A feature selection approach for identification of signature genes from SAGE data

Abstract Background One goal of gene expression profiling is to identify signature genes that robustly distinguish different types or grades of tumors. Several tumor classifiers based on expression profiling have been proposed using microarray technique. Due to important differences in the probabilistic models of microarray and SAGE technologies, it is important to develop suitable techniques to select specific genes from SAGE measurements. Results A new framework to select specific genes that distinguish different biological states based on the analysis of SAGE data is proposed. The new framework applies the bolstered error for the identification of strong genes that separate the biological states in a feature space defined by the gene expression of a training set. Credibility intervals defined from a probabilistic model of SAGE measurements are used to identify the genes that distinguish the different states with more reliability among all gene groups selected by the strong genes method. A score taking into account the credibility and the bolstered error values in order to rank the groups of considered genes is proposed. Results obtained using SAGE data from gliomas are presented, thus corroborating the introduced methodology. Conclusion The model representing counting data, such as SAGE, provides additional statistical information that allows a more robust analysis. The additional statistical information provided by the probabilistic model is incorporated in the methodology described in the paper. The introduced method is suitable to identify signature genes that lead to a good separation of the biological states using SAGE and may be adapted for other counting methods such as Massive Parallel Signature Sequencing (MPSS) or the recent Sequencing-By-Synthesis (SBS) technique. Some of such genes identified by the proposed method may be useful to generate classifiers.

Reliable identification of mycobacterial species by PCR-restriction enzyme analysis (PRA)-hsp65 in a reference laboratory and elaboration of a sequence-based extended algorithm of PRA-hsp65 patterns

Abstract Background Identification of nontuberculous mycobacteria (NTM) based on phenotypic tests is time-consuming, labor-intensive, expensive and often provides erroneous or inconclusive results. In the molecular method referred to as PRA-hsp65, a fragment of the hsp65 gene is amplified by PCR and then analyzed by restriction digest; this rapid approach offers the promise of accurate, cost-effective species identification. The aim of this study was to determine whether species identification of NTM using PRA-hsp65 is sufficiently reliable to serve as the routine methodology in a reference laboratory. Results A total of 434 NTM isolates were obtained from 5019 cultures submitted to the Institute Adolpho Lutz, Sao Paulo Brazil, between January 2000 and January 2001. Species identification was performed for all isolates using conventional phenotypic methods and PRA-hsp65. For isolates for which these methods gave discordant results, definitive species identification was obtained by sequencing a 441 bp fragment of hsp65. Phenotypic evaluation and PRA-hsp65 were concordant for 321 (74%) isolates. These assignments were presumed to be correct. For the remaining 113 discordant isolates, definitive identification was based on sequencing a 441 bp fragment of hsp65. PRA-hsp65 identified 30 isolates with hsp65 alleles representing 13 previously unreported PRA-hsp65 patterns. Overall, species identification by PRA-hsp65 was significantly more accurate than by phenotype methods (392 (90.3%) vs. 338 (77.9%), respectively; p < .0001, Fisher's test). Among the 333 isolates representing the most common pathogenic species, PRA-hsp65 provided an incorrect result for only 1.2%. Conclusion PRA-hsp65 is a rapid and highly reliable method and deserves consideration by any clinical microbiology laboratory charged with performing species identification of NTM.

Identification of protein-coding and non-coding RNA expression profiles in CD34+ and in stromal cells in refractory anemia with ringed sideroblasts

Abstract Background Myelodysplastic syndromes (MDS) are a group of clonal hematological disorders characterized by ineffective hematopoiesis with morphological evidence of marrow cell dysplasia resulting in peripheral blood cytopenia. Microarray technology has permitted a refined high-throughput mapping of the transcriptional activity in the human genome. Non-coding RNAs (ncRNAs) transcribed from intronic regions of genes are involved in a number of processes related to post-transcriptional control of gene expression, and in the regulation of exon-skipping and intron retention. Characterization of ncRNAs in progenitor cells and stromal cells of MDS patients could be strategic for understanding gene expression regulation in this disease. Methods In this study, gene expression profiles of CD34+ cells of 4 patients with MDS of refractory anemia with ringed sideroblasts (RARS) subgroup and stromal cells of 3 patients with MDS-RARS were compared with healthy individuals using 44 k combined intron-exon oligoarrays, which included probes for exons of protein-coding genes, and for non-coding RNAs transcribed from intronic regions in either the sense or antisense strands. Real-time RT-PCR was performed to confirm the expression levels of selected transcripts. Results In CD34+ cells of MDS-RARS patients, 216 genes were significantly differentially expressed (q-value ≤ 0.01) in comparison to healthy individuals, of which 65 (30%) were non-coding transcripts. In stromal cells of MDS-RARS, 12 genes were significantly differentially expressed (q-value ≤ 0.05) in comparison to healthy individuals, of which 3 (25%) were non-coding transcripts. Conclusions These results demonstrated, for the first time, the differential ncRNA expression profile between MDS-RARS and healthy individuals, in CD34+ cells and stromal cells, suggesting that ncRNAs may play an important role during the development of myelodysplastic syndromes.

Identification of differentially expressed genes from Trichoderma harzianum during growth on cell wall of Fusarium solani as a tool for biotechnological application

Background: The species of T. harzianum are well known for their biocontrol activity against many plant pathogens. However, there is a lack of studies concerning its use as a biological control agent against F. solani, a pathogen involved in several crop diseases. In this study, we have used subtractive library hybridization (SSH) and quantitative real-time PCR (RT-qPCR) techniques in order to explore changes in T. harzianum genes expression during growth on cell wall of F. solani (FSCW) or glucose. RT-qPCR was also used to examine the regulation of 18 genes, potentially involved in biocontrol, during confrontation between T. harzianum and F. solani. Results: Data obtained from two subtractive libraries were compared after annotation using the Blast2GO suite. A total of 417 and 78 readable EST sequence were annotated in the FSCW and glucose libraries, respectively. Functional annotation of these genes identified diverse biological processes and molecular functions required during T. harzianum growth on FSCW or glucose. We identified various genes of biotechnological value encoding to proteins which function such as transporters, hydrolytic activity, adherence, appressorium development and pathogenesis. Fifteen genes were up-regulated and sixteen were down-regulated at least at one-time point during growth of T. harzianum in FSCW. During the confrontation assay most of the genes were up-regulated, mainly after contact, when the interaction has been established. Conclusions: This study demonstrates that T. harzianum expressed different genes when grown on FSCW compared to glucose. It provides insights into the mechanisms of gene expression involved in mycoparasitism of T. harzianum against F. solani. The identification and evaluation of these genes may contribute to the development of an efficient biological control agent.

Analysis of ripening-related gene expression in papaya using an Arabidopsis-based microarray

Abstract Background Papaya (Carica papaya L.) is a commercially important crop that produces climacteric fruits with a soft and sweet pulp that contain a wide range of health promoting phytochemicals. Despite its importance, little is known about transcriptional modifications during papaya fruit ripening and their control. In this study we report the analysis of ripe papaya transcriptome by using a cross-species (XSpecies) microarray technique based on the phylogenetic proximity between papaya and Arabidopsis thaliana. Results Papaya transcriptome analyses resulted in the identification of 414 ripening-related genes with some having their expression validated by qPCR. The transcription profile was compared with that from ripening tomato and grape. There were many similarities between papaya and tomato especially with respect to the expression of genes encoding proteins involved in primary metabolism, regulation of transcription, biotic and abiotic stress and cell wall metabolism. XSpecies microarray data indicated that transcription factors (TFs) of the MADS-box, NAC and AP2/ERF gene families were involved in the control of papaya ripening and revealed that cell wall-related gene expression in papaya had similarities to the expression profiles seen in Arabidopsis during hypocotyl development. Conclusion The cross-species array experiment identified a ripening-related set of genes in papaya allowing the comparison of transcription control between papaya and other fruit bearing taxa during the ripening process.

Phylogenetic identification of marine bacteria isolated from deep-sea sediments of the eastern South Atlantic Ocean

The deep-sea environments of the South Atlantic Ocean are less studied in comparison to the North Atlantic and Pacific Oceans. With the aim of identifying the deep-sea bacteria in this less known ocean, 70 strains were isolated from eight sediment samples (depth range between 1905 to 5560 m) collected in the eastern part of the South Atlantic, from the equatorial region to the Cape Abyssal Plain, using three different culture media. The strains were classified into three phylogenetic groups, Gammaproteobacteria, Firmicutes and Actinobacteria, by the analysis of 16s rRNA gene sequences. Gammaproteobacteria and Firmicutes were the most frequently identified groups, with Halomonas the most frequent genus among the strains. Microorganisms belonging to Firmicutes were the only ones observed in all samples. Sixteen of the 41 identified operational taxonomic units probably represent new species. The presence of potentially new species reinforces the need for new studies in the deep-sea environments of the South Atlantic.

Identification of SL addition trans-splicing acceptor sites in the internal transcribed spacer I region of pre-rRNA in Leishmania (Leishmania) amazonensis

Trypanosomatidae is a family of early branching eukaryotes harbouring a distinctive repertoire of gene expression strategies. Functional mature messenger RNA is generated via the trans-splicing and polyadenylation processing of constitutively transcribed polycistronic units. Recently, trans-splicing of pre-small subunit ribosomal RNA in the 5' external transcribed spacer region and of precursor tRNAsec have been described. Here, we used a previously validated semi-nested reverse transcription-polymerase chain reaction strategy to investigate internal transcribed spacer (ITS) I acceptor sites in total RNA from Leishmania (Leishmania) amazonensis. Two distinct spliced leader-containing RNAs were detected indicating that trans-splicing reactions occur at two AG acceptor sites mapped in this ITS region. These data provide further evidence of the wide spectrum of RNA molecules that act as trans-splicing acceptors in trypanosomatids.