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The scale of post-transcriptional regulation and the implications of its interplay with other forms of regulation on environmental acclimation is underexplored for organisms of the domain Archaea. Here, we have investigated the scale of post-transcriptional regulation in the extremely halophilic archaeon Halobacterium salinarum NRC-1 by integrating transcriptome-wide locations of transcript processing sites (TPS) and SmAP1 binding, genome-wide locations of antisense RNAs (asRNAs), and consequences of RNase_2099C knockout on differential expression of all genes. This integrated analysis has discovered that 54% of all protein-coding genes in the genome of this haloarchaeon are likely targeted by multiple mechanisms for putative post-transcriptional processing and regulation, with about 20% of genes likely regulated by combinatorial schemes involving SmAP1, asRNAs, and RNase_2099C. Comparative analysis of mRNA levels (RNA-Seq) and protein levels (SWATH-MS) for 2,579 genes over four phases of batch culture growth in complex medium has generated additional evidence for conditional post-transcriptional regulation of 7% of all protein-coding genes. We demonstrate that post-transcriptional regulation may act to fine-tune specialized and rapid acclimation to stressful environments, e.g., as a switch to turn on gas vesicle biogenesis to promote vertical relocation in anoxic conditions and to modulate frequency of transposition by IS elements of the IS200/IS605, IS4, and ISH3 families. Findings from this study are provided as an atlas in a public web resource (https://halodata.systemsbiology.net).IMPORTANCEWhile the transcriptional regulation landscape of archaea has been extensively investigated, we currently have limited knowledge about post-transcriptional regulation and its driving mechanisms in this domain of life. In this study, we collected and integrated omics data from multiple sources and technologies to infer post-transcriptionally regulated genes and the putative mechanisms modulating their expression at the protein level in Halobacterium salinarum NRC-1. The results suggest that post-transcriptional regulation may drive environmental acclimation by regulating hallmark biological processes. To foster discoveries by other research groups interested in the topic, we extended our integrated data to the public in the form of an interactive atlas (https://halodata.systemsbiology.net).

Although Autism Spectrum Disorders (ASD) is recognized as being heavily influenced by genetic factors, the role of epigenetic and environmental factors is still being established. This study aimed to identify ASD vulnerability components based on familial history and intrauterine environmental stress exposure, explore possible vulnerability subgroups, access DNA methylation age acceleration (AA) as a proxy of stress exposure during life, and evaluate the association of ASD vulnerability components and AA to phenotypic severity measures. Principal Component Analysis (PCA) was used to search the vulnerability components from 67 mothers of autistic children. We found that PC1 had a higher correlation with psychosocial stress (maternal stress, maternal education, and social class), and PC2 had a higher correlation with biological factors (psychiatric family history and gestational complications). Comparing the methylome between above and below PC1 average subgroups we found 11,879 statistically significant differentially methylated probes (DMPs, p &lt, 0.05). DMPs CpG sites were enriched in variably methylated regions (VMRs), most showing environmental and genetic influences. Hypermethylated probes presented higher rates in different regulatory regions associated with functional SNPs, indicating that the subgroups may have different affected regulatory regions and their liability to disease explained by common variations. Vulnerability components score moderated by epigenetic clock AA was associated with Vineland Total score (p = 0.0036, adjR2 = 0.31), suggesting risk factors with stress burden can influence ASD phenotype.

Background Prostate cancer displays different morphologies which, in turn, affect patient outcome. This fact prompted questions about the lineage relationship between differentiated, more treatable prostate adenocarcinoma and poorly differentiated, less treatable non-adenocarcinoma including small cell carcinoma, and the molecular mechanism underlying prostate cancer differentiation. Methods Newly available non-adenocarcinoma/small cell carcinoma PDX LuCaP lines were analyzed for expression of stem cell transcription factors (scTF) LIN28A, NANOG, POU5F1, SOX2, which are responsible for reprogramming or de-differentiation. cDNA of these genes were cloned from small cell carcinoma LuCaP 145.1 into expression vectors to determine if they could function in reprogramming. Results Expression of scTF was detected in small cell carcinoma LuCaP 93, 145.1, 145.2, and non-adenocarcinoma LuCaP 173.1, 173.2A. Transfection of scTF from LuCaP 145.1 altered the gene expression of prostate non-small cell carcinoma cells, as well as fibroblasts. The resultant cells grew in stem-like colonies. Of note was a 10-fold lower expression of B2M in the transfected cells. Low B2M was also characteristic of LuCaP 145.1. Conversely, B2M was increased when stem cells were induced to differentiate. Conclusions This work suggested a pathway in the emergence of non-adenocarcinoma/small cell carcinoma from adenocarcinoma through activation of scTF genes that produced cancer de-differentiation. Electronic supplementary material The online version of this article (10.1186/s12885-019-5680-7) contains supplementary material, which is available to authorized users.

Post-transcriptional processing of messenger RNA is an important regulatory strategy that allows relatively fast responses to changes in environmental conditions. In halophile systems biology, the protein perspective of this problem (i.e., ribonucleases which implement the cleavages) is generally more studied than the RNA perspective (i.e., processing sites). In the present in silico work, we mapped genome-wide transcriptional processing sites (TPS) in two halophilic model organisms, Halobacterium&nbsp, salinarum NRC-1 and Haloferax&nbsp, volcanii DS2. TPS were established by reanalysis of publicly available differential RNA-seq (dRNA-seq) data, searching for non-primary (monophosphorylated RNAs) enrichment. We found 2093 TPS in 43% of H. salinarum genes and 3515 TPS in 49% of H. volcanii chromosomal genes. Of the 244 conserved TPS sites found, the majority were located around start and stop codons of orthologous genes. Specific genes are highlighted when discussing antisense, ribosome and insertion sequence associated TPS. Examples include the cell division gene ftsZ2, whose differential processing signal along growth was detected and correlated with post-transcriptional regulation, and biogenesis of sense overlapping transcripts associated with IS200/IS605. We hereby present the comparative, transcriptomics-based processing site maps with a companion browsing interface.

Antisense RNAs (asRNAs) are present in diverse organisms and play important roles in gene regulation. In this work, we mapped the primary antisense transcriptome in the halophilic archaeon Halobacterium salinarum NRC-1. By reanalyzing publicly available data, we mapped antisense transcription start sites (aTSSs) and inferred the probable 3&prime, ends of these transcripts. We analyzed the resulting asRNAs according to the size, location, function of genes on the opposite strand, expression levels and conservation. We show that at least 21% of the genes contain asRNAs in H. salinarum. Most of these asRNAs are expressed at low levels. They are located antisense to genes related to distinctive characteristics of H. salinarum, such as bacteriorhodopsin, gas vesicles, transposases and other important biological processes such as translation. We provide evidence to support asRNAs in type II toxin&ndash, antitoxin systems in archaea. We also analyzed public Ribosome profiling (Ribo-seq) data and found that ~10% of the asRNAs are ribosome-associated non-coding RNAs (rancRNAs), with asRNAs from transposases overrepresented. Using a comparative transcriptomics approach, we found that ~19% of the asRNAs annotated in H. salinarum belong to genes with an ortholog in Haloferax volcanii, in which an aTSS could be identified with positional equivalence. This shows that most asRNAs are not conserved between these halophilic archaea.

In prostate tumors, both the epithelial and stromal mesenchyme compartments show gene expression changes from their respective normal counterpart. In fact, there are more such changes in the stroma than the epithelium. These include down-regulated expression of genes involved in smooth muscle cell differentiation and those differentially expressed between prostate and bladder, i.e., organ-restricted. In development, the stromal cell type mediates tissue formation from differentiation of stem or progenitor cells. Diseases like cancer may arise as a result of defective stromal signaling. Stromal signaling can be demonstrated by co-culture of stromal cells and embryonal carcinoma NCCIT cells used as a stem cell substitute. In co-culture, stromal cells induce NCCIT cells through diffusible molecules to lose stem cell gene expression, gain expression of prostate genes, alter cytomorphology, and lower proliferation. This NCCIT response is varied as co-cultured bladder stromal cells induce a different gene expression. At the same time, NCCIT factors also affect gene expression of co-cultured stromal cells. NCCIT induces normal prostate tissue (NP) stromal cells to become more like cancer-associated (CP) stromal cells in both mRNA and microRNA expression. In contrast, NCCIT shows minimal effect on CP stromal cells. CP stromal cells may represent a less differentiated state in the prostate stromal cell lineage.

HTself is a web-based bioinformatics tool designed to deal with the classification of differential gene expression in low replication microarray studies. It is based on a statistical test that uses self-self experiments to derive intensity-dependent cutoffs. We developed an extension of HTself, originally released in 2005, by calculating P values instead of using a fixed acceptance level α. As before, the statistic used to compute single-spot P values is obtained from the Gaussian kernel density estimator method applied to self-self data. Different spots corresponding to the same biological gene (replicas) give rise to a set of independent P values that can be combined by well-known statistical methods. The combined P value can be used to decide whether a gene can be considered differentially expressed or not. HTself2 is a new version of HTself that uses P values combination. It is implemented as a user-friendly desktop application to help laboratories without a bioinformatics infrastructure.

Sucrose is the major product of photosynthesis in many higher plants. It is transported from the source tissue through the phloem to various sink tissues to support plant growth, development and reproduction. Knowledge on the signal transduction pathways involved in sucrose synthesis in mature leaves is limited. Using a microarray approach, we analyzed the expression profiles of 1920 sugarcane genes encoding signal transduction elements, transcription factors and stress-related proteins. We used individuals from a population segregating for sugar content and gene expression profiles were obtained from seven individuals with highest and seven with lowest sugar content. Surprisingly, from the 24 differentially expressed genes, 19 were more expressed in plants containing low-sugar content. Three of these genes encoded 14-3-3 like proteins, which have been found to reduce sucrose phosphate synthase (SPS) activity. Another encoded an SNF1-related protein similar to a protein kinase that phosphorylates SPS in vitro making it a target for the interaction with 14-3-3 proteins. The up-regulation of eight stress related genes in the lower sugar content plants supports a view that sugar levels modulate a complex signal transduction network that seems to involve responses that are related to stress. Evidence that hormone signaling is related to the sucrose content was also found. These data reinforced the usefulness of genomic approaches to uncover how sucrose metabolism can be regulated in sugarcane.

Xylella fastidiosa is the etiologic agent of diseases in a wide range of economically important crops including citrus variegated chlorosis, a major threat to the Brazilian citrus industry. The genomes of several strains of this phytopathogen have been completely sequenced enabling large-scale functional studies. In this work we used whole-genome DNA microarrays to investigate the transcription profile of X. fastidiosa grown in defined media with different glucose concentrations. Our analysis revealed that while transcripts related to fastidian gum production were unaffected, colicin-V-like and fimbria precursors were induced in high glucose medium. Based on these results, we suggest a model for colicin-defense mechanism in X. fastidiosa.

The existence of sense overlapping transcripts that share regulatory and coding information in the same genomic sequence shows an additional level of prokaryotic gene expression complexity. Here we report the discovery of ncRNAs associated with IS1341-type transposase (tnpB) genes, at the 3'-end of such elements, with examples in archaea and bacteria. Focusing on the model haloarchaeon Halobacterium salinarum NRC-1, we show the existence of sense overlapping transcripts (sotRNAs) for all its IS1341-type transposases. Publicly available transcriptome compendium show condition-dependent differential regulation between sotRNAs and their cognate genes. These sotRNAs allowed us to find a UUCA tetraloop motif that is present in other archaea (ncRNA family HgcC) and in a H. salinarum intergenic ncRNA derived from a palindrome associated transposable elements (PATE). Overexpression of one sotRNA and the PATE-derived RNA harboring the tetraloop motif improved H. salinarum growth, indicating that these ncRNAs are functional.

A plethora of non-coding RNAs has been discovered using high-resolution transcriptomics tools, indicating that transcriptional and post-transcriptional regulation is much more complex than previously appreciated. Small RNAs associated with transcription start sites of annotated coding regions (TSSaRNAs) are pervasive in both eukaryotes and bacteria. Here, we provide evidence for existence of TSSaRNAs in several archaeal transcriptomes including: Halobacterium salinarum, Pyrococcus furiosus, Methanococcus maripaludis, and Sulfolobus solfataricus. We validated TSSaRNAs from the model archaeon Halobacterium salinarum NRC-1 by deep sequencing two independent small-RNA enriched (RNA-seq) and a primary-transcript enriched (dRNA-seq) strand-specific libraries. We identified 652 transcripts, of which 179 were shown to be primary transcripts (∼7% of the annotated genome). Distinct growth-associated expression patterns between TSSaRNAs and their cognate genes were observed, indicating a possible role in environmental responses that may result from RNA polymerase with varying pausing rhythms. This work shows that TSSaRNAs are ubiquitous across all domains of life.

Background Ontologies have increasingly been used in the biomedical domain, which has prompted the emergence of different initiatives to facilitate their development and integration. The Open Biological and Biomedical Ontologies (OBO) Foundry consortium provides a repository of life-science ontologies, which are developed according to a set of shared principles. This consortium has developed an ontology called OBO Relation Ontology aiming at standardizing the different types of biological entity classes and associated relationships. Since ontologies are primarily intended to be used by humans, the use of graphical notations for ontology development facilitates the capture, comprehension and communication of knowledge between its users. However, OBO Foundry ontologies are captured and represented basically using text-based notations. The Unified Modeling Language (UML) provides a standard and widely-used graphical notation for modeling computer systems. UML provides a well-defined set of modeling elements, which can be extended using a built-in extension mechanism named Profile. Thus, this work aims at developing a UML profile for the OBO Relation Ontology to provide a domain-specific set of modeling elements that can be used to create standard UML-based ontologies in the biomedical domain. Results We have studied the OBO Relation Ontology, the UML metamodel and the UML profiling mechanism. Based on these studies, we have proposed an extension to the UML metamodel in conformance with the OBO Relation Ontology and we have defined a profile that implements the extended metamodel. Finally, we have applied the proposed UML profile in the development of a number of fragments from different ontologies. Particularly, we have considered the Gene Ontology (GO), the PRotein Ontology (PRO) and the Xenopus Anatomy and Development Ontology (XAO). Conclusions The use of an established and well-known graphical language in the development of biomedical ontologies provides a more intuitive form of capturing and representing knowledge than using only text-based notations. The use of the profile requires the domain expert to reason about the underlying semantics of the concepts and relationships being modeled, which helps preventing the introduction of inconsistencies in an ontology under development and facilitates the identification and correction of errors in an already defined ontology.

Xylella fastidiosa is the etiologic agent of a wide range of plant diseases, including citrus variegated chlorosis (CVC), a major threat to citrus industry. The genomes of several strains of this phytopathogen were completely sequenced, enabling large-scale functional studies. DNA microarrays representing 2,608 (91.6%) coding sequences (CDS) of X. fastidiosa CVC strain 9a5c were used to investigate transcript levels during growth with different iron availabilities. When treated with the iron chelator 2,2′-dipyridyl, 193 CDS were considered up-regulated and 216 were considered down-regulated. Upon incubation with 100 μM ferric pyrophosphate, 218 and 256 CDS were considered up- and down-regulated, respectively. Differential expression for a subset of 44 CDS was further evaluated by reverse transcription-quantitative PCR. Several CDS involved with regulatory functions, pathogenicity, and cell structure were modulated under both conditions assayed, suggesting that major changes in cell architecture and metabolism occur when X. fastidiosa cells are exposed to extreme variations in iron concentration. Interestingly, the modulated CDS include those related to colicin V-like bacteriocin synthesis and secretion and to functions of pili/fimbriae. We also investigated the contribution of the ferric uptake regulator Fur to the iron stimulon of X. fastidiosa . The promoter regions of the strain 9a5c genome were screened for putative Fur boxes, and candidates were analyzed by electrophoretic mobility shift assays. Taken together, our data support the hypothesis that Fur is not solely responsible for the modulation of the iron stimulon of X. fastidiosa , and they present novel evidence for iron regulation of pathogenicity determinants.

Listeria monocytogenes is a food-borne, opportunistic, bacterial pathogen causing a wide spectrum of diseases, including meningitis, septicemia, abortion, and gastroenteritis, in humans and animals. Among the 13 L. monocytogenes serovars described, human listeriosis is mostly associated with strains of serovars 4b, 1/2b, and 1/2a. Within the species L. monocytogenes , three phylogenetic lineages are described. Serovar 1/2a belongs to phylogenetic lineage I, while serovars 4b and 1/2b group in phylogenetic lineage II. To explore the role of gene expression in the adaptation of L. monocytogenes strains of these two major lineages to different environments, as well as in virulence, we performed whole-genome expression profiling of six L. monocytogenes isolates of serovars 4b, 1/2b, and 1/2a of distinct origins, using a newly constructed Listeria multigenome DNA array. Comparison of the global gene expression profiles revealed differences among strains. The expression profiles of two strains having distinct 50% lethal doses, as assessed in the mouse model, were further analyzed. Gene ontology term enrichment analysis of the differentially expressed genes identified differences in protein-, nucleic acid-, carbon metabolism-, and virulence-related gene expression. Comparison of the expression profiles of the core genomes of all strains revealed differences between the two lineages with respect to cell wall synthesis, the stress-related sigma B regulon and virulence-related genes. These findings suggest different patterns of interaction with host cells and the environment, key factors for host colonization and survival in the environment.

Xylella fastidiosa is a phytopathogenic bacterium that is responsible for diseases in many economically important crops. Although different strains have been studied, little is known about X. fastidiosa stress responses. One of the better characterized stress responses in bacteria is the heat shock response, which induces the expression of specific genes to prevent protein misfolding and aggregation and to promote degradation of the irreversibly denatured polypeptides. To investigate X. fastidiosa genes involved in the heat shock response, we performed a whole-genome microarray analysis in a time course experiment. Globally, 261 genes were induced (9.7%) and 222 genes were repressed (8.3%). The expression profiles of the differentially expressed genes were grouped, and their expression patterns were validated by quantitative reverse transcription-PCR experiments. We determined the transcription start sites of six heat shock-inducible genes and analyzed their promoter regions, which allowed us to propose a putative consensus for σ 32 promoters in Xylella and to suggest additional genes as putative members of this regulon. Besides the induction of classical heat shock protein genes, we observed the up-regulation of virulence-associated genes such as vapD and of genes for hemagglutinins, hemolysin, and xylan-degrading enzymes, which may indicate the importance of heat stress to bacterial pathogenesis. In addition, we observed the repression of genes related to fimbriae, aerobic respiration, and protein biosynthesis and the induction of genes related to the extracytoplasmic stress response and some phage-related genes, revealing the complex network of genes that work together in response to heat shock.

Background Spotted cDNA microarrays generally employ co-hybridization of fluorescently-labeled RNA targets to produce gene expression ratios for subsequent analysis. Direct comparison of two RNA samples in the same microarray provides the highest level of accuracy; however, due to the number of combinatorial pair-wise comparisons, the direct method is impractical for studies including large number of individual samples (e.g., tumor classification studies). For such studies, indirect comparisons using a common reference standard have been the preferred method. Here we evaluated the precision and accuracy of reconstructed ratios from three indirect methods relative to ratios obtained from direct hybridizations, herein considered as the gold-standard. Results We performed hybridizations using a fixed amount of Cy3-labeled reference oligonucleotide (RefOligo) against distinct Cy5-labeled targets from prostate, breast and kidney tumor samples. Reconstructed ratios between all tissue pairs were derived from ratios between each tissue sample and RefOligo. Reconstructed ratios were compared to (i) ratios obtained in parallel from direct pair-wise hybridizations of tissue samples, and to (ii) reconstructed ratios derived from hybridization of each tissue against a reference RNA pool (RefPool). To evaluate the effect of the external references, reconstructed ratios were also calculated directly from intensity values of single-channel (One-Color) measurements derived from tissue sample data collected in the RefOligo experiments. We show that the average coefficient of variation of ratios between intra- and inter-slide replicates derived from RefOligo, RefPool and One-Color were similar and 2 to 4-fold higher than ratios obtained in direct hybridizations. Correlation coefficients calculated for all three tissue comparisons were also similar. In addition, the performance of all indirect methods in terms of their robustness to identify genes deemed as differentially expressed based on direct hybridizations, as well as false-positive and false-negative rates, were found to be comparable. Conclusion RefOligo produces ratios as precise and accurate as ratios reconstructed from a RNA pool, thus representing a reliable alternative in reference-based hybridization experiments. In addition, One-Color measurements alone can reconstruct expression ratios without loss in precision or accuracy. We conclude that both methods are adequate options in large-scale projects where the amount of a common reference RNA pool is usually restrictive.

Different statistical methods have been used to classify a gene as differentially expressed in microarray experiments. They usually require a number of experimental observations to be adequately applied. However, many microarray experiments are constrained to low replication designs for different reasons, from financial restrictions to scarcely available RNA samples. Although performed in a high-throughput framework, there are few experimental replicas for each gene to allow the use of traditional or state-of-art statistical methods. In this work, we present a web-based bioinformatics tool that deals with real-life problems concerning low replication experiments. It uses an empirically derived criterion to classify a gene as differentially expressed by combining two widely accepted ideas in microarray analysis: self–self experiments to derive intensity-dependent cutoffs and non-parametric estimation techniques. To help laboratories without a bioinformatics infrastructure, we implemented the tool in a user-friendly website (http://blasto.iq. usp.br/� rvencio/HTself).

Submitted by Guilherme Lemeszenski (guilherme@nead.unesp.br) on 2014-02-26T17:22:38Z No. of bitstreams: 1 WOS000230919700003.pdf: 708129 bytes, checksum: 81dfe301960a8a0aef14a8a21d2abd09 (MD5) Made available in DSpace on 2014-02-26T17:22:38Z (GMT). No. of bitstreams: 1 WOS000230919700003.pdf: 708129 bytes, checksum: 81dfe301960a8a0aef14a8a21d2abd09 (MD5) Previous issue date: 2005-02-28 Submitted by Vitor Silverio Rodrigues (vitorsrodrigues@reitoria.unesp.br) on 2014-05-20T13:17:32Z No. of bitstreams: 1 WOS000230919700003.pdf: 708129 bytes, checksum: 81dfe301960a8a0aef14a8a21d2abd09 (MD5) Made available in DSpace on 2014-05-20T13:17:32Z (GMT). No. of bitstreams: 1 WOS000230919700003.pdf: 708129 bytes, checksum: 81dfe301960a8a0aef14a8a21d2abd09 (MD5) Previous issue date: 2005-02-28 A collection of 237,954 sugarcane ESTs was examined in search of signal transduction genes. Over 3,500 components involved in several aspects of signal transduction, transcription, development, cell cycle, stress responses and pathogen interaction were compiled into the Sugarcane Signal Transduction (SUCAST) Catalogue. Sequence comparisons and protein domain analysis revealed 477 receptors, 510 protein kinases, 107 protein phosphatases, 75 small GTPases, 17 G-proteins, 114 calcium and inositol metabolism proteins, and over 600 transcription factors. The elements were distributed into 29 main categories subdivided into 409 sub-categories. Genes with no matches in the public databases and of unknown function were also catalogued. A cDNA microarray was constructed to profile individual variation of plants cultivated in the field and transcript abundance in six plant organs (flowers, roots, leaves, lateral buds, and 1(st) and 4(th) internodes). From 1280 distinct elements analyzed, 217 (17%) presented differential expression in two biological samples of at least one of the tissues tested. A total of 153 genes (12%) presented highly similar expression levels in all tissues. A virtual profile matrix was constructed and the expression profiles were validated by real-time PCR. The expression data presented can aid in assigning function for the sugarcane genes and be useful for promoter characterization of this and other economically important grasses. Univ São Paulo, Inst Quim, Dept Bioquim, BR-05508900 São Paulo, Brazil Univ São Paulo, Inst Matemat & Estatist, Dept Estatist, BR-05508090 São Paulo, Brazil Univ Estadual Campinas, Inst Biol, Dept Genet & Evolucao, BR-13083970 Campinas, SP, Brazil Univ Estadual Campinas, Ctr Biol Mol & Engn Genet, BR-13083970 Campinas, SP, Brazil Ctr Tecnol Copersucar, BR-13400970 São Paulo, Brazil Univ Estadual Paulista, Fac Ciências Agr & Vet Jaboticabal, Dept Tecnol, Ctr Estocagem Clones,BCCCtr, BR-14870000 São Paulo, Brazil Univ Estadual Paulista, Fac Ciências Agr & Vet Jaboticabal, Dept Tecnol, Ctr Estocagem Clones,BCCCtr, BR-14870000 São Paulo, Brazil

Xylella fastidiosa is a phytopathogenic bacterium that causes serious diseases in a wide range of economically important crops. Despite extensive comparative analyses of genome sequences of Xylella pathogenic strains from different plant hosts, nonpathogenic strains have not been studied. In this report, we show that X. fastidiosa strain J1a12, associated with citrus variegated chlorosis (CVC), is nonpathogenic when injected into citrus and tobacco plants. Furthermore, a DNA microarray-based comparison of J1a12 with 9a5c, a CVC strain that is highly pathogenic and had its genome completely sequenced, revealed that 14 coding sequences of strain 9a5c are absent or highly divergent in strain J1a12. Among them, we found an arginase and a fimbrial adhesin precursor of type III pilus, which were confirmed to be absent in the nonpathogenic strain by PCR and DNA sequencing. The absence of arginase can be correlated to the inability of J1a12 to multiply in host plants. This enzyme has been recently shown to act as a bacterial survival mechanism by down-regulating host nitric oxide production. The lack of the adhesin precursor gene is in accordance with the less aggregated phenotype observed for J1a12 cells growing in vitro. Thus, the absence of both genes can be associated with the failure of the J1a12 strain to establish and spread in citrus and tobacco plants. These results provide the first detailed comparison between a nonpathogenic strain and a pathogenic strain of X. fastidiosa , constituting an important step towards understanding the molecular basis of the disease.

Trypanosoma cruzi presents high genetic diversity and parasite isolates show remarkable differences in biological parameters. In this study, we evaluated whether DNA microarrays containing CL Brener cDNAs can be used for comparative genomics and for the analysis of gene expression in T. cruzi. We constructed a prototype microarray with 710 expression sequence tags of CL Brener and 20 sequences of T. cruzi strains. These probes represent 665 unique genes. Results from four hybridisations with genomic DNA of Silvio (T. cruzi I) and CL Brener (hybrid genotype) identified 9.3% of the probes (68/730) differentially represented in the two genomes. Data from eight hybridisations with cDNA obtained from three independent parasite harvests of Silvio and CL Brener disclosed 84 sequences of 730 (11.5%) that showed statistical significant (P < or = 0.01) changes in expression (1.6-6.5-fold). Some of the array-identified sequences were confirmed by Southern and Northern blot analysis. Only 20% of the probes with increased expression in Silvio or CL Brener presented higher hybridisation with genomic DNA of either strain. Approximately 2.5% (18/730) and 9.0% (65/730) of the probes were differentially expressed (P < or = 0.01), respectively, in epimastigotes and metacyclic trypomastigotes of two T. cruzi II strains isolated from chronic chagasic patients. Microarrays identified several sequences for which differences in gene copy number and/or in the levels of RNA transcripts were previously demonstrated by different approaches. The data indicate that DNA microarrays are a useful tool for comparative studies between strains and provide further evidence for a high level of post-transcriptional regulation of RNA abundance in T. cruzi.

Background Uncovering the molecular mechanism underlying expansion of hematopoietic stem and progenitor cells is critical to extend current therapeutic applications and to understand how its deregulation relates to leukemia. The characterization of genes commonly relevant to stem/progenitor cell expansion and tumor development should facilitate the identification of novel therapeutic targets in cancer. Methods CD34+/CD133+ progenitor cells were purified from human umbilical cord blood and expanded in vitro. Correlated molecular changes were analyzed by gene expression profiling using microarrays covering up to 55,000 transcripts. Genes regulated during progenitor cell expansion were identified and functionally classified. Aberrant expression of such genes in cancer was indicated by in silico SAGE. Differential expression of selected genes was assessed by real-time PCR in hematopoietic cells from chronic myeloid leukemia patients and healthy individuals. Results Several genes and signaling pathways not previously associated with ex vivo expansion of CD133+/CD34+ cells were identified, most of which associated with cancer. Regulation of MEK/ERK and Hedgehog signaling genes in addition to numerous proto-oncogenes was detected during conditions of enhanced progenitor cell expansion. Quantitative real-time PCR analysis confirmed down-regulation of several newly described cancer-associated genes in CD133+/CD34+ cells, including DOCK4 and SPARCL1 tumor suppressors, and parallel results were verified when comparing their expression in cells from chronic myeloid leukemia patients Conclusion Our findings reveal potential molecular targets for oncogenic transformation in CD133+/CD34+ cells and strengthen the link between deregulation of stem/progenitor cell expansion and the malignant process.

Background An important challenge for transcript counting methods such as Serial Analysis of Gene Expression (SAGE), "Digital Northern" or Massively Parallel Signature Sequencing (MPSS), is to carry out statistical analyses that account for the within-class variability, i.e., variability due to the intrinsic biological differences among sampled individuals of the same class, and not only variability due to technical sampling error.

Background Prostate tumor heterogeneity is a major factor in disease management. Heterogeneity could be due to multiple cancer cell types with distinct gene expression. Of clinical importance is the so-called cancer stem cell type. Cell type-specific transcriptomes are used to examine lineage relationship among cancer cell types and their expression similarity to normal cell types including stem/progenitor cells. Methods Transcriptomes were determined by Affymetrix DNA array analysis for the following cell types. Putative prostate progenitor cell populations were characterized and isolated by expression of the membrane transporter ABCG2. Stem cells were represented by embryonic stem and embryonal carcinoma cells. The cancer cell types were Gleason pattern 3 (glandular histomorphology) and pattern 4 (aglandular) sorted from primary tumors, cultured prostate cancer cell lines originally established from metastatic lesions, xenografts LuCaP 35 (adenocarcinoma phenotype) and LuCaP 49 (neuroendocrine/small cell carcinoma) grown in mice. No detectable gene expression differences were detected among serial passages of the LuCaP xenografts. Results Based on transcriptomes, the different cancer cell types could be clustered into a luminal-like grouping and a non-luminal-like (also not basal-like) grouping. The non-luminal-like types showed expression more similar to that of stem/progenitor cells than the luminal-like types. However, none showed expression of stem cell genes known to maintain stemness. Conclusions Non-luminal-like types are all representatives of aggressive disease, and this could be attributed to the similarity in overall gene expression to stem and progenitor cell types.

Background The study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heteregeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data. Results We have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data. Conclusions The proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools and data sources. The methodology can be used in the development of connectors supporting both simple and nontrivial processing requirements, thus assuring accurate data exchange and information interpretation from exchanged data.

Background - Sucrose content is a highly desirable trait in sugarcane as the worldwide demand for cost-effective biofuels surges. Sugarcane cultivars differ in their capacity to accumulate sucrose and breeding programs routinely perform crosses to identify genotypes able to produce more sucrose. Sucrose content in the mature internodes reach around 20% of the culms dry weight. Genotypes in the populations reflect their genetic program and may display contrasting growth, development, and physiology, all of which affect carbohydrate metabolism. Few studies have profiled gene expression related to sugarcane's sugar content. The identification of signal transduction components and transcription factors that might regulate sugar accumulation is highly desirable if we are to improve this characteristic of sugarcane plants. Results - We have evaluated thirty genotypes that have different Brix (sugar) levels and identified genes differentially expressed in internodes using cDNA microarrays. These genes were compared to existing gene expression data for sugarcane plants subjected to diverse stress and hormone treatments. The comparisons revealed a strong overlap between the drought and sucrose-content datasets and a limited overlap with ABA signaling. Genes associated with sucrose content were extensively validated by qRT-PCR, which highlighted several protein kinases and transcription factors that are likely to be regulators of sucrose accumulation. The data also indicate that aquaporins, as well as lignin biosynthesis and cell wall metabolism genes, are strongly related to sucrose accumulation. Moreover, sucrose-associated genes were shown to be directly responsive to short term sucrose stimuli, confirming their role in sugar-related pathways. Conclusion - Gene expression analysis of sugarcane populations contrasting for sucrose content indicated a possible overlap with drought and cell wall metabolism processes and suggested signaling and transcriptional regulators to be used as molecular markers in breeding programs. Transgenic research is necessary to further clarify the role of the genes and define targets useful for sugarcane improvement programs based on transgenic plants.