Identification of new genes in Sinorhizobium meliloti using the Genome Sequencer FLX system

<p>Abstract</p> <p>Background</p> <p><it>Sinorhizobium meliloti </it>is an agriculturally important model symbiont. There is an ongoing need to update and improve its genome annotation. In this study, we used a high-throughput pyrosequencing approach to sequence the transcriptome of <it>S. meliloti</it>, and search for new bacterial genes missed in the previous genome annotation. This is the first report of sequencing a bacterial transcriptome using the pyrosequencing technology.</p> <p>Results</p> <p>Our pilot sequencing run generated 19,005 reads with an average length of 136 nucleotides per read. From these data, we identified 20 new genes. These new gene transcripts were confirmed by RT-PCR and their possible functions were analyzed.</p> <p>Conclusion</p> <p>Our results indicate that high-throughput sequence analysis of bacterial transcriptomes is feasible and next-generation sequencing technologies will greatly facilitate the discovery of new genes and improve genome annotation.</p

Gene Expression and Isoform Variation Analysis using Affymetrix Exon Arrays

Correction to Bemmo A, Benovoy D, Kwan T, Gaffney DJ, Jensen RV, Majewski J: Gene expression and isoform variation analysis using Affymetrix Exon Arrays. BMC Genomics 2008, 9: 529

Transcriptome sequencing of the Microarray Quality Control (MAQC) RNA reference samples using next generation sequencing

<p>Abstract</p> <p>Background</p> <p>Transcriptome sequencing using next-generation sequencing platforms will soon be competing with DNA microarray technologies for global gene expression analysis. As a preliminary evaluation of these promising technologies, we performed deep sequencing of cDNA synthesized from the Microarray Quality Control (MAQC) reference RNA samples using Roche's 454 Genome Sequencer FLX.</p> <p>Results</p> <p>We generated more that 3.6 million sequence reads of average length 250 bp for the MAQC A and B samples and introduced a data analysis pipeline for translating cDNA read counts into gene expression levels. Using BLAST, 90% of the reads mapped to the human genome and 64% of the reads mapped to the RefSeq database of well annotated genes with e-values ≤ 10^-20. We measured gene expression levels in the A and B samples by counting the numbers of reads that mapped to individual RefSeq genes in multiple sequencing runs to evaluate the MAQC quality metrics for reproducibility, sensitivity, specificity, and accuracy and compared the results with DNA microarrays and Quantitative RT-PCR (QRTPCR) from the MAQC studies. In addition, 88% of the reads were successfully aligned directly to the human genome using the AceView alignment programs with an average 90% sequence similarity to identify 137,899 unique exon junctions, including 22,193 new exon junctions not yet contained in the RefSeq database.</p> <p>Conclusion</p> <p>Using the MAQC metrics for evaluating the performance of gene expression platforms, the ExpressSeq results for gene expression levels showed excellent reproducibility, sensitivity, and specificity that improved systematically with increasing shotgun sequencing depth, and quantitative accuracy that was comparable to DNA microarrays and QRTPCR. In addition, a careful mapping of the reads to the genome using the AceView alignment programs shed new light on the complexity of the human transcriptome including the discovery of thousands of new splice variants.</p

Drop-on-Demand Single Cell Isolation and Total RNA Analysis

Peer reviewe

Global Analysis of Gene Expression: Methods, Interpretation, and Pitfalls

Abstract Over the past 15 years, global analysis of mRNA expression has emerged as a powerful strategy for biological discovery. Using the power of parallel processing, robotics, and computer-based informatics, a number of high-throughput methods have been devised. These include DNA microarrays, serial analysis of gene expression, quantitative RT-PCR, differential-display RT-PCR, and massively parallel signature sequencing. Each of these methods has inherent advantages and disadvantages, often related to expense, technical difficulty, specificity, and reliability. Further, the ability to generate large data sets of gene expression has led to new challenges in bioinformatics. Nonetheless, this technological revolution is transforming disease classification, gene discovery, and our understanding of regulatory gene networks

The Reproducibility of Lists of Differentially Expressed Genes in Microarray Studies

Reproducibility is a fundamental requirement in scientific experiments and clinical contexts. Recent publications raise concerns about the reliability of microarray technology because of the apparent lack of agreement between lists of differentially expressed genes (DEGs). In this study we demonstrate that (1) such discordance may stem from ranking and selecting DEGs solely by statistical significance (P) derived from widely used simple t-tests; (2) when fold change (FC) is used as the ranking criterion, the lists become much more reproducible, especially when fewer genes are selected; and (3) the instability of short DEG lists based on P cutoffs is an expected mathematical consequence of the high variability of the t-values. We recommend the use of FC ranking plus a non-stringent P cutoff as a baseline practice in order to generate more reproducible DEG lists. The FC criterion enhances reproducibility while the P criterion balances sensitivity and specificity

Bio-psychosocial determinants of time lost from work following non life threatening acute orthopaedic trauma

<p>Abstract</p> <p>Background</p> <p>To determine factors predicting the duration of time away from work following acute orthopaedic non life threatening trauma</p> <p>Methods</p> <p>Prospective cohort study conducted at four hospitals in Victoria, Australia. The cohort comprised 168 patients aged 18-64 years who were working prior to the injury and sustained a range of acute unintentional orthopaedic injuries resulting in hospitalization. Baseline data was obtained by survey and medical record review. Multivariate Cox proportional hazards regression analysis was used to examine the association between potential predictors and the duration of time away from work during the six month study. The study achieved 89% follow-up.</p> <p>Results</p> <p>Of the 168 participants recruited to the study, 68% returned to work during the six month study. Multivariate Cox proportional hazards regression analysis identified that blue collar work, negative pain attitudes with respect to work, high initial pain intensity, injury severity, older age, initial need for surgery, the presence of co-morbid health conditions at study entry and an orthopaedic injury to more than one region were associated with extended duration away from work following the injury. Participants in receipt of compensation who reported high social functioning at two weeks were 2.58 times more likely to have returned to work than similar participants reporting low social functioning. When only those who had returned to work were considered, the participant reported reason for return to work " to fill the day" was a significant predictor of earlier RTW [RR 2.41 (95% C.I 1.35-4.30)] whereas "financial security" and "because they felt able to" did not achieve significance.</p> <p>Conclusions</p> <p>Many injury-related and psycho social factors affect the duration of time away from work following orthopaedic injury. Some of these are potentially modifiable and may be amenable to intervention. Further consideration of the reasons provided by participants for returning to work may provide important opportunities for social marketing approaches designed to alleviate the financial and social burden associated with work disability.</p