phorest: a web-based tool for comparative analyses of expressed sequence tag data

Comparative analysis of expressed sequence tags is becoming an important tool in molecular ecology for comparing gene expression in organisms grown in certain environments. Additionally, expressed sequence tag database information can be used for the construction of DNA microarrays and for the detection of single nucleotide polymorphisms. For such applications, we present PHOREST, a web-based tool for managing, analysing and comparing various collections of expressed sequence tags. It is written in PHP (PHP: Hypertext Preprocessor) and runs on UNIX, Microsoft Windows and Macintosh (Mac OS X) platforms

A computational-based update on microRNAs and their targets in barley (Hordeum vulgare L.)

<p>Abstract</p> <p>Background</p> <p>Many plant species have been investigated in the last years for the identification and characterization of the corresponding miRNAs, nevertheless extensive studies are not yet available on barley (at the time of this writing). To extend and to update information on miRNAs and their targets in barley and to identify candidate polymorphisms at miRNA target sites, the features of previously known plant miRNAs have been used to systematically search for barley miRNA homologues and targets in the publicly available ESTs database. Matching sequences have then been related to Unigene clusters on which most of this study was based.</p> <p>Results</p> <p>One hundred-fifty-six microRNA mature sequences belonging to 50 miRNA families have been found to significantly match at least one EST sequence in barley. As expected on the basis of phylogenetic relations, miRNAs putatively orthologous to those of <it>Triticum </it>are significantly over-represented inside the set of identified barley microRNA mature sequences. Many previously known and several putatively new miRNA/target pairs have been identified. When the predicted microRNA targets were grouped into functional categories, biological processes previously known to be regulated by miRNAs, such as development and response to biotic and abiotic stress, have been highlighted and most of the target molecular functions were related to transcription regulation. Candidate microRNA coding genes have been reported and genetic variation (SNPs/indels) both in functional regions of putative miRNAs (mature sequence) and at miRNA target sites has been found.</p> <p>Conclusions</p> <p>This study has provided an update of the information on barley miRNAs and their targets representing a foundation for future studies. Many of previously known plant microRNAs have homologues in barley with expected important roles during development, nutrient deprivation, biotic and abiotic stress response and other important physiological processes. Putative polymorphisms at miRNA target sites have been identified and they can represent an interesting source for the identification of functional genetic variability.</p

In Vitro vs In Silico Detected SNPs for the Development of a Genotyping Array: What Can We Learn from a Non-Model Species?

Background: There is considerable interest in the high-throughput discovery and genotyping of single nucleotide polymorphisms (SNPs) to accelerate genetic mapping and enable association studies. This study provides an assessment of EST-derived and resequencing-derived SNP quality in maritime pine (Pinus pinaster Ait.), a conifer characterized by a huge genome size (~23.8 Gb/C). [br/] Methodology/Principal Findings: A 384-SNPs GoldenGate genotyping array was built from i/ 184 SNPs originally detected in a set of 40 re-sequenced candidate genes (in vitro SNPs), chosen on the basis of functionality scores, presence of neighboring polymorphisms, minor allele frequencies and linkage disequilibrium and ii/ 200 SNPs screened from ESTs (in silico SNPs) selected based on the number of ESTs used for SNP detection, the SNP minor allele frequency and the quality of SNP flanking sequences. The global success rate of the assay was 66.9%, and a conversion rate (considering only polymorphic SNPs) of 51% was achieved. In vitro SNPs showed significantly higher genotyping-success and conversion rates than in silico SNPs (+11.5% and +18.5%, respectively). The reproducibility was 100%, and the genotyping error rate very low (0.54%, dropping down to 0.06% when removing four SNPs showing elevated error rates). [br/] Conclusions/Significance: This study demonstrates that ESTs provide a resource for SNP identification in non-model species, which do not require any additional bench work and little bio-informatics analysis. However, the time and cost benefits of in silico SNPs are counterbalanced by a lower conversion rate than in vitro SNPs. This drawback is acceptable for population-based experiments, but could be dramatic in experiments involving samples from narrow genetic backgrounds. In addition, we showed that both the visual inspection of genotyping clusters and the estimation of a per SNP error rate should help identify markers that are not suitable to the GoldenGate technology in species characterized by a large and complex genome

Generation of a reference transcriptome for evaluating rainbow trout responses to various stressors

<p>Abstract</p> <p>Background</p> <p>Fish under intensive culture conditions are exposed to a variety of acute and chronic stressors, including high rearing densities, sub-optimal water quality, and severe thermal fluctuations. Such stressors are inherent in aquaculture production and can induce physiological responses with adverse effects on traits important to producers and consumers, including those associated with growth, nutrition, reproduction, immune response, and fillet quality. Understanding and monitoring the biological mechanisms underlying stress responses will facilitate alleviating their negative effects through selective breeding and changes in management practices, resulting in improved animal welfare and production efficiency.</p> <p>Results</p> <p>Physiological responses to five treatments associated with stress were characterized by measuring plasma lysozyme activity, glucose, lactate, chloride, and cortisol concentrations, in addition to stress-associated transcripts by quantitative PCR. Results indicate that the fish had significant stressor-specific changes in their physiological conditions. Sequencing of a pooled normalized transcriptome library created from gill, brain, liver, spleen, kidney and muscle RNA of control and stressed fish produced 3,160,306 expressed sequence tags which were assembled and annotated. SNP discovery resulted in identification of ~58,000 putative single nucleotide polymorphisms including 24,479 which were predicted to fall within exons. Of these, 4907 were predicted to occupy the first position of a codon and 4110 the second, increasing the probability to impact amino acid sequence variation and potentially gene function.</p> <p>Conclusion</p> <p>We have generated and characterized a reference transcriptome for rainbow trout that represents multiple tissues responding to multiple stressors common to aquaculture production environments. This resource compliments existing public transcriptome data and will facilitate approaches aiming to evaluate gene expression associated with stress in this species.</p

Mining SNPs From EST Databases

There is considerable interest in the discovery and characterization of single nucleotide polymorphisms (SNPs) to enable the analysis of the potential relationships between human genotype and phenotype. Here we present a strategy that permits the rapid discovery of SNPs from publicly available expressed sequence tag (EST) databases. From a set of ESTs derived from 19 different cDNA libraries, we assembled 300,000 distinct sequences and identified 850 mismatches from contiguous EST data sets (candidate SNP sites), without de novo sequencing. Through a polymerase-mediated, single-base, primer extension technique, Genetic Bit Analysis (GBA), we confirmed the presence of a subset of these candidate SNP sites and have estimated the allele frequencies in three human populations with different ethnic origins. Altogether, our approach provides a basis for rapid and efficient regional and genome-wide SNP discovery using data assembled from sequences from different libraries of cDNAs. [The SNPs identified in this study can be found in the National Center of Biotechnology (NCBI) SNP database under submitter handles ORCHID (SNPS-981210-A) and debnick (SNPS-981209-A and SNPS-981209-B).