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Results for “transcriptomic profiling”

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PubMed2026

Blood-derived gene expression profiles associated with dietary microalgae oil intake and methane emission variation in lambs.

BACKGROUND: Minimising methane (CH4) emissions from livestock production is a global priority, and feed modifications, such as supplementing diets with microalgae, have previously been shown to help reducing enteric CH4 production. This study explored blood-derived host gene expression profiles from twenty lambs supplemented with increasing levels of microalgae oil to investigate their transcriptional responses associated with varying microalgae oil levels while also exploring the host systemic responses towards varied CH4 productions. RESULTS: Findings revealed no significant changes in CH4 production with increasing levels of microalgae oil intake through phenotypic analysis (P = 0.18). However inter-individual variations in CH4 production ranged from 27.02 to 47.86 g/day throughout the study period. Blood RNA-Sequencing identified 64 significant genes including DHCR7, DHCR24, HMGCS1, INSIG1, LSS, MSMO1, and SQLE, which were involved in lipid metabolism, and steroid biosynthesis that became enriched alongside increasing microalgae oil intake levels thereby contributing to a positive impact on lambs' metabolic functions. Additionally, seven significant blood-expressed host genes (NME4, MARCHF3, PLXNB3, LOC132657460, LOC121819234, LOC105603087, LOC101116551) functionally enriched in nucleotide metabolic pathways and immune responses were identified to have significant positive associations with increasing CH4 production. Importantly, this study found no overlap between genes associated with microalgae oil intake and those linked to CH4 emissions. CONCLUSIONS: Findings suggest that microalgae oil intake and inter-individual variations in CH₄ production are associated with distinct blood-derived transcriptional responses. Although such signals should be interpreted as proxies for systemic host responses rather than direct measures of rumen-specific processes, these results emphasise the importance of considering host-associated molecular variations alongside dietary CH₄-mitigation strategies.

Animals↗

PubMed2025

Exploring diagnostic m6A regulators in primary open-angle glaucoma: insight from gene signature and possible mechanisms by which key genes function.

PURPOSE: The purpose of this study was to interrogate the potential role of N6-methyladenosine (m6A) regulators in the process of trabecular meshwork (TM) tissue damage in patients with primary open-angle glaucoma (POAG). METHODS: Firstly, the expression profile of m6A regulators in TM tissues of POAG patients was comprehensively analyzed by bioinformatics analysis; Plasmid transfection and siRNA gene interference were used to enhance or weaken the expression levels of YTHDC2 in human trabecular meshwork cells (HTMCs); Cell migration ability was detected by transwell chamber assay; Immunofluorescence staining assay was used to evaluate the expression of extracellular matrix (ECM) related proteins. RESULTS: Through the analysis of GSE27276 database, 5 m6A regulators with different expression in POAG were screened out. The results of random forest model showed that these 5 m6A regulators exhibited diagnostic potential and were characteristic genes of POAG. All POAG samples could be effectively divided into two groups based on the expression levels of these 5 hub m6A regulators. Immune cell infiltration analysis indicated that the levels of activated CD8+ T cells and regulatory T cells were different in the two subtypes. HTMC oxidative stress cell model and TGF-β2 stimulation cell model were further constructed to verify the expression of the aforementioned hub m6A regulators, and it was found that YTHDC2 mRNA showed the same expression trend in both models. The silencing of YTHDC2 enhanced the migration ability of HTMCs and increased the synthesis ability of ECM. However, when YTHDC2ΔYTH, which lacks the YTH domain, is overexpressed in HTMCs, there is no significant change in the ECM synthesis ability. CONCLUSIONS: The differentially expressed m6A regulators in TM tissues may serve as potential diagnostic biomarkers for POAG. And, in HTMCs, the expression level of YTHDC2 mRNA was changed under oxidative stress or TGF-β2 intervention, and then exerted its regulation on cell migration and ECM synthesis capability through m6A modification, which may be an important part of the disease process of POAG.

Humans↗

PubMed2026

Decoding glioblastoma evolution and heterogeneity through mechanistic modeling: implications for clinical translation.

Glioblastoma (GBM) is one of the most aggressive and lethal primary brain tumors in adults, characterized by dynamic clonal evolution and extensive genomic, cellular, spatial, and microenvironmental heterogeneity. Multi-omics studies have revealed that GBM follows complex evolutionary trajectories involving genetic, epigenetic, transcriptional, and immune-microenvironmental remodeling as tumors grow, adapt to the brain microenvironment, and acquire therapeutic resistance. Increasing evidence suggests that GBM may originate from aberrant neural stem or progenitor cells, including those residing in the subventricular zone, and that glioblastoma stem cells (GSCs) contribute to tumor propagation, heterogeneity, and recurrence. A key conceptual challenge is to reconcile hierarchical cancer stem cell models, in which GSCs are viewed as relatively stable tumor-propagating subpopulations, with dynamic state plasticity models, in which stem-like properties can be reversibly acquired or lost during transitions among proneural-like, mesenchymal-like, invasive, and therapy-tolerant states. Recent advances in single-cell profiling, spatial transcriptomics, lineage tracing, organoid culture, 3D bioprinting, genetically engineered models, and artificial intelligence (AI)-assisted computational modeling have substantially improved the ability to study these processes. However, no currently available model fully recapitulates human GBM heterogeneity, recurrence, treatment history, and tumor-microenvironment interactions. Therefore, model selection should be guided by clearly defined mechanistic questions rather than by reliance on any single platform. This review summarizes current advances in in vitro, ex vivo, in vivo, and computational models for studying GBM evolution and heterogeneity, and discusses how integrated model pipelines may improve preclinical drug testing, treatment-response prediction, and precision neuro-oncology.

Humans↗

PubMed2021

RP-REP Ribosomal Profiling Reports: an open-source cloud-enabled framework for reproducible ribosomal profiling data processing, analysis, and result reporting.

Ribosomal profiling is an emerging experimental technology to measure protein synthesis by sequencing short mRNA fragments undergoing translation in ribosomes. Applied on the genome wide scale, this is a powerful tool to profile global protein synthesis within cell populations of interest. Such information can be utilized for biomarker discovery and detection of treatment-responsive genes. However, analysis of ribosomal profiling data requires careful preprocessing to reduce the impact of artifacts and dedicated statistical methods for visualizing and modeling the high-dimensional discrete read count data. Here we present Ribosomal Profiling Reports (RP-REP), a new open-source cloud-enabled software that allows users to execute start-to-end gene-level ribosomal profiling and RNA-Seq analysis on a pre-configured Amazon Virtual Machine Image (AMI) hosted on AWS or on the user's own Ubuntu Linux server. The software works with FASTQ files stored locally, on AWS S3, or at the Sequence Read Archive (SRA). RP-REP automatically executes a series of customizable steps including filtering of contaminant RNA, enrichment of true ribosomal footprints, reference alignment and gene translation quantification, gene body coverage, CRAM compression, reference alignment QC, data normalization, multivariate data visualization, identification of differentially translated genes, and generation of heatmaps, co-translated gene clusters, enriched pathways, and other custom visualizations. RP-REP provides functionality to contrast RNA-SEQ and ribosomal profiling results, and calculates translational efficiency per gene. The software outputs a PDF report and publication-ready table and figure files. As a use case, we provide RP-REP results for a dengue virus study that tested cytosol and endoplasmic reticulum cellular fractions of human Huh7 cells pre-infection and at 6 h, 12 h, 24 h, and 40 h post-infection. Case study results, Ubuntu installation scripts, and the most recent RP-REP source code are accessible at GitHub. The cloud-ready AMI is available at AWS (AMI ID: RPREP RSEQREP (Ribosome Profiling and RNA-Seq Reports) v2.1 (ami-00b92f52d763145d3)).

AMI↗

PubMed2005

Microarray-based functional protein profiling using peptide nucleic acid-encoded libraries.

The availability of complete genome sequences from numerous organisms has provided investigators with the challenge of assigning physiologic functions to the encoded gene products. To facilitate this process, multiple technologies have been developed to profile the transcriptome and the proteome, including methods to monitor the function of enzymes in complex biologic systems. These methods typically target specific classes of enzymes and attempt to correlate the enzymatic activity with the specific phenotype of interest. Here, technologies to measure enzymatic activity on a subproteomic scale are reviewed, including the authors' own efforts, which are based on self-assembled microarrays utilizing peptide nucleic acid-encoded small-molecule libraries.

Animals↗

PubMed2026

Complement expression profiles in human glomerular mesangial cells, endothelial cells, podocytes and proximal tubular epithelial cells.

BACKGROUND: Local expression of complement components in the kidney has been reported sporadically in both diseased and normal kidneys. This study aimed to comprehensively characterize the expression of complement components in human glomerular mesangial cells (GMCs), glomerular endothelial cells (GECs), podocytes, and proximal tubular epithelial cells (PTECs) in non-diseased renal tissue. METHODS: Complement expression in cultured human renal intrinsic cells was initially evaluated using reverse transcription polymerase chain reaction and immunofluorescence staining. These findings were further examined using publicly available single-cell RNA-sequencing datasets and 10×Genomics single-cell RNA sequencing of non-diseased human kidney tissue. The analyses focused on complement components involved in the initiation of the classical, lectin, and alternative pathways, as well as components shared among these activation pathways, terminal pathway components, complement regulators, and complement receptors. RESULTS: Complement components unique to the initial phase for classical pathway (C1S, C1R, C2, C4), lectin pathway (MBL2, FCN1, MASP1), alternative pathway (CFB, CFD), and the C3 component shared by the three activation pathways were detected in these cells. The components shared by the terminal pathways including C5, C6, C7, C8 and C9 exhibited lower expression, while complement regulators (CFH, CFI, CD55/DAF, CD46/MCP, CD59, C4BPB, PROS1/Protein S) or receptors (CD93/C1QR1, CR1), particularly membrane-bound proteins, such as DAF, MCP and CD59, which inhibit complement activation and the formation of the membrane attack complex, showed relatively high expression. CONCLUSION: These results showed that all four types of intrinsic renal cells expressed multiple complement components associated with the classical, lectin, and alternative pathways. In non-diseased kidney tissue, complement regulatory molecules involved in the control of complement activation showed relatively higher expression, whereas components of the terminal complement pathway were expressed at relatively lower levels, suggesting that renal intrinsic cells maintain a locally poised but tightly regulated complement system.

Humans↗

PubMed2004

[The fight against doping: today and tomorrow].

Since Antiquity, sport persons have used doping methods to improve their performance. The methods used today are increasingly specific and professional As a corrolary, doping is becoming extremely difficult to detect: because many prohibited drugs are rapidly metabolized (short half life); it is often impossible to distinguish between the natural and recombinant hormone products; several prohibited substances are not screened for; therapeutic use authorization (TUA)--a recent recommendation from the World antidoping agency (WADA)--and advances in gene therapy are giving cheaters new possibilities. It is necessary to promote a new approach to doping detection by determining potential specific links between changes in human biological profiles (proteom, transcriptom, metabonom), and the use of a given drug. Developments in nanotechnology, and notably" labs on a chip" should prove useful in this respect.

Doping in Sports↗

PubMed2005

Analysis of the female gametophyte transcriptome of Arabidopsis by comparative expression profiling.

The extensive data on the transcription of the plant genome are derived primarily from the sporophytic generation. There currently is little information on genes that are expressed during female gametophyte development in angiosperms, and it is not known whether the female gametophyte transcriptome contains a major set of genes that are not expressed in the sporophyte or whether it is primarily a subset of the sporophytic transcriptome. Because the embryo sac is embedded within the maternal ovule tissue, we have utilized the Arabidopsis (Arabidopsis thaliana) mutant sporocyteless that produces ovules without embryo sacs, together with the ATH1 Arabidopsis whole-genome oligonucleotide array, to identify genes that are preferentially or specifically expressed in female gametophyte development. From analysis of the datasets, 225 genes are identified as female gametophyte genes, likely a lower limit as stringent criteria were used for the analysis, eliminating many low expressed genes. Nearly 45% of the identified genes were not previously detected by sporophytic expression profiling, suggesting that the embryo sac transcriptome may contain a significant fraction of transcripts restricted to the gametophyte. Validation of six candidate genes was performed using promoterbeta-glucuronidase fusions, and all of these showed embryo sac-specific expression in the ovule. The unfiltered expression data from this study can be used to evaluate the possibility of female gametophytic expression for any gene in the ATH1 array, and contribute to identification of the functions of the component of the Arabidopsis genome not represented in studies of sporophytic expression and function.

Arabidopsis↗

PubMed2006

Integrative investigation of metabolic and transcriptomic data.

BACKGROUND: New analysis methods are being developed to integrate data from transcriptome, proteome, interactome, metabolome, and other investigative approaches. At the same time, existing methods are being modified to serve the objectives of systems biology and permit the interpretation of the huge datasets currently being generated by high-throughput methods. RESULTS: Transcriptomic and metabolic data from chemostat fermentors were collected with the aim of investigating the relationship between these two data sets. The variation in transcriptome data in response to three physiological or genetic perturbations (medium composition, growth rate, and specific gene deletions) was investigated using linear modelling, and open reading-frames (ORFs) whose expression changed significantly in response to these perturbations were identified. Assuming that the metabolic profile is a function of the transcriptome profile, expression levels of the different ORFs were used to model the metabolic variables via Partial Least Squares (Projection to Latent Structures--PLS) using PLS toolbox in Matlab. CONCLUSION: The experimental design allowed the analyses to discriminate between the effects which the growth medium, dilution rate, and the deletion of specific genes had on the transcriptome and metabolite profiles. Metabolite data were modelled as a function of the transcriptome to determine their congruence. The genes that are involved in central carbon metabolism of yeast cells were found to be the ORFs with the most significant contribution to the model.

Algorithms↗

PubMed2005

Transcriptome of Treponema pallidum: gene expression profile during experimental rabbit infection.

RNA transcript levels in the syphilis spirochete Treponema pallidum subsp. pallidum (Nichols) isolated from experimentally infected rabbits were determined by the use of DNA microarray technology. This characterization of the T. pallidum transcriptome during experimental infection provides further insight into the importance of gene expression levels for the survival and pathogenesis of this bacterium.

Animals↗

PubMed2003

Targeted cellular process profiling approach for uterine leiomyoma using cDNA microarray, proteomics and gene ontology analysis.

This study utilized both cDNA microarray and two-dimensional protein gel electrophoresis technology to investigate the multiple interactions of genes and proteins involved in uterine leiomyoma pathophysiology. Also, the gene ontology analysis was used to systematically characterize the global expression profiles at cellular process levels. We profiled differentially expressed transcriptome and proteome in six-paired leiomyoma and normal myometrium. Screening up to 17 000 genes identified 21 upregulated and 50 downregulated genes. The gene-expression profiles were classified into mutually dependent 420 functional sets, resulting in 611 cellular processes according to the gene ontology. Also, protein analysis using two-dimensional gel electrophoresis identified 33 proteins (17 upregulated and 16 downregulated) of more than 500 total spots, which was classified into 302 cellular processes. Of these functional profilings, downregulations of transcriptomes and proteoms were shown in cell adhesion, cell motility, organogenesis, enzyme regulator, structural molecule activity and response to external stimulus functional activities that are supposed to play important roles in pathophysiology. In contrast, the upregulation was only shown in nucleic acid-binding activity. Taken together, potentially significant pathogenetic cellular processes were identified and showed that the downregulated functional profiling has a significant impact on the discovery of pathogenic pathway in leiomyoma. Also, the gene ontology analysis can overcome the complexity of expression profiles of cDNA microarray and two-dimensional protein analysis via its cellular process-level approach. Therefore, a valuable prognostic candidate gene with relevance to disease-specific pathogenesis can be found at cellular process levels.

Cell Communication↗

PubMed2026

High-throughput single-cell proteomics and transcriptomics from same cells with a nanoliter-scale, spin-transfer approach.

Single-cell multiomic platforms provide a comprehensive snapshot of cellular states and cell types by offering critical insights into the spatiotemporal regulation of biomolecular networks at a systems level, thereby defining the basis of multicellularity. Here, we introduce nanoSPINS, an advanced platform that enables high-throughput profiling and integrative analysis of the transcriptome and proteome from the same single cells using RNA sequencing and isobaric labeling LC-MS-based proteomics, respectively. NanoSPINS can efficiently transfer mRNA-containing droplets across two microarrays via a centrifugation-based approach, while proteins are retained on the initial platform. Benchmarking of nanoSPINS on two cell lines demonstrates its ability to generate global proteomic and transcriptomic profiles that align well with previously established methodologies/platforms. The incorporation of isobaric TMTpro labeling into this single-cell multiomics platform significantly enhances the throughput of single-cell proteomic analyses. Through the high-throughput quantification of the proteome and transcriptome, nanoSPINS not only facilitates the identification of molecular features at both mRNA and protein level but also provides larger sample sizes for improved statistical power in clustering and differential abundance. Given the broad applicability of single-cell multiomics in biological research and clinical settings, we believe nanoSPINS represents a powerful platform for the characterization of heterogeneous cell populations.

Single-Cell Analysis↗

PubMed2004

A genomic view of estrogen actions in human breast cancer cells by expression profiling of the hormone-responsive transcriptome.

Estrogen controls key cellular functions of responsive cells including the ability to survive, replicate, communicate and adapt to the extracellular milieu. Changes in the expression of 8400 genes were monitored here by cDNA microarray analysis during the first 32 h of human breast cancer (BC) ZR-75.1 cell stimulation with a mitogenic dose of 17beta-estradiol, a timing which corresponds to completion of a full mitotic cycle in hormone-stimulated cells. Hierarchical clustering of 344 genes whose expression either increases or decreases significantly in response to estrogen reveals that the gene expression program activated by the hormone in these cells shows 8 main patterns of gene activation/inhibition. This newly identified estrogen-responsive transcriptome represents more than a simple cell cycle response, as only a few affected genes belong to the transcriptional program of the cell division cycle of eukaryotes, or showed a similar expression profile in other mitogen-stimulated human cells. Indeed, based on the functions assigned to the products of the genes they control, estrogen appears to affect several key features of BC cells, including their metabolic status, proliferation, survival, differentiation and resistance to stress and chemotherapy, as well as RNA and protein synthesis, maturation and turn-over rates. Interestingly, the estrogen-responsive transcriptome does not appear randomly interspersed in the genome. In chromosome 17, for example, a site particularly rich in genes activated by the hormone, physical association of co-regulated genes in clusters is evident in several instances, suggesting the likely existence of estrogen-responsive domains in the human genome.

Breast Neoplasms↗

PubMed2006

Transcriptome amplification methods in gene expression profiling.

The increasing use of microarray expression profiling to study the molecular biology of cancer and the cellular physiology of difficult-to-isolate cell types has led to a need for methods that accurately and precisely amplify small quantities of RNA. The purpose of this review is to provide an overview of the existing methods for transcriptome amplification and to define the parameters for comparing different amplification methods. The authors propose a standardized protocol for the assessment and evaluation of amplification methods, focusing on a new whole-transcriptome amplification kit, which amplifies total RNA into cDNA fragments. Reproducibility and reliability of the method were analyzed and discussed using both quantitative real-time PCR and a high-density oligonucleotide microarray platform.

DNA, Complementary↗

PubMed2026

Proteogenomic features define subtypes of mantle cell lymphoma.

Mantle cell lymphoma (MCL) is a biologically heterogeneous B-cell malignancy. Although genomics and transcriptomics have delineated parts of the MCL disease spectrum, proteomics remains largely unexplored. Here, we conducted a comprehensive proteogenomic analysis integrating genomics, transcriptomics, and proteomics on peripheral blood samples from 27 patients with MCL and 4 healthy donors to investigate the translational and posttranslational dimensions of MCL. Our study identified 1296 downregulated and 468 upregulated proteins in MCL cells. The splicing pathways were significantly upregulated at both the mRNA and protein levels, suggesting a critical role for aberrant RNA splicing in MCL pathogenesis. Integration of proteomic data with genetic aberrations revealed immunoglobulin heavy chain variable mutational status and CCND1 mutation are associated with distinctive transcriptomic and proteomic profiles, which correspond to significant differences in clinical outcomes. A multiomics molecular stratification model incorporating proteomic data showed superior predictive power for patient survival compared with single-omics models (concordance index, 0.83 vs 0.74). This study provides, to our knowledge, the first comprehensive proteogenomic profile of MCL, offering novel insights into its molecular mechanisms and clinical behavior. The identification of molecular subtypes and prognostic protein signatures underscores the potential of proteomics to guide precision medicine strategies for MCL.

Humans↗

PubMed2006

Comparative profiling of the sense and antisense transcriptome of maize lines.

BACKGROUND: There are thousands of maize lines with distinctive normal as well as mutant phenotypes. To determine the validity of comparisons among mutants in different lines, we first address the question of how similar the transcriptomes are in three standard lines at four developmental stages. RESULTS: Four tissues (leaves, 1 mm anthers, 1.5 mm anthers, pollen) from one hybrid and one inbred maize line were hybridized with the W23 inbred on Agilent oligonucleotide microarrays with 21,000 elements. Tissue-specific gene expression patterns were documented, with leaves having the most tissue-specific transcripts. Haploid pollen expresses about half as many genes as the other samples. High overlap of gene expression was found between leaves and anthers. Anther and pollen transcript expression showed high conservation among the three lines while leaves had more divergence. Antisense transcripts represented about 6 to 14 percent of total transcriptome by tissue type but were similar across lines. Gene Ontology (GO) annotations were assigned and tabulated. Enrichment in GO terms related to cell-cycle functions was found for the identified antisense transcripts. Microarray results were validated via quantitative real-time PCR and by hybridization to a second oligonucleotide microarray platform. CONCLUSION: Despite high polymorphisms and structural differences among maize inbred lines, the transcriptomes of the three lines displayed remarkable similarities, especially in both reproductive samples (anther and pollen). We also identified potential stage markers for maize anther development. A large number of antisense transcripts were detected and implicated in important biological functions given the enrichment of particular GO classes.

Expressed Sequence Tags↗

PubMed2026

Optics-free spatial genomics for mapping mammalian brain aging by IRISeq.

Spatial transcriptomics has emerged as a transformative approach for in situ mapping of cellular heterogeneity and interactions, yet existing methods often compromise throughput, cost and tissue coverage. Here we introduce Imaging Reconstruction using Indexed Sequencing (IRISeq): an optics-free, cost-effective platform that leverages spatial interaction mapping by indexed sequencing to profile tissues at adjustable sizes and resolutions (5-50 µm). We applied IRISeq to map gene expression across more than 70 coronal sections from both adult and aged mouse brains, including wild-type and two lymphocyte-deficient models (Rag1 and Prkdc mutants) and generated more than 460,000 spatial transcriptome profiles. Our integrated analysis with 783,264 single-cell transcriptomes revealed region-specific aging signatures that are lymphocyte dependent, notably a downregulation of interferon signaling and inflammation in ventricular regions upon lymphocyte depletion, alongside mutant-specific upregulation of senescence pathways. Furthermore, lymphocyte deficiency was linked to preserved abundance of ependymal cells that line the brain's ventricles and to distinct microglial state dynamics, highlighting a key role for lymphocytes in driving inflammatory processes during brain aging. Overall, IRISeq provides a high-throughput and cost-effective solution for spatially resolved transcriptomic profiling, opening new avenues for elucidating region-specific cellular mechanisms underlying aging and identifying potential therapeutic targets to preserve brain homeostasis.

Animals↗

PubMed2002

Complementary profiling of gene expression at the transcriptome and proteome levels in Saccharomyces cerevisiae.

Using an integrated genomic and proteomic approach, we have investigated the effects of carbon source perturbation on steady-state gene expression in the yeast Saccharomyces cerevisiae growing on either galactose or ethanol. For many genes, significant differences between the abundance ratio of the messenger RNA transcript and the corresponding protein product were observed. Insights into the perturbative effects on genes involved in respiration, energy generation, and protein synthesis were obtained that would not have been apparent from measurements made at either the messenger RNA or protein level alone, illustrating the power of integrating different types of data obtained from the same sample for the comprehensive characterization of biological systems and processes.

Databases as Topic↗