A score system for quality evaluation of RNA sequence tags: an improvement for gene expression profiling

Background: High-throughput molecular approaches for gene expression profiling, such as Serial Analysis of Gene Expression (SAGE), Massively Parallel Signature Sequencing (MPSS) or Sequencing-by-Synthesis (SBS) represent powerful techniques that provide global transcription profiles of different cell types through sequencing of short fragments of transcripts, denominated sequence tags. These techniques have improved our understanding about the relationships between these expression profiles and cellular phenotypes. Despite this, more reliable datasets are still necessary. In this work, we present a web-based tool named S3T: Score System for Sequence Tags, to index sequenced tags in accordance with their reliability. This is made through a series of evaluations based on a defined rule set. S3T allows the identification/selection of tags, considered more reliable for further gene expression analysis. Results: This methodology was applied to a public SAGE dataset. In order to compare data before and after filtering, a hierarchical clustering analysis was performed in samples from the same type of tissue, in distinct biological conditions, using these two datasets. Our results provide evidences suggesting that it is possible to find more congruous clusters after using S3T scoring system. Conclusion: These results substantiate the proposed application to generate more reliable data. This is a significant contribution for determination of global gene expression profiles. The library analysis with S3T is freely available at http://gdm.fmrp.usp.br/s3t/.S3T source code and datasets can also be downloaded from the aforementioned website.

Evaluation of the chicken transcriptome by SAGE of B cells and the DT40 cell line

Background: The understanding of whole genome sequences in higher eukaryotes depends to a large degree on the reliable definition of transcription units including exon/intron structures, translated open reading frames (ORFs) and flanking untranslated regions. The best currently available chicken transcript catalog is the Ensembl build based on the mappings of a relatively small number of full length cDNAs and ESTs to the genome as well as genome sequence derived in silico gene predictions.Results: We use Long Serial Analysis of Gene Expression (LongSAGE) in bursal lymphocytes and the DT40 cell line to verify the quality and completeness of the annotated transcripts. 53.6% of the more than 38,000 unique SAGE tags (unitags) match to full length bursal cDNAs, the Ensembl transcript build or the genome sequence. The majority of all matching unitags show single matches to the genome, but no matches to the genome derived Ensembl transcript build. Nevertheless, most of these tags map close to the 3' boundaries of annotated Ensembl transcripts.Conclusions: These results suggests that rather few genes are missing in the current Ensembl chicken transcript build, but that the 3' ends of many transcripts may not have been accurately predicted. The tags with no match in the transcript sequences can now be used to improve gene predictions, pinpoint the genomic location of entirely missed transcripts and optimize the accuracy of gene finder software.

Differential Gene Expression between Fall- and Spring-Run Chinook Salmon Assessed by Long Serial Analysis of Gene Expression

Of all Pacific salmonids, Chinook salmon Oncorhynchus tshawytscha display the greatest variability in return times to freshwater. The molecular mechanisms of these differential return times have not been well described. Current methods, such as long serial analysis of gene expression (LongSAGE) and microarrays, allow gene expression to be analyzed for thousands of genes simultaneously. To investigate whether differential gene expression is observed between fall- and spring-run Chinook salmon from California's Central Valley, LongSAGE libraries were constructed. Three libraries containing between 25,512 and 29,372 sequenced tags (21 base pairs/tag) were generated using messenger RNA from the brains of adult Chinook salmon returning in fall and spring and from one ocean-caught Chinook salmon. Tags were annotated to genes using complementary DNA libraries from Atlantic salmon Salmo salar and rainbow trout O. mykiss. Differentially expressed genes, as estimated by differences in the number of sequence tags, were found in all pairwise comparisons of libraries (freshwater versus saltwater = 40 genes; fall versus spring = 11 genes: and spawning versus nonspawning = 51 genes). The gene for ependymin, an extracellular glycoprotein involved in behavioral plasticity in fish, exhibited the most differential expression among the three groupings. Reverse transcription polymerase chain reaction analysis verified the differential expression of ependymin between the fall- and spring-run samples. These LongSAGE libraries, the first reported for Chinook salmon, provide a window of the transcriptional changes during Chinook salmon return migration to freshwater and spawning and increase the amount of expressed sequence data.