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PubMed2005

Analysis of the growth phase-associated transcriptome of Streptococcus pyogenes.

Streptococcus pyogenes (group A streptococci, GAS) is a human pathogen which probably varies its multiplication rate and thus, growth phases in association with the type of infection caused in its host. To create a basis for future determinations of such associations, the genome-wide growth phase-related GAS transcriptome was assessed in the present study. Therefore, the published serotype M1 S. pyogenes genome sequence as well as the partially sequenced serotype M18 and M49 GAS genomes were used to produce DNA microarrays that carried 2256 oligonucleotide probes matching 3662 open reading frames (ORFs). With these microarrays, the transcriptome of the serotype M49 GAS strain 591 grown to the exponential, transition, and early stationary growth phases was assessed in seven independent experiments. The gained data were compared to real-time RT-PCR assays. Data analysis was refined by a novel approach, i.e. grouping of expressed genes to four classes according to relative transcript abundance and gene functions. At the different growth phases, 86.7%, 79.5% and 55.7% of the at least 1883 ORFs contained in the serotype M49 genome were expressed above the defined detection level. Contrary to the general trend, transcript amounts of genes in the functional groups of transport and membrane proteins as well as stress response factors peaked at the transition phase. The most prominent changes in the transcript abundances were predominantly observed for sugar compound transport and turnover-related ORFs. The majority of known virulence genes had their maximum expression during the transition phase, consistent with the proposed associated change in virulence behavior of the bacteria. With these results, it will now be feasible to assess the in situ growth phase of a given GAS strain during any type of infection by measuring the expression of selected marker genes.

DNA, Bacterial↗

PubMed2026

BCL11B enhancer hijacking by t(14;16)(q32;q24) translocation defines a novel high-risk subtype of T-ALL.

The molecular classification of T-cell acute lymphoblastic leukemia (T-ALL) remains incomplete, limiting risk stratification and the development of targeted therapies. Enhancer hijacking is a critical oncogenic mechanism that deregulates proto-oncogenes by repositioning cisregulatory regions via structural variants. Here, we performed an integrated analysis of pediatric and adult T-ALL and mixed-phenotype acute leukemias (MPALs), using whole-genome and whole-transcriptome sequencing. This analysis identified a group of 14 patients with predominantly T-lineage neoplasms driven by a t(14;16)(q32;q24) translocation, harboring universal GATA3 mutations and CDKN2A/B deletions. Mechanistically, this translocation repositions the ThymoD locus downstream of BCL11B, causing monoallelic, ectopic overexpression of FENDRR and mesenchymal transcription factor genes FOXF1 and FOXC2 and activating epithelial-mesenchymal transition transcription signatures. Immunophenotypic and single-cell RNA sequencing analyses revealed marked lineage ambiguity with myeloid and B-cell differentiation potentials specific to this subtype. Furthermore, functional analyses in CD34+ cord blood cells demonstrated that FOXF1 overexpression promotes myeloid differentiation while suppressing T-cell differentiation, serving as a key factor for lineage specification. Clinically, this subtype was detected in 0.15% to 4.0% of T-ALL/MPAL cases depending on the cohort, showing a median age of 15 years and enrichment in adolescents and young adults. Importantly, patients with t(14;16)(q32;q24) have an extremely poor prognosis, showing a trend toward worse outcomes than high-risk groups such as KMT2A-rearranged early T-cell progenitor-like, SPI1-rearranged, and LMO2 γδ-like T-ALLs. The unique molecular landscape and poor prognosis of patients with the t(14;16)(q32;q24) translocation underscore the need for the development of novel subtype-specific therapeutic approaches.

Humans↗

PubMed2026

From transcriptomic profiling to precision oncology: a bibliometric analysis of RNA sequencing in acute myeloid leukemia.

BACKGROUND: RNA sequencing (RNA-seq) has become an important tool for investigating the molecular heterogeneity of acute myeloid leukemia (AML); however, the global development and thematic evolution of this field remain inadequately characterized. OBJECTIVE: To map the global landscape of AML RNA-seq research and identify major knowledge domains, emerging themes, and temporal changes in research priorities. METHODS: Publications indexed in the Web of Science Core Collection and Scopus between January 1, 2007, and August 18, 2025, were retrieved. After database filtering, merging, and deduplication, 3,460 articles and reviews were included. CiteSpace, VOSviewer, the bibliometrix R package, and Microsoft Excel were used to analyze publication trends, collaboration networks, co-citation structures, keyword evolution, and citation bursts. RESULTS: Publication output increased steadily, accelerating after 2014. China contributed the largest number of publications (n = 547, 15.8%), whereas the United States had the highest total citation count. Major publication outlets spanned hematology, oncology, genomics, and molecular biology. Co-citation analysis identified prominent themes involving next-generation sequencing, gene mutations, KMT2A rearrangements, epigenetic dysregulation, leukemia-initiating cells, drug resistance, biomarkers, T-cell biology, and single-cell sequencing. Earlier literature emphasized sequencing technologies, gene expression profiling, and molecular alterations, whereas recent publications show increasing representation of cellular heterogeneity, single-cell transcriptomics, drug resistance, biomarker applications, immune-related research, and computational interpretation. CONCLUSION: While molecular characterization remains foundational, AML RNA-seq research has broadened to encompass increasingly prominent cellular, functional, computational, and translational dimensions. This study provides a structured overview of the field; nevertheless, bibliometric prominence should not be interpreted as direct evidence of clinical utility.

RNA sequencing↗

PubMed2004

Proteome analysis reveals disease-associated marker proteins to differentiate RA patients from other inflammatory joint diseases with the potential to monitor anti-TNFalpha therapy.

New experimental approaches of molecular medicine such as transcriptome and proteome analysis have been implemented in rheumatology research. Two-dimensional gel electrophoresis in combination with mass spectrometry was used to visualize and to identify proteins in synovial fluid (SF) and plasma samples from patients with rheumatoid arthritis (RA) and osteoarthritis (OA). The small calcium binding protein S100A9 (MRP14) was identified as a discriminatory marker protein in SF by global proteomic analysis. To confirm these results and to examine the reproducibility and the applicability as a diagnostic marker, levels of the S100A8 (MRP8)/A9 (MRP14) heterocomplex in plasma and in synovial fluid were validated from patients with RA, OA, and other inflammatory joint diseases using enzyme immunoassay techniques. It was found that plasma levels of the S100A8/A9 heterocomplex correlate well with levels in SF, and hence, determination of plasma levels can be used to distinguish RA patients from patients with other inflammatory joint diseases, as well as from OA patients and controls. Initial studies on RA patients also indicate that plasma levels of the S100A8/A9 heterocomplex are a useful marker in monitoring anti TNFalpha therapy.

ATP-Binding Cassette Transporters↗

PubMed2026

REACTOR: REgulon Activity analysis and Comparison Tool for single-cell transcriptOmics Research.

SUMMARY: We introduce REACTOR, a computational tool designed to detect differential activity of transcriptional regulators and their target genes (regulons) in single-cell RNA-sequencing data. It expands the currently available framework for regulon analysis by introducing a robust statistical test to detect differential regulon activity between conditions, such as disease versus control, with multiple replicates. By contrasting different conditions, REACTOR enables identification of key condition- and cell type-specific regulons. To demonstrate the use of REACTOR, we illustrate its performance in a publicly available COVID-19 dataset. AVAILABILITY: REACTOR R-package together with an implementation vignette are available at https://www.github.com/elolab/REACTOR.

Regulon↗

PubMed2005

[Development of the new tumor markers].

Serum tumor markers are invasive diagnostic tools for malignant tumors and have been commonly used for purposes of screening, prognosis and selection of treatments. In order to develop a new marker, gene expression analysis technologies such as DNA microarray, differential display, cDNA subtraction, and serial analysis of gene expression, which enable investigators to obtain comprehensive data with respect to gene-expression profiles, are progressing rapidly. Several studies have already demonstrated the usefulness of these techniques for identifying novel cancer-related genes and for classifying human cancers at the molecular level. However, significant differences between the abundance ratio of the mRNA transcript and the corresponding protein product are observed for many genes. Also, the protein level in serum is affected by many physiological conditions and related circumstances, not only by mRNA levels in the cell. Therefore, quantitative proteomics technology based on high-resolution two-dimensional gel electrophoresis and mass spectrometric analysis is being developed. One of our goals is the serological evaluation for the new candidate proteins derived from the information of the above transcriptome and/or proteome analysis as a tumor marker. In this report, I will discuss the practical process of the investigation with special regards to a new protein named ALCAN which has been studied through cDNA cloning, preparation of recombinant protein and monoclonal antibodies, construction of immune assay system, and clinical evaluation.

Biomarkers, Tumor↗

PubMed2005

Microarray and bioinformatic detection of novel and established genes expressed in experimental anti-Thy1 nephritis.

BACKGROUND: Microarray technology is a powerful tool that can probe the molecular pathogenesis of renal injury. In this present study microarray analysis was used to monitor serial changes in the renal transcriptome of a rat model of mesangial proliferative glomerulonephritis. Administration of anti-Thy1 antibody results in phases of acute mesangial injury (day 2), cell proliferation (day 5), matrix expansion (days 5 and 7), and subsequent healing (day 14). METHODS: Using Affymetrix (RAE230A) microarrays coupled with sequential primary biologic function-focused and secondary "baited" global cluster analysis, a cohort of established and putative novel modulators of mesangial cell turnover was identified. RESULTS: Cluster analysis of proliferative genes identified a number of gene expression profiles. The most striking pattern was increased gene expression at day 5, a cluster that included platelet-derived growth factor (PDGF), cyclins and transforming growth factor-beta (TGF-beta). The gene expression patterns identified by primary focused cluster analysis were used as bioinformatic bait and resulted in the identification of novel families of genes such as the S100 family. The expression of established and novel genes was confirmed using reverse transcription-polymerase chain reaction (RT-PCR). Next, in vivo gene expression was compared to PDGF-stimulated mesangial cells in vitro revealing similar patterns of dysregulation. CONCLUSION: Transcriptomic analysis defined both known and novel molecules involved in mesangial cell proliferation in vitro and in vivo and defined a panel of molecules that are potential contributors to mesangial cell dysfunction in glomerular disease.

Animals↗

PubMed2002

Reproducibility of oligonucleotide microarray transcriptome analyses. An interlaboratory comparison using chemostat cultures of Saccharomyces cerevisiae.

Assessment of reproducibility of DNA-microarray analysis from published data sets is complicated by the use of different microbial strains, cultivation techniques, and analytical procedures. Because intra- and interlaboratory reproducibility is highly relevant for application of DNA-microarray analysis in functional genomics and metabolic engineering, we designed a set of experiments to specifically address this issue. Saccharomyces cerevisiae CEN.PK113-7D was grown under defined conditions in glucose-limited chemostats, followed by transcriptome analysis with Affymetrix GeneChip arrays. In each of the laboratories, three independent replicate cultures were grown aerobically as well as anaerobically. Although variations introduced by in vitro handling steps were small and unbiased, greater variation from replicate cultures underscored that, to obtain reliable information, experimental replication is essential. Under aerobic conditions, 86% of the most highly expressed yeast genes showed an average intralaboratory coefficient of variation of 0.23. This is significantly lower than previously reported for shake-flask-culture transcriptome analyses and probably reflects the strict control of growth conditions in chemostats. Using the triplicate data sets and appropriate statistical analysis, the change calls from anaerobic versus aerobic comparisons yielded an over 95% agreement between the laboratories for transcripts that changed by over 2-fold, leaving only a small fraction of genes that exhibited laboratory bias.

Aerobiosis↗

PubMed2026

Characterization of carbon metabolism in a highly adhesive bacterium Acinetobacter sp. Tol 5 capable of assimilating diverse hydrocarbons and aromatic compounds.

Sustainable bioproduction requires developing robust microbial chassis with broad metabolic versatility and suitability for industrial applications. Acinetobacter sp. Tol 5 is a highly adhesive bacterium capable of utilizing various hydrocarbons, making it a promising chassis candidate for immobilized whole-cell catalysis. In this study, we characterized the carbon metabolism of Tol 5 by reconstructing metabolic pathway maps from its genomic data and analyzing the transcriptomes of cells grown on ethanol, hexadecane, toluene, and phenol. Genomic analysis revealed that Tol 5 has limited capacity for sugar utilization but possesses a wide range of metabolic pathways for alkane and aromatic compounds, including five distinct aromatic degradation routes that expand the known metabolic diversity of the genus Acinetobacter. Transcriptome analysis identified the specific pathway genes induced in response to each carbon source. During growth on phenol, alkylbenzene degradation genes were upregulated alongside phenol monooxygenase genes, suggesting possible substrate-dependent cross-regulation between aromatic degradation pathways. Gene disruption experiments indicated that phenol monooxygenase is required for phenol assimilation, whereas toluene dioxygenase may contribute to earlier entry into exponential growth while potentially limiting final biomass accumulation. These findings provide a comprehensive view of the carbon metabolism of Tol 5 and a basis for assessing its potential in bioprocesses using non-sugar carbon sources.

Acinetobacter↗

PubMed2006

Regional copy number-independent deregulation of transcription in cancer.

Genetic and epigenetic alterations have been identified that lead to transcriptional deregulation in cancers. Genetic mechanisms may affect single genes or regions containing several neighboring genes, as has been shown for DNA copy number changes. It was recently reported that epigenetic suppression of gene expression can also extend to a whole region; this is known as long-range epigenetic silencing. Various techniques are available for identifying regional genetic alterations, but no large-scale analysis has yet been carried out to obtain an overview of regional epigenetic alterations. We carried out an exhaustive search for regions susceptible to such mechanisms using a combination of transcriptome correlation map analysis and array CGH data for a series of bladder carcinomas. We validated one candidate region experimentally, demonstrating histone methylation leading to the loss of expression of neighboring genes without DNA methylation.

Cell Line, Tumor↗

PubMed2004

Analysis of differentially expressed parasite genes and proteins using transcriptomics and proteomics.

At any particular point in time, the full complement of transcribed RNAs and relevant proteins of a cell are known as the transcriptome and proteome, respectively. The composition of these two populations changes throughout the life cycle of a parasite or in response to environmental factors, such as drug treatments. Comparing the changes in the composition of the transcriptome and proteome between different life-cycle stages or in the same stage but under different conditions can be of particular interest, as it can allow the identification of potentially important differentially expressed genes and proteins. Combining the analysis of both the transcriptome and proteome in tandem allows changes in RNA transcripts to be followed right through to changes in the level of protein expression. The protocols in this chapter describe methods for analyzing the transcriptome, by using suppression subtraction hybridization to construct subtracted complementary DNA libraries, and the proteome, by using two-dimensional sodium dodecyl sulfate-polyacrylamide gel electrophoresis. These two methods are then integrated to allow the global changes in RNA and protein expression to be examined. The protocols have been adapted for working on parasites and contain extensive notes.

Animals↗

PubMed2025

Dynamic allelic expression in mouse mammary glands across the adult developmental cycle.

The mammary gland, which primarily develops postnatally, undergoes significant changes during pregnancy and lactation to facilitate milk production. Through the generation and analysis of 480 transcriptomes, we provide the most detailed allelic expression map of the mammary gland, cataloguing cell-type-specific expression from ex-vivo purified cell populations over 10 developmental stages, enabling comparative analysis. The work identifies genes involved in the mammary gland cycle, parental-origin-specific and genetic background-specific expression at cellular and temporal resolution, genes associated with human lactation disorders and breast cancer. Genomic imprinting, a mechanism regulating gene expression based on parental origin, is crucial for controlling gene dosage and stem cell potential throughout development. The analysis identified 25 imprinted genes monoallelically expressed in the mammary gland, with several showing allele-specific expression in distinct cell types. No novel imprinted genes were identified and the absence of biallelically expressed imprinted genes suggests that, unlike in brain, selective absence of imprinting does not regulate gene dosage in the mammary gland. This research highlights transcriptional dynamics within mammary gland cells and identifies novel candidate genes potentially significant in the tissue during pregnancy and lactation. Overall, this comprehensive atlas represents a valuable resource for future studies on expression and transcriptional dynamics in mammary cells.

Animals↗

PubMed2006

Transcriptomic response to differentiation induction.

BACKGROUND: Microarrays used for gene expression studies yield large amounts of data. The processing of such data typically leads to lists of differentially-regulated genes. A common terminal data analysis step is to map pathways of potentially interrelated genes. METHODS: We applied a transcriptomics analysis tool to elucidate the underlying pathways of leukocyte maturation at the genomic level in an established cellular model of leukemia by examining time-course data in two subclones of U-937 cells. Leukemias such as Acute Promyelocytic Leukemia (APL) are characterized by a block in the hematopoietic stem cell maturation program at a point when expansion of clones which should be destined to mature into terminally-differentiated effector cells get locked into endless proliferation with few cells reaching maturation. Treatment with retinoic acid, depending on the precise genomic abnormality, often releases the responsible promyelocytes from this blockade but clinically can yield adverse sequellae in terms of potentially lethal side effects, referred to as retinoic acid syndrome. RESULTS: Briefly, the list of genes for temporal patterns of expression was pasted into the ABCC GRID Promoter TFSite Comparison Page website tool and the outputs for each pattern were examined for possible coordinated regulation by shared regelems (regulatory elements). We found it informative to use this novel web tool for identifying, on a genomic scale, genes regulated by drug treatment. CONCLUSION: Improvement is needed in understanding the nature of the mutations responsible for controlling the maturation process and how these genes regulate downstream effects if there is to be better targeting of chemical interventions. Expanded implementation of the techniques and results reported here may better direct future efforts to improve treatment for diseases not restricted to APL.

Cell Differentiation↗

PubMed2006

Transcriptome analyses of male germ cells with serial analysis of gene expression (SAGE).

Serial analysis of gene expression (SAGE) provides an alternative with additional advantages to microarrays for studying gene expression during spermatogenesis. The digitized transcriptome provided by SAGE of purified mouse germ cells identified 27,504 species of transcripts expressed in type A spermatogonia, pachytene spermatocytes, and round spermatids. Over 2700 of these transcripts were novel. Computational analyses allowed the identification of clusters of co-regulated genes, cell-specific promoter modules, cell-specific biological processes, as well as "preferential" biological networks in different cell types. These analyses provided potential drug targets for interference of specific pathways at different stages of spermatogenesis. Analyses of the transcriptomes revealed the prominent role of cytochrome c oxidase in germ cells and suggest a novel role for this enzyme in cytochrome c-mediated apoptosis in spermatogonia. A number of genes were shown to undergo differential splicing during spermatogenesis giving rise to cell-specific splice variants.

Alternative Splicing↗

PubMed2004

Analysis of the root nodule-enhanced transcriptome in soybean.

For high throughput screening of root nodule-enhanced genes, cDNA libraries specific for three different developmental stages of soybean root nodules were constructed after inoculation with Bradyrhizobium japonicum USDA110. 5,469 cDNA clones were sequenced and grouped into 2,511 non-redundant (nr) ESTs consisting of 769 contigs and 1,742 singletons. Using similarity searches against several public databases we constructed a functional classification of the ESTs into root nodule-specific nodulin genes, stress-responsive genes and genes related to carbon and nitrogen metabolism. We also constructed a cDNA microarray with 382 selected clones that appeared to be up-regulated in the root nodule. Using the microarray we compared the transcript levels of uninfected roots and root nodules from four developmental stages. We identified 81 genes that were differentially expressed, and grouped them into seven clusters according to the similarity of their expression profiles, using a hierarchical clustering algorithm. Clusters 1, 2, 3, and 6, comprised of 58 genes, showed root nodule-enhanced expression. The information from this study will be used to analyze the roles of root nodule-specific genes and signaling pathways during root nodule development.

Databases, Nucleic Acid↗

PubMed2005

Metabolic and transcriptomic adaptation of Lactococcus lactis subsp. lactis Biovar diacetylactis in response to autoacidification and temperature downshift in skim milk.

For the first time, a combined genome-wide transcriptome and metabolic analysis was performed with a dairy Lactococcus lactis subsp. lactis biovar diacetylactis strain under dynamic conditions similar to the conditions encountered during the cheese-making process. A culture was grown in skim milk in an anaerobic environment without pH regulation and with a controlled temperature downshift. Fermentation kinetics, as well as central metabolism enzyme activities, were determined throughout the culture. Based on the enzymatic analysis, a type of glycolytic control was postulated, which was shared by most of the enzymes during the growth phase; in particular, the phosphofructokinase and some enzymes of the phosphoglycerate pathway during the postacidification phase were implicated. These conclusions were reinforced by whole-genome transcriptomic data. First, limited enzyme activities relative to the carbon flux were measured for most of the glycolytic enzymes; second, transcripts and enzyme activities exhibited similar changes during the culture; and third, genes involved in alternative metabolic pathways derived from some glycolytic metabolites were induced just upstream of the postulated glycolytic bottlenecks, as a consequence of accumulation of these metabolites. Other transcriptional responses to autoacidification and a decrease in temperature were induced at the end of the growth phase and were partially maintained during the stationary phase. If specific responses to acid and cold stresses were identified, this exhaustive analysis also enabled induction of unexpected pathways to be shown.

Acclimatization↗

PubMed2002

A partial transcriptome of human epidermis.

Serial analysis of gene expression (SAGE) is a powerful technique for global expression profiling without prior knowledge of the genes of interest. We carried out SAGE analysis of purified keratinocytes derived from human skin biopsy specimens, resulting in a partial transcriptome of human epidermis. We identified 7645 unique SAGE tags with quantitative information from 15,131 collected SAGE tags obtained from approximately 3 x 10(6) epidermal cells. This catalog contains a large number of genes that were not previously known to be expressed by human epidermis. Comparison with the databases of all known human SAGE tags allowed us to identify a number of keratinocyte-specific tags that putatively correspond to formerly unknown genes. Surprisingly, human epidermal keratinocytes in vivo show relatively low expression levels of genes typically associated with epidermal differentiation, whereas the expression levels of housekeeping genes are considerably higher than in cultured keratinocytes. This study provides a first step toward a transcriptome of human epidermis and, as such, harbors a wealth of information to identify genes involved in skin function, and candidate genes for genetic skin disorders.

Base Sequence↗

PubMed2006

Analysis of the root-hair morphogenesis transcriptome reveals the molecular identity of six genes with roles in root-hair development in Arabidopsis.

Root-hair morphogenesis is a model for studying the genetic regulation of plant cell development, and double-mutant analyses have revealed a complex genetic network underlying the development of this type of cell. Therefore, to increase knowledge of gene expression in root hairs and to identify new genes involved in root-hair morphogenesis, the transcriptomes of the root-hair differentiation zone of wild-type (WT) plants and a tip-growth defective root-hair mutant, rhd2-1, were compared using Affymetrix ATH1 GeneChips. A set of 606 genes with significantly greater expression in WT plants defines the 'root-hair morphogenesis transcriptome'. Compared with the whole genome, this set is highly enriched in genes known to be involved in root-hair morphogenesis. The additional gene families and functional groups enriched in the root-hair morphogenesis transcriptome are cell wall enzymes, hydroxyproline-rich glycoproteins (extensins) and arabinogalactan proteins, peroxidases, receptor-like kinases and proteins with predicted glycosylphosphatidylinositol (GPI) anchors. To discover new root-hair genes, 159 T-DNA insertion lines identified from the root-hair morphogenesis transcriptome were screened for defects in root-hair morphogenesis. This identified knockout mutations in six genes (RHM1-RHM6) that affected root-hair morphogenesis and that had not previously been identified at the molecular level: At2g03720 (similar to Escherichia coli universal stress protein); At3g54870 (armadillo-repeat containing kinesin-related protein); At4g18640 (leucine-rich repeat receptor-like kinase subfamily VI); At4g26690 (glycerophosphoryl diester phosphodiesterase-like GPI-anchored protein); At5g49270 (COBL9 GPI-anchored protein) and At5g65090 (inositol-1,4,5 triphosphate 5-phosphatase-like protein). The mutants were transcript null, their root-hair phenotypes were characterized and complementation testing with uncloned root-hair genes was performed. The results suggest a role for GPI-anchored proteins and lipid rafts in root-hair tip growth because two of these genes (At4g26690 and At5g49270) encode predicted GPI-anchored proteins likely to be associated with lipid rafts, and several other genes previously shown to be required for root-hair development also encode proteins associated with sterol-rich lipid rafts.

Arabidopsis↗