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PubMed2006

VAMP: visualization and analysis of array-CGH, transcriptome and other molecular profiles.

MOTIVATION: Microarray-based CGH (Comparative Genomic Hybridization), transcriptome arrays and other large-scale genomic technologies are now routinely used to generate a vast amount of genomic profiles. Exploratory analysis of this data is crucial in helping to understand the data and to help form biological hypotheses. This step requires visualization of the data in a meaningful way to visualize the results and to perform first level analyses. RESULTS: We have developed a graphical user interface for visualization and first level analysis of molecular profiles. It is currently in use at the Institut Curie for cancer research projects involving CGH arrays, transcriptome arrays, SNP (single nucleotide polymorphism) arrays, loss of heterozygosity results (LOH), and Chromatin ImmunoPrecipitation arrays (ChIP chips). The interface offers the possibility of studying these different types of information in a consistent way. Several views are proposed, such as the classical CGH karyotype view or genome-wide multi-tumor comparison. Many functionalities for analyzing CGH data are provided by the interface, including looking for recurrent regions of alterations, confrontation to transcriptome data or clinical information, and clustering. Our tool consists of PHP scripts and of an applet written in Java. It can be run on public datasets at http://bioinfo.curie.fr/vamp AVAILABILITY: The VAMP software (Visualization and Analysis of array-CGH,transcriptome and other Molecular Profiles) is available upon request. It can be tested on public datasets at http://bioinfo.curie.fr/vamp. The documentation is available at http://bioinfo.curie.fr/vamp/doc.

Algorithms↗
PubMed2005

Exploring the plant transcriptome through phylogenetic profiling.

Publicly available protein sequences represent only a small fraction of the full catalog of genes encoded by the genomes of different plants, such as green algae, mosses, gymnosperms, and angiosperms. By contrast, an enormous amount of expressed sequence tags (ESTs) exists for a wide variety of plant species, representing a substantial part of all transcribed plant genes. Integrating protein and EST sequences in comparative and evolutionary analyses is not straightforward because of the heterogeneous nature of both types of sequence data. By combining information from publicly available EST and protein sequences for 32 different plant species, we identified more than 250,000 plant proteins organized in more than 12,000 gene families. Approximately 60% of the proteins are absent from current sequence databases but provide important new information about plant gene families. Analysis of the distribution of gene families over different plant species through phylogenetic profiling reveals interesting insights into plant gene evolution, and identifies species- and lineage-specific gene families, orphan genes, and conserved core genes across the green plant lineage. We counted a similar number of approximately 9,500 gene families in monocotyledonous and eudicotyledonous plants and found strong evidence for the existence of at least 33,700 genes in rice (Oryza sativa). Interestingly, the larger number of genes in rice compared to Arabidopsis (Arabidopsis thaliana) can partially be explained by a larger amount of species-specific single-copy genes and species-specific gene families. In addition, a majority of large gene families, typically containing more than 50 genes, are bigger in rice than Arabidopsis, whereas the opposite seems true for small gene families.

Arabidopsis↗
PubMed2006

[Importance of development of ecotoxicogenomics in understanding molecular mechanisms of chemicals in developing animals].

Developing organisms are sensitive to estrogenic chemicals. Exposure to estrogens or estrogenic chemicals during critical periods of development induces persistent changes in reproductive as well as nonreproductive organs, including persistent molecular alterations. Chemicals released into the environment potentially disrupt the endocrine system in wild animals and humans, some of which exhibit estrogenic or anti-androgenic activity by binding to estrogen or androgen receptors. Estrogen-responsive genes and critical developmental windows of various animal species, therefore, should be identified to understand the molecular basis of estrogenic activity during embryonic development. To understand molecular mechanisms of estrogenic chemicals in developing organisms, we identified estrogen-responsive genes using cDNA microarrays and a quantitative reverse transcriptase-polymerase chain reaction, and genes related to estrogen-independent vaginal changes in mice induced by estrogens during a critical window. We also analyzed genes in Xenopus laevis embryos related to abnormalities induced by estrogenic chemicals using cDNA microarrays. Estrogen receptors and other steroid hormone receptors were cloned in various species, including the American alligator, crocodile, Florida red-bellied turtle, Silurana tropicalis, roach, Fundulus and mosquito fish. An environmental androgen, trenbolone, was found to induce persistent changes in the gonopodium and ovotestis in mosquito fish. In Daphnia magna, juvenile hormone agonists induce the production of male offspring. Tributyltin (TBT) induces imposex in rockshell through retinoid X receptor (RXR) activation. Microarray technology is a powerful tool for understanding the molecular mechanism of receptor-mediated toxicology in various animal species. Ecotoxicogenomics is a multidisciplinary field concerned with elucidating how the entire genome is involved in the biological response of wild animals exposed to environmental toxicants and stressors. Ecotoxicogenomics combines information from studies of genomic-scale mRNA profiling by microarray analysis (transcriptomics), protein profiling (proteomics), metabolite profiling (metabolonomics) and computational models to understand the roles of gene-environment interaction in the chemical toxicity. To understand the molecular mechanism of chemicals in developing wildlife, the establishment of ecotoxicogenomics is essential in the near future.

Amphibians↗
PubMed2003

Composition and dynamics of the Caenorhabditis elegans early embryonic transcriptome.

Temporal profiles of transcript abundance during embryonic development were obtained by whole-genome expression analysis from precisely staged C. elegans embryos. The result is a highly resolved time course that commences with the zygote and extends into mid-gastrulation, spanning the transition from maternal to embryonic control of development and including the presumptive specification of most major cell fates. Transcripts for nearly half (8890) of the predicted open reading frames are detected and expression levels for the majority of them (>70%) change over time. The transcriptome is stable up to the four-cell stage where it begins rapidly changing until the rate of change plateaus before gastrulation. At gastrulation temporal patterns of maternal degradation and embryonic expression intersect indicating a mid-blastula transition from maternal to embryonic control of development. In addition, we find that embryonic genes tend to be expressed transiently on a time scale consistent with developmental decisions being made with each cell cycle. Furthermore, overall rates of synthesis and degradation are matched such that the transcriptome maintains a steady-state frequency distribution. Finally, a versatile analytical platform based on cluster analysis and developmental classification of genes is provided.

Animals↗
PubMed2001

Insight into hepatocellular carcinogenesis at transcriptome level by comparing gene expression profiles of hepatocellular carcinoma with those of corresponding noncancerous liver.

Human hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. In this work, we report on a comprehensive characterization of gene expression profiles of hepatitis B virus-positive HCC through the generation of a large set of 5'-read expressed sequence tag (EST) clusters (11,065 in total) from HCC and noncancerous liver samples, which then were applied to a cDNA microarray system containing 12,393 genes/ESTs and to comparison with a public database. The commercial cDNA microarray, which contains 1,176 known genes related to oncogenesis, was used also for profiling gene expression. Integrated data from the above approaches identified 2,253 genes/ESTs as candidates with differential expression. A number of genes related to oncogenesis and hepatic function/differentiation were selected for further semiquantitative reverse transcriptase-PCR analysis in 29 paired HCC/noncancerous liver samples. Many genes involved in cell cycle regulation such as cyclins, cyclin-dependent kinases, and cell cycle negative regulators were deregulated in most patients with HCC. Aberrant expression of the Wnt-beta-catenin pathway and enzymes for DNA replication also could contribute to the pathogenesis of HCC. The alteration of transcription levels was noted in a large number of genes implicated in metabolism, whereas a profile change of others might represent a status of dedifferentiation of the malignant hepatocytes, both considered as potential markers of diagnostic value. Notably, the altered transcriptome profiles in HCC could be correlated to a number of chromosome regions with amplification or loss of heterozygosity, providing one of the underlying causes of the transcription anomaly of HCC.

Carcinoma, Hepatocellular↗
PubMed2001

Profiling the adult human liver transcriptome: analysis by cDNA array hybridization.

BACKGROUND/AIMS: A comprehensive profile of genes expressed at the mRNA level (transcriptome) in human liver tissue is important for elucidating the pathogenesis and treatment of hepatic diseases. The recent development of cDNA array hybridization allows the parallel monitoring of thousands of genes expressed in a single organ. METHODS: High-density microarrays containing 4043 known and unique human cDNA gene targets were used to quantitatively analyze the expression of genes in human livers. Expressed gene transcripts were classified by function and listed with information of their chromosomal positions. Computational analysis was used to cluster genes according to similarity in pattern of gene expression. RESULTS: A total of 2418 unique gene transcripts were detected in five liver specimens. Through relational database analysis, we determined 1212 genes that were commonly expressed in 4 of the five liver specimens. Furthermore, analysis of the total 2418 expressed genes by self-organizing maps and hierarchical clustering unexpectedly revealed a genomic acute phase response in two of the liver specimens. CONCLUSIONS: These findings represent a comprehensive preliminary molecular index of genes transcribed in the adult human liver. The information may serve as a resource for speeding up the discovery of genes underlying human hepatic diseases.

Adult↗
PubMed2003

Systematic expression profiling of the mouse transcriptome using RIKEN cDNA microarrays.

The number of known mRNA transcripts in the mouse has been greatly expanded by the RIKEN Mouse Gene Encyclopedia project. Validation of their reproducible expression in a tissue is an important contribution to the study of functional genomics. In this report, we determine the expression profile of 57,931 clones on 20 mouse tissues using cDNA microarrays. Of these 57,931 clones, 22,928 clones correspond to the FANTOM2 clone set. The set represents 20,234 transcriptional units (TUs) out of 33,409 TUs in the FANTOM2 set. We identified 7206 separate clones that satisfied stringent criteria for tissue-specific expression. Gene Ontology terms were assigned for these 7206 clones, and the proportion of 'molecular function' ontology for each tissue-specific clone was examined. These data will provide insights into the function of each tissue. Tissue-specific gene expression profiles obtained using our cDNA microarrays were also compared with the data extracted from the GNF Expression Atlas based on Affymetrix microarrays. One major outcome of the RIKEN transcriptome analysis is the identification of numerous nonprotein-coding mRNAs. The expression profile was also used to obtain evidence of expression for putative noncoding RNAs. In addition, 1926 clones (70%) of 2768 clones that were categorized as "unknown EST," and 1969 (58%) clones of 3388 clones that were categorized as "unclassifiable" were also shown to be reproducibly expressed.

Animals↗
PubMed2026

Spatial multiomics in biomedical research: advances beyond transcriptomics.

Coordinated changes in gene expression, epigenetic regulation, protein and metabolic activities together drive disease progression and determine clinical outcomes. While spatially resolved transcriptomics has been widely adopted across biomedical fields, it offers an incomplete picture limited to transcriptomic levels. Here, we survey the latest developments in spatial multiomics technologies, with particular emphasis on platforms that extend beyond conventional transcriptomics and profile genomics, epigenomics, proteomics, or metabolomics within intact tissues. These approaches are rapidly becoming commercialized, and here we highlight major technical breakthroughs, enhanced sample compatibility, emerging applications, and computational tools for data analysis. This Review aims to equip researchers with a clear understanding of the current technological landscape and to accelerate the adoption of spatial multiomics methods in biomedical research.

Humans↗
PubMed2006

Differentially profiling the low-expression transcriptomes of human hepatoma using a novel SSH/microarray approach.

BACKGROUND: The main limitation in performing genome-wide gene-expression profiling is the assay of low-expression genes. Approaches with high throughput and high sensitivity for assaying low-expression transcripts are urgently needed for functional genomic studies. Combination of the suppressive subtractive hybridization (SSH) and cDNA microarray techniques using the subtracted cDNA clones as probes printed on chips has greatly improved the efficiency for fishing out the differentially expressed clones and has been used before. However, it remains tedious and inefficient sequencing works for identifying genes including the great number of redundancy in the subtracted amplicons, and sacrifices the original advantages of high sensitivity of SSH in profiling low-expression transcriptomes. RESULTS: We modified the previous combination of SSH and microarray methods by directly using the subtracted amplicons as targets to hybridize the pre-made cDNA microarrays (named as "SSH/microarray"). mRNA prepared from three pairs of hepatoma and non-hepatoma liver tissues was subjected to the SSH/microarray assays, as well as directly to regular cDNA microarray assays for comparison. As compared to the original SSH and microarray combination assays, the modified SSH/microarray assays allowed for much easier inspection of the subtraction efficiency and identification of genes in the subtracted amplicons without tedious and inefficient sequencing work. On the other hand, 5015 of the 9376 genes originally filtered out by the regular cDNA microarray assays because of low expression became analyzable by the SSH/microarray assays. Moreover, the SSH/microarray assays detected about ten times more (701 vs. 69) HCC differentially expressed genes (at least a two-fold difference and P < 0.01), particularly for those with rare transcripts, than did the regular cDNA microarray assays. The differential expression was validated in 9 randomly selected genes in 18 pairs of hepatoma/non-hepatoma liver tissues using quantitative RT-PCR. The SSH/microarray approaches resulted in identifying many differentially expressed genes implicated in the regulation of cell cycle, cell death, signal transduction and cell morphogenesis, suggesting the involvement of multi-biological processes in hepato-carcinogenesis. CONCLUSION: The modified SSH/microarray approach is a simple but high-sensitive and high-efficient tool for differentially profiling the low-expression transcriptomes. It is most adequate for applying to functional genomic studies.

Carcinoma, Hepatocellular↗
PubMed2026

Effects of rumen fluid transplantation on longissimus dorsi muscle development in Xizang sheep: An association analysis based on transcriptomic and serum metabolomic profiles.

This study aimed to investigate the effects of rumen fluid transplantation (RFT) on the growth and development of the longissimus dorsi muscle in female Xizang sheep. After RFT, muscle lightness differed significantly between the two groups, with the LDC group showing significantly higher lightness than the LDT group. In contrast, no significant differences were observed between groups in other muscle phenotypic traits, including drip loss, pH, cooking loss, shear force, redness, and yellowness. Antioxidant-related indices (SOD, GSH-PX, MDA, CAT, and T-AOC) also showed no significant differences between groups. Histological analysis revealed that muscle fiber length, width, and density were significantly greater in the experimental group than in the control group. Transcriptomic analysis identified 515 differentially expressed genes (DEGs), of which 419 were downregulated. KEGG analysis indicated that genes involved in muscle development-related pathways, such as cell adhesion and the PI3K-Akt signaling pathway, were predominantly downregulated. Key serum metabolites (L-kynurenine, IPA, allantoin, and propionylcarnitine) showed highly significant positive correlations with muscle fiber growth indices. In contrast, metabolites such as l-carnitine, acetylcarnitine, and citrulline were negatively correlated with muscle fiber growth, but positively correlated with the expression of muscle structure-related genes (COL11A1 and EFNA5) and with meat lightness. Overall, this study provides new insights into the potential molecular basis by which RFT influences muscle growth and development. However, the mechanisms by which RFT affects muscle development and meat quality-related traits remain unclear and warrant further investigation.

Animals↗
PubMed2026

Preliminary Exploration on Melatonin-Mediated Protective Effects in Intracranial Aneurysms: Transcriptomic, Proteomic, and Metabolomic Profiling of Cerebral Vascular Tissues Combined with in vivo Animal Experiments.

BACKGROUND: Intracranial aneurysm (IA) is a life-threatening cerebrovascular disease with unclear molecular mechanisms and limited drug treatment. Our previous research has shown that melatonin (MLT) has potential protective effects in IA, but its mechanism remains unclear. The purpose of this study is to explore the pathological mechanism of IA and the therapeutic mechanism of MLT by integrating transcriptomic, proteomic and metabolomic analyses. METHODS: In this study, mouse models of IA were successfully established by combining elastase injection with angiotensin II infusion. C57BL/6 mice were divided into control, IA model, IA model+MLT, and IA model+nimodipine groups. The pathological conditions were evaluated by hematoxylin-eosin (HE) staining, TUNEL staining, and scanning electron microscopy. Transcriptomic (n=3 for each group), proteomic (n=3 for each group), and metabolomic (n=6 for each group) analyses were performed based on cerebral vascular tissue samples. The screening thresholds for differentially expressed genes and differentially expressed proteins were P <0.05 and fold change >1.5 and fold change <0.667. The screening criteria for differential metabolites were variable importance for the projection (VIP)> 1.0, fold change >1.2 and fold change <0.833, and P <0.05. RESULTS: MLT alleviated brain tissue damage, vascular endothelial damage, structural disruption, and apoptosis in IA mice. Transcriptomic, proteomic and metabolomic analyses identified numerous differential molecules. Functional annotation revealed that these molecules may be involved in biological pathways and processes such as immune inflammation, vascular remodeling, extracellular matrix remodeling, neuropeptide activity, oxidative stress and metabolic pathways, thereby regulating the occurrence and development of IA or mediating the therapeutic effects of MLT. Furthermore, transcriptomic and proteomic analyses also suggest that there may be extensive post-transcriptional, translational and post-translational regulatory events in the progression of IA and the therapeutic effects of MLT. Integrated transcriptomic and proteomic analyses suggest that Npy may be a key molecule in regulating IA progression and mediating MLT therapeutic effects, and its potential value is further supported by our immunohistochemical validation results. CONCLUSION: Multi-omics integrative analysis preliminarily revealed that the potential mechanisms of MLT may involve the regulation of inflammatory response, vascular remodeling, extracellular matrix remodeling, neuropeptide activity, oxidative stress, metabolic pathways, and post-transcriptional/translational regulation.

Animals↗
PubMed2005

Effective transcriptome amplification for expression profiling on sense-oriented oligonucleotide microarrays.

Gene expression analysis using microarrays of synthetic long oligonucleotides is limited in that it requires substantial amounts of RNA. To obtain these quantities from minute amounts of starting material, protocols were developed that linearly amplify mRNA by cDNA synthesis and in vitro transcription. Since orientation of the product is antisense (aRNA), it is inapplicable for dye-labelling by reverse transcription and hybridization to sense-oriented oligonucleotide arrays. Here, we introduce a novel protocol in which aRNA labelling is achieved by a combination of two reverse and one forward transcription reactions followed by dye-incorporation using Klenow fragment, generating fluorescent antisense cDNA. We demonstrate high fidelity in arrays using up to 10(5)-fold amplification, starting from 2 ng total RNA. The generated data are highly reproducible and maintain relative gene expression levels between samples. These results demonstrate that our protocol describes an efficient and reliable technique to expand the applicability of oligonucleotide arrays to studies where RNA is the limited source material.

DNA, Antisense↗
PubMed2004

Adipose tissue transcriptome by serial analysis of gene expression.

OBJECTIVE: To describe the genomic expression profile or transcriptome of adipose tissue using the serial analysis of gene expression method. RESEARCH METHODS AND PROCEDURES: The serial analysis of gene expression strategy is based on isolation of short sequences (tags), which usually correspond to unique transcripts, and on their concatenation into long DNA molecules, which are then cloned and sequenced. Experiments were performed with mRNA from retroperitoneal adipose tissue of male C57BL6 mice. RESULTS: We isolated 45,996 tags corresponding to more than 17,000 different genes. Eighty-eight genes were expressed at more than 0.1% of the total population and represented 26% of the mRNA population identified. The most expressed genes were: carbonic anhydrase 3 (1.97%), cytochrome c oxidase (COX) 1 (1.47%), COX2 (1.25%), diazepam binding inhibitor (1.04%), a novel transcript (0.87%), COX3 (0.55%), fatty acid-binding protein 4 (0.55%), and NADH dehydrogenase 4 (0.52%). Other genes known to be expressed in adipose tissue, such as uncoupling protein 2, angiotensinogen, adipsin, and insulin-like growth factor 1, were found at a lower level. Several tags corresponding to novel transcripts were also found. DISCUSSION: To our knowledge, the present results provide for the first time a quantitative description of the transcriptome in adipose tissue.

Adipose Tissue↗
PubMed2006

Transcriptomes of human prostate cells.

BACKGROUND: The gene expression profiles of most human tissues have been studied by determining the transcriptome of whole tissue homogenates. Due to the solid composition of tissues it is difficult to study the transcriptomes of individual cell types that compose a tissue. To overcome the problem of heterogeneity we have developed a method to isolate individual cell types from whole tissue that are a source of RNA suitable for transcriptome profiling. RESULTS: Using monoclonal antibodies specific for basal (integrin beta4), luminal secretory (dipeptidyl peptidase IV), stromal fibromuscular (integrin alpha 1), and endothelial (PECAM-1) cells, respectively, we separated the cell types of the prostate with magnetic cell sorting (MACS). Gene expression of MACS-sorted cell populations was assessed with Affymetrix GeneChips. Analysis of the data provided insight into gene expression patterns at the level of individual cell populations in the prostate. CONCLUSION: In this study, we have determined the transcriptome profile of a solid tissue at the level of individual cell types. Our data will be useful for studying prostate development and cancer progression in the context of single cell populations within the organ.

Bone Morphogenetic Proteins↗
PubMed2004

Salivary transcriptome diagnostics for oral cancer detection.

PURPOSE: Oral fluid (saliva) meets the demand for noninvasive, accessible, and highly efficient diagnostic medium. Recent discovery that a large panel of human RNA can be reliably detected in saliva gives rise to a novel clinical approach, salivary transcriptome diagnostics. The purpose of this study is to evaluate the diagnostic value of this new approach by using oral squamous cell carcinoma (OSCC) as the proof-of-principle disease. EXPERIMENTAL DESIGN: Unstimulated saliva was collected from patients (n = 32) with primary T1/T2 OSCC and normal subjects (n = 32) with matched age, gender, and smoking history. RNA isolation was done from the saliva supernatant, followed by two-round linear amplification with T7 RNA polymerase. Human Genome U133A microarrays were applied for profiling human salivary transcriptome. The different gene expression patterns were analyzed by combining a t test comparison and a fold-change analysis on 10 matched cancer patients and controls. Quantitative polymerase chain reaction (qPCR) was used to validate the selected genes that showed significant difference (P < 0.01) by microarray. The predictive power of these salivary mRNA biomarkers was analyzed by receiver operating characteristic curve and classification models. RESULTS: Microarray analysis showed there are 1,679 genes exhibited significantly different expression level in saliva between cancer patients and controls (P < 0.05). Seven cancer-related mRNA biomarkers that exhibited at least a 3.5-fold elevation in OSCC saliva (P < 0.01) were consistently validated by qPCR on saliva samples from OSCC patients (n = 32) and controls (n = 32). These potential salivary RNA biomarkers are transcripts of IL8, IL1B, DUSP1, HA3, OAZ1, S100P, and SAT. The combinations of these biomarkers yielded sensitivity (91%) and specificity (91%) in distinguishing OSCC from the controls. CONCLUSIONS: The utility of salivary transcriptome diagnostics is successfully demonstrated in this study for oral cancer detection. This novel clinical approach could be exploited to a robust, high-throughput, and reproducible tool for early cancer detection. Salivary transcriptome profiling can be applied to evaluate its usefulness for other major disease applications as well as for normal health surveillance.

Biomarkers, Tumor↗
PubMed2026

Stage-specific ROMO1 in rheumatoid arthritis: predictive immune insights into the MIF pathway and HLA-DR/IL2RA axis via integrated GWAS, transcriptomic, single-cell, and spatial profiling.

Emerging evidence links reactive oxygen species modulator 1 (ROMO1), a key mitochondrial ROS regulator, to rheumatoid arthritis (RA) pathogenesis. However, its exact mechanism remains elusive given the conflicting evidence about its specific function. We used a four-level integrative framework combining multi-omics data and literature&#x2011;supported mechanistic inference. At the genetic level, Mendelian randomization (MR) was performed to explore potential causal relationships between ROMO1, IL2RA, HLA-DR, MIF, and RA risk, followed by differential expression analysis and machine learning-based feature selection to identify key mROS genes. The temporal expression dynamics of ROMO1 were assessed in RA progression. At the cellular and tissue levels, we integrated single-cell RNA sequencing and spatial transcriptomics to map cell-type-specific expression and synovial localization of ROMO1-related immune cells and pathways. Finally, our multi-omics findings were contextualized with literature-supported mechanistic inference. (1) MR results were consistent with a potential protective effect of ROMO1 on RA (OR&#x2009;=&#x2009;0.52) and its potential regulation of risk factors IL2RA (OR&#x2009;=&#x2009;0.46) and HLA-DR (OR&#x2009;=&#x2009;0.40). Conversely, IL2RA (OR&#x2009;=&#x2009;1.42), HLA-DR (OR&#x2009;=&#x2009;1.88), and MIF (OR&#x2009;=&#x2009;1.17) were positively associated with RA risk. Additionally, ROMO1 was identified as a top candidate diagnostic predictor with stage-specific dynamics: downregulated in the early but upregulated in the late/remission stages. (2) Single-cell RNA sequencing showed ROMO1's cell-specific expression in CD14+&#x2009;HLA-DR+&#x2009;CD74+&#x2009;monocytes and CD4+&#x2009;IL2RA+&#x2009;T cells. Cell communication analysis further suggested that these cells may participate in MIF pathway regulation. Spatial transcriptomics subsequently identified that ROMO1-related cells localized to synovial pathological regions, with MIF pathway changes correlated with RA progression. (3) Finally, literature-supported mechanistic inference suggests that ROMO1 may modulate mROS levels to promote anti-inflammatory M2 macrophage polarization, which could theoretically contribute to reduced systemic inflammation and the alleviation of multi-organ decline in RA. This integrated multi-omics investigation, supported by literature-based mechanistic inference, suggests ROMO1 as a stage-dependent biomarker candidate and potential immune regulator in RA.

Humans↗
PubMed2000

Expression profile viewer (ExProView): a software tool for transcriptome analysis.

A software tool, Expression Profile Viewer (ExProView), for analysis of gene expression profiles derived from expressed sequence tags (ESTs) and SAGE (serial analysis of gene expression) is presented. The software visualizes a complete set of classified transcript data in a two-dimensional array of dots, a "virtual chip," in which each dot represents a known gene as characterized in the transcript databases Expressed Gene Anatomy Database or UniGene. The virtual chip display can be changed between representations of different conceptual systems for gene/protein classification and grouping. Four alternative projections are currently available: (i) cellular role, (ii) subcellular compartment, (iii) chromosome localization, and (iv) total UniGene display. However, the chip can be adapted to any other desired layout. By selecting dots, further information about the represented genes is obtained from the local database and WWW links. The software thus provides a visualization of global mRNA expression at the descriptive level and guides in the exploration of patterns of functional expression, while maintaining direct access to detailed information on each individual gene. To evaluate the software, public EST and SAGE gene expression data obtained from the Cancer Genome Anatomy Project at the National Center for Biotechnology Information were analyzed and visualized. A demonstration of the software is available at http://www.biochem.kth. se/exproview/.

Data Display↗