A Genome-Scale Atlas Reveals Complex Interplay of Transcription and Translation in an Archaeon.

The scale of post-transcriptional regulation and the implications of its interplay with other forms of regulation in environmental acclimation are 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 the transcriptome-wide locations of transcript processing sites (TPSs) and SmAP1 binding, the genome-wide locations of antisense RNAs (asRNAs), and the consequences of RNase_2099C knockout on the 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 being regulated by combinatorial schemes involving SmAP1, asRNAs, and RNase_2099C. Comparative analysis of mRNA levels (transcriptome sequencing [RNA-Seq]) and protein levels (sequential window acquisition of all theoretical fragment ion spectra mass spectrometry [SWATH-MS]) for 2,579 genes over four phases of batch culture growth in complex medium generated additional evidence for the 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 under anoxic conditions and modulate the frequency of transposition by insertion sequence (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). IMPORTANCE While 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).

Integrating Methylome and Transcriptome Signatures Expands the Molecular Classification of the Pituitary Tumors.

OBJECTIVE: To explore pituitary tumors by methylome and transcriptome signatures in a heterogeneous ethnic population. METHODS: In this retrospective cross-sectional study, clinicopathological features, methylome, and transcriptome were evaluated in pituitary tumors from 77 patients (61% women, age 12-72 years) followed due to functioning (FPT: GH-secreting n = 18, ACTH-secreting n = 14) and nonfunctioning pituitary tumors (NFPT, n = 45) at Ribeirao Preto Medical School, University of São Paulo. RESULTS: Unsupervised hierarchical clustering analysis (UHCA) of methylome (n = 77) and transcriptome (n = 65 out of 77) revealed 3 clusters each: one enriched by FPT, one by NFPT, and a third by ACTH-secreting and NFPT. Comparison between each omics-derived clusters identified 3568 and 5994 differentially methylated and expressed genes, respectively, which were associated with each other, with tumor clinical presentation, and with 2017 and 2022 WHO classifications. UHCA considering 11 transcripts related to pituitary development/differentiation also supported 3 clusters: POU1F1-driven somatotroph, TBX19-driven corticotroph, and NR5A1-driven gonadotroph adenomas, with rare exceptions (NR5A1 expressed in few GH-secreting and corticotroph silent adenomas; POU1F1 in few ACTH-secreting adenomas; and TBX19 in few NFPTs). CONCLUSION: This large heterogenic ethnic Brazilian cohort confirms that integrated methylome and transcriptome signatures classify FPT and NFPT, which are associated with clinical presentation and tumor invasiveness. Moreover, the cluster NFPT/ACTH-secreting adenomas raises interest regarding tumor heterogeneity, supporting the challenge raised by the 2017 and 2022 WHO definition regarding the discrepancy, in rare cases, between clinical presentation and pituitary lineage markers. Finally, making our data publicly available enables further studies to validate genes/pathways involved in pituitary tumor pathogenesis and prognosis.

Low Salt Influences Archaellum-Based Motility, Glycerol Metabolism, and Gas Vesicles Biogenesis in Halobacterium salinarum.

Halobacterium salinarum NRC-1 is an extremophile that grows optimally at 4.3 M NaCl concentration. In spite of being an established model microorganism for the archaea domain, direct comparisons between its proteome and transcriptome during osmotic stress are still not available. Through RNA-seq-based transcriptomics, we compared a low salt (2.6 M NaCl) stress condition with 4.3 M of NaCl and found 283 differentially expressed loci. The more commonly found classes of genes were: ABC-type transporters and transcription factors. Similarities, and most importantly, differences between our findings and previously published datasets in similar experimental conditions are discussed. We validated three important biological processes differentially expressed: gas vesicles production (due to down-regulation of gvpA1b, gvpC1b, gvpN1b, and gvpO1b); archaellum formation (due to down-regulation of arlI, arlB1, arlB2, and arlB3); and glycerol metabolism (due to up-regulation of glpA1, glpB, and glpC). Direct comparison between transcriptomics and proteomics showed 58% agreement between mRNA and protein level changes, pointing to post-transcriptional regulation candidates. From those genes, we highlight rpl15e, encoding for the 50S ribosomal protein L15e, for which we hypothesize an ionic strength-dependent conformational change that guides post-transcriptional processing of its mRNA and, thus, possible salt-dependent regulation of the translation machinery.

Environmental Influences Measured by Epigenetic Clock and Vulnerability Components at Birth Impact Clinical ASD Heterogeneity.

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 < 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.

Halobacterium salinarum and Haloferax volcanii Comparative Transcriptomics Reveals Conserved Transcriptional Processing Sites.

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 salinarum NRC-1 and Haloferax 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.

Lineage relationship between prostate adenocarcinoma and small cell carcinoma.

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.

The Primary Antisense Transcriptome of Halobacterium salinarum NRC-1.

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' 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⁻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.

Internal RNAs overlapping coding sequences can drive the production of alternative proteins in archaea.

Prokaryotic genomes show a high level of information compaction often with different molecules transcribed from the same locus. Although antisense RNAs have been relatively well studied, RNAs in the same strand, internal RNAs (intraRNAs), are still poorly understood. The question of how common is the translation of overlapping reading frames remains open. We address this question in the model archaeon Halobacterium salinarum. In the present work we used differential RNA-seq (dRNA-seq) in H. salinarum NRC-1 to locate intraRNA signals in subsets of internal transcription start sites (iTSS) and establish the open reading frames associated to them (intraORFs). Using C-terminally flagged proteins, we experimentally observed isoforms accurately predicted by intraRNA translation for kef1, acs3 and orc4 genes. We also recovered from the literature and mass spectrometry databases several instances of protein isoforms consistent with intraRNA translation such as the gas vesicle protein gene gvpC1. We found evidence for intraRNAs in horizontally transferred genes such as the chaperone dnaK and the aerobic respiration related cydA in both H. salinarum and Escherichia coli. Also, intraRNA translation evidence in H. salinarum, E. coli and yeast of a universal elongation factor (aEF-2, fusA and eEF-2) suggests that this is an ancient phenomenon present in all domains of life.

Conditional deletion of ELL2 induces murine prostate intraepithelial neoplasia.

Elongation factor, RNA polymerase II, 2 (ELL2) is an RNA Pol II elongation factor with functional properties similar to ELL that can interact with the prostate tumor suppressor EAF2. In the prostate, ELL2 is an androgen response gene that is upregulated in benign prostatic hyperplasia (BPH). We recently showed that ELL2 loss could enhance prostate cancer cell proliferation and migration, and that ELL2 gene expression was downregulated in high Gleason score prostate cancer specimens. Here, prostate-specific deletion of ELL2 in a mouse model revealed a potential role for ELL2 as a prostate tumor suppressor in vivoEll2-knockout mice exhibited prostatic defects including increased epithelial proliferation, vascularity and PIN lesions similar to the previously determined prostate phenotype in Eaf2-knockout mice. Microarray analysis of prostates from Ell2-knockout and wild-type mice on a C57BL/6J background at age 3 months and qPCR validation at 17 months of age revealed a number of differentially expressed genes associated with proliferation, cellular motility and epithelial and neural differentiation. OncoPrint analysis identified combined downregulation or deletion in prostate adenocarcinoma cases from the Cancer Genome Atlas (TCGA) data portal. These results suggest that ELL2 and its pathway genes likely play an important role in the development and progression of prostate cancer.

Conversion of Prostate Adenocarcinoma to Small Cell Carcinoma-Like by Reprogramming.

The lineage relationship between prostate adenocarcinoma and small cell carcinoma was studied by using the LuCaP family of xenografts established from primary neoplasm to metastasis. Expression of four stem cell transcription factor (TF) genes, LIN28A, NANOG, POU5F1, SOX2, were analyzed in the LuCaP lines. These genes, when force expressed in differentiated cells, can reprogram the recipients into stem-like induced pluripotent stem (iPS) cells. Most LuCaP lines expressed POU5F1, while LuCaP 145.1, representative of small cell carcinoma, expressed all four. Through transcriptome database query, many small cell carcinoma genes were also found in stem cells. To test the hypothesis that prostate cancer progression from "differentiated" adenocarcinoma to "undifferentiated" small cell carcinoma could involve re-expression of stem cell genes, the four TF genes were transduced via lentiviral vectors into five adenocarcinoma LuCaP lines-70CR, 73CR, 86.2, 92, 105CR-as done in iPS cell reprogramming. The resultant cells from these five transductions displayed a morphology of small size and dark appearing unlike the parentals. Transcriptome analysis of LuCaP 70CR* ("*" to denote transfected progeny) revealed a unique gene expression close to that of LuCaP 145.1. In a prostate principal components analysis space based on cell-type transcriptomes, the different LuCaP transcriptome datapoints were aligned to suggest a possible ordered sequence of expression changes from the differentiated luminal-like adenocarcinoma cell types to the less differentiated, more stem-like small cell carcinoma types, and LuCaP 70CR*. Prostate cancer progression can thus be molecularly characterized by loss of differentiation with re-expression of stem cell genes. J. Cell. Physiol. 231: 2040-2047, 2016. © 2016 Wiley Periodicals, Inc.

Processing of voided urine for prostate cancer RNA biomarker analysis.

BACKGROUND: Voided urine samples have been shown to contain cells released from prostate tumors. Could good quality RNA from cells in urine be obtained from every donor for multimarker analysis? In addition, could urine donation be as simple as possible, a practical consideration for a lab test, without involving a prostate massage (as indicated for PCA3 testing), which precludes frequent collection; needing it done at a specific time of day (e.g., first or second urine); and requiring prompt processing of samples in clinics with limited molecular biology capability? METHODS: Collected urine samples were pelleted, and the RNA isolated was processed for cDNA synthesis and in vitro transcription to generate amplified sense aRNA. The resultant aRNA was rigorously analyzed for possible introduced changes. DMSO was used as a cell preservative for frozen storage of urine samples. RESULTS: Good quality aRNA was obtained for over 100 samples collected at two different institutions. The process of RNA amplification removed co-isolated DNA in some samples, which did not affect RNA amplification. Amplification did not amplify genes that were absent and produce other expression alterations. The sense aRNA could be used to generate urinary transcriptomes specific to individual patients. No chaotropic agents for RNA preservation were added to the urine samples so that the supernatant could be used for analysis of secreted protein biomarkers. The time of donation was not important since patients were seen during the entire day. DMSO was an effective cell preservative for freezing urine. CONCLUSIONS: Urinary RNA can be readily isolated and amplified for prostate cancer biomarker analysis. Individual patients had unique set of transcripts derived from their tumor.

A Methodology for the Development of RESTful Semantic Web Services for Gene Expression Analysis.

Gene expression studies are generally performed through multi-step analysis processes, which require the integrated use of a number of analysis tools. In order to facilitate tool/data integration, an increasing number of analysis tools have been developed as or adapted to semantic web services. In recent years, some approaches have been defined for the development and semantic annotation of web services created from legacy software tools, but these approaches still present many limitations. In addition, to the best of our knowledge, no suitable approach has been defined for the functional genomics domain. Therefore, this paper aims at defining an integrated methodology for the implementation of RESTful semantic web services created from gene expression analysis tools and the semantic annotation of such services. We have applied our methodology to the development of a number of services to support the analysis of different types of gene expression data, including microarray and RNASeq. All developed services are publicly available in the Gene Expression Analysis Services (GEAS) Repository at http://dcm.ffclrp.usp.br/lssb/geas. Additionally, we have used a number of the developed services to create different integrated analysis scenarios to reproduce parts of two gene expression studies documented in the literature. The first study involves the analysis of one-color microarray data obtained from multiple sclerosis patients and healthy donors. The second study comprises the analysis of RNA-Seq data obtained from melanoma cells to investigate the role of the remodeller BRG1 in the proliferation and morphology of these cells. Our methodology provides concrete guidelines and technical details in order to facilitate the systematic development of semantic web services. Moreover, it encourages the development and reuse of these services for the creation of semantically integrated solutions for gene expression analysis.

SIFTER-T: a scalable and optimized framework for the SIFTER phylogenomic method of probabilistic protein domain annotation.

Statistical Inference of Function Through Evolutionary Relationships (SIFTER) is a powerful computational platform for probabilistic protein domain annotation. Nevertheless, SIFTER is not widely used, likely due to usability and scalability issues. Here we present SIFTER-T (SIFTER Throughput-optimized), a substantial improvement over SIFTER's original proof-of-principle implementation. SIFTER-T is optimized for better performance, allowing it to be used at the genome-wide scale. Compared to SIFTER 2.0, SIFTER-T achieved an 87-fold performance improvement using published test data sets for the known annotations recovering module and a 72.3% speed increase for the gene tree generation module in quad-core machines, as well as a major decrease in memory usage during the realignment phase. Memory optimization allowed an expanded set of proteins to be handled by SIFTER's probabilistic method. The improvement in performance and automation that we achieved allowed us to build a web server to bring the power of Bayesian phylogenomic inference to the genomics community. SIFTER-T and its online interface are freely available under GNU license at http://labpib.fmrp.usp.br/methods/SIFTER-t/ and https://github.com/dcasbioinfo/SIFTER-t.

Sense overlapping transcripts in IS1341-type transposase genes are functional non-coding RNAs in archaea.

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 metabolomic protocol for plant systematics by matrix-assisted laser-desorption/ionization time-of flight mass spectrometry.

Matrix-assisted laser desorption/ionization time-of flight mass spectrometry (MALDI-TOF MS) has been widely used for the identification and classification of microorganisms based on their proteomic fingerprints. However, the use of MALDI-TOF MS in plant research has been very limited. In the present study, a first protocol is proposed for metabolic fingerprinting by MALDI-TOF MS using three different MALDI matrices with subsequent multivariate data analysis by in-house algorithms implemented in the R environment for the taxonomic classification of plants from different genera, families and orders. By merging the data acquired with different matrices, different ionization modes and using careful algorithms and parameter selection, we demonstrate that a close taxonomic classification can be achieved based on plant metabolic fingerprints, with 92% similarity to the taxonomic classifications found in literature. The present work therefore highlights the great potential of applying MALDI-TOF MS for the taxonomic classification of plants and, furthermore, provides a preliminary foundation for future research.

Reprogramming of prostate cancer cells--technical challenges.

Prostate cancer progression is characterized by tumor dedifferentiation. Cancer cells of less differentiated tumors have a gene expression/transcriptome more similar to that of stem cells. In dedifferentiation, cancer cells may follow a specific program of gene expression changes to a stem-like state. In order to treat cancer effectively, the stem-like cancer cells and cancer differentiation pathway need to be identified and studied. Due to the very low abundance of stem-like cancer cells, their isolation from fresh human tumors is technically challenging. Induced pluripotent stem cell technology can reprogram differentiated cells into stem-like, and this may be a tool to generate sufficient stem-like cancer cells.

Transcription start site associated RNAs (TSSaRNAs) are ubiquitous in all domains of life.

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.

Mass spectrometry in plant metabolomics strategies: from analytical platforms to data acquisition and processing.

Covering: up to 2013. Plant metabolomics is a relatively recent research field that has gained increasing interest in the past few years. Up to the present day numerous review articles and guide books on the subject have been published. This review article focuses on the current applications and limitations of the modern mass spectrometry techniques, especially in combination with electrospray ionisation (ESI), an ionisation method which is most commonly applied in metabolomics studies. As a possible alternative to ESI, perspectives on matrix-assisted laser desorption/ionisation mass spectrometry (MALDI-MS) in metabolomics studies are introduced, a method which still is not widespread in the field. In metabolomics studies the results must always be interpreted in the context of the applied sampling procedures as well as data analysis. Different sampling strategies are introduced and the importance of data analysis is illustrated in the example of metabolic network modelling.

ProbMetab: an R package for Bayesian probabilistic annotation of LC-MS-based metabolomics.

We present ProbMetab, an R package that promotes substantial improvement in automatic probabilistic liquid chromatography-mass spectrometry-based metabolome annotation. The inference engine core is based on a Bayesian model implemented to (i) allow diverse source of experimental data and metadata to be systematically incorporated into the model with alternative ways to calculate the likelihood function and (ii) allow sensitive selection of biologically meaningful biochemical reaction databases as Dirichlet-categorical prior distribution. Additionally, to ensure result interpretation by system biologists, we display the annotation in a network where observed mass peaks are connected if their candidate metabolites are substrate/product of known biochemical reactions. This graph can be overlaid with other graph-based analysis, such as partial correlation networks, in a visualization scheme exported to Cytoscape, with web and stand-alone versions.

Semantic integration of gene expression analysis tools and data sources using software connectors.

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 heterogeneous 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.