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PubMed2003

Gene for gene alignment between the Brassica and Arabidopsis genomes by direct transcriptome mapping.

We report a global gene for gene alignment of the genomes of Brassica oleracea and Arabidopsis thaliana by construction of a transcriptome map based on B. oleracea cDNAs obtained from leaf tissue. cDNAs were synthesized from total RNA extracted from individual F2s of a mapping population resulting from crossing double-haploids of broccoli and cauliflower. The map consisted of 247 cDNA markers obtained by the SRAP technique. After sequencing 190 of the polymorphic cDNA bands, FASTA detected 169 sequences with similarity to genes reported in Arabidopsis. There was extensive colinearity between the two genomes for chromosomal segments rather than for whole chromosomes, often showing inversions and deletions/insertions. Large-scale duplications were observed in the B. oleracea genome, but were unevenly distributed, arguing against ancient triplication of the entire genome. The most duplicated segments corresponded to those found on Arabidopsis chromosomes 1 and 5, whereas chromosomes 2 and 4 were the least represented in Brassica. Clear differences in the similarity score value of related sequences allowed the identification of orthologs. Transcriptome mapping is an efficient approach that allows gene-for-gene alignment between a fully sequenced and a poorly characterized genome.

Arabidopsis↗

PubMed2004

Towards a transcriptome definition of microglial cells.

This study provides an expression signature of interferon-gamma (IFN-gamma)-activated microglia. Microglia are macrophage precursor cells residing in the brain and spinal cord. The microglial phenotype is highly plastic and changes in response to numerous pathological stimuli. IFN-gamma has been established as a strong immunological activator of microglial cells both in vitro and in vivo. Affymetrix RG_U34A microarrays were used to determine the effect of IFN-gamma stimulation on migroglia cells isolated from newborn Lewis rat brains. More than 8,000 gene sequences were examined, i.e., 7,000 known genes and 1,000 expressed sequence tag (EST) clusters. Under baseline conditions, microglia expressed 326 of 8,000 genes examined (approximately 4% of all genes, 182 known and 144 ESTs). Transcription of only 34 of 7,000 known genes and 8 of 1,000 ESTs was induced by IFN-gamma stimulation. The majority of the newly expressed genes encode pro-inflammatory cytokines and components of the MHC-mediated antigen presentation pathway. The expression of 60 of 182 identified genes and of 9 of 144 ESTs was increased by IFN-gamma, whereas 29 of 182 known genes and 7 of 144 ESTs were down-regulated or undetectable in IFN-gamma-stimulated cultures. Overall, the activating effect of IFN-gamma on the microglial transcriptome showed restriction to pathways involved in antigen presentation, protein degradation, actin binding, cell adhesion, apoptosis, and cell signaling. In comparison, down-regulatory effects of IFN-gamma stimulation appeared to be confined to pathways of growth regulation, remodeling of the extracellular matrix, lipid metabolism, and lysosomal processing. In addition, transcriptomic profiling revealed previously unknown microglial genes that were de novo expressed, such as calponin 3, or indicated differential regulatory responses, such as down-regulation of cathepsins that are up-regulated in response to other microglia stimulators.

Animals↗

PubMed2006

Transcriptome analysis reveals link between proteasomal and mitochondrial pathways in Parkinson's disease.

There is growing evidence that dysfunction of the mitochondrial respiratory chain and failure of the cellular protein degradation machinery, specifically the ubiquitin-proteasome system, play an important role in the pathogenesis of Parkinson's disease. We now show that the corresponding pathways of these two systems are linked at the transcriptomic level in Parkinsonian substantia nigra. We examined gene expression in medial and lateral substantia nigra (SN) as well as in frontal cortex using whole genome DNA oligonucleotide microarrays. In this study, we use a hypothesis-driven approach in analysing microarray data to describe the expression of mitochondrial and ubiquitin-proteasomal system (UPS) genes in Parkinson's disease (PD). Although a number of genes showed up-regulation, we found an overall decrease in expression affecting the majority of mitochondrial and UPS sequences. The down-regulated genes include genes that encode subunits of complex I and the Parkinson's-disease-linked UCHL1. The observed changes in expression were very similar for both medial and lateral SN and also affected the PD cerebral cortex. As revealed by "gene shaving" clustering analysis, there was a very significant correlation between the transcriptomic profiles of both systems including in control brains. Therefore, the mitochondria and the proteasome form a higher-order gene regulatory network that is severely perturbed in Parkinson's disease. Our quantitative results also suggest that Parkinson's disease is a disease of more than one cell class, i.e. that it goes beyond the catecholaminergic neuron and involves glia as well.

Brain↗

PubMed2006

Profiling transcriptome complexity and secondary metabolite synthesis in a benthic soft coral, Sinularia polydactyla.

Sinularia polydactyla, an abundant Indo-Pacific soft coral species, exhibits biochemical phenotypic plasticity, prompting investigations into differences in mRNA diversity and complexity in response to predation stress. Changes in transcriptome complexity of S. polydactyla cDNA libraries were measured using reannealing rate assays that employ an informatics-based analysis of kinetic profiles. This method allows for quick, high-throughput analysis of sequence complexity and has been used to compare transcriptome-level differences in other marine invertebrates. Here, S. polydactyla colonies were transplanted between two sites exhibiting high and low predation levels. Statistically significant differences between bite scar counts found on different transplant groups suggest site-specific variation in predation. Changes in mRNA pool complexity were quantified to indicate shifts in secondary metabolite concentration between treatment groups. Examining the complexity of the mRNA pool in this soft coral is one of the first steps toward understanding the mechanisms of phenotypic plasticity at a biochemical and molecular level.

Animals↗

PubMed2004

Bioinformatic analysis of primary endothelial cell gene array data illustrated by the analysis of transcriptome changes in endothelial cells exposed to VEGF-A and PlGF.

We recently published a review in this journal describing the design, hybridisation and basic data processing required to use gene arrays to investigate vascular biology (Evans et al. Angiogenesis 2003; 6: 93-104). Here, we build on this review by describing a set of powerful and robust methods for the analysis and interpretation of gene array data derived from primary vascular cell cultures. First, we describe the evaluation of transcriptome heterogeneity between primary cultures derived from different individuals, and estimation of the false discovery rate introduced by this heterogeneity and by experimental noise. Then, we discuss the appropriate use of Bayesian t-tests, clustering and independent component analysis to mine the data. We illustrate these principles by analysis of a previously unpublished set of gene array data in which human umbilical vein endothelial cells (HUVEC) cultured in either rich or low-serum media were exposed to vascular endothelial growth factor (VEGF)-A165 or placental growth factor (PlGF)-1(131). We have used Affymetrix U95A gene arrays to map the effects of these factors on the HUVEC transcriptome. These experiments followed a paired design and were biologically replicated three times. In addition, one experiment was repeated using serial analysis of gene expression (SAGE). In contrast to some previous studies, we found that VEGF-A and PlGF consistently regulated only small, non-overlapping and culture media-dependant sets of HUVEC transcripts, despite causing significant cell biological changes.

Cells, Cultured↗

PubMed2006

The impact of genomic alterations on the transcriptome: a prostate cancer cell line case study.

Genetic instability may lead to the loss/gain of transcriptional control. Here we investigated the effect of genomic instability, that is loss/gain of chromosomal regions on the global transcriptome of prostate cancer cell line DU145. The genomic loss/gain map obtained through BAC array-based CGH was superimposed on the dynamic transcriptome of DU145 cells treated with serum for 0 h (serum starved), 2 h and 12 h. The genomic analysis suggested that in DU145 cells: (1) chromosomal gains are prominent than losses and (2) copy number changes are associated with chromosome-specific and dynamic gene expression regulatory mechanisms. A significant proportion of the genes in the stable regions of the chromosome were up-regulated whereas a higher proportion of genes were down-regulated at 2 and 12 h in the deleted regions of the chromosomes following serum treatment. No change in expression was observed for the genes in the gained regions over a period of time. This analysis led us to propose that loss of heterozygosity leads to an overall transcriptional down-regulation that may further lead to a decrease in the expression of putative tumor suppressors. The genomic profile of DU145 is similar to pathological specimens of prostate cancer, hence the genomic/transcriptomic signature of DU145 can be used to understand the pathology of prostate cancer. It is expected that this analysis will allow a better understanding of transcriptional regulatory mechanisms in the context of genomic loss and gain and may lead to the discovery of novel oncogenes and tumor suppressors and the underlying regulatory pathways.

Cell Line, Tumor↗

PubMed2004

Arabidopsis whole-transcriptome profiling defines the features of coordinated regulations that occur during secondary growth.

Secondary growth in the inflorescence stems of Arabidopsis plants was induced by a combination of short-day and long-day treatments. The induced stems were divided into three different stem developmental stages (i.e., immature, intermediate, and mature) with regard to secondary growth. Whole transcriptome microarrays were used to examine the changes in global gene expression occurring at the different stem developmental stages. Over 70% of the Arabidopsis transcriptome was expressed in the stem tissues. In the mature stems with secondary growth, 567 genes were upregulated 5-fold or higher and 530 were downregulated, when compared to immature stems (with no secondary growth) and 10-day old seedlings (with no inflorescence stem). The transcription phenotypes obtained from the stems at different developmental stages largely confirm the existing insights into the biochemical processes involved in the sequential events that lead to wood formation. The major difference found between the stems undergoing secondary growth and only primary growth was in the expression profiles of transcriptional regulation-and signal transduction-related genes. An analysis of several shoot apical meristem (SAM) activity-related gene expression patterns in the stems indicated that the genetic control of secondary meristem activity might be governed by a different mechanism from that of SAM. The current study established the expression patterns of many unknown genes and identified candidate genes that are involved in the genetic regulation of secondary growth. The findings described in this report should improve our understanding of the molecular mechanisms that regulate the growth and development of the stem.

Apoptosis↗

PubMed2025

Transcriptomic landscape of NK cell-related genes in hepatocellular carcinoma: associations with prognosis and therapeutic response.

Hepatocellular carcinoma (HCC) is a highly aggressive and heterogeneous malignancy, in which natural killer (NK) cells play a crucial role in tumor progression and immune surveillance. This study aimed to characterize the transcriptomic landscape of NK cell-associated genes (NAGs) and explore their associations with clinical outcomes and therapeutic responses in HCC. Using transcriptomic data from The Cancer Genome Atlas (TCGA), we identified key NAGs through comprehensive statistical analyses. Patients were stratified into distinct risk groups based on NAG expression profiles. Low-risk patients demonstrated better survival, higher immune infiltration, and greater predicted sensitivity to immunotherapy, whereas high-risk patients were associated with reduced chemotherapy responsiveness. These findings contribute to a deeper understanding of the immunogenomic features of HCC and provide a basis for developing personalized therapeutic approaches centered on NK cell-related mechanisms.

Hepatocellular carcinoma↗

PubMed2005

Transcriptomic fingerprinting of bone marrow-derived hepatic beta2m-/Thy-1+ stem cells.

The aim of the present study was to determine if the bone marrow (BM) beta2m-/Thy-1+ stem cells isolated from common bile duct ligated (CBDL) rats possess hepatocyte-like characteristics in their global gene expression profiles. The Affymetrix RG U34A arrays were used to conduct transcriptomic profiling on BM beta2m-/Thy-1+ stem cells isolated from CBDL and control rats as well as primary hepatocytes. Forty-one probe sets were up-regulated more than 2-fold in CBDL-derived beta2m-/Thy-1+ BM stem cells compared to control BM stem cells. Twenty-seven probe sets were present in both CBDL-derived beta2m-/Thy-1+ BM stem cells and control hepatocytes but absent in control beta2m-/Thy-1+ BM stem cells, including Tcf1 and Dbp. Compared to the control beta2m-/Thy-1+ BM stem cells, CBDL-derived beta2m-/Thy-1+ BM stem cells shared more commonly expressed genes with hepatocytes. Overall, CBDL-derived beta2m-/Thy-1+ stem cells displayed a different transcriptomic fingerprint compared with beta2m-/Thy-1+ BM stem cells isolated from control rats; and CBDL-derived beta2m-/Thy-1+ stem cells started to express some hepatocyte-like genes.

Animals↗

PubMed2006

Human equilibrative nucleoside transporter-1 (hENT1) is required for the transcriptomic response of the nucleoside-derived drug 5'-DFUR in breast cancer MCF7 cells.

Nucleoside analogues are broadly used in cancer treatment. Although nucleoside metabolism is a necessary step in the development of their cytotoxicity, mediated transport across the plasma membrane might be needed for nucleoside-derived drugs to exert their pharmacological action. In this study, we have addressed the question of whether particular plasma membrane transporters contribute to the transcriptomic response associated with nucleoside-derived drug therapy. Firstly, we have characterized the nucleoside transporters responsible for 5'-DFUR uptake into the breast cancer cell line MCF7. 5'-DFUR is the immediate precursor of 5-FU and a metabolite of the orally administered pro-drug capecitabine, currently used in the treatment of breast cancer and other solid tumors. Although 5'-DFUR is a substrate for both plasma membrane equilibrative nucleoside carriers, hENT1 shows higher affinity for this molecule than hENT2. Inhibition of hENT1 function partially protected MCF7 cells from 5'-DFUR-induced cytotoxicity. Secondly, we have used a pharmacogenomic approach to determine how inhibition of hENT1 function contributes to the transcriptomic response associated to 5'-DFUR treatment. Under hENT1 inhibition most of the transcriptional targets of 5'-DFUR action, which were genes associated with apoptosis and cell cycle progression were blocked. This study demonstrates that although 5'-DFUR is substrate for both equilibrative nucleoside carriers, hENT1 function is essential for the full transcriptional response to 5'-DFUR treatment.

Antimetabolites, Antineoplastic↗

PubMed2026

Integrated transcriptomic analysis of mRNA and miRNA in Brown adipose tissue of the greater horseshoe bats during hibernation.

Hibernation enables animals survive harsh environments by conserving energy through reduced metabolism and body temperature. Brown adipose tissue (BAT) plays a critical role in non-shivering thermogenesis, crucial for warming up during arousal phase. The greater horseshoe bats (Rhinolophus nippon) are typical hibernators and non-shivering thermogenesis in BAT tissue may persist throughout the arousal process in bats. This study examines gene expression and regulatory changes in BAT of these bats across active, hibernation, and arousal phases using transcriptome and miRNA sequencing. A total of 2721 differentially expressed mRNAs and 268 differentially expressed miRNAs were identified. The results reveal that the BAT transcriptome undergoes state-dependent remodeling throughout the hibernation process. The most pronounced divergence occurs between the active phase and torpor, involving cell cycle arrest, immunosuppression, thermogenic signal desensitization, and upregulation of lipid metabolism and autophagy pathways, reflecting the coordinated adaptation of energy conservation and thermogenic reserve. In contrast, transcriptional alterations between torpor and arousal are extremely limited, indicating that torpid BAT is already pre-primed for thermogenesis and requires only modest transcriptional adjustments to activate heat production. Notably, although body temperature recovers to active-phase levels during arousal, the molecular signature of BAT remains highly similar to that of the torpid state. Furthermore, the core thermogenic gene UCP1 showed no significant expression differences across the three groups. In conclusion, this study systematically delineates the miRNA-mRNA regulatory landscape of bat BAT across the hibernation process, and deepens our understanding of the thermoregulatory mechanisms underlying mammalian hibernation.

BAT↗

PubMed2006

Neuronal transcriptome of Aplysia: neuronal compartments and circuitry.

Molecular analyses of Aplysia, a well-established model organism for cellular and systems neural science, have been seriously handicapped by a lack of adequate genomic information. By sequencing cDNA libraries from the central nervous system (CNS), we have identified over 175,000 expressed sequence tags (ESTs), of which 19,814 are unique neuronal gene products and represent 50%-70% of the total Aplysia neuronal transcriptome. We have characterized the transcriptome at three levels: (1) the central nervous system, (2) the elementary components of a simple behavior: the gill-withdrawal reflex-by analyzing sensory, motor, and serotonergic modulatory neurons, and (3) processes of individual neurons. In addition to increasing the amount of available gene sequences of Aplysia by two orders of magnitude, this collection represents the largest database available for any member of the Lophotrochozoa and therefore provides additional insights into evolutionary strategies used by this highly successful diversified lineage, one of the three proposed superclades of bilateral animals.

Animals↗

PubMed2004

The operons, a criterion to compare the reliability of transcriptome analysis tools: ICA is more reliable than ANOVA, PLS and PCA.

The number of statistical tools used to analyze transcriptome data is continuously increasing and no one, definitive method has so far emerged. There is a need for comparison and a number of different approaches has been taken to evaluate the effectiveness of the different statistical tools available for microarray analyses. In this paper, we describe a simple and efficient protocol to compare the reliability of different statistical tools available for microarray analyses. It exploits the fact that genes within an operon exhibit the same expression patterns. In order to compare the tools, the genes are ranked according to the most relevant criterion for each tool; for each tool we look at the number of different operons represented within the first twenty genes detected. We then look at the size of the interval within which we find the most significant genes belonging to each operon in question. This allows us to define and estimate the sensitivity and accuracy of each statistical tool. We have compared four statistical tools using Bacillus subtilis expression data: the analysis of variance (ANOVA), the principal component analysis (PCA), the independent component analysis (ICA) and the partial least square regression (PLS). Our results show ICA to be the most sensitive and accurate of the tools tested. In this article, we have used the protocol to compare statistical tools applied to the analysis of differential gene expression. However, it can also be applied without modification to compare the statistical tools developed for other types of transcriptome analyses, like the study of gene co-expression.

Bacillus subtilis↗

PubMed2003

Interplay of transcriptomics and proteomics.

Despite the obvious attractions of parallel profiling of transcripts and proteins on a global 'omic' scale, there are practical and biological differences involved in their application. Transcriptomics is now a robust, high-throughput, cost-effective technology capable of simultaneously quantifying tens of thousands of defined mRNA species in a miniaturized, automated format. Conversely, proteomic analysis is currently much more limited in breadth and depth of coverage owing to variations in protein abundance, hydrophobicity, stability, size and charge. Nevertheless, transcriptomic and proteomic data can be compared and contrasted provided the studies are carefully designed and interpreted. Differential splicing, post-translational modifications and data integration are among some of the future challenges to tackle.

Biotechnology↗

PubMedDate not supplied

Zipf's law and human transcriptomes: an explanation with an evolutionary model.

Detailed analysis of human gene expression data reveals several patterns of relationship between transcript frequency and abundance rank. In muscle and liver, organs composed primarily of a homogeneous population of differentiated cells, they obey Zipf's law. In cell lines, epithelial tissue and compiled transcriptome data, only high-rankers deviate from it. We propose an evolutionary process model during which expression level changes stochastically proportionally to its intensity, providing a novel interpretation of transcriptome data and of evolutionary constraints on gene expression.

Evolution, Molecular↗

PubMed2006

Transcriptome shock after interspecific hybridization in senecio is ameliorated by genome duplication.

Allopolyploidy, which involves genome doubling of an interspecific hybrid is an important mechanism of abrupt speciation in flowering plants [1-6]. Recent studies show that allopolyploid formation is accompanied by extensive changes to patterns of parental gene expression ("transcriptome shock") [7-15] and that this is likely the consequence of interspecific hybridization rather than polyploidization [16]. To investigate the relative impacts of hybridization and polyploidization on transcription, we compared floral gene expression in allohexaploid Senecio cambrensis with that in its parent species, S. vulgaris (tetraploid) and S. squalidus (diploid), and their triploid F1 hybrid, S. x baxteri [17]. Major changes to parental gene expression were associated principally with S. x baxteri, suggesting that the polyploidization event responsible for the formation of S. cambrensis had a widespread calming effect on altered gene expression arising from hybridization [17]. To test this hypothesis, we analyzed floral gene expression in resynthesized lines of S. cambrensis and show that, for many genes, the "transcriptome shock" observed in S. x baxteri is calmed ("ameliorated") after genome doubling in the first generation of synthetic S. cambrensis and this altered expression pattern is maintained in subsequent generations. These findings indicate that hybridization and polyploidization have immediate yet distinct effects on large-scale patterns of gene expression.

Gene Duplication↗

PubMed2005

Specific effects of microRNAs on the plant transcriptome.

Most plant microRNAs (miRNAs) have perfect or near-perfect complementarity with their targets. This is consistent with their primary mode of action being cleavage of target mRNAs, similar to that induced by perfectly complementary small interfering RNAs (siRNAs). However, there are natural targets with up to five mismatches. Furthermore, artificial siRNAs can have substantial effects on so-called off-targets, to which they have only limited complementarity. By analyzing the transcriptome of plants overexpressing different miRNAs, we have deduced a set of empirical parameters for target recognition. Compared to artificial siRNAs, authentic plant miRNAs appear to have much higher specificity, which may reflect their coevolution with the remainder of the transcriptome. We also demonstrate that miR172, previously thought to act primarily by translational repression, can efficiently guide mRNA cleavage, although the effects on steady-state levels of target transcripts are obscured by strong feedback regulation. This finding unifies the view of plant miRNA action.

Base Pairing↗

PubMed2026

Linking MRI radiomics to transcriptomics-based radiosensitivity in lower-grade glioma: A radiogenomic framework.

BACKGROUND: RSI is a transcriptomics-based biomarker associated with radiotherapy outcomes, but its clinical application is constrained by the requirement for tumor tissue and RNA sequencing. This study investigates whether MRI-derived radiomic features can reflect RSI-defined intrinsic radiosensitivity in lower-grade glioma.This addresses a critical gap arising from the limited availability of matched imaging and genomic data in routine clinical practice. METHODS: MRI-derived radiomic features were extracted from FLAIR images of lower-grade glioma patients obtained from TCIA and matched with transcriptomic data from TCGA. A total of 107 patients with both MRI and RNA sequencing data were included in the radiogenomic analysis. Radiomic features were ranked using a Borda-based ensemble feature selection strategy. Five supervised machine-learning classifiers were trained to predict RSI-based radiosensitivity classification, and model interpretability was assessed using SHAP within radiogenomic framework. RESULTS: Classification performance increased with feature number and stabilized at compact subset of 13 radiomic features. Logistic regression showed stable performance with an AUC of 0.82 (95 % CI: 0.71-0.93). SHAP analysis indicated that heterogeneity-related texture features were dominant contributors to model predictions, with many associated with the RR phenotype, while others were linked to the RS phenotype. CONCLUSION: An MRI-based radiomic signature enables non-invasive prediction of RSI-defined radiosensitivity in lower-grade glioma. Rather than offering an immediately deployable clinical tool, this study establishes a proof-of-concept radiogenomic framework demonstrating that intrinsic radiosensitivity, traditionally assessed through invasive molecular assays, can be approximated using quantitative imaging features. These findings highlight the potential of imaging-based radiosensitivity assessment and provide a foundation for future radiogenomic investigations.

Lower-grade glioma↗