CleanEST: a database of cleansed EST libraries

The EST division of GenBank, dbEST, is widely used in many applications such as gene discovery and verification of exon–intron structure. However, the use of EST sequences in the dbEST libraries is often hampered by inconsistent terminology used to describe the library sources and by the presence of contaminated sequences. Here, we describe CleanEST, a novel database server that classified dbEST libraries and removes contaminants. We classified all dbEST libraries according to species and sequencing center. In addition, we further classified human EST libraries by anatomical and pathological systems according to eVOC ontologies. For each dbEST library, we provide two different cleansed sequences: ‘pre-cleansed’ and ‘user-cleansed’. To generate pre-cleansed sequences, we cleansed sequences in dbEST by alignment of EST sequences against well-known contamination sources: UniVec, Escherichia coli, mitochondria and chloroplast (for plant). To provide user-cleansed sequences, we built an automatic user-cleansing pipeline, in which sequences of a user-selected library are cleansed on-the-fly according to user-selected options. The server is available at http://cleanest.kobic.re.kr/ and the database is updated monthly

The TIGR Gene Indices: clustering and assembling EST and known genes and integration with eukaryotic genomes

Although the list of completed genome sequencing projects has expanded rapidly, sequencing and analysis of expressed sequence tags (ESTs) remain a primary tool for discovery of novel genes in many eukaryotes and a key element in genome annotation. The TIGR Gene Indices (http://www.tigr.org/tdb/tgi) are a collection of 77 species-specific databases that use a highly refined protocol to analyze gene and EST sequences in an attempt to identify and characterize expressed transcripts and to present them on the Web in a user-friendly, consistent fashion. A Gene Index database is constructed for each selected organism by first clustering, then assembling EST and annotated cDNA and gene sequences from GenBank. This process produces a set of unique, high-fidelity virtual transcripts, or tentative consensus (TC) sequences. The TC sequences can be used to provide putative genes with functional annotation, to link the transcripts to genetic and physical maps, to provide links to orthologous and paralogous genes, and as a resource for comparative and functional genomic analysis

PLEXdb: gene expression resources for plants and plant pathogens

PLEXdb (http://www.plexdb.org), in partnership with community databases, supports comparisons of gene expression across multiple plant and pathogen species, promoting individuals and/or consortia to upload genome-scale data sets to contrast them to previously archived data. These analyses facilitate the interpretation of structure, function and regulation of genes in economically important plants. A list of Gene Atlas experiments highlights data sets that give responses across different developmental stages, conditions and tissues. Tools at PLEXdb allow users to perform complex analyses quickly and easily. The Model Genome Interrogator (MGI) tool supports mapping gene lists onto corresponding genes from model plant organisms, including rice and Arabidopsis. MGI predicts homologies, displays gene structures and supporting information for annotated genes and full-length cDNAs. The gene list-processing wizard guides users through PLEXdb functions for creating, analyzing, annotating and managing gene lists. Users can upload their own lists or create them from the output of PLEXdb tools, and then apply diverse higher level analyses, such as ANOVA and clustering. PLEXdb also provides methods for users to track how gene expression changes across many different experiments using the Gene OscilloScope. This tool can identify interesting expression patterns, such as up-regulation under diverse conditions or checking any gene’s suitability as a steady-state control

A whole-genome assembly of the domestic cow, Bos taurus

Background: The genome of the domestic cow, Bos taurus, was sequenced using a mixture of hierarchical and whole-genome shotgun sequencing methods. Results: We have assembled the 35 million sequence reads and applied a variety of assembly improvement techniques, creating an assembly of 2.86 billion base pairs that has multiple improvements over previous assemblies: it is more complete, covering more of the genome; thousands of gaps have been closed; many erroneous inversions, deletions, and translocations have been corrected; and thousands of single-nucleotide errors have been corrected. Our evaluation using independent metrics demonstrates that the resulting assembly is substantially more accurate and complete than alternative versions. Conclusions: By using independent mapping data and conserved synteny between the cow and human genomes, we were able to construct an assembly with excellent large-scale contiguity in which a large majority (approximately 91%) of the genome has been placed onto the 30 B. taurus chromosomes. We constructed a new cow-human synteny map that expands upon previous maps. We also identified for the first time a portion of the B. taurus Y chromosome. © 2009 Zimin et al.; licensee BioMed Central Ltd

Features generated for computational splice-site prediction correspond to functional elements

<p>Abstract</p> <p>Background</p> <p>Accurate selection of splice sites during the splicing of precursors to messenger RNA requires both relatively well-characterized signals at the splice sites and auxiliary signals in the adjacent exons and introns. We previously described a feature generation algorithm (FGA) that is capable of achieving high classification accuracy on human 3' splice sites. In this paper, we extend the splice-site prediction to 5' splice sites and explore the generated features for biologically meaningful splicing signals.</p> <p>Results</p> <p>We present examples from the observed features that correspond to known signals, both core signals (including the branch site and pyrimidine tract) and auxiliary signals (including GGG triplets and exon splicing enhancers). We present evidence that features identified by FGA include splicing signals not found by other methods.</p> <p>Conclusion</p> <p>Our generated features capture known biological signals in the expected sequence interval flanking splice sites. The method can be easily applied to other species and to similar classification problems, such as tissue-specific regulatory elements, polyadenylation sites, promoters, etc.</p

An efficient approach to finding Siraitia grosvenorii triterpene biosynthetic genes by RNA-seq and digital gene expression analysis

<p>Abstract</p> <p>Background</p> <p><it>Siraitia grosvenorii </it>(Luohanguo) is an herbaceous perennial plant native to southern China and most prevalent in Guilin city. Its fruit contains a sweet, fleshy, edible pulp that is widely used in traditional Chinese medicine. The major bioactive constituents in the fruit extract are the cucurbitane-type triterpene saponins known as mogrosides. Among them, mogroside V is nearly 300 times sweeter than sucrose. However, little is known about mogrosides biosynthesis in <it>S. grosvenorii</it>, especially the late steps of the pathway.</p> <p>Results</p> <p>In this study, a cDNA library generated from of equal amount of RNA taken from <it>S. grosvenorii </it>fruit at 50 days after flowering (DAF) and 70 DAF were sequenced using Illumina/Solexa platform. More than 48,755,516 high-quality reads from a cDNA library were generated that was assembled into 43,891 unigenes. De novo assembly and gap-filling generated 43,891 unigenes with an average sequence length of 668 base pairs. A total of 26,308 (59.9%) unique sequences were annotated and 11,476 of the unique sequences were assigned to specific metabolic pathways by the Kyoto Encyclopedia of Genes and Genomes. cDNA sequences for all of the known enzymes involved in mogrosides backbone synthesis were identified from our library. Additionally, a total of eighty-five cytochrome P450 (CYP450) and ninety UDP-glucosyltransferase (UDPG) unigenes were identified, some of which appear to encode enzymes responsible for the conversion of the mogroside backbone into the various mogrosides. Digital gene expression profile (DGE) analysis using Solexa sequencing was performed on three important stages of fruit development, and based on their expression pattern, seven <it>CYP450</it>s and five <it>UDPG</it>s were selected as the candidates most likely to be involved in mogrosides biosynthesis.</p> <p>Conclusion</p> <p>A combination of RNA-seq and DGE analysis based on the next generation sequencing technology was shown to be a powerful method for identifying candidate genes encoding enzymes responsible for the biosynthesis of novel secondary metabolites in a non-model plant. Seven <it>CYP450</it>s and five <it>UDPG</it>s were selected as potential candidates involved in mogrosides biosynthesis. The transcriptome data from this study provides an important resource for understanding the formation of major bioactive constituents in the fruit extract from <it>S. grosvenorii</it>.</p

SpiroESTdb: a transcriptome database and online tool for sparganum expressed sequences tags

<p>Abstract</p> <p>Background</p> <p>Sparganum (plerocercoid of <it>Spirometra erinacei</it>) is a parasite that possesses the remarkable ability to survive by successfully modifying its physiology and morphology to suit various hosts and can be found in various tissues, even the nervous system. However, surprisingly little is known about the molecular function of genes that are expressed during the course of the parasite life cycle. To begin to decipher the molecular processes underlying gene function, we constructed a database of expressed sequence tags (ESTs) generated from sparganum.</p> <p>Findings</p> <p>SpiroESTdb is a web-based information resource that is built upon the annotation and curation of 5,655 ESTs data. SpiroESTdb provides an integrated platform for expressed sequence data, expression dynamics, functional genes, genetic markers including single nucleotide polymorphisms and tandem repeats, gene ontology and KEGG pathway information. Moreover, SpiroESTdb supports easy access to gene pages, such as (i) curation and query forms, (ii) <it>in </it><it>silico </it>expression profiling and (iii) BLAST search tools. Comprehensive descriptions of the sparganum content of all sequenced data are available, including summary reports. The contents of SpiroESTdb can be viewed and downloaded from the web (<url>http://pathod.cdc.go.kr/spiroestdb</url>).</p> <p>Conclusions</p> <p>This integrative web-based database of sequence data, functional annotations and expression profiling data will serve as a useful tool to help understand and expand the characterization of parasitic infections. It can also be used to identify potential industrial drug targets and vaccine candidate genes.</p

Polysomal mRNA Association and Gene Expression in <i>Trypanosoma brucei</i>

Background: The contrasting physiological environments of Trypanosoma brucei procyclic (insect vector) and bloodstream (mammalian host) forms necessitates deployment of different molecular processes and, therefore, changes in protein expression. Transcriptional regulation is unusual in T. brucei because the arrangement of genes is polycistronic; however, genes which are transcribed together are subsequently cleaved into separate mRNAs by trans-splicing. Following pre-mRNA processing, the regulation of mature mRNA stability is a tightly controlled cellular process. While many stage-specific transcripts have been identified, previous studies using RNA-seq suggest that changes in overall transcript level do not necessarily reflect the abundance of the corresponding protein. Methods: To better understand the regulation of gene expression in T. brucei, we performed a bioinformatic analysis of RNA-seq on total, sub-polysomal, and polysomal mRNA samples. We further cross-referenced our dataset with a previously published proteomics dataset to identify new protein coding sequences. Results: Our analyses showed that several long non-coding RNAs are more abundant in the sub-polysome samples, which possibly implicates them in regulating cellular differentiation in T. brucei. We also improved the annotation of the T.brucei genome by identifying new putative protein coding transcripts that were confirmed by mass spectrometry data. Conclusions: Several long non-coding RNAs are more abundant in the sub-polysome cellular fractions and might pay a role in the regulation of gene expression. We hope that these data will be of wide general interest, as well as being of specific value to researchers studying gene regulation expression and life stage transitions in T. brucei

EasyCluster: a fast and efficient gene-oriented clustering tool for large-scale transcriptome data

<p>Abstract</p> <p>Background</p> <p>ESTs and full-length cDNAs represent an invaluable source of evidence for inferring reliable gene structures and discovering potential alternative splicing events. In newly sequenced genomes, these tasks may not be practicable owing to the lack of appropriate training sets. However, when expression data are available, they can be used to build EST clusters related to specific genomic transcribed <it>loci</it>. Common strategies recently employed to this end are based on sequence similarity between transcripts and can lead, in specific conditions, to inconsistent and erroneous clustering. In order to improve the cluster building and facilitate all downstream annotation analyses, we developed a simple genome-based methodology to generate gene-oriented clusters of ESTs when a genomic sequence and a pool of related expressed sequences are provided. Our procedure has been implemented in the software EasyCluster and takes into account the spliced nature of ESTs after an <it>ad hoc </it>genomic mapping.</p> <p>Methods</p> <p>EasyCluster uses the well-known GMAP program in order to perform a very quick EST-to-genome mapping in addition to the detection of reliable splice sites. Given a genomic sequence and a pool of ESTs/FL-cDNAs, EasyCluster starts building genomic and EST local databases and runs GMAP. Subsequently, it parses results creating an initial collection of pseudo-clusters by grouping ESTs according to the overlap of their genomic coordinates on the same strand. In the final step, EasyCluster refines the clustering by again running GMAP on each pseudo-cluster and groups together ESTs sharing at least one splice site.</p> <p>Results</p> <p>The higher accuracy of EasyCluster with respect to other clustering tools has been verified by means of a manually cured benchmark of human EST clusters. Additional datasets including the Unigene cluster Hs.122986 and ESTs related to the human <it>HOXA </it>gene family have also been used to demonstrate the better clustering capability of EasyCluster over current genome-based web service tools such as ASmodeler and BIPASS. EasyCluster has also been used to provide a first compilation of gene-oriented clusters in the <it>Ricinus communis </it>oilseed plant for which no Unigene clusters are yet available, as well as an evaluation of the alternative splicing in this plant species.</p

Fast splice site detection using information content and feature reduction

Background: Accurate identification of splice sites in DNA sequences plays a key role in the prediction of gene structure in eukaryotes. Already many computational methods have been proposed for the detection of splice sites and some of them showed high prediction accuracy. However, most of these methods are limited in terms of their long computation time when applied to whole genome sequence data. Results: In this paper we propose a hybrid algorithm which combines several effective and informative input features with the state of the art support vector machine (SVM). To obtain the input features we employ information content method based on Shannon\u27s information theory, Shapiro\u27s score scheme, and Markovian probabilities. We also use a feature elimination scheme to reduce the less informative features from the input data. Conclusion: In this study we propose a new feature based splice site detection method that shows improved acceptor and donor splice site detection in DNA sequences when the performance is compared with various state of the art and well known method