The web server of IBM's Bioinformatics and Pattern Discovery group: 2004 update

PubMed Central

Huynh, Tien; Rigoutsos, Isidore

2004-01-01

In this report, we provide an update on the services and content which are available on the web server of IBM's Bioinformatics and Pattern Discovery group. The server, which is operational around the clock, provides access to a large number of methods that have been developed and published by the group's members. There is an increasing number of problems that these tools can help tackle; these problems range from the discovery of patterns in streams of events and the computation of multiple sequence alignments, to the discovery of genes in nucleic acid sequences, the identification—directly from sequence—of structural deviations from α-helicity and the annotation of amino acid sequences for antimicrobial activity. Additionally, annotations for more than 130 archaeal, bacterial, eukaryotic and viral genomes are now available on-line and can be searched interactively. The tools and code bundles continue to be accessible from http://cbcsrv.watson.ibm.com/Tspd.html whereas the genomics annotations are available at http://cbcsrv.watson.ibm.com/Annotations/. PMID:15215340

SIMAP--a comprehensive database of pre-calculated protein sequence similarities, domains, annotations and clusters.

PubMed

Rattei, Thomas; Tischler, Patrick; Götz, Stefan; Jehl, Marc-André; Hoser, Jonathan; Arnold, Roland; Conesa, Ana; Mewes, Hans-Werner

2010-01-01

The prediction of protein function as well as the reconstruction of evolutionary genesis employing sequence comparison at large is still the most powerful tool in sequence analysis. Due to the exponential growth of the number of known protein sequences and the subsequent quadratic growth of the similarity matrix, the computation of the Similarity Matrix of Proteins (SIMAP) becomes a computational intensive task. The SIMAP database provides a comprehensive and up-to-date pre-calculation of the protein sequence similarity matrix, sequence-based features and sequence clusters. As of September 2009, SIMAP covers 48 million proteins and more than 23 million non-redundant sequences. Novel features of SIMAP include the expansion of the sequence space by including databases such as ENSEMBL as well as the integration of metagenomes based on their consistent processing and annotation. Furthermore, protein function predictions by Blast2GO are pre-calculated for all sequences in SIMAP and the data access and query functions have been improved. SIMAP assists biologists to query the up-to-date sequence space systematically and facilitates large-scale downstream projects in computational biology. Access to SIMAP is freely provided through the web portal for individuals (http://mips.gsf.de/simap/) and for programmatic access through DAS (http://webclu.bio.wzw.tum.de/das/) and Web-Service (http://mips.gsf.de/webservices/services/SimapService2.0?wsdl).

Alignment-Annotator web server: rendering and annotating sequence alignments.

PubMed

Gille, Christoph; Fähling, Michael; Weyand, Birgit; Wieland, Thomas; Gille, Andreas

2014-07-01

Alignment-Annotator is a novel web service designed to generate interactive views of annotated nucleotide and amino acid sequence alignments (i) de novo and (ii) embedded in other software. All computations are performed at server side. Interactivity is implemented in HTML5, a language native to web browsers. The alignment is initially displayed using default settings and can be modified with the graphical user interfaces. For example, individual sequences can be reordered or deleted using drag and drop, amino acid color code schemes can be applied and annotations can be added. Annotations can be made manually or imported (BioDAS servers, the UniProt, the Catalytic Site Atlas and the PDB). Some edits take immediate effect while others require server interaction and may take a few seconds to execute. The final alignment document can be downloaded as a zip-archive containing the HTML files. Because of the use of HTML the resulting interactive alignment can be viewed on any platform including Windows, Mac OS X, Linux, Android and iOS in any standard web browser. Importantly, no plugins nor Java are required and therefore Alignment-Anotator represents the first interactive browser-based alignment visualization. http://www.bioinformatics.org/strap/aa/ and http://strap.charite.de/aa/. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Alignment-Annotator web server: rendering and annotating sequence alignments

PubMed Central

Gille, Christoph; Fähling, Michael; Weyand, Birgit; Wieland, Thomas; Gille, Andreas

2014-01-01

Alignment-Annotator is a novel web service designed to generate interactive views of annotated nucleotide and amino acid sequence alignments (i) de novo and (ii) embedded in other software. All computations are performed at server side. Interactivity is implemented in HTML5, a language native to web browsers. The alignment is initially displayed using default settings and can be modified with the graphical user interfaces. For example, individual sequences can be reordered or deleted using drag and drop, amino acid color code schemes can be applied and annotations can be added. Annotations can be made manually or imported (BioDAS servers, the UniProt, the Catalytic Site Atlas and the PDB). Some edits take immediate effect while others require server interaction and may take a few seconds to execute. The final alignment document can be downloaded as a zip-archive containing the HTML files. Because of the use of HTML the resulting interactive alignment can be viewed on any platform including Windows, Mac OS X, Linux, Android and iOS in any standard web browser. Importantly, no plugins nor Java are required and therefore Alignment-Anotator represents the first interactive browser-based alignment visualization. Availability: http://www.bioinformatics.org/strap/aa/ and http://strap.charite.de/aa/. PMID:24813445

Cazymes Analysis Toolkit (CAT): Webservice for searching and analyzing carbohydrateactive enzymes in a newly sequenced organism using CAZy database

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

Karpinets, Tatiana V; Park, Byung; Syed, Mustafa H

2010-01-01

The Carbohydrate-Active Enzyme (CAZy) database provides a rich set of manually annotated enzymes that degrade, modify, or create glycosidic bonds. Despite rich and invaluable information stored in the database, software tools utilizing this information for annotation of newly sequenced genomes by CAZy families are limited. We have employed two annotation approaches to fill the gap between manually curated high-quality protein sequences collected in the CAZy database and the growing number of other protein sequences produced by genome or metagenome sequencing projects. The first approach is based on a similarity search against the entire non-redundant sequences of the CAZy database. Themore » second approach performs annotation using links or correspondences between the CAZy families and protein family domains. The links were discovered using the association rule learning algorithm applied to sequences from the CAZy database. The approaches complement each other and in combination achieved high specificity and sensitivity when cross-evaluated with the manually curated genomes of Clostridium thermocellum ATCC 27405 and Saccharophagus degradans 2-40. The capability of the proposed framework to predict the function of unknown protein domains (DUF) and of hypothetical proteins in the genome of Neurospora crassa is demonstrated. The framework is implemented as a Web service, the CAZymes Analysis Toolkit (CAT), and is available at http://cricket.ornl.gov/cgi-bin/cat.cgi.« less

Ensembl 2004.

PubMed

Birney, E; Andrews, D; Bevan, P; Caccamo, M; Cameron, G; Chen, Y; Clarke, L; Coates, G; Cox, T; Cuff, J; Curwen, V; Cutts, T; Down, T; Durbin, R; Eyras, E; Fernandez-Suarez, X M; Gane, P; Gibbins, B; Gilbert, J; Hammond, M; Hotz, H; Iyer, V; Kahari, A; Jekosch, K; Kasprzyk, A; Keefe, D; Keenan, S; Lehvaslaiho, H; McVicker, G; Melsopp, C; Meidl, P; Mongin, E; Pettett, R; Potter, S; Proctor, G; Rae, M; Searle, S; Slater, G; Smedley, D; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Storey, R; Ureta-Vidal, A; Woodwark, C; Clamp, M; Hubbard, T

2004-01-01

The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organize biology around the sequences of large genomes. It is a comprehensive and integrated source of annotation of large genome sequences, available via interactive website, web services or flat files. As well as being one of the leading sources of genome annotation, Ensembl is an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements. The facilities of the system range from sequence analysis to data storage and visualization and installations exist around the world both in companies and at academic sites. With a total of nine genome sequences available from Ensembl and more genomes to follow, recent developments have focused mainly on closer integration between genomes and external data.

Annotation and visualization of endogenous retroviral sequences using the Distributed Annotation System (DAS) and eBioX

PubMed Central

Martínez Barrio, Álvaro; Lagercrantz, Erik; Sperber, Göran O; Blomberg, Jonas; Bongcam-Rudloff, Erik

2009-01-01

Background The Distributed Annotation System (DAS) is a widely used network protocol for sharing biological information. The distributed aspects of the protocol enable the use of various reference and annotation servers for connecting biological sequence data to pertinent annotations in order to depict an integrated view of the data for the final user. Results An annotation server has been devised to provide information about the endogenous retroviruses detected and annotated by a specialized in silico tool called RetroTector. We describe the procedure to implement the DAS 1.5 protocol commands necessary for constructing the DAS annotation server. We use our server to exemplify those steps. Data distribution is kept separated from visualization which is carried out by eBioX, an easy to use open source program incorporating multiple bioinformatics utilities. Some well characterized endogenous retroviruses are shown in two different DAS clients. A rapid analysis of areas free from retroviral insertions could be facilitated by our annotations. Conclusion The DAS protocol has shown to be advantageous in the distribution of endogenous retrovirus data. The distributed nature of the protocol is also found to aid in combining annotation and visualization along a genome in order to enhance the understanding of ERV contribution to its evolution. Reference and annotation servers are conjointly used by eBioX to provide visualization of ERV annotations as well as other data sources. Our DAS data source can be found in the central public DAS service repository, , or at . PMID:19534743

PFAAT version 2.0: a tool for editing, annotating, and analyzing multiple sequence alignments.

PubMed

Caffrey, Daniel R; Dana, Paul H; Mathur, Vidhya; Ocano, Marco; Hong, Eun-Jong; Wang, Yaoyu E; Somaroo, Shyamal; Caffrey, Brian E; Potluri, Shobha; Huang, Enoch S

2007-10-11

By virtue of their shared ancestry, homologous sequences are similar in their structure and function. Consequently, multiple sequence alignments are routinely used to identify trends that relate to function. This type of analysis is particularly productive when it is combined with structural and phylogenetic analysis. Here we describe the release of PFAAT version 2.0, a tool for editing, analyzing, and annotating multiple sequence alignments. Support for multiple annotations is a key component of this release as it provides a framework for most of the new functionalities. The sequence annotations are accessible from the alignment and tree, where they are typically used to label sequences or hyperlink them to related databases. Sequence annotations can be created manually or extracted automatically from UniProt entries. Once a multiple sequence alignment is populated with sequence annotations, sequences can be easily selected and sorted through a sophisticated search dialog. The selected sequences can be further analyzed using statistical methods that explicitly model relationships between the sequence annotations and residue properties. Residue annotations are accessible from the alignment viewer and are typically used to designate binding sites or properties for a particular residue. Residue annotations are also searchable, and allow one to quickly select alignment columns for further sequence analysis, e.g. computing percent identities. Other features include: novel algorithms to compute sequence conservation, mapping conservation scores to a 3D structure in Jmol, displaying secondary structure elements, and sorting sequences by residue composition. PFAAT provides a framework whereby end-users can specify knowledge for a protein family in the form of annotation. The annotations can be combined with sophisticated analysis to test hypothesis that relate to sequence, structure and function.

Sma3s: a three-step modular annotator for large sequence datasets.

PubMed

Muñoz-Mérida, Antonio; Viguera, Enrique; Claros, M Gonzalo; Trelles, Oswaldo; Pérez-Pulido, Antonio J

2014-08-01

Automatic sequence annotation is an essential component of modern 'omics' studies, which aim to extract information from large collections of sequence data. Most existing tools use sequence homology to establish evolutionary relationships and assign putative functions to sequences. However, it can be difficult to define a similarity threshold that achieves sufficient coverage without sacrificing annotation quality. Defining the correct configuration is critical and can be challenging for non-specialist users. Thus, the development of robust automatic annotation techniques that generate high-quality annotations without needing expert knowledge would be very valuable for the research community. We present Sma3s, a tool for automatically annotating very large collections of biological sequences from any kind of gene library or genome. Sma3s is composed of three modules that progressively annotate query sequences using either: (i) very similar homologues, (ii) orthologous sequences or (iii) terms enriched in groups of homologous sequences. We trained the system using several random sets of known sequences, demonstrating average sensitivity and specificity values of ~85%. In conclusion, Sma3s is a versatile tool for high-throughput annotation of a wide variety of sequence datasets that outperforms the accuracy of other well-established annotation algorithms, and it can enrich existing database annotations and uncover previously hidden features. Importantly, Sma3s has already been used in the functional annotation of two published transcriptomes. © The Author 2014. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

An Approach to Function Annotation for Proteins of Unknown Function (PUFs) in the Transcriptome of Indian Mulberry.

PubMed

Dhanyalakshmi, K H; Naika, Mahantesha B N; Sajeevan, R S; Mathew, Oommen K; Shafi, K Mohamed; Sowdhamini, Ramanathan; N Nataraja, Karaba

2016-01-01

The modern sequencing technologies are generating large volumes of information at the transcriptome and genome level. Translation of this information into a biological meaning is far behind the race due to which a significant portion of proteins discovered remain as proteins of unknown function (PUFs). Attempts to uncover the functional significance of PUFs are limited due to lack of easy and high throughput functional annotation tools. Here, we report an approach to assign putative functions to PUFs, identified in the transcriptome of mulberry, a perennial tree commonly cultivated as host of silkworm. We utilized the mulberry PUFs generated from leaf tissues exposed to drought stress at whole plant level. A sequence and structure based computational analysis predicted the probable function of the PUFs. For rapid and easy annotation of PUFs, we developed an automated pipeline by integrating diverse bioinformatics tools, designated as PUFs Annotation Server (PUFAS), which also provides a web service API (Application Programming Interface) for a large-scale analysis up to a genome. The expression analysis of three selected PUFs annotated by the pipeline revealed abiotic stress responsiveness of the genes, and hence their potential role in stress acclimation pathways. The automated pipeline developed here could be extended to assign functions to PUFs from any organism in general. PUFAS web server is available at http://caps.ncbs.res.in/pufas/ and the web service is accessible at http://capservices.ncbs.res.in/help/pufas.

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

OVAS: an open-source variant analysis suite with inheritance modelling.

PubMed

Mozere, Monika; Tekman, Mehmet; Kari, Jameela; Bockenhauer, Detlef; Kleta, Robert; Stanescu, Horia

2018-02-08

The advent of modern high-throughput genetics continually broadens the gap between the rising volume of sequencing data, and the tools required to process them. The need to pinpoint a small subset of functionally important variants has now shifted towards identifying the critical differences between normal variants and disease-causing ones. The ever-increasing reliance on cloud-based services for sequence analysis and the non-transparent methods they utilize has prompted the need for more in-situ services that can provide a safer and more accessible environment to process patient data, especially in circumstances where continuous internet usage is limited. To address these issues, we herein propose our standalone Open-source Variant Analysis Sequencing (OVAS) pipeline; consisting of three key stages of processing that pertain to the separate modes of annotation, filtering, and interpretation. Core annotation performs variant-mapping to gene-isoforms at the exon/intron level, append functional data pertaining the type of variant mutation, and determine hetero/homozygosity. An extensive inheritance-modelling module in conjunction with 11 other filtering components can be used in sequence ranging from single quality control to multi-file penetrance model specifics such as X-linked recessive or mosaicism. Depending on the type of interpretation required, additional annotation is performed to identify organ specificity through gene expression and protein domains. In the course of this paper we analysed an autosomal recessive case study. OVAS made effective use of the filtering modules to recapitulate the results of the study by identifying the prescribed compound-heterozygous disease pattern from exome-capture sequence input samples. OVAS is an offline open-source modular-driven analysis environment designed to annotate and extract useful variants from Variant Call Format (VCF) files, and process them under an inheritance context through a top-down filtering schema of swappable modules, run entirely off a live bootable medium and accessed locally through a web-browser.

TnpPred: A Web Service for the Robust Prediction of Prokaryotic Transposases

PubMed Central

Riadi, Gonzalo; Medina-Moenne, Cristobal; Holmes, David S.

2012-01-01

Transposases (Tnps) are enzymes that participate in the movement of insertion sequences (ISs) within and between genomes. Genes that encode Tnps are amongst the most abundant and widely distributed genes in nature. However, they are difficult to predict bioinformatically and given the increasing availability of prokaryotic genomes and metagenomes, it is incumbent to develop rapid, high quality automatic annotation of ISs. This need prompted us to develop a web service, termed TnpPred for Tnp discovery. It provides better sensitivity and specificity for Tnp predictions than given by currently available programs as determined by ROC analysis. TnpPred should be useful for improving genome annotation. The TnpPred web service is freely available for noncommercial use. PMID:23251097

Draft genome sequence of Bradyrhizobium sp. strain BR 3262, an effective microsymbiont recommended for cowpea inoculation in Brazil.

PubMed

Simões-Araújo, Jean Luiz; Leite, Jakson; Marie Rouws, Luc Felicianus; Passos, Samuel Ribeiro; Xavier, Gustavo Ribeiro; Rumjanek, Norma Gouvêa; Zilli, Jerri Édson

The strain BR 3262 was isolated from nodule of cowpea (Vigna unguiculata L. Walp) growing in soil of the Atlantic Forest area in Brazil and it is reported as an efficient nitrogen fixing bacterium associated to cowpea. Firstly, this strain was assigned as Bradyrhizobium elkanii, however, recently a more detailed genetic and molecular characterization has indicated it could be a Bradyrhizobium pachyrhizi species. We report here the draft genome sequence of B. pachyrhizi strain BR 3262, an elite bacterium used as inoculant for cowpea. The whole genome with 116 scaffolds, 8,965,178bp and 63.8% of C+G content for BR 3262 was obtained using Illumina MiSeq sequencing technology. Annotation was added by the RAST prokaryotic genome annotation service and shown 8369 coding sequences, 52 RNAs genes, classified in 504 subsystems. Published by Elsevier Editora Ltda.

Annotation, submission and screening of repetitive elements in Repbase: RepbaseSubmitter and Censor.

PubMed

Kohany, Oleksiy; Gentles, Andrew J; Hankus, Lukasz; Jurka, Jerzy

2006-10-25

Repbase is a reference database of eukaryotic repetitive DNA, which includes prototypic sequences of repeats and basic information described in annotations. Updating and maintenance of the database requires specialized tools, which we have created and made available for use with Repbase, and which may be useful as a template for other curated databases. We describe the software tools RepbaseSubmitter and Censor, which are designed to facilitate updating and screening the content of Repbase. RepbaseSubmitter is a java-based interface for formatting and annotating Repbase entries. It eliminates many common formatting errors, and automates actions such as calculation of sequence lengths and composition, thus facilitating curation of Repbase sequences. In addition, it has several features for predicting protein coding regions in sequences; searching and including Pubmed references in Repbase entries; and searching the NCBI taxonomy database for correct inclusion of species information and taxonomic position. Censor is a tool to rapidly identify repetitive elements by comparison to known repeats. It uses WU-BLAST for speed and sensitivity, and can conduct DNA-DNA, DNA-protein, or translated DNA-translated DNA searches of genomic sequence. Defragmented output includes a map of repeats present in the query sequence, with the options to report masked query sequence(s), repeat sequences found in the query, and alignments. Censor and RepbaseSubmitter are available as both web-based services and downloadable versions. They can be found at http://www.girinst.org/repbase/submission.html (RepbaseSubmitter) and http://www.girinst.org/censor/index.php (Censor).

SOBA: sequence ontology bioinformatics analysis.

PubMed

Moore, Barry; Fan, Guozhen; Eilbeck, Karen

2010-07-01

The advent of cheaper, faster sequencing technologies has pushed the task of sequence annotation from the exclusive domain of large-scale multi-national sequencing projects to that of research laboratories and small consortia. The bioinformatics burden placed on these laboratories, some with very little programming experience can be daunting. Fortunately, there exist software libraries and pipelines designed with these groups in mind, to ease the transition from an assembled genome to an annotated and accessible genome resource. We have developed the Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome. We envisage its use during annotation jamborees, genome comparison and for use by developers for rapid feedback during annotation software development and testing. SOBA also provides annotation consistency feedback to ensure correct use of terminology within annotations, and guides users to add new terms to the Sequence Ontology when required. SOBA is available at http://www.sequenceontology.org/cgi-bin/soba.cgi.

An efficient annotation and gene-expression derivation tool for Illumina Solexa datasets.

PubMed

Hosseini, Parsa; Tremblay, Arianne; Matthews, Benjamin F; Alkharouf, Nadim W

2010-07-02

The data produced by an Illumina flow cell with all eight lanes occupied, produces well over a terabyte worth of images with gigabytes of reads following sequence alignment. The ability to translate such reads into meaningful annotation is therefore of great concern and importance. Very easily, one can get flooded with such a great volume of textual, unannotated data irrespective of read quality or size. CASAVA, a optional analysis tool for Illumina sequencing experiments, enables the ability to understand INDEL detection, SNP information, and allele calling. To not only extract from such analysis, a measure of gene expression in the form of tag-counts, but furthermore to annotate such reads is therefore of significant value. We developed TASE (Tag counting and Analysis of Solexa Experiments), a rapid tag-counting and annotation software tool specifically designed for Illumina CASAVA sequencing datasets. Developed in Java and deployed using jTDS JDBC driver and a SQL Server backend, TASE provides an extremely fast means of calculating gene expression through tag-counts while annotating sequenced reads with the gene's presumed function, from any given CASAVA-build. Such a build is generated for both DNA and RNA sequencing. Analysis is broken into two distinct components: DNA sequence or read concatenation, followed by tag-counting and annotation. The end result produces output containing the homology-based functional annotation and respective gene expression measure signifying how many times sequenced reads were found within the genomic ranges of functional annotations. TASE is a powerful tool to facilitate the process of annotating a given Illumina Solexa sequencing dataset. Our results indicate that both homology-based annotation and tag-count analysis are achieved in very efficient times, providing researchers to delve deep in a given CASAVA-build and maximize information extraction from a sequencing dataset. TASE is specially designed to translate sequence data in a CASAVA-build into functional annotations while producing corresponding gene expression measurements. Achieving such analysis is executed in an ultrafast and highly efficient manner, whether the analysis be a single-read or paired-end sequencing experiment. TASE is a user-friendly and freely available application, allowing rapid analysis and annotation of any given Illumina Solexa sequencing dataset with ease.

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

FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation.

PubMed

Bolleman, Jerven T; Mungall, Christopher J; Strozzi, Francesco; Baran, Joachim; Dumontier, Michel; Bonnal, Raoul J P; Buels, Robert; Hoehndorf, Robert; Fujisawa, Takatomo; Katayama, Toshiaki; Cock, Peter J A

2016-06-13

Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that described this potentially complex location information as subject-predicate-object triples. We have developed an ontology, the Feature Annotation Location Description Ontology (FALDO), to describe the positions of annotated features on linear and circular sequences. FALDO can be used to describe nucleotide features in sequence records, protein annotations, and glycan binding sites, among other features in coordinate systems of the aforementioned "omics" areas. Using the same data format to represent sequence positions that are independent of file formats allows us to integrate sequence data from multiple sources and data types. The genome browser JBrowse is used to demonstrate accessing multiple SPARQL endpoints to display genomic feature annotations, as well as protein annotations from UniProt mapped to genomic locations. Our ontology allows users to uniformly describe - and potentially merge - sequence annotations from multiple sources. Data sources using FALDO can prospectively be retrieved using federalised SPARQL queries against public SPARQL endpoints and/or local private triple stores.

FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation

DOE PAGES

Bolleman, Jerven T.; Mungall, Christopher J.; Strozzi, Francesco; ...

2016-06-13

Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that described this potentially complex location information as subject-predicate-object triples. In this paper, we have developed an ontology, the Feature Annotation Location Description Ontology (FALDO), to describe the positions of annotated features on linear and circular sequences. FALDO can be used to describe nucleotide features in sequence records, protein annotations, and glycan binding sites, among other features in coordinate systems of the aforementioned “omics” areas. Using the same data formatmore » to represent sequence positions that are independent of file formats allows us to integrate sequence data from multiple sources and data types. The genome browser JBrowse is used to demonstrate accessing multiple SPARQL endpoints to display genomic feature annotations, as well as protein annotations from UniProt mapped to genomic locations. Our ontology allows users to uniformly describe – and potentially merge – sequence annotations from multiple sources. Finally, data sources using FALDO can prospectively be retrieved using federalised SPARQL queries against public SPARQL endpoints and/or local private triple stores.« less

FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation

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

Bolleman, Jerven T.; Mungall, Christopher J.; Strozzi, Francesco

Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that described this potentially complex location information as subject-predicate-object triples. In this paper, we have developed an ontology, the Feature Annotation Location Description Ontology (FALDO), to describe the positions of annotated features on linear and circular sequences. FALDO can be used to describe nucleotide features in sequence records, protein annotations, and glycan binding sites, among other features in coordinate systems of the aforementioned “omics” areas. Using the same data formatmore » to represent sequence positions that are independent of file formats allows us to integrate sequence data from multiple sources and data types. The genome browser JBrowse is used to demonstrate accessing multiple SPARQL endpoints to display genomic feature annotations, as well as protein annotations from UniProt mapped to genomic locations. Our ontology allows users to uniformly describe – and potentially merge – sequence annotations from multiple sources. Finally, data sources using FALDO can prospectively be retrieved using federalised SPARQL queries against public SPARQL endpoints and/or local private triple stores.« less

Protein sequence annotation in the genome era: the annotation concept of SWISS-PROT+TREMBL.

PubMed

Apweiler, R; Gateau, A; Contrino, S; Martin, M J; Junker, V; O'Donovan, C; Lang, F; Mitaritonna, N; Kappus, S; Bairoch, A

1997-01-01

SWISS-PROT is a curated protein sequence database which strives to provide a high level of annotation, a minimal level of redundancy and high level of integration with other databases. Ongoing genome sequencing projects have dramatically increased the number of protein sequences to be incorporated into SWISS-PROT. Since we do not want to dilute the quality standards of SWISS-PROT by incorporating sequences without proper sequence analysis and annotation, we cannot speed up the incorporation of new incoming data indefinitely. However, as we also want to make the sequences available as fast as possible, we introduced TREMBL (TRanslation of EMBL nucleotide sequence database), a supplement to SWISS-PROT. TREMBL consists of computer-annotated entries in SWISS-PROT format derived from the translation of all coding sequences (CDS) in the EMBL nucleotide sequence database, except for CDS already included in SWISS-PROT. While TREMBL is already of immense value, its computer-generated annotation does not match the quality of SWISS-PROTs. The main difference is in the protein functional information attached to sequences. With this in mind, we are dedicating substantial effort to develop and apply computer methods to enhance the functional information attached to TREMBL entries.

GGRNA: an ultrafast, transcript-oriented search engine for genes and transcripts

PubMed Central

Naito, Yuki; Bono, Hidemasa

2012-01-01

GGRNA (http://GGRNA.dbcls.jp/) is a Google-like, ultrafast search engine for genes and transcripts. The web server accepts arbitrary words and phrases, such as gene names, IDs, gene descriptions, annotations of gene and even nucleotide/amino acid sequences through one simple search box, and quickly returns relevant RefSeq transcripts. A typical search takes just a few seconds, which dramatically enhances the usability of routine searching. In particular, GGRNA can search sequences as short as 10 nt or 4 amino acids, which cannot be handled easily by popular sequence analysis tools. Nucleotide sequences can be searched allowing up to three mismatches, or the query sequences may contain degenerate nucleotide codes (e.g. N, R, Y, S). Furthermore, Gene Ontology annotations, Enzyme Commission numbers and probe sequences of catalog microarrays are also incorporated into GGRNA, which may help users to conduct searches by various types of keywords. GGRNA web server will provide a simple and powerful interface for finding genes and transcripts for a wide range of users. All services at GGRNA are provided free of charge to all users. PMID:22641850

GGRNA: an ultrafast, transcript-oriented search engine for genes and transcripts.

PubMed

Naito, Yuki; Bono, Hidemasa

2012-07-01

GGRNA (http://GGRNA.dbcls.jp/) is a Google-like, ultrafast search engine for genes and transcripts. The web server accepts arbitrary words and phrases, such as gene names, IDs, gene descriptions, annotations of gene and even nucleotide/amino acid sequences through one simple search box, and quickly returns relevant RefSeq transcripts. A typical search takes just a few seconds, which dramatically enhances the usability of routine searching. In particular, GGRNA can search sequences as short as 10 nt or 4 amino acids, which cannot be handled easily by popular sequence analysis tools. Nucleotide sequences can be searched allowing up to three mismatches, or the query sequences may contain degenerate nucleotide codes (e.g. N, R, Y, S). Furthermore, Gene Ontology annotations, Enzyme Commission numbers and probe sequences of catalog microarrays are also incorporated into GGRNA, which may help users to conduct searches by various types of keywords. GGRNA web server will provide a simple and powerful interface for finding genes and transcripts for a wide range of users. All services at GGRNA are provided free of charge to all users.

An efficient annotation and gene-expression derivation tool for Illumina Solexa datasets

PubMed Central

2010-01-01

Background The data produced by an Illumina flow cell with all eight lanes occupied, produces well over a terabyte worth of images with gigabytes of reads following sequence alignment. The ability to translate such reads into meaningful annotation is therefore of great concern and importance. Very easily, one can get flooded with such a great volume of textual, unannotated data irrespective of read quality or size. CASAVA, a optional analysis tool for Illumina sequencing experiments, enables the ability to understand INDEL detection, SNP information, and allele calling. To not only extract from such analysis, a measure of gene expression in the form of tag-counts, but furthermore to annotate such reads is therefore of significant value. Findings We developed TASE (Tag counting and Analysis of Solexa Experiments), a rapid tag-counting and annotation software tool specifically designed for Illumina CASAVA sequencing datasets. Developed in Java and deployed using jTDS JDBC driver and a SQL Server backend, TASE provides an extremely fast means of calculating gene expression through tag-counts while annotating sequenced reads with the gene's presumed function, from any given CASAVA-build. Such a build is generated for both DNA and RNA sequencing. Analysis is broken into two distinct components: DNA sequence or read concatenation, followed by tag-counting and annotation. The end result produces output containing the homology-based functional annotation and respective gene expression measure signifying how many times sequenced reads were found within the genomic ranges of functional annotations. Conclusions TASE is a powerful tool to facilitate the process of annotating a given Illumina Solexa sequencing dataset. Our results indicate that both homology-based annotation and tag-count analysis are achieved in very efficient times, providing researchers to delve deep in a given CASAVA-build and maximize information extraction from a sequencing dataset. TASE is specially designed to translate sequence data in a CASAVA-build into functional annotations while producing corresponding gene expression measurements. Achieving such analysis is executed in an ultrafast and highly efficient manner, whether the analysis be a single-read or paired-end sequencing experiment. TASE is a user-friendly and freely available application, allowing rapid analysis and annotation of any given Illumina Solexa sequencing dataset with ease. PMID:20598141

The Proteins API: accessing key integrated protein and genome information

PubMed Central

Antunes, Ricardo; Alpi, Emanuele; Gonzales, Leonardo; Liu, Wudong; Luo, Jie; Qi, Guoying; Turner, Edd

2017-01-01

Abstract The Proteins API provides searching and programmatic access to protein and associated genomics data such as curated protein sequence positional annotations from UniProtKB, as well as mapped variation and proteomics data from large scale data sources (LSS). Using the coordinates service, researchers are able to retrieve the genomic sequence coordinates for proteins in UniProtKB. This, the LSS genomics and proteomics data for UniProt proteins is programmatically only available through this service. A Swagger UI has been implemented to provide documentation, an interface for users, with little or no programming experience, to ‘talk’ to the services to quickly and easily formulate queries with the services and obtain dynamically generated source code for popular programming languages, such as Java, Perl, Python and Ruby. Search results are returned as standard JSON, XML or GFF data objects. The Proteins API is a scalable, reliable, fast, easy to use RESTful services that provides a broad protein information resource for users to ask questions based upon their field of expertise and allowing them to gain an integrated overview of protein annotations available to aid their knowledge gain on proteins in biological processes. The Proteins API is available at (http://www.ebi.ac.uk/proteins/api/doc). PMID:28383659

The Proteins API: accessing key integrated protein and genome information.

PubMed

Nightingale, Andrew; Antunes, Ricardo; Alpi, Emanuele; Bursteinas, Borisas; Gonzales, Leonardo; Liu, Wudong; Luo, Jie; Qi, Guoying; Turner, Edd; Martin, Maria

2017-07-03

The Proteins API provides searching and programmatic access to protein and associated genomics data such as curated protein sequence positional annotations from UniProtKB, as well as mapped variation and proteomics data from large scale data sources (LSS). Using the coordinates service, researchers are able to retrieve the genomic sequence coordinates for proteins in UniProtKB. This, the LSS genomics and proteomics data for UniProt proteins is programmatically only available through this service. A Swagger UI has been implemented to provide documentation, an interface for users, with little or no programming experience, to 'talk' to the services to quickly and easily formulate queries with the services and obtain dynamically generated source code for popular programming languages, such as Java, Perl, Python and Ruby. Search results are returned as standard JSON, XML or GFF data objects. The Proteins API is a scalable, reliable, fast, easy to use RESTful services that provides a broad protein information resource for users to ask questions based upon their field of expertise and allowing them to gain an integrated overview of protein annotations available to aid their knowledge gain on proteins in biological processes. The Proteins API is available at (http://www.ebi.ac.uk/proteins/api/doc). © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

MitoFish and MitoAnnotator: A Mitochondrial Genome Database of Fish with an Accurate and Automatic Annotation Pipeline

PubMed Central

Iwasaki, Wataru; Fukunaga, Tsukasa; Isagozawa, Ryota; Yamada, Koichiro; Maeda, Yasunobu; Satoh, Takashi P.; Sado, Tetsuya; Mabuchi, Kohji; Takeshima, Hirohiko; Miya, Masaki; Nishida, Mutsumi

2013-01-01

Mitofish is a database of fish mitochondrial genomes (mitogenomes) that includes powerful and precise de novo annotations for mitogenome sequences. Fish occupy an important position in the evolution of vertebrates and the ecology of the hydrosphere, and mitogenomic sequence data have served as a rich source of information for resolving fish phylogenies and identifying new fish species. The importance of a mitogenomic database continues to grow at a rapid pace as massive amounts of mitogenomic data are generated with the advent of new sequencing technologies. A severe bottleneck seems likely to occur with regard to mitogenome annotation because of the overwhelming pace of data accumulation and the intrinsic difficulties in annotating sequences with degenerating transfer RNA structures, divergent start/stop codons of the coding elements, and the overlapping of adjacent elements. To ease this data backlog, we developed an annotation pipeline named MitoAnnotator. MitoAnnotator automatically annotates a fish mitogenome with a high degree of accuracy in approximately 5 min; thus, it is readily applicable to data sets of dozens of sequences. MitoFish also contains re-annotations of previously sequenced fish mitogenomes, enabling researchers to refer to them when they find annotations that are likely to be erroneous or while conducting comparative mitogenomic analyses. For users who need more information on the taxonomy, habitats, phenotypes, or life cycles of fish, MitoFish provides links to related databases. MitoFish and MitoAnnotator are freely available at http://mitofish.aori.u-tokyo.ac.jp/ (last accessed August 28, 2013); all of the data can be batch downloaded, and the annotation pipeline can be used via a web interface. PMID:23955518

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.

CHOgenome.org 2.0: Genome resources and website updates.

PubMed

Kremkow, Benjamin G; Baik, Jong Youn; MacDonald, Madolyn L; Lee, Kelvin H

2015-07-01

Chinese hamster ovary (CHO) cells are a major host cell line for the production of therapeutic proteins, and CHO cell and Chinese hamster (CH) genomes have recently been sequenced using next-generation sequencing methods. CHOgenome.org was launched in 2011 (version 1.0) to serve as a database repository and to provide bioinformatics tools for the CHO community. CHOgenome.org (version 1.0) maintained GenBank CHO-K1 genome data, identified CHO-omics literature, and provided a CHO-specific BLAST service. Recent major updates to CHOgenome.org (version 2.0) include new sequence and annotation databases for both CHO and CH genomes, a more user-friendly website, and new research tools, including a proteome browser and a genome viewer. CHO cell-line specific sequences and annotations facilitate cell line development opportunities, several of which are discussed. Moving forward, CHOgenome.org will host the increasing amount of CHO-omics data and continue to make useful bioinformatics tools available to the CHO community. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Tidying Up International Nucleotide Sequence Databases: Ecological, Geographical and Sequence Quality Annotation of ITS Sequences of Mycorrhizal Fungi

PubMed Central

Tedersoo, Leho; Abarenkov, Kessy; Nilsson, R. Henrik; Schüssler, Arthur; Grelet, Gwen-Aëlle; Kohout, Petr; Oja, Jane; Bonito, Gregory M.; Veldre, Vilmar; Jairus, Teele; Ryberg, Martin; Larsson, Karl-Henrik; Kõljalg, Urmas

2011-01-01

Sequence analysis of the ribosomal RNA operon, particularly the internal transcribed spacer (ITS) region, provides a powerful tool for identification of mycorrhizal fungi. The sequence data deposited in the International Nucleotide Sequence Databases (INSD) are, however, unfiltered for quality and are often poorly annotated with metadata. To detect chimeric and low-quality sequences and assign the ectomycorrhizal fungi to phylogenetic lineages, fungal ITS sequences were downloaded from INSD, aligned within family-level groups, and examined through phylogenetic analyses and BLAST searches. By combining the fungal sequence database UNITE and the annotation and search tool PlutoF, we also added metadata from the literature to these accessions. Altogether 35,632 sequences belonged to mycorrhizal fungi or originated from ericoid and orchid mycorrhizal roots. Of these sequences, 677 were considered chimeric and 2,174 of low read quality. Information detailing country of collection, geographical coordinates, interacting taxon and isolation source were supplemented to cover 78.0%, 33.0%, 41.7% and 96.4% of the sequences, respectively. These annotated sequences are publicly available via UNITE (http://unite.ut.ee/) for downstream biogeographic, ecological and taxonomic analyses. In European Nucleotide Archive (ENA; http://www.ebi.ac.uk/ena/), the annotated sequences have a special link-out to UNITE. We intend to expand the data annotation to additional genes and all taxonomic groups and functional guilds of fungi. PMID:21949797

Superior ab initio identification, annotation and characterisation of TEs and segmental duplications from genome assemblies.

PubMed

Zeng, Lu; Kortschak, R Daniel; Raison, Joy M; Bertozzi, Terry; Adelson, David L

2018-01-01

Transposable Elements (TEs) are mobile DNA sequences that make up significant fractions of amniote genomes. However, they are difficult to detect and annotate ab initio because of their variable features, lengths and clade-specific variants. We have addressed this problem by refining and developing a Comprehensive ab initio Repeat Pipeline (CARP) to identify and cluster TEs and other repetitive sequences in genome assemblies. The pipeline begins with a pairwise alignment using krishna, a custom aligner. Single linkage clustering is then carried out to produce families of repetitive elements. Consensus sequences are then filtered for protein coding genes and then annotated using Repbase and a custom library of retrovirus and reverse transcriptase sequences. This process yields three types of family: fully annotated, partially annotated and unannotated. Fully annotated families reflect recently diverged/young known TEs present in Repbase. The remaining two types of families contain a mixture of novel TEs and segmental duplications. These can be resolved by aligning these consensus sequences back to the genome to assess copy number vs. length distribution. Our pipeline has three significant advantages compared to other methods for ab initio repeat identification: 1) we generate not only consensus sequences, but keep the genomic intervals for the original aligned sequences, allowing straightforward analysis of evolutionary dynamics, 2) consensus sequences represent low-divergence, recently/currently active TE families, 3) segmental duplications are annotated as a useful by-product. We have compared our ab initio repeat annotations for 7 genome assemblies to other methods and demonstrate that CARP compares favourably with RepeatModeler, the most widely used repeat annotation package.

Superior ab initio identification, annotation and characterisation of TEs and segmental duplications from genome assemblies

PubMed Central

Zeng, Lu; Kortschak, R. Daniel; Raison, Joy M.

2018-01-01

Transposable Elements (TEs) are mobile DNA sequences that make up significant fractions of amniote genomes. However, they are difficult to detect and annotate ab initio because of their variable features, lengths and clade-specific variants. We have addressed this problem by refining and developing a Comprehensive ab initio Repeat Pipeline (CARP) to identify and cluster TEs and other repetitive sequences in genome assemblies. The pipeline begins with a pairwise alignment using krishna, a custom aligner. Single linkage clustering is then carried out to produce families of repetitive elements. Consensus sequences are then filtered for protein coding genes and then annotated using Repbase and a custom library of retrovirus and reverse transcriptase sequences. This process yields three types of family: fully annotated, partially annotated and unannotated. Fully annotated families reflect recently diverged/young known TEs present in Repbase. The remaining two types of families contain a mixture of novel TEs and segmental duplications. These can be resolved by aligning these consensus sequences back to the genome to assess copy number vs. length distribution. Our pipeline has three significant advantages compared to other methods for ab initio repeat identification: 1) we generate not only consensus sequences, but keep the genomic intervals for the original aligned sequences, allowing straightforward analysis of evolutionary dynamics, 2) consensus sequences represent low-divergence, recently/currently active TE families, 3) segmental duplications are annotated as a useful by-product. We have compared our ab initio repeat annotations for 7 genome assemblies to other methods and demonstrate that CARP compares favourably with RepeatModeler, the most widely used repeat annotation package. PMID:29538441

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.

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

MIPS bacterial genomes functional annotation benchmark dataset.

PubMed

Tetko, Igor V; Brauner, Barbara; Dunger-Kaltenbach, Irmtraud; Frishman, Goar; Montrone, Corinna; Fobo, Gisela; Ruepp, Andreas; Antonov, Alexey V; Surmeli, Dimitrij; Mewes, Hans-Wernen

2005-05-15

Any development of new methods for automatic functional annotation of proteins according to their sequences requires high-quality data (as benchmark) as well as tedious preparatory work to generate sequence parameters required as input data for the machine learning methods. Different program settings and incompatible protocols make a comparison of the analyzed methods difficult. The MIPS Bacterial Functional Annotation Benchmark dataset (MIPS-BFAB) is a new, high-quality resource comprising four bacterial genomes manually annotated according to the MIPS functional catalogue (FunCat). These resources include precalculated sequence parameters, such as sequence similarity scores, InterPro domain composition and other parameters that could be used to develop and benchmark methods for functional annotation of bacterial protein sequences. These data are provided in XML format and can be used by scientists who are not necessarily experts in genome annotation. BFAB is available at http://mips.gsf.de/proj/bfab

NLSdb-major update for database of nuclear localization signals and nuclear export signals.

PubMed

Bernhofer, Michael; Goldberg, Tatyana; Wolf, Silvana; Ahmed, Mohamed; Zaugg, Julian; Boden, Mikael; Rost, Burkhard

2018-01-04

NLSdb is a database collecting nuclear export signals (NES) and nuclear localization signals (NLS) along with experimentally annotated nuclear and non-nuclear proteins. NES and NLS are short sequence motifs related to protein transport out of and into the nucleus. The updated NLSdb now contains 2253 NLS and introduces 398 NES. The potential sets of novel NES and NLS have been generated by a simple 'in silico mutagenesis' protocol. We started with motifs annotated by experiments. In step 1, we increased specificity such that no known non-nuclear protein matched the refined motif. In step 2, we increased the sensitivity trying to match several different families with a motif. We then iterated over steps 1 and 2. The final set of 2253 NLS motifs matched 35% of 8421 experimentally verified nuclear proteins (up from 21% for the previous version) and none of 18 278 non-nuclear proteins. We updated the web interface providing multiple options to search protein sequences for NES and NLS motifs, and to evaluate your own signal sequences. NLSdb can be accessed via Rostlab services at: https://rostlab.org/services/nlsdb/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

Aggregating and Predicting Sequence Labels from Crowd Annotations

PubMed Central

Nguyen, An T.; Wallace, Byron C.; Li, Junyi Jessy; Nenkova, Ani; Lease, Matthew

2017-01-01

Despite sequences being core to NLP, scant work has considered how to handle noisy sequence labels from multiple annotators for the same text. Given such annotations, we consider two complementary tasks: (1) aggregating sequential crowd labels to infer a best single set of consensus annotations; and (2) using crowd annotations as training data for a model that can predict sequences in unannotated text. For aggregation, we propose a novel Hidden Markov Model variant. To predict sequences in unannotated text, we propose a neural approach using Long Short Term Memory. We evaluate a suite of methods across two different applications and text genres: Named-Entity Recognition in news articles and Information Extraction from biomedical abstracts. Results show improvement over strong baselines. Our source code and data are available online1. PMID:29093611

GFam: a platform for automatic annotation of gene families.

PubMed

Sasidharan, Rajkumar; Nepusz, Tamás; Swarbreck, David; Huala, Eva; Paccanaro, Alberto

2012-10-01

We have developed GFam, a platform for automatic annotation of gene/protein families. GFam provides a framework for genome initiatives and model organism resources to build domain-based families, derive meaningful functional labels and offers a seamless approach to propagate functional annotation across periodic genome updates. GFam is a hybrid approach that uses a greedy algorithm to chain component domains from InterPro annotation provided by its 12 member resources followed by a sequence-based connected component analysis of un-annotated sequence regions to derive consensus domain architecture for each sequence and subsequently generate families based on common architectures. Our integrated approach increases sequence coverage by 7.2 percentage points and residue coverage by 14.6 percentage points higher than the coverage relative to the best single-constituent database within InterPro for the proteome of Arabidopsis. The true power of GFam lies in maximizing annotation provided by the different InterPro data sources that offer resource-specific coverage for different regions of a sequence. GFam's capability to capture higher sequence and residue coverage can be useful for genome annotation, comparative genomics and functional studies. GFam is a general-purpose software and can be used for any collection of protein sequences. The software is open source and can be obtained from http://www.paccanarolab.org/software/gfam/.

MIPS: analysis and annotation of genome information in 2007

PubMed Central

Mewes, H. W.; Dietmann, S.; Frishman, D.; Gregory, R.; Mannhaupt, G.; Mayer, K. F. X.; Münsterkötter, M.; Ruepp, A.; Spannagl, M.; Stümpflen, V.; Rattei, T.

2008-01-01

The Munich Information Center for Protein Sequences (MIPS-GSF, Neuherberg, Germany) combines automatic processing of large amounts of sequences with manual annotation of selected model genomes. Due to the massive growth of the available data, the depth of annotation varies widely between independent databases. Also, the criteria for the transfer of information from known to orthologous sequences are diverse. To cope with the task of global in-depth genome annotation has become unfeasible. Therefore, our efforts are dedicated to three levels of annotation: (i) the curation of selected genomes, in particular from fungal and plant taxa (e.g. CYGD, MNCDB, MatDB), (ii) the comprehensive, consistent, automatic annotation employing exhaustive methods for the computation of sequence similarities and sequence-related attributes as well as the classification of individual sequences (SIMAP, PEDANT and FunCat) and (iii) the compilation of manually curated databases for protein interactions based on scrutinized information from the literature to serve as an accepted set of reliable annotated interaction data (MPACT, MPPI, CORUM). All databases and tools described as well as the detailed descriptions of our projects can be accessed through the MIPS web server (http://mips.gsf.de). PMID:18158298

MIPS: analysis and annotation of genome information in 2007.

PubMed

Mewes, H W; Dietmann, S; Frishman, D; Gregory, R; Mannhaupt, G; Mayer, K F X; Münsterkötter, M; Ruepp, A; Spannagl, M; Stümpflen, V; Rattei, T

2008-01-01

The Munich Information Center for Protein Sequences (MIPS-GSF, Neuherberg, Germany) combines automatic processing of large amounts of sequences with manual annotation of selected model genomes. Due to the massive growth of the available data, the depth of annotation varies widely between independent databases. Also, the criteria for the transfer of information from known to orthologous sequences are diverse. To cope with the task of global in-depth genome annotation has become unfeasible. Therefore, our efforts are dedicated to three levels of annotation: (i) the curation of selected genomes, in particular from fungal and plant taxa (e.g. CYGD, MNCDB, MatDB), (ii) the comprehensive, consistent, automatic annotation employing exhaustive methods for the computation of sequence similarities and sequence-related attributes as well as the classification of individual sequences (SIMAP, PEDANT and FunCat) and (iii) the compilation of manually curated databases for protein interactions based on scrutinized information from the literature to serve as an accepted set of reliable annotated interaction data (MPACT, MPPI, CORUM). All databases and tools described as well as the detailed descriptions of our projects can be accessed through the MIPS web server (http://mips.gsf.de).

Challenges in Whole-Genome Annotation of Pyrosequenced Eukaryotic Genomes

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

Kuo, Alan; Grigoriev, Igor

2009-04-17

Pyrosequencing technologies such as 454/Roche and Solexa/Illumina vastly lower the cost of nucleotide sequencing compared to the traditional Sanger method, and thus promise to greatly expand the number of sequenced eukaryotic genomes. However, the new technologies also bring new challenges such as shorter reads and new kinds and higher rates of sequencing errors, which complicate genome assembly and gene prediction. At JGI we are deploying 454 technology for the sequencing and assembly of ever-larger eukaryotic genomes. Here we describe our first whole-genome annotation of a purely 454-sequenced fungal genome that is larger than a yeast (>30 Mbp). The pezizomycotine (filamentousmore » ascomycote) Aspergillus carbonarius belongs to the Aspergillus section Nigri species complex, members of which are significant as platforms for bioenergy and bioindustrial technology, as members of soil microbial communities and players in the global carbon cycle, and as agricultural toxigens. Application of a modified version of the standard JGI Annotation Pipeline has so far predicted ~;;10k genes. ~;;12percent of these preliminary annotations suffer a potential frameshift error, which is somewhat higher than the ~;;9percent rate in the Sanger-sequenced and conventionally assembled and annotated genome of fellow Aspergillus section Nigri member A. niger. Also,>90percent of A. niger genes have potential homologs in the A. carbonarius preliminary annotation. Weconclude, and with further annotation and comparative analysis expect to confirm, that 454 sequencing strategies provide a promising substrate for annotation of modestly sized eukaryotic genomes. We will also present results of annotation of a number of other pyrosequenced fungal genomes of bioenergy interest.« less

Bovine Genome Database: supporting community annotation and analysis of the Bos taurus genome

PubMed Central

2010-01-01

Background A goal of the Bovine Genome Database (BGD; http://BovineGenome.org) has been to support the Bovine Genome Sequencing and Analysis Consortium (BGSAC) in the annotation and analysis of the bovine genome. We were faced with several challenges, including the need to maintain consistent quality despite diversity in annotation expertise in the research community, the need to maintain consistent data formats, and the need to minimize the potential duplication of annotation effort. With new sequencing technologies allowing many more eukaryotic genomes to be sequenced, the demand for collaborative annotation is likely to increase. Here we present our approach, challenges and solutions facilitating a large distributed annotation project. Results and Discussion BGD has provided annotation tools that supported 147 members of the BGSAC in contributing 3,871 gene models over a fifteen-week period, and these annotations have been integrated into the bovine Official Gene Set. Our approach has been to provide an annotation system, which includes a BLAST site, multiple genome browsers, an annotation portal, and the Apollo Annotation Editor configured to connect directly to our Chado database. In addition to implementing and integrating components of the annotation system, we have performed computational analyses to create gene evidence tracks and a consensus gene set, which can be viewed on individual gene pages at BGD. Conclusions We have provided annotation tools that alleviate challenges associated with distributed annotation. Our system provides a consistent set of data to all annotators and eliminates the need for annotators to format data. Involving the bovine research community in genome annotation has allowed us to leverage expertise in various areas of bovine biology to provide biological insight into the genome sequence. PMID:21092105

Taverna: a tool for building and running workflows of services

PubMed Central

Hull, Duncan; Wolstencroft, Katy; Stevens, Robert; Goble, Carole; Pocock, Mathew R.; Li, Peter; Oinn, Tom

2006-01-01

Taverna is an application that eases the use and integration of the growing number of molecular biology tools and databases available on the web, especially web services. It allows bioinformaticians to construct workflows or pipelines of services to perform a range of different analyses, such as sequence analysis and genome annotation. These high-level workflows can integrate many different resources into a single analysis. Taverna is available freely under the terms of the GNU Lesser General Public License (LGPL) from . PMID:16845108

Using comparative genome analysis to identify problems in annotated microbial genomes.

PubMed

Poptsova, Maria S; Gogarten, J Peter

2010-07-01

Genome annotation is a tedious task that is mostly done by automated methods; however, the accuracy of these approaches has been questioned since the beginning of the sequencing era. Genome annotation is a multilevel process, and errors can emerge at different stages: during sequencing, as a result of gene-calling procedures, and in the process of assigning gene functions. Missed or wrongly annotated genes differentially impact different types of analyses. Here we discuss and demonstrate how the methods of comparative genome analysis can refine annotations by locating missing orthologues. We also discuss possible reasons for errors and show that the second-generation annotation systems, which combine multiple gene-calling programs with similarity-based methods, perform much better than the first annotation tools. Since old errors may propagate to the newly sequenced genomes, we emphasize that the problem of continuously updating popular public databases is an urgent and unresolved one. Due to the progress in genome-sequencing technologies, automated annotation techniques will remain the main approach in the future. Researchers need to be aware of the existing errors in the annotation of even well-studied genomes, such as Escherichia coli, and consider additional quality control for their results.

SEED Servers: High-Performance Access to the SEED Genomes, Annotations, and Metabolic Models

PubMed Central

Aziz, Ramy K.; Devoid, Scott; Disz, Terrence; Edwards, Robert A.; Henry, Christopher S.; Olsen, Gary J.; Olson, Robert; Overbeek, Ross; Parrello, Bruce; Pusch, Gordon D.; Stevens, Rick L.; Vonstein, Veronika; Xia, Fangfang

2012-01-01

The remarkable advance in sequencing technology and the rising interest in medical and environmental microbiology, biotechnology, and synthetic biology resulted in a deluge of published microbial genomes. Yet, genome annotation, comparison, and modeling remain a major bottleneck to the translation of sequence information into biological knowledge, hence computational analysis tools are continuously being developed for rapid genome annotation and interpretation. Among the earliest, most comprehensive resources for prokaryotic genome analysis, the SEED project, initiated in 2003 as an integration of genomic data and analysis tools, now contains >5,000 complete genomes, a constantly updated set of curated annotations embodied in a large and growing collection of encoded subsystems, a derived set of protein families, and hundreds of genome-scale metabolic models. Until recently, however, maintaining current copies of the SEED code and data at remote locations has been a pressing issue. To allow high-performance remote access to the SEED database, we developed the SEED Servers (http://www.theseed.org/servers): four network-based servers intended to expose the data in the underlying relational database, support basic annotation services, offer programmatic access to the capabilities of the RAST annotation server, and provide access to a growing collection of metabolic models that support flux balance analysis. The SEED servers offer open access to regularly updated data, the ability to annotate prokaryotic genomes, the ability to create metabolic reconstructions and detailed models of metabolism, and access to hundreds of existing metabolic models. This work offers and supports a framework upon which other groups can build independent research efforts. Large integrations of genomic data represent one of the major intellectual resources driving research in biology, and programmatic access to the SEED data will provide significant utility to a broad collection of potential users. PMID:23110173

Apollo: a sequence annotation editor

PubMed Central

Lewis, SE; Searle, SMJ; Harris, N; Gibson, M; Iyer, V; Richter, J; Wiel, C; Bayraktaroglu, L; Birney, E; Crosby, MA; Kaminker, JS; Matthews, BB; Prochnik, SE; Smith, CD; Tupy, JL; Rubin, GM; Misra, S; Mungall, CJ; Clamp, ME

2002-01-01

The well-established inaccuracy of purely computational methods for annotating genome sequences necessitates an interactive tool to allow biological experts to refine these approximations by viewing and independently evaluating the data supporting each annotation. Apollo was developed to meet this need, enabling curators to inspect genome annotations closely and edit them. FlyBase biologists successfully used Apollo to annotate the Drosophila melanogaster genome and it is increasingly being used as a starting point for the development of customized annotation editing tools for other genome projects. PMID:12537571

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.

BioSAVE: display of scored annotation within a sequence context.

PubMed

Pollock, Richard F; Adryan, Boris

2008-03-20

Visualization of sequence annotation is a common feature in many bioinformatics tools. For many applications it is desirable to restrict the display of such annotation according to a score cutoff, as biological interpretation can be difficult in the presence of the entire data. Unfortunately, many visualisation solutions are somewhat static in the way they handle such score cutoffs. We present BioSAVE, a sequence annotation viewer with on-the-fly selection of visualisation thresholds for each feature. BioSAVE is a versatile OS X program for visual display of scored features (annotation) within a sequence context. The program reads sequence and additional supplementary annotation data (e.g., position weight matrix matches, conservation scores, structural domains) from a variety of commonly used file formats and displays them graphically. Onscreen controls then allow for live customisation of these graphics, including on-the-fly selection of visualisation thresholds for each feature. Possible applications of the program include display of transcription factor binding sites in a genomic context or the visualisation of structural domain assignments in protein sequences and many more. The dynamic visualisation of these annotations is useful, e.g., for the determination of cutoff values of predicted features to match experimental data. Program, source code and exemplary files are freely available at the BioSAVE homepage.

BioSAVE: Display of scored annotation within a sequence context

PubMed Central

Pollock, Richard F; Adryan, Boris

2008-01-01

Background Visualization of sequence annotation is a common feature in many bioinformatics tools. For many applications it is desirable to restrict the display of such annotation according to a score cutoff, as biological interpretation can be difficult in the presence of the entire data. Unfortunately, many visualisation solutions are somewhat static in the way they handle such score cutoffs. Results We present BioSAVE, a sequence annotation viewer with on-the-fly selection of visualisation thresholds for each feature. BioSAVE is a versatile OS X program for visual display of scored features (annotation) within a sequence context. The program reads sequence and additional supplementary annotation data (e.g., position weight matrix matches, conservation scores, structural domains) from a variety of commonly used file formats and displays them graphically. Onscreen controls then allow for live customisation of these graphics, including on-the-fly selection of visualisation thresholds for each feature. Conclusion Possible applications of the program include display of transcription factor binding sites in a genomic context or the visualisation of structural domain assignments in protein sequences and many more. The dynamic visualisation of these annotations is useful, e.g., for the determination of cutoff values of predicted features to match experimental data. Program, source code and exemplary files are freely available at the BioSAVE homepage. PMID:18366701

Improved Annotation of 3′ Untranslated Regions and Complex Loci by Combination of Strand-Specific Direct RNA Sequencing, RNA-Seq and ESTs

PubMed Central

Song, Junfang; Duc, Céline; Storey, Kate G.; McLean, W. H. Irwin; Brown, Sara J.; Simpson, Gordon G.; Barton, Geoffrey J.

2014-01-01

The reference annotations made for a genome sequence provide the framework for all subsequent analyses of the genome. Correct and complete annotation in addition to the underlying genomic sequence is particularly important when interpreting the results of RNA-seq experiments where short sequence reads are mapped against the genome and assigned to genes according to the annotation. Inconsistencies in annotations between the reference and the experimental system can lead to incorrect interpretation of the effect on RNA expression of an experimental treatment or mutation in the system under study. Until recently, the genome-wide annotation of 3′ untranslated regions received less attention than coding regions and the delineation of intron/exon boundaries. In this paper, data produced for samples in Human, Chicken and A. thaliana by the novel single-molecule, strand-specific, Direct RNA Sequencing technology from Helicos Biosciences which locates 3′ polyadenylation sites to within +/− 2 nt, were combined with archival EST and RNA-Seq data. Nine examples are illustrated where this combination of data allowed: (1) gene and 3′ UTR re-annotation (including extension of one 3′ UTR by 5.9 kb); (2) disentangling of gene expression in complex regions; (3) clearer interpretation of small RNA expression and (4) identification of novel genes. While the specific examples displayed here may become obsolete as genome sequences and their annotations are refined, the principles laid out in this paper will be of general use both to those annotating genomes and those seeking to interpret existing publically available annotations in the context of their own experimental data. PMID:24722185

Evaluation and integration of functional annotation pipelines for newly sequenced organisms: the potato genome as a test case.

PubMed

Amar, David; Frades, Itziar; Danek, Agnieszka; Goldberg, Tatyana; Sharma, Sanjeev K; Hedley, Pete E; Proux-Wera, Estelle; Andreasson, Erik; Shamir, Ron; Tzfadia, Oren; Alexandersson, Erik

2014-12-05

For most organisms, even if their genome sequence is available, little functional information about individual genes or proteins exists. Several annotation pipelines have been developed for functional analysis based on sequence, 'omics', and literature data. However, researchers encounter little guidance on how well they perform. Here, we used the recently sequenced potato genome as a case study. The potato genome was selected since its genome is newly sequenced and it is a non-model plant even if there is relatively ample information on individual potato genes, and multiple gene expression profiles are available. We show that the automatic gene annotations of potato have low accuracy when compared to a "gold standard" based on experimentally validated potato genes. Furthermore, we evaluate six state-of-the-art annotation pipelines and show that their predictions are markedly dissimilar (Jaccard similarity coefficient of 0.27 between pipelines on average). To overcome this discrepancy, we introduce a simple GO structure-based algorithm that reconciles the predictions of the different pipelines. We show that the integrated annotation covers more genes, increases by over 50% the number of highly co-expressed GO processes, and obtains much higher agreement with the gold standard. We find that different annotation pipelines produce different results, and show how to integrate them into a unified annotation that is of higher quality than each single pipeline. We offer an improved functional annotation of both PGSC and ITAG potato gene models, as well as tools that can be applied to additional pipelines and improve annotation in other organisms. This will greatly aid future functional analysis of '-omics' datasets from potato and other organisms with newly sequenced genomes. The new potato annotations are available with this paper.

ORCAN-a web-based meta-server for real-time detection and functional annotation of orthologs.

PubMed

Zielezinski, Andrzej; Dziubek, Michal; Sliski, Jan; Karlowski, Wojciech M

2017-04-15

ORCAN (ORtholog sCANner) is a web-based meta-server for one-click evolutionary and functional annotation of protein sequences. The server combines information from the most popular orthology-prediction resources, including four tools and four online databases. Functional annotation utilizes five additional comparisons between the query and identified homologs, including: sequence similarity, protein domain architectures, functional motifs, Gene Ontology term assignments and a list of associated articles. Furthermore, the server uses a plurality-based rating system to evaluate the orthology relationships and to rank the reference proteins by their evolutionary and functional relevance to the query. Using a dataset of ∼1 million true yeast orthologs as a sample reference set, we show that combining multiple orthology-prediction tools in ORCAN increases the sensitivity and precision by 1-2 percent points. The service is available for free at http://www.combio.pl/orcan/ . wmk@amu.edu.pl. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Similarity-based gene detection: using COGs to find evolutionarily-conserved ORFs.

PubMed

Powell, Bradford C; Hutchison, Clyde A

2006-01-19

Experimental verification of gene products has not kept pace with the rapid growth of microbial sequence information. However, existing annotations of gene locations contain sufficient information to screen for probable errors. Furthermore, comparisons among genomes become more informative as more genomes are examined. We studied all open reading frames (ORFs) of at least 30 codons from the genomes of 27 sequenced bacterial strains. We grouped the potential peptide sequences encoded from the ORFs by forming Clusters of Orthologous Groups (COGs). We used this grouping in order to find homologous relationships that would not be distinguishable from noise when using simple BLAST searches. Although COG analysis was initially developed to group annotated genes, we applied it to the task of grouping anonymous DNA sequences that may encode proteins. "Mixed COGs" of ORFs (clusters in which some sequences correspond to annotated genes and some do not) are attractive targets when seeking errors of gene prediction. Examination of mixed COGs reveals some situations in which genes appear to have been missed in current annotations and a smaller number of regions that appear to have been annotated as gene loci erroneously. This technique can also be used to detect potential pseudogenes or sequencing errors. Our method uses an adjustable parameter for degree of conservation among the studied genomes (stringency). We detail results for one level of stringency at which we found 83 potential genes which had not previously been identified, 60 potential pseudogenes, and 7 sequences with existing gene annotations that are probably incorrect. Systematic study of sequence conservation offers a way to improve existing annotations by identifying potentially homologous regions where the annotation of the presence or absence of a gene is inconsistent among genomes.

Similarity-based gene detection: using COGs to find evolutionarily-conserved ORFs

PubMed Central

Powell, Bradford C; Hutchison, Clyde A

2006-01-01

Background Experimental verification of gene products has not kept pace with the rapid growth of microbial sequence information. However, existing annotations of gene locations contain sufficient information to screen for probable errors. Furthermore, comparisons among genomes become more informative as more genomes are examined. We studied all open reading frames (ORFs) of at least 30 codons from the genomes of 27 sequenced bacterial strains. We grouped the potential peptide sequences encoded from the ORFs by forming Clusters of Orthologous Groups (COGs). We used this grouping in order to find homologous relationships that would not be distinguishable from noise when using simple BLAST searches. Although COG analysis was initially developed to group annotated genes, we applied it to the task of grouping anonymous DNA sequences that may encode proteins. Results "Mixed COGs" of ORFs (clusters in which some sequences correspond to annotated genes and some do not) are attractive targets when seeking errors of gene predicion. Examination of mixed COGs reveals some situations in which genes appear to have been missed in current annotations and a smaller number of regions that appear to have been annotated as gene loci erroneously. This technique can also be used to detect potential pseudogenes or sequencing errors. Our method uses an adjustable parameter for degree of conservation among the studied genomes (stringency). We detail results for one level of stringency at which we found 83 potential genes which had not previously been identified, 60 potential pseudogenes, and 7 sequences with existing gene annotations that are probably incorrect. Conclusion Systematic study of sequence conservation offers a way to improve existing annotations by identifying potentially homologous regions where the annotation of the presence or absence of a gene is inconsistent among genomes. PMID:16423288

ASGARD: an open-access database of annotated transcriptomes for emerging model arthropod species.

PubMed

Zeng, Victor; Extavour, Cassandra G

2012-01-01

The increased throughput and decreased cost of next-generation sequencing (NGS) have shifted the bottleneck genomic research from sequencing to annotation, analysis and accessibility. This is particularly challenging for research communities working on organisms that lack the basic infrastructure of a sequenced genome, or an efficient way to utilize whatever sequence data may be available. Here we present a new database, the Assembled Searchable Giant Arthropod Read Database (ASGARD). This database is a repository and search engine for transcriptomic data from arthropods that are of high interest to multiple research communities but currently lack sequenced genomes. We demonstrate the functionality and utility of ASGARD using de novo assembled transcriptomes from the milkweed bug Oncopeltus fasciatus, the cricket Gryllus bimaculatus and the amphipod crustacean Parhyale hawaiensis. We have annotated these transcriptomes to assign putative orthology, coding region determination, protein domain identification and Gene Ontology (GO) term annotation to all possible assembly products. ASGARD allows users to search all assemblies by orthology annotation, GO term annotation or Basic Local Alignment Search Tool. User-friendly features of ASGARD include search term auto-completion suggestions based on database content, the ability to download assembly product sequences in FASTA format, direct links to NCBI data for predicted orthologs and graphical representation of the location of protein domains and matches to similar sequences from the NCBI non-redundant database. ASGARD will be a useful repository for transcriptome data from future NGS studies on these and other emerging model arthropods, regardless of sequencing platform, assembly or annotation status. This database thus provides easy, one-stop access to multi-species annotated transcriptome information. We anticipate that this database will be useful for members of multiple research communities, including developmental biology, physiology, evolutionary biology, ecology, comparative genomics and phylogenomics. Database URL: asgard.rc.fas.harvard.edu.

RATT: Rapid Annotation Transfer Tool

PubMed Central

Otto, Thomas D.; Dillon, Gary P.; Degrave, Wim S.; Berriman, Matthew

2011-01-01

Second-generation sequencing technologies have made large-scale sequencing projects commonplace. However, making use of these datasets often requires gene function to be ascribed genome wide. Although tool development has kept pace with the changes in sequence production, for tasks such as mapping, de novo assembly or visualization, genome annotation remains a challenge. We have developed a method to rapidly provide accurate annotation for new genomes using previously annotated genomes as a reference. The method, implemented in a tool called RATT (Rapid Annotation Transfer Tool), transfers annotations from a high-quality reference to a new genome on the basis of conserved synteny. We demonstrate that a Mycobacterium tuberculosis genome or a single 2.5 Mb chromosome from a malaria parasite can be annotated in less than five minutes with only modest computational resources. RATT is available at http://ratt.sourceforge.net. PMID:21306991

AutoFACT: An Automatic Functional Annotation and Classification Tool

PubMed Central

Koski, Liisa B; Gray, Michael W; Lang, B Franz; Burger, Gertraud

2005-01-01

Background Assignment of function to new molecular sequence data is an essential step in genomics projects. The usual process involves similarity searches of a given sequence against one or more databases, an arduous process for large datasets. Results We present AutoFACT, a fully automated and customizable annotation tool that assigns biologically informative functions to a sequence. Key features of this tool are that it (1) analyzes nucleotide and protein sequence data; (2) determines the most informative functional description by combining multiple BLAST reports from several user-selected databases; (3) assigns putative metabolic pathways, functional classes, enzyme classes, GeneOntology terms and locus names; and (4) generates output in HTML, text and GFF formats for the user's convenience. We have compared AutoFACT to four well-established annotation pipelines. The error rate of functional annotation is estimated to be only between 1–2%. Comparison of AutoFACT to the traditional top-BLAST-hit annotation method shows that our procedure increases the number of functionally informative annotations by approximately 50%. Conclusion AutoFACT will serve as a useful annotation tool for smaller sequencing groups lacking dedicated bioinformatics staff. It is implemented in PERL and runs on LINUX/UNIX platforms. AutoFACT is available at . PMID:15960857

JNSViewer—A JavaScript-based Nucleotide Sequence Viewer for DNA/RNA secondary structures

PubMed Central

Dong, Min; Graham, Mitchell; Yadav, Nehul

2017-01-01

Many tools are available for visualizing RNA or DNA secondary structures, but there is scarce implementation in JavaScript that provides seamless integration with the increasingly popular web computational platforms. We have developed JNSViewer, a highly interactive web service, which is bundled with several popular tools for DNA/RNA secondary structure prediction and can provide precise and interactive correspondence among nucleotides, dot-bracket data, secondary structure graphs, and genic annotations. In JNSViewer, users can perform RNA secondary structure predictions with different programs and settings, add customized genic annotations in GFF format to structure graphs, search for specific linear motifs, and extract relevant structure graphs of sub-sequences. JNSViewer also allows users to choose a transcript or specific segment of Arabidopsis thaliana genome sequences and predict the corresponding secondary structure. Popular genome browsers (i.e., JBrowse and BrowserGenome) were integrated into JNSViewer to provide powerful visualizations of chromosomal locations, genic annotations, and secondary structures. In addition, we used StructureFold with default settings to predict some RNA structures for Arabidopsis by incorporating in vivo high-throughput RNA structure profiling data and stored the results in our web server, which might be a useful resource for RNA secondary structure studies in plants. JNSViewer is available at http://bioinfolab.miamioh.edu/jnsviewer/index.html. PMID:28582416

SeqHound: biological sequence and structure database as a platform for bioinformatics research

PubMed Central

2002-01-01

Background SeqHound has been developed as an integrated biological sequence, taxonomy, annotation and 3-D structure database system. It provides a high-performance server platform for bioinformatics research in a locally-hosted environment. Results SeqHound is based on the National Center for Biotechnology Information data model and programming tools. It offers daily updated contents of all Entrez sequence databases in addition to 3-D structural data and information about sequence redundancies, sequence neighbours, taxonomy, complete genomes, functional annotation including Gene Ontology terms and literature links to PubMed. SeqHound is accessible via a web server through a Perl, C or C++ remote API or an optimized local API. It provides functionality necessary to retrieve specialized subsets of sequences, structures and structural domains. Sequences may be retrieved in FASTA, GenBank, ASN.1 and XML formats. Structures are available in ASN.1, XML and PDB formats. Emphasis has been placed on complete genomes, taxonomy, domain and functional annotation as well as 3-D structural functionality in the API, while fielded text indexing functionality remains under development. SeqHound also offers a streamlined WWW interface for simple web-user queries. Conclusions The system has proven useful in several published bioinformatics projects such as the BIND database and offers a cost-effective infrastructure for research. SeqHound will continue to develop and be provided as a service of the Blueprint Initiative at the Samuel Lunenfeld Research Institute. The source code and examples are available under the terms of the GNU public license at the Sourceforge site http://sourceforge.net/projects/slritools/ in the SLRI Toolkit. PMID:12401134

miRBase: integrating microRNA annotation and deep-sequencing data.

PubMed

Kozomara, Ana; Griffiths-Jones, Sam

2011-01-01

miRBase is the primary online repository for all microRNA sequences and annotation. The current release (miRBase 16) contains over 15,000 microRNA gene loci in over 140 species, and over 17,000 distinct mature microRNA sequences. Deep-sequencing technologies have delivered a sharp rise in the rate of novel microRNA discovery. We have mapped reads from short RNA deep-sequencing experiments to microRNAs in miRBase and developed web interfaces to view these mappings. The user can view all read data associated with a given microRNA annotation, filter reads by experiment and count, and search for microRNAs by tissue- and stage-specific expression. These data can be used as a proxy for relative expression levels of microRNA sequences, provide detailed evidence for microRNA annotations and alternative isoforms of mature microRNAs, and allow us to revisit previous annotations. miRBase is available online at: http://www.mirbase.org/.

HAMAP in 2013, new developments in the protein family classification and annotation system

PubMed Central

Pedruzzi, Ivo; Rivoire, Catherine; Auchincloss, Andrea H.; Coudert, Elisabeth; Keller, Guillaume; de Castro, Edouard; Baratin, Delphine; Cuche, Béatrice A.; Bougueleret, Lydie; Poux, Sylvain; Redaschi, Nicole; Xenarios, Ioannis; Bridge, Alan

2013-01-01

HAMAP (High-quality Automated and Manual Annotation of Proteins—available at http://hamap.expasy.org/) is a system for the classification and annotation of protein sequences. It consists of a collection of manually curated family profiles for protein classification, and associated annotation rules that specify annotations that apply to family members. HAMAP was originally developed to support the manual curation of UniProtKB/Swiss-Prot records describing microbial proteins. Here we describe new developments in HAMAP, including the extension of HAMAP to eukaryotic proteins, the use of HAMAP in the automated annotation of UniProtKB/TrEMBL, providing high-quality annotation for millions of protein sequences, and the future integration of HAMAP into a unified system for UniProtKB annotation, UniRule. HAMAP is continuously updated by expert curators with new family profiles and annotation rules as new protein families are characterized. The collection of HAMAP family classification profiles and annotation rules can be browsed and viewed on the HAMAP website, which also provides an interface to scan user sequences against HAMAP profiles. PMID:23193261

deFUME: Dynamic exploration of functional metagenomic sequencing data.

PubMed

van der Helm, Eric; Geertz-Hansen, Henrik Marcus; Genee, Hans Jasper; Malla, Sailesh; Sommer, Morten Otto Alexander

2015-07-31

Functional metagenomic selections represent a powerful technique that is widely applied for identification of novel genes from complex metagenomic sources. However, whereas hundreds to thousands of clones can be easily generated and sequenced over a few days of experiments, analyzing the data is time consuming and constitutes a major bottleneck for experimental researchers in the field. Here we present the deFUME web server, an easy-to-use web-based interface for processing, annotation and visualization of functional metagenomics sequencing data, tailored to meet the requirements of non-bioinformaticians. The web-server integrates multiple analysis steps into one single workflow: read assembly, open reading frame prediction, and annotation with BLAST, InterPro and GO classifiers. Analysis results are visualized in an online dynamic web-interface. The deFUME webserver provides a fast track from raw sequence to a comprehensive visual data overview that facilitates effortless inspection of gene function, clustering and distribution. The webserver is available at cbs.dtu.dk/services/deFUME/and the source code is distributed at github.com/EvdH0/deFUME.

Active learning reduces annotation time for clinical concept extraction.

PubMed

Kholghi, Mahnoosh; Sitbon, Laurianne; Zuccon, Guido; Nguyen, Anthony

2017-10-01

To investigate: (1) the annotation time savings by various active learning query strategies compared to supervised learning and a random sampling baseline, and (2) the benefits of active learning-assisted pre-annotations in accelerating the manual annotation process compared to de novo annotation. There are 73 and 120 discharge summary reports provided by Beth Israel institute in the train and test sets of the concept extraction task in the i2b2/VA 2010 challenge, respectively. The 73 reports were used in user study experiments for manual annotation. First, all sequences within the 73 reports were manually annotated from scratch. Next, active learning models were built to generate pre-annotations for the sequences selected by a query strategy. The annotation/reviewing time per sequence was recorded. The 120 test reports were used to measure the effectiveness of the active learning models. When annotating from scratch, active learning reduced the annotation time up to 35% and 28% compared to a fully supervised approach and a random sampling baseline, respectively. Reviewing active learning-assisted pre-annotations resulted in 20% further reduction of the annotation time when compared to de novo annotation. The number of concepts that require manual annotation is a good indicator of the annotation time for various active learning approaches as demonstrated by high correlation between time rate and concept annotation rate. Active learning has a key role in reducing the time required to manually annotate domain concepts from clinical free text, either when annotating from scratch or reviewing active learning-assisted pre-annotations. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimizing high performance computing workflow for protein functional annotation.

PubMed

Stanberry, Larissa; Rekepalli, Bhanu; Liu, Yuan; Giblock, Paul; Higdon, Roger; Montague, Elizabeth; Broomall, William; Kolker, Natali; Kolker, Eugene

2014-09-10

Functional annotation of newly sequenced genomes is one of the major challenges in modern biology. With modern sequencing technologies, the protein sequence universe is rapidly expanding. Newly sequenced bacterial genomes alone contain over 7.5 million proteins. The rate of data generation has far surpassed that of protein annotation. The volume of protein data makes manual curation infeasible, whereas a high compute cost limits the utility of existing automated approaches. In this work, we present an improved and optmized automated workflow to enable large-scale protein annotation. The workflow uses high performance computing architectures and a low complexity classification algorithm to assign proteins into existing clusters of orthologous groups of proteins. On the basis of the Position-Specific Iterative Basic Local Alignment Search Tool the algorithm ensures at least 80% specificity and sensitivity of the resulting classifications. The workflow utilizes highly scalable parallel applications for classification and sequence alignment. Using Extreme Science and Engineering Discovery Environment supercomputers, the workflow processed 1,200,000 newly sequenced bacterial proteins. With the rapid expansion of the protein sequence universe, the proposed workflow will enable scientists to annotate big genome data.

Optimizing high performance computing workflow for protein functional annotation

PubMed Central

Stanberry, Larissa; Rekepalli, Bhanu; Liu, Yuan; Giblock, Paul; Higdon, Roger; Montague, Elizabeth; Broomall, William; Kolker, Natali; Kolker, Eugene

2014-01-01

Functional annotation of newly sequenced genomes is one of the major challenges in modern biology. With modern sequencing technologies, the protein sequence universe is rapidly expanding. Newly sequenced bacterial genomes alone contain over 7.5 million proteins. The rate of data generation has far surpassed that of protein annotation. The volume of protein data makes manual curation infeasible, whereas a high compute cost limits the utility of existing automated approaches. In this work, we present an improved and optmized automated workflow to enable large-scale protein annotation. The workflow uses high performance computing architectures and a low complexity classification algorithm to assign proteins into existing clusters of orthologous groups of proteins. On the basis of the Position-Specific Iterative Basic Local Alignment Search Tool the algorithm ensures at least 80% specificity and sensitivity of the resulting classifications. The workflow utilizes highly scalable parallel applications for classification and sequence alignment. Using Extreme Science and Engineering Discovery Environment supercomputers, the workflow processed 1,200,000 newly sequenced bacterial proteins. With the rapid expansion of the protein sequence universe, the proposed workflow will enable scientists to annotate big genome data. PMID:25313296

JGI Plant Genomics Gene Annotation Pipeline

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

Shu, Shengqiang; Rokhsar, Dan; Goodstein, David

2014-07-14

Plant genomes vary in size and are highly complex with a high amount of repeats, genome duplication and tandem duplication. Gene encodes a wealth of information useful in studying organism and it is critical to have high quality and stable gene annotation. Thanks to advancement of sequencing technology, many plant species genomes have been sequenced and transcriptomes are also sequenced. To use these vastly large amounts of sequence data to make gene annotation or re-annotation in a timely fashion, an automatic pipeline is needed. JGI plant genomics gene annotation pipeline, called integrated gene call (IGC), is our effort toward thismore » aim with aid of a RNA-seq transcriptome assembly pipeline. It utilizes several gene predictors based on homolog peptides and transcript ORFs. See Methods for detail. Here we present genome annotation of JGI flagship green plants produced by this pipeline plus Arabidopsis and rice except for chlamy which is done by a third party. The genome annotations of these species and others are used in our gene family build pipeline and accessible via JGI Phytozome portal whose URL and front page snapshot are shown below.« less

Community annotation and bioinformatics workforce development in concert--Little Skate Genome Annotation Workshops and Jamborees.

PubMed

Wang, Qinghua; Arighi, Cecilia N; King, Benjamin L; Polson, Shawn W; Vincent, James; Chen, Chuming; Huang, Hongzhan; Kingham, Brewster F; Page, Shallee T; Rendino, Marc Farnum; Thomas, William Kelley; Udwary, Daniel W; Wu, Cathy H

2012-01-01

Recent advances in high-throughput DNA sequencing technologies have equipped biologists with a powerful new set of tools for advancing research goals. The resulting flood of sequence data has made it critically important to train the next generation of scientists to handle the inherent bioinformatic challenges. The North East Bioinformatics Collaborative (NEBC) is undertaking the genome sequencing and annotation of the little skate (Leucoraja erinacea) to promote advancement of bioinformatics infrastructure in our region, with an emphasis on practical education to create a critical mass of informatically savvy life scientists. In support of the Little Skate Genome Project, the NEBC members have developed several annotation workshops and jamborees to provide training in genome sequencing, annotation and analysis. Acting as a nexus for both curation activities and dissemination of project data, a project web portal, SkateBase (http://skatebase.org) has been developed. As a case study to illustrate effective coupling of community annotation with workforce development, we report the results of the Mitochondrial Genome Annotation Jamborees organized to annotate the first completely assembled element of the Little Skate Genome Project, as a culminating experience for participants from our three prior annotation workshops. We are applying the physical/virtual infrastructure and lessons learned from these activities to enhance and streamline the genome annotation workflow, as we look toward our continuing efforts for larger-scale functional and structural community annotation of the L. erinacea genome.

Community annotation and bioinformatics workforce development in concert—Little Skate Genome Annotation Workshops and Jamborees

PubMed Central

Wang, Qinghua; Arighi, Cecilia N.; King, Benjamin L.; Polson, Shawn W.; Vincent, James; Chen, Chuming; Huang, Hongzhan; Kingham, Brewster F.; Page, Shallee T.; Farnum Rendino, Marc; Thomas, William Kelley; Udwary, Daniel W.; Wu, Cathy H.

2012-01-01

Recent advances in high-throughput DNA sequencing technologies have equipped biologists with a powerful new set of tools for advancing research goals. The resulting flood of sequence data has made it critically important to train the next generation of scientists to handle the inherent bioinformatic challenges. The North East Bioinformatics Collaborative (NEBC) is undertaking the genome sequencing and annotation of the little skate (Leucoraja erinacea) to promote advancement of bioinformatics infrastructure in our region, with an emphasis on practical education to create a critical mass of informatically savvy life scientists. In support of the Little Skate Genome Project, the NEBC members have developed several annotation workshops and jamborees to provide training in genome sequencing, annotation and analysis. Acting as a nexus for both curation activities and dissemination of project data, a project web portal, SkateBase (http://skatebase.org) has been developed. As a case study to illustrate effective coupling of community annotation with workforce development, we report the results of the Mitochondrial Genome Annotation Jamborees organized to annotate the first completely assembled element of the Little Skate Genome Project, as a culminating experience for participants from our three prior annotation workshops. We are applying the physical/virtual infrastructure and lessons learned from these activities to enhance and streamline the genome annotation workflow, as we look toward our continuing efforts for larger-scale functional and structural community annotation of the L. erinacea genome. PMID:22434832

dbWFA: a web-based database for functional annotation of Triticum aestivum transcripts

PubMed Central

Vincent, Jonathan; Dai, Zhanwu; Ravel, Catherine; Choulet, Frédéric; Mouzeyar, Said; Bouzidi, M. Fouad; Agier, Marie; Martre, Pierre

2013-01-01

The functional annotation of genes based on sequence homology with genes from model species genomes is time-consuming because it is necessary to mine several unrelated databases. The aim of the present work was to develop a functional annotation database for common wheat Triticum aestivum (L.). The database, named dbWFA, is based on the reference NCBI UniGene set, an expressed gene catalogue built by expressed sequence tag clustering, and on full-length coding sequences retrieved from the TriFLDB database. Information from good-quality heterogeneous sources, including annotations for model plant species Arabidopsis thaliana (L.) Heynh. and Oryza sativa L., was gathered and linked to T. aestivum sequences through BLAST-based homology searches. Even though the complexity of the transcriptome cannot yet be fully appreciated, we developed a tool to easily and promptly obtain information from multiple functional annotation systems (Gene Ontology, MapMan bin codes, MIPS Functional Categories, PlantCyc pathway reactions and TAIR gene families). The use of dbWFA is illustrated here with several query examples. We were able to assign a putative function to 45% of the UniGenes and 81% of the full-length coding sequences from TriFLDB. Moreover, comparison of the annotation of the whole T. aestivum UniGene set along with curated annotations of the two model species assessed the accuracy of the annotation provided by dbWFA. To further illustrate the use of dbWFA, genes specifically expressed during the early cell division or late storage polymer accumulation phases of T. aestivum grain development were identified using a clustering analysis and then annotated using dbWFA. The annotation of these two sets of genes was consistent with previous analyses of T. aestivum grain transcriptomes and proteomes. Database URL: urgi.versailles.inra.fr/dbWFA/ PMID:23660284

Sockeye: A 3D Environment for Comparative Genomics

PubMed Central

Montgomery, Stephen B.; Astakhova, Tamara; Bilenky, Mikhail; Birney, Ewan; Fu, Tony; Hassel, Maik; Melsopp, Craig; Rak, Marcin; Robertson, A. Gordon; Sleumer, Monica; Siddiqui, Asim S.; Jones, Steven J.M.

2004-01-01

Comparative genomics techniques are used in bioinformatics analyses to identify the structural and functional properties of DNA sequences. As the amount of available sequence data steadily increases, the ability to perform large-scale comparative analyses has become increasingly relevant. In addition, the growing complexity of genomic feature annotation means that new approaches to genomic visualization need to be explored. We have developed a Java-based application called Sockeye that uses three-dimensional (3D) graphics technology to facilitate the visualization of annotation and conservation across multiple sequences. This software uses the Ensembl database project to import sequence and annotation information from several eukaryotic species. A user can additionally import their own custom sequence and annotation data. Individual annotation objects are displayed in Sockeye by using custom 3D models. Ensembl-derived and imported sequences can be analyzed by using a suite of multiple and pair-wise alignment algorithms. The results of these comparative analyses are also displayed in the 3D environment of Sockeye. By using the Java3D API to visualize genomic data in a 3D environment, we are able to compactly display cross-sequence comparisons. This provides the user with a novel platform for visualizing and comparing genomic feature organization. PMID:15123592

Integrating sequence and structural biology with DAS

PubMed Central

Prlić, Andreas; Down, Thomas A; Kulesha, Eugene; Finn, Robert D; Kähäri, Andreas; Hubbard, Tim JP

2007-01-01

Background The Distributed Annotation System (DAS) is a network protocol for exchanging biological data. It is frequently used to share annotations of genomes and protein sequence. Results Here we present several extensions to the current DAS 1.5 protocol. These provide new commands to share alignments, three dimensional molecular structure data, add the possibility for registration and discovery of DAS servers, and provide a convention how to provide different types of data plots. We present examples of web sites and applications that use the new extensions. We operate a public registry of DAS sources, which now includes entries for more than 250 distinct sources. Conclusion Our DAS extensions are essential for the management of the growing number of services and exchange of diverse biological data sets. In addition the extensions allow new types of applications to be developed and scientific questions to be addressed. The registry of DAS sources is available at PMID:17850653

AGORA : Organellar genome annotation from the amino acid and nucleotide references.

PubMed

Jung, Jaehee; Kim, Jong Im; Jeong, Young-Sik; Yi, Gangman

2018-03-29

Next-generation sequencing (NGS) technologies have led to the accumulation of highthroughput sequence data from various organisms in biology. To apply gene annotation of organellar genomes for various organisms, more optimized tools for functional gene annotation are required. Almost all gene annotation tools are mainly focused on the chloroplast genome of land plants or the mitochondrial genome of animals.We have developed a web application AGORA for the fast, user-friendly, and improved annotations of organellar genomes. AGORA annotates genes based on a BLAST-based homology search and clustering with selected reference sequences from the NCBI database or user-defined uploaded data. AGORA can annotate the functional genes in almost all mitochondrion and plastid genomes of eukaryotes. The gene annotation of a genome with an exon-intron structure within a gene or inverted repeat region is also available. It provides information of start and end positions of each gene, BLAST results compared with the reference sequence, and visualization of gene map by OGDRAW. Users can freely use the software, and the accessible URL is https://bigdata.dongguk.edu/gene_project/AGORA/.The main module of the tool is implemented by the python and php, and the web page is built by the HTML and CSS to support all browsers. gangman@dongguk.edu.

Characteristics of the Lotus japonicus gene repertoire deduced from large-scale expressed sequence tag (EST) analysis.

PubMed

Asamizu, Erika; Nakamura, Yasukazu; Sato, Shusei; Tabata, Satoshi

2004-02-01

To perform a comprehensive analysis of genes expressed in a model legume, Lotus japonicus, a total of 74472 3'-end expressed sequence tags (EST) were generated from cDNA libraries produced from six different organs. Clustering of sequences was performed with an identity criterion of 95% for 50 bases, and a total of 20457 non-redundant sequences, 8503 contigs and 11954 singletons were generated. EST sequence coverage was analyzed by using the annotated L. japonicus genomic sequence and 1093 of the 1889 predicted protein-encoding genes (57.9%) were hit by the EST sequence(s). Gene content was compared to several plant species. Among the 8503 contigs, 471 were identified as sequences conserved only in leguminous species and these included several disease resistance-related genes. This suggested that in legumes, these genes may have evolved specifically to resist pathogen attack. The rate of gene sequence divergence was assessed by comparing similarity level and functional category based on the Gene Ontology (GO) annotation of Arabidopsis genes. This revealed that genes encoding ribosomal proteins, as well as those related to translation, photosynthesis, and cellular structure were more abundantly represented in the highly conserved class, and that genes encoding transcription factors and receptor protein kinases were abundantly represented in the less conserved class. To make the sequence information and the cDNA clones available to the research community, a Web database with useful services was created at http://www.kazusa.or.jp/en/plant/lotus/EST/.

Lessons learned from the initial sequencing of the pig genome: comparative analysis of an 8 Mb region of pig chromosome 17

PubMed Central

Hart, Elizabeth A; Caccamo, Mario; Harrow, Jennifer L; Humphray, Sean J; Gilbert, James GR; Trevanion, Steve; Hubbard, Tim; Rogers, Jane; Rothschild, Max F

2007-01-01

Background We describe here the sequencing, annotation and comparative analysis of an 8 Mb region of pig chromosome 17, which provides a useful test region to assess coverage and quality for the pig genome sequencing project. We report our findings comparing the annotation of draft sequence assembled at different depths of coverage. Results Within this region we annotated 71 loci, of which 53 are orthologous to human known coding genes. When compared to the syntenic regions in human (20q13.13-q13.33) and mouse (chromosome 2, 167.5 Mb-178.3 Mb), this region was found to be highly conserved with respect to gene order. The most notable difference between the three species is the presence of a large expansion of zinc finger coding genes and pseudogenes on mouse chromosome 2 between Edn3 and Phactr3 that is absent from pig and human. All of our annotation has been made publicly available in the Vertebrate Genome Annotation browser, VEGA. We assessed the impact of coverage on sequence assembly across this region and found, as expected, that increased sequence depth resulted in fewer, longer contigs. One-third of our annotated loci could not be fully re-aligned back to the low coverage version of the sequence, principally because the transcripts are fragmented over several contigs. Conclusion We have demonstrated the considerable advantages of sequencing at increased read depths and discuss the implications that lower coverage sequence may have on subsequent comparative and functional studies, particularly those involving complex loci such as GNAS. PMID:17705864

Comparative Omics-Driven Genome Annotation Refinement: Application across Yersiniae

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

Rutledge, Alexandra C.; Jones, Marcus B.; Chauhan, Sadhana

2012-03-27

Genome sequencing continues to be a rapidly evolving technology, yet most downstream aspects of genome annotation pipelines remain relatively stable or are even being abandoned. To date, the perceived value of manual curation for genome annotations is not offset by the real cost and time associated with the process. In order to balance the large number of sequences generated, the annotation process is now performed almost exclusively in an automated fashion for most genome sequencing projects. One possible way to reduce errors inherent to automated computational annotations is to apply data from 'omics' measurements (i.e. transcriptional and proteomic) to themore » un-annotated genome with a proteogenomic-based approach. This approach does require additional experimental and bioinformatics methods to include omics technologies; however, the approach is readily automatable and can benefit from rapid developments occurring in those research domains as well. The annotation process can be improved by experimental validation of transcription and translation and aid in the discovery of annotation errors. Here the concept of annotation refinement has been extended to include a comparative assessment of genomes across closely related species, as is becoming common in sequencing efforts. Transcriptomic and proteomic data derived from three highly similar pathogenic Yersiniae (Y. pestis CO92, Y. pestis pestoides F, and Y. pseudotuberculosis PB1/+) was used to demonstrate a comprehensive comparative omic-based annotation methodology. Peptide and oligo measurements experimentally validated the expression of nearly 40% of each strain's predicted proteome and revealed the identification of 28 novel and 68 previously incorrect protein-coding sequences (e.g., observed frameshifts, extended start sites, and translated pseudogenes) within the three current Yersinia genome annotations. Gene loss is presumed to play a major role in Y. pestis acquiring its niche as a virulent pathogen, thus the discovery of many translated pseudogenes underscores a need for functional analyses to investigate hypotheses related to divergence. Refinements included the discovery of a seemingly essential ribosomal protein, several virulence-associated factors, and a transcriptional regulator, among other proteins, most of which are annotated as hypothetical, that were missed during annotation.« less

P2RP: a Web-based framework for the identification and analysis of regulatory proteins in prokaryotic genomes.

PubMed

Barakat, Mohamed; Ortet, Philippe; Whitworth, David E

2013-04-20

Regulatory proteins (RPs) such as transcription factors (TFs) and two-component system (TCS) proteins control how prokaryotic cells respond to changes in their external and/or internal state. Identification and annotation of TFs and TCSs is non-trivial, and between-genome comparisons are often confounded by different standards in annotation. There is a need for user-friendly, fast and convenient tools to allow researchers to overcome the inherent variability in annotation between genome sequences. We have developed the web-server P2RP (Predicted Prokaryotic Regulatory Proteins), which enables users to identify and annotate TFs and TCS proteins within their sequences of interest. Users can input amino acid or genomic DNA sequences, and predicted proteins therein are scanned for the possession of DNA-binding domains and/or TCS domains. RPs identified in this manner are categorised into families, unambiguously annotated, and a detailed description of their features generated, using an integrated software pipeline. P2RP results can then be outputted in user-specified formats. Biologists have an increasing need for fast and intuitively usable tools, which is why P2RP has been developed as an interactive system. As well as assisting experimental biologists to interrogate novel sequence data, it is hoped that P2RP will be built into genome annotation pipelines and re-annotation processes, to increase the consistency of RP annotation in public genomic sequences. P2RP is the first publicly available tool for predicting and analysing RP proteins in users' sequences. The server is freely available and can be accessed along with documentation at http://www.p2rp.org.

Solving the Problem: Genome Annotation Standards before the Data Deluge.

PubMed

Klimke, William; O'Donovan, Claire; White, Owen; Brister, J Rodney; Clark, Karen; Fedorov, Boris; Mizrachi, Ilene; Pruitt, Kim D; Tatusova, Tatiana

2011-10-15

The promise of genome sequencing was that the vast undiscovered country would be mapped out by comparison of the multitude of sequences available and would aid researchers in deciphering the role of each gene in every organism. Researchers recognize that there is a need for high quality data. However, different annotation procedures, numerous databases, and a diminishing percentage of experimentally determined gene functions have resulted in a spectrum of annotation quality. NCBI in collaboration with sequencing centers, archival databases, and researchers, has developed the first international annotation standards, a fundamental step in ensuring that high quality complete prokaryotic genomes are available as gold standard references. Highlights include the development of annotation assessment tools, community acceptance of protein naming standards, comparison of annotation resources to provide consistent annotation, and improved tracking of the evidence used to generate a particular annotation. The development of a set of minimal standards, including the requirement for annotated complete prokaryotic genomes to contain a full set of ribosomal RNAs, transfer RNAs, and proteins encoding core conserved functions, is an historic milestone. The use of these standards in existing genomes and future submissions will increase the quality of databases, enabling researchers to make accurate biological discoveries.

Solving the Problem: Genome Annotation Standards before the Data Deluge

PubMed Central

Klimke, William; O'Donovan, Claire; White, Owen; Brister, J. Rodney; Clark, Karen; Fedorov, Boris; Mizrachi, Ilene; Pruitt, Kim D.; Tatusova, Tatiana

2011-01-01

The promise of genome sequencing was that the vast undiscovered country would be mapped out by comparison of the multitude of sequences available and would aid researchers in deciphering the role of each gene in every organism. Researchers recognize that there is a need for high quality data. However, different annotation procedures, numerous databases, and a diminishing percentage of experimentally determined gene functions have resulted in a spectrum of annotation quality. NCBI in collaboration with sequencing centers, archival databases, and researchers, has developed the first international annotation standards, a fundamental step in ensuring that high quality complete prokaryotic genomes are available as gold standard references. Highlights include the development of annotation assessment tools, community acceptance of protein naming standards, comparison of annotation resources to provide consistent annotation, and improved tracking of the evidence used to generate a particular annotation. The development of a set of minimal standards, including the requirement for annotated complete prokaryotic genomes to contain a full set of ribosomal RNAs, transfer RNAs, and proteins encoding core conserved functions, is an historic milestone. The use of these standards in existing genomes and future submissions will increase the quality of databases, enabling researchers to make accurate biological discoveries. PMID:22180819

Brassica ASTRA: an integrated database for Brassica genomic research.

PubMed

Love, Christopher G; Robinson, Andrew J; Lim, Geraldine A C; Hopkins, Clare J; Batley, Jacqueline; Barker, Gary; Spangenberg, German C; Edwards, David

2005-01-01

Brassica ASTRA is a public database for genomic information on Brassica species. The database incorporates expressed sequences with Swiss-Prot and GenBank comparative sequence annotation as well as secondary Gene Ontology (GO) annotation derived from the comparison with Arabidopsis TAIR GO annotations. Simple sequence repeat molecular markers are identified within resident sequences and mapped onto the closely related Arabidopsis genome sequence. Bacterial artificial chromosome (BAC) end sequences derived from the Multinational Brassica Genome Project are also mapped onto the Arabidopsis genome sequence enabling users to identify candidate Brassica BACs corresponding to syntenic regions of Arabidopsis. This information is maintained in a MySQL database with a web interface providing the primary means of interrogation. The database is accessible at http://hornbill.cspp.latrobe.edu.au.

Saccharomyces cerevisiae: gene annotation and genome variability, state of the art through comparative genomics.

PubMed

Louis, Ed

2011-01-01

In the early days of the yeast genome sequencing project, gene annotation was in its infancy and suffered the problem of many false positive annotations as well as missed genes. The lack of other sequences for comparison also prevented the annotation of conserved, functional sequences that were not coding. We are now in an era of comparative genomics where many closely related as well as more distantly related genomes are available for direct sequence and synteny comparisons allowing for more probable predictions of genes and other functional sequences due to conservation. We also have a plethora of functional genomics data which helps inform gene annotation for previously uncharacterised open reading frames (ORFs)/genes. For Saccharomyces cerevisiae this has resulted in a continuous updating of the gene and functional sequence annotations in the reference genome helping it retain its position as the best characterized eukaryotic organism's genome. A single reference genome for a species does not accurately describe the species and this is quite clear in the case of S. cerevisiae where the reference strain is not ideal for brewing or baking due to missing genes. Recent surveys of numerous isolates, from a variety of sources, using a variety of technologies have revealed a great deal of variation amongst isolates with genome sequence surveys providing information on novel genes, undetectable by other means. We now have a better understanding of the extant variation in S. cerevisiae as a species as well as some idea of how much we are missing from this understanding. As with gene annotation, comparative genomics enhances the discovery and description of genome variation and is providing us with the tools for understanding genome evolution, adaptation and selection, and underlying genetics of complex traits.

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

India Allele Finder: a web-based annotation tool for identifying common alleles in next-generation sequencing data of Indian origin.

PubMed

Zhang, Jimmy F; James, Francis; Shukla, Anju; Girisha, Katta M; Paciorkowski, Alex R

2017-06-27

We built India Allele Finder, an online searchable database and command line tool, that gives researchers access to variant frequencies of Indian Telugu individuals, using publicly available fastq data from the 1000 Genomes Project. Access to appropriate population-based genomic variant annotation can accelerate the interpretation of genomic sequencing data. In particular, exome analysis of individuals of Indian descent will identify population variants not reflected in European exomes, complicating genomic analysis for such individuals. India Allele Finder offers improved ease-of-use to investigators seeking to identify and annotate sequencing data from Indian populations. We describe the use of India Allele Finder to identify common population variants in a disease quartet whole exome dataset, reducing the number of candidate single nucleotide variants from 84 to 7. India Allele Finder is freely available to investigators to annotate genomic sequencing data from Indian populations. Use of India Allele Finder allows efficient identification of population variants in genomic sequencing data, and is an example of a population-specific annotation tool that simplifies analysis and encourages international collaboration in genomics research.

Year 2 Report: Protein Function Prediction Platform

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

Zhou, C E

2012-04-27

Upon completion of our second year of development in a 3-year development cycle, we have completed a prototype protein structure-function annotation and function prediction system: Protein Function Prediction (PFP) platform (v.0.5). We have met our milestones for Years 1 and 2 and are positioned to continue development in completion of our original statement of work, or a reasonable modification thereof, in service to DTRA Programs involved in diagnostics and medical countermeasures research and development. The PFP platform is a multi-scale computational modeling system for protein structure-function annotation and function prediction. As of this writing, PFP is the only existing fullymore » automated, high-throughput, multi-scale modeling, whole-proteome annotation platform, and represents a significant advance in the field of genome annotation (Fig. 1). PFP modules perform protein functional annotations at the sequence, systems biology, protein structure, and atomistic levels of biological complexity (Fig. 2). Because these approaches provide orthogonal means of characterizing proteins and suggesting protein function, PFP processing maximizes the protein functional information that can currently be gained by computational means. Comprehensive annotation of pathogen genomes is essential for bio-defense applications in pathogen characterization, threat assessment, and medical countermeasure design and development in that it can short-cut the time and effort required to select and characterize protein biomarkers.« less

Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis

PubMed Central

Du, Yushen; Wu, Nicholas C.; Jiang, Lin; Zhang, Tianhao; Gong, Danyang; Shu, Sara; Wu, Ting-Ting

2016-01-01

ABSTRACT Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp), we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available. PMID:27803181

Processing sequence annotation data using the Lua programming language.

PubMed

Ueno, Yutaka; Arita, Masanori; Kumagai, Toshitaka; Asai, Kiyoshi

2003-01-01

The data processing language in a graphical software tool that manages sequence annotation data from genome databases should provide flexible functions for the tasks in molecular biology research. Among currently available languages we adopted the Lua programming language. It fulfills our requirements to perform computational tasks for sequence map layouts, i.e. the handling of data containers, symbolic reference to data, and a simple programming syntax. Upon importing a foreign file, the original data are first decomposed in the Lua language while maintaining the original data schema. The converted data are parsed by the Lua interpreter and the contents are stored in our data warehouse. Then, portions of annotations are selected and arranged into our catalog format to be depicted on the sequence map. Our sequence visualization program was successfully implemented, embedding the Lua language for processing of annotation data and layout script. The program is available at http://staff.aist.go.jp/yutaka.ueno/guppy/.

The Bologna Annotation Resource (BAR 3.0): improving protein functional annotation

PubMed Central

Casadio, Rita

2017-01-01

Abstract BAR 3.0 updates our server BAR (Bologna Annotation Resource) for predicting protein structural and functional features from sequence. We increase data volume, query capabilities and information conveyed to the user. The core of BAR 3.0 is a graph-based clustering procedure of UniProtKB sequences, following strict pairwise similarity criteria (sequence identity ≥40% with alignment coverage ≥90%). Each cluster contains the available annotation downloaded from UniProtKB, GO, PFAM and PDB. After statistical validation, GO terms and PFAM domains are cluster-specific and annotate new sequences entering the cluster after satisfying similarity constraints. BAR 3.0 includes 28 869 663 sequences in 1 361 773 clusters, of which 22.2% (22 241 661 sequences) and 47.4% (24 555 055 sequences) have at least one validated GO term and one PFAM domain, respectively. 1.4% of the clusters (36% of all sequences) include PDB structures and the cluster is associated to a hidden Markov model that allows building template-target alignment suitable for structural modeling. Some other 3 399 026 sequences are singletons. BAR 3.0 offers an improved search interface, allowing queries by UniProtKB-accession, Fasta sequence, GO-term, PFAM-domain, organism, PDB and ligand/s. When evaluated on the CAFA2 targets, BAR 3.0 largely outperforms our previous version and scores among state-of-the-art methods. BAR 3.0 is publicly available and accessible at http://bar.biocomp.unibo.it/bar3. PMID:28453653

PSS-3D1D: an improved 3D1D profile method of protein fold recognition for the annotation of twilight zone sequences.

PubMed

Ganesan, K; Parthasarathy, S

2011-12-01

Annotation of any newly determined protein sequence depends on the pairwise sequence identity with known sequences. However, for the twilight zone sequences which have only 15-25% identity, the pair-wise comparison methods are inadequate and the annotation becomes a challenging task. Such sequences can be annotated by using methods that recognize their fold. Bowie et al. described a 3D1D profile method in which the amino acid sequences that fold into a known 3D structure are identified by their compatibility to that known 3D structure. We have improved the above method by using the predicted secondary structure information and employ it for fold recognition from the twilight zone sequences. In our Protein Secondary Structure 3D1D (PSS-3D1D) method, a score (w) for the predicted secondary structure of the query sequence is included in finding the compatibility of the query sequence to the known fold 3D structures. In the benchmarks, the PSS-3D1D method shows a maximum of 21% improvement in predicting correctly the α + β class of folds from the sequences with twilight zone level of identity, when compared with the 3D1D profile method. Hence, the PSS-3D1D method could offer more clues than the 3D1D method for the annotation of twilight zone sequences. The web based PSS-3D1D method is freely available in the PredictFold server at http://bioinfo.bdu.ac.in/servers/ .

A domain-centric solution to functional genomics via dcGO Predictor

PubMed Central

2013-01-01

Background Computational/manual annotations of protein functions are one of the first routes to making sense of a newly sequenced genome. Protein domain predictions form an essential part of this annotation process. This is due to the natural modularity of proteins with domains as structural, evolutionary and functional units. Sometimes two, three, or more adjacent domains (called supra-domains) are the operational unit responsible for a function, e.g. via a binding site at the interface. These supra-domains have contributed to functional diversification in higher organisms. Traditionally functional ontologies have been applied to individual proteins, rather than families of related domains and supra-domains. We expect, however, to some extent functional signals can be carried by protein domains and supra-domains, and consequently used in function prediction and functional genomics. Results Here we present a domain-centric Gene Ontology (dcGO) perspective. We generalize a framework for automatically inferring ontological terms associated with domains and supra-domains from full-length sequence annotations. This general framework has been applied specifically to primary protein-level annotations from UniProtKB-GOA, generating GO term associations with SCOP domains and supra-domains. The resulting 'dcGO Predictor', can be used to provide functional annotation to protein sequences. The functional annotation of sequences in the Critical Assessment of Function Annotation (CAFA) has been used as a valuable opportunity to validate our method and to be assessed by the community. The functional annotation of all completely sequenced genomes has demonstrated the potential for domain-centric GO enrichment analysis to yield functional insights into newly sequenced or yet-to-be-annotated genomes. This generalized framework we have presented has also been applied to other domain classifications such as InterPro and Pfam, and other ontologies such as mammalian phenotype and disease ontology. The dcGO and its predictor are available at http://supfam.org/SUPERFAMILY/dcGO including an enrichment analysis tool. Conclusions As functional units, domains offer a unique perspective on function prediction regardless of whether proteins are multi-domain or single-domain. The 'dcGO Predictor' holds great promise for contributing to a domain-centric functional understanding of genomes in the next generation sequencing era. PMID:23514627

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

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.

Annotate-it: a Swiss-knife approach to annotation, analysis and interpretation of single nucleotide variation in human disease

PubMed Central

2012-01-01

The increasing size and complexity of exome/genome sequencing data requires new tools for clinical geneticists to discover disease-causing variants. Bottlenecks in identifying the causative variation include poor cross-sample querying, constantly changing functional annotation and not considering existing knowledge concerning the phenotype. We describe a methodology that facilitates exploration of patient sequencing data towards identification of causal variants under different genetic hypotheses. Annotate-it facilitates handling, analysis and interpretation of high-throughput single nucleotide variant data. We demonstrate our strategy using three case studies. Annotate-it is freely available and test data are accessible to all users at http://www.annotate-it.org. PMID:23013645

TRAP: automated classification, quantification and annotation of tandemly repeated sequences.

PubMed

Sobreira, Tiago José P; Durham, Alan M; Gruber, Arthur

2006-02-01

TRAP, the Tandem Repeats Analysis Program, is a Perl program that provides a unified set of analyses for the selection, classification, quantification and automated annotation of tandemly repeated sequences. TRAP uses the results of the Tandem Repeats Finder program to perform a global analysis of the satellite content of DNA sequences, permitting researchers to easily assess the tandem repeat content for both individual sequences and whole genomes. The results can be generated in convenient formats such as HTML and comma-separated values. TRAP can also be used to automatically generate annotation data in the format of feature table and GFF files.

PAZAR: a framework for collection and dissemination of cis-regulatory sequence annotation

PubMed Central

Portales-Casamar, Elodie; Kirov, Stefan; Lim, Jonathan; Lithwick, Stuart; Swanson, Magdalena I; Ticoll, Amy; Snoddy, Jay; Wasserman, Wyeth W

2007-01-01

PAZAR is an open-access and open-source database of transcription factor and regulatory sequence annotation with associated web interface and programming tools for data submission and extraction. Curated boutique data collections can be maintained and disseminated through the unified schema of the mall-like PAZAR repository. The Pleiades Promoter Project collection of brain-linked regulatory sequences is introduced to demonstrate the depth of annotation possible within PAZAR. PAZAR, located at , is open for business. PMID:17916232

PAZAR: a framework for collection and dissemination of cis-regulatory sequence annotation.

PubMed

Portales-Casamar, Elodie; Kirov, Stefan; Lim, Jonathan; Lithwick, Stuart; Swanson, Magdalena I; Ticoll, Amy; Snoddy, Jay; Wasserman, Wyeth W

2007-01-01

PAZAR is an open-access and open-source database of transcription factor and regulatory sequence annotation with associated web interface and programming tools for data submission and extraction. Curated boutique data collections can be maintained and disseminated through the unified schema of the mall-like PAZAR repository. The Pleiades Promoter Project collection of brain-linked regulatory sequences is introduced to demonstrate the depth of annotation possible within PAZAR. PAZAR, located at http://www.pazar.info, is open for business.

MEETING: Chlamydomonas Annotation Jamboree - October 2003

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

Grossman, Arthur R

2007-04-13

Shotgun sequencing of the nuclear genome of Chlamydomonas reinhardtii (Chlamydomonas throughout) was performed at an approximate 10X coverage by JGI. Roughly half of the genome is now contained on 26 scaffolds, all of which are at least 1.6 Mb, and the coverage of the genome is ~95%. There are now over 200,000 cDNA sequence reads that we have generated as part of the Chlamydomonas genome project (Grossman, 2003; Shrager et al., 2003; Grossman et al. 2007; Merchant et al., 2007); other sequences have also been generated by the Kasuza sequence group (Asamizu et al., 1999; Asamizu et al., 2000) ormore » individual laboratories that have focused on specific genes. Shrager et al. (2003) placed the reads into distinct contigs (an assemblage of reads with overlapping nucleotide sequences), and contigs that group together as part of the same genes have been designated ACEs (assembly of contigs generated from EST information). All of the reads have also been mapped to the Chlamydomonas nuclear genome and the cDNAs and their corresponding genomic sequences have been reassembled, and the resulting assemblage is called an ACEG (an Assembly of contiguous EST sequences supported by genomic sequence) (Jain et al., 2007). Most of the unique genes or ACEGs are also represented by gene models that have been generated by the Joint Genome Institute (JGI, Walnut Creek, CA). These gene models have been placed onto the DNA scaffolds and are presented as a track on the Chlamydomonas genome browser associated with the genome portal (http://genome.jgi-psf.org/Chlre3/Chlre3.home.html). Ultimately, the meeting grant awarded by DOE has helped enormously in the development of an annotation pipeline (a set of guidelines used in the annotation of genes) and resulted in high quality annotation of over 4,000 genes; the annotators were from both Europe and the USA. Some of the people who led the annotation initiative were Arthur Grossman, Olivier Vallon, and Sabeeha Merchant (with many individual annotators from Europe and the USA). Olivier Vallon has been most active in continued input of annotation information.« less

BioXSD: the common data-exchange format for everyday bioinformatics web services.

PubMed

Kalas, Matús; Puntervoll, Pål; Joseph, Alexandre; Bartaseviciūte, Edita; Töpfer, Armin; Venkataraman, Prabakar; Pettifer, Steve; Bryne, Jan Christian; Ison, Jon; Blanchet, Christophe; Rapacki, Kristoffer; Jonassen, Inge

2010-09-15

The world-wide community of life scientists has access to a large number of public bioinformatics databases and tools, which are developed and deployed using diverse technologies and designs. More and more of the resources offer programmatic web-service interface. However, efficient use of the resources is hampered by the lack of widely used, standard data-exchange formats for the basic, everyday bioinformatics data types. BioXSD has been developed as a candidate for standard, canonical exchange format for basic bioinformatics data. BioXSD is represented by a dedicated XML Schema and defines syntax for biological sequences, sequence annotations, alignments and references to resources. We have adapted a set of web services to use BioXSD as the input and output format, and implemented a test-case workflow. This demonstrates that the approach is feasible and provides smooth interoperability. Semantics for BioXSD is provided by annotation with the EDAM ontology. We discuss in a separate section how BioXSD relates to other initiatives and approaches, including existing standards and the Semantic Web. The BioXSD 1.0 XML Schema is freely available at http://www.bioxsd.org/BioXSD-1.0.xsd under the Creative Commons BY-ND 3.0 license. The http://bioxsd.org web page offers documentation, examples of data in BioXSD format, example workflows with source codes in common programming languages, an updated list of compatible web services and tools and a repository of feature requests from the community.

Dictionary-driven protein annotation.

PubMed

Rigoutsos, Isidore; Huynh, Tien; Floratos, Aris; Parida, Laxmi; Platt, Daniel

2002-09-01

Computational methods seeking to automatically determine the properties (functional, structural, physicochemical, etc.) of a protein directly from the sequence have long been the focus of numerous research groups. With the advent of advanced sequencing methods and systems, the number of amino acid sequences that are being deposited in the public databases has been increasing steadily. This has in turn generated a renewed demand for automated approaches that can annotate individual sequences and complete genomes quickly, exhaustively and objectively. In this paper, we present one such approach that is centered around and exploits the Bio-Dictionary, a collection of amino acid patterns that completely covers the natural sequence space and can capture functional and structural signals that have been reused during evolution, within and across protein families. Our annotation approach also makes use of a weighted, position-specific scoring scheme that is unaffected by the over-representation of well-conserved proteins and protein fragments in the databases used. For a given query sequence, the method permits one to determine, in a single pass, the following: local and global similarities between the query and any protein already present in a public database; the likeness of the query to all available archaeal/ bacterial/eukaryotic/viral sequences in the database as a function of amino acid position within the query; the character of secondary structure of the query as a function of amino acid position within the query; the cytoplasmic, transmembrane or extracellular behavior of the query; the nature and position of binding domains, active sites, post-translationally modified sites, signal peptides, etc. In terms of performance, the proposed method is exhaustive, objective and allows for the rapid annotation of individual sequences and full genomes. Annotation examples are presented and discussed in Results, including individual queries and complete genomes that were released publicly after we built the Bio-Dictionary that is used in our experiments. Finally, we have computed the annotations of more than 70 complete genomes and made them available on the World Wide Web at http://cbcsrv.watson.ibm.com/Annotations/.

BEAUTY: an enhanced BLAST-based search tool that integrates multiple biological information resources into sequence similarity search results.

PubMed

Worley, K C; Wiese, B A; Smith, R F

1995-09-01

BEAUTY (BLAST enhanced alignment utility) is an enhanced version of the NCBI's BLAST data base search tool that facilitates identification of the functions of matched sequences. We have created new data bases of conserved regions and functional domains for protein sequences in NCBI's Entrez data base, and BEAUTY allows this information to be incorporated directly into BLAST search results. A Conserved Regions Data Base, containing the locations of conserved regions within Entrez protein sequences, was constructed by (1) clustering the entire data base into families, (2) aligning each family using our PIMA multiple sequence alignment program, and (3) scanning the multiple alignments to locate the conserved regions within each aligned sequence. A separate Annotated Domains Data Base was constructed by extracting the locations of all annotated domains and sites from sequences represented in the Entrez, PROSITE, BLOCKS, and PRINTS data bases. BEAUTY performs a BLAST search of those Entrez sequences with conserved regions and/or annotated domains. BEAUTY then uses the information from the Conserved Regions and Annotated Domains data bases to generate, for each matched sequence, a schematic display that allows one to directly compare the relative locations of (1) the conserved regions, (2) annotated domains and sites, and (3) the locally aligned regions matched in the BLAST search. In addition, BEAUTY search results include World-Wide Web hypertext links to a number of external data bases that provide a variety of additional types of information on the function of matched sequences. This convenient integration of protein families, conserved regions, annotated domains, alignment displays, and World-Wide Web resources greatly enhances the biological informativeness of sequence similarity searches. BEAUTY searches can be performed remotely on our system using the "BCM Search Launcher" World-Wide Web pages (URL is < http:/ /gc.bcm.tmc.edu:8088/ search-launcher/launcher.html > ).

RefSeq microbial genomes database: new representation and annotation strategy.

PubMed

Tatusova, Tatiana; Ciufo, Stacy; Fedorov, Boris; O'Neill, Kathleen; Tolstoy, Igor

2014-01-01

The source of the microbial genomic sequences in the RefSeq collection is the set of primary sequence records submitted to the International Nucleotide Sequence Database public archives. These can be accessed through the Entrez search and retrieval system at http://www.ncbi.nlm.nih.gov/genome. Next-generation sequencing has enabled researchers to perform genomic sequencing at rates that were unimaginable in the past. Microbial genomes can now be sequenced in a matter of hours, which has led to a significant increase in the number of assembled genomes deposited in the public archives. This huge increase in DNA sequence data presents new challenges for the annotation, analysis and visualization bioinformatics tools. New strategies have been developed for the annotation and representation of reference genomes and sequence variations derived from population studies and clinical outbreaks.

MicroScope: a platform for microbial genome annotation and comparative genomics

PubMed Central

Vallenet, D.; Engelen, S.; Mornico, D.; Cruveiller, S.; Fleury, L.; Lajus, A.; Rouy, Z.; Roche, D.; Salvignol, G.; Scarpelli, C.; Médigue, C.

2009-01-01

The initial outcome of genome sequencing is the creation of long text strings written in a four letter alphabet. The role of in silico sequence analysis is to assist biologists in the act of associating biological knowledge with these sequences, allowing investigators to make inferences and predictions that can be tested experimentally. A wide variety of software is available to the scientific community, and can be used to identify genomic objects, before predicting their biological functions. However, only a limited number of biologically interesting features can be revealed from an isolated sequence. Comparative genomics tools, on the other hand, by bringing together the information contained in numerous genomes simultaneously, allow annotators to make inferences based on the idea that evolution and natural selection are central to the definition of all biological processes. We have developed the MicroScope platform in order to offer a web-based framework for the systematic and efficient revision of microbial genome annotation and comparative analysis (http://www.genoscope.cns.fr/agc/microscope). Starting with the description of the flow chart of the annotation processes implemented in the MicroScope pipeline, and the development of traditional and novel microbial annotation and comparative analysis tools, this article emphasizes the essential role of expert annotation as a complement of automatic annotation. Several examples illustrate the use of implemented tools for the review and curation of annotations of both new and publicly available microbial genomes within MicroScope’s rich integrated genome framework. The platform is used as a viewer in order to browse updated annotation information of available microbial genomes (more than 440 organisms to date), and in the context of new annotation projects (117 bacterial genomes). The human expertise gathered in the MicroScope database (about 280,000 independent annotations) contributes to improve the quality of microbial genome annotation, especially for genomes initially analyzed by automatic procedures alone. Database URLs: http://www.genoscope.cns.fr/agc/mage and http://www.genoscope.cns.fr/agc/microcyc PMID:20157493

MicroScope: a platform for microbial genome annotation and comparative genomics.

PubMed

Vallenet, D; Engelen, S; Mornico, D; Cruveiller, S; Fleury, L; Lajus, A; Rouy, Z; Roche, D; Salvignol, G; Scarpelli, C; Médigue, C

2009-01-01

The initial outcome of genome sequencing is the creation of long text strings written in a four letter alphabet. The role of in silico sequence analysis is to assist biologists in the act of associating biological knowledge with these sequences, allowing investigators to make inferences and predictions that can be tested experimentally. A wide variety of software is available to the scientific community, and can be used to identify genomic objects, before predicting their biological functions. However, only a limited number of biologically interesting features can be revealed from an isolated sequence. Comparative genomics tools, on the other hand, by bringing together the information contained in numerous genomes simultaneously, allow annotators to make inferences based on the idea that evolution and natural selection are central to the definition of all biological processes. We have developed the MicroScope platform in order to offer a web-based framework for the systematic and efficient revision of microbial genome annotation and comparative analysis (http://www.genoscope.cns.fr/agc/microscope). Starting with the description of the flow chart of the annotation processes implemented in the MicroScope pipeline, and the development of traditional and novel microbial annotation and comparative analysis tools, this article emphasizes the essential role of expert annotation as a complement of automatic annotation. Several examples illustrate the use of implemented tools for the review and curation of annotations of both new and publicly available microbial genomes within MicroScope's rich integrated genome framework. The platform is used as a viewer in order to browse updated annotation information of available microbial genomes (more than 440 organisms to date), and in the context of new annotation projects (117 bacterial genomes). The human expertise gathered in the MicroScope database (about 280,000 independent annotations) contributes to improve the quality of microbial genome annotation, especially for genomes initially analyzed by automatic procedures alone.Database URLs: http://www.genoscope.cns.fr/agc/mage and http://www.genoscope.cns.fr/agc/microcyc.

Current challenges in genome annotation through structural biology and bioinformatics.

PubMed

Furnham, Nicholas; de Beer, Tjaart A P; Thornton, Janet M

2012-10-01

With the huge volume in genomic sequences being generated from high-throughout sequencing projects the requirement for providing accurate and detailed annotations of gene products has never been greater. It is proving to be a huge challenge for computational biologists to use as much information as possible from experimental data to provide annotations for genome data of unknown function. A central component to this process is to use experimentally determined structures, which provide a means to detect homology that is not discernable from just the sequence and permit the consequences of genomic variation to be realized at the molecular level. In particular, structures also form the basis of many bioinformatics methods for improving the detailed functional annotations of enzymes in combination with similarities in sequence and chemistry. Copyright © 2012. Published by Elsevier Ltd.

PlantCAZyme: a database for plant carbohydrate-active enzymes

PubMed Central

Ekstrom, Alexander; Taujale, Rahil; McGinn, Nathan; Yin, Yanbin

2014-01-01

PlantCAZyme is a database built upon dbCAN (database for automated carbohydrate active enzyme annotation), aiming to provide pre-computed sequence and annotation data of carbohydrate active enzymes (CAZymes) to plant carbohydrate and bioenergy research communities. The current version contains data of 43 790 CAZymes of 159 protein families from 35 plants (including angiosperms, gymnosperms, lycophyte and bryophyte mosses) and chlorophyte algae with fully sequenced genomes. Useful features of the database include: (i) a BLAST server and a HMMER server that allow users to search against our pre-computed sequence data for annotation purpose, (ii) a download page to allow batch downloading data of a specific CAZyme family or species and (iii) protein browse pages to provide an easy access to the most comprehensive sequence and annotation data. Database URL: http://cys.bios.niu.edu/plantcazyme/ PMID:25125445

High Precision Prediction of Functional Sites in Protein Structures

PubMed Central

Buturovic, Ljubomir; Wong, Mike; Tang, Grace W.; Altman, Russ B.; Petkovic, Dragutin

2014-01-01

We address the problem of assigning biological function to solved protein structures. Computational tools play a critical role in identifying potential active sites and informing screening decisions for further lab analysis. A critical parameter in the practical application of computational methods is the precision, or positive predictive value. Precision measures the level of confidence the user should have in a particular computed functional assignment. Low precision annotations lead to futile laboratory investigations and waste scarce research resources. In this paper we describe an advanced version of the protein function annotation system FEATURE, which achieved 99% precision and average recall of 95% across 20 representative functional sites. The system uses a Support Vector Machine classifier operating on the microenvironment of physicochemical features around an amino acid. We also compared performance of our method with state-of-the-art sequence-level annotator Pfam in terms of precision, recall and localization. To our knowledge, no other functional site annotator has been rigorously evaluated against these key criteria. The software and predictive models are incorporated into the WebFEATURE service at http://feature.stanford.edu/wf4.0-beta. PMID:24632601

The Bologna Annotation Resource (BAR 3.0): improving protein functional annotation.

PubMed

Profiti, Giuseppe; Martelli, Pier Luigi; Casadio, Rita

2017-07-03

BAR 3.0 updates our server BAR (Bologna Annotation Resource) for predicting protein structural and functional features from sequence. We increase data volume, query capabilities and information conveyed to the user. The core of BAR 3.0 is a graph-based clustering procedure of UniProtKB sequences, following strict pairwise similarity criteria (sequence identity ≥40% with alignment coverage ≥90%). Each cluster contains the available annotation downloaded from UniProtKB, GO, PFAM and PDB. After statistical validation, GO terms and PFAM domains are cluster-specific and annotate new sequences entering the cluster after satisfying similarity constraints. BAR 3.0 includes 28 869 663 sequences in 1 361 773 clusters, of which 22.2% (22 241 661 sequences) and 47.4% (24 555 055 sequences) have at least one validated GO term and one PFAM domain, respectively. 1.4% of the clusters (36% of all sequences) include PDB structures and the cluster is associated to a hidden Markov model that allows building template-target alignment suitable for structural modeling. Some other 3 399 026 sequences are singletons. BAR 3.0 offers an improved search interface, allowing queries by UniProtKB-accession, Fasta sequence, GO-term, PFAM-domain, organism, PDB and ligand/s. When evaluated on the CAFA2 targets, BAR 3.0 largely outperforms our previous version and scores among state-of-the-art methods. BAR 3.0 is publicly available and accessible at http://bar.biocomp.unibo.it/bar3. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

AGeNNT: annotation of enzyme families by means of refined neighborhood networks.

PubMed

Kandlinger, Florian; Plach, Maximilian G; Merkl, Rainer

2017-05-25

Large enzyme families may contain functionally diverse members that give rise to clusters in a sequence similarity network (SSN). In prokaryotes, the genome neighborhood of a gene-product is indicative of its function and thus, a genome neighborhood network (GNN) deduced for an SSN provides strong clues to the specific function of enzymes constituting the different clusters. The Enzyme Function Initiative ( http://enzymefunction.org/ ) offers services that compute SSNs and GNNs. We have implemented AGeNNT that utilizes these services, albeit with datasets purged with respect to unspecific protein functions and overrepresented species. AGeNNT generates refined GNNs (rGNNs) that consist of cluster-nodes representing the sequences under study and Pfam-nodes representing enzyme functions encoded in the respective neighborhoods. For cluster-nodes, AGeNNT summarizes the phylogenetic relationships of the contributing species and a statistic indicates how unique nodes and GNs are within this rGNN. Pfam-nodes are annotated with additional features like GO terms describing protein function. For edges, the coverage is given, which is the relative number of neighborhoods containing the considered enzyme function (Pfam-node). AGeNNT is available at https://github.com/kandlinf/agennt . An rGNN is easier to interpret than a conventional GNN, which commonly contains proteins without enzymatic function and overly specific neighborhoods due to phylogenetic bias. The implemented filter routines and the statistic allow the user to identify those neighborhoods that are most indicative of a specific metabolic capacity. Thus, AGeNNT facilitates to distinguish and annotate functionally different members of enzyme families.

Plant genome and transcriptome annotations: from misconceptions to simple solutions

PubMed Central

Bolger, Marie E; Arsova, Borjana; Usadel, Björn

2018-01-01

Abstract Next-generation sequencing has triggered an explosion of available genomic and transcriptomic resources in the plant sciences. Although genome and transcriptome sequencing has become orders of magnitudes cheaper and more efficient, often the functional annotation process is lagging behind. This might be hampered by the lack of a comprehensive enumeration of simple-to-use tools available to the plant researcher. In this comprehensive review, we present (i) typical ontologies to be used in the plant sciences, (ii) useful databases and resources used for functional annotation, (iii) what to expect from an annotated plant genome, (iv) an automated annotation pipeline and (v) a recipe and reference chart outlining typical steps used to annotate plant genomes/transcriptomes using publicly available resources. PMID:28062412

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.

GI-POP: a combinational annotation and genomic island prediction pipeline for ongoing microbial genome projects.

PubMed

Lee, Chi-Ching; Chen, Yi-Ping Phoebe; Yao, Tzu-Jung; Ma, Cheng-Yu; Lo, Wei-Cheng; Lyu, Ping-Chiang; Tang, Chuan Yi

2013-04-10

Sequencing of microbial genomes is important because of microbial-carrying antibiotic and pathogenetic activities. However, even with the help of new assembling software, finishing a whole genome is a time-consuming task. In most bacteria, pathogenetic or antibiotic genes are carried in genomic islands. Therefore, a quick genomic island (GI) prediction method is useful for ongoing sequencing genomes. In this work, we built a Web server called GI-POP (http://gipop.life.nthu.edu.tw) which integrates a sequence assembling tool, a functional annotation pipeline, and a high-performance GI predicting module, in a support vector machine (SVM)-based method called genomic island genomic profile scanning (GI-GPS). The draft genomes of the ongoing genome projects in contigs or scaffolds can be submitted to our Web server, and it provides the functional annotation and highly probable GI-predicting results. GI-POP is a comprehensive annotation Web server designed for ongoing genome project analysis. Researchers can perform annotation and obtain pre-analytic information include possible GIs, coding/non-coding sequences and functional analysis from their draft genomes. This pre-analytic system can provide useful information for finishing a genome sequencing project. Copyright © 2012 Elsevier B.V. All rights reserved.

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.

Pfarao: a web application for protein family analysis customized for cytoskeletal and motor proteins (CyMoBase).

PubMed

Odronitz, Florian; Kollmar, Martin

2006-11-29

Annotation of protein sequences of eukaryotic organisms is crucial for the understanding of their function in the cell. Manual annotation is still by far the most accurate way to correctly predict genes. The classification of protein sequences, their phylogenetic relation and the assignment of function involves information from various sources. This often leads to a collection of heterogeneous data, which is hard to track. Cytoskeletal and motor proteins consist of large and diverse superfamilies comprising up to several dozen members per organism. Up to date there is no integrated tool available to assist in the manual large-scale comparative genomic analysis of protein families. Pfarao (Protein Family Application for Retrieval, Analysis and Organisation) is a database driven online working environment for the analysis of manually annotated protein sequences and their relationship. Currently, the system can store and interrelate a wide range of information about protein sequences, species, phylogenetic relations and sequencing projects as well as links to literature and domain predictions. Sequences can be imported from multiple sequence alignments that are generated during the annotation process. A web interface allows to conveniently browse the database and to compile tabular and graphical summaries of its content. We implemented a protein sequence-centric web application to store, organize, interrelate, and present heterogeneous data that is generated in manual genome annotation and comparative genomics. The application has been developed for the analysis of cytoskeletal and motor proteins (CyMoBase) but can easily be adapted for any protein.

Hymenoptera Genome Database: integrating genome annotations in HymenopteraMine

PubMed Central

Elsik, Christine G.; Tayal, Aditi; Diesh, Colin M.; Unni, Deepak R.; Emery, Marianne L.; Nguyen, Hung N.; Hagen, Darren E.

2016-01-01

We report an update of the Hymenoptera Genome Database (HGD) (http://HymenopteraGenome.org), a model organism database for insect species of the order Hymenoptera (ants, bees and wasps). HGD maintains genomic data for 9 bee species, 10 ant species and 1 wasp, including the versions of genome and annotation data sets published by the genome sequencing consortiums and those provided by NCBI. A new data-mining warehouse, HymenopteraMine, based on the InterMine data warehousing system, integrates the genome data with data from external sources and facilitates cross-species analyses based on orthology. New genome browsers and annotation tools based on JBrowse/WebApollo provide easy genome navigation, and viewing of high throughput sequence data sets and can be used for collaborative genome annotation. All of the genomes and annotation data sets are combined into a single BLAST server that allows users to select and combine sequence data sets to search. PMID:26578564

StructRNAfinder: an automated pipeline and web server for RNA families prediction.

PubMed

Arias-Carrasco, Raúl; Vásquez-Morán, Yessenia; Nakaya, Helder I; Maracaja-Coutinho, Vinicius

2018-02-17

The function of many noncoding RNAs (ncRNAs) depend upon their secondary structures. Over the last decades, several methodologies have been developed to predict such structures or to use them to functionally annotate RNAs into RNA families. However, to fully perform this analysis, researchers should utilize multiple tools, which require the constant parsing and processing of several intermediate files. This makes the large-scale prediction and annotation of RNAs a daunting task even to researchers with good computational or bioinformatics skills. We present an automated pipeline named StructRNAfinder that predicts and annotates RNA families in transcript or genome sequences. This single tool not only displays the sequence/structural consensus alignments for each RNA family, according to Rfam database but also provides a taxonomic overview for each assigned functional RNA. Moreover, we implemented a user-friendly web service that allows researchers to upload their own nucleotide sequences in order to perform the whole analysis. Finally, we provided a stand-alone version of StructRNAfinder to be used in large-scale projects. The tool was developed under GNU General Public License (GPLv3) and is freely available at http://structrnafinder.integrativebioinformatics.me . The main advantage of StructRNAfinder relies on the large-scale processing and integrating the data obtained by each tool and database employed along the workflow, of which several files are generated and displayed in user-friendly reports, useful for downstream analyses and data exploration.

The challenge of annotating protein sequences: The tale of eight domains of unknown function in Pfam.

PubMed

Goonesekere, Nalin C W; Shipely, Krysten; O'Connor, Kevin

2010-06-01

The Pfam database is an important tool in genome annotation, since it provides a collection of curated protein families. However, a subset of these families, known as domains of unknown function (DUFs), remains poorly characterized. We have related sequences from DUF404, DUF407, DUF482, DUF608, DUF810, DUF853, DUF976 and DUF1111 to homologs in PDB, within the midnight zone (9-20%) of sequence identity. These relationships were extended to provide functional annotation by sequence analysis and model building. Also described are examples of residue plasticity within enzyme active sites, and change of function within homologous sequences of a DUF. Copyright 2010 Elsevier Ltd. All rights reserved.

An effective approach for annotation of protein families with low sequence similarity and conserved motifs: identifying GDSL hydrolases across the plant kingdom.

PubMed

Vujaklija, Ivan; Bielen, Ana; Paradžik, Tina; Biđin, Siniša; Goldstein, Pavle; Vujaklija, Dušica

2016-02-18

The massive accumulation of protein sequences arising from the rapid development of high-throughput sequencing, coupled with automatic annotation, results in high levels of incorrect annotations. In this study, we describe an approach to decrease annotation errors of protein families characterized by low overall sequence similarity. The GDSL lipolytic family comprises proteins with multifunctional properties and high potential for pharmaceutical and industrial applications. The number of proteins assigned to this family has increased rapidly over the last few years. In particular, the natural abundance of GDSL enzymes reported recently in plants indicates that they could be a good source of novel GDSL enzymes. We noticed that a significant proportion of annotated sequences lack specific GDSL motif(s) or catalytic residue(s). Here, we applied motif-based sequence analyses to identify enzymes possessing conserved GDSL motifs in selected proteomes across the plant kingdom. Motif-based HMM scanning (Viterbi decoding-VD and posterior decoding-PD) and the here described PD/VD protocol were successfully applied on 12 selected plant proteomes to identify sequences with GDSL motifs. A significant number of identified GDSL sequences were novel. Moreover, our scanning approach successfully detected protein sequences lacking at least one of the essential motifs (171/820) annotated by Pfam profile search (PfamA) as GDSL. Based on these analyses we provide a curated list of GDSL enzymes from the selected plants. CLANS clustering and phylogenetic analysis helped us to gain a better insight into the evolutionary relationship of all identified GDSL sequences. Three novel GDSL subfamilies as well as unreported variations in GDSL motifs were discovered in this study. In addition, analyses of selected proteomes showed a remarkable expansion of GDSL enzymes in the lycophyte, Selaginella moellendorffii. Finally, we provide a general motif-HMM scanner which is easily accessible through the graphical user interface ( http://compbio.math.hr/ ). Our results show that scanning with a carefully parameterized motif-HMM is an effective approach for annotation of protein families with low sequence similarity and conserved motifs. The results of this study expand current knowledge and provide new insights into the evolution of the large GDSL-lipase family in land plants.

Issues with RNA-seq analysis in non-model organisms: A salmonid example.

PubMed

Sundaram, Arvind; Tengs, Torstein; Grimholt, Unni

2017-10-01

High throughput sequencing (HTS) is useful for many purposes as exemplified by the other topics included in this special issue. The purpose of this paper is to look into the unique challenges of using this technology in non-model organisms where resources such as genomes, functional genome annotations or genome complexity provide obstacles not met in model organisms. To describe these challenges, we narrow our scope to RNA sequencing used to study differential gene expression in response to pathogen challenge. As a demonstration species we chose Atlantic salmon, which has a sequenced genome with poor annotation and an added complexity due to many duplicated genes. We find that our RNA-seq analysis pipeline deciphers between duplicates despite high sequence identity. However, annotation issues provide problems in linking differentially expressed genes to pathways. Also, comparing results between approaches and species are complicated due to lack of standardized annotation. Copyright © 2017 Elsevier Ltd. All rights reserved.

G2S: a web-service for annotating genomic variants on 3D protein structures.

PubMed

Wang, Juexin; Sheridan, Robert; Sumer, S Onur; Schultz, Nikolaus; Xu, Dong; Gao, Jianjiong

2018-06-01

Accurately mapping and annotating genomic locations on 3D protein structures is a key step in structure-based analysis of genomic variants detected by recent large-scale sequencing efforts. There are several mapping resources currently available, but none of them provides a web API (Application Programming Interface) that supports programmatic access. We present G2S, a real-time web API that provides automated mapping of genomic variants on 3D protein structures. G2S can align genomic locations of variants, protein locations, or protein sequences to protein structures and retrieve the mapped residues from structures. G2S API uses REST-inspired design and it can be used by various clients such as web browsers, command terminals, programming languages and other bioinformatics tools for bringing 3D structures into genomic variant analysis. The webserver and source codes are freely available at https://g2s.genomenexus.org. g2s@genomenexus.org. Supplementary data are available at Bioinformatics online.

ISEScan: automated identification of insertion sequence elements in prokaryotic genomes.

PubMed

Xie, Zhiqun; Tang, Haixu

2017-11-01

The insertion sequence (IS) elements are the smallest but most abundant autonomous transposable elements in prokaryotic genomes, which play a key role in prokaryotic genome organization and evolution. With the fast growing genomic data, it is becoming increasingly critical for biology researchers to be able to accurately and automatically annotate ISs in prokaryotic genome sequences. The available automatic IS annotation systems are either providing only incomplete IS annotation or relying on the availability of existing genome annotations. Here, we present a new IS elements annotation pipeline to address these issues. ISEScan is a highly sensitive software pipeline based on profile hidden Markov models constructed from manually curated IS elements. ISEScan performs better than existing IS annotation systems when tested on prokaryotic genomes with curated annotations of IS elements. Applying it to 2784 prokaryotic genomes, we report the global distribution of IS families across taxonomic clades in Archaea and Bacteria. ISEScan is implemented in Python and released as an open source software at https://github.com/xiezhq/ISEScan. hatang@indiana.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Protein Information Resource: a community resource for expert annotation of protein data

PubMed Central

Barker, Winona C.; Garavelli, John S.; Hou, Zhenglin; Huang, Hongzhan; Ledley, Robert S.; McGarvey, Peter B.; Mewes, Hans-Werner; Orcutt, Bruce C.; Pfeiffer, Friedhelm; Tsugita, Akira; Vinayaka, C. R.; Xiao, Chunlin; Yeh, Lai-Su L.; Wu, Cathy

2001-01-01

The Protein Information Resource, in collaboration with the Munich Information Center for Protein Sequences (MIPS) and the Japan International Protein Information Database (JIPID), produces the most comprehensive and expertly annotated protein sequence database in the public domain, the PIR-International Protein Sequence Database. To provide timely and high quality annotation and promote database interoperability, the PIR-International employs rule-based and classification-driven procedures based on controlled vocabulary and standard nomenclature and includes status tags to distinguish experimentally determined from predicted protein features. The database contains about 200 000 non-redundant protein sequences, which are classified into families and superfamilies and their domains and motifs identified. Entries are extensively cross-referenced to other sequence, classification, genome, structure and activity databases. The PIR web site features search engines that use sequence similarity and database annotation to facilitate the analysis and functional identification of proteins. The PIR-Inter­national databases and search tools are accessible on the PIR web site at http://pir.georgetown.edu/ and at the MIPS web site at http://www.mips.biochem.mpg.de. The PIR-International Protein Sequence Database and other files are also available by FTP. PMID:11125041

Initial sequence and comparative analysis of the cat genome

PubMed Central

Pontius, Joan U.; Mullikin, James C.; Smith, Douglas R.; Lindblad-Toh, Kerstin; Gnerre, Sante; Clamp, Michele; Chang, Jean; Stephens, Robert; Neelam, Beena; Volfovsky, Natalia; Schäffer, Alejandro A.; Agarwala, Richa; Narfström, Kristina; Murphy, William J.; Giger, Urs; Roca, Alfred L.; Antunes, Agostinho; Menotti-Raymond, Marilyn; Yuhki, Naoya; Pecon-Slattery, Jill; Johnson, Warren E.; Bourque, Guillaume; Tesler, Glenn; O’Brien, Stephen J.

2007-01-01

The genome sequence (1.9-fold coverage) of an inbred Abyssinian domestic cat was assembled, mapped, and annotated with a comparative approach that involved cross-reference to annotated genome assemblies of six mammals (human, chimpanzee, mouse, rat, dog, and cow). The results resolved chromosomal positions for 663,480 contigs, 20,285 putative feline gene orthologs, and 133,499 conserved sequence blocks (CSBs). Additional annotated features include repetitive elements, endogenous retroviral sequences, nuclear mitochondrial (numt) sequences, micro-RNAs, and evolutionary breakpoints that suggest historic balancing of translocation and inversion incidences in distinct mammalian lineages. Large numbers of single nucleotide polymorphisms (SNPs), deletion insertion polymorphisms (DIPs), and short tandem repeats (STRs), suitable for linkage or association studies were characterized in the context of long stretches of chromosome homozygosity. In spite of the light coverage capturing ∼65% of euchromatin sequence from the cat genome, these comparative insights shed new light on the tempo and mode of gene/genome evolution in mammals, promise several research applications for the cat, and also illustrate that a comparative approach using more deeply covered mammals provides an informative, preliminary annotation of a light (1.9-fold) coverage mammal genome sequence. PMID:17975172

Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis.

PubMed

Du, Yushen; Wu, Nicholas C; Jiang, Lin; Zhang, Tianhao; Gong, Danyang; Shu, Sara; Wu, Ting-Ting; Sun, Ren

2016-11-01

Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp), we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available. To fully comprehend the diverse functions of a protein, it is essential to understand the functionality of individual residues. Current methods are highly dependent on evolutionary sequence conservation, which is usually limited by sampling size. Sequence conservation-based methods are further confounded by structural constraints and multifunctionality of proteins. Here we present a method that can systematically identify and annotate functional residues of a given protein. We used a high-throughput functional profiling platform to identify essential residues. Coupling it with homologous-structure comparison, we were able to annotate multiple functions of proteins. We demonstrated the method with the PB1 protein of influenza A virus and identified novel functional residues in addition to its canonical function as an RNA-dependent RNA polymerase. Not limited to virology, this method is generally applicable to other proteins that can be functionally selected and about which homologous-structure information is available. Copyright © 2016 Du et al.

A new approach for annotation of transposable elements using small RNA mapping

PubMed Central

El Baidouri, Moaine; Kim, Kyung Do; Abernathy, Brian; Arikit, Siwaret; Maumus, Florian; Panaud, Olivier; Meyers, Blake C.; Jackson, Scott A.

2015-01-01

Transposable elements (TEs) are mobile genomic DNA sequences found in most organisms. They so densely populate the genomes of many eukaryotic species that they are often the major constituents. With the rapid generation of many plant genome sequencing projects over the past few decades, there is an urgent need for improved TE annotation as a prerequisite for genome-wide studies. Analogous to the use of RNA-seq for gene annotation, we propose a new method for de novo TE annotation that uses as a guide 24 nt-siRNAs that are a part of TE silencing pathways. We use this new approach, called TASR (for Transposon Annotation using Small RNAs), for de novo annotation of TEs in Arabidopsis, rice and soybean and demonstrate that this strategy can be successfully applied for de novo TE annotation in plants. Executable PERL is available for download from: http://tasr-pipeline.sourceforge.net/ PMID:25813049

Apollo2Go: a web service adapter for the Apollo genome viewer to enable distributed genome annotation.

PubMed

Klee, Kathrin; Ernst, Rebecca; Spannagl, Manuel; Mayer, Klaus F X

2007-08-30

Apollo, a genome annotation viewer and editor, has become a widely used genome annotation and visualization tool for distributed genome annotation projects. When using Apollo for annotation, database updates are carried out by uploading intermediate annotation files into the respective database. This non-direct database upload is laborious and evokes problems of data synchronicity. To overcome these limitations we extended the Apollo data adapter with a generic, configurable web service client that is able to retrieve annotation data in a GAME-XML-formatted string and pass it on to Apollo's internal input routine. This Apollo web service adapter, Apollo2Go, simplifies the data exchange in distributed projects and aims to render the annotation process more comfortable. The Apollo2Go software is freely available from ftp://ftpmips.gsf.de/plants/apollo_webservice.

Apollo2Go: a web service adapter for the Apollo genome viewer to enable distributed genome annotation

PubMed Central

Klee, Kathrin; Ernst, Rebecca; Spannagl, Manuel; Mayer, Klaus FX

2007-01-01

Background Apollo, a genome annotation viewer and editor, has become a widely used genome annotation and visualization tool for distributed genome annotation projects. When using Apollo for annotation, database updates are carried out by uploading intermediate annotation files into the respective database. This non-direct database upload is laborious and evokes problems of data synchronicity. Results To overcome these limitations we extended the Apollo data adapter with a generic, configurable web service client that is able to retrieve annotation data in a GAME-XML-formatted string and pass it on to Apollo's internal input routine. Conclusion This Apollo web service adapter, Apollo2Go, simplifies the data exchange in distributed projects and aims to render the annotation process more comfortable. The Apollo2Go software is freely available from . PMID:17760972

[Transcriptome analysis of Dunaliella viridis].

PubMed

Zhu, Shuai-qi; Gong, Yi-fu; Hang, Yu-qing; Liu, Hao; Wang, He-yu

2015-08-01

In order to understand the gene information, function, haloduric pathway (glycerolipid metabolism) and related key genes for Dunaliella viridis, we used Illumina HiSeqTM 2000 high-throughput sequencing technology to sequence its transcriptome. Trinity soft was used to assemble the data to form transcripts. Based on the Clusters of Orthologous Groups (COG), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG ) databases, we carried out functional annotation and classification, pathway annotation, and the opening reading fragment (ORF) sequence prediction of transcripts. The key genes in the glycerolipid metabolism were analyzed. The results suggested that 81,593 transcripts were found, and 77,117 ORF sequences were predicted, accounting for 94.50% of all transcripts. COG classification results showed that 16,569 transcripts were assigned to 24 categories. GO classification annotated 76,436 transcripts. The number of transcripts for biologcial processes was 30,678, accounting for 40.14% of all transcripts. KEGG pathway analysis showed that 26,428 transcripts were annotated to 317 pathways, and 131 pathways were related to metabolism, accounting for 41.32% of all annotated pathways. Only one transcript was annotated as coding the key enzyme dihydroxyacetone kinase involved in the glycerolipid pathway. This enzyme could be related to glycerol biosynthesis under salt stress. This study further improved the gene information and laid the foundation of metabolic pathway research for Dunaliella viridis.

Enhanced functionalities for annotating and indexing clinical text with the NCBO Annotator.

PubMed

Tchechmedjiev, Andon; Abdaoui, Amine; Emonet, Vincent; Melzi, Soumia; Jonnagaddala, Jitendra; Jonquet, Clement

2018-06-01

Second use of clinical data commonly involves annotating biomedical text with terminologies and ontologies. The National Center for Biomedical Ontology Annotator is a frequently used annotation service, originally designed for biomedical data, but not very suitable for clinical text annotation. In order to add new functionalities to the NCBO Annotator without hosting or modifying the original Web service, we have designed a proxy architecture that enables seamless extensions by pre-processing of the input text and parameters, and post processing of the annotations. We have then implemented enhanced functionalities for annotating and indexing free text such as: scoring, detection of context (negation, experiencer, temporality), new output formats and coarse-grained concept recognition (with UMLS Semantic Groups). In this paper, we present the NCBO Annotator+, a Web service which incorporates these new functionalities as well as a small set of evaluation results for concept recognition and clinical context detection on two standard evaluation tasks (Clef eHealth 2017, SemEval 2014). The Annotator+ has been successfully integrated into the SIFR BioPortal platform-an implementation of NCBO BioPortal for French biomedical terminologies and ontologies-to annotate English text. A Web user interface is available for testing and ontology selection (http://bioportal.lirmm.fr/ncbo_annotatorplus); however the Annotator+ is meant to be used through the Web service application programming interface (http://services.bioportal.lirmm.fr/ncbo_annotatorplus). The code is openly available, and we also provide a Docker packaging to enable easy local deployment to process sensitive (e.g. clinical) data in-house (https://github.com/sifrproject). andon.tchechmedjiev@lirmm.fr. Supplementary data are available at Bioinformatics online.

Flavitrack: an annotated database of flavivirus sequences

PubMed Central

Misra, Milind

2009-01-01

Motivation Properly annotated sequence data for flaviviruses, which cause diseases, such as tick-borne encephalitis (TBE), dengue fever (DF), West Nile (WN) and yellow fever (YF), can aid in the design of antiviral drugs and vaccines to prevent their spread. Flavitrack was designed to help identify conserved sequence motifs, interpret mutational and structural data and track evolution of phenotypic properties. Summary Flavitrack contains over 590 complete flavivirus genome/protein sequences and information on known mutations and literature references. Each sequence has been manually annotated according to its date and place of isolation, phenotype and lethality. Internal tools are provided to rapidly determine relationships between viruses in Flavitrack and sequences provided by the user. Availability http://carnot.utmb.edu/flavitrack Contact chschein@utmb.edu Supplementary information http://carnot.utmb.edu/flavitrack/B1S1.html PMID:17660525

A RESTful API for accessing microbial community data for MG-RAST.

PubMed

Wilke, Andreas; Bischof, Jared; Harrison, Travis; Brettin, Tom; D'Souza, Mark; Gerlach, Wolfgang; Matthews, Hunter; Paczian, Tobias; Wilkening, Jared; Glass, Elizabeth M; Desai, Narayan; Meyer, Folker

2015-01-01

Metagenomic sequencing has produced significant amounts of data in recent years. For example, as of summer 2013, MG-RAST has been used to annotate over 110,000 data sets totaling over 43 Terabases. With metagenomic sequencing finding even wider adoption in the scientific community, the existing web-based analysis tools and infrastructure in MG-RAST provide limited capability for data retrieval and analysis, such as comparative analysis between multiple data sets. Moreover, although the system provides many analysis tools, it is not comprehensive. By opening MG-RAST up via a web services API (application programmers interface) we have greatly expanded access to MG-RAST data, as well as provided a mechanism for the use of third-party analysis tools with MG-RAST data. This RESTful API makes all data and data objects created by the MG-RAST pipeline accessible as JSON objects. As part of the DOE Systems Biology Knowledgebase project (KBase, http://kbase.us) we have implemented a web services API for MG-RAST. This API complements the existing MG-RAST web interface and constitutes the basis of KBase's microbial community capabilities. In addition, the API exposes a comprehensive collection of data to programmers. This API, which uses a RESTful (Representational State Transfer) implementation, is compatible with most programming environments and should be easy to use for end users and third parties. It provides comprehensive access to sequence data, quality control results, annotations, and many other data types. Where feasible, we have used standards to expose data and metadata. Code examples are provided in a number of languages both to show the versatility of the API and to provide a starting point for users. We present an API that exposes the data in MG-RAST for consumption by our users, greatly enhancing the utility of the MG-RAST service.

Dictionary-driven protein annotation

PubMed Central

Rigoutsos, Isidore; Huynh, Tien; Floratos, Aris; Parida, Laxmi; Platt, Daniel

2002-01-01

Computational methods seeking to automatically determine the properties (functional, structural, physicochemical, etc.) of a protein directly from the sequence have long been the focus of numerous research groups. With the advent of advanced sequencing methods and systems, the number of amino acid sequences that are being deposited in the public databases has been increasing steadily. This has in turn generated a renewed demand for automated approaches that can annotate individual sequences and complete genomes quickly, exhaustively and objectively. In this paper, we present one such approach that is centered around and exploits the Bio-Dictionary, a collection of amino acid patterns that completely covers the natural sequence space and can capture functional and structural signals that have been reused during evolution, within and across protein families. Our annotation approach also makes use of a weighted, position-specific scoring scheme that is unaffected by the over-representation of well-conserved proteins and protein fragments in the databases used. For a given query sequence, the method permits one to determine, in a single pass, the following: local and global similarities between the query and any protein already present in a public database; the likeness of the query to all available archaeal/bacterial/eukaryotic/viral sequences in the database as a function of amino acid position within the query; the character of secondary structure of the query as a function of amino acid position within the query; the cytoplasmic, transmembrane or extracellular behavior of the query; the nature and position of binding domains, active sites, post-translationally modified sites, signal peptides, etc. In terms of performance, the proposed method is exhaustive, objective and allows for the rapid annotation of individual sequences and full genomes. Annotation examples are presented and discussed in Results, including individual queries and complete genomes that were released publicly after we built the Bio-Dictionary that is used in our experiments. Finally, we have computed the annotations of more than 70 complete genomes and made them available on the World Wide Web at http://cbcsrv.watson.ibm.com/Annotations/. PMID:12202776

Data partitioning enables the use of standard SOAP Web Services in genome-scale workflows.

PubMed

Sztromwasser, Pawel; Puntervoll, Pål; Petersen, Kjell

2011-07-26

Biological databases and computational biology tools are provided by research groups around the world, and made accessible on the Web. Combining these resources is a common practice in bioinformatics, but integration of heterogeneous and often distributed tools and datasets can be challenging. To date, this challenge has been commonly addressed in a pragmatic way, by tedious and error-prone scripting. Recently however a more reliable technique has been identified and proposed as the platform that would tie together bioinformatics resources, namely Web Services. In the last decade the Web Services have spread wide in bioinformatics, and earned the title of recommended technology. However, in the era of high-throughput experimentation, a major concern regarding Web Services is their ability to handle large-scale data traffic. We propose a stream-like communication pattern for standard SOAP Web Services, that enables efficient flow of large data traffic between a workflow orchestrator and Web Services. We evaluated the data-partitioning strategy by comparing it with typical communication patterns on an example pipeline for genomic sequence annotation. The results show that data-partitioning lowers resource demands of services and increases their throughput, which in consequence allows to execute in-silico experiments on genome-scale, using standard SOAP Web Services and workflows. As a proof-of-principle we annotated an RNA-seq dataset using a plain BPEL workflow engine.

dbWGFP: a database and web server of human whole-genome single nucleotide variants and their functional predictions.

PubMed

Wu, Jiaxin; Wu, Mengmeng; Li, Lianshuo; Liu, Zhuo; Zeng, Wanwen; Jiang, Rui

2016-01-01

The recent advancement of the next generation sequencing technology has enabled the fast and low-cost detection of all genetic variants spreading across the entire human genome, making the application of whole-genome sequencing a tendency in the study of disease-causing genetic variants. Nevertheless, there still lacks a repository that collects predictions of functionally damaging effects of human genetic variants, though it has been well recognized that such predictions play a central role in the analysis of whole-genome sequencing data. To fill this gap, we developed a database named dbWGFP (a database and web server of human whole-genome single nucleotide variants and their functional predictions) that contains functional predictions and annotations of nearly 8.58 billion possible human whole-genome single nucleotide variants. Specifically, this database integrates 48 functional predictions calculated by 17 popular computational methods and 44 valuable annotations obtained from various data sources. Standalone software, user-friendly query services and free downloads of this database are available at http://bioinfo.au.tsinghua.edu.cn/dbwgfp. dbWGFP provides a valuable resource for the analysis of whole-genome sequencing, exome sequencing and SNP array data, thereby complementing existing data sources and computational resources in deciphering genetic bases of human inherited diseases. © The Author(s) 2016. Published by Oxford University Press.

GAP Final Technical Report 12-14-04

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

Andrew J. Bordner, PhD, Senior Research Scientist

2004-12-14

The Genomics Annotation Platform (GAP) was designed to develop new tools for high throughput functional annotation and characterization of protein sequences and structures resulting from genomics and structural proteomics, benchmarking and application of those tools. Furthermore, this platform integrated the genomic scale sequence and structural analysis and prediction tools with the advanced structure prediction and bioinformatics environment of ICM. The development of GAP was primarily oriented towards the annotation of new biomolecular structures using both structural and sequence data. Even though the amount of protein X-ray crystal data is growing exponentially, the volume of sequence data is growing even moremore » rapidly. This trend was exploited by leveraging the wealth of sequence data to provide functional annotation for protein structures. The additional information provided by GAP is expected to assist the majority of the commercial users of ICM, who are involved in drug discovery, in identifying promising drug targets as well in devising strategies for the rational design of therapeutics directed at the protein of interest. The GAP also provided valuable tools for biochemistry education, and structural genomics centers. In addition, GAP incorporates many novel prediction and analysis methods not available in other molecular modeling packages. This development led to signing the first Molsoft agreement in the structural genomics annotation area with the University of oxford Structural Genomics Center. This commercial agreement validated the Molsoft efforts under the GAP project and provided the basis for further development of the large scale functional annotation platform.« less

Non-redundant patent sequence databases with value-added annotations at two levels

PubMed Central

Li, Weizhong; McWilliam, Hamish; de la Torre, Ana Richart; Grodowski, Adam; Benediktovich, Irina; Goujon, Mickael; Nauche, Stephane; Lopez, Rodrigo

2010-01-01

The European Bioinformatics Institute (EMBL-EBI) provides public access to patent data, including abstracts, chemical compounds and sequences. Sequences can appear multiple times due to the filing of the same invention with multiple patent offices, or the use of the same sequence by different inventors in different contexts. Information relating to the source invention may be incomplete, and biological information available in patent documents elsewhere may not be reflected in the annotation of the sequence. Search and analysis of these data have become increasingly challenging for both the scientific and intellectual-property communities. Here, we report a collection of non-redundant patent sequence databases, which cover the EMBL-Bank nucleotides patent class and the patent protein databases and contain value-added annotations from patent documents. The databases were created at two levels by the use of sequence MD5 checksums. Sequences within a level-1 cluster are 100% identical over their whole length. Level-2 clusters were defined by sub-grouping level-1 clusters based on patent family information. Value-added annotations, such as publication number corrections, earliest publication dates and feature collations, significantly enhance the quality of the data, allowing for better tracking and cross-referencing. The databases are available format: http://www.ebi.ac.uk/patentdata/nr/. PMID:19884134

Non-redundant patent sequence databases with value-added annotations at two levels.

PubMed

Li, Weizhong; McWilliam, Hamish; de la Torre, Ana Richart; Grodowski, Adam; Benediktovich, Irina; Goujon, Mickael; Nauche, Stephane; Lopez, Rodrigo

2010-01-01

The European Bioinformatics Institute (EMBL-EBI) provides public access to patent data, including abstracts, chemical compounds and sequences. Sequences can appear multiple times due to the filing of the same invention with multiple patent offices, or the use of the same sequence by different inventors in different contexts. Information relating to the source invention may be incomplete, and biological information available in patent documents elsewhere may not be reflected in the annotation of the sequence. Search and analysis of these data have become increasingly challenging for both the scientific and intellectual-property communities. Here, we report a collection of non-redundant patent sequence databases, which cover the EMBL-Bank nucleotides patent class and the patent protein databases and contain value-added annotations from patent documents. The databases were created at two levels by the use of sequence MD5 checksums. Sequences within a level-1 cluster are 100% identical over their whole length. Level-2 clusters were defined by sub-grouping level-1 clusters based on patent family information. Value-added annotations, such as publication number corrections, earliest publication dates and feature collations, significantly enhance the quality of the data, allowing for better tracking and cross-referencing. The databases are available format: http://www.ebi.ac.uk/patentdata/nr/.

Pfarao: a web application for protein family analysis customized for cytoskeletal and motor proteins (CyMoBase)

PubMed Central

Odronitz, Florian; Kollmar, Martin

2006-01-01

Background Annotation of protein sequences of eukaryotic organisms is crucial for the understanding of their function in the cell. Manual annotation is still by far the most accurate way to correctly predict genes. The classification of protein sequences, their phylogenetic relation and the assignment of function involves information from various sources. This often leads to a collection of heterogeneous data, which is hard to track. Cytoskeletal and motor proteins consist of large and diverse superfamilies comprising up to several dozen members per organism. Up to date there is no integrated tool available to assist in the manual large-scale comparative genomic analysis of protein families. Description Pfarao (Protein Family Application for Retrieval, Analysis and Organisation) is a database driven online working environment for the analysis of manually annotated protein sequences and their relationship. Currently, the system can store and interrelate a wide range of information about protein sequences, species, phylogenetic relations and sequencing projects as well as links to literature and domain predictions. Sequences can be imported from multiple sequence alignments that are generated during the annotation process. A web interface allows to conveniently browse the database and to compile tabular and graphical summaries of its content. Conclusion We implemented a protein sequence-centric web application to store, organize, interrelate, and present heterogeneous data that is generated in manual genome annotation and comparative genomics. The application has been developed for the analysis of cytoskeletal and motor proteins (CyMoBase) but can easily be adapted for any protein. PMID:17134497

Sequence- and Structure-Based Functional Annotation and Assessment of Metabolic Transporters in Aspergillus oryzae: A Representative Case Study

PubMed Central

Raethong, Nachon; Wong-ekkabut, Jirasak; Laoteng, Kobkul; Vongsangnak, Wanwipa

2016-01-01

Aspergillus oryzae is widely used for the industrial production of enzymes. In A. oryzae metabolism, transporters appear to play crucial roles in controlling the flux of molecules for energy generation, nutrients delivery, and waste elimination in the cell. While the A. oryzae genome sequence is available, transporter annotation remains limited and thus the connectivity of metabolic networks is incomplete. In this study, we developed a metabolic annotation strategy to understand the relationship between the sequence, structure, and function for annotation of A. oryzae metabolic transporters. Sequence-based analysis with manual curation showed that 58 genes of 12,096 total genes in the A. oryzae genome encoded metabolic transporters. Under consensus integrative databases, 55 unambiguous metabolic transporter genes were distributed into channels and pores (7 genes), electrochemical potential-driven transporters (33 genes), and primary active transporters (15 genes). To reveal the transporter functional role, a combination of homology modeling and molecular dynamics simulation was implemented to assess the relationship between sequence to structure and structure to function. As in the energy metabolism of A. oryzae, the H+-ATPase encoded by the AO090005000842 gene was selected as a representative case study of multilevel linkage annotation. Our developed strategy can be used for enhancing metabolic network reconstruction. PMID:27274991

Sequence- and Structure-Based Functional Annotation and Assessment of Metabolic Transporters in Aspergillus oryzae: A Representative Case Study.

PubMed

Raethong, Nachon; Wong-Ekkabut, Jirasak; Laoteng, Kobkul; Vongsangnak, Wanwipa

2016-01-01

Aspergillus oryzae is widely used for the industrial production of enzymes. In A. oryzae metabolism, transporters appear to play crucial roles in controlling the flux of molecules for energy generation, nutrients delivery, and waste elimination in the cell. While the A. oryzae genome sequence is available, transporter annotation remains limited and thus the connectivity of metabolic networks is incomplete. In this study, we developed a metabolic annotation strategy to understand the relationship between the sequence, structure, and function for annotation of A. oryzae metabolic transporters. Sequence-based analysis with manual curation showed that 58 genes of 12,096 total genes in the A. oryzae genome encoded metabolic transporters. Under consensus integrative databases, 55 unambiguous metabolic transporter genes were distributed into channels and pores (7 genes), electrochemical potential-driven transporters (33 genes), and primary active transporters (15 genes). To reveal the transporter functional role, a combination of homology modeling and molecular dynamics simulation was implemented to assess the relationship between sequence to structure and structure to function. As in the energy metabolism of A. oryzae, the H(+)-ATPase encoded by the AO090005000842 gene was selected as a representative case study of multilevel linkage annotation. Our developed strategy can be used for enhancing metabolic network reconstruction.

BioXSD: the common data-exchange format for everyday bioinformatics web services

PubMed Central

Kalaš, Matúš; Puntervoll, Pæl; Joseph, Alexandre; Bartaševičiūtė, Edita; Töpfer, Armin; Venkataraman, Prabakar; Pettifer, Steve; Bryne, Jan Christian; Ison, Jon; Blanchet, Christophe; Rapacki, Kristoffer; Jonassen, Inge

2010-01-01

Motivation: The world-wide community of life scientists has access to a large number of public bioinformatics databases and tools, which are developed and deployed using diverse technologies and designs. More and more of the resources offer programmatic web-service interface. However, efficient use of the resources is hampered by the lack of widely used, standard data-exchange formats for the basic, everyday bioinformatics data types. Results: BioXSD has been developed as a candidate for standard, canonical exchange format for basic bioinformatics data. BioXSD is represented by a dedicated XML Schema and defines syntax for biological sequences, sequence annotations, alignments and references to resources. We have adapted a set of web services to use BioXSD as the input and output format, and implemented a test-case workflow. This demonstrates that the approach is feasible and provides smooth interoperability. Semantics for BioXSD is provided by annotation with the EDAM ontology. We discuss in a separate section how BioXSD relates to other initiatives and approaches, including existing standards and the Semantic Web. Availability: The BioXSD 1.0 XML Schema is freely available at http://www.bioxsd.org/BioXSD-1.0.xsd under the Creative Commons BY-ND 3.0 license. The http://bioxsd.org web page offers documentation, examples of data in BioXSD format, example workflows with source codes in common programming languages, an updated list of compatible web services and tools and a repository of feature requests from the community. Contact: matus.kalas@bccs.uib.no; developers@bioxsd.org; support@bioxsd.org PMID:20823319

INDIGO – INtegrated Data Warehouse of MIcrobial GenOmes with Examples from the Red Sea Extremophiles

PubMed Central

Alam, Intikhab; Antunes, André; Kamau, Allan Anthony; Ba alawi, Wail; Kalkatawi, Manal; Stingl, Ulrich; Bajic, Vladimir B.

2013-01-01

Background The next generation sequencing technologies substantially increased the throughput of microbial genome sequencing. To functionally annotate newly sequenced microbial genomes, a variety of experimental and computational methods are used. Integration of information from different sources is a powerful approach to enhance such annotation. Functional analysis of microbial genomes, necessary for downstream experiments, crucially depends on this annotation but it is hampered by the current lack of suitable information integration and exploration systems for microbial genomes. Results We developed a data warehouse system (INDIGO) that enables the integration of annotations for exploration and analysis of newly sequenced microbial genomes. INDIGO offers an opportunity to construct complex queries and combine annotations from multiple sources starting from genomic sequence to protein domain, gene ontology and pathway levels. This data warehouse is aimed at being populated with information from genomes of pure cultures and uncultured single cells of Red Sea bacteria and Archaea. Currently, INDIGO contains information from Salinisphaera shabanensis, Haloplasma contractile, and Halorhabdus tiamatea - extremophiles isolated from deep-sea anoxic brine lakes of the Red Sea. We provide examples of utilizing the system to gain new insights into specific aspects on the unique lifestyle and adaptations of these organisms to extreme environments. Conclusions We developed a data warehouse system, INDIGO, which enables comprehensive integration of information from various resources to be used for annotation, exploration and analysis of microbial genomes. It will be regularly updated and extended with new genomes. It is aimed to serve as a resource dedicated to the Red Sea microbes. In addition, through INDIGO, we provide our Automatic Annotation of Microbial Genomes (AAMG) pipeline. The INDIGO web server is freely available at http://www.cbrc.kaust.edu.sa/indigo. PMID:24324765

INDIGO - INtegrated data warehouse of microbial genomes with examples from the red sea extremophiles.

PubMed

Alam, Intikhab; Antunes, André; Kamau, Allan Anthony; Ba Alawi, Wail; Kalkatawi, Manal; Stingl, Ulrich; Bajic, Vladimir B

2013-01-01

The next generation sequencing technologies substantially increased the throughput of microbial genome sequencing. To functionally annotate newly sequenced microbial genomes, a variety of experimental and computational methods are used. Integration of information from different sources is a powerful approach to enhance such annotation. Functional analysis of microbial genomes, necessary for downstream experiments, crucially depends on this annotation but it is hampered by the current lack of suitable information integration and exploration systems for microbial genomes. We developed a data warehouse system (INDIGO) that enables the integration of annotations for exploration and analysis of newly sequenced microbial genomes. INDIGO offers an opportunity to construct complex queries and combine annotations from multiple sources starting from genomic sequence to protein domain, gene ontology and pathway levels. This data warehouse is aimed at being populated with information from genomes of pure cultures and uncultured single cells of Red Sea bacteria and Archaea. Currently, INDIGO contains information from Salinisphaera shabanensis, Haloplasma contractile, and Halorhabdus tiamatea - extremophiles isolated from deep-sea anoxic brine lakes of the Red Sea. We provide examples of utilizing the system to gain new insights into specific aspects on the unique lifestyle and adaptations of these organisms to extreme environments. We developed a data warehouse system, INDIGO, which enables comprehensive integration of information from various resources to be used for annotation, exploration and analysis of microbial genomes. It will be regularly updated and extended with new genomes. It is aimed to serve as a resource dedicated to the Red Sea microbes. In addition, through INDIGO, we provide our Automatic Annotation of Microbial Genomes (AAMG) pipeline. The INDIGO web server is freely available at http://www.cbrc.kaust.edu.sa/indigo.

WImpiBLAST: web interface for mpiBLAST to help biologists perform large-scale annotation using high performance computing.

PubMed

Sharma, Parichit; Mantri, Shrikant S

2014-01-01

The function of a newly sequenced gene can be discovered by determining its sequence homology with known proteins. BLAST is the most extensively used sequence analysis program for sequence similarity search in large databases of sequences. With the advent of next generation sequencing technologies it has now become possible to study genes and their expression at a genome-wide scale through RNA-seq and metagenome sequencing experiments. Functional annotation of all the genes is done by sequence similarity search against multiple protein databases. This annotation task is computationally very intensive and can take days to obtain complete results. The program mpiBLAST, an open-source parallelization of BLAST that achieves superlinear speedup, can be used to accelerate large-scale annotation by using supercomputers and high performance computing (HPC) clusters. Although many parallel bioinformatics applications using the Message Passing Interface (MPI) are available in the public domain, researchers are reluctant to use them due to lack of expertise in the Linux command line and relevant programming experience. With these limitations, it becomes difficult for biologists to use mpiBLAST for accelerating annotation. No web interface is available in the open-source domain for mpiBLAST. We have developed WImpiBLAST, a user-friendly open-source web interface for parallel BLAST searches. It is implemented in Struts 1.3 using a Java backbone and runs atop the open-source Apache Tomcat Server. WImpiBLAST supports script creation and job submission features and also provides a robust job management interface for system administrators. It combines script creation and modification features with job monitoring and management through the Torque resource manager on a Linux-based HPC cluster. Use case information highlights the acceleration of annotation analysis achieved by using WImpiBLAST. Here, we describe the WImpiBLAST web interface features and architecture, explain design decisions, describe workflows and provide a detailed analysis.

WImpiBLAST: Web Interface for mpiBLAST to Help Biologists Perform Large-Scale Annotation Using High Performance Computing

PubMed Central

Sharma, Parichit; Mantri, Shrikant S.

2014-01-01

The function of a newly sequenced gene can be discovered by determining its sequence homology with known proteins. BLAST is the most extensively used sequence analysis program for sequence similarity search in large databases of sequences. With the advent of next generation sequencing technologies it has now become possible to study genes and their expression at a genome-wide scale through RNA-seq and metagenome sequencing experiments. Functional annotation of all the genes is done by sequence similarity search against multiple protein databases. This annotation task is computationally very intensive and can take days to obtain complete results. The program mpiBLAST, an open-source parallelization of BLAST that achieves superlinear speedup, can be used to accelerate large-scale annotation by using supercomputers and high performance computing (HPC) clusters. Although many parallel bioinformatics applications using the Message Passing Interface (MPI) are available in the public domain, researchers are reluctant to use them due to lack of expertise in the Linux command line and relevant programming experience. With these limitations, it becomes difficult for biologists to use mpiBLAST for accelerating annotation. No web interface is available in the open-source domain for mpiBLAST. We have developed WImpiBLAST, a user-friendly open-source web interface for parallel BLAST searches. It is implemented in Struts 1.3 using a Java backbone and runs atop the open-source Apache Tomcat Server. WImpiBLAST supports script creation and job submission features and also provides a robust job management interface for system administrators. It combines script creation and modification features with job monitoring and management through the Torque resource manager on a Linux-based HPC cluster. Use case information highlights the acceleration of annotation analysis achieved by using WImpiBLAST. Here, we describe the WImpiBLAST web interface features and architecture, explain design decisions, describe workflows and provide a detailed analysis. PMID:24979410

EuroPineDB: a high-coverage web database for maritime pine transcriptome

PubMed Central

2011-01-01

Background Pinus pinaster is an economically and ecologically important species that is becoming a woody gymnosperm model. Its enormous genome size makes whole-genome sequencing approaches are hard to apply. Therefore, the expressed portion of the genome has to be characterised and the results and annotations have to be stored in dedicated databases. Description EuroPineDB is the largest sequence collection available for a single pine species, Pinus pinaster (maritime pine), since it comprises 951 641 raw sequence reads obtained from non-normalised cDNA libraries and high-throughput sequencing from adult (xylem, phloem, roots, stem, needles, cones, strobili) and embryonic (germinated embryos, buds, callus) maritime pine tissues. Using open-source tools, sequences were optimally pre-processed, assembled, and extensively annotated (GO, EC and KEGG terms, descriptions, SNPs, SSRs, ORFs and InterPro codes). As a result, a 10.5× P. pinaster genome was covered and assembled in 55 322 UniGenes. A total of 32 919 (59.5%) of P. pinaster UniGenes were annotated with at least one description, revealing at least 18 466 different genes. The complete database, which is designed to be scalable, maintainable, and expandable, is freely available at: http://www.scbi.uma.es/pindb/. It can be retrieved by gene libraries, pine species, annotations, UniGenes and microarrays (i.e., the sequences are distributed in two-colour microarrays; this is the only conifer database that provides this information) and will be periodically updated. Small assemblies can be viewed using a dedicated visualisation tool that connects them with SNPs. Any sequence or annotation set shown on-screen can be downloaded. Retrieval mechanisms for sequences and gene annotations are provided. Conclusions The EuroPineDB with its integrated information can be used to reveal new knowledge, offers an easy-to-use collection of information to directly support experimental work (including microarray hybridisation), and provides deeper knowledge on the maritime pine transcriptome. PMID:21762488

Introducing meta-services for biomedical information extraction

PubMed Central

Leitner, Florian; Krallinger, Martin; Rodriguez-Penagos, Carlos; Hakenberg, Jörg; Plake, Conrad; Kuo, Cheng-Ju; Hsu, Chun-Nan; Tsai, Richard Tzong-Han; Hung, Hsi-Chuan; Lau, William W; Johnson, Calvin A; Sætre, Rune; Yoshida, Kazuhiro; Chen, Yan Hua; Kim, Sun; Shin, Soo-Yong; Zhang, Byoung-Tak; Baumgartner, William A; Hunter, Lawrence; Haddow, Barry; Matthews, Michael; Wang, Xinglong; Ruch, Patrick; Ehrler, Frédéric; Özgür, Arzucan; Erkan, Güneş; Radev, Dragomir R; Krauthammer, Michael; Luong, ThaiBinh; Hoffmann, Robert; Sander, Chris; Valencia, Alfonso

2008-01-01

We introduce the first meta-service for information extraction in molecular biology, the BioCreative MetaServer (BCMS; ). This prototype platform is a joint effort of 13 research groups and provides automatically generated annotations for PubMed/Medline abstracts. Annotation types cover gene names, gene IDs, species, and protein-protein interactions. The annotations are distributed by the meta-server in both human and machine readable formats (HTML/XML). This service is intended to be used by biomedical researchers and database annotators, and in biomedical language processing. The platform allows direct comparison, unified access, and result aggregation of the annotations. PMID:18834497

Using hidden Markov models and observed evolution to annotate viral genomes.

PubMed

McCauley, Stephen; Hein, Jotun

2006-06-01

ssRNA (single stranded) viral genomes are generally constrained in length and utilize overlapping reading frames to maximally exploit the coding potential within the genome length restrictions. This overlapping coding phenomenon leads to complex evolutionary constraints operating on the genome. In regions which code for more than one protein, silent mutations in one reading frame generally have a protein coding effect in another. To maximize coding flexibility in all reading frames, overlapping regions are often compositionally biased towards amino acids which are 6-fold degenerate with respect to the 64 codon alphabet. Previous methodologies have used this fact in an ad hoc manner to look for overlapping genes by motif matching. In this paper differentiated nucleotide compositional patterns in overlapping regions are incorporated into a probabilistic hidden Markov model (HMM) framework which is used to annotate ssRNA viral genomes. This work focuses on single sequence annotation and applies an HMM framework to ssRNA viral annotation. A description of how the HMM is parameterized, whilst annotating within a missing data framework is given. A Phylogenetic HMM (Phylo-HMM) extension, as applied to 14 aligned HIV2 sequences is also presented. This evolutionary extension serves as an illustration of the potential of the Phylo-HMM framework for ssRNA viral genomic annotation. The single sequence annotation procedure (SSA) is applied to 14 different strains of the HIV2 virus. Further results on alternative ssRNA viral genomes are presented to illustrate more generally the performance of the method. The results of the SSA method are encouraging however there is still room for improvement, and since there is overwhelming evidence to indicate that comparative methods can improve coding sequence (CDS) annotation, the SSA method is extended to a Phylo-HMM to incorporate evolutionary information. The Phylo-HMM extension is applied to the same set of 14 HIV2 sequences which are pre-aligned. The performance improvement that results from including the evolutionary information in the analysis is illustrated.

Hymenoptera Genome Database: integrating genome annotations in HymenopteraMine.

PubMed

Elsik, Christine G; Tayal, Aditi; Diesh, Colin M; Unni, Deepak R; Emery, Marianne L; Nguyen, Hung N; Hagen, Darren E

2016-01-04

We report an update of the Hymenoptera Genome Database (HGD) (http://HymenopteraGenome.org), a model organism database for insect species of the order Hymenoptera (ants, bees and wasps). HGD maintains genomic data for 9 bee species, 10 ant species and 1 wasp, including the versions of genome and annotation data sets published by the genome sequencing consortiums and those provided by NCBI. A new data-mining warehouse, HymenopteraMine, based on the InterMine data warehousing system, integrates the genome data with data from external sources and facilitates cross-species analyses based on orthology. New genome browsers and annotation tools based on JBrowse/WebApollo provide easy genome navigation, and viewing of high throughput sequence data sets and can be used for collaborative genome annotation. All of the genomes and annotation data sets are combined into a single BLAST server that allows users to select and combine sequence data sets to search. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

A Polyglot Approach to Bioinformatics Data Integration: A Phylogenetic Analysis of HIV-1

PubMed Central

Reisman, Steven; Hatzopoulos, Thomas; Läufer, Konstantin; Thiruvathukal, George K.; Putonti, Catherine

2016-01-01

As sequencing technologies continue to drop in price and increase in throughput, new challenges emerge for the management and accessibility of genomic sequence data. We have developed a pipeline for facilitating the storage, retrieval, and subsequent analysis of molecular data, integrating both sequence and metadata. Taking a polyglot approach involving multiple languages, libraries, and persistence mechanisms, sequence data can be aggregated from publicly available and local repositories. Data are exposed in the form of a RESTful web service, formatted for easy querying, and retrieved for downstream analyses. As a proof of concept, we have developed a resource for annotated HIV-1 sequences. Phylogenetic analyses were conducted for >6,000 HIV-1 sequences revealing spatial and temporal factors influence the evolution of the individual genes uniquely. Nevertheless, signatures of origin can be extrapolated even despite increased globalization. The approach developed here can easily be customized for any species of interest. PMID:26819543

GAMES identifies and annotates mutations in next-generation sequencing projects.

PubMed

Sana, Maria Elena; Iascone, Maria; Marchetti, Daniela; Palatini, Jeff; Galasso, Marco; Volinia, Stefano

2011-01-01

Next-generation sequencing (NGS) methods have the potential for changing the landscape of biomedical science, but at the same time pose several problems in analysis and interpretation. Currently, there are many commercial and public software packages that analyze NGS data. However, the limitations of these applications include output which is insufficiently annotated and of difficult functional comprehension to end users. We developed GAMES (Genomic Analysis of Mutations Extracted by Sequencing), a pipeline aiming to serve as an efficient middleman between data deluge and investigators. GAMES attains multiple levels of filtering and annotation, such as aligning the reads to a reference genome, performing quality control and mutational analysis, integrating results with genome annotations and sorting each mismatch/deletion according to a range of parameters. Variations are matched to known polymorphisms. The prediction of functional mutations is achieved by using different approaches. Overall GAMES enables an effective complexity reduction in large-scale DNA-sequencing projects. GAMES is available free of charge to academic users and may be obtained from http://aqua.unife.it/GAMES.

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.

The 2nd DBCLS BioHackathon: interoperable bioinformatics Web services for integrated applications

PubMed Central

2011-01-01

Background The interaction between biological researchers and the bioinformatics tools they use is still hampered by incomplete interoperability between such tools. To ensure interoperability initiatives are effectively deployed, end-user applications need to be aware of, and support, best practices and standards. Here, we report on an initiative in which software developers and genome biologists came together to explore and raise awareness of these issues: BioHackathon 2009. Results Developers in attendance came from diverse backgrounds, with experts in Web services, workflow tools, text mining and visualization. Genome biologists provided expertise and exemplar data from the domains of sequence and pathway analysis and glyco-informatics. One goal of the meeting was to evaluate the ability to address real world use cases in these domains using the tools that the developers represented. This resulted in i) a workflow to annotate 100,000 sequences from an invertebrate species; ii) an integrated system for analysis of the transcription factor binding sites (TFBSs) enriched based on differential gene expression data obtained from a microarray experiment; iii) a workflow to enumerate putative physical protein interactions among enzymes in a metabolic pathway using protein structure data; iv) a workflow to analyze glyco-gene-related diseases by searching for human homologs of glyco-genes in other species, such as fruit flies, and retrieving their phenotype-annotated SNPs. Conclusions Beyond deriving prototype solutions for each use-case, a second major purpose of the BioHackathon was to highlight areas of insufficiency. We discuss the issues raised by our exploration of the problem/solution space, concluding that there are still problems with the way Web services are modeled and annotated, including: i) the absence of several useful data or analysis functions in the Web service "space"; ii) the lack of documentation of methods; iii) lack of compliance with the SOAP/WSDL specification among and between various programming-language libraries; and iv) incompatibility between various bioinformatics data formats. Although it was still difficult to solve real world problems posed to the developers by the biological researchers in attendance because of these problems, we note the promise of addressing these issues within a semantic framework. PMID:21806842

The 2nd DBCLS BioHackathon: interoperable bioinformatics Web services for integrated applications.

PubMed

Katayama, Toshiaki; Wilkinson, Mark D; Vos, Rutger; Kawashima, Takeshi; Kawashima, Shuichi; Nakao, Mitsuteru; Yamamoto, Yasunori; Chun, Hong-Woo; Yamaguchi, Atsuko; Kawano, Shin; Aerts, Jan; Aoki-Kinoshita, Kiyoko F; Arakawa, Kazuharu; Aranda, Bruno; Bonnal, Raoul Jp; Fernández, José M; Fujisawa, Takatomo; Gordon, Paul Mk; Goto, Naohisa; Haider, Syed; Harris, Todd; Hatakeyama, Takashi; Ho, Isaac; Itoh, Masumi; Kasprzyk, Arek; Kido, Nobuhiro; Kim, Young-Joo; Kinjo, Akira R; Konishi, Fumikazu; Kovarskaya, Yulia; von Kuster, Greg; Labarga, Alberto; Limviphuvadh, Vachiranee; McCarthy, Luke; Nakamura, Yasukazu; Nam, Yunsun; Nishida, Kozo; Nishimura, Kunihiro; Nishizawa, Tatsuya; Ogishima, Soichi; Oinn, Tom; Okamoto, Shinobu; Okuda, Shujiro; Ono, Keiichiro; Oshita, Kazuki; Park, Keun-Joon; Putnam, Nicholas; Senger, Martin; Severin, Jessica; Shigemoto, Yasumasa; Sugawara, Hideaki; Taylor, James; Trelles, Oswaldo; Yamasaki, Chisato; Yamashita, Riu; Satoh, Noriyuki; Takagi, Toshihisa

2011-08-02

The interaction between biological researchers and the bioinformatics tools they use is still hampered by incomplete interoperability between such tools. To ensure interoperability initiatives are effectively deployed, end-user applications need to be aware of, and support, best practices and standards. Here, we report on an initiative in which software developers and genome biologists came together to explore and raise awareness of these issues: BioHackathon 2009. Developers in attendance came from diverse backgrounds, with experts in Web services, workflow tools, text mining and visualization. Genome biologists provided expertise and exemplar data from the domains of sequence and pathway analysis and glyco-informatics. One goal of the meeting was to evaluate the ability to address real world use cases in these domains using the tools that the developers represented. This resulted in i) a workflow to annotate 100,000 sequences from an invertebrate species; ii) an integrated system for analysis of the transcription factor binding sites (TFBSs) enriched based on differential gene expression data obtained from a microarray experiment; iii) a workflow to enumerate putative physical protein interactions among enzymes in a metabolic pathway using protein structure data; iv) a workflow to analyze glyco-gene-related diseases by searching for human homologs of glyco-genes in other species, such as fruit flies, and retrieving their phenotype-annotated SNPs. Beyond deriving prototype solutions for each use-case, a second major purpose of the BioHackathon was to highlight areas of insufficiency. We discuss the issues raised by our exploration of the problem/solution space, concluding that there are still problems with the way Web services are modeled and annotated, including: i) the absence of several useful data or analysis functions in the Web service "space"; ii) the lack of documentation of methods; iii) lack of compliance with the SOAP/WSDL specification among and between various programming-language libraries; and iv) incompatibility between various bioinformatics data formats. Although it was still difficult to solve real world problems posed to the developers by the biological researchers in attendance because of these problems, we note the promise of addressing these issues within a semantic framework.

VAT: a computational framework to functionally annotate variants in personal genomes within a cloud-computing environment.

PubMed

Habegger, Lukas; Balasubramanian, Suganthi; Chen, David Z; Khurana, Ekta; Sboner, Andrea; Harmanci, Arif; Rozowsky, Joel; Clarke, Declan; Snyder, Michael; Gerstein, Mark

2012-09-01

The functional annotation of variants obtained through sequencing projects is generally assumed to be a simple intersection of genomic coordinates with genomic features. However, complexities arise for several reasons, including the differential effects of a variant on alternatively spliced transcripts, as well as the difficulty in assessing the impact of small insertions/deletions and large structural variants. Taking these factors into consideration, we developed the Variant Annotation Tool (VAT) to functionally annotate variants from multiple personal genomes at the transcript level as well as obtain summary statistics across genes and individuals. VAT also allows visualization of the effects of different variants, integrates allele frequencies and genotype data from the underlying individuals and facilitates comparative analysis between different groups of individuals. VAT can either be run through a command-line interface or as a web application. Finally, in order to enable on-demand access and to minimize unnecessary transfers of large data files, VAT can be run as a virtual machine in a cloud-computing environment. VAT is implemented in C and PHP. The VAT web service, Amazon Machine Image, source code and detailed documentation are available at vat.gersteinlab.org.

First Pass Annotation of Promoters on Human Chromosome 22

PubMed Central

Scherf, Matthias; Klingenhoff, Andreas; Frech, Kornelie; Quandt, Kerstin; Schneider, Ralf; Grote, Korbinian; Frisch, Matthias; Gailus-Durner, Valérie; Seidel, Alexander; Brack-Werner, Ruth; Werner, Thomas

2001-01-01

The publication of the first almost complete sequence of a human chromosome (chromosome 22) is a major milestone in human genomics. Together with the sequence, an excellent annotation of genes was published which certainly will serve as an information resource for numerous future projects. We noted that the annotation did not cover regulatory regions; in particular, no promoter annotation has been provided. Here we present an analysis of the complete published chromosome 22 sequence for promoters. A recent breakthrough in specific in silico prediction of promoter regions enabled us to attempt large-scale prediction of promoter regions on chromosome 22. Scanning of sequence databases revealed only 20 experimentally verified promoters, of which 10 were correctly predicted by our approach. Nearly 40% of our 465 predicted promoter regions are supported by the currently available gene annotation. Promoter finding also provides a biologically meaningful method for “chromosomal scaffolding”, by which long genomic sequences can be divided into segments starting with a gene. As one example, the combination of promoter region prediction with exon/intron structure predictions greatly enhances the specificity of de novo gene finding. The present study demonstrates that it is possible to identify promoters in silico on the chromosomal level with sufficient reliability for experimental planning and indicates that a wealth of information about regulatory regions can be extracted from current large-scale (megabase) sequencing projects. Results are available on-line at http://genomatix.gsf.de/chr22/. PMID:11230158

xGDBvm: A Web GUI-Driven Workflow for Annotating Eukaryotic Genomes in the Cloud[OPEN

PubMed Central

Merchant, Nirav

2016-01-01

Genome-wide annotation of gene structure requires the integration of numerous computational steps. Currently, annotation is arguably best accomplished through collaboration of bioinformatics and domain experts, with broad community involvement. However, such a collaborative approach is not scalable at today’s pace of sequence generation. To address this problem, we developed the xGDBvm software, which uses an intuitive graphical user interface to access a number of common genome analysis and gene structure tools, preconfigured in a self-contained virtual machine image. Once their virtual machine instance is deployed through iPlant’s Atmosphere cloud services, users access the xGDBvm workflow via a unified Web interface to manage inputs, set program parameters, configure links to high-performance computing (HPC) resources, view and manage output, apply analysis and editing tools, or access contextual help. The xGDBvm workflow will mask the genome, compute spliced alignments from transcript and/or protein inputs (locally or on a remote HPC cluster), predict gene structures and gene structure quality, and display output in a public or private genome browser complete with accessory tools. Problematic gene predictions are flagged and can be reannotated using the integrated yrGATE annotation tool. xGDBvm can also be configured to append or replace existing data or load precomputed data. Multiple genomes can be annotated and displayed, and outputs can be archived for sharing or backup. xGDBvm can be adapted to a variety of use cases including de novo genome annotation, reannotation, comparison of different annotations, and training or teaching. PMID:27020957

xGDBvm: A Web GUI-Driven Workflow for Annotating Eukaryotic Genomes in the Cloud.

PubMed

Duvick, Jon; Standage, Daniel S; Merchant, Nirav; Brendel, Volker P

2016-04-01

Genome-wide annotation of gene structure requires the integration of numerous computational steps. Currently, annotation is arguably best accomplished through collaboration of bioinformatics and domain experts, with broad community involvement. However, such a collaborative approach is not scalable at today's pace of sequence generation. To address this problem, we developed the xGDBvm software, which uses an intuitive graphical user interface to access a number of common genome analysis and gene structure tools, preconfigured in a self-contained virtual machine image. Once their virtual machine instance is deployed through iPlant's Atmosphere cloud services, users access the xGDBvm workflow via a unified Web interface to manage inputs, set program parameters, configure links to high-performance computing (HPC) resources, view and manage output, apply analysis and editing tools, or access contextual help. The xGDBvm workflow will mask the genome, compute spliced alignments from transcript and/or protein inputs (locally or on a remote HPC cluster), predict gene structures and gene structure quality, and display output in a public or private genome browser complete with accessory tools. Problematic gene predictions are flagged and can be reannotated using the integrated yrGATE annotation tool. xGDBvm can also be configured to append or replace existing data or load precomputed data. Multiple genomes can be annotated and displayed, and outputs can be archived for sharing or backup. xGDBvm can be adapted to a variety of use cases including de novo genome annotation, reannotation, comparison of different annotations, and training or teaching. © 2016 American Society of Plant Biologists. All rights reserved.

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.

Homology to peptide pattern for annotation of carbohydrate-active enzymes and prediction of function.

PubMed

Busk, P K; Pilgaard, B; Lezyk, M J; Meyer, A S; Lange, L

2017-04-12

Carbohydrate-active enzymes are found in all organisms and participate in key biological processes. These enzymes are classified in 274 families in the CAZy database but the sequence diversity within each family makes it a major task to identify new family members and to provide basis for prediction of enzyme function. A fast and reliable method for de novo annotation of genes encoding carbohydrate-active enzymes is to identify conserved peptides in the curated enzyme families followed by matching of the conserved peptides to the sequence of interest as demonstrated for the glycosyl hydrolase and the lytic polysaccharide monooxygenase families. This approach not only assigns the enzymes to families but also provides functional prediction of the enzymes with high accuracy. We identified conserved peptides for all enzyme families in the CAZy database with Peptide Pattern Recognition. The conserved peptides were matched to protein sequence for de novo annotation and functional prediction of carbohydrate-active enzymes with the Hotpep method. Annotation of protein sequences from 12 bacterial and 16 fungal genomes to families with Hotpep had an accuracy of 0.84 (measured as F1-score) compared to semiautomatic annotation by the CAZy database whereas the dbCAN HMM-based method had an accuracy of 0.77 with optimized parameters. Furthermore, Hotpep provided a functional prediction with 86% accuracy for the annotated genes. Hotpep is available as a stand-alone application for MS Windows. Hotpep is a state-of-the-art method for automatic annotation and functional prediction of carbohydrate-active enzymes.

Mercury: Next-gen Data Analysis and Annotation Pipeline (Seventh Annual Sequencing, Finishing, Analysis in the Future (SFAF) Meeting 2012)

ScienceCinema

Sexton, David

2018-01-22

David Sexton (Baylor) gives a talk titled "Mercury: Next-gen Data Analysis and Annotation Pipeline" at the 7th Annual Sequencing, Finishing, Analysis in the Future (SFAF) Meeting held in June, 2012 in Santa Fe, NM.

Mercury: Next-gen Data Analysis and Annotation Pipeline (Seventh Annual Sequencing, Finishing, Analysis in the Future (SFAF) Meeting 2012)

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

Sexton, David

2012-06-01

David Sexton (Baylor) gives a talk titled "Mercury: Next-gen Data Analysis and Annotation Pipeline" at the 7th Annual Sequencing, Finishing, Analysis in the Future (SFAF) Meeting held in June, 2012 in Santa Fe, NM.

Sequencing, De Novo Assembly, and Annotation of the Complete Genome of a New Thraustochytrid Species, Strain CCAP_4062/3

PubMed Central

Seddiki, Khawla; Godart, François; Aiese Cigliano, Riccardo; Sanseverino, Walter; Barakat, Mohamed; Ortet, Philippe; Rébeillé, Fabrice; Maréchal, Eric

2018-01-01

ABSTRACT Thraustochytrids are ecologically and biotechnologically relevant marine species. We report here the de novo assembly and annotation of the whole-genome sequence of a new thraustochytrid strain, CCAP_4062/3. The genome size was estimated at 38.7 Mb with 11,853 predicted coding sequences, and the GC content was scored at 57%. PMID:29545303

RNA-Seq analysis and transcriptome assembly for blackberry (Rubus sp. Var. Lochness) fruit.

PubMed

Garcia-Seco, Daniel; Zhang, Yang; Gutierrez-Mañero, Francisco J; Martin, Cathie; Ramos-Solano, Beatriz

2015-01-22

There is an increasing interest in berries, especially blackberries in the diet, because of recent reports of their health benefits due to their high content of flavonoids. A broad range of genomic tools are available for other Rosaceae species but these tools are still lacking in the Rubus genus, thus limiting gene discovery and the breeding of improved varieties. De novo RNA-seq of ripe blackberries grown under field conditions was performed using Illumina Hiseq 2000. Almost 9 billion nucleotide bases were sequenced in total. Following assembly, 42,062 consensus sequences were detected. For functional annotation, 33,040 (NR), 32,762 (NT), 21,932 (Swiss-Prot), 20,134 (KEGG), 13,676 (COG), 24,168 (GO) consensus sequences were annotated using different databases; in total 34,552 annotated sequences were identified. For protein prediction analysis, the number of coding DNA sequences (CDS) that mapped to the protein database was 32,540. Non redundant (NR), annotation showed that 25,418 genes (73.5%) has the highest similarity with Fragaria vesca subspecies vesca. Reanalysis was undertaken by aligning the reads with this reference genome for a deeper analysis of the transcriptome. We demonstrated that de novo assembly, using Trinity and later annotation with Blast using different databases, were complementary to alignment to the reference sequence using SOAPaligner/SOAP2. The Fragaria reference genome belongs to a species in the same family as blackberry (Rosaceae) but to a different genus. Since blackberries are tetraploids, the possibility of artefactual gene chimeras resulting from mis-assembly was tested with one of the genes sequenced by RNAseq, Chalcone Synthase (CHS). cDNAs encoding this protein were cloned and sequenced. Primers designed to the assembled sequences accurately distinguished different contigs, at least for chalcone synthase genes. We prepared and analysed transcriptome data from ripe blackberries, for which prior genomic information was limited. This new sequence information will improve the knowledge of this important and healthy fruit, providing an invaluable new tool for biological research.

Complete Genome Sequence of Listeria monocytogenes DFPST0073, Isolated from Imported Mexican Soft Cheese.

PubMed

Salazar, Joelle K; Gonsalves, Lauren J; Schill, Kristin M; Sanchez Leon, Maria; Anderson, Nathan; Keller, Susanne E

2018-06-07

The genome of Listeria monocytogenes strain DFPST0073, isolated from imported fresh Mexican soft cheese in 2003, was sequenced using the Illumina MiSeq platform. Reads were assembled using SPAdes, and genome annotation was performed using the NCBI Prokaryotic Genome Annotation Pipeline.

Transcriptome assembly, gene annotation and tissue gene expression atlas of the rainbow trout

USDA-ARS?s Scientific Manuscript database

Efforts to obtain a comprehensive genome sequence for rainbow trout are ongoing and will be complimented by transcriptome information that will enhance genome assembly and annotation. Previously, we reported a transcriptome reference sequence using a 19X coverage of Sanger and 454-pyrosequencing dat...

MEGAnnotator: a user-friendly pipeline for microbial genomes assembly and annotation.

PubMed

Lugli, Gabriele Andrea; Milani, Christian; Mancabelli, Leonardo; van Sinderen, Douwe; Ventura, Marco

2016-04-01

Genome annotation is one of the key actions that must be undertaken in order to decipher the genetic blueprint of organisms. Thus, a correct and reliable annotation is essential in rendering genomic data valuable. Here, we describe a bioinformatics pipeline based on freely available software programs coordinated by a multithreaded script named MEGAnnotator (Multithreaded Enhanced prokaryotic Genome Annotator). This pipeline allows the generation of multiple annotated formats fulfilling the NCBI guidelines for assembled microbial genome submission, based on DNA shotgun sequencing reads, and minimizes manual intervention, while also reducing waiting times between software program executions and improving final quality of both assembly and annotation outputs. MEGAnnotator provides an efficient way to pre-arrange the assembly and annotation work required to process NGS genome sequence data. The script improves the final quality of microbial genome annotation by reducing ambiguous annotations. Moreover, the MEGAnnotator platform allows the user to perform a partial annotation of pre-assembled genomes and includes an option to accomplish metagenomic data set assemblies. MEGAnnotator platform will be useful for microbiologists interested in genome analyses of bacteria as well as those investigating the complexity of microbial communities that do not possess the necessary skills to prepare their own bioinformatics pipeline. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Whole genome sequence and genome annotation of Colletotrichum acutatum, causal agent of anthracnose in pepper plants in South Korea.

PubMed

Han, Joon-Hee; Chon, Jae-Kyung; Ahn, Jong-Hwa; Choi, Ik-Young; Lee, Yong-Hwan; Kim, Kyoung Su

2016-06-01

Colletotrichum acutatum is a destructive fungal pathogen which causes anthracnose in a wide range of crops. Here we report the whole genome sequence and annotation of C. acutatum strain KC05, isolated from an infected pepper in Kangwon, South Korea. Genomic DNA from the KC05 strain was used for the whole genome sequencing using a PacBio sequencer and the MiSeq system. The KC05 genome was determined to be 52,190,760 bp in size with a G + C content of 51.73% in 27 scaffolds and to contain 13,559 genes with an average length of 1516 bp. Gene prediction and annotation were performed by incorporating RNA-Seq data. The genome sequence of the KC05 was deposited at DDBJ/ENA/GenBank under the accession number LUXP00000000.

Ensembl 2002: accommodating comparative genomics.

PubMed

Clamp, M; Andrews, D; Barker, D; Bevan, P; Cameron, G; Chen, Y; Clark, L; Cox, T; Cuff, J; Curwen, V; Down, T; Durbin, R; Eyras, E; Gilbert, J; Hammond, M; Hubbard, T; Kasprzyk, A; Keefe, D; Lehvaslaiho, H; Iyer, V; Melsopp, C; Mongin, E; Pettett, R; Potter, S; Rust, A; Schmidt, E; Searle, S; Slater, G; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Stupka, E; Ureta-Vidal, A; Vastrik, I; Birney, E

2003-01-01

The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organise biology around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of human, mouse and other genome sequences, available as either an interactive web site or as flat files. Ensembl also integrates manually annotated gene structures from external sources where available. As well as being one of the leading sources of genome annotation, Ensembl is an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements. These range from sequence analysis to data storage and visualisation and installations exist around the world in both companies and at academic sites. With both human and mouse genome sequences available and more vertebrate sequences to follow, many of the recent developments in Ensembl have focusing on developing automatic comparative genome analysis and visualisation.

Revisiting Criteria for Plant MicroRNA Annotation in the Era of Big Data[OPEN

PubMed Central

2018-01-01

MicroRNAs (miRNAs) are ∼21-nucleotide-long regulatory RNAs that arise from endonucleolytic processing of hairpin precursors. Many function as essential posttranscriptional regulators of target mRNAs and long noncoding RNAs. Alongside miRNAs, plants also produce large numbers of short interfering RNAs (siRNAs), which are distinguished from miRNAs primarily by their biogenesis (typically processed from long double-stranded RNA instead of single-stranded hairpins) and functions (typically via roles in transcriptional regulation instead of posttranscriptional regulation). Next-generation DNA sequencing methods have yielded extensive data sets of plant small RNAs, resulting in many miRNA annotations. However, it has become clear that many miRNA annotations are questionable. The sheer number of endogenous siRNAs compared with miRNAs has been a major factor in the erroneous annotation of siRNAs as miRNAs. Here, we provide updated criteria for the confident annotation of plant miRNAs, suitable for the era of “big data” from DNA sequencing. The updated criteria emphasize replication and the minimization of false positives, and they require next-generation sequencing of small RNAs. We argue that improved annotation systems are needed for miRNAs and all other classes of plant small RNAs. Finally, to illustrate the complexities of miRNA and siRNA annotation, we review the evolution and functions of miRNAs and siRNAs in plants. PMID:29343505

Long-read sequencing data analysis for yeasts.

PubMed

Yue, Jia-Xing; Liti, Gianni

2018-06-01

Long-read sequencing technologies have become increasingly popular due to their strengths in resolving complex genomic regions. As a leading model organism with small genome size and great biotechnological importance, the budding yeast Saccharomyces cerevisiae has many isolates currently being sequenced with long reads. However, analyzing long-read sequencing data to produce high-quality genome assembly and annotation remains challenging. Here, we present a modular computational framework named long-read sequencing data analysis for yeasts (LRSDAY), the first one-stop solution that streamlines this process. Starting from the raw sequencing reads, LRSDAY can produce chromosome-level genome assembly and comprehensive genome annotation in a highly automated manner with minimal manual intervention, which is not possible using any alternative tool available to date. The annotated genomic features include centromeres, protein-coding genes, tRNAs, transposable elements (TEs), and telomere-associated elements. Although tailored for S. cerevisiae, we designed LRSDAY to be highly modular and customizable, making it adaptable to virtually any eukaryotic organism. When applying LRSDAY to an S. cerevisiae strain, it takes ∼41 h to generate a complete and well-annotated genome from ∼100× Pacific Biosciences (PacBio) running the basic workflow with four threads. Basic experience working within the Linux command-line environment is recommended for carrying out the analysis using LRSDAY.

MicroScope-an integrated resource for community expertise of gene functions and comparative analysis of microbial genomic and metabolic data.

PubMed

Médigue, Claudine; Calteau, Alexandra; Cruveiller, Stéphane; Gachet, Mathieu; Gautreau, Guillaume; Josso, Adrien; Lajus, Aurélie; Langlois, Jordan; Pereira, Hugo; Planel, Rémi; Roche, David; Rollin, Johan; Rouy, Zoe; Vallenet, David

2017-09-12

The overwhelming list of new bacterial genomes becoming available on a daily basis makes accurate genome annotation an essential step that ultimately determines the relevance of thousands of genomes stored in public databanks. The MicroScope platform (http://www.genoscope.cns.fr/agc/microscope) is an integrative resource that supports systematic and efficient revision of microbial genome annotation, data management and comparative analysis. Starting from the results of our syntactic, functional and relational annotation pipelines, MicroScope provides an integrated environment for the expert annotation and comparative analysis of prokaryotic genomes. It combines tools and graphical interfaces to analyze genomes and to perform the manual curation of gene function in a comparative genomics and metabolic context. In this article, we describe the free-of-charge MicroScope services for the annotation and analysis of microbial (meta)genomes, transcriptomic and re-sequencing data. Then, the functionalities of the platform are presented in a way providing practical guidance and help to the nonspecialists in bioinformatics. Newly integrated analysis tools (i.e. prediction of virulence and resistance genes in bacterial genomes) and original method recently developed (the pan-genome graph representation) are also described. Integrated environments such as MicroScope clearly contribute, through the user community, to help maintaining accurate resources. © The Author 2017. Published by Oxford University Press.

Systematic analysis of snake neurotoxins' functional classification using a data warehousing approach.

PubMed

Siew, Joyce Phui Yee; Khan, Asif M; Tan, Paul T J; Koh, Judice L Y; Seah, Seng Hong; Koo, Chuay Yeng; Chai, Siaw Ching; Armugam, Arunmozhiarasi; Brusic, Vladimir; Jeyaseelan, Kandiah

2004-12-12

Sequence annotations, functional and structural data on snake venom neurotoxins (svNTXs) are scattered across multiple databases and literature sources. Sequence annotations and structural data are available in the public molecular databases, while functional data are almost exclusively available in the published articles. There is a need for a specialized svNTXs database that contains NTX entries, which are organized, well annotated and classified in a systematic manner. We have systematically analyzed svNTXs and classified them using structure-function groups based on their structural, functional and phylogenetic properties. Using conserved motifs in each phylogenetic group, we built an intelligent module for the prediction of structural and functional properties of unknown NTXs. We also developed an annotation tool to aid the functional prediction of newly identified NTXs as an additional resource for the venom research community. We created a searchable online database of NTX proteins sequences (http://research.i2r.a-star.edu.sg/Templar/DB/snake_neurotoxin). This database can also be found under Swiss-Prot Toxin Annotation Project website (http://www.expasy.org/sprot/).

Integrating multiple genomic data to predict disease-causing nonsynonymous single nucleotide variants in exome sequencing studies.

PubMed

Wu, Jiaxin; Li, Yanda; Jiang, Rui

2014-03-01

Exome sequencing has been widely used in detecting pathogenic nonsynonymous single nucleotide variants (SNVs) for human inherited diseases. However, traditional statistical genetics methods are ineffective in analyzing exome sequencing data, due to such facts as the large number of sequenced variants, the presence of non-negligible fraction of pathogenic rare variants or de novo mutations, and the limited size of affected and normal populations. Indeed, prevalent applications of exome sequencing have been appealing for an effective computational method for identifying causative nonsynonymous SNVs from a large number of sequenced variants. Here, we propose a bioinformatics approach called SPRING (Snv PRioritization via the INtegration of Genomic data) for identifying pathogenic nonsynonymous SNVs for a given query disease. Based on six functional effect scores calculated by existing methods (SIFT, PolyPhen2, LRT, MutationTaster, GERP and PhyloP) and five association scores derived from a variety of genomic data sources (gene ontology, protein-protein interactions, protein sequences, protein domain annotations and gene pathway annotations), SPRING calculates the statistical significance that an SNV is causative for a query disease and hence provides a means of prioritizing candidate SNVs. With a series of comprehensive validation experiments, we demonstrate that SPRING is valid for diseases whose genetic bases are either partly known or completely unknown and effective for diseases with a variety of inheritance styles. In applications of our method to real exome sequencing data sets, we show the capability of SPRING in detecting causative de novo mutations for autism, epileptic encephalopathies and intellectual disability. We further provide an online service, the standalone software and genome-wide predictions of causative SNVs for 5,080 diseases at http://bioinfo.au.tsinghua.edu.cn/spring.

Artemis and ACT: viewing, annotating and comparing sequences stored in a relational database.

PubMed

Carver, Tim; Berriman, Matthew; Tivey, Adrian; Patel, Chinmay; Böhme, Ulrike; Barrell, Barclay G; Parkhill, Julian; Rajandream, Marie-Adèle

2008-12-01

Artemis and Artemis Comparison Tool (ACT) have become mainstream tools for viewing and annotating sequence data, particularly for microbial genomes. Since its first release, Artemis has been continuously developed and supported with additional functionality for editing and analysing sequences based on feedback from an active user community of laboratory biologists and professional annotators. Nevertheless, its utility has been somewhat restricted by its limitation to reading and writing from flat files. Therefore, a new version of Artemis has been developed, which reads from and writes to a relational database schema, and allows users to annotate more complex, often large and fragmented, genome sequences. Artemis and ACT have now been extended to read and write directly to the Generic Model Organism Database (GMOD, http://www.gmod.org) Chado relational database schema. In addition, a Gene Builder tool has been developed to provide structured forms and tables to edit coordinates of gene models and edit functional annotation, based on standard ontologies, controlled vocabularies and free text. Artemis and ACT are freely available (under a GPL licence) for download (for MacOSX, UNIX and Windows) at the Wellcome Trust Sanger Institute web sites: http://www.sanger.ac.uk/Software/Artemis/ http://www.sanger.ac.uk/Software/ACT/

Inferring transposons activity chronology by TRANScendence - TEs database and de-novo mining tool.

PubMed

Startek, Michał Piotr; Nogły, Jakub; Gromadka, Agnieszka; Grzebelus, Dariusz; Gambin, Anna

2017-10-16

The constant progress in sequencing technology leads to ever increasing amounts of genomic data. In the light of current evidence transposable elements (TEs for short) are becoming useful tools for learning about the evolution of host genome. Therefore the software for genome-wide detection and analysis of TEs is of great interest. Here we describe the computational tool for mining, classifying and storing TEs from newly sequenced genomes. This is an online, web-based, user-friendly service, enabling users to upload their own genomic data, and perform de-novo searches for TEs. The detected TEs are automatically analyzed, compared to reference databases, annotated, clustered into families, and stored in TEs repository. Also, the genome-wide nesting structure of found elements are detected and analyzed by new method for inferring evolutionary history of TEs. We illustrate the functionality of our tool by performing a full-scale analyses of TE landscape in Medicago truncatula genome. TRANScendence is an effective tool for the de-novo annotation and classification of transposable elements in newly-acquired genomes. Its streamlined interface makes it well-suited for evolutionary studies.

A Comprehensive Approach to Sequence-oriented IsomiR annotation (CASMIR): demonstration with IsomiR profiling in colorectal neoplasia.

PubMed

Wu, Chung Wah; Evans, Jared M; Huang, Shengbing; Mahoney, Douglas W; Dukek, Brian A; Taylor, William R; Yab, Tracy C; Smyrk, Thomas C; Jen, Jin; Kisiel, John B; Ahlquist, David A

2018-05-25

MicroRNA (miRNA) profiling is an important step in studying biological associations and identifying marker candidates. miRNA exists in isoforms, called isomiRs, which may exhibit distinct properties. With conventional profiling methods, limitations in assay and analysis platforms may compromise isomiR interrogation. We introduce a comprehensive approach to sequence-oriented isomiR annotation (CASMIR) to allow unbiased identification of global isomiRs from small RNA sequencing data. In this approach, small RNA reads are maintained as independent sequences instead of being summarized under miRNA names. IsomiR features are identified through step-wise local alignment against canonical forms and precursor sequences. Through customizing the reference database, CASMIR is applicable to isomiR annotation across species. To demonstrate its application, we investigated isomiR profiles in normal and neoplastic human colorectal epithelia. We also ran miRDeep2, a popular miRNA analysis algorithm to validate isomiRs annotated by CASMIR. With CASMIR, specific and biologically relevant isomiR patterns could be identified. We note that specific isomiRs are often more abundant than their canonical forms. We identify isomiRs that are commonly up-regulated in both colorectal cancer and advanced adenoma, and illustrate advantages in targeting isomiRs as potential biomarkers over canonical forms. Studying miRNAs at the isomiR level could reveal new insight into miRNA biology and inform assay design for specific isomiRs. CASMIR facilitates comprehensive annotation of isomiR features in small RNA sequencing data for isomiR profiling and differential expression analysis.

Comparative analysis of grapevine whole-genome gene predictions, functional annotation, categorization and integration of the predicted gene sequences

PubMed Central

2012-01-01

Background The first draft assembly and gene prediction of the grapevine genome (8X base coverage) was made available to the scientific community in 2007, and functional annotation was developed on this gene prediction. Since then additional Sanger sequences were added to the 8X sequences pool and a new version of the genomic sequence with superior base coverage (12X) was produced. Results In order to more efficiently annotate the function of the genes predicted in the new assembly, it is important to build on as much of the previous work as possible, by transferring 8X annotation of the genome to the 12X version. The 8X and 12X assemblies and gene predictions of the grapevine genome were compared to answer the question, “Can we uniquely map 8X predicted genes to 12X predicted genes?” The results show that while the assemblies and gene structure predictions are too different to make a complete mapping between them, most genes (18,725) showed a one-to-one relationship between 8X predicted genes and the last version of 12X predicted genes. In addition, reshuffled genomic sequence structures appeared. These highlight regions of the genome where the gene predictions need to be taken with caution. Based on the new grapevine gene functional annotation and in-depth functional categorization, twenty eight new molecular networks have been created for VitisNet while the existing networks were updated. Conclusions The outcomes of this study provide a functional annotation of the 12X genes, an update of VitisNet, the system of the grapevine molecular networks, and a new functional categorization of genes. Data are available at the VitisNet website (http://www.sdstate.edu/ps/research/vitis/pathways.cfm). PMID:22554261

Patome: a database server for biological sequence annotation and analysis in issued patents and published patent applications.

PubMed

Lee, Byungwook; Kim, Taehyung; Kim, Seon-Kyu; Lee, Kwang H; Lee, Doheon

2007-01-01

With the advent of automated and high-throughput techniques, the number of patent applications containing biological sequences has been increasing rapidly. However, they have attracted relatively little attention compared to other sequence resources. We have built a database server called Patome, which contains biological sequence data disclosed in patents and published applications, as well as their analysis information. The analysis is divided into two steps. The first is an annotation step in which the disclosed sequences were annotated with RefSeq database. The second is an association step where the sequences were linked to Entrez Gene, OMIM and GO databases, and their results were saved as a gene-patent table. From the analysis, we found that 55% of human genes were associated with patenting. The gene-patent table can be used to identify whether a particular gene or disease is related to patenting. Patome is available at http://www.patome.org/; the information is updated bimonthly.

Patome: a database server for biological sequence annotation and analysis in issued patents and published patent applications

PubMed Central

Lee, Byungwook; Kim, Taehyung; Kim, Seon-Kyu; Lee, Kwang H.; Lee, Doheon

2007-01-01

With the advent of automated and high-throughput techniques, the number of patent applications containing biological sequences has been increasing rapidly. However, they have attracted relatively little attention compared to other sequence resources. We have built a database server called Patome, which contains biological sequence data disclosed in patents and published applications, as well as their analysis information. The analysis is divided into two steps. The first is an annotation step in which the disclosed sequences were annotated with RefSeq database. The second is an association step where the sequences were linked to Entrez Gene, OMIM and GO databases, and their results were saved as a gene–patent table. From the analysis, we found that 55% of human genes were associated with patenting. The gene–patent table can be used to identify whether a particular gene or disease is related to patenting. Patome is available at ; the information is updated bimonthly. PMID:17085479

BRILIA: Integrated Tool for High-Throughput Annotation and Lineage Tree Assembly of B-Cell Repertoires.

PubMed

Lee, Donald W; Khavrutskii, Ilja V; Wallqvist, Anders; Bavari, Sina; Cooper, Christopher L; Chaudhury, Sidhartha

2016-01-01

The somatic diversity of antigen-recognizing B-cell receptors (BCRs) arises from Variable (V), Diversity (D), and Joining (J) (VDJ) recombination and somatic hypermutation (SHM) during B-cell development and affinity maturation. The VDJ junction of the BCR heavy chain forms the highly variable complementarity determining region 3 (CDR3), which plays a critical role in antigen specificity and binding affinity. Tracking the selection and mutation of the CDR3 can be useful in characterizing humoral responses to infection and vaccination. Although tens to hundreds of thousands of unique BCR genes within an expressed B-cell repertoire can now be resolved with high-throughput sequencing, tracking SHMs is still challenging because existing annotation methods are often limited by poor annotation coverage, inconsistent SHM identification across the VDJ junction, or lack of B-cell lineage data. Here, we present B-cell repertoire inductive lineage and immunosequence annotator (BRILIA), an algorithm that leverages repertoire-wide sequencing data to globally improve the VDJ annotation coverage, lineage tree assembly, and SHM identification. On benchmark tests against simulated human and mouse BCR repertoires, BRILIA correctly annotated germline and clonally expanded sequences with 94 and 70% accuracy, respectively, and it has a 90% SHM-positive prediction rate in the CDR3 of heavily mutated sequences; these are substantial improvements over existing methods. We used BRILIA to process BCR sequences obtained from splenic germinal center B cells extracted from C57BL/6 mice. BRILIA returned robust B-cell lineage trees and yielded SHM patterns that are consistent across the VDJ junction and agree with known biological mechanisms of SHM. By contrast, existing BCR annotation tools, which do not account for repertoire-wide clonal relationships, systematically underestimated both the size of clonally related B-cell clusters and yielded inconsistent SHM frequencies. We demonstrate BRILIA's utility in B-cell repertoire studies related to VDJ gene usage, mechanisms for adenosine mutations, and SHM hot spot motifs. Furthermore, we show that the complete gene usage annotation and SHM identification across the entire CDR3 are essential for studying the B-cell affinity maturation process through immunosequencing methods.

CyanoBase: the cyanobacteria genome database update 2010.

PubMed

Nakao, Mitsuteru; Okamoto, Shinobu; Kohara, Mitsuyo; Fujishiro, Tsunakazu; Fujisawa, Takatomo; Sato, Shusei; Tabata, Satoshi; Kaneko, Takakazu; Nakamura, Yasukazu

2010-01-01

CyanoBase (http://genome.kazusa.or.jp/cyanobase) is the genome database for cyanobacteria, which are model organisms for photosynthesis. The database houses cyanobacteria species information, complete genome sequences, genome-scale experiment data, gene information, gene annotations and mutant information. In this version, we updated these datasets and improved the navigation and the visual display of the data views. In addition, a web service API now enables users to retrieve the data in various formats with other tools, seamlessly.

CycADS: an annotation database system to ease the development and update of BioCyc databases

PubMed Central

Vellozo, Augusto F.; Véron, Amélie S.; Baa-Puyoulet, Patrice; Huerta-Cepas, Jaime; Cottret, Ludovic; Febvay, Gérard; Calevro, Federica; Rahbé, Yvan; Douglas, Angela E.; Gabaldón, Toni; Sagot, Marie-France; Charles, Hubert; Colella, Stefano

2011-01-01

In recent years, genomes from an increasing number of organisms have been sequenced, but their annotation remains a time-consuming process. The BioCyc databases offer a framework for the integrated analysis of metabolic networks. The Pathway tool software suite allows the automated construction of a database starting from an annotated genome, but it requires prior integration of all annotations into a specific summary file or into a GenBank file. To allow the easy creation and update of a BioCyc database starting from the multiple genome annotation resources available over time, we have developed an ad hoc data management system that we called Cyc Annotation Database System (CycADS). CycADS is centred on a specific database model and on a set of Java programs to import, filter and export relevant information. Data from GenBank and other annotation sources (including for example: KAAS, PRIAM, Blast2GO and PhylomeDB) are collected into a database to be subsequently filtered and extracted to generate a complete annotation file. This file is then used to build an enriched BioCyc database using the PathoLogic program of Pathway Tools. The CycADS pipeline for annotation management was used to build the AcypiCyc database for the pea aphid (Acyrthosiphon pisum) whose genome was recently sequenced. The AcypiCyc database webpage includes also, for comparative analyses, two other metabolic reconstruction BioCyc databases generated using CycADS: TricaCyc for Tribolium castaneum and DromeCyc for Drosophila melanogaster. Linked to its flexible design, CycADS offers a powerful software tool for the generation and regular updating of enriched BioCyc databases. The CycADS system is particularly suited for metabolic gene annotation and network reconstruction in newly sequenced genomes. Because of the uniform annotation used for metabolic network reconstruction, CycADS is particularly useful for comparative analysis of the metabolism of different organisms. Database URL: http://www.cycadsys.org PMID:21474551

Swine transcriptome characterization by combined Iso-Seq and RNA-seq for annotating the emerging long read-based reference genome

USDA-ARS?s Scientific Manuscript database

PacBio long-read sequencing technology is increasingly popular in genome sequence assembly and transcriptome cataloguing. Recently, a new-generation pig reference genome was assembled based on long reads from this technology. To finely annotate this genome assembly, transcriptomes of nine tissues fr...

Complete genome sequence of an attenuated Sparfloxacin-resistant Streptococcus agalactiae strain 138spar

USDA-ARS?s Scientific Manuscript database

The complete genome of a sparfloxacin-resistant Streptococcus agalactiae vaccine strain 138spar is 1,838,126 bp in size. The genome has 1892 coding sequences and 82 RNAs. The annotation of the genome is added by the NCBI Prokaryotic Genome Annotation Pipeline. The publishing of this genome will allo...

The Biofuel Feedstock Genomics Resource: a web-based portal and database to enable functional genomics of plant biofuel feedstock species.

PubMed

Childs, Kevin L; Konganti, Kranti; Buell, C Robin

2012-01-01

Major feedstock sources for future biofuel production are likely to be high biomass producing plant species such as poplar, pine, switchgrass, sorghum and maize. One active area of research in these species is genome-enabled improvement of lignocellulosic biofuel feedstock quality and yield. To facilitate genomic-based investigations in these species, we developed the Biofuel Feedstock Genomic Resource (BFGR), a database and web-portal that provides high-quality, uniform and integrated functional annotation of gene and transcript assembly sequences from species of interest to lignocellulosic biofuel feedstock researchers. The BFGR includes sequence data from 54 species and permits researchers to view, analyze and obtain annotation at the gene, transcript, protein and genome level. Annotation of biochemical pathways permits the identification of key genes and transcripts central to the improvement of lignocellulosic properties in these species. The integrated nature of the BFGR in terms of annotation methods, orthologous/paralogous relationships and linkage to seven species with complete genome sequences allows comparative analyses for biofuel feedstock species with limited sequence resources. Database URL: http://bfgr.plantbiology.msu.edu.

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

The Protein Information Resource: an integrated public resource of functional annotation of proteins

PubMed Central

Wu, Cathy H.; Huang, Hongzhan; Arminski, Leslie; Castro-Alvear, Jorge; Chen, Yongxing; Hu, Zhang-Zhi; Ledley, Robert S.; Lewis, Kali C.; Mewes, Hans-Werner; Orcutt, Bruce C.; Suzek, Baris E.; Tsugita, Akira; Vinayaka, C. R.; Yeh, Lai-Su L.; Zhang, Jian; Barker, Winona C.

2002-01-01

The Protein Information Resource (PIR) serves as an integrated public resource of functional annotation of protein data to support genomic/proteomic research and scientific discovery. The PIR, in collaboration with the Munich Information Center for Protein Sequences (MIPS) and the Japan International Protein Information Database (JIPID), produces the PIR-International Protein Sequence Database (PSD), the major annotated protein sequence database in the public domain, containing about 250 000 proteins. To improve protein annotation and the coverage of experimentally validated data, a bibliography submission system is developed for scientists to submit, categorize and retrieve literature information. Comprehensive protein information is available from iProClass, which includes family classification at the superfamily, domain and motif levels, structural and functional features of proteins, as well as cross-references to over 40 biological databases. To provide timely and comprehensive protein data with source attribution, we have introduced a non-redundant reference protein database, PIR-NREF. The database consists of about 800 000 proteins collected from PIR-PSD, SWISS-PROT, TrEMBL, GenPept, RefSeq and PDB, with composite protein names and literature data. To promote database interoperability, we provide XML data distribution and open database schema, and adopt common ontologies. The PIR web site (http://pir.georgetown.edu/) features data mining and sequence analysis tools for information retrieval and functional identification of proteins based on both sequence and annotation information. The PIR databases and other files are also available by FTP (ftp://nbrfa.georgetown.edu/pir_databases). PMID:11752247

High-performance web services for querying gene and variant annotation.

PubMed

Xin, Jiwen; Mark, Adam; Afrasiabi, Cyrus; Tsueng, Ginger; Juchler, Moritz; Gopal, Nikhil; Stupp, Gregory S; Putman, Timothy E; Ainscough, Benjamin J; Griffith, Obi L; Torkamani, Ali; Whetzel, Patricia L; Mungall, Christopher J; Mooney, Sean D; Su, Andrew I; Wu, Chunlei

2016-05-06

Efficient tools for data management and integration are essential for many aspects of high-throughput biology. In particular, annotations of genes and human genetic variants are commonly used but highly fragmented across many resources. Here, we describe MyGene.info and MyVariant.info, high-performance web services for querying gene and variant annotation information. These web services are currently accessed more than three million times permonth. They also demonstrate a generalizable cloud-based model for organizing and querying biological annotation information. MyGene.info and MyVariant.info are provided as high-performance web services, accessible at http://mygene.info and http://myvariant.info . Both are offered free of charge to the research community.

The draft genome sequence and annotation of the desert woodrat Neotoma lepida.

PubMed

Campbell, Michael; Oakeson, Kelly F; Yandell, Mark; Halpert, James R; Dearing, Denise

2016-09-01

We present the de novo draft genome sequence for a vertebrate mammalian herbivore, the desert woodrat (Neotoma lepida). This species is of ecological and evolutionary interest with respect to ingestion, microbial detoxification and hepatic metabolism of toxic plant secondary compounds from the highly toxic creosote bush (Larrea tridentata) and the juniper shrub (Juniperus monosperma). The draft genome sequence and annotation have been deposited at GenBank under the accession LZPO01000000.

Genome sequencing and annotation of Serratia sp. strain TEL.

PubMed

Lephoto, Tiisetso E; Gray, Vincent M

2015-12-01

We present the annotation of the draft genome sequence of Serratia sp. strain TEL (GenBank accession number KP711410). This organism was isolated from entomopathogenic nematode Oscheius sp. strain TEL (GenBank accession number KM492926) collected from grassland soil and has a genome size of 5,000,541 bp and 542 subsystems. The genome sequence can be accessed at DDBJ/EMBL/GenBank under the accession number LDEG00000000.

Maize - GO annotation methods, evaluation, and review (Maize-GAMER)

USDA-ARS?s Scientific Manuscript database

Making a genome sequence accessible and useful involves three basic steps: genome assembly, structural annotation, and functional annotation. The quality of data generated at each step influences the accuracy of inferences that can be made, with high-quality analyses produce better datasets resultin...

High-throughput annotation of full-length long noncoding RNAs with capture long-read sequencing.

PubMed

Lagarde, Julien; Uszczynska-Ratajczak, Barbara; Carbonell, Silvia; Pérez-Lluch, Sílvia; Abad, Amaya; Davis, Carrie; Gingeras, Thomas R; Frankish, Adam; Harrow, Jennifer; Guigo, Roderic; Johnson, Rory

2017-12-01

Accurate annotation of genes and their transcripts is a foundation of genomics, but currently no annotation technique combines throughput and accuracy. As a result, reference gene collections remain incomplete-many gene models are fragmentary, and thousands more remain uncataloged, particularly for long noncoding RNAs (lncRNAs). To accelerate lncRNA annotation, the GENCODE consortium has developed RNA Capture Long Seq (CLS), which combines targeted RNA capture with third-generation long-read sequencing. Here we present an experimental reannotation of the GENCODE intergenic lncRNA populations in matched human and mouse tissues that resulted in novel transcript models for 3,574 and 561 gene loci, respectively. CLS approximately doubled the annotated complexity of targeted loci, outperforming existing short-read techniques. Full-length transcript models produced by CLS enabled us to definitively characterize the genomic features of lncRNAs, including promoter and gene structure, and protein-coding potential. Thus, CLS removes a long-standing bottleneck in transcriptome annotation and generates manual-quality full-length transcript models at high-throughput scales.

A method for automatically extracting infectious disease-related primers and probes from the literature

PubMed Central

2010-01-01

Background Primer and probe sequences are the main components of nucleic acid-based detection systems. Biologists use primers and probes for different tasks, some related to the diagnosis and prescription of infectious diseases. The biological literature is the main information source for empirically validated primer and probe sequences. Therefore, it is becoming increasingly important for researchers to navigate this important information. In this paper, we present a four-phase method for extracting and annotating primer/probe sequences from the literature. These phases are: (1) convert each document into a tree of paper sections, (2) detect the candidate sequences using a set of finite state machine-based recognizers, (3) refine problem sequences using a rule-based expert system, and (4) annotate the extracted sequences with their related organism/gene information. Results We tested our approach using a test set composed of 297 manuscripts. The extracted sequences and their organism/gene annotations were manually evaluated by a panel of molecular biologists. The results of the evaluation show that our approach is suitable for automatically extracting DNA sequences, achieving precision/recall rates of 97.98% and 95.77%, respectively. In addition, 76.66% of the detected sequences were correctly annotated with their organism name. The system also provided correct gene-related information for 46.18% of the sequences assigned a correct organism name. Conclusions We believe that the proposed method can facilitate routine tasks for biomedical researchers using molecular methods to diagnose and prescribe different infectious diseases. In addition, the proposed method can be expanded to detect and extract other biological sequences from the literature. The extracted information can also be used to readily update available primer/probe databases or to create new databases from scratch. PMID:20682041

Enriching public descriptions of marine phages using the Genomic Standards Consortium MIGS standard

PubMed Central

Duhaime, Melissa Beth; Kottmann, Renzo; Field, Dawn; Glöckner, Frank Oliver

2011-01-01

In any sequencing project, the possible depth of comparative analysis is determined largely by the amount and quality of the accompanying contextual data. The structure, content, and storage of this contextual data should be standardized to ensure consistent coverage of all sequenced entities and facilitate comparisons. The Genomic Standards Consortium (GSC) has developed the “Minimum Information about Genome/Metagenome Sequences (MIGS/MIMS)” checklist for the description of genomes and here we annotate all 30 publicly available marine bacteriophage sequences to the MIGS standard. These annotations build on existing International Nucleotide Sequence Database Collaboration (INSDC) records, and confirm, as expected that current submissions lack most MIGS fields. MIGS fields were manually curated from the literature and placed in XML format as specified by the Genomic Contextual Data Markup Language (GCDML). These “machine-readable” reports were then analyzed to highlight patterns describing this collection of genomes. Completed reports are provided in GCDML. This work represents one step towards the annotation of our complete collection of genome sequences and shows the utility of capturing richer metadata along with raw sequences. PMID:21677864

Towards the VWO Annotation Service: a Success Story of the IMAGE RPI Expert Rating System

NASA Astrophysics Data System (ADS)

Reinisch, B. W.; Galkin, I. A.; Fung, S. F.; Benson, R. F.; Kozlov, A. V.; Khmyrov, G. M.; Garcia, L. N.

2010-12-01

Interpretation of Heliophysics wave data requires specialized knowledge of wave phenomena. Users of the virtual wave observatory (VWO) will greatly benefit from a data annotation service that will allow querying of data by phenomenon type, thus helping accomplish the VWO goal to make Heliophysics wave data searchable, understandable, and usable by the scientific community. Individual annotations can be sorted by phenomenon type and reduced into event lists (catalogs). However, in contrast to the event lists, annotation records allow a greater flexibility of collaborative management by more easily admitting operations of addition, revision, or deletion. They can therefore become the building blocks for an interactive Annotation Service with a suitable graphic user interface to the VWO middleware. The VWO Annotation Service vision is an interactive, collaborative sharing of domain expert knowledge with fellow scientists and students alike. An effective prototype of the VWO Annotation Service has been in operation at the University of Massachusetts Lowell since 2001. An expert rating system (ERS) was developed for annotating the IMAGE radio plasma imager (RPI) active sounding data containing 1.2 million plasmagrams. The RPI data analysts can use ERS to submit expert ratings of plasmagram features, such as presence of echo traces resulted from reflected RPI signals from distant plasma structures. Since its inception in 2001, the RPI ERS has accumulated 7351 expert plasmagram ratings in 16 phenomenon categories, together with free-text descriptions and other metadata. In addition to human expert ratings, the system holds 225,125 ratings submitted by the CORPRAL data prospecting software that employs a model of the human pre-attentive vision to select images potentially containing interesting features. The annotation records proved to be instrumental in a number of investigations where manual data exploration would have been prohibitively tedious and expensive. Especially useful are queries of the annotation database for successive plasmagrams containing echo traces. Several success stories of the RPI ERS using this capability will be discussed, particularly in terms of how they may be extended to develop the VWO Annotation Service.

Cloning, analysis and functional annotation of expressed sequence tags from the Earthworm Eisenia fetida

PubMed Central

Pirooznia, Mehdi; Gong, Ping; Guan, Xin; Inouye, Laura S; Yang, Kuan; Perkins, Edward J; Deng, Youping

2007-01-01

Background Eisenia fetida, commonly known as red wiggler or compost worm, belongs to the Lumbricidae family of the Annelida phylum. Little is known about its genome sequence although it has been extensively used as a test organism in terrestrial ecotoxicology. In order to understand its gene expression response to environmental contaminants, we cloned 4032 cDNAs or expressed sequence tags (ESTs) from two E. fetida libraries enriched with genes responsive to ten ordnance related compounds using suppressive subtractive hybridization-PCR. Results A total of 3144 good quality ESTs (GenBank dbEST accession number EH669363–EH672369 and EL515444–EL515580) were obtained from the raw clone sequences after cleaning. Clustering analysis yielded 2231 unique sequences including 448 contigs (from 1361 ESTs) and 1783 singletons. Comparative genomic analysis showed that 743 or 33% of the unique sequences shared high similarity with existing genes in the GenBank nr database. Provisional function annotation assigned 830 Gene Ontology terms to 517 unique sequences based on their homology with the annotated genomes of four model organisms Drosophila melanogaster, Mus musculus, Saccharomyces cerevisiae, and Caenorhabditis elegans. Seven percent of the unique sequences were further mapped to 99 Kyoto Encyclopedia of Genes and Genomes pathways based on their matching Enzyme Commission numbers. All the information is stored and retrievable at a highly performed, web-based and user-friendly relational database called EST model database or ESTMD version 2. Conclusion The ESTMD containing the sequence and annotation information of 4032 E. fetida ESTs is publicly accessible at . PMID:18047730

Improved annotation through genome-scale metabolic modeling of Aspergillus oryzae

PubMed Central

Vongsangnak, Wanwipa; Olsen, Peter; Hansen, Kim; Krogsgaard, Steen; Nielsen, Jens

2008-01-01

Background Since ancient times the filamentous fungus Aspergillus oryzae has been used in the fermentation industry for the production of fermented sauces and the production of industrial enzymes. Recently, the genome sequence of A. oryzae with 12,074 annotated genes was released but the number of hypothetical proteins accounted for more than 50% of the annotated genes. Considering the industrial importance of this fungus, it is therefore valuable to improve the annotation and further integrate genomic information with biochemical and physiological information available for this microorganism and other related fungi. Here we proposed the gene prediction by construction of an A. oryzae Expressed Sequence Tag (EST) library, sequencing and assembly. We enhanced the function assignment by our developed annotation strategy. The resulting better annotation was used to reconstruct the metabolic network leading to a genome scale metabolic model of A. oryzae. Results Our assembled EST sequences we identified 1,046 newly predicted genes in the A. oryzae genome. Furthermore, it was possible to assign putative protein functions to 398 of the newly predicted genes. Noteworthy, our annotation strategy resulted in assignment of new putative functions to 1,469 hypothetical proteins already present in the A. oryzae genome database. Using the substantially improved annotated genome we reconstructed the metabolic network of A. oryzae. This network contains 729 enzymes, 1,314 enzyme-encoding genes, 1,073 metabolites and 1,846 (1,053 unique) biochemical reactions. The metabolic reactions are compartmentalized into the cytosol, the mitochondria, the peroxisome and the extracellular space. Transport steps between the compartments and the extracellular space represent 281 reactions, of which 161 are unique. The metabolic model was validated and shown to correctly describe the phenotypic behavior of A. oryzae grown on different carbon sources. Conclusion A much enhanced annotation of the A. oryzae genome was performed and a genome-scale metabolic model of A. oryzae was reconstructed. The model accurately predicted the growth and biomass yield on different carbon sources. The model serves as an important resource for gaining further insight into our understanding of A. oryzae physiology. PMID:18500999

Metagenomic gene annotation by a homology-independent approach

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

Froula, Jeff; Zhang, Tao; Salmeen, Annette

2011-06-02

Fully understanding the genetic potential of a microbial community requires functional annotation of all the genes it encodes. The recently developed deep metagenome sequencing approach has enabled rapid identification of millions of genes from a complex microbial community without cultivation. Current homology-based gene annotation fails to detect distantly-related or structural homologs. Furthermore, homology searches with millions of genes are very computational intensive. To overcome these limitations, we developed rhModeller, a homology-independent software pipeline to efficiently annotate genes from metagenomic sequencing projects. Using cellulases and carbonic anhydrases as two independent test cases, we demonstrated that rhModeller is much faster than HMMERmore » but with comparable accuracy, at 94.5percent and 99.9percent accuracy, respectively. More importantly, rhModeller has the ability to detect novel proteins that do not share significant homology to any known protein families. As {approx}50percent of the 2 million genes derived from the cow rumen metagenome failed to be annotated based on sequence homology, we tested whether rhModeller could be used to annotate these genes. Preliminary results suggest that rhModeller is robust in the presence of missense and frameshift mutations, two common errors in metagenomic genes. Applying the pipeline to the cow rumen genes identified 4,990 novel cellulases candidates and 8,196 novel carbonic anhydrase candidates.In summary, we expect rhModeller to dramatically increase the speed and quality of metagnomic gene annotation.« less

Association algorithm to mine the rules that govern enzyme definition and to classify protein sequences.

PubMed

Chiu, Shih-Hau; Chen, Chien-Chi; Yuan, Gwo-Fang; Lin, Thy-Hou

2006-06-15

The number of sequences compiled in many genome projects is growing exponentially, but most of them have not been characterized experimentally. An automatic annotation scheme must be in an urgent need to reduce the gap between the amount of new sequences produced and reliable functional annotation. This work proposes rules for automatically classifying the fungus genes. The approach involves elucidating the enzyme classifying rule that is hidden in UniProt protein knowledgebase and then applying it for classification. The association algorithm, Apriori, is utilized to mine the relationship between the enzyme class and significant InterPro entries. The candidate rules are evaluated for their classificatory capacity. There were five datasets collected from the Swiss-Prot for establishing the annotation rules. These were treated as the training sets. The TrEMBL entries were treated as the testing set. A correct enzyme classification rate of 70% was obtained for the prokaryote datasets and a similar rate of about 80% was obtained for the eukaryote datasets. The fungus training dataset which lacks an enzyme class description was also used to evaluate the fungus candidate rules. A total of 88 out of 5085 test entries were matched with the fungus rule set. These were otherwise poorly annotated using their functional descriptions. The feasibility of using the method presented here to classify enzyme classes based on the enzyme domain rules is evident. The rules may be also employed by the protein annotators in manual annotation or implemented in an automatic annotation flowchart.

NCBI prokaryotic genome annotation pipeline.

PubMed

Tatusova, Tatiana; DiCuccio, Michael; Badretdin, Azat; Chetvernin, Vyacheslav; Nawrocki, Eric P; Zaslavsky, Leonid; Lomsadze, Alexandre; Pruitt, Kim D; Borodovsky, Mark; Ostell, James

2016-08-19

Recent technological advances have opened unprecedented opportunities for large-scale sequencing and analysis of populations of pathogenic species in disease outbreaks, as well as for large-scale diversity studies aimed at expanding our knowledge across the whole domain of prokaryotes. To meet the challenge of timely interpretation of structure, function and meaning of this vast genetic information, a comprehensive approach to automatic genome annotation is critically needed. In collaboration with Georgia Tech, NCBI has developed a new approach to genome annotation that combines alignment based methods with methods of predicting protein-coding and RNA genes and other functional elements directly from sequence. A new gene finding tool, GeneMarkS+, uses the combined evidence of protein and RNA placement by homology as an initial map of annotation to generate and modify ab initio gene predictions across the whole genome. Thus, the new NCBI's Prokaryotic Genome Annotation Pipeline (PGAP) relies more on sequence similarity when confident comparative data are available, while it relies more on statistical predictions in the absence of external evidence. The pipeline provides a framework for generation and analysis of annotation on the full breadth of prokaryotic taxonomy. For additional information on PGAP see https://www.ncbi.nlm.nih.gov/genome/annotation_prok/ and the NCBI Handbook, https://www.ncbi.nlm.nih.gov/books/NBK174280/. Published by Oxford University Press on behalf of Nucleic Acids Research 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

SNPdbe: constructing an nsSNP functional impacts database.

PubMed

Schaefer, Christian; Meier, Alice; Rost, Burkhard; Bromberg, Yana

2012-02-15

Many existing databases annotate experimentally characterized single nucleotide polymorphisms (SNPs). Each non-synonymous SNP (nsSNP) changes one amino acid in the gene product (single amino acid substitution;SAAS). This change can either affect protein function or be neutral in that respect. Most polymorphisms lack experimental annotation of their functional impact. Here, we introduce SNPdbe-SNP database of effects, with predictions of computationally annotated functional impacts of SNPs. Database entries represent nsSNPs in dbSNP and 1000 Genomes collection, as well as variants from UniProt and PMD. SAASs come from >2600 organisms; 'human' being the most prevalent. The impact of each SAAS on protein function is predicted using the SNAP and SIFT algorithms and augmented with experimentally derived function/structure information and disease associations from PMD, OMIM and UniProt. SNPdbe is consistently updated and easily augmented with new sources of information. The database is available as an MySQL dump and via a web front end that allows searches with any combination of organism names, sequences and mutation IDs. http://www.rostlab.org/services/snpdbe.

VAT: a computational framework to functionally annotate variants in personal genomes within a cloud-computing environment

PubMed Central

Habegger, Lukas; Balasubramanian, Suganthi; Chen, David Z.; Khurana, Ekta; Sboner, Andrea; Harmanci, Arif; Rozowsky, Joel; Clarke, Declan; Snyder, Michael; Gerstein, Mark

2012-01-01

Summary: The functional annotation of variants obtained through sequencing projects is generally assumed to be a simple intersection of genomic coordinates with genomic features. However, complexities arise for several reasons, including the differential effects of a variant on alternatively spliced transcripts, as well as the difficulty in assessing the impact of small insertions/deletions and large structural variants. Taking these factors into consideration, we developed the Variant Annotation Tool (VAT) to functionally annotate variants from multiple personal genomes at the transcript level as well as obtain summary statistics across genes and individuals. VAT also allows visualization of the effects of different variants, integrates allele frequencies and genotype data from the underlying individuals and facilitates comparative analysis between different groups of individuals. VAT can either be run through a command-line interface or as a web application. Finally, in order to enable on-demand access and to minimize unnecessary transfers of large data files, VAT can be run as a virtual machine in a cloud-computing environment. Availability and Implementation: VAT is implemented in C and PHP. The VAT web service, Amazon Machine Image, source code and detailed documentation are available at vat.gersteinlab.org. Contact: lukas.habegger@yale.edu or mark.gerstein@yale.edu Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:22743228

Linking microarray reporters with protein functions.

PubMed

Gaj, Stan; van Erk, Arie; van Haaften, Rachel I M; Evelo, Chris T A

2007-09-26

The analysis of microarray experiments requires accurate and up-to-date functional annotation of the microarray reporters to optimize the interpretation of the biological processes involved. Pathway visualization tools are used to connect gene expression data with existing biological pathways by using specific database identifiers that link reporters with elements in the pathways. This paper proposes a novel method that aims to improve microarray reporter annotation by BLASTing the original reporter sequences against a species-specific EMBL subset, that was derived from and crosslinked back to the highly curated UniProt database. The resulting alignments were filtered using high quality alignment criteria and further compared with the outcome of a more traditional approach, where reporter sequences were BLASTed against EnsEMBL followed by locating the corresponding protein (UniProt) entry for the high quality hits. Combining the results of both methods resulted in successful annotation of > 58% of all reporter sequences with UniProt IDs on two commercial array platforms, increasing the amount of Incyte reporters that could be coupled to Gene Ontology terms from 32.7% to 58.3% and to a local GenMAPP pathway from 9.6% to 16.7%. For Agilent, 35.3% of the total reporters are now linked towards GO nodes and 7.1% on local pathways. Our methods increased the annotation quality of microarray reporter sequences and allowed us to visualize more reporters using pathway visualization tools. Even in cases where the original reporter annotation showed the correct description the new identifiers often allowed improved pathway and Gene Ontology linking. These methods are freely available at http://www.bigcat.unimaas.nl/public/publications/Gaj_Annotation/.

DWARF – a data warehouse system for analyzing protein families

PubMed Central

Fischer, Markus; Thai, Quan K; Grieb, Melanie; Pleiss, Jürgen

2006-01-01

Background The emerging field of integrative bioinformatics provides the tools to organize and systematically analyze vast amounts of highly diverse biological data and thus allows to gain a novel understanding of complex biological systems. The data warehouse DWARF applies integrative bioinformatics approaches to the analysis of large protein families. Description The data warehouse system DWARF integrates data on sequence, structure, and functional annotation for protein fold families. The underlying relational data model consists of three major sections representing entities related to the protein (biochemical function, source organism, classification to homologous families and superfamilies), the protein sequence (position-specific annotation, mutant information), and the protein structure (secondary structure information, superimposed tertiary structure). Tools for extracting, transforming and loading data from public available resources (ExPDB, GenBank, DSSP) are provided to populate the database. The data can be accessed by an interface for searching and browsing, and by analysis tools that operate on annotation, sequence, or structure. We applied DWARF to the family of α/β-hydrolases to host the Lipase Engineering database. Release 2.3 contains 6138 sequences and 167 experimentally determined protein structures, which are assigned to 37 superfamilies 103 homologous families. Conclusion DWARF has been designed for constructing databases of large structurally related protein families and for evaluating their sequence-structure-function relationships by a systematic analysis of sequence, structure and functional annotation. It has been applied to predict biochemical properties from sequence, and serves as a valuable tool for protein engineering. PMID:17094801

Sma3s: A universal tool for easy functional annotation of proteomes and transcriptomes.

PubMed

Casimiro-Soriguer, Carlos S; Muñoz-Mérida, Antonio; Pérez-Pulido, Antonio J

2017-06-01

The current cheapening of next-generation sequencing has led to an enormous growth in the number of sequenced genomes and transcriptomes, allowing wet labs to get the sequences from their organisms of study. To make the most of these data, one of the first things that should be done is the functional annotation of the protein-coding genes. But it used to be a slow and tedious step that can involve the characterization of thousands of sequences. Sma3s is an accurate computational tool for annotating proteins in an unattended way. Now, we have developed a completely new version, which includes functionalities that will be of utility for fundamental and applied science. Currently, the results provide functional categories such as biological processes, which become useful for both characterizing particular sequence datasets and comparing results from different projects. But one of the most important implemented innovations is that it has now low computational requirements, and the complete annotation of a simple proteome or transcriptome usually takes around 24 hours in a personal computer. Sma3s has been tested with a large amount of complete proteomes and transcriptomes, and it has demonstrated its potential in health science and other specific projects. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

PlantRNA, a database for tRNAs of photosynthetic eukaryotes.

PubMed

Cognat, Valérie; Pawlak, Gaël; Duchêne, Anne-Marie; Daujat, Magali; Gigant, Anaïs; Salinas, Thalia; Michaud, Morgane; Gutmann, Bernard; Giegé, Philippe; Gobert, Anthony; Maréchal-Drouard, Laurence

2013-01-01

PlantRNA database (http://plantrna.ibmp.cnrs.fr/) compiles transfer RNA (tRNA) gene sequences retrieved from fully annotated plant nuclear, plastidial and mitochondrial genomes. The set of annotated tRNA gene sequences has been manually curated for maximum quality and confidence. The novelty of this database resides in the inclusion of biological information relevant to the function of all the tRNAs entered in the library. This includes 5'- and 3'-flanking sequences, A and B box sequences, region of transcription initiation and poly(T) transcription termination stretches, tRNA intron sequences, aminoacyl-tRNA synthetases and enzymes responsible for tRNA maturation and modification. Finally, data on mitochondrial import of nuclear-encoded tRNAs as well as the bibliome for the respective tRNAs and tRNA-binding proteins are also included. The current annotation concerns complete genomes from 11 organisms: five flowering plants (Arabidopsis thaliana, Oryza sativa, Populus trichocarpa, Medicago truncatula and Brachypodium distachyon), a moss (Physcomitrella patens), two green algae (Chlamydomonas reinhardtii and Ostreococcus tauri), one glaucophyte (Cyanophora paradoxa), one brown alga (Ectocarpus siliculosus) and a pennate diatom (Phaeodactylum tricornutum). The database will be regularly updated and implemented with new plant genome annotations so as to provide extensive information on tRNA biology to the research community.

CyanoBase: the cyanobacteria genome database update 2010

PubMed Central

Nakao, Mitsuteru; Okamoto, Shinobu; Kohara, Mitsuyo; Fujishiro, Tsunakazu; Fujisawa, Takatomo; Sato, Shusei; Tabata, Satoshi; Kaneko, Takakazu; Nakamura, Yasukazu

2010-01-01

CyanoBase (http://genome.kazusa.or.jp/cyanobase) is the genome database for cyanobacteria, which are model organisms for photosynthesis. The database houses cyanobacteria species information, complete genome sequences, genome-scale experiment data, gene information, gene annotations and mutant information. In this version, we updated these datasets and improved the navigation and the visual display of the data views. In addition, a web service API now enables users to retrieve the data in various formats with other tools, seamlessly. PMID:19880388

High-throughput comparison, functional annotation, and metabolic modeling of plant genomes using the PlantSEED resource

USDA-ARS?s Scientific Manuscript database

The increasing number of sequenced plant genomes is placing new demands on the methods applied to analyze, annotate, and model these genomes. Today's annotation pipelines result in inconsistent gene assignments that complicate comparative analyses and prevent efficient construction of metabolic mode...

Escherichia coli K-12: a cooperatively developed annotation snapshot—2005

PubMed Central

Riley, Monica; Abe, Takashi; Arnaud, Martha B.; Berlyn, Mary K.B.; Blattner, Frederick R.; Chaudhuri, Roy R.; Glasner, Jeremy D.; Horiuchi, Takashi; Keseler, Ingrid M.; Kosuge, Takehide; Mori, Hirotada; Perna, Nicole T.; Plunkett, Guy; Rudd, Kenneth E.; Serres, Margrethe H.; Thomas, Gavin H.; Thomson, Nicholas R.; Wishart, David; Wanner, Barry L.

2006-01-01

The goal of this group project has been to coordinate and bring up-to-date information on all genes of Escherichia coli K-12. Annotation of the genome of an organism entails identification of genes, the boundaries of genes in terms of precise start and end sites, and description of the gene products. Known and predicted functions were assigned to each gene product on the basis of experimental evidence or sequence analysis. Since both kinds of evidence are constantly expanding, no annotation is complete at any moment in time. This is a snapshot analysis based on the most recent genome sequences of two E.coli K-12 bacteria. An accurate and up-to-date description of E.coli K-12 genes is of particular importance to the scientific community because experimentally determined properties of its gene products provide fundamental information for annotation of innumerable genes of other organisms. Availability of the complete genome sequence of two K-12 strains allows comparison of their genotypes and mutant status of alleles. PMID:16397293

The Génolevures database.

PubMed

Martin, Tiphaine; Sherman, David J; Durrens, Pascal

2011-01-01

The Génolevures online database (URL: http://www.genolevures.org) stores and provides the data and results obtained by the Génolevures Consortium through several campaigns of genome annotation of the yeasts in the Saccharomycotina subphylum (hemiascomycetes). This database is dedicated to large-scale comparison of these genomes, storing not only the different chromosomal elements detected in the sequences, but also the logical relations between them. The database is divided into a public part, accessible to anyone through Internet, and a private part where the Consortium members make genome annotations with our Magus annotation system; this system is used to annotate several related genomes in parallel. The public database is widely consulted and offers structured data, organized using a REST web site architecture that allows for automated requests. The implementation of the database, as well as its associated tools and methods, is evolving to cope with the influx of genome sequences produced by Next Generation Sequencing (NGS). Copyright © 2011 Académie des sciences. Published by Elsevier SAS. All rights reserved.

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.

DeepBase: annotation and discovery of microRNAs and other noncoding RNAs from deep-sequencing data.

PubMed

Yang, Jian-Hua; Qu, Liang-Hu

2012-01-01

Recent advances in high-throughput deep-sequencing technology have produced large numbers of short and long RNA sequences and enabled the detection and profiling of known and novel microRNAs (miRNAs) and other noncoding RNAs (ncRNAs) at unprecedented sensitivity and depth. In this chapter, we describe the use of deepBase, a database that we have developed to integrate all public deep-sequencing data and to facilitate the comprehensive annotation and discovery of miRNAs and other ncRNAs from these data. deepBase provides an integrative, interactive, and versatile web graphical interface to evaluate miRBase-annotated miRNA genes and other known ncRNAs, explores the expression patterns of miRNAs and other ncRNAs, and discovers novel miRNAs and other ncRNAs from deep-sequencing data. deepBase also provides a deepView genome browser to comparatively analyze these data at multiple levels. deepBase is available at http://deepbase.sysu.edu.cn/.

Sequencing, Analysis, and Annotation of Expressed Sequence Tags for Camelus dromedarius

PubMed Central

Al-Swailem, Abdulaziz M.; Shehata, Maher M.; Abu-Duhier, Faisel M.; Al-Yamani, Essam J.; Al-Busadah, Khalid A.; Al-Arawi, Mohammed S.; Al-Khider, Ali Y.; Al-Muhaimeed, Abdullah N.; Al-Qahtani, Fahad H.; Manee, Manee M.; Al-Shomrani, Badr M.; Al-Qhtani, Saad M.; Al-Harthi, Amer S.; Akdemir, Kadir C.; Otu, Hasan H.

2010-01-01

Despite its economical, cultural, and biological importance, there has not been a large scale sequencing project to date for Camelus dromedarius. With the goal of sequencing complete DNA of the organism, we first established and sequenced camel EST libraries, generating 70,272 reads. Following trimming, chimera check, repeat masking, cluster and assembly, we obtained 23,602 putative gene sequences, out of which over 4,500 potentially novel or fast evolving gene sequences do not carry any homology to other available genomes. Functional annotation of sequences with similarities in nucleotide and protein databases has been obtained using Gene Ontology classification. Comparison to available full length cDNA sequences and Open Reading Frame (ORF) analysis of camel sequences that exhibit homology to known genes show more than 80% of the contigs with an ORF>300 bp and ∼40% hits extending to the start codons of full length cDNAs suggesting successful characterization of camel genes. Similarity analyses are done separately for different organisms including human, mouse, bovine, and rat. Accompanying web portal, CAGBASE (http://camel.kacst.edu.sa/), hosts a relational database containing annotated EST sequences and analysis tools with possibility to add sequences from public domain. We anticipate our results to provide a home base for genomic studies of camel and other comparative studies enabling a starting point for whole genome sequencing of the organism. PMID:20502665

Long-read sequencing of the coffee bean transcriptome reveals the diversity of full-length transcripts

PubMed Central

Cheng, Bing; Furtado, Agnelo

2017-01-01

Abstract Polyploidization contributes to the complexity of gene expression, resulting in numerous related but different transcripts. This study explored the transcriptome diversity and complexity of the tetraploid Arabica coffee (Coffea arabica) bean. Long-read sequencing (LRS) by Pacbio Isoform sequencing (Iso-seq) was used to obtain full-length transcripts without the difficulty and uncertainty of assembly required for reads from short-read technologies. The tetraploid transcriptome was annotated and compared with data from the sub-genome progenitors. Caffeine and sucrose genes were targeted for case analysis. An isoform-level tetraploid coffee bean reference transcriptome with 95 995 distinct transcripts (average 3236 bp) was obtained. A total of 88 715 sequences (92.42%) were annotated with BLASTx against NCBI non-redundant plant proteins, including 34 719 high-quality annotations. Further BLASTn analysis against NCBI non-redundant nucleotide sequences, Coffea canephora coding sequences with UTR, C. arabica ESTs, and Rfam resulted in 1213 sequences without hits, were potential novel genes in coffee. Longer UTRs were captured, especially in the 5΄UTRs, facilitating the identification of upstream open reading frames. The LRS also revealed more and longer transcript variants in key caffeine and sucrose metabolism genes from this polyploid genome. Long sequences (>10 kilo base) were poorly annotated. LRS technology shows the limitation of previous studies. It provides an important tool to produce a reference transcriptome including more of the diversity of full-length transcripts to help understand the biology and support the genetic improvement of polyploid species such as coffee. PMID:29048540

A RESTful API for accessing microbial community data for MG-RAST

DOE PAGES

Wilke, Andreas; Bischof, Jared; Harrison, Travis; ...

2015-01-08

Metagenomic sequencing has produced significant amounts of data in recent years. For example, as of summer 2013, MGRAST has been used to annotate over 110,000 data sets totaling over 43 Terabases. With metagenomic sequencing finding even wider adoption in the scientific community, the existing web-based analysis tools and infrastructure in MG-RAST provide limited capability for data retrieval and analysis, such as comparative analysis between multiple data sets. Moreover, although the system provides many analysis tools, it is not comprehensive. By opening MG-RAST up via a web services API (application programmers interface) we have greatly expanded access to MG-RAST data, asmore » well as provided a mechanism for the use of third-party analysis tools with MG-RAST data. This RESTful API makes all data and data objects created by the MG-RAST pipeline accessible as JSON objects. As part of the DOE Systems Biology Knowledgebase project (KBase, http:// kbase.us) we have implemented a web services API for MG-RAST. This API complements the existing MG-RAST web interface and constitutes the basis of KBase’s microbial community capabilities. In addition, the API exposes a comprehensive collection of data to programmers. This API, which uses a RESTful (Representational State Transfer) implementation, is compatible with most programming environments and should be easy to use for end users and third parties. It provides comprehensive access to sequence data, quality control results, annotations, and many other data types. Where feasible, we have used standards to expose data and metadata. Code examples are provided in a number of languages both to show the versatility of the API and to provide a starting point for users. We present an API that exposes the data in MG-RAST for consumption by our users, greatly enhancing the utility of the MG-RAST service.« less

A RESTful API for Accessing Microbial Community Data for MG-RAST

PubMed Central

Wilke, Andreas; Bischof, Jared; Harrison, Travis; Brettin, Tom; D'Souza, Mark; Gerlach, Wolfgang; Matthews, Hunter; Paczian, Tobias; Wilkening, Jared; Glass, Elizabeth M.; Desai, Narayan; Meyer, Folker

2015-01-01

Metagenomic sequencing has produced significant amounts of data in recent years. For example, as of summer 2013, MG-RAST has been used to annotate over 110,000 data sets totaling over 43 Terabases. With metagenomic sequencing finding even wider adoption in the scientific community, the existing web-based analysis tools and infrastructure in MG-RAST provide limited capability for data retrieval and analysis, such as comparative analysis between multiple data sets. Moreover, although the system provides many analysis tools, it is not comprehensive. By opening MG-RAST up via a web services API (application programmers interface) we have greatly expanded access to MG-RAST data, as well as provided a mechanism for the use of third-party analysis tools with MG-RAST data. This RESTful API makes all data and data objects created by the MG-RAST pipeline accessible as JSON objects. As part of the DOE Systems Biology Knowledgebase project (KBase, http://kbase.us) we have implemented a web services API for MG-RAST. This API complements the existing MG-RAST web interface and constitutes the basis of KBase's microbial community capabilities. In addition, the API exposes a comprehensive collection of data to programmers. This API, which uses a RESTful (Representational State Transfer) implementation, is compatible with most programming environments and should be easy to use for end users and third parties. It provides comprehensive access to sequence data, quality control results, annotations, and many other data types. Where feasible, we have used standards to expose data and metadata. Code examples are provided in a number of languages both to show the versatility of the API and to provide a starting point for users. We present an API that exposes the data in MG-RAST for consumption by our users, greatly enhancing the utility of the MG-RAST service. PMID:25569221

Transcriptator: An Automated Computational Pipeline to Annotate Assembled Reads and Identify Non Coding RNA.

PubMed

Tripathi, Kumar Parijat; Evangelista, Daniela; Zuccaro, Antonio; Guarracino, Mario Rosario

2015-01-01

RNA-seq is a new tool to measure RNA transcript counts, using high-throughput sequencing at an extraordinary accuracy. It provides quantitative means to explore the transcriptome of an organism of interest. However, interpreting this extremely large data into biological knowledge is a problem, and biologist-friendly tools are lacking. In our lab, we developed Transcriptator, a web application based on a computational Python pipeline with a user-friendly Java interface. This pipeline uses the web services available for BLAST (Basis Local Search Alignment Tool), QuickGO and DAVID (Database for Annotation, Visualization and Integrated Discovery) tools. It offers a report on statistical analysis of functional and Gene Ontology (GO) annotation's enrichment. It helps users to identify enriched biological themes, particularly GO terms, pathways, domains, gene/proteins features and protein-protein interactions related informations. It clusters the transcripts based on functional annotations and generates a tabular report for functional and gene ontology annotations for each submitted transcript to the web server. The implementation of QuickGo web-services in our pipeline enable the users to carry out GO-Slim analysis, whereas the integration of PORTRAIT (Prediction of transcriptomic non coding RNA (ncRNA) by ab initio methods) helps to identify the non coding RNAs and their regulatory role in transcriptome. In summary, Transcriptator is a useful software for both NGS and array data. It helps the users to characterize the de-novo assembled reads, obtained from NGS experiments for non-referenced organisms, while it also performs the functional enrichment analysis of differentially expressed transcripts/genes for both RNA-seq and micro-array experiments. It generates easy to read tables and interactive charts for better understanding of the data. The pipeline is modular in nature, and provides an opportunity to add new plugins in the future. Web application is freely available at: http://www-labgtp.na.icar.cnr.it/Transcriptator.

Open semantic annotation of scientific publications using DOMEO.

PubMed

Ciccarese, Paolo; Ocana, Marco; Clark, Tim

2012-04-24

Our group has developed a useful shared software framework for performing, versioning, sharing and viewing Web annotations of a number of kinds, using an open representation model. The Domeo Annotation Tool was developed in tandem with this open model, the Annotation Ontology (AO). Development of both the Annotation Framework and the open model was driven by requirements of several different types of alpha users, including bench scientists and biomedical curators from university research labs, online scientific communities, publishing and pharmaceutical companies.Several use cases were incrementally implemented by the toolkit. These use cases in biomedical communications include personal note-taking, group document annotation, semantic tagging, claim-evidence-context extraction, reagent tagging, and curation of textmining results from entity extraction algorithms. We report on the Domeo user interface here. Domeo has been deployed in beta release as part of the NIH Neuroscience Information Framework (NIF, http://www.neuinfo.org) and is scheduled for production deployment in the NIF's next full release.Future papers will describe other aspects of this work in detail, including Annotation Framework Services and components for integrating with external textmining services, such as the NCBO Annotator web service, and with other textmining applications using the Apache UIMA framework.

Open semantic annotation of scientific publications using DOMEO

PubMed Central

2012-01-01

Background Our group has developed a useful shared software framework for performing, versioning, sharing and viewing Web annotations of a number of kinds, using an open representation model. Methods The Domeo Annotation Tool was developed in tandem with this open model, the Annotation Ontology (AO). Development of both the Annotation Framework and the open model was driven by requirements of several different types of alpha users, including bench scientists and biomedical curators from university research labs, online scientific communities, publishing and pharmaceutical companies. Several use cases were incrementally implemented by the toolkit. These use cases in biomedical communications include personal note-taking, group document annotation, semantic tagging, claim-evidence-context extraction, reagent tagging, and curation of textmining results from entity extraction algorithms. Results We report on the Domeo user interface here. Domeo has been deployed in beta release as part of the NIH Neuroscience Information Framework (NIF, http://www.neuinfo.org) and is scheduled for production deployment in the NIF’s next full release. Future papers will describe other aspects of this work in detail, including Annotation Framework Services and components for integrating with external textmining services, such as the NCBO Annotator web service, and with other textmining applications using the Apache UIMA framework. PMID:22541592

The new modern era of yeast genomics: community sequencing and the resulting annotation of multiple Saccharomyces cerevisiae strains at the Saccharomyces Genome Database

PubMed Central

Engel, Stacia R.; Cherry, J. Michael

2013-01-01

The first completed eukaryotic genome sequence was that of the yeast Saccharomyces cerevisiae, and the Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/) is the original model organism database. SGD remains the authoritative community resource for the S. cerevisiae reference genome sequence and its annotation, and continues to provide comprehensive biological information correlated with S. cerevisiae genes and their products. A diverse set of yeast strains have been sequenced to explore commercial and laboratory applications, and a brief history of those strains is provided. The publication of these new genomes has motivated the creation of new tools, and SGD will annotate and provide comparative analyses of these sequences, correlating changes with variations in strain phenotypes and protein function. We are entering a new era at SGD, as we incorporate these new sequences and make them accessible to the scientific community, all in an effort to continue in our mission of educating researchers and facilitating discovery. Database URL: http://www.yeastgenome.org/ PMID:23487186

Unified Sequence-Based Association Tests Allowing for Multiple Functional Annotations and Meta-analysis of Noncoding Variation in Metabochip Data.

PubMed

He, Zihuai; Xu, Bin; Lee, Seunggeun; Ionita-Laza, Iuliana

2017-09-07

Substantial progress has been made in the functional annotation of genetic variation in the human genome. Integrative analysis that incorporates such functional annotations into sequencing studies can aid the discovery of disease-associated genetic variants, especially those with unknown function and located outside protein-coding regions. Direct incorporation of one functional annotation as weight in existing dispersion and burden tests can suffer substantial loss of power when the functional annotation is not predictive of the risk status of a variant. Here, we have developed unified tests that can utilize multiple functional annotations simultaneously for integrative association analysis with efficient computational techniques. We show that the proposed tests significantly improve power when variant risk status can be predicted by functional annotations. Importantly, when functional annotations are not predictive of risk status, the proposed tests incur only minimal loss of power in relation to existing dispersion and burden tests, and under certain circumstances they can even have improved power by learning a weight that better approximates the underlying disease model in a data-adaptive manner. The tests can be constructed with summary statistics of existing dispersion and burden tests for sequencing data, therefore allowing meta-analysis of multiple studies without sharing individual-level data. We applied the proposed tests to a meta-analysis of noncoding rare variants in Metabochip data on 12,281 individuals from eight studies for lipid traits. By incorporating the Eigen functional score, we detected significant associations between noncoding rare variants in SLC22A3 and low-density lipoprotein and total cholesterol, associations that are missed by standard dispersion and burden tests. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

CuGene as a tool to view and explore genomic data

NASA Astrophysics Data System (ADS)

Haponiuk, Michał; Pawełkowicz, Magdalena; Przybecki, Zbigniew; Nowak, Robert M.

2017-08-01

Integrated CuGene is an easy-to-use, open-source, on-line tool that can be used to browse, analyze, and query genomic data and annotations. It places annotation tracks beneath genome coordinate positions, allowing rapid visual correlation of different types of information. It also allows users to upload and display their own experimental results or annotation sets. An important functionality of the application is a possibility to find similarity between sequences by applying four different algorithms of different accuracy. The presented tool was tested on real genomic data and is extensively used by Polish Consortium of Cucumber Genome Sequencing.

Unique Features of the Loblolly Pine (Pinus taeda L.) Megagenome Revealed Through Sequence Annotation

PubMed Central

Wegrzyn, Jill L.; Liechty, John D.; Stevens, Kristian A.; Wu, Le-Shin; Loopstra, Carol A.; Vasquez-Gross, Hans A.; Dougherty, William M.; Lin, Brian Y.; Zieve, Jacob J.; Martínez-García, Pedro J.; Holt, Carson; Yandell, Mark; Zimin, Aleksey V.; Yorke, James A.; Crepeau, Marc W.; Puiu, Daniela; Salzberg, Steven L.; de Jong, Pieter J.; Mockaitis, Keithanne; Main, Doreen; Langley, Charles H.; Neale, David B.

2014-01-01

The largest genus in the conifer family Pinaceae is Pinus, with over 100 species. The size and complexity of their genomes (∼20–40 Gb, 2n = 24) have delayed the arrival of a well-annotated reference sequence. In this study, we present the annotation of the first whole-genome shotgun assembly of loblolly pine (Pinus taeda L.), which comprises 20.1 Gb of sequence. The MAKER-P annotation pipeline combined evidence-based alignments and ab initio predictions to generate 50,172 gene models, of which 15,653 are classified as high confidence. Clustering these gene models with 13 other plant species resulted in 20,646 gene families, of which 1554 are predicted to be unique to conifers. Among the conifer gene families, 159 are composed exclusively of loblolly pine members. The gene models for loblolly pine have the highest median and mean intron lengths of 24 fully sequenced plant genomes. Conifer genomes are full of repetitive DNA, with the most significant contributions from long-terminal-repeat retrotransposons. In depth analysis of the tandem and interspersed repetitive content yielded a combined estimate of 82%. PMID:24653211

PARRoT- a homology-based strategy to quantify and compare RNA-sequencing from non-model organisms.

PubMed

Gan, Ruei-Chi; Chen, Ting-Wen; Wu, Timothy H; Huang, Po-Jung; Lee, Chi-Ching; Yeh, Yuan-Ming; Chiu, Cheng-Hsun; Huang, Hsien-Da; Tang, Petrus

2016-12-22

Next-generation sequencing promises the de novo genomic and transcriptomic analysis of samples of interests. However, there are only a few organisms having reference genomic sequences and even fewer having well-defined or curated annotations. For transcriptome studies focusing on organisms lacking proper reference genomes, the common strategy is de novo assembly followed by functional annotation. However, things become even more complicated when multiple transcriptomes are compared. Here, we propose a new analysis strategy and quantification methods for quantifying expression level which not only generate a virtual reference from sequencing data, but also provide comparisons between transcriptomes. First, all reads from the transcriptome datasets are pooled together for de novo assembly. The assembled contigs are searched against NCBI NR databases to find potential homolog sequences. Based on the searched result, a set of virtual transcripts are generated and served as a reference transcriptome. By using the same reference, normalized quantification values including RC (read counts), eRPKM (estimated RPKM) and eTPM (estimated TPM) can be obtained that are comparable across transcriptome datasets. In order to demonstrate the feasibility of our strategy, we implement it in the web service PARRoT. PARRoT stands for Pipeline for Analyzing RNA Reads of Transcriptomes. It analyzes gene expression profiles for two transcriptome sequencing datasets. For better understanding of the biological meaning from the comparison among transcriptomes, PARRoT further provides linkage between these virtual transcripts and their potential function through showing best hits in SwissProt, NR database, assigning GO terms. Our demo datasets showed that PARRoT can analyze two paired-end transcriptomic datasets of approximately 100 million reads within just three hours. In this study, we proposed and implemented a strategy to analyze transcriptomes from non-reference organisms which offers the opportunity to quantify and compare transcriptome profiles through a homolog based virtual transcriptome reference. By using the homolog based reference, our strategy effectively avoids the problems that may cause from inconsistencies among transcriptomes. This strategy will shed lights on the field of comparative genomics for non-model organism. We have implemented PARRoT as a web service which is freely available at http://parrot.cgu.edu.tw .

Higher Order Thinking in Collaborative Video Annotations: Investigating Discourse Modeling and the Staggering of Learner Participation

ERIC Educational Resources Information Center

Howard, Craig Dennis

2012-01-01

"Collaborative video annotation" (CVA) allows multiple users to annotate video and create a discussion asynchronously. This dissertation investigates 14 small-group CVA discussions held on YouTube in a pre-service teacher education course. Fourteen groups of 6-12 pre-service teachers (141 total) participated. Five of these groups (48…

Transcriptome sequence analysis of an ornamental plant, Ananas comosus var. bracteatus, revealed the potential unigenes involved in terpenoid and phenylpropanoid biosynthesis.

PubMed

Ma, Jun; Kanakala, S; He, Yehua; Zhang, Junli; Zhong, Xiaolan

2015-01-01

Ananas comosus var. bracteatus (Red Pineapple) is an important ornamental plant for its colorful leaves and decorative red fruits. Because of its complex genome, it is difficult to understand the molecular mechanisms involved in the growth and development. Thus high-throughput transcriptome sequencing of Ananas comosus var. bracteatus is necessary to generate large quantities of transcript sequences for the purpose of gene discovery and functional genomic studies. The Ananas comosus var. bracteatus transcriptome was sequenced by the Illumina paired-end sequencing technology. We obtained a total of 23.5 million high quality sequencing reads, 1,555,808 contigs and 41,052 unigenes. In total 41,052 unigenes of Ananas comosus var. bracteatus, 23,275 unigenes were annotated in the NCBI non-redundant protein database and 23,134 unigenes were annotated in the Swiss-Port database. Out of these, 17,748 and 8,505 unigenes were assigned to gene ontology categories and clusters of orthologous groups, respectively. Functional annotation against Kyoto Encyclopedia of Genes and Genomes Pathway database identified 5,825 unigenes which were mapped to 117 pathways. The assembly predicted many unigenes that were previously unknown. The annotated unigenes were compared against pineapple, rice, maize, Arabidopsis, and sorghum. Unigenes that did not match any of those five sequence datasets are considered to be Ananas comosus var. bracteatus unique. We predicted unigenes encoding enzymes involved in terpenoid and phenylpropanoid biosynthesis. The sequence data provide the most comprehensive transcriptomic resource currently available for Ananas comosus var. bracteatus. To our knowledge; this is the first report on the de novo transcriptome sequencing of the Ananas comosus var. bracteatus. Unigenes obtained in this study, may help improve future gene expression, genetic and genomics studies in Ananas comosus var. bracteatus.

Transcriptome Sequence Analysis of an Ornamental Plant, Ananas comosus var. bracteatus, Revealed the Potential Unigenes Involved in Terpenoid and Phenylpropanoid Biosynthesis

PubMed Central

Ma, Jun; Kanakala, S.; He, Yehua; Zhang, Junli; Zhong, Xiaolan

2015-01-01

Background Ananas comosus var. bracteatus (Red Pineapple) is an important ornamental plant for its colorful leaves and decorative red fruits. Because of its complex genome, it is difficult to understand the molecular mechanisms involved in the growth and development. Thus high-throughput transcriptome sequencing of Ananas comosus var. bracteatus is necessary to generate large quantities of transcript sequences for the purpose of gene discovery and functional genomic studies. Results The Ananas comosus var. bracteatus transcriptome was sequenced by the Illumina paired-end sequencing technology. We obtained a total of 23.5 million high quality sequencing reads, 1,555,808 contigs and 41,052 unigenes. In total 41,052 unigenes of Ananas comosus var. bracteatus, 23,275 unigenes were annotated in the NCBI non-redundant protein database and 23,134 unigenes were annotated in the Swiss-Port database. Out of these, 17,748 and 8,505 unigenes were assigned to gene ontology categories and clusters of orthologous groups, respectively. Functional annotation against Kyoto Encyclopedia of Genes and Genomes Pathway database identified 5,825 unigenes which were mapped to 117 pathways. The assembly predicted many unigenes that were previously unknown. The annotated unigenes were compared against pineapple, rice, maize, Arabidopsis, and sorghum. Unigenes that did not match any of those five sequence datasets are considered to be Ananas comosus var. bracteatus unique. We predicted unigenes encoding enzymes involved in terpenoid and phenylpropanoid biosynthesis. Conclusion The sequence data provide the most comprehensive transcriptomic resource currently available for Ananas comosus var. bracteatus. To our knowledge; this is the first report on the de novo transcriptome sequencing of the Ananas comosus var. bracteatus. Unigenes obtained in this study, may help improve future gene expression, genetic and genomics studies in Ananas comosus var. bracteatus. PMID:25769053

Incorporating evolution of transcription factor binding sites into annotated alignments.

PubMed

Bais, Abha S; Grossmann, Stefen; Vingron, Martin

2007-08-01

Identifying transcription factor binding sites (TFBSs) is essential to elucidate putative regulatory mechanisms. A common strategy is to combine cross-species conservation with single sequence TFBS annotation to yield "conserved TFBSs". Most current methods in this field adopt a multi-step approach that segregates the two aspects. Again, it is widely accepted that the evolutionary dynamics of binding sites differ from those of the surrounding sequence. Hence, it is desirable to have an approach that explicitly takes this factor into account. Although a plethora of approaches have been proposed for the prediction of conserved TFBSs, very few explicitly model TFBS evolutionary properties, while additionally being multi-step. Recently, we introduced a novel approach to simultaneously align and annotate conserved TFBSs in a pair of sequences. Building upon the standard Smith-Waterman algorithm for local alignments, SimAnn introduces additional states for profiles to output extended alignments or annotated alignments. That is, alignments with parts annotated as gaplessly aligned TFBSs (pair-profile hits)are generated. Moreover,the pair- profile related parameters are derived in a sound statistical framework. In this article, we extend this approach to explicitly incorporate evolution of binding sites in the SimAnn framework. We demonstrate the extension in the theoretical derivations through two position-specific evolutionary models, previously used for modelling TFBS evolution. In a simulated setting, we provide a proof of concept that the approach works given the underlying assumptions,as compared to the original work. Finally, using a real dataset of experimentally verified binding sites in human-mouse sequence pairs,we compare the new approach (eSimAnn) to an existing multi-step tool that also considers TFBS evolution. Although it is widely accepted that binding sites evolve differently from the surrounding sequences, most comparative TFBS identification methods do not explicitly consider this.Additionally, prediction of conserved binding sites is carried out in a multi-step approach that segregates alignment from TFBS annotation. In this paper, we demonstrate how the simultaneous alignment and annotation approach of SimAnn can be further extended to incorporate TFBS evolutionary relationships. We study how alignments and binding site predictions interplay at varying evolutionary distances and for various profile qualities.

Transcriptome Assembly, Gene Annotation and Tissue Gene Expression Atlas of the Rainbow Trout

PubMed Central

Salem, Mohamed; Paneru, Bam; Al-Tobasei, Rafet; Abdouni, Fatima; Thorgaard, Gary H.; Rexroad, Caird E.; Yao, Jianbo

2015-01-01

Efforts to obtain a comprehensive genome sequence for rainbow trout are ongoing and will be complemented by transcriptome information that will enhance genome assembly and annotation. Previously, transcriptome reference sequences were reported using data from different sources. Although the previous work added a great wealth of sequences, a complete and well-annotated transcriptome is still needed. In addition, gene expression in different tissues was not completely addressed in the previous studies. In this study, non-normalized cDNA libraries were sequenced from 13 different tissues of a single doubled haploid rainbow trout from the same source used for the rainbow trout genome sequence. A total of ~1.167 billion paired-end reads were de novo assembled using the Trinity RNA-Seq assembler yielding 474,524 contigs > 500 base-pairs. Of them, 287,593 had homologies to the NCBI non-redundant protein database. The longest contig of each cluster was selected as a reference, yielding 44,990 representative contigs. A total of 4,146 contigs (9.2%), including 710 full-length sequences, did not match any mRNA sequences in the current rainbow trout genome reference. Mapping reads to the reference genome identified an additional 11,843 transcripts not annotated in the genome. A digital gene expression atlas revealed 7,678 housekeeping and 4,021 tissue-specific genes. Expression of about 16,000–32,000 genes (35–71% of the identified genes) accounted for basic and specialized functions of each tissue. White muscle and stomach had the least complex transcriptomes, with high percentages of their total mRNA contributed by a small number of genes. Brain, testis and intestine, in contrast, had complex transcriptomes, with a large numbers of genes involved in their expression patterns. This study provides comprehensive de novo transcriptome information that is suitable for functional and comparative genomics studies in rainbow trout, including annotation of the genome. PMID:25793877

ORFer--retrieval of protein sequences and open reading frames from GenBank and storage into relational databases or text files.

PubMed

Büssow, Konrad; Hoffmann, Steve; Sievert, Volker

2002-12-19

Functional genomics involves the parallel experimentation with large sets of proteins. This requires management of large sets of open reading frames as a prerequisite of the cloning and recombinant expression of these proteins. A Java program was developed for retrieval of protein and nucleic acid sequences and annotations from NCBI GenBank, using the XML sequence format. Annotations retrieved by ORFer include sequence name, organism and also the completeness of the sequence. The program has a graphical user interface, although it can be used in a non-interactive mode. For protein sequences, the program also extracts the open reading frame sequence, if available, and checks its correct translation. ORFer accepts user input in the form of single or lists of GenBank GI identifiers or accession numbers. It can be used to extract complete sets of open reading frames and protein sequences from any kind of GenBank sequence entry, including complete genomes or chromosomes. Sequences are either stored with their features in a relational database or can be exported as text files in Fasta or tabulator delimited format. The ORFer program is freely available at http://www.proteinstrukturfabrik.de/orfer. The ORFer program allows for fast retrieval of DNA sequences, protein sequences and their open reading frames and sequence annotations from GenBank. Furthermore, storage of sequences and features in a relational database is supported. Such a database can supplement a laboratory information system (LIMS) with appropriate sequence information.

RNASeq-based genome annotation and identification of long-noncoding RNAs in the grapevine cultivar 'Riesling'

USDA-ARS?s Scientific Manuscript database

The technological advances of RNA-seq and de novo transcriptome assembly have enabled genome annotation and transcriptome profiling in heterozygous species. This is a promising approach to improving the annotation of the reference genome sequence of grapevine (Vitis vinifera L.), a species of high-l...

Protein Annotators' Assistant: A Novel Application of Information Retrieval Techniques.

ERIC Educational Resources Information Center

Wise, Michael J.

2000-01-01

Protein Annotators' Assistant (PAA) is a software system which assists protein annotators in assigning functions to newly sequenced proteins. PAA employs a number of information retrieval techniques in a novel setting and is thus related to text categorization, where multiple categories may be suggested, except that in this case none of the…

Functional Annotation of the Arabidopsis Genome Using Controlled Vocabularies1

PubMed Central

Berardini, Tanya Z.; Mundodi, Suparna; Reiser, Leonore; Huala, Eva; Garcia-Hernandez, Margarita; Zhang, Peifen; Mueller, Lukas A.; Yoon, Jungwoon; Doyle, Aisling; Lander, Gabriel; Moseyko, Nick; Yoo, Danny; Xu, Iris; Zoeckler, Brandon; Montoya, Mary; Miller, Neil; Weems, Dan; Rhee, Seung Y.

2004-01-01

Controlled vocabularies are increasingly used by databases to describe genes and gene products because they facilitate identification of similar genes within an organism or among different organisms. One of The Arabidopsis Information Resource's goals is to associate all Arabidopsis genes with terms developed by the Gene Ontology Consortium that describe the molecular function, biological process, and subcellular location of a gene product. We have also developed terms describing Arabidopsis anatomy and developmental stages and use these to annotate published gene expression data. As of March 2004, we used computational and manual annotation methods to make 85,666 annotations representing 26,624 unique loci. We focus on associating genes to controlled vocabulary terms based on experimental data from the literature and use The Arabidopsis Information Resource-developed PubSearch software to facilitate this process. Each annotation is tagged with a combination of evidence codes, evidence descriptions, and references that provide a robust means to assess data quality. Annotation of all Arabidopsis genes will allow quantitative comparisons between sets of genes derived from sources such as microarray experiments. The Arabidopsis annotation data will also facilitate annotation of newly sequenced plant genomes by using sequence similarity to transfer annotations to homologous genes. In addition, complete and up-to-date annotations will make unknown genes easy to identify and target for experimentation. Here, we describe the process of Arabidopsis functional annotation using a variety of data sources and illustrate several ways in which this information can be accessed and used to infer knowledge about Arabidopsis and other plant species. PMID:15173566

Lynx web services for annotations and systems analysis of multi-gene disorders.

PubMed

Sulakhe, Dinanath; Taylor, Andrew; Balasubramanian, Sandhya; Feng, Bo; Xie, Bingqing; Börnigen, Daniela; Dave, Utpal J; Foster, Ian T; Gilliam, T Conrad; Maltsev, Natalia

2014-07-01

Lynx is a web-based integrated systems biology platform that supports annotation and analysis of experimental data and generation of weighted hypotheses on molecular mechanisms contributing to human phenotypes and disorders of interest. Lynx has integrated multiple classes of biomedical data (genomic, proteomic, pathways, phenotypic, toxicogenomic, contextual and others) from various public databases as well as manually curated data from our group and collaborators (LynxKB). Lynx provides tools for gene list enrichment analysis using multiple functional annotations and network-based gene prioritization. Lynx provides access to the integrated database and the analytical tools via REST based Web Services (http://lynx.ci.uchicago.edu/webservices.html). This comprises data retrieval services for specific functional annotations, services to search across the complete LynxKB (powered by Lucene), and services to access the analytical tools built within the Lynx platform. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Association algorithm to mine the rules that govern enzyme definition and to classify protein sequences

PubMed Central

Chiu, Shih-Hau; Chen, Chien-Chi; Yuan, Gwo-Fang; Lin, Thy-Hou

2006-01-01

Background The number of sequences compiled in many genome projects is growing exponentially, but most of them have not been characterized experimentally. An automatic annotation scheme must be in an urgent need to reduce the gap between the amount of new sequences produced and reliable functional annotation. This work proposes rules for automatically classifying the fungus genes. The approach involves elucidating the enzyme classifying rule that is hidden in UniProt protein knowledgebase and then applying it for classification. The association algorithm, Apriori, is utilized to mine the relationship between the enzyme class and significant InterPro entries. The candidate rules are evaluated for their classificatory capacity. Results There were five datasets collected from the Swiss-Prot for establishing the annotation rules. These were treated as the training sets. The TrEMBL entries were treated as the testing set. A correct enzyme classification rate of 70% was obtained for the prokaryote datasets and a similar rate of about 80% was obtained for the eukaryote datasets. The fungus training dataset which lacks an enzyme class description was also used to evaluate the fungus candidate rules. A total of 88 out of 5085 test entries were matched with the fungus rule set. These were otherwise poorly annotated using their functional descriptions. Conclusion The feasibility of using the method presented here to classify enzyme classes based on the enzyme domain rules is evident. The rules may be also employed by the protein annotators in manual annotation or implemented in an automatic annotation flowchart. PMID:16776838

Mining a database of single amplified genomes from Red Sea brine pool extremophiles—improving reliability of gene function prediction using a profile and pattern matching algorithm (PPMA)

PubMed Central

Grötzinger, Stefan W.; Alam, Intikhab; Ba Alawi, Wail; Bajic, Vladimir B.; Stingl, Ulrich; Eppinger, Jörg

2014-01-01

Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs) and poor homology of novel extremophile's genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the Integrated Data Warehouse of Microbial Genomes (INDIGO) data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes) may translate into false positives when searching for specific functions. The Profile and Pattern Matching (PPM) strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO)-terms (which represent enzyme function profiles) and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern). The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2577 enzyme commission (E.C.) numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from six different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter) and PROSITE IDs (pattern filter). Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits) are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns) are present. Scripts for annotation, as well as for the PPM algorithm, are available through the INDIGO website. PMID:24778629

Linking microarray reporters with protein functions

PubMed Central

Gaj, Stan; van Erk, Arie; van Haaften, Rachel IM; Evelo, Chris TA

2007-01-01

Background The analysis of microarray experiments requires accurate and up-to-date functional annotation of the microarray reporters to optimize the interpretation of the biological processes involved. Pathway visualization tools are used to connect gene expression data with existing biological pathways by using specific database identifiers that link reporters with elements in the pathways. Results This paper proposes a novel method that aims to improve microarray reporter annotation by BLASTing the original reporter sequences against a species-specific EMBL subset, that was derived from and crosslinked back to the highly curated UniProt database. The resulting alignments were filtered using high quality alignment criteria and further compared with the outcome of a more traditional approach, where reporter sequences were BLASTed against EnsEMBL followed by locating the corresponding protein (UniProt) entry for the high quality hits. Combining the results of both methods resulted in successful annotation of > 58% of all reporter sequences with UniProt IDs on two commercial array platforms, increasing the amount of Incyte reporters that could be coupled to Gene Ontology terms from 32.7% to 58.3% and to a local GenMAPP pathway from 9.6% to 16.7%. For Agilent, 35.3% of the total reporters are now linked towards GO nodes and 7.1% on local pathways. Conclusion Our methods increased the annotation quality of microarray reporter sequences and allowed us to visualize more reporters using pathway visualization tools. Even in cases where the original reporter annotation showed the correct description the new identifiers often allowed improved pathway and Gene Ontology linking. These methods are freely available at http://www.bigcat.unimaas.nl/public/publications/Gaj_Annotation/. PMID:17897448

Family Support Services. A Review of the Literature and Selected Annotated Bibliography.

ERIC Educational Resources Information Center

Wolcott, Ilene

This document contains a literature review and annotated bibliography on family support services in Australia and overseas. Literature relating to services for families with dependent adolescent children as well as young children is included. The review and bibliography concentrate primarily on community-based services defined in the literature as…

TSSAR: TSS annotation regime for dRNA-seq data.

PubMed

Amman, Fabian; Wolfinger, Michael T; Lorenz, Ronny; Hofacker, Ivo L; Stadler, Peter F; Findeiß, Sven

2014-03-27

Differential RNA sequencing (dRNA-seq) is a high-throughput screening technique designed to examine the architecture of bacterial operons in general and the precise position of transcription start sites (TSS) in particular. Hitherto, dRNA-seq data were analyzed by visualizing the sequencing reads mapped to the reference genome and manually annotating reliable positions. This is very labor intensive and, due to the subjectivity, biased. Here, we present TSSAR, a tool for automated de novo TSS annotation from dRNA-seq data that respects the statistics of dRNA-seq libraries. TSSAR uses the premise that the number of sequencing reads starting at a certain genomic position within a transcriptional active region follows a Poisson distribution with a parameter that depends on the local strength of expression. The differences of two dRNA-seq library counts thus follow a Skellam distribution. This provides a statistical basis to identify significantly enriched primary transcripts.We assessed the performance by analyzing a publicly available dRNA-seq data set using TSSAR and two simple approaches that utilize user-defined score cutoffs. We evaluated the power of reproducing the manual TSS annotation. Furthermore, the same data set was used to reproduce 74 experimentally validated TSS in H. pylori from reliable techniques such as RACE or primer extension. Both analyses showed that TSSAR outperforms the static cutoff-dependent approaches. Having an automated and efficient tool for analyzing dRNA-seq data facilitates the use of the dRNA-seq technique and promotes its application to more sophisticated analysis. For instance, monitoring the plasticity and dynamics of the transcriptomal architecture triggered by different stimuli and growth conditions becomes possible.The main asset of a novel tool for dRNA-seq analysis that reaches out to a broad user community is usability. As such, we provide TSSAR both as intuitive RESTful Web service ( http://rna.tbi.univie.ac.at/TSSAR) together with a set of post-processing and analysis tools, as well as a stand-alone version for use in high-throughput dRNA-seq data analysis pipelines.

E-RNAi: a web application for the multi-species design of RNAi reagents—2010 update

PubMed Central

Horn, Thomas; Boutros, Michael

2010-01-01

The design of RNA interference (RNAi) reagents is an essential step for performing loss-of-function studies in many experimental systems. The availability of sequenced and annotated genomes greatly facilitates RNAi experiments in an increasing number of organisms that were previously not genetically tractable. The E-RNAi web-service, accessible at http://www.e-rnai.org/, provides a computational resource for the optimized design and evaluation of RNAi reagents. The 2010 update of E-RNAi now covers 12 genomes, including Drosophila, Caenorhabditis elegans, human, emerging model organisms such as Schmidtea mediterranea and Acyrthosiphon pisum, as well as the medically relevant vectors Anopheles gambiae and Aedes aegypti. The web service calculates RNAi reagents based on the input of target sequences, sequence identifiers or by visual selection of target regions through a genome browser interface. It identifies optimized RNAi target-sites by ranking sequences according to their predicted specificity, efficiency and complexity. E-RNAi also facilitates the design of secondary RNAi reagents for validation experiments, evaluation of pooled siRNA reagents and batch design. Results are presented online, as a downloadable HTML report and as tab-delimited files. PMID:20444868

Variation analysis and gene annotation of eight MHC haplotypes: The MHC Haplotype Project

PubMed Central

Horton, Roger; Gibson, Richard; Coggill, Penny; Miretti, Marcos; Allcock, Richard J.; Almeida, Jeff; Forbes, Simon; Gilbert, James G. R.; Halls, Karen; Harrow, Jennifer L.; Hart, Elizabeth; Howe, Kevin; Jackson, David K.; Palmer, Sophie; Roberts, Anne N.; Sims, Sarah; Stewart, C. Andrew; Traherne, James A.; Trevanion, Steve; Wilming, Laurens; Rogers, Jane; de Jong, Pieter J.; Elliott, John F.; Sawcer, Stephen; Todd, John A.; Trowsdale, John

2008-01-01

The human major histocompatibility complex (MHC) is contained within about 4 Mb on the short arm of chromosome 6 and is recognised as the most variable region in the human genome. The primary aim of the MHC Haplotype Project was to provide a comprehensively annotated reference sequence of a single, human leukocyte antigen-homozygous MHC haplotype and to use it as a basis against which variations could be assessed from seven other similarly homozygous cell lines, representative of the most common MHC haplotypes in the European population. Comparison of the haplotype sequences, including four haplotypes not previously analysed, resulted in the identification of >44,000 variations, both substitutions and indels (insertions and deletions), which have been submitted to the dbSNP database. The gene annotation uncovered haplotype-specific differences and confirmed the presence of more than 300 loci, including over 160 protein-coding genes. Combined analysis of the variation and annotation datasets revealed 122 gene loci with coding substitutions of which 97 were non-synonymous. The haplotype (A3-B7-DR15; PGF cell line) designated as the new MHC reference sequence, has been incorporated into the human genome assembly (NCBI35 and subsequent builds), and constitutes the largest single-haplotype sequence of the human genome to date. The extensive variation and annotation data derived from the analysis of seven further haplotypes have been made publicly available and provide a framework and resource for future association studies of all MHC-associated diseases and transplant medicine. PMID:18193213

TypeLoader: A fast and efficient automated workflow for the annotation and submission of novel full-length HLA alleles.

PubMed

Surendranath, V; Albrecht, V; Hayhurst, J D; Schöne, B; Robinson, J; Marsh, S G E; Schmidt, A H; Lange, V

2017-07-01

Recent years have seen a rapid increase in the discovery of novel allelic variants of the human leukocyte antigen (HLA) genes. Commonly, only the exons encoding the peptide binding domains of novel HLA alleles are submitted. As a result, the IPD-IMGT/HLA Database lacks sequence information outside those regions for the majority of known alleles. This has implications for the application of the new sequencing technologies, which deliver sequence data often covering the complete gene. As these technologies simplify the characterization of the complete gene regions, it is desirable for novel alleles to be submitted as full-length sequences to the database. However, the manual annotation of full-length alleles and the generation of specific formats required by the sequence repositories is prone to error and time consuming. We have developed TypeLoader to address both these facets. With only the full-length sequence as a starting point, Typeloader performs automatic sequence annotation and subsequently handles all steps involved in preparing the specific formats for submission with very little manual intervention. TypeLoader is routinely used at the DKMS Life Science Lab and has aided in the successful submission of more than 900 novel HLA alleles as full-length sequences to the European Nucleotide Archive repository and the IPD-IMGT/HLA Database with a 95% reduction in the time spent on annotation and submission when compared with handling these processes manually. TypeLoader is implemented as a web application and can be easily installed and used on a standalone Linux desktop system or within a Linux client/server architecture. TypeLoader is downloadable from http://www.github.com/DKMS-LSL/typeloader. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Sequencing and characterizing the genome of Estrella lausannensis as an undergraduate project: training students and biological insights.

PubMed

Bertelli, Claire; Aeby, Sébastien; Chassot, Bérénice; Clulow, James; Hilfiker, Olivier; Rappo, Samuel; Ritzmann, Sébastien; Schumacher, Paolo; Terrettaz, Céline; Benaglio, Paola; Falquet, Laurent; Farinelli, Laurent; Gharib, Walid H; Goesmann, Alexander; Harshman, Keith; Linke, Burkhard; Miyazaki, Ryo; Rivolta, Carlo; Robinson-Rechavi, Marc; van der Meer, Jan Roelof; Greub, Gilbert

2015-01-01

With the widespread availability of high-throughput sequencing technologies, sequencing projects have become pervasive in the molecular life sciences. The huge bulk of data generated daily must be analyzed further by biologists with skills in bioinformatics and by "embedded bioinformaticians," i.e., bioinformaticians integrated in wet lab research groups. Thus, students interested in molecular life sciences must be trained in the main steps of genomics: sequencing, assembly, annotation and analysis. To reach that goal, a practical course has been set up for master students at the University of Lausanne: the "Sequence a genome" class. At the beginning of the academic year, a few bacterial species whose genome is unknown are provided to the students, who sequence and assemble the genome(s) and perform manual annotation. Here, we report the progress of the first class from September 2010 to June 2011 and the results obtained by seven master students who specifically assembled and annotated the genome of Estrella lausannensis, an obligate intracellular bacterium related to Chlamydia. The draft genome of Estrella is composed of 29 scaffolds encompassing 2,819,825 bp that encode for 2233 putative proteins. Estrella also possesses a 9136 bp plasmid that encodes for 14 genes, among which we found an integrase and a toxin/antitoxin module. Like all other members of the Chlamydiales order, Estrella possesses a highly conserved type III secretion system, considered as a key virulence factor. The annotation of the Estrella genome also allowed the characterization of the metabolic abilities of this strictly intracellular bacterium. Altogether, the students provided the scientific community with the Estrella genome sequence and a preliminary understanding of the biology of this recently-discovered bacterial genus, while learning to use cutting-edge technologies for sequencing and to perform bioinformatics analyses.

Wheat EST resources for functional genomics of abiotic stress

PubMed Central

Houde, Mario; Belcaid, Mahdi; Ouellet, François; Danyluk, Jean; Monroy, Antonio F; Dryanova, Ani; Gulick, Patrick; Bergeron, Anne; Laroche, André; Links, Matthew G; MacCarthy, Luke; Crosby, William L; Sarhan, Fathey

2006-01-01

Background Wheat is an excellent species to study freezing tolerance and other abiotic stresses. However, the sequence of the wheat genome has not been completely characterized due to its complexity and large size. To circumvent this obstacle and identify genes involved in cold acclimation and associated stresses, a large scale EST sequencing approach was undertaken by the Functional Genomics of Abiotic Stress (FGAS) project. Results We generated 73,521 quality-filtered ESTs from eleven cDNA libraries constructed from wheat plants exposed to various abiotic stresses and at different developmental stages. In addition, 196,041 ESTs for which tracefiles were available from the National Science Foundation wheat EST sequencing program and DuPont were also quality-filtered and used in the analysis. Clustering of the combined ESTs with d2_cluster and TGICL yielded a few large clusters containing several thousand ESTs that were refractory to routine clustering techniques. To resolve this problem, the sequence proximity and "bridges" were identified by an e-value distance graph to manually break clusters into smaller groups. Assembly of the resolved ESTs generated a 75,488 unique sequence set (31,580 contigs and 43,908 singletons/singlets). Digital expression analyses indicated that the FGAS dataset is enriched in stress-regulated genes compared to the other public datasets. Over 43% of the unique sequence set was annotated and classified into functional categories according to Gene Ontology. Conclusion We have annotated 29,556 different sequences, an almost 5-fold increase in annotated sequences compared to the available wheat public databases. Digital expression analysis combined with gene annotation helped in the identification of several pathways associated with abiotic stress. The genomic resources and knowledge developed by this project will contribute to a better understanding of the different mechanisms that govern stress tolerance in wheat and other cereals. PMID:16772040

Rapid Identification of Sequences for Orphan Enzymes to Power Accurate Protein Annotation

PubMed Central

Ojha, Sunil; Watson, Douglas S.; Bomar, Martha G.; Galande, Amit K.; Shearer, Alexander G.

2013-01-01

The power of genome sequencing depends on the ability to understand what those genes and their proteins products actually do. The automated methods used to assign functions to putative proteins in newly sequenced organisms are limited by the size of our library of proteins with both known function and sequence. Unfortunately this library grows slowly, lagging well behind the rapid increase in novel protein sequences produced by modern genome sequencing methods. One potential source for rapidly expanding this functional library is the “back catalog” of enzymology – “orphan enzymes,” those enzymes that have been characterized and yet lack any associated sequence. There are hundreds of orphan enzymes in the Enzyme Commission (EC) database alone. In this study, we demonstrate how this orphan enzyme “back catalog” is a fertile source for rapidly advancing the state of protein annotation. Starting from three orphan enzyme samples, we applied mass-spectrometry based analysis and computational methods (including sequence similarity networks, sequence and structural alignments, and operon context analysis) to rapidly identify the specific sequence for each orphan while avoiding the most time- and labor-intensive aspects of typical sequence identifications. We then used these three new sequences to more accurately predict the catalytic function of 385 previously uncharacterized or misannotated proteins. We expect that this kind of rapid sequence identification could be efficiently applied on a larger scale to make enzymology’s “back catalog” another powerful tool to drive accurate genome annotation. PMID:24386392

Rapid identification of sequences for orphan enzymes to power accurate protein annotation.

PubMed

Ramkissoon, Kevin R; Miller, Jennifer K; Ojha, Sunil; Watson, Douglas S; Bomar, Martha G; Galande, Amit K; Shearer, Alexander G

2013-01-01

The power of genome sequencing depends on the ability to understand what those genes and their proteins products actually do. The automated methods used to assign functions to putative proteins in newly sequenced organisms are limited by the size of our library of proteins with both known function and sequence. Unfortunately this library grows slowly, lagging well behind the rapid increase in novel protein sequences produced by modern genome sequencing methods. One potential source for rapidly expanding this functional library is the "back catalog" of enzymology--"orphan enzymes," those enzymes that have been characterized and yet lack any associated sequence. There are hundreds of orphan enzymes in the Enzyme Commission (EC) database alone. In this study, we demonstrate how this orphan enzyme "back catalog" is a fertile source for rapidly advancing the state of protein annotation. Starting from three orphan enzyme samples, we applied mass-spectrometry based analysis and computational methods (including sequence similarity networks, sequence and structural alignments, and operon context analysis) to rapidly identify the specific sequence for each orphan while avoiding the most time- and labor-intensive aspects of typical sequence identifications. We then used these three new sequences to more accurately predict the catalytic function of 385 previously uncharacterized or misannotated proteins. We expect that this kind of rapid sequence identification could be efficiently applied on a larger scale to make enzymology's "back catalog" another powerful tool to drive accurate genome annotation.

Genome Wide Re-Annotation of Caldicellulosiruptor saccharolyticus with New Insights into Genes Involved in Biomass Degradation and Hydrogen Production

PubMed Central

Chowdhary, Nupoor; Selvaraj, Ashok; KrishnaKumaar, Lakshmi; Kumar, Gopal Ramesh

2015-01-01

Caldicellulosiruptor saccharolyticus has proven itself to be an excellent candidate for biological hydrogen (H2) production, but still it has major drawbacks like sensitivity to high osmotic pressure and low volumetric H2 productivity, which should be considered before it can be used industrially. A whole genome re-annotation work has been carried out as an attempt to update the incomplete genome information that causes gap in the knowledge especially in the area of metabolic engineering, to improve the H2 producing capabilities of C. saccharolyticus. Whole genome re-annotation was performed through manual means for 2,682 Coding Sequences (CDSs). Bioinformatics tools based on sequence similarity, motif search, phylogenetic analysis and fold recognition were employed for re-annotation. Our methodology could successfully add functions for 409 hypothetical proteins (HPs), 46 proteins previously annotated as putative and assigned more accurate functions for the known protein sequences. Homology based gene annotation has been used as a standard method for assigning function to novel proteins, but over the past few years many non-homology based methods such as genomic context approaches for protein function prediction have been developed. Using non-homology based functional prediction methods, we were able to assign cellular processes or physical complexes for 249 hypothetical sequences. Our re-annotation pipeline highlights the addition of 231 new CDSs generated from MicroScope Platform, to the original genome with functional prediction for 49 of them. The re-annotation of HPs and new CDSs is stored in the relational database that is available on the MicroScope web-based platform. In parallel, a comparative genome analyses were performed among the members of genus Caldicellulosiruptor to understand the function and evolutionary processes. Further, with results from integrated re-annotation studies (homology and genomic context approach), we strongly suggest that Csac_0437 and Csac_0424 encode for glycoside hydrolases (GH) and are proposed to be involved in the decomposition of recalcitrant plant polysaccharides. Similarly, HPs: Csac_0732, Csac_1862, Csac_1294 and Csac_0668 are suggested to play a significant role in biohydrogen production. Function prediction of these HPs by using our integrated approach will considerably enhance the interpretation of large-scale experiments targeting this industrially important organism. PMID:26196387

Genome Wide Re-Annotation of Caldicellulosiruptor saccharolyticus with New Insights into Genes Involved in Biomass Degradation and Hydrogen Production.

PubMed

Chowdhary, Nupoor; Selvaraj, Ashok; KrishnaKumaar, Lakshmi; Kumar, Gopal Ramesh

2015-01-01

Caldicellulosiruptor saccharolyticus has proven itself to be an excellent candidate for biological hydrogen (H2) production, but still it has major drawbacks like sensitivity to high osmotic pressure and low volumetric H2 productivity, which should be considered before it can be used industrially. A whole genome re-annotation work has been carried out as an attempt to update the incomplete genome information that causes gap in the knowledge especially in the area of metabolic engineering, to improve the H2 producing capabilities of C. saccharolyticus. Whole genome re-annotation was performed through manual means for 2,682 Coding Sequences (CDSs). Bioinformatics tools based on sequence similarity, motif search, phylogenetic analysis and fold recognition were employed for re-annotation. Our methodology could successfully add functions for 409 hypothetical proteins (HPs), 46 proteins previously annotated as putative and assigned more accurate functions for the known protein sequences. Homology based gene annotation has been used as a standard method for assigning function to novel proteins, but over the past few years many non-homology based methods such as genomic context approaches for protein function prediction have been developed. Using non-homology based functional prediction methods, we were able to assign cellular processes or physical complexes for 249 hypothetical sequences. Our re-annotation pipeline highlights the addition of 231 new CDSs generated from MicroScope Platform, to the original genome with functional prediction for 49 of them. The re-annotation of HPs and new CDSs is stored in the relational database that is available on the MicroScope web-based platform. In parallel, a comparative genome analyses were performed among the members of genus Caldicellulosiruptor to understand the function and evolutionary processes. Further, with results from integrated re-annotation studies (homology and genomic context approach), we strongly suggest that Csac_0437 and Csac_0424 encode for glycoside hydrolases (GH) and are proposed to be involved in the decomposition of recalcitrant plant polysaccharides. Similarly, HPs: Csac_0732, Csac_1862, Csac_1294 and Csac_0668 are suggested to play a significant role in biohydrogen production. Function prediction of these HPs by using our integrated approach will considerably enhance the interpretation of large-scale experiments targeting this industrially important organism.

Structural and functional annotation of the porcine immunome

PubMed Central

2013-01-01

Background The domestic pig is known as an excellent model for human immunology and the two species share many pathogens. Susceptibility to infectious disease is one of the major constraints on swine performance, yet the structure and function of genes comprising the pig immunome are not well-characterized. The completion of the pig genome provides the opportunity to annotate the pig immunome, and compare and contrast pig and human immune systems. Results The Immune Response Annotation Group (IRAG) used computational curation and manual annotation of the swine genome assembly 10.2 (Sscrofa10.2) to refine the currently available automated annotation of 1,369 immunity-related genes through sequence-based comparison to genes in other species. Within these genes, we annotated 3,472 transcripts. Annotation provided evidence for gene expansions in several immune response families, and identified artiodactyl-specific expansions in the cathelicidin and type 1 Interferon families. We found gene duplications for 18 genes, including 13 immune response genes and five non-immune response genes discovered in the annotation process. Manual annotation provided evidence for many new alternative splice variants and 8 gene duplications. Over 1,100 transcripts without porcine sequence evidence were detected using cross-species annotation. We used a functional approach to discover and accurately annotate porcine immune response genes. A co-expression clustering analysis of transcriptomic data from selected experimental infections or immune stimulations of blood, macrophages or lymph nodes identified a large cluster of genes that exhibited a correlated positive response upon infection across multiple pathogens or immune stimuli. Interestingly, this gene cluster (cluster 4) is enriched for known general human immune response genes, yet contains many un-annotated porcine genes. A phylogenetic analysis of the encoded proteins of cluster 4 genes showed that 15% exhibited an accelerated evolution as compared to 4.1% across the entire genome. Conclusions This extensive annotation dramatically extends the genome-based knowledge of the molecular genetics and structure of a major portion of the porcine immunome. Our complementary functional approach using co-expression during immune response has provided new putative immune response annotation for over 500 porcine genes. Our phylogenetic analysis of this core immunome cluster confirms rapid evolutionary change in this set of genes, and that, as in other species, such genes are important components of the pig’s adaptation to pathogen challenge over evolutionary time. These comprehensive and integrated analyses increase the value of the porcine genome sequence and provide important tools for global analyses and data-mining of the porcine immune response. PMID:23676093

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

Evaluations of Firms and Professionals Who Provide Consumer Services. An Annotated Bibliography of Consumer Services.

ERIC Educational Resources Information Center

Jackson, Gregg B.; Meyer, Francine H.

This annotated bibliography contains summaries of studies of consumer services in 39 fields, plus summaries of publications of interest to consumer advocates, published during the past 10 years. Since most service providers do business in a single locale, the evaluations are usually local in scope (for example, a comparison of major appliance…

Comparison of methods for library construction and short read annotation of shellfish viral metagenomes.

PubMed

Wei, Hong-Ying; Huang, Sheng; Wang, Jiang-Yong; Gao, Fang; Jiang, Jing-Zhe

2018-03-01

The emergence and widespread use of high-throughput sequencing technologies have promoted metagenomic studies on environmental or animal samples. Library construction for metagenome sequencing and annotation of the produced sequence reads are important steps in such studies and influence the quality of metagenomic data. In this study, we collected some marine mollusk samples, such as Crassostrea hongkongensis, Chlamys farreri, and Ruditapes philippinarum, from coastal areas in South China. These samples were divided into two batches to compare two library construction methods for shellfish viral metagenome. Our analysis showed that reverse-transcribing RNA into cDNA and then amplifying it simultaneously with DNA by whole genome amplification (WGA) yielded a larger amount of DNA compared to using only WGA or WTA (whole transcriptome amplification). Moreover, higher quality libraries were obtained by agarose gel extraction rather than with AMPure bead size selection. However, the latter can also provide good results if combined with the adjustment of the filter parameters. This, together with its simplicity, makes it a viable alternative. Finally, we compared three annotation tools (BLAST, DIAMOND, and Taxonomer) and two reference databases (NCBI's NR and Uniprot's Uniref). Considering the limitations of computing resources and data transfer speed, we propose the use of DIAMOND with Uniref for annotating metagenomic short reads as its running speed can guarantee a good annotation rate. This study may serve as a useful reference for selecting methods for Shellfish viral metagenome library construction and read annotation.

A Factor Graph Approach to Automated GO Annotation

PubMed Central

Spetale, Flavio E.; Tapia, Elizabeth; Krsticevic, Flavia; Roda, Fernando; Bulacio, Pilar

2016-01-01

As volume of genomic data grows, computational methods become essential for providing a first glimpse onto gene annotations. Automated Gene Ontology (GO) annotation methods based on hierarchical ensemble classification techniques are particularly interesting when interpretability of annotation results is a main concern. In these methods, raw GO-term predictions computed by base binary classifiers are leveraged by checking the consistency of predefined GO relationships. Both formal leveraging strategies, with main focus on annotation precision, and heuristic alternatives, with main focus on scalability issues, have been described in literature. In this contribution, a factor graph approach to the hierarchical ensemble formulation of the automated GO annotation problem is presented. In this formal framework, a core factor graph is first built based on the GO structure and then enriched to take into account the noisy nature of GO-term predictions. Hence, starting from raw GO-term predictions, an iterative message passing algorithm between nodes of the factor graph is used to compute marginal probabilities of target GO-terms. Evaluations on Saccharomyces cerevisiae, Arabidopsis thaliana and Drosophila melanogaster protein sequences from the GO Molecular Function domain showed significant improvements over competing approaches, even when protein sequences were naively characterized by their physicochemical and secondary structure properties or when loose noisy annotation datasets were considered. Based on these promising results and using Arabidopsis thaliana annotation data, we extend our approach to the identification of most promising molecular function annotations for a set of proteins of unknown function in Solanum lycopersicum. PMID:26771463

A Factor Graph Approach to Automated GO Annotation.

PubMed

Spetale, Flavio E; Tapia, Elizabeth; Krsticevic, Flavia; Roda, Fernando; Bulacio, Pilar

2016-01-01

As volume of genomic data grows, computational methods become essential for providing a first glimpse onto gene annotations. Automated Gene Ontology (GO) annotation methods based on hierarchical ensemble classification techniques are particularly interesting when interpretability of annotation results is a main concern. In these methods, raw GO-term predictions computed by base binary classifiers are leveraged by checking the consistency of predefined GO relationships. Both formal leveraging strategies, with main focus on annotation precision, and heuristic alternatives, with main focus on scalability issues, have been described in literature. In this contribution, a factor graph approach to the hierarchical ensemble formulation of the automated GO annotation problem is presented. In this formal framework, a core factor graph is first built based on the GO structure and then enriched to take into account the noisy nature of GO-term predictions. Hence, starting from raw GO-term predictions, an iterative message passing algorithm between nodes of the factor graph is used to compute marginal probabilities of target GO-terms. Evaluations on Saccharomyces cerevisiae, Arabidopsis thaliana and Drosophila melanogaster protein sequences from the GO Molecular Function domain showed significant improvements over competing approaches, even when protein sequences were naively characterized by their physicochemical and secondary structure properties or when loose noisy annotation datasets were considered. Based on these promising results and using Arabidopsis thaliana annotation data, we extend our approach to the identification of most promising molecular function annotations for a set of proteins of unknown function in Solanum lycopersicum.

A manually annotated Actinidia chinensis var. chinensis (kiwifruit) genome highlights the challenges associated with draft genomes and gene prediction in plants.

PubMed

Pilkington, Sarah M; Crowhurst, Ross; Hilario, Elena; Nardozza, Simona; Fraser, Lena; Peng, Yongyan; Gunaseelan, Kularajathevan; Simpson, Robert; Tahir, Jibran; Deroles, Simon C; Templeton, Kerry; Luo, Zhiwei; Davy, Marcus; Cheng, Canhong; McNeilage, Mark; Scaglione, Davide; Liu, Yifei; Zhang, Qiong; Datson, Paul; De Silva, Nihal; Gardiner, Susan E; Bassett, Heather; Chagné, David; McCallum, John; Dzierzon, Helge; Deng, Cecilia; Wang, Yen-Yi; Barron, Lorna; Manako, Kelvina; Bowen, Judith; Foster, Toshi M; Erridge, Zoe A; Tiffin, Heather; Waite, Chethi N; Davies, Kevin M; Grierson, Ella P; Laing, William A; Kirk, Rebecca; Chen, Xiuyin; Wood, Marion; Montefiori, Mirco; Brummell, David A; Schwinn, Kathy E; Catanach, Andrew; Fullerton, Christina; Li, Dawei; Meiyalaghan, Sathiyamoorthy; Nieuwenhuizen, Niels; Read, Nicola; Prakash, Roneel; Hunter, Don; Zhang, Huaibi; McKenzie, Marian; Knäbel, Mareike; Harris, Alastair; Allan, Andrew C; Gleave, Andrew; Chen, Angela; Janssen, Bart J; Plunkett, Blue; Ampomah-Dwamena, Charles; Voogd, Charlotte; Leif, Davin; Lafferty, Declan; Souleyre, Edwige J F; Varkonyi-Gasic, Erika; Gambi, Francesco; Hanley, Jenny; Yao, Jia-Long; Cheung, Joey; David, Karine M; Warren, Ben; Marsh, Ken; Snowden, Kimberley C; Lin-Wang, Kui; Brian, Lara; Martinez-Sanchez, Marcela; Wang, Mindy; Ileperuma, Nadeesha; Macnee, Nikolai; Campin, Robert; McAtee, Peter; Drummond, Revel S M; Espley, Richard V; Ireland, Hilary S; Wu, Rongmei; Atkinson, Ross G; Karunairetnam, Sakuntala; Bulley, Sean; Chunkath, Shayhan; Hanley, Zac; Storey, Roy; Thrimawithana, Amali H; Thomson, Susan; David, Charles; Testolin, Raffaele; Huang, Hongwen; Hellens, Roger P; Schaffer, Robert J

2018-04-16

Most published genome sequences are drafts, and most are dominated by computational gene prediction. Draft genomes typically incorporate considerable sequence data that are not assigned to chromosomes, and predicted genes without quality confidence measures. The current Actinidia chinensis (kiwifruit) 'Hongyang' draft genome has 164 Mb of sequences unassigned to pseudo-chromosomes, and omissions have been identified in the gene models. A second genome of an A. chinensis (genotype Red5) was fully sequenced. This new sequence resulted in a 554.0 Mb assembly with all but 6 Mb assigned to pseudo-chromosomes. Pseudo-chromosomal comparisons showed a considerable number of translocation events have occurred following a whole genome duplication (WGD) event some consistent with centromeric Robertsonian-like translocations. RNA sequencing data from 12 tissues and ab initio analysis informed a genome-wide manual annotation, using the WebApollo tool. In total, 33,044 gene loci represented by 33,123 isoforms were identified, named and tagged for quality of evidential support. Of these 3114 (9.4%) were identical to a protein within 'Hongyang' The Kiwifruit Information Resource (KIR v2). Some proportion of the differences will be varietal polymorphisms. However, as most computationally predicted Red5 models required manual re-annotation this proportion is expected to be small. The quality of the new gene models was tested by fully sequencing 550 cloned 'Hort16A' cDNAs and comparing with the predicted protein models for Red5 and both the original 'Hongyang' assembly and the revised annotation from KIR v2. Only 48.9% and 63.5% of the cDNAs had a match with 90% identity or better to the original and revised 'Hongyang' annotation, respectively, compared with 90.9% to the Red5 models. Our study highlights the need to take a cautious approach to draft genomes and computationally predicted genes. Our use of the manual annotation tool WebApollo facilitated manual checking and correction of gene models enabling improvement of computational prediction. This utility was especially relevant for certain types of gene families such as the EXPANSIN like genes. Finally, this high quality gene set will supply the kiwifruit and general plant community with a new tool for genomics and other comparative analysis.

MACARON: A python framework to identify and re-annotate multi-base affected codons in whole genome/exome sequence data.

PubMed

Khan, Waqasuddin; Saripella, Ganapathi Varma-; Ludwig, Thomas; Cuppens, Tania; Thibord, Florian; Génin, Emmanuelle; Deleuze, Jean-Francois; Trégouët, David-Alexandre

2018-05-03

Predicted deleteriousness of coding variants is a frequently used criterion to filter out variants detected in next-generation sequencing projects and to select candidates impacting on the risk of human diseases. Most available dedicated tools implement a base-to-base annotation approach that could be biased in presence of several variants in the same genetic codon. We here proposed the MACARON program that, from a standard VCF file, identifies, re-annotates and predicts the amino acid change resulting from multiple single nucleotide variants (SNVs) within the same genetic codon. Applied to the whole exome dataset of 573 individuals, MACARON identifies 114 situations where multiple SNVs within a genetic codon induce an amino acid change that is different from those predicted by standard single SNV annotation tool. Such events are not uncommon and deserve to be studied in sequencing projects with inconclusive findings. MACARON is written in python with codes available on the GENMED website (www.genmed.fr). david-alexandre.tregouet@inserm.fr. Supplementary data are available at Bioinformatics online.

T3SEdb: data warehousing of virulence effectors secreted by the bacterial Type III Secretion System.

PubMed

Tay, Daniel Ming Ming; Govindarajan, Kunde Ramamoorthy; Khan, Asif M; Ong, Terenze Yao Rui; Samad, Hanif M; Soh, Wei Wei; Tong, Minyan; Zhang, Fan; Tan, Tin Wee

2010-10-15

Effectors of Type III Secretion System (T3SS) play a pivotal role in establishing and maintaining pathogenicity in the host and therefore the identification of these effectors is important in understanding virulence. However, the effectors display high level of sequence diversity, therefore making the identification a difficult process. There is a need to collate and annotate existing effector sequences in public databases to enable systematic analyses of these sequences for development of models for screening and selection of putative novel effectors from bacterial genomes that can be validated by a smaller number of key experiments. Herein, we present T3SEdb http://effectors.bic.nus.edu.sg/T3SEdb, a specialized database of annotated T3SS effector (T3SE) sequences containing 1089 records from 46 bacterial species compiled from the literature and public protein databases. Procedures have been defined for i) comprehensive annotation of experimental status of effectors, ii) submission and curation review of records by users of the database, and iii) the regular update of T3SEdb existing and new records. Keyword fielded and sequence searches (BLAST, regular expression) are supported for both experimentally verified and hypothetical T3SEs. More than 171 clusters of T3SEs were detected based on sequence identity comparisons (intra-cluster difference up to ~60%). Owing to this high level of sequence diversity of T3SEs, the T3SEdb provides a large number of experimentally known effector sequences with wide species representation for creation of effector predictors. We created a reliable effector prediction tool, integrated into the database, to demonstrate the application of the database for such endeavours. T3SEdb is the first specialised database reported for T3SS effectors, enriched with manual annotations that facilitated systematic construction of a reliable prediction model for identification of novel effectors. The T3SEdb represents a platform for inclusion of additional annotations of metadata for future developments of sophisticated effector prediction models for screening and selection of putative novel effectors from bacterial genomes/proteomes that can be validated by a small number of key experiments.

Genome Annotation Generator: a simple tool for generating and correcting WGS annotation tables for NCBI submission.

PubMed

Geib, Scott M; Hall, Brian; Derego, Theodore; Bremer, Forest T; Cannoles, Kyle; Sim, Sheina B

2018-04-01

One of the most overlooked, yet critical, components of a whole genome sequencing (WGS) project is the submission and curation of the data to a genomic repository, most commonly the National Center for Biotechnology Information (NCBI). While large genome centers or genome groups have developed software tools for post-annotation assembly filtering, annotation, and conversion into the NCBI's annotation table format, these tools typically require back-end setup and connection to an Structured Query Language (SQL) database and/or some knowledge of programming (Perl, Python) to implement. With WGS becoming commonplace, genome sequencing projects are moving away from the genome centers and into the ecology or biology lab, where fewer resources are present to support the process of genome assembly curation. To fill this gap, we developed software to assess, filter, and transfer annotation and convert a draft genome assembly and annotation set into the NCBI annotation table (.tbl) format, facilitating submission to the NCBI Genome Assembly database. This software has no dependencies, is compatible across platforms, and utilizes a simple command to perform a variety of simple and complex post-analysis, pre-NCBI submission WGS project tasks. The Genome Annotation Generator is a consistent and user-friendly bioinformatics tool that can be used to generate a .tbl file that is consistent with the NCBI submission pipeline. The Genome Annotation Generator achieves the goal of providing a publicly available tool that will facilitate the submission of annotated genome assemblies to the NCBI. It is useful for any individual researcher or research group that wishes to submit a genome assembly of their study system to the NCBI.

Genome Annotation Generator: a simple tool for generating and correcting WGS annotation tables for NCBI submission

PubMed Central

Hall, Brian; Derego, Theodore; Bremer, Forest T; Cannoles, Kyle

2018-01-01

Abstract Background One of the most overlooked, yet critical, components of a whole genome sequencing (WGS) project is the submission and curation of the data to a genomic repository, most commonly the National Center for Biotechnology Information (NCBI). While large genome centers or genome groups have developed software tools for post-annotation assembly filtering, annotation, and conversion into the NCBI’s annotation table format, these tools typically require back-end setup and connection to an Structured Query Language (SQL) database and/or some knowledge of programming (Perl, Python) to implement. With WGS becoming commonplace, genome sequencing projects are moving away from the genome centers and into the ecology or biology lab, where fewer resources are present to support the process of genome assembly curation. To fill this gap, we developed software to assess, filter, and transfer annotation and convert a draft genome assembly and annotation set into the NCBI annotation table (.tbl) format, facilitating submission to the NCBI Genome Assembly database. This software has no dependencies, is compatible across platforms, and utilizes a simple command to perform a variety of simple and complex post-analysis, pre-NCBI submission WGS project tasks. Findings The Genome Annotation Generator is a consistent and user-friendly bioinformatics tool that can be used to generate a .tbl file that is consistent with the NCBI submission pipeline Conclusions The Genome Annotation Generator achieves the goal of providing a publicly available tool that will facilitate the submission of annotated genome assemblies to the NCBI. It is useful for any individual researcher or research group that wishes to submit a genome assembly of their study system to the NCBI. PMID:29635297

The Comprehensive Phytopathogen Genomics Resource: a web-based resource for data-mining plant pathogen genomes.

PubMed

Hamilton, John P; Neeno-Eckwall, Eric C; Adhikari, Bishwo N; Perna, Nicole T; Tisserat, Ned; Leach, Jan E; Lévesque, C André; Buell, C Robin

2011-01-01

The Comprehensive Phytopathogen Genomics Resource (CPGR) provides a web-based portal for plant pathologists and diagnosticians to view the genome and trancriptome sequence status of 806 bacterial, fungal, oomycete, nematode, viral and viroid plant pathogens. Tools are available to search and analyze annotated genome sequences of 74 bacterial, fungal and oomycete pathogens. Oomycete and fungal genomes are obtained directly from GenBank, whereas bacterial genome sequences are downloaded from the A Systematic Annotation Package (ASAP) database that provides curation of genomes using comparative approaches. Curated lists of bacterial genes relevant to pathogenicity and avirulence are also provided. The Plant Pathogen Transcript Assemblies Database provides annotated assemblies of the transcribed regions of 82 eukaryotic genomes from publicly available single pass Expressed Sequence Tags. Data-mining tools are provided along with tools to create candidate diagnostic markers, an emerging use for genomic sequence data in plant pathology. The Plant Pathogen Ribosomal DNA (rDNA) database is a resource for pathogens that lack genome or transcriptome data sets and contains 131 755 rDNA sequences from GenBank for 17 613 species identified as plant pathogens and related genera. Database URL: http://cpgr.plantbiology.msu.edu.

Proteogenomics produces comprehensive and highly accurate protein-coding gene annotation in a complete genome assembly of Malassezia sympodialis

PubMed Central

Tellgren-Roth, Christian; Baudo, Charles D.; Kennell, John C.; Sun, Sheng; Billmyre, R. Blake; Schröder, Markus S.; Andersson, Anna; Holm, Tina; Sigurgeirsson, Benjamin; Wu, Guangxi; Sankaranarayanan, Sundar Ram; Siddharthan, Rahul; Sanyal, Kaustuv; Lundeberg, Joakim; Nystedt, Björn; Boekhout, Teun; Dawson, Thomas L.; Heitman, Joseph

2017-01-01

Abstract Complete and accurate genome assembly and annotation is a crucial foundation for comparative and functional genomics. Despite this, few complete eukaryotic genomes are available, and genome annotation remains a major challenge. Here, we present a complete genome assembly of the skin commensal yeast Malassezia sympodialis and demonstrate how proteogenomics can substantially improve gene annotation. Through long-read DNA sequencing, we obtained a gap-free genome assembly for M. sympodialis (ATCC 42132), comprising eight nuclear and one mitochondrial chromosome. We also sequenced and assembled four M. sympodialis clinical isolates, and showed their value for understanding Malassezia reproduction by confirming four alternative allele combinations at the two mating-type loci. Importantly, we demonstrated how proteomics data could be readily integrated with transcriptomics data in standard annotation tools. This increased the number of annotated protein-coding genes by 14% (from 3612 to 4113), compared to using transcriptomics evidence alone. Manual curation further increased the number of protein-coding genes by 9% (to 4493). All of these genes have RNA-seq evidence and 87% were confirmed by proteomics. The M. sympodialis genome assembly and annotation presented here is at a quality yet achieved only for a few eukaryotic organisms, and constitutes an important reference for future host-microbe interaction studies. PMID:28100699

Exploring the dark foldable proteome by considering hydrophobic amino acids topology

PubMed Central

Bitard-Feildel, Tristan; Callebaut, Isabelle

2017-01-01

The protein universe corresponds to the set of all proteins found in all organisms. A way to explore it is by taking into account the domain content of the proteins. However, some part of sequences and many entire sequences remain un-annotated despite a converging number of domain families. The un-annotated part of the protein universe is referred to as the dark proteome and remains poorly characterized. In this study, we quantify the amount of foldable domains within the dark proteome by using the hydrophobic cluster analysis methodology. These un-annotated foldable domains were grouped using a combination of remote homology searches and domain annotations, leading to define different levels of darkness. The dark foldable domains were analyzed to understand what make them different from domains stored in databases and thus difficult to annotate. The un-annotated domains of the dark proteome universe display specific features relative to database domains: shorter length, non-canonical content and particular topology in hydrophobic residues, higher propensity for disorder, and a higher energy. These features make them hard to relate to known families. Based on these observations, we emphasize that domain annotation methodologies can still be improved to fully apprehend and decipher the molecular evolution of the protein universe. PMID:28134276

DDBJ read annotation pipeline: a cloud computing-based pipeline for high-throughput analysis of next-generation sequencing data.

PubMed

Nagasaki, Hideki; Mochizuki, Takako; Kodama, Yuichi; Saruhashi, Satoshi; Morizaki, Shota; Sugawara, Hideaki; Ohyanagi, Hajime; Kurata, Nori; Okubo, Kousaku; Takagi, Toshihisa; Kaminuma, Eli; Nakamura, Yasukazu

2013-08-01

High-performance next-generation sequencing (NGS) technologies are advancing genomics and molecular biological research. However, the immense amount of sequence data requires computational skills and suitable hardware resources that are a challenge to molecular biologists. The DNA Data Bank of Japan (DDBJ) of the National Institute of Genetics (NIG) has initiated a cloud computing-based analytical pipeline, the DDBJ Read Annotation Pipeline (DDBJ Pipeline), for a high-throughput annotation of NGS reads. The DDBJ Pipeline offers a user-friendly graphical web interface and processes massive NGS datasets using decentralized processing by NIG supercomputers currently free of charge. The proposed pipeline consists of two analysis components: basic analysis for reference genome mapping and de novo assembly and subsequent high-level analysis of structural and functional annotations. Users may smoothly switch between the two components in the pipeline, facilitating web-based operations on a supercomputer for high-throughput data analysis. Moreover, public NGS reads of the DDBJ Sequence Read Archive located on the same supercomputer can be imported into the pipeline through the input of only an accession number. This proposed pipeline will facilitate research by utilizing unified analytical workflows applied to the NGS data. The DDBJ Pipeline is accessible at http://p.ddbj.nig.ac.jp/.

Large-scale identification and characterization of alternative splicing variants of human gene transcripts using 56 419 completely sequenced and manually annotated full-length cDNAs

PubMed Central

Takeda, Jun-ichi; Suzuki, Yutaka; Nakao, Mitsuteru; Barrero, Roberto A.; Koyanagi, Kanako O.; Jin, Lihua; Motono, Chie; Hata, Hiroko; Isogai, Takao; Nagai, Keiichi; Otsuki, Tetsuji; Kuryshev, Vladimir; Shionyu, Masafumi; Yura, Kei; Go, Mitiko; Thierry-Mieg, Jean; Thierry-Mieg, Danielle; Wiemann, Stefan; Nomura, Nobuo; Sugano, Sumio; Gojobori, Takashi; Imanishi, Tadashi

2006-01-01

We report the first genome-wide identification and characterization of alternative splicing in human gene transcripts based on analysis of the full-length cDNAs. Applying both manual and computational analyses for 56 419 completely sequenced and precisely annotated full-length cDNAs selected for the H-Invitational human transcriptome annotation meetings, we identified 6877 alternative splicing genes with 18 297 different alternative splicing variants. A total of 37 670 exons were involved in these alternative splicing events. The encoded protein sequences were affected in 6005 of the 6877 genes. Notably, alternative splicing affected protein motifs in 3015 genes, subcellular localizations in 2982 genes and transmembrane domains in 1348 genes. We also identified interesting patterns of alternative splicing, in which two distinct genes seemed to be bridged, nested or having overlapping protein coding sequences (CDSs) of different reading frames (multiple CDS). In these cases, completely unrelated proteins are encoded by a single locus. Genome-wide annotations of alternative splicing, relying on full-length cDNAs, should lay firm groundwork for exploring in detail the diversification of protein function, which is mediated by the fast expanding universe of alternative splicing variants. PMID:16914452

DDBJ Read Annotation Pipeline: A Cloud Computing-Based Pipeline for High-Throughput Analysis of Next-Generation Sequencing Data

PubMed Central

Nagasaki, Hideki; Mochizuki, Takako; Kodama, Yuichi; Saruhashi, Satoshi; Morizaki, Shota; Sugawara, Hideaki; Ohyanagi, Hajime; Kurata, Nori; Okubo, Kousaku; Takagi, Toshihisa; Kaminuma, Eli; Nakamura, Yasukazu

2013-01-01

High-performance next-generation sequencing (NGS) technologies are advancing genomics and molecular biological research. However, the immense amount of sequence data requires computational skills and suitable hardware resources that are a challenge to molecular biologists. The DNA Data Bank of Japan (DDBJ) of the National Institute of Genetics (NIG) has initiated a cloud computing-based analytical pipeline, the DDBJ Read Annotation Pipeline (DDBJ Pipeline), for a high-throughput annotation of NGS reads. The DDBJ Pipeline offers a user-friendly graphical web interface and processes massive NGS datasets using decentralized processing by NIG supercomputers currently free of charge. The proposed pipeline consists of two analysis components: basic analysis for reference genome mapping and de novo assembly and subsequent high-level analysis of structural and functional annotations. Users may smoothly switch between the two components in the pipeline, facilitating web-based operations on a supercomputer for high-throughput data analysis. Moreover, public NGS reads of the DDBJ Sequence Read Archive located on the same supercomputer can be imported into the pipeline through the input of only an accession number. This proposed pipeline will facilitate research by utilizing unified analytical workflows applied to the NGS data. The DDBJ Pipeline is accessible at http://p.ddbj.nig.ac.jp/. PMID:23657089

bpRNA: large-scale automated annotation and analysis of RNA secondary structure.

PubMed

Danaee, Padideh; Rouches, Mason; Wiley, Michelle; Deng, Dezhong; Huang, Liang; Hendrix, David

2018-05-09

While RNA secondary structure prediction from sequence data has made remarkable progress, there is a need for improved strategies for annotating the features of RNA secondary structures. Here, we present bpRNA, a novel annotation tool capable of parsing RNA structures, including complex pseudoknot-containing RNAs, to yield an objective, precise, compact, unambiguous, easily-interpretable description of all loops, stems, and pseudoknots, along with the positions, sequence, and flanking base pairs of each such structural feature. We also introduce several new informative representations of RNA structure types to improve structure visualization and interpretation. We have further used bpRNA to generate a web-accessible meta-database, 'bpRNA-1m', of over 100 000 single-molecule, known secondary structures; this is both more fully and accurately annotated and over 20-times larger than existing databases. We use a subset of the database with highly similar (≥90% identical) sequences filtered out to report on statistical trends in sequence, flanking base pairs, and length. Both the bpRNA method and the bpRNA-1m database will be valuable resources both for specific analysis of individual RNA molecules and large-scale analyses such as are useful for updating RNA energy parameters for computational thermodynamic predictions, improving machine learning models for structure prediction, and for benchmarking structure-prediction algorithms.

EST Express: PHP/MySQL based automated annotation of ESTs from expression libraries

PubMed Central

Smith, Robin P; Buchser, William J; Lemmon, Marcus B; Pardinas, Jose R; Bixby, John L; Lemmon, Vance P

2008-01-01

Background Several biological techniques result in the acquisition of functional sets of cDNAs that must be sequenced and analyzed. The emergence of redundant databases such as UniGene and centralized annotation engines such as Entrez Gene has allowed the development of software that can analyze a great number of sequences in a matter of seconds. Results We have developed "EST Express", a suite of analytical tools that identify and annotate ESTs originating from specific mRNA populations. The software consists of a user-friendly GUI powered by PHP and MySQL that allows for online collaboration between researchers and continuity with UniGene, Entrez Gene and RefSeq. Two key features of the software include a novel, simplified Entrez Gene parser and tools to manage cDNA library sequencing projects. We have tested the software on a large data set (2,016 samples) produced by subtractive hybridization. Conclusion EST Express is an open-source, cross-platform web server application that imports sequences from cDNA libraries, such as those generated through subtractive hybridization or yeast two-hybrid screens. It then provides several layers of annotation based on Entrez Gene and RefSeq to allow the user to highlight useful genes and manage cDNA library projects. PMID:18402700

EST Express: PHP/MySQL based automated annotation of ESTs from expression libraries.

PubMed

Smith, Robin P; Buchser, William J; Lemmon, Marcus B; Pardinas, Jose R; Bixby, John L; Lemmon, Vance P

2008-04-10

Several biological techniques result in the acquisition of functional sets of cDNAs that must be sequenced and analyzed. The emergence of redundant databases such as UniGene and centralized annotation engines such as Entrez Gene has allowed the development of software that can analyze a great number of sequences in a matter of seconds. We have developed "EST Express", a suite of analytical tools that identify and annotate ESTs originating from specific mRNA populations. The software consists of a user-friendly GUI powered by PHP and MySQL that allows for online collaboration between researchers and continuity with UniGene, Entrez Gene and RefSeq. Two key features of the software include a novel, simplified Entrez Gene parser and tools to manage cDNA library sequencing projects. We have tested the software on a large data set (2,016 samples) produced by subtractive hybridization. EST Express is an open-source, cross-platform web server application that imports sequences from cDNA libraries, such as those generated through subtractive hybridization or yeast two-hybrid screens. It then provides several layers of annotation based on Entrez Gene and RefSeq to allow the user to highlight useful genes and manage cDNA library projects.

The Eimeria Transcript DB: an integrated resource for annotated transcripts of protozoan parasites of the genus Eimeria

PubMed Central

Rangel, Luiz Thibério; Novaes, Jeniffer; Durham, Alan M.; Madeira, Alda Maria B. N.; Gruber, Arthur

2013-01-01

Parasites of the genus Eimeria infect a wide range of vertebrate hosts, including chickens. We have recently reported a comparative analysis of the transcriptomes of Eimeria acervulina, Eimeria maxima and Eimeria tenella, integrating ORESTES data produced by our group and publicly available Expressed Sequence Tags (ESTs). All cDNA reads have been assembled, and the reconstructed transcripts have been submitted to a comprehensive functional annotation pipeline. Additional studies included orthology assignment across apicomplexan parasites and clustering analyses of gene expression profiles among different developmental stages of the parasites. To make all this body of information publicly available, we constructed the Eimeria Transcript Database (EimeriaTDB), a web repository that provides access to sequence data, annotation and comparative analyses. Here, we describe the web interface, available sequence data sets and query tools implemented on the site. The main goal of this work is to offer a public repository of sequence and functional annotation data of reconstructed transcripts of parasites of the genus Eimeria. We believe that EimeriaTDB will represent a valuable and complementary resource for the Eimeria scientific community and for those researchers interested in comparative genomics of apicomplexan parasites. Database URL: http://www.coccidia.icb.usp.br/eimeriatdb/ PMID:23411718

Using deep RNA sequencing for the structural annotation of the laccaria bicolor mycorrhizal transcriptome.

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

Larsen, P. E.; Trivedi, G.; Sreedasyam, A.

2010-07-06

Accurate structural annotation is important for prediction of function and required for in vitro approaches to characterize or validate the gene expression products. Despite significant efforts in the field, determination of the gene structure from genomic data alone is a challenging and inaccurate process. The ease of acquisition of transcriptomic sequence provides a direct route to identify expressed sequences and determine the correct gene structure. We developed methods to utilize RNA-seq data to correct errors in the structural annotation and extend the boundaries of current gene models using assembly approaches. The methods were validated with a transcriptomic data set derivedmore » from the fungus Laccaria bicolor, which develops a mycorrhizal symbiotic association with the roots of many tree species. Our analysis focused on the subset of 1501 gene models that are differentially expressed in the free living vs. mycorrhizal transcriptome and are expected to be important elements related to carbon metabolism, membrane permeability and transport, and intracellular signaling. Of the set of 1501 gene models, 1439 (96%) successfully generated modified gene models in which all error flags were successfully resolved and the sequences aligned to the genomic sequence. The remaining 4% (62 gene models) either had deviations from transcriptomic data that could not be spanned or generated sequence that did not align to genomic sequence. The outcome of this process is a set of high confidence gene models that can be reliably used for experimental characterization of protein function. 69% of expressed mycorrhizal JGI 'best' gene models deviated from the transcript sequence derived by this method. The transcriptomic sequence enabled correction of a majority of the structural inconsistencies and resulted in a set of validated models for 96% of the mycorrhizal genes. The method described here can be applied to improve gene structural annotation in other species, provided that there is a sequenced genome and a set of gene models.« less

Improved annotation with de novo transcriptome assembly in four social amoeba species.

PubMed

Singh, Reema; Lawal, Hajara M; Schilde, Christina; Glöckner, Gernot; Barton, Geoffrey J; Schaap, Pauline; Cole, Christian

2017-01-31

Annotation of gene models and transcripts is a fundamental step in genome sequencing projects. Often this is performed with automated prediction pipelines, which can miss complex and atypical genes or transcripts. RNA sequencing (RNA-seq) data can aid the annotation with empirical data. Here we present de novo transcriptome assemblies generated from RNA-seq data in four Dictyostelid species: D. discoideum, P. pallidum, D. fasciculatum and D. lacteum. The assemblies were incorporated with existing gene models to determine corrections and improvement on a whole-genome scale. This is the first time this has been performed in these eukaryotic species. An initial de novo transcriptome assembly was generated by Trinity for each species and then refined with Program to Assemble Spliced Alignments (PASA). The completeness and quality were assessed with the Benchmarking Universal Single-Copy Orthologs (BUSCO) and Transrate tools at each stage of the assemblies. The final datasets of 11,315-12,849 transcripts contained 5,610-7,712 updates and corrections to >50% of existing gene models including changes to hundreds or thousands of protein products. Putative novel genes are also identified and alternative splice isoforms were observed for the first time in P. pallidum, D. lacteum and D. fasciculatum. In taking a whole transcriptome approach to genome annotation with empirical data we have been able to enrich the annotations of four existing genome sequencing projects. In doing so we have identified updates to the majority of the gene annotations across all four species under study and found putative novel genes and transcripts which could be worthy for follow-up. The new transcriptome data we present here will be a valuable resource for genome curators in the Dictyostelia and we propose this effective methodology for use in other genome annotation projects.

Annotation-based genome-wide SNP discovery in the large and complex Aegilops tauschii genome using next-generation sequencing without a reference genome sequence

PubMed Central

2011-01-01

Background Many plants have large and complex genomes with an abundance of repeated sequences. Many plants are also polyploid. Both of these attributes typify the genome architecture in the tribe Triticeae, whose members include economically important wheat, rye and barley. Large genome sizes, an abundance of repeated sequences, and polyploidy present challenges to genome-wide SNP discovery using next-generation sequencing (NGS) of total genomic DNA by making alignment and clustering of short reads generated by the NGS platforms difficult, particularly in the absence of a reference genome sequence. Results An annotation-based, genome-wide SNP discovery pipeline is reported using NGS data for large and complex genomes without a reference genome sequence. Roche 454 shotgun reads with low genome coverage of one genotype are annotated in order to distinguish single-copy sequences and repeat junctions from repetitive sequences and sequences shared by paralogous genes. Multiple genome equivalents of shotgun reads of another genotype generated with SOLiD or Solexa are then mapped to the annotated Roche 454 reads to identify putative SNPs. A pipeline program package, AGSNP, was developed and used for genome-wide SNP discovery in Aegilops tauschii-the diploid source of the wheat D genome, and with a genome size of 4.02 Gb, of which 90% is repetitive sequences. Genomic DNA of Ae. tauschii accession AL8/78 was sequenced with the Roche 454 NGS platform. Genomic DNA and cDNA of Ae. tauschii accession AS75 was sequenced primarily with SOLiD, although some Solexa and Roche 454 genomic sequences were also generated. A total of 195,631 putative SNPs were discovered in gene sequences, 155,580 putative SNPs were discovered in uncharacterized single-copy regions, and another 145,907 putative SNPs were discovered in repeat junctions. These SNPs were dispersed across the entire Ae. tauschii genome. To assess the false positive SNP discovery rate, DNA containing putative SNPs was amplified by PCR from AL8/78 and AS75 and resequenced with the ABI 3730 xl. In a sample of 302 randomly selected putative SNPs, 84.0% in gene regions, 88.0% in repeat junctions, and 81.3% in uncharacterized regions were validated. Conclusion An annotation-based genome-wide SNP discovery pipeline for NGS platforms was developed. The pipeline is suitable for SNP discovery in genomic libraries of complex genomes and does not require a reference genome sequence. The pipeline is applicable to all current NGS platforms, provided that at least one such platform generates relatively long reads. The pipeline package, AGSNP, and the discovered 497,118 Ae. tauschii SNPs can be accessed at (http://avena.pw.usda.gov/wheatD/agsnp.shtml). PMID:21266061

An outlook on the fungal internal transcribed spacer sequences in GenBank and the introduction of a web-based tool for the exploration of fungal diversity.

PubMed

Ryberg, Martin; Kristiansson, Erik; Sjökvist, Elisabet; Nilsson, R Henrik

2009-01-01

The environmental and distributional data associated with fungal internal transcribed spacer (ITS) sequences in GenBank are investigated and a new web-based tool with which these sequences can be explored is introduced. All fungal ITS sequences in GenBank were classified as either identified to species level or insufficiently identified and compared using BLAST. The results are made available as a biweekly updated web service that can be queried to retrieve all insufficiently identified sequences (IIS) associated with any fungal genus. The most commonly available annotation items in GenBank are isolation source (55%); country of origin (50%); and specific host (38%). The molecular sampling of fungi shows a bias towards North America, Europe, China, and Japan whereas vast geographical areas remain effectively unexplored. Mycorrhizal and parasitic genera are on average associated with more IIS than are saprophytic taxa. Glomus, Alternaria, and Tomentella are the genera represented by the highest number of insufficiently identified ITS sequences in GenBank. The web service presented (http://andromeda.botany.gu.se/emerencia.html#genus_search) offers new means, particularly for mycorrhizal and plant pathogenic fungi, to examine the IIS in GenBank in a taxon-oriented framework and to explore their metadata in an easily accessible and time-efficient manner.

Inferring Higher Functional Information for RIKEN Mouse Full-Length cDNA Clones With FACTS

PubMed Central

Nagashima, Takeshi; Silva, Diego G.; Petrovsky, Nikolai; Socha, Luis A.; Suzuki, Harukazu; Saito, Rintaro; Kasukawa, Takeya; Kurochkin, Igor V.; Konagaya, Akihiko; Schönbach, Christian

2003-01-01

FACTS (Functional Association/Annotation of cDNA Clones from Text/Sequence Sources) is a semiautomated knowledge discovery and annotation system that integrates molecular function information derived from sequence analysis results (sequence inferred) with functional information extracted from text. Text-inferred information was extracted from keyword-based retrievals of MEDLINE abstracts and by matching of gene or protein names to OMIM, BIND, and DIP database entries. Using FACTS, we found that 47.5% of the 60,770 RIKEN mouse cDNA FANTOM2 clone annotations were informative for text searches. MEDLINE queries yielded molecular interaction-containing sentences for 23.1% of the clones. When disease MeSH and GO terms were matched with retrieved abstracts, 22.7% of clones were associated with potential diseases, and 32.5% with GO identifiers. A significant number (23.5%) of disease MeSH-associated clones were also found to have a hereditary disease association (OMIM Morbidmap). Inferred neoplastic and nervous system disease represented 49.6% and 36.0% of disease MeSH-associated clones, respectively. A comparison of sequence-based GO assignments with informative text-based GO assignments revealed that for 78.2% of clones, identical GO assignments were provided for that clone by either method, whereas for 21.8% of clones, the assignments differed. In contrast, for OMIM assignments, only 28.5% of clones had identical sequence-based and text-based OMIM assignments. Sequence, sentence, and term-based functional associations are included in the FACTS database (http://facts.gsc.riken.go.jp/), which permits results to be annotated and explored through web-accessible keyword and sequence search interfaces. The FACTS database will be a critical tool for investigating the functional complexity of the mouse transcriptome, cDNA-inferred interactome (molecular interactions), and pathome (pathologies). PMID:12819151

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

Comparative sequence analysis of Sordaria macrospora and Neurospora crassa as a means to improve genome annotation.

PubMed

Nowrousian, Minou; Würtz, Christian; Pöggeler, Stefanie; Kück, Ulrich

2004-03-01

One of the most challenging parts of large scale sequencing projects is the identification of functional elements encoded in a genome. Recently, studies of genomes of up to six different Saccharomyces species have demonstrated that a comparative analysis of genome sequences from closely related species is a powerful approach to identify open reading frames and other functional regions within genomes [Science 301 (2003) 71, Nature 423 (2003) 241]. Here, we present a comparison of selected sequences from Sordaria macrospora to their corresponding Neurospora crassa orthologous regions. Our analysis indicates that due to the high degree of sequence similarity and conservation of overall genomic organization, S. macrospora sequence information can be used to simplify the annotation of the N. crassa genome.

Quality of Computationally Inferred Gene Ontology Annotations

PubMed Central

Škunca, Nives; Altenhoff, Adrian; Dessimoz, Christophe

2012-01-01

Gene Ontology (GO) has established itself as the undisputed standard for protein function annotation. Most annotations are inferred electronically, i.e. without individual curator supervision, but they are widely considered unreliable. At the same time, we crucially depend on those automated annotations, as most newly sequenced genomes are non-model organisms. Here, we introduce a methodology to systematically and quantitatively evaluate electronic annotations. By exploiting changes in successive releases of the UniProt Gene Ontology Annotation database, we assessed the quality of electronic annotations in terms of specificity, reliability, and coverage. Overall, we not only found that electronic annotations have significantly improved in recent years, but also that their reliability now rivals that of annotations inferred by curators when they use evidence other than experiments from primary literature. This work provides the means to identify the subset of electronic annotations that can be relied upon—an important outcome given that >98% of all annotations are inferred without direct curation. PMID:22693439

Pooled assembly of marine metagenomic datasets: enriching annotation through chimerism.

PubMed

Magasin, Jonathan D; Gerloff, Dietlind L

2015-02-01

Despite advances in high-throughput sequencing, marine metagenomic samples remain largely opaque. A typical sample contains billions of microbial organisms from thousands of genomes and quadrillions of DNA base pairs. Its derived metagenomic dataset underrepresents this complexity by orders of magnitude because of the sparseness and shortness of sequencing reads. Read shortness and sequencing errors pose a major challenge to accurate species and functional annotation. This includes distinguishing known from novel species. Often the majority of reads cannot be annotated and thus cannot help our interpretation of the sample. Here, we demonstrate quantitatively how careful assembly of marine metagenomic reads within, but also across, datasets can alleviate this problem. For 10 simulated datasets, each with species complexity modeled on a real counterpart, chimerism remained within the same species for most contigs (97%). For 42 real pyrosequencing ('454') datasets, assembly increased the proportion of annotated reads, and even more so when datasets were pooled, by on average 1.6% (max 6.6%) for species, 9.0% (max 28.7%) for Pfam protein domains and 9.4% (max 22.9%) for PANTHER gene families. Our results outline exciting prospects for data sharing in the metagenomics community. While chimeric sequences should be avoided in other areas of metagenomics (e.g. biodiversity analyses), conservative pooled assembly is advantageous for annotation specificity and sensitivity. Intriguingly, our experiment also found potential prospects for (low-cost) discovery of new species in 'old' data. dgerloff@ffame.org Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

GarlicESTdb: an online database and mining tool for garlic EST sequences.

PubMed

Kim, Dae-Won; Jung, Tae-Sung; Nam, Seong-Hyeuk; Kwon, Hyuk-Ryul; Kim, Aeri; Chae, Sung-Hwa; Choi, Sang-Haeng; Kim, Dong-Wook; Kim, Ryong Nam; Park, Hong-Seog

2009-05-18

Allium sativum., commonly known as garlic, is a species in the onion genus (Allium), which is a large and diverse one containing over 1,250 species. Its close relatives include chives, onion, leek and shallot. Garlic has been used throughout recorded history for culinary, medicinal use and health benefits. Currently, the interest in garlic is highly increasing due to nutritional and pharmaceutical value including high blood pressure and cholesterol, atherosclerosis and cancer. For all that, there are no comprehensive databases available for Expressed Sequence Tags(EST) of garlic for gene discovery and future efforts of genome annotation. That is why we developed a new garlic database and applications to enable comprehensive analysis of garlic gene expression. GarlicESTdb is an integrated database and mining tool for large-scale garlic (Allium sativum) EST sequencing. A total of 21,595 ESTs collected from an in-house cDNA library were used to construct the database. The analysis pipeline is an automated system written in JAVA and consists of the following components: automatic preprocessing of EST reads, assembly of raw sequences, annotation of the assembled sequences, storage of the analyzed information into MySQL databases, and graphic display of all processed data. A web application was implemented with the latest J2EE (Java 2 Platform Enterprise Edition) software technology (JSP/EJB/JavaServlet) for browsing and querying the database, for creation of dynamic web pages on the client side, and for mapping annotated enzymes to KEGG pathways, the AJAX framework was also used partially. The online resources, such as putative annotation, single nucleotide polymorphisms (SNP) and tandem repeat data sets, can be searched by text, explored on the website, searched using BLAST, and downloaded. To archive more significant BLAST results, a curation system was introduced with which biologists can easily edit best-hit annotation information for others to view. The GarlicESTdb web application is freely available at http://garlicdb.kribb.re.kr. GarlicESTdb is the first incorporated online information database of EST sequences isolated from garlic that can be freely accessed and downloaded. It has many useful features for interactive mining of EST contigs and datasets from each library, including curation of annotated information, expression profiling, information retrieval, and summary of statistics of functional annotation. Consequently, the development of GarlicESTdb will provide a crucial contribution to biologists for data-mining and more efficient experimental studies.

BigQ: a NoSQL based framework to handle genomic variants in i2b2.

PubMed

Gabetta, Matteo; Limongelli, Ivan; Rizzo, Ettore; Riva, Alberto; Segagni, Daniele; Bellazzi, Riccardo

2015-12-29

Precision medicine requires the tight integration of clinical and molecular data. To this end, it is mandatory to define proper technological solutions able to manage the overwhelming amount of high throughput genomic data needed to test associations between genomic signatures and human phenotypes. The i2b2 Center (Informatics for Integrating Biology and the Bedside) has developed a widely internationally adopted framework to use existing clinical data for discovery research that can help the definition of precision medicine interventions when coupled with genetic data. i2b2 can be significantly advanced by designing efficient management solutions of Next Generation Sequencing data. We developed BigQ, an extension of the i2b2 framework, which integrates patient clinical phenotypes with genomic variant profiles generated by Next Generation Sequencing. A visual programming i2b2 plugin allows retrieving variants belonging to the patients in a cohort by applying filters on genomic variant annotations. We report an evaluation of the query performance of our system on more than 11 million variants, showing that the implemented solution scales linearly in terms of query time and disk space with the number of variants. In this paper we describe a new i2b2 web service composed of an efficient and scalable document-based database that manages annotations of genomic variants and of a visual programming plug-in designed to dynamically perform queries on clinical and genetic data. The system therefore allows managing the fast growing volume of genomic variants and can be used to integrate heterogeneous genomic annotations.

An Atlas of annotations of Hydra vulgaris transcriptome.

PubMed

Evangelista, Daniela; Tripathi, Kumar Parijat; Guarracino, Mario Rosario

2016-09-22

RNA sequencing takes advantage of the Next Generation Sequencing (NGS) technologies for analyzing RNA transcript counts with an excellent accuracy. Trying to interpret this huge amount of data in biological information is still a key issue, reason for which the creation of web-resources useful for their analysis is highly desiderable. Starting from a previous work, Transcriptator, we present the Atlas of Hydra's vulgaris, an extensible web tool in which its complete transcriptome is annotated. In order to provide to the users an advantageous resource that include the whole functional annotated transcriptome of Hydra vulgaris water polyp, we implemented the Atlas web-tool contains 31.988 accesible and downloadable transcripts of this non-reference model organism. Atlas, as a freely available resource, can be considered a valuable tool to rapidly retrieve functional annotation for transcripts differentially expressed in Hydra vulgaris exposed to the distinct experimental treatments. WEB RESOURCE URL: http://www-labgtp.na.icar.cnr.it/Atlas .

Exploiting proteomic data for genome annotation and gene model validation in Aspergillus niger.

PubMed

Wright, James C; Sugden, Deana; Francis-McIntyre, Sue; Riba-Garcia, Isabel; Gaskell, Simon J; Grigoriev, Igor V; Baker, Scott E; Beynon, Robert J; Hubbard, Simon J

2009-02-04

Proteomic data is a potentially rich, but arguably unexploited, data source for genome annotation. Peptide identifications from tandem mass spectrometry provide prima facie evidence for gene predictions and can discriminate over a set of candidate gene models. Here we apply this to the recently sequenced Aspergillus niger fungal genome from the Joint Genome Institutes (JGI) and another predicted protein set from another A.niger sequence. Tandem mass spectra (MS/MS) were acquired from 1d gel electrophoresis bands and searched against all available gene models using Average Peptide Scoring (APS) and reverse database searching to produce confident identifications at an acceptable false discovery rate (FDR). 405 identified peptide sequences were mapped to 214 different A.niger genomic loci to which 4093 predicted gene models clustered, 2872 of which contained the mapped peptides. Interestingly, 13 (6%) of these loci either had no preferred predicted gene model or the genome annotators' chosen "best" model for that genomic locus was not found to be the most parsimonious match to the identified peptides. The peptides identified also boosted confidence in predicted gene structures spanning 54 introns from different gene models. This work highlights the potential of integrating experimental proteomics data into genomic annotation pipelines much as expressed sequence tag (EST) data has been. A comparison of the published genome from another strain of A.niger sequenced by DSM showed that a number of the gene models or proteins with proteomics evidence did not occur in both genomes, further highlighting the utility of the method.

Defining functional distance using manifold embeddings of gene ontology annotations

PubMed Central

Lerman, Gilad; Shakhnovich, Boris E.

2007-01-01

Although rigorous measures of similarity for sequence and structure are now well established, the problem of defining functional relationships has been particularly daunting. Here, we present several manifold embedding techniques to compute distances between Gene Ontology (GO) functional annotations and consequently estimate functional distances between protein domains. To evaluate accuracy, we correlate the functional distance to the well established measures of sequence, structural, and phylogenetic similarities. Finally, we show that manual classification of structures into folds and superfamilies is mirrored by proximity in the newly defined function space. We show how functional distances place structure–function relationships in biological context resulting in insight into divergent and convergent evolution. The methods and results in this paper can be readily generalized and applied to a wide array of biologically relevant investigations, such as accuracy of annotation transference, the relationship between sequence, structure, and function, or coherence of expression modules. PMID:17595300

Complete genome sequence of Metallosphaera cuprina, a metal sulfide-oxidizing archaeon from a hot spring.

PubMed

Liu, Li-Jun; You, Xiao-Yan; Zheng, Huajun; Wang, Shengyue; Jiang, Cheng-Ying; Liu, Shuang-Jiang

2011-07-01

The genome of the metal sulfide-oxidizing, thermoacidophilic strain Metallosphaera cuprina Ar-4 has been completely sequenced and annotated. Originally isolated from a sulfuric hot spring, strain Ar-4 grows optimally at 65°C and a pH of 3.5. The M. cuprina genome has a 1,840,348-bp circular chromosome (2,029 open reading frames [ORFs]) and is 16% smaller than the previously sequenced Metallosphaera sedula genome. Compared to the M. sedula genome, there are no counterpart genes in the M. cuprina genome for about 480 ORFs in the M. sedula genome, of which 243 ORFs are annotated as hypothetical protein genes. Still, there are 233 ORFs uniquely occurring in M. cuprina. Genome annotation supports that M. cuprina lives a facultative life on CO(2) and organics and obtains energy from oxidation of sulfidic ores and reduced inorganic sulfuric compounds.

Computational annotation of genes differentially expressed along olive fruit development

PubMed Central

Galla, Giulio; Barcaccia, Gianni; Ramina, Angelo; Collani, Silvio; Alagna, Fiammetta; Baldoni, Luciana; Cultrera, Nicolò GM; Martinelli, Federico; Sebastiani, Luca; Tonutti, Pietro

2009-01-01

Background Olea europaea L. is a traditional tree crop of the Mediterranean basin with a worldwide economical high impact. Differently from other fruit tree species, little is known about the physiological and molecular basis of the olive fruit development and a few sequences of genes and gene products are available for olive in public databases. This study deals with the identification of large sets of differentially expressed genes in developing olive fruits and the subsequent computational annotation by means of different software. Results mRNA from fruits of the cv. Leccino sampled at three different stages [i.e., initial fruit set (stage 1), completed pit hardening (stage 2) and veraison (stage 3)] was used for the identification of differentially expressed genes putatively involved in main processes along fruit development. Four subtractive hybridization libraries were constructed: forward and reverse between stage 1 and 2 (libraries A and B), and 2 and 3 (libraries C and D). All sequenced clones (1,132 in total) were analyzed through BlastX against non-redundant NCBI databases and about 60% of them showed similarity to known proteins. A total of 89 out of 642 differentially expressed unique sequences was further investigated by Real-Time PCR, showing a validation of the SSH results as high as 69%. Library-specific cDNA repertories were annotated according to the three main vocabularies of the gene ontology (GO): cellular component, biological process and molecular function. BlastX analysis, GO terms mapping and annotation analysis were performed using the Blast2GO software, a research tool designed with the main purpose of enabling GO based data mining on sequence sets for which no GO annotation is yet available. Bioinformatic analysis pointed out a significantly different distribution of the annotated sequences for each GO category, when comparing the three fruit developmental stages. The olive fruit-specific transcriptome dataset was used to query all known KEGG (Kyoto Encyclopaedia of Genes and Genomes) metabolic pathways for characterizing and positioning retrieved EST records. The integration of the olive sequence datasets within the MapMan platform for microarray analysis allowed the identification of specific biosynthetic pathways useful for the definition of key functional categories in time course analyses for gene groups. Conclusion The bioinformatic annotation of all gene sequences was useful to shed light on metabolic pathways and transcriptional aspects related to carbohydrates, fatty acids, secondary metabolites, transcription factors and hormones as well as response to biotic and abiotic stresses throughout olive drupe development. These results represent a first step toward both functional genomics and systems biology research for understanding the gene functions and regulatory networks in olive fruit growth and ripening. PMID:19852839

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

Davis, James J.; Brettin, Thomas; Dietrich, Emily M.

Here, the Pathosystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center. Recent changes to PATRIC include a redesign of the web interface and some new services that provide users with a platform that takes them from raw reads to an integrated analysis experience. The redesigned interface allows researchers direct access to tools and data, and the emphasis has changed to user-created genome-groups, with detailed summaries and views of the data that researchers have selected. Perhaps the biggest change has been the enhanced capability for researchers to analyze their private data and compare it to the available public data.more » Researchers can assemble their raw sequence reads and annotate the contigs using RASTtk. PATRIC also provides services for RNA-Seq, variation, model reconstruction and differential expression analysis, all delivered through an updated private workspace. Private data can be compared by `virtual integration' to any of PATRIC's public data. The number of genomes available for comparison in PATRIC has expanded to over 80 000, with a special emphasis on genomes with antimicrobial resistance data. PATRIC uses this data to improve both subsystem annotation and k-mer classification, and tags new genomes as having signatures that indicate susceptibility or resistance to specific antibiotics.« less

NCBI-compliant genome submissions: tips and tricks to save time and money.

PubMed

Pirovano, Walter; Boetzer, Marten; Derks, Martijn F L; Smit, Sandra

2017-03-01

Genome sequences nowadays play a central role in molecular biology and bioinformatics. These sequences are shared with the scientific community through sequence databases. The sequence repositories of the International Nucleotide Sequence Database Collaboration (INSDC, comprising GenBank, ENA and DDBJ) are the largest in the world. Preparing an annotated sequence in such a way that it will be accepted by the database is challenging because many validation criteria apply. In our opinion, it is an undesirable situation that researchers who want to submit their sequence need either a lot of experience or help from partners to get the job done. To save valuable time and money, we list a number of recommendations for people who want to submit an annotated genome to a sequence database, as well as for tool developers, who could help to ease the process. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Blast2GO goes grid: developing a grid-enabled prototype for functional genomics analysis.

PubMed

Aparicio, G; Götz, S; Conesa, A; Segrelles, D; Blanquer, I; García, J M; Hernandez, V; Robles, M; Talon, M

2006-01-01

The vast amount in complexity of data generated in Genomic Research implies that new dedicated and powerful computational tools need to be developed to meet their analysis requirements. Blast2GO (B2G) is a bioinformatics tool for Gene Ontology-based DNA or protein sequence annotation and function-based data mining. The application has been developed with the aim of affering an easy-to-use tool for functional genomics research. Typical B2G users are middle size genomics labs carrying out sequencing, ETS and microarray projects, handling datasets up to several thousand sequences. In the current version of B2G. The power and analytical potential of both annotation and function data-mining is somehow restricted to the computational power behind each particular installation. In order to be able to offer the possibility of an enhanced computational capacity within this bioinformatics application, a Grid component is being developed. A prototype has been conceived for the particular problem of speeding up the Blast searches to obtain fast results for large datasets. Many efforts have been done in the literature concerning the speeding up of Blast searches, but few of them deal with the use of large heterogeneous production Grid Infrastructures. These are the infrastructures that could reach the largest number of resources and the best load balancing for data access. The Grid Service under development will analyse requests based on the number of sequences, splitting them accordingly to the available resources. Lower-level computation will be performed through MPIBLAST. The software architecture is based on the WSRF standard.

Comprehensive phylogenetic analysis of bacterial reverse transcriptases.

PubMed

Toro, Nicolás; Nisa-Martínez, Rafael

2014-01-01

Much less is known about reverse transcriptases (RTs) in prokaryotes than in eukaryotes, with most prokaryotic enzymes still uncharacterized. Two surveys involving BLAST searches for RT genes in prokaryotic genomes revealed the presence of large numbers of diverse, uncharacterized RTs and RT-like sequences. Here, using consistent annotation across all sequenced bacterial species from GenBank and other sources via RAST, available from the PATRIC (Pathogenic Resource Integration Center) platform, we have compiled the data for currently annotated reverse transcriptases from completely sequenced bacterial genomes. RT sequences are broadly distributed across bacterial phyla, but green sulfur bacteria and cyanobacteria have the highest levels of RT sequence diversity (≤85% identity) per genome. By contrast, phylum Actinobacteria, for which a large number of genomes have been sequenced, was found to have a low RT sequence diversity. Phylogenetic analyses revealed that bacterial RTs could be classified into 17 main groups: group II introns, retrons/retron-like RTs, diversity-generating retroelements (DGRs), Abi-like RTs, CRISPR-Cas-associated RTs, group II-like RTs (G2L), and 11 other groups of RTs of unknown function. Proteobacteria had the highest potential functional diversity, as they possessed most of the RT groups. Group II introns and DGRs were the most widely distributed RTs in bacterial phyla. Our results provide insights into bacterial RT phylogeny and the basis for an update of annotation systems based on sequence/domain homology.

Comprehensive Phylogenetic Analysis of Bacterial Reverse Transcriptases

PubMed Central

Toro, Nicolás; Nisa-Martínez, Rafael

2014-01-01

Much less is known about reverse transcriptases (RTs) in prokaryotes than in eukaryotes, with most prokaryotic enzymes still uncharacterized. Two surveys involving BLAST searches for RT genes in prokaryotic genomes revealed the presence of large numbers of diverse, uncharacterized RTs and RT-like sequences. Here, using consistent annotation across all sequenced bacterial species from GenBank and other sources via RAST, available from the PATRIC (Pathogenic Resource Integration Center) platform, we have compiled the data for currently annotated reverse transcriptases from completely sequenced bacterial genomes. RT sequences are broadly distributed across bacterial phyla, but green sulfur bacteria and cyanobacteria have the highest levels of RT sequence diversity (≤85% identity) per genome. By contrast, phylum Actinobacteria, for which a large number of genomes have been sequenced, was found to have a low RT sequence diversity. Phylogenetic analyses revealed that bacterial RTs could be classified into 17 main groups: group II introns, retrons/retron-like RTs, diversity-generating retroelements (DGRs), Abi-like RTs, CRISPR-Cas-associated RTs, group II-like RTs (G2L), and 11 other groups of RTs of unknown function. Proteobacteria had the highest potential functional diversity, as they possessed most of the RT groups. Group II introns and DGRs were the most widely distributed RTs in bacterial phyla. Our results provide insights into bacterial RT phylogeny and the basis for an update of annotation systems based on sequence/domain homology. PMID:25423096

Gene discovery in the hamster: a comparative genomics approach for gene annotation by sequencing of hamster testis cDNAs

PubMed Central

Oduru, Sreedhar; Campbell, Janee L; Karri, SriTulasi; Hendry, William J; Khan, Shafiq A; Williams, Simon C

2003-01-01

Background Complete genome annotation will likely be achieved through a combination of computer-based analysis of available genome sequences combined with direct experimental characterization of expressed regions of individual genomes. We have utilized a comparative genomics approach involving the sequencing of randomly selected hamster testis cDNAs to begin to identify genes not previously annotated on the human, mouse, rat and Fugu (pufferfish) genomes. Results 735 distinct sequences were analyzed for their relatedness to known sequences in public databases. Eight of these sequences were derived from previously unidentified genes and expression of these genes in testis was confirmed by Northern blotting. The genomic locations of each sequence were mapped in human, mouse, rat and pufferfish, where applicable, and the structure of their cognate genes was derived using computer-based predictions, genomic comparisons and analysis of uncharacterized cDNA sequences from human and macaque. Conclusion The use of a comparative genomics approach resulted in the identification of eight cDNAs that correspond to previously uncharacterized genes in the human genome. The proteins encoded by these genes included a new member of the kinesin superfamily, a SET/MYND-domain protein, and six proteins for which no specific function could be predicted. Each gene was expressed primarily in testis, suggesting that they may play roles in the development and/or function of testicular cells. PMID:12783626

Finding needles in haystacks: linking scientific names, reference specimens and molecular data for Fungi.

PubMed

Schoch, Conrad L; Robbertse, Barbara; Robert, Vincent; Vu, Duong; Cardinali, Gianluigi; Irinyi, Laszlo; Meyer, Wieland; Nilsson, R Henrik; Hughes, Karen; Miller, Andrew N; Kirk, Paul M; Abarenkov, Kessy; Aime, M Catherine; Ariyawansa, Hiran A; Bidartondo, Martin; Boekhout, Teun; Buyck, Bart; Cai, Qing; Chen, Jie; Crespo, Ana; Crous, Pedro W; Damm, Ulrike; De Beer, Z Wilhelm; Dentinger, Bryn T M; Divakar, Pradeep K; Dueñas, Margarita; Feau, Nicolas; Fliegerova, Katerina; García, Miguel A; Ge, Zai-Wei; Griffith, Gareth W; Groenewald, Johannes Z; Groenewald, Marizeth; Grube, Martin; Gryzenhout, Marieka; Gueidan, Cécile; Guo, Liangdong; Hambleton, Sarah; Hamelin, Richard; Hansen, Karen; Hofstetter, Valérie; Hong, Seung-Beom; Houbraken, Jos; Hyde, Kevin D; Inderbitzin, Patrik; Johnston, Peter R; Karunarathna, Samantha C; Kõljalg, Urmas; Kovács, Gábor M; Kraichak, Ekaphan; Krizsan, Krisztina; Kurtzman, Cletus P; Larsson, Karl-Henrik; Leavitt, Steven; Letcher, Peter M; Liimatainen, Kare; Liu, Jian-Kui; Lodge, D Jean; Luangsa-ard, Janet Jennifer; Lumbsch, H Thorsten; Maharachchikumbura, Sajeewa S N; Manamgoda, Dimuthu; Martín, María P; Minnis, Andrew M; Moncalvo, Jean-Marc; Mulè, Giuseppina; Nakasone, Karen K; Niskanen, Tuula; Olariaga, Ibai; Papp, Tamás; Petkovits, Tamás; Pino-Bodas, Raquel; Powell, Martha J; Raja, Huzefa A; Redecker, Dirk; Sarmiento-Ramirez, J M; Seifert, Keith A; Shrestha, Bhushan; Stenroos, Soili; Stielow, Benjamin; Suh, Sung-Oui; Tanaka, Kazuaki; Tedersoo, Leho; Telleria, M Teresa; Udayanga, Dhanushka; Untereiner, Wendy A; Diéguez Uribeondo, Javier; Subbarao, Krishna V; Vágvölgyi, Csaba; Visagie, Cobus; Voigt, Kerstin; Walker, Donald M; Weir, Bevan S; Weiß, Michael; Wijayawardene, Nalin N; Wingfield, Michael J; Xu, J P; Yang, Zhu L; Zhang, Ning; Zhuang, Wen-Ying; Federhen, Scott

2014-01-01

DNA phylogenetic comparisons have shown that morphology-based species recognition often underestimates fungal diversity. Therefore, the need for accurate DNA sequence data, tied to both correct taxonomic names and clearly annotated specimen data, has never been greater. Furthermore, the growing number of molecular ecology and microbiome projects using high-throughput sequencing require fast and effective methods for en masse species assignments. In this article, we focus on selecting and re-annotating a set of marker reference sequences that represent each currently accepted order of Fungi. The particular focus is on sequences from the internal transcribed spacer region in the nuclear ribosomal cistron, derived from type specimens and/or ex-type cultures. Re-annotated and verified sequences were deposited in a curated public database at the National Center for Biotechnology Information (NCBI), namely the RefSeq Targeted Loci (RTL) database, and will be visible during routine sequence similarity searches with NR_prefixed accession numbers. A set of standards and protocols is proposed to improve the data quality of new sequences, and we suggest how type and other reference sequences can be used to improve identification of Fungi. Database URL: http://www.ncbi.nlm.nih.gov/bioproject/PRJNA177353. Published by Oxford University Press 2013. This work is written by US Government employees and is in the public domain in the US.

MimoSA: a system for minimotif annotation

PubMed Central

2010-01-01

Background Minimotifs are short peptide sequences within one protein, which are recognized by other proteins or molecules. While there are now several minimotif databases, they are incomplete. There are reports of many minimotifs in the primary literature, which have yet to be annotated, while entirely novel minimotifs continue to be published on a weekly basis. Our recently proposed function and sequence syntax for minimotifs enables us to build a general tool that will facilitate structured annotation and management of minimotif data from the biomedical literature. Results We have built the MimoSA application for minimotif annotation. The application supports management of the Minimotif Miner database, literature tracking, and annotation of new minimotifs. MimoSA enables the visualization, organization, selection and editing functions of minimotifs and their attributes in the MnM database. For the literature components, Mimosa provides paper status tracking and scoring of papers for annotation through a freely available machine learning approach, which is based on word correlation. The paper scoring algorithm is also available as a separate program, TextMine. Form-driven annotation of minimotif attributes enables entry of new minimotifs into the MnM database. Several supporting features increase the efficiency of annotation. The layered architecture of MimoSA allows for extensibility by separating the functions of paper scoring, minimotif visualization, and database management. MimoSA is readily adaptable to other annotation efforts that manually curate literature into a MySQL database. Conclusions MimoSA is an extensible application that facilitates minimotif annotation and integrates with the Minimotif Miner database. We have built MimoSA as an application that integrates dynamic abstract scoring with a high performance relational model of minimotif syntax. MimoSA's TextMine, an efficient paper-scoring algorithm, can be used to dynamically rank papers with respect to context. PMID:20565705

De novo RNA-seq and functional annotation of Ornithonyssus bacoti.

PubMed

Niu, DongLing; Wang, RuiLing; Zhao, YaE; Yang, Rui; Hu, Li

2018-06-01

Ornithonyssus bacoti (Hirst) (Acari: Macronyssidae) is a vector and reservoir of pathogens causing serious infectious diseases, such as epidemic hemorrhagic fever, endemic typhus, tularemia, and leptospirosis. Its genome and transcriptome data are lacking in public databases. In this study, total RNA was extracted from live O. bacoti to conduct RNA-seq, functional annotation, coding domain sequence (CDS) prediction and simple sequence repeats (SSRs) detection. The results showed that 65.8 million clean reads were generated and assembled into 72,185 unigenes, of which 49.4% were annotated by seven functional databases. 23,121 unigenes were annotated and assigned to 457 species by non-redundant protein sequence database. The BLAST top-two hit species were Metaseiulus occidentalis and Ixodes scapularis. The procedure detected 12,426 SSRs, of which tri- and di-nucleotides were the most abundant types and the representative motifs were AAT/ATT and AC/GT. 26,936 CDS were predicted with a mean length of 711 bp. 87 unigenes of 30 functional genes, which are usually involved in stress responses, drug resistance, movement, metabolism and allergy, were further identified by bioinformatics methods. The unigenes putatively encoding cytochrome P450 proteins were further analyzed phylogenetically. In conclusion, this study completed the RNA-seq and functional annotation of O. bacoti successfully, which provides reliable molecular data for its future studies of gene function and molecular markers.

Web Apollo: a web-based genomic annotation editing platform.

PubMed

Lee, Eduardo; Helt, Gregg A; Reese, Justin T; Munoz-Torres, Monica C; Childers, Chris P; Buels, Robert M; Stein, Lincoln; Holmes, Ian H; Elsik, Christine G; Lewis, Suzanna E

2013-08-30

Web Apollo is the first instantaneous, collaborative genomic annotation editor available on the web. One of the natural consequences following from current advances in sequencing technology is that there are more and more researchers sequencing new genomes. These researchers require tools to describe the functional features of their newly sequenced genomes. With Web Apollo researchers can use any of the common browsers (for example, Chrome or Firefox) to jointly analyze and precisely describe the features of a genome in real time, whether they are in the same room or working from opposite sides of the world.

Web Apollo: a web-based genomic annotation editing platform

PubMed Central

2013-01-01

Web Apollo is the first instantaneous, collaborative genomic annotation editor available on the web. One of the natural consequences following from current advances in sequencing technology is that there are more and more researchers sequencing new genomes. These researchers require tools to describe the functional features of their newly sequenced genomes. With Web Apollo researchers can use any of the common browsers (for example, Chrome or Firefox) to jointly analyze and precisely describe the features of a genome in real time, whether they are in the same room or working from opposite sides of the world. PMID:24000942

Next Generation Models for Storage and Representation of Microbial Biological Annotation

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

Quest, Daniel J; Land, Miriam L; Brettin, Thomas S

2010-01-01

Background Traditional genome annotation systems were developed in a very different computing era, one where the World Wide Web was just emerging. Consequently, these systems are built as centralized black boxes focused on generating high quality annotation submissions to GenBank/EMBL supported by expert manual curation. The exponential growth of sequence data drives a growing need for increasingly higher quality and automatically generated annotation. Typical annotation pipelines utilize traditional database technologies, clustered computing resources, Perl, C, and UNIX file systems to process raw sequence data, identify genes, and predict and categorize gene function. These technologies tightly couple the annotation software systemmore » to hardware and third party software (e.g. relational database systems and schemas). This makes annotation systems hard to reproduce, inflexible to modification over time, difficult to assess, difficult to partition across multiple geographic sites, and difficult to understand for those who are not domain experts. These systems are not readily open to scrutiny and therefore not scientifically tractable. The advent of Semantic Web standards such as Resource Description Framework (RDF) and OWL Web Ontology Language (OWL) enables us to construct systems that address these challenges in a new comprehensive way. Results Here, we develop a framework for linking traditional data to OWL-based ontologies in genome annotation. We show how data standards can decouple hardware and third party software tools from annotation pipelines, thereby making annotation pipelines easier to reproduce and assess. An illustrative example shows how TURTLE (Terse RDF Triple Language) can be used as a human readable, but also semantically-aware, equivalent to GenBank/EMBL files. Conclusions The power of this approach lies in its ability to assemble annotation data from multiple databases across multiple locations into a representation that is understandable to researchers. In this way, all researchers, experimental and computational, will more easily understand the informatics processes constructing genome annotation and ultimately be able to help improve the systems that produce them.« less

PFP: Automated prediction of gene ontology functional annotations with confidence scores using protein sequence data.

PubMed

Hawkins, Troy; Chitale, Meghana; Luban, Stanislav; Kihara, Daisuke

2009-02-15

Protein function prediction is a central problem in bioinformatics, increasing in importance recently due to the rapid accumulation of biological data awaiting interpretation. Sequence data represents the bulk of this new stock and is the obvious target for consideration as input, as newly sequenced organisms often lack any other type of biological characterization. We have previously introduced PFP (Protein Function Prediction) as our sequence-based predictor of Gene Ontology (GO) functional terms. PFP interprets the results of a PSI-BLAST search by extracting and scoring individual functional attributes, searching a wide range of E-value sequence matches, and utilizing conventional data mining techniques to fill in missing information. We have shown it to be effective in predicting both specific and low-resolution functional attributes when sufficient data is unavailable. Here we describe (1) significant improvements to the PFP infrastructure, including the addition of prediction significance and confidence scores, (2) a thorough benchmark of performance and comparisons to other related prediction methods, and (3) applications of PFP predictions to genome-scale data. We applied PFP predictions to uncharacterized protein sequences from 15 organisms. Among these sequences, 60-90% could be annotated with a GO molecular function term at high confidence (>or=80%). We also applied our predictions to the protein-protein interaction network of the Malaria plasmodium (Plasmodium falciparum). High confidence GO biological process predictions (>or=90%) from PFP increased the number of fully enriched interactions in this dataset from 23% of interactions to 94%. Our benchmark comparison shows significant performance improvement of PFP relative to GOtcha, InterProScan, and PSI-BLAST predictions. This is consistent with the performance of PFP as the overall best predictor in both the AFP-SIG '05 and CASP7 function (FN) assessments. PFP is available as a web service at http://dragon.bio.purdue.edu/pfp/. (c) 2008 Wiley-Liss, Inc.

The fast changing landscape of sequencing technologies and their impact on microbial genome assemblies and annotation.

PubMed

Mavromatis, Konstantinos; Land, Miriam L; Brettin, Thomas S; Quest, Daniel J; Copeland, Alex; Clum, Alicia; Goodwin, Lynne; Woyke, Tanja; Lapidus, Alla; Klenk, Hans Peter; Cottingham, Robert W; Kyrpides, Nikos C

2012-01-01

The emergence of next generation sequencing (NGS) has provided the means for rapid and high throughput sequencing and data generation at low cost, while concomitantly creating a new set of challenges. The number of available assembled microbial genomes continues to grow rapidly and their quality reflects the quality of the sequencing technology used, but also of the analysis software employed for assembly and annotation. In this work, we have explored the quality of the microbial draft genomes across various sequencing technologies. We have compared the draft and finished assemblies of 133 microbial genomes sequenced at the Department of Energy-Joint Genome Institute and finished at the Los Alamos National Laboratory using a variety of combinations of sequencing technologies, reflecting the transition of the institute from Sanger-based sequencing platforms to NGS platforms. The quality of the public assemblies and of the associated gene annotations was evaluated using various metrics. Results obtained with the different sequencing technologies, as well as their effects on downstream processes, were analyzed. Our results demonstrate that the Illumina HiSeq 2000 sequencing system, the primary sequencing technology currently used for de novo genome sequencing and assembly at JGI, has various advantages in terms of total sequence throughput and cost, but it also introduces challenges for the downstream analyses. In all cases assembly results although on average are of high quality, need to be viewed critically and consider sources of errors in them prior to analysis. These data follow the evolution of microbial sequencing and downstream processing at the JGI from draft genome sequences with large gaps corresponding to missing genes of significant biological role to assemblies with multiple small gaps (Illumina) and finally to assemblies that generate almost complete genomes (Illumina+PacBio).

Revised annotation of Plutella xylostella microRNAs and their genome-wide target identification.

PubMed

Etebari, K; Asgari, S

2016-12-01

The diamondback moth, Plutella xylostella, is the most devastating pest of brassica crops worldwide. Although 128 mature microRNAs (miRNAs) have been annotated from this species in miRBase, there is a need to extend and correct the current P. xylostella miRNA repertoire as a result of its recently improved genome assembly and more available small RNA sequence data. We used our new ultra-deep sequence data and bioinformatics to re-annotate the P. xylostella genome for high confidence miRNAs with the correct 5p and 3p arm features. Furthermore, all the P. xylostella annotated genes were also screened to identify potential miRNA binding sites using three target-predicting algorithms. In total, 203 mature miRNAs were annotated, including 33 novel miRNAs. We identified 7691 highly confident binding sites for 160 pxy-miRNAs. The data provided here will facilitate future studies involving functional analyses of P. xylostella miRNAs as a platform to introduce novel approaches for sustainable management of this destructive pest. © 2016 The Royal Entomological Society.

Proteogenomics produces comprehensive and highly accurate protein-coding gene annotation in a complete genome assembly of Malassezia sympodialis.

PubMed

Zhu, Yafeng; Engström, Pär G; Tellgren-Roth, Christian; Baudo, Charles D; Kennell, John C; Sun, Sheng; Billmyre, R Blake; Schröder, Markus S; Andersson, Anna; Holm, Tina; Sigurgeirsson, Benjamin; Wu, Guangxi; Sankaranarayanan, Sundar Ram; Siddharthan, Rahul; Sanyal, Kaustuv; Lundeberg, Joakim; Nystedt, Björn; Boekhout, Teun; Dawson, Thomas L; Heitman, Joseph; Scheynius, Annika; Lehtiö, Janne

2017-03-17

Complete and accurate genome assembly and annotation is a crucial foundation for comparative and functional genomics. Despite this, few complete eukaryotic genomes are available, and genome annotation remains a major challenge. Here, we present a complete genome assembly of the skin commensal yeast Malassezia sympodialis and demonstrate how proteogenomics can substantially improve gene annotation. Through long-read DNA sequencing, we obtained a gap-free genome assembly for M. sympodialis (ATCC 42132), comprising eight nuclear and one mitochondrial chromosome. We also sequenced and assembled four M. sympodialis clinical isolates, and showed their value for understanding Malassezia reproduction by confirming four alternative allele combinations at the two mating-type loci. Importantly, we demonstrated how proteomics data could be readily integrated with transcriptomics data in standard annotation tools. This increased the number of annotated protein-coding genes by 14% (from 3612 to 4113), compared to using transcriptomics evidence alone. Manual curation further increased the number of protein-coding genes by 9% (to 4493). All of these genes have RNA-seq evidence and 87% were confirmed by proteomics. The M. sympodialis genome assembly and annotation presented here is at a quality yet achieved only for a few eukaryotic organisms, and constitutes an important reference for future host-microbe interaction studies. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

MIPS: analysis and annotation of proteins from whole genomes

PubMed Central

Mewes, H. W.; Amid, C.; Arnold, R.; Frishman, D.; Güldener, U.; Mannhaupt, G.; Münsterkötter, M.; Pagel, P.; Strack, N.; Stümpflen, V.; Warfsmann, J.; Ruepp, A.

2004-01-01

The Munich Information Center for Protein Sequences (MIPS-GSF), Neuherberg, Germany, provides protein sequence-related information based on whole-genome analysis. The main focus of the work is directed toward the systematic organization of sequence-related attributes as gathered by a variety of algorithms, primary information from experimental data together with information compiled from the scientific literature. MIPS maintains automatically generated and manually annotated genome-specific databases, develops systematic classification schemes for the functional annotation of protein sequences and provides tools for the comprehensive analysis of protein sequences. This report updates the information on the yeast genome (CYGD), the Neurospora crassa genome (MNCDB), the database of complete cDNAs (German Human Genome Project, NGFN), the database of mammalian protein–protein interactions (MPPI), the database of FASTA homologies (SIMAP), and the interface for the fast retrieval of protein-associated information (QUIPOS). The Arabidopsis thaliana database, the rice database, the plant EST databases (MATDB, MOsDB, SPUTNIK), as well as the databases for the comprehensive set of genomes (PEDANT genomes) are described elsewhere in the 2003 and 2004 NAR database issues, respectively. All databases described, and the detailed descriptions of our projects can be accessed through the MIPS web server (http://mips.gsf.de). PMID:14681354

MIPS: analysis and annotation of proteins from whole genomes.

PubMed

Mewes, H W; Amid, C; Arnold, R; Frishman, D; Güldener, U; Mannhaupt, G; Münsterkötter, M; Pagel, P; Strack, N; Stümpflen, V; Warfsmann, J; Ruepp, A

2004-01-01

The Munich Information Center for Protein Sequences (MIPS-GSF), Neuherberg, Germany, provides protein sequence-related information based on whole-genome analysis. The main focus of the work is directed toward the systematic organization of sequence-related attributes as gathered by a variety of algorithms, primary information from experimental data together with information compiled from the scientific literature. MIPS maintains automatically generated and manually annotated genome-specific databases, develops systematic classification schemes for the functional annotation of protein sequences and provides tools for the comprehensive analysis of protein sequences. This report updates the information on the yeast genome (CYGD), the Neurospora crassa genome (MNCDB), the database of complete cDNAs (German Human Genome Project, NGFN), the database of mammalian protein-protein interactions (MPPI), the database of FASTA homologies (SIMAP), and the interface for the fast retrieval of protein-associated information (QUIPOS). The Arabidopsis thaliana database, the rice database, the plant EST databases (MATDB, MOsDB, SPUTNIK), as well as the databases for the comprehensive set of genomes (PEDANT genomes) are described elsewhere in the 2003 and 2004 NAR database issues, respectively. All databases described, and the detailed descriptions of our projects can be accessed through the MIPS web server (http://mips.gsf.de).

GenomeRNAi: a database for cell-based RNAi phenotypes.

PubMed

Horn, Thomas; Arziman, Zeynep; Berger, Juerg; Boutros, Michael

2007-01-01

RNA interference (RNAi) has emerged as a powerful tool to generate loss-of-function phenotypes in a variety of organisms. Combined with the sequence information of almost completely annotated genomes, RNAi technologies have opened new avenues to conduct systematic genetic screens for every annotated gene in the genome. As increasing large datasets of RNAi-induced phenotypes become available, an important challenge remains the systematic integration and annotation of functional information. Genome-wide RNAi screens have been performed both in Caenorhabditis elegans and Drosophila for a variety of phenotypes and several RNAi libraries have become available to assess phenotypes for almost every gene in the genome. These screens were performed using different types of assays from visible phenotypes to focused transcriptional readouts and provide a rich data source for functional annotation across different species. The GenomeRNAi database provides access to published RNAi phenotypes obtained from cell-based screens and maps them to their genomic locus, including possible non-specific regions. The database also gives access to sequence information of RNAi probes used in various screens. It can be searched by phenotype, by gene, by RNAi probe or by sequence and is accessible at http://rnai.dkfz.de.

GenomeRNAi: a database for cell-based RNAi phenotypes

PubMed Central

Horn, Thomas; Arziman, Zeynep; Berger, Juerg; Boutros, Michael

2007-01-01

RNA interference (RNAi) has emerged as a powerful tool to generate loss-of-function phenotypes in a variety of organisms. Combined with the sequence information of almost completely annotated genomes, RNAi technologies have opened new avenues to conduct systematic genetic screens for every annotated gene in the genome. As increasing large datasets of RNAi-induced phenotypes become available, an important challenge remains the systematic integration and annotation of functional information. Genome-wide RNAi screens have been performed both in Caenorhabditis elegans and Drosophila for a variety of phenotypes and several RNAi libraries have become available to assess phenotypes for almost every gene in the genome. These screens were performed using different types of assays from visible phenotypes to focused transcriptional readouts and provide a rich data source for functional annotation across different species. The GenomeRNAi database provides access to published RNAi phenotypes obtained from cell-based screens and maps them to their genomic locus, including possible non-specific regions. The database also gives access to sequence information of RNAi probes used in various screens. It can be searched by phenotype, by gene, by RNAi probe or by sequence and is accessible at PMID:17135194

Complete Chloroplast Genome Sequence and Annotation of the Tropical japonica Group of Asian Cultivated Rice (Oryza sativa L.)

PubMed Central

Wang, Shuo

2016-01-01

We announce here the first complete chloroplast genome sequence of the tropical japonica rice, along with its genome structure and functional annotation. The plant was collected from Indonesia and deposited as a germplasm accession of the International Rice GenBank Collection (IRGC 66630) at the International Rice Research Institute (IRRI). This genome provides valuable data for the future utilization of the germplasm of rice. PMID:26893422

Dfam: a database of repetitive DNA based on profile hidden Markov models.

PubMed

Wheeler, Travis J; Clements, Jody; Eddy, Sean R; Hubley, Robert; Jones, Thomas A; Jurka, Jerzy; Smit, Arian F A; Finn, Robert D

2013-01-01

We present a database of repetitive DNA elements, called Dfam (http://dfam.janelia.org). Many genomes contain a large fraction of repetitive DNA, much of which is made up of remnants of transposable elements (TEs). Accurate annotation of TEs enables research into their biology and can shed light on the evolutionary processes that shape genomes. Identification and masking of TEs can also greatly simplify many downstream genome annotation and sequence analysis tasks. The commonly used TE annotation tools RepeatMasker and Censor depend on sequence homology search tools such as cross_match and BLAST variants, as well as Repbase, a collection of known TE families each represented by a single consensus sequence. Dfam contains entries corresponding to all Repbase TE entries for which instances have been found in the human genome. Each Dfam entry is represented by a profile hidden Markov model, built from alignments generated using RepeatMasker and Repbase. When used in conjunction with the hidden Markov model search tool nhmmer, Dfam produces a 2.9% increase in coverage over consensus sequence search methods on a large human benchmark, while maintaining low false discovery rates, and coverage of the full human genome is 54.5%. The website provides a collection of tools and data views to support improved TE curation and annotation efforts. Dfam is also available for download in flat file format or in the form of MySQL table dumps.

Transcriptome sequencing and annotation for the Jamaican fruit bat (Artibeus jamaicensis).

PubMed

Shaw, Timothy I; Srivastava, Anuj; Chou, Wen-Chi; Liu, Liang; Hawkinson, Ann; Glenn, Travis C; Adams, Rick; Schountz, Tony

2012-01-01

The Jamaican fruit bat (Artibeus jamaicensis) is one of the most common bats in the tropical Americas. It is thought to be a potential reservoir host of Tacaribe virus, an arenavirus closely related to the South American hemorrhagic fever viruses. We performed transcriptome sequencing and annotation from lung, kidney and spleen tissues using 454 and Illumina platforms to develop this species as an animal model. More than 100,000 contigs were assembled, with 25,000 genes that were functionally annotated. Of the remaining unannotated contigs, 80% were found within bat genomes or transcriptomes. Annotated genes are involved in a broad range of activities ranging from cellular metabolism to genome regulation through ncRNAs. Reciprocal BLAST best hits yielded 8,785 sequences that are orthologous to mouse, rat, cattle, horse and human. Species tree analysis of sequences from 2,378 loci was used to achieve 95% bootstrap support for the placement of bat as sister to the clade containing horse, dog, and cattle. Through substitution rate estimation between bat and human, 32 genes were identified with evidence for positive selection. We also identified 466 immune-related genes, which may be useful for studying Tacaribe virus infection of this species. The Jamaican fruit bat transcriptome dataset is a resource that should provide additional candidate markers for studying bat evolution and ecology, and tools for analysis of the host response and pathology of disease.

Improved systematic tRNA gene annotation allows new insights into the evolution of mitochondrial tRNA structures and into the mechanisms of mitochondrial genome rearrangements

PubMed Central

Jühling, Frank; Pütz, Joern; Bernt, Matthias; Donath, Alexander; Middendorf, Martin; Florentz, Catherine; Stadler, Peter F.

2012-01-01

Transfer RNAs (tRNAs) are present in all types of cells as well as in organelles. tRNAs of animal mitochondria show a low level of primary sequence conservation and exhibit ‘bizarre’ secondary structures, lacking complete domains of the common cloverleaf. Such sequences are hard to detect and hence frequently missed in computational analyses and mitochondrial genome annotation. Here, we introduce an automatic annotation procedure for mitochondrial tRNA genes in Metazoa based on sequence and structural information in manually curated covariance models. The method, applied to re-annotate 1876 available metazoan mitochondrial RefSeq genomes, allows to distinguish between remaining functional genes and degrading ‘pseudogenes’, even at early stages of divergence. The subsequent analysis of a comprehensive set of mitochondrial tRNA genes gives new insights into the evolution of structures of mitochondrial tRNA sequences as well as into the mechanisms of genome rearrangements. We find frequent losses of tRNA genes concentrated in basal Metazoa, frequent independent losses of individual parts of tRNA genes, particularly in Arthropoda, and wide-spread conserved overlaps of tRNAs in opposite reading direction. Direct evidence for several recent Tandem Duplication-Random Loss events is gained, demonstrating that this mechanism has an impact on the appearance of new mitochondrial gene orders. PMID:22139921

cnvScan: a CNV screening and annotation tool to improve the clinical utility of computational CNV prediction from exome sequencing data.

PubMed

Samarakoon, Pubudu Saneth; Sorte, Hanne Sørmo; Stray-Pedersen, Asbjørg; Rødningen, Olaug Kristin; Rognes, Torbjørn; Lyle, Robert

2016-01-14

With advances in next generation sequencing technology and analysis methods, single nucleotide variants (SNVs) and indels can be detected with high sensitivity and specificity in exome sequencing data. Recent studies have demonstrated the ability to detect disease-causing copy number variants (CNVs) in exome sequencing data. However, exonic CNV prediction programs have shown high false positive CNV counts, which is the major limiting factor for the applicability of these programs in clinical studies. We have developed a tool (cnvScan) to improve the clinical utility of computational CNV prediction in exome data. cnvScan can accept input from any CNV prediction program. cnvScan consists of two steps: CNV screening and CNV annotation. CNV screening evaluates CNV prediction using quality scores and refines this using an in-house CNV database, which greatly reduces the false positive rate. The annotation step provides functionally and clinically relevant information using multiple source datasets. We assessed the performance of cnvScan on CNV predictions from five different prediction programs using 64 exomes from Primary Immunodeficiency (PIDD) patients, and identified PIDD-causing CNVs in three individuals from two different families. In summary, cnvScan reduces the time and effort required to detect disease-causing CNVs by reducing the false positive count and providing annotation. This improves the clinical utility of CNV detection in exome data.

Introduction to the fathead minnow genome browser and ...

EPA Pesticide Factsheets

Ab initio gene prediction and evidence alignment were used to produce the first annotations for the fathead minnow SOAPdenovo genome assembly. Additionally, a genome browser hosted at genome.setac.org provides simplified access to the annotation data in context with fathead minnow genomic sequence. This work is meant to extend the utility of fathead minnow genome as a resource and enable the continued development of this species as a model organism. The fathead minnow (Pimephales promelas) is a laboratory model organism widely used in regulatory toxicity testing and ecotoxicology research. Despite, the wealth of toxicological data for this organism, until recently genome scale information was lacking for the species, which limited the utility of the species for pathway-based toxicity testing and research. As part of a EPA Pathfinder Innovation Project, next generation sequencing was applied to generate a draft genome assembly, which was published in 2016. However, application of those genome-scale sequencing resources was still limited by the lack of available gene annotations for fathead minnow. Here we report on development of a first generation genome annotation for fathead minnow and the dissemination of that information through a web-based browser that makes it easy to search for genes of interest, extract the corresponding sequence, identify intron and exon boundaries and regulatory regions, and align the computationally predicted genes with other supporti

Transcriptome-based differentiation of closely-related Miscanthus lines.

PubMed

Chouvarine, Philippe; Cooksey, Amanda M; McCarthy, Fiona M; Ray, David A; Baldwin, Brian S; Burgess, Shane C; Peterson, Daniel G

2012-01-01

Distinguishing between individuals is critical to those conducting animal/plant breeding, food safety/quality research, diagnostic and clinical testing, and evolutionary biology studies. Classical genetic identification studies are based on marker polymorphisms, but polymorphism-based techniques are time and labor intensive and often cannot distinguish between closely related individuals. Illumina sequencing technologies provide the detailed sequence data required for rapid and efficient differentiation of related species, lines/cultivars, and individuals in a cost-effective manner. Here we describe the use of Illumina high-throughput exome sequencing, coupled with SNP mapping, as a rapid means of distinguishing between related cultivars of the lignocellulosic bioenergy crop giant miscanthus (Miscanthus × giganteus). We provide the first exome sequence database for Miscanthus species complete with Gene Ontology (GO) functional annotations. A SNP comparative analysis of rhizome-derived cDNA sequences was successfully utilized to distinguish three Miscanthus × giganteus cultivars from each other and from other Miscanthus species. Moreover, the resulting phylogenetic tree generated from SNP frequency data parallels the known breeding history of the plants examined. Some of the giant miscanthus plants exhibit considerable sequence divergence. Here we describe an analysis of Miscanthus in which high-throughput exome sequencing was utilized to differentiate between closely related genotypes despite the current lack of a reference genome sequence. We functionally annotated the exome sequences and provide resources to support Miscanthus systems biology. In addition, we demonstrate the use of the commercial high-performance cloud computing to do computational GO annotation.

A computational genomics pipeline for prokaryotic sequencing projects.

PubMed

Kislyuk, Andrey O; Katz, Lee S; Agrawal, Sonia; Hagen, Matthew S; Conley, Andrew B; Jayaraman, Pushkala; Nelakuditi, Viswateja; Humphrey, Jay C; Sammons, Scott A; Govil, Dhwani; Mair, Raydel D; Tatti, Kathleen M; Tondella, Maria L; Harcourt, Brian H; Mayer, Leonard W; Jordan, I King

2010-08-01

New sequencing technologies have accelerated research on prokaryotic genomes and have made genome sequencing operations outside major genome sequencing centers routine. However, no off-the-shelf solution exists for the combined assembly, gene prediction, genome annotation and data presentation necessary to interpret sequencing data. The resulting requirement to invest significant resources into custom informatics support for genome sequencing projects remains a major impediment to the accessibility of high-throughput sequence data. We present a self-contained, automated high-throughput open source genome sequencing and computational genomics pipeline suitable for prokaryotic sequencing projects. The pipeline has been used at the Georgia Institute of Technology and the Centers for Disease Control and Prevention for the analysis of Neisseria meningitidis and Bordetella bronchiseptica genomes. The pipeline is capable of enhanced or manually assisted reference-based assembly using multiple assemblers and modes; gene predictor combining; and functional annotation of genes and gene products. Because every component of the pipeline is executed on a local machine with no need to access resources over the Internet, the pipeline is suitable for projects of a sensitive nature. Annotation of virulence-related features makes the pipeline particularly useful for projects working with pathogenic prokaryotes. The pipeline is licensed under the open-source GNU General Public License and available at the Georgia Tech Neisseria Base (http://nbase.biology.gatech.edu/). The pipeline is implemented with a combination of Perl, Bourne Shell and MySQL and is compatible with Linux and other Unix systems.

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.

MIPS: a database for genomes and protein sequences

PubMed Central

Mewes, H. W.; Frishman, D.; Güldener, U.; Mannhaupt, G.; Mayer, K.; Mokrejs, M.; Morgenstern, B.; Münsterkötter, M.; Rudd, S.; Weil, B.

2002-01-01

The Munich Information Center for Protein Sequences (MIPS-GSF, Neuherberg, Germany) continues to provide genome-related information in a systematic way. MIPS supports both national and European sequencing and functional analysis projects, develops and maintains automatically generated and manually annotated genome-specific databases, develops systematic classification schemes for the functional annotation of protein sequences, and provides tools for the comprehensive analysis of protein sequences. This report updates the information on the yeast genome (CYGD), the Neurospora crassa genome (MNCDB), the databases for the comprehensive set of genomes (PEDANT genomes), the database of annotated human EST clusters (HIB), the database of complete cDNAs from the DHGP (German Human Genome Project), as well as the project specific databases for the GABI (Genome Analysis in Plants) and HNB (Helmholtz–Netzwerk Bioinformatik) networks. The Arabidospsis thaliana database (MATDB), the database of mitochondrial proteins (MITOP) and our contribution to the PIR International Protein Sequence Database have been described elsewhere [Schoof et al. (2002) Nucleic Acids Res., 30, 91–93; Scharfe et al. (2000) Nucleic Acids Res., 28, 155–158; Barker et al. (2001) Nucleic Acids Res., 29, 29–32]. All databases described, the protein analysis tools provided and the detailed descriptions of our projects can be accessed through the MIPS World Wide Web server (http://mips.gsf.de). PMID:11752246

MIPS: a database for genomes and protein sequences.

PubMed

Mewes, H W; Frishman, D; Güldener, U; Mannhaupt, G; Mayer, K; Mokrejs, M; Morgenstern, B; Münsterkötter, M; Rudd, S; Weil, B

2002-01-01

The Munich Information Center for Protein Sequences (MIPS-GSF, Neuherberg, Germany) continues to provide genome-related information in a systematic way. MIPS supports both national and European sequencing and functional analysis projects, develops and maintains automatically generated and manually annotated genome-specific databases, develops systematic classification schemes for the functional annotation of protein sequences, and provides tools for the comprehensive analysis of protein sequences. This report updates the information on the yeast genome (CYGD), the Neurospora crassa genome (MNCDB), the databases for the comprehensive set of genomes (PEDANT genomes), the database of annotated human EST clusters (HIB), the database of complete cDNAs from the DHGP (German Human Genome Project), as well as the project specific databases for the GABI (Genome Analysis in Plants) and HNB (Helmholtz-Netzwerk Bioinformatik) networks. The Arabidospsis thaliana database (MATDB), the database of mitochondrial proteins (MITOP) and our contribution to the PIR International Protein Sequence Database have been described elsewhere [Schoof et al. (2002) Nucleic Acids Res., 30, 91-93; Scharfe et al. (2000) Nucleic Acids Res., 28, 155-158; Barker et al. (2001) Nucleic Acids Res., 29, 29-32]. All databases described, the protein analysis tools provided and the detailed descriptions of our projects can be accessed through the MIPS World Wide Web server (http://mips.gsf.de).

The distributed annotation system.

PubMed

Dowell, R D; Jokerst, R M; Day, A; Eddy, S R; Stein, L

2001-01-01

Currently, most genome annotation is curated by centralized groups with limited resources. Efforts to share annotations transparently among multiple groups have not yet been satisfactory. Here we introduce a concept called the Distributed Annotation System (DAS). DAS allows sequence annotations to be decentralized among multiple third-party annotators and integrated on an as-needed basis by client-side software. The communication between client and servers in DAS is defined by the DAS XML specification. Annotations are displayed in layers, one per server. Any client or server adhering to the DAS XML specification can participate in the system; we describe a simple prototype client and server example. The DAS specification is being used experimentally by Ensembl, WormBase, and the Berkeley Drosophila Genome Project. Continued success will depend on the readiness of the research community to adopt DAS and provide annotations. All components are freely available from the project website http://www.biodas.org/.

CSTminer: a web tool for the identification of coding and noncoding conserved sequence tags through cross-species genome comparison

PubMed Central

Castrignanò, Tiziana; Canali, Alessandro; Grillo, Giorgio; Liuni, Sabino; Mignone, Flavio; Pesole, Graziano

2004-01-01

The identification and characterization of genome tracts that are highly conserved across species during evolution may contribute significantly to the functional annotation of whole-genome sequences. Indeed, such sequences are likely to correspond to known or unknown coding exons or regulatory motifs. Here, we present a web server implementing a previously developed algorithm that, by comparing user-submitted genome sequences, is able to identify statistically significant conserved blocks and assess their coding or noncoding nature through the measure of a coding potential score. The web tool, available at http://www.caspur.it/CSTminer/, is dynamically interconnected with the Ensembl genome resources and produces a graphical output showing a map of detected conserved sequences and annotated gene features. PMID:15215464

BioModels.net Web Services, a free and integrated toolkit for computational modelling software.

PubMed

Li, Chen; Courtot, Mélanie; Le Novère, Nicolas; Laibe, Camille

2010-05-01

Exchanging and sharing scientific results are essential for researchers in the field of computational modelling. BioModels.net defines agreed-upon standards for model curation. A fundamental one, MIRIAM (Minimum Information Requested in the Annotation of Models), standardises the annotation and curation process of quantitative models in biology. To support this standard, MIRIAM Resources maintains a set of standard data types for annotating models, and provides services for manipulating these annotations. Furthermore, BioModels.net creates controlled vocabularies, such as SBO (Systems Biology Ontology) which strictly indexes, defines and links terms used in Systems Biology. Finally, BioModels Database provides a free, centralised, publicly accessible database for storing, searching and retrieving curated and annotated computational models. Each resource provides a web interface to submit, search, retrieve and display its data. In addition, the BioModels.net team provides a set of Web Services which allows the community to programmatically access the resources. A user is then able to perform remote queries, such as retrieving a model and resolving all its MIRIAM Annotations, as well as getting the details about the associated SBO terms. These web services use established standards. Communications rely on SOAP (Simple Object Access Protocol) messages and the available queries are described in a WSDL (Web Services Description Language) file. Several libraries are provided in order to simplify the development of client software. BioModels.net Web Services make one step further for the researchers to simulate and understand the entirety of a biological system, by allowing them to retrieve biological models in their own tool, combine queries in workflows and efficiently analyse models.

A Molecular Framework for Understanding DCIS

DTIC Science & Technology

2016-10-01

well. Pathologic and Clinical Annotation Database A clinical annotation database titled the Breast Oncology Database has been established to...complement the procured SPORE sample characteristics and annotated pathology data. This Breast Oncology Database is an offsite clinical annotation...database adheres to CSMC Enterprise Information Services (EIS) research database security standards. The Breast Oncology Database consists of: 9 Baseline

WikiGenomes: an open web application for community consumption and curation of gene annotation data in Wikidata

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

Putman, Tim E.; Lelong, Sebastien; Burgstaller-Muehlbacher, Sebastian

With the advancement of genome-sequencing technologies, new genomes are being sequenced daily. Although these sequences are deposited in publicly available data warehouses, their functional and genomic annotations (beyond genes which are predicted automatically) mostly reside in the text of primary publications. Professional curators are hard at work extracting those annotations from the literature for the most studied organisms and depositing them in structured databases. However, the resources don’t exist to fund the comprehensive curation of the thousands of newly sequenced organisms in this manner. Here, we describe WikiGenomes (wikigenomes.org), a web application that facilitates the consumption and curation of genomicmore » data by the entire scientific community. WikiGenomes is based on Wikidata, an openly editable knowledge graph with the goal of aggregating published knowledge into a free and open database. WikiGenomes empowers the individual genomic researcher to contribute their expertise to the curation effort and integrates the knowledge into Wikidata, enabling it to be accessed by anyone without restriction.« less

WikiGenomes: an open web application for community consumption and curation of gene annotation data in Wikidata

DOE PAGES

Putman, Tim E.; Lelong, Sebastien; Burgstaller-Muehlbacher, Sebastian; ...

2017-03-06

With the advancement of genome-sequencing technologies, new genomes are being sequenced daily. Although these sequences are deposited in publicly available data warehouses, their functional and genomic annotations (beyond genes which are predicted automatically) mostly reside in the text of primary publications. Professional curators are hard at work extracting those annotations from the literature for the most studied organisms and depositing them in structured databases. However, the resources don’t exist to fund the comprehensive curation of the thousands of newly sequenced organisms in this manner. Here, we describe WikiGenomes (wikigenomes.org), a web application that facilitates the consumption and curation of genomicmore » data by the entire scientific community. WikiGenomes is based on Wikidata, an openly editable knowledge graph with the goal of aggregating published knowledge into a free and open database. WikiGenomes empowers the individual genomic researcher to contribute their expertise to the curation effort and integrates the knowledge into Wikidata, enabling it to be accessed by anyone without restriction.« less

A database of annotated tentative orthologs from crop abiotic stress transcripts.

PubMed

Balaji, Jayashree; Crouch, Jonathan H; Petite, Prasad V N S; Hoisington, David A

2006-10-07

A minimal requirement to initiate a comparative genomics study on plant responses to abiotic stresses is a dataset of orthologous sequences. The availability of a large amount of sequence information, including those derived from stress cDNA libraries allow for the identification of stress related genes and orthologs associated with the stress response. Orthologous sequences serve as tools to explore genes and their relationships across species. For this purpose, ESTs from stress cDNA libraries across 16 crop species including 6 important cereal crops and 10 dicots were systematically collated and subjected to bioinformatics analysis such as clustering, grouping of tentative orthologous sets, identification of protein motifs/patterns in the predicted protein sequence, and annotation with stress conditions, tissue/library source and putative function. All data are available to the scientific community at http://intranet.icrisat.org/gt1/tog/homepage.htm. We believe that the availability of annotated plant abiotic stress ortholog sets will be a valuable resource for researchers studying the biology of environmental stresses in plant systems, molecular evolution and genomics.

Automatic annotation of protein motif function with Gene Ontology terms.

PubMed

Lu, Xinghua; Zhai, Chengxiang; Gopalakrishnan, Vanathi; Buchanan, Bruce G

2004-09-02

Conserved protein sequence motifs are short stretches of amino acid sequence patterns that potentially encode the function of proteins. Several sequence pattern searching algorithms and programs exist foridentifying candidate protein motifs at the whole genome level. However, a much needed and important task is to determine the functions of the newly identified protein motifs. The Gene Ontology (GO) project is an endeavor to annotate the function of genes or protein sequences with terms from a dynamic, controlled vocabulary and these annotations serve well as a knowledge base. This paper presents methods to mine the GO knowledge base and use the association between the GO terms assigned to a sequence and the motifs matched by the same sequence as evidence for predicting the functions of novel protein motifs automatically. The task of assigning GO terms to protein motifs is viewed as both a binary classification and information retrieval problem, where PROSITE motifs are used as samples for mode training and functional prediction. The mutual information of a motif and aGO term association is found to be a very useful feature. We take advantage of the known motifs to train a logistic regression classifier, which allows us to combine mutual information with other frequency-based features and obtain a probability of correct association. The trained logistic regression model has intuitively meaningful and logically plausible parameter values, and performs very well empirically according to our evaluation criteria. In this research, different methods for automatic annotation of protein motifs have been investigated. Empirical result demonstrated that the methods have a great potential for detecting and augmenting information about the functions of newly discovered candidate protein motifs.

Integrative specimen information service - a campus-wide resource for tissue banking, experimental data annotation, and analysis services.

PubMed

Schadow, Gunther; Dhaval, Rakesh; McDonald, Clement J; Ragg, Susanne

2006-01-01

We present the architecture and approach of an evolving campus-wide information service for tissues with clinical and data annotations to be used and contributed to by clinical researchers across the campus. The services provided include specimen tracking, long term data storage, and computational analysis services. The project is conceived and sustained by collaboration among researchers on the campus as well as participation in standards organizations and national collaboratives.

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.

Using phylogenetically-informed annotation (PIA) to search for light-interacting genes in transcriptomes from non-model organisms.

PubMed

Speiser, Daniel I; Pankey, M Sabrina; Zaharoff, Alexander K; Battelle, Barbara A; Bracken-Grissom, Heather D; Breinholt, Jesse W; Bybee, Seth M; Cronin, Thomas W; Garm, Anders; Lindgren, Annie R; Patel, Nipam H; Porter, Megan L; Protas, Meredith E; Rivera, Ajna S; Serb, Jeanne M; Zigler, Kirk S; Crandall, Keith A; Oakley, Todd H

2014-11-19

Tools for high throughput sequencing and de novo assembly make the analysis of transcriptomes (i.e. the suite of genes expressed in a tissue) feasible for almost any organism. Yet a challenge for biologists is that it can be difficult to assign identities to gene sequences, especially from non-model organisms. Phylogenetic analyses are one useful method for assigning identities to these sequences, but such methods tend to be time-consuming because of the need to re-calculate trees for every gene of interest and each time a new data set is analyzed. In response, we employed existing tools for phylogenetic analysis to produce a computationally efficient, tree-based approach for annotating transcriptomes or new genomes that we term Phylogenetically-Informed Annotation (PIA), which places uncharacterized genes into pre-calculated phylogenies of gene families. We generated maximum likelihood trees for 109 genes from a Light Interaction Toolkit (LIT), a collection of genes that underlie the function or development of light-interacting structures in metazoans. To do so, we searched protein sequences predicted from 29 fully-sequenced genomes and built trees using tools for phylogenetic analysis in the Osiris package of Galaxy (an open-source workflow management system). Next, to rapidly annotate transcriptomes from organisms that lack sequenced genomes, we repurposed a maximum likelihood-based Evolutionary Placement Algorithm (implemented in RAxML) to place sequences of potential LIT genes on to our pre-calculated gene trees. Finally, we implemented PIA in Galaxy and used it to search for LIT genes in 28 newly-sequenced transcriptomes from the light-interacting tissues of a range of cephalopod mollusks, arthropods, and cubozoan cnidarians. Our new trees for LIT genes are available on the Bitbucket public repository ( http://bitbucket.org/osiris_phylogenetics/pia/ ) and we demonstrate PIA on a publicly-accessible web server ( http://galaxy-dev.cnsi.ucsb.edu/pia/ ). Our new trees for LIT genes will be a valuable resource for researchers studying the evolution of eyes or other light-interacting structures. We also introduce PIA, a high throughput method for using phylogenetic relationships to identify LIT genes in transcriptomes from non-model organisms. With simple modifications, our methods may be used to search for different sets of genes or to annotate data sets from taxa outside of Metazoa.

In silico analysis of expressed sequence tags from Trichostrongylus vitrinus (Nematoda): comparison of the automated ESTExplorer workflow platform with conventional database searches.

PubMed

Nagaraj, Shivashankar H; Gasser, Robin B; Nisbet, Alasdair J; Ranganathan, Shoba

2008-01-01

The analysis of expressed sequence tags (EST) offers a rapid and cost effective approach to elucidate the transcriptome of an organism, but requires several computational methods for assembly and annotation. Researchers frequently analyse each step manually, which is laborious and time consuming. We have recently developed ESTExplorer, a semi-automated computational workflow system, in order to achieve the rapid analysis of EST datasets. In this study, we evaluated EST data analysis for the parasitic nematode Trichostrongylus vitrinus (order Strongylida) using ESTExplorer, compared with database matching alone. We functionally annotated 1776 ESTs obtained via suppressive-subtractive hybridisation from T. vitrinus, an important parasitic trichostrongylid of small ruminants. Cluster and comparative genomic analyses of the transcripts using ESTExplorer indicated that 290 (41%) sequences had homologues in Caenorhabditis elegans, 329 (42%) in parasitic nematodes, 202 (28%) in organisms other than nematodes, and 218 (31%) had no significant match to any sequence in the current databases. Of the C. elegans homologues, 90 were associated with 'non-wildtype' double-stranded RNA interference (RNAi) phenotypes, including embryonic lethality, maternal sterility, sterile progeny, larval arrest and slow growth. We could functionally classify 267 (38%) sequences using the Gene Ontologies (GO) and establish pathway associations for 230 (33%) sequences using the Kyoto Encyclopedia of Genes and Genomes (KEGG). Further examination of this EST dataset revealed a number of signalling molecules, proteases, protease inhibitors, enzymes, ion channels and immune-related genes. In addition, we identified 40 putative secreted proteins that could represent potential candidates for developing novel anthelmintics or vaccines. We further compared the automated EST sequence annotations, using ESTExplorer, with database search results for individual T. vitrinus ESTs. ESTExplorer reliably and rapidly annotated 301 ESTs, with pathway and GO information, eliminating 60 low quality hits from database searches. We evaluated the efficacy of ESTExplorer in analysing EST data, and demonstrate that computational tools can be used to accelerate the process of gene discovery in EST sequencing projects. The present study has elucidated sets of relatively conserved and potentially novel genes for biological investigation, and the annotated EST set provides further insight into the molecular biology of T. vitrinus, towards the identification of novel drug targets.

Genome scaffolding and annotation for the pathogen vector Ixodes ricinus by ultra-long single molecule sequencing.

PubMed

Cramaro, Wibke J; Hunewald, Oliver E; Bell-Sakyi, Lesley; Muller, Claude P

2017-02-08

Global warming and other ecological changes have facilitated the expansion of Ixodes ricinus tick populations. Ixodes ricinus is the most important carrier of vector-borne pathogens in Europe, transmitting viruses, protozoa and bacteria, in particular Borrelia burgdorferi (sensu lato), the causative agent of Lyme borreliosis, the most prevalent vector-borne disease in humans in the Northern hemisphere. To faster control this disease vector, a better understanding of the I. ricinus tick is necessary. To facilitate such studies, we recently published the first reference genome of this highly prevalent pathogen vector. Here, we further extend these studies by scaffolding and annotating the first reference genome by using ultra-long sequencing reads from third generation single molecule sequencing. In addition, we present the first genome size estimation for I. ricinus ticks and the embryo-derived cell line IRE/CTVM19. 235,953 contigs were integrated into 204,904 scaffolds, extending the currently known genome lengths by more than 30% from 393 to 516 Mb and the N50 contig value by 87% from 1643 bp to a N50 scaffold value of 3067 bp. In addition, 25,263 sequences were annotated by comparison to the tick's North American relative Ixodes scapularis. After (conserved) hypothetical proteins, zinc finger proteins, secreted proteins and P450 coding proteins were the most prevalent protein categories annotated. Interestingly, more than 50% of the amino acid sequences matching the homology threshold had 95-100% identity to the corresponding I. scapularis gene models. The sequence information was complemented by the first genome size estimation for this species. Flow cytometry-based genome size analysis revealed a haploid genome size of 2.65Gb for I. ricinus ticks and 3.80 Gb for the cell line. We present a first draft sequence map of the I. ricinus genome based on a PacBio-Illumina assembly. The I. ricinus genome was shown to be 26% (500 Mb) larger than the genome of its American relative I. scapularis. Based on the genome size of 2.65 Gb we estimated that we covered about 67% of the non-repetitive sequences. Genome annotation will facilitate screening for specific molecular pathways in I. ricinus cells and provides an overview of characteristics and functions.

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

proGenomes: a resource for consistent functional and taxonomic annotations of prokaryotic genomes.

PubMed

Mende, Daniel R; Letunic, Ivica; Huerta-Cepas, Jaime; Li, Simone S; Forslund, Kristoffer; Sunagawa, Shinichi; Bork, Peer

2017-01-04

The availability of microbial genomes has opened many new avenues of research within microbiology. This has been driven primarily by comparative genomics approaches, which rely on accurate and consistent characterization of genomic sequences. It is nevertheless difficult to obtain consistent taxonomic and integrated functional annotations for defined prokaryotic clades. Thus, we developed proGenomes, a resource that provides user-friendly access to currently 25 038 high-quality genomes whose sequences and consistent annotations can be retrieved individually or by taxonomic clade. These genomes are assigned to 5306 consistent and accurate taxonomic species clusters based on previously established methodology. proGenomes also contains functional information for almost 80 million protein-coding genes, including a comprehensive set of general annotations and more focused annotations for carbohydrate-active enzymes and antibiotic resistance genes. Additionally, broad habitat information is provided for many genomes. All genomes and associated information can be downloaded by user-selected clade or multiple habitat-specific sets of representative genomes. We expect that the availability of high-quality genomes with comprehensive functional annotations will promote advances in clinical microbial genomics, functional evolution and other subfields of microbiology. proGenomes is available at http://progenomes.embl.de. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

NCBI Reference Sequence (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins

PubMed Central

Pruitt, Kim D.; Tatusova, Tatiana; Maglott, Donna R.

2005-01-01

The National Center for Biotechnology Information (NCBI) Reference Sequence (RefSeq) database (http://www.ncbi.nlm.nih.gov/RefSeq/) provides a non-redundant collection of sequences representing genomic data, transcripts and proteins. Although the goal is to provide a comprehensive dataset representing the complete sequence information for any given species, the database pragmatically includes sequence data that are currently publicly available in the archival databases. The database incorporates data from over 2400 organisms and includes over one million proteins representing significant taxonomic diversity spanning prokaryotes, eukaryotes and viruses. Nucleotide and protein sequences are explicitly linked, and the sequences are linked to other resources including the NCBI Map Viewer and Gene. Sequences are annotated to include coding regions, conserved domains, variation, references, names, database cross-references, and other features using a combined approach of collaboration and other input from the scientific community, automated annotation, propagation from GenBank and curation by NCBI staff. PMID:15608248

Exploiting proteomic data for genome annotation and gene model validation in Aspergillus niger

PubMed Central

Wright, James C; Sugden, Deana; Francis-McIntyre, Sue; Riba-Garcia, Isabel; Gaskell, Simon J; Grigoriev, Igor V; Baker, Scott E; Beynon, Robert J; Hubbard, Simon J

2009-01-01

Background Proteomic data is a potentially rich, but arguably unexploited, data source for genome annotation. Peptide identifications from tandem mass spectrometry provide prima facie evidence for gene predictions and can discriminate over a set of candidate gene models. Here we apply this to the recently sequenced Aspergillus niger fungal genome from the Joint Genome Institutes (JGI) and another predicted protein set from another A.niger sequence. Tandem mass spectra (MS/MS) were acquired from 1d gel electrophoresis bands and searched against all available gene models using Average Peptide Scoring (APS) and reverse database searching to produce confident identifications at an acceptable false discovery rate (FDR). Results 405 identified peptide sequences were mapped to 214 different A.niger genomic loci to which 4093 predicted gene models clustered, 2872 of which contained the mapped peptides. Interestingly, 13 (6%) of these loci either had no preferred predicted gene model or the genome annotators' chosen "best" model for that genomic locus was not found to be the most parsimonious match to the identified peptides. The peptides identified also boosted confidence in predicted gene structures spanning 54 introns from different gene models. Conclusion This work highlights the potential of integrating experimental proteomics data into genomic annotation pipelines much as expressed sequence tag (EST) data has been. A comparison of the published genome from another strain of A.niger sequenced by DSM showed that a number of the gene models or proteins with proteomics evidence did not occur in both genomes, further highlighting the utility of the method. PMID:19193216

Complete Chloroplast Genome Sequence and Annotation of the Tropical japonica Group of Asian Cultivated Rice (Oryza sativa L.).

PubMed

Wang, Shuo; Gao, Li-Zhi

2016-02-18

We announce here the first complete chloroplast genome sequence of the tropical japonica rice, along with its genome structure and functional annotation. The plant was collected from Indonesia and deposited as a germplasm accession of the International Rice GenBank Collection (IRGC 66630) at the International Rice Research Institute (IRRI). This genome provides valuable data for the future utilization of the germplasm of rice. Copyright © 2016 Wang and Gao.

PLAN: a web platform for automating high-throughput BLAST searches and for managing and mining results.

PubMed

He, Ji; Dai, Xinbin; Zhao, Xuechun

2007-02-09

BLAST searches are widely used for sequence alignment. The search results are commonly adopted for various functional and comparative genomics tasks such as annotating unknown sequences, investigating gene models and comparing two sequence sets. Advances in sequencing technologies pose challenges for high-throughput analysis of large-scale sequence data. A number of programs and hardware solutions exist for efficient BLAST searching, but there is a lack of generic software solutions for mining and personalized management of the results. Systematically reviewing the results and identifying information of interest remains tedious and time-consuming. Personal BLAST Navigator (PLAN) is a versatile web platform that helps users to carry out various personalized pre- and post-BLAST tasks, including: (1) query and target sequence database management, (2) automated high-throughput BLAST searching, (3) indexing and searching of results, (4) filtering results online, (5) managing results of personal interest in favorite categories, (6) automated sequence annotation (such as NCBI NR and ontology-based annotation). PLAN integrates, by default, the Decypher hardware-based BLAST solution provided by Active Motif Inc. with a greatly improved efficiency over conventional BLAST software. BLAST results are visualized by spreadsheets and graphs and are full-text searchable. BLAST results and sequence annotations can be exported, in part or in full, in various formats including Microsoft Excel and FASTA. Sequences and BLAST results are organized in projects, the data publication levels of which are controlled by the registered project owners. In addition, all analytical functions are provided to public users without registration. PLAN has proved a valuable addition to the community for automated high-throughput BLAST searches, and, more importantly, for knowledge discovery, management and sharing based on sequence alignment results. The PLAN web interface is platform-independent, easily configurable and capable of comprehensive expansion, and user-intuitive. PLAN is freely available to academic users at http://bioinfo.noble.org/plan/. The source code for local deployment is provided under free license. Full support on system utilization, installation, configuration and customization are provided to academic users.

PLAN: a web platform for automating high-throughput BLAST searches and for managing and mining results

PubMed Central

He, Ji; Dai, Xinbin; Zhao, Xuechun

2007-01-01

Background BLAST searches are widely used for sequence alignment. The search results are commonly adopted for various functional and comparative genomics tasks such as annotating unknown sequences, investigating gene models and comparing two sequence sets. Advances in sequencing technologies pose challenges for high-throughput analysis of large-scale sequence data. A number of programs and hardware solutions exist for efficient BLAST searching, but there is a lack of generic software solutions for mining and personalized management of the results. Systematically reviewing the results and identifying information of interest remains tedious and time-consuming. Results Personal BLAST Navigator (PLAN) is a versatile web platform that helps users to carry out various personalized pre- and post-BLAST tasks, including: (1) query and target sequence database management, (2) automated high-throughput BLAST searching, (3) indexing and searching of results, (4) filtering results online, (5) managing results of personal interest in favorite categories, (6) automated sequence annotation (such as NCBI NR and ontology-based annotation). PLAN integrates, by default, the Decypher hardware-based BLAST solution provided by Active Motif Inc. with a greatly improved efficiency over conventional BLAST software. BLAST results are visualized by spreadsheets and graphs and are full-text searchable. BLAST results and sequence annotations can be exported, in part or in full, in various formats including Microsoft Excel and FASTA. Sequences and BLAST results are organized in projects, the data publication levels of which are controlled by the registered project owners. In addition, all analytical functions are provided to public users without registration. Conclusion PLAN has proved a valuable addition to the community for automated high-throughput BLAST searches, and, more importantly, for knowledge discovery, management and sharing based on sequence alignment results. The PLAN web interface is platform-independent, easily configurable and capable of comprehensive expansion, and user-intuitive. PLAN is freely available to academic users at . The source code for local deployment is provided under free license. Full support on system utilization, installation, configuration and customization are provided to academic users. PMID:17291345

The pig X and Y Chromosomes: structure, sequence, and evolution

PubMed Central

Skinner, Benjamin M.; Sargent, Carole A.; Churcher, Carol; Hunt, Toby; Herrero, Javier; Loveland, Jane E.; Dunn, Matt; Louzada, Sandra; Fu, Beiyuan; Chow, William; Gilbert, James; Austin-Guest, Siobhan; Beal, Kathryn; Carvalho-Silva, Denise; Cheng, William; Gordon, Daria; Grafham, Darren; Hardy, Matt; Harley, Jo; Hauser, Heidi; Howden, Philip; Howe, Kerstin; Lachani, Kim; Ellis, Peter J.I.; Kelly, Daniel; Kerry, Giselle; Kerwin, James; Ng, Bee Ling; Threadgold, Glen; Wileman, Thomas; Wood, Jonathan M.D.; Yang, Fengtang; Harrow, Jen; Affara, Nabeel A.; Tyler-Smith, Chris

2016-01-01

We have generated an improved assembly and gene annotation of the pig X Chromosome, and a first draft assembly of the pig Y Chromosome, by sequencing BAC and fosmid clones from Duroc animals and incorporating information from optical mapping and fiber-FISH. The X Chromosome carries 1033 annotated genes, 690 of which are protein coding. Gene order closely matches that found in primates (including humans) and carnivores (including cats and dogs), which is inferred to be ancestral. Nevertheless, several protein-coding genes present on the human X Chromosome were absent from the pig, and 38 pig-specific X-chromosomal genes were annotated, 22 of which were olfactory receptors. The pig Y-specific Chromosome sequence generated here comprises 30 megabases (Mb). A 15-Mb subset of this sequence was assembled, revealing two clusters of male-specific low copy number genes, separated by an ampliconic region including the HSFY gene family, which together make up most of the short arm. Both clusters contain palindromes with high sequence identity, presumably maintained by gene conversion. Many of the ancestral X-related genes previously reported in at least one mammalian Y Chromosome are represented either as active genes or partial sequences. This sequencing project has allowed us to identify genes—both single copy and amplified—on the pig Y Chromosome, to compare the pig X and Y Chromosomes for homologous sequences, and thereby to reveal mechanisms underlying pig X and Y Chromosome evolution. PMID:26560630

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.

Genome-wide transcription start site profiling in biofilm-grown Burkholderia cenocepacia J2315.

PubMed

Sass, Andrea M; Van Acker, Heleen; Förstner, Konrad U; Van Nieuwerburgh, Filip; Deforce, Dieter; Vogel, Jörg; Coenye, Tom

2015-10-13

Burkholderia cenocepacia is a soil-dwelling Gram-negative Betaproteobacterium with an important role as opportunistic pathogen in humans. Infections with B. cenocepacia are very difficult to treat due to their high intrinsic resistance to most antibiotics. Biofilm formation further adds to their antibiotic resistance. B. cenocepacia harbours a large, multi-replicon genome with a high GC-content, the reference genome of strain J2315 includes 7374 annotated genes. This study aims to annotate transcription start sites and identify novel transcripts on a whole genome scale. RNA extracted from B. cenocepacia J2315 biofilms was analysed by differential RNA-sequencing and the resulting dataset compared to data derived from conventional, global RNA-sequencing. Transcription start sites were annotated and further analysed according to their position relative to annotated genes. Four thousand ten transcription start sites were mapped over the whole B. cenocepacia genome and the primary transcription start site of 2089 genes expressed in B. cenocepacia biofilms were defined. For 64 genes a start codon alternative to the annotated one was proposed. Substantial antisense transcription for 105 genes and two novel protein coding sequences were identified. The distribution of internal transcription start sites can be used to identify genomic islands in B. cenocepacia. A potassium pump strongly induced only under biofilm conditions was found and 15 non-coding small RNAs highly expressed in biofilms were discovered. Mapping transcription start sites across the B. cenocepacia genome added relevant information to the J2315 annotation. Genes and novel regulatory RNAs putatively involved in B. cenocepacia biofilm formation were identified. These findings will help in understanding regulation of B. cenocepacia biofilm formation.

Extending SEQenv: a taxa-centric approach to environmental annotations of 16S rDNA sequences

PubMed Central

Jeffries, Thomas C.; Ijaz, Umer Z.; Hamonts, Kelly

2017-01-01

Understanding how the environment selects a given taxon and the diversity patterns that emerge as a result of environmental filtering can dramatically improve our ability to analyse any environment in depth as well as advancing our knowledge on how the response of different taxa can impact each other and ecosystem functions. Most of the work investigating microbial biogeography has been site-specific, and logical environmental factors, rather than geographical location, may be more influential on microbial diversity. SEQenv, a novel pipeline aiming to provide environmental annotations of sequences emerged to provide a consistent description of the environmental niches using the ENVO ontology. While the pipeline provides a list of environmental terms on the basis of sample datasets and, therefore, the annotations obtained are at the dataset level, it lacks a taxa centric approach to environmental annotation. The work here describes an extension developed to enhance the SEQenv pipeline, which provided the means to directly generate environmental annotations for taxa under different contexts. 16S rDNA amplicon datasets belonging to distinct biomes were selected to illustrate the applicability of the extended SEQenv pipeline. A literature survey of the results demonstrates the immense importance of sequence level environmental annotations by illustrating the distribution of both taxa across environments as well as the various environmental sources of a specific taxon. Significantly enhancing the SEQenv pipeline in the process, this information would be valuable to any biologist seeking to understand the various taxa present in the habitat and the environment they originated from, enabling a more thorough analysis of which lineages are abundant in certain habitats and the recovery of patterns in taxon distribution across different habitats and environmental gradients. PMID:29038749

ESTuber db: an online database for Tuber borchii EST sequences.

PubMed

Lazzari, Barbara; Caprera, Andrea; Cosentino, Cristian; Stella, Alessandra; Milanesi, Luciano; Viotti, Angelo

2007-03-08

The ESTuber database (http://www.itb.cnr.it/estuber) includes 3,271 Tuber borchii expressed sequence tags (EST). The dataset consists of 2,389 sequences from an in-house prepared cDNA library from truffle vegetative hyphae, and 882 sequences downloaded from GenBank and representing four libraries from white truffle mycelia and ascocarps at different developmental stages. An automated pipeline was prepared to process EST sequences using public software integrated by in-house developed Perl scripts. Data were collected in a MySQL database, which can be queried via a php-based web interface. Sequences included in the ESTuber db were clustered and annotated against three databases: the GenBank nr database, the UniProtKB database and a third in-house prepared database of fungi genomic sequences. An algorithm was implemented to infer statistical classification among Gene Ontology categories from the ontology occurrences deduced from the annotation procedure against the UniProtKB database. Ontologies were also deduced from the annotation of more than 130,000 EST sequences from five filamentous fungi, for intra-species comparison purposes. Further analyses were performed on the ESTuber db dataset, including tandem repeats search and comparison of the putative protein dataset inferred from the EST sequences to the PROSITE database for protein patterns identification. All the analyses were performed both on the complete sequence dataset and on the contig consensus sequences generated by the EST assembly procedure. The resulting web site is a resource of data and links related to truffle expressed genes. The Sequence Report and Contig Report pages are the web interface core structures which, together with the Text search utility and the Blast utility, allow easy access to the data stored in the database.

ABrowse--a customizable next-generation genome browser framework.

PubMed

Kong, Lei; Wang, Jun; Zhao, Shuqi; Gu, Xiaocheng; Luo, Jingchu; Gao, Ge

2012-01-05

With the rapid growth of genome sequencing projects, genome browser is becoming indispensable, not only as a visualization system but also as an interactive platform to support open data access and collaborative work. Thus a customizable genome browser framework with rich functions and flexible configuration is needed to facilitate various genome research projects. Based on next-generation web technologies, we have developed a general-purpose genome browser framework ABrowse which provides interactive browsing experience, open data access and collaborative work support. By supporting Google-map-like smooth navigation, ABrowse offers end users highly interactive browsing experience. To facilitate further data analysis, multiple data access approaches are supported for external platforms to retrieve data from ABrowse. To promote collaborative work, an online user-space is provided for end users to create, store and share comments, annotations and landmarks. For data providers, ABrowse is highly customizable and configurable. The framework provides a set of utilities to import annotation data conveniently. To build ABrowse on existing annotation databases, data providers could specify SQL statements according to database schema. And customized pages for detailed information display of annotation entries could be easily plugged in. For developers, new drawing strategies could be integrated into ABrowse for new types of annotation data. In addition, standard web service is provided for data retrieval remotely, providing underlying machine-oriented programming interface for open data access. ABrowse framework is valuable for end users, data providers and developers by providing rich user functions and flexible customization approaches. The source code is published under GNU Lesser General Public License v3.0 and is accessible at http://www.abrowse.org/. To demonstrate all the features of ABrowse, a live demo for Arabidopsis thaliana genome has been built at http://arabidopsis.cbi.edu.cn/.

Initial description of primate-specific cystine-knot Prometheus genes and differential gene expansions of D-dopachrome tautomerase genes

PubMed Central

Premzl, Marko

2015-01-01

Using eutherian comparative genomic analysis protocol and public genomic sequence data sets, the present work attempted to update and revise two gene data sets. The most comprehensive third party annotation gene data sets of eutherian adenohypophysis cystine-knot genes (128 complete coding sequences), and d-dopachrome tautomerases and macrophage migration inhibitory factor genes (30 complete coding sequences) were annotated. For example, the present study first described primate-specific cystine-knot Prometheus genes, as well as differential gene expansions of D-dopachrome tautomerase genes. Furthermore, new frameworks of future experiments of two eutherian gene data sets were proposed. PMID:25941635

Next-Generation Genomics Facility at C-CAMP: Accelerating Genomic Research in India

PubMed Central

S, Chandana; Russiachand, Heikham; H, Pradeep; S, Shilpa; M, Ashwini; S, Sahana; B, Jayanth; Atla, Goutham; Jain, Smita; Arunkumar, Nandini; Gowda, Malali

2014-01-01

Next-Generation Sequencing (NGS; http://www.genome.gov/12513162) is a recent life-sciences technological revolution that allows scientists to decode genomes or transcriptomes at a much faster rate with a lower cost. Genomic-based studies are in a relatively slow pace in India due to the non-availability of genomics experts, trained personnel and dedicated service providers. Using NGS there is a lot of potential to study India's national diversity (of all kinds). We at the Centre for Cellular and Molecular Platforms (C-CAMP) have launched the Next Generation Genomics Facility (NGGF) to provide genomics service to scientists, to train researchers and also work on national and international genomic projects. We have HiSeq1000 from Illumina and GS-FLX Plus from Roche454. The long reads from GS FLX Plus, and high sequence depth from HiSeq1000, are the best and ideal hybrid approaches for de novo and re-sequencing of genomes and transcriptomes. At our facility, we have sequenced around 70 different organisms comprising of more than 388 genomes and 615 transcriptomes – prokaryotes and eukaryotes (fungi, plants and animals). In addition we have optimized other unique applications such as small RNA (miRNA, siRNA etc), long Mate-pair sequencing (2 to 20 Kb), Coding sequences (Exome), Methylome (ChIP-Seq), Restriction Mapping (RAD-Seq), Human Leukocyte Antigen (HLA) typing, mixed genomes (metagenomes) and target amplicons, etc. Translating DNA sequence data from NGS sequencer into meaningful information is an important exercise. Under NGGF, we have bioinformatics experts and high-end computing resources to dissect NGS data such as genome assembly and annotation, gene expression, target enrichment, variant calling (SSR or SNP), comparative analysis etc. Our services (sequencing and bioinformatics) have been utilized by more than 45 organizations (academia and industry) both within India and outside, resulting several publications in peer-reviewed journals and several genomic/transcriptomic data is available at NCBI.

DaMold: A data-mining platform for variant annotation and visualization in molecular diagnostics research.

PubMed

Pandey, Ram Vinay; Pabinger, Stephan; Kriegner, Albert; Weinhäusel, Andreas

2017-07-01

Next-generation sequencing (NGS) has become a powerful and efficient tool for routine mutation screening in clinical research. As each NGS test yields hundreds of variants, the current challenge is to meaningfully interpret the data and select potential candidates. Analyzing each variant while manually investigating several relevant databases to collect specific information is a cumbersome and time-consuming process, and it requires expertise and familiarity with these databases. Thus, a tool that can seamlessly annotate variants with clinically relevant databases under one common interface would be of great help for variant annotation, cross-referencing, and visualization. This tool would allow variants to be processed in an automated and high-throughput manner and facilitate the investigation of variants in several genome browsers. Several analysis tools are available for raw sequencing-read processing and variant identification, but an automated variant filtering, annotation, cross-referencing, and visualization tool is still lacking. To fulfill these requirements, we developed DaMold, a Web-based, user-friendly tool that can filter and annotate variants and can access and compile information from 37 resources. It is easy to use, provides flexible input options, and accepts variants from NGS and Sanger sequencing as well as hotspots in VCF and BED formats. DaMold is available as an online application at http://damold.platomics.com/index.html, and as a Docker container and virtual machine at https://sourceforge.net/projects/damold/. © 2017 Wiley Periodicals, Inc.

A comprehensive collection of annotations to interpret sequence variation in human mitochondrial transfer RNAs.

PubMed

Diroma, Maria Angela; Lubisco, Paolo; Attimonelli, Marcella

2016-11-08

The abundance of biological data characterizing the genomics era is contributing to a comprehensive understanding of human mitochondrial genetics. Nevertheless, many aspects are still unclear, specifically about the variability of the 22 human mitochondrial transfer RNA (tRNA) genes and their involvement in diseases. The complex enrichment and isolation of tRNAs in vitro leads to an incomplete knowledge of their post-transcriptional modifications and three-dimensional folding, essential for correct tRNA functioning. An accurate annotation of mitochondrial tRNA variants would be definitely useful and appreciated by mitochondrial researchers and clinicians since the most of bioinformatics tools for variant annotation and prioritization available so far cannot shed light on the functional role of tRNA variations. To this aim, we updated our MToolBox pipeline for mitochondrial DNA analysis of high throughput and Sanger sequencing data by integrating tRNA variant annotations in order to identify and characterize relevant variants not only in protein coding regions, but also in tRNA genes. The annotation step in the pipeline now provides detailed information for variants mapping onto the 22 mitochondrial tRNAs. For each mt-tRNA position along the entire genome, the relative tRNA numbering, tRNA type, cloverleaf secondary domains (loops and stems), mature nucleotide and interactions in the three-dimensional folding were reported. Moreover, pathogenicity predictions for tRNA and rRNA variants were retrieved from the literature and integrated within the annotations provided by MToolBox, both in the stand-alone version and web-based tool at the Mitochondrial Disease Sequence Data Resource (MSeqDR) website. All the information available in the annotation step of MToolBox were exploited to generate custom tracks which can be displayed in the GBrowse instance at MSeqDR website. To the best of our knowledge, specific data regarding mitochondrial variants in tRNA genes were introduced for the first time in a tool for mitochondrial genome analysis, supporting the interpretation of genetic variants in specific genomic contexts.

The 'dark matter' in the plant genomes: non-coding and unannotated DNA sequences associated with open chromatin.

PubMed

Jiang, Jiming

2015-04-01

Sequencing of complete plant genomes has become increasingly more routine since the advent of the next-generation sequencing technology. Identification and annotation of large amounts of noncoding but functional DNA sequences, including cis-regulatory DNA elements (CREs), have become a new frontier in plant genome research. Genomic regions containing active CREs bound to regulatory proteins are hypersensitive to DNase I digestion and are called DNase I hypersensitive sites (DHSs). Several recent DHS studies in plants illustrate that DHS datasets produced by DNase I digestion followed by next-generation sequencing (DNase-seq) are highly valuable for the identification and characterization of CREs associated with plant development and responses to environmental cues. DHS-based genomic profiling has opened a door to identify and annotate the 'dark matter' in sequenced plant genomes. Copyright © 2015 Elsevier Ltd. All rights reserved.

CDD/SPARCLE: functional classification of proteins via subfamily domain architectures.

PubMed

Marchler-Bauer, Aron; Bo, Yu; Han, Lianyi; He, Jane; Lanczycki, Christopher J; Lu, Shennan; Chitsaz, Farideh; Derbyshire, Myra K; Geer, Renata C; Gonzales, Noreen R; Gwadz, Marc; Hurwitz, David I; Lu, Fu; Marchler, Gabriele H; Song, James S; Thanki, Narmada; Wang, Zhouxi; Yamashita, Roxanne A; Zhang, Dachuan; Zheng, Chanjuan; Geer, Lewis Y; Bryant, Stephen H

2017-01-04

NCBI's Conserved Domain Database (CDD) aims at annotating biomolecular sequences with the location of evolutionarily conserved protein domain footprints, and functional sites inferred from such footprints. An archive of pre-computed domain annotation is maintained for proteins tracked by NCBI's Entrez database, and live search services are offered as well. CDD curation staff supplements a comprehensive collection of protein domain and protein family models, which have been imported from external providers, with representations of selected domain families that are curated in-house and organized into hierarchical classifications of functionally distinct families and sub-families. CDD also supports comparative analyses of protein families via conserved domain architectures, and a recent curation effort focuses on providing functional characterizations of distinct subfamily architectures using SPARCLE: Subfamily Protein Architecture Labeling Engine. CDD can be accessed at https://www.ncbi.nlm.nih.gov/Structure/cdd/cdd.shtml. Published by Oxford University Press on behalf of Nucleic Acids Research 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Leveraging biomedical ontologies and annotation services to organize microbiome data from Mammalian hosts.

PubMed

Sarkar, Indra Neil

2010-11-13

A better understanding of commensal microbiotic communities ("microbiomes") may provide valuable insights to human health. Towards this goal, an essential step may be the development of approaches to organize data that can enable comparative hypotheses across mammalian microbiomes. The present study explores the feasibility of using existing biomedical informatics resources - especially focusing on those available at the National Center for Biomedical Ontology - to organize microbiome data contained within large sequence repositories, such as GenBank. The results indicate that the Foundational Model of Anatomy and SNOMED CT can be used to organize greater than 90% of the bacterial organisms associated with 10 domesticated mammalian species. The promising findings suggest that the current biomedical informatics infrastructure may be used towards the organizing of microbiome data beyond humans. Furthermore, the results identify key concepts that might be organized into a semantic structure for incorporation into subsequent annotations that could facilitate comparative biomedical hypotheses pertaining to human health.

IMG ER: a system for microbial genome annotation expert review and curation.

PubMed

Markowitz, Victor M; Mavromatis, Konstantinos; Ivanova, Natalia N; Chen, I-Min A; Chu, Ken; Kyrpides, Nikos C

2009-09-01

A rapidly increasing number of microbial genomes are sequenced by organizations worldwide and are eventually included into various public genome data resources. The quality of the annotations depends largely on the original dataset providers, with erroneous or incomplete annotations often carried over into the public resources and difficult to correct. We have developed an Expert Review (ER) version of the Integrated Microbial Genomes (IMG) system, with the goal of supporting systematic and efficient revision of microbial genome annotations. IMG ER provides tools for the review and curation of annotations of both new and publicly available microbial genomes within IMG's rich integrated genome framework. New genome datasets are included into IMG ER prior to their public release either with their native annotations or with annotations generated by IMG ER's annotation pipeline. IMG ER tools allow addressing annotation problems detected with IMG's comparative analysis tools, such as genes missed by gene prediction pipelines or genes without an associated function. Over the past year, IMG ER was used for improving the annotations of about 150 microbial genomes.

Identification and DNA annotation of a plasmid isolated from Chromobacterium violaceum.

PubMed

Lima, Daniel C; Nyberg, Lena K; Westerlund, Fredrik; Batistuzzo de Medeiros, Silvia R

2018-03-28

Chromobacterium violaceum is a ß-proteobacterium found widely worldwide with important biotechnological properties and is associated to lethal sepsis in immune-depressed individuals. In this work, we report the discover, complete sequence and annotation of a plasmid detected in C. violaceum that has been unnoticed until now. We used DNA single-molecule analysis to confirm that the episome found was a circular molecule and then proceeded with NGS sequencing. After DNA annotation, we found that this extra-chromosomal DNA is probably a defective bacteriophage of approximately 44 kilobases, with 39 ORFs comprising, mostly hypothetical proteins. We also found DNA sequences that ensure proper plasmid replication and partitioning as well as a toxin addiction system. This report sheds light on the biology of this important species, helping us to understand the mechanisms by which C. violaceum endures to several harsh conditions. This discovery could also be a first step in the development of a DNA manipulation tool in this bacterium.

Blood transcriptomics of captive forest musk deer (Moschus berezovskii) and possible associations with the immune response to abscesses.

PubMed

Sun, Xiaoning; Cai, Ruibo; Jin, Xuelin; Shafer, Aaron B A; Hu, Xiaolong; Yang, Shuang; Li, Yimeng; Qi, Lei; Liu, Shuqiang; Hu, Defu

2018-01-12

Forest musk deer (Moschus berezovskii; FMD) are both economically valuable and highly endangered. A problem for FMD captive breeding programs has been the susceptibility of FMD to abscesses. To investigate the mechanisms of abscess development in FMD, the blood transcriptomes of three purulent and three healthy individuals were generated. A total of ~39.68 Gb bases were generated using Illumina HiSeq 4000 sequencing technology and 77,752 unigenes were identified after assembling. All the unigenes were annotated, with 63,531 (81.71%) mapping to at least one database. Based on these functional annotations, 45,798 coding sequences (CDS) were detected, along with 12,697 simple sequence repeats (SSRs) and 65,536 single nucleotide polymorphisms (SNPs). A total of 113 unigenes were found to be differentially expressed between healthy and purulent individuals. Functional annotation indicated that most of these differentially expressed genes were involved in the regulation of immune system processes, particularly those associated with parasitic and bacterial infection pathways.

MetaPathways v2.5: quantitative functional, taxonomic and usability improvements.

PubMed

Konwar, Kishori M; Hanson, Niels W; Bhatia, Maya P; Kim, Dongjae; Wu, Shang-Ju; Hahn, Aria S; Morgan-Lang, Connor; Cheung, Hiu Kan; Hallam, Steven J

2015-10-15

Next-generation sequencing is producing vast amounts of sequence information from natural and engineered ecosystems. Although this data deluge has an enormous potential to transform our lives, knowledge creation and translation need software applications that scale with increasing data processing and analysis requirements. Here, we present improvements to MetaPathways, an annotation and analysis pipeline for environmental sequence information that expedites this transformation. We specifically address pathway prediction hazards through integration of a weighted taxonomic distance and enable quantitative comparison of assembled annotations through a normalized read-mapping measure. Additionally, we improve LAST homology searches through BLAST-equivalent E-values and output formats that are natively compatible with prevailing software applications. Finally, an updated graphical user interface allows for keyword annotation query and projection onto user-defined functional gene hierarchies, including the Carbohydrate-Active Enzyme database. MetaPathways v2.5 is available on GitHub: http://github.com/hallamlab/metapathways2. shallam@mail.ubc.ca Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

The coffee genome hub: a resource for coffee genomes

PubMed Central

Dereeper, Alexis; Bocs, Stéphanie; Rouard, Mathieu; Guignon, Valentin; Ravel, Sébastien; Tranchant-Dubreuil, Christine; Poncet, Valérie; Garsmeur, Olivier; Lashermes, Philippe; Droc, Gaëtan

2015-01-01

The whole genome sequence of Coffea canephora, the perennial diploid species known as Robusta, has been recently released. In the context of the C. canephora genome sequencing project and to support post-genomics efforts, we developed the Coffee Genome Hub (http://coffee-genome.org/), an integrative genome information system that allows centralized access to genomics and genetics data and analysis tools to facilitate translational and applied research in coffee. We provide the complete genome sequence of C. canephora along with gene structure, gene product information, metabolism, gene families, transcriptomics, syntenic blocks, genetic markers and genetic maps. The hub relies on generic software (e.g. GMOD tools) for easy querying, visualizing and downloading research data. It includes a Genome Browser enhanced by a Community Annotation System, enabling the improvement of automatic gene annotation through an annotation editor. In addition, the hub aims at developing interoperability among other existing South Green tools managing coffee data (phylogenomics resources, SNPs) and/or supporting data analyses with the Galaxy workflow manager. PMID:25392413

Non-Coding RNA Analysis Using the Rfam Database.

PubMed

Kalvari, Ioanna; Nawrocki, Eric P; Argasinska, Joanna; Quinones-Olvera, Natalia; Finn, Robert D; Bateman, Alex; Petrov, Anton I

2018-06-01

Rfam is a database of non-coding RNA families in which each family is represented by a multiple sequence alignment, a consensus secondary structure, and a covariance model. Using a combination of manual and literature-based curation and a custom software pipeline, Rfam converts descriptions of RNA families found in the scientific literature into computational models that can be used to annotate RNAs belonging to those families in any DNA or RNA sequence. Valuable research outputs that are often locked up in figures and supplementary information files are encapsulated in Rfam entries and made accessible through the Rfam Web site. The data produced by Rfam have a broad application, from genome annotation to providing training sets for algorithm development. This article gives an overview of how to search and navigate the Rfam Web site, and how to annotate sequences with RNA families. The Rfam database is freely available at http://rfam.org. © 2018 by John Wiley & Sons, Inc. Copyright © 2018 John Wiley & Sons, Inc.

Health Economics Research: An Annotated Bibliography.

ERIC Educational Resources Information Center

Dillard, Carole D.; And Others

This annotated bibliography lists books and journal articles published since 1976 which deal with health economics and which are based on health services research supported by the National Center for Health Services Research (NCHSR). Articles prepared by NCHSR staff are listed as intramural. All other articles cite the NCHSR grant or contract…

Personal Assistance Services (PAS): Toward Universal Access to Support. Annotated Bibliography.

ERIC Educational Resources Information Center

Racino, Julie Ann

This annotated bibliography provides approximately 100 summaries and evaluations of documents, published from 1979 to 1995, on personal assistance services (PAS) for individuals with disabilities. Studies and articles were selected for inclusion based upon their capacity to inform the development of PAS models, including conceptual, policy, and…

Counselor's Information Service; a Quarterly Annotated Bibliography of Current Literature on Educational and Vocational Guidance. Volume 30, Number 1, February 1975.

ERIC Educational Resources Information Center

B'nai B'rith, Washington, DC. Career and Counseling Services.

The Counselor's Information Service is a quarterly publication of the B'nai B'rith Career and Counseling Services. This annotated bibliography of current literature on educational and vocational guidance provides the names and addresses of the publishers of the material reviewed and the cost of each publication. The reviews are organized according…

Counselor's Information Service; a Quarterly Annotated Bibliography of Current Literature on Educational and Vocational Guidance. Volume 30, Number 2, May 1975.

ERIC Educational Resources Information Center

B'nai B'rith, Washington, DC. Career and Counseling Services.

The Counselor's Information Service is a quarterly publication of the B'nai B'rith Career and Counseling Services. This annotated bibliography of current literature on educational and vocational guidance provides the names and addresses of the publishers of the material reviewed and the cost of each publication. The reviews are organized according…

Sputnik: a database platform for comparative plant genomics.

PubMed

Rudd, Stephen; Mewes, Hans-Werner; Mayer, Klaus F X

2003-01-01

Two million plant ESTs, from 20 different plant species, and totalling more than one 1000 Mbp of DNA sequence, represents a formidable transcriptomic resource. Sputnik uses the potential of this sequence resource to fill some of the information gap in the un-sequenced plant genomes and to serve as the foundation for in silicio comparative plant genomics. The complexity of the individual EST collections has been reduced using optimised EST clustering techniques. Annotation of cluster sequences is performed by exploiting and transferring information from the comprehensive knowledgebase already produced for the completed model plant genome (Arabidopsis thaliana) and by performing additional state of-the-art sequence analyses relevant to today's plant biologist. Functional predictions, comparative analyses and associative annotations for 500 000 plant EST derived peptides make Sputnik (http://mips.gsf.de/proj/sputnik/) a valid platform for contemporary plant genomics.

Sputnik: a database platform for comparative plant genomics

PubMed Central

Rudd, Stephen; Mewes, Hans-Werner; Mayer, Klaus F.X.

2003-01-01

Two million plant ESTs, from 20 different plant species, and totalling more than one 1000 Mbp of DNA sequence, represents a formidable transcriptomic resource. Sputnik uses the potential of this sequence resource to fill some of the information gap in the un-sequenced plant genomes and to serve as the foundation for in silicio comparative plant genomics. The complexity of the individual EST collections has been reduced using optimised EST clustering techniques. Annotation of cluster sequences is performed by exploiting and transferring information from the comprehensive knowledgebase already produced for the completed model plant genome (Arabidopsis thaliana) and by performing additional state of-the-art sequence analyses relevant to today's plant biologist. Functional predictions, comparative analyses and associative annotations for 500 000 plant EST derived peptides make Sputnik (http://mips.gsf.de/proj/sputnik/) a valid platform for contemporary plant genomics. PMID:12519965

Transcriptome deep-sequencing and clustering of expressed isoforms from Favia corals

PubMed Central

2013-01-01

Background Genomic and transcriptomic sequence data are essential tools for tackling ecological problems. Using an approach that combines next-generation sequencing, de novo transcriptome assembly, gene annotation and synthetic gene construction, we identify and cluster the protein families from Favia corals from the northern Red Sea. Results We obtained 80 million 75 bp paired-end cDNA reads from two Favia adult samples collected at 65 m (Fav1, Fav2) on the Illumina GA platform, and generated two de novo assemblies using ABySS and CAP3. After removing redundancy and filtering out low quality reads, our transcriptome datasets contained 58,268 (Fav1) and 62,469 (Fav2) contigs longer than 100 bp, with N50 values of 1,665 bp and 1,439 bp, respectively. Using the proteome of the sea anemone Nematostella vectensis as a reference, we were able to annotate almost 20% of each dataset using reciprocal homology searches. Homologous clustering of these annotated transcripts allowed us to divide them into 7,186 (Fav1) and 6,862 (Fav2) homologous transcript clusters (E-value ≤ 2e-30). Functional annotation categories were assigned to homologous clusters using the functional annotation of Nematostella vectensis. General annotation of the assembled transcripts was improved 1-3% using the Acropora digitifera proteome. In addition, we screened these transcript isoform clusters for fluorescent proteins (FPs) homologs and identified seven potential FP homologs in Fav1, and four in Fav2. These transcripts were validated as bona fide FP transcripts via robust fluorescence heterologous expression. Annotation of the assembled contigs revealed that 1.34% and 1.61% (in Fav1 and Fav2, respectively) of the total assembled contigs likely originated from the corals’ algal symbiont, Symbiodinium spp. Conclusions Here we present a study to identify the homologous transcript isoform clusters from the transcriptome of Favia corals using a far-related reference proteome. Furthermore, the symbiont-derived transcripts were isolated from the datasets and their contribution quantified. This is the first annotated transcriptome of the genus Favia, a major increase in genomics resources available in this important family of corals. PMID:23937070

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.

Analysis of beta-carotene hydroxylase gene cDNA isolated from the American oil-palm (Elaeis oleifera) mesocarp tissue cDNA library

PubMed Central

Bhore, Subhash J; Kassim, Amelia; Loh, Chye Ying; Shah, Farida H

2010-01-01

It is well known that the nutritional quality of the American oil-palm (Elaeis oleifera) mesocarp oil is superior to that of African oil-palm (Elaeis guineensis Jacq. Tenera) mesocarp oil. Therefore, it is of important to identify the genetic features for its superior value. This could be achieved through the genome sequencing of the oil-palm. However, the genome sequence is not available in the public domain due to commercial secrecy. Hence, we constructed a cDNA library and generated expressed sequence tags (3,205) from the mesocarp tissue of the American oil-palm. We continued to annotate each of these cDNAs after submitting to GenBank/DDBJ/EMBL. A rough analysis turned our attention to the beta-carotene hydroxylase (Chyb) enzyme encoding cDNA. Then, we completed the full sequencing of cDNA clone for its both strands using M13 forward and reverse primers. The full nucleotide and protein sequence was further analyzed and annotated using various Bioinformatics tools. The analysis results showed the presence of fatty acid hydroxylase superfamily domain in the protein sequence. The multiple sequence alignment of selected Chyb amino acid sequences from other plant species and algal members with E. oleifera Chyb using ClustalW and its phylogenetic analysis suggest that Chyb from monocotyledonous plant species, Lilium hubrid, Crocus sativus and Zea mays are the most evolutionary related with E. oleifera Chyb. This study reports the annotation of E. oleifera Chyb. Abbreviations ESTs - expressed sequence tags, EoChyb - Elaeis oleifera beta-carotene hydroxylase, MC - main cluster PMID:21364789

Specialized microbial databases for inductive exploration of microbial genome sequences

PubMed Central

Fang, Gang; Ho, Christine; Qiu, Yaowu; Cubas, Virginie; Yu, Zhou; Cabau, Cédric; Cheung, Frankie; Moszer, Ivan; Danchin, Antoine

2005-01-01

Background The enormous amount of genome sequence data asks for user-oriented databases to manage sequences and annotations. Queries must include search tools permitting function identification through exploration of related objects. Methods The GenoList package for collecting and mining microbial genome databases has been rewritten using MySQL as the database management system. Functions that were not available in MySQL, such as nested subquery, have been implemented. Results Inductive reasoning in the study of genomes starts from "islands of knowledge", centered around genes with some known background. With this concept of "neighborhood" in mind, a modified version of the GenoList structure has been used for organizing sequence data from prokaryotic genomes of particular interest in China. GenoChore , a set of 17 specialized end-user-oriented microbial databases (including one instance of Microsporidia, Encephalitozoon cuniculi, a member of Eukarya) has been made publicly available. These databases allow the user to browse genome sequence and annotation data using standard queries. In addition they provide a weekly update of searches against the world-wide protein sequences data libraries, allowing one to monitor annotation updates on genes of interest. Finally, they allow users to search for patterns in DNA or protein sequences, taking into account a clustering of genes into formal operons, as well as providing extra facilities to query sequences using predefined sequence patterns. Conclusion This growing set of specialized microbial databases organize data created by the first Chinese bacterial genome programs (ThermaList, Thermoanaerobacter tencongensis, LeptoList, with two different genomes of Leptospira interrogans and SepiList, Staphylococcus epidermidis) associated to related organisms for comparison. PMID:15698474

A computational genomics pipeline for prokaryotic sequencing projects

PubMed Central

Kislyuk, Andrey O.; Katz, Lee S.; Agrawal, Sonia; Hagen, Matthew S.; Conley, Andrew B.; Jayaraman, Pushkala; Nelakuditi, Viswateja; Humphrey, Jay C.; Sammons, Scott A.; Govil, Dhwani; Mair, Raydel D.; Tatti, Kathleen M.; Tondella, Maria L.; Harcourt, Brian H.; Mayer, Leonard W.; Jordan, I. King

2010-01-01

Motivation: New sequencing technologies have accelerated research on prokaryotic genomes and have made genome sequencing operations outside major genome sequencing centers routine. However, no off-the-shelf solution exists for the combined assembly, gene prediction, genome annotation and data presentation necessary to interpret sequencing data. The resulting requirement to invest significant resources into custom informatics support for genome sequencing projects remains a major impediment to the accessibility of high-throughput sequence data. Results: We present a self-contained, automated high-throughput open source genome sequencing and computational genomics pipeline suitable for prokaryotic sequencing projects. The pipeline has been used at the Georgia Institute of Technology and the Centers for Disease Control and Prevention for the analysis of Neisseria meningitidis and Bordetella bronchiseptica genomes. The pipeline is capable of enhanced or manually assisted reference-based assembly using multiple assemblers and modes; gene predictor combining; and functional annotation of genes and gene products. Because every component of the pipeline is executed on a local machine with no need to access resources over the Internet, the pipeline is suitable for projects of a sensitive nature. Annotation of virulence-related features makes the pipeline particularly useful for projects working with pathogenic prokaryotes. Availability and implementation: The pipeline is licensed under the open-source GNU General Public License and available at the Georgia Tech Neisseria Base (http://nbase.biology.gatech.edu/). The pipeline is implemented with a combination of Perl, Bourne Shell and MySQL and is compatible with Linux and other Unix systems. Contact: king.jordan@biology.gatech.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20519285

Developing national on-line services to annotate and analyse underwater imagery in a research cloud

NASA Astrophysics Data System (ADS)

Proctor, R.; Langlois, T.; Friedman, A.; Davey, B.

2017-12-01

Fish image annotation data is currently collected by various research, management and academic institutions globally (+100,000's hours of deployments) with varying degrees of standardisation and limited formal collaboration or data synthesis. We present a case study of how national on-line services, developed within a domain-oriented research cloud, have been used to annotate habitat images and synthesise fish annotation data sets collected using Autonomous Underwater Vehicles (AUVs) and baited remote underwater stereo-video (stereo-BRUV). Two developing software tools have been brought together in the marine science cloud to provide marine biologists with a powerful service for image annotation. SQUIDLE+ is an online platform designed for exploration, management and annotation of georeferenced images & video data. It provides a flexible annotation framework allowing users to work with their preferred annotation schemes. We have used SQUIDLE+ to sample the habitat composition and complexity of images of the benthos collected using stereo-BRUV. GlobalArchive is designed to be a centralised repository of aquatic ecological survey data with design principles including ease of use, secure user access, flexible data import, and the collection of any sampling and image analysis information. To easily share and synthesise data we have implemented data sharing protocols, including Open Data and synthesis Collaborations, and a spatial map to explore global datasets and filter to create a synthesis. These tools in the science cloud, together with a virtual desktop analysis suite offering python and R environments offer an unprecedented capability to deliver marine biodiversity information of value to marine managers and scientists alike.

The Co-regulation Data Harvester: Automating gene annotation starting from a transcriptome database

NASA Astrophysics Data System (ADS)

Tsypin, Lev M.; Turkewitz, Aaron P.

Identifying co-regulated genes provides a useful approach for defining pathway-specific machinery in an organism. To be efficient, this approach relies on thorough genome annotation, a process much slower than genome sequencing per se. Tetrahymena thermophila, a unicellular eukaryote, has been a useful model organism and has a fully sequenced but sparsely annotated genome. One important resource for studying this organism has been an online transcriptomic database. We have developed an automated approach to gene annotation in the context of transcriptome data in T. thermophila, called the Co-regulation Data Harvester (CDH). Beginning with a gene of interest, the CDH identifies co-regulated genes by accessing the Tetrahymena transcriptome database. It then identifies their closely related genes (orthologs) in other organisms by using reciprocal BLAST searches. Finally, it collates the annotations of those orthologs' functions, which provides the user with information to help predict the cellular role of the initial query. The CDH, which is freely available, represents a powerful new tool for analyzing cell biological pathways in Tetrahymena. Moreover, to the extent that genes and pathways are conserved between organisms, the inferences obtained via the CDH should be relevant, and can be explored, in many other systems.

Fuzzy measures on the Gene Ontology for gene product similarity.

PubMed

Popescu, Mihail; Keller, James M; Mitchell, Joyce A

2006-01-01

One of the most important objects in bioinformatics is a gene product (protein or RNA). For many gene products, functional information is summarized in a set of Gene Ontology (GO) annotations. For these genes, it is reasonable to include similarity measures based on the terms found in the GO or other taxonomy. In this paper, we introduce several novel measures for computing the similarity of two gene products annotated with GO terms. The fuzzy measure similarity (FMS) has the advantage that it takes into consideration the context of both complete sets of annotation terms when computing the similarity between two gene products. When the two gene products are not annotated by common taxonomy terms, we propose a method that avoids a zero similarity result. To account for the variations in the annotation reliability, we propose a similarity measure based on the Choquet integral. These similarity measures provide extra tools for the biologist in search of functional information for gene products. The initial testing on a group of 194 sequences representing three proteins families shows a higher correlation of the FMS and Choquet similarities to the BLAST sequence similarities than the traditional similarity measures such as pairwise average or pairwise maximum.

Genome assembly and transcriptome resource for river buffalo, Bubalus bubalis (2n = 50).

PubMed

Williams, John L; 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

2017-10-01

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 (2 n = 50) and the swamp (2 n = 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. © The Author 2017. Published by Oxford University Press.

Draft genome of the red harvester ant Pogonomyrmex barbatus.

PubMed

Smith, Chris R; Smith, Christopher D; Robertson, Hugh M; Helmkampf, Martin; Zimin, Aleksey; Yandell, Mark; Holt, Carson; Hu, Hao; Abouheif, Ehab; Benton, Richard; Cash, Elizabeth; Croset, Vincent; Currie, Cameron R; Elhaik, Eran; Elsik, Christine G; Favé, Marie-Julie; Fernandes, Vilaiwan; Gibson, Joshua D; Graur, Dan; Gronenberg, Wulfila; Grubbs, Kirk J; Hagen, Darren E; Viniegra, Ana Sofia Ibarraran; Johnson, Brian R; Johnson, Reed M; Khila, Abderrahman; Kim, Jay W; Mathis, Kaitlyn A; Munoz-Torres, Monica C; Murphy, Marguerite C; Mustard, Julie A; Nakamura, Rin; Niehuis, Oliver; Nigam, Surabhi; Overson, Rick P; Placek, Jennifer E; Rajakumar, Rajendhran; Reese, Justin T; Suen, Garret; Tao, Shu; Torres, Candice W; Tsutsui, Neil D; Viljakainen, Lumi; Wolschin, Florian; Gadau, Jürgen

2011-04-05

We report the draft genome sequence of the red harvester ant, Pogonomyrmex barbatus. The genome was sequenced using 454 pyrosequencing, and the current assembly and annotation were completed in less than 1 y. Analyses of conserved gene groups (more than 1,200 manually annotated genes to date) suggest a high-quality assembly and annotation comparable to recently sequenced insect genomes using Sanger sequencing. The red harvester ant is a model for studying reproductive division of labor, phenotypic plasticity, and sociogenomics. Although the genome of P. barbatus is similar to other sequenced hymenopterans (Apis mellifera and Nasonia vitripennis) in GC content and compositional organization, and possesses a complete CpG methylation toolkit, its predicted genomic CpG content differs markedly from the other hymenopterans. Gene networks involved in generating key differences between the queen and worker castes (e.g., wings and ovaries) show signatures of increased methylation and suggest that ants and bees may have independently co-opted the same gene regulatory mechanisms for reproductive division of labor. Gene family expansions (e.g., 344 functional odorant receptors) and pseudogene accumulation in chemoreception and P450 genes compared with A. mellifera and N. vitripennis are consistent with major life-history changes during the adaptive radiation of Pogonomyrmex spp., perhaps in parallel with the development of the North American deserts.

Concomitant prediction of function and fold at the domain level with GO-based profiles.

PubMed

Lopez, Daniel; Pazos, Florencio

2013-01-01

Predicting the function of newly sequenced proteins is crucial due to the pace at which these raw sequences are being obtained. Almost all resources for predicting protein function assign functional terms to whole chains, and do not distinguish which particular domain is responsible for the allocated function. This is not a limitation of the methodologies themselves but it is due to the fact that in the databases of functional annotations these methods use for transferring functional terms to new proteins, these annotations are done on a whole-chain basis. Nevertheless, domains are the basic evolutionary and often functional units of proteins. In many cases, the domains of a protein chain have distinct molecular functions, independent from each other. For that reason resources with functional annotations at the domain level, as well as methodologies for predicting function for individual domains adapted to these resources are required.We present a methodology for predicting the molecular function of individual domains, based on a previously developed database of functional annotations at the domain level. The approach, which we show outperforms a standard method based on sequence searches in assigning function, concomitantly predicts the structural fold of the domains and can give hints on the functionally important residues associated to the predicted function.

Gene annotation from scientific literature using mappings between keyword systems.

PubMed

Pérez, Antonio J; Perez-Iratxeta, Carolina; Bork, Peer; Thode, Guillermo; Andrade, Miguel A

2004-09-01

The description of genes in databases by keywords helps the non-specialist to quickly grasp the properties of a gene and increases the efficiency of computational tools that are applied to gene data (e.g. searching a gene database for sequences related to a particular biological process). However, the association of keywords to genes or protein sequences is a difficult process that ultimately implies examination of the literature related to a gene. To support this task, we present a procedure to derive keywords from the set of scientific abstracts related to a gene. Our system is based on the automated extraction of mappings between related terms from different databases using a model of fuzzy associations that can be applied with all generality to any pair of linked databases. We tested the system by annotating genes of the SWISS-PROT database with keywords derived from the abstracts linked to their entries (stored in the MEDLINE database of scientific references). The performance of the annotation procedure was much better for SWISS-PROT keywords (recall of 47%, precision of 68%) than for Gene Ontology terms (recall of 8%, precision of 67%). The algorithm can be publicly accessed and used for the annotation of sequences through a web server at http://www.bork.embl.de/kat

Genome3D: a UK collaborative project to annotate genomic sequences with predicted 3D structures based on SCOP and CATH domains.

PubMed

Lewis, Tony E; Sillitoe, Ian; Andreeva, Antonina; Blundell, Tom L; Buchan, Daniel W A; Chothia, Cyrus; Cuff, Alison; Dana, Jose M; Filippis, Ioannis; Gough, Julian; Hunter, Sarah; Jones, David T; Kelley, Lawrence A; Kleywegt, Gerard J; Minneci, Federico; Mitchell, Alex; Murzin, Alexey G; Ochoa-Montaño, Bernardo; Rackham, Owen J L; Smith, James; Sternberg, Michael J E; Velankar, Sameer; Yeats, Corin; Orengo, Christine

2013-01-01

Genome3D, available at http://www.genome3d.eu, is a new collaborative project that integrates UK-based structural resources to provide a unique perspective on sequence-structure-function relationships. Leading structure prediction resources (DomSerf, FUGUE, Gene3D, pDomTHREADER, Phyre and SUPERFAMILY) provide annotations for UniProt sequences to indicate the locations of structural domains (structural annotations) and their 3D structures (structural models). Structural annotations and 3D model predictions are currently available for three model genomes (Homo sapiens, E. coli and baker's yeast), and the project will extend to other genomes in the near future. As these resources exploit different strategies for predicting structures, the main aim of Genome3D is to enable comparisons between all the resources so that biologists can see where predictions agree and are therefore more trusted. Furthermore, as these methods differ in whether they build their predictions using CATH or SCOP, Genome3D also contains the first official mapping between these two databases. This has identified pairs of similar superfamilies from the two resources at various degrees of consensus (532 bronze pairs, 527 silver pairs and 370 gold pairs).

Identification of Functionally Related Enzymes by Learning-to-Rank Methods.

PubMed

Stock, Michiel; Fober, Thomas; Hüllermeier, Eyke; Glinca, Serghei; Klebe, Gerhard; Pahikkala, Tapio; Airola, Antti; De Baets, Bernard; Waegeman, Willem

2014-01-01

Enzyme sequences and structures are routinely used in the biological sciences as queries to search for functionally related enzymes in online databases. To this end, one usually departs from some notion of similarity, comparing two enzymes by looking for correspondences in their sequences, structures or surfaces. For a given query, the search operation results in a ranking of the enzymes in the database, from very similar to dissimilar enzymes, while information about the biological function of annotated database enzymes is ignored. In this work, we show that rankings of that kind can be substantially improved by applying kernel-based learning algorithms. This approach enables the detection of statistical dependencies between similarities of the active cleft and the biological function of annotated enzymes. This is in contrast to search-based approaches, which do not take annotated training data into account. Similarity measures based on the active cleft are known to outperform sequence-based or structure-based measures under certain conditions. We consider the Enzyme Commission (EC) classification hierarchy for obtaining annotated enzymes during the training phase. The results of a set of sizeable experiments indicate a consistent and significant improvement for a set of similarity measures that exploit information about small cavities in the surface of enzymes.

MIPS: a database for genomes and protein sequences.

PubMed Central

Mewes, H W; Heumann, K; Kaps, A; Mayer, K; Pfeiffer, F; Stocker, S; Frishman, D

1999-01-01

The Munich Information Center for Protein Sequences (MIPS-GSF), Martinsried near Munich, Germany, develops and maintains genome oriented databases. It is commonplace that the amount of sequence data available increases rapidly, but not the capacity of qualified manual annotation at the sequence databases. Therefore, our strategy aims to cope with the data stream by the comprehensive application of analysis tools to sequences of complete genomes, the systematic classification of protein sequences and the active support of sequence analysis and functional genomics projects. This report describes the systematic and up-to-date analysis of genomes (PEDANT), a comprehensive database of the yeast genome (MYGD), a database reflecting the progress in sequencing the Arabidopsis thaliana genome (MATD), the database of assembled, annotated human EST clusters (MEST), and the collection of protein sequence data within the framework of the PIR-International Protein Sequence Database (described elsewhere in this volume). MIPS provides access through its WWW server (http://www.mips.biochem.mpg.de) to a spectrum of generic databases, including the above mentioned as well as a database of protein families (PROTFAM), the MITOP database, and the all-against-all FASTA database. PMID:9847138

A guide to best practices for Gene Ontology (GO) manual annotation

PubMed Central

Balakrishnan, Rama; Harris, Midori A.; Huntley, Rachael; Van Auken, Kimberly; Cherry, J. Michael

2013-01-01

The Gene Ontology Consortium (GOC) is a community-based bioinformatics project that classifies gene product function through the use of structured controlled vocabularies. A fundamental application of the Gene Ontology (GO) is in the creation of gene product annotations, evidence-based associations between GO definitions and experimental or sequence-based analysis. Currently, the GOC disseminates 126 million annotations covering >374 000 species including all the kingdoms of life. This number includes two classes of GO annotations: those created manually by experienced biocurators reviewing the literature or by examination of biological data (1.1 million annotations covering 2226 species) and those generated computationally via automated methods. As manual annotations are often used to propagate functional predictions between related proteins within and between genomes, it is critical to provide accurate consistent manual annotations. Toward this goal, we present here the conventions defined by the GOC for the creation of manual annotation. This guide represents the best practices for manual annotation as established by the GOC project over the past 12 years. We hope this guide will encourage research communities to annotate gene products of their interest to enhance the corpus of GO annotations available to all. Database URL: http://www.geneontology.org PMID:23842463

Analysis of expressed sequence tags (ESTs) from cocoa (Theobroma cacao L) upon infection with Phytophthora megakarya.

PubMed

Naganeeswaran, Sudalaimuthu Asari; Subbian, Elain Apshara; Ramaswamy, Manimekalai

2012-01-01

Phytophthora megakarya, the causative agent of cacao black pod disease in West African countries causes an extensive loss of yield. In this study we have analyzed 4 libraries of ESTs derived from Phytophthora megakarya infected cocoa leaf and pod tissues. Totally 6379 redundant sequences were retrieved from ESTtik database and EST processing was performed using seqclean tool. Clustering and assembling using CAP3 generated 3333 non-redundant (907 contigs and 2426 singletons) sequences. The primary sequence analysis of 3333 non-redundant sequences showed that the GC percentage was 42.7 and the sequence length ranged from 101 - 2576 nucleotides. Further, functional analysis (Blast, Interproscan, Gene ontology and KEGG search) were executed and 1230 orthologous genes were annotated. Totally 272 enzymes corresponding to 114 metabolic pathways were identified. Functional annotation revealed that most of the sequences are related to molecular function, stress response and biological processes. The annotated enzymes are aldehyde dehydrogenase (E.C: 1.2.1.3), catalase (E.C: 1.11.1.6), acetyl-CoA C-acetyltransferase (E.C: 2.3.1.9), threonine ammonia-lyase (E.C: 4.3.1.19), acetolactate synthase (E.C: 2.2.1.6), O-methyltransferase (E.C: 2.1.1.68) which play an important role in amino acid biosynthesis and phenyl propanoid biosynthesis. All this information was stored in MySQL database management system to be used in future for reconstruction of biotic stress response pathway in cocoa.

Exogean: a framework for annotating protein-coding genes in eukaryotic genomic DNA

PubMed Central

Djebali, Sarah; Delaplace, Franck; Crollius, Hugues Roest

2006-01-01

Background Accurate and automatic gene identification in eukaryotic genomic DNA is more than ever of crucial importance to efficiently exploit the large volume of assembled genome sequences available to the community. Automatic methods have always been considered less reliable than human expertise. This is illustrated in the EGASP project, where reference annotations against which all automatic methods are measured are generated by human annotators and experimentally verified. We hypothesized that replicating the accuracy of human annotators in an automatic method could be achieved by formalizing the rules and decisions that they use, in a mathematical formalism. Results We have developed Exogean, a flexible framework based on directed acyclic colored multigraphs (DACMs) that can represent biological objects (for example, mRNA, ESTs, protein alignments, exons) and relationships between them. Graphs are analyzed to process the information according to rules that replicate those used by human annotators. Simple individual starting objects given as input to Exogean are thus combined and synthesized into complex objects such as protein coding transcripts. Conclusion We show here, in the context of the EGASP project, that Exogean is currently the method that best reproduces protein coding gene annotations from human experts, in terms of identifying at least one exact coding sequence per gene. We discuss current limitations of the method and several avenues for improvement. PMID:16925841

GAPP: A Proteogenomic Software for Genome Annotation and Global Profiling of Post-translational Modifications in Prokaryotes.

PubMed

Zhang, Jia; Yang, Ming-Kun; Zeng, Honghui; Ge, Feng

2016-11-01

Although the number of sequenced prokaryotic genomes is growing rapidly, experimentally verified annotation of prokaryotic genome remains patchy and challenging. To facilitate genome annotation efforts for prokaryotes, we developed an open source software called GAPP for genome annotation and global profiling of post-translational modifications (PTMs) in prokaryotes. With a single command, it provides a standard workflow to validate and refine predicted genetic models and discover diverse PTM events. We demonstrated the utility of GAPP using proteomic data from Helicobacter pylori, one of the major human pathogens that is responsible for many gastric diseases. Our results confirmed 84.9% of the existing predicted H. pylori proteins, identified 20 novel protein coding genes, and corrected four existing gene models with regard to translation initiation sites. In particular, GAPP revealed a large repertoire of PTMs using the same proteomic data and provided a rich resource that can be used to examine the functions of reversible modifications in this human pathogen. This software is a powerful tool for genome annotation and global discovery of PTMs and is applicable to any sequenced prokaryotic organism; we expect that it will become an integral part of ongoing genome annotation efforts for prokaryotes. GAPP is freely available at https://sourceforge.net/projects/gappproteogenomic/. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Counselor's Information Service; a Quarterly Annotated Bibliography of Current Literature on Educational and Vocational Guidance (with Special Supplement). Volume 30, Number 3, September 1975.

ERIC Educational Resources Information Center

B'nai B'rith, Washington, DC. Career and Counseling Services.

The Counselor's Information Service is a quarterly publication of the B'nai B'rith Career and Counseling Services. This annotated bibliography of current literature on educational and vocational guidance provides the names and addresses of the publishers of the material reviewed and the cost of each publication. The reviews are organized according…

The Saccharomyces Genome Database Variant Viewer

PubMed Central

Sheppard, Travis K.; Hitz, Benjamin C.; Engel, Stacia R.; Song, Giltae; Balakrishnan, Rama; Binkley, Gail; Costanzo, Maria C.; Dalusag, Kyla S.; Demeter, Janos; Hellerstedt, Sage T.; Karra, Kalpana; Nash, Robert S.; Paskov, Kelley M.; Skrzypek, Marek S.; Weng, Shuai; Wong, Edith D.; Cherry, J. Michael

2016-01-01

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org) is the authoritative community resource for the Saccharomyces cerevisiae reference genome sequence and its annotation. In recent years, we have moved toward increased representation of sequence variation and allelic differences within S. cerevisiae. The publication of numerous additional genomes has motivated the creation of new tools for their annotation and analysis. Here we present the Variant Viewer: a dynamic open-source web application for the visualization of genomic and proteomic differences. Multiple sequence alignments have been constructed across high quality genome sequences from 11 different S. cerevisiae strains and stored in the SGD. The alignments and summaries are encoded in JSON and used to create a two-tiered dynamic view of the budding yeast pan-genome, available at http://www.yeastgenome.org/variant-viewer. PMID:26578556

Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center

DOE PAGES

Davis, James J.; Brettin, Thomas; Dietrich, Emily M.; ...

2016-11-28

Here, the Pathosystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center. Recent changes to PATRIC include a redesign of the web interface and some new services that provide users with a platform that takes them from raw reads to an integrated analysis experience. The redesigned interface allows researchers direct access to tools and data, and the emphasis has changed to user-created genome-groups, with detailed summaries and views of the data that researchers have selected. Perhaps the biggest change has been the enhanced capability for researchers to analyze their private data and compare it to the available public data.more » Researchers can assemble their raw sequence reads and annotate the contigs using RASTtk. PATRIC also provides services for RNA-Seq, variation, model reconstruction and differential expression analysis, all delivered through an updated private workspace. Private data can be compared by `virtual integration' to any of PATRIC's public data. The number of genomes available for comparison in PATRIC has expanded to over 80 000, with a special emphasis on genomes with antimicrobial resistance data. PATRIC uses this data to improve both subsystem annotation and k-mer classification, and tags new genomes as having signatures that indicate susceptibility or resistance to specific antibiotics.« less

Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center

PubMed Central

Wattam, Alice R.; Davis, James J.; Assaf, Rida; Boisvert, Sébastien; Brettin, Thomas; Bun, Christopher; Conrad, Neal; Dietrich, Emily M.; Disz, Terry; Gabbard, Joseph L.; Gerdes, Svetlana; Henry, Christopher S.; Kenyon, Ronald W.; Machi, Dustin; Mao, Chunhong; Nordberg, Eric K.; Olsen, Gary J.; Murphy-Olson, Daniel E.; Olson, Robert; Overbeek, Ross; Parrello, Bruce; Pusch, Gordon D.; Shukla, Maulik; Vonstein, Veronika; Warren, Andrew; Xia, Fangfang; Yoo, Hyunseung; Stevens, Rick L.

2017-01-01

The Pathosystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center (https://www.patricbrc.org). Recent changes to PATRIC include a redesign of the web interface and some new services that provide users with a platform that takes them from raw reads to an integrated analysis experience. The redesigned interface allows researchers direct access to tools and data, and the emphasis has changed to user-created genome-groups, with detailed summaries and views of the data that researchers have selected. Perhaps the biggest change has been the enhanced capability for researchers to analyze their private data and compare it to the available public data. Researchers can assemble their raw sequence reads and annotate the contigs using RASTtk. PATRIC also provides services for RNA-Seq, variation, model reconstruction and differential expression analysis, all delivered through an updated private workspace. Private data can be compared by ‘virtual integration’ to any of PATRIC's public data. The number of genomes available for comparison in PATRIC has expanded to over 80 000, with a special emphasis on genomes with antimicrobial resistance data. PATRIC uses this data to improve both subsystem annotation and k-mer classification, and tags new genomes as having signatures that indicate susceptibility or resistance to specific antibiotics. PMID:27899627

Comparison of topological clustering within protein networks using edge metrics that evaluate full sequence, full structure, and active site microenvironment similarity.

PubMed

Leuthaeuser, Janelle B; Knutson, Stacy T; Kumar, Kiran; Babbitt, Patricia C; Fetrow, Jacquelyn S

2015-09-01

The development of accurate protein function annotation methods has emerged as a major unsolved biological problem. Protein similarity networks, one approach to function annotation via annotation transfer, group proteins into similarity-based clusters. An underlying assumption is that the edge metric used to identify such clusters correlates with functional information. In this contribution, this assumption is evaluated by observing topologies in similarity networks using three different edge metrics: sequence (BLAST), structure (TM-Align), and active site similarity (active site profiling, implemented in DASP). Network topologies for four well-studied protein superfamilies (enolase, peroxiredoxin (Prx), glutathione transferase (GST), and crotonase) were compared with curated functional hierarchies and structure. As expected, network topology differs, depending on edge metric; comparison of topologies provides valuable information on structure/function relationships. Subnetworks based on active site similarity correlate with known functional hierarchies at a single edge threshold more often than sequence- or structure-based networks. Sequence- and structure-based networks are useful for identifying sequence and domain similarities and differences; therefore, it is important to consider the clustering goal before deciding appropriate edge metric. Further, conserved active site residues identified in enolase and GST active site subnetworks correspond with published functionally important residues. Extension of this analysis yields predictions of functionally determinant residues for GST subgroups. These results support the hypothesis that active site similarity-based networks reveal clusters that share functional details and lay the foundation for capturing functionally relevant hierarchies using an approach that is both automatable and can deliver greater precision in function annotation than current similarity-based methods. © 2015 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Developmental Gene Discovery in a Hemimetabolous Insect: De Novo Assembly and Annotation of a Transcriptome for the Cricket Gryllus bimaculatus

PubMed Central

Zeng, Victor; Ewen-Campen, Ben; Horch, Hadley W.; Roth, Siegfried; Mito, Taro; Extavour, Cassandra G.

2013-01-01

Most genomic resources available for insects represent the Holometabola, which are insects that undergo complete metamorphosis like beetles and flies. In contrast, the Hemimetabola (direct developing insects), representing the basal branches of the insect tree, have very few genomic resources. We have therefore created a large and publicly available transcriptome for the hemimetabolous insect Gryllus bimaculatus (cricket), a well-developed laboratory model organism whose potential for functional genetic experiments is currently limited by the absence of genomic resources. cDNA was prepared using mRNA obtained from adult ovaries containing all stages of oogenesis, and from embryo samples on each day of embryogenesis. Using 454 Titanium pyrosequencing, we sequenced over four million raw reads, and assembled them into 21,512 isotigs (predicted transcripts) and 120,805 singletons with an average coverage per base pair of 51.3. We annotated the transcriptome manually for over 400 conserved genes involved in embryonic patterning, gametogenesis, and signaling pathways. BLAST comparison of the transcriptome against the NCBI non-redundant protein database (nr) identified significant similarity to nr sequences for 55.5% of transcriptome sequences, and suggested that the transcriptome may contain 19,874 unique transcripts. For predicted transcripts without significant similarity to known sequences, we assessed their similarity to other orthopteran sequences, and determined that these transcripts contain recognizable protein domains, largely of unknown function. We created a searchable, web-based database to allow public access to all raw, assembled and annotated data. This database is to our knowledge the largest de novo assembled and annotated transcriptome resource available for any hemimetabolous insect. We therefore anticipate that these data will contribute significantly to more effective and higher-throughput deployment of molecular analysis tools in Gryllus. PMID:23671567

Comparison of topological clustering within protein networks using edge metrics that evaluate full sequence, full structure, and active site microenvironment similarity

PubMed Central

Leuthaeuser, Janelle B; Knutson, Stacy T; Kumar, Kiran; Babbitt, Patricia C; Fetrow, Jacquelyn S

2015-01-01

The development of accurate protein function annotation methods has emerged as a major unsolved biological problem. Protein similarity networks, one approach to function annotation via annotation transfer, group proteins into similarity-based clusters. An underlying assumption is that the edge metric used to identify such clusters correlates with functional information. In this contribution, this assumption is evaluated by observing topologies in similarity networks using three different edge metrics: sequence (BLAST), structure (TM-Align), and active site similarity (active site profiling, implemented in DASP). Network topologies for four well-studied protein superfamilies (enolase, peroxiredoxin (Prx), glutathione transferase (GST), and crotonase) were compared with curated functional hierarchies and structure. As expected, network topology differs, depending on edge metric; comparison of topologies provides valuable information on structure/function relationships. Subnetworks based on active site similarity correlate with known functional hierarchies at a single edge threshold more often than sequence- or structure-based networks. Sequence- and structure-based networks are useful for identifying sequence and domain similarities and differences; therefore, it is important to consider the clustering goal before deciding appropriate edge metric. Further, conserved active site residues identified in enolase and GST active site subnetworks correspond with published functionally important residues. Extension of this analysis yields predictions of functionally determinant residues for GST subgroups. These results support the hypothesis that active site similarity-based networks reveal clusters that share functional details and lay the foundation for capturing functionally relevant hierarchies using an approach that is both automatable and can deliver greater precision in function annotation than current similarity-based methods. PMID:26073648

De novo transcriptomic analysis and development of EST-SSRs for Sorbus pohuashanensis (Hance) Hedl.

PubMed Central

Guan, Xuelian; Fu, Qiang; Zhang, Ze; Hu, Zenghui; Zheng, Jian; Lu, Yizeng; Li, Wei

2017-01-01

Sorbus pohuashanensis is a native tree species of northern China that is used for a variety of ecological purposes. The species is often grown as an ornamental landscape tree because of its beautiful form, silver flowers in early summer, attractive pinnate leaves in summer, and red leaves and fruits in autumn. However, development and further utilization of the species are hindered by the lack of comprehensive genetic information, which impedes research into its genetics and molecular biology. Recent advances in de novo transcriptome sequencing (RNA-seq) technology have provided an effective means to obtain genomic information from non-model species. Here, we applied RNA-seq for sequencing S. pohuashanensis leaves and obtained a total of 137,506 clean reads. After assembly, 96,213 unigenes with an average length of 770 bp were obtained. We found that 64.5% of the unigenes could be annotated using bioinformatics tools to analyze gene function and alignment with the NCBI database. Overall, 59,089 unigenes were annotated using the Nr database(non-redundant protein database), 35,225 unigenes were annotated using the GO (Gene Ontology categories) database, and 33,168 unigenes were annotated using COG (Cluster of Orthologous Groups). Analysis of the unigenes using the KEGG (Kyoto Encyclopedia of Genes and Genomes) database indicated that 13,953 unigenes were involved in 322 metabolic pathways. Finally, simple sequence repeat (SSR) site detection identified 6,604 unigenes that included EST-SSRs and a total of 7,473 EST-SSRs in the unigene sequences. Fifteen polymorphic SSRs were screened and found to be of use for future genetic research. These unigene sequences will provide important genetic resources for genetic improvement and investigation of biochemical processes in S. pohuashanensis. PMID:28614366

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 American cranberry mitochondrial genome reveals the presence of selenocysteine (tRNA-Sec and SECIS) insertion machinery in land plants.

PubMed

Fajardo, Diego; Schlautman, Brandon; Steffan, Shawn; Polashock, James; Vorsa, Nicholi; Zalapa, Juan

2014-02-25

This is the first de novo assembly and annotation of a complete mitochondrial genome in the Ericales order from the American cranberry (Vaccinium macrocarpon Ait.). Moreover, only four complete Asterid mitochondrial genomes have been made publicly available. The cranberry mitochondrial genome was assembled and reconstructed from whole genome 454 Roche GS-FLX and Illumina shotgun sequences. Compared with other Asterids, the reconstruction of the genome revealed an average size mitochondrion (459,678 nt) with relatively little repetitive sequences and DNA of plastid origin. The complete mitochondrial genome of cranberry was annotated obtaining a total of 34 genes classified based on their putative function, plus three ribosomal RNAs, and 17 transfer RNAs. Maternal organellar cranberry inheritance was inferred by analyzing gene variation in the cranberry mitochondria and plastid genomes. The annotation of cranberry mitochondrial genome revealed the presence of two copies of tRNA-Sec and a selenocysteine insertion sequence (SECIS) element which were lost in plants during evolution. This is the first report of a land plant possessing selenocysteine insertion machinery at the sequence level. Published by Elsevier B.V.

The Internet and Library and Information Services: A Review, Analysis, and Annotated Bibliography. Occasional Papers No. 202.

ERIC Educational Resources Information Center

Liu, Lewis-Guodo

This work provides a review and analysis of the literature and an annotated bibliography of 446 sources on the Internet and library and information services. The bibliography is divided alphabetically according to the following topics: academic libraries and scholarly research; bibliographies, directories, guides, and glossaries; business…

Ethical Issues in Health Services: A Report and Annotated Bibliography.

ERIC Educational Resources Information Center

Carmody, James

This publication identifies, discusses, and lists areas for further research for five ethical issues related to health services: 1) the right to health care; 2) death and euthanasia; 3) human experimentation; 4) genetic engineering; and, 5) abortion. Following a discussion of each issue is a selected annotated bibliography covering the years 1967…

Complete genome sequence of the plant pathogen Erwinia amylovora strain ATCC 49946

USDA-ARS?s Scientific Manuscript database

Erwinia amylovora causes the economically important disease fire blight that affects rosaceous plants, especially pear and apple. Here we report the complete genome sequence and annotation of strain ATCC 49946. The analysis of the sequence and its comparison with sequenced genomes of closely related...

Ten steps to get started in Genome Assembly and Annotation

PubMed Central

Dominguez Del Angel, Victoria; Hjerde, Erik; Sterck, Lieven; Capella-Gutierrez, Salvadors; Notredame, Cederic; Vinnere Pettersson, Olga; Amselem, Joelle; Bouri, Laurent; Bocs, Stephanie; Klopp, Christophe; Gibrat, Jean-Francois; Vlasova, Anna; Leskosek, Brane L.; Soler, Lucile; Binzer-Panchal, Mahesh; Lantz, Henrik

2018-01-01

As a part of the ELIXIR-EXCELERATE efforts in capacity building, we present here 10 steps to facilitate researchers getting started in genome assembly and genome annotation. The guidelines given are broadly applicable, intended to be stable over time, and cover all aspects from start to finish of a general assembly and annotation project. Intrinsic properties of genomes are discussed, as is the importance of using high quality DNA. Different sequencing technologies and generally applicable workflows for genome assembly are also detailed. We cover structural and functional annotation and encourage readers to also annotate transposable elements, something that is often omitted from annotation workflows. The importance of data management is stressed, and we give advice on where to submit data and how to make your results Findable, Accessible, Interoperable, and Reusable (FAIR). PMID:29568489

Analyses of deep mammalian sequence alignments and constraint predictions for 1% of the human genome

PubMed Central

Margulies, Elliott H.; Cooper, Gregory M.; Asimenos, George; Thomas, Daryl J.; Dewey, Colin N.; Siepel, Adam; Birney, Ewan; Keefe, Damian; Schwartz, Ariel S.; Hou, Minmei; Taylor, James; Nikolaev, Sergey; Montoya-Burgos, Juan I.; Löytynoja, Ari; Whelan, Simon; Pardi, Fabio; Massingham, Tim; Brown, James B.; Bickel, Peter; Holmes, Ian; Mullikin, James C.; Ureta-Vidal, Abel; Paten, Benedict; Stone, Eric A.; Rosenbloom, Kate R.; Kent, W. James; Bouffard, Gerard G.; Guan, Xiaobin; Hansen, Nancy F.; Idol, Jacquelyn R.; Maduro, Valerie V.B.; Maskeri, Baishali; McDowell, Jennifer C.; Park, Morgan; Thomas, Pamela J.; Young, Alice C.; Blakesley, Robert W.; Muzny, Donna M.; Sodergren, Erica; Wheeler, David A.; Worley, Kim C.; Jiang, Huaiyang; Weinstock, George M.; Gibbs, Richard A.; Graves, Tina; Fulton, Robert; Mardis, Elaine R.; Wilson, Richard K.; Clamp, Michele; Cuff, James; Gnerre, Sante; Jaffe, David B.; Chang, Jean L.; Lindblad-Toh, Kerstin; Lander, Eric S.; Hinrichs, Angie; Trumbower, Heather; Clawson, Hiram; Zweig, Ann; Kuhn, Robert M.; Barber, Galt; Harte, Rachel; Karolchik, Donna; Field, Matthew A.; Moore, Richard A.; Matthewson, Carrie A.; Schein, Jacqueline E.; Marra, Marco A.; Antonarakis, Stylianos E.; Batzoglou, Serafim; Goldman, Nick; Hardison, Ross; Haussler, David; Miller, Webb; Pachter, Lior; Green, Eric D.; Sidow, Arend

2007-01-01

A key component of the ongoing ENCODE project involves rigorous comparative sequence analyses for the initially targeted 1% of the human genome. Here, we present orthologous sequence generation, alignment, and evolutionary constraint analyses of 23 mammalian species for all ENCODE targets. Alignments were generated using four different methods; comparisons of these methods reveal large-scale consistency but substantial differences in terms of small genomic rearrangements, sensitivity (sequence coverage), and specificity (alignment accuracy). We describe the quantitative and qualitative trade-offs concomitant with alignment method choice and the levels of technical error that need to be accounted for in applications that require multisequence alignments. Using the generated alignments, we identified constrained regions using three different methods. While the different constraint-detecting methods are in general agreement, there are important discrepancies relating to both the underlying alignments and the specific algorithms. However, by integrating the results across the alignments and constraint-detecting methods, we produced constraint annotations that were found to be robust based on multiple independent measures. Analyses of these annotations illustrate that most classes of experimentally annotated functional elements are enriched for constrained sequences; however, large portions of each class (with the exception of protein-coding sequences) do not overlap constrained regions. The latter elements might not be under primary sequence constraint, might not be constrained across all mammals, or might have expendable molecular functions. Conversely, 40% of the constrained sequences do not overlap any of the functional elements that have been experimentally identified. Together, these findings demonstrate and quantify how many genomic functional elements await basic molecular characterization. PMID:17567995

Genomic Sequence Variation Markup Language (GSVML).

PubMed

Nakaya, Jun; Kimura, Michio; Hiroi, Kaei; Ido, Keisuke; Yang, Woosung; Tanaka, Hiroshi

2010-02-01

With the aim of making good use of internationally accumulated genomic sequence variation data, which is increasing rapidly due to the explosive amount of genomic research at present, the development of an interoperable data exchange format and its international standardization are necessary. Genomic Sequence Variation Markup Language (GSVML) will focus on genomic sequence variation data and human health applications, such as gene based medicine or pharmacogenomics. We developed GSVML through eight steps, based on case analysis and domain investigations. By focusing on the design scope to human health applications and genomic sequence variation, we attempted to eliminate ambiguity and to ensure practicability. We intended to satisfy the requirements derived from the use case analysis of human-based clinical genomic applications. Based on database investigations, we attempted to minimize the redundancy of the data format, while maximizing the data covering range. We also attempted to ensure communication and interface ability with other Markup Languages, for exchange of omics data among various omics researchers or facilities. The interface ability with developing clinical standards, such as the Health Level Seven Genotype Information model, was analyzed. We developed the human health-oriented GSVML comprising variation data, direct annotation, and indirect annotation categories; the variation data category is required, while the direct and indirect annotation categories are optional. The annotation categories contain omics and clinical information, and have internal relationships. For designing, we examined 6 cases for three criteria as human health application and 15 data elements for three criteria as data formats for genomic sequence variation data exchange. The data format of five international SNP databases and six Markup Languages and the interface ability to the Health Level Seven Genotype Model in terms of 317 items were investigated. GSVML was developed as a potential data exchanging format for genomic sequence variation data exchange focusing on human health applications. The international standardization of GSVML is necessary, and is currently underway. GSVML can be applied to enhance the utilization of genomic sequence variation data worldwide by providing a communicable platform between clinical and research applications. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.

SplicingTypesAnno: annotating and quantifying alternative splicing events for RNA-Seq data.

PubMed

Sun, Xiaoyong; Zuo, Fenghua; Ru, Yuanbin; Guo, Jiqiang; Yan, Xiaoyan; Sablok, Gaurav

2015-04-01

Alternative splicing plays a key role in the regulation of the central dogma. Four major types of alternative splicing have been classified as intron retention, exon skipping, alternative 5 splice sites or alternative donor sites, and alternative 3 splice sites or alternative acceptor sites. A few algorithms have been developed to detect splice junctions from RNA-Seq reads. However, there are few tools targeting at the major alternative splicing types at the exon/intron level. This type of analysis may reveal subtle, yet important events of alternative splicing, and thus help gain deeper understanding of the mechanism of alternative splicing. This paper describes a user-friendly R package, extracting, annotating and analyzing alternative splicing types for sequence alignment files from RNA-Seq. SplicingTypesAnno can: (1) provide annotation for major alternative splicing at exon/intron level. By comparing the annotation from GTF/GFF file, it identifies the novel alternative splicing sites; (2) offer a convenient two-level analysis: genome-scale annotation for users with high performance computing environment, and gene-scale annotation for users with personal computers; (3) generate a user-friendly web report and additional BED files for IGV visualization. SplicingTypesAnno is a user-friendly R package for extracting, annotating and analyzing alternative splicing types at exon/intron level for sequence alignment files from RNA-Seq. It is publically available at https://sourceforge.net/projects/splicingtypes/files/ or http://genome.sdau.edu.cn/research/software/SplicingTypesAnno.html. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Arkas: Rapid reproducible RNAseq analysis

PubMed Central

Colombo, Anthony R.; J. Triche Jr, Timothy; Ramsingh, Giridharan

2017-01-01

The recently introduced Kallisto pseudoaligner has radically simplified the quantification of transcripts in RNA-sequencing experiments.  We offer cloud-scale RNAseq pipelines Arkas-Quantification, and Arkas-Analysis available within Illumina’s BaseSpace cloud application platform which expedites Kallisto preparatory routines, reliably calculates differential expression, and performs gene-set enrichment of REACTOME pathways .  Due to inherit inefficiencies of scale, Illumina's BaseSpace computing platform offers a massively parallel distributive environment improving data management services and data importing.   Arkas-Quantification deploys Kallisto for parallel cloud computations and is conveniently integrated downstream from the BaseSpace Sequence Read Archive (SRA) import/conversion application titled SRA Import.  Arkas-Analysis annotates the Kallisto results by extracting structured information directly from source FASTA files with per-contig metadata, calculates the differential expression and gene-set enrichment analysis on both coding genes and transcripts. The Arkas cloud pipeline supports ENSEMBL transcriptomes and can be used downstream from the SRA Import facilitating raw sequencing importing, SRA FASTQ conversion, RNA quantification and analysis steps. PMID:28868134

Towards a complete map of the human long non-coding RNA transcriptome.

PubMed

Uszczynska-Ratajczak, Barbara; Lagarde, Julien; Frankish, Adam; Guigó, Roderic; Johnson, Rory

2018-05-23

Gene maps, or annotations, enable us to navigate the functional landscape of our genome. They are a resource upon which virtually all studies depend, from single-gene to genome-wide scales and from basic molecular biology to medical genetics. Yet present-day annotations suffer from trade-offs between quality and size, with serious but often unappreciated consequences for downstream studies. This is particularly true for long non-coding RNAs (lncRNAs), which are poorly characterized compared to protein-coding genes. Long-read sequencing technologies promise to improve current annotations, paving the way towards a complete annotation of lncRNAs expressed throughout a human lifetime.

The DNA Data Bank of Japan launches a new resource, the DDBJ Omics Archive of functional genomics experiments.

PubMed

Kodama, Yuichi; Mashima, Jun; Kaminuma, Eli; Gojobori, Takashi; Ogasawara, Osamu; Takagi, Toshihisa; Okubo, Kousaku; Nakamura, Yasukazu

2012-01-01

The DNA Data Bank of Japan (DDBJ; http://www.ddbj.nig.ac.jp) maintains and provides archival, retrieval and analytical resources for biological information. The central DDBJ resource consists of public, open-access nucleotide sequence databases including raw sequence reads, assembly information and functional annotation. Database content is exchanged with EBI and NCBI within the framework of the International Nucleotide Sequence Database Collaboration (INSDC). In 2011, DDBJ launched two new resources: the 'DDBJ Omics Archive' (DOR; http://trace.ddbj.nig.ac.jp/dor) and BioProject (http://trace.ddbj.nig.ac.jp/bioproject). DOR is an archival database of functional genomics data generated by microarray and highly parallel new generation sequencers. Data are exchanged between the ArrayExpress at EBI and DOR in the common MAGE-TAB format. BioProject provides an organizational framework to access metadata about research projects and the data from the projects that are deposited into different databases. In this article, we describe major changes and improvements introduced to the DDBJ services, and the launch of two new resources: DOR and BioProject.

Transcriptome sequencing and identification of cold tolerance genes in hardy Corylus species (C. heterophylla Fisch) floral buds.

PubMed

Chen, Xin; Zhang, Jin; Liu, Qingzhong; Guo, Wei; Zhao, Tiantian; Ma, Qinghua; Wang, Guixi

2014-01-01

The genus Corylus is an important woody species in Northeast China. Its products, hazelnuts, constitute one of the most important raw materials for the pastry and chocolate industry. However, limited genetic research has focused on Corylus because of the lack of genomic resources. The advent of high-throughput sequencing technologies provides a turning point for Corylus research. In the present study, we performed de novo transcriptome sequencing for the first time to produce a comprehensive database for the Corylus heterophylla Fisch floral buds. The C. heterophylla Fisch floral buds transcriptome was sequenced using the Illumina paired-end sequencing technology. We produced 28,930,890 raw reads and assembled them into 82,684 contigs. A total of 40,941 unigenes were identified, among which 30,549 were annotated in the NCBI Non-redundant (Nr) protein database and 18,581 were annotated in the Swiss-Prot database. Of these annotated unigenes, 25,311 and 10,514 unigenes were assigned to gene ontology (GO) categories and clusters of orthologous groups (COG), respectively. We could map 17,207 unigenes onto 128 pathways using the Kyoto Encyclopedia of Genes and Genomes Pathway (KEGG) database. Additionally, based on the transcriptome, we constructed a candidate cold tolerance gene set of C. heterophylla Fisch floral buds. The expression patterns of selected genes during four stages of cold acclimation suggested that these genes might be involved in different cold responsive stages in C. heterophylla Fisch floral buds. The transcriptome of C. heterophylla Fisch floral buds was deep sequenced, de novo assembled, and annotated, providing abundant data to better understand the C. heterophylla Fisch floral buds transcriptome. Candidate genes potentially involved in cold tolerance were identified, providing a material basis for future molecular mechanism analysis of C. heterophylla Fisch floral buds tolerant to cold stress.

i5k | National Agricultural Library

Science.gov Websites

genome browser, and the Apollo manual curation service. Over 50 arthropod genomes are now part of the i5k (done by Dan Hughes at Baylor) with manual annotations by the research community (done via Web Apollo with manual annotations by the research community (via the Apollo manual annotation software). insects

Annotated Bibliography, Part Two, Final Report for Phase I, Rural Shared Services.

ERIC Educational Resources Information Center

Northern Montana Coll., Havre.

Part Two of a four-part report, designed to identify, evaluate, and synthesize shared services research and development efforts conducted throughout the nation, presents an annotated bibliography of 32 books and 36 articles which describe various attempts to improve rural education. The 68 publications dating from 1958 to 1968 were selected by a…

Office of Maternal and Child Health Active Projects FY 1989. An Annotated Listing.

ERIC Educational Resources Information Center

National Center for Education in Maternal and Child Health, Washington, DC.

An annotated listing is presented of projects offering maternal and child health care services. These projects, referred to as special projects of regional and national significance (SPRANS), are supported by the Office of Maternal and Child Health of the Department of Health and Human Services. The first section provides information on services…

Genome content analysis yields new insights into the relationship between the human malaria parasite Plasmodium falciparum and its anopheline vectors.

PubMed

Oppenheim, Sara J; Rosenfeld, Jeffrey A; DeSalle, Rob

2017-02-27

The persistent and growing gap between the availability of sequenced genomes and the ability to assign functions to sequenced genes led us to explore ways to maximize the information content of automated annotation for studies of anopheline mosquitos. Specifically, we use genome content analysis of a large number of previously sequenced anopheline mosquitos to follow the loss and gain of protein families over the evolutionary history of this group. The importance of this endeavor lies in the potential for comparative genomic studies between Anopheles and closely related non-vector species to reveal ancestral genome content dynamics involved in vector competence. In addition, comparisons within Anopheles could identify genome content changes responsible for variation in the vectorial capacity of this family of important parasite vectors. The competence and capacity of P. falciparum vectors do not appear to be phylogenetically constrained within the Anophelinae. Instead, using ancestral reconstruction methods, we suggest that a previously unexamined component of vector biology, anopheline nucleotide metabolism, may contribute to the unique status of anophelines as P. falciparum vectors. While the fitness effects of nucleotide co-option by P. falciparum parasites on their anopheline hosts are not yet known, our results suggest that anopheline genome content may be responding to selection pressure from P. falciparum. Whether this response is defensive, in an attempt to redress improper nucleotide balance resulting from P. falciparum infection, or perhaps symbiotic, resulting from an as-yet-unknown mutualism between anophelines and P. falciparum, is an open question that deserves further study. Clearly, there is a wealth of functional information to be gained from detailed manual genome annotation, yet the rapid increase in the number of available sequences means that most researchers will not have the time or resources to manually annotate all the sequence data they generate. We believe that efforts to maximize the amount of information obtained from automated annotation can help address the functional annotation deficit that most evolutionary biologists now face, and here demonstrate the value of such an approach.

Analysis and Functional Annotation of an Expressed Sequence Tag Collection for Tropical Crop Sugarcane

PubMed Central

Vettore, André L.; da Silva, Felipe R.; Kemper, Edson L.; Souza, Glaucia M.; da Silva, Aline M.; Ferro, Maria Inês T.; Henrique-Silva, Flavio; Giglioti, Éder A.; Lemos, Manoel V.F.; Coutinho, Luiz L.; Nobrega, Marina P.; Carrer, Helaine; França, Suzelei C.; Bacci, Maurício; Goldman, Maria Helena S.; Gomes, Suely L.; Nunes, Luiz R.; Camargo, Luis E.A.; Siqueira, Walter J.; Van Sluys, Marie-Anne; Thiemann, Otavio H.; Kuramae, Eiko E.; Santelli, Roberto V.; Marino, Celso L.; Targon, Maria L.P.N.; Ferro, Jesus A.; Silveira, Henrique C.S.; Marini, Danyelle C.; Lemos, Eliana G.M.; Monteiro-Vitorello, Claudia B.; Tambor, José H.M.; Carraro, Dirce M.; Roberto, Patrícia G.; Martins, Vanderlei G.; Goldman, Gustavo H.; de Oliveira, Regina C.; Truffi, Daniela; Colombo, Carlos A.; Rossi, Magdalena; de Araujo, Paula G.; Sculaccio, Susana A.; Angella, Aline; Lima, Marleide M.A.; de Rosa, Vicente E.; Siviero, Fábio; Coscrato, Virginia E.; Machado, Marcos A.; Grivet, Laurent; Di Mauro, Sonia M.Z.; Nobrega, Francisco G.; Menck, Carlos F.M.; Braga, Marilia D.V.; Telles, Guilherme P.; Cara, Frank A.A.; Pedrosa, Guilherme; Meidanis, João; Arruda, Paulo

2003-01-01

To contribute to our understanding of the genome complexity of sugarcane, we undertook a large-scale expressed sequence tag (EST) program. More than 260,000 cDNA clones were partially sequenced from 26 standard cDNA libraries generated from different sugarcane tissues. After the processing of the sequences, 237,954 high-quality ESTs were identified. These ESTs were assembled into 43,141 putative transcripts. Of the assembled sequences, 35.6% presented no matches with existing sequences in public databases. A global analysis of the whole SUCEST data set indicated that 14,409 assembled sequences (33% of the total) contained at least one cDNA clone with a full-length insert. Annotation of the 43,141 assembled sequences associated almost 50% of the putative identified sugarcane genes with protein metabolism, cellular communication/signal transduction, bioenergetics, and stress responses. Inspection of the translated assembled sequences for conserved protein domains revealed 40,821 amino acid sequences with 1415 Pfam domains. Reassembling the consensus sequences of the 43,141 transcripts revealed a 22% redundancy in the first assembling. This indicated that possibly 33,620 unique genes had been identified and indicated that >90% of the sugarcane expressed genes were tagged. PMID:14613979

An approach to describing and analysing bulk biological annotation quality: a case study using UniProtKB.

PubMed

Bell, Michael J; Gillespie, Colin S; Swan, Daniel; Lord, Phillip

2012-09-15

Annotations are a key feature of many biological databases, used to convey our knowledge of a sequence to the reader. Ideally, annotations are curated manually, however manual curation is costly, time consuming and requires expert knowledge and training. Given these issues and the exponential increase of data, many databases implement automated annotation pipelines in an attempt to avoid un-annotated entries. Both manual and automated annotations vary in quality between databases and annotators, making assessment of annotation reliability problematic for users. The community lacks a generic measure for determining annotation quality and correctness, which we look at addressing within this article. Specifically we investigate word reuse within bulk textual annotations and relate this to Zipf's Principle of Least Effort. We use the UniProt Knowledgebase (UniProtKB) as a case study to demonstrate this approach since it allows us to compare annotation change, both over time and between automated and manually curated annotations. By applying power-law distributions to word reuse in annotation, we show clear trends in UniProtKB over time, which are consistent with existing studies of quality on free text English. Further, we show a clear distinction between manual and automated analysis and investigate cohorts of protein records as they mature. These results suggest that this approach holds distinct promise as a mechanism for judging annotation quality. Source code is available at the authors website: http://homepages.cs.ncl.ac.uk/m.j.bell1/annotation. phillip.lord@newcastle.ac.uk.

Metabolic Pathway Assignment of Plant Genes based on Phylogenetic Profiling–A Feasibility Study

PubMed Central

Weißenborn, Sandra; Walther, Dirk

2017-01-01

Despite many developed experimental and computational approaches, functional gene annotation remains challenging. With the rapidly growing number of sequenced genomes, the concept of phylogenetic profiling, which predicts functional links between genes that share a common co-occurrence pattern across different genomes, has gained renewed attention as it promises to annotate gene functions based on presence/absence calls alone. We applied phylogenetic profiling to the problem of metabolic pathway assignments of plant genes with a particular focus on secondary metabolism pathways. We determined phylogenetic profiles for 40,960 metabolic pathway enzyme genes with assigned EC numbers from 24 plant species based on sequence and pathway annotation data from KEGG and Ensembl Plants. For gene sequence family assignments, needed to determine the presence or absence of particular gene functions in the given plant species, we included data of all 39 species available at the Ensembl Plants database and established gene families based on pairwise sequence identities and annotation information. Aside from performing profiling comparisons, we used machine learning approaches to predict pathway associations from phylogenetic profiles alone. Selected metabolic pathways were indeed found to be composed of gene families of greater than expected phylogenetic profile similarity. This was particularly evident for primary metabolism pathways, whereas for secondary pathways, both the available annotation in different species as well as the abstraction of functional association via distinct pathways proved limiting. While phylogenetic profile similarity was generally not found to correlate with gene co-expression, direct physical interactions of proteins were reflected by a significantly increased profile similarity suggesting an application of phylogenetic profiling methods as a filtering step in the identification of protein-protein interactions. This feasibility study highlights the potential and challenges associated with phylogenetic profiling methods for the detection of functional relationships between genes as well as the need to enlarge the set of plant genes with proven secondary metabolism involvement as well as the limitations of distinct pathways as abstractions of relationships between genes. PMID:29163570

DNApod: DNA polymorphism annotation database from next-generation sequence read archives.

PubMed

Mochizuki, Takako; Tanizawa, Yasuhiro; Fujisawa, Takatomo; Ohta, Tazro; Nikoh, Naruo; Shimizu, Tokurou; Toyoda, Atsushi; Fujiyama, Asao; Kurata, Nori; Nagasaki, Hideki; Kaminuma, Eli; Nakamura, Yasukazu

2017-01-01

With the rapid advances in next-generation sequencing (NGS), datasets for DNA polymorphisms among various species and strains have been produced, stored, and distributed. However, reliability varies among these datasets because the experimental and analytical conditions used differ among assays. Furthermore, such datasets have been frequently distributed from the websites of individual sequencing projects. It is desirable to integrate DNA polymorphism data into one database featuring uniform quality control that is distributed from a single platform at a single place. DNA polymorphism annotation database (DNApod; http://tga.nig.ac.jp/dnapod/) is an integrated database that stores genome-wide DNA polymorphism datasets acquired under uniform analytical conditions, and this includes uniformity in the quality of the raw data, the reference genome version, and evaluation algorithms. DNApod genotypic data are re-analyzed whole-genome shotgun datasets extracted from sequence read archives, and DNApod distributes genome-wide DNA polymorphism datasets and known-gene annotations for each DNA polymorphism. This new database was developed for storing genome-wide DNA polymorphism datasets of plants, with crops being the first priority. Here, we describe our analyzed data for 679, 404, and 66 strains of rice, maize, and sorghum, respectively. The analytical methods are available as a DNApod workflow in an NGS annotation system of the DNA Data Bank of Japan and a virtual machine image. Furthermore, DNApod provides tables of links of identifiers between DNApod genotypic data and public phenotypic data. To advance the sharing of organism knowledge, DNApod offers basic and ubiquitous functions for multiple alignment and phylogenetic tree construction by using orthologous gene information.

DNApod: DNA polymorphism annotation database from next-generation sequence read archives

PubMed Central

Mochizuki, Takako; Tanizawa, Yasuhiro; Fujisawa, Takatomo; Ohta, Tazro; Nikoh, Naruo; Shimizu, Tokurou; Toyoda, Atsushi; Fujiyama, Asao; Kurata, Nori; Nagasaki, Hideki; Kaminuma, Eli; Nakamura, Yasukazu

2017-01-01

With the rapid advances in next-generation sequencing (NGS), datasets for DNA polymorphisms among various species and strains have been produced, stored, and distributed. However, reliability varies among these datasets because the experimental and analytical conditions used differ among assays. Furthermore, such datasets have been frequently distributed from the websites of individual sequencing projects. It is desirable to integrate DNA polymorphism data into one database featuring uniform quality control that is distributed from a single platform at a single place. DNA polymorphism annotation database (DNApod; http://tga.nig.ac.jp/dnapod/) is an integrated database that stores genome-wide DNA polymorphism datasets acquired under uniform analytical conditions, and this includes uniformity in the quality of the raw data, the reference genome version, and evaluation algorithms. DNApod genotypic data are re-analyzed whole-genome shotgun datasets extracted from sequence read archives, and DNApod distributes genome-wide DNA polymorphism datasets and known-gene annotations for each DNA polymorphism. This new database was developed for storing genome-wide DNA polymorphism datasets of plants, with crops being the first priority. Here, we describe our analyzed data for 679, 404, and 66 strains of rice, maize, and sorghum, respectively. The analytical methods are available as a DNApod workflow in an NGS annotation system of the DNA Data Bank of Japan and a virtual machine image. Furthermore, DNApod provides tables of links of identifiers between DNApod genotypic data and public phenotypic data. To advance the sharing of organism knowledge, DNApod offers basic and ubiquitous functions for multiple alignment and phylogenetic tree construction by using orthologous gene information. PMID:28234924

Proteogenomic Analysis of Polymorphisms and Gene Annotation Divergences in Prokaryotes using a Clustered Mass Spectrometry-Friendly Database*

PubMed Central

de Souza, Gustavo A.; Arntzen, Magnus Ø.; Fortuin, Suereta; Schürch, Anita C.; Målen, Hiwa; McEvoy, Christopher R. E.; van Soolingen, Dick; Thiede, Bernd; Warren, Robin M.; Wiker, Harald G.

2011-01-01

Precise annotation of genes or open reading frames is still a difficult task that results in divergence even for data generated from the same genomic sequence. This has an impact in further proteomic studies, and also compromises the characterization of clinical isolates with many specific genetic variations that may not be represented in the selected database. We recently developed software called multistrain mass spectrometry prokaryotic database builder (MSMSpdbb) that can merge protein databases from several sources and be applied on any prokaryotic organism, in a proteomic-friendly approach. We generated a database for the Mycobacterium tuberculosis complex (using three strains of Mycobacterium bovis and five of M. tuberculosis), and analyzed data collected from two laboratory strains and two clinical isolates of M. tuberculosis. We identified 2561 proteins, of which 24 were present in M. tuberculosis H37Rv samples, but not annotated in the M. tuberculosis H37Rv genome. We were also able to identify 280 nonsynonymous single amino acid polymorphisms and confirm 367 translational start sites. As a proof of concept we applied the database to whole-genome DNA sequencing data of one of the clinical isolates, which allowed the validation of 116 predicted single amino acid polymorphisms and the annotation of 131 N-terminal start sites. Moreover we identified regions not present in the original M. tuberculosis H37Rv sequence, indicating strain divergence or errors in the reference sequence. In conclusion, we demonstrated the potential of using a merged database to better characterize laboratory or clinical bacterial strains. PMID:21030493

Reptilian Transcriptomes v2.0: An Extensive Resource for Sauropsida Genomics and Transcriptomics

PubMed Central

Tzika, Athanasia C.; Ullate-Agote, Asier; Grbic, Djordje; Milinkovitch, Michel C.

2015-01-01

Despite the availability of deep-sequencing techniques, genomic and transcriptomic data remain unevenly distributed across phylogenetic groups. For example, reptiles are poorly represented in sequence databases, hindering functional evolutionary and developmental studies in these lineages substantially more diverse than mammals. In addition, different studies use different assembly and annotation protocols, inhibiting meaningful comparisons. Here, we present the “Reptilian Transcriptomes Database 2.0,” which provides extensive annotation of transcriptomes and genomes from species covering the major reptilian lineages. To this end, we sequenced normalized complementary DNA libraries of multiple adult tissues and various embryonic stages of the leopard gecko and the corn snake and gathered published reptilian sequence data sets from representatives of the four extant orders of reptiles: Squamata (snakes and lizards), the tuatara, crocodiles, and turtles. The LANE runner 2.0 software was implemented to annotate all assemblies within a single integrated pipeline. We show that this approach increases the annotation completeness of the assembled transcriptomes/genomes. We then built large concatenated protein alignments of single-copy genes and inferred phylogenetic trees that support the positions of turtles and the tuatara as sister groups of Archosauria and Squamata, respectively. The Reptilian Transcriptomes Database 2.0 resource will be updated to include selected new data sets as they become available, thus making it a reference for differential expression studies, comparative genomics and transcriptomics, linkage mapping, molecular ecology, and phylogenomic analyses involving reptiles. The database is available at www.reptilian-transcriptomes.org and can be enquired using a wwwblast server installed at the University of Geneva. PMID:26133641

SG-ADVISER mtDNA: a web server for mitochondrial DNA annotation with data from 200 samples of a healthy aging cohort.

PubMed

Rueda, Manuel; Torkamani, Ali

2017-08-18

Whole genome and exome sequencing usually include reads containing mitochondrial DNA (mtDNA). Yet, state-of-the-art pipelines and services for human nuclear genome variant calling and annotation do not handle mitochondrial genome data appropriately. As a consequence, any researcher desiring to add mtDNA variant analysis to their investigations is forced to explore the literature for mtDNA pipelines, evaluate them, and implement their own instance of the desired tool. This task is far from trivial, and can be prohibitive for non-bioinformaticians. We have developed SG-ADVISER mtDNA, a web server to facilitate the analysis and interpretation of mtDNA genomic data coming from next generation sequencing (NGS) experiments. The server was built in the context of our SG-ADVISER framework and on top of the MtoolBox platform (Calabrese et al., Bioinformatics 30(21):3115-3117, 2014), and includes most of its functionalities (i.e., assembly of mitochondrial genomes, heteroplasmic fractions, haplogroup assignment, functional and prioritization analysis of mitochondrial variants) as well as a back-end and a front-end interface. The server has been tested with unpublished data from 200 individuals of a healthy aging cohort (Erikson et al., Cell 165(4):1002-1011, 2016) and their data is made publicly available here along with a preliminary analysis of the variants. We observed that individuals over ~90 years old carried low levels of heteroplasmic variants in their genomes. SG-ADVISER mtDNA is a fast and functional tool that allows for variant calling and annotation of human mtDNA data coming from NGS experiments. The server was built with simplicity in mind, and builds on our own experience in interpreting mtDNA variants in the context of sudden death and rare diseases. Our objective is to provide an interface for non-bioinformaticians aiming to acquire (or contrast) mtDNA annotations via MToolBox. SG-ADVISER web server is freely available to all users at https://genomics.scripps.edu/mtdna .

Construction of a robust microarray from a non-model species (largemouth bass) using pyrosequencing technology

PubMed Central

Garcia-Reyero, Natàlia; Griffitt, Robert J.; Liu, Li; Kroll, Kevin J.; Farmerie, William G.; Barber, David S.; Denslow, Nancy D.

2009-01-01

A novel custom microarray for largemouth bass (Micropterus salmoides) was designed with sequences obtained from a normalized cDNA library using the 454 Life Sciences GS-20 pyrosequencer. This approach yielded in excess of 58 million bases of high-quality sequence. The sequence information was combined with 2,616 reads obtained by traditional suppressive subtractive hybridizations to derive a total of 31,391 unique sequences. Annotation and coding sequences were predicted for these transcripts where possible. 16,350 annotated transcripts were selected as target sequences for the design of the custom largemouth bass oligonucleotide microarray. The microarray was validated by examining the transcriptomic response in male largemouth bass exposed to 17β-œstradiol. Transcriptomic responses were assessed in liver and gonad, and indicated gene expression profiles typical of exposure to œstradiol. The results demonstrate the potential to rapidly create the tools necessary to assess large scale transcriptional responses in non-model species, paving the way for expanded impact of toxicogenomics in ecotoxicology. PMID:19936325

Representing annotation compositionality and provenance for the Semantic Web

PubMed Central

2013-01-01

Background Though the annotation of digital artifacts with metadata has a long history, the bulk of that work focuses on the association of single terms or concepts to single targets. As annotation efforts expand to capture more complex information, annotations will need to be able to refer to knowledge structures formally defined in terms of more atomic knowledge structures. Existing provenance efforts in the Semantic Web domain primarily focus on tracking provenance at the level of whole triples and do not provide enough detail to track how individual triple elements of annotations were derived from triple elements of other annotations. Results We present a task- and domain-independent ontological model for capturing annotations and their linkage to their denoted knowledge representations, which can be singular concepts or more complex sets of assertions. We have implemented this model as an extension of the Information Artifact Ontology in OWL and made it freely available, and we show how it can be integrated with several prominent annotation and provenance models. We present several application areas for the model, ranging from linguistic annotation of text to the annotation of disease-associations in genome sequences. Conclusions With this model, progressively more complex annotations can be composed from other annotations, and the provenance of compositional annotations can be represented at the annotation level or at the level of individual elements of the RDF triples composing the annotations. This in turn allows for progressively richer annotations to be constructed from previous annotation efforts, the precise provenance recording of which facilitates evidence-based inference and error tracking. PMID:24268021

Unbiased Taxonomic Annotation of Metagenomic Samples

PubMed Central

Fosso, Bruno; Pesole, Graziano; Rosselló, Francesc

2018-01-01

Abstract The classification of reads from a metagenomic sample using a reference taxonomy is usually based on first mapping the reads to the reference sequences and then classifying each read at a node under the lowest common ancestor of the candidate sequences in the reference taxonomy with the least classification error. However, this taxonomic annotation can be biased by an imbalanced taxonomy and also by the presence of multiple nodes in the taxonomy with the least classification error for a given read. In this article, we show that the Rand index is a better indicator of classification error than the often used area under the receiver operating characteristic (ROC) curve and F-measure for both balanced and imbalanced reference taxonomies, and we also address the second source of bias by reducing the taxonomic annotation problem for a whole metagenomic sample to a set cover problem, for which a logarithmic approximation can be obtained in linear time and an exact solution can be obtained by integer linear programming. Experimental results with a proof-of-concept implementation of the set cover approach to taxonomic annotation in a next release of the TANGO software show that the set cover approach further reduces ambiguity in the taxonomic annotation obtained with TANGO without distorting the relative abundance profile of the metagenomic sample. PMID:29028181

UniProtKB/Swiss-Prot, the Manually Annotated Section of the UniProt KnowledgeBase: How to Use the Entry View.

PubMed

Boutet, Emmanuel; Lieberherr, Damien; Tognolli, Michael; Schneider, Michel; Bansal, Parit; Bridge, Alan J; Poux, Sylvain; Bougueleret, Lydie; Xenarios, Ioannis

2016-01-01

The Universal Protein Resource (UniProt, http://www.uniprot.org ) consortium is an initiative of the SIB Swiss Institute of Bioinformatics (SIB), the European Bioinformatics Institute (EBI) and the Protein Information Resource (PIR) to provide the scientific community with a central resource for protein sequences and functional information. The UniProt consortium maintains the UniProt KnowledgeBase (UniProtKB), updated every 4 weeks, and several supplementary databases including the UniProt Reference Clusters (UniRef) and the UniProt Archive (UniParc).The Swiss-Prot section of the UniProt KnowledgeBase (UniProtKB/Swiss-Prot) contains publicly available expertly manually annotated protein sequences obtained from a broad spectrum of organisms. Plant protein entries are produced in the frame of the Plant Proteome Annotation Program (PPAP), with an emphasis on characterized proteins of Arabidopsis thaliana and Oryza sativa. High level annotations provided by UniProtKB/Swiss-Prot are widely used to predict annotation of newly available proteins through automatic pipelines.The purpose of this chapter is to present a guided tour of a UniProtKB/Swiss-Prot entry. We will also present some of the tools and databases that are linked to each entry.

OrthoMCL: Identification of Ortholog Groups for Eukaryotic Genomes

PubMed Central

Li, Li; Stoeckert, Christian J.; Roos, David S.

2003-01-01

The identification of orthologous groups is useful for genome annotation, studies on gene/protein evolution, comparative genomics, and the identification of taxonomically restricted sequences. Methods successfully exploited for prokaryotic genome analysis have proved difficult to apply to eukaryotes, however, as larger genomes may contain multiple paralogous genes, and sequence information is often incomplete. OrthoMCL provides a scalable method for constructing orthologous groups across multiple eukaryotic taxa, using a Markov Cluster algorithm to group (putative) orthologs and paralogs. This method performs similarly to the INPARANOID algorithm when applied to two genomes, but can be extended to cluster orthologs from multiple species. OrthoMCL clusters are coherent with groups identified by EGO, but improved recognition of “recent” paralogs permits overlapping EGO groups representing the same gene to be merged. Comparison with previously assigned EC annotations suggests a high degree of reliability, implying utility for automated eukaryotic genome annotation. OrthoMCL has been applied to the proteome data set from seven publicly available genomes (human, fly, worm, yeast, Arabidopsis, the malaria parasite Plasmodium falciparum, and Escherichia coli). A Web interface allows queries based on individual genes or user-defined phylogenetic patterns (http://www.cbil.upenn.edu/gene-family). Analysis of clusters incorporating P. falciparum genes identifies numerous enzymes that were incompletely annotated in first-pass annotation of the parasite genome. PMID:12952885

Algorithms for Hidden Markov Models Restricted to Occurrences of Regular Expressions

PubMed Central

Tataru, Paula; Sand, Andreas; Hobolth, Asger; Mailund, Thomas; Pedersen, Christian N. S.

2013-01-01

Hidden Markov Models (HMMs) are widely used probabilistic models, particularly for annotating sequential data with an underlying hidden structure. Patterns in the annotation are often more relevant to study than the hidden structure itself. A typical HMM analysis consists of annotating the observed data using a decoding algorithm and analyzing the annotation to study patterns of interest. For example, given an HMM modeling genes in DNA sequences, the focus is on occurrences of genes in the annotation. In this paper, we define a pattern through a regular expression and present a restriction of three classical algorithms to take the number of occurrences of the pattern in the hidden sequence into account. We present a new algorithm to compute the distribution of the number of pattern occurrences, and we extend the two most widely used existing decoding algorithms to employ information from this distribution. We show experimentally that the expectation of the distribution of the number of pattern occurrences gives a highly accurate estimate, while the typical procedure can be biased in the sense that the identified number of pattern occurrences does not correspond to the true number. We furthermore show that using this distribution in the decoding algorithms improves the predictive power of the model. PMID:24833225

Jannovar: a java library for exome annotation.

PubMed

Jäger, Marten; Wang, Kai; Bauer, Sebastian; Smedley, Damian; Krawitz, Peter; Robinson, Peter N

2014-05-01

Transcript-based annotation and pedigree analysis are two basic steps in the computational analysis of whole-exome sequencing experiments in genetic diagnostics and disease-gene discovery projects. Here, we present Jannovar, a stand-alone Java application as well as a Java library designed to be used in larger software frameworks for exome and genome analysis. Jannovar uses an interval tree to identify all transcripts affected by a given variant, and provides Human Genome Variation Society-compliant annotations both for variants affecting coding sequences and splice junctions as well as untranslated regions and noncoding RNA transcripts. Jannovar can also perform family-based pedigree analysis with Variant Call Format (VCF) files with data from members of a family segregating a Mendelian disorder. Using a desktop computer, Jannovar requires a few seconds to annotate a typical VCF file with exome data. Jannovar is freely available under the BSD2 license. Source code as well as the Java application and library file can be downloaded from http://compbio.charite.de (with tutorial) and https://github.com/charite/jannovar. © 2014 WILEY PERIODICALS, INC.

A draft annotation and overview of the human genome

PubMed Central

Wright, Fred A; Lemon, William J; Zhao, Wei D; Sears, Russell; Zhuo, Degen; Wang, Jian-Ping; Yang, Hee-Yung; Baer, Troy; Stredney, Don; Spitzner, Joe; Stutz, Al; Krahe, Ralf; Yuan, Bo

2001-01-01

Background The recent draft assembly of the human genome provides a unified basis for describing genomic structure and function. The draft is sufficiently accurate to provide useful annotation, enabling direct observations of previously inferred biological phenomena. Results We report here a functionally annotated human gene index placed directly on the genome. The index is based on the integration of public transcript, protein, and mapping information, supplemented with computational prediction. We describe numerous global features of the genome and examine the relationship of various genetic maps with the assembly. In addition, initial sequence analysis reveals highly ordered chromosomal landscapes associated with paralogous gene clusters and distinct functional compartments. Finally, these annotation data were synthesized to produce observations of gene density and number that accord well with historical estimates. Such a global approach had previously been described only for chromosomes 21 and 22, which together account for 2.2% of the genome. Conclusions We estimate that the genome contains 65,000-75,000 transcriptional units, with exon sequences comprising 4%. The creation of a comprehensive gene index requires the synthesis of all available computational and experimental evidence. PMID:11516338

The Ensembl genome database project.

PubMed

Hubbard, T; Barker, D; Birney, E; Cameron, G; Chen, Y; Clark, L; Cox, T; Cuff, J; Curwen, V; Down, T; Durbin, R; Eyras, E; Gilbert, J; Hammond, M; Huminiecki, L; Kasprzyk, A; Lehvaslaiho, H; Lijnzaad, P; Melsopp, C; Mongin, E; Pettett, R; Pocock, M; Potter, S; Rust, A; Schmidt, E; Searle, S; Slater, G; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Stupka, E; Ureta-Vidal, A; Vastrik, I; Clamp, M

2002-01-01

The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organise biology around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of the human genome sequence, with confirmed gene predictions that have been integrated with external data sources, and is available as either an interactive web site or as flat files. It is also an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements from sequence analysis to data storage and visualisation. The Ensembl site is one of the leading sources of human genome sequence annotation and provided much of the analysis for publication by the international human genome project of the draft genome. The Ensembl system is being installed around the world in both companies and academic sites on machines ranging from supercomputers to laptops.

Translational genomics for plant breeding with the genome sequence explosion.

PubMed

Kang, Yang Jae; Lee, Taeyoung; Lee, Jayern; Shim, Sangrea; Jeong, Haneul; Satyawan, Dani; Kim, Moon Young; Lee, Suk-Ha

2016-04-01

The use of next-generation sequencers and advanced genotyping technologies has propelled the field of plant genomics in model crops and plants and enhanced the discovery of hidden bridges between genotypes and phenotypes. The newly generated reference sequences of unstudied minor plants can be annotated by the knowledge of model plants via translational genomics approaches. Here, we reviewed the strategies of translational genomics and suggested perspectives on the current databases of genomic resources and the database structures of translated information on the new genome. As a draft picture of phenotypic annotation, translational genomics on newly sequenced plants will provide valuable assistance for breeders and researchers who are interested in genetic studies. © 2015 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation.

PubMed

O'Leary, Nuala A; Wright, Mathew W; Brister, J Rodney; Ciufo, Stacy; Haddad, Diana; McVeigh, Rich; Rajput, Bhanu; Robbertse, Barbara; Smith-White, Brian; Ako-Adjei, Danso; Astashyn, Alexander; Badretdin, Azat; Bao, Yiming; Blinkova, Olga; Brover, Vyacheslav; Chetvernin, Vyacheslav; Choi, Jinna; Cox, Eric; Ermolaeva, Olga; Farrell, Catherine M; Goldfarb, Tamara; Gupta, Tripti; Haft, Daniel; Hatcher, Eneida; Hlavina, Wratko; Joardar, Vinita S; Kodali, Vamsi K; Li, Wenjun; Maglott, Donna; Masterson, Patrick; McGarvey, Kelly M; Murphy, Michael R; O'Neill, Kathleen; Pujar, Shashikant; Rangwala, Sanjida H; Rausch, Daniel; Riddick, Lillian D; Schoch, Conrad; Shkeda, Andrei; Storz, Susan S; Sun, Hanzhen; Thibaud-Nissen, Francoise; Tolstoy, Igor; Tully, Raymond E; Vatsan, Anjana R; Wallin, Craig; Webb, David; Wu, Wendy; Landrum, Melissa J; Kimchi, Avi; Tatusova, Tatiana; DiCuccio, Michael; Kitts, Paul; Murphy, Terence D; Pruitt, Kim D

2016-01-04

The RefSeq project at the National Center for Biotechnology Information (NCBI) maintains and curates a publicly available database of annotated genomic, transcript, and protein sequence records (http://www.ncbi.nlm.nih.gov/refseq/). The RefSeq project leverages the data submitted to the International Nucleotide Sequence Database Collaboration (INSDC) against a combination of computation, manual curation, and collaboration to produce a standard set of stable, non-redundant reference sequences. The RefSeq project augments these reference sequences with current knowledge including publications, functional features and informative nomenclature. The database currently represents sequences from more than 55,000 organisms (>4800 viruses, >40,000 prokaryotes and >10,000 eukaryotes; RefSeq release 71), ranging from a single record to complete genomes. This paper summarizes the current status of the viral, prokaryotic, and eukaryotic branches of the RefSeq project, reports on improvements to data access and details efforts to further expand the taxonomic representation of the collection. We also highlight diverse functional curation initiatives that support multiple uses of RefSeq data including taxonomic validation, genome annotation, comparative genomics, and clinical testing. We summarize our approach to utilizing available RNA-Seq and other data types in our manual curation process for vertebrate, plant, and other species, and describe a new direction for prokaryotic genomes and protein name management. Published by Oxford University Press on behalf of Nucleic Acids Research 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.

A UIMA wrapper for the NCBO annotator.

PubMed

Roeder, Christophe; Jonquet, Clement; Shah, Nigam H; Baumgartner, William A; Verspoor, Karin; Hunter, Lawrence

2010-07-15

The Unstructured Information Management Architecture (UIMA) framework and web services are emerging as useful tools for integrating biomedical text mining tools. This note describes our work, which wraps the National Center for Biomedical Ontology (NCBO) Annotator-an ontology-based annotation service-to make it available as a component in UIMA workflows. This wrapper is freely available on the web at http://bionlp-uima.sourceforge.net/ as part of the UIMA tools distribution from the Center for Computational Pharmacology (CCP) at the University of Colorado School of Medicine. It has been implemented in Java for support on Mac OS X, Linux and MS Windows.

The language of gene ontology: a Zipf's law analysis.

PubMed

Kalankesh, Leila Ranandeh; Stevens, Robert; Brass, Andy

2012-06-07

Most major genome projects and sequence databases provide a GO annotation of their data, either automatically or through human annotators, creating a large corpus of data written in the language of GO. Texts written in natural language show a statistical power law behaviour, Zipf's law, the exponent of which can provide useful information on the nature of the language being used. We have therefore explored the hypothesis that collections of GO annotations will show similar statistical behaviours to natural language. Annotations from the Gene Ontology Annotation project were found to follow Zipf's law. Surprisingly, the measured power law exponents were consistently different between annotation captured using the three GO sub-ontologies in the corpora (function, process and component). On filtering the corpora using GO evidence codes we found that the value of the measured power law exponent responded in a predictable way as a function of the evidence codes used to support the annotation. Techniques from computational linguistics can provide new insights into the annotation process. GO annotations show similar statistical behaviours to those seen in natural language with measured exponents that provide a signal which correlates with the nature of the evidence codes used to support the annotations, suggesting that the measured exponent might provide a signal regarding the information content of the annotation.

Automated Update, Revision, and Quality Control of the Maize Genome Annotations Using MAKER-P Improves the B73 RefGen_v3 Gene Models and Identifies New Genes1[OPEN

PubMed Central

Law, MeiYee; Childs, Kevin L.; Campbell, Michael S.; Stein, Joshua C.; Olson, Andrew J.; Holt, Carson; Panchy, Nicholas; Lei, Jikai; Jiao, Dian; Andorf, Carson M.; Lawrence, Carolyn J.; Ware, Doreen; Shiu, Shin-Han; Sun, Yanni; Jiang, Ning; Yandell, Mark

2015-01-01

The large size and relative complexity of many plant genomes make creation, quality control, and dissemination of high-quality gene structure annotations challenging. In response, we have developed MAKER-P, a fast and easy-to-use genome annotation engine for plants. Here, we report the use of MAKER-P to update and revise the maize (Zea mays) B73 RefGen_v3 annotation build (5b+) in less than 3 h using the iPlant Cyberinfrastructure. MAKER-P identified and annotated 4,466 additional, well-supported protein-coding genes not present in the 5b+ annotation build, added additional untranslated regions to 1,393 5b+ gene models, identified 2,647 5b+ gene models that lack any supporting evidence (despite the use of large and diverse evidence data sets), identified 104,215 pseudogene fragments, and created an additional 2,522 noncoding gene annotations. We also describe a method for de novo training of MAKER-P for the annotation of newly sequenced grass genomes. Collectively, these results lead to the 6a maize genome annotation and demonstrate the utility of MAKER-P for rapid annotation, management, and quality control of grasses and other difficult-to-annotate plant genomes. PMID:25384563

Recognition of Protein-coding Genes Based on Z-curve Algorithms

PubMed Central

-Biao Guo, Feng; Lin, Yan; -Ling Chen, Ling

2014-01-01

Recognition of protein-coding genes, a classical bioinformatics issue, is an absolutely needed step for annotating newly sequenced genomes. The Z-curve algorithm, as one of the most effective methods on this issue, has been successfully applied in annotating or re-annotating many genomes, including those of bacteria, archaea and viruses. Two Z-curve based ab initio gene-finding programs have been developed: ZCURVE (for bacteria and archaea) and ZCURVE_V (for viruses and phages). ZCURVE_C (for 57 bacteria) and Zfisher (for any bacterium) are web servers for re-annotation of bacterial and archaeal genomes. The above four tools can be used for genome annotation or re-annotation, either independently or combined with the other gene-finding programs. In addition to recognizing protein-coding genes and exons, Z-curve algorithms are also effective in recognizing promoters and translation start sites. Here, we summarize the applications of Z-curve algorithms in gene finding and genome annotation. PMID:24822027

Similar Ratios of Introns to Intergenic Sequence across Animal Genomes

PubMed Central

Wörheide, Gert

2017-01-01

Abstract One central goal of genome biology is to understand how the usage of the genome differs between organisms. Our knowledge of genome composition, needed for downstream inferences, is critically dependent on gene annotations, yet problems associated with gene annotation and assembly errors are usually ignored in comparative genomics. Here, we analyze the genomes of 68 species across 12 animal phyla and some single-cell eukaryotes for general trends in genome composition and transcription, taking into account problems of gene annotation. We show that, regardless of genome size, the ratio of introns to intergenic sequence is comparable across essentially all animals, with nearly all deviations dominated by increased intergenic sequence. Genomes of model organisms have ratios much closer to 1:1, suggesting that the majority of published genomes of nonmodel organisms are underannotated and consequently omit substantial numbers of genes, with likely negative impact on evolutionary interpretations. Finally, our results also indicate that most animals transcribe half or more of their genomes arguing against differences in genome usage between animal groups, and also suggesting that the transcribed portion is more dependent on genome size than previously thought. PMID:28633296

PlantFuncSSR: Integrating First and Next Generation Transcriptomics for Mining of SSR-Functional Domains Markers

PubMed Central

Sablok, Gaurav; Pérez-Pulido, Antonio J.; Do, Thac; Seong, Tan Y.; Casimiro-Soriguer, Carlos S.; La Porta, Nicola; Ralph, Peter J.; Squartini, Andrea; Muñoz-Merida, Antonio; Harikrishna, Jennifer A.

2016-01-01

Analysis of repetitive DNA sequence content and divergence among the repetitive functional classes is a well-accepted approach for estimation of inter- and intra-generic differences in plant genomes. Among these elements, microsatellites, or Simple Sequence Repeats (SSRs), have been widely demonstrated as powerful genetic markers for species and varieties discrimination. We present PlantFuncSSRs platform having more than 364 plant species with more than 2 million functional SSRs. They are provided with detailed annotations for easy functional browsing of SSRs and with information on primer pairs and associated functional domains. PlantFuncSSRs can be leveraged to identify functional-based genic variability among the species of interest, which might be of particular interest in developing functional markers in plants. This comprehensive on-line portal unifies mining of SSRs from first and next generation sequencing datasets, corresponding primer pairs and associated in-depth functional annotation such as gene ontology annotation, gene interactions and its identification from reference protein databases. PlantFuncSSRs is freely accessible at: http://www.bioinfocabd.upo.es/plantssr. PMID:27446111

Viral genome analysis and knowledge management.

PubMed

Kuiken, Carla; Yoon, Hyejin; Abfalterer, Werner; Gaschen, Brian; Lo, Chienchi; Korber, Bette

2013-01-01

One of the challenges of genetic data analysis is to combine information from sources that are distributed around the world and accessible through a wide array of different methods and interfaces. The HIV database and its footsteps, the hepatitis C virus (HCV) and hemorrhagic fever virus (HFV) databases, have made it their mission to make different data types easily available to their users. This involves a large amount of behind-the-scenes processing, including quality control and analysis of the sequences and their annotation. Gene and protein sequences are distilled from the sequences that are stored in GenBank; to this end, both submitter annotation and script-generated sequences are used. Alignments of both nucleotide and amino acid sequences are generated, manually curated, distilled into an alignment model, and regenerated in an iterative cycle that results in ever better new alignments. Annotation of epidemiological and clinical information is parsed, checked, and added to the database. User interfaces are updated, and new interfaces are added based upon user requests. Vital for its success, the database staff are heavy users of the system, which enables them to fix bugs and find opportunities for improvement. In this chapter we describe some of the infrastructure that keeps these heavily used analysis platforms alive and vital after nearly 25 years of use. The database/analysis platforms described in this chapter can be accessed at http://hiv.lanl.gov http://hcv.lanl.gov http://hfv.lanl.gov.

Analysis of the Aedes albopictus C6/36 genome provides insight into cell line utility for viral propagation.

PubMed

Miller, Jason R; Koren, Sergey; Dilley, Kari A; Puri, Vinita; Brown, David M; Harkins, Derek M; Thibaud-Nissen, Françoise; Rosen, Benjamin; Chen, Xiao-Guang; Tu, Zhijian; Sharakhov, Igor V; Sharakhova, Maria V; Sebra, Robert; Stockwell, Timothy B; Bergman, Nicholas H; Sutton, Granger G; Phillippy, Adam M; Piermarini, Peter M; Shabman, Reed S

2018-03-01

The 50-year-old Aedes albopictus C6/36 cell line is a resource for the detection, amplification, and analysis of mosquito-borne viruses including Zika, dengue, and chikungunya. The cell line is derived from an unknown number of larvae from an unspecified strain of Aedes albopictus mosquitoes. Toward improved utility of the cell line for research in virus transmission, we present an annotated assembly of the C6/36 genome. The C6/36 genome assembly has the largest contig N50 (3.3 Mbp) of any mosquito assembly, presents the sequences of both haplotypes for most of the diploid genome, reveals independent null mutations in both alleles of the Dicer locus, and indicates a male-specific genome. Gene annotation was computed with publicly available mosquito transcript sequences. Gene expression data from cell line RNA sequence identified enrichment of growth-related pathways and conspicuous deficiency in aquaporins and inward rectifier K+ channels. As a test of utility, RNA sequence data from Zika-infected cells were mapped to the C6/36 genome and transcriptome assemblies. Host subtraction reduced the data set by 89%, enabling faster characterization of nonhost reads. The C6/36 genome sequence and annotation should enable additional uses of the cell line to study arbovirus vector interactions and interventions aimed at restricting the spread of human disease.

Consistency of VDJ Rearrangement and Substitution Parameters Enables Accurate B Cell Receptor Sequence Annotation.

PubMed

Ralph, Duncan K; Matsen, Frederick A

2016-01-01

VDJ rearrangement and somatic hypermutation work together to produce antibody-coding B cell receptor (BCR) sequences for a remarkable diversity of antigens. It is now possible to sequence these BCRs in high throughput; analysis of these sequences is bringing new insight into how antibodies develop, in particular for broadly-neutralizing antibodies against HIV and influenza. A fundamental step in such sequence analysis is to annotate each base as coming from a specific one of the V, D, or J genes, or from an N-addition (a.k.a. non-templated insertion). Previous work has used simple parametric distributions to model transitions from state to state in a hidden Markov model (HMM) of VDJ recombination, and assumed that mutations occur via the same process across sites. However, codon frame and other effects have been observed to violate these parametric assumptions for such coding sequences, suggesting that a non-parametric approach to modeling the recombination process could be useful. In our paper, we find that indeed large modern data sets suggest a model using parameter-rich per-allele categorical distributions for HMM transition probabilities and per-allele-per-position mutation probabilities, and that using such a model for inference leads to significantly improved results. We present an accurate and efficient BCR sequence annotation software package using a novel HMM "factorization" strategy. This package, called partis (https://github.com/psathyrella/partis/), is built on a new general-purpose HMM compiler that can perform efficient inference given a simple text description of an HMM.

Generation, annotation and analysis of ESTs from Trichoderma harzianum CECT 2413

PubMed Central

Vizcaíno, Juan Antonio; González, Francisco Javier; Suárez, M Belén; Redondo, José; Heinrich, Julian; Delgado-Jarana, Jesús; Hermosa, Rosa; Gutiérrez, Santiago; Monte, Enrique; Llobell, Antonio; Rey, Manuel

2006-01-01

Background The filamentous fungus Trichoderma harzianum is used as biological control agent of several plant-pathogenic fungi. In order to study the genome of this fungus, a functional genomics project called "TrichoEST" was developed to give insights into genes involved in biological control activities using an approach based on the generation of expressed sequence tags (ESTs). Results Eight different cDNA libraries from T. harzianum strain CECT 2413 were constructed. Different growth conditions involving mainly different nutrient conditions and/or stresses were used. We here present the analysis of the 8,710 ESTs generated. A total of 3,478 unique sequences were identified of which 81.4% had sequence similarity with GenBank entries, using the BLASTX algorithm. Using the Gene Ontology hierarchy, we performed the annotation of 51.1% of the unique sequences and compared its distribution among the gene libraries. Additionally, the InterProScan algorithm was used in order to further characterize the sequences. The identification of the putatively secreted proteins was also carried out. Later, based on the EST abundance, we examined the highly expressed genes and a hydrophobin was identified as the gene expressed at the highest level. We compared our collection of ESTs with the previous collections obtained from Trichoderma species and we also compared our sequence set with different complete eukaryotic genomes from several animals, plants and fungi. Accordingly, the presence of similar sequences in different kingdoms was also studied. Conclusion This EST collection and its annotation provide a significant resource for basic and applied research on T. harzianum, a fungus with a high biotechnological interest. PMID:16872539

Identification of novel biomass-degrading enzymes from genomic dark matter: Populating genomic sequence space with functional annotation.

PubMed

Piao, Hailan; Froula, Jeff; Du, Changbin; Kim, Tae-Wan; Hawley, Erik R; Bauer, Stefan; Wang, Zhong; Ivanova, Nathalia; Clark, Douglas S; Klenk, Hans-Peter; Hess, Matthias

2014-08-01

Although recent nucleotide sequencing technologies have significantly enhanced our understanding of microbial genomes, the function of ∼35% of genes identified in a genome currently remains unknown. To improve the understanding of microbial genomes and consequently of microbial processes it will be crucial to assign a function to this "genomic dark matter." Due to the urgent need for additional carbohydrate-active enzymes for improved production of transportation fuels from lignocellulosic biomass, we screened the genomes of more than 5,500 microorganisms for hypothetical proteins that are located in the proximity of already known cellulases. We identified, synthesized and expressed a total of 17 putative cellulase genes with insufficient sequence similarity to currently known cellulases to be identified as such using traditional sequence annotation techniques that rely on significant sequence similarity. The recombinant proteins of the newly identified putative cellulases were subjected to enzymatic activity assays to verify their hydrolytic activity towards cellulose and lignocellulosic biomass. Eleven (65%) of the tested enzymes had significant activity towards at least one of the substrates. This high success rate highlights that a gene context-based approach can be used to assign function to genes that are otherwise categorized as "genomic dark matter" and to identify biomass-degrading enzymes that have little sequence similarity to already known cellulases. The ability to assign function to genes that have no related sequence representatives with functional annotation will be important to enhance our understanding of microbial processes and to identify microbial proteins for a wide range of applications. © 2014 Wiley Periodicals, Inc.

EFICAz2: enzyme function inference by a combined approach enhanced by machine learning.

PubMed

Arakaki, Adrian K; Huang, Ying; Skolnick, Jeffrey

2009-04-13

We previously developed EFICAz, an enzyme function inference approach that combines predictions from non-completely overlapping component methods. Two of the four components in the original EFICAz are based on the detection of functionally discriminating residues (FDRs). FDRs distinguish between member of an enzyme family that are homofunctional (classified under the EC number of interest) or heterofunctional (annotated with another EC number or lacking enzymatic activity). Each of the two FDR-based components is associated to one of two specific kinds of enzyme families. EFICAz exhibits high precision performance, except when the maximal test to training sequence identity (MTTSI) is lower than 30%. To improve EFICAz's performance in this regime, we: i) increased the number of predictive components and ii) took advantage of consensual information from the different components to make the final EC number assignment. We have developed two new EFICAz components, analogs to the two FDR-based components, where the discrimination between homo and heterofunctional members is based on the evaluation, via Support Vector Machine models, of all the aligned positions between the query sequence and the multiple sequence alignments associated to the enzyme families. Benchmark results indicate that: i) the new SVM-based components outperform their FDR-based counterparts, and ii) both SVM-based and FDR-based components generate unique predictions. We developed classification tree models to optimally combine the results from the six EFICAz components into a final EC number prediction. The new implementation of our approach, EFICAz2, exhibits a highly improved prediction precision at MTTSI < 30% compared to the original EFICAz, with only a slight decrease in prediction recall. A comparative analysis of enzyme function annotation of the human proteome by EFICAz2 and KEGG shows that: i) when both sources make EC number assignments for the same protein sequence, the assignments tend to be consistent and ii) EFICAz2 generates considerably more unique assignments than KEGG. Performance benchmarks and the comparison with KEGG demonstrate that EFICAz2 is a powerful and precise tool for enzyme function annotation, with multiple applications in genome analysis and metabolic pathway reconstruction. The EFICAz2 web service is available at: http://cssb.biology.gatech.edu/skolnick/webservice/EFICAz2/index.html.

GAVIN: Gene-Aware Variant INterpretation for medical sequencing.

PubMed

van der Velde, K Joeri; de Boer, Eddy N; van Diemen, Cleo C; Sikkema-Raddatz, Birgit; Abbott, Kristin M; Knopperts, Alain; Franke, Lude; Sijmons, Rolf H; de Koning, Tom J; Wijmenga, Cisca; Sinke, Richard J; Swertz, Morris A

2017-01-16

We present Gene-Aware Variant INterpretation (GAVIN), a new method that accurately classifies variants for clinical diagnostic purposes. Classifications are based on gene-specific calibrations of allele frequencies from the ExAC database, likely variant impact using SnpEff, and estimated deleteriousness based on CADD scores for >3000 genes. In a benchmark on 18 clinical gene sets, we achieve a sensitivity of 91.4% and a specificity of 76.9%. This accuracy is unmatched by 12 other tools. We provide GAVIN as an online MOLGENIS service to annotate VCF files and as an open source executable for use in bioinformatic pipelines. It can be found at http://molgenis.org/gavin .

Expanded microbial genome coverage and improved protein family annotation in the COG database

PubMed Central

Galperin, Michael Y.; Makarova, Kira S.; Wolf, Yuri I.; Koonin, Eugene V.

2015-01-01

Microbial genome sequencing projects produce numerous sequences of deduced proteins, only a small fraction of which have been or will ever be studied experimentally. This leaves sequence analysis as the only feasible way to annotate these proteins and assign to them tentative functions. The Clusters of Orthologous Groups of proteins (COGs) database (http://www.ncbi.nlm.nih.gov/COG/), first created in 1997, has been a popular tool for functional annotation. Its success was largely based on (i) its reliance on complete microbial genomes, which allowed reliable assignment of orthologs and paralogs for most genes; (ii) orthology-based approach, which used the function(s) of the characterized member(s) of the protein family (COG) to assign function(s) to the entire set of carefully identified orthologs and describe the range of potential functions when there were more than one; and (iii) careful manual curation of the annotation of the COGs, aimed at detailed prediction of the biological function(s) for each COG while avoiding annotation errors and overprediction. Here we present an update of the COGs, the first since 2003, and a comprehensive revision of the COG annotations and expansion of the genome coverage to include representative complete genomes from all bacterial and archaeal lineages down to the genus level. This re-analysis of the COGs shows that the original COG assignments had an error rate below 0.5% and allows an assessment of the progress in functional genomics in the past 12 years. During this time, functions of many previously uncharacterized COGs have been elucidated and tentative functional assignments of many COGs have been validated, either by targeted experiments or through the use of high-throughput methods. A particularly important development is the assignment of functions to several widespread, conserved proteins many of which turned out to participate in translation, in particular rRNA maturation and tRNA modification. The new version of the COGs is expected to become an important tool for microbial genomics. PMID:25428365

Draft genome sequence and annotation of Lactobacillus acetotolerans BM-LA14527, a beer-spoilage bacteria.

PubMed

Liu, Junyan; Li, Lin; Peters, Brian M; Li, Bing; Deng, Yang; Xu, Zhenbo; Shirtliff, Mark E

2016-09-01

Lactobacillus acetotolerans is a hard-to-culture beer-spoilage bacterium capable of entering into the viable putative nonculturable (VPNC) state. As part of an initial strategy to investigate the phenotypic behavior of L. acetotolerans, draft genome sequencing was performed. Results demonstrated a total of 1824 predicted annotated genes, with several potential VPNC- and beer-spoilage-associated genes identified. Importantly, this is the first genome sequence of L. acetotolerans as beer-spoilage bacteria and it may aid in further analysis of L. acetotolerans and other beer-spoilage bacteria, with direct implications for food safety control in the beer brewing industry. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Protein Function Prediction: Problems and Pitfalls.

PubMed

Pearson, William R

2015-09-03

The characterization of new genomes based on their protein sets has been revolutionized by new sequencing technologies, but biologists seeking to exploit new sequence information are often frustrated by the challenges associated with accurately assigning biological functions to newly identified proteins. Here, we highlight some of the challenges in functional inference from sequence similarity. Investigators can improve the accuracy of function prediction by (1) being conservative about the evolutionary distance to a protein of known function; (2) considering the ambiguous meaning of "functional similarity," and (3) being aware of the limitations of annotations in functional databases. Protein function prediction does not offer "one-size-fits-all" solutions. Prediction strategies work better when the idiosyncrasies of function and functional annotation are better understood. Copyright © 2015 John Wiley & Sons, Inc.

BepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes

PubMed Central

Jespersen, Martin Closter; Peters, Bjoern

2017-01-01

Abstract Antibodies have become an indispensable tool for many biotechnological and clinical applications. They bind their molecular target (antigen) by recognizing a portion of its structure (epitope) in a highly specific manner. The ability to predict epitopes from antigen sequences alone is a complex task. Despite substantial effort, limited advancement has been achieved over the last decade in the accuracy of epitope prediction methods, especially for those that rely on the sequence of the antigen only. Here, we present BepiPred-2.0 (http://www.cbs.dtu.dk/services/BepiPred/), a web server for predicting B-cell epitopes from antigen sequences. BepiPred-2.0 is based on a random forest algorithm trained on epitopes annotated from antibody-antigen protein structures. This new method was found to outperform other available tools for sequence-based epitope prediction both on epitope data derived from solved 3D structures, and on a large collection of linear epitopes downloaded from the IEDB database. The method displays results in a user-friendly and informative way, both for computer-savvy and non-expert users. We believe that BepiPred-2.0 will be a valuable tool for the bioinformatics and immunology community. PMID:28472356

Exome sequencing reveals novel genetic loci influencing obesity-related traits in Hispanic children

USDA-ARS?s Scientific Manuscript database

To perform whole exome sequencing in 928 Hispanic children and identify variants and genes associated with childhood obesity.Single-nucleotide variants (SNVs) were identified from Illumina whole exome sequencing data using integrated read mapping, variant calling, and an annotation pipeline (Mercury...

xHMMER3x2: Utilizing HMMER3's speed and HMMER2's sensitivity and specificity in the glocal alignment mode for improved large-scale protein domain annotation.

PubMed

Yap, Choon-Kong; Eisenhaber, Birgit; Eisenhaber, Frank; Wong, Wing-Cheong

2016-11-29

While the local-mode HMMER3 is notable for its massive speed improvement, the slower glocal-mode HMMER2 is more exact for domain annotation by enforcing full domain-to-sequence alignments. Since a unit of domain necessarily implies a unit of function, local-mode HMMER3 alone remains insufficient for precise function annotation tasks. In addition, the incomparable E-values for the same domain model by different HMMER builds create difficulty when checking for domain annotation consistency on a large-scale basis. In this work, both the speed of HMMER3 and glocal-mode alignment of HMMER2 are combined within the xHMMER3x2 framework for tackling the large-scale domain annotation task. Briefly, HMMER3 is utilized for initial domain detection so that HMMER2 can subsequently perform the glocal-mode, sequence-to-full-domain alignments for the detected HMMER3 hits. An E-value calibration procedure is required to ensure that the search space by HMMER2 is sufficiently replicated by HMMER3. We find that the latter is straightforwardly possible for ~80% of the models in the Pfam domain library (release 29). However in the case of the remaining ~20% of HMMER3 domain models, the respective HMMER2 counterparts are more sensitive. Thus, HMMER3 searches alone are insufficient to ensure sensitivity and a HMMER2-based search needs to be initiated. When tested on the set of UniProt human sequences, xHMMER3x2 can be configured to be between 7× and 201× faster than HMMER2, but with descending domain detection sensitivity from 99.8 to 95.7% with respect to HMMER2 alone; HMMER3's sensitivity was 95.7%. At extremes, xHMMER3x2 is either the slow glocal-mode HMMER2 or the fast HMMER3 with glocal-mode. Finally, the E-values to false-positive rates (FPR) mapping by xHMMER3x2 allows E-values of different model builds to be compared, so that any annotation discrepancies in a large-scale annotation exercise can be flagged for further examination by dissectHMMER. The xHMMER3x2 workflow allows large-scale domain annotation speed to be drastically improved over HMMER2 without compromising for domain-detection with regard to sensitivity and sequence-to-domain alignment incompleteness. The xHMMER3x2 code and its webserver (for Pfam release 27, 28 and 29) are freely available at http://xhmmer3x2.bii.a-star.edu.sg/ . Reviewed by Thomas Dandekar, L. Aravind, Oliviero Carugo and Shamil Sunyaev. For the full reviews, please go to the Reviewers' comments section.

Counselor's Information Service: A Quarterly Annotated Bibliography of Current Literature on Educational and Vocational Guidance. Volume 30, Number 4, December 1975.

ERIC Educational Resources Information Center

B'nai B'rith, Washington, DC. Career and Counseling Services.

This publication is a quarterly annotated bibliography of current literature on educational and vocational guidance, and is developed by the B'nai B'rith Career and Counseling Services, Washington, D.C. The topics covered are occupational information, educational, vocational and personal guidance; guidance administration and procedures; student…

Sourcebook for Sex Equality: In-Service Training. An Annotated Listing of Materials and Media for Affirmative Action In-Service Training. Bibliographic Series, 2.

ERIC Educational Resources Information Center

Hulme, Marylin A., Comp.

The materials contained in this annotated bibliography include films, slide shows, information resources, evaluation materials, sample workshop formats, and guidelines for sex-fair and race-fair materials and group activities. The bibliography is divided into four sections: (1) "General Resources" includes readings in sex role stereotyping,…

Evaluation of web-based annotation of ophthalmic images for multicentric clinical trials.

PubMed

Chalam, K V; Jain, P; Shah, V A; Shah, Gaurav Y

2006-06-01

An Internet browser-based annotation system can be used to identify and describe features in digitalized retinal images, in multicentric clinical trials, in real time. In this web-based annotation system, the user employs a mouse to draw and create annotations on a transparent layer, that encapsulates the observations and interpretations of a specific image. Multiple annotation layers may be overlaid on a single image. These layers may correspond to annotations by different users on the same image or annotations of a temporal sequence of images of a disease process, over a period of time. In addition, geometrical properties of annotated figures may be computed and measured. The annotations are stored in a central repository database on a server, which can be retrieved by multiple users in real time. This system facilitates objective evaluation of digital images and comparison of double-blind readings of digital photographs, with an identifiable audit trail. Annotation of ophthalmic images allowed clinically feasible and useful interpretation to track properties of an area of fundus pathology. This provided an objective method to monitor properties of pathologies over time, an essential component of multicentric clinical trials. The annotation system also allowed users to view stereoscopic images that are stereo pairs. This web-based annotation system is useful and valuable in monitoring patient care, in multicentric clinical trials, telemedicine, teaching and routine clinical settings.

37 CFR 41.110 - Filing claim information.

Code of Federal Regulations, 2011 CFR

2011-07-01

..., each party must file a clean copy of its involved claims and, if a biotechnology material sequence is a... in a drawing or biotechnology material sequence, file an annotated copy of the claim indicating in...

37 CFR 41.110 - Filing claim information.

Code of Federal Regulations, 2010 CFR

2010-07-01

..., each party must file a clean copy of its involved claims and, if a biotechnology material sequence is a... in a drawing or biotechnology material sequence, file an annotated copy of the claim indicating in...

Cancer Genome Interpreter annotates the biological and clinical relevance of tumor alterations.

PubMed

Tamborero, David; Rubio-Perez, Carlota; Deu-Pons, Jordi; Schroeder, Michael P; Vivancos, Ana; Rovira, Ana; Tusquets, Ignasi; Albanell, Joan; Rodon, Jordi; Tabernero, Josep; de Torres, Carmen; Dienstmann, Rodrigo; Gonzalez-Perez, Abel; Lopez-Bigas, Nuria

2018-03-28

While tumor genome sequencing has become widely available in clinical and research settings, the interpretation of tumor somatic variants remains an important bottleneck. Here we present the Cancer Genome Interpreter, a versatile platform that automates the interpretation of newly sequenced cancer genomes, annotating the potential of alterations detected in tumors to act as drivers and their possible effect on treatment response. The results are organized in different levels of evidence according to current knowledge, which we envision can support a broad range of oncology use cases. The resource is publicly available at http://www.cancergenomeinterpreter.org .

Comparative high-throughput transcriptome sequencing and development of SiESTa, the Silene EST annotation database

PubMed Central

2011-01-01

Background The genus Silene is widely used as a model system for addressing ecological and evolutionary questions in plants, but advances in using the genus as a model system are impeded by the lack of available resources for studying its genome. Massively parallel sequencing cDNA has recently developed into an efficient method for characterizing the transcriptomes of non-model organisms, generating massive amounts of data that enable the study of multiple species in a comparative framework. The sequences generated provide an excellent resource for identifying expressed genes, characterizing functional variation and developing molecular markers, thereby laying the foundations for future studies on gene sequence and gene expression divergence. Here, we report the results of a comparative transcriptome sequencing study of eight individuals representing four Silene and one Dianthus species as outgroup. All sequences and annotations have been deposited in a newly developed and publicly available database called SiESTa, the Silene EST annotation database. Results A total of 1,041,122 EST reads were generated in two runs on a Roche GS-FLX 454 pyrosequencing platform. EST reads were analyzed separately for all eight individuals sequenced and were assembled into contigs using TGICL. These were annotated with results from BLASTX searches and Gene Ontology (GO) terms, and thousands of single-nucleotide polymorphisms (SNPs) were characterized. Unassembled reads were kept as singletons and together with the contigs contributed to the unigenes characterized in each individual. The high quality of unigenes is evidenced by the proportion (49%) that have significant hits in similarity searches with the A. thaliana proteome. The SiESTa database is accessible at http://www.siesta.ethz.ch. Conclusion The sequence collections established in the present study provide an important genomic resource for four Silene and one Dianthus species and will help to further develop Silene as a plant model system. The genes characterized will be useful for future research not only in the species included in the present study, but also in related species for which no genomic resources are yet available. Our results demonstrate the efficiency of massively parallel transcriptome sequencing in a comparative framework as an approach for developing genomic resources in diverse groups of non-model organisms. PMID:21791039

MannDB: A microbial annotation database for protein characterization

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

Zhou, C; Lam, M; Smith, J

2006-05-19

MannDB was created to meet a need for rapid, comprehensive automated protein sequence analyses to support selection of proteins suitable as targets for driving the development of reagents for pathogen or protein toxin detection. Because a large number of open-source tools were needed, it was necessary to produce a software system to scale the computations for whole-proteome analysis. Thus, we built a fully automated system for executing software tools and for storage, integration, and display of automated protein sequence analysis and annotation data. MannDB is a relational database that organizes data resulting from fully automated, high-throughput protein-sequence analyses using open-sourcemore » tools. Types of analyses provided include predictions of cleavage, chemical properties, classification, features, functional assignment, post-translational modifications, motifs, antigenicity, and secondary structure. Proteomes (lists of hypothetical and known proteins) are downloaded and parsed from Genbank and then inserted into MannDB, and annotations from SwissProt are downloaded when identifiers are found in the Genbank entry or when identical sequences are identified. Currently 36 open-source tools are run against MannDB protein sequences either on local systems or by means of batch submission to external servers. In addition, BLAST against protein entries in MvirDB, our database of microbial virulence factors, is performed. A web client browser enables viewing of computational results and downloaded annotations, and a query tool enables structured and free-text search capabilities. When available, links to external databases, including MvirDB, are provided. MannDB contains whole-proteome analyses for at least one representative organism from each category of biological threat organism listed by APHIS, CDC, HHS, NIAID, USDA, USFDA, and WHO. MannDB comprises a large number of genomes and comprehensive protein sequence analyses representing organisms listed as high-priority agents on the websites of several governmental organizations concerned with bio-terrorism. MannDB provides the user with a BLAST interface for comparison of native and non-native sequences and a query tool for conveniently selecting proteins of interest. In addition, the user has access to a web-based browser that compiles comprehensive and extensive reports.« less

De Novo Assembly and Characterization of the Transcriptome of the Chinese Medicinal Herb, Gentiana rigescens

PubMed Central

Zhang, Xiaodong; Allan, Andrew C.; Li, Caixia; Wang, Yuanzhong; Yao, Qiuyang

2015-01-01

Gentiana rigescens is an important medicinal herb in China. The main validated medicinal component gentiopicroside is synthesized in shoots, but is mainly found in the plant’s roots. The gentiopicroside biosynthetic pathway and its regulatory control remain to be elucidated. Genome resources of gentian are limited. Next-generation sequencing (NGS) technologies can aid in supplying global gene expression profiles. In this study we present sequence and transcript abundance data for the root and leaf transcriptome of G. rigescens, obtained using the Illumina Hiseq2000. Over fifty million clean reads were obtained from leaf and root libraries. This yields 76,717 unigenes with an average length of 753 bp. Among these, 33,855 unigenes were identified as putative homologs of annotated sequences in public protein and nucleotide databases. Digital abundance analysis identified 3306 unigenes differentially enriched between leaf and root. Unigenes found in both tissues were categorized according to their putative functional categories. Of the differentially expressed genes, over 130 were annotated as related to terpenoid biosynthesis. This work is the first study of global transcriptome analyses in gentian. These sequences and putative functional data comprise a resource for future investigation of terpenoid biosynthesis in Gentianaceae species and annotation of the gentiopicroside biosynthetic pathway and its regulatory mechanisms. PMID:26006235

Functional sequencing read annotation for high precision microbiome analysis

PubMed Central

Zhu, Chengsheng; Miller, Maximilian; Marpaka, Srinayani; Vaysberg, Pavel; Rühlemann, Malte C; Wu, Guojun; Heinsen, Femke-Anouska; Tempel, Marie; Zhao, Liping; Lieb, Wolfgang; Franke, Andre; Bromberg, Yana

2018-01-01

Abstract The vast majority of microorganisms on Earth reside in often-inseparable environment-specific communities—microbiomes. Meta-genomic/-transcriptomic sequencing could reveal the otherwise inaccessible functionality of microbiomes. However, existing analytical approaches focus on attributing sequencing reads to known genes/genomes, often failing to make maximal use of available data. We created faser (functional annotation of sequencing reads), an algorithm that is optimized to map reads to molecular functions encoded by the read-correspondent genes. The mi-faser microbiome analysis pipeline, combining faser with our manually curated reference database of protein functions, accurately annotates microbiome molecular functionality. mi-faser’s minutes-per-microbiome processing speed is significantly faster than that of other methods, allowing for large scale comparisons. Microbiome function vectors can be compared between different conditions to highlight environment-specific and/or time-dependent changes in functionality. Here, we identified previously unseen oil degradation-specific functions in BP oil-spill data, as well as functional signatures of individual-specific gut microbiome responses to a dietary intervention in children with Prader–Willi syndrome. Our method also revealed variability in Crohn's Disease patient microbiomes and clearly distinguished them from those of related healthy individuals. Our analysis highlighted the microbiome role in CD pathogenicity, demonstrating enrichment of patient microbiomes in functions that promote inflammation and that help bacteria survive it. PMID:29194524

Breaking the 1000-gene barrier for Mimivirus using ultra-deep genome and transcriptome sequencing.

PubMed

Legendre, Matthieu; Santini, Sébastien; Rico, Alain; Abergel, Chantal; Claverie, Jean-Michel

2011-03-04

Mimivirus, a giant dsDNA virus infecting Acanthamoeba, is the prototype of the mimiviridae family, the latest addition to the family of the nucleocytoplasmic large DNA viruses (NCLDVs). Its 1.2 Mb-genome was initially predicted to encode 917 genes. A subsequent RNA-Seq analysis precisely mapped many transcript boundaries and identified 75 new genes. We now report a much deeper analysis using the SOLiD™ technology combining RNA-Seq of the Mimivirus transcriptome during the infectious cycle (202.4 Million reads), and a complete genome re-sequencing (45.3 Million reads). This study corrected the genome sequence and identified several single nucleotide polymorphisms. Our results also provided clear evidence of previously overlooked transcription units, including an important RNA polymerase subunit distantly related to Euryarchea homologues. The total Mimivirus gene count is now 1018, 11% greater than the original annotation. This study highlights the huge progress brought about by ultra-deep sequencing for the comprehensive annotation of virus genomes, opening the door to a complete one-nucleotide resolution level description of their transcriptional activity, and to the realistic modeling of the viral genome expression at the ultimate molecular level. This work also illustrates the need to go beyond bioinformatics-only approaches for the annotation of short protein and non-coding genes in viral genomes.

MODBASE, a database of annotated comparative protein structure models

PubMed Central

Pieper, Ursula; Eswar, Narayanan; Stuart, Ashley C.; Ilyin, Valentin A.; Sali, Andrej

2002-01-01

MODBASE (http://guitar.rockefeller.edu/modbase) is a relational database of annotated comparative protein structure models for all available protein sequences matched to at least one known protein structure. The models are calculated by MODPIPE, an automated modeling pipeline that relies on PSI-BLAST, IMPALA and MODELLER. MODBASE uses the MySQL relational database management system for flexible and efficient querying, and the MODVIEW Netscape plugin for viewing and manipulating multiple sequences and structures. It is updated regularly to reflect the growth of the protein sequence and structure databases, as well as improvements in the software for calculating the models. For ease of access, MODBASE is organized into different datasets. The largest dataset contains models for domains in 304 517 out of 539 171 unique protein sequences in the complete TrEMBL database (23 March 2001); only models based on significant alignments (PSI-BLAST E-value < 10–4) and models assessed to have the correct fold are included. Other datasets include models for target selection and structure-based annotation by the New York Structural Genomics Research Consortium, models for prediction of genes in the Drosophila melanogaster genome, models for structure determination of several ribosomal particles and models calculated by the MODWEB comparative modeling web server. PMID:11752309

Deep landscape update of dispersed and tandem repeats in the genome model of the red jungle fowl, Gallus gallus, using a series of de novo investigating tools.

PubMed

Guizard, Sébastien; Piégu, Benoît; Arensburger, Peter; Guillou, Florian; Bigot, Yves

2016-08-19

The program RepeatMasker and the database Repbase-ISB are part of the most widely used strategy for annotating repeats in animal genomes. They have been used to show that avian genomes have a lower repeat content (8-12 %) than the sequenced genomes of many vertebrate species (30-55 %). However, the efficiency of such a library-based strategies is dependent on the quality and completeness of the sequences in the database that is used. An alternative to these library based methods are methods that identify repeats de novo. These alternative methods have existed for a least a decade and may be more powerful than the library based methods. We have used an annotation strategy involving several complementary de novo tools to determine the repeat content of the model genome galGal4 (1.04 Gbp), including identifying simple sequence repeats (SSRs), tandem repeats and transposable elements (TEs). We annotated over one Gbp. of the galGal4 genome and showed that it is composed of approximately 19 % SSRs and TEs repeats. Furthermore, we estimate that the actual genome of the red jungle fowl contains about 31-35 % repeats. We find that library-based methods tend to overestimate TE diversity. These results have a major impact on the current understanding of repeats distributions throughout chromosomes in the red jungle fowl. Our results are a proof of concept of the reliability of using de novo tools to annotate repeats in large animal genomes. They have also revealed issues that will need to be resolved in order to develop gold-standard methodologies for annotating repeats in eukaryote genomes.

A homologue of the defender against the apoptotic death gene (dad1 )in UV-exposed Chlamydomonas cells is downregulated with the onset of programmed cell death.

PubMed

Moharikar, Swati; D'Souza, Jacinta S; Rao, Basuthkar J

2007-03-01

We report here the isolation of a homologue of the potential anti-apoptotic gene, defender against apoptotic death (dad1 )from Chlamydomonas reinhardtii cells.Using polymerase chain reaction (PCR),we investigated its expression in the execution process of programmed cell death (PCD)in UV-C exposed dying C.reinhardtii cells.Reverse- transcriptase (RT)-PCR showed that C.reinhardtii dad1 amplification was drastically reduced in UV-C exposed dying C.reinhardtii cells.We connect the downregulation of dad1 with the upregulation of apoptosis protease activating factor-1 (APAF-1)and the physiological changes that occur in C.reinhardtii cells upon exposure to 12 J/m 2 UV-C in order to show a reciprocal relationship between proapoptotic and inhibitor of apoptosis factors.The temporal changes indicate a correlation between the onset of cell death and dad1 downregulation.The sequence of the PCR product of the cDNA encoding the dad1 homologue was aligned with the annotated dad1 (C_20215)from the Chlamydomonas database (http://genome.jgi-psf.org:8080/annotator/servlet/jgi.annotation.Annotation?pDb=chlre2); Annotation?pDb=chlre2 );this sequence was found to show 100% identity,both at the nucleotide and amino acid level. The 327 bp transcript showed an open reading frame of 87 amino acid residues.The deduced amino acid sequence of the putative C.reinhardtii DAD1 homologue showed 54% identity with Oryza sativa, 56 identity with Drosophila melanogaster, 66% identity with Xenopus laevis, and 64% identity with Homo sapiens,Sus scrofa,Gallus gallus,Rattus norvegicus and Mus musculus.

ReprOlive: a database with linked data for the olive tree (Olea europaea L.) reproductive transcriptome

PubMed Central

Carmona, Rosario; Zafra, Adoración; Seoane, Pedro; Castro, Antonio J.; Guerrero-Fernández, Darío; Castillo-Castillo, Trinidad; Medina-García, Ana; Cánovas, Francisco M.; Aldana-Montes, José F.; Navas-Delgado, Ismael; Alché, Juan de Dios; Claros, M. Gonzalo

2015-01-01

Plant reproductive transcriptomes have been analyzed in different species due to the agronomical and biotechnological importance of plant reproduction. Here we presented an olive tree reproductive transcriptome database with samples from pollen and pistil at different developmental stages, and leaf and root as control vegetative tissues http://reprolive.eez.csic.es). It was developed from 2,077,309 raw reads to 1,549 Sanger sequences. Using a pre-defined workflow based on open-source tools, sequences were pre-processed, assembled, mapped, and annotated with expression data, descriptions, GO terms, InterPro signatures, EC numbers, KEGG pathways, ORFs, and SSRs. Tentative transcripts (TTs) were also annotated with the corresponding orthologs in Arabidopsis thaliana from TAIR and RefSeq databases to enable Linked Data integration. It results in a reproductive transcriptome comprising 72,846 contigs with average length of 686 bp, of which 63,965 (87.8%) included at least one functional annotation, and 55,356 (75.9%) had an ortholog. A minimum of 23,568 different TTs was identified and 5,835 of them contain a complete ORF. The representative reproductive transcriptome can be reduced to 28,972 TTs for further gene expression studies. Partial transcriptomes from pollen, pistil, and vegetative tissues as control were also constructed. ReprOlive provides free access and download capability to these results. Retrieval mechanisms for sequences and transcript annotations are provided. Graphical localization of annotated enzymes into KEGG pathways is also possible. Finally, ReprOlive has included a semantic conceptualisation by means of a Resource Description Framework (RDF) allowing a Linked Data search for extracting the most updated information related to enzymes, interactions, allergens, structures, and reactive oxygen species. PMID:26322066

A post-assembly genome-improvement toolkit (PAGIT) to obtain annotated genomes from contigs.

PubMed

Swain, Martin T; Tsai, Isheng J; Assefa, Samual A; Newbold, Chris; Berriman, Matthew; Otto, Thomas D

2012-06-07

Genome projects now produce draft assemblies within weeks owing to advanced high-throughput sequencing technologies. For milestone projects such as Escherichia coli or Homo sapiens, teams of scientists were employed to manually curate and finish these genomes to a high standard. Nowadays, this is not feasible for most projects, and the quality of genomes is generally of a much lower standard. This protocol describes software (PAGIT) that is used to improve the quality of draft genomes. It offers flexible functionality to close gaps in scaffolds, correct base errors in the consensus sequence and exploit reference genomes (if available) in order to improve scaffolding and generating annotations. The protocol is most accessible for bacterial and small eukaryotic genomes (up to 300 Mb), such as pathogenic bacteria, malaria and parasitic worms. Applying PAGIT to an E. coli assembly takes ∼24 h: it doubles the average contig size and annotates over 4,300 gene models.

Comprehensive Annotation of the Parastagonospora nodorum Reference Genome Using Next-Generation Genomics, Transcriptomics and Proteogenomics

PubMed Central

Dodhia, Kejal; Stoll, Thomas; Hastie, Marcus; Furuki, Eiko; Ellwood, Simon R.; Williams, Angela H.; Tan, Yew-Foon; Testa, Alison C.; Gorman, Jeffrey J.; Oliver, Richard P.

2016-01-01

Parastagonospora nodorum, the causal agent of Septoria nodorum blotch (SNB), is an economically important pathogen of wheat (Triticum spp.), and a model for the study of necrotrophic pathology and genome evolution. The reference P. nodorum strain SN15 was the first Dothideomycete with a published genome sequence, and has been used as the basis for comparison within and between species. Here we present an updated reference genome assembly with corrections of SNP and indel errors in the underlying genome assembly from deep resequencing data as well as extensive manual annotation of gene models using transcriptomic and proteomic sources of evidence (https://github.com/robsyme/Parastagonospora_nodorum_SN15). The updated assembly and annotation includes 8,366 genes with modified protein sequence and 866 new genes. This study shows the benefits of using a wide variety of experimental methods allied to expert curation to generate a reliable set of gene models. PMID:26840125

Alga-PrAS (Algal Protein Annotation Suite): A Database of Comprehensive Annotation in Algal Proteomes

PubMed Central

Kurotani, Atsushi; Yamada, Yutaka

2017-01-01

Algae are smaller organisms than land plants and offer clear advantages in research over terrestrial species in terms of rapid production, short generation time and varied commercial applications. Thus, studies investigating the practical development of effective algal production are important and will improve our understanding of both aquatic and terrestrial plants. In this study we estimated multiple physicochemical and secondary structural properties of protein sequences, the predicted presence of post-translational modification (PTM) sites, and subcellular localization using a total of 510,123 protein sequences from the proteomes of 31 algal and three plant species. Algal species were broadly selected from green and red algae, glaucophytes, oomycetes, diatoms and other microalgal groups. The results were deposited in the Algal Protein Annotation Suite database (Alga-PrAS; http://alga-pras.riken.jp/), which can be freely accessed online. PMID:28069893

STINGRAY: system for integrated genomic resources and analysis.

PubMed

Wagner, Glauber; Jardim, Rodrigo; Tschoeke, Diogo A; Loureiro, Daniel R; Ocaña, Kary A C S; Ribeiro, Antonio C B; Emmel, Vanessa E; Probst, Christian M; Pitaluga, André N; Grisard, Edmundo C; Cavalcanti, Maria C; Campos, Maria L M; Mattoso, Marta; Dávila, Alberto M R

2014-03-07

The STINGRAY system has been conceived to ease the tasks of integrating, analyzing, annotating and presenting genomic and expression data from Sanger and Next Generation Sequencing (NGS) platforms. STINGRAY includes: (a) a complete and integrated workflow (more than 20 bioinformatics tools) ranging from functional annotation to phylogeny; (b) a MySQL database schema, suitable for data integration and user access control; and (c) a user-friendly graphical web-based interface that makes the system intuitive, facilitating the tasks of data analysis and annotation. STINGRAY showed to be an easy to use and complete system for analyzing sequencing data. While both Sanger and NGS platforms are supported, the system could be faster using Sanger data, since the large NGS datasets could potentially slow down the MySQL database usage. STINGRAY is available at http://stingray.biowebdb.org and the open source code at http://sourceforge.net/projects/stingray-biowebdb/.

Citrus sinensis annotation project (CAP): a comprehensive database for sweet orange genome.

PubMed

Wang, Jia; Chen, Dijun; Lei, Yang; Chang, Ji-Wei; Hao, Bao-Hai; Xing, Feng; Li, Sen; Xu, Qiang; Deng, Xiu-Xin; Chen, Ling-Ling

2014-01-01

Citrus is one of the most important and widely grown fruit crop with global production ranking firstly among all the fruit crops in the world. Sweet orange accounts for more than half of the Citrus production both in fresh fruit and processed juice. We have sequenced the draft genome of a double-haploid sweet orange (C. sinensis cv. Valencia), and constructed the Citrus sinensis annotation project (CAP) to store and visualize the sequenced genomic and transcriptome data. CAP provides GBrowse-based organization of sweet orange genomic data, which integrates ab initio gene prediction, EST, RNA-seq and RNA-paired end tag (RNA-PET) evidence-based gene annotation. Furthermore, we provide a user-friendly web interface to show the predicted protein-protein interactions (PPIs) and metabolic pathways in sweet orange. CAP provides comprehensive information beneficial to the researchers of sweet orange and other woody plants, which is freely available at http://citrus.hzau.edu.cn/.

Sheep genome functional annotation reveals proximal regulatory elements contributed to the evolution of modern breeds.

PubMed

Naval-Sanchez, Marina; Nguyen, Quan; McWilliam, Sean; Porto-Neto, Laercio R; Tellam, Ross; Vuocolo, Tony; Reverter, Antonio; Perez-Enciso, Miguel; Brauning, Rudiger; Clarke, Shannon; McCulloch, Alan; Zamani, Wahid; Naderi, Saeid; Rezaei, Hamid Reza; Pompanon, Francois; Taberlet, Pierre; Worley, Kim C; Gibbs, Richard A; Muzny, Donna M; Jhangiani, Shalini N; Cockett, Noelle; Daetwyler, Hans; Kijas, James

2018-02-28

Domestication fundamentally reshaped animal morphology, physiology and behaviour, offering the opportunity to investigate the molecular processes driving evolutionary change. Here we assess sheep domestication and artificial selection by comparing genome sequence from 43 modern breeds (Ovis aries) and their Asian mouflon ancestor (O. orientalis) to identify selection sweeps. Next, we provide a comparative functional annotation of the sheep genome, validated using experimental ChIP-Seq of sheep tissue. Using these annotations, we evaluate the impact of selection and domestication on regulatory sequences and find that sweeps are significantly enriched for protein coding genes, proximal regulatory elements of genes and genome features associated with active transcription. Finally, we find individual sites displaying strong allele frequency divergence are enriched for the same regulatory features. Our data demonstrate that remodelling of gene expression is likely to have been one of the evolutionary forces that drove phenotypic diversification of this common livestock species.

STINGRAY: system for integrated genomic resources and analysis

PubMed Central

2014-01-01

Background The STINGRAY system has been conceived to ease the tasks of integrating, analyzing, annotating and presenting genomic and expression data from Sanger and Next Generation Sequencing (NGS) platforms. Findings STINGRAY includes: (a) a complete and integrated workflow (more than 20 bioinformatics tools) ranging from functional annotation to phylogeny; (b) a MySQL database schema, suitable for data integration and user access control; and (c) a user-friendly graphical web-based interface that makes the system intuitive, facilitating the tasks of data analysis and annotation. Conclusion STINGRAY showed to be an easy to use and complete system for analyzing sequencing data. While both Sanger and NGS platforms are supported, the system could be faster using Sanger data, since the large NGS datasets could potentially slow down the MySQL database usage. STINGRAY is available at http://stingray.biowebdb.org and the open source code at http://sourceforge.net/projects/stingray-biowebdb/. PMID:24606808

The De Novo Transcriptome and Its Functional Annotation in the Seed Beetle Callosobruchus maculatus.

PubMed

Sayadi, Ahmed; Immonen, Elina; Bayram, Helen; Arnqvist, Göran

2016-01-01

Despite their unparalleled biodiversity, the genomic resources available for beetles (Coleoptera) remain relatively scarce. We present an integrative and high quality annotated transcriptome of the beetle Callosobruchus maculatus, an important and cosmopolitan agricultural pest as well as an emerging model species in ecology and evolutionary biology. Using Illumina sequencing technology, we sequenced 492 million read pairs generated from 51 samples of different developmental stages (larvae, pupae and adults) of C. maculatus. Reads were de novo assembled using the Trinity software, into a single combined assembly as well as into three separate assemblies based on data from the different developmental stages. The combined assembly generated 218,192 transcripts and 145,883 putative genes. Putative genes were annotated with the Blast2GO software and the Trinotate pipeline. In total, 33,216 putative genes were successfully annotated using Blastx against the Nr (non-redundant) database and 13,382 were assigned to 34,100 Gene Ontology (GO) terms. We classified 5,475 putative genes into Clusters of Orthologous Groups (COG) and 116 metabolic pathways maps were predicted based on the annotation. Our analyses suggested that the transcriptional specificity increases with ontogeny. For example, out of 33,216 annotated putative genes, 51 were only expressed in larvae, 63 only in pupae and 171 only in adults. Our study illustrates the importance of including samples from several developmental stages when the aim is to provide an integrative and high quality annotated transcriptome. Our results will represent an invaluable resource for those working with the ecology, evolution and pest control of C. maculatus, as well for comparative studies of the transcriptomics and genomics of beetles more generally.

The De Novo Transcriptome and Its Functional Annotation in the Seed Beetle Callosobruchus maculatus

PubMed Central

Sayadi, Ahmed; Immonen, Elina; Bayram, Helen

2016-01-01

Despite their unparalleled biodiversity, the genomic resources available for beetles (Coleoptera) remain relatively scarce. We present an integrative and high quality annotated transcriptome of the beetle Callosobruchus maculatus, an important and cosmopolitan agricultural pest as well as an emerging model species in ecology and evolutionary biology. Using Illumina sequencing technology, we sequenced 492 million read pairs generated from 51 samples of different developmental stages (larvae, pupae and adults) of C. maculatus. Reads were de novo assembled using the Trinity software, into a single combined assembly as well as into three separate assemblies based on data from the different developmental stages. The combined assembly generated 218,192 transcripts and 145,883 putative genes. Putative genes were annotated with the Blast2GO software and the Trinotate pipeline. In total, 33,216 putative genes were successfully annotated using Blastx against the Nr (non-redundant) database and 13,382 were assigned to 34,100 Gene Ontology (GO) terms. We classified 5,475 putative genes into Clusters of Orthologous Groups (COG) and 116 metabolic pathways maps were predicted based on the annotation. Our analyses suggested that the transcriptional specificity increases with ontogeny. For example, out of 33,216 annotated putative genes, 51 were only expressed in larvae, 63 only in pupae and 171 only in adults. Our study illustrates the importance of including samples from several developmental stages when the aim is to provide an integrative and high quality annotated transcriptome. Our results will represent an invaluable resource for those working with the ecology, evolution and pest control of C. maculatus, as well for comparative studies of the transcriptomics and genomics of beetles more generally. PMID:27442123

Draft genome sequence of an aflatoxigenic Aspergillus species, A. bombycis

USDA-ARS?s Scientific Manuscript database

The genome of the A. bombycis Type strain was sequenced using a Personal Genome Machine, followed by annotation of its predicted genes. The genome size for A. bombycis was found to be approximately 37 Mb and contained 12,266 genes. This announcement introduces a sequenced genome for an aflatoxigenic...

Launching genomics into the cloud: deployment of Mercury, a next generation sequence analysis pipeline.

PubMed

Reid, Jeffrey G; Carroll, Andrew; Veeraraghavan, Narayanan; Dahdouli, Mahmoud; Sundquist, Andreas; English, Adam; Bainbridge, Matthew; White, Simon; Salerno, William; Buhay, Christian; Yu, Fuli; Muzny, Donna; Daly, Richard; Duyk, Geoff; Gibbs, Richard A; Boerwinkle, Eric

2014-01-29

Massively parallel DNA sequencing generates staggering amounts of data. Decreasing cost, increasing throughput, and improved annotation have expanded the diversity of genomics applications in research and clinical practice. This expanding scale creates analytical challenges: accommodating peak compute demand, coordinating secure access for multiple analysts, and sharing validated tools and results. To address these challenges, we have developed the Mercury analysis pipeline and deployed it in local hardware and the Amazon Web Services cloud via the DNAnexus platform. Mercury is an automated, flexible, and extensible analysis workflow that provides accurate and reproducible genomic results at scales ranging from individuals to large cohorts. By taking advantage of cloud computing and with Mercury implemented on the DNAnexus platform, we have demonstrated a powerful combination of a robust and fully validated software pipeline and a scalable computational resource that, to date, we have applied to more than 10,000 whole genome and whole exome samples.

FOUNTAIN: A JAVA open-source package to assist large sequencing projects

PubMed Central

Buerstedde, Jean-Marie; Prill, Florian

2001-01-01

Background Better automation, lower cost per reaction and a heightened interest in comparative genomics has led to a dramatic increase in DNA sequencing activities. Although the large sequencing projects of specialized centers are supported by in-house bioinformatics groups, many smaller laboratories face difficulties managing the appropriate processing and storage of their sequencing output. The challenges include documentation of clones, templates and sequencing reactions, and the storage, annotation and analysis of the large number of generated sequences. Results We describe here a new program, named FOUNTAIN, for the management of large sequencing projects . FOUNTAIN uses the JAVA computer language and data storage in a relational database. Starting with a collection of sequencing objects (clones), the program generates and stores information related to the different stages of the sequencing project using a web browser interface for user input. The generated sequences are subsequently imported and annotated based on BLAST searches against the public databases. In addition, simple algorithms to cluster sequences and determine putative polymorphic positions are implemented. Conclusions A simple, but flexible and scalable software package is presented to facilitate data generation and storage for large sequencing projects. Open source and largely platform and database independent, we wish FOUNTAIN to be improved and extended in a community effort. PMID:11591214

The Saccharomyces Genome Database Variant Viewer.

PubMed

Sheppard, Travis K; Hitz, Benjamin C; Engel, Stacia R; Song, Giltae; Balakrishnan, Rama; Binkley, Gail; Costanzo, Maria C; Dalusag, Kyla S; Demeter, Janos; Hellerstedt, Sage T; Karra, Kalpana; Nash, Robert S; Paskov, Kelley M; Skrzypek, Marek S; Weng, Shuai; Wong, Edith D; Cherry, J Michael

2016-01-04

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org) is the authoritative community resource for the Saccharomyces cerevisiae reference genome sequence and its annotation. In recent years, we have moved toward increased representation of sequence variation and allelic differences within S. cerevisiae. The publication of numerous additional genomes has motivated the creation of new tools for their annotation and analysis. Here we present the Variant Viewer: a dynamic open-source web application for the visualization of genomic and proteomic differences. Multiple sequence alignments have been constructed across high quality genome sequences from 11 different S. cerevisiae strains and stored in the SGD. The alignments and summaries are encoded in JSON and used to create a two-tiered dynamic view of the budding yeast pan-genome, available at http://www.yeastgenome.org/variant-viewer. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

The Draft Genome Sequence of a Novel High-Efficient Butanol-Producing Bacterium Clostridium Diolis Strain WST.

PubMed

Chen, Chaoyang; Sun, Chongran; Wu, Yi-Rui

2018-03-21

A wild-type solventogenic strain Clostridium diolis WST, isolated from mangrove sediments, was characterized to produce high amount of butanol and acetone with negligible level of ethanol and acids from glucose via a unique acetone-butanol (AB) fermentation pathway. Through the genomic sequencing, the assembled draft genome of strain WST is calculated to be 5.85 Mb with a GC content of 29.69% and contains 5263 genes that contribute to the annotation of 5049 protein-coding sequences. Within these annotated genes, the butanol dehydrogenase gene (bdh) was determined to be in a higher amount from strain WST compared to other Clostridial strains, which is positively related to its high-efficient production of butanol. Therefore, we present a draft genome sequence analysis of strain WST in this article that should facilitate to further understand the solventogenic mechanism of this special microorganism.

Factors influencing success of clinical genome sequencing across a broad spectrum of disorders

PubMed Central

Lise, Stefano; Broxholme, John; Cazier, Jean-Baptiste; Rimmer, Andy; Kanapin, Alexander; Lunter, Gerton; Fiddy, Simon; Allan, Chris; Aricescu, A. Radu; Attar, Moustafa; Babbs, Christian; Becq, Jennifer; Beeson, David; Bento, Celeste; Bignell, Patricia; Blair, Edward; Buckle, Veronica J; Bull, Katherine; Cais, Ondrej; Cario, Holger; Chapel, Helen; Copley, Richard R; Cornall, Richard; Craft, Jude; Dahan, Karin; Davenport, Emma E; Dendrou, Calliope; Devuyst, Olivier; Fenwick, Aimée L; Flint, Jonathan; Fugger, Lars; Gilbert, Rodney D; Goriely, Anne; Green, Angie; Greger, Ingo H.; Grocock, Russell; Gruszczyk, Anja V; Hastings, Robert; Hatton, Edouard; Higgs, Doug; Hill, Adrian; Holmes, Chris; Howard, Malcolm; Hughes, Linda; Humburg, Peter; Johnson, David; Karpe, Fredrik; Kingsbury, Zoya; Kini, Usha; Knight, Julian C; Krohn, Jonathan; Lamble, Sarah; Langman, Craig; Lonie, Lorne; Luck, Joshua; McCarthy, Davis; McGowan, Simon J; McMullin, Mary Frances; Miller, Kerry A; Murray, Lisa; Németh, Andrea H; Nesbit, M Andrew; Nutt, David; Ormondroyd, Elizabeth; Oturai, Annette Bang; Pagnamenta, Alistair; Patel, Smita Y; Percy, Melanie; Petousi, Nayia; Piazza, Paolo; Piret, Sian E; Polanco-Echeverry, Guadalupe; Popitsch, Niko; Powrie, Fiona; Pugh, Chris; Quek, Lynn; Robbins, Peter A; Robson, Kathryn; Russo, Alexandra; Sahgal, Natasha; van Schouwenburg, Pauline A; Schuh, Anna; Silverman, Earl; Simmons, Alison; Sørensen, Per Soelberg; Sweeney, Elizabeth; Taylor, John; Thakker, Rajesh V; Tomlinson, Ian; Trebes, Amy; Twigg, Stephen RF; Uhlig, Holm H; Vyas, Paresh; Vyse, Tim; Wall, Steven A; Watkins, Hugh; Whyte, Michael P; Witty, Lorna; Wright, Ben; Yau, Chris; Buck, David; Humphray, Sean; Ratcliffe, Peter J; Bell, John I; Wilkie, Andrew OM; Bentley, David; Donnelly, Peter; McVean, Gilean

2015-01-01

To assess factors influencing the success of whole genome sequencing for mainstream clinical diagnosis, we sequenced 217 individuals from 156 independent cases across a broad spectrum of disorders in whom prior screening had identified no pathogenic variants. We quantified the number of candidate variants identified using different strategies for variant calling, filtering, annotation and prioritisation. We found that jointly calling variants across samples, filtering against both local and external databases, deploying multiple annotation tools and using familial transmission above biological plausibility contributed to accuracy. Overall, we identified disease causing variants in 21% of cases, rising to 34% (23/68) for Mendelian disorders and 57% (8/14) in trios. We also discovered 32 potentially clinically actionable variants in 18 genes unrelated to the referral disorder, though only four were ultimately considered reportable. Our results demonstrate the value of genome sequencing for routine clinical diagnosis, but also highlight many outstanding challenges. PMID:25985138

Rapid storage and retrieval of genomic intervals from a relational database system using nested containment lists

PubMed Central

Wiley, Laura K.; Sivley, R. Michael; Bush, William S.

2013-01-01

Efficient storage and retrieval of genomic annotations based on range intervals is necessary, given the amount of data produced by next-generation sequencing studies. The indexing strategies of relational database systems (such as MySQL) greatly inhibit their use in genomic annotation tasks. This has led to the development of stand-alone applications that are dependent on flat-file libraries. In this work, we introduce MyNCList, an implementation of the NCList data structure within a MySQL database. MyNCList enables the storage, update and rapid retrieval of genomic annotations from the convenience of a relational database system. Range-based annotations of 1 million variants are retrieved in under a minute, making this approach feasible for whole-genome annotation tasks. Database URL: https://github.com/bushlab/mynclist PMID:23894185

Rapid storage and retrieval of genomic intervals from a relational database system using nested containment lists.

PubMed

Wiley, Laura K; Sivley, R Michael; Bush, William S

2013-01-01

Efficient storage and retrieval of genomic annotations based on range intervals is necessary, given the amount of data produced by next-generation sequencing studies. The indexing strategies of relational database systems (such as MySQL) greatly inhibit their use in genomic annotation tasks. This has led to the development of stand-alone applications that are dependent on flat-file libraries. In this work, we introduce MyNCList, an implementation of the NCList data structure within a MySQL database. MyNCList enables the storage, update and rapid retrieval of genomic annotations from the convenience of a relational database system. Range-based annotations of 1 million variants are retrieved in under a minute, making this approach feasible for whole-genome annotation tasks. Database URL: https://github.com/bushlab/mynclist.

Automated update, revision, and quality control of the maize genome annotations using MAKER-P improves the B73 RefGen_v3 gene models and identifies new genes.

PubMed

Law, MeiYee; Childs, Kevin L; Campbell, Michael S; Stein, Joshua C; Olson, Andrew J; Holt, Carson; Panchy, Nicholas; Lei, Jikai; Jiao, Dian; Andorf, Carson M; Lawrence, Carolyn J; Ware, Doreen; Shiu, Shin-Han; Sun, Yanni; Jiang, Ning; Yandell, Mark

2015-01-01

The large size and relative complexity of many plant genomes make creation, quality control, and dissemination of high-quality gene structure annotations challenging. In response, we have developed MAKER-P, a fast and easy-to-use genome annotation engine for plants. Here, we report the use of MAKER-P to update and revise the maize (Zea mays) B73 RefGen_v3 annotation build (5b+) in less than 3 h using the iPlant Cyberinfrastructure. MAKER-P identified and annotated 4,466 additional, well-supported protein-coding genes not present in the 5b+ annotation build, added additional untranslated regions to 1,393 5b+ gene models, identified 2,647 5b+ gene models that lack any supporting evidence (despite the use of large and diverse evidence data sets), identified 104,215 pseudogene fragments, and created an additional 2,522 noncoding gene annotations. We also describe a method for de novo training of MAKER-P for the annotation of newly sequenced grass genomes. Collectively, these results lead to the 6a maize genome annotation and demonstrate the utility of MAKER-P for rapid annotation, management, and quality control of grasses and other difficult-to-annotate plant genomes. © 2015 American Society of Plant Biologists. All Rights Reserved.