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PubMed2006

Proteome and transcriptome analysis of 5-fluoro-2'-deoxyuridine-induced cell death mechanisms.

5-Fluoro-2'-deoxyuridine (FUdR) inhibits thymidylate synthase. The inhibition of thymidylate synthase causes an imbalance of intracellular deoxyribonucleoside triphosphate (dNTP) pools which subsequently induced cell death. We have been investigated the molecular mechanisms of cell death in mouse mammary tumor FM3A cells, F28-7 strain and its mutant F28-7-A strain, after treated with FUdR. We have previously been reported that F28-7 strain induced DNA cleavage into chromosomal sized fragments and subsequently develop necrosis, but F28-7-A strain induced DNA cleavage into oligonucleosomal sized fragments and subsequently develop apoptosis after treated with FUdR. In this report, in order to understand the molecular mechanisms of regulate of two differential cell death necrosis and apoptosis, we identify cell death regulator by using proteome and transcriptome analysis. When compared with the proteome from F28-7 strain and F28-7-A strain, it was found that ten proteins were increased and six proteins were decreased in F28-7-A strain. Furthermore, transcriptome analysis shows that 127 genes were increased and 181 genes were decreased in F28-7-A strain. These differentially expressed proteins and genes were involved in various cellular processes such as cell cycle regulation, apoptosis, proliferation, and differentiation. These two techniques clarified numerous features in F28-7 strain and F28-7-A strain. Our results revealed that numerous features indicated the coordinated regulation of molecular networks from various aspects of necrosis or apoptosis at the proteome and transcriptome levels.

Animals↗

PubMed2006

Robust analysis of 5'-transcript ends (5'-RATE): a novel technique for transcriptome analysis and genome annotation.

Complicated cloning procedures and the high cost of sequencing have inhibited the wide application of serial analysis of gene expression and massively parallel signature sequencing for genome-wide transcriptome profiling of complex genomes. Here we describe a new method called robust analysis of 5'-transcript ends (5'-RATE) for rapid and cost-effective isolation of long 5' transcript ends (approximately 80 bp). It consists of three major steps including 5'-oligocapping of mRNA, NlaIII tag and ditag generation, and pyrosequencing of NlaIII tags. Complicated steps, such as purification and cloning of concatemers, colony picking and plasmid DNA purification, are eliminated and the conventional Sanger sequencing method is replaced with the newly developed pyrosequencing method. Sequence analysis of a maize 5'-RATE library revealed complex alternative transcription start sites and a 5' poly(A) tail in maize transcripts. Our results demonstrate that 5'-RATE is a simple, fast and cost-effective method for transcriptome analysis and genome annotation of complex genomes.

5' Untranslated Regions↗

PubMed2002

Transcriptome analysis of acetate metabolism in Corynebacterium glutamicum using a newly developed metabolic array.

Following the determination of the whole-genome sequence of Corynebacterium glutamicum, we have developed a DNA array to extensively investigate gene expression and regulation relevant to carbon metabolism. For this purpose, a total of 120 C. glutamicum genes, including those in central metabolism and amino acid biosyntheses, were amplified by PCR and printed onto glass slides. The resulting array, designated a "metabolic array", was used for hybridization with fluorescently labeled cDNA probes generated by reverse transcription from total RNA samples. As the first demonstration of transcriptome analysis in this industrially important microorganism, we applied the metabolic array to study differential transcription profiles between cells grown on glucose and on acetate as the sole carbon source. The changes in gene expression observed for the known acetate-regulated genes (aceA, aceB, pta, and ack) were well consistent with the literature data of northern analyses and enzyme assays, indicating the utility of the metabolic array in transcriptome analysis of C. glutamicum. In addition to the known responses, many previously unrecognized co-regulated genes were identified. For example, several TCA cycle genes, such as gltA, sdhA, sdhB, fumH, and mdh, and the gluconeogenic gene pck were up-regulated in the acetate medium. On the other hand, a few genes involved in glycolysis and the pentose phosphate pathway, as well as many amino acid biosynthetic genes, were down-regulated in acetate. Furthermore, two gap genes, gapA and gapB, were found to be inversely regulated, suggesting the presence of a new regulatory step for carbon metabolism between glycolysis and gluconeogenesis.

Acetates↗

PubMed2026

PotatoRTD and TomatoRTD: Comprehensive Reference Transcript Datasets for Accurate Transcriptome Analysis and Isoform Discovery.

Transcriptome annotations provide essential information on transcript locations, sequences and structures, including transcription start, end sites and splice junctions. They underpin key biological analyses such as gene and transcript quantification, and the study of transcriptional and post-transcriptional regulation, including alternative transcription initiation, polyadenylation and splicing. Accurate characterisation of transcript isoforms is critical for understanding how gene expression relates to functional protein products. However, for many species-including Solanaceae crops such as potato and tomato-current annotations suffer from limited isoform coverage, with tens or hundreds of thousands of splice junctions and transcript isoforms missing. This undermines the completeness and accuracy of transcript-level analyses. Here, by generating Iso-seq and RNA-seq on a range of tissues and samples, we have produced transcriptome annotations for both potato and tomato with improved coverage, diversity, accurate splice junctions, and transcript start and end sites. We have also made these high-quality resources accessible through genome browsers. These enhanced annotations will enable more accurate transcriptome analyses, supporting higher-resolution and novel biological discoveries.

Solanum tuberosum↗

PubMed2002

The Gene Resource Locator: gene locus maps for transcriptome analysis.

Since the advent of the draft human genome sequence there has been growing interest in transcriptome analysis based on genomic data. The Gene Resource Locator (GRL) assembles gene maps that include information on gene-expression patterns, cis-elements in regulatory regions and alternatively spliced transcripts. The database was constructed using customized software, and currently contains 2.2 million alignments (exon-intron structures). The alignments have been annotated and integrated into a system that encompasses approximately 90 000 EST loci sharing common exons, 8091 alternatively spliced transcript groups, 10 801 expression-profile groups, 8066 candidate regulatory regions in full-length cDNAs, and 1 million SNP loci. We have used Flash technology to build a dynamic web viewer that facilitates browsing through the millions of alignments. All of the information is available through the World Wide Web at the Gene Resource Locator web site (http://grl.gi.k.u-tokyo.ac.jp).

Alternative Splicing↗

PubMed2026

An integrated proteomics and transcriptomics analysis highlights concordance between protein turnover and carbohydrate transport and metabolism as key functional categories during the growth of Trichophyton rubrum.

Dermatophytes are a class of keratinophilic skin fungi that invade host skin, hair, and nails to acquire nutrients. An integrated multi-omics approach utilizing liquid chromatography-tandem mass spectrometry and RNA-seq after growth in a protein-rich soy medium was employed to capture the major subset of secreted protein families of Trichophyton rubrum. The secretome consisted mainly of proteases and cell wall-degrading enzymes, with subtilisins (Sub6 and Sub7), metallopeptidase (LAP2), and chitinase having the most abundant peptides. Transcriptional profiling indicated fungal adaptation in protein-rich media to process the protein nutrients through modulation of metabolism and general cellular function pathways. Correlation analysis between proteomics and transcriptomics data using functional KOG categories shows high concordance of KOG categories O (posttranslational modification, protein turnover, and chaperones), P (inorganic ion transport and metabolism), and G (carbohydrate transport and metabolism), as per cosine similarity analysis.IMPORTANCEDermatophytes are keratinophilic skin fungal pathogens that invade host skin, hair, and nails to acquire nutrients. There is an epidemic-like increase in infections, as well as an increase in antimicrobial resistance among dermatophytes, as witnessed over the last decade. There is hence a need to understand the key pathways and virulence factors required during growth and infection. We present an integrated multi-omics analysis (proteomics and transcriptomics data) using a vector-based similarity approach to show high concordance of KOG functional categories belonging to posttranslational modification, protein turnover, carbohydrate transport, and metabolism.

Proteomics↗

PubMed2004

[Transcriptome analysis of virus-infected cells].

Human genome project revealed that human genes are derived from 30,000-40,000 species of genetic loci, which had been estimated as approximately 100,000. The project also promoted devising novel tools that enable us to analyze biological phenomena comprehensively. Microarray technology is a representative of the novel tools in genomics and engages us to explore genome-wide expression levels of genes simultaneously (transcriptome analysis). Here we show transcriptomes obtained from 10 species of cells infected with human cytomegalovirus, as a model virus, by a synthetic DNA microarray system that we have established recently. Our system provides simultaneous and parallel description on alteration of expression of viral and host genes that are represented within a single area on a slide glass. Moreover, we propose a project entitled 'comparative virology on cellular responses of infected hosts' that consists of multiple acquisition and integration of transcriptomes from a combination of several cells and viruses as a panel on the identical platform. The attempt should extract a novel concept in virology from investigation on differences and similarities among influence of a virus on a variety of different cells and conversely among responses of a species of cells against a variety of different viruses.

Cytomegalovirus↗

PubMed2005

Full transcriptome analysis of rhabdomyosarcoma, normal, and fetal skeletal muscle: statistical comparison of multiple SAGE libraries.

Rhabdomyosarcoma (RMS) is the most frequent soft tissue sarcoma in children. Improved treatment strategies have increased overall survival, but the response of approximately one-third of the patients is still poor. To increase the knowledge of RMS pathogenesis, we performed the first full transcriptome analysis of RMS using serial analysis of gene expression (SAGE). With a G-test for the simultaneous comparison of subsets of SAGE libraries of normal skeletal muscle, embryonal (ERMS) and alveolar (ARMS) RMS, we identified 251 differentially expressed genes. A literature-mining procedure demonstrated that 158 of these genes have not previously been associated with RMS or normal muscle. Gene Ontology (GO) analysis assigned 198 of the 251 genes to muscle-specific classes, including those involved in normal myogenic development, as well as tumor-related classes. Prominent GO classes were those associated with proliferation and actin reorganization, which are processes that play roles during early muscle development, muscle function, and tumor progression. Using custom microarrays, we confirmed the (up- or down-) regulation of 80% of 98 differentially expressed genes. Another SAGE library of 19- to 22-week-old fetal skeletal muscle was compared with the RMS and normal muscle transcriptomes. Cluster analysis showed that the RMS and fetal muscle SAGE libraries formed one cluster distinct from normal muscle samples. Moreover, the expression profile of 86% of the differentially expressed genes between normal muscle and RMS was highly similar in fetal muscle and RMS. In conclusion, the G-test is a robust tool for analyzing groups of SAGE libraries and correctly identifies genes marking the difference between fully differentiated skeletal muscle and RMS. This study not only substantiates the close association between embryonic myogenesis and RMS development but also provides a rich source of candidate genes to further elucidate the etiology of RMS or to identify diagnostic and/or prognostic markers.

Cell Adhesion↗

PubMed2005

Transcriptome analysis of zebrafish embryogenesis using microarrays.

Zebrafish (Danio rerio) is a well-recognized model for the study of vertebrate developmental genetics, yet at the same time little is known about the transcriptional events that underlie zebrafish embryogenesis. Here we have employed microarray analysis to study the temporal activity of developmentally regulated genes during zebrafish embryogenesis. Transcriptome analysis at 12 different embryonic time points covering five different developmental stages (maternal, blastula, gastrula, segmentation, and pharyngula) revealed a highly dynamic transcriptional profile. Hierarchical clustering, stage-specific clustering, and algorithms to detect onset and peak of gene expression revealed clearly demarcated transcript clusters with maximum gene activity at distinct developmental stages as well as co-regulated expression of gene groups involved in dedicated functions such as organogenesis. Our study also revealed a previously unidentified cohort of genes that are transcribed prior to the mid-blastula transition, a time point earlier than when the zygotic genome was traditionally thought to become active. Here we provide, for the first time to our knowledge, a comprehensive list of developmentally regulated zebrafish genes and their expression profiles during embryogenesis, including novel information on the temporal expression of several thousand previously uncharacterized genes. The expression data generated from this study are accessible to all interested scientists from our institute resource database (http://giscompute.gis.a-star.edu.sg/~govind/zebrafish/data_download.html).

Journal Article↗

PubMed2006

A transcriptome analysis of isoamyl alcohol-induced filamentation in yeast reveals a novel role for Gre2p as isovaleraldehyde reductase.

A transcriptome analysis was performed of Saccharomyces cerevisiae undergoing isoamyl alcohol-induced filament formation. In the crucial first 5 h of this process, only four mRNA species displayed strong and statistically significant increases in their levels of more than 10-fold. Two of these (YEL071w/DLD3 and YOL151w/GRE2) appear to play important roles in filamentation. The biochemical activities ascribed to these two genes (d-lactate dehydrogenase and methylglyoxal reductase, respectively) displayed similarly timed increases to those of their respective mRNAs. Mutants carrying dld3 mutations displayed reduced filamentation in 0.5% isoamyl alcohol and needed a higher concentration of isoamyl alcohol to effect more complete filament formation. Hence, DLD3 seems to be required for a full response to isoamyl alcohol, but is not absolutely essential for it. Mutants carrying gre2 mutations were derepressed for filament formation and formed large, invasive filaments even in the absence of isoamyl alcohol. These results indicate a previously unsuspected and novel role for the GRE2 gene product as a suppressor of filamentation by virtue of encoding isovaleraldehyde reductase activity.

Aldehydes↗

PubMed2000

[Transcriptome analysis and pharmacogenomics].

Pharmacogenomics is defined as identification of loci which are involved in determining the responsiveness and distinguishing responders and non-responders to a given drug. Genome sequencing, transcriptome and proteome analysis are of particular significance in pharmacogenomics. Sequencing is used to locate polymorphisms, and monitoring of gene expression can provide clues about the genomic response to disease and treatment. The transcriptome analysis can be done by methods of random cDNA sequencing (expressed sequence tag project, body map project, serial analysis of gene expression, etc.), mRNA display (differential display, fluorescent differential display, RNA arbitrary primed PCR, molecular indexing, gene expression fingerprinting, etc.) and differential hybridization (cDNA high density filter, cDNA microarray, oligomicrochip, etc.). We describe the principle and application of trancriptome analysis in pharmacogenomics, especially differential display and cDNA microarray. We used transcriptome analysis to identify therapeutic target genes by studying the change of gene expression in animal models of oxidative stress and hypoxia and found novel drug target candidates through this pharmacogenomic strategy.

Animals↗

PubMed2004

Robust-LongSAGE (RL-SAGE): a substantially improved LongSAGE method for gene discovery and transcriptome analysis.

Serial analysis of gene expression (SAGE) is a widely used technique for large-scale transcriptome analysis in mammalian systems. Recently, a modified version called LongSAGE (S. Saha, A.B. Sparks, C. Rago, V. Akmaev, C.J. Wang, B. Vogelstein, K.W. Kinzler [2002] Nat Biotechnol 20: 508-512) was reported by increasing tag length up to 21 bp. Although the procedures for these two methods are similar, a detailed protocol for LongSAGE library construction has not been reported yet, and several technical difficulties associated with concatemer cloning and purification have not been solved. In this study, we report a substantially improved LongSAGE method called Robust-LongSAGE, which has four major improvements when compared with the previously reported protocols. First, a small amount of mRNA (50 ng) was enough for a library construction. Second, enhancement of cDNA adapter and ditag formation was achieved through an extended ligation period (overnight). Third, only 20 ditag polymerase chain reactions were needed to obtain a complete library (up to 90% reduction compared with the original protocols). Fourth, concatemers were partially digested with NlaIII before cloning into vector (pZEro-1), greatly improving cloning efficiency. The significant contribution of Robust-LongSAGE is that it solved the major technical difficulties, such as low cloning efficiency and small insert sizes associated with existing SAGE and LongSAGE protocols. Using this protocol, one can generate two to three libraries, each containing over 4.5 million tags, within a month. We recently have constructed five libraries from rice (Oryza sativa), one from maize (Zea mays), and one from the rice blast fungus (Magnaporthe grisea).

Base Sequence↗

PubMed2005

Transcriptome analysis of the murine forelimb and hindlimb autopod.

To gain insight into the coordination of gene expression profiles during forelimb and hindlimb differentiation, a transcriptome analysis of mouse embryonic autopod tissues was performed using Affymetrix Murine Gene Chips (MOE-430). Forty-four transcripts with expression differences higher than 2-fold (T test, P < or = 0.05) were detected between forelimb and hindlimb tissues including 38 new transcripts such as Rdh10, Frzb, Tbx18, and Hip that exhibit differential limb expression. A comparison of gene expression profiles in the forelimb, hindlimb, and brain revealed 24 limb-signature genes whose expression was significantly enriched in limb autopod versus brain tissue (fold change >2, P < or = 0.05). Interestingly, the genes exhibiting enrichment in the developing autopod also segregated into significant fore- and hindlimb-specific clusters (P < or = 0.05) suggesting that by E 12.5, unique gene combinations are being used during the differentiation of each autopod type.

Animals↗

PubMed2026

Transcriptomic analysis reveals the molecular mechanisms underlying the inhibition of Mytilus edulis attachment by biofouling control agents.

This study combined acute toxicity assays, phenotypic quantification, and transcriptomic profiling to systematically investigate the inhibitory effects and molecular regulatory mechanisms of a novel alkylamine-based antifouling agent on survival, byssus secretion, and attachment behavior of juvenile Mytilus edulis. The 96 h-LC50 of the agent to juvenile M. edulis was 8.84 mg/L, and 10 mg/L of the agent completely inhibited mussel attachment within 24 h, significantly reducing byssal thread number, length, and diameter while increasing detachment frequency, resulting in irreversible attachment failure. Transcriptomic analysis identified 2746 differentially expressed genes, which were mainly enriched in pathways including signal transduction, immune defense, stress response, cytoskeleton organization, and protein binding. KEGG and GSEA enrichment revealed that the antifouling agent activated the MAPK stress signaling pathway, disturbed transcriptional regulation, and impaired intracellular homeostasis and cytoskeletal stability, thereby synergistically suppressing the expression of key byssal protein genes including mfp-1 and mfp-3 and ultimately blocking byssus synthesis and adhesion. This study clarifies the multi-pathway molecular mechanism underlying antifouling agent-induced attachment inhibition in M. edulis, and provides core molecular targets and theoretical support for developing efficient, specific antifouling activity, and potentially applicable marine antifouling technologies.

Animals↗

PubMed2025

Spatial transcriptomic analysis of mouse parathyroid gland cells expressing an activating variant of Gcm2.

Glial cells missing 2 (GCM2) is an essential transcription factor for the development of parathyroid glands. Germline GCM2 variants that repress or enhance transcriptional activity predispose a subset of patients to hypoparathyroidism or hyperparathyroidism, respectively. A recurrent germline heterozygous activating missense variant of GCM2, p.Y394S has been identified in some patients with primary hyperparathyroidism. A genetically engineered knock-in mouse model of this variant corresponding to p.Y392S in the mouse Gcm2 gene (Gcm2 +/Y392S) did not show obvious parathyroid tumors. However, in GCM2-binding site mediated luciferase reporter assays in HEK293 cells, the mouse and the human variant both exhibited enhanced transcriptional activity. Therefore, we assessed the effect of this variant on gene expression in vivo in parathyroid glands from Gcm2 +/Y392S and WT mice. Using the 10x Genomics Visium platform, spatially resolved transcriptomic analysis was performed on formalin-fixed and paraffin-embedded (FFPE) tracheal tissue sections of Gcm2 +/Y392S and WT mice to capture RNA from parathyroid glands together with other cell types in the tissue sections. Transcriptome sequence data analysis detected 8 different clusters in the tissue sections based on similarity of gene expression profiles. Cluster-1, which contained parathyroid gland cells expressing Pth and Gcm2, was further evaluated for transcripts that were differentially expressed more than 2-fold in Gcm2 +/Y392S compared to WT. Increased transcript level of Lgals3 (galectin-3) was seen in Gcm2 +/Y392S parathyroid gland cells which is among markers of parathyroid carcinoma. Galectin-3 protein was detected in available FFPE human parathyroid samples of patients with germline heterozygous activating GCM2 variants, p.Y394S (n = 4/10) or p.L379Q (n = 2/2). These results indicate a potential for growth and malignancy of parathyroid glands expressing GCM2 variants. The transcriptomic data of mouse parathyroid gland cells generated in this study can serve as a valuable resource for investigating genes and pathways in normal or abnormal parathyroid gland growth and physiology.

GCM2, gene↗

PubMed2026

Transcriptome Analysis, Machine Learning, and Experimental Identification of CDK7 Affecting the Progression of Pregnancy-induced Hypertension by Influencing Macrophage Polarization.

INTRODUCTION: Pregnancy-induced hypertension (PIH) is a severe pregnancy complication characterized by placental insufficiency, abnormal vascular remodeling, and immune dysregulation, but personalized therapeutic markers remain unclear. This study aimed to identify key genes and explore immune mechanisms in PIH using transcriptome analysis, machine learning, and experimental validation. METHODS: We analyzed the GSE204835 transcriptomic dataset to screen differentially expressed genes (DEGs) and performed Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, and Gene Set Enrichment Analysis (GSEA) for functional annotation. Immune infiltration analysis was also performed to examine the immune landscape in PIH. Least Absolute Shrinkage and Selection Operator (LASSO) regression identified key genes, which were validated in a PIH cell model. Flow cytometry and immunofluorescence assays assessed the effect of CDK7 knockdown on macrophage polarization. RESULTS: A total of 1,598 DEGs (1,123 upregulated, 475 downregulated) were identified. Enrichment analyses highlighted associations with embryonic organ development, oxidative phosphorylation, angiogenesis, and oxidative stress. Immune infiltration analysis revealed altered eosinophil and macrophage polarization in PIH. LASSO regression selected 12 key genes, with CDK7 showing the most significant upregulation in the PIH model. CDK7 knockdown promoted macrophage polarization toward the anti-inflammatory M2 phenotype. DISCUSSION: These findings link CDK7 to immune dysregulation in PIH by modulating macrophage polarization, expanding our understanding of PIH's molecular mechanisms. The study's limitations include reliance on public datasets and in vitro models, warranting in vivo validation. CONCLUSION: CDK7 emerges as a potential therapeutic target for PIH, offering new insights into immunoregulatory interventions for this complication.

Female↗

PubMed2006

Global transcriptome analysis of Staphylococcus aureus response to hydrogen peroxide.

Staphylococcus aureus responds with protective strategies against phagocyte-derived reactive oxidants to infect humans. Herein, we report the transcriptome analysis of the cellular response of S. aureus to hydrogen peroxide-induced oxidative stress. The data indicate that the oxidative response includes the induction of genes involved in virulence, DNA repair, and notably, anaerobic metabolism.

Gene Expression Profiling↗

PubMed2025

Colorectal Liver Metastasis Pathomics Model: Integrating Single-Cell and Spatial Transcriptome Analysis With Pathomics for Predicting Liver Metastasis in Colorectal Cancer.

The liver is the primary target organ for hematologic metastasis of colorectal cancer (CRC), and CRC liver metastasis (CRLM) often precludes radical resection, making it the leading cause of death in patients with CRC. To improve the identification and prediction of liver metastasis risk, we identified a cell type of liver metastasis--triggering malignant cells (LMTMCs) through integrating single-cell RNA sequencing and spatial transcriptome analysis. Multiomics cell communication analysis indicated that the interaction between fibroblasts and LMTMCs through the COL1A1-CD44/SDC4 and LAMA4-CD44 signaling axes could promote CRLM. By applying the one-class logistic regression algorithm, we developed a CRLM scoring system in the bulk RNA-sequencing data according to the abundance of LMTMCs in each individual. Using the grouping labels derived from the CRLM scoring system in the bulk data and the corresponding whole-slide images without any manual annotations at the region or pixel level, processed via slide-level weakly supervised learning, a deep-learning model based on the ResNet18 architecture, called Colorectal Liver Metastasis Pathomics Model, was developed to predict the risk of liver metastasis in patients with CRC. The Colorectal Liver Metastasis Pathomics Model achieved an area under the curve of 0.84 at the internal test set of The Cancer Genome Atlas-CRC histology images. In the external independent validation sets, namely the Affiliated Hospital of Southwest Medical University and the Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University cohorts, the areas under the curve were 0.89 and 0.72, respectively, indicating effective classification performances. This study provided new insights and tools for the early identification of CRLM and demonstrated the potential of combining multiomics with deep learning-based pathomics in cancer research.

Humans↗