and tryptophanyl-tRNA synthetase (TrpRS) predicted to be derived from DPANN superphylum archaea, while the cognate tRNATyr and tRNATrp genes reveal bacterial or archaeal origins. We identified a trace of domain fusion and swapping in the archaeal-type TyrRS gene of a bacterial lineage, suggesting that CPR bacteria may have used this mechanism to create diverse proteins. Archaeal-type TrpRS of bacteria and a few TrpRS species of DPANN archaea represent a new phylogenetic clade (named TrpRS-A). The TrpRS-A open reading frames (ORFs) are always associated with another ORF (named ORF1) encoding an unknown protein without global sequence identity to any known protein. However, our protein structure prediction identified a putative HIGH-motif and KMSKS-motif as well as many α-helices that are characteristic of class I aminoacyl-tRNA synthetase (aaRS) homologs. These results provide another example of the diversity of molecular components that implement the genetic code and provide a clue to the early evolution of life and the genetic code. PMID:28230768

RNA catalysis and the origins of life

NASA Technical Reports Server (NTRS)

Orgel, Leslie E.

1986-01-01

The role of RNA catalysis in the origins of life is considered in connection with the discovery of riboszymes, which are RNA molecules that catalyze sequence-specific hydrolysis and transesterification reactions of RNA substrates. Due to this discovery, theories positing protein-free replication as preceding the appearance of the genetic code are more plausible. The scope of RNA catalysis in biology and chemistry is discussed, and it is noted that the development of methods to select (or predict) RNA sequences with preassigned catalytic functions would be a major contribution to the study of life's origins.

SnowyOwl: accurate prediction of fungal genes by using RNA-Seq and homology information to select among ab initio models

PubMed Central

2014-01-01

Background Locating the protein-coding genes in novel genomes is essential to understanding and exploiting the genomic information but it is still difficult to accurately predict all the genes. The recent availability of detailed information about transcript structure from high-throughput sequencing of messenger RNA (RNA-Seq) delineates many expressed genes and promises increased accuracy in gene prediction. Computational gene predictors have been intensively developed for and tested in well-studied animal genomes. Hundreds of fungal genomes are now or will soon be sequenced. The differences of fungal genomes from animal genomes and the phylogenetic sparsity of well-studied fungi call for gene-prediction tools tailored to them. Results SnowyOwl is a new gene prediction pipeline that uses RNA-Seq data to train and provide hints for the generation of Hidden Markov Model (HMM)-based gene predictions and to evaluate the resulting models. The pipeline has been developed and streamlined by comparing its predictions to manually curated gene models in three fungal genomes and validated against the high-quality gene annotation of Neurospora crassa; SnowyOwl predicted N. crassa genes with 83% sensitivity and 65% specificity. SnowyOwl gains sensitivity by repeatedly running the HMM gene predictor Augustus with varied input parameters and selectivity by choosing the models with best homology to known proteins and best agreement with the RNA-Seq data. Conclusions SnowyOwl efficiently uses RNA-Seq data to produce accurate gene models in both well-studied and novel fungal genomes. The source code for the SnowyOwl pipeline (in Python) and a web interface (in PHP) is freely available from http://sourceforge.net/projects/snowyowl/. PMID:24980894

Complete genome sequence of Parvibaculum lavamentivorans type strain (DS-1(T)).

PubMed

Schleheck, David; Weiss, Michael; Pitluck, Sam; Bruce, David; Land, Miriam L; Han, Shunsheng; Saunders, Elizabeth; Tapia, Roxanne; Detter, Chris; Brettin, Thomas; Han, James; Woyke, Tanja; Goodwin, Lynne; Pennacchio, Len; Nolan, Matt; Cook, Alasdair M; Kjelleberg, Staffan; Thomas, Torsten

2011-12-31

Parvibaculum lavamentivorans DS-1(T) is the type species of the novel genus Parvibaculum in the novel family Rhodobiaceae (formerly Phyllobacteriaceae) of the order Rhizobiales of Alphaproteobacteria. Strain DS-1(T) is a non-pigmented, aerobic, heterotrophic bacterium and represents the first tier member of environmentally important bacterial communities that catalyze the complete degradation of synthetic laundry surfactants. Here we describe the features of this organism, together with the complete genome sequence and annotation. The 3,914,745 bp long genome with its predicted 3,654 protein coding genes is the first completed genome sequence of the genus Parvibaculum, and the first genome sequence of a representative of the family Rhodobiaceae.

GATA: A graphic alignment tool for comparative sequenceanalysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nix, David A.; Eisen, Michael B.

2005-01-01

Several problems exist with current methods used to align DNA sequences for comparative sequence analysis. Most dynamic programming algorithms assume that conserved sequence elements are collinear. This assumption appears valid when comparing orthologous protein coding sequences. Functional constraints on proteins provide strong selective pressure against sequence inversions, and minimize sequence duplications and feature shuffling. For non-coding sequences this collinearity assumption is often invalid. For example, enhancers contain clusters of transcription factor binding sites that change in number, orientation, and spacing during evolution yet the enhancer retains its activity. Dotplot analysis is often used to estimate non-coding sequence relatedness. Yet dotmore » plots do not actually align sequences and thus cannot account well for base insertions or deletions. Moreover, they lack an adequate statistical framework for comparing sequence relatedness and are limited to pairwise comparisons. Lastly, dot plots and dynamic programming text outputs fail to provide an intuitive means for visualizing DNA alignments.« less

UniDrug-target: a computational tool to identify unique drug targets in pathogenic bacteria.

PubMed

Chanumolu, Sree Krishna; Rout, Chittaranjan; Chauhan, Rajinder S

2012-01-01

Targeting conserved proteins of bacteria through antibacterial medications has resulted in both the development of resistant strains and changes to human health by destroying beneficial microbes which eventually become breeding grounds for the evolution of resistances. Despite the availability of more than 800 genomes sequences, 430 pathways, 4743 enzymes, 9257 metabolic reactions and protein (three-dimensional) 3D structures in bacteria, no pathogen-specific computational drug target identification tool has been developed. A web server, UniDrug-Target, which combines bacterial biological information and computational methods to stringently identify pathogen-specific proteins as drug targets, has been designed. Besides predicting pathogen-specific proteins essentiality, chokepoint property, etc., three new algorithms were developed and implemented by using protein sequences, domains, structures, and metabolic reactions for construction of partial metabolic networks (PMNs), determination of conservation in critical residues, and variation analysis of residues forming similar cavities in proteins sequences. First, PMNs are constructed to determine the extent of disturbances in metabolite production by targeting a protein as drug target. Conservation of pathogen-specific protein's critical residues involved in cavity formation and biological function determined at domain-level with low-matching sequences. Last, variation analysis of residues forming similar cavities in proteins sequences from pathogenic versus non-pathogenic bacteria and humans is performed. The server is capable of predicting drug targets for any sequenced pathogenic bacteria having fasta sequences and annotated information. The utility of UniDrug-Target server was demonstrated for Mycobacterium tuberculosis (H37Rv). The UniDrug-Target identified 265 mycobacteria pathogen-specific proteins, including 17 essential proteins which can be potential drug targets. UniDrug-Target is expected to accelerate pathogen-specific drug targets identification which will increase their success and durability as drugs developed against them have less chance to develop resistances and adverse impact on environment. The server is freely available at http://117.211.115.67/UDT/main.html. The standalone application (source codes) is available at http://www.bioinformatics.org/ftp/pub/bioinfojuit/UDT.rar.

A subset of conserved mammalian long non-coding RNAs are fossils of ancestral protein-coding genes.

PubMed

Hezroni, Hadas; Ben-Tov Perry, Rotem; Meir, Zohar; Housman, Gali; Lubelsky, Yoav; Ulitsky, Igor

2017-08-30

Only a small portion of human long non-coding RNAs (lncRNAs) appear to be conserved outside of mammals, but the events underlying the birth of new lncRNAs in mammals remain largely unknown. One potential source is remnants of protein-coding genes that transitioned into lncRNAs. We systematically compare lncRNA and protein-coding loci across vertebrates, and estimate that up to 5% of conserved mammalian lncRNAs are derived from lost protein-coding genes. These lncRNAs have specific characteristics, such as broader expression domains, that set them apart from other lncRNAs. Fourteen lncRNAs have sequence similarity with the loci of the contemporary homologs of the lost protein-coding genes. We propose that selection acting on enhancer sequences is mostly responsible for retention of these regions. As an example of an RNA element from a protein-coding ancestor that was retained in the lncRNA, we describe in detail a short translated ORF in the JPX lncRNA that was derived from an upstream ORF in a protein-coding gene and retains some of its functionality. We estimate that ~ 55 annotated conserved human lncRNAs are derived from parts of ancestral protein-coding genes, and loss of coding potential is thus a non-negligible source of new lncRNAs. Some lncRNAs inherited regulatory elements influencing transcription and translation from their protein-coding ancestors and those elements can influence the expression breadth and functionality of these lncRNAs.

Systematic asymmetric nucleotide exchanges produce human mitochondrial RNAs cryptically encoding for overlapping protein coding genes.

PubMed

Seligmann, Hervé

2013-05-07

GenBank's EST database includes RNAs matching exactly human mitochondrial sequences assuming systematic asymmetric nucleotide exchange-transcription along exchange rules: A→G→C→U/T→A (12 ESTs), A→U/T→C→G→A (4 ESTs), C→G→U/T→C (3 ESTs), and A→C→G→U/T→A (1 EST), no RNAs correspond to other potential asymmetric exchange rules. Hypothetical polypeptides translated from nucleotide-exchanged human mitochondrial protein coding genes align with numerous GenBank proteins, predicted secondary structures resemble their putative GenBank homologue's. Two independent methods designed to detect overlapping genes (one based on nucleotide contents analyses in relation to replicative deamination gradients at third codon positions, and circular code analyses of codon contents based on frame redundancy), confirm nucleotide-exchange-encrypted overlapping genes. Methods converge on which genes are most probably active, and which not, and this for the various exchange rules. Mean EST lengths produced by different nucleotide exchanges are proportional to (a) extents that various bioinformatics analyses confirm the protein coding status of putative overlapping genes; (b) known kinetic chemistry parameters of the corresponding nucleotide substitutions by the human mitochondrial DNA polymerase gamma (nucleotide DNA misinsertion rates); (c) stop codon densities in predicted overlapping genes (stop codon readthrough and exchanging polymerization regulate gene expression by counterbalancing each other). Numerous rarely expressed proteins seem encoded within regular mitochondrial genes through asymmetric nucleotide exchange, avoiding lengthening genomes. Intersecting evidence between several independent approaches confirms the working hypothesis status of gene encryption by systematic nucleotide exchanges. Copyright © 2013 Elsevier Ltd. All rights reserved.

Theory of prokaryotic genome evolution.

PubMed

Sela, Itamar; Wolf, Yuri I; Koonin, Eugene V

2016-10-11

Bacteria and archaea typically possess small genomes that are tightly packed with protein-coding genes. The compactness of prokaryotic genomes is commonly perceived as evidence of adaptive genome streamlining caused by strong purifying selection in large microbial populations. In such populations, even the small cost incurred by nonfunctional DNA because of extra energy and time expenditure is thought to be sufficient for this extra genetic material to be eliminated by selection. However, contrary to the predictions of this model, there exists a consistent, positive correlation between the strength of selection at the protein sequence level, measured as the ratio of nonsynonymous to synonymous substitution rates, and microbial genome size. Here, by fitting the genome size distributions in multiple groups of prokaryotes to predictions of mathematical models of population evolution, we show that only models in which acquisition of additional genes is, on average, slightly beneficial yield a good fit to genomic data. These results suggest that the number of genes in prokaryotic genomes reflects the equilibrium between the benefit of additional genes that diminishes as the genome grows and deletion bias (i.e., the rate of deletion of genetic material being slightly greater than the rate of acquisition). Thus, new genes acquired by microbial genomes, on average, appear to be adaptive. The tight spacing of protein-coding genes likely results from a combination of the deletion bias and purifying selection that efficiently eliminates nonfunctional, noncoding sequences.

Using information content and base frequencies to distinguish mutations from genetic polymorphisms in splice junction recognition sites.

PubMed

Rogan, P K; Schneider, T D

1995-01-01

Predicting the effects of nucleotide substitutions in human splice sites has been based on analysis of consensus sequences. We used a graphic representation of sequence conservation and base frequency, the sequence logo, to demonstrate that a change in a splice acceptor of hMSH2 (a gene associated with familial nonpolyposis colon cancer) probably does not reduce splicing efficiency. This confirms a population genetic study that suggested that this substitution is a genetic polymorphism. The information theory-based sequence logo is quantitative and more sensitive than the corresponding splice acceptor consensus sequence for detection of true mutations. Information analysis may potentially be used to distinguish polymorphisms from mutations in other types of transcriptional, translational, or protein-coding motifs.

Translation efficiency of heterologous proteins is significantly affected by the genetic context of RBS sequences in engineered cyanobacterium Synechocystis sp. PCC 6803.

PubMed

Thiel, Kati; Mulaku, Edita; Dandapani, Hariharan; Nagy, Csaba; Aro, Eva-Mari; Kallio, Pauli

2018-03-02

Photosynthetic cyanobacteria have been studied as potential host organisms for direct solar-driven production of different carbon-based chemicals from CO 2 and water, as part of the development of sustainable future biotechnological applications. The engineering approaches, however, are still limited by the lack of comprehensive information on most optimal expression strategies and validated species-specific genetic elements which are essential for increasing the intricacy, predictability and efficiency of the systems. This study focused on the systematic evaluation of the key translational control elements, ribosome binding sites (RBS), in the cyanobacterial host Synechocystis sp. PCC 6803, with the objective of expanding the palette of tools for more rigorous engineering approaches. An expression system was established for the comparison of 13 selected RBS sequences in Synechocystis, using several alternative reporter proteins (sYFP2, codon-optimized GFPmut3 and ethylene forming enzyme) as quantitative indicators of the relative translation efficiencies. The set-up was shown to yield highly reproducible expression patterns in independent analytical series with low variation between biological replicates, thus allowing statistical comparison of the activities of the different RBSs in vivo. While the RBSs covered a relatively broad overall expression level range, the downstream gene sequence was demonstrated in a rigorous manner to have a clear impact on the resulting translational profiles. This was expected to reflect interfering sequence-specific mRNA-level interaction between the RBS and the coding region, yet correlation between potential secondary structure formation and observed translation levels could not be resolved with existing in silico prediction tools. The study expands our current understanding on the potential and limitations associated with the regulation of protein expression at translational level in engineered cyanobacteria. The acquired information can be used for selecting appropriate RBSs for optimizing over-expression constructs or multicistronic pathways in Synechocystis, while underlining the complications in predicting the activity due to gene-specific interactions which may reduce the translational efficiency for a given RBS-gene combination. Ultimately, the findings emphasize the need for additional characterized insulator sequence elements to decouple the interaction between the RBS and the coding region for future engineering approaches.

Sequence-based prediction of protein-binding sites in DNA: comparative study of two SVM models.

PubMed

Park, Byungkyu; Im, Jinyong; Tuvshinjargal, Narankhuu; Lee, Wook; Han, Kyungsook

2014-11-01

As many structures of protein-DNA complexes have been known in the past years, several computational methods have been developed to predict DNA-binding sites in proteins. However, its inverse problem (i.e., predicting protein-binding sites in DNA) has received much less attention. One of the reasons is that the differences between the interaction propensities of nucleotides are much smaller than those between amino acids. Another reason is that DNA exhibits less diverse sequence patterns than protein. Therefore, predicting protein-binding DNA nucleotides is much harder than predicting DNA-binding amino acids. We computed the interaction propensity (IP) of nucleotide triplets with amino acids using an extensive dataset of protein-DNA complexes, and developed two support vector machine (SVM) models that predict protein-binding nucleotides from sequence data alone. One SVM model predicts protein-binding nucleotides using DNA sequence data alone, and the other SVM model predicts protein-binding nucleotides using both DNA and protein sequences. In a 10-fold cross-validation with 1519 DNA sequences, the SVM model that uses DNA sequence data only predicted protein-binding nucleotides with an accuracy of 67.0%, an F-measure of 67.1%, and a Matthews correlation coefficient (MCC) of 0.340. With an independent dataset of 181 DNAs that were not used in training, it achieved an accuracy of 66.2%, an F-measure 66.3% and a MCC of 0.324. Another SVM model that uses both DNA and protein sequences achieved an accuracy of 69.6%, an F-measure of 69.6%, and a MCC of 0.383 in a 10-fold cross-validation with 1519 DNA sequences and 859 protein sequences. With an independent dataset of 181 DNAs and 143 proteins, it showed an accuracy of 67.3%, an F-measure of 66.5% and a MCC of 0.329. Both in cross-validation and independent testing, the second SVM model that used both DNA and protein sequence data showed better performance than the first model that used DNA sequence data. To the best of our knowledge, this is the first attempt to predict protein-binding nucleotides in a given DNA sequence from the sequence data alone. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Draft genome sequence of Enterococcus faecium strain LMG 8148.

PubMed

Michiels, Joran E; Van den Bergh, Bram; Fauvart, Maarten; Michiels, Jan

2016-01-01

Enterococcus faecium, traditionally considered a harmless gut commensal, is emerging as an important nosocomial pathogen showing increasing rates of multidrug resistance. We report the draft genome sequence of E. faecium strain LMG 8148, isolated in 1968 from a human in Gothenburg, Sweden. The draft genome has a total length of 2,697,490 bp, a GC-content of 38.3 %, and 2,402 predicted protein-coding sequences. The isolation of this strain predates the emergence of E. faecium as a nosocomial pathogen. Consequently, its genome can be useful in comparative genomic studies investigating the evolution of E. faecium as a pathogen.

Genome-guided exploration of metabolic features of Streptomyces peucetius ATCC 27952: past, current, and prospect.

PubMed

Thuan, Nguyen Huy; Dhakal, Dipesh; Pokhrel, Anaya Raj; Chu, Luan Luong; Van Pham, Thi Thuy; Shrestha, Anil; Sohng, Jae Kyung

2018-05-01

Streptomyces peucetius ATCC 27952 produces two major anthracyclines, doxorubicin (DXR) and daunorubicin (DNR), which are potent chemotherapeutic agents for the treatment of several cancers. In order to gain detailed insight on genetics and biochemistry of the strain, the complete genome was determined and analyzed. The result showed that its complete sequence contains 7187 protein coding genes in a total of 8,023,114 bp, whereas 87% of the genome contributed to the protein coding region. The genomic sequence included 18 rRNA, 66 tRNAs, and 3 non-coding RNAs. In silico studies predicted ~ 68 biosynthetic gene clusters (BCGs) encoding diverse classes of secondary metabolites, including non-ribosomal polyketide synthase (NRPS), polyketide synthase (PKS I, II, and III), terpenes, and others. Detailed analysis of the genome sequence revealed versatile biocatalytic enzymes such as cytochrome P450 (CYP), electron transfer systems (ETS) genes, methyltransferase (MT), glycosyltransferase (GT). In addition, numerous functional genes (transporter gene, SOD, etc.) and regulatory genes (afsR-sp, metK-sp, etc.) involved in the regulation of secondary metabolites were found. This minireview summarizes the genome-based genome mining (GM) of diverse BCGs and genome exploration (GE) of versatile biocatalytic enzymes, and other enzymes involved in maintenance and regulation of metabolism of S. peucetius. The detailed analysis of genome sequence provides critically important knowledge useful in the bioengineering of the strain or harboring catalytically efficient enzymes for biotechnological applications.

The cDNA sequence of mouse Pgp-1 and homology to human CD44 cell surface antigen and proteoglycan core/link proteins.

PubMed

Wolffe, E J; Gause, W C; Pelfrey, C M; Holland, S M; Steinberg, A D; August, J T

1990-01-05

We describe the isolation and sequencing of a cDNA encoding mouse Pgp-1. An oligonucleotide probe corresponding to the NH2-terminal sequence of the purified protein was synthesized by the polymerase chain reaction and used to screen a mouse macrophage lambda gt11 library. A cDNA clone with an insert of 1.2 kilobases was selected and sequenced. In Northern blot analysis, only cells expressing Pgp-1 contained mRNA species that hybridized with this Pgp-1 cDNA. The nucleotide sequence of the cDNA has a single open reading frame that yields a protein-coding sequence of 1076 base pairs followed by a 132-base pair 3'-untranslated sequence that includes a putative polyadenylation signal but no poly(A) tail. The translated sequence comprises a 13-amino acid signal peptide followed by a polypeptide core of 345 residues corresponding to an Mr of 37,800. Portions of the deduced amino acid sequence were identical to those obtained by amino acid sequence analysis from the purified glycoprotein, confirming that the cDNA encodes Pgp-1. The predicted structure of Pgp-1 includes an NH2-terminal extracellular domain (residues 14-265), a transmembrane domain (residues 266-286), and a cytoplasmic tail (residues 287-358). Portions of the mouse Pgp-1 sequence are highly similar to that of the human CD44 cell surface glycoprotein implicated in cell adhesion. The protein also shows sequence similarity to the proteoglycan tandem repeat sequences found in cartilage link protein and cartilage proteoglycan core protein which are thought to be involved in binding to hyaluronic acid.

The Mitochondrial Cytochrome Oxidase Subunit I Gene Occurs on a Minichromosome with Extensive Heteroplasmy in Two Species of Chewing Lice, Geomydoecus aurei and Thomomydoecus minor

PubMed Central

Pietan, Lucas L.; Spradling, Theresa A.

2016-01-01

In animals, mitochondrial DNA (mtDNA) typically occurs as a single circular chromosome with 13 protein-coding genes and 22 tRNA genes. The various species of lice examined previously, however, have shown mitochondrial genome rearrangements with a range of chromosome sizes and numbers. Our research demonstrates that the mitochondrial genomes of two species of chewing lice found on pocket gophers, Geomydoecus aurei and Thomomydoecus minor, are fragmented with the 1,536 base-pair (bp) cytochrome-oxidase subunit I (cox1) gene occurring as the only protein-coding gene on a 1,916–1,964 bp minicircular chromosome in the two species, respectively. The cox1 gene of T. minor begins with an atypical start codon, while that of G. aurei does not. Components of the non-protein coding sequence of G. aurei and T. minor include a tRNA (isoleucine) gene, inverted repeat sequences consistent with origins of replication, and an additional non-coding region that is smaller than the non-coding sequence of other lice with such fragmented mitochondrial genomes. Sequences of cox1 minichromosome clones for each species reveal extensive length and sequence heteroplasmy in both coding and noncoding regions. The highly variable non-gene regions of G. aurei and T. minor have little sequence similarity with one another except for a 19-bp region of phylogenetically conserved sequence with unknown function. PMID:27589589

Novel coding, translation, and gene expression of a replicating covalently closed circular RNA of 220 nt.

PubMed

AbouHaidar, Mounir Georges; Venkataraman, Srividhya; Golshani, Ashkan; Liu, Bolin; Ahmad, Tauqeer

2014-10-07

The highly structured (64% GC) covalently closed circular (CCC) RNA (220 nt) of the virusoid associated with rice yellow mottle virus codes for a 16-kDa highly basic protein using novel modalities for coding, translation, and gene expression. This CCC RNA is the smallest among all known viroids and virusoids and the only one that codes proteins. Its sequence possesses an internal ribosome entry site and is directly translated through two (or three) completely overlapping ORFs (shifting to a new reading frame at the end of each round). The initiation and termination codons overlap UGAUGA (underline highlights the initiation codon AUG within the combined initiation-termination sequence). Termination codons can be ignored to obtain larger read-through proteins. This circular RNA with no noncoding sequences is a unique natural supercompact "nanogenome."

MOCAT: A Metagenomics Assembly and Gene Prediction Toolkit

PubMed Central

Li, Junhua; Chen, Weineng; Chen, Hua; Mende, Daniel R.; Arumugam, Manimozhiyan; Pan, Qi; Liu, Binghang; Qin, Junjie; Wang, Jun; Bork, Peer

2012-01-01

MOCAT is a highly configurable, modular pipeline for fast, standardized processing of single or paired-end sequencing data generated by the Illumina platform. The pipeline uses state-of-the-art programs to quality control, map, and assemble reads from metagenomic samples sequenced at a depth of several billion base pairs, and predict protein-coding genes on assembled metagenomes. Mapping against reference databases allows for read extraction or removal, as well as abundance calculations. Relevant statistics for each processing step can be summarized into multi-sheet Excel documents and queryable SQL databases. MOCAT runs on UNIX machines and integrates seamlessly with the SGE and PBS queuing systems, commonly used to process large datasets. The open source code and modular architecture allow users to modify or exchange the programs that are utilized in the various processing steps. Individual processing steps and parameters were benchmarked and tested on artificial, real, and simulated metagenomes resulting in an improvement of selected quality metrics. MOCAT can be freely downloaded at http://www.bork.embl.de/mocat/. PMID:23082188

MOCAT: a metagenomics assembly and gene prediction toolkit.

PubMed

Kultima, Jens Roat; Sunagawa, Shinichi; Li, Junhua; Chen, Weineng; Chen, Hua; Mende, Daniel R; Arumugam, Manimozhiyan; Pan, Qi; Liu, Binghang; Qin, Junjie; Wang, Jun; Bork, Peer

2012-01-01

MOCAT is a highly configurable, modular pipeline for fast, standardized processing of single or paired-end sequencing data generated by the Illumina platform. The pipeline uses state-of-the-art programs to quality control, map, and assemble reads from metagenomic samples sequenced at a depth of several billion base pairs, and predict protein-coding genes on assembled metagenomes. Mapping against reference databases allows for read extraction or removal, as well as abundance calculations. Relevant statistics for each processing step can be summarized into multi-sheet Excel documents and queryable SQL databases. MOCAT runs on UNIX machines and integrates seamlessly with the SGE and PBS queuing systems, commonly used to process large datasets. The open source code and modular architecture allow users to modify or exchange the programs that are utilized in the various processing steps. Individual processing steps and parameters were benchmarked and tested on artificial, real, and simulated metagenomes resulting in an improvement of selected quality metrics. MOCAT can be freely downloaded at http://www.bork.embl.de/mocat/.

Recognizing short coding sequences of prokaryotic genome using a novel iteratively adaptive sparse partial least squares algorithm

PubMed Central

2013-01-01

Background Significant efforts have been made to address the problem of identifying short genes in prokaryotic genomes. However, most known methods are not effective in detecting short genes. Because of the limited information contained in short DNA sequences, it is very difficult to accurately distinguish between protein coding and non-coding sequences in prokaryotic genomes. We have developed a new Iteratively Adaptive Sparse Partial Least Squares (IASPLS) algorithm as the classifier to improve the accuracy of the identification process. Results For testing, we chose the short coding and non-coding sequences from seven prokaryotic organisms. We used seven feature sets (including GC content, Z-curve, etc.) of short genes. In comparison with GeneMarkS, Metagene, Orphelia, and Heuristic Approachs methods, our model achieved the best prediction performance in identification of short prokaryotic genes. Even when we focused on the very short length group ([60–100 nt)), our model provided sensitivity as high as 83.44% and specificity as high as 92.8%. These values are two or three times higher than three of the other methods while Metagene fails to recognize genes in this length range. The experiments also proved that the IASPLS can improve the identification accuracy in comparison with other widely used classifiers, i.e. Logistic, Random Forest (RF) and K nearest neighbors (KNN). The accuracy in using IASPLS was improved 5.90% or more in comparison with the other methods. In addition to the improvements in accuracy, IASPLS required ten times less computer time than using KNN or RF. Conclusions It is conclusive that our method is preferable for application as an automated method of short gene classification. Its linearity and easily optimized parameters make it practicable for predicting short genes of newly-sequenced or under-studied species. Reviewers This article was reviewed by Alexey Kondrashov, Rajeev Azad (nominated by Dr J.Peter Gogarten) and Yuriy Fofanov (nominated by Dr Janet Siefert). PMID:24067167

Identification and Classification of New Transcripts in Dorper and Small-Tailed Han Sheep Skeletal Muscle Transcriptomes.

PubMed

Chao, Tianle; Wang, Guizhi; Wang, Jianmin; Liu, Zhaohua; Ji, Zhibin; Hou, Lei; Zhang, Chunlan

2016-01-01

High-throughput mRNA sequencing enables the discovery of new transcripts and additional parts of incompletely annotated transcripts. Compared with the human and cow genomes, the reference annotation level of the sheep genome is still low. An investigation of new transcripts in sheep skeletal muscle will improve our understanding of muscle development. Therefore, applying high-throughput sequencing, two cDNA libraries from the biceps brachii of small-tailed Han sheep and Dorper sheep were constructed, and whole-transcriptome analysis was performed to determine the unknown transcript catalogue of this tissue. In this study, 40,129 transcripts were finally mapped to the sheep genome. Among them, 3,467 transcripts were determined to be unannotated in the current reference sheep genome and were defined as new transcripts. Based on protein-coding capacity prediction and comparative analysis of sequence similarity, 246 transcripts were classified as portions of unannotated genes or incompletely annotated genes. Another 1,520 transcripts were predicted with high confidence to be long non-coding RNAs. Our analysis also revealed 334 new transcripts that displayed specific expression in ruminants and uncovered a number of new transcripts without intergenus homology but with specific expression in sheep skeletal muscle. The results confirmed a complex transcript pattern of coding and non-coding RNA in sheep skeletal muscle. This study provided important information concerning the sheep genome and transcriptome annotation, which could provide a basis for further study.

Long non-coding RNAs and their biological roles in plants.

PubMed

Liu, Xue; Hao, Lili; Li, Dayong; Zhu, Lihuang; Hu, Songnian

2015-06-01

With the development of genomics and bioinformatics, especially the extensive applications of high-throughput sequencing technology, more transcriptional units with little or no protein-coding potential have been discovered. Such RNA molecules are called non-protein-coding RNAs (npcRNAs or ncRNAs). Among them, long npcRNAs or ncRNAs (lnpcRNAs or lncRNAs) represent diverse classes of transcripts longer than 200 nucleotides. In recent years, the lncRNAs have been considered as important regulators in many essential biological processes. In plants, although a large number of lncRNA transcripts have been predicted and identified in few species, our current knowledge of their biological functions is still limited. Here, we have summarized recent studies on their identification, characteristics, classification, bioinformatics, resources, and current exploration of their biological functions in plants. Copyright © 2015 The Authors. Production and hosting by Elsevier Ltd.. All rights reserved.

Genomic Sequence around Butterfly Wing Development Genes: Annotation and Comparative Analysis

PubMed Central

Conceição, Inês C.; Long, Anthony D.; Gruber, Jonathan D.; Beldade, Patrícia

2011-01-01

Background Analysis of genomic sequence allows characterization of genome content and organization, and access beyond gene-coding regions for identification of functional elements. BAC libraries, where relatively large genomic regions are made readily available, are especially useful for species without a fully sequenced genome and can increase genomic coverage of phylogenetic and biological diversity. For example, no butterfly genome is yet available despite the unique genetic and biological properties of this group, such as diversified wing color patterns. The evolution and development of these patterns is being studied in a few target species, including Bicyclus anynana, where a whole-genome BAC library allows targeted access to large genomic regions. Methodology/Principal Findings We characterize ∼1.3 Mb of genomic sequence around 11 selected genes expressed in B. anynana developing wings. Extensive manual curation of in silico predictions, also making use of a large dataset of expressed genes for this species, identified repetitive elements and protein coding sequence, and highlighted an expansion of Alcohol dehydrogenase genes. Comparative analysis with orthologous regions of the lepidopteran reference genome allowed assessment of conservation of fine-scale synteny (with detection of new inversions and translocations) and of DNA sequence (with detection of high levels of conservation of non-coding regions around some, but not all, developmental genes). Conclusions The general properties and organization of the available B. anynana genomic sequence are similar to the lepidopteran reference, despite the more than 140 MY divergence. Our results lay the groundwork for further studies of new interesting findings in relation to both coding and non-coding sequence: 1) the Alcohol dehydrogenase expansion with higher similarity between the five tandemly-repeated B. anynana paralogs than with the corresponding B. mori orthologs, and 2) the high conservation of non-coding sequence around the genes wingless and Ecdysone receptor, both involved in multiple developmental processes including wing pattern formation. PMID:21909358

Evolution of the alternative AQP2 gene: Acquisition of a novel protein-coding sequence in dolphins.

PubMed

Kishida, Takushi; Suzuki, Miwa; Takayama, Asuka

2018-01-01

Taxon-specific de novo protein-coding sequences are thought to be important for taxon-specific environmental adaptation. A recent study revealed that bottlenose dolphins acquired a novel isoform of aquaporin 2 generated by alternative splicing (alternative AQP2), which helps dolphins to live in hyperosmotic seawater. The AQP2 gene consists of four exons, but the alternative AQP2 gene lacks the fourth exon and instead has a longer third exon that includes the original third exon and a part of the original third intron. Here, we show that the latter half of the third exon of the alternative AQP2 arose from a non-protein-coding sequence. Intact ORF of this de novo sequence is shared not by all cetaceans, but only by delphinoids. However, this sequence is conservative in all modern cetaceans, implying that this de novo sequence potentially plays important roles for marine adaptation in cetaceans. Copyright © 2017 Elsevier Inc. All rights reserved.

Complete Mitochondrial Genome of Echinostoma hortense (Digenea: Echinostomatidae).

PubMed

Liu, Ze-Xuan; Zhang, Yan; Liu, Yu-Ting; Chang, Qiao-Cheng; Su, Xin; Fu, Xue; Yue, Dong-Mei; Gao, Yuan; Wang, Chun-Ren

2016-04-01

Echinostoma hortense (Digenea: Echinostomatidae) is one of the intestinal flukes with medical importance in humans. However, the mitochondrial (mt) genome of this fluke has not been known yet. The present study has determined the complete mt genome sequences of E. hortense and assessed the phylogenetic relationships with other digenean species for which the complete mt genome sequences are available in GenBank using concatenated amino acid sequences inferred from 12 protein-coding genes. The mt genome of E. hortense contained 12 protein-coding genes, 22 transfer RNA genes, 2 ribosomal RNA genes, and 1 non-coding region. The length of the mt genome of E. hortense was 14,994 bp, which was somewhat smaller than those of other trematode species. Phylogenetic analyses based on concatenated nucleotide sequence datasets for all 12 protein-coding genes using maximum parsimony (MP) method showed that E. hortense and Hypoderaeum conoideum gathered together, and they were closer to each other than to Fasciolidae and other echinostomatid trematodes. The availability of the complete mt genome sequences of E. hortense provides important genetic markers for diagnostics, population genetics, and evolutionary studies of digeneans.

Complete Mitochondrial Genome of Echinostoma hortense (Digenea: Echinostomatidae)

PubMed Central

Liu, Ze-Xuan; Zhang, Yan; Liu, Yu-Ting; Chang, Qiao-Cheng; Su, Xin; Fu, Xue; Yue, Dong-Mei; Gao, Yuan; Wang, Chun-Ren

2016-01-01

Echinostoma hortense (Digenea: Echinostomatidae) is one of the intestinal flukes with medical importance in humans. However, the mitochondrial (mt) genome of this fluke has not been known yet. The present study has determined the complete mt genome sequences of E. hortense and assessed the phylogenetic relationships with other digenean species for which the complete mt genome sequences are available in GenBank using concatenated amino acid sequences inferred from 12 protein-coding genes. The mt genome of E. hortense contained 12 protein-coding genes, 22 transfer RNA genes, 2 ribosomal RNA genes, and 1 non-coding region. The length of the mt genome of E. hortense was 14,994 bp, which was somewhat smaller than those of other trematode species. Phylogenetic analyses based on concatenated nucleotide sequence datasets for all 12 protein-coding genes using maximum parsimony (MP) method showed that E. hortense and Hypoderaeum conoideum gathered together, and they were closer to each other than to Fasciolidae and other echinostomatid trematodes. The availability of the complete mt genome sequences of E. hortense provides important genetic markers for diagnostics, population genetics, and evolutionary studies of digeneans. PMID:27180575

Beta.-glucosidase coding sequences and protein from orpinomyces PC-2

DOEpatents

Li, Xin-Liang; Ljungdahl, Lars G.; Chen, Huizhong; Ximenes, Eduardo A.

2001-02-06

Provided is a novel .beta.-glucosidase from Orpinomyces sp. PC2, nucleotide sequences encoding the mature protein and the precursor protein, and methods for recombinant production of this .beta.-glucosidase.

Computational RNomics of Drosophilids

PubMed Central

Rose, Dominic; Hackermüller, Jörg; Washietl, Stefan; Reiche, Kristin; Hertel, Jana; Findeiß, Sven; Stadler, Peter F; Prohaska, Sonja J

2007-01-01

Background Recent experimental and computational studies have provided overwhelming evidence for a plethora of diverse transcripts that are unrelated to protein-coding genes. One subclass consists of those RNAs that require distinctive secondary structure motifs to exert their biological function and hence exhibit distinctive patterns of sequence conservation characteristic for positive selection on RNA secondary structure. The deep-sequencing of 12 drosophilid species coordinated by the NHGRI provides an ideal data set of comparative computational approaches to determine those genomic loci that code for evolutionarily conserved RNA motifs. This class of loci includes the majority of the known small ncRNAs as well as structured RNA motifs in mRNAs. We report here on a genome-wide survey using RNAz. Results We obtain 16 000 high quality predictions among which we recover the majority of the known ncRNAs. Taking a pessimistically estimated false discovery rate of 40% into account, this implies that at least some ten thousand loci in the Drosophila genome show the hallmarks of stabilizing selection action of RNA structure, and hence are most likely functional at the RNA level. A subset of RNAz predictions overlapping with TRF1 and BRF binding sites [Isogai et al., EMBO J. 26: 79–89 (2007)], which are plausible candidates of Pol III transcripts, have been studied in more detail. Among these sequences we identify several "clusters" of ncRNA candidates with striking structural similarities. Conclusion The statistical evaluation of the RNAz predictions in comparison with a similar analysis of vertebrate genomes [Washietl et al., Nat. Biotech. 23: 1383–1390 (2005)] shows that qualitatively similar fractions of structured RNAs are found in introns, UTRs, and intergenic regions. The intergenic RNA structures, however, are concentrated much more closely around known protein-coding loci, suggesting that flies have significantly smaller complement of independent structured ncRNAs compared to mammals. PMID:17996037

Predicting residue-wise contact orders in proteins by support vector regression.

PubMed

Song, Jiangning; Burrage, Kevin

2006-10-03

The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

A comprehensive catalog of human KRAB-associated zinc finger genes: Insights into the evolutionary history of a large family of transcriptional repressors

PubMed Central

Huntley, Stuart; Baggott, Daniel M.; Hamilton, Aaron T.; Tran-Gyamfi, Mary; Yang, Shan; Kim, Joomyeong; Gordon, Laurie; Branscomb, Elbert; Stubbs, Lisa

2006-01-01

Krüppel-type zinc finger (ZNF) motifs are prevalent components of transcription factor proteins in all eukaryotes. KRAB-ZNF proteins, in which a potent repressor domain is attached to a tandem array of DNA-binding zinc-finger motifs, are specific to tetrapod vertebrates and represent the largest class of ZNF proteins in mammals. To define the full repertoire of human KRAB-ZNF proteins, we searched the genome sequence for key motifs and then constructed and manually curated gene models incorporating those sequences. The resulting gene catalog contains 423 KRAB-ZNF protein-coding loci, yielding alternative transcripts that altogether predict at least 742 structurally distinct proteins. Active rounds of segmental duplication, involving single genes or larger regions and including both tandem and distributed duplication events, have driven the expansion of this mammalian gene family. Comparisons between the human genes and ZNF loci mined from the draft mouse, dog, and chimpanzee genomes not only identified 103 KRAB-ZNF genes that are conserved in mammals but also highlighted a substantial level of lineage-specific change; at least 136 KRAB-ZNF coding genes are primate specific, including many recent duplicates. KRAB-ZNF genes are widely expressed and clustered genes are typically not coregulated, indicating that paralogs have evolved to fill roles in many different biological processes. To facilitate further study, we have developed a Web-based public resource with access to gene models, sequences, and other data, including visualization tools to provide genomic context and interaction with other public data sets. PMID:16606702

Kullback Leibler divergence in complete bacterial and phage genomes

PubMed Central

Akhter, Sajia; Kashef, Mona T.; Ibrahim, Eslam S.; Bailey, Barbara

2017-01-01

The amino acid content of the proteins encoded by a genome may predict the coding potential of that genome and may reflect lifestyle restrictions of the organism. Here, we calculated the Kullback–Leibler divergence from the mean amino acid content as a metric to compare the amino acid composition for a large set of bacterial and phage genome sequences. Using these data, we demonstrate that (i) there is a significant difference between amino acid utilization in different phylogenetic groups of bacteria and phages; (ii) many of the bacteria with the most skewed amino acid utilization profiles, or the bacteria that host phages with the most skewed profiles, are endosymbionts or parasites; (iii) the skews in the distribution are not restricted to certain metabolic processes but are common across all bacterial genomic subsystems; (iv) amino acid utilization profiles strongly correlate with GC content in bacterial genomes but very weakly correlate with the G+C percent in phage genomes. These findings might be exploited to distinguish coding from non-coding sequences in large data sets, such as metagenomic sequence libraries, to help in prioritizing subsequent analyses. PMID:29204318

Kullback Leibler divergence in complete bacterial and phage genomes.

PubMed

Akhter, Sajia; Aziz, Ramy K; Kashef, Mona T; Ibrahim, Eslam S; Bailey, Barbara; Edwards, Robert A

2017-01-01

The amino acid content of the proteins encoded by a genome may predict the coding potential of that genome and may reflect lifestyle restrictions of the organism. Here, we calculated the Kullback-Leibler divergence from the mean amino acid content as a metric to compare the amino acid composition for a large set of bacterial and phage genome sequences. Using these data, we demonstrate that (i) there is a significant difference between amino acid utilization in different phylogenetic groups of bacteria and phages; (ii) many of the bacteria with the most skewed amino acid utilization profiles, or the bacteria that host phages with the most skewed profiles, are endosymbionts or parasites; (iii) the skews in the distribution are not restricted to certain metabolic processes but are common across all bacterial genomic subsystems; (iv) amino acid utilization profiles strongly correlate with GC content in bacterial genomes but very weakly correlate with the G+C percent in phage genomes. These findings might be exploited to distinguish coding from non-coding sequences in large data sets, such as metagenomic sequence libraries, to help in prioritizing subsequent analyses.

SCMPSP: Prediction and characterization of photosynthetic proteins based on a scoring card method.

PubMed

Vasylenko, Tamara; Liou, Yi-Fan; Chen, Hong-An; Charoenkwan, Phasit; Huang, Hui-Ling; Ho, Shinn-Ying

2015-01-01

Photosynthetic proteins (PSPs) greatly differ in their structure and function as they are involved in numerous subprocesses that take place inside an organelle called a chloroplast. Few studies predict PSPs from sequences due to their high variety of sequences and structues. This work aims to predict and characterize PSPs by establishing the datasets of PSP and non-PSP sequences and developing prediction methods. A novel bioinformatics method of predicting and characterizing PSPs based on scoring card method (SCMPSP) was used. First, a dataset consisting of 649 PSPs was established by using a Gene Ontology term GO:0015979 and 649 non-PSPs from the SwissProt database with sequence identity <= 25%.- Several prediction methods are presented based on support vector machine (SVM), decision tree J48, Bayes, BLAST, and SCM. The SVM method using dipeptide features-performed well and yielded - a test accuracy of 72.31%. The SCMPSP method uses the estimated propensity scores of 400 dipeptides - as PSPs and has a test accuracy of 71.54%, which is comparable to that of the SVM method. The derived propensity scores of 20 amino acids were further used to identify informative physicochemical properties for characterizing PSPs. The analytical results reveal the following four characteristics of PSPs: 1) PSPs favour hydrophobic side chain amino acids; 2) PSPs are composed of the amino acids prone to form helices in membrane environments; 3) PSPs have low interaction with water; and 4) PSPs prefer to be composed of the amino acids of electron-reactive side chains. The SCMPSP method not only estimates the propensity of a sequence to be PSPs, it also discovers characteristics that further improve understanding of PSPs. The SCMPSP source code and the datasets used in this study are available at http://iclab.life.nctu.edu.tw/SCMPSP/.

Evaluating High-Throughput Ab Initio Gene Finders to Discover Proteins Encoded in Eukaryotic Pathogen Genomes Missed by Laboratory Techniques

PubMed Central

Goodswen, Stephen J.; Kennedy, Paul J.; Ellis, John T.

2012-01-01

Next generation sequencing technology is advancing genome sequencing at an unprecedented level. By unravelling the code within a pathogen’s genome, every possible protein (prior to post-translational modifications) can theoretically be discovered, irrespective of life cycle stages and environmental stimuli. Now more than ever there is a great need for high-throughput ab initio gene finding. Ab initio gene finders use statistical models to predict genes and their exon-intron structures from the genome sequence alone. This paper evaluates whether existing ab initio gene finders can effectively predict genes to deduce proteins that have presently missed capture by laboratory techniques. An aim here is to identify possible patterns of prediction inaccuracies for gene finders as a whole irrespective of the target pathogen. All currently available ab initio gene finders are considered in the evaluation but only four fulfil high-throughput capability: AUGUSTUS, GeneMark_hmm, GlimmerHMM, and SNAP. These gene finders require training data specific to a target pathogen and consequently the evaluation results are inextricably linked to the availability and quality of the data. The pathogen, Toxoplasma gondii, is used to illustrate the evaluation methods. The results support current opinion that predicted exons by ab initio gene finders are inaccurate in the absence of experimental evidence. However, the results reveal some patterns of inaccuracy that are common to all gene finders and these inaccuracies may provide a focus area for future gene finder developers. PMID:23226328

Gene discovery in Eimeria tenella by immunoscreening cDNA expression libraries of sporozoites and schizonts with chicken intestinal antibodies.

PubMed

Réfega, Susana; Girard-Misguich, Fabienne; Bourdieu, Christiane; Péry, Pierre; Labbé, Marie

2003-04-02

Specific antibodies were produced ex vivo from intestinal culture of Eimeria tenella infected chickens. The specificity of these intestinal antibodies was tested against different parasite stages. These antibodies were used to immunoscreen first generation schizont and sporozoite cDNA libraries permitting the identification of new E. tenella antigens. We obtained a total of 119 cDNA clones which were subjected to sequence analysis. The sequences coding for the proteins inducing local immune responses were compared with nucleotide or protein databases and with expressed sequence tags (ESTs) databases. We identified new Eimeria genes coding for heat shock proteins, a ribosomal protein, a pyruvate kinase and a pyridoxine kinase. Specific features of other sequences are discussed.

orthAgogue: an agile tool for the rapid prediction of orthology relations.

PubMed

Ekseth, Ole Kristian; Kuiper, Martin; Mironov, Vladimir

2014-03-01

The comparison of genes and gene products across species depends on high-quality tools to determine the relationships between gene or protein sequences from various species. Although some excellent applications are available and widely used, their performance leaves room for improvement. We developed orthAgogue: a multithreaded C application for high-speed estimation of homology relations in massive datasets, operated via a flexible and easy command-line interface. The orthAgogue software is distributed under the GNU license. The source code and binaries compiled for Linux are available at https://code.google.com/p/orthagogue/.

A novel deletion/insertion mutation in the mRNA transcribed from one {alpha}1(I) collagen allele in a family with dominant type III OI and germline mosaicism

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, O.; Masters, C.; Lewis, M.B.

1994-09-01

In an 8-year-old girl and her father, both of whom have severe type III OI, we have previously used RNA/RNA hybrid analysis to demonstrate a mismatch in the region of {alpha}1(I) mRNA coding for aa 558-861. We used SSCP to further localize the abnormality to a subregion coding for aa 579-679. This region was subcloned and sequenced. Each patient`s cDNA has a deletion of the sequences coding for the last residue of exon 34, and all of exons 35 and 36 (aa 604-639), followed by an insertion of 156 nt from the 3{prime}-end of intron 36. PCR amplification of leukocytemore » DNA from the patients and the clinically normal paternal grandmother yielded two fragments: a 1007 bp fragment predicted from normal genomic sequences and a 445 bp fragment. Subcloning and sequencing of the shorter genomic PCR product confirmed the presence of a 565 bp genomic deletion from the end of exon 34 to the middle of intron 36. The abnormal protein is apparently synthesized and incorporated into helix. The inserted nucleotides are in frame with the collagenous sequence and contain no stop codons. They encode a 52 aa non-collagenous region. The fibroblast procollagen of the patients has both normal and electrophoretically delayed pro{alpha}(I) bands. The electrophoretically delayed procollagen is very sensitive to pepsin or trypsin digestion, as predicted by its non-collagenous sequence, and cannot be visualized as collagen. This unique OI collagen mutation is an excellent candidate for molecular targeting to {open_quotes}turn off{close_quotes} a dominant mutant allele.« less

Integrative Annotation of 21,037 Human Genes Validated by Full-Length cDNA Clones

PubMed Central

Imanishi, Tadashi; Itoh, Takeshi; Suzuki, Yutaka; O'Donovan, Claire; Fukuchi, Satoshi; Koyanagi, Kanako O; Barrero, Roberto A; Tamura, Takuro; Yamaguchi-Kabata, Yumi; Tanino, Motohiko; Yura, Kei; Miyazaki, Satoru; Ikeo, Kazuho; Homma, Keiichi; Kasprzyk, Arek; Nishikawa, Tetsuo; Hirakawa, Mika; Thierry-Mieg, Jean; Thierry-Mieg, Danielle; Ashurst, Jennifer; Jia, Libin; Nakao, Mitsuteru; Thomas, Michael A; Mulder, Nicola; Karavidopoulou, Youla; Jin, Lihua; Kim, Sangsoo; Yasuda, Tomohiro; Lenhard, Boris; Eveno, Eric; Suzuki, Yoshiyuki; Yamasaki, Chisato; Takeda, Jun-ichi; Gough, Craig; Hilton, Phillip; Fujii, Yasuyuki; Sakai, Hiroaki; Tanaka, Susumu; Amid, Clara; Bellgard, Matthew; Bonaldo, Maria de Fatima; Bono, Hidemasa; Bromberg, Susan K; Brookes, Anthony J; Bruford, Elspeth; Carninci, Piero; Chelala, Claude; Couillault, Christine; de Souza, Sandro J.; Debily, Marie-Anne; Devignes, Marie-Dominique; Dubchak, Inna; Endo, Toshinori; Estreicher, Anne; Eyras, Eduardo; Fukami-Kobayashi, Kaoru; R. Gopinath, Gopal; Graudens, Esther; Hahn, Yoonsoo; Han, Michael; Han, Ze-Guang; Hanada, Kousuke; Hanaoka, Hideki; Harada, Erimi; Hashimoto, Katsuyuki; Hinz, Ursula; Hirai, Momoki; Hishiki, Teruyoshi; Hopkinson, Ian; Imbeaud, Sandrine; Inoko, Hidetoshi; Kanapin, Alexander; Kaneko, Yayoi; Kasukawa, Takeya; Kelso, Janet; Kersey, Paul; Kikuno, Reiko; Kimura, Kouichi; Korn, Bernhard; Kuryshev, Vladimir; Makalowska, Izabela; Makino, Takashi; Mano, Shuhei; Mariage-Samson, Regine; Mashima, Jun; Matsuda, Hideo; Mewes, Hans-Werner; Minoshima, Shinsei; Nagai, Keiichi; Nagasaki, Hideki; Nagata, Naoki; Nigam, Rajni; Ogasawara, Osamu; Ohara, Osamu; Ohtsubo, Masafumi; Okada, Norihiro; Okido, Toshihisa; Oota, Satoshi; Ota, Motonori; Ota, Toshio; Otsuki, Tetsuji; Piatier-Tonneau, Dominique; Poustka, Annemarie; Ren, Shuang-Xi; Saitou, Naruya; Sakai, Katsunaga; Sakamoto, Shigetaka; Sakate, Ryuichi; Schupp, Ingo; Servant, Florence; Sherry, Stephen; Shiba, Rie; Shimizu, Nobuyoshi; Shimoyama, Mary; Simpson, Andrew J; Soares, Bento; Steward, Charles; Suwa, Makiko; Suzuki, Mami; Takahashi, Aiko; Tamiya, Gen; Tanaka, Hiroshi; Taylor, Todd; Terwilliger, Joseph D; Unneberg, Per; Veeramachaneni, Vamsi; Watanabe, Shinya; Wilming, Laurens; Yasuda, Norikazu; Yoo, Hyang-Sook; Stodolsky, Marvin; Makalowski, Wojciech; Go, Mitiko; Nakai, Kenta; Takagi, Toshihisa; Kanehisa, Minoru; Sakaki, Yoshiyuki; Quackenbush, John; Okazaki, Yasushi; Hayashizaki, Yoshihide; Hide, Winston; Chakraborty, Ranajit; Nishikawa, Ken; Sugawara, Hideaki; Tateno, Yoshio; Chen, Zhu; Oishi, Michio; Tonellato, Peter; Apweiler, Rolf; Okubo, Kousaku; Wagner, Lukas; Wiemann, Stefan; Strausberg, Robert L; Isogai, Takao; Auffray, Charles; Nomura, Nobuo; Sugano, Sumio

2004-01-01

The human genome sequence defines our inherent biological potential; the realization of the biology encoded therein requires knowledge of the function of each gene. Currently, our knowledge in this area is still limited. Several lines of investigation have been used to elucidate the structure and function of the genes in the human genome. Even so, gene prediction remains a difficult task, as the varieties of transcripts of a gene may vary to a great extent. We thus performed an exhaustive integrative characterization of 41,118 full-length cDNAs that capture the gene transcripts as complete functional cassettes, providing an unequivocal report of structural and functional diversity at the gene level. Our international collaboration has validated 21,037 human gene candidates by analysis of high-quality full-length cDNA clones through curation using unified criteria. This led to the identification of 5,155 new gene candidates. It also manifested the most reliable way to control the quality of the cDNA clones. We have developed a human gene database, called the H-Invitational Database (H-InvDB; http://www.h-invitational.jp/). It provides the following: integrative annotation of human genes, description of gene structures, details of novel alternative splicing isoforms, non-protein-coding RNAs, functional domains, subcellular localizations, metabolic pathways, predictions of protein three-dimensional structure, mapping of known single nucleotide polymorphisms (SNPs), identification of polymorphic microsatellite repeats within human genes, and comparative results with mouse full-length cDNAs. The H-InvDB analysis has shown that up to 4% of the human genome sequence (National Center for Biotechnology Information build 34 assembly) may contain misassembled or missing regions. We found that 6.5% of the human gene candidates (1,377 loci) did not have a good protein-coding open reading frame, of which 296 loci are strong candidates for non-protein-coding RNA genes. In addition, among 72,027 uniquely mapped SNPs and insertions/deletions localized within human genes, 13,215 nonsynonymous SNPs, 315 nonsense SNPs, and 452 indels occurred in coding regions. Together with 25 polymorphic microsatellite repeats present in coding regions, they may alter protein structure, causing phenotypic effects or resulting in disease. The H-InvDB platform represents a substantial contribution to resources needed for the exploration of human biology and pathology. PMID:15103394

Next generation sequencing and analysis of a conserved transcriptome of New Zealand's kiwi.

PubMed

Subramanian, Sankar; Huynen, Leon; Millar, Craig D; Lambert, David M

2010-12-15

Kiwi is a highly distinctive, flightless and endangered ratite bird endemic to New Zealand. To understand the patterns of molecular evolution of the nuclear protein-coding genes in brown kiwi (Apteryx australis mantelli) and to determine the timescale of avian history we sequenced a transcriptome obtained from a kiwi embryo using next generation sequencing methods. We then assembled the conserved protein-coding regions using the chicken proteome as a scaffold. Using 1,543 conserved protein coding genes we estimated the neutral evolutionary divergence between the kiwi and chicken to be ~45%, which is approximately equal to the divergence computed for the human-mouse pair using the same set of genes. A large fraction of genes was found to be under high selective constraint, as most of the expressed genes appeared to be involved in developmental gene regulation. Our study suggests a significant relationship between gene expression levels and protein evolution. Using sequences from over 700 nuclear genes we estimated the divergence between the two basal avian groups, Palaeognathae and Neognathae to be 132 million years, which is consistent with previous studies using mitochondrial genes. The results of this investigation revealed patterns of mutation and purifying selection in conserved protein coding regions in birds. Furthermore this study suggests a relatively cost-effective way of obtaining a glimpse into the fundamental molecular evolutionary attributes of a genome, particularly when no closely related genomic sequence is available.

Integrating protein structural dynamics and evolutionary analysis with Bio3D.

PubMed

Skjærven, Lars; Yao, Xin-Qiu; Scarabelli, Guido; Grant, Barry J

2014-12-10

Popular bioinformatics approaches for studying protein functional dynamics include comparisons of crystallographic structures, molecular dynamics simulations and normal mode analysis. However, determining how observed displacements and predicted motions from these traditionally separate analyses relate to each other, as well as to the evolution of sequence, structure and function within large protein families, remains a considerable challenge. This is in part due to the general lack of tools that integrate information of molecular structure, dynamics and evolution. Here, we describe the integration of new methodologies for evolutionary sequence, structure and simulation analysis into the Bio3D package. This major update includes unique high-throughput normal mode analysis for examining and contrasting the dynamics of related proteins with non-identical sequences and structures, as well as new methods for quantifying dynamical couplings and their residue-wise dissection from correlation network analysis. These new methodologies are integrated with major biomolecular databases as well as established methods for evolutionary sequence and comparative structural analysis. New functionality for directly comparing results derived from normal modes, molecular dynamics and principal component analysis of heterogeneous experimental structure distributions is also included. We demonstrate these integrated capabilities with example applications to dihydrofolate reductase and heterotrimeric G-protein families along with a discussion of the mechanistic insight provided in each case. The integration of structural dynamics and evolutionary analysis in Bio3D enables researchers to go beyond a prediction of single protein dynamics to investigate dynamical features across large protein families. The Bio3D package is distributed with full source code and extensive documentation as a platform independent R package under a GPL2 license from http://thegrantlab.org/bio3d/ .

Information and redundancy in the burial folding code of globular proteins within a wide range of shapes and sizes.

PubMed

Ferreira, Diogo C; van der Linden, Marx G; de Oliveira, Leandro C; Onuchic, José N; de Araújo, Antônio F Pereira

2016-04-01

Recent ab initio folding simulations for a limited number of small proteins have corroborated a previous suggestion that atomic burial information obtainable from sequence could be sufficient for tertiary structure determination when combined to sequence-independent geometrical constraints. Here, we use simulations parameterized by native burials to investigate the required amount of information in a diverse set of globular proteins comprising different structural classes and a wide size range. Burial information is provided by a potential term pushing each atom towards one among a small number L of equiprobable concentric layers. An upper bound for the required information is provided by the minimal number of layers L(min) still compatible with correct folding behavior. We obtain L(min) between 3 and 5 for seven small to medium proteins with 50 ≤ Nr ≤ 110 residues while for a larger protein with Nr = 141 we find that L ≥ 6 is required to maintain native stability. We additionally estimate the usable redundancy for a given L ≥ L(min) from the burial entropy associated to the largest folding-compatible fraction of "superfluous" atoms, for which the burial term can be turned off or target layers can be chosen randomly. The estimated redundancy for small proteins with L = 4 is close to 0.8. Our results are consistent with the above-average quality of burial predictions used in previous simulations and indicate that the fraction of approachable proteins could increase significantly with even a mild, plausible, improvement on sequence-dependent burial prediction or on sequence-independent constraints that augment the detectable redundancy during simulations. © 2016 Wiley Periodicals, Inc.

Immunoreactivity of polyclonal antibodies generated against the carboxy terminus of the predicted amino acid sequence of the Huntington disease gene

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alkatib, G.; Graham, R.; Pelmear-Telenius, A.

1994-09-01

A cDNA fragment spanning the 3{prime}-end of the Huntington disease gene (from 8052 to 9252) was cloned into a prokaryotic expression vector containing the E. Coli lac promoter and a portion of the coding sequence for {beta}-galactosidase. The truncated {beta}-galactosidase gene was cleaved with BamHl and fused in frame to the BamHl fragment of the Huntington disease gene 3{prime}-end. Expression analysis of proteins made in E. Coli revealed that 20-30% of the total cellular proteins was represented by the {beta}-galactosidase-huntingtin fusion protein. The identity of the Huntington disease protein amino acid sequences was confirmed by protein sequence analysis. Affinity chromatographymore » was used to purify large quantities of the fusion protein from bacterial cell lysates. Affinity-purified proteins were used to immunize New Zealand white rabbits for antibody production. The generated polyclonal antibodies were used to immunoprecipitate the Huntington disease gene product expressed in a neuroblastoma cell line. In this cell line the antibodies precipitated two protein bands of apparent gel migrations of 200 and 150 kd which together, correspond to the calculated molecular weight of the Huntington disease gene product (350 kd). Immunoblotting experiments revealed the presence of a large precursor protein in the range of 350-750 kd which is in agreement with the predicted molecular weight of the protein without post-translational modifications. These results indicate that the huntingtin protein is cleaved into two subunits in this neuroblastoma cell line and implicate that cleavage of a large precursor protein may contribute to its biological activity. Experiments are ongoing to determine the precursor-product relationship and to examine the synthesis of the huntingtin protein in freshly isolated rat brains, and to determine cellular and subcellular distribution of the gene product.« less

Predicting disulfide connectivity from protein sequence using multiple sequence feature vectors and secondary structure.

PubMed

Song, Jiangning; Yuan, Zheng; Tan, Hao; Huber, Thomas; Burrage, Kevin

2007-12-01

Disulfide bonds are primary covalent crosslinks between two cysteine residues in proteins that play critical roles in stabilizing the protein structures and are commonly found in extracy-toplasmatic or secreted proteins. In protein folding prediction, the localization of disulfide bonds can greatly reduce the search in conformational space. Therefore, there is a great need to develop computational methods capable of accurately predicting disulfide connectivity patterns in proteins that could have potentially important applications. We have developed a novel method to predict disulfide connectivity patterns from protein primary sequence, using a support vector regression (SVR) approach based on multiple sequence feature vectors and predicted secondary structure by the PSIPRED program. The results indicate that our method could achieve a prediction accuracy of 74.4% and 77.9%, respectively, when averaged on proteins with two to five disulfide bridges using 4-fold cross-validation, measured on the protein and cysteine pair on a well-defined non-homologous dataset. We assessed the effects of different sequence encoding schemes on the prediction performance of disulfide connectivity. It has been shown that the sequence encoding scheme based on multiple sequence feature vectors coupled with predicted secondary structure can significantly improve the prediction accuracy, thus enabling our method to outperform most of other currently available predictors. Our work provides a complementary approach to the current algorithms that should be useful in computationally assigning disulfide connectivity patterns and helps in the annotation of protein sequences generated by large-scale whole-genome projects. The prediction web server and Supplementary Material are accessible at http://foo.maths.uq.edu.au/~huber/disulfide

Novel coding, translation, and gene expression of a replicating covalently closed circular RNA of 220 nt

PubMed Central

AbouHaidar, Mounir Georges; Venkataraman, Srividhya; Golshani, Ashkan; Liu, Bolin; Ahmad, Tauqeer

2014-01-01

The highly structured (64% GC) covalently closed circular (CCC) RNA (220 nt) of the virusoid associated with rice yellow mottle virus codes for a 16-kDa highly basic protein using novel modalities for coding, translation, and gene expression. This CCC RNA is the smallest among all known viroids and virusoids and the only one that codes proteins. Its sequence possesses an internal ribosome entry site and is directly translated through two (or three) completely overlapping ORFs (shifting to a new reading frame at the end of each round). The initiation and termination codons overlap UGAUGA (underline highlights the initiation codon AUG within the combined initiation-termination sequence). Termination codons can be ignored to obtain larger read-through proteins. This circular RNA with no noncoding sequences is a unique natural supercompact “nanogenome.” PMID:25253891

Cloning, sequencing, disruption and phenotypic analysis of uvsC, an Aspergillus nidulans homologue of yeast RAD51.

PubMed

van Heemst, D; Swart, K; Holub, E F; van Dijk, R; Offenberg, H H; Goosen, T; van den Broek, H W; Heyting, C

1997-05-01

We have cloned the uvsC gene of Aspergillus nidulans by complementation of the A. nidulans uvsC114 mutant. The predicted protein UVSC shows 67.4% sequence identity to the Saccharomyces cerevisiae Rad51 protein and 27.4% sequence identity to the Escherichia coli RecA protein. Transcription of uvsC is induced by methyl-methane sulphonate (MMS), as is transcription of RAD51 of yeast. Similar levels of uvsC transcription were observed after MMS induction in a uvsC+ strain and the uvsC114 mutant. The coding sequence of the uvsC114 allele has a deletion of 6 bp, which results in deletion of two amino acids and replacement of one amino acid in the translation product. In order to gain more insight into the biological function of the uvsC gene, a uvsC null mutant was constructed, in which the entire uvsC coding sequence was replaced by a selectable marker gene. Meiotic and mitotic phenotypes of a uvsC+ strain, the uvsC114 mutant and the uvsC null mutant were compared. The uvsC null mutant was more sensitive to both UV and MMS than the uvsC114 mutant. The uvsC114 mutant arrested in meiotic prophase-I. The uvsC null mutant arrested at an earlier stage, before the onset of meiosis. One possible interpretation of these meiotic phenotypes is that the A. nidulans homologue of Rad51 of yeast has a role both in the specialized processes preceding meiosis and in meiotic prophase I.

Detecting long tandem duplications in genomic sequences.

PubMed

Audemard, Eric; Schiex, Thomas; Faraut, Thomas

2012-05-08

Detecting duplication segments within completely sequenced genomes provides valuable information to address genome evolution and in particular the important question of the emergence of novel functions. The usual approach to gene duplication detection, based on all-pairs protein gene comparisons, provides only a restricted view of duplication. In this paper, we introduce ReD Tandem, a software using a flow based chaining algorithm targeted at detecting tandem duplication arrays of moderate to longer length regions, with possibly locally weak similarities, directly at the DNA level. On the A. thaliana genome, using a reference set of tandem duplicated genes built using TAIR,(a) we show that ReD Tandem is able to predict a large fraction of recently duplicated genes (dS  <  1) and that it is also able to predict tandem duplications involving non coding elements such as pseudo-genes or RNA genes. ReD Tandem allows to identify large tandem duplications without any annotation, leading to agnostic identification of tandem duplications. This approach nicely complements the usual protein gene based which ignores duplications involving non coding regions. It is however inherently restricted to relatively recent duplications. By recovering otherwise ignored events, ReD Tandem gives a more comprehensive view of existing evolutionary processes and may also allow to improve existing annotations.

Nmf9 Encodes a Highly Conserved Protein Important to Neurological Function in Mice and Flies.

PubMed

Zhang, Shuxiao; Ross, Kevin D; Seidner, Glen A; Gorman, Michael R; Poon, Tiffany H; Wang, Xiaobo; Keithley, Elizabeth M; Lee, Patricia N; Martindale, Mark Q; Joiner, William J; Hamilton, Bruce A

2015-07-01

Many protein-coding genes identified by genome sequencing remain without functional annotation or biological context. Here we define a novel protein-coding gene, Nmf9, based on a forward genetic screen for neurological function. ENU-induced and genome-edited null mutations in mice produce deficits in vestibular function, fear learning and circadian behavior, which correlated with Nmf9 expression in inner ear, amygdala, and suprachiasmatic nuclei. Homologous genes from unicellular organisms and invertebrate animals predict interactions with small GTPases, but the corresponding domains are absent in mammalian Nmf9. Intriguingly, homozygotes for null mutations in the Drosophila homolog, CG45058, show profound locomotor defects and premature death, while heterozygotes show striking effects on sleep and activity phenotypes. These results link a novel gene orthology group to discrete neurological functions, and show conserved requirement across wide phylogenetic distance and domain level structural changes.

The sequence of camelpox virus shows it is most closely related to variola virus, the cause of smallpox.

PubMed

Gubser, Caroline; Smith, Geoffrey L

2002-04-01

Camelpox virus (CMPV) and variola virus (VAR) are orthopoxviruses (OPVs) that share several biological features and cause high mortality and morbidity in their single host species. The sequence of a virulent CMPV strain was determined; it is 202182 bp long, with inverted terminal repeats (ITRs) of 6045 bp and has 206 predicted open reading frames (ORFs). As for other poxviruses, the genes are tightly packed with little non-coding sequence. Most genes within 25 kb of each terminus are transcribed outwards towards the terminus, whereas genes within the centre of the genome are transcribed from either DNA strand. The central region of the genome contains genes that are highly conserved in other OPVs and 87 of these are conserved in all sequenced chordopoxviruses. In contrast, genes towards either terminus are more variable and encode proteins involved in host range, virulence or immunomodulation. In some cases, these are broken versions of genes found in other OPVs. The relationship of CMPV to other OPVs was analysed by comparisons of DNA and predicted protein sequences, repeats within the ITRs and arrangement of ORFs within the terminal regions. Each comparison gave the same conclusion: CMPV is the closest known virus to variola virus, the cause of smallpox.

Discovery of functional elements in 12 Drosophila genomes using evolutionary signatures

PubMed Central

Stark, Alexander; Lin, Michael F.; Kheradpour, Pouya; Pedersen, Jakob S.; Parts, Leopold; Carlson, Joseph W.; Crosby, Madeline A.; Rasmussen, Matthew D.; Roy, Sushmita; Deoras, Ameya N.; Ruby, J. Graham; Brennecke, Julius; Hodges, Emily; Hinrichs, Angie S.; Caspi, Anat; Paten, Benedict; Park, Seung-Won; Han, Mira V.; Maeder, Morgan L.; Polansky, Benjamin J.; Robson, Bryanne E.; Aerts, Stein; van Helden, Jacques; Hassan, Bassem; Gilbert, Donald G.; Eastman, Deborah A.; Rice, Michael; Weir, Michael; Hahn, Matthew W.; Park, Yongkyu; Dewey, Colin N.; Pachter, Lior; Kent, W. James; Haussler, David; Lai, Eric C.; Bartel, David P.; Hannon, Gregory J.; Kaufman, Thomas C.; Eisen, Michael B.; Clark, Andrew G.; Smith, Douglas; Celniker, Susan E.; Gelbart, William M.; Kellis, Manolis

2008-01-01

Sequencing of multiple related species followed by comparative genomics analysis constitutes a powerful approach for the systematic understanding of any genome. Here, we use the genomes of 12 Drosophila species for the de novo discovery of functional elements in the fly. Each type of functional element shows characteristic patterns of change, or ‘evolutionary signatures’, dictated by its precise selective constraints. Such signatures enable recognition of new protein-coding genes and exons, spurious and incorrect gene annotations, and numerous unusual gene structures, including abundant stop-codon readthrough. Similarly, we predict non-protein-coding RNA genes and structures, and new microRNA (miRNA) genes. We provide evidence of miRNA processing and functionality from both hairpin arms and both DNA strands. We identify several classes of pre- and post-transcriptional regulatory motifs, and predict individual motif instances with high confidence. We also study how discovery power scales with the divergence and number of species compared, and we provide general guidelines for comparative studies. PMID:17994088

Delineating slowly and rapidly evolving fractions of the Drosophila genome.

PubMed

Keith, Jonathan M; Adams, Peter; Stephen, Stuart; Mattick, John S

2008-05-01

Evolutionary conservation is an important indicator of function and a major component of bioinformatic methods to identify non-protein-coding genes. We present a new Bayesian method for segmenting pairwise alignments of eukaryotic genomes while simultaneously classifying segments into slowly and rapidly evolving fractions. We also describe an information criterion similar to the Akaike Information Criterion (AIC) for determining the number of classes. Working with pairwise alignments enables detection of differences in conservation patterns among closely related species. We analyzed three whole-genome and three partial-genome pairwise alignments among eight Drosophila species. Three distinct classes of conservation level were detected. Sequences comprising the most slowly evolving component were consistent across a range of species pairs, and constituted approximately 62-66% of the D. melanogaster genome. Almost all (>90%) of the aligned protein-coding sequence is in this fraction, suggesting much of it (comprising the majority of the Drosophila genome, including approximately 56% of non-protein-coding sequences) is functional. The size and content of the most rapidly evolving component was species dependent, and varied from 1.6% to 4.8%. This fraction is also enriched for protein-coding sequence (while containing significant amounts of non-protein-coding sequence), suggesting it is under positive selection. We also classified segments according to conservation and GC content simultaneously. This analysis identified numerous sub-classes of those identified on the basis of conservation alone, but was nevertheless consistent with that classification. Software, data, and results available at www.maths.qut.edu.au/-keithj/. Genomic segments comprising the conservation classes available in BED format.

Automated conserved non-coding sequence (CNS) discovery reveals differences in gene content and promoter evolution among grasses

PubMed Central

Turco, Gina; Schnable, James C.; Pedersen, Brent; Freeling, Michael

2013-01-01

Conserved non-coding sequences (CNS) are islands of non-coding sequence that, like protein coding exons, show less divergence in sequence between related species than functionless DNA. Several CNSs have been demonstrated experimentally to function as cis-regulatory regions. However, the specific functions of most CNSs remain unknown. Previous searches for CNS in plants have either anchored on exons and only identified nearby sequences or required years of painstaking manual annotation. Here we present an open source tool that can accurately identify CNSs between any two related species with sequenced genomes, including both those immediately adjacent to exons and distal sequences separated by >12 kb of non-coding sequence. We have used this tool to characterize new motifs, associate CNSs with additional functions, and identify previously undetected genes encoding RNA and protein in the genomes of five grass species. We provide a list of 15,363 orthologous CNSs conserved across all grasses tested. We were also able to identify regulatory sequences present in the common ancestor of grasses that have been lost in one or more extant grass lineages. Lists of orthologous gene pairs and associated CNSs are provided for reference inbred lines of arabidopsis, Japonica rice, foxtail millet, sorghum, brachypodium, and maize. PMID:23874343

The nucleotide sequence of RNA1 of Lettuce big-vein virus, genus Varicosavirus, reveals its relation to nonsegmented negative-strand RNA viruses.

PubMed

Sasaya, Takahide; Ishikawa, Koichi; Koganezawa, Hiroki

2002-06-05

The complete nucleotide sequence of RNA1 from Lettuce big-vein virus (LBVV), the type member of the genus Varicosavirus, was determined. LBVV RNA1 consists of 6797 nucleotides and contains one large ORF that encodes a large (L) protein of 2040 amino acids with a predicted M(r) of 232,092. Northern blot hybridization analysis indicated that the LBVV RNA1 is a negative-sense RNA. Database searches showed that the amino acid sequence of L protein is homologous to those of L polymerases of nonsegmented negative-strand RNA viruses. A cluster dendrogram derived from alignments of the LBVV L protein and the L polymerases indicated that the L protein is most closely related to the L polymerases of plant rhabdoviruses. Transcription termination/polyadenylation signal-like poly(U) tracts that resemble those in rhabdovirus and paramyxovirus RNAs were present upstream and downstream of the coding region. Although LBVV is related to rhabdoviruses, a key distinguishing feature is that the genome of LBVV is segmented. The results reemphasize the need to reconsider the taxonomic position of varicosaviruses.

PaperBLAST: Text Mining Papers for Information about Homologs.

PubMed

Price, Morgan N; Arkin, Adam P

2017-01-01

Large-scale genome sequencing has identified millions of protein-coding genes whose function is unknown. Many of these proteins are similar to characterized proteins from other organisms, but much of this information is missing from annotation databases and is hidden in the scientific literature. To make this information accessible, PaperBLAST uses EuropePMC to search the full text of scientific articles for references to genes. PaperBLAST also takes advantage of curated resources (Swiss-Prot, GeneRIF, and EcoCyc) that link protein sequences to scientific articles. PaperBLAST's database includes over 700,000 scientific articles that mention over 400,000 different proteins. Given a protein of interest, PaperBLAST quickly finds similar proteins that are discussed in the literature and presents snippets of text from relevant articles or from the curators. PaperBLAST is available at http://papers.genomics.lbl.gov/. IMPORTANCE With the recent explosion of genome sequencing data, there are now millions of uncharacterized proteins. If a scientist becomes interested in one of these proteins, it can be very difficult to find information as to its likely function. Often a protein whose sequence is similar, and which is likely to have a similar function, has been studied already, but this information is not available in any database. To help find articles about similar proteins, PaperBLAST searches the full text of scientific articles for protein identifiers or gene identifiers, and it links these articles to protein sequences. Then, given a protein of interest, it can quickly find similar proteins in its database by using standard software (BLAST), and it can show snippets of text from relevant papers. We hope that PaperBLAST will make it easier for biologists to predict proteins' functions.

Identification of a Conserved Non-Protein-Coding Genomic Element that Plays an Essential Role in Alphabaculovirus Pathogenesis

PubMed Central

Kikhno, Irina

2014-01-01

Highly homologous sequences 154–157 bp in length grouped under the name of “conserved non-protein-coding element” (CNE) were revealed in all of the sequenced genomes of baculoviruses belonging to the genus Alphabaculovirus. A CNE alignment led to the detection of a set of highly conserved nucleotide clusters that occupy strictly conserved positions in the CNE sequence. The significant length of the CNE and conservation of both its length and cluster architecture were identified as a combination of characteristics that make this CNE different from known viral non-coding functional sequences. The essential role of the CNE in the Alphabaculovirus life cycle was demonstrated through the use of a CNE-knockout Autographa californica multiple nucleopolyhedrovirus (AcMNPV) bacmid. It was shown that the essential function of the CNE was not mediated by the presumed expression activities of the protein- and non-protein-coding genes that overlap the AcMNPV CNE. On the basis of the presented data, the AcMNPV CNE was categorized as a complex-structured, polyfunctional genomic element involved in an essential DNA transaction that is associated with an undefined function of the baculovirus genome. PMID:24740153

Recombinant pinoresinol/lariciresinol reductase, recombinant dirigent protein, and methods of use

DOEpatents

Lewis, Norman G.; Davin, Laurence B.; Dinkova-Kostova, Albena T.; Fujita, Masayuki; Gang, David R.; Sarkanen, Simo; Ford, Joshua D.

2001-04-03

Dirigent proteins and pinoresinol/lariciresinol reductases have been isolated, together with cDNAs encoding dirigent proteins and pinoresinol/lariciresinol reductases. Accordingly, isolated DNA sequences are provided which code for the expression of dirigent proteins and pinoresinol/lariciresinol reductases. In other aspects, replicable recombinant cloning vehicles are provided which code for dirigent proteins or pinoresinol/lariciresinol reductases or for a base sequence sufficiently complementary to at least a portion of dirigent protein or pinoresinol/lariciresinol reductase DNA or RNA to enable hybridization therewith. In yet other aspects, modified host cells are provided that have been transformed, transfected, infected and/or injected with a recombinant cloning vehicle and/or DNA sequence encoding dirigent protein or pinoresinol/lariciresinol reductase. Thus, systems and methods are provided for the recombinant expression of dirigent proteins and/or pinoresinol/lariciresinol reductases.

HomPPI: a class of sequence homology based protein-protein interface prediction methods

PubMed Central

2011-01-01

Background Although homology-based methods are among the most widely used methods for predicting the structure and function of proteins, the question as to whether interface sequence conservation can be effectively exploited in predicting protein-protein interfaces has been a subject of debate. Results We studied more than 300,000 pair-wise alignments of protein sequences from structurally characterized protein complexes, including both obligate and transient complexes. We identified sequence similarity criteria required for accurate homology-based inference of interface residues in a query protein sequence. Based on these analyses, we developed HomPPI, a class of sequence homology-based methods for predicting protein-protein interface residues. We present two variants of HomPPI: (i) NPS-HomPPI (Non partner-specific HomPPI), which can be used to predict interface residues of a query protein in the absence of knowledge of the interaction partner; and (ii) PS-HomPPI (Partner-specific HomPPI), which can be used to predict the interface residues of a query protein with a specific target protein. Our experiments on a benchmark dataset of obligate homodimeric complexes show that NPS-HomPPI can reliably predict protein-protein interface residues in a given protein, with an average correlation coefficient (CC) of 0.76, sensitivity of 0.83, and specificity of 0.78, when sequence homologs of the query protein can be reliably identified. NPS-HomPPI also reliably predicts the interface residues of intrinsically disordered proteins. Our experiments suggest that NPS-HomPPI is competitive with several state-of-the-art interface prediction servers including those that exploit the structure of the query proteins. The partner-specific classifier, PS-HomPPI can, on a large dataset of transient complexes, predict the interface residues of a query protein with a specific target, with a CC of 0.65, sensitivity of 0.69, and specificity of 0.70, when homologs of both the query and the target can be reliably identified. The HomPPI web server is available at http://homppi.cs.iastate.edu/. Conclusions Sequence homology-based methods offer a class of computationally efficient and reliable approaches for predicting the protein-protein interface residues that participate in either obligate or transient interactions. For query proteins involved in transient interactions, the reliability of interface residue prediction can be improved by exploiting knowledge of putative interaction partners. PMID:21682895

PaperBLAST: Text Mining Papers for Information about Homologs

DOE PAGES

Price, Morgan N.; Arkin, Adam P.

2017-08-15

Large-scale genome sequencing has identified millions of protein-coding genes whose function is unknown. Many of these proteins are similar to characterized proteins from other organisms, but much of this information is missing from annotation databases and is hidden in the scientific literature. To make this information accessible, PaperBLAST uses EuropePMC to search the full text of scientific articles for references to genes. PaperBLAST also takes advantage of curated resources (Swiss-Prot, GeneRIF, and EcoCyc) that link protein sequences to scientific articles. PaperBLAST’s database includes over 700,000 scientific articles that mention over 400,000 different proteins. Given a protein of interest, PaperBLAST quicklymore » finds similar proteins that are discussed in the literature and presents snippets of text from relevant articles or from the curators. With the recent explosion of genome sequencing data, there are now millions of uncharacterized proteins. If a scientist becomes interested in one of these proteins, it can be very difficult to find information as to its likely function. Often a protein whose sequence is similar, and which is likely to have a similar function, has been studied already, but this information is not available in any database. To help find articles about similar proteins, PaperBLAST searches the full text of scientific articles for protein identifiers or gene identifiers, and it links these articles to protein sequences. Then, given a protein of interest, it can quickly find similar proteins in its database by using standard software (BLAST), and it can show snippets of text from relevant papers. We hope that PaperBLAST will make it easier for biologists to predict proteins’ functions.« less

PaperBLAST: Text Mining Papers for Information about Homologs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Price, Morgan N.; Arkin, Adam P.

Large-scale genome sequencing has identified millions of protein-coding genes whose function is unknown. Many of these proteins are similar to characterized proteins from other organisms, but much of this information is missing from annotation databases and is hidden in the scientific literature. To make this information accessible, PaperBLAST uses EuropePMC to search the full text of scientific articles for references to genes. PaperBLAST also takes advantage of curated resources (Swiss-Prot, GeneRIF, and EcoCyc) that link protein sequences to scientific articles. PaperBLAST’s database includes over 700,000 scientific articles that mention over 400,000 different proteins. Given a protein of interest, PaperBLAST quicklymore » finds similar proteins that are discussed in the literature and presents snippets of text from relevant articles or from the curators. With the recent explosion of genome sequencing data, there are now millions of uncharacterized proteins. If a scientist becomes interested in one of these proteins, it can be very difficult to find information as to its likely function. Often a protein whose sequence is similar, and which is likely to have a similar function, has been studied already, but this information is not available in any database. To help find articles about similar proteins, PaperBLAST searches the full text of scientific articles for protein identifiers or gene identifiers, and it links these articles to protein sequences. Then, given a protein of interest, it can quickly find similar proteins in its database by using standard software (BLAST), and it can show snippets of text from relevant papers. We hope that PaperBLAST will make it easier for biologists to predict proteins’ functions.« less

PaperBLAST: Text Mining Papers for Information about Homologs

PubMed Central

Arkin, Adam P.

2017-01-01

ABSTRACT Large-scale genome sequencing has identified millions of protein-coding genes whose function is unknown. Many of these proteins are similar to characterized proteins from other organisms, but much of this information is missing from annotation databases and is hidden in the scientific literature. To make this information accessible, PaperBLAST uses EuropePMC to search the full text of scientific articles for references to genes. PaperBLAST also takes advantage of curated resources (Swiss-Prot, GeneRIF, and EcoCyc) that link protein sequences to scientific articles. PaperBLAST’s database includes over 700,000 scientific articles that mention over 400,000 different proteins. Given a protein of interest, PaperBLAST quickly finds similar proteins that are discussed in the literature and presents snippets of text from relevant articles or from the curators. PaperBLAST is available at http://papers.genomics.lbl.gov/. IMPORTANCE With the recent explosion of genome sequencing data, there are now millions of uncharacterized proteins. If a scientist becomes interested in one of these proteins, it can be very difficult to find information as to its likely function. Often a protein whose sequence is similar, and which is likely to have a similar function, has been studied already, but this information is not available in any database. To help find articles about similar proteins, PaperBLAST searches the full text of scientific articles for protein identifiers or gene identifiers, and it links these articles to protein sequences. Then, given a protein of interest, it can quickly find similar proteins in its database by using standard software (BLAST), and it can show snippets of text from relevant papers. We hope that PaperBLAST will make it easier for biologists to predict proteins’ functions. PMID:28845458

Chromosome-level genome assembly and transcriptome of the green alga Chromochloris zofingiensis illuminates astaxanthin production.

PubMed

Roth, Melissa S; Cokus, Shawn J; Gallaher, Sean D; Walter, Andreas; Lopez, David; Erickson, Erika; Endelman, Benjamin; Westcott, Daniel; Larabell, Carolyn A; Merchant, Sabeeha S; Pellegrini, Matteo; Niyogi, Krishna K

2017-05-23

Microalgae have potential to help meet energy and food demands without exacerbating environmental problems. There is interest in the unicellular green alga Chromochloris zofingiensis , because it produces lipids for biofuels and a highly valuable carotenoid nutraceutical, astaxanthin. To advance understanding of its biology and facilitate commercial development, we present a C. zofingiensis chromosome-level nuclear genome, organelle genomes, and transcriptome from diverse growth conditions. The assembly, derived from a combination of short- and long-read sequencing in conjunction with optical mapping, revealed a compact genome of ∼58 Mbp distributed over 19 chromosomes containing 15,274 predicted protein-coding genes. The genome has uniform gene density over chromosomes, low repetitive sequence content (∼6%), and a high fraction of protein-coding sequence (∼39%) with relatively long coding exons and few coding introns. Functional annotation of gene models identified orthologous families for the majority (∼73%) of genes. Synteny analysis uncovered localized but scrambled blocks of genes in putative orthologous relationships with other green algae. Two genes encoding beta-ketolase ( BKT ), the key enzyme synthesizing astaxanthin, were found in the genome, and both were up-regulated by high light. Isolation and molecular analysis of astaxanthin-deficient mutants showed that BKT1 is required for the production of astaxanthin. Moreover, the transcriptome under high light exposure revealed candidate genes that could be involved in critical yet missing steps of astaxanthin biosynthesis, including ABC transporters, cytochrome P450 enzymes, and an acyltransferase. The high-quality genome and transcriptome provide insight into the green algal lineage and carotenoid production.

Chromosome-level genome assembly and transcriptome of the green alga Chromochloris zofingiensis illuminates astaxanthin production

DOE PAGES

Roth, Melissa S.; Cokus, Shawn J.; Gallaher, Sean D.; ...

2017-05-08

Microalgae have potential to help meet energy and food demands without exacerbating environmental problems. There is interest in the unicellular green alga Chromochloris zofingiensis, because it produces lipids for biofuels and a highly valuable carotenoid nutraceutical, astaxanthin. Here, to advance understanding of its biology and facilitate commercial development, we present a C. zofingiensis chromosome-level nuclear genome, organelle genomes, and transcriptome from diverse growth conditions. The assembly, derived from a combination of short- and long-read sequencing in conjunction with optical mapping, revealed a compact genome of ~58 Mbp distributed over 19 chromosomes containing 15,274 predicted protein-coding genes. The genome has uniformmore » gene density over chromosomes, low repetitive sequence content (~6%), and a high fraction of protein-coding sequence (~39%) with relatively long coding exons and few coding introns. Functional annotation of gene models identified orthologous families for the majority (~73%) of genes. Synteny analysis uncovered localized but scrambled blocks of genes in putative orthologous relationships with other green algae. Two genes encoding beta-ketolase (BKT), the key enzyme synthesizing astaxanthin, were found in the genome, and both were up-regulated by high light. Isolation and molecular analysis of astaxanthin-deficient mutants showed that BKT1 is required for the production of astaxanthin. Moreover, the transcriptome under high light exposure revealed candidate genes that could be involved in critical yet missing steps of astaxanthin biosynthesis, including ABC transporters, cytochrome P450 enzymes, and an acyltransferase. Finally, the high-quality genome and transcriptome provide insight into the green algal lineage and carotenoid production.« less

Chromosome-level genome assembly and transcriptome of the green alga Chromochloris zofingiensis illuminates astaxanthin production

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roth, Melissa S.; Cokus, Shawn J.; Gallaher, Sean D.

Microalgae have potential to help meet energy and food demands without exacerbating environmental problems. There is interest in the unicellular green alga Chromochloris zofingiensis, because it produces lipids for biofuels and a highly valuable carotenoid nutraceutical, astaxanthin. Here, to advance understanding of its biology and facilitate commercial development, we present a C. zofingiensis chromosome-level nuclear genome, organelle genomes, and transcriptome from diverse growth conditions. The assembly, derived from a combination of short- and long-read sequencing in conjunction with optical mapping, revealed a compact genome of ~58 Mbp distributed over 19 chromosomes containing 15,274 predicted protein-coding genes. The genome has uniformmore » gene density over chromosomes, low repetitive sequence content (~6%), and a high fraction of protein-coding sequence (~39%) with relatively long coding exons and few coding introns. Functional annotation of gene models identified orthologous families for the majority (~73%) of genes. Synteny analysis uncovered localized but scrambled blocks of genes in putative orthologous relationships with other green algae. Two genes encoding beta-ketolase (BKT), the key enzyme synthesizing astaxanthin, were found in the genome, and both were up-regulated by high light. Isolation and molecular analysis of astaxanthin-deficient mutants showed that BKT1 is required for the production of astaxanthin. Moreover, the transcriptome under high light exposure revealed candidate genes that could be involved in critical yet missing steps of astaxanthin biosynthesis, including ABC transporters, cytochrome P450 enzymes, and an acyltransferase. Finally, the high-quality genome and transcriptome provide insight into the green algal lineage and carotenoid production.« less

Chromosome-level genome assembly and transcriptome of the green alga Chromochloris zofingiensis illuminates astaxanthin production

PubMed Central

Roth, Melissa S.; Cokus, Shawn J.; Gallaher, Sean D.; Walter, Andreas; Lopez, David; Erickson, Erika; Endelman, Benjamin; Westcott, Daniel; Larabell, Carolyn A.; Merchant, Sabeeha S.; Pellegrini, Matteo

2017-01-01

Microalgae have potential to help meet energy and food demands without exacerbating environmental problems. There is interest in the unicellular green alga Chromochloris zofingiensis, because it produces lipids for biofuels and a highly valuable carotenoid nutraceutical, astaxanthin. To advance understanding of its biology and facilitate commercial development, we present a C. zofingiensis chromosome-level nuclear genome, organelle genomes, and transcriptome from diverse growth conditions. The assembly, derived from a combination of short- and long-read sequencing in conjunction with optical mapping, revealed a compact genome of ∼58 Mbp distributed over 19 chromosomes containing 15,274 predicted protein-coding genes. The genome has uniform gene density over chromosomes, low repetitive sequence content (∼6%), and a high fraction of protein-coding sequence (∼39%) with relatively long coding exons and few coding introns. Functional annotation of gene models identified orthologous families for the majority (∼73%) of genes. Synteny analysis uncovered localized but scrambled blocks of genes in putative orthologous relationships with other green algae. Two genes encoding beta-ketolase (BKT), the key enzyme synthesizing astaxanthin, were found in the genome, and both were up-regulated by high light. Isolation and molecular analysis of astaxanthin-deficient mutants showed that BKT1 is required for the production of astaxanthin. Moreover, the transcriptome under high light exposure revealed candidate genes that could be involved in critical yet missing steps of astaxanthin biosynthesis, including ABC transporters, cytochrome P450 enzymes, and an acyltransferase. The high-quality genome and transcriptome provide insight into the green algal lineage and carotenoid production. PMID:28484037

Capturing the Biofuel Wellhead and Powerhouse: The Chloroplast and Mitochondrial Genomes of the Leguminous Feedstock Tree Pongamia pinnata

PubMed Central

Kazakoff, Stephen H.; Imelfort, Michael; Edwards, David; Koehorst, Jasper; Biswas, Bandana; Batley, Jacqueline; Scott, Paul T.; Gresshoff, Peter M.

2012-01-01

Pongamia pinnata (syn. Millettia pinnata) is a novel, fast-growing arboreal legume that bears prolific quantities of oil-rich seeds suitable for the production of biodiesel and aviation biofuel. Here, we have used Illumina® ‘Second Generation DNA Sequencing (2GS)’ and a new short-read de novo assembler, SaSSY, to assemble and annotate the Pongamia chloroplast (152,968 bp; cpDNA) and mitochondrial (425,718 bp; mtDNA) genomes. We also show that SaSSY can be used to accurately assemble 2GS data, by re-assembling the Lotus japonicus cpDNA and in the process assemble its mtDNA (380,861 bp). The Pongamia cpDNA contains 77 unique protein-coding genes and is almost 60% gene-dense. It contains a 50 kb inversion common to other legumes, as well as a novel 6.5 kb inversion that is responsible for the non-disruptive, re-orientation of five protein-coding genes. Additionally, two copies of an inverted repeat firmly place the species outside the subclade of the Fabaceae lacking the inverted repeat. The Pongamia and L. japonicus mtDNA contain just 33 and 31 unique protein-coding genes, respectively, and like other angiosperm mtDNA, have expanded intergenic and multiple repeat regions. Through comparative analysis with Vigna radiata we measured the average synonymous and non-synonymous divergence of all three legume mitochondrial (1.59% and 2.40%, respectively) and chloroplast (8.37% and 8.99%, respectively) protein-coding genes. Finally, we explored the relatedness of Pongamia within the Fabaceae and showed the utility of the organellar genome sequences by mapping transcriptomic data to identify up- and down-regulated stress-responsive gene candidates and confirm in silico predicted RNA editing sites. PMID:23272141

Capturing the biofuel wellhead and powerhouse: the chloroplast and mitochondrial genomes of the leguminous feedstock tree Pongamia pinnata.

PubMed

Kazakoff, Stephen H; Imelfort, Michael; Edwards, David; Koehorst, Jasper; Biswas, Bandana; Batley, Jacqueline; Scott, Paul T; Gresshoff, Peter M

2012-01-01

Pongamia pinnata (syn. Millettia pinnata) is a novel, fast-growing arboreal legume that bears prolific quantities of oil-rich seeds suitable for the production of biodiesel and aviation biofuel. Here, we have used Illumina® 'Second Generation DNA Sequencing (2GS)' and a new short-read de novo assembler, SaSSY, to assemble and annotate the Pongamia chloroplast (152,968 bp; cpDNA) and mitochondrial (425,718 bp; mtDNA) genomes. We also show that SaSSY can be used to accurately assemble 2GS data, by re-assembling the Lotus japonicus cpDNA and in the process assemble its mtDNA (380,861 bp). The Pongamia cpDNA contains 77 unique protein-coding genes and is almost 60% gene-dense. It contains a 50 kb inversion common to other legumes, as well as a novel 6.5 kb inversion that is responsible for the non-disruptive, re-orientation of five protein-coding genes. Additionally, two copies of an inverted repeat firmly place the species outside the subclade of the Fabaceae lacking the inverted repeat. The Pongamia and L. japonicus mtDNA contain just 33 and 31 unique protein-coding genes, respectively, and like other angiosperm mtDNA, have expanded intergenic and multiple repeat regions. Through comparative analysis with Vigna radiata we measured the average synonymous and non-synonymous divergence of all three legume mitochondrial (1.59% and 2.40%, respectively) and chloroplast (8.37% and 8.99%, respectively) protein-coding genes. Finally, we explored the relatedness of Pongamia within the Fabaceae and showed the utility of the organellar genome sequences by mapping transcriptomic data to identify up- and down-regulated stress-responsive gene candidates and confirm in silico predicted RNA editing sites.

Characterisation of the genomes of four putative vesiculoviruses: tench rhabdovirus, grass carp rhabdovirus, perch rhabdovirus and eel rhabdovirus European X.

PubMed

Stone, David M; Kerr, Rose C; Hughes, Margaret; Radford, Alan D; Darby, Alistair C

2013-11-01

The complete coding sequences were determined for four putative vesiculoviruses isolated from fish. Sequence alignment and phylogenetic analysis based on the predicted amino acid sequences of the five main proteins assigned tench rhabdovirus and grass carp rhabdovirus together with spring viraemia of carp and pike fry rhabdovirus to a lineage that was distinct from the mammalian vesiculoviruses. Perch rhabdovirus, eel virus European X, lake trout rhabdovirus 903/87 and sea trout virus were placed in a second lineage that was also distinct from the recognised genera in the family Rhabdoviridae. Establishment of two new rhabdovirus genera, "Perhabdovirus" and "Sprivivirus", is discussed.

APADB: a database for alternative polyadenylation and microRNA regulation events

PubMed Central

Müller, Sören; Rycak, Lukas; Afonso-Grunz, Fabian; Winter, Peter; Zawada, Adam M.; Damrath, Ewa; Scheider, Jessica; Schmäh, Juliane; Koch, Ina; Kahl, Günter; Rotter, Björn

2014-01-01

Alternative polyadenylation (APA) is a widespread mechanism that contributes to the sophisticated dynamics of gene regulation. Approximately 50% of all protein-coding human genes harbor multiple polyadenylation (PA) sites; their selective and combinatorial use gives rise to transcript variants with differing length of their 3′ untranslated region (3′UTR). Shortened variants escape UTR-mediated regulation by microRNAs (miRNAs), especially in cancer, where global 3′UTR shortening accelerates disease progression, dedifferentiation and proliferation. Here we present APADB, a database of vertebrate PA sites determined by 3′ end sequencing, using massive analysis of complementary DNA ends. APADB provides (A)PA sites for coding and non-coding transcripts of human, mouse and chicken genes. For human and mouse, several tissue types, including different cancer specimens, are available. APADB records the loss of predicted miRNA binding sites and visualizes next-generation sequencing reads that support each PA site in a genome browser. The database tables can either be browsed according to organism and tissue or alternatively searched for a gene of interest. APADB is the largest database of APA in human, chicken and mouse. The stored information provides experimental evidence for thousands of PA sites and APA events. APADB combines 3′ end sequencing data with prediction algorithms of miRNA binding sites, allowing to further improve prediction algorithms. Current databases lack correct information about 3′UTR lengths, especially for chicken, and APADB provides necessary information to close this gap. Database URL: http://tools.genxpro.net/apadb/ PMID:25052703

ChIP-seq Accurately Predicts Tissue-Specific Activity of Enhancers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Visel, Axel; Blow, Matthew J.; Li, Zirong

2009-02-01

A major yet unresolved quest in decoding the human genome is the identification of the regulatory sequences that control the spatial and temporal expression of genes. Distant-acting transcriptional enhancers are particularly challenging to uncover since they are scattered amongst the vast non-coding portion of the genome. Evolutionary sequence constraint can facilitate the discovery of enhancers, but fails to predict when and where they are active in vivo. Here, we performed chromatin immunoprecipitation with the enhancer-associated protein p300, followed by massively-parallel sequencing, to map several thousand in vivo binding sites of p300 in mouse embryonic forebrain, midbrain, and limb tissue. Wemore » tested 86 of these sequences in a transgenic mouse assay, which in nearly all cases revealed reproducible enhancer activity in those tissues predicted by p300 binding. Our results indicate that in vivo mapping of p300 binding is a highly accurate means for identifying enhancers and their associated activities and suggest that such datasets will be useful to study the role of tissue-specific enhancers in human biology and disease on a genome-wide scale.« less

Gene and translation initiation site prediction in metagenomic sequences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hyatt, Philip Douglas; LoCascio, Philip F; Hauser, Loren John

2012-01-01

Gene prediction in metagenomic sequences remains a difficult problem. Current sequencing technologies do not achieve sufficient coverage to assemble the individual genomes in a typical sample; consequently, sequencing runs produce a large number of short sequences whose exact origin is unknown. Since these sequences are usually smaller than the average length of a gene, algorithms must make predictions based on very little data. We present MetaProdigal, a metagenomic version of the gene prediction program Prodigal, that can identify genes in short, anonymous coding sequences with a high degree of accuracy. The novel value of the method consists of enhanced translationmore » initiation site identification, ability to identify sequences that use alternate genetic codes and confidence values for each gene call. We compare the results of MetaProdigal with other methods and conclude with a discussion of future improvements.« less

Insights from the genome of a high alkaline cellulase producing Aspergillus fumigatus strain obtained from Peruvian Amazon rainforest.

PubMed

Paul, Sujay; Zhang, Angel; Ludeña, Yvette; Villena, Gretty K; Yu, Fengan; Sherman, David H; Gutiérrez-Correa, Marcel

2017-06-10

Here, we report the complete genome sequence of a high alkaline cellulase producing Aspergillus fumigatus strain LMB-35Aa isolated from soil of Peruvian Amazon rainforest. The genome is ∼27.5mb in size, comprises of 228 scaffolds with an average GC content of 50%, and is predicted to contain a total of 8660 protein-coding genes. Of which, 6156 are with known function; it codes for 607 putative CAZymes families potentially involved in carbohydrate metabolism. Several important cellulose degrading genes, such as endoglucanase A, endoglucanase B, endoglucanase D and beta-glucosidase, are also identified. The genome of A. fumigatus strain LMB-35Aa represents the first whole sequenced genome of non-clinical, high cellulase producing A. fumigatus strain isolated from forest soil. Copyright © 2017 Elsevier B.V. All rights reserved.

RBSDesigner: software for designing synthetic ribosome binding sites that yields a desired level of protein expression.

PubMed

Na, Dokyun; Lee, Doheon

2010-10-15

RBSDesigner predicts the translation efficiency of existing mRNA sequences and designs synthetic ribosome binding sites (RBSs) for a given coding sequence (CDS) to yield a desired level of protein expression. The program implements the mathematical model for translation initiation described in Na et al. (Mathematical modeling of translation initiation for the estimation of its efficiency to computationally design mRNA sequences with a desired expression level in prokaryotes. BMC Syst. Biol., 4, 71). The program additionally incorporates the effect on translation efficiency of the spacer length between a Shine-Dalgarno (SD) sequence and an AUG codon, which is crucial for the incorporation of fMet-tRNA into the ribosome. RBSDesigner provides a graphical user interface (GUI) for the convenient design of synthetic RBSs. RBSDesigner is written in Python and Microsoft Visual Basic 6.0 and is publicly available as precompiled stand-alone software on the web (http://rbs.kaist.ac.kr). dhlee@kaist.ac.kr

Nucleotide sequence of the gene for the Mr 32,000 thylakoid membrane protein from Spinacia oleracea and Nicotiana debneyi predicts a totally conserved primary translation product of Mr 38,950

PubMed Central

Zurawski, Gerard; Bohnert, Hans J.; Whitfeld, Paul R.; Bottomley, Warwick

1982-01-01

The gene for the so-called Mr 32,000 rapidly labeled photosystem II thylakoid membrane protein (here designated psbA) of spinach (Spinacia oleracea) chloroplasts is located on the chloroplast DNA in the large single-copy region immediately adjacent to one of the inverted repeat sequences. In this paper we show that the size of the mRNA for this protein is ≈ 1.25 kilobases and that the direction of transcription is towards the inverted repeat unit. The nucleotide sequence of the gene and its flanking regions is presented. The only large open reading frame in the sequence codes for a protein of Mr 38,950. The nucleotide sequence of psbA from Nicotiana debneyi also has been determined, and comparison of the sequences from the two species shows them to be highly conserved (>95% homology) throughout the entire reading frame. Conservation of the amino acid sequence is absolute, there being no changes in a total of 353 residues. This leads us to conclude that the primary translation product of psbA must be a protein of Mr 38,950. The protein is characterized by the complete absence of lysine residues and is relatively rich in hydrophobic amino acids, which tend to be clustered. Transcription of spinach psbA starts about 86 base pairs before the first ATG codon. Immediately upstream from this point there is a sequence typical of that found in E. coli promoters. An almost identical sequence occurs in the equivalent region of N. debneyi DNA. Images PMID:16593262

The complete mitochondrial genome of Hydra vulgaris (Hydroida: Hydridae).

PubMed

Pan, Hong-Chun; Fang, Hong-Yan; Li, Shi-Wei; Liu, Jun-Hong; Wang, Ying; Wang, An-Tai

2014-12-01

The complete mitochondrial genome of Hydra vulgaris (Hydroida: Hydridae) is composed of two linear DNA molecules. The mitochondrial DNA (mtDNA) molecule 1 is 8010 bp long and contains six protein-coding genes, large subunit rRNA, methionine and tryptophan tRNAs, two pseudogenes consisting respectively of a partial copy of COI, and terminal sequences at two ends of the linear mtDNA, while the mtDNA molecule 2 is 7576 bp long and contains seven protein-coding genes, small subunit rRNA, methionine tRNA, a pseudogene consisting of a partial copy of COI and terminal sequences at two ends of the linear mtDNA. COI gene begins with GTG as start codon, whereas other 12 protein-coding genes start with a typical ATG initiation codon. In addition, all protein-coding genes are terminated with TAA as stop codon.

FIST: a sensory domain for diverse signal transduction pathways in prokaryotes and ubiquitin signaling in eukaryotes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Borziak, Kirill; Jouline, Igor B

2007-01-01

Motivation: Sensory domains that are conserved among Bacteria, Archaea and Eucarya are important detectors of common signals detected by living cells. Due to their high sequence divergence, sensory domains are difficult to identify. We systematically look for novel sensory domains using sensitive profile-based searches initi-ated with regions of signal transduction proteins where no known domains can be identified by current domain models. Results: Using profile searches followed by multiple sequence alignment, structure prediction, and domain architecture analysis, we have identified a novel sensory domain termed FIST, which is present in signal transduction proteins from Bacteria, Archaea and Eucarya. Remote similaritymore » to a known ligand-binding fold and chromosomal proximity of FIST-encoding genes to those coding for proteins involved in amino acid metabolism and transport suggest that FIST domains bind small ligands, such as amino acids.« less

The PRC2-binding long non-coding RNAs in human and mouse genomes are associated with predictive sequence features

NASA Astrophysics Data System (ADS)

Tu, Shiqi; Yuan, Guo-Cheng; Shao, Zhen

2017-01-01

Recently, long non-coding RNAs (lncRNAs) have emerged as an important class of molecules involved in many cellular processes. One of their primary functions is to shape epigenetic landscape through interactions with chromatin modifying proteins. However, mechanisms contributing to the specificity of such interactions remain poorly understood. Here we took the human and mouse lncRNAs that were experimentally determined to have physical interactions with Polycomb repressive complex 2 (PRC2), and systematically investigated the sequence features of these lncRNAs by developing a new computational pipeline for sequences composition analysis, in which each sequence is considered as a series of transitions between adjacent nucleotides. Through that, PRC2-binding lncRNAs were found to be associated with a set of distinctive and evolutionarily conserved sequence features, which can be utilized to distinguish them from the others with considerable accuracy. We further identified fragments of PRC2-binding lncRNAs that are enriched with these sequence features, and found they show strong PRC2-binding signals and are more highly conserved across species than the other parts, implying their functional importance.

Comparison of the protein-coding gene content of Chlamydia trachomatis and Protochlamydia amoebophila using a Raspberry Pi computer.

PubMed

Robson, James F; Barker, Daniel

2015-10-13

To demonstrate the bioinformatics capabilities of a low-cost computer, the Raspberry Pi, we present a comparison of the protein-coding gene content of two species in phylum Chlamydiae: Chlamydia trachomatis, a common sexually transmitted infection of humans, and Candidatus Protochlamydia amoebophila, a recently discovered amoebal endosymbiont. Identifying species-specific proteins and differences in protein families could provide insights into the unique phenotypes of the two species. Using a Raspberry Pi computer, sequence similarity-based protein families were predicted across the two species, C. trachomatis and P. amoebophila, and their members counted. Examples include nine multi-protein families unique to C. trachomatis, 132 multi-protein families unique to P. amoebophila and one family with multiple copies in both. Most families unique to C. trachomatis were polymorphic outer-membrane proteins. Additionally, multiple protein families lacking functional annotation were found. Predicted functional interactions suggest one of these families is involved with the exodeoxyribonuclease V complex. The Raspberry Pi computer is adequate for a comparative genomics project of this scope. The protein families unique to P. amoebophila may provide a basis for investigating the host-endosymbiont interaction. However, additional species should be included; and further laboratory research is required to identify the functions of unknown or putative proteins. Multiple outer membrane proteins were found in C. trachomatis, suggesting importance for host evasion. The tyrosine transport protein family is shared between both species, with four proteins in C. trachomatis and two in P. amoebophila. Shared protein families could provide a starting point for discovery of wide-spectrum drugs against Chlamydiae.

@TOME-2: a new pipeline for comparative modeling of protein-ligand complexes.

PubMed

Pons, Jean-Luc; Labesse, Gilles

2009-07-01

@TOME 2.0 is new web pipeline dedicated to protein structure modeling and small ligand docking based on comparative analyses. @TOME 2.0 allows fold recognition, template selection, structural alignment editing, structure comparisons, 3D-model building and evaluation. These tasks are routinely used in sequence analyses for structure prediction. In our pipeline the necessary software is efficiently interconnected in an original manner to accelerate all the processes. Furthermore, we have also connected comparative docking of small ligands that is performed using protein-protein superposition. The input is a simple protein sequence in one-letter code with no comment. The resulting 3D model, protein-ligand complexes and structural alignments can be visualized through dedicated Web interfaces or can be downloaded for further studies. These original features will aid in the functional annotation of proteins and the selection of templates for molecular modeling and virtual screening. Several examples are described to highlight some of the new functionalities provided by this pipeline. The server and its documentation are freely available at http://abcis.cbs.cnrs.fr/AT2/

Conserved thioredoxin fold is present in Pisum sativum L. sieve element occlusion-1 protein

PubMed Central

Umate, Pavan; Tuteja, Renu

2010-01-01

Homology-based three-dimensional model for Pisum sativum sieve element occlusion 1 (Ps.SEO1) (forisomes) protein was constructed. A stretch of amino acids (residues 320 to 456) which is well conserved in all known members of forisomes proteins was used to model the 3D structure of Ps.SEO1. The structural prediction was done using Protein Homology/analogY Recognition Engine (PHYRE) web server. Based on studies of local sequence alignment, the thioredoxin-fold containing protein [Structural Classification of Proteins (SCOP) code d1o73a_], a member of the glutathione peroxidase family was selected as a template for modeling the spatial structure of Ps.SEO1. Selection was based on comparison of primary sequence, higher match quality and alignment accuracy. Motif 1 (EVF) is conserved in Ps.SEO1, Vicia faba (Vf.For1) and Medicago truncatula (MT.SEO3); motif 2 (KKED) is well conserved across all forisomes proteins and motif 3 (IGYIGNP) is conserved in Ps.SEO1 and Vf.For1. PMID:20404566

The genome of flax (Linum usitatissimum) assembled de novo from short shotgun sequence reads.

PubMed

Wang, Zhiwen; Hobson, Neil; Galindo, Leonardo; Zhu, Shilin; Shi, Daihu; McDill, Joshua; Yang, Linfeng; Hawkins, Simon; Neutelings, Godfrey; Datla, Raju; Lambert, Georgina; Galbraith, David W; Grassa, Christopher J; Geraldes, Armando; Cronk, Quentin C; Cullis, Christopher; Dash, Prasanta K; Kumar, Polumetla A; Cloutier, Sylvie; Sharpe, Andrew G; Wong, Gane K-S; Wang, Jun; Deyholos, Michael K

2012-11-01

Flax (Linum usitatissimum) is an ancient crop that is widely cultivated as a source of fiber, oil and medicinally relevant compounds. To accelerate crop improvement, we performed whole-genome shotgun sequencing of the nuclear genome of flax. Seven paired-end libraries ranging in size from 300 bp to 10 kb were sequenced using an Illumina genome analyzer. A de novo assembly, comprised exclusively of deep-coverage (approximately 94× raw, approximately 69× filtered) short-sequence reads (44-100 bp), produced a set of scaffolds with N(50) =694 kb, including contigs with N(50)=20.1 kb. The contig assembly contained 302 Mb of non-redundant sequence representing an estimated 81% genome coverage. Up to 96% of published flax ESTs aligned to the whole-genome shotgun scaffolds. However, comparisons with independently sequenced BACs and fosmids showed some mis-assembly of regions at the genome scale. A total of 43384 protein-coding genes were predicted in the whole-genome shotgun assembly, and up to 93% of published flax ESTs, and 86% of A. thaliana genes aligned to these predicted genes, indicating excellent coverage and accuracy at the gene level. Analysis of the synonymous substitution rates (K(s) ) observed within duplicate gene pairs was consistent with a recent (5-9 MYA) whole-genome duplication in flax. Within the predicted proteome, we observed enrichment of many conserved domains (Pfam-A) that may contribute to the unique properties of this crop, including agglutinin proteins. Together these results show that de novo assembly, based solely on whole-genome shotgun short-sequence reads, is an efficient means of obtaining nearly complete genome sequence information for some plant species. © 2012 The Authors. The Plant Journal © 2012 Blackwell Publishing Ltd.

Consistent prediction of GO protein localization.

PubMed

Spetale, Flavio E; Arce, Debora; Krsticevic, Flavia; Bulacio, Pilar; Tapia, Elizabeth

2018-05-17

The GO-Cellular Component (GO-CC) ontology provides a controlled vocabulary for the consistent description of the subcellular compartments or macromolecular complexes where proteins may act. Current machine learning-based methods used for the automated GO-CC annotation of proteins suffer from the inconsistency of individual GO-CC term predictions. Here, we present FGGA-CC + , a class of hierarchical graph-based classifiers for the consistent GO-CC annotation of protein coding genes at the subcellular compartment or macromolecular complex levels. Aiming to boost the accuracy of GO-CC predictions, we make use of the protein localization knowledge in the GO-Biological Process (GO-BP) annotations to boost the accuracy of GO-CC prediction. As a result, FGGA-CC + classifiers are built from annotation data in both the GO-CC and GO-BP ontologies. Due to their graph-based design, FGGA-CC + classifiers are fully interpretable and their predictions amenable to expert analysis. Promising results on protein annotation data from five model organisms were obtained. Additionally, successful validation results in the annotation of a challenging subset of tandem duplicated genes in the tomato non-model organism were accomplished. Overall, these results suggest that FGGA-CC + classifiers can indeed be useful for satisfying the huge demand of GO-CC annotation arising from ubiquitous high throughout sequencing and proteomic projects.

Crystal Structure of Cocosin, A Potential Food Allergen from Coconut (Cocos nucifera).

PubMed

Jin, Tengchuan; Wang, Cheng; Zhang, Caiying; Wang, Yang; Chen, Yu-Wei; Guo, Feng; Howard, Andrew; Cao, Min-Jie; Fu, Tong-Jen; McHugh, Tara H; Zhang, Yuzhu

2017-08-30

Coconut (Cocos nucifera) is an important palm tree. Coconut fruit is widely consumed. The most abundant storage protein in coconut fruit is cocosin (a likely food allergen), which belongs to the 11S globulin family. Cocosin was crystallized near a century ago, but its structure remains unknown. By optimizing crystallization conditions and cryoprotectant solutions, we were able to obtain cocosin crystals that diffracted to 1.85 Å. The cocosin gene was cloned from genomic DNA isolated from dry coconut tissue. The protein sequence deduced from the predicted cocosin coding sequence was used to guide model building and structure refinement. The structure of cocosin was determined for the first time, and it revealed a typical 11S globulin feature of a double layer doughnut-shaped hexamer.

Structure of Lmaj006129AAA, a hypothetical protein from Leishmania major

DOE Office of Scientific and Technical Information (OSTI.GOV)

Arakaki, Tracy; Le Trong, Isolde; Structural Genomics of Pathogenic Protozoa

2006-03-01

The crystal structure of a conserved hypothetical protein from L. major, Pfam sequence family PF04543, structural genomics target ID Lmaj006129AAA, has been determined at a resolution of 1.6 Å. The gene product of structural genomics target Lmaj006129 from Leishmania major codes for a 164-residue protein of unknown function. When SeMet expression of the full-length gene product failed, several truncation variants were created with the aid of Ginzu, a domain-prediction method. 11 truncations were selected for expression, purification and crystallization based upon secondary-structure elements and disorder. The structure of one of these variants, Lmaj006129AAH, was solved by multiple-wavelength anomalous diffraction (MAD)more » using ELVES, an automatic protein crystal structure-determination system. This model was then successfully used as a molecular-replacement probe for the parent full-length target, Lmaj006129AAA. The final structure of Lmaj006129AAA was refined to an R value of 0.185 (R{sub free} = 0.229) at 1.60 Å resolution. Structure and sequence comparisons based on Lmaj006129AAA suggest that proteins belonging to Pfam sequence families PF04543 and PF01878 may share a common ligand-binding motif.« less

RVMAB: Using the Relevance Vector Machine Model Combined with Average Blocks to Predict the Interactions of Proteins from Protein Sequences.

PubMed

An, Ji-Yong; You, Zhu-Hong; Meng, Fan-Rong; Xu, Shu-Juan; Wang, Yin

2016-05-18

Protein-Protein Interactions (PPIs) play essential roles in most cellular processes. Knowledge of PPIs is becoming increasingly more important, which has prompted the development of technologies that are capable of discovering large-scale PPIs. Although many high-throughput biological technologies have been proposed to detect PPIs, there are unavoidable shortcomings, including cost, time intensity, and inherently high false positive and false negative rates. For the sake of these reasons, in silico methods are attracting much attention due to their good performances in predicting PPIs. In this paper, we propose a novel computational method known as RVM-AB that combines the Relevance Vector Machine (RVM) model and Average Blocks (AB) to predict PPIs from protein sequences. The main improvements are the results of representing protein sequences using the AB feature representation on a Position Specific Scoring Matrix (PSSM), reducing the influence of noise using a Principal Component Analysis (PCA), and using a Relevance Vector Machine (RVM) based classifier. We performed five-fold cross-validation experiments on yeast and Helicobacter pylori datasets, and achieved very high accuracies of 92.98% and 95.58% respectively, which is significantly better than previous works. In addition, we also obtained good prediction accuracies of 88.31%, 89.46%, 91.08%, 91.55%, and 94.81% on other five independent datasets C. elegans, M. musculus, H. sapiens, H. pylori, and E. coli for cross-species prediction. To further evaluate the proposed method, we compare it with the state-of-the-art support vector machine (SVM) classifier on the yeast dataset. The experimental results demonstrate that our RVM-AB method is obviously better than the SVM-based method. The promising experimental results show the efficiency and simplicity of the proposed method, which can be an automatic decision support tool. To facilitate extensive studies for future proteomics research, we developed a freely available web server called RVMAB-PPI in Hypertext Preprocessor (PHP) for predicting PPIs. The web server including source code and the datasets are available at http://219.219.62.123:8888/ppi_ab/.

Recominant Pinoresino-Lariciresinol Reductase, Recombinant Dirigent Protein And Methods Of Use

DOEpatents

Lewis, Norman G.; Davin, Laurence B.; Dinkova-Kostova, Albena T.; Fujita, Masayuki , Gang; David R. , Sarkanen; Simo , Ford; Joshua D.

2003-10-21

Dirigent proteins and pinoresinol/lariciresinol reductases have been isolated, together with cDNAs encoding dirigent proteins and pinoresinol/lariciresinol reductases. Accordingly, isolated DNA sequences are provided from source species Forsythia intermedia, Thuja plicata, Tsuga heterophylla, Eucommia ulmoides, Linum usitatissimum, and Schisandra chinensis, which code for the expression of dirigent proteins and pinoresinol/lariciresinol reductases. In other aspects, replicable recombinant cloning vehicles are provided which code for dirigent proteins or pinoresinol/lariciresinol reductases or for a base sequence sufficiently complementary to at least a portion of dirigent protein or pinoresinol/lariciresinol reductase DNA or RNA to enable hybridization therewith. In yet other aspects, modified host cells are provided that have been transformed, transfected, infected and/or injected with a recombinant cloning vehicle and/or DNA sequence encoding dirigent protein or pinoresinol/lariciresinol reductase. Thus, systems and methods are provided for the recombinant expression of dirigent proteins and/or pinoresinol/lariciresinol reductases.

Genome sequencing and comparative genomics of honey bee microsporidia, Nosema apis reveal novel insights into host-parasite interactions.

PubMed

Chen, Yan ping; Pettis, Jeffery S; Zhao, Yan; Liu, Xinyue; Tallon, Luke J; Sadzewicz, Lisa D; Li, Renhua; Zheng, Huoqing; Huang, Shaokang; Zhang, Xuan; Hamilton, Michele C; Pernal, Stephen F; Melathopoulos, Andony P; Yan, Xianghe; Evans, Jay D

2013-07-05

The microsporidia parasite Nosema contributes to the steep global decline of honey bees that are critical pollinators of food crops. There are two species of Nosema that have been found to infect honey bees, Nosema apis and N. ceranae. Genome sequencing of N. apis and comparative genome analysis with N. ceranae, a fully sequenced microsporidia species, reveal novel insights into host-parasite interactions underlying the parasite infections. We applied the whole-genome shotgun sequencing approach to sequence and assemble the genome of N. apis which has an estimated size of 8.5 Mbp. We predicted 2,771 protein- coding genes and predicted the function of each putative protein using the Gene Ontology. The comparative genomic analysis led to identification of 1,356 orthologs that are conserved between the two Nosema species and genes that are unique characteristics of the individual species, thereby providing a list of virulence factors and new genetic tools for studying host-parasite interactions. We also identified a highly abundant motif in the upstream promoter regions of N. apis genes. This motif is also conserved in N. ceranae and other microsporidia species and likely plays a role in gene regulation across the microsporidia. The availability of the N. apis genome sequence is a significant addition to the rapidly expanding body of microsprodian genomic data which has been improving our understanding of eukaryotic genome diversity and evolution in a broad sense. The predicted virulent genes and transcriptional regulatory elements are potential targets for innovative therapeutics to break down the life cycle of the parasite.

The structure of the human interferon alpha/beta receptor gene.

PubMed

Lutfalla, G; Gardiner, K; Proudhon, D; Vielh, E; Uzé, G

1992-02-05

Using the cDNA coding for the human interferon alpha/beta receptor (IFNAR), the IFNAR gene has been physically mapped relative to the other loci of the chromosome 21q22.1 region. 32,906 base pairs covering the IFNAR gene have been cloned and sequenced. Primer extension and solution hybridization-ribonuclease protection have been used to determine that the transcription of the gene is initiated in a broad region of 20 base pairs. Some aspects of the polymorphism of the gene, including noncoding sequences, have been analyzed; some are allelic differences in the coding sequence that induce amino acid variations in the resulting protein. The exon structure of the IFNAR gene and of that of the available genes for the receptors of the cytokine/growth hormone/prolactin/interferon receptor family have been compared with the predictions for the secondary structure of those receptors. From this analysis, we postulate a common origin and propose an hypothesis for the divergence from the immunoglobulin superfamily.

DNA Multiple Sequence Alignment Guided by Protein Domains: The MSA-PAD 2.0 Method.

PubMed

Balech, Bachir; Monaco, Alfonso; Perniola, Michele; Santamaria, Monica; Donvito, Giacinto; Vicario, Saverio; Maggi, Giorgio; Pesole, Graziano

2018-01-01

Multiple sequence alignment (MSA) is a fundamental component in many DNA sequence analyses including metagenomics studies and phylogeny inference. When guided by protein profiles, DNA multiple alignments assume a higher precision and robustness. Here we present details of the use of the upgraded version of MSA-PAD (2.0), which is a DNA multiple sequence alignment framework able to align DNA sequences coding for single/multiple protein domains guided by PFAM or user-defined annotations. MSA-PAD has two alignment strategies, called "Gene" and "Genome," accounting for coding domains order and genomic rearrangements, respectively. Novel options were added to the present version, where the MSA can be guided by protein profiles provided by the user. This allows MSA-PAD 2.0 to run faster and to add custom protein profiles sometimes not present in PFAM database according to the user's interest. MSA-PAD 2.0 is currently freely available as a Web application at https://recasgateway.cloud.ba.infn.it/ .

Can mutational GC-pressure create new linear B-cell epitopes in herpes simplex virus type 1 glycoprotein B?

PubMed

Khrustalev, Vladislav Victorovich

2009-01-01

We showed that GC-content of nucleotide sequences coding for linear B-cell epitopes of herpes simplex virus type 1 (HSV1) glycoprotein B (gB) is higher than GC-content of sequences coding for epitope-free regions of this glycoprotein (G + C = 73 and 64%, respectively). Linear B-cell epitopes have been predicted in HSV1 gB by BepiPred algorithm ( www.cbs.dtu.dk/services/BepiPred ). Proline is an acrophilic amino acid residue (it is usually situated on the surface of protein globules, and so included in linear B-cell epitopes). Indeed, the level of proline is much higher in predicted epitopes of gB than in epitope-free regions (17.8% versus 1.8%). This amino acid is coded by GC-rich codons (CCX) that can be produced due to nucleotide substitutions caused by mutational GC-pressure. GC-pressure will also lead to disappearance of acrophobic phenylalanine, isoleucine, methionine and tyrosine coded by GC-poor codons. Results of our "in-silico directed mutagenesis" showed that single nonsynonymous substitutions in AT to GC direction in two long epitope-free regions of gB will cause formation of new linear epitopes or elongation of previously existing epitopes flanking these regions in 25% of 539 possible cases. The calculations of GC-content and amino acid content have been performed by CodonChanges algorithm ( www.barkovsky.hotmail.ru ).

A catalog for the transcripts from the venomous structures of the caterpillar Lonomia obliqua: identification of the proteins potentially involved in the coagulation disorder and hemorrhagic syndrome

PubMed Central

Veiga, Ana B. G.; Ribeiro, José M. C.; Guimarães, Jorge A.; Francischetti, Ivo M.B.

2010-01-01

Accidents with the caterpillar Lonomia obliqua are often associated with a coagulation disorder and hemorrhagic syndrome in humans. In the present study, we have constructed cDNA libraries from two venomous structures of the caterpillar, namely the tegument and the bristle. High-throughput sequencing and bioinformatics analyses were performed in parallel. Over one thousand cDNAs were obtained and clustered to produce a database of 538 contigs and singletons (clusters) for the tegument library and 368 for the bristle library. We have thus identified dozens of full-length cDNAs coding for proteins with sequence homology to snake venom prothrombin activator, trypsin-like enzymes, blood coagulation factors and prophenoloxidase cascade activators. We also report cDNA coding for cysteine proteases, Group III phospholipase A2, C-type lectins, lipocalins, in addition to protease inhibitors including serpins, Kazal-type inhibitors, cystatins and trypsin inhibitor-like molecules. Antibacterial proteins and housekeeping genes are also described. A significant number of sequences were devoid of database matches, suggesting that their biologic function remains to be defined. We also report the N-terminus of the most abundant proteins present in the bristle, tegument, hemolymph, and "cryosecretion". Thus, we have created a catalog that contains the predicted molecular weight, isoelectric point, accession number, and putative function for each selected molecule from the venomous structures of L. obliqua. The role of these molecules in the coagulation disorder and hemorrhagic syndrome caused by envenomation with this caterpillar is discussed. All sequence information and the Supplemental Data, including Figures and Tables with hyperlinks to FASTA-formatted files for each contig and the best match to the Databases, are available at http://www.ncbi.nih.gov/projects/omes. PMID:16023793

A deep learning method for lincRNA detection using auto-encoder algorithm.

PubMed

Yu, Ning; Yu, Zeng; Pan, Yi

2017-12-06

RNA sequencing technique (RNA-seq) enables scientists to develop novel data-driven methods for discovering more unidentified lincRNAs. Meantime, knowledge-based technologies are experiencing a potential revolution ignited by the new deep learning methods. By scanning the newly found data set from RNA-seq, scientists have found that: (1) the expression of lincRNAs appears to be regulated, that is, the relevance exists along the DNA sequences; (2) lincRNAs contain some conversed patterns/motifs tethered together by non-conserved regions. The two evidences give the reasoning for adopting knowledge-based deep learning methods in lincRNA detection. Similar to coding region transcription, non-coding regions are split at transcriptional sites. However, regulatory RNAs rather than message RNAs are generated. That is, the transcribed RNAs participate the biological process as regulatory units instead of generating proteins. Identifying these transcriptional regions from non-coding regions is the first step towards lincRNA recognition. The auto-encoder method achieves 100% and 92.4% prediction accuracy on transcription sites over the putative data sets. The experimental results also show the excellent performance of predictive deep neural network on the lincRNA data sets compared with support vector machine and traditional neural network. In addition, it is validated through the newly discovered lincRNA data set and one unreported transcription site is found by feeding the whole annotated sequences through the deep learning machine, which indicates that deep learning method has the extensive ability for lincRNA prediction. The transcriptional sequences of lincRNAs are collected from the annotated human DNA genome data. Subsequently, a two-layer deep neural network is developed for the lincRNA detection, which adopts the auto-encoder algorithm and utilizes different encoding schemes to obtain the best performance over intergenic DNA sequence data. Driven by those newly annotated lincRNA data, deep learning methods based on auto-encoder algorithm can exert their capability in knowledge learning in order to capture the useful features and the information correlation along DNA genome sequences for lincRNA detection. As our knowledge, this is the first application to adopt the deep learning techniques for identifying lincRNA transcription sequences.

1-deoxy-d-xylulose-5-phosphate reductoisomerases and method of use

DOEpatents

Croteau, Rodney B.; Lange, Bernd M.

2001-01-01

The present invention relates to isolated DNA sequences which code for the expression of plant 1-deoxy-D-xylulose-5-phosphate reductoisomerase protein, such as the sequence presented in SEQ ID NO:1 which encodes a 1-deoxy-D-xylulose-5-phosphate reductoisomerase protein from peppermint (Mentha x piperita). Additionally, the present invention relates to isolated plant 1-deoxy-D-xylulose-5-phosphate reductoisomerase protein. In other aspects, the present invention is directed to replicable recombinant cloning vehicles comprising a nucleic acid sequence which codes for a plant 1-deoxy-D-xylulose-5-phosphate reductoisomerase, to modified host cells transformed, transfected, infected and/or injected with a recombinant cloning vehicle and/or DNA sequence of the invention.

1-deoxy-D-xylulose-5-phosphate reductoisomerases, and methods of use

DOEpatents

Croteau, Rodney B.; Lange, Bernd M.

2002-07-16

The present invention relates to isolated DNA sequences which code for the expression of plant 1-deoxy-D-xylulose-5-phosphate reductoisomerase protein, such as the sequence presented in SEQ ID NO:1 which encodes a 1-deoxy-D-xylulose-5-phosphate reductoisomerase protein from peppermint (Mentha x piperita). Additionally, the present invention relates to isolated plant 1-deoxy-D-xylulose-5-phosphate reductoisomerase protein. In other aspects, the present invention is directed to replicable recombinant cloning vehicles comprising a nucleic acid sequence which codes for a plant 1-deoxy-D-xylulose-5-phosphate reductoisomerase, to modified host cells transformed, transfected, infected and/or injected with a recombinant cloning vehicle and/or DNA sequence of the invention.

Genome Sequence of the Bacterium Streptomyces davawensis JCM 4913 and Heterologous Production of the Unique Antibiotic Roseoflavin

PubMed Central

Jankowitsch, Frank; Schwarz, Julia; Rückert, Christian; Gust, Bertolt; Szczepanowski, Rafael; Blom, Jochen; Pelzer, Stefan; Kalinowski, Jörn

2012-01-01

Streptomyces davawensis JCM 4913 synthesizes the antibiotic roseoflavin, a structural riboflavin (vitamin B2) analog. Here, we report the 9,466,619-bp linear chromosome of S. davawensis JCM 4913 and a 89,331-bp linear plasmid. The sequence has an average G+C content of 70.58% and contains six rRNA operons (16S-23S-5S) and 69 tRNA genes. The 8,616 predicted protein-coding sequences include 32 clusters coding for secondary metabolites, several of which are unique to S. davawensis. The chromosome contains long terminal inverted repeats of 33,255 bp each and atypical telomeres. Sequence analysis with regard to riboflavin biosynthesis revealed three different patterns of gene organization in Streptomyces species. Heterologous expression of a set of genes present on a subgenomic fragment of S. davawensis resulted in the production of roseoflavin by the host Streptomyces coelicolor M1152. Phylogenetic analysis revealed that S. davawensis is a close relative of Streptomyces cinnabarinus, and much to our surprise, we found that the latter bacterium is a roseoflavin producer as well. PMID:23043000

Approaches to Fungal Genome Annotation

PubMed Central

Haas, Brian J.; Zeng, Qiandong; Pearson, Matthew D.; Cuomo, Christina A.; Wortman, Jennifer R.

2011-01-01

Fungal genome annotation is the starting point for analysis of genome content. This generally involves the application of diverse methods to identify features on a genome assembly such as protein-coding and non-coding genes, repeats and transposable elements, and pseudogenes. Here we describe tools and methods leveraged for eukaryotic genome annotation with a focus on the annotation of fungal nuclear and mitochondrial genomes. We highlight the application of the latest technologies and tools to improve the quality of predicted gene sets. The Broad Institute eukaryotic genome annotation pipeline is described as one example of how such methods and tools are integrated into a sequencing center’s production genome annotation environment. PMID:22059117

Analysis of Antisense Expression by Whole Genome Tiling Microarrays and siRNAs Suggests Mis-Annotation of Arabidopsis Orphan Protein-Coding Genes

PubMed Central

Richardson, Casey R.; Luo, Qing-Jun; Gontcharova, Viktoria; Jiang, Ying-Wen; Samanta, Manoj; Youn, Eunseog; Rock, Christopher D.

2010-01-01

Background MicroRNAs (miRNAs) and trans-acting small-interfering RNAs (tasi-RNAs) are small (20–22 nt long) RNAs (smRNAs) generated from hairpin secondary structures or antisense transcripts, respectively, that regulate gene expression by Watson-Crick pairing to a target mRNA and altering expression by mechanisms related to RNA interference. The high sequence homology of plant miRNAs to their targets has been the mainstay of miRNA prediction algorithms, which are limited in their predictive power for other kingdoms because miRNA complementarity is less conserved yet transitive processes (production of antisense smRNAs) are active in eukaryotes. We hypothesize that antisense transcription and associated smRNAs are biomarkers which can be computationally modeled for gene discovery. Principal Findings We explored rice (Oryza sativa) sense and antisense gene expression in publicly available whole genome tiling array transcriptome data and sequenced smRNA libraries (as well as C. elegans) and found evidence of transitivity of MIRNA genes similar to that found in Arabidopsis. Statistical analysis of antisense transcript abundances, presence of antisense ESTs, and association with smRNAs suggests several hundred Arabidopsis ‘orphan’ hypothetical genes are non-coding RNAs. Consistent with this hypothesis, we found novel Arabidopsis homologues of some MIRNA genes on the antisense strand of previously annotated protein-coding genes. A Support Vector Machine (SVM) was applied using thermodynamic energy of binding plus novel expression features of sense/antisense transcription topology and siRNA abundances to build a prediction model of miRNA targets. The SVM when trained on targets could predict the “ancient” (deeply conserved) class of validated Arabidopsis MIRNA genes with an accuracy of 84%, and 76% for “new” rapidly-evolving MIRNA genes. Conclusions Antisense and smRNA expression features and computational methods may identify novel MIRNA genes and other non-coding RNAs in plants and potentially other kingdoms, which can provide insight into antisense transcription, miRNA evolution, and post-transcriptional gene regulation. PMID:20520764

Comparative analysis of mitochondrial genomes between a wheat K-type cytoplasmic male sterility (CMS) line and its maintainer line.

PubMed

Liu, Huitao; Cui, Peng; Zhan, Kehui; Lin, Qiang; Zhuo, Guoyin; Guo, Xiaoli; Ding, Feng; Yang, Wenlong; Liu, Dongcheng; Hu, Songnian; Yu, Jun; Zhang, Aimin

2011-03-29

Plant mitochondria, semiautonomous organelles that function as manufacturers of cellular ATP, have their own genome that has a slow rate of evolution and rapid rearrangement. Cytoplasmic male sterility (CMS), a common phenotype in higher plants, is closely associated with rearrangements in mitochondrial DNA (mtDNA), and is widely used to produce F1 hybrid seeds in a variety of valuable crop species. Novel chimeric genes deduced from mtDNA rearrangements causing CMS have been identified in several plants, such as rice, sunflower, pepper, and rapeseed, but there are very few reports about mtDNA rearrangements in wheat. In the present work, we describe the mitochondrial genome of a wheat K-type CMS line and compare it with its maintainer line. The complete mtDNA sequence of a wheat K-type (with cytoplasm of Aegilops kotschyi) CMS line, Ks3, was assembled into a master circle (MC) molecule of 647,559 bp and found to harbor 34 known protein-coding genes, three rRNAs (18 S, 26 S, and 5 S rRNAs), and 16 different tRNAs. Compared to our previously published sequence of a K-type maintainer line, Km3, we detected Ks3-specific mtDNA (> 100 bp, 11.38%) and repeats (> 100 bp, 29 units) as well as genes that are unique to each line: rpl5 was missing in Ks3 and trnH was absent from Km3. We also defined 32 single nucleotide polymorphisms (SNPs) in 13 protein-coding, albeit functionally irrelevant, genes, and predicted 22 unique ORFs in Ks3, representing potential candidates for K-type CMS. All these sequence variations are candidates for involvement in CMS. A comparative analysis of the mtDNA of several angiosperms, including those from Ks3, Km3, rice, maize, Arabidopsis thaliana, and rapeseed, showed that non-coding sequences of higher plants had mostly divergent multiple reorganizations during the mtDNA evolution of higher plants. The complete mitochondrial genome of the wheat K-type CMS line Ks3 is very different from that of its maintainer line Km3, especially in non-coding sequences. Sequence rearrangement has produced novel chimeric ORFs, which may be candidate genes for CMS. Comparative analysis of several angiosperm mtDNAs indicated that non-coding sequences are the most frequently reorganized during mtDNA evolution in higher plants.

Bitis gabonica (Gaboon viper) snake venom gland: toward a catalog for the full- length transcripts (cDNA) and proteins

PubMed Central

Francischetti, Ivo M. B.; My-Pham, Van; Harrison, Jim; Garfield, Mark K.; Ribeiro, José M. C.

2010-01-01

The venom gland of the snake Bitis gabonica (Gaboon viper) was used for the first time to construct a unidirectional cDNA phage library followed by high-throughput sequencing and bioinformatic analysis. Hundreds of cDNAs were obtained and clustered into contigs. We found mostly novel full-length cDNA coding for metalloproteases (P-II and P-III classes), Lys49-phospholipase A2, serine proteases with essential mutations in the active site, Kunitz protease inhibitors, several C-type lectins, bradykinin-potentiating peptide, vascular endothelial growth factor, nucleotidases and nucleases, nerve growth factor, and L-amino acid oxidases. Two new members of the recently described short coding region family of disintegrin, displaying RGD and MLD motifs are reported. In addition, we have identified for the first time a cytokine-like molecule and a multi-Kunitz protease inhibitor in snake venoms. The CLUSTAL alignment and the unrooted cladograms for selected families of B. gabonica venom proteins are also presented. A significant number of sequences were devoid of database matches, suggesting that their biologic function remains to be identified. This paper also reports the N-terminus of the 15 most abundant venom proteins and the sequences matching their corresponding transcripts. The electronic version of this manuscript, available on request, contains spreadsheets with hyperlinks to FASTA-formatted files for each contig and the best match to the GenBank and Conserved Domain Databases, in addition to CLUSTAL alignments of each contig. We have thus generated a comprehensive catalog of the B. gabonica venom gland, containing for each secreted protein: i) the predicted molecular weight, ii) the predicted isoelectric point, iii) the accession number, and iv) the putative function. The role of these molecules is discussed in the context of the envenomation caused by the Gaboon viper. PMID:15276202

Specific and Modular Binding Code for Cytosine Recognition in Pumilio/FBF (PUF) RNA-binding Domains

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dong, Shuyun; Wang, Yang; Cassidy-Amstutz, Caleb

2011-10-28

Pumilio/fem-3 mRNA-binding factor (PUF) proteins possess a recognition code for bases A, U, and G, allowing designed RNA sequence specificity of their modular Pumilio (PUM) repeats. However, recognition side chains in a PUM repeat for cytosine are unknown. Here we report identification of a cytosine-recognition code by screening random amino acid combinations at conserved RNA recognition positions using a yeast three-hybrid system. This C-recognition code is specific and modular as specificity can be transferred to different positions in the RNA recognition sequence. A crystal structure of a modified PUF domain reveals specific contacts between an arginine side chain and themore » cytosine base. We applied the C-recognition code to design PUF domains that recognize targets with multiple cytosines and to generate engineered splicing factors that modulate alternative splicing. Finally, we identified a divergent yeast PUF protein, Nop9p, that may recognize natural target RNAs with cytosine. This work deepens our understanding of natural PUF protein target recognition and expands the ability to engineer PUF domains to recognize any RNA sequence.« less

Posterior Predictive Bayesian Phylogenetic Model Selection

PubMed Central

Lewis, Paul O.; Xie, Wangang; Chen, Ming-Hui; Fan, Yu; Kuo, Lynn

2014-01-01

We present two distinctly different posterior predictive approaches to Bayesian phylogenetic model selection and illustrate these methods using examples from green algal protein-coding cpDNA sequences and flowering plant rDNA sequences. The Gelfand–Ghosh (GG) approach allows dissection of an overall measure of model fit into components due to posterior predictive variance (GGp) and goodness-of-fit (GGg), which distinguishes this method from the posterior predictive P-value approach. The conditional predictive ordinate (CPO) method provides a site-specific measure of model fit useful for exploratory analyses and can be combined over sites yielding the log pseudomarginal likelihood (LPML) which is useful as an overall measure of model fit. CPO provides a useful cross-validation approach that is computationally efficient, requiring only a sample from the posterior distribution (no additional simulation is required). Both GG and CPO add new perspectives to Bayesian phylogenetic model selection based on the predictive abilities of models and complement the perspective provided by the marginal likelihood (including Bayes Factor comparisons) based solely on the fit of competing models to observed data. [Bayesian; conditional predictive ordinate; CPO; L-measure; LPML; model selection; phylogenetics; posterior predictive.] PMID:24193892

Reverse vaccinology as an approach for developing Histophilus somni vaccine candidates.

PubMed

Madampage, Claudia Avis; Rawlyk, Neil; Crockford, Gordon; Wang, Yejun; White, Aaron P; Brownlie, Robert; Van Donkersgoed, Joyce; Dorin, Craig; Potter, Andrew

2015-11-01

Histophilosis of cattle is caused by the Gram negative bacterial pathogen Histophilus somni (H. somni) which is also associated with the bovine respiratory disease (BRD) complex. Existing vaccines for H. somni include either killed cells or bacteria-free outer membrane proteins from the organism which have proven to be moderately successful. In this study, reverse vaccinology was used to predict potential H. somni vaccine candidates from genome sequences. In turn, these may protect animals against new strains circulating in the field. Whole genome sequencing of six recent clinical H. somni isolates was performed using an Illumina MiSeq and compared to six genomes from the 1980's. De novo assembly of crude whole genomes was completed using Geneious 6.1.7. Protein coding regions was predicted using Glimmer3. Scores from multiple web-based programs were utilized to evaluate the antigenicity of these predicted proteins which were finally ranked based on their surface exposure scores. A single new strain was selected for future vaccine development based on conservation of the protein candidates among all 12 isolates. A positive signal with convalescent serum for these antigens in western blots indicates in vivo recognition. In order to test the protective capacity of these antigens bovine animal trials are ongoing. Copyright © 2015 The International Alliance for Biological Standardization. Published by Elsevier Ltd. All rights reserved.

Putative Nonribosomal Peptide Synthetase and Cytochrome P450 Genes Responsible for Tentoxin Biosynthesis in Alternaria alternata ZJ33.

PubMed

Li, You-Hai; Han, Wen-Jin; Gui, Xi-Wu; Wei, Tao; Tang, Shuang-Yan; Jin, Jian-Ming

2016-08-02

Tentoxin, a cyclic tetrapeptide produced by several Alternaria species, inhibits the F₁-ATPase activity of chloroplasts, resulting in chlorosis in sensitive plants. In this study, we report two clustered genes, encoding a putative non-ribosome peptide synthetase (NRPS) TES and a cytochrome P450 protein TES1, that are required for tentoxin biosynthesis in Alternaria alternata strain ZJ33, which was isolated from blighted leaves of Eupatorium adenophorum. Using a pair of primers designed according to the consensus sequences of the adenylation domain of NRPSs, two fragments containing putative adenylation domains were amplified from A. alternata ZJ33, and subsequent PCR analyses demonstrated that these fragments belonged to the same NRPS coding sequence. With no introns, TES consists of a single 15,486 base pair open reading frame encoding a predicted 5161 amino acid protein. Meanwhile, the TES1 gene is predicted to contain five introns and encode a 506 amino acid protein. The TES protein is predicted to be comprised of four peptide synthase modules with two additional N-methylation domains, and the number and arrangement of the modules in TES were consistent with the number and arrangement of the amino acid residues of tentoxin, respectively. Notably, both TES and TES1 null mutants generated via homologous recombination failed to produce tentoxin. This study provides the first evidence concerning the biosynthesis of tentoxin in A. alternata.

pseudoMap: an innovative and comprehensive resource for identification of siRNA-mediated mechanisms in human transcribed pseudogenes.

PubMed

Chan, Wen-Ling; Yang, Wen-Kuang; Huang, Hsien-Da; Chang, Jan-Gowth

2013-01-01

RNA interference (RNAi) is a gene silencing process within living cells, which is controlled by the RNA-induced silencing complex with a sequence-specific manner. In flies and mice, the pseudogene transcripts can be processed into short interfering RNAs (siRNAs) that regulate protein-coding genes through the RNAi pathway. Following these findings, we construct an innovative and comprehensive database to elucidate siRNA-mediated mechanism in human transcribed pseudogenes (TPGs). To investigate TPG producing siRNAs that regulate protein-coding genes, we mapped the TPGs to small RNAs (sRNAs) that were supported by publicly deep sequencing data from various sRNA libraries and constructed the TPG-derived siRNA-target interactions. In addition, we also presented that TPGs can act as a target for miRNAs that actually regulate the parental gene. To enable the systematic compilation and updating of these results and additional information, we have developed a database, pseudoMap, capturing various types of information, including sequence data, TPG and cognate annotation, deep sequencing data, RNA-folding structure, gene expression profiles, miRNA annotation and target prediction. As our knowledge, pseudoMap is the first database to demonstrate two mechanisms of human TPGs: encoding siRNAs and decoying miRNAs that target the parental gene. pseudoMap is freely accessible at http://pseudomap.mbc.nctu.edu.tw/. Database URL: http://pseudomap.mbc.nctu.edu.tw/

High-quality permanent draft genome sequence of the extremely osmotolerant diphenol degrading bacterium Halotalea alkalilenta AW-7T, and emended description of the genus Halotalea

DOE PAGES

Ntougias, Spyridon; Lapidus, Alla; Copeland, Alex; ...

2015-08-13

Members of the genus Halotalea (family Halomonadaceae) are of high significance since they can tolerate the greatest glucose and maltose concentrations ever reported for known bacteria and are involved in the degradation of industrial effluents. Here, the characteristics and the permanent-draft genome sequence and annotation of Halotalea alkalilenta AW-7T are described. The microorganism was sequenced as a part of the Genomic Encyclopedia of Type Strains, Phase I: the one thousand microbial genomes (KMG) project at the DOE Joint Genome Institute, and it is the only strain within the genus Halotalea having its genome sequenced. The genome is 4,467,826 bp longmore » and consists of 40 scaffolds with 64.62 % average GC content. A total of 4,104 genes were predicted, comprising of 4,028 protein-coding and 76 RNA genes. Most protein-coding genes (87.79 %) were assigned to a putative function. Halotalea alkalilenta AW-7T encodes the catechol and protocatechuate degradation to β-ketoadipate via the β-ketoadipate and protocatechuate ortho-cleavage degradation pathway, and it possesses the genetic ability to detoxify fluoroacetate, cyanate and acrylonitrile. Lastly, an emended description of the genus Halotalea Ntougias et al. 2007 is also provided in order to describe the delayed fermentation ability of the type strain.« less

Cloning and sequence analysis of a cDNA clone coding for the mouse GM2 activator protein.

PubMed Central

Bellachioma, G; Stirling, J L; Orlacchio, A; Beccari, T

1993-01-01

A cDNA (1.1 kb) containing the complete coding sequence for the mouse GM2 activator protein was isolated from a mouse macrophage library using a cDNA for the human protein as a probe. There was a single ATG located 12 bp from the 5' end of the cDNA clone followed by an open reading frame of 579 bp. Northern blot analysis of mouse macrophage RNA showed that there was a single band with a mobility corresponding to a size of 2.3 kb. We deduce from this that the mouse mRNA, in common with the mRNA for the human GM2 activator protein, has a long 3' untranslated sequence of approx. 1.7 kb. Alignment of the mouse and human deduced amino acid sequences showed 68% identity overall and 75% identity for the sequence on the C-terminal side of the first 31 residues, which in the human GM2 activator protein contains the signal peptide. Hydropathicity plots showed great similarity between the mouse and human sequences even in regions of low sequence similarity. There is a single N-glycosylation site in the mouse GM2 activator protein sequence (Asn151-Phe-Thr) which differs in its location from the single site reported in the human GM2 activator protein sequence (Asn63-Val-Thr). Images Figure 1 PMID:7689829

DNA-based watermarks using the DNA-Crypt algorithm.

PubMed

Heider, Dominik; Barnekow, Angelika

2007-05-29

The aim of this paper is to demonstrate the application of watermarks based on DNA sequences to identify the unauthorized use of genetically modified organisms (GMOs) protected by patents. Predicted mutations in the genome can be corrected by the DNA-Crypt program leaving the encrypted information intact. Existing DNA cryptographic and steganographic algorithms use synthetic DNA sequences to store binary information however, although these sequences can be used for authentication, they may change the target DNA sequence when introduced into living organisms. The DNA-Crypt algorithm and image steganography are based on the same watermark-hiding principle, namely using the least significant base in case of DNA-Crypt and the least significant bit in case of the image steganography. It can be combined with binary encryption algorithms like AES, RSA or Blowfish. DNA-Crypt is able to correct mutations in the target DNA with several mutation correction codes such as the Hamming-code or the WDH-code. Mutations which can occur infrequently may destroy the encrypted information, however an integrated fuzzy controller decides on a set of heuristics based on three input dimensions, and recommends whether or not to use a correction code. These three input dimensions are the length of the sequence, the individual mutation rate and the stability over time, which is represented by the number of generations. In silico experiments using the Ypt7 in Saccharomyces cerevisiae shows that the DNA watermarks produced by DNA-Crypt do not alter the translation of mRNA into protein. The program is able to store watermarks in living organisms and can maintain the original information by correcting mutations itself. Pairwise or multiple sequence alignments show that DNA-Crypt produces few mismatches between the sequences similar to all steganographic algorithms.

DNA-based watermarks using the DNA-Crypt algorithm

PubMed Central

Heider, Dominik; Barnekow, Angelika

2007-01-01

Background The aim of this paper is to demonstrate the application of watermarks based on DNA sequences to identify the unauthorized use of genetically modified organisms (GMOs) protected by patents. Predicted mutations in the genome can be corrected by the DNA-Crypt program leaving the encrypted information intact. Existing DNA cryptographic and steganographic algorithms use synthetic DNA sequences to store binary information however, although these sequences can be used for authentication, they may change the target DNA sequence when introduced into living organisms. Results The DNA-Crypt algorithm and image steganography are based on the same watermark-hiding principle, namely using the least significant base in case of DNA-Crypt and the least significant bit in case of the image steganography. It can be combined with binary encryption algorithms like AES, RSA or Blowfish. DNA-Crypt is able to correct mutations in the target DNA with several mutation correction codes such as the Hamming-code or the WDH-code. Mutations which can occur infrequently may destroy the encrypted information, however an integrated fuzzy controller decides on a set of heuristics based on three input dimensions, and recommends whether or not to use a correction code. These three input dimensions are the length of the sequence, the individual mutation rate and the stability over time, which is represented by the number of generations. In silico experiments using the Ypt7 in Saccharomyces cerevisiae shows that the DNA watermarks produced by DNA-Crypt do not alter the translation of mRNA into protein. Conclusion The program is able to store watermarks in living organisms and can maintain the original information by correcting mutations itself. Pairwise or multiple sequence alignments show that DNA-Crypt produces few mismatches between the sequences similar to all steganographic algorithms. PMID:17535434

Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines

PubMed Central

2010-01-01

Background Protein-protein interaction (PPI) plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods have motivated the development of computational methods for predicting PPIs. As protein interactions generally occur via domains instead of the whole molecules, predicting domain-domain interaction (DDI) is an important step toward PPI prediction. Computational methods developed so far have utilized information from various sources at different levels, from primary sequences, to molecular structures, to evolutionary profiles. Results In this paper, we propose a computational method to predict DDI using support vector machines (SVMs), based on domains represented as interaction profile hidden Markov models (ipHMM) where interacting residues in domains are explicitly modeled according to the three dimensional structural information available at the Protein Data Bank (PDB). Features about the domains are extracted first as the Fisher scores derived from the ipHMM and then selected using singular value decomposition (SVD). Domain pairs are represented by concatenating their selected feature vectors, and classified by a support vector machine trained on these feature vectors. The method is tested by leave-one-out cross validation experiments with a set of interacting protein pairs adopted from the 3DID database. The prediction accuracy has shown significant improvement as compared to InterPreTS (Interaction Prediction through Tertiary Structure), an existing method for PPI prediction that also uses the sequences and complexes of known 3D structure. Conclusions We show that domain-domain interaction prediction can be significantly enhanced by exploiting information inherent in the domain profiles via feature selection based on Fisher scores, singular value decomposition and supervised learning based on support vector machines. Datasets and source code are freely available on the web at http://liao.cis.udel.edu/pub/svdsvm. Implemented in Matlab and supported on Linux and MS Windows. PMID:21034480

Comparative genome analysis of entomopathogenic fungi reveals a complex set of secreted proteins.

PubMed

Staats, Charley Christian; Junges, Angela; Guedes, Rafael Lucas Muniz; Thompson, Claudia Elizabeth; de Morais, Guilherme Loss; Boldo, Juliano Tomazzoni; de Almeida, Luiz Gonzaga Paula; Andreis, Fábio Carrer; Gerber, Alexandra Lehmkuhl; Sbaraini, Nicolau; da Paixão, Rana Louise de Andrade; Broetto, Leonardo; Landell, Melissa; Santi, Lucélia; Beys-da-Silva, Walter Orlando; Silveira, Carolina Pereira; Serrano, Thaiane Rispoli; de Oliveira, Eder Silva; Kmetzsch, Lívia; Vainstein, Marilene Henning; de Vasconcelos, Ana Tereza Ribeiro; Schrank, Augusto

2014-09-29

Metarhizium anisopliae is an entomopathogenic fungus used in the biological control of some agricultural insect pests, and efforts are underway to use this fungus in the control of insect-borne human diseases. A large repertoire of proteins must be secreted by M. anisopliae to cope with the various available nutrients as this fungus switches through different lifestyles, i.e., from a saprophytic, to an infectious, to a plant endophytic stage. To further evaluate the predicted secretome of M. anisopliae, we employed genomic and transcriptomic analyses, coupled with phylogenomic analysis, focusing on the identification and characterization of secreted proteins. We determined the M. anisopliae E6 genome sequence and compared this sequence to other entomopathogenic fungi genomes. A robust pipeline was generated to evaluate the predicted secretomes of M. anisopliae and 15 other filamentous fungi, leading to the identification of a core of secreted proteins. Transcriptomic analysis using the tick Rhipicephalus microplus cuticle as an infection model during two periods of infection (48 and 144 h) allowed the identification of several differentially expressed genes. This analysis concluded that a large proportion of the predicted secretome coding genes contained altered transcript levels in the conditions analyzed in this study. In addition, some specific secreted proteins from Metarhizium have an evolutionary history similar to orthologs found in Beauveria/Cordyceps. This similarity suggests that a set of secreted proteins has evolved to participate in entomopathogenicity. The data presented represents an important step to the characterization of the role of secreted proteins in the virulence and pathogenicity of M. anisopliae.

Discrete Ramanujan transform for distinguishing the protein coding regions from other regions.

PubMed

Hua, Wei; Wang, Jiasong; Zhao, Jian

2014-01-01

Based on the study of Ramanujan sum and Ramanujan coefficient, this paper suggests the concepts of discrete Ramanujan transform and spectrum. Using Voss numerical representation, one maps a symbolic DNA strand as a numerical DNA sequence, and deduces the discrete Ramanujan spectrum of the numerical DNA sequence. It is well known that of discrete Fourier power spectrum of protein coding sequence has an important feature of 3-base periodicity, which is widely used for DNA sequence analysis by the technique of discrete Fourier transform. It is performed by testing the signal-to-noise ratio at frequency N/3 as a criterion for the analysis, where N is the length of the sequence. The results presented in this paper show that the property of 3-base periodicity can be only identified as a prominent spike of the discrete Ramanujan spectrum at period 3 for the protein coding regions. The signal-to-noise ratio for discrete Ramanujan spectrum is defined for numerical measurement. Therefore, the discrete Ramanujan spectrum and the signal-to-noise ratio of a DNA sequence can be used for distinguishing the protein coding regions from the noncoding regions. All the exon and intron sequences in whole chromosomes 1, 2, 3 and 4 of Caenorhabditis elegans have been tested and the histograms and tables from the computational results illustrate the reliability of our method. In addition, we have analyzed theoretically and gotten the conclusion that the algorithm for calculating discrete Ramanujan spectrum owns the lower computational complexity and higher computational accuracy. The computational experiments show that the technique by using discrete Ramanujan spectrum for classifying different DNA sequences is a fast and effective method. Copyright © 2014 Elsevier Ltd. All rights reserved.

Identifying the missing proteins in human proteome by biological language model.

PubMed

Dong, Qiwen; Wang, Kai; Liu, Xuan

2016-12-23

With the rapid development of high-throughput sequencing technology, the proteomics research becomes a trendy field in the post genomics era. It is necessary to identify all the native-encoding protein sequences for further function and pathway analysis. Toward that end, the Human Proteome Organization lunched the Human Protein Project in 2011. However many proteins are hard to be detected by experiment methods, which becomes one of the bottleneck in Human Proteome Project. In consideration of the complicatedness of detecting these missing proteins by using wet-experiment approach, here we use bioinformatics method to pre-filter the missing proteins. Since there are analogy between the biological sequences and natural language, the n-gram models from Natural Language Processing field has been used to filter the missing proteins. The dataset used in this study contains 616 missing proteins from the "uncertain" category of the neXtProt database. There are 102 proteins deduced by the n-gram model, which have high probability to be native human proteins. We perform a detail analysis on the predicted structure and function of these missing proteins and also compare the high probability proteins with other mass spectrum datasets. The evaluation shows that the results reported here are in good agreement with those obtained by other well-established databases. The analysis shows that 102 proteins may be native gene-coding proteins and some of the missing proteins are membrane or natively disordered proteins which are hard to be detected by experiment methods.

Apophysomyces variabilis: draft genome sequence and comparison of predictive virulence determinants with other medically important Mucorales.

PubMed

Prakash, Hariprasath; Rudramurthy, Shivaprakash Mandya; Gandham, Prasad S; Ghosh, Anup Kumar; Kumar, Milner M; Badapanda, Chandan; Chakrabarti, Arunaloke

2017-09-18

Apophysomyces species are prevalent in tropical countries and A. variabilis is the second most frequent agent causing mucormycosis in India. Among Apophysomyces species, A. elegans, A. trapeziformis and A. variabilis are commonly incriminated in human infections. The genome sequences of A. elegans and A. trapeziformis are available in public database, but not A. variabilis. We, therefore, performed the whole genome sequence of A. variabilis to explore its genomic structure and possible genes determining the virulence of the organism. The whole genome of A. variabilis NCCPF 102052 was sequenced and the genomic structure of A. variabilis was compared with already available genome structures of A. elegans, A. trapeziformis and other medically important Mucorales. The total size of genome assembly of A. variabilis was 39.38 Mb with 12,764 protein-coding genes. The transposable elements (TEs) were low in Apophysomyces genome and the retrotransposon Ty3-gypsy was the common TE. Phylogenetically, Apophysomyces species were grouped closely with Phycomyces blakesleeanus. OrthoMCL analysis revealed 3025 orthologues proteins, which were common in those three pathogenic Apophysomyces species. Expansion of multiple gene families/duplication was observed in Apophysomyces genomes. Approximately 6% of Apophysomyces genes were predicted to be associated with virulence on PHIbase analysis. The virulence determinants included the protein families of CotH proteins (invasins), proteases, iron utilisation pathways, siderophores and signal transduction pathways. Serine proteases were the major group of proteases found in all Apophysomyces genomes. The carbohydrate active enzymes (CAZymes) constitute the majority of the secretory proteins. The present study is the maiden attempt to sequence and analyze the genomic structure of A. variabilis. Together with available genome sequence of A. elegans and A. trapeziformis, the study helped to indicate the possible virulence determinants of pathogenic Apophysomyces species. The presence of unique CAZymes in cell wall might be exploited in future for antifungal drug development.

Beta carbonic anhydrases: novel targets for pesticides and anti-parasitic agents in agriculture and livestock husbandry.

PubMed

Zolfaghari Emameh, Reza; Barker, Harlan; Hytönen, Vesa P; Tolvanen, Martti E E; Parkkila, Seppo

2014-08-29

The genomes of many insect and parasite species contain beta carbonic anhydrase (β-CA) protein coding sequences. The lack of β-CA proteins in mammals makes them interesting target proteins for inhibition in treatment of some infectious diseases and pests. Many insects and parasites represent important pests for agriculture and cause enormous economic damage worldwide. Meanwhile, pollution of the environment by old pesticides, emergence of strains resistant to them, and their off-target effects are major challenges for agriculture and society. In this study, we analyzed a multiple sequence alignment of 31 β-CAs from insects, some parasites, and selected plant species relevant to agriculture and livestock husbandry. Using bioinformatics tools a phylogenetic tree was generated and the subcellular localizations and antigenic sites of each protein were predicted. Structural models for β-CAs of Ancylostoma caninum, Ascaris suum, Trichinella spiralis, and Entamoeba histolytica, were built using Pisum sativum and Mycobacterium tuberculosis β-CAs as templates. Six β-CAs of insects and parasites and six β-CAs of plants are predicted to be mitochondrial and chloroplastic, respectively, and thus may be involved in important metabolic functions. All 31 sequences showed the presence of the highly conserved β-CA active site sequence motifs, CXDXR and HXXC (C: cysteine, D: aspartic acid, R: arginine, H: histidine, X: any residue). We discovered that these two motifs are more antigenic than others. Homology models suggested that these motifs are mostly buried and thus not well accessible for recognition by antibodies. The predicted mitochondrial localization of several β-CAs and hidden antigenic epitopes within the protein molecule, suggest that they may not be considered major targets for vaccines. Instead, they are promising candidate enzymes for small-molecule inhibitors which can easily penetrate the cell membrane. Based on current knowledge, we conclude that β-CAs are potential targets for development of small molecule pesticides or anti-parasitic agents with minimal side effects on vertebrates.

The Coding of Biological Information: From Nucleotide Sequence to Protein Recognition

NASA Astrophysics Data System (ADS)

Štambuk, Nikola

The paper reviews the classic results of Swanson, Dayhoff, Grantham, Blalock and Root-Bernstein, which link genetic code nucleotide patterns to the protein structure, evolution and molecular recognition. Symbolic representation of the binary addresses defining particular nucleotide and amino acid properties is discussed, with consideration of: structure and metric of the code, direct correspondence between amino acid and nucleotide information, and molecular recognition of the interacting protein motifs coded by the complementary DNA and RNA strands.

Drosophila Nora virus capsid proteins differ from those of other picorna-like viruses.

PubMed

Ekström, Jens-Ola; Habayeb, Mazen S; Srivastava, Vaibhav; Kieselbach, Thomas; Wingsle, Gunnar; Hultmark, Dan

2011-09-01

The recently discovered Nora virus from Drosophila melanogaster is a single-stranded RNA virus. Its published genomic sequence encodes a typical picorna-like cassette of replicative enzymes, but no capsid proteins similar to those in other picorna-like viruses. We have now done additional sequencing at the termini of the viral genome, extending it by 455 nucleotides at the 5' end, but no more coding sequence was found. The completeness of the final 12,333-nucleotide sequence was verified by the production of infectious virus from the cloned genome. To identify the capsid proteins, we purified Nora virus particles and analyzed their proteins by mass spectrometry. Our results show that the capsid is built from three major proteins, VP4A, B and C, encoded in the fourth open reading frame of the viral genome. The viral particles also contain traces of a protein from the third open reading frame, VP3. VP4A and B are not closely related to other picorna-like virus capsid proteins in sequence, but may form similar jelly roll folds. VP4C differs from the others and is predicted to have an essentially α-helical conformation. In a related virus, identified from EST database sequences from Nasonia parasitoid wasps, VP4C is encoded in a separate open reading frame, separated from VP4A and B by a frame-shift. This opens a possibility that VP4C is produced in non-equimolar quantities. Altogether, our results suggest that the Nora virus capsid has a different protein organization compared to the order Picornavirales. Copyright © 2011 Elsevier B.V. All rights reserved.

Predicting protein-binding RNA nucleotides with consideration of binding partners.

PubMed

Tuvshinjargal, Narankhuu; Lee, Wook; Park, Byungkyu; Han, Kyungsook

2015-06-01

In recent years several computational methods have been developed to predict RNA-binding sites in protein. Most of these methods do not consider interacting partners of a protein, so they predict the same RNA-binding sites for a given protein sequence even if the protein binds to different RNAs. Unlike the problem of predicting RNA-binding sites in protein, the problem of predicting protein-binding sites in RNA has received little attention mainly because it is much more difficult and shows a lower accuracy on average. In our previous study, we developed a method that predicts protein-binding nucleotides from an RNA sequence. In an effort to improve the prediction accuracy and usefulness of the previous method, we developed a new method that uses both RNA and protein sequence data. In this study, we identified effective features of RNA and protein molecules and developed a new support vector machine (SVM) model to predict protein-binding nucleotides from RNA and protein sequence data. The new model that used both protein and RNA sequence data achieved a sensitivity of 86.5%, a specificity of 86.2%, a positive predictive value (PPV) of 72.6%, a negative predictive value (NPV) of 93.8% and Matthews correlation coefficient (MCC) of 0.69 in a 10-fold cross validation; it achieved a sensitivity of 58.8%, a specificity of 87.4%, a PPV of 65.1%, a NPV of 84.2% and MCC of 0.48 in independent testing. For comparative purpose, we built another prediction model that used RNA sequence data alone and ran it on the same dataset. In a 10 fold-cross validation it achieved a sensitivity of 85.7%, a specificity of 80.5%, a PPV of 67.7%, a NPV of 92.2% and MCC of 0.63; in independent testing it achieved a sensitivity of 67.7%, a specificity of 78.8%, a PPV of 57.6%, a NPV of 85.2% and MCC of 0.45. In both cross-validations and independent testing, the new model that used both RNA and protein sequences showed a better performance than the model that used RNA sequence data alone in most performance measures. To the best of our knowledge, this is the first sequence-based prediction of protein-binding nucleotides in RNA which considers the binding partner of RNA. The new model will provide valuable information for designing biochemical experiments to find putative protein-binding sites in RNA with unknown structure. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

ComplexContact: a web server for inter-protein contact prediction using deep learning.

PubMed

Zeng, Hong; Wang, Sheng; Zhou, Tianming; Zhao, Feifeng; Li, Xiufeng; Wu, Qing; Xu, Jinbo

2018-05-22

ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.

Mitochondrial genomes of the jungle crow Corvus macrorhynchos (Passeriformes: Corvidae) from shed feathers and a phylogenetic analysis of genus Corvus using mitochondrial protein-coding genes.

PubMed

Krzeminska, Urszula; Wilson, Robyn; Rahman, Sadequr; Song, Beng Kah; Seneviratne, Sampath; Gan, Han Ming; Austin, Christopher M

2016-07-01

The complete mitochondrial genomes of two jungle crows (Corvus macrorhynchos) were sequenced. DNA was extracted from tissue samples obtained from shed feathers collected in the field in Sri Lanka and sequenced using the Illumina MiSeq Personal Sequencer. Jungle crow mitogenomes have a structural organization typical of the genus Corvus and are 16,927 bp and 17,066 bp in length, both comprising 13 protein-coding genes, 22 transfer RNA genes, 2 ribosomal subunit genes, and a non-coding control region. In addition, we complement already available house crow (Corvus spelendens) mitogenome resources by sequencing an individual from Singapore. A phylogenetic tree constructed from Corvidae family mitogenome sequences available on GenBank is presented. We confirm the monophyly of the genus Corvus and propose to use complete mitogenome resources for further intra- and interspecies genetic studies.

Amino- and carboxyl-terminal amino acid sequences of proteins coded by gag gene of murine leukemia virus

PubMed Central

Oroszlan, Stephen; Henderson, Louis E.; Stephenson, John R.; Copeland, Terry D.; Long, Cedric W.; Ihle, James N.; Gilden, Raymond V.

1978-01-01

The amino- and carboxyl-terminal amino acid sequences of proteins (p10, p12, p15, and p30) coded by the gag gene of Rauscher and AKR murine leukemia viruses were determined. Among these proteins, p15 from both viruses appears to have a blocked amino end. Proline was found to be the common NH2 terminus of both p30s and both p12s, and alanine of both p10s. The amino-terminal sequences of p30s are identical, as are those of p10s, while the p12 sequences are clearly distinctive but also show substantial homology. The carboxyl-terminal amino acids of both viral p30s and p12s are leucine and phenylalanine, respectively. Rauscher leukemia virus p15 has tyrosine as the carboxyl terminus while AKR virus p15 has phenylalanine in this position. The compositional and sequence data provide definite chemical criteria for the identification of analogous gag gene products and for the comparison of viral proteins isolated in different laboratories. On the basis of amino acid sequences and the previously proposed H-p15-p12-p30-p10-COOH peptide sequence in the precursor polyprotein, a model for cleavage sites involved in the post-translational processing of the precursor coded for by the gag gene is proposed. PMID:206897

MHC class I-associated peptides derive from selective regions of the human genome.

PubMed

Pearson, Hillary; Daouda, Tariq; Granados, Diana Paola; Durette, Chantal; Bonneil, Eric; Courcelles, Mathieu; Rodenbrock, Anja; Laverdure, Jean-Philippe; Côté, Caroline; Mader, Sylvie; Lemieux, Sébastien; Thibault, Pierre; Perreault, Claude

2016-12-01

MHC class I-associated peptides (MAPs) define the immune self for CD8+ T lymphocytes and are key targets of cancer immunosurveillance. Here, the goals of our work were to determine whether the entire set of protein-coding genes could generate MAPs and whether specific features influence the ability of discrete genes to generate MAPs. Using proteogenomics, we have identified 25,270 MAPs isolated from the B lymphocytes of 18 individuals who collectively expressed 27 high-frequency HLA-A,B allotypes. The entire MAP repertoire presented by these 27 allotypes covered only 10% of the exomic sequences expressed in B lymphocytes. Indeed, 41% of expressed protein-coding genes generated no MAPs, while 59% of genes generated up to 64 MAPs, often derived from adjacent regions and presented by different allotypes. We next identified several features of transcripts and proteins associated with efficient MAP production. From these data, we built a logistic regression model that predicts with good accuracy whether a gene generates MAPs. Our results show preferential selection of MAPs from a limited repertoire of proteins with distinctive features. The notion that the MHC class I immunopeptidome presents only a small fraction of the protein-coding genome for monitoring by the immune system has profound implications in autoimmunity and cancer immunology.

MHC class I–associated peptides derive from selective regions of the human genome

PubMed Central

Pearson, Hillary; Granados, Diana Paola; Durette, Chantal; Bonneil, Eric; Courcelles, Mathieu; Rodenbrock, Anja; Laverdure, Jean-Philippe; Côté, Caroline; Thibault, Pierre

2016-01-01

MHC class I–associated peptides (MAPs) define the immune self for CD8+ T lymphocytes and are key targets of cancer immunosurveillance. Here, the goals of our work were to determine whether the entire set of protein-coding genes could generate MAPs and whether specific features influence the ability of discrete genes to generate MAPs. Using proteogenomics, we have identified 25,270 MAPs isolated from the B lymphocytes of 18 individuals who collectively expressed 27 high-frequency HLA-A,B allotypes. The entire MAP repertoire presented by these 27 allotypes covered only 10% of the exomic sequences expressed in B lymphocytes. Indeed, 41% of expressed protein-coding genes generated no MAPs, while 59% of genes generated up to 64 MAPs, often derived from adjacent regions and presented by different allotypes. We next identified several features of transcripts and proteins associated with efficient MAP production. From these data, we built a logistic regression model that predicts with good accuracy whether a gene generates MAPs. Our results show preferential selection of MAPs from a limited repertoire of proteins with distinctive features. The notion that the MHC class I immunopeptidome presents only a small fraction of the protein-coding genome for monitoring by the immune system has profound implications in autoimmunity and cancer immunology. PMID:27841757

Characterization of the complete mitochondrial genome of Marshallagia marshalli and phylogenetic implications for the superfamily Trichostrongyloidea.

PubMed

Sun, Miao-Miao; Han, Liang; Zhang, Fu-Kai; Zhou, Dong-Hui; Wang, Shu-Qing; Ma, Jun; Zhu, Xing-Quan; Liu, Guo-Hua

2018-01-01

Marshallagia marshalli (Nematoda: Trichostrongylidae) infection can lead to serious parasitic gastroenteritis in sheep, goat, and wild ruminant, causing significant socioeconomic losses worldwide. Up to now, the study concerning the molecular biology of M. marshalli is limited. Herein, we sequenced the complete mitochondrial (mt) genome of M. marshalli and examined its phylogenetic relationship with selected members of the superfamily Trichostrongyloidea using Bayesian inference (BI) based on concatenated mt amino acid sequence datasets. The complete mt genome sequence of M. marshalli is 13,891 bp, including 12 protein-coding genes, 22 transfer RNA genes, and 2 ribosomal RNA genes. All protein-coding genes are transcribed in the same direction. Phylogenetic analyses based on concatenated amino acid sequences of the 12 protein-coding genes supported the monophylies of the families Haemonchidae, Molineidae, and Dictyocaulidae with strong statistical support, but rejected the monophyly of the family Trichostrongylidae. The determination of the complete mt genome sequence of M. marshalli provides novel genetic markers for studying the systematics, population genetics, and molecular epidemiology of M. marshalli and its congeners.

The mitochondrial genome of the multicolored Asian lady beetle Harmonia axyridis (Pallas) and a phylogenetic analysis of the Polyphaga (Insecta: Coleoptera).

PubMed

Niu, Fang-Fang; Zhu, Liang; Wang, Su; Wei, Shu-Jun

2016-07-01

Here, we report the mitochondrial genome sequence of the multicolored Asian lady beetle Harmonia axyridis (Pallas, 1773) (Coleoptera: Coccinellidae) (GenBank accession No. KR108208). This is the first species with sequenced mitochondrial genome from the genus Harmonia. The current length with partitial A + T-rich region of this mitochondrial genome is 16,387 bp. All the typical genes were sequenced except the trnI and trnQ. As in most other sequenced mitochondrial genomes of Coleoptera, there is no re-arrangement in the sequenced region compared with the pupative ancestral arrangement of insects. All protein-coding genes start with ATN codons. Five, five and three protein-coding genes stop with termination codon TAA, TA and T, respectively. Phylogenetic analysis using Bayesian method based on the first and second codon positions of the protein-coding genes supported that the Scirtidae is a basal lineage of Polyphaga. The Harmonia and the Coccinella form a sister lineage. The monophyly of Staphyliniformia, Scarabaeiformia and Cucujiformia was supported. The Buprestidae was found to be a sister group to the Bostrichiformia.

The genome sequence of the plant pathogen Xylella fastidiosa. The Xylella fastidiosa Consortium of the Organization for Nucleotide Sequencing and Analysis.

PubMed

Simpson, A J; Reinach, F C; Arruda, P; Abreu, F A; Acencio, M; Alvarenga, R; Alves, L M; Araya, J E; Baia, G S; Baptista, C S; Barros, M H; Bonaccorsi, E D; Bordin, S; Bové, J M; Briones, M R; Bueno, M R; Camargo, A A; Camargo, L E; Carraro, D M; Carrer, H; Colauto, N B; Colombo, C; Costa, F F; Costa, M C; Costa-Neto, C M; Coutinho, L L; Cristofani, M; Dias-Neto, E; Docena, C; El-Dorry, H; Facincani, A P; Ferreira, A J; Ferreira, V C; Ferro, J A; Fraga, J S; França, S C; Franco, M C; Frohme, M; Furlan, L R; Garnier, M; Goldman, G H; Goldman, M H; Gomes, S L; Gruber, A; Ho, P L; Hoheisel, J D; Junqueira, M L; Kemper, E L; Kitajima, J P; Krieger, J E; Kuramae, E E; Laigret, F; Lambais, M R; Leite, L C; Lemos, E G; Lemos, M V; Lopes, S A; Lopes, C R; Machado, J A; Machado, M A; Madeira, A M; Madeira, H M; Marino, C L; Marques, M V; Martins, E A; Martins, E M; Matsukuma, A Y; Menck, C F; Miracca, E C; Miyaki, C Y; Monteriro-Vitorello, C B; Moon, D H; Nagai, M A; Nascimento, A L; Netto, L E; Nhani, A; Nobrega, F G; Nunes, L R; Oliveira, M A; de Oliveira, M C; de Oliveira, R C; Palmieri, D A; Paris, A; Peixoto, B R; Pereira, G A; Pereira, H A; Pesquero, J B; Quaggio, R B; Roberto, P G; Rodrigues, V; de M Rosa, A J; de Rosa, V E; de Sá, R G; Santelli, R V; Sawasaki, H E; da Silva, A C; da Silva, A M; da Silva, F R; da Silva, W A; da Silveira, J F; Silvestri, M L; Siqueira, W J; de Souza, A A; de Souza, A P; Terenzi, M F; Truffi, D; Tsai, S M; Tsuhako, M H; Vallada, H; Van Sluys, M A; Verjovski-Almeida, S; Vettore, A L; Zago, M A; Zatz, M; Meidanis, J; Setubal, J C

2000-07-13

Xylella fastidiosa is a fastidious, xylem-limited bacterium that causes a range of economically important plant diseases. Here we report the complete genome sequence of X. fastidiosa clone 9a5c, which causes citrus variegated chlorosis--a serious disease of orange trees. The genome comprises a 52.7% GC-rich 2,679,305-base-pair (bp) circular chromosome and two plasmids of 51,158 bp and 1,285 bp. We can assign putative functions to 47% of the 2,904 predicted coding regions. Efficient metabolic functions are predicted, with sugars as the principal energy and carbon source, supporting existence in the nutrient-poor xylem sap. The mechanisms associated with pathogenicity and virulence involve toxins, antibiotics and ion sequestration systems, as well as bacterium-bacterium and bacterium-host interactions mediated by a range of proteins. Orthologues of some of these proteins have only been identified in animal and human pathogens; their presence in X. fastidiosa indicates that the molecular basis for bacterial pathogenicity is both conserved and independent of host. At least 83 genes are bacteriophage-derived and include virulence-associated genes from other bacteria, providing direct evidence of phage-mediated horizontal gene transfer.

Transcriptome Analysis of the Chrysanthemum Foliar Nematode, Aphelenchoides ritzemabosi (Aphelenchida: Aphelenchoididae)

PubMed Central

Li, Jun-Yi; Xie, Hui; Xu, Chun-Ling; Li, Yu

2016-01-01

The chrysanthemum foliar nematode (CFN), Aphelenchoides ritzemabosi, is a plant parasitic nematode that attacks many plants. In this study, a transcriptomes of mixed-stage population of CFN was sequenced on the Illumina HiSeq 2000 platform. 68.10 million Illumina high quality paired end reads were obtained which generated 26,817 transcripts with a mean length of 1,032 bp and an N50 of 1,672 bp, of which 16,467 transcripts were annotated against six databases. In total, 20,311 coding region sequences (CDS), 495 simple sequence repeats (SSRs) and 8,353 single-nucleotide polymorphisms (SNPs) were predicted, respectively. The CFN with the most shared sequences was B. xylophilus with 16,846 (62.82%) common transcripts and 10,543 (39.31%) CFN transcripts matched sequences of all of four plant parasitic nematodes compared. A total of 111 CFN transcripts were predicted as homologues of 7 types of carbohydrate-active enzymes (CAZymes) with plant/fungal cell wall-degrading activities, fewer transcripts were predicted as homologues of plant cell wall-degrading enzymes than fungal cell wall-degrading enzymes. The phylogenetic analysis of GH5, GH16, GH43 and GH45 proteins between CFN and other organisms showed CFN and other nematodes have a closer phylogenetic relationship. In the CFN transcriptome, sixteen types of genes orthologues with seven classes of protein families involved in the RNAi pathway in C. elegans were predicted. This research provides comprehensive gene expression information at the transcriptional level, which will facilitate the elucidation of the molecular mechanisms of CFN and the distribution of gene functions at the macro level, potentially revealing improved methods for controlling CFN. PMID:27875578

FRAGSION: ultra-fast protein fragment library generation by IOHMM sampling.

PubMed

Bhattacharya, Debswapna; Adhikari, Badri; Li, Jilong; Cheng, Jianlin

2016-07-01

Speed, accuracy and robustness of building protein fragment library have important implications in de novo protein structure prediction since fragment-based methods are one of the most successful approaches in template-free modeling (FM). Majority of the existing fragment detection methods rely on database-driven search strategies to identify candidate fragments, which are inherently time-consuming and often hinder the possibility to locate longer fragments due to the limited sizes of databases. Also, it is difficult to alleviate the effect of noisy sequence-based predicted features such as secondary structures on the quality of fragment. Here, we present FRAGSION, a database-free method to efficiently generate protein fragment library by sampling from an Input-Output Hidden Markov Model. FRAGSION offers some unique features compared to existing approaches in that it (i) is lightning-fast, consuming only few seconds of CPU time to generate fragment library for a protein of typical length (300 residues); (ii) can generate dynamic-size fragments of any length (even for the whole protein sequence) and (iii) offers ways to handle noise in predicted secondary structure during fragment sampling. On a FM dataset from the most recent Critical Assessment of Structure Prediction, we demonstrate that FGRAGSION provides advantages over the state-of-the-art fragment picking protocol of ROSETTA suite by speeding up computation by several orders of magnitude while achieving comparable performance in fragment quality. Source code and executable versions of FRAGSION for Linux and MacOS is freely available to non-commercial users at http://sysbio.rnet.missouri.edu/FRAGSION/ It is bundled with a manual and example data. chengji@missouri.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Implication of common and disease specific variants in CLU, CR1, and PICALM.

PubMed

Ferrari, Raffaele; Moreno, Jorge H; Minhajuddin, Abu T; O'Bryant, Sid E; Reisch, Joan S; Barber, Robert C; Momeni, Parastoo

2012-08-01

Two recent genome-wide association studies (GWAS) for late onset Alzheimer's disease (LOAD) revealed 3 new genes: clusterin (CLU), phosphatidylinositol binding clathrin assembly protein (PICALM), and complement receptor 1 (CR1). In order to evaluate association with these genome-wide association study-identified genes and to isolate the variants contributing to the pathogenesis of LOAD, we genotyped the top single nucleotide polymorphisms (SNPs), rs11136000 (CLU), rs3818361 (CR1), and rs3851179 (PICALM), and sequenced the entire coding regions of these genes in our cohort of 342 LOAD patients and 277 control subjects. We confirmed the association of rs3851179 (PICALM) (p = 7.4 × 10(-3)) with the disease status. Through sequencing we identified 18 variants in CLU, 3 of which were found exclusively in patients; 8 variants (out of 65) in CR1 gene were only found in patients and the 16 variants identified in PICALM gene were present in both patients and controls. In silico analysis of the variants in PICALM did not predict any damaging effect on the protein. The haplotype analysis of the variants in each gene predicted a common haplotype when the 3 single nucleotide polymorphisms rs11136000 (CLU), rs3818361 (CR1), and rs3851179 (PICALM), respectively, were included. For each gene the haplotype structure and size differed between patients and controls. In conclusion, we confirmed association of CLU, CR1, and PICALM genes with the disease status in our cohort through identification of a number of disease-specific variants among patients through the sequencing of the coding region of these genes. Published by Elsevier Inc.

Integrative structural annotation of de novo RNA-Seq provides an accurate reference gene set of the enormous genome of the onion (Allium cepa L.)

PubMed Central

Kim, Seungill; Kim, Myung-Shin; Kim, Yong-Min; Yeom, Seon-In; Cheong, Kyeongchae; Kim, Ki-Tae; Jeon, Jongbum; Kim, Sunggil; Kim, Do-Sun; Sohn, Seong-Han; Lee, Yong-Hwan; Choi, Doil

2015-01-01

The onion (Allium cepa L.) is one of the most widely cultivated and consumed vegetable crops in the world. Although a considerable amount of onion transcriptome data has been deposited into public databases, the sequences of the protein-coding genes are not accurate enough to be used, owing to non-coding sequences intermixed with the coding sequences. We generated a high-quality, annotated onion transcriptome from de novo sequence assembly and intensive structural annotation using the integrated structural gene annotation pipeline (ISGAP), which identified 54,165 protein-coding genes among 165,179 assembled transcripts totalling 203.0 Mb by eliminating the intron sequences. ISGAP performed reliable annotation, recognizing accurate gene structures based on reference proteins, and ab initio gene models of the assembled transcripts. Integrative functional annotation and gene-based SNP analysis revealed a whole biological repertoire of genes and transcriptomic variation in the onion. The method developed in this study provides a powerful tool for the construction of reference gene sets for organisms based solely on de novo transcriptome data. Furthermore, the reference genes and their variation described here for the onion represent essential tools for molecular breeding and gene cloning in Allium spp. PMID:25362073

Large-scale analysis of full-length cDNAs from the tomato (Solanum lycopersicum) cultivar Micro-Tom, a reference system for the Solanaceae genomics.

PubMed

Aoki, Koh; Yano, Kentaro; Suzuki, Ayako; Kawamura, Shingo; Sakurai, Nozomu; Suda, Kunihiro; Kurabayashi, Atsushi; Suzuki, Tatsuya; Tsugane, Taneaki; Watanabe, Manabu; Ooga, Kazuhide; Torii, Maiko; Narita, Takanori; Shin-I, Tadasu; Kohara, Yuji; Yamamoto, Naoki; Takahashi, Hideki; Watanabe, Yuichiro; Egusa, Mayumi; Kodama, Motoichiro; Ichinose, Yuki; Kikuchi, Mari; Fukushima, Sumire; Okabe, Akiko; Arie, Tsutomu; Sato, Yuko; Yazawa, Katsumi; Satoh, Shinobu; Omura, Toshikazu; Ezura, Hiroshi; Shibata, Daisuke

2010-03-30

The Solanaceae family includes several economically important vegetable crops. The tomato (Solanum lycopersicum) is regarded as a model plant of the Solanaceae family. Recently, a number of tomato resources have been developed in parallel with the ongoing tomato genome sequencing project. In particular, a miniature cultivar, Micro-Tom, is regarded as a model system in tomato genomics, and a number of genomics resources in the Micro-Tom-background, such as ESTs and mutagenized lines, have been established by an international alliance. To accelerate the progress in tomato genomics, we developed a collection of fully-sequenced 13,227 Micro-Tom full-length cDNAs. By checking redundant sequences, coding sequences, and chimeric sequences, a set of 11,502 non-redundant full-length cDNAs (nrFLcDNAs) was generated. Analysis of untranslated regions demonstrated that tomato has longer 5'- and 3'-untranslated regions than most other plants but rice. Classification of functions of proteins predicted from the coding sequences demonstrated that nrFLcDNAs covered a broad range of functions. A comparison of nrFLcDNAs with genes of sixteen plants facilitated the identification of tomato genes that are not found in other plants, most of which did not have known protein domains. Mapping of the nrFLcDNAs onto currently available tomato genome sequences facilitated prediction of exon-intron structure. Introns of tomato genes were longer than those of Arabidopsis and rice. According to a comparison of exon sequences between the nrFLcDNAs and the tomato genome sequences, the frequency of nucleotide mismatch in exons between Micro-Tom and the genome-sequencing cultivar (Heinz 1706) was estimated to be 0.061%. The collection of Micro-Tom nrFLcDNAs generated in this study will serve as a valuable genomic tool for plant biologists to bridge the gap between basic and applied studies. The nrFLcDNA sequences will help annotation of the tomato whole-genome sequence and aid in tomato functional genomics and molecular breeding. Full-length cDNA sequences and their annotations are provided in the database KaFTom http://www.pgb.kazusa.or.jp/kaftom/ via the website of the National Bioresource Project Tomato http://tomato.nbrp.jp.

Incorporating information on predicted solvent accessibility to the co-evolution-based study of protein interactions.

PubMed

Ochoa, David; García-Gutiérrez, Ponciano; Juan, David; Valencia, Alfonso; Pazos, Florencio

2013-01-27

A widespread family of methods for studying and predicting protein interactions using sequence information is based on co-evolution, quantified as similarity of phylogenetic trees. Part of the co-evolution observed between interacting proteins could be due to co-adaptation caused by inter-protein contacts. In this case, the co-evolution is expected to be more evident when evaluated on the surface of the proteins or the internal layers close to it. In this work we study the effect of incorporating information on predicted solvent accessibility to three methods for predicting protein interactions based on similarity of phylogenetic trees. We evaluate the performance of these methods in predicting different types of protein associations when trees based on positions with different characteristics of predicted accessibility are used as input. We found that predicted accessibility improves the results of two recent versions of the mirrortree methodology in predicting direct binary physical interactions, while it neither improves these methods, nor the original mirrortree method, in predicting other types of interactions. That improvement comes at no cost in terms of applicability since accessibility can be predicted for any sequence. We also found that predictions of protein-protein interactions are improved when multiple sequence alignments with a richer representation of sequences (including paralogs) are incorporated in the accessibility prediction.

Rapid evolution of cis-regulatory sequences via local point mutations

NASA Technical Reports Server (NTRS)

Stone, J. R.; Wray, G. A.

2001-01-01

Although the evolution of protein-coding sequences within genomes is well understood, the same cannot be said of the cis-regulatory regions that control transcription. Yet, changes in gene expression are likely to constitute an important component of phenotypic evolution. We simulated the evolution of new transcription factor binding sites via local point mutations. The results indicate that new binding sites appear and become fixed within populations on microevolutionary timescales under an assumption of neutral evolution. Even combinations of two new binding sites evolve very quickly. We predict that local point mutations continually generate considerable genetic variation that is capable of altering gene expression.

Molecular cloning and sequence analysis of the gene coding for the 57kDa soluble antigen of the salmonid fish pathogen Renibacterium salmoninarum

USGS Publications Warehouse

Chien, Maw-Sheng; Gilbert , Teresa L.; Huang, Chienjin; Landolt, Marsha L.; O'Hara, Patrick J.; Winton, James R.

1992-01-01

The complete sequence coding for the 57-kDa major soluble antigen of the salmonid fish pathogen, Renibacterium salmoninarum, was determined. The gene contained an opening reading frame of 1671 nucleotides coding for a protein of 557 amino acids with a calculated Mr value of 57190. The first 26 amino acids constituted a signal peptide. The deduced sequence for amino acid residues 27–61 was in agreement with the 35 N-terminal amino acid residues determined by microsequencing, suggesting the protein in synthesized as a 557-amino acid precursor and processed to produce a mature protein of Mr 54505. Two regions of the protein contained imperfect direct repeats. The first region contained two copies of an 81-residue repeat, the second contained five copies of an unrelated 25-residue repeat. Also, a perfect inverted repeat (including three in-frame UAA stop codons) was observed at the carboxyl-terminus of the gene.

Sequencing and comparative genomic analysis of 1227 Felis catus cDNA sequences enriched for developmental, clinical and nutritional phenotypes

PubMed Central

2012-01-01

Background The feline genome is valuable to the veterinary and model organism genomics communities because the cat is an obligate carnivore and a model for endangered felids. The initial public release of the Felis catus genome assembly provided a framework for investigating the genomic basis of feline biology. However, the entire set of protein coding genes has not been elucidated. Results We identified and characterized 1227 protein coding feline sequences, of which 913 map to public sequences and 314 are novel. These sequences have been deposited into NCBI's genbank database and complement public genomic resources by providing additional protein coding sequences that fill in some of the gaps in the feline genome assembly. Through functional and comparative genomic analyses, we gained an understanding of the role of these sequences in feline development, nutrition and health. Specifically, we identified 104 orthologs of human genes associated with Mendelian disorders. We detected negative selection within sequences with gene ontology annotations associated with intracellular trafficking, cytoskeleton and muscle functions. We detected relatively less negative selection on protein sequences encoding extracellular networks, apoptotic pathways and mitochondrial gene ontology annotations. Additionally, we characterized feline cDNA sequences that have mouse orthologs associated with clinical, nutritional and developmental phenotypes. Together, this analysis provides an overview of the value of our cDNA sequences and enhances our understanding of how the feline genome is similar to, and different from other mammalian genomes. Conclusions The cDNA sequences reported here expand existing feline genomic resources by providing high-quality sequences annotated with comparative genomic information providing functional, clinical, nutritional and orthologous gene information. PMID:22257742

SeqRate: sequence-based protein folding type classification and rates prediction

PubMed Central

2010-01-01

Background Protein folding rate is an important property of a protein. Predicting protein folding rate is useful for understanding protein folding process and guiding protein design. Most previous methods of predicting protein folding rate require the tertiary structure of a protein as an input. And most methods do not distinguish the different kinetic nature (two-state folding or multi-state folding) of the proteins. Here we developed a method, SeqRate, to predict both protein folding kinetic type (two-state versus multi-state) and real-value folding rate using sequence length, amino acid composition, contact order, contact number, and secondary structure information predicted from only protein sequence with support vector machines. Results We systematically studied the contributions of individual features to folding rate prediction. On a standard benchmark dataset, the accuracy of folding kinetic type classification is 80%. The Pearson correlation coefficient and the mean absolute difference between predicted and experimental folding rates (sec-1) in the base-10 logarithmic scale are 0.81 and 0.79 for two-state protein folders, and 0.80 and 0.68 for three-state protein folders. SeqRate is the first sequence-based method for protein folding type classification and its accuracy of fold rate prediction is improved over previous sequence-based methods. Its performance can be further enhanced with additional information, such as structure-based geometric contacts, as inputs. Conclusions Both the web server and software of predicting folding rate are publicly available at http://casp.rnet.missouri.edu/fold_rate/index.html. PMID:20438647

SCPRED: accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences.

PubMed

Kurgan, Lukasz; Cios, Krzysztof; Chen, Ke

2008-05-01

Protein structure prediction methods provide accurate results when a homologous protein is predicted, while poorer predictions are obtained in the absence of homologous templates. However, some protein chains that share twilight-zone pairwise identity can form similar folds and thus determining structural similarity without the sequence similarity would be desirable for the structure prediction. The folding type of a protein or its domain is defined as the structural class. Current structural class prediction methods that predict the four structural classes defined in SCOP provide up to 63% accuracy for the datasets in which sequence identity of any pair of sequences belongs to the twilight-zone. We propose SCPRED method that improves prediction accuracy for sequences that share twilight-zone pairwise similarity with sequences used for the prediction. SCPRED uses a support vector machine classifier that takes several custom-designed features as its input to predict the structural classes. Based on extensive design that considers over 2300 index-, composition- and physicochemical properties-based features along with features based on the predicted secondary structure and content, the classifier's input includes 8 features based on information extracted from the secondary structure predicted with PSI-PRED and one feature computed from the sequence. Tests performed with datasets of 1673 protein chains, in which any pair of sequences shares twilight-zone similarity, show that SCPRED obtains 80.3% accuracy when predicting the four SCOP-defined structural classes, which is superior when compared with over a dozen recent competing methods that are based on support vector machine, logistic regression, and ensemble of classifiers predictors. The SCPRED can accurately find similar structures for sequences that share low identity with sequence used for the prediction. The high predictive accuracy achieved by SCPRED is attributed to the design of the features, which are capable of separating the structural classes in spite of their low dimensionality. We also demonstrate that the SCPRED's predictions can be successfully used as a post-processing filter to improve performance of modern fold classification methods.

SCPRED: Accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences

PubMed Central

Kurgan, Lukasz; Cios, Krzysztof; Chen, Ke

2008-01-01

Background Protein structure prediction methods provide accurate results when a homologous protein is predicted, while poorer predictions are obtained in the absence of homologous templates. However, some protein chains that share twilight-zone pairwise identity can form similar folds and thus determining structural similarity without the sequence similarity would be desirable for the structure prediction. The folding type of a protein or its domain is defined as the structural class. Current structural class prediction methods that predict the four structural classes defined in SCOP provide up to 63% accuracy for the datasets in which sequence identity of any pair of sequences belongs to the twilight-zone. We propose SCPRED method that improves prediction accuracy for sequences that share twilight-zone pairwise similarity with sequences used for the prediction. Results SCPRED uses a support vector machine classifier that takes several custom-designed features as its input to predict the structural classes. Based on extensive design that considers over 2300 index-, composition- and physicochemical properties-based features along with features based on the predicted secondary structure and content, the classifier's input includes 8 features based on information extracted from the secondary structure predicted with PSI-PRED and one feature computed from the sequence. Tests performed with datasets of 1673 protein chains, in which any pair of sequences shares twilight-zone similarity, show that SCPRED obtains 80.3% accuracy when predicting the four SCOP-defined structural classes, which is superior when compared with over a dozen recent competing methods that are based on support vector machine, logistic regression, and ensemble of classifiers predictors. Conclusion The SCPRED can accurately find similar structures for sequences that share low identity with sequence used for the prediction. The high predictive accuracy achieved by SCPRED is attributed to the design of the features, which are capable of separating the structural classes in spite of their low dimensionality. We also demonstrate that the SCPRED's predictions can be successfully used as a post-processing filter to improve performance of modern fold classification methods. PMID:18452616

Molecular cloning and evolutionary analysis of the calcium-modulated contractile protein, centrin, in green algae and land plants.

PubMed

Bhattacharya, D; Steinkötter, J; Melkonian, M

1993-12-01

Centrin (= caltractin) is a ubiquitous, cytoskeletal protein which is a member of the EF-hand superfamily of calcium-binding proteins. A centrin-coding cDNA was isolated and characterized from the prasinophyte green alga Scherffelia dubia. Centrin PCR amplification primers were used to isolate partial, homologous cDNA sequences from the green algae Tetraselmis striata and Spermatozopsis similis. Annealing analyses suggested that centrin is a single-copy-coding region in T. striata and S. similis and other green algae studied. Centrin-coding regions from S. dubia, S. similis and T. striata encode four colinear EF-hand domains which putatively bind calcium. Phylogenetic analyses, including homologous sequences from Chlamydomonas reinhardtii and the land plant Atriplex nummularia, demonstrate that the domains of centrins are congruent and arose from the two-fold duplication of an ancestral EF hand with Domains 1+3 and Domains 2+4 clustering. The domains of centrins are also congruent with those of calmodulins demonstrating that, like calmodulin, centrin is an ancient protein which arose within the ancestor of all eukaryotes via gene duplication. Phylogenetic relationships inferred from centrin-coding region comparisons mirror results of small subunit ribosomal RNA sequence analyses suggesting that centrin-coding regions are useful evolutionary markers within the green algae.

Phylogenetic and Structural Analysis of the Pluripotency Factor Sex-Determining Region Y box2 Gene of Camelus dromedarius (cSox2).

PubMed

Alawad, Abdullah; Alharbi, Sultan; Alhazzaa, Othman; Alagrafi, Faisal; Alkhrayef, Mohammed; Alhamdan, Ziyad; Alenazi, Abdullah; Al-Johi, Hasan; Alanazi, Ibrahim O; Hammad, Mohamed

2016-01-01

Although the sequencing information of Sox2 cDNA for many mammalian is available, the Sox2 cDNA of Camelus dromedaries has not yet been characterized. The objective of this study was to sequence and characterize Sox2 cDNA from the brain of C. dromedarius (also known as Arabian camel). A full coding sequence of the Sox2 gene from the brain of C. dromedarius was amplified by reverse transcription PCRjmc and then sequenced using the 3730XL series platform Sequencer (Applied Biosystem) for the first time. The cDNA sequence displayed an open reading frame of 822 nucleotides, encoding a protein of 273 amino acids. The molecular weight and the isoelectric point of the translated protein were calculated as 29.825 kDa and 10.11, respectively, using bioinformatics analysis. The predicted cSox2 protein sequence exhibited high identity: 99% for Homo sapiens, Mus musculus, Bos taurus, and Vicugna pacos; 98% for Sus scrofa and 93% for Camelus ferus. A 3D structure was built based on the available crystal structure of the HMG-box domain of human stem cell transcription factor Sox2 (PDB: 2 LE4) with 81 residues and predicting bioinformatics software for 273 amino acid residues. The comparison confirms the presence of the HMG-box domain in the cSox2 protein. The orthologous phylogenetic analysis showed that the Sox2 isoform from C. dromedarius was grouped with humans, alpacas, cattle, and pigs. We believe that this genetic and structural information will be a helpful source for the annotation. Furthermore, Sox2 is one of the transcription factors that contributes to the generation-induced pluripotent stem cells (iPSCs), which in turn will probably help generate camel induced pluripotent stem cells (CiPSCs).

Whole Genome Sequences of Three Treponema pallidum ssp. pertenue Strains: Yaws and Syphilis Treponemes Differ in Less than 0.2% of the Genome Sequence

PubMed Central

Chen, Lei; Pospíšilová, Petra; Strouhal, Michal; Qin, Xiang; Mikalová, Lenka; Norris, Steven J.; Muzny, Donna M.; Gibbs, Richard A.; Fulton, Lucinda L.; Sodergren, Erica; Weinstock, George M.; Šmajs, David

2012-01-01

Background The yaws treponemes, Treponema pallidum ssp. pertenue (TPE) strains, are closely related to syphilis causing strains of Treponema pallidum ssp. pallidum (TPA). Both yaws and syphilis are distinguished on the basis of epidemiological characteristics, clinical symptoms, and several genetic signatures of the corresponding causative agents. Methodology/Principal Findings To precisely define genetic differences between TPA and TPE, high-quality whole genome sequences of three TPE strains (Samoa D, CDC-2, Gauthier) were determined using next-generation sequencing techniques. TPE genome sequences were compared to four genomes of TPA strains (Nichols, DAL-1, SS14, Chicago). The genome structure was identical in all three TPE strains with similar length ranging between 1,139,330 bp and 1,139,744 bp. No major genome rearrangements were found when compared to the four TPA genomes. The whole genome nucleotide divergence (dA) between TPA and TPE subspecies was 4.7 and 4.8 times higher than the observed nucleotide diversity (π) among TPA and TPE strains, respectively, corresponding to 99.8% identity between TPA and TPE genomes. A set of 97 (9.9%) TPE genes encoded proteins containing two or more amino acid replacements or other major sequence changes. The TPE divergent genes were mostly from the group encoding potential virulence factors and genes encoding proteins with unknown function. Conclusions/Significance Hypothetical genes, with genetic differences, consistently found between TPE and TPA strains are candidates for syphilitic treponemes virulence factors. Seventeen TPE genes were predicted under positive selection, and eleven of them coded either for predicted exported proteins or membrane proteins suggesting their possible association with the cell surface. Sequence changes between TPE and TPA strains and changes specific to individual strains represent suitable targets for subspecies- and strain-specific molecular diagnostics. PMID:22292095

Prediction of Protein Structural Classes for Low-Similarity Sequences Based on Consensus Sequence and Segmented PSSM.

PubMed

Liang, Yunyun; Liu, Sanyang; Zhang, Shengli

2015-01-01

Prediction of protein structural classes for low-similarity sequences is useful for understanding fold patterns, regulation, functions, and interactions of proteins. It is well known that feature extraction is significant to prediction of protein structural class and it mainly uses protein primary sequence, predicted secondary structure sequence, and position-specific scoring matrix (PSSM). Currently, prediction solely based on the PSSM has played a key role in improving the prediction accuracy. In this paper, we propose a novel method called CSP-SegPseP-SegACP by fusing consensus sequence (CS), segmented PsePSSM, and segmented autocovariance transformation (ACT) based on PSSM. Three widely used low-similarity datasets (1189, 25PDB, and 640) are adopted in this paper. Then a 700-dimensional (700D) feature vector is constructed and the dimension is decreased to 224D by using principal component analysis (PCA). To verify the performance of our method, rigorous jackknife cross-validation tests are performed on 1189, 25PDB, and 640 datasets. Comparison of our results with the existing PSSM-based methods demonstrates that our method achieves the favorable and competitive performance. This will offer an important complementary to other PSSM-based methods for prediction of protein structural classes for low-similarity sequences.

General overview on structure prediction of twilight-zone proteins.

PubMed

Khor, Bee Yin; Tye, Gee Jun; Lim, Theam Soon; Choong, Yee Siew

2015-09-04

Protein structure prediction from amino acid sequence has been one of the most challenging aspects in computational structural biology despite significant progress in recent years showed by critical assessment of protein structure prediction (CASP) experiments. When experimentally determined structures are unavailable, the predictive structures may serve as starting points to study a protein. If the target protein consists of homologous region, high-resolution (typically <1.5 Å) model can be built via comparative modelling. However, when confronted with low sequence similarity of the target protein (also known as twilight-zone protein, sequence identity with available templates is less than 30%), the protein structure prediction has to be initiated from scratch. Traditionally, twilight-zone proteins can be predicted via threading or ab initio method. Based on the current trend, combination of different methods brings an improved success in the prediction of twilight-zone proteins. In this mini review, the methods, progresses and challenges for the prediction of twilight-zone proteins were discussed.

The complete mitochondrial genome and phylogenetic analysis of the giant panda (Ailuropoda melanoleuca).

PubMed

Peng, Rui; Zeng, Bo; Meng, Xiuxiang; Yue, Bisong; Zhang, Zhihe; Zou, Fangdong

2007-08-01

The complete mitochondrial genome sequence of the giant panda, Ailuropoda melanoleuca, was determined by the long and accurate polymerase chain reaction (LA-PCR) with conserved primers and primer walking sequence methods. The complete mitochondrial DNA is 16,805 nucleotides in length and contains two ribosomal RNA genes, 13 protein-coding genes, 22 transfer RNA genes and one control region. The total length of the 13 protein-coding genes is longer than the American black bear, brown bear and polar bear by 3 amino acids at the end of ND5 gene. The codon usage also followed the typical vertebrate pattern except for an unusual ATT start codon, which initiates the NADH dehydrogenase subunit 5 (ND5) gene. The molecular phylogenetic analysis was performed on the sequences of 12 concatenated heavy-strand encoded protein-coding genes, and suggested that the giant panda is most closely related to bears.

Prediction of cis/trans isomerization in proteins using PSI-BLAST profiles and secondary structure information.

PubMed

Song, Jiangning; Burrage, Kevin; Yuan, Zheng; Huber, Thomas

2006-03-09

The majority of peptide bonds in proteins are found to occur in the trans conformation. However, for proline residues, a considerable fraction of Prolyl peptide bonds adopt the cis form. Proline cis/trans isomerization is known to play a critical role in protein folding, splicing, cell signaling and transmembrane active transport. Accurate prediction of proline cis/trans isomerization in proteins would have many important applications towards the understanding of protein structure and function. In this paper, we propose a new approach to predict the proline cis/trans isomerization in proteins using support vector machine (SVM). The preliminary results indicated that using Radial Basis Function (RBF) kernels could lead to better prediction performance than that of polynomial and linear kernel functions. We used single sequence information of different local window sizes, amino acid compositions of different local sequences, multiple sequence alignment obtained from PSI-BLAST and the secondary structure information predicted by PSIPRED. We explored these different sequence encoding schemes in order to investigate their effects on the prediction performance. The training and testing of this approach was performed on a newly enlarged dataset of 2424 non-homologous proteins determined by X-Ray diffraction method using 5-fold cross-validation. Selecting the window size 11 provided the best performance for determining the proline cis/trans isomerization based on the single amino acid sequence. It was found that using multiple sequence alignments in the form of PSI-BLAST profiles could significantly improve the prediction performance, the prediction accuracy increased from 62.8% with single sequence to 69.8% and Matthews Correlation Coefficient (MCC) improved from 0.26 with single local sequence to 0.40. Furthermore, if coupled with the predicted secondary structure information by PSIPRED, our method yielded a prediction accuracy of 71.5% and MCC of 0.43, 9% and 0.17 higher than the accuracy achieved based on the singe sequence information, respectively. A new method has been developed to predict the proline cis/trans isomerization in proteins based on support vector machine, which used the single amino acid sequence with different local window sizes, the amino acid compositions of local sequence flanking centered proline residues, the position-specific scoring matrices (PSSMs) extracted by PSI-BLAST and the predicted secondary structures generated by PSIPRED. The successful application of SVM approach in this study reinforced that SVM is a powerful tool in predicting proline cis/trans isomerization in proteins and biological sequence analysis.

Ovine mitochondrial DNA sequence variation and its association with production and reproduction traits within an Afec-Assaf flock.

PubMed

Reicher, S; Seroussi, E; Weller, J I; Rosov, A; Gootwine, E

2012-07-01

Polymorphisms in mitochondrial DNA (mtDNA) protein- and tRNA-coding genes were shown to be associated with various diseases in humans as well as with production and reproduction traits in livestock. Alignment of full length mitochondria sequences from the 5 known ovine haplogroups: HA (n = 3), HB (n = 5), HC (n = 3), HD (n = 2), and HE (n = 2; GenBank accession nos. HE577847-50 and 11 published complete ovine mitochondria sequences) revealed sequence variation in 10 out of the 13 protein coding mtDNA sequences. Twenty-six of the 245 variable sites found in the protein coding sequences represent non-synonymous mutations. Sequence variation was observed also in 8 out of the 22 tRNA mtDNA sequences. On the basis of the mtDNA control region and cytochrome b partial sequences along with information on maternal lineages within an Afec-Assaf flock, 1,126 Afec-Assaf ewes were assigned to mitochondrial haplogroups HA, HB, and HC, with frequencies of 0.43, 0.43, and 0.14, respectively. Analysis of birth weight and growth rate records of lamb (n = 1286) and productivity from 4,993 lambing records revealed no association between mitochondrial haplogroup affiliation and female longevity, lambs perinatal survival rate, birth weight, and daily growth rate of lambs up to 150 d that averaged 1,664 d, 88.3%, 4.5 kg, and 320 g/d, respectively. However, significant (P < 0.0001) differences among the haplogroups were found for prolificacy of ewes, with prolificacies (mean ± SE) of 2.14 ± 0.04, 2.25 ± 0.04, and 2.30 ± 0.06 lamb born/ewe lambing for the HA, HB, and the HC haplogroups, respectively. Our results highlight the ovine mitogenome genetic variation in protein- and tRNA coding genes and suggest that sequence variation in ovine mtDNA is associated with variation in ewe prolificacy.

Model for Codon Position Bias in RNA Editing

NASA Astrophysics Data System (ADS)

Liu, Tsunglin; Bundschuh, Ralf

2005-08-01

RNA editing can be crucial for the expression of genetic information via inserting, deleting, or substituting a few nucleotides at specific positions in an RNA sequence. Within coding regions in an RNA sequence, editing usually occurs with a certain bias in choosing the positions of the editing sites. In the mitochondrial genes of Physarum polycephalum, many more editing events have been observed at the third codon position than at the first and second, while in some plant mitochondria the second codon position dominates. Here we propose an evolutionary model that explains this bias as the basis of selection at the protein level. The model predicts a distribution of the three positions rather close to the experimental observation in Physarum. This suggests that the codon position bias in Physarum is mainly a consequence of selection at the protein level.

A model for codon position bias in RNA editing

NASA Astrophysics Data System (ADS)

Bundschuh, Ralf; Liu, Tsunglin

2006-03-01

RNA editing can be crucial for the expression of genetic information via inserting, deleting, or substituting a few nucleotides at specific positions in an RNA sequence. Within coding regions in an RNA sequence, editing usually occurs with a certain bias in choosing the positions of the editing sites. In the mitochondrial genes of Physarum polycephalum, many more editing events have been observed at the third codon position than at the first and second, while in some plant mitochondria the second codon position dominates. Here we propose an evolutionary model that explains this bias as the basis of selection at the protein level. The model predicts a distribution of the three positions rather close to the experimental observation in Physarum. This suggests that the codon position bias in Physarum is mainly a consequence of selection at the protein level.

Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks

PubMed Central

Avsec, Žiga; Cheng, Jun; Gagneur, Julien

2018-01-01

Abstract Motivation Regulatory sequences are not solely defined by their nucleic acid sequence but also by their relative distances to genomic landmarks such as transcription start site, exon boundaries or polyadenylation site. Deep learning has become the approach of choice for modeling regulatory sequences because of its strength to learn complex sequence features. However, modeling relative distances to genomic landmarks in deep neural networks has not been addressed. Results Here we developed spline transformation, a neural network module based on splines to flexibly and robustly model distances. Modeling distances to various genomic landmarks with spline transformations significantly increased state-of-the-art prediction accuracy of in vivo RNA-binding protein binding sites for 120 out of 123 proteins. We also developed a deep neural network for human splice branchpoint based on spline transformations that outperformed the current best, already distance-based, machine learning model. Compared to piecewise linear transformation, as obtained by composition of rectified linear units, spline transformation yields higher prediction accuracy as well as faster and more robust training. As spline transformation can be applied to further quantities beyond distances, such as methylation or conservation, we foresee it as a versatile component in the genomics deep learning toolbox. Availability and implementation Spline transformation is implemented as a Keras layer in the CONCISE python package: https://github.com/gagneurlab/concise. Analysis code is available at https://github.com/gagneurlab/Manuscript_Avsec_Bioinformatics_2017. Contact avsec@in.tum.de or gagneur@in.tum.de Supplementary information Supplementary data are available at Bioinformatics online. PMID:29155928

Molecular cloning and functional analysis of MRLC2 in Tianfu, Boer, and Chengdu Ma goats.

PubMed

Xu, H G; Xu, G Y; Wan, L; Ma, J

2013-03-15

To determine the molecular basis of heterosis in goats, fluorescence quantitative polymerase chain reaction (PCR) was performed to investigate myosin-regulatory light chain 2 (MRLC2) gene expression in the longissimus dorsi muscle tissues of the Tianfu goat and its parents, the Boer and Chengdu Ma goats. The goat MRLC2 gene was differentially expressed in the crossbreed, and the purebred mRNA were isolated and identified using fluorescence quantitative reverse transcription-PCR (RT-PCR). The complete coding sequence of MRLC2 was obtained using the cDNA method, and the full-length coding sequence consisted of 513 bp encoding 172 amino acids. The EF-hand superfamily domain of the MRLC2 protein is well conserved in caprine and other animals. The deduced amino acid sequence of MRLC2 shared significant identity with MRLC2 from other mammals. Phylogenetic tree analysis revealed that the MRLC2 protein was closely related to MRLC2 in other mammals. Several predicted miRNA target sites were found in the coding sequence of caprine MRLC2 mRNA. Analysis by RT-PCR showed that MRLC2 mRNA was present in the heart, stomach, liver, spleen, lung, small intestine, kidney, leg muscle, abdominal muscle, and longissimus dorsi muscles. In particular, the high expression of MRLC2 mRNA was detected in the longissimus dorsi, leg muscle, abdominal muscle, stomach, and heart, but low levels of expression were also observed in the liver, spleen, lung, small intestine, and kidney. The expression of the MRLC2 gene was upregulated in the longissimus dorsi muscle of Boer and Tianfu goats, and it was moderately upregulated in Chengdu Ma goats.

Complete genome sequencing of the luminescent bacterium, Vibrio qinghaiensis sp. Q67 using PacBio technology

NASA Astrophysics Data System (ADS)

Gong, Liang; Wu, Yu; Jian, Qijie; Yin, Chunxiao; Li, Taotao; Gupta, Vijai Kumar; Duan, Xuewu; Jiang, Yueming

2018-01-01

Vibrio qinghaiensis sp.-Q67 (Vqin-Q67) is a freshwater luminescent bacterium that continuously emits blue-green light (485 nm). The bacterium has been widely used for detecting toxic contaminants. Here, we report the complete genome sequence of Vqin-Q67, obtained using third-generation PacBio sequencing technology. Continuous long reads were attained from three PacBio sequencing runs and reads >500 bp with a quality value of >0.75 were merged together into a single dataset. This resultant highly-contiguous de novo assembly has no genome gaps, and comprises two chromosomes with substantial genetic information, including protein-coding genes, non-coding RNA, transposon and gene islands. Our dataset can be useful as a comparative genome for evolution and speciation studies, as well as for the analysis of protein-coding gene families, the pathogenicity of different Vibrio species in fish, the evolution of non-coding RNA and transposon, and the regulation of gene expression in relation to the bioluminescence of Vqin-Q67.

CpGAVAS, an integrated web server for the annotation, visualization, analysis, and GenBank submission of completely sequenced chloroplast genome sequences

PubMed Central

2012-01-01

Background The complete sequences of chloroplast genomes provide wealthy information regarding the evolutionary history of species. With the advance of next-generation sequencing technology, the number of completely sequenced chloroplast genomes is expected to increase exponentially, powerful computational tools annotating the genome sequences are in urgent need. Results We have developed a web server CPGAVAS. The server accepts a complete chloroplast genome sequence as input. First, it predicts protein-coding and rRNA genes based on the identification and mapping of the most similar, full-length protein, cDNA and rRNA sequences by integrating results from Blastx, Blastn, protein2genome and est2genome programs. Second, tRNA genes and inverted repeats (IR) are identified using tRNAscan, ARAGORN and vmatch respectively. Third, it calculates the summary statistics for the annotated genome. Fourth, it generates a circular map ready for publication. Fifth, it can create a Sequin file for GenBank submission. Last, it allows the extractions of protein and mRNA sequences for given list of genes and species. The annotation results in GFF3 format can be edited using any compatible annotation editing tools. The edited annotations can then be uploaded to CPGAVAS for update and re-analyses repeatedly. Using known chloroplast genome sequences as test set, we show that CPGAVAS performs comparably to another application DOGMA, while having several superior functionalities. Conclusions CPGAVAS allows the semi-automatic and complete annotation of a chloroplast genome sequence, and the visualization, editing and analysis of the annotation results. It will become an indispensible tool for researchers studying chloroplast genomes. The software is freely accessible from http://www.herbalgenomics.org/cpgavas. PMID:23256920

mPUMA: a computational approach to microbiota analysis by de novo assembly of operational taxonomic units based on protein-coding barcode sequences.

PubMed

Links, Matthew G; Chaban, Bonnie; Hemmingsen, Sean M; Muirhead, Kevin; Hill, Janet E

2013-08-15

Formation of operational taxonomic units (OTU) is a common approach to data aggregation in microbial ecology studies based on amplification and sequencing of individual gene targets. The de novo assembly of OTU sequences has been recently demonstrated as an alternative to widely used clustering methods, providing robust information from experimental data alone, without any reliance on an external reference database. Here we introduce mPUMA (microbial Profiling Using Metagenomic Assembly, http://mpuma.sourceforge.net), a software package for identification and analysis of protein-coding barcode sequence data. It was developed originally for Cpn60 universal target sequences (also known as GroEL or Hsp60). Using an unattended process that is independent of external reference sequences, mPUMA forms OTUs by DNA sequence assembly and is capable of tracking OTU abundance. mPUMA processes microbial profiles both in terms of the direct DNA sequence as well as in the translated amino acid sequence for protein coding barcodes. By forming OTUs and calculating abundance through an assembly approach, mPUMA is capable of generating inputs for several popular microbiota analysis tools. Using SFF data from sequencing of a synthetic community of Cpn60 sequences derived from the human vaginal microbiome, we demonstrate that mPUMA can faithfully reconstruct all expected OTU sequences and produce compositional profiles consistent with actual community structure. mPUMA enables analysis of microbial communities while empowering the discovery of novel organisms through OTU assembly.

MitoNuc: a database of nuclear genes coding for mitochondrial proteins. Update 2002.

PubMed

Attimonelli, Marcella; Catalano, Domenico; Gissi, Carmela; Grillo, Giorgio; Licciulli, Flavio; Liuni, Sabino; Santamaria, Monica; Pesole, Graziano; Saccone, Cecilia

2002-01-01

Mitochondria, besides their central role in energy metabolism, have recently been found to be involved in a number of basic processes of cell life and to contribute to the pathogenesis of many degenerative diseases. All functions of mitochondria depend on the interaction of nuclear and organelle genomes. Mitochondrial genomes have been extensively sequenced and analysed and data have been collected in several specialised databases. In order to collect information on nuclear coded mitochondrial proteins we developed MitoNuc, a database containing detailed information on sequenced nuclear genes coding for mitochondrial proteins in Metazoa. The MitoNuc database can be retrieved through SRS and is available via the web site http://bighost.area.ba.cnr.it/mitochondriome where other mitochondrial databases developed by our group, the complete list of the sequenced mitochondrial genomes, links to other mitochondrial sites and related information, are available. The MitoAln database, related to MitoNuc in the previous release, reporting the multiple alignments of the relevant homologous protein coding regions, is no longer supported in the present release. In order to keep the links among entries in MitoNuc from homologous proteins, a new field in the database has been defined: the cluster identifier, an alpha numeric code used to identify each cluster of homologous proteins. A comment field derived from the corresponding SWISS-PROT entry has been introduced; this reports clinical data related to dysfunction of the protein. The logic scheme of MitoNuc database has been implemented in the ORACLE DBMS. This will allow the end-users to retrieve data through a friendly interface that will be soon implemented.

Genetic analyses of bone morphogenetic protein 2, 4 and 7 in congenital combined pituitary hormone deficiency.

PubMed

Breitfeld, Jana; Martens, Susanne; Klammt, Jürgen; Schlicke, Marina; Pfäffle, Roland; Krause, Kerstin; Weidle, Kerstin; Schleinitz, Dorit; Stumvoll, Michael; Führer, Dagmar; Kovacs, Peter; Tönjes, Anke

2013-12-01

The complex process of development of the pituitary gland is regulated by a number of signalling molecules and transcription factors. Mutations in these factors have been identified in rare cases of congenital hypopituitarism but for most subjects with combined pituitary hormone deficiency (CPHD) genetic causes are unknown. Bone morphogenetic proteins (BMPs) affect induction and growth of the pituitary primordium and thus represent plausible candidates for mutational screening of patients with CPHD. We sequenced BMP2, 4 and 7 in 19 subjects with CPHD. For validation purposes, novel genetic variants were genotyped in 1046 healthy subjects. Additionally, potential functional relevance for most promising variants has been assessed by phylogenetic analyses and prediction of effects on protein structure. Sequencing revealed two novel variants and confirmed 30 previously known polymorphisms and mutations in BMP2, 4 and 7. Although phylogenetic analyses indicated that these variants map within strongly conserved gene regions, there was no direct support for their impact on protein structure when applying predictive bioinformatics tools. A mutation in the BMP4 coding region resulting in an amino acid exchange (p.Arg300Pro) appeared most interesting among the identified variants. Further functional analyses are required to ultimately map the relevance of these novel variants in CPHD.

Genetic analyses of bone morphogenetic protein 2, 4 and 7 in congenital combined pituitary hormone deficiency

PubMed Central

2013-01-01

Background The complex process of development of the pituitary gland is regulated by a number of signalling molecules and transcription factors. Mutations in these factors have been identified in rare cases of congenital hypopituitarism but for most subjects with combined pituitary hormone deficiency (CPHD) genetic causes are unknown. Bone morphogenetic proteins (BMPs) affect induction and growth of the pituitary primordium and thus represent plausible candidates for mutational screening of patients with CPHD. Methods We sequenced BMP2, 4 and 7 in 19 subjects with CPHD. For validation purposes, novel genetic variants were genotyped in 1046 healthy subjects. Additionally, potential functional relevance for most promising variants has been assessed by phylogenetic analyses and prediction of effects on protein structure. Results Sequencing revealed two novel variants and confirmed 30 previously known polymorphisms and mutations in BMP2, 4 and 7. Although phylogenetic analyses indicated that these variants map within strongly conserved gene regions, there was no direct support for their impact on protein structure when applying predictive bioinformatics tools. Conclusions A mutation in the BMP4 coding region resulting in an amino acid exchange (p.Arg300Pro) appeared most interesting among the identified variants. Further functional analyses are required to ultimately map the relevance of these novel variants in CPHD. PMID:24289245

Complete Genome Sequence of the Soil Actinomycete Kocuria rhizophila▿

PubMed Central

Takarada, Hiromi; Sekine, Mitsuo; Kosugi, Hiroki; Matsuo, Yasunori; Fujisawa, Takatomo; Omata, Seiha; Kishi, Emi; Shimizu, Ai; Tsukatani, Naofumi; Tanikawa, Satoshi; Fujita, Nobuyuki; Harayama, Shigeaki

2008-01-01

The soil actinomycete Kocuria rhizophila belongs to the suborder Micrococcineae, a divergent bacterial group for which only a limited amount of genomic information is currently available. K. rhizophila is also important in industrial applications; e.g., it is commonly used as a standard quality control strain for antimicrobial susceptibility testing. Sequencing and annotation of the genome of K. rhizophila DC2201 (NBRC 103217) revealed a single circular chromosome (2,697,540 bp; G+C content of 71.16%) containing 2,357 predicted protein-coding genes. Most of the predicted proteins (87.7%) were orthologous to actinobacterial proteins, and the genome showed fairly good conservation of synteny with taxonomically related actinobacterial genomes. On the other hand, the genome seems to encode much smaller numbers of proteins necessary for secondary metabolism (one each of nonribosomal peptide synthetase and type III polyketide synthase), transcriptional regulation, and lateral gene transfer, reflecting the small genome size. The presence of probable metabolic pathways for the transformation of phenolic compounds generated from the decomposition of plant materials, and the presence of a large number of genes associated with membrane transport, particularly amino acid transporters and drug efflux pumps, may contribute to the organism's utilization of root exudates, as well as the tolerance to various organic compounds. PMID:18408034

The Genome of the Generalist Plant Pathogen Fusarium avenaceum Is Enriched with Genes Involved in Redox, Signaling and Secondary Metabolism

PubMed Central

Lysøe, Erik; Harris, Linda J.; Walkowiak, Sean; Subramaniam, Rajagopal; Divon, Hege H.; Riiser, Even S.; Llorens, Carlos; Gabaldón, Toni; Kistler, H. Corby; Jonkers, Wilfried; Kolseth, Anna-Karin; Nielsen, Kristian F.; Thrane, Ulf; Frandsen, Rasmus J. N.

2014-01-01

Fusarium avenaceum is a fungus commonly isolated from soil and associated with a wide range of host plants. We present here three genome sequences of F. avenaceum, one isolated from barley in Finland and two from spring and winter wheat in Canada. The sizes of the three genomes range from 41.6–43.1 MB, with 13217–13445 predicted protein-coding genes. Whole-genome analysis showed that the three genomes are highly syntenic, and share>95% gene orthologs. Comparative analysis to other sequenced Fusaria shows that F. avenaceum has a very large potential for producing secondary metabolites, with between 75 and 80 key enzymes belonging to the polyketide, non-ribosomal peptide, terpene, alkaloid and indole-diterpene synthase classes. In addition to known metabolites from F. avenaceum, fuscofusarin and JM-47 were detected for the first time in this species. Many protein families are expanded in F. avenaceum, such as transcription factors, and proteins involved in redox reactions and signal transduction, suggesting evolutionary adaptation to a diverse and cosmopolitan ecology. We found that 20% of all predicted proteins were considered to be secreted, supporting a life in the extracellular space during interaction with plant hosts. PMID:25409087

[Convergent origin of repeats in genes coding for globular proteins. An analysis of the factors determining the presence of inverted and symmetrical repeats].

PubMed

Solov'ev, V V; Kel', A E; Kolchanov, N A

1989-01-01

The factors, determining the presence of inverted and symmetrical repeats in genes coding for globular proteins, have been analysed. An interesting property of genetical code has been revealed in the analysis of symmetrical repeats: the pairs of symmetrical codons corresponded to pairs of amino acids with mostly similar physical-chemical parameters. This property may explain the presence of symmetrical repeats and palindromes only in genes coding for beta-structural proteins-polypeptides, where amino acids with similar physical-chemical properties occupy symmetrical positions. A stochastic model of evolution of polynucleotide sequences has been used for analysis of inverted repeats. The modelling demonstrated that only limiting of sequences (uneven frequencies of used codons) is enough for arising of nonrandom inverted repeats in genes.

Mitochondrial genetic codes evolve to match amino acid requirements of proteins.

PubMed

Swire, Jonathan; Judson, Olivia P; Burt, Austin

2005-01-01

Mitochondria often use genetic codes different from the standard genetic code. Now that many mitochondrial genomes have been sequenced, these variant codes provide the first opportunity to examine empirically the processes that produce new genetic codes. The key question is: Are codon reassignments the sole result of mutation and genetic drift? Or are they the result of natural selection? Here we present an analysis of 24 phylogenetically independent codon reassignments in mitochondria. Although the mutation-drift hypothesis can explain reassignments from stop to an amino acid, we found that it cannot explain reassignments from one amino acid to another. In particular--and contrary to the predictions of the mutation-drift hypothesis--the codon involved in such a reassignment was not rare in the ancestral genome. Instead, such reassignments appear to take place while the codon is in use at an appreciable frequency. Moreover, the comparison of inferred amino acid usage in the ancestral genome with the neutral expectation shows that the amino acid gaining the codon was selectively favored over the amino acid losing the codon. These results are consistent with a simple model of weak selection on the amino acid composition of proteins in which codon reassignments are selected because they compensate for multiple slightly deleterious mutations throughout the mitochondrial genome. We propose that the selection pressure is for reduced protein synthesis cost: most reassignments give amino acids that are less expensive to synthesize. Taken together, our results strongly suggest that mitochondrial genetic codes evolve to match the amino acid requirements of proteins.

Protein domain analysis of genomic sequence data reveals regulation of LRR related domains in plant transpiration in Ficus.

PubMed

Lang, Tiange; Yin, Kangquan; Liu, Jinyu; Cao, Kunfang; Cannon, Charles H; Du, Fang K

2014-01-01

Predicting protein domains is essential for understanding a protein's function at the molecular level. However, up till now, there has been no direct and straightforward method for predicting protein domains in species without a reference genome sequence. In this study, we developed a functionality with a set of programs that can predict protein domains directly from genomic sequence data without a reference genome. Using whole genome sequence data, the programming functionality mainly comprised DNA assembly in combination with next-generation sequencing (NGS) assembly methods and traditional methods, peptide prediction and protein domain prediction. The proposed new functionality avoids problems associated with de novo assembly due to micro reads and small single repeats. Furthermore, we applied our functionality for the prediction of leucine rich repeat (LRR) domains in four species of Ficus with no reference genome, based on NGS genomic data. We found that the LRRNT_2 and LRR_8 domains are related to plant transpiration efficiency, as indicated by the stomata index, in the four species of Ficus. The programming functionality established in this study provides new insights for protein domain prediction, which is particularly timely in the current age of NGS data expansion.

Cryptic tRNAs in chaetognath mitochondrial genomes.

PubMed

Barthélémy, Roxane-Marie; Seligmann, Hervé

2016-06-01

The chaetognaths constitute a small and enigmatic phylum of little marine invertebrates. Both nuclear and mitochondrial genomes have numerous originalities, some phylum-specific. Until recently, their mitogenomes seemed containing only one tRNA gene (trnMet), but a recent study found in two chaetognath mitogenomes two and four tRNA genes. Moreover, apparently two conspecific mitogenomes have different tRNA gene numbers (one and two). Reanalyses by tRNAscan-SE and ARWEN softwares of the five available complete chaetognath mitogenomes suggest numerous additional tRNA genes from different types. Their total number never reaches the 22 found in most other invertebrates using that genetic code. Predicted error compensation between codon-anticodon mismatch and tRNA misacylation suggests translational activity by tRNAs predicted solely according to secondary structure for tRNAs predicted by tRNAscan-SE, not ARWEN. Numbers of predicted stop-suppressor (antitermination) tRNAs coevolve with predicted overlapping, frameshifted protein coding genes including stop codons. Sequence alignments in secondary structure prediction with non-chaetognath tRNAs suggest that the most likely functional tRNAs are in intergenic regions, as regular mt-tRNAs. Due to usually short intergenic regions, generally tRNA sequences partially overlap with flanking genes. Some tRNA pairs seem templated by sense-antisense strands. Moreover, 16S rRNA genes, but not 12S rRNAs, appear as tRNA nurseries, as previously suggested for multifunctional ribosomal-like protogenomes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Prediction of Spontaneous Protein Deamidation from Sequence-Derived Secondary Structure and Intrinsic Disorder.

PubMed

Lorenzo, J Ramiro; Alonso, Leonardo G; Sánchez, Ignacio E

2015-01-01

Asparagine residues in proteins undergo spontaneous deamidation, a post-translational modification that may act as a molecular clock for the regulation of protein function and turnover. Asparagine deamidation is modulated by protein local sequence, secondary structure and hydrogen bonding. We present NGOME, an algorithm able to predict non-enzymatic deamidation of internal asparagine residues in proteins in the absence of structural data, using sequence-based predictions of secondary structure and intrinsic disorder. Compared to previous algorithms, NGOME does not require three-dimensional structures yet yields better predictions than available sequence-only methods. Four case studies of specific proteins show how NGOME may help the user identify deamidation-prone asparagine residues, often related to protein gain of function, protein degradation or protein misfolding in pathological processes. A fifth case study applies NGOME at a proteomic scale and unveils a correlation between asparagine deamidation and protein degradation in yeast. NGOME is freely available as a webserver at the National EMBnet node Argentina, URL: http://www.embnet.qb.fcen.uba.ar/ in the subpage "Protein and nucleic acid structure and sequence analysis".

Genome Sequence of the Mesophilic Thermotogales Bacterium Mesotoga prima MesG1.Ag.4.2 Reveals the Largest Thermotogales Genome To Date

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhaxybayeva, Olga; Swithers, Kristen S; Foght, Julia

2012-01-01

Here we describe the genome of Mesotoga prima MesG1.Ag4.2, the first genome of a mesophilic Thermotogales bacterium. Mesotoga prima was isolated from a polychlorinated biphenyl (PCB)-dechlorinating enrichment culture from Baltimore Harbor sediments. Its 2.97 Mb genome is considerably larger than any previously sequenced Thermotogales genomes, which range between 1.86 and 2.30 Mb. This larger size is due to both higher numbers of protein-coding genes and larger intergenic regions. In particular, the M. prima genome contains more genes for proteins involved in regulatory functions, for instance those involved in regulation of transcription. Together with its closest relative, Kosmotoga olearia, it alsomore » encodes different types of proteins involved in environmental and cell-cell interactions as compared with other Thermotogales bacteria. Amino acid composition analysis of M. prima proteins implies that this lineage has inhabited low-temperature environments for a long time. A large fraction of the M. prima genome has been acquired by lateral gene transfer (LGT): a DarkHorse analysis suggests that 766 (32%) of predicted protein-coding genes have been involved in LGT after Mesotoga diverged from the other Thermotogales lineages. A notable example of a lineage-specific LGT event is a reductive dehalogenase gene - a key enzyme in dehalorespiration, indicating M. prima may have a more active role in PCB dechlorination than was previously assumed.« less

Complete mitochondrial genome sequence of the heart failure model of cardiomyopathic Syrian hamster (Mesocricetus auratus).

PubMed

Hu, Bo; Liu, Dong-Xing; Zhang, Yu-Qing; Song, Jian-Tao; Ji, Xian-Fei; Hou, Zhi-Qiang; Zhang, Zhen-Hai

2016-05-01

In this study we sequenced the complete mitochondrial genome sequencing of a heart failure model of cardiomyopathic Syrian hamster (Mesocricetus auratus) for the first time. The total length of the mitogenome was 16,267 bp. It harbored 13 protein-coding genes, 2 ribosomal RNA genes, 22 transfer RNA genes and 1 non-coding control region.

PDB-UF: database of predicted enzymatic functions for unannotated protein structures from structural genomics.

PubMed

von Grotthuss, Marcin; Plewczynski, Dariusz; Ginalski, Krzysztof; Rychlewski, Leszek; Shakhnovich, Eugene I

2006-02-06

The number of protein structures from structural genomics centers dramatically increases in the Protein Data Bank (PDB). Many of these structures are functionally unannotated because they have no sequence similarity to proteins of known function. However, it is possible to successfully infer function using only structural similarity. Here we present the PDB-UF database, a web-accessible collection of predictions of enzymatic properties using structure-function relationship. The assignments were conducted for three-dimensional protein structures of unknown function that come from structural genomics initiatives. We show that 4 hypothetical proteins (with PDB accession codes: 1VH0, 1NS5, 1O6D, and 1TO0), for which standard BLAST tools such as PSI-BLAST or RPS-BLAST failed to assign any function, are probably methyltransferase enzymes. We suggest that the structure-based prediction of an EC number should be conducted having the different similarity score cutoff for different protein folds. Moreover, performing the annotation using two different algorithms can reduce the rate of false positive assignments. We believe, that the presented web-based repository will help to decrease the number of protein structures that have functions marked as "unknown" in the PDB file. http://paradox.harvard.edu/PDB-UF and http://bioinfo.pl/PDB-UF.

Draft Genome Sequence of Bacillus cereus CITVM-11.1, a Strain Exhibiting Interesting Antifungal Activities.

PubMed

Caballero, Javier; Peralta, Cecilia; Molla, Antonella; Del Valle, Eleodoro E; Caballero, Primitivo; Berry, Colin; Felipe, Verónica; Yaryura, Pablo; Palma, Leopoldo

2018-01-01

Bacillus cereus is a gram-positive, spore-forming bacterium possessing an important and historical record as a human-pathogenic bacterium. However, several strains of this species exhibit interesting potential to be used as plant growth-promoting rhizobacteria. Here, we report the draft genome sequence of B. cereus strain CITVM-11.1, which consists of 37 contig sequences, accounting for 5,746,486 bp (with a GC content of 34.8%) and 5,752 predicted protein-coding sequences. Several of them could potentially be involved in plant-bacterium interactions and may contribute to the strong antagonistic activity shown by this strain against the charcoal root rot fungus, Macrophomina phaseolina. This genomic sequence also showed a number of genes that may confer this strain resistance against several polluting heavy metals and for the bioconversion of mycotoxins. © 2018 S. Karger AG, Basel.

Hidden Structural Codes in Protein Intrinsic Disorder.

PubMed

Borkosky, Silvia S; Camporeale, Gabriela; Chemes, Lucía B; Risso, Marikena; Noval, María Gabriela; Sánchez, Ignacio E; Alonso, Leonardo G; de Prat Gay, Gonzalo

2017-10-17

Intrinsic disorder is a major structural category in biology, accounting for more than 30% of coding regions across the domains of life, yet consists of conformational ensembles in equilibrium, a major challenge in protein chemistry. Anciently evolved papillomavirus genomes constitute an unparalleled case for sequence to structure-function correlation in cases in which there are no folded structures. E7, the major transforming oncoprotein of human papillomaviruses, is a paradigmatic example among the intrinsically disordered proteins. Analysis of a large number of sequences of the same viral protein allowed for the identification of a handful of residues with absolute conservation, scattered along the sequence of its N-terminal intrinsically disordered domain, which intriguingly are mostly leucine residues. Mutation of these led to a pronounced increase in both α-helix and β-sheet structural content, reflected by drastic effects on equilibrium propensities and oligomerization kinetics, and uncovers the existence of local structural elements that oppose canonical folding. These folding relays suggest the existence of yet undefined hidden structural codes behind intrinsic disorder in this model protein. Thus, evolution pinpoints conformational hot spots that could have not been identified by direct experimental methods for analyzing or perturbing the equilibrium of an intrinsically disordered protein ensemble.

End Joining-Mediated Gene Expression in Mammalian Cells Using PCR-Amplified DNA Constructs that Contain Terminator in Front of Promoter.

PubMed

Nakamura, Mikiko; Suzuki, Ayako; Akada, Junko; Tomiyoshi, Keisuke; Hoshida, Hisashi; Akada, Rinji

2015-12-01

Mammalian gene expression constructs are generally prepared in a plasmid vector, in which a promoter and terminator are located upstream and downstream of a protein-coding sequence, respectively. In this study, we found that front terminator constructs-DNA constructs containing a terminator upstream of a promoter rather than downstream of a coding region-could sufficiently express proteins as a result of end joining of the introduced DNA fragment. By taking advantage of front terminator constructs, FLAG substitutions, and deletions were generated using mutagenesis primers to identify amino acids specifically recognized by commercial FLAG antibodies. A minimal epitope sequence for polyclonal FLAG antibody recognition was also identified. In addition, we analyzed the sequence of a C-terminal Ser-Lys-Leu peroxisome localization signal, and identified the key residues necessary for peroxisome targeting. Moreover, front terminator constructs of hepatitis B surface antigen were used for deletion analysis, leading to the identification of regions required for the particle formation. Collectively, these results indicate that front terminator constructs allow for easy manipulations of C-terminal protein-coding sequences, and suggest that direct gene expression with PCR-amplified DNA is useful for high-throughput protein analysis in mammalian cells.

Novel numerical and graphical representation of DNA sequences and proteins.

PubMed

Randić, M; Novic, M; Vikić-Topić, D; Plavsić, D

2006-12-01

We have introduced novel numerical and graphical representations of DNA, which offer a simple and unique characterization of DNA sequences. The numerical representation of a DNA sequence is given as a sequence of real numbers derived from a unique graphical representation of the standard genetic code. There is no loss of information on the primary structure of a DNA sequence associated with this numerical representation. The novel representations are illustrated with the coding sequences of the first exon of beta-globin gene of half a dozen species in addition to human. The method can be extended to proteins as is exemplified by humanin, a 24-aa peptide that has recently been identified as a specific inhibitor of neuronal cell death induced by familial Alzheimer's disease mutant genes.

TANDEM: matching proteins with tandem mass spectra.

PubMed

Craig, Robertson; Beavis, Ronald C

2004-06-12

Tandem mass spectra obtained from fragmenting peptide ions contain some peptide sequence specific information, but often there is not enough information to sequence the original peptide completely. Several proprietary software applications have been developed to attempt to match the spectra with a list of protein sequences that may contain the sequence of the peptide. The application TANDEM was written to provide the proteomics research community with a set of components that can be used to test new methods and algorithms for performing this type of sequence-to-data matching. The source code and binaries for this software are available at http://www.proteome.ca/opensource.html, for Windows, Linux and Macintosh OSX. The source code is made available under the Artistic License, from the authors.

Computational prediction of secretion systems and secretomes of Brucella: identification of novel type IV effectors and their interaction with the host.

PubMed

Sankarasubramanian, Jagadesan; Vishnu, Udayakumar S; Dinakaran, Vasudevan; Sridhar, Jayavel; Gunasekaran, Paramasamy; Rajendhran, Jeyaprakash

2016-01-01

Brucella spp. are facultative intracellular pathogens that cause brucellosis in various mammals including humans. Brucella survive inside the host cells by forming vacuoles and subverting host defence systems. This study was aimed to predict the secretion systems and the secretomes of Brucella spp. from 39 complete genome sequences available in the databases. Furthermore, an attempt was made to identify the type IV secretion effectors and their interactions with host proteins. We predicted the secretion systems of Brucella by the KEGG pathway and SecReT4. Brucella secretomes and type IV effectors (T4SEs) were predicted through genome-wide screening using JVirGel and S4TE, respectively. Protein-protein interactions of Brucella T4SEs with their hosts were analyzed by HPIDB 2.0. Genes coding for Sec and Tat pathways of secretion and type I (T1SS), type IV (T4SS) and type V (T5SS) secretion systems were identified and they are conserved in all the species of Brucella. In addition to the well-known VirB operon coding for the type IV secretion system (T4SS), we have identified the presence of additional genes showing homology with T4SS of other organisms. On the whole, 10.26 to 14.94% of total proteomes were found to be either secreted (secretome) or membrane associated (membrane proteome). Approximately, 1.7 to 3.0% of total proteomes were identified as type IV secretion effectors (T4SEs). Prediction of protein-protein interactions showed 29 and 36 host-pathogen specific interactions between Bos taurus (cattle)-B. abortus and Ovis aries (sheep)-B. melitensis, respectively. Functional characterization of the predicted T4SEs and their interactions with their respective hosts may reveal the secrets of host specificity of Brucella.

RNA 3D Structural Motifs: Definition, Identification, Annotation, and Database Searching

NASA Astrophysics Data System (ADS)

Nasalean, Lorena; Stombaugh, Jesse; Zirbel, Craig L.; Leontis, Neocles B.

Structured RNA molecules resemble proteins in the hierarchical organization of their global structures, folding and broad range of functions. Structured RNAs are composed of recurrent modular motifs that play specific functional roles. Some motifs direct the folding of the RNA or stabilize the folded structure through tertiary interactions. Others bind ligands or proteins or catalyze chemical reactions. Therefore, it is desirable, starting from the RNA sequence, to be able to predict the locations of recurrent motifs in RNA molecules. Conversely, the potential occurrence of one or more known 3D RNA motifs may indicate that a genomic sequence codes for a structured RNA molecule. To identify known RNA structural motifs in new RNA sequences, precise structure-based definitions are needed that specify the core nucleotides of each motif and their conserved interactions. By comparing instances of each recurrent motif and applying base pair isosteriCity relations, one can identify neutral mutations that preserve its structure and function in the contexts in which it occurs.

Experimental Assessment of Splicing Variants Using Expression Minigenes and Comparison with In Silico Predictions

PubMed Central

Sharma, Neeraj; Sosnay, Patrick R.; Ramalho, Anabela S.; Douville, Christopher; Franca, Arianna; Gottschalk, Laura B.; Park, Jeenah; Lee, Melissa; Vecchio-Pagan, Briana; Raraigh, Karen S.; Amaral, Margarida D.; Karchin, Rachel; Cutting, Garry R.

2015-01-01

Assessment of the functional consequences of variants near splice sites is a major challenge in the diagnostic laboratory. To address this issue, we created expression minigenes (EMGs) to determine the RNA and protein products generated by splice site variants (n = 10) implicated in cystic fibrosis (CF). Experimental results were compared with the splicing predictions of eight in silico tools. EMGs containing the full-length Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) coding sequence and flanking intron sequences generated wild-type transcript and fully processed protein in Human Embryonic Kidney (HEK293) and CF bronchial epithelial (CFBE41o-) cells. Quantification of variant induced aberrant mRNA isoforms was concordant using fragment analysis and pyrosequencing. The splicing patterns of c.1585−1G>A and c.2657+5G>A were comparable to those reported in primary cells from individuals bearing these variants. Bioinformatics predictions were consistent with experimental results for 9/10 variants (MES), 8/10 variants (NNSplice), and 7/10 variants (SSAT and Sroogle). Programs that estimate the consequences of mis-splicing predicted 11/16 (HSF and ASSEDA) and 10/16 (Fsplice and SplicePort) experimentally observed mRNA isoforms. EMGs provide a robust experimental approach for clinical interpretation of splice site variants and refinement of in silico tools. PMID:25066652

Protein location prediction using atomic composition and global features of the amino acid sequence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cherian, Betsy Sheena, E-mail: betsy.skb@gmail.com; Nair, Achuthsankar S.

2010-01-22

Subcellular location of protein is constructive information in determining its function, screening for drug candidates, vaccine design, annotation of gene products and in selecting relevant proteins for further studies. Computational prediction of subcellular localization deals with predicting the location of a protein from its amino acid sequence. For a computational localization prediction method to be more accurate, it should exploit all possible relevant biological features that contribute to the subcellular localization. In this work, we extracted the biological features from the full length protein sequence to incorporate more biological information. A new biological feature, distribution of atomic composition is effectivelymore » used with, multiple physiochemical properties, amino acid composition, three part amino acid composition, and sequence similarity for predicting the subcellular location of the protein. Support Vector Machines are designed for four modules and prediction is made by a weighted voting system. Our system makes prediction with an accuracy of 100, 82.47, 88.81 for self-consistency test, jackknife test and independent data test respectively. Our results provide evidence that the prediction based on the biological features derived from the full length amino acid sequence gives better accuracy than those derived from N-terminal alone. Considering the features as a distribution within the entire sequence will bring out underlying property distribution to a greater detail to enhance the prediction accuracy.« less

EUGENE'HOM: A generic similarity-based gene finder using multiple homologous sequences.

PubMed

Foissac, Sylvain; Bardou, Philippe; Moisan, Annick; Cros, Marie-Josée; Schiex, Thomas

2003-07-01

EUGENE'HOM is a gene prediction software for eukaryotic organisms based on comparative analysis. EUGENE'HOM is able to take into account multiple homologous sequences from more or less closely related organisms. It integrates the results of TBLASTX analysis, splice site and start codon prediction and a robust coding/non-coding probabilistic model which allows EUGENE'HOM to handle sequences from a variety of organisms. The current target of EUGENE'HOM is plant sequences. The EUGENE'HOM web site is available at http://genopole.toulouse.inra.fr/bioinfo/eugene/EuGeneHom/cgi-bin/EuGeneHom.pl.

A Deep Learning Framework for Robust and Accurate Prediction of ncRNA-Protein Interactions Using Evolutionary Information.

PubMed

Yi, Hai-Cheng; You, Zhu-Hong; Huang, De-Shuang; Li, Xiao; Jiang, Tong-Hai; Li, Li-Ping

2018-06-01

The interactions between non-coding RNAs (ncRNAs) and proteins play an important role in many biological processes, and their biological functions are primarily achieved by binding with a variety of proteins. High-throughput biological techniques are used to identify protein molecules bound with specific ncRNA, but they are usually expensive and time consuming. Deep learning provides a powerful solution to computationally predict RNA-protein interactions. In this work, we propose the RPI-SAN model by using the deep-learning stacked auto-encoder network to mine the hidden high-level features from RNA and protein sequences and feed them into a random forest (RF) model to predict ncRNA binding proteins. Stacked assembling is further used to improve the accuracy of the proposed method. Four benchmark datasets, including RPI2241, RPI488, RPI1807, and NPInter v2.0, were employed for the unbiased evaluation of five established prediction tools: RPI-Pred, IPMiner, RPISeq-RF, lncPro, and RPI-SAN. The experimental results show that our RPI-SAN model achieves much better performance than other methods, with accuracies of 90.77%, 89.7%, 96.1%, and 99.33%, respectively. It is anticipated that RPI-SAN can be used as an effective computational tool for future biomedical researches and can accurately predict the potential ncRNA-protein interacted pairs, which provides reliable guidance for biological research. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

OSPREY: protein design with ensembles, flexibility, and provable algorithms.

PubMed

Gainza, Pablo; Roberts, Kyle E; Georgiev, Ivelin; Lilien, Ryan H; Keedy, Daniel A; Chen, Cheng-Yu; Reza, Faisal; Anderson, Amy C; Richardson, David C; Richardson, Jane S; Donald, Bruce R

2013-01-01

We have developed a suite of protein redesign algorithms that improves realistic in silico modeling of proteins. These algorithms are based on three characteristics that make them unique: (1) improved flexibility of the protein backbone, protein side-chains, and ligand to accurately capture the conformational changes that are induced by mutations to the protein sequence; (2) modeling of proteins and ligands as ensembles of low-energy structures to better approximate binding affinity; and (3) a globally optimal protein design search, guaranteeing that the computational predictions are optimal with respect to the input model. Here, we illustrate the importance of these three characteristics. We then describe OSPREY, a protein redesign suite that implements our protein design algorithms. OSPREY has been used prospectively, with experimental validation, in several biomedically relevant settings. We show in detail how OSPREY has been used to predict resistance mutations and explain why improved flexibility, ensembles, and provability are essential for this application. OSPREY is free and open source under a Lesser GPL license. The latest version is OSPREY 2.0. The program, user manual, and source code are available at www.cs.duke.edu/donaldlab/software.php. osprey@cs.duke.edu. Copyright © 2013 Elsevier Inc. All rights reserved.

Sounds of silence: synonymous nucleotides as a key to biological regulation and complexity

PubMed Central

Shabalina, Svetlana A.; Spiridonov, Nikolay A.; Kashina, Anna

2013-01-01

Messenger RNA is a key component of an intricate regulatory network of its own. It accommodates numerous nucleotide signals that overlap protein coding sequences and are responsible for multiple levels of regulation and generation of biological complexity. A wealth of structural and regulatory information, which mRNA carries in addition to the encoded amino acid sequence, raises the question of how these signals and overlapping codes are delineated along non-synonymous and synonymous positions in protein coding regions, especially in eukaryotes. Silent or synonymous codon positions, which do not determine amino acid sequences of the encoded proteins, define mRNA secondary structure and stability and affect the rate of translation, folding and post-translational modifications of nascent polypeptides. The RNA level selection is acting on synonymous sites in both prokaryotes and eukaryotes and is more common than previously thought. Selection pressure on the coding gene regions follows three-nucleotide periodic pattern of nucleotide base-pairing in mRNA, which is imposed by the genetic code. Synonymous positions of the coding regions have a higher level of hybridization potential relative to non-synonymous positions, and are multifunctional in their regulatory and structural roles. Recent experimental evidence and analysis of mRNA structure and interspecies conservation suggest that there is an evolutionary tradeoff between selective pressure acting at the RNA and protein levels. Here we provide a comprehensive overview of the studies that define the role of silent positions in regulating RNA structure and processing that exert downstream effects on proteins and their functions. PMID:23293005

Improved detection of DNA-binding proteins via compression technology on PSSM information.

PubMed

Wang, Yubo; Ding, Yijie; Guo, Fei; Wei, Leyi; Tang, Jijun

2017-01-01

Since the importance of DNA-binding proteins in multiple biomolecular functions has been recognized, an increasing number of researchers are attempting to identify DNA-binding proteins. In recent years, the machine learning methods have become more and more compelling in the case of protein sequence data soaring, because of their favorable speed and accuracy. In this paper, we extract three features from the protein sequence, namely NMBAC (Normalized Moreau-Broto Autocorrelation), PSSM-DWT (Position-specific scoring matrix-Discrete Wavelet Transform), and PSSM-DCT (Position-specific scoring matrix-Discrete Cosine Transform). We also employ feature selection algorithm on these feature vectors. Then, these features are fed into the training SVM (support vector machine) model as classifier to predict DNA-binding proteins. Our method applys three datasets, namely PDB1075, PDB594 and PDB186, to evaluate the performance of our approach. The PDB1075 and PDB594 datasets are employed for Jackknife test and the PDB186 dataset is used for the independent test. Our method achieves the best accuracy in the Jacknife test, from 79.20% to 86.23% and 80.5% to 86.20% on PDB1075 and PDB594 datasets, respectively. In the independent test, the accuracy of our method comes to 76.3%. The performance of independent test also shows that our method has a certain ability to be effectively used for DNA-binding protein prediction. The data and source code are at https://doi.org/10.6084/m9.figshare.5104084.

Genome-Wide Prediction and Analysis of 3D-Domain Swapped Proteins in the Human Genome from Sequence Information.

PubMed

Upadhyay, Atul Kumar; Sowdhamini, Ramanathan

2016-01-01

3D-domain swapping is one of the mechanisms of protein oligomerization and the proteins exhibiting this phenomenon have many biological functions. These proteins, which undergo domain swapping, have acquired much attention owing to their involvement in human diseases, such as conformational diseases, amyloidosis, serpinopathies, proteionopathies etc. Early realisation of proteins in the whole human genome that retain tendency to domain swap will enable many aspects of disease control management. Predictive models were developed by using machine learning approaches with an average accuracy of 78% (85.6% of sensitivity, 87.5% of specificity and an MCC value of 0.72) to predict putative domain swapping in protein sequences. These models were applied to many complete genomes with special emphasis on the human genome. Nearly 44% of the protein sequences in the human genome were predicted positive for domain swapping. Enrichment analysis was performed on the positively predicted sequences from human genome for their domain distribution, disease association and functional importance based on Gene Ontology (GO). Enrichment analysis was also performed to infer a better understanding of the functional importance of these sequences. Finally, we developed hinge region prediction, in the given putative domain swapped sequence, by using important physicochemical properties of amino acids.

Evaluation of a Genome-Scale In Silico Metabolic Model for Geobacter metallireducens Using Proteomic Data from a Field Biostimulation Experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fang, Yilin; Wilkins, Michael J.; Yabusaki, Steven B.

2012-12-12

Biomass and shotgun global proteomics data that reflected relative protein abundances from samples collected during the 2008 experiment at the U.S. Department of Energy Integrated Field-Scale Subsurface Research Challenge site in Rifle, Colorado, provided an unprecedented opportunity to validate a genome-scale metabolic model of Geobacter metallireducens and assess its performance with respect to prediction of metal reduction, biomass yield, and growth rate under dynamic field conditions. Reconstructed from annotated genomic sequence, biochemical, and physiological data, the constraint-based in silico model of G. metallireducens relates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes.more » Proteomic analysis showed that 180 of the 637 G. metallireducens proteins detected during the 2008 experiment were associated with specific metabolic reactions in the in silico model. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through the in silico model reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low fluxes through amino acid transport and metabolism, revealed pathways or flux constraints in the in silico model that could be updated to more accurately predict metabolic processes that occur in the subsurface environment.« less

Genome sequence of Plasmopara viticola and insight into the pathogenic mechanism

PubMed Central

Yin, Ling; An, Yunhe; Qu, Junjie; Li, Xinlong; Zhang, Yali; Dry, Ian; Wu, Huijuan; Lu, Jiang

2017-01-01

Plasmopara viticola causes downy mildew disease of grapevine which is one of the most devastating diseases of viticulture worldwide. Here we report a 101.3 Mb whole genome sequence of P. viticola isolate ‘JL-7-2’ obtained by a combination of Illumina and PacBio sequencing technologies. The P. viticola genome contains 17,014 putative protein-coding genes and has ~26% repetitive sequences. A total of 1,301 putative secreted proteins, including 100 putative RXLR effectors and 90 CRN effectors were identified in this genome. In the secretome, 261 potential pathogenicity genes and 95 carbohydrate-active enzymes were predicted. Transcriptional analysis revealed that most of the RXLR effectors, pathogenicity genes and carbohydrate-active enzymes were significantly up-regulated during infection. Comparative genomic analysis revealed that P. viticola evolved independently from the Arabidopsis downy mildew pathogen Hyaloperonospora arabidopsidis. The availability of the P. viticola genome provides a valuable resource not only for comparative genomic analysis and evolutionary studies among oomycetes, but also enhance our knowledge on the mechanism of interactions between this biotrophic pathogen and its host. PMID:28417959

Automated eukaryotic gene structure annotation using EVidenceModeler and the Program to Assemble Spliced Alignments

PubMed Central

Haas, Brian J; Salzberg, Steven L; Zhu, Wei; Pertea, Mihaela; Allen, Jonathan E; Orvis, Joshua; White, Owen; Buell, C Robin; Wortman, Jennifer R

2008-01-01

EVidenceModeler (EVM) is presented as an automated eukaryotic gene structure annotation tool that reports eukaryotic gene structures as a weighted consensus of all available evidence. EVM, when combined with the Program to Assemble Spliced Alignments (PASA), yields a comprehensive, configurable annotation system that predicts protein-coding genes and alternatively spliced isoforms. Our experiments on both rice and human genome sequences demonstrate that EVM produces automated gene structure annotation approaching the quality of manual curation. PMID:18190707

Sense-antisense (complementary) peptide interactions and the proteomic code; potential opportunities in biology and pharmaceutical science.

PubMed

Miller, Andrew D

2015-02-01

A sense peptide can be defined as a peptide whose sequence is coded by the nucleotide sequence (read 5' → 3') of the sense (positive) strand of DNA. Conversely, an antisense (complementary) peptide is coded by the corresponding nucleotide sequence (read 5' → 3') of the antisense (negative) strand of DNA. Research has been accumulating steadily to suggest that sense peptides are capable of specific interactions with their corresponding antisense peptides. Unfortunately, although more and more examples of specific sense-antisense peptide interactions are emerging, the very idea of such interactions does not conform to standard biology dogma and so there remains a sizeable challenge to lift this concept from being perceived as a peripheral phenomenon if not worse, into becoming part of the scientific mainstream. Specific interactions have now been exploited for the inhibition of number of widely different protein-protein and protein-receptor interactions in vitro and in vivo. Further, antisense peptides have also been used to induce the production of antibodies targeted to specific receptors or else the production of anti-idiotypic antibodies targeted against auto-antibodies. Such illustrations of utility would seem to suggest that observed sense-antisense peptide interactions are not just the consequence of a sequence of coincidental 'lucky-hits'. Indeed, at the very least, one might conclude that sense-antisense peptide interactions represent a potentially new and different source of leads for drug discovery. But could there be more to come from studies in this area? Studies on the potential mechanism of sense-antisense peptide interactions suggest that interactions may be driven by amino acid residue interactions specified from the genetic code. If so, such specified amino acid residue interactions could form the basis for an even wider amino acid residue interaction code (proteomic code) that links gene sequences to actual protein structure and function, even entire genomes to entire proteomes. The possibility that such a proteomic code should exist is discussed. So too the potential implications for biology and pharmaceutical science are also discussed were such a code to exist.

GeneSilico protein structure prediction meta-server.

PubMed

Kurowski, Michal A; Bujnicki, Janusz M

2003-07-01

Rigorous assessments of protein structure prediction have demonstrated that fold recognition methods can identify remote similarities between proteins when standard sequence search methods fail. It has been shown that the accuracy of predictions is improved when refined multiple sequence alignments are used instead of single sequences and if different methods are combined to generate a consensus model. There are several meta-servers available that integrate protein structure predictions performed by various methods, but they do not allow for submission of user-defined multiple sequence alignments and they seldom offer confidentiality of the results. We developed a novel WWW gateway for protein structure prediction, which combines the useful features of other meta-servers available, but with much greater flexibility of the input. The user may submit an amino acid sequence or a multiple sequence alignment to a set of methods for primary, secondary and tertiary structure prediction. Fold-recognition results (target-template alignments) are converted into full-atom 3D models and the quality of these models is uniformly assessed. A consensus between different FR methods is also inferred. The results are conveniently presented on-line on a single web page over a secure, password-protected connection. The GeneSilico protein structure prediction meta-server is freely available for academic users at http://genesilico.pl/meta.

GeneSilico protein structure prediction meta-server

PubMed Central

Kurowski, Michal A.; Bujnicki, Janusz M.

2003-01-01

Rigorous assessments of protein structure prediction have demonstrated that fold recognition methods can identify remote similarities between proteins when standard sequence search methods fail. It has been shown that the accuracy of predictions is improved when refined multiple sequence alignments are used instead of single sequences and if different methods are combined to generate a consensus model. There are several meta-servers available that integrate protein structure predictions performed by various methods, but they do not allow for submission of user-defined multiple sequence alignments and they seldom offer confidentiality of the results. We developed a novel WWW gateway for protein structure prediction, which combines the useful features of other meta-servers available, but with much greater flexibility of the input. The user may submit an amino acid sequence or a multiple sequence alignment to a set of methods for primary, secondary and tertiary structure prediction. Fold-recognition results (target-template alignments) are converted into full-atom 3D models and the quality of these models is uniformly assessed. A consensus between different FR methods is also inferred. The results are conveniently presented on-line on a single web page over a secure, password-protected connection. The GeneSilico protein structure prediction meta-server is freely available for academic users at http://genesilico.pl/meta. PMID:12824313

The primary structure of the Saccharomyces cerevisiae gene for 3-phosphoglycerate kinase.

PubMed Central

Hitzeman, R A; Hagie, F E; Hayflick, J S; Chen, C Y; Seeburg, P H; Derynck, R

1982-01-01

The DNA sequence of the gene for the yeast glycolytic enzyme, 3-phosphoglycerate kinase (PGK), has been obtained by sequencing part of a 3.1 kbp HindIII fragment obtained from the yeast genome. The structural gene sequence corresponds to a reading frame of 1251 bp coding for 416 amino acids with no intervening DNA sequences. The amino acid sequence is approximately 65 percent homologous with human and horse PGK protein sequences and is in general agreement with the published protein sequence for yeast PGK. As for other highly expressed structural genes in yeast, the coding sequence is highly codon biased with 95 percent of the amino acids coded for by a select 25 codons (out of 61 possible). Besides structural DNA sequence, 291 bp of 5'-flanking sequence and 286 bp of 3'-flanking sequence were determined. Transcription starts 36 nucleotides upstream from the translational start and stops 86-93 nucleotides downstream from the translational stop. These results suggest a non-polyadenylated mRNA length of 1373 to 1380 nucleotides, which is consistent with the observed length of 1500 nucleotides for polyadenylated PGK mRNA. A sequence TATATATAAA is found at 145 nucleotides upstream from the translational start. This sequence resembles the TATAAA box that is possibly associated with RNA polymerase II binding. Images PMID:6296791

Genome of turbot rhabdovirus exhibits unusual non-coding regions and an additional ORF that could be expressed in fish cell.

PubMed

Zhu, Ruo-Lin; Lei, Xiao-Ying; Ke, Fei; Yuan, Xiu-Ping; Zhang, Qi-Ya

2011-02-01

Genomic sequence of Scophthalmus maximus rhabdovirus (SMRV) isolated from diseased turbot has been characterized. The complete genome of SMRV comprises 11,492 nucleotides and encodes five typical rhabdovirus genes N, P, M, G and L. In addition, two open reading frames (ORF) are predicted overlapping with P gene, one upstream of P and smaller than P (temporarily called Ps), and another in P gene which may encodes a protein similar to the vesicular stomatitis virus C protein. The C ORF is contained within the P ORF. The five typical proteins share the highest sequence identities (48.9%) with the corresponding proteins of rhabdoviruses in genus Vesiculovirus. Phylogenetic analysis of partial L protein sequence indicates that SMRV is close to genus Vesiculovirus. The first 13 nucleotides at the ends of the SMRV genome are absolutely inverse complementarity. The gene junctions between the five genes show conserved polyadenylation signal (CATGA(7)) and intergenic dinucleotide (CT) followed by putative transcription initiation sequence A(A/G)(C/G)A(A/G/T), which are different from known rhabdoviruses. The entire Ps ORF was cloned and expressed, and used to generate polyclonal antibody in mice. One obvious band could be detected in SMRV-infected carp leucocyte cells (CLCs) by anti-Ps/C serum via Western blot, and the subcellular localization of Ps-GFP fusion protein exhibited cytoplasm distribution as multiple punctuate or doughnut shaped foci of uneven size. Copyright © 2010 Elsevier B.V. All rights reserved.

De Novo Assembly of the Donkey White Blood Cell Transcriptome and a Comparative Analysis of Phenotype-Associated Genes between Donkeys and Horses

PubMed Central

Xie, Feng-Yun; Feng, Yu-Long; Wang, Hong-Hui; Ma, Yun-Feng; Yang, Yang; Wang, Yin-Chao; Shen, Wei; Pan, Qing-Jie; Yin, Shen; Sun, Yu-Jiang; Ma, Jun-Yu

2015-01-01

Prior to the mechanization of agriculture and labor-intensive tasks, humans used donkeys (Equus africanus asinus) for farm work and packing. However, as mechanization increased, donkeys have been increasingly raised for meat, milk, and fur in China. To maintain the development of the donkey industry, breeding programs should focus on traits related to these new uses. Compared to conventional marker-assisted breeding plans, genome- and transcriptome-based selection methods are more efficient and effective. To analyze the coding genes of the donkey genome, we assembled the transcriptome of donkey white blood cells de novo. Using transcriptomic deep-sequencing data, we identified 264,714 distinct donkey unigenes and predicted 38,949 protein fragments. We annotated the donkey unigenes by BLAST searches against the non-redundant (NR) protein database. We also compared the donkey protein sequences with those of the horse (E. caballus) and wild horse (E. przewalskii), and linked the donkey protein fragments with mammalian phenotypes. As the outer ear size of donkeys and horses are obviously different, we compared the outer ear size-associated proteins in donkeys and horses. We identified three ear size-associated proteins, HIC1, PRKRA, and KMT2A, with sequence differences among the donkey, horse, and wild horse loci. Since the donkey genome sequence has not been released, the de novo assembled donkey transcriptome is helpful for preliminary investigations of donkey cultivars and for genetic improvement. PMID:26208029

De Novo Assembly of the Donkey White Blood Cell Transcriptome and a Comparative Analysis of Phenotype-Associated Genes between Donkeys and Horses.

PubMed

Xie, Feng-Yun; Feng, Yu-Long; Wang, Hong-Hui; Ma, Yun-Feng; Yang, Yang; Wang, Yin-Chao; Shen, Wei; Pan, Qing-Jie; Yin, Shen; Sun, Yu-Jiang; Ma, Jun-Yu

2015-01-01

Prior to the mechanization of agriculture and labor-intensive tasks, humans used donkeys (Equus africanus asinus) for farm work and packing. However, as mechanization increased, donkeys have been increasingly raised for meat, milk, and fur in China. To maintain the development of the donkey industry, breeding programs should focus on traits related to these new uses. Compared to conventional marker-assisted breeding plans, genome- and transcriptome-based selection methods are more efficient and effective. To analyze the coding genes of the donkey genome, we assembled the transcriptome of donkey white blood cells de novo. Using transcriptomic deep-sequencing data, we identified 264,714 distinct donkey unigenes and predicted 38,949 protein fragments. We annotated the donkey unigenes by BLAST searches against the non-redundant (NR) protein database. We also compared the donkey protein sequences with those of the horse (E. caballus) and wild horse (E. przewalskii), and linked the donkey protein fragments with mammalian phenotypes. As the outer ear size of donkeys and horses are obviously different, we compared the outer ear size-associated proteins in donkeys and horses. We identified three ear size-associated proteins, HIC1, PRKRA, and KMT2A, with sequence differences among the donkey, horse, and wild horse loci. Since the donkey genome sequence has not been released, the de novo assembled donkey transcriptome is helpful for preliminary investigations of donkey cultivars and for genetic improvement.

Closed Genome Sequence of Chryseobacterium piperi Strain CTMT/ATCC BAA-1782, a Gram-Negative Bacterium with Clostridial Neurotoxin-Like Coding Sequences

PubMed Central

Wentz, Travis G.; Muruvanda, Tim; Thirunavukkarasu, Nagarajan; Hoffmann, Maria; Allard, Marc W.; Hodge, David R.; Pillai, Segaran P.; Hammack, Thomas S.; Brown, Eric W.

2017-01-01

ABSTRACT Clostridial neurotoxins, including botulinum and tetanus neurotoxins, are among the deadliest known bacterial toxins. Until recently, the horizontal mobility of this toxin gene family appeared to be limited to the genus Clostridium. We report here the closed genome sequence of Chryseobacterium piperi, a Gram-negative bacterium containing coding sequences with homology to clostridial neurotoxin family proteins. PMID:29192076

The first draft genome of the aquatic model plant Lemna minor opens the route for future stress physiology research and biotechnological applications.

PubMed

Van Hoeck, Arne; Horemans, Nele; Monsieurs, Pieter; Cao, Hieu Xuan; Vandenhove, Hildegarde; Blust, Ronny

2015-01-01

Freshwater duckweed, comprising the smallest, fastest growing and simplest macrophytes has various applications in agriculture, phytoremediation and energy production. Lemna minor, the so-called common duckweed, is a model system of these aquatic plants for ecotoxicological bioassays, genetic transformation tools and industrial applications. Given the ecotoxic relevance and high potential for biomass production, whole-genome information of this cosmopolitan duckweed is needed. The 472 Mbp assembly of the L. minor genome (2n = 40; estimated 481 Mbp; 98.1 %) contains 22,382 protein-coding genes and 61.5 % repetitive sequences. The repeat content explains 94.5 % of the genome size difference in comparison with the greater duckweed, Spirodela polyrhiza (2n = 40; 158 Mbp; 19,623 protein-coding genes; and 15.79 % repetitive sequences). Comparison of proteins from other monocot plants, protein ortholog identification, OrthoMCL, suggests 1356 duckweed-specific groups (3367 proteins, 15.0 % total L. minor proteins) and 795 Lemna-specific groups (2897 proteins, 12.9 % total L. minor proteins). Interestingly, proteins involved in biosynthetic processes in response to various stimuli and hydrolase activities are enriched in the Lemna proteome in comparison with the Spirodela proteome. The genome sequence and annotation of L. minor protein-coding genes provide new insights in biological understanding and biomass production applications of Lemna species.

Palindromic repetitive DNA elements with coding potential in Methanocaldococcus jannaschii.

PubMed

Suyama, Mikita; Lathe, Warren C; Bork, Peer

2005-10-10

We have identified 141 novel palindromic repetitive elements in the genome of euryarchaeon Methanocaldococcus jannaschii. The total length of these elements is 14.3kb, which corresponds to 0.9% of the total genomic sequence and 6.3% of all extragenic regions. The elements can be divided into three groups (MJRE1-3) based on the sequence similarity. The low sequence identity within each of the groups suggests rather old origin of these elements in M. jannaschii. Three MJRE2 elements were located within the protein coding regions without disrupting the coding potential of the host genes, indicating that insertion of repeats might be a widespread mechanism to enhance sequence diversity in coding regions.

CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction.

PubMed

Cui, Xuefeng; Lu, Zhiwu; Wang, Sheng; Jing-Yan Wang, Jim; Gao, Xin

2016-06-15

Protein homology detection, a fundamental problem in computational biology, is an indispensable step toward predicting protein structures and understanding protein functions. Despite the advances in recent decades on sequence alignment, threading and alignment-free methods, protein homology detection remains a challenging open problem. Recently, network methods that try to find transitive paths in the protein structure space demonstrate the importance of incorporating network information of the structure space. Yet, current methods merge the sequence space and the structure space into a single space, and thus introduce inconsistency in combining different sources of information. We present a novel network-based protein homology detection method, CMsearch, based on cross-modal learning. Instead of exploring a single network built from the mixture of sequence and structure space information, CMsearch builds two separate networks to represent the sequence space and the structure space. It then learns sequence-structure correlation by simultaneously taking sequence information, structure information, sequence space information and structure space information into consideration. We tested CMsearch on two challenging tasks, protein homology detection and protein structure prediction, by querying all 8332 PDB40 proteins. Our results demonstrate that CMsearch is insensitive to the similarity metrics used to define the sequence and the structure spaces. By using HMM-HMM alignment as the sequence similarity metric, CMsearch clearly outperforms state-of-the-art homology detection methods and the CASP-winning template-based protein structure prediction methods. Our program is freely available for download from http://sfb.kaust.edu.sa/Pages/Software.aspx : xin.gao@kaust.edu.sa Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Isolation and characterization of a cDNA clone for the complete protein coding region of the delta subunit of the mouse acetylcholine receptor.

PubMed Central

LaPolla, R J; Mayne, K M; Davidson, N

1984-01-01

A mouse cDNA clone has been isolated that contains the complete coding region of a protein highly homologous to the delta subunit of the Torpedo acetylcholine receptor (AcChoR). The cDNA library was constructed in the vector lambda 10 from membrane-associated poly(A)+ RNA from BC3H-1 mouse cells. Surprisingly, the delta clone was selected by hybridization with cDNA encoding the gamma subunit of the Torpedo AcChoR. The nucleotide sequence of the mouse cDNA clone contains an open reading frame of 520 amino acids. This amino acid sequence exhibits 59% and 50% sequence homology to the Torpedo AcChoR delta and gamma subunits, respectively. However, the mouse nucleotide sequence has several stretches of high homology with the Torpedo gamma subunit cDNA, but not with delta. The mouse protein has the same general structural features as do the Torpedo subunits. It is encoded by a 3.3-kilobase mRNA. There is probably only one, but at most two, chromosomal genes coding for this or closely related sequences. Images PMID:6096870

Putative Nonribosomal Peptide Synthetase and Cytochrome P450 Genes Responsible for Tentoxin Biosynthesis in Alternaria alternata ZJ33

PubMed Central

Li, You-Hai; Han, Wen-Jin; Gui, Xi-Wu; Wei, Tao; Tang, Shuang-Yan; Jin, Jian-Ming

2016-01-01

Tentoxin, a cyclic tetrapeptide produced by several Alternaria species, inhibits the F1-ATPase activity of chloroplasts, resulting in chlorosis in sensitive plants. In this study, we report two clustered genes, encoding a putative non-ribosome peptide synthetase (NRPS) TES and a cytochrome P450 protein TES1, that are required for tentoxin biosynthesis in Alternaria alternata strain ZJ33, which was isolated from blighted leaves of Eupatorium adenophorum. Using a pair of primers designed according to the consensus sequences of the adenylation domain of NRPSs, two fragments containing putative adenylation domains were amplified from A. alternata ZJ33, and subsequent PCR analyses demonstrated that these fragments belonged to the same NRPS coding sequence. With no introns, TES consists of a single 15,486 base pair open reading frame encoding a predicted 5161 amino acid protein. Meanwhile, the TES1 gene is predicted to contain five introns and encode a 506 amino acid protein. The TES protein is predicted to be comprised of four peptide synthase modules with two additional N-methylation domains, and the number and arrangement of the modules in TES were consistent with the number and arrangement of the amino acid residues of tentoxin, respectively. Notably, both TES and TES1 null mutants generated via homologous recombination failed to produce tentoxin. This study provides the first evidence concerning the biosynthesis of tentoxin in A. alternata. PMID:27490569

The genome of woodland strawberry (Fragaria vesca)

PubMed Central

Shulaev, Vladimir; Sargent, Daniel J; Crowhurst, Ross N; Mockler, Todd C; Folkerts, Otto; Delcher, Arthur L; Jaiswal, Pankaj; Mockaitis, Keithanne; Liston, Aaron; Mane, Shrinivasrao P; Burns, Paul; Davis, Thomas M; Slovin, Janet P; Bassil, Nahla; Hellens, Roger P; Evans, Clive; Harkins, Tim; Kodira, Chinnappa; Desany, Brian; Crasta, Oswald R; Jensen, Roderick V; Allan, Andrew C; Michael, Todd P; Setubal, Joao Carlos; Celton, Jean-Marc; Rees, D Jasper G; Williams, Kelly P; Holt, Sarah H; Ruiz Rojas, Juan Jairo; Chatterjee, Mithu; Liu, Bo; Silva, Herman; Meisel, Lee; Adato, Avital; Filichkin, Sergei A; Troggio, Michela; Viola, Roberto; Ashman, Tia-Lynn; Wang, Hao; Dharmawardhana, Palitha; Elser, Justin; Raja, Rajani; Priest, Henry D; Bryant, Douglas W; Fox, Samuel E; Givan, Scott A; Wilhelm, Larry J; Naithani, Sushma; Christoffels, Alan; Salama, David Y; Carter, Jade; Girona, Elena Lopez; Zdepski, Anna; Wang, Wenqin; Kerstetter, Randall A; Schwab, Wilfried; Korban, Schuyler S; Davik, Jahn; Monfort, Amparo; Denoyes-Rothan, Beatrice; Arus, Pere; Mittler, Ron; Flinn, Barry; Aharoni, Asaph; Bennetzen, Jeffrey L; Salzberg, Steven L; Dickerman, Allan W; Velasco, Riccardo; Borodovsky, Mark; Veilleux, Richard E; Folta, Kevin M

2012-01-01

The woodland strawberry, Fragaria vesca (2n = 2x = 14), is a versatile experimental plant system. This diminutive herbaceous perennial has a small genome (240 Mb), is amenable to genetic transformation and shares substantial sequence identity with the cultivated strawberry (Fragaria × ananassa) and other economically important rosaceous plants. Here we report the draft F. vesca genome, which was sequenced to ×39 coverage using second-generation technology, assembled de novo and then anchored to the genetic linkage map into seven pseudochromosomes. This diploid strawberry sequence lacks the large genome duplications seen in other rosids. Gene prediction modeling identified 34,809 genes, with most being supported by transcriptome mapping. Genes critical to valuable horticultural traits including flavor, nutritional value and flowering time were identified. Macrosyntenic relationships between Fragaria and Prunus predict a hypothetical ancestral Rosaceae genome that had nine chromosomes. New phylogenetic analysis of 154 protein-coding genes suggests that assignment of Populus to Malvidae, rather than Fabidae, is warranted. PMID:21186353

Integrative structural annotation of de novo RNA-Seq provides an accurate reference gene set of the enormous genome of the onion (Allium cepa L.).

PubMed

Kim, Seungill; Kim, Myung-Shin; Kim, Yong-Min; Yeom, Seon-In; Cheong, Kyeongchae; Kim, Ki-Tae; Jeon, Jongbum; Kim, Sunggil; Kim, Do-Sun; Sohn, Seong-Han; Lee, Yong-Hwan; Choi, Doil

2015-02-01

The onion (Allium cepa L.) is one of the most widely cultivated and consumed vegetable crops in the world. Although a considerable amount of onion transcriptome data has been deposited into public databases, the sequences of the protein-coding genes are not accurate enough to be used, owing to non-coding sequences intermixed with the coding sequences. We generated a high-quality, annotated onion transcriptome from de novo sequence assembly and intensive structural annotation using the integrated structural gene annotation pipeline (ISGAP), which identified 54,165 protein-coding genes among 165,179 assembled transcripts totalling 203.0 Mb by eliminating the intron sequences. ISGAP performed reliable annotation, recognizing accurate gene structures based on reference proteins, and ab initio gene models of the assembled transcripts. Integrative functional annotation and gene-based SNP analysis revealed a whole biological repertoire of genes and transcriptomic variation in the onion. The method developed in this study provides a powerful tool for the construction of reference gene sets for organisms based solely on de novo transcriptome data. Furthermore, the reference genes and their variation described here for the onion represent essential tools for molecular breeding and gene cloning in Allium spp. © The Author 2014. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

Kangaroo – A pattern-matching program for biological sequences

PubMed Central

2002-01-01

Background Biologists are often interested in performing a simple database search to identify proteins or genes that contain a well-defined sequence pattern. Many databases do not provide straightforward or readily available query tools to perform simple searches, such as identifying transcription binding sites, protein motifs, or repetitive DNA sequences. However, in many cases simple pattern-matching searches can reveal a wealth of information. We present in this paper a regular expression pattern-matching tool that was used to identify short repetitive DNA sequences in human coding regions for the purpose of identifying potential mutation sites in mismatch repair deficient cells. Results Kangaroo is a web-based regular expression pattern-matching program that can search for patterns in DNA, protein, or coding region sequences in ten different organisms. The program is implemented to facilitate a wide range of queries with no restriction on the length or complexity of the query expression. The program is accessible on the web at http://bioinfo.mshri.on.ca/kangaroo/ and the source code is freely distributed at http://sourceforge.net/projects/slritools/. Conclusion A low-level simple pattern-matching application can prove to be a useful tool in many research settings. For example, Kangaroo was used to identify potential genetic targets in a human colorectal cancer variant that is characterized by a high frequency of mutations in coding regions containing mononucleotide repeats. PMID:12150718

Programmable DNA-binding proteins from Burkholderia provide a fresh perspective on the TALE-like repeat domain

PubMed Central

de Lange, Orlando; Wolf, Christina; Dietze, Jörn; Elsaesser, Janett; Morbitzer, Robert; Lahaye, Thomas

2014-01-01

The tandem repeats of transcription activator like effectors (TALEs) mediate sequence-specific DNA binding using a simple code. Naturally, TALEs are injected by Xanthomonas bacteria into plant cells to manipulate the host transcriptome. In the laboratory TALE DNA binding domains are reprogrammed and used to target a fused functional domain to a genomic locus of choice. Research into the natural diversity of TALE-like proteins may provide resources for the further improvement of current TALE technology. Here we describe TALE-like proteins from the endosymbiotic bacterium Burkholderia rhizoxinica, termed Bat proteins. Bat repeat domains mediate sequence-specific DNA binding with the same code as TALEs, despite less than 40% sequence identity. We show that Bat proteins can be adapted for use as transcription factors and nucleases and that sequence preferences can be reprogrammed. Unlike TALEs, the core repeats of each Bat protein are highly polymorphic. This feature allowed us to explore alternative strategies for the design of custom Bat repeat arrays, providing novel insights into the functional relevance of non-RVD residues. The Bat proteins offer fertile grounds for research into the creation of improved programmable DNA-binding proteins and comparative insights into TALE-like evolution. PMID:24792163

Prediction of multi-drug resistance transporters using a novel sequence analysis method [version 2; referees: 2 approved

DOE PAGES

McDermott, Jason E.; Bruillard, Paul; Overall, Christopher C.; ...

2015-03-09

There are many examples of groups of proteins that have similar function, but the determinants of functional specificity may be hidden by lack of sequencesimilarity, or by large groups of similar sequences with different functions. Transporters are one such protein group in that the general function, transport, can be easily inferred from the sequence, but the substrate specificity can be impossible to predict from sequence with current methods. In this paper we describe a linguistic-based approach to identify functional patterns from groups of unaligned protein sequences and its application to predict multi-drug resistance transporters (MDRs) from bacteria. We first showmore » that our method can recreate known patterns from PROSITE for several motifs from unaligned sequences. We then show that the method, MDRpred, can predict MDRs with greater accuracy and positive predictive value than a collection of currently available family-based models from the Pfam database. Finally, we apply MDRpred to a large collection of protein sequences from an environmental microbiome study to make novel predictions about drug resistance in a potential environmental reservoir.« less

Experimental and statistical post-validation of positive example EST sequences carrying peroxisome targeting signals type 1 (PTS1)

PubMed Central

Lingner, Thomas; Kataya, Amr R. A.; Reumann, Sigrun

2012-01-01

We recently developed the first algorithms specifically for plants to predict proteins carrying peroxisome targeting signals type 1 (PTS1) from genome sequences.1 As validated experimentally, the prediction methods are able to correctly predict unknown peroxisomal Arabidopsis proteins and to infer novel PTS1 tripeptides. The high prediction performance is primarily determined by the large number and sequence diversity of the underlying positive example sequences, which mainly derived from EST databases. However, a few constructs remained cytosolic in experimental validation studies, indicating sequencing errors in some ESTs. To identify erroneous sequences, we validated subcellular targeting of additional positive example sequences in the present study. Moreover, we analyzed the distribution of prediction scores separately for each orthologous group of PTS1 proteins, which generally resembled normal distributions with group-specific mean values. The cytosolic sequences commonly represented outliers of low prediction scores and were located at the very tail of a fitted normal distribution. Three statistical methods for identifying outliers were compared in terms of sensitivity and specificity.” Their combined application allows elimination of erroneous ESTs from positive example data sets. This new post-validation method will further improve the prediction accuracy of both PTS1 and PTS2 protein prediction models for plants, fungi, and mammals. PMID:22415050

Experimental and statistical post-validation of positive example EST sequences carrying peroxisome targeting signals type 1 (PTS1).

PubMed

Lingner, Thomas; Kataya, Amr R A; Reumann, Sigrun

2012-02-01

We recently developed the first algorithms specifically for plants to predict proteins carrying peroxisome targeting signals type 1 (PTS1) from genome sequences. As validated experimentally, the prediction methods are able to correctly predict unknown peroxisomal Arabidopsis proteins and to infer novel PTS1 tripeptides. The high prediction performance is primarily determined by the large number and sequence diversity of the underlying positive example sequences, which mainly derived from EST databases. However, a few constructs remained cytosolic in experimental validation studies, indicating sequencing errors in some ESTs. To identify erroneous sequences, we validated subcellular targeting of additional positive example sequences in the present study. Moreover, we analyzed the distribution of prediction scores separately for each orthologous group of PTS1 proteins, which generally resembled normal distributions with group-specific mean values. The cytosolic sequences commonly represented outliers of low prediction scores and were located at the very tail of a fitted normal distribution. Three statistical methods for identifying outliers were compared in terms of sensitivity and specificity." Their combined application allows elimination of erroneous ESTs from positive example data sets. This new post-validation method will further improve the prediction accuracy of both PTS1 and PTS2 protein prediction models for plants, fungi, and mammals.

New in protein structure and function annotation: hotspots, single nucleotide polymorphisms and the 'Deep Web'.

PubMed

Bromberg, Yana; Yachdav, Guy; Ofran, Yanay; Schneider, Reinhard; Rost, Burkhard

2009-05-01

The rapidly increasing quantity of protein sequence data continues to widen the gap between available sequences and annotations. Comparative modeling suggests some aspects of the 3D structures of approximately half of all known proteins; homology- and network-based inferences annotate some aspect of function for a similar fraction of the proteome. For most known protein sequences, however, there is detailed knowledge about neither their function nor their structure. Comprehensive efforts towards the expert curation of sequence annotations have failed to meet the demand of the rapidly increasing number of available sequences. Only the automated prediction of protein function in the absence of homology can close the gap between available sequences and annotations in the foreseeable future. This review focuses on two novel methods for automated annotation, and briefly presents an outlook on how modern web software may revolutionize the field of protein sequence annotation. First, predictions of protein binding sites and functional hotspots, and the evolution of these into the most successful type of prediction of protein function from sequence will be discussed. Second, a new tool, comprehensive in silico mutagenesis, which contributes important novel predictions of function and at the same time prepares for the onset of the next sequencing revolution, will be described. While these two new sub-fields of protein prediction represent the breakthroughs that have been achieved methodologically, it will then be argued that a different development might further change the way biomedical researchers benefit from annotations: modern web software can connect the worldwide web in any browser with the 'Deep Web' (ie, proprietary data resources). The availability of this direct connection, and the resulting access to a wealth of data, may impact drug discovery and development more than any existing method that contributes to protein annotation.

Folding and Stabilization of Native-Sequence-Reversed Proteins

PubMed Central

Zhang, Yuanzhao; Weber, Jeffrey K; Zhou, Ruhong

2016-01-01

Though the problem of sequence-reversed protein folding is largely unexplored, one might speculate that reversed native protein sequences should be significantly more foldable than purely random heteropolymer sequences. In this article, we investigate how the reverse-sequences of native proteins might fold by examining a series of small proteins of increasing structural complexity (α-helix, β-hairpin, α-helix bundle, and α/β-protein). Employing a tandem protein structure prediction algorithmic and molecular dynamics simulation approach, we find that the ability of reverse sequences to adopt native-like folds is strongly influenced by protein size and the flexibility of the native hydrophobic core. For β-hairpins with reverse-sequences that fail to fold, we employ a simple mutational strategy for guiding stable hairpin formation that involves the insertion of amino acids into the β-turn region. This systematic look at reverse sequence duality sheds new light on the problem of protein sequence-structure mapping and may serve to inspire new protein design and protein structure prediction protocols. PMID:27113844

Folding and Stabilization of Native-Sequence-Reversed Proteins

NASA Astrophysics Data System (ADS)

Zhang, Yuanzhao; Weber, Jeffrey K.; Zhou, Ruhong

2016-04-01

Though the problem of sequence-reversed protein folding is largely unexplored, one might speculate that reversed native protein sequences should be significantly more foldable than purely random heteropolymer sequences. In this article, we investigate how the reverse-sequences of native proteins might fold by examining a series of small proteins of increasing structural complexity (α-helix, β-hairpin, α-helix bundle, and α/β-protein). Employing a tandem protein structure prediction algorithmic and molecular dynamics simulation approach, we find that the ability of reverse sequences to adopt native-like folds is strongly influenced by protein size and the flexibility of the native hydrophobic core. For β-hairpins with reverse-sequences that fail to fold, we employ a simple mutational strategy for guiding stable hairpin formation that involves the insertion of amino acids into the β-turn region. This systematic look at reverse sequence duality sheds new light on the problem of protein sequence-structure mapping and may serve to inspire new protein design and protein structure prediction protocols.

A protein block based fold recognition method for the annotation of twilight zone sequences.

PubMed

Suresh, V; Ganesan, K; Parthasarathy, S

2013-03-01

The description of protein backbone was recently improved with a group of structural fragments called Structural Alphabets instead of the regular three states (Helix, Sheet and Coil) secondary structure description. Protein Blocks is one of the Structural Alphabets used to describe each and every region of protein backbone including the coil. According to de Brevern (2000) the Protein Blocks has 16 structural fragments and each one has 5 residues in length. Protein Blocks fragments are highly informative among the available Structural Alphabets and it has been used for many applications. Here, we present a protein fold recognition method based on Protein Blocks for the annotation of twilight zone sequences. In our method, we align the predicted Protein Blocks of a query amino acid sequence with a library of assigned Protein Blocks of 953 known folds using the local pair-wise alignment. The alignment results with z-value ≥ 2.5 and P-value ≤ 0.08 are predicted as possible folds. Our method is able to recognize the possible folds for nearly 35.5% of the twilight zone sequences with their predicted Protein Block sequence obtained by pb_prediction, which is available at Protein Block Export server.

A fresh look at the male-specific region of the human Y chromosome.

PubMed

Jangravi, Zohreh; Alikhani, Mehdi; Arefnezhad, Babak; Sharifi Tabar, Mehdi; Taleahmad, Sara; Karamzadeh, Razieh; Jadaliha, Mahdieh; Mousavi, Seyed Ahmad; Ahmadi Rastegar, Diba; Parsamatin, Pouria; Vakilian, Haghighat; Mirshahvaladi, Shahab; Sabbaghian, Marjan; Mohseni Meybodi, Anahita; Mirzaei, Mehdi; Shahhoseini, Maryam; Ebrahimi, Marzieh; Piryaei, Abbas; Moosavi-Movahedi, Ali Akbar; Haynes, Paul A; Goodchild, Ann K; Nasr-Esfahani, Mohammad Hossein; Jabbari, Esmaiel; Baharvand, Hossein; Sedighi Gilani, Mohammad Ali; Gourabi, Hamid; Salekdeh, Ghasem Hosseini

2013-01-04

The Chromosome-centric Human Proteome Project (C-HPP) aims to systematically map the entire human proteome with the intent to enhance our understanding of human biology at the cellular level. This project attempts simultaneously to establish a sound basis for the development of diagnostic, prognostic, therapeutic, and preventive medical applications. In Iran, current efforts focus on mapping the proteome of the human Y chromosome. The male-specific region of the Y chromosome (MSY) is unique in many aspects and comprises 95% of the chromosome's length. The MSY continually retains its haploid state and is full of repeated sequences. It is responsible for important biological roles such as sex determination and male fertility. Here, we present the most recent update of MSY protein-encoding genes and their association with various traits and diseases including sex determination and reversal, spermatogenesis and male infertility, cancers such as prostate cancers, sex-specific effects on the brain and behavior, and graft-versus-host disease. We also present information available from RNA sequencing, protein-protein interaction, post-translational modification of MSY protein-coding genes and their implications in biological systems. An overview of Human Y chromosome Proteome Project is presented and a systematic approach is suggested to ensure that at least one of each predicted protein-coding gene's major representative proteins will be characterized in the context of its major anatomical sites of expression, its abundance, and its functional relevance in a biological and/or medical context. There are many technical and biological issues that will need to be overcome in order to accomplish the full scale mapping.

Nucleotide sequence determination of guinea-pig casein B mRNA reveals homology with bovine and rat alpha s1 caseins and conservation of the non-coding regions of the mRNA.

PubMed Central

Hall, L; Laird, J E; Craig, R K

1984-01-01

Nucleotide sequence analysis of cloned guinea-pig casein B cDNA sequences has identified two casein B variants related to the bovine and rat alpha s1 caseins. Amino acid homology was largely confined to the known bovine or predicted rat phosphorylation sites and within the 'signal' precursor sequence. Comparison of the deduced nucleotide sequence of the guinea-pig and rat alpha s1 casein mRNA species showed greater sequence conservation in the non-coding than in the coding regions, suggesting a functional and possibly regulatory role for the non-coding regions of casein mRNA. The results provide insight into the evolution of the casein genes, and raise questions as to the role of conserved nucleotide sequences within the non-coding regions of mRNA species. Images Fig. 1. PMID:6548375

Distribution of nitrogen fixation and nitrogenase-like sequences amongst microbial genomes

PubMed Central

2012-01-01

Background The metabolic capacity for nitrogen fixation is known to be present in several prokaryotic species scattered across taxonomic groups. Experimental detection of nitrogen fixation in microbes requires species-specific conditions, making it difficult to obtain a comprehensive census of this trait. The recent and rapid increase in the availability of microbial genome sequences affords novel opportunities to re-examine the occurrence and distribution of nitrogen fixation genes. The current practice for computational prediction of nitrogen fixation is to use the presence of the nifH and/or nifD genes. Results Based on a careful comparison of the repertoire of nitrogen fixation genes in known diazotroph species we propose a new criterion for computational prediction of nitrogen fixation: the presence of a minimum set of six genes coding for structural and biosynthetic components, namely NifHDK and NifENB. Using this criterion, we conducted a comprehensive search in fully sequenced genomes and identified 149 diazotrophic species, including 82 known diazotrophs and 67 species not known to fix nitrogen. The taxonomic distribution of nitrogen fixation in Archaea was limited to the Euryarchaeota phylum; within the Bacteria domain we predict that nitrogen fixation occurs in 13 different phyla. Of these, seven phyla had not hitherto been known to contain species capable of nitrogen fixation. Our analyses also identified protein sequences that are similar to nitrogenase in organisms that do not meet the minimum-gene-set criteria. The existence of nitrogenase-like proteins lacking conserved co-factor ligands in both diazotrophs and non-diazotrophs suggests their potential for performing other, as yet unidentified, metabolic functions. Conclusions Our predictions expand the known phylogenetic diversity of nitrogen fixation, and suggest that this trait may be much more common in nature than it is currently thought. The diverse phylogenetic distribution of nitrogenase-like proteins indicates potential new roles for anciently duplicated and divergent members of this group of enzymes. PMID:22554235

Prediction of protein tertiary structure from sequences using a very large back-propagation neural network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, X.; Wilcox, G.L.

1993-12-31

We have implemented large scale back-propagation neural networks on a 544 node Connection Machine, CM-5, using the C language in MIMD mode. The program running on 512 processors performs backpropagation learning at 0.53 Gflops, which provides 76 million connection updates per second. We have applied the network to the prediction of protein tertiary structure from sequence information alone. A neural network with one hidden layer and 40 million connections is trained to learn the relationship between sequence and tertiary structure. The trained network yields predicted structures of some proteins on which it has not been trained given only their sequences.more » Presentation of the Fourier transform of the sequences accentuates periodicity in the sequence and yields good generalization with greatly increased training efficiency. Training simulations with a large, heterologous set of protein structures (111 proteins from CM-5 time) to solutions with under 2% RMS residual error within the training set (random responses give an RMS error of about 20%). Presentation of 15 sequences of related proteins in a testing set of 24 proteins yields predicted structures with less than 8% RMS residual error, indicating good apparent generalization.« less

Cell cycle dependent intracellular distribution of two spliced isoforms of TCP/ILF3 proteins.

PubMed

Xu, You Hai; Leonova, Tatyana; Grabowski, Gregory A

2003-12-01

TCP80 is an approximately 80kDa mammalian cytoplasmic protein that binds to a set of mRNAs and inhibits their translation in vitro and ex vivo. This protein has high sequence similarity to interleukin-2 enhancer-binding factors (NF90/ILF3) and the M-phase phosphoprotein (MPP4)/DRBP76. A 110kDa immunologic isoform of TCP80/NF90/MPP4/DRBP76, termed TCP110, also is present in cytoplasm and nuclei of many types of cells. A cDNA sequence coding for TCP110 was derived by 5(')RACE. The TCP110 sequence is identical to ILF3. The gene coding for TCP110/ILF3 mapped to human chromosome 19 and the gene organization was analyzed using TCP80 and TCP110/ILF3 cDNA sequences. The TCP/ILF3 gene spans >34.8kb and contains 21 exons. At least one alternatively spliced product involving exons 19-21 exists and predicts the formation of either TCP80 or TCP110/ILF3. However, the functional relationships of TCP80 and TCP110/ILF3 required elucidation. The metabolic turnover rates and subcellular distribution of TCP80 and TCP110/ILF3 during the cell cycle showed TCP80 to be relatively stable (t(1/2)=5 days) in the cytoplasmic compartment. In comparison, TCP110/ILF3 migrated between the cytoplasmic and nuclear compartments during the cell cycle. The TCP110 C-terminal segment contains an additional nuclear localizing signal that plays a role in its nuclear translocation. This study indicates that the multiple cellular functions, i.e., translation control, interleukin-2 enhancer binding, or cell division, of TCP/ILF3 are fulfilled by alternatively spliced isoforms.

Identification of a psoriasis susceptibility candidate gene by linkage disequilibrium mapping with a localized single nucleotide polymorphism map.

PubMed

Hewett, Duncan; Samuelsson, Lena; Polding, Joanne; Enlund, Fredrik; Smart, Devi; Cantone, Kathryn; See, Chee Gee; Chadha, Sapna; Inerot, Annica; Enerback, Charlotta; Montgomery, Doug; Christodolou, Chris; Robinson, Phil; Matthews, Paul; Plumpton, Mary; Wahlstrom, Jan; Swanbeck, Gunnar; Martinsson, Tommy; Roses, Allen; Riley, John; Purvis, Ian

2002-03-01

Psoriasis is a chronic inflammatory disease of the skin with both genetic and environmental risk factors. Here we describe the creation of a single-nucleotide polymorphism (SNP) map spanning 900-1200 kb of chromosome 3q21, which had been previously recognized as containing a psoriasis susceptibility locus, PSORS5. We genotyped 644 individuals, from 195 Swedish psoriatic families, for 19 polymorphisms. Linkage disequilibrium (LD) between marker and disease was assessed using the transmission/disequilibrium test (TDT). In the TDT analysis, alleles of three of these SNPs showed significant association with disease (P<0.05). A 160-kb interval encompassing these three SNPs was sequenced, and a coding sequence consisting of 13 exons was identified. The predicted protein shares 30-40% homology with the family of cation/chloride cotransporters. A five-marker haplotype spanning the 3' half of this gene is associated with psoriasis to a P value of 3.8<10(-5). We have called this gene SLC12A8, coding for a member of the solute carrier family 12 proteins. It belongs to a class of genes that were previously unrecognized as playing a role in psoriasis pathogenesis.

TANGLE: Two-Level Support Vector Regression Approach for Protein Backbone Torsion Angle Prediction from Primary Sequences

PubMed Central

Song, Jiangning; Tan, Hao; Wang, Mingjun; Webb, Geoffrey I.; Akutsu, Tatsuya

2012-01-01

Protein backbone torsion angles (Phi) and (Psi) involve two rotation angles rotating around the Cα-N bond (Phi) and the Cα-C bond (Psi). Due to the planarity of the linked rigid peptide bonds, these two angles can essentially determine the backbone geometry of proteins. Accordingly, the accurate prediction of protein backbone torsion angle from sequence information can assist the prediction of protein structures. In this study, we develop a new approach called TANGLE (Torsion ANGLE predictor) to predict the protein backbone torsion angles from amino acid sequences. TANGLE uses a two-level support vector regression approach to perform real-value torsion angle prediction using a variety of features derived from amino acid sequences, including the evolutionary profiles in the form of position-specific scoring matrices, predicted secondary structure, solvent accessibility and natively disordered region as well as other global sequence features. When evaluated based on a large benchmark dataset of 1,526 non-homologous proteins, the mean absolute errors (MAEs) of the Phi and Psi angle prediction are 27.8° and 44.6°, respectively, which are 1% and 3% respectively lower than that using one of the state-of-the-art prediction tools ANGLOR. Moreover, the prediction of TANGLE is significantly better than a random predictor that was built on the amino acid-specific basis, with the p-value<1.46e-147 and 7.97e-150, respectively by the Wilcoxon signed rank test. As a complementary approach to the current torsion angle prediction algorithms, TANGLE should prove useful in predicting protein structural properties and assisting protein fold recognition by applying the predicted torsion angles as useful restraints. TANGLE is freely accessible at http://sunflower.kuicr.kyoto-u.ac.jp/~sjn/TANGLE/. PMID:22319565

FastRNABindR: Fast and Accurate Prediction of Protein-RNA Interface Residues.

PubMed

El-Manzalawy, Yasser; Abbas, Mostafa; Malluhi, Qutaibah; Honavar, Vasant

2016-01-01

A wide range of biological processes, including regulation of gene expression, protein synthesis, and replication and assembly of many viruses are mediated by RNA-protein interactions. However, experimental determination of the structures of protein-RNA complexes is expensive and technically challenging. Hence, a number of computational tools have been developed for predicting protein-RNA interfaces. Some of the state-of-the-art protein-RNA interface predictors rely on position-specific scoring matrix (PSSM)-based encoding of the protein sequences. The computational efforts needed for generating PSSMs severely limits the practical utility of protein-RNA interface prediction servers. In this work, we experiment with two approaches, random sampling and sequence similarity reduction, for extracting a representative reference database of protein sequences from more than 50 million protein sequences in UniRef100. Our results suggest that random sampled databases produce better PSSM profiles (in terms of the number of hits used to generate the profile and the distance of the generated profile to the corresponding profile generated using the entire UniRef100 data as well as the accuracy of the machine learning classifier trained using these profiles). Based on our results, we developed FastRNABindR, an improved version of RNABindR for predicting protein-RNA interface residues using PSSM profiles generated using 1% of the UniRef100 sequences sampled uniformly at random. To the best of our knowledge, FastRNABindR is the only protein-RNA interface residue prediction online server that requires generation of PSSM profiles for query sequences and accepts hundreds of protein sequences per submission. Our approach for determining the optimal BLAST database for a protein-RNA interface residue classification task has the potential of substantially speeding up, and hence increasing the practical utility of, other amino acid sequence based predictors of protein-protein and protein-DNA interfaces.

Mutational analysis of the Wolfram syndrome gene in two families with chromosome 4p-linked bipolar affective disorder.

PubMed

Evans, K L; Lawson, D; Meitinger, T; Blackwood, D H; Porteous, D J

2000-04-03

Bipolar affective disorder (BPAD) is a complex disease with a significant genetic component. Heterozygous carriers of Wolfram syndrome (WFS) are at increased risk of psychiatric illness. A gene for WFS (WFS1) has recently been cloned and mapped to chromosome 4p, in the general region we previously reported as showing linkage to BPAD. Here we present sequence analysis of the WFS1 coding sequence in five affected individuals from two chromosome 4p-linked families. This resulted in the identification of six polymorphisms, two of which are predicted to change the amino acid sequence of the WFS1 protein, however none of the changes segregated with disease status. Am. J. Med. Genet. (Neuropsychiatr. Genet.) 96:158-160, 2000. Copyright 2000 Wiley-Liss, Inc.

Identification of human microRNA targets from isolated argonaute protein complexes.

PubMed

Beitzinger, Michaela; Peters, Lasse; Zhu, Jia Yun; Kremmer, Elisabeth; Meister, Gunter

2007-06-01

MicroRNAs (miRNAs) constitute a class of small non-coding RNAs that regulate gene expression on the level of translation and/or mRNA stability. Mammalian miRNAs associate with members of the Argonaute (Ago) protein family and bind to partially complementary sequences in the 3' untranslated region (UTR) of specific target mRNAs. Computer algorithms based on factors such as free binding energy or sequence conservation have been used to predict miRNA target mRNAs. Based on such predictions, up to one third of all mammalian mRNAs seem to be under miRNA regulation. However, due to the low degree of complementarity between the miRNA and its target, such computer programs are often imprecise and therefore not very reliable. Here we report the first biochemical identification approach of miRNA targets from human cells. Using highly specific monoclonal antibodies against members of the Ago protein family, we co-immunoprecipitate Ago-bound mRNAs and identify them by cloning. Interestingly, most of the identified targets are also predicted by different computer programs. Moreover, we randomly analyzed six different target candidates and were able to experimentally validate five as miRNA targets. Our data clearly indicate that miRNA targets can be experimentally identified from Ago complexes and therefore provide a new tool to directly analyze miRNA function.

Isolation and molecular identification of Sunshine virus, a novel paramyxovirus found in Australian snakes.

PubMed

Hyndman, Timothy H; Marschang, Rachel E; Wellehan, James F X; Nicholls, Philip K

2012-10-01

This paper describes the isolation and molecular identification of a novel paramyxovirus found during an investigation of an outbreak of neurorespiratory disease in a collection of Australian pythons. Using Illumina® high-throughput sequencing, a 17,187 nucleotide sequence was assembled from RNA extracts from infected viper heart cells (VH2) displaying widespread cytopathic effects in the form of multinucleate giant cells. The sequence appears to contain all the coding regions of the genome, including the following predicted paramyxoviral open reading frames (ORFs): 3'--Nucleocapsid (N)--putative Phosphoprotein (P)--Matrix (M)--Fusion (F)--putative attachment protein--Polymerase (L)--5'. There is also a 540 nucleotide ORF between the N and putative P genes that may be an additional coding region. Phylogenetic analyses of the complete N, M, F and L genes support the clustering of this virus within the family Paramyxoviridae but outside both of the current subfamilies: Paramyxovirinae and Pneumovirinae. We propose to name this new virus, Sunshine virus, after the geographic origin of the first isolate--the Sunshine Coast of Queensland, Australia. Copyright © 2012 Elsevier B.V. All rights reserved.

Whole Exome Sequencing Identifies Rare Protein-Coding Variants in Behçet's Disease.

PubMed

Ognenovski, Mikhail; Renauer, Paul; Gensterblum, Elizabeth; Kötter, Ina; Xenitidis, Theodoros; Henes, Jörg C; Casali, Bruno; Salvarani, Carlo; Direskeneli, Haner; Kaufman, Kenneth M; Sawalha, Amr H

2016-05-01

Behçet's disease (BD) is a systemic inflammatory disease with an incompletely understood etiology. Despite the identification of multiple common genetic variants associated with BD, rare genetic variants have been less explored. We undertook this study to investigate the role of rare variants in BD by performing whole exome sequencing in BD patients of European descent. Whole exome sequencing was performed in a discovery set comprising 14 German BD patients of European descent. For replication and validation, Sanger sequencing and Sequenom genotyping were performed in the discovery set and in 2 additional independent sets of 49 German BD patients and 129 Italian BD patients of European descent. Genetic association analysis was then performed in BD patients and 503 controls of European descent. Functional effects of associated genetic variants were assessed using bioinformatic approaches. Using whole exome sequencing, we identified 77 rare variants (in 74 genes) with predicted protein-damaging effects in BD. These variants were genotyped in 2 additional patient sets and then analyzed to reveal significant associations with BD at 2 genetic variants detected in all 3 patient sets that remained significant after Bonferroni correction. We detected genetic association between BD and LIMK2 (rs149034313), involved in regulating cytoskeletal reorganization, and between BD and NEIL1 (rs5745908), involved in base excision DNA repair (P = 3.22 × 10(-4) and P = 5.16 × 10(-4) , respectively). The LIMK2 association is a missense variant with predicted protein damage that may influence functional interactions with proteins involved in cytoskeletal regulation by Rho GTPase, inflammation mediated by chemokine and cytokine signaling pathways, T cell activation, and angiogenesis (Bonferroni-corrected P = 5.63 × 10(-14) , P = 7.29 × 10(-6) , P = 1.15 × 10(-5) , and P = 6.40 × 10(-3) , respectively). The genetic association in NEIL1 is a predicted splice donor variant that may introduce a deleterious intron retention and result in a noncoding transcript variant. We used whole exome sequencing in BD for the first time and identified 2 rare putative protein-damaging genetic variants associated with this disease. These genetic variants might influence cytoskeletal regulation and DNA repair mechanisms in BD and might provide further insight into increased leukocyte tissue infiltration and the role of oxidative stress in BD. © 2016, American College of Rheumatology.

Knowledge-based computational intelligence development for predicting protein secondary structures from sequences.

PubMed

Shen, Hong-Bin; Yi, Dong-Liang; Yao, Li-Xiu; Yang, Jie; Chou, Kuo-Chen

2008-10-01

In the postgenomic age, with the avalanche of protein sequences generated and relatively slow progress in determining their structures by experiments, it is important to develop automated methods to predict the structure of a protein from its sequence. The membrane proteins are a special group in the protein family that accounts for approximately 30% of all proteins; however, solved membrane protein structures only represent less than 1% of known protein structures to date. Although a great success has been achieved for developing computational intelligence techniques to predict secondary structures in both globular and membrane proteins, there is still much challenging work in this regard. In this review article, we firstly summarize the recent progress of automation methodology development in predicting protein secondary structures, especially in membrane proteins; we will then give some future directions in this research field.

cncRNAs: Bi-functional RNAs with protein coding and non-coding functions

PubMed Central

Kumari, Pooja; Sampath, Karuna

2015-01-01

For many decades, the major function of mRNA was thought to be to provide protein-coding information embedded in the genome. The advent of high-throughput sequencing has led to the discovery of pervasive transcription of eukaryotic genomes and opened the world of RNA-mediated gene regulation. Many regulatory RNAs have been found to be incapable of protein coding and are hence termed as non-coding RNAs (ncRNAs). However, studies in recent years have shown that several previously annotated non-coding RNAs have the potential to encode proteins, and conversely, some coding RNAs have regulatory functions independent of the protein they encode. Such bi-functional RNAs, with both protein coding and non-coding functions, which we term as ‘cncRNAs’, have emerged as new players in cellular systems. Here, we describe the functions of some cncRNAs identified from bacteria to humans. Because the functions of many RNAs across genomes remains unclear, we propose that RNAs be classified as coding, non-coding or both only after careful analysis of their functions. PMID:26498036

Genomic analysis suggests that mRNA destabilization by the microprocessor is specialized for the auto-regulation of Dgcr8.

PubMed

Shenoy, Archana; Blelloch, Robert

2009-09-11

The Microprocessor, containing the RNA binding protein Dgcr8 and RNase III enzyme Drosha, is responsible for processing primary microRNAs to precursor microRNAs. The Microprocessor regulates its own levels by cleaving hairpins in the 5'UTR and coding region of the Dgcr8 mRNA, thereby destabilizing the mature transcript. To determine whether the Microprocessor has a broader role in directly regulating other coding mRNA levels, we integrated results from expression profiling and ultra high-throughput deep sequencing of small RNAs. Expression analysis of mRNAs in wild-type, Dgcr8 knockout, and Dicer knockout mouse embryonic stem (ES) cells uncovered mRNAs that were specifically upregulated in the Dgcr8 null background. A number of these transcripts had evolutionarily conserved predicted hairpin targets for the Microprocessor. However, analysis of deep sequencing data of 18 to 200nt small RNAs in mouse ES, HeLa, and HepG2 indicates that exonic sequence reads that map in a pattern consistent with Microprocessor activity are unique to Dgcr8. We conclude that the Microprocessor's role in directly destabilizing coding mRNAs is likely specifically targeted to Dgcr8 itself, suggesting a specialized cellular mechanism for gene auto-regulation.

The solution structure of the pentatricopeptide repeat protein PPR10 upon binding atpH RNA

PubMed Central

Gully, Benjamin S.; Cowieson, Nathan; Stanley, Will A.; Shearston, Kate; Small, Ian D.; Barkan, Alice; Bond, Charles S.

2015-01-01

The pentatricopeptide repeat (PPR) protein family is a large family of RNA-binding proteins that is characterized by tandem arrays of a degenerate 35-amino-acid motif which form an α-solenoid structure. PPR proteins influence the editing, splicing, translation and stability of specific RNAs in mitochondria and chloroplasts. Zea mays PPR10 is amongst the best studied PPR proteins, where sequence-specific binding to two RNA transcripts, atpH and psaJ, has been demonstrated to follow a recognition code where the identity of two amino acids per repeat determines the base-specificity. A recently solved ZmPPR10:psaJ complex crystal structure suggested a homodimeric complex with considerably fewer sequence-specific protein–RNA contacts than inferred previously. Here we describe the solution structure of the ZmPPR10:atpH complex using size-exclusion chromatography-coupled synchrotron small-angle X-ray scattering (SEC-SY-SAXS). Our results support prior evidence that PPR10 binds RNA as a monomer, and that it does so in a manner that is commensurate with a canonical and predictable RNA-binding mode across much of the RNA–protein interface. PMID:25609698

Analysis of cellulose synthase genes from domesticated apple identifies collinear genes WDR53 and CesA8A: partial co-expression, bicistronic mRNA, and alternative splicing of CESA8A

PubMed Central

Guerriero, Gea; Spadiut, Oliver; Kerschbamer, Christine; Giorno, Filomena; Baric, Sanja; Ezcurra, Inés

2016-01-01

Cellulose synthase (CesA) genes constitute a complex multigene family with six major phylogenetic clades in angiosperms. The recently sequenced genome of domestic apple, Malus×domestica, was mined for CesA genes, by blasting full-length cellulose synthase protein (CESA) sequences annotated in the apple genome against protein databases from the plant models Arabidopsis thaliana and Populus trichocarpa. Thirteen genes belonging to the six angiosperm CesA clades and coding for proteins with conserved residues typical of processive glycosyltransferases from family 2 were detected. Based on their phylogenetic relationship to Arabidopsis CESAs, as well as expression patterns, a nomenclature is proposed to facilitate further studies. Examination of their genomic organization revealed that MdCesA8-A is closely linked and co-oriented with WDR53, a gene coding for a WD40 repeat protein. The WDR53 and CesA8 genes display conserved collinearity in dicots and are partially co-expressed in the apple xylem. Interestingly, the presence of a bicistronic WDR53–CesA8A transcript was detected in phytoplasma-infected phloem tissues of apple. The bicistronic transcript contains a spliced intergenic sequence that is predicted to fold into hairpin structures typical of internal ribosome entry sites, suggesting its potential cap-independent translation. Surprisingly, the CesA8A cistron is alternatively spliced and lacks the zinc-binding domain. The possible roles of WDR53 and the alternatively spliced CESA8 variant during cellulose biosynthesis in M.×domestica are discussed. PMID:23048131

Molecular cloning of chitinase 33 (chit33) gene from Trichoderma atroviride

PubMed Central

Matroudi, S.; Zamani, M.R.; Motallebi, M.

2008-01-01

In this study Trichoderma atroviride was selected as over producer of chitinase enzyme among 30 different isolates of Trichoderma sp. on the basis of chitinase specific activity. From this isolate the genomic and cDNA clones encoding chit33 have been isolated and sequenced. Comparison of genomic and cDNA sequences for defining gene structure indicates that this gene contains three short introns and also an open reading frame coding for a protein of 321 amino acids. The deduced amino acid sequence includes a 19 aa putative signal peptide. Homology between this sequence and other reported Trichoderma Chit33 proteins are discussed. The coding sequence of chit33 gene was cloned in pEt26b(+) expression vector and expressed in E. coli. PMID:24031242

PredictProtein—an open resource for online prediction of protein structural and functional features

PubMed Central

Yachdav, Guy; Kloppmann, Edda; Kajan, Laszlo; Hecht, Maximilian; Goldberg, Tatyana; Hamp, Tobias; Hönigschmid, Peter; Schafferhans, Andrea; Roos, Manfred; Bernhofer, Michael; Richter, Lothar; Ashkenazy, Haim; Punta, Marco; Schlessinger, Avner; Bromberg, Yana; Schneider, Reinhard; Vriend, Gerrit; Sander, Chris; Ben-Tal, Nir; Rost, Burkhard

2014-01-01

PredictProtein is a meta-service for sequence analysis that has been predicting structural and functional features of proteins since 1992. Queried with a protein sequence it returns: multiple sequence alignments, predicted aspects of structure (secondary structure, solvent accessibility, transmembrane helices (TMSEG) and strands, coiled-coil regions, disulfide bonds and disordered regions) and function. The service incorporates analysis methods for the identification of functional regions (ConSurf), homology-based inference of Gene Ontology terms (metastudent), comprehensive subcellular localization prediction (LocTree3), protein–protein binding sites (ISIS2), protein–polynucleotide binding sites (SomeNA) and predictions of the effect of point mutations (non-synonymous SNPs) on protein function (SNAP2). Our goal has always been to develop a system optimized to meet the demands of experimentalists not highly experienced in bioinformatics. To this end, the PredictProtein results are presented as both text and a series of intuitive, interactive and visually appealing figures. The web server and sources are available at http://ppopen.rostlab.org. PMID:24799431

Predicting Protein-Protein Interaction Sites with a Novel Membership Based Fuzzy SVM Classifier.

PubMed

Sriwastava, Brijesh K; Basu, Subhadip; Maulik, Ujjwal

2015-01-01

Predicting residues that participate in protein-protein interactions (PPI) helps to identify, which amino acids are located at the interface. In this paper, we show that the performance of the classical support vector machine (SVM) algorithm can further be improved with the use of a custom-designed fuzzy membership function, for the partner-specific PPI interface prediction problem. We evaluated the performances of both classical SVM and fuzzy SVM (F-SVM) on the PPI databases of three different model proteomes of Homo sapiens, Escherichia coli and Saccharomyces Cerevisiae and calculated the statistical significance of the developed F-SVM over classical SVM algorithm. We also compared our performance with the available state-of-the-art fuzzy methods in this domain and observed significant performance improvements. To predict interaction sites in protein complexes, local composition of amino acids together with their physico-chemical characteristics are used, where the F-SVM based prediction method exploits the membership function for each pair of sequence fragments. The average F-SVM performance (area under ROC curve) on the test samples in 10-fold cross validation experiment are measured as 77.07, 78.39, and 74.91 percent for the aforementioned organisms respectively. Performances on independent test sets are obtained as 72.09, 73.24 and 82.74 percent respectively. The software is available for free download from http://code.google.com/p/cmater-bioinfo.

Complete chloroplast genome sequence of common bermudagrass (Cynodon dactylon (L.) Pers.) and comparative analysis within the family Poaceae

PubMed Central

Huang, Ya-Yi; Cho, Shu-Ting; Haryono, Mindia; Kuo, Chih-Horng

2017-01-01

Common bermudagrass (Cynodon dactylon (L.) Pers.) belongs to the subfamily Chloridoideae of the Poaceae family, one of the most important plant families ecologically and economically. This grass has a long connection with human culture but its systematics is relatively understudied. In this study, we sequenced and investigated the chloroplast genome of common bermudagrass, which is 134,297 bp in length with two single copy regions (LSC: 79,732 bp; SSC: 12,521 bp) and a pair of inverted repeat (IR) regions (21,022 bp). The annotation contains a total of 128 predicted genes, including 82 protein-coding, 38 tRNA, and 8 rRNA genes. Additionally, our in silico analyses identified 10 sets of repeats longer than 20 bp and predicted the presence of 36 RNA editing sites. Overall, the chloroplast genome of common bermudagrass resembles those from other Poaceae lineages. Compared to most angiosperms, the accD gene and the introns of both clpP and rpoC1 genes are missing. Additionally, the ycf1, ycf2, ycf15, and ycf68 genes are pseudogenized and two genome rearrangements exist. Our phylogenetic analysis based on 47 chloroplast protein-coding genes supported the placement of common bermudagrass within Chloridoideae. Our phylogenetic character mapping based on the parsimony principle further indicated that the loss of the accD gene and clpP introns, the pseudogenization of four ycf genes, and the two rearrangements occurred only once after the most recent common ancestor of the Poaceae diverged from other monocots, which could explain the unusual long branch leading to the Poaceae when phylogeny is inferred based on chloroplast sequences. PMID:28617867

Complete chloroplast genome sequence of common bermudagrass (Cynodon dactylon (L.) Pers.) and comparative analysis within the family Poaceae.

PubMed

Huang, Ya-Yi; Cho, Shu-Ting; Haryono, Mindia; Kuo, Chih-Horng

2017-01-01

Common bermudagrass (Cynodon dactylon (L.) Pers.) belongs to the subfamily Chloridoideae of the Poaceae family, one of the most important plant families ecologically and economically. This grass has a long connection with human culture but its systematics is relatively understudied. In this study, we sequenced and investigated the chloroplast genome of common bermudagrass, which is 134,297 bp in length with two single copy regions (LSC: 79,732 bp; SSC: 12,521 bp) and a pair of inverted repeat (IR) regions (21,022 bp). The annotation contains a total of 128 predicted genes, including 82 protein-coding, 38 tRNA, and 8 rRNA genes. Additionally, our in silico analyses identified 10 sets of repeats longer than 20 bp and predicted the presence of 36 RNA editing sites. Overall, the chloroplast genome of common bermudagrass resembles those from other Poaceae lineages. Compared to most angiosperms, the accD gene and the introns of both clpP and rpoC1 genes are missing. Additionally, the ycf1, ycf2, ycf15, and ycf68 genes are pseudogenized and two genome rearrangements exist. Our phylogenetic analysis based on 47 chloroplast protein-coding genes supported the placement of common bermudagrass within Chloridoideae. Our phylogenetic character mapping based on the parsimony principle further indicated that the loss of the accD gene and clpP introns, the pseudogenization of four ycf genes, and the two rearrangements occurred only once after the most recent common ancestor of the Poaceae diverged from other monocots, which could explain the unusual long branch leading to the Poaceae when phylogeny is inferred based on chloroplast sequences.

Kinetic models of gene expression including non-coding RNAs

NASA Astrophysics Data System (ADS)

Zhdanov, Vladimir P.

2011-03-01

In cells, genes are transcribed into mRNAs, and the latter are translated into proteins. Due to the feedbacks between these processes, the kinetics of gene expression may be complex even in the simplest genetic networks. The corresponding models have already been reviewed in the literature. A new avenue in this field is related to the recognition that the conventional scenario of gene expression is fully applicable only to prokaryotes whose genomes consist of tightly packed protein-coding sequences. In eukaryotic cells, in contrast, such sequences are relatively rare, and the rest of the genome includes numerous transcript units representing non-coding RNAs (ncRNAs). During the past decade, it has become clear that such RNAs play a crucial role in gene expression and accordingly influence a multitude of cellular processes both in the normal state and during diseases. The numerous biological functions of ncRNAs are based primarily on their abilities to silence genes via pairing with a target mRNA and subsequently preventing its translation or facilitating degradation of the mRNA-ncRNA complex. Many other abilities of ncRNAs have been discovered as well. Our review is focused on the available kinetic models describing the mRNA, ncRNA and protein interplay. In particular, we systematically present the simplest models without kinetic feedbacks, models containing feedbacks and predicting bistability and oscillations in simple genetic networks, and models describing the effect of ncRNAs on complex genetic networks. Mathematically, the presentation is based primarily on temporal mean-field kinetic equations. The stochastic and spatio-temporal effects are also briefly discussed.

@TOME-2: a new pipeline for comparative modeling of protein–ligand complexes

PubMed Central

Pons, Jean-Luc; Labesse, Gilles

2009-01-01

@TOME 2.0 is new web pipeline dedicated to protein structure modeling and small ligand docking based on comparative analyses. @TOME 2.0 allows fold recognition, template selection, structural alignment editing, structure comparisons, 3D-model building and evaluation. These tasks are routinely used in sequence analyses for structure prediction. In our pipeline the necessary software is efficiently interconnected in an original manner to accelerate all the processes. Furthermore, we have also connected comparative docking of small ligands that is performed using protein–protein superposition. The input is a simple protein sequence in one-letter code with no comment. The resulting 3D model, protein–ligand complexes and structural alignments can be visualized through dedicated Web interfaces or can be downloaded for further studies. These original features will aid in the functional annotation of proteins and the selection of templates for molecular modeling and virtual screening. Several examples are described to highlight some of the new functionalities provided by this pipeline. The server and its documentation are freely available at http://abcis.cbs.cnrs.fr/AT2/ PMID:19443448

P-class pentatricopeptide repeat proteins are required for efficient 5′ end formation of plant mitochondrial transcripts

PubMed Central

Binder, Stefan; Stoll, Katrin; Stoll, Birgit

2013-01-01

It is well recognized that flowering plants maintain a particularly broad spectrum of factors to support gene expression in mitochondria. Many of these factors are pentatricopeptide repeat (PPR) proteins that participate in virtually all processes dealing with RNA. One of these processes is the post-transcriptional generation of mature 5′ termini of RNA. Several PPR proteins are required for efficient 5′ maturation of mitochondrial mRNA and rRNA. These so-called RNA PROCESSING FACTORs (RPF) exclusively represent P-class PPR proteins, mainly composed of canonical PPR motifs without any extra domains. Applying the recent PPR-nucleotide recognition code, binding sites of RPF are predicted on the 5′ leader sequences. The sequence-specific interaction of an RPF with one or a few RNA substrates probably directly or indirectly recruits an as-yet-unidentified endonuclease to the processing site(s). The identification and characterization of RPF is a major step toward the understanding of the role of 5′ end maturation in flowering plant mitochondria. PMID:24184847

Genomics of Clostridium taeniosporum, an organism which forms endospores with ribbon-like appendages

PubMed Central

Cambridge, Joshua M.; Blinkova, Alexandra L.; Salvador Rocha, Erick I.; Bode Hernández, Addys; Moreno, Maday; Ginés-Candelaria, Edwin; Goetz, Benjamin M.; Hunicke-Smith, Scott; Satterwhite, Ed; Tucker, Haley O.

2018-01-01

Clostridium taeniosporum, a non-pathogenic anaerobe closely related to the C. botulinum Group II members, was isolated from Crimean lake silt about 60 years ago. Its endospores are surrounded by an encasement layer which forms a trunk at one spore pole to which about 12–14 large, ribbon-like appendages are attached. The genome consists of one 3,264,813 bp, circular chromosome (with 26.6% GC) and three plasmids. The chromosome contains 2,892 potential protein coding sequences: 2,124 have specific functions, 147 have general functions, 228 are conserved but without known function and 393 are hypothetical based on the fact that no statistically significant orthologs were found. The chromosome also contains 101 genes for stable RNAs, including 7 rRNA clusters. Over 84% of the protein coding sequences and 96% of the stable RNA coding regions are oriented in the same direction as replication. The three known appendage genes are located within a single cluster with five other genes, the protein products of which are closely related, in terms of sequence, to the known appendage proteins. The relatedness of the deduced protein products suggests that all or some of the closely related genes might code for minor appendage proteins or assembly factors. The appendage genes might be unique among the known clostridia; no statistically significant orthologs were found within other clostridial genomes for which sequence data are available. The C. taeniosporum chromosome contains two functional prophages, one Siphoviridae and one Myoviridae, and one defective prophage. Three plasmids of 5.9, 69.7 and 163.1 Kbp are present. These data are expected to contribute to future studies of developmental, structural and evolutionary biology and to potential industrial applications of this organism. PMID:29293521

Genomics of Clostridium taeniosporum, an organism which forms endospores with ribbon-like appendages.

PubMed

Cambridge, Joshua M; Blinkova, Alexandra L; Salvador Rocha, Erick I; Bode Hernández, Addys; Moreno, Maday; Ginés-Candelaria, Edwin; Goetz, Benjamin M; Hunicke-Smith, Scott; Satterwhite, Ed; Tucker, Haley O; Walker, James R

2018-01-01

Clostridium taeniosporum, a non-pathogenic anaerobe closely related to the C. botulinum Group II members, was isolated from Crimean lake silt about 60 years ago. Its endospores are surrounded by an encasement layer which forms a trunk at one spore pole to which about 12-14 large, ribbon-like appendages are attached. The genome consists of one 3,264,813 bp, circular chromosome (with 26.6% GC) and three plasmids. The chromosome contains 2,892 potential protein coding sequences: 2,124 have specific functions, 147 have general functions, 228 are conserved but without known function and 393 are hypothetical based on the fact that no statistically significant orthologs were found. The chromosome also contains 101 genes for stable RNAs, including 7 rRNA clusters. Over 84% of the protein coding sequences and 96% of the stable RNA coding regions are oriented in the same direction as replication. The three known appendage genes are located within a single cluster with five other genes, the protein products of which are closely related, in terms of sequence, to the known appendage proteins. The relatedness of the deduced protein products suggests that all or some of the closely related genes might code for minor appendage proteins or assembly factors. The appendage genes might be unique among the known clostridia; no statistically significant orthologs were found within other clostridial genomes for which sequence data are available. The C. taeniosporum chromosome contains two functional prophages, one Siphoviridae and one Myoviridae, and one defective prophage. Three plasmids of 5.9, 69.7 and 163.1 Kbp are present. These data are expected to contribute to future studies of developmental, structural and evolutionary biology and to potential industrial applications of this organism.

Involvement of Two Latex-Clearing Proteins during Rubber Degradation and Insights into the Subsequent Degradation Pathway Revealed by the Genome Sequence of Gordonia polyisoprenivorans Strain VH2

PubMed Central

Hiessl, Sebastian; Schuldes, Jörg; Thürmer, Andrea; Halbsguth, Tobias; Bröker, Daniel; Angelov, Angel; Liebl, Wolfgang; Daniel, Rolf

2012-01-01

The increasing production of synthetic and natural poly(cis-1,4-isoprene) rubber leads to huge challenges in waste management. Only a few bacteria are known to degrade rubber, and little is known about the mechanism of microbial rubber degradation. The genome of Gordonia polyisoprenivorans strain VH2, which is one of the most effective rubber-degrading bacteria, was sequenced and annotated to elucidate the degradation pathway and other features of this actinomycete. The genome consists of a circular chromosome of 5,669,805 bp and a circular plasmid of 174,494 bp with average GC contents of 67.0% and 65.7%, respectively. It contains 5,110 putative protein-coding sequences, including many candidate genes responsible for rubber degradation and other biotechnically relevant pathways. Furthermore, we detected two homologues of a latex-clearing protein, which is supposed to be a key enzyme in rubber degradation. The deletion of these two genes for the first time revealed clear evidence that latex-clearing protein is essential for the microbial utilization of rubber. Based on the genome sequence, we predict a pathway for the microbial degradation of rubber which is supported by previous and current data on transposon mutagenesis, deletion mutants, applied comparative genomics, and literature search. PMID:22327575

EUGÈNE'HOM: a generic similarity-based gene finder using multiple homologous sequences

PubMed Central

Foissac, Sylvain; Bardou, Philippe; Moisan, Annick; Cros, Marie-Josée; Schiex, Thomas

2003-01-01

EUGÈNE'HOM is a gene prediction software for eukaryotic organisms based on comparative analysis. EUGÈNE'HOM is able to take into account multiple homologous sequences from more or less closely related organisms. It integrates the results of TBLASTX analysis, splice site and start codon prediction and a robust coding/non-coding probabilistic model which allows EUGÈNE'HOM to handle sequences from a variety of organisms. The current target of EUGÈNE'HOM is plant sequences. The EUGÈNE'HOM web site is available at http://genopole.toulouse.inra.fr/bioinfo/eugene/EuGeneHom/cgi-bin/EuGeneHom.pl. PMID:12824408

Genome sequencing of the lizard parasite Leishmania tarentolae reveals loss of genes associated to the intracellular stage of human pathogenic species

PubMed Central

Raymond, Frédéric; Boisvert, Sébastien; Roy, Gaétan; Ritt, Jean-François; Légaré, Danielle; Isnard, Amandine; Stanke, Mario; Olivier, Martin; Tremblay, Michel J.; Papadopoulou, Barbara; Ouellette, Marc; Corbeil, Jacques

2012-01-01

The Leishmania tarentolae Parrot-TarII strain genome sequence was resolved to an average 16-fold mean coverage by next-generation DNA sequencing technologies. This is the first non-pathogenic to humans kinetoplastid protozoan genome to be described thus providing an opportunity for comparison with the completed genomes of pathogenic Leishmania species. A high synteny was observed between all sequenced Leishmania species. A limited number of chromosomal regions diverged between L. tarentolae and L. infantum, while remaining syntenic to L. major. Globally, >90% of the L. tarentolae gene content was shared with the other Leishmania species. We identified 95 predicted coding sequences unique to L. tarentolae and 250 genes that were absent from L. tarentolae. Interestingly, many of the latter genes were expressed in the intracellular amastigote stage of pathogenic species. In addition, genes coding for products involved in antioxidant defence or participating in vesicular-mediated protein transport were underrepresented in L. tarentolae. In contrast to other Leishmania genomes, two gene families were expanded in L. tarentolae, namely the zinc metallo-peptidase surface glycoprotein GP63 and the promastigote surface antigen PSA31C. Overall, L. tarentolae's gene content appears better adapted to the promastigote insect stage rather than the amastigote mammalian stage. PMID:21998295

Predicting highly-connected hubs in protein interaction networks by QSAR and biological data descriptors

PubMed Central

Hsing, Michael; Byler, Kendall; Cherkasov, Artem

2009-01-01

Hub proteins (those engaged in most physical interactions in a protein interaction network (PIN) have recently gained much research interest due to their essential role in mediating cellular processes and their potential therapeutic value. It is straightforward to identify hubs if the underlying PIN is experimentally determined; however, theoretical hub prediction remains a very challenging task, as physicochemical properties that differentiate hubs from less connected proteins remain mostly uncharacterized. To adequately distinguish hubs from non-hub proteins we have utilized over 1300 protein descriptors, some of which represent QSAR (quantitative structure-activity relationship) parameters, and some reflect sequence-derived characteristics of proteins including domain composition and functional annotations. Those protein descriptors, together with available protein interaction data have been processed by a machine learning method (boosting trees) and resulted in the development of hub classifiers that are capable of predicting highly interacting proteins for four model organisms: Escherichia coli, Saccharomyces cerevisiae, Drosophila melanogaster and Homo sapiens. More importantly, through the analyses of the most relevant protein descriptors, we are able to demonstrate that hub proteins not only share certain common physicochemical and structural characteristics that make them different from non-hub counterparts, but they also exhibit species-specific characteristics that should be taken into account when analyzing different PINs. The developed prediction models can be used for determining highly interacting proteins in the four studied species to assist future proteomics experiments and PIN analyses. Availability The source code and executable program of the hub classifier are available for download at: http://www.cnbi2.ca/hub-analysis/ PMID:20198194

High-quality draft genome sequence of the Thermus amyloliquefaciens type strain YIM 77409 T with an incomplete denitrification pathway

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, En -Min; Murugapiran, Senthil K.; Mefferd, Chrisabelle C.

Thermus amyloliquefaciens type strain YIM 77409 T is a thermophilic, Gram-negative, non-motile and rod-shaped bacterium isolated from Niujie Hot Spring in Eryuan County, Yunnan Province, southwest China. In the present study we describe the features of strain YIM 77409 T together with its genome sequence and annotation. The genome is 2,160,855 bp long and consists of 6 scaffolds with 67.4 % average GC content. A total of 2,313 genes were predicted, comprising 2,257 protein-coding and 56 RNA genes. The genome is predicted to encode a complete glycolysis, pentose phosphate pathway, and tricarboxylic acid cycle. Additionally, a large number of transportersmore » and enzymes for heterotrophy highlight the broad heterotrophic lifestyle of this organism. Furthermore, a denitrification gene cluster included genes predicted to encode enzymes for the sequential reduction of nitrate to nitrous oxide, consistent with the incomplete denitrification phenotype of this strain.« less

High-quality draft genome sequence of the Thermus amyloliquefaciens type strain YIM 77409 T with an incomplete denitrification pathway

DOE PAGES

Zhou, En -Min; Murugapiran, Senthil K.; Mefferd, Chrisabelle C.; ...

2016-02-27

Thermus amyloliquefaciens type strain YIM 77409 T is a thermophilic, Gram-negative, non-motile and rod-shaped bacterium isolated from Niujie Hot Spring in Eryuan County, Yunnan Province, southwest China. In the present study we describe the features of strain YIM 77409 T together with its genome sequence and annotation. The genome is 2,160,855 bp long and consists of 6 scaffolds with 67.4 % average GC content. A total of 2,313 genes were predicted, comprising 2,257 protein-coding and 56 RNA genes. The genome is predicted to encode a complete glycolysis, pentose phosphate pathway, and tricarboxylic acid cycle. Additionally, a large number of transportersmore » and enzymes for heterotrophy highlight the broad heterotrophic lifestyle of this organism. Furthermore, a denitrification gene cluster included genes predicted to encode enzymes for the sequential reduction of nitrate to nitrous oxide, consistent with the incomplete denitrification phenotype of this strain.« less

ICAM-1-related long non-coding RNA: promoter analysis and expression in human retinal endothelial cells.

PubMed

Lumsden, Amanda L; Ma, Yuefang; Ashander, Liam M; Stempel, Andrew J; Keating, Damien J; Smith, Justine R; Appukuttan, Binoy

2018-05-09

Regulation of intercellular adhesion molecule (ICAM)-1 in retinal endothelial cells is a promising druggable target for retinal vascular diseases. The ICAM-1-related (ICR) long non-coding RNA stabilizes ICAM-1 transcript, increasing protein expression. However, studies of ICR involvement in disease have been limited as the promoter is uncharacterized. To address this issue, we undertook a comprehensive in silico analysis of the human ICR gene promoter region. We used genomic evolutionary rate profiling to identify a 115 base pair (bp) sequence within 500 bp upstream of the transcription start site of the annotated human ICR gene that was conserved across 25 eutherian genomes. A second constrained sequence upstream of the orthologous mouse gene (68 bp; conserved across 27 Eutherian genomes including human) was also discovered. Searching these elements identified 33 matrices predictive of binding sites for transcription factors known to be responsive to a broad range of pathological stimuli, including hypoxia, and metabolic and inflammatory proteins. Five phenotype-associated single nucleotide polymorphisms (SNPs) in the immediate vicinity of these elements included four SNPs (i.e. rs2569693, rs281439, rs281440 and rs11575074) predicted to impact binding motifs of transcription factors, and thus the expression of ICR and ICAM-1 genes, with potential to influence disease susceptibility. We verified that human retinal endothelial cells expressed ICR, and observed induction of expression by tumor necrosis factor-α.

Nucleic and Amino Acid Sequences Support Structure-Based Viral Classification.

PubMed

Sinclair, Robert M; Ravantti, Janne J; Bamford, Dennis H

2017-04-15

Viral capsids ensure viral genome integrity by protecting the enclosed nucleic acids. Interactions between the genome and capsid and between individual capsid proteins (i.e., capsid architecture) are intimate and are expected to be characterized by strong evolutionary conservation. For this reason, a capsid structure-based viral classification has been proposed as a way to bring order to the viral universe. The seeming lack of sufficient sequence similarity to reproduce this classification has made it difficult to reject structural convergence as the basis for the classification. We reinvestigate whether the structure-based classification for viral coat proteins making icosahedral virus capsids is in fact supported by previously undetected sequence similarity. Since codon choices can influence nascent protein folding cotranslationally, we searched for both amino acid and nucleotide sequence similarity. To demonstrate the sensitivity of the approach, we identify a candidate gene for the pandoravirus capsid protein. We show that the structure-based classification is strongly supported by amino acid and also nucleotide sequence similarities, suggesting that the similarities are due to common descent. The correspondence between structure-based and sequence-based analyses of the same proteins shown here allow them to be used in future analyses of the relationship between linear sequence information and macromolecular function, as well as between linear sequence and protein folds. IMPORTANCE Viral capsids protect nucleic acid genomes, which in turn encode capsid proteins. This tight coupling of protein shell and nucleic acids, together with strong functional constraints on capsid protein folding and architecture, leads to the hypothesis that capsid protein-coding nucleotide sequences may retain signatures of ancient viral evolution. We have been able to show that this is indeed the case, using the major capsid proteins of viruses forming icosahedral capsids. Importantly, we detected similarity at the nucleotide level between capsid protein-coding regions from viruses infecting cells belonging to all three domains of life, reproducing a previously established structure-based classification of icosahedral viral capsids. Copyright © 2017 Sinclair et al.

Nucleic and Amino Acid Sequences Support Structure-Based Viral Classification

PubMed Central

Sinclair, Robert M.; Ravantti, Janne J.

2017-01-01

ABSTRACT Viral capsids ensure viral genome integrity by protecting the enclosed nucleic acids. Interactions between the genome and capsid and between individual capsid proteins (i.e., capsid architecture) are intimate and are expected to be characterized by strong evolutionary conservation. For this reason, a capsid structure-based viral classification has been proposed as a way to bring order to the viral universe. The seeming lack of sufficient sequence similarity to reproduce this classification has made it difficult to reject structural convergence as the basis for the classification. We reinvestigate whether the structure-based classification for viral coat proteins making icosahedral virus capsids is in fact supported by previously undetected sequence similarity. Since codon choices can influence nascent protein folding cotranslationally, we searched for both amino acid and nucleotide sequence similarity. To demonstrate the sensitivity of the approach, we identify a candidate gene for the pandoravirus capsid protein. We show that the structure-based classification is strongly supported by amino acid and also nucleotide sequence similarities, suggesting that the similarities are due to common descent. The correspondence between structure-based and sequence-based analyses of the same proteins shown here allow them to be used in future analyses of the relationship between linear sequence information and macromolecular function, as well as between linear sequence and protein folds. IMPORTANCE Viral capsids protect nucleic acid genomes, which in turn encode capsid proteins. This tight coupling of protein shell and nucleic acids, together with strong functional constraints on capsid protein folding and architecture, leads to the hypothesis that capsid protein-coding nucleotide sequences may retain signatures of ancient viral evolution. We have been able to show that this is indeed the case, using the major capsid proteins of viruses forming icosahedral capsids. Importantly, we detected similarity at the nucleotide level between capsid protein-coding regions from viruses infecting cells belonging to all three domains of life, reproducing a previously established structure-based classification of icosahedral viral capsids. PMID:28122979

Gene finding in metatranscriptomic sequences.

PubMed

Ismail, Wazim Mohammed; Ye, Yuzhen; Tang, Haixu

2014-01-01

Metatranscriptomic sequencing is a highly sensitive bioassay of functional activity in a microbial community, providing complementary information to the metagenomic sequencing of the community. The acquisition of the metatranscriptomic sequences will enable us to refine the annotations of the metagenomes, and to study the gene activities and their regulation in complex microbial communities and their dynamics. In this paper, we present TransGeneScan, a software tool for finding genes in assembled transcripts from metatranscriptomic sequences. By incorporating several features of metatranscriptomic sequencing, including strand-specificity, short intergenic regions, and putative antisense transcripts into a Hidden Markov Model, TranGeneScan can predict a sense transcript containing one or multiple genes (in an operon) or an antisense transcript. We tested TransGeneScan on a mock metatranscriptomic data set containing three known bacterial genomes. The results showed that TranGeneScan performs better than metagenomic gene finders (MetaGeneMark and FragGeneScan) on predicting protein coding genes in assembled transcripts, and achieves comparable or even higher accuracy than gene finders for microbial genomes (Glimmer and GeneMark). These results imply, with the assistance of metatranscriptomic sequencing, we can obtain a broad and precise picture about the genes (and their functions) in a microbial community. TransGeneScan is available as open-source software on SourceForge at https://sourceforge.net/projects/transgenescan/.

Cloning and sequence determination of the gene coding for the pyruvate phosphate dikinase of Entamoeba histolytica.

PubMed

Saavedra-Lira, E; Pérez-Montfort, R

1994-05-16

We isolated three overlapping clones from a DNA genomic library of Entamoeba histolytica strain HM1:IMSS, whose translated nucleotide (nt) sequence shows similarities of 51, 48 and 47% with the amino acid (aa) sequences reported for the pyruvate phosphate dikinases from Bacteroides symbiosus, maize and Flaveria trinervia, respectively. The reading frame determined codes for a protein of 886 aa.

TriAnnot: A Versatile and High Performance Pipeline for the Automated Annotation of Plant Genomes

PubMed Central

Leroy, Philippe; Guilhot, Nicolas; Sakai, Hiroaki; Bernard, Aurélien; Choulet, Frédéric; Theil, Sébastien; Reboux, Sébastien; Amano, Naoki; Flutre, Timothée; Pelegrin, Céline; Ohyanagi, Hajime; Seidel, Michael; Giacomoni, Franck; Reichstadt, Mathieu; Alaux, Michael; Gicquello, Emmanuelle; Legeai, Fabrice; Cerutti, Lorenzo; Numa, Hisataka; Tanaka, Tsuyoshi; Mayer, Klaus; Itoh, Takeshi; Quesneville, Hadi; Feuillet, Catherine

2012-01-01

In support of the international effort to obtain a reference sequence of the bread wheat genome and to provide plant communities dealing with large and complex genomes with a versatile, easy-to-use online automated tool for annotation, we have developed the TriAnnot pipeline. Its modular architecture allows for the annotation and masking of transposable elements, the structural, and functional annotation of protein-coding genes with an evidence-based quality indexing, and the identification of conserved non-coding sequences and molecular markers. The TriAnnot pipeline is parallelized on a 712 CPU computing cluster that can run a 1-Gb sequence annotation in less than 5 days. It is accessible through a web interface for small scale analyses or through a server for large scale annotations. The performance of TriAnnot was evaluated in terms of sensitivity, specificity, and general fitness using curated reference sequence sets from rice and wheat. In less than 8 h, TriAnnot was able to predict more than 83% of the 3,748 CDS from rice chromosome 1 with a fitness of 67.4%. On a set of 12 reference Mb-sized contigs from wheat chromosome 3B, TriAnnot predicted and annotated 93.3% of the genes among which 54% were perfectly identified in accordance with the reference annotation. It also allowed the curation of 12 genes based on new biological evidences, increasing the percentage of perfect gene prediction to 63%. TriAnnot systematically showed a higher fitness than other annotation pipelines that are not improved for wheat. As it is easily adaptable to the annotation of other plant genomes, TriAnnot should become a useful resource for the annotation of large and complex genomes in the future. PMID:22645565

The mitochondrial genomes of the acoelomorph worms Paratomella rubra, Isodiametra pulchra and Archaphanostoma ylvae.

PubMed

Robertson, Helen E; Lapraz, François; Egger, Bernhard; Telford, Maximilian J; Schiffer, Philipp H

2017-05-12

Acoels are small, ubiquitous - but understudied - marine worms with a very simple body plan. Their internal phylogeny is still not fully resolved, and the position of their proposed phylum Xenacoelomorpha remains debated. Here we describe mitochondrial genome sequences from the acoels Paratomella rubra and Isodiametra pulchra, and the complete mitochondrial genome of the acoel Archaphanostoma ylvae. The P. rubra and A. ylvae sequences are typical for metazoans in size and gene content. The larger I. pulchra  mitochondrial genome contains both ribosomal genes, 21 tRNAs, but only 11 protein-coding genes. We find evidence suggesting a duplicated sequence in the I. pulchra mitochondrial genome. The P. rubra, I. pulchra and A. ylvae mitochondria have a unique genome organisation in comparison to other metazoan mitochondrial genomes. We found a large degree of protein-coding gene and tRNA overlap with little non-coding sequence in the compact P. rubra genome. Conversely, the A. ylvae and I. pulchra genomes have many long non-coding sequences between genes, likely driving genome size expansion in the latter. Phylogenetic trees inferred from mitochondrial genes retrieve Xenacoelomorpha as an early branching taxon in the deuterostomes. Sequence divergence analysis between P. rubra sampled in England and Spain indicates cryptic diversity.

Metal resistance sequences and transgenic plants

DOEpatents

Meagher, Richard Brian; Summers, Anne O.; Rugh, Clayton L.

1999-10-12

The present invention provides nucleic acid sequences encoding a metal ion resistance protein, which are expressible in plant cells. The metal resistance protein provides for the enzymatic reduction of metal ions including but not limited to divalent Cu, divalent mercury, trivalent gold, divalent cadmium, lead ions and monovalent silver ions. Transgenic plants which express these coding sequences exhibit increased resistance to metal ions in the environment as compared with plants which have not been so genetically modified. Transgenic plants with improved resistance to organometals including alkylmercury compounds, among others, are provided by the further inclusion of plant-expressible organometal lyase coding sequences, as specifically exemplified by the plant-expressible merB coding sequence. Furthermore, these transgenic plants which have been genetically modified to express the metal resistance coding sequences of the present invention can participate in the bioremediation of metal contamination via the enzymatic reduction of metal ions. Transgenic plants resistant to organometals can further mediate remediation of organic metal compounds, for example, alkylmetal compounds including but not limited to methyl mercury, methyl lead compounds, methyl cadmium and methyl arsenic compounds, in the environment by causing the freeing of mercuric or other metal ions and the reduction of the ionic mercury or other metal ions to the less toxic elemental mercury or other metals.

Genome assembly and transcriptome resource for river buffalo, Bubalus bubalis (2n = 50)

PubMed Central

Iamartino, Daniela; Pruitt, Kim D; Sonstegard, Tad; Smith, Timothy P L; Low, Wai Yee; Biagini, Tommaso; Bomba, Lorenzo; Capomaccio, Stefano; Castiglioni, Bianca; Coletta, Angelo; Corrado, Federica; Ferré, Fabrizio; Iannuzzi, Leopoldo; Lawley, Cynthia; Macciotta, Nicolò; McClure, Matthew; Mancini, Giordano; Matassino, Donato; Mazza, Raffaele; Milanesi, Marco; Moioli, Bianca; Morandi, Nicola; Ramunno, Luigi; Peretti, Vincenzo; Pilla, Fabio; Ramelli, Paola; Schroeder, Steven; Strozzi, Francesco; Thibaud-Nissen, Francoise; Zicarelli, Luigi; Ajmone-Marsan, Paolo; Valentini, Alessio; Chillemi, Giovanni; Zimin, Aleksey

2017-01-01

Abstract Water buffalo is a globally important species for agriculture and local economies. A de novo assembled, well-annotated reference sequence for the water buffalo is an important prerequisite for studying the biology of this species, and is necessary to manage genetic diversity and to use modern breeding and genomic selection techniques. However, no such genome assembly has been previously reported. There are 2 species of domestic water buffalo, the river (2n = 50) and the swamp (2n = 48) buffalo. Here we describe a draft quality reference sequence for the river buffalo created from Illumina GA and Roche 454 short read sequences using the MaSuRCA assembler. The assembled sequence is 2.83 Gb, consisting of 366 983 scaffolds with a scaffold N50 of 1.41 Mb and contig N50 of 21 398 bp. Annotation of the genome was supported by transcriptome data from 30 tissues and identified 21 711 predicted protein coding genes. Searches for complete mammalian BUSCO gene groups found 98.6% of curated single copy orthologs present among predicted genes, which suggests a high level of completeness of the genome. The annotated sequence is available from NCBI at accession GCA_000471725.1. PMID:29048578

Deep sequencing of Salmonella RNA associated with heterologous Hfq proteins in vivo reveals small RNAs as a major target class and identifies RNA processing phenotypes.

PubMed

Sittka, Alexandra; Sharma, Cynthia M; Rolle, Katarzyna; Vogel, Jörg

2009-01-01

The bacterial Sm-like protein, Hfq, is a key factor for the stability and function of small non-coding RNAs (sRNAs) in Escherichia coli. Homologues of this protein have been predicted in many distantly related organisms yet their functional conservation as sRNA-binding proteins has not entirely been clear. To address this, we expressed in Salmonella the Hfq proteins of two eubacteria (Neisseria meningitides, Aquifex aeolicus) and an archaeon (Methanocaldococcus jannaschii), and analyzed the associated RNA by deep sequencing. This in vivo approach identified endogenous Salmonella sRNAs as a major target of the foreign Hfq proteins. New Salmonella sRNA species were also identified, and some of these accumulated specifically in the presence of a foreign Hfq protein. In addition, we observed specific RNA processing defects, e.g., suppression of precursor processing of SraH sRNA by Methanocaldococcus Hfq, or aberrant accumulation of extracytoplasmic target mRNAs of the Salmonella GcvB, MicA or RybB sRNAs. Taken together, our study provides evidence of a conserved inherent sRNA-binding property of Hfq, which may facilitate the lateral transmission of regulatory sRNAs among distantly related species. It also suggests that the expression of heterologous RNA-binding proteins combined with deep sequencing analysis of RNA ligands can be used as a molecular tool to dissect individual steps of RNA metabolism in vivo.

Molecular characterization of amino acid deletion in VP1 (1D) protein and novel amino acid substitutions in 3D polymerase protein of foot and mouth disease virus subtype A/Iran87.

PubMed

Esmaelizad, Majid; Jelokhani-Niaraki, Saber; Hashemnejad, Khadije; Kamalzadeh, Morteza; Lotfi, Mohsen

2011-12-01

The nucleotide sequence of the VP1 (1D) and partial 3D polymerase (3D(pol)) coding regions of the foot and mouth disease virus (FMDV) vaccine strain A/Iran87, a highly passaged isolate (~150 passages), was determined and aligned with previously published FMDV serotype A sequences. Overall analysis of the amino acid substitutions revealed that the partial 3D(pol) coding region contained four amino acid alterations. Amino acid sequence comparison of the VP1 coding region of the field isolates revealed deletions in the highly passaged Iranian isolate (A/Iran87). The prominent G-H loop of the FMDV VP1 protein contains the conserved arginine-glycine-aspartic acid (RGD) tripeptide, which is a well-known ligand for a specific cell surface integrin. Despite losing the RGD sequence of the VP1 protein and an Asp(26)→Glu substitution in a beta sheet located within a small groove of the 3D(pol) protein, the virus grew in BHK 21 suspension cell cultures. Since this strain has been used as a vaccine strain, it may be inferred that the RGD deletion has no critical role in virus attachment to the cell during the initiation of infection. It is probable that this FMDV subtype can utilize other pathways for cell attachment.

Draft Genome Sequences of Two Bacillus thuringiensis Strains and Characterization of a Putative 41.9-kDa Insecticidal Toxin

PubMed Central

Palma, Leopoldo; Muñoz, Delia; Berry, Colin; Murillo, Jesús; Caballero, Primitivo

2014-01-01

In this work, we report the genome sequencing of two Bacillus thuringiensis strains using Illumina next-generation sequencing technology (NGS). Strain Hu4-2, toxic to many lepidopteran pest species and to some mosquitoes, encoded genes for two insecticidal crystal (Cry) proteins, cry1Ia and cry9Ea, and a vegetative insecticidal protein (Vip) gene, vip3Ca2. Strain Leapi01 contained genes coding for seven Cry proteins (cry1Aa, cry1Ca, cry1Da, cry2Ab, cry9Ea and two cry1Ia gene variants) and a vip3 gene (vip3Aa10). A putative novel insecticidal protein gene 1143 bp long was found in both strains, whose sequences exhibited 100% nucleotide identity. The predicted protein showed 57 and 100% pairwise identity to protein sequence 72 from a patented Bt strain (US8318900) and to a putative 41.9-kDa insecticidal toxin from Bacillus cereus, respectively. The 41.9-kDa protein, containing a C-terminal 6× HisTag fusion, was expressed in Escherichia coli and tested for the first time against four lepidopteran species (Mamestra brassicae, Ostrinia nubilalis, Spodoptera frugiperda and S. littoralis) and the green-peach aphid Myzus persicae at doses as high as 4.8 µg/cm2 and 1.5 mg/mL, respectively. At these protein concentrations, the recombinant 41.9-kDa protein caused no mortality or symptoms of impaired growth against any of the insects tested, suggesting that these species are outside the protein’s target range or that the protein may not, in fact, be toxic. While the use of the polymerase chain reaction has allowed a significant increase in the number of Bt insecticidal genes characterized to date, novel NGS technologies promise a much faster, cheaper and efficient screening of Bt pesticidal proteins. PMID:24784323

Prediction of the translocon-mediated membrane insertion free energies of protein sequences.

PubMed

Park, Yungki; Helms, Volkhard

2008-05-15

Helical membrane proteins (HMPs) play crucial roles in a variety of cellular processes. Unlike water-soluble proteins, HMPs need not only to fold but also get inserted into the membrane to be fully functional. This process of membrane insertion is mediated by the translocon complex. Thus, it is of great interest to develop computational methods for predicting the translocon-mediated membrane insertion free energies of protein sequences. We have developed Membrane Insertion (MINS), a novel sequence-based computational method for predicting the membrane insertion free energies of protein sequences. A benchmark test gives a correlation coefficient of 0.74 between predicted and observed free energies for 357 known cases, which corresponds to a mean unsigned error of 0.41 kcal/mol. These results are significantly better than those obtained by traditional hydropathy analysis. Moreover, the ability of MINS to reasonably predict membrane insertion free energies of protein sequences allows for effective identification of transmembrane (TM) segments. Subsequently, MINS was applied to predict the membrane insertion free energies of 316 TM segments found in known structures. An in-depth analysis of the predicted free energies reveals a number of interesting findings about the biogenesis and structural stability of HMPs. A web server for MINS is available at http://service.bioinformatik.uni-saarland.de/mins

A traditional evolutionary history of foot-and-mouth disease viruses in Southeast Asia challenged by analyses of non-structural protein coding sequences

USDA-ARS?s Scientific Manuscript database

Molecular epidemiology and evolution of foot-and-mouth disease virus (FMDV) are widely studied using genomic sequences encoding VP1, the capsid protein containing the most relevant antigenic domains. Although sequencing of the full viral genome is not used as a routine diagnostic or surveillance too...

Random oligonucleotide mutagenesis: application to a large protein coding sequence of a major histocompatibility complex class I gene, H-2DP.

PubMed Central

Murray, R; Pederson, K; Prosser, H; Muller, D; Hutchison, C A; Frelinger, J A

1988-01-01

We have used random oligonucleotide mutagenesis (or saturation mutagenesis) to create a library of point mutations in the alpha 1 protein domain of a Major Histocompatibility Complex (MHC) molecule. This protein domain is critical for T cell and B cell recognition. We altered the MHC class I H-2DP gene sequence such that synthetic mutant alpha 1 exons (270 bp of coding sequence), which contain mutations identified by sequence analysis, can replace the wild type alpha 1 exon. The synthetic exons were constructed from twelve overlapping oligonucleotides which contained an average of 1.3 random point mutations per intact exon. DNA sequence analysis of mutant alpha 1 exons has shown a point mutant distribution that fits a Poisson distribution, and thus emphasizes the utility of this mutagenesis technique to "scan" a large protein sequence for important mutations. We report our use of saturation mutagenesis to scan an entire exon of the H-2DP gene, a cassette strategy to replace the wild type alpha 1 exon with individual mutant alpha 1 exons, and analysis of mutant molecules expressed on the surface of transfected mouse L cells. Images PMID:2903482

Hidden Markov model approach for identifying the modular framework of the protein backbone.

PubMed

Camproux, A C; Tuffery, P; Chevrolat, J P; Boisvieux, J F; Hazout, S

1999-12-01

The hidden Markov model (HMM) was used to identify recurrent short 3D structural building blocks (SBBs) describing protein backbones, independently of any a priori knowledge. Polypeptide chains are decomposed into a series of short segments defined by their inter-alpha-carbon distances. Basically, the model takes into account the sequentiality of the observed segments and assumes that each one corresponds to one of several possible SBBs. Fitting the model to a database of non-redundant proteins allowed us to decode proteins in terms of 12 distinct SBBs with different roles in protein structure. Some SBBs correspond to classical regular secondary structures. Others correspond to a significant subdivision of their bounding regions previously considered to be a single pattern. The major contribution of the HMM is that this model implicitly takes into account the sequential connections between SBBs and thus describes the most probable pathways by which the blocks are connected to form the framework of the protein structures. Validation of the SBBs code was performed by extracting SBB series repeated in recoding proteins and examining their structural similarities. Preliminary results on the sequence specificity of SBBs suggest promising perspectives for the prediction of SBBs or series of SBBs from the protein sequences.

The Ever-Evolving Concept of the Gene: The Use of RNA/Protein Experimental Techniques to Understand Genome Functions

PubMed Central

Cipriano, Andrea; Ballarino, Monica

2018-01-01

The completion of the human genome sequence together with advances in sequencing technologies have shifted the paradigm of the genome, as composed of discrete and hereditable coding entities, and have shown the abundance of functional noncoding DNA. This part of the genome, previously dismissed as “junk” DNA, increases proportionally with organismal complexity and contributes to gene regulation beyond the boundaries of known protein-coding genes. Different classes of functionally relevant nonprotein-coding RNAs are transcribed from noncoding DNA sequences. Among them are the long noncoding RNAs (lncRNAs), which are thought to participate in the basal regulation of protein-coding genes at both transcriptional and post-transcriptional levels. Although knowledge of this field is still limited, the ability of lncRNAs to localize in different cellular compartments, to fold into specific secondary structures and to interact with different molecules (RNA or proteins) endows them with multiple regulatory mechanisms. It is becoming evident that lncRNAs may play a crucial role in most biological processes such as the control of development, differentiation and cell growth. This review places the evolution of the concept of the gene in its historical context, from Darwin's hypothetical mechanism of heredity to the post-genomic era. We discuss how the original idea of protein-coding genes as unique determinants of phenotypic traits has been reconsidered in light of the existence of noncoding RNAs. We summarize the technological developments which have been made in the genome-wide identification and study of lncRNAs and emphasize the methodologies that have aided our understanding of the complexity of lncRNA-protein interactions in recent years. PMID:29560353

Conservation of Shannon's redundancy for proteins. [information theory applied to amino acid sequences

NASA Technical Reports Server (NTRS)

Gatlin, L. L.

1974-01-01

Concepts of information theory are applied to examine various proteins in terms of their redundancy in natural originators such as animals and plants. The Monte Carlo method is used to derive information parameters for random protein sequences. Real protein sequence parameters are compared with the standard parameters of protein sequences having a specific length. The tendency of a chain to contain some amino acids more frequently than others and the tendency of a chain to contain certain amino acid pairs more frequently than other pairs are used as randomness measures of individual protein sequences. Non-periodic proteins are generally found to have random Shannon redundancies except in cases of constraints due to short chain length and genetic codes. Redundant characteristics of highly periodic proteins are discussed. A degree of periodicity parameter is derived.

Draft versus finished sequence data for DNA and protein diagnostic signature development

PubMed Central

Gardner, Shea N.; Lam, Marisa W.; Smith, Jason R.; Torres, Clinton L.; Slezak, Tom R.

2005-01-01

Sequencing pathogen genomes is costly, demanding careful allocation of limited sequencing resources. We built a computational Sequencing Analysis Pipeline (SAP) to guide decisions regarding the amount of genomic sequencing necessary to develop high-quality diagnostic DNA and protein signatures. SAP uses simulations to estimate the number of target genomes and close phylogenetic relatives (near neighbors or NNs) to sequence. We use SAP to assess whether draft data are sufficient or finished sequencing is required using Marburg and variola virus sequences. Simulations indicate that intermediate to high-quality draft with error rates of 10−3–10−5 (∼8× coverage) of target organisms is suitable for DNA signature prediction. Low-quality draft with error rates of ∼1% (3× to 6× coverage) of target isolates is inadequate for DNA signature prediction, although low-quality draft of NNs is sufficient, as long as the target genomes are of high quality. For protein signature prediction, sequencing errors in target genomes substantially reduce the detection of amino acid sequence conservation, even if the draft is of high quality. In summary, high-quality draft of target and low-quality draft of NNs appears to be a cost-effective investment for DNA signature prediction, but may lead to underestimation of predicted protein signatures. PMID:16243783

Mutations Affecting Expression of the rosy Locus in Drosophila melanogaster

PubMed Central

Lee, Chong Sung; Curtis, Daniel; McCarron, Margaret; Love, Carol; Gray, Mark; Bender, Welcome; Chovnick, Arthur

1987-01-01

The rosy locus in Drosophila melanogaster codes for the enzyme xanthine dehydrogenase (XDH). Previous studies defined a "control element" near the 5' end of the gene, where variant sites affected the amount of rosy mRNA and protein produced. We have determined the DNA sequence of this region from both genomic and cDNA clones, and from the ry+10 underproducer strain. This variant strain had many sequence differences, so that the site of the regulatory change could not be fixed. A mutagenesis was also undertaken to isolate new regulatory mutations. We induced 376 new mutations with 1-ethyl-1-nitrosourea (ENU) and screened them to isolate those that reduced the amount of XDH protein produced, but did not change the properties of the enzyme. Genetic mapping was used to find mutations located near the 5' end of the gene. DNA from each of seven mutants was cloned and sequenced through the 5' region. Mutant base changes were identified in all seven; they appear to affect splicing and translation of the rosy mRNA. In a related study (T. P. Keith et al. 1987), the genomic and cDNA sequences are extended through the 3' end of the gene; the combined sequences define the processing pattern of the rosy transcript and predict the amino acid sequence of XDH. PMID:3036645

The complete mitochondrial genome of Papilio glaucus and its phylogenetic implications.

PubMed

Shen, Jinhui; Cong, Qian; Grishin, Nick V

2015-09-01

Due to the intriguing morphology, lifecycle, and diversity of butterflies and moths, Lepidoptera are emerging as model organisms for the study of genetics, evolution and speciation. The progress of these studies relies on decoding Lepidoptera genomes, both nuclear and mitochondrial. Here we describe a protocol to obtain mitogenomes from Next Generation Sequencing reads performed for whole-genome sequencing and report the complete mitogenome of Papilio (Pterourus) glaucus. The circular mitogenome is 15,306 bp in length and rich in A and T. It contains 13 protein-coding genes (PCGs), 22 transfer-RNA-coding genes (tRNA), and 2 ribosomal-RNA-coding genes (rRNA), with a gene order typical for mitogenomes of Lepidoptera. We performed phylogenetic analyses based on PCG and RNA-coding genes or protein sequences using Bayesian Inference and Maximum Likelihood methods. The phylogenetic trees consistently show that among species with available mitogenomes Papilio glaucus is the closest to Papilio (Agehana) maraho from Asia.

Graph pyramids for protein function prediction

PubMed Central

2015-01-01

Background Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Methods Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Results Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data. PMID:26044522

Graph pyramids for protein function prediction.

PubMed

Sandhan, Tushar; Yoo, Youngjun; Choi, Jin; Kim, Sun

2015-01-01

Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data.

Genome-wide prediction of cis-regulatory regions using supervised deep learning methods.

PubMed

Li, Yifeng; Shi, Wenqiang; Wasserman, Wyeth W

2018-05-31

In the human genome, 98% of DNA sequences are non-protein-coding regions that were previously disregarded as junk DNA. In fact, non-coding regions host a variety of cis-regulatory regions which precisely control the expression of genes. Thus, Identifying active cis-regulatory regions in the human genome is critical for understanding gene regulation and assessing the impact of genetic variation on phenotype. The developments of high-throughput sequencing and machine learning technologies make it possible to predict cis-regulatory regions genome wide. Based on rich data resources such as the Encyclopedia of DNA Elements (ENCODE) and the Functional Annotation of the Mammalian Genome (FANTOM) projects, we introduce DECRES based on supervised deep learning approaches for the identification of enhancer and promoter regions in the human genome. Due to their ability to discover patterns in large and complex data, the introduction of deep learning methods enables a significant advance in our knowledge of the genomic locations of cis-regulatory regions. Using models for well-characterized cell lines, we identify key experimental features that contribute to the predictive performance. Applying DECRES, we delineate locations of 300,000 candidate enhancers genome wide (6.8% of the genome, of which 40,000 are supported by bidirectional transcription data), and 26,000 candidate promoters (0.6% of the genome). The predicted annotations of cis-regulatory regions will provide broad utility for genome interpretation from functional genomics to clinical applications. The DECRES model demonstrates potentials of deep learning technologies when combined with high-throughput sequencing data, and inspires the development of other advanced neural network models for further improvement of genome annotations.

Molecular identification and functional characterisation of uncoupling protein 4 in larva and pupa fat body mitochondria from the beetle Zophobas atratus.

PubMed

Slocinska, Malgorzata; Antos-Krzeminska, Nina; Rosinski, Grzegorz; Jarmuszkiewicz, Wieslawa

2012-08-01

Uncoupling protein 4 (UCP4) is a member of the UCP subfamily that mediates mitochondrial uncoupling, and sequence alignment predicts the existence of UCP4 in several insects. The present study demonstrates the first molecular identification of a partial Zophobas atratus UCP4-coding sequence and the functional characterisation of ZaUCP4 in the mitochondria of larval and pupal fat bodies of the beetle. ZaUCP4 shows a high similarity to predicted insect UCP4 isoforms and known mammalian UCP4s, both at the nucleotide and amino acid sequence levels. Bioenergetic studies clearly demonstrate UCP function in mitochondria from larval and pupal fat bodies. In non-phosphorylating mitochondria, ZaUCP activity was stimulated by palmitic acid and inhibited by the purine nucleotide GTP. In phosphorylating mitochondria, ZaUCP4 activity decreased the yield of oxidative phosphorylation. ZaUCP4 was immunodetected with antibodies raised against human UCP4 as a single 36-kDa band. A lower expression of ZaUCP4 at the level of mRNA and protein and a decreased ZaUCP4 activity were observed in the Z. atratus pupal fat body compared with the larval fat body. The different expression patterns and activity of ZaUCP4 during the larval-pupal transformation indicates an important physiological role for UCP4 in insect fat body development and function during insect metamorphosis. Copyright © 2012 Elsevier Inc. All rights reserved.

Programmable DNA-binding proteins from Burkholderia provide a fresh perspective on the TALE-like repeat domain.

PubMed

de Lange, Orlando; Wolf, Christina; Dietze, Jörn; Elsaesser, Janett; Morbitzer, Robert; Lahaye, Thomas

2014-06-01

The tandem repeats of transcription activator like effectors (TALEs) mediate sequence-specific DNA binding using a simple code. Naturally, TALEs are injected by Xanthomonas bacteria into plant cells to manipulate the host transcriptome. In the laboratory TALE DNA binding domains are reprogrammed and used to target a fused functional domain to a genomic locus of choice. Research into the natural diversity of TALE-like proteins may provide resources for the further improvement of current TALE technology. Here we describe TALE-like proteins from the endosymbiotic bacterium Burkholderia rhizoxinica, termed Bat proteins. Bat repeat domains mediate sequence-specific DNA binding with the same code as TALEs, despite less than 40% sequence identity. We show that Bat proteins can be adapted for use as transcription factors and nucleases and that sequence preferences can be reprogrammed. Unlike TALEs, the core repeats of each Bat protein are highly polymorphic. This feature allowed us to explore alternative strategies for the design of custom Bat repeat arrays, providing novel insights into the functional relevance of non-RVD residues. The Bat proteins offer fertile grounds for research into the creation of improved programmable DNA-binding proteins and comparative insights into TALE-like evolution. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Analysis of the complete nucleotide sequence and functional organization of the genome of Streptococcus pneumoniae bacteriophage Cp-1.

PubMed

Martín, A C; López, R; García, P

1996-06-01

Cp-1, a bacteriophage infecting Streptococcus pneumoniae, has a linear double-stranded DNA genome, with a terminal protein covalently linked to its 5' ends, that replicates by the protein-priming mechanism. We describe here the complete DNA sequence and transcriptional map of the Cp-1 genome. These analyses have led to the firm assignment of 10 genes and the localization of 19 additional open reading frames in the 19,345-bp Cp-1 DNA. Striking similarities and differences between some of these proteins and those of the Bacillus subtilis phage phi 29, a system that also replicates its DNA by the protein-priming mechanism, have been revealed. The genes coding for structural proteins and assembly factors are located in the central part of the Cp-1 genome. Several proteins corresponding to the predicted gene products were identified by in vitro and in vivo expression of the cloned genes. Mature major head protein from the virion particles results from hydrolysis of the primary gene product at the His-49 residue, whereas the phage gene is expressed in Escherichia coli without modification. We have also identified two open reading frames coding for proteins that show high degrees of similarity to the N- and C-terminal regions, respectively, of the single tail protein identified in phi 29. Sequencing and primer extension analysis suggest transcription of a small RNA showing a secondary structure similar to that of the prohead RNA required for the ATP-dependent packaging of phi 29 DNA. On the basis of its temporal expression, transcription of the Cp-1 genome takes place in two stages, early and late. Combined Northern (RNA) blot and primer extension experiments allowed us to map the 5' initiation sites of the transcripts, and we found that only three genes were transcribed from right to left. These analyses reveal that there are also noticeable differences between Cp-l and phi 29 in transcriptional organization. Considered together, the observations reported here provide new tangible evidence on phylogenetic relationships between B. subtilis and S. pneumoniae.