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At least 1,333 records · Page 74Linked to original sources
PubMed2006

A comprehensive SAGE database for the analysis of gammadelta T cells.

Gammadelta T cells have been conserved since the adaptive immune system arose, yet their importance is still unclear. In an attempt to compensate for the lack of a broad knowledge base of gammadelta T cells across species, global analyses of gammadelta T cell transcriptomes have been performed using serial analysis of gene expression (SAGE). Twelve new SAGE libraries were generated from the following bovine lymphocyte populations: magnetic bead-sorted blood gammadelta T cells, spleen gammadelta T cells and enriched spleen alphabeta T cells from a single calf, both rested and Con A/IL2 stimulated, and flow cytometry-sorted blood gammadelta and alphabeta T cells each either rested, Con A/IL2, or phorbol 12 myristate 13-acetate/ionomycin stimulated. These new libraries complement two earlier SAGE libraries of circulating gammadelta T cell subsets. These databases were analyzed using new web-based bioinformatic tools, which allow the user to rapidly compare gene expression patterns within these and other SAGE and standard expressed sequence tag libraries generated from different cell types and different species. These analyses revealed striking differences between blood and spleen gammadelta T cells and how these cells respond to mitogenic stimulation. These analyses also confirm previous studies that suggested that global gene expression in gammadelta and alphabeta T cells is quite similar; however, a 5-fold increase in gammadelta T cell-specific transcripts could be induced by Con A/IL2 stimulation. These new public databases provide additional resources for the annotation/analysis of global gene expression in gammadelta T cells, which will facilitate studies of the biology of this enigmatic lymphoid cell.

Animals↗
PubMed2003

The genetic architecture of odor-guided behavior in Drosophila: epistasis and the transcriptome.

We combined transcriptional profiling and quantitative genetic analysis to elucidate the genetic architecture of olfactory behavior in Drosophila melanogaster. We applied whole-genome expression analysis to five coisogenic smell-impaired (smi) mutant lines and their control. We used analysis of variance to partition variation in transcript abundance between males and females and between smi genotypes and to determine the genotype-by-sex interaction. A total of 666 genes showed sexual dimorphism in transcript abundance, and 530 genes were coregulated in response to one or more smi mutations, showing considerable epistasis at the level of the transcriptome in response to single mutations. Quantitative complementation tests of mutations at these coregulated genes with the smi mutations showed that in most cases (67%) epistatic interactions for olfactory behavior mirrored epistasis at the level of transcription, thus identifying new candidate genes regulating olfactory behavior.

Animals↗
PubMed2026

Integrative TWAS and multi-omics analyses prioritize HSPE1 as a candidate risk gene for bipolar disorder with immune cell-specific regulatory evidence.

BACKGROUND: Bipolar disorder (BD) is a severe psychiatric disorder associated with substantial disability. Although genome-wide association studies have identified multiple BD-associated loci, the underlying genes and mechanisms remain incompletely understood. METHODS: We integrated a European-ancestry BD genome-wide association dataset with cross-tissue and tissue-specific transcriptome-wide association studies (TWAS) and complementary gene-based analysis. Candidate genes were further evaluated using differential expression analysis, consensus clustering, immune infiltration analysis, machine learning, summary-data-based Mendelian randomization, Mendelian randomization using single-cell expression quantitative trait locus data, single-nucleus transcriptomics, phenome-wide association analysis, and virtual screening. RESULTS: The integrative analyses prioritized 37 candidate genes. Peripheral-blood differential-expression analysis identified 14 genes that remained significant after FDR correction, and their expression profiles separated BD samples into two expression-defined clusters. Machine-learning analysis selected UNC50, LMAN2L, LYG2, HSPE1, and KANSL3 for an exploratory classification nomogram. SMR associated genetically predicted higher HSPE1 expression with increased BD risk in two blood eQTL datasets. Cell-type-specific analyses indicated HSPE1-related associations in T-cell and natural killer cell subsets, while single-nucleus analysis descriptively showed higher HSPE1 expression in medial thalamic T cells from BD samples. PheWAS identified no genome-wide significant associations for HSPE1, whereas virtual screening identified candidate compounds with favorable predicted docking scores against the HSPE1 structure. CONCLUSION: This integrative multi-omics study identified HSPE1 as a candidate BD risk gene with immune-cell-related regulatory evidence, providing insight into BD pathogenesis and supporting functional validation.

Humans↗
PubMed2000

Operomics: molecular analysis of tissues from DNA to RNA to protein.

The identification of coding sequences in a number of species, including human in the near future, has ushered in the post-genome era. In this era, technologies are becoming available that allow the profiling of tissues and cell populations at the genomic, transcriptomic and proteomic levels. The molecular analysis of tissues at all three levels has been referred to as operomics. This review covers some basic technologies for operomics and their application to some lymphoid disorders. It is proposed that no one type of analysis is fully informative and that information that can be derived from the different compartments encompassed in operomics is complementary. Prospects for introducing such profiling technologies into the clinical laboratory will depend on their robustness, their user friendliness and the clinical relevance of the added information they provide, which cannot be captured through other technologies in use in the clinical laboratory.

Genomics↗
PubMed2002

Transcriptomics in predictive toxicology.

Once again, genomics is about to change drug development. Following its major impact on target discovery and assay development, which increased the number of compounds at early stages of the process, genomics is now zeroing in on the prediction of potential toxicological problems of compounds. Toxicogenomics is the analysis of toxicological processes at the transcriptome level of a target organ or cell. By simultaneously monitoring the effect of a compound on the transcription levels of hundreds to thousands of genes, toxicogenomics can provide an enormous amount of data. This data bears information on the way in which compounds act at the molecular level, reaching far beyond the mere conclusion of whether or not a particular toxicological outcome is elicited. By compiling transcription profiles for well-known toxicants, we are beginning to learn how to analyze this novel type of data in the context of mechanistic and predictive toxicology.

Animals↗
PubMed2005

Genomic technologies and the interrogation of the transcriptome.

Functional genomics refers to the study of whole genomes and the function of its constituent parts to explain biological processes. Though these investigations may involve whole proteome analysis, the primary focus is on the transcriptome and how it is regulated. Recent advances in technologies that can interrogate cellular transcripts on a genome-wide scale seek the complete disclosure of the transcriptome over time-intervals and across many different cellular states. This massively complex data when viewed as a whole can provide surprisingly precise assessment of cellular conditions. Moreover, these data can define hierarchies of importance and have shown us new transcriptional elements. Herein, we describe the technologies and the experimental strategies to study the transcriptome that would be pertinent to cancer and ageing research.

Animals↗
PubMed2025

Next-generation sequencing in breast cancer: current clinical applications and future directions.

INTRODUCTION: Breast cancer is a heterogeneous disease that claims 670,000 lives by 2022. Omic technologies, particularly next generation sequencing (NGS) offers promising avenues for precision medicine. American Society of Clinical Oncology (ASCO) outlines genomic testing's utility, emphasizing prognostic and diagnostic potential. OBJECTIVES: This review succinctly explores NGS's evolution and clinical applications of NGS in breast cancer, thereby guiding future research to enhance patient care. METHODS: Comprehensive literature searches were conducted using databases such as PubMed, Google Scholar, and ResearchGate, focusing on keywords including breast cancer, HER-2 low breast cancer, circulating tumour DNA, single-cell RNA sequencing, and next-generation sequencing. Peer-reviewed, high-quality articles published in English were selected for inclusion. RESULTS: Previous studies have explored the evolution of NGS technology and its clinical applications in breast cancer, including genomic and transcriptomic characterization, treatment guidance, and resistance prediction. Molecular profiling of challenging entities such as early-onset breast cancer and HER-2 low tumours was summarized, with key findings highlighted. This review also discusses emerging technologies, including circulating DNA and single-cell sequencing, as promising avenues for discovery. CONCLUSION: NGS has revealed the genomic and transcriptomic diversity of breast cancer, identifying actionable alterations associated with chemotherapy response and resistance to therapies such as trastuzumab, TKIs, and CDK4/6 inhibitors. Circulating tumour DNA (ctDNA) shows potential for diagnosis, prediction, prognosis, and monitoring, despite tumour heterogeneity. Single-cell analysis enables exploration of individual cell transcriptomes, though high costs and low throughput remain barriers to widespread adoption. HER2-low tumours continue to pose significant research challenges.

Humans↗
PubMed2026

Cerium dioxide nanoparticle exposure attenuates mobility-linked antibiotic resistome signatures across the soil-lettuce continuum.

Antibiotic resistance genes (ARGs) are contaminants of emerging concern in agricultural microbiomes. Their association with mobile genetic elements (MGEs) can enhance dissemination across soil-plant interfaces, creating potential environmental and food-chain exposure risks. However, how engineered nanoparticles modulate relative ARG abundance and mobility-linked resistome features in plant-associated microbiomes remains poorly understood. Here, we examined the effects of graded, experimentally elevated cerium dioxide nanoparticle (CeO2 NP) loadings in a soil-lettuce system by integrating compartment-resolved metagenomics, ARG-MGE co-occurrence analysis, putative host-reservoir profiling, transcriptomics, and functional assays. Metagenomic profiling identified 16 ARG types and 125 subtypes and revealed niche-dependent microbiome restructuring under CeO2 NP exposure. Rhizosphere relative ARG abundance showed a negative dose-associated trend, although overall inter-group differences were not significant, whereas leaf endophytes showed a weaker response. Relative MGE abundance decreased significantly in both compartments, and lower assembly-level ARG-MGE co-occurrence reflected fewer ARGs detected in MGE-associated genomic contexts, whereas fewer multi-ARG contigs suggested reduced ARG clustering and potential co-selection. Putative host-reservoir analysis associated key efflux determinants with bacterial families whose relative representation declined following CeO2 NP exposure. Transcriptomic profiling of representative putative ARG hosts revealed host-specific responses, including downregulation of genes involved in central metabolism and Sec-dependent trafficking. Complementary host assays showed reduced apparent envelope permeability and lower recovery of tetracycline-resistant recipient-identity colonies in the plasmid-associated host system. Together, under the tested elevated-loading conditions, CeO2 NP exposure was associated with lower relative ARG signals and weaker mobility-linked resistome features across the soil-lettuce continuum, providing mechanistic insight into nanoparticle-resistome interactions in soil-plant systems.

ARG dissemination↗
PubMed2006

Systems biology approaches identify ATF3 as a negative regulator of Toll-like receptor 4.

The innate immune system is absolutely required for host defence, but, uncontrolled, it leads to inflammatory disease. This control is mediated, in part, by cytokines that are secreted by macrophages. Immune regulation is extraordinarily complex, and can be best investigated with systems approaches (that is, using computational tools to predict regulatory networks arising from global, high-throughput data sets). Here we use cluster analysis of a comprehensive set of transcriptomic data derived from Toll-like receptor (TLR)-activated macrophages to identify a prominent group of genes that appear to be regulated by activating transcription factor 3 (ATF3), a member of the CREB/ATF family of transcription factors. Network analysis predicted that ATF3 is part of a transcriptional complex that also contains members of the nuclear factor (NF)-kappaB family of transcription factors. Promoter analysis of the putative ATF3-regulated gene cluster demonstrated an over-representation of closely apposed ATF3 and NF-kappaB binding sites, which was verified by chromatin immunoprecipitation and hybridization to a DNA microarray. This cluster included important cytokines such as interleukin (IL)-6 and IL-12b. ATF3 and Rel (a component of NF-kappaB) were shown to bind to the regulatory regions of these genes upon macrophage activation. A kinetic model of Il6 and Il12b messenger RNA expression as a function of ATF3 and NF-kappaB promoter binding predicted that ATF3 is a negative regulator of Il6 and Il12b transcription, and this hypothesis was validated using Atf3-null mice. ATF3 seems to inhibit Il6 and Il12b transcription by altering chromatin structure, thereby restricting access to transcription factors. Because ATF3 is itself induced by lipopolysaccharide, it seems to regulate TLR-stimulated inflammatory responses as part of a negative-feedback loop.

Activating Transcription Factor 3↗
PubMed2006

Identification of pathogenesis-related ESTs in the crucifer downy mildew oomycete Hyaloperonospora parasitica by high-throughput differential display analysis of distinct phenotypic interactions with Brassica oleracea.

Crucifer downy mildew is caused by the obligatory biotrophic oomycete Hyaloperonospora parasitica (formerly Peronospora parasitica). So far, isolates infecting Arabidopsis thaliana have proven to be non-pathogenic on other crucifers and, despite its unequivocal merit as a research model, the pathosystem A. thaliana-H. parasitica by itself will not provide all the answers onto crucifer downy mildew genetics and biology. In this report, we present the development of a differential display (DD)-based strategy, suitable for high-throughput analysis of expressed sequence tags (ESTs) in plant-pathogen interactions, in this work applied to the analysis of the pathosystem Brassica oleracea-H. parasitica interaction transcriptome. Our purpose was the mining for pathogen-specific ESTs that can be used in future research for virulence factors and Avr genes. A total of 743 specific cDNAs showing differential expression in B. oleracea seedlings infected with H. parasitica, as opposed to healthy seedlings, were isolated by DD-PCR. We found 21 exclusively H. parasitica cDNAs from 433 sequenced DD clones, 18 encoding for potential new genes. Our results reinforce the abilities of DD-PCR for differential screening of pathosystems transcriptomes, leading to the finding of more new potential genes than the previously used techniques. Both the improved DD-based methodology and the graphical representations based on Venn diagrams from polyominoes are appropriate for large-scale analysis of multiple interaction transcriptomes. The obtained data are also innovative since this is the first approach to study the interaction of H. parasitica with its natural host.

Base Sequence↗
PubMed2004

The unique transcriptome through day 3 of human preimplantation development.

Successful human development is dependent upon a cascade of events following fertilization. Unfortunately, knowledge of these critical events in humans is remarkably incomplete. Although hundreds of thousands of human embryos are cultured yearly at infertility centers worldwide, the vast majority fail to develop in culture or following transfer to the uterus. In this study, we sought to characterize global patterns of gene expression in individual, normal embryos during the first three days of embryonic life using microarrays; we then compared gene expression between normally growing and growth-arrested embryos using quantitative PCR. Our results documented several novel findings. First, we found that a complex pattern of gene expression exists; most genes that are transcriptionally modulated during the first three days following fertilization are not upregulated, as was previously thought, but are downregulated. Second, we observed that the majority of genes exhibiting differential expression during preimplantation development are of unknown identity and/or function. Third, we show that embryonic transcriptional programs are clearly established by day 3 following fertilization, even in embryos that arrested prematurely with 2-, 3- or 4-cells. This indicates that failure to activate transcription is not associated with the majority of human preimplantation embryo loss. Finally, taken together, these results provide the first global analysis of the human preimplantation embryo transcriptome, and demonstrate that RNA can be amplified from single oocytes and embryos for analysis by cDNA microarray technology, thus lending credence to additional studies of genetic regulation in these cell types, as well as in other small biological samples.

Blastocyst↗
PubMed2026

RECQL correlates with immune infiltration and serves as a prognostic biomarker and therapeutic predictor in gastric cancer.

BACKGROUND: RecQ-like helicase (RECQL), a member of the RecQ-like DNA helicase family, plays a crucial role in maintaining genomic stability. However, its relevance in gastric cancer (GC) has not been fully investigated. This study aimed to explore the clinical significance, biological functions, and potential role of RECQL in the tumor immune microenvironment of GC through comprehensive bioinformatics analyses and in vitro experiments. METHODS: Weighted gene co-expression network analysis (WGCNA), differential expression analysis, and least absolute shrinkage and selection operator (LASSO) regression were performed using public datasets [The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD), GSE150290] to identify key genes associated with GC progression. Subsequently, key pathways were identified through functional enrichment analysis, while immune infiltration and spatial transcriptomic analyses were conducted to characterize RECQL expression and its association with the tumor immune microenvironment. Finally, the effects of RECQL knockdown on the biological function of GC cells were assessed through Cell Counting Kit-8 (CCK-8), colony formation, scratch, and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assays. RESULTS: RECQL was significantly upregulated in GC tissues and correlated with advanced clinical stage and poor prognosis. Gene set enrichment analysis (GSEA) revealed a strong association between high RECQL expression and DNA repair pathway. Immune infiltration analysis indicated significant enrichment of M2 macrophages in the high-RECQL group, along with upregulation of immune checkpoint molecules including PDCD1, CTLA4, and CD274. Spatial transcriptomics further demonstrated co-localization of RECQL with myeloid cell-enriched regions in tumor parenchymal areas. Furthermore, in vitro experimental results indicated that RECQL was highly expressed in GC cell lines, and its knockdown effectively inhibited the viability, proliferation, and migration capabilities of HGC-27 cells, while enhancing their apoptosis. CONCLUSIONS: RECQL serves as a promising biomarker and potential therapeutic target in GC.

DNA repair↗
PubMed2004

Integrated transcriptome and proteome data: the challenges ahead.

The recent availability of platform technologies for high throughput proteome analysis has led to the emergence of integrated messenger RNA and protein expression data. The Pearson correlation coefficients for these data range from 0.46 to 0.76. In these integrated studies, serial analyses of gene expression and DNA microarrays have been used to quantify the transcriptome, while proteome analysis has been based on two-dimensional gel electrophoresis, isotope coded affinity tags and multidimensional protein identification technology. This paper provides a comprehensive review of the analytical techniques used in these studies and explores the extent to which the choice of experimental methodology can bias the correlation or the ability to detect proteins.

Animals↗
PubMed2004

Reusing microarrays within closely related species: experimental validation through phylogenetic inference.

Microarrays are generally designed for a specific set of organisms, and this poses a limitation for researchers wanting to conduct investigations on gene expression in organisms that are, in some sense, not "popular" enough. In this article, we demonstrate that microarrays may in fact be reusable for aggregate expression analysis for species that are evolutionarily related. Our validation approach is based on this assumption and draws a phylogenetic conclusion that is deemed to be true only if the assumption of reusability is valid. This article demonstrates that microarrays developed using the human transcriptome are reusable for aggregate expression analysis of primates in general.

Animals↗
PubMed2026

Single-cell RNA sequencing provides further insights into the immunostimulatory action of freeze-dried Lactiplantibacillus plantarum on Penaeus vannamei shrimp.

Immunostimulation through dietary interventions opened new avenues in developing disease control and prevention tools for shrimp aquaculture. We have previously shown that feeding with freeze-dried Lactiplantibacillus plantarum (LAB) increased disease resistance of Penaeus vannamei against both Vibrio parahaemolyticus and white spot syndrome virus (WSSV) based on bulk RNA sequencing of shrimp gills. This tissue participates in ion transport and serves as a first line of defense against environmental stressors and pathogenic infections. However, characterization of their cell composition and functions remains limited. Here, we implemented a single-cell RNA sequencing approach to further gather insights into how feeding with freeze-dried LAB modulates host immunity which may not be evident with bulk RNA sequencing approach. A total of five clusters with unique transcriptional signatures were identified, corresponding to pillar cells, septal cells, and sessile hemocytes. Pseudo-bulk analyses at global- and cluster-levels showed differential expression of genes related to host immunity and metabolism. We further revealed how overall transcriptomic changes are not exclusively caused by gene expression changes but may also be driven by cell population dynamics. This study highlighted how single-cell RNA sequencing approach may shed light on the mechanisms of action of immunostimulants which may be masked in bulk transcriptome analyses.

Animals↗
PubMed2005

Genome-wide profiling of stored mRNA in Arabidopsis thaliana seed germination: epigenetic and genetic regulation of transcription in seed.

To reveal the transcriptomes of Arabidopsis seed, comprehensive expression analysis was performed using ATH1 GeneChips (Affymetrix, Santa Clara, CA, USA). In the dry seed, more than 12 000 stored mRNA species were detected, including all ontological categories. Statistical analysis revealed that promoters of highly expressed genes in wild-type dry seeds overrepresented abscisic acid-responsive elements (ABREs) containing the core motif ACGT. Although the coupling element and seed-specific enhancer RY motif alone were not prominently overrepresented in genes with high expression, the presence of these elements in combination with ABRE was associated with particularly high gene expression. The transcriptome of the imbibed seeds differed from that of the dry seed even at 6 h after seed imbibition. After imbibition many upregulated and downregulated genes were co-regulated in clusters of three to five genes. Genes for which expression was affected by the abi5 mutation tended to be located in clusters, suggesting that transactivation by ABI5 is not restricted to a single gene, but affects other proximal genes. Furthermore, cytosine methylation was observed not only in large silent retrotransposon clusters in centromeric regions, but also in non-centromeric silent gene clusters in the seed. These results suggest that such regions might be transcriptionally silenced by methylation or heterochromatin structures. Our analyses reveal that transcriptomes of Arabidopsis seed are characterized by multiple regulatory mechanisms: epigenetic chromatin structures, chromosomal locations (e.g. co-regulated gene clusters) and cis-acting elements.

Arabidopsis↗
PubMed2005

Gene expression profile of activated microglia under conditions associated with dopamine neuronal damage.

Microglia are the resident antigen-presenting cells within the central nervous system (CNS), and they serve immune-like functions in protecting the brain against injury and invading pathogens. By contrast, activated microglia can secrete numerous reactants that damage neurons. The pathogenesis of various neurodegenerative diseases has been associated with microglial activation, but the signaling pathways that program a neuronally protective or destructive phenotype in microglia are not known. To increase the understanding of microglial activation, microarray analysis was used to profile the transcriptome of BV-2 microglial cells after activation. Microglia were activated by lipopolysaccharide, the HIV neurotoxic protein TAT, and dopamine quinone, each of which has been linked to dopamine neuronal damage. We identified 210 of 9882 genes whose expression was differentially regulated by all activators (116 increased and 94 decreased in expression). Gene ontology analysis assigned up-regulated genes to a number of specific biological processes and molecular functions, including immune response, inflammation, and cytokine/chemokine activity. Genes down-regulated in expression contribute to conditions that are permissive of microglial migration, lowered adhesion to matrix, lessened phagocytosis, and reduction in receptors that oppose chemotaxis and inflammation. These results elaborate a broad profile of microglial genes whose expression is altered by conditions associated with both neurodegenerative diseases and microglial activation.

Animals↗
PubMed2006

GO-Diff: mining functional differentiation between EST-based transcriptomes.

BACKGROUND: Large-scale sequencing efforts produced millions of Expressed Sequence Tags (ESTs) collectively representing differentiated biochemical and functional states. Analysis of these EST libraries reveals differential gene expressions, and therefore EST data sets constitute valuable resources for comparative transcriptomics. To translate differentially expressed genes into a better understanding of the underlying biological phenomena, existing microarray analysis approaches usually involve the integration of gene expression with Gene Ontology (GO) databases to derive comparable functional profiles. However, methods are not available yet to process EST-derived transcription maps to enable GO-based global functional profiling for comparative transcriptomics in a high throughput manner. RESULTS: Here we present GO-Diff, a GO-based functional profiling approach towards high throughput EST-based gene expression analysis and comparative transcriptomics. Utilizing holistic gene expression information, the software converts EST frequencies into EST Coverage Ratios of GO Terms. The ratios are then tested for statistical significances to uncover differentially represented GO terms between the compared transcriptomes, and functional differences are thus inferred. We demonstrated the validity and the utility of this software by identifying differentially represented GO terms in three application cases: intra-species comparison; meta-analysis to test a specific hypothesis; inter-species comparison. GO-Diff findings were consistent with previous knowledge and provided new clues for further discoveries. A comprehensive test on the GO-Diff results using series of comparisons between EST libraries of human and mouse tissues showed acceptable levels of consistency: 61% for human-human; 69% for mouse-mouse; 47% for human-mouse. CONCLUSION: GO-Diff is the first software integrating EST profiles with GO knowledge databases to mine functional differentiation between biological systems, e.g. tissues of the same species or the same tissue cross species. With rapid accumulation of EST resources in the public domain and expanding sequencing effort in individual laboratories, GO-Diff is useful as a screening tool before undertaking serious expression studies.

Animals↗