Annotated Gene Sequences Research Articles

Whole genome analysis for plant growth promotion profiling of Pantoea agglomerans CPHN2, a non-rhizobial nodule endophyte.

Reduced agricultural production as well as issues like nutrient-depleted soils, eutrophication, and groundwater contamination have drawn attention to the use of endophyte-based bioformulations to restore soil fertility. Pantoea agglomerans CPHN2, a non-rhizobial nodule endophyte isolated from Cicer arietinum, exhibited a variety of plant growth-promoting traits. In this study, we used NextSeq500 technology to analyze whole-genome sequence information of this plant growth-promoting endophytic bacteria. The genome of P. agglomerans CPHN2 has a length of 4,839,532 bp and a G + C content of 55.2%. The whole genome comprises three different genomic fractions, comprising one circular chromosome and two circular plasmids. A comparative analysis between P. agglomerans CPHN2 and 10 genetically similar strains was performed using a bacterial pan-genome pipeline. All the predicted and annotated gene sequences for plant growth promotions (PGPs), such as phosphate solubilization, siderophore synthesis, nitrogen metabolism, and indole-3-acetic acid (IAA) of P. agglomerans CPHN2, were identified. The whole-genome analysis of P. agglomerans CPHN2 provides an insight into the mechanisms underlying PGP by endophytes and its potential applications as a biofertilizer.

FAWMine: An integrated database and analysis platform for fall armyworm genomics.

Fall armyworm (Spodoptera frugiperda), a native insect species in the Americas, is rapidly becoming a major agricultural pest worldwide and is causing great damage to corn, rice, soybeans, and other crops. To control this pest, scientists have accumulated a great deal of high-throughput data of fall armyworm, and nine versions of its genomes and transcriptomes have been published. However, easily accessing and performing integrated analysis of these omics data sets is challenging. Here, we developed the Fall Armyworm Genome Database (FAWMine, http://159.226.67.243:8080/fawmine/) to maintain genome sequences, structural and functional annotations, transcriptomes, co-expression, protein interactions, homologs, pathways, and single-nucleotide variations. FAWMine provides a powerful framework that helps users to perform flexible and customized searching, present integrated data sets using diverse visualization methods, output results tables in a range of file formats, analyze candidate gene lists using multiple widgets, and query data available in other InterMine systems. Additionally, stand-alone JBrowse and BLAST services are also established, allowing the users to visualize RNA-Seq data and search genome and annotated gene sequences. Altogether, FAWMine is a useful tool for querying, visualizing, and analyzing compiled data sets rapidly and efficiently. FAWMine will be continually updated to function as a community resource for fall armyworm genomics and pest control research.

Goat Genomic Resources: The Search for Genes Associated with Its Economic Traits.

Goat plays a crucial role in human livelihoods, being a major source of meat, milk, fiber, and hides, particularly under adverse climatic conditions. The goat genomics related to the candidate gene approach is now being used to recognize molecular mechanisms that have different expressions of growth, reproductive, milk, wool, and disease resistance. The appropriate literature on this topic has been reviewed in this article. Several genetic characterization attempts of different goats have reported the existence of genotypic and morphological variations between different goat populations. As a result, different whole-genome sequences along with annotated gene sequences, gene function, and other genomic information of different goats are available in different databases. The main objective of this review is to search the genes associated with economic traits in goats. More than 271 candidate genes have been discovered in goats. Candidate genes influence the physiological pathway, metabolism, and expression of phenotypes. These genes have different functions on economically important traits. Some genes have pleiotropic effect for expression of phenotypic traits. Hence, recognizing candidate genes and their mutations that cause variations in gene expression and phenotype of an economic trait can help breeders look for genetic markers for specific economic traits. The availability of reference whole-genome assembly of goats, annotated genes, and transcriptomics makes comparative genomics a useful tool for systemic genetic upgradation. Identification and characterization of trait-associated sequence variations and gene will provide powerful means to give positive influences for future goat breeding program.

Environmental metagenome classification for constructing a microbiome fingerprint

BackgroundNowadays, not only are single genomes commonly analyzed, but also metagenomes, which are sets of, DNA fragments (reads) derived from microbes living in a given environment. Metagenome analysis is aimed at extracting crucial information on the organisms that have left their traces in an investigated environmental sample.In this study we focus on the MetaSUB Forensics Challenge (organized within the CAMDA 2018 conference) which consists in predicting the geographical origin of metagenomic samples. Contrary to the existing methods for environmental classification that are based on taxonomic or functional classification, we rely on the similarity between a sample and the reference database computed at a reads level.ResultsWe report the results of our extensive experimental study to investigate the behavior of our method and its sensitivity to different parameters. In our tests, we have followed the protocol of the MetaSUB Challenge, which allowed us to compare the obtained results with the solutions based on taxonomic and functional classification.ConclusionsThe results reported in the paper indicate that our method is competitive with those based on taxonomic classification. Importantly, by measuring the similarity at the reads level, we avoid the necessity of using large databases with annotated gene sequences. Hence our main finding is that environmental classification of metagenomic data can be proceeded without using large databases required for taxonomic or functional classification.ReviewersThis article was reviewed by Eran Elhaik, Alexandra Bettina Graf, Chengsheng Zhu, and Andre Kahles.

Isolation and characterization of hypoxia inducible gene connective tissue growth factor (CTGF) in Labeo rohita.

The connective tissue growth factor gene plays important role in several biological processes and also responsive to hypoxia stress in fishes. The freshwater fish, Labeo rohita, highly cultured in Indian subcontinent for food, is reported as hypoxia sensitive but annotation and sequences of nuclear geneswere not available for this species so far in the public domain, except some transcripts. In this study, an attempt was made for isolation and annotation of the CTGF gene in L. rohita using information of zebrafish from the same family. The CTGF gene sequence was obtained by aligning assembled genome of L. rohita, (NCBI BioProject ID: PRJNA437789), with the CTGF protein of zebrafish. Eight overlapping sets of forward and reverse primers fromaligned regionwere designed for amplification of around 600bp long successive overlapping fragments of CTGF gene in L. rohita. Assembly and annotation of overlapping fragments confirmed a complete 2421bp long CTGF gene sequence with a full coding region that comprised of five exons between 308 and 1921 positions. This annotated CTGF gene sequence was submitted to GenBank (Acc. No. KY940466). Characterization of CTGF will be an initiative in identification of hypoxia response genes in L. rohita which may further help in understanding the mechanism of hypoxia tolerability in this species.

Comprehensive genomic analysis of a plant growth-promoting rhizobacterium Pantoea agglomerans strain P5

In this study, we provide a comparative genomic analysis of Pantoea agglomerans strain P5 and 10 closely related strains based on phylogenetic analyses. A next-generation shotgun strategy was implemented using the Illumina HiSeq 2500 technology followed by core- and pan-genome analysis. The genome of P. agglomerans strain P5 contains an assembly size of 5082485 bp with 55.4% G + C content. P. agglomerans consists of 2981 core and 3159 accessory genes for Coding DNA Sequences (CDSs) based on the pan-genome analysis. Strain P5 can be grouped closely with strains PG734 and 299 R using pan and core genes, respectively. All the predicted and annotated gene sequences were allocated to KEGG pathways. Accordingly, genes involved in plant growth-promoting (PGP) ability, including phosphate solubilization, IAA and siderophore production, acetoin and 2,3-butanediol synthesis and bacterial secretion, were assigned. This study provides an in-depth view of the PGP characteristics of strain P5, highlighting its potential use in agriculture as a biofertilizer.

Don't just dump your data and run: Authors should submit as much experimental information as possible when uploading sequence data.

If you have, in any way, been involved with genetic research over the past 10 years, then you have likely heard of the Sequence Read Archive (SRA), which is jointly housed at the National Center for Biotechnology (NCBI), the DNA Data Bank of Japan (DDBJ), and the European Bioinformatics Institute (EBI). And if you regularly work with genome or transcriptome sequence information, then you have probably extracted data from and/or deposited data into the SRA. For those who are unfamiliar with it, the SRA is an international public online archive for next‐generation sequencing (NGS) data, which was established about a decade ago under the guidance of the International Nucleotide Sequence Database Collaboration (INSDC) [1], [2]. Despite nearly being shut down in 2011 [3], it has grown at a staggering rate over the past 10 years. As of September 1, 2017, it housed over five quadrillion (1015) open‐access bases of NGS data, coming from thousands of different species and spanning the entire gamut of cellular and viral life. It contains DNA‐ and RNA‐sequencing (DNA‐seq and RNA‐seq) reads of every kind, from bisulfite‐seq to strand‐specific RNA‐seq to single‐cell DNA‐seq, and it accepts reads from every type of NGS platform, be it Illumina, Ion Torrent, or PacBio sequencing. In other words, the SRA is a crucial and central resource in the fast‐paced and increasingly important domain of contemporary genetic research. > … the SRA is a crucial and central resource in the fast‐paced and increasingly important domain of contemporary genetic research. ### The Sequence Read Archive The SRA can be easily accessed and searched via the NCBI (https://www.ncbi.nlm.nih.gov/sra), DDBJ (http://trace.ddbj.nig.ac.jp/dra/index_e.html), and EBI (http://www.ebi.ac.uk/ena/submit/read-submission) websites. Once there, you will find yourself at a sequencing‐read superstore. With a decent Wi‐Fi connection, a couple of keyword searches, and a few clicks of the trackpad, you can quickly …

Whole genome analysis of halotolerant and alkalotolerant plant growth-promoting rhizobacterium Klebsiella sp. D5A

This research undertook the systematic analysis of the Klebsiella sp. D5A genome and identification of genes that contribute to plant growth-promoting (PGP) traits, especially genes related to salt tolerance and wide pH adaptability. The genome sequence of isolate D5A was obtained using an Illumina HiSeq 2000 sequencing system with average coverages of 174.7× and 200.1× using the paired-end and mate-pair sequencing, respectively. Predicted and annotated gene sequences were analyzed for similarity with the Kyoto Encyclopedia of Genes and Genomes (KEGG) enzyme database followed by assignment of each gene into the KEGG pathway charts. The results show that the Klebsiella sp. D5A genome has a total of 5,540,009 bp with 57.15% G + C content. PGP conferring genes such as indole-3-acetic acid (IAA) biosynthesis, phosphate solubilization, siderophore production, acetoin and 2,3-butanediol synthesis, and N2 fixation were determined. Moreover, genes putatively responsible for resistance to high salinity including glycine-betaine synthesis, trehalose synthesis and a number of osmoregulation receptors and transport systems were also observed in the D5A genome together with numerous genes that contribute to pH homeostasis. These genes reveal the genetic adaptation of D5A to versatile environmental conditions and the effectiveness of the isolate to serve as a plant growth stimulator.

Isolation and identification of Ralstonia mannitolilytica strains from a patient with septicaemia and analysis of their drug resistance genes

Objective To isolate and identify the pathogenic bacteria from peripheral blood of a patient with septicemia of unknown etiology and to analyze their drug resistance genes. Methods Two peripheral blood samples were collected from the patient after having fever. Several assays including culturing bacteria on blood agar plates by using streaking technique, Gram-staining of bacterial colonies and microscopic observation, VITEK 2-compact automatic bacterium detection and analysis system as well as a sequencing analysis of the 16s rRNA gene were performed to identify the bacterial pathogens in blood samples. Microdilution test was performed to detect the drug susceptibilities of isolated bacteria to antibiotics. Confirmatory tests were performed to detect the production of β-lactamase and extended spectrum β-lactamase by the isolated strains and the phenotypes of AmpC enzyme and carbapenemase. PCR was used to identify the β-lactamase-encoding genes in the isolated strains by using the primers of 19 common β-lactamase-, AmpC enzyme- and carbapenemase-encoding genes in Enterobacteriaceae strains and the primers of 21 annotated gene sequences encoding the β-lactamase of a Ralstonia mannitolilytica strain. The PCR products were sequenced and analyzed after T-A cloning. Results Ralstonia mannitolilytica strains were isolated from the two peripheral blood samples. The isolated strains were sensitive to ceftriaxone, cefepime, ciprofloxacin, ofloxacin, tigecycline and compound sulfamethoxazole (SMZ-TMP), but resistant to the other 11 tested antibiotics. Results of PCR amplification by using the primers of common genes encoding β-lactamase of Enterobacteriaceae strains were all negative. Fragments of genes encoding the β-lactamase of the isolated Ralstonia mannitolilytica strain were successfully amplified, which were TK49_09850, TK49_12955, TK49_14470, TK49_14495 and TK49_18990. The sequences of the amplified gene fragments were not similar to those of the common β-lactamase-encoding genes in Enterobacteriaceae strains. Conclusion The patient was infected with Ralstonia mannitolilytica. The isolated Ralstonia mannitolilytica strain showed a high-level drug resistance with a noticeable diversity against different β-lactam antibiotics. The genes encoding β-lactamase of the isolated Ralstonia mannitolilytica strain were completely different to those of Enterobacteriaceae strains. Key words: Ralstonia mannitolilytica; Septicaemia; Isolation and identification; Drug resistance; β-lactamase-encoding gene

First insights into the large genome of Epimedium sagittatum (Sieb. et Zucc) Maxim, a Chinese Ttaditional medicinal plant.

Epimedium sagittatum (Sieb. et Zucc) Maxim is a member of the Berberidaceae family of basal eudicot plants, widely distributed and used as a traditional medicinal plant in China for therapeutic effects on many diseases with a long history. Recent data shows that E. sagittatum has a relatively large genome, with a haploid genome size of ~4496 Mbp, divided into a small number of only 12 diploid chromosomes (2n = 2x = 12). However, little is known about Epimedium genome structure and composition. Here we present the analysis of 691 kb of high-quality genomic sequence derived from 672 randomly selected plasmid clones of E. sagittatum genomic DNA, representing ~0.0154% of the genome. The sampled sequences comprised at least 78.41% repetitive DNA elements and 2.51% confirmed annotated gene sequences, with a total GC% content of 39%. Retrotransposons represented the major class of transposable element (TE) repeats identified (65.37% of all TE repeats), particularly LTR (Long Terminal Repeat) retrotransposons (52.27% of all TE repeats). Chromosome analysis and Fluorescence in situ Hybridization of Gypsy-Ty3 retrotransposons were performed to survey the E. sagittatum genome at the cytological level. Our data provide the first insights into the composition and structure of the E. sagittatum genome, and will facilitate the functional genomic analysis of this valuable medicinal plant.

PlantRNA, a database for tRNAs of photosynthetic eukaryotes.

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.

De novo sequence assembly and characterisation of a partial transcriptome for an evolutionarily distinct reptile, the tuatara (Sphenodon punctatus)

BackgroundThe tuatara (Sphenodon punctatus) is a species of extraordinary zoological interest, being the only surviving member of an entire order of reptiles which diverged early in amniote evolution. In addition to their unique phylogenetic placement, many aspects of tuatara biology, including temperature-dependent sex determination, cold adaptation and extreme longevity have the potential to inform studies of genome evolution and development. Despite increasing interest in the tuatara genome, genomic resources for the species are still very limited. We aimed to address this by assembling a transcriptome for tuatara from an early-stage embryo, which will provide a resource for genome annotation, molecular marker development and studies of development and adaptation in tuatara.ResultsWe obtained 30 million paired-end 50 bp reads from an Illumina Genome Analyzer and assembled them with Velvet and Oases using a range of kmers. After removing redundancy and filtering out low quality transcripts, our transcriptome dataset contained 32911 transcripts, with an N50 of 675 and a mean length of 451 bp. Almost 50% (15965) of these transcripts could be annotated by comparison with the NCBI non-redundant (NR) protein database or the chicken, green anole and zebrafish UniGene sets. A scan of candidate genes and repetitive elements revealed genes involved in immune function, sex differentiation and temperature-sensitivity, as well as over 200 microsatellite markers.ConclusionsThis dataset represents a major increase in genomic resources for the tuatara, increasing the number of annotated gene sequences from just 60 to almost 16,000. This will facilitate future research in sex determination, genome evolution, local adaptation and population genetics of tuatara, as well as inform studies on amniote evolution.

Computational inference of grammars for larger-than-gene structures from annotated gene sequences

Larger than gene structures (LGS) are DNA segments that include at least one gene and often other segments such as inverted repeats and gene promoters. Mobile genetic elements (MGE) such as integrons are LGS that play an important role in horizontal gene transfer, primarily in Gram-negative organisms. Known LGS have a profound effect on organism virulence, antibiotic resistance and other properties of the organism due to the number of genes involved. Expert-compiled grammars have been shown to be an effective computational representation of LGS, well suited to automating annotation, and supporting de novo gene discovery. However, development of LGS grammars by experts is labour intensive and restricted to known LGS. This study uses computational grammar inference methods to automate LGS discovery. We compare the ability of six algorithms to infer LGS grammars from DNA sequences annotated with genes and other short sequences. We compared the predictive power of learned grammars against an expert-developed grammar for gene cassette arrays found in Class 1, 2 and 3 integrons, which are modular LGS containing up to 9 of about 240 cassette types. Using a Bayesian generalization algorithm our inferred grammar was able to predict > 95% of MGE structures in a corpus of 1760 sequences obtained from Genbank (F-score 75%). Even with 100% noise added to the training and test sets, we obtained an F-score of 68%, indicating that the method is robust and has the potential to predict de novo LGS structures when the underlying gene features are known. http://www2.chi.unsw.edu.au/attacca.

Modularity and Distribution of Sulfur Metabolism Genes in Bacterial Populations: Search and Design

Biological Engineering involves global DNA sampling and modular design from genetic parts. A new approach reflected by natural history is based on the recognition of interchangeable DNA fragments that move around the world due to horizontal gene transfer. According to the large scale, metagenomics provide opportunities to sequence whole genomes within environmental populations. Annotated gene sequences, protein structures, and metabolic data can be used to design small biosystems from interchangeable genetic parts, the same as from functional modules. To illustrate this, the 21 genes for sulfur metabolism were inferred from the genome of bacterium Vesicomyosocius okutanii HA, and the distribution of two gene clusters (dissimilatory sulfite reductase - dsr and sulfur-oxidation - sox) within environmental samples was investigated. The correlation between the dsr and sox clusters for the experimental set of 41 stations was R = 0.86 which demonstrates the complementarity of dsr and sox metabolic pathways in environmental populations. Hypothetical functions were assigned using comparisons with known proteins. The 18 reads from symbionts of gutless worm Olavius algarvensis showed a high identity to large AprA protein from V.okutanii. In addition, comparative 3D modeling of hypothetical DsrB protein revealed sulfite reductase ferredoxin-like half domain, sulfite reductase 4Fe-4S domain, and a repressor of phase-1 flagellin. The simplistic reconstruction of sulfur metabolism from parts and examples of hierarchical modularity in nature are given. The origin of modularity is considered in the context of minimal cell and horizontal gene transfer. The role of ancient sulphur metabolism in modularization is discussed under the umbrella of iron-sulfur world theory (Wachtershauser, 1988), deep-hot biosphere model (Gold, 1992), and radiolysis hypothesis (Garzon and Garzon, 2001). The reverse engineering approach based on natural genetic modules is proposed for understanding early life.

The coding potential of the human genome: global compositional properties identify with statistical significance a plethora of new potential coding regions

Bioinformatics predictions of coding sequences rely on details models of compositional properties of genes. Such models are based on large, genome-specific training sets of known genes. Although these models are optimal for the identification of 'average' genes, they may be over-parameterized to allow recognition of genes of anomalous properties, for example genes coding for very short peptides. We have developed two approaches to the identification of coding sequences that rely on more general compositional principles that we expect to be conserved over a wider variety of genes. The first approach is based on the observation that coding regions generally exhibit contrasting global compositional properties in the three codon positions, depending on the overall base composition of the sequence. For example, sequences rich in C and G bases have a much higher GC content in third codon position and a relatively low GC content in second codon position. General rules on the base content at the three codon positions as a function of the overall base content can be identified and exploited to score sequence regions for their coding potential. More generally, the period-three structure of coding regions imposes compositional periodicity to the sequence that, irrespective of the specific type of contrasts that we might expect to see, result in a significantly non-random distribution of bases. Applying these principles, we have devised two algorithms to detect potential coding regions in sequences of any composition, one based on overall compositional expectations and one based on overall contrasts. We have applied our procedure to the human genome. To our surprise, we have detected a plethora of regions, not overlapping with any of the currently annotated gene sequences, that display with high statistical significance a periodic structure often conforming to expectations for coding regions in terms of base-type composition. The frequency of these regions is far greater than the random frequency observed in corresponding scrambled sequences. Most of these regions also show levels of complexity that distinguish them from repetitive elements and that are consistent with the complexity of known genes. Our bioinformatics results provide a rich source of information for future experimental analyses and the potential for exciting new discoveries.

Hydrogen and Nickel Metabolism inHelicobacterSpecies

Anaerobic microorganisms (such as clostridia) present in the large intestine of animals generate molecular hydrogen (H(2)) by fermentation using "H(2)-evolving" hydrogenases. The gas can also be detected in other tissues in mice, including the stomach, liver, spleen, or small intestine. It is established that this available H(2) can in turn be used as a source of energy by some pathogenic bacteria, including Helicobacter species like H. pylori and H. hepaticus. Both species possess one hydrogenase, which has been studied for H(2) oxidation characteristics and for its role in conferring animal colonization. On the basis of available annotated gene sequences, other Helicobacter species also appear to have one well-conserved respiratory, membrane-bound, nickel-iron-containing [NiFe] hydrogenase. Although H. pylori has been well-studied, many other (poorly studied) Helicobacter species likely represent a spectrum of emerging pathogens. The important role of hydrogenases in Helicobacter species is discussed, and the hydrogenases, their maturation/accessory factors, their regulation, as well as nickel transport and metabolism among the different species are compared.

Use of molecular hydrogen as an energy substrate by human pathogenic bacteria

Molecular hydrogen is produced as a fermentation by-product in the large intestine of animals and its production can be correlated with the digestibility of the carbohydrates consumed. Pathogenic Helicobacter species (Helicobacter pylori and H. hepaticus) have the ability to use H(2) through a respiratory hydrogenase, and it was demonstrated that the gas is present in the tissues colonized by these pathogens (the stomach and the liver respectively of live animals). Mutant strains of H. pylori unable to use H(2) are deficient in colonizing mice compared with the parent strain. On the basis of available annotated gene sequence information, the enteric pathogen Salmonella, like other enteric bacteria, contains three putative membrane-associated H(2)-using hydrogenase enzymes. From the analysis of gene-targeted mutants it is concluded that each of the three membrane-bound hydrogenases of Salmonella enterica serovar Typhimurium are coupled with an H(2)-oxidizing respiratory pathway. From microelectrode probe measurements on live mice, H(2) could be detected at approx. 50 muM levels within the tissues (liver and spleen), which are colonized by Salmonella. The half-saturation affinity of whole cells of these pathogens for H(2) is much less than this, so it is expected that the (H(2)-utilizing) hydrogenase enzymes be saturated with the reducing substrate in vivo. All three enteric NiFe hydrogenase enzymes contribute to virulence of the bacterium in a typhoid fever-mouse model, and the combined removal of all three hydrogenases resulted in a strain that is avirulent and (in contrast with the parent strain) one that is not able to pass the intestinal tract to invade liver or spleen tissue. It is proposed that H(2) utilization and specifically its oxidation, coupled with a respiratory pathway, is required for energy production to permit growth and maintain efficient virulence of a number of pathogenic bacteria during infection of animals. These would be expected to include the Campylobacter jejuni, a bacterium closely related to Helicobacter, as well as many enteric bacteria (Escherichia coli, Shigella and Yersinia species).

PolyMAPr: Programs for polymorphism database mining, annotation, and functional analysis

Pharmacogenomic and disease-association studies rely on identifying a comprehensive set of polymorphisms within candidate genes. Public SNP databases are a rich source of polymorphism data, but mining them effectively requires overcoming at least four challenges: ensuring accurate annotations for genes and polymorphisms, eliminating both inter- and intra-database redundancy, integrating data from multiple public sources with data generated locally, and prioritizing the variants for further study. PolyMAPr (Polymorphism Mining and Annotation Programs)' was developed to overcome these challenges and to improve the efficiency of database mining and polymorphism annotation. PolyMAPr takes as input a file containing a list of genes to be processed and files containing each annotated gene sequence. Polymorphic sequences obtained from public databases (dbSNP, CGAP, and JSNP) or through local SNP discovery efforts, as well as oligonucleotide sequences (e.g., PCR primers), are mapped to the annotated gene sequences and named according to suggested nomenclature guidelines. The functional effects of nonsynonymous coding-region SNPs (cSNPs) and any variants that might alter exon splicing enhancer (ESE) sites, putative transcription factor binding sites, or intron-exon splice sites are predicted. The output files are accessible though a browser interface. In addition, the results are also provided in Extensible Markup Language (XML) format to facilitate uploading them into a local relational database. PolyMAPr increases the efficiency of mining public databases for genetic variants within candidate genes and provides a mechanism by which data from multiple sources (both public and private) can be uniformly integrated, thereby significantly reducing the effort required to obtain a comprehensive set of polymorphisms for pharmacogenomic and disease-association studies. PolyMAPr can be obtained from http://pharmacogenomics.wustl.edu.

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.

Respiratory Hydrogen Use by Salmonella enterica Serovar Typhimurium Is Essential for Virulence

Based on available annotated gene sequence information, the enteric pathogen salmonella, like other enteric bacteria, contains three putative membrane-associated H2-using hydrogenase enzymes. These enzymes split molecular H2, releasing low-potential electrons that are used to reduce quinone or heme-containing components of the respiratory chain. Here we show that each of the three distinct membrane-associated hydrogenases of Salmonella enterica serovar Typhimurium is coupled to a respiratory pathway that uses oxygen as the terminal electron acceptor. Cells grown in a blood-based medium expressed four times the amount of hydrogenase (H2 oxidation) activity that cells grown on Luria Bertani medium did. Cells suspended in phosphate-buffered saline consumed 2 mol of H2 per mol of O2 used in the H2-O2 respiratory pathway, and the activity was inhibited by the respiration inhibitor cyanide. Molecular hydrogen levels averaging over 40 microM were measured in organs (i.e., livers and spleens) of live mice, and levels within the intestinal tract (the presumed origin of the gas) were four times greater than this. The half-saturation affinity of S. enterica serovar Typhimurium for H2 is only 2.1 microM, so it is expected that H2-utilizing hydrogenase enzymes are saturated with the reducing substrate in vivo. All three hydrogenase enzymes contribute to the virulence of the bacterium in a typhoid fever-mouse model, based on results from strains with mutations in each of the three hydrogenase genes. The introduced mutations are nonpolar, and growth of the mutant strains was like that of the parent strain. The combined removal of all three hydrogenases resulted in a strain that is avirulent and (in contrast to the parent strain) one that is unable to invade liver or spleen tissue. The introduction of one of the hydrogenase genes into the triple mutant strain on a low-copy-number plasmid resulted in a strain that was able to both oxidize H2 and cause morbidity in mice within 11 days of inoculation; therefore, the avirulent phenotype of the triple mutant is not due to an unknown spurious mutation. We conclude that H2 utilization in a respiratory fashion is required for energy production to permit salmonella growth and subsequent virulence during infection.