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Results for “transcriptomic profiling”

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At least 523 records · Page 29Linked to original sources

PubMed2003

Discovery of imprinted transcripts in the mouse transcriptome using large-scale expression profiling.

Candidate imprinted transcriptional units in the mouse genome were identified systematically from 27,663 FANTOM2 full-length mouse cDNA clones by expression profiling. Large-scale cDNA microarrays were used to detect differential expression dependent upon chromosomal parent of origin by comparing the mRNA levels in the total tissue of 9.5 dpc parthenogenote and androgenote mouse embryos. Of the FANTOM2 transcripts, 2114 were identified as candidates on the basis of the array data. Of these, 39 mapped to known imprinted regions of the mouse genome, 56 were considered as nonprotein-coding RNAs, and 159 were natural antisense transcripts. The imprinted expression of two transcripts located in the mouse chromosomal region syntenic to the human Prader-Willi syndrome region was confirmed experimentally. We further mapped all candidate imprinted transcripts to the mouse and human genome and were shown in correlation with the imprinting disease loci. These data provide a major resource for understanding the role of imprinting in mammalian inherited traits.

Animals↗

PubMed2006

Transcriptional networks of knockout cell lines identify functional specificities of H-Ras and N-Ras: significant involvement of N-Ras in biotic and defense responses.

We characterized differential gene expression profiles of fibroblast cell lines harboring single or double-homozygous null mutations in H-ras and N-ras. Whereas the expression level of the individual H-, N- and K-ras genes appeared unaffected by the presence or absence of the other ras loci, significant differences were observed between the expression profiles of cells missing N-ras and/or H-ras. Absence of N-ras produced much stronger effects than absence of H-ras over the profile of the cellular transcriptome. N-ras(-/-) and H-ras(-/-) fibroblasts displayed rather antagonistic expression profiles and the transcriptome of H-ras(-/-) cells was significantly closer to that of wild-type fibroblasts than to that of N-ras(-/-) cells. Classifying all differentially expressed genes into functional categories suggested specific roles for H-Ras and N-Ras. It was particularly striking in N-ras(-/-) cells the upregulation of a remarkable number of immunity-related genes, as well as of several loci involved in apoptosis. Reverse-phase protein array assays demonstrated in the same N-ras(-/-) cells the overexpression and nuclear migration of tyrosine phosphorylated signal transducer and activator of transcription 1 (Stat1) which was concomitant with transcriptional activation mediated by interferon-stimulated response elements. Significantly enhanced numbers of apoptotic cells were also detected in cultures of N-ras(-/-) cells. Our data support the notion that different Ras isoforms play functionally distinct cellular roles and indicate that N-Ras is significantly involved in immune modulation/host defense and apoptotic responses.

Animals↗

PubMed2006

Transgenesis has less impact on the transcriptome of wheat grain than conventional breeding.

Detailed global gene expression profiles have been obtained for a series of transgenic and conventionally bred wheat lines expressing additional genes encoding HMW (high molecular weight) subunits of glutenin, a group of endosperm-specific seed storage proteins known to determine dough strength and therefore bread-making quality. Differences in endosperm and leaf transcriptome profiles between untransformed and derived transgenic lines were consistently extremely small, when analysing plants containing either transgenes only, or also marker genes. Differences observed in gene expression in the endosperm between conventionally bred material were much larger in comparison to differences between transgenic and untransformed lines exhibiting the same complements of gluten subunits. These results suggest that the presence of the transgenes did not significantly alter gene expression and that, at this level of investigation, transgenic plants could be considered substantially equivalent to untransformed parental lines.

Breeding↗

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↗

PubMed2026

Accurately Deciphering Tissue Heterogeneity From Spatial Multi-Modal and Multi-Omics With STransformer.

Advances in spatially resolved technologies enable the simultaneous acquisition of diverse data modalities within a tissue slice while preserving critical spatial context, which presents unprecedented opportunities to decipher intricate tissue heterogeneity. However, existing computational approaches lack the intrinsic flexibility to universally process both spatial multi-modal and multi-omics data. Here, we introduce STransformer, a unified deep learning framework designed to seamlessly accommodate a comprehensive landscape of spatial data. By simultaneously capturing short-range cellular interactions and tissue-wide semantic patterns, it extracts robust representations to accurately dissect complex tissue heterogeneity. Systematic evaluations across diverse species, tissue types, and data modalities highlight its profound versatility. For spatial multi-modal data, STransformer delineates intricate anatomical structures in the human cortex, uncovers pathological mechanisms in Alzheimer's disease, and characterizes dynamic spatiotemporal developmental trajectories during chicken cardiogenesis. Scaling to spatial multi-omics data, STransformer synergizes spatial transcriptomic and proteomic profiles to decipher intricate immune microenvironments within the human tonsil, and jointly analyzes spatial epigenomic and transcriptomic data to infer regulatory mechanisms in the mouse embryonic brain. Consequently, STransformer serves as a highly versatile and robust analytical framework for advancing our understanding of tissue heterogeneity and disease pathogenesis.

Multiomics↗

PubMed2006

Transcriptome analysis in Catharanthus roseus leaves and roots for comparative terpenoid indole alkaloid profiles.

In Catharanthus roseus (L.) G. Don each tissue is known to produce a distinct spectrum of terpenoid indole alkaloids. Since the invaluable antineoplastic bisindole alkaloids are restricted to the aerial parts of the plant and do not occur in its underground tissues, identification of the structural and regulatory factors operating distinctly in the shoot/leaf of the plant will be a necessity for modulation of bisindole alkaloid biosynthesis. This study aimed at elucidating the differential gene expression in the two main tissues (leaf and root) of the plant, well known for their distinct terpenoid indole alkaloid profiles. The leaf and root transcriptomes of C. roseus were comparatively analysed using two different approaches: (i) indirectly through construction and characterization of separate cDNA libraries; and (ii) directly through a strategically designed suppression subtractive hybridization, using the leaf and root cDNA populations as tester and driver, respectively. A total of 155 ESTs (55 and 45 from the separate leaf and root cDNA libraries, respectively, and 55 from the subtracted leaf-specific cDNA library) were subjected to homology-based classification and submitted to dbEST. The direct approach yielded an EST for sgd (strictosidine beta-D-glucosidase) and 16 novel ESTs. Dat (acetyl-CoA: 4-O-deacetylvindoline 4-O-acetyl-transferase) and sgd transcripts could not be detected in the root system of the plant (cv. 'Dhawal') at any developmental stage (6 d, 6 weeks, or 6 months). The growth-related decrease in shoot/leaf dat and sgd transcript levels was paralleled by a concomitant decrease in shoot/leaf vindoline content.

Acetyltransferases↗

PubMed2005

The biological limitations of transcriptomics in elucidating stress and stress responses.

Global analysis of mRNA abundance via genomic arrays (i.e. transcriptomics or transcriptional profiling) is one approach to finding the genes that matter to organisms undergoing environmental stress. In evolutionary analyses of stress, mRNA abundance is often invoked as a proxy for the protein activity that may underlie variation in fitness. To provoke discussion of the utility and sensible application of this valuable approach, this manuscript examines the adequacy of mRNA abundance as a proxy for protein activity, fitness and stress. Published work to date suggests that mRNA abundance typically provides little information on protein activity and fitness and cannot substitute for detailed functional and ecological analyses of candidate genes. While the transcriptional profile can be an exquisitely sensitive indicator of stress, simpler indicators will often suffice. In view of this outcome, transcriptomics should undergo careful cost-benefit analysis before investigators deploy it in studies of stress responses and their evolution.

Adaptation, Biological↗

PubMed2003

Microarray expression profiling: capturing a genome-wide portrait of the transcriptome.

The bacterial transcriptome is a dynamic entity that reflects the organism's immediate, ongoing and genome-wide response to its environment. Microarray expression profiling provides a comprehensive portrait of the transcriptional world enabling us to view the organism as a 'system' that is more than the sum of its parts. The vigilance of microorganisms to environmental change, the alacrity of the transcriptional response, the short half-life of bacterial mRNA and the genome-scale nature of the investigation collectively explain the power of this method. These same features pose the most significant experimental design and execution issues which, unless surmounted, predictably generate a distorted image of the transcriptome. Conversely, the expression profile of a properly conceived and conducted microarray experiment can be used for hypothesis testing: disclosure of the metabolic and biosynthetic pathways that underlie adaptation of the organism to chang-ing conditions of growth; the identification of co-ordinately regulated genes; the regulatory circuits and signal transduction systems that mediate the adaptive response; and temporal features of developmental programmes. The study of bacterial pathogenesis by microarray expression profiling poses special challenges and opportunities. Although the technical hurdles are many, obtaining expression profiles of an organism growing in tissue will probably reveal strategies for growth and survival in the host's microenvironment. Identifying these colonization strategies and their cognate expression patterns involves a 'deconstruction' process that combines bioinformatics analysis and in vitro DNA array experimentation.

Bacteria↗

PubMed2025

Learning directed acyclic graphs for ligands and receptors based on spatially resolved transcriptomic data of ovarian cancer.

To unravel the mechanism of immune activation and suppression within tumors, a critical step is to identify transcriptional signals governing cell-cell communication between tumor and immune/stromal cells in the tumor microenvironment. Central to this communication are interactions between secreted ligands and cell-surface receptors, creating a highly connected signaling network among cells. Recent advancements in in situ-omics profiling, particularly spatial transcriptomic (ST) technology, provide unique opportunities to directly characterize ligand-receptor signaling networks that power cell-cell communication. In this paper, we propose a novel statistical method, LRnetST, to characterize the ligand-receptor interaction networks between adjacent tumor and immune/stroma cells based on ST data. LRnetST utilizes a directed acyclic graph model with a novel approach to handle the zero-inflated distributions of ST data. It also leverages existing ligand-receptor regulation databases as prior information, and employs a bootstrap aggregation strategy to achieve robust network estimation. Application of LRnetST to ST data of high-grade serous ovarian tumor samples revealed both common and distinct ligand-receptor regulations across different tumors. Some of these interactions were validated through both a MERFISH dataset and a CosMx SMI dataset of independent ovarian tumor samples. These results cast light on biological processes relating to the communication between tumor and immune/stromal cells in ovarian tumors. An open-source R package of LRnetST is available on GitHub at https://github.com/jie108/LRnetST.

Humans↗

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↗

PubMed2002

mRNA expression profiling of laser microbeam microdissected cells from slender embryonic structures.

Microarray hybridization has rapidly evolved as an important tool for genomic studies and studies of gene regulation at the transcriptome level. Expression profiles from homogenous samples such as yeast and mammalian cell cultures are currently extending our understanding of biology, whereas analyses of multicellular organisms are more difficult because of tissue complexity. The combination of laser microdissection, RNA amplification, and microarray hybridization has the potential to provide expression profiles from selected populations of cells in vivo. In this article, we present and evaluate an experimental procedure for global gene expression analysis of slender embryonic structures using laser microbeam microdissection and laser pressure catapulting. As a proof of principle, expression profiles from 1000 cells in the mouse embryonic (E9.5) dorsal aorta were generated and compared with profiles for captured mesenchymal cells located one cell diameter further away from the aortic lumen. A number of genes were overexpressed in the aorta, including 11 previously known markers for blood vessels. Among the blood vessel markers were endoglin, tie-2, PDGFB, and integrin-beta1, that are important regulators of blood vessel formation. This demonstrates that microarray analysis of laser microbeam micro-dissected cells is sufficiently sensitive for identifying genes with regulative functions.

Animals↗

PubMed2007

Global gene expression profiling of Bacillus subtilis in response to ammonium and tryptophan starvation as revealed by transcriptome and proteome analysis.

The global gene expression profile of Bacillus subtilis in response to ammonium and tryptophan starvation was analyzed using transcriptomics and proteomics which gained novel insights into these starvation responses. The results demonstrate that both starvation conditions induce specific, overlapping and general starvation responses. The TnrA regulon, the glutamine synthetase (glnA) as well as the sigma(L)-dependent bkd and roc operons were most strongly and specifically induced after ammonium starvation. These are involved in the uptake and utilization of ammonium and alternative nitrogen sources such as amino acids, gamma-aminobutyrate, nitrate/nitrite, uric acid/urea and oligopeptides. In addition, several carbon catabolite-controlled genes (e.g. acsA, citB), the alpha-acetolactate synthase/-decarboxylase alsSD operon and several aminotransferase genes were specifically induced after ammonium starvation. The induction of sigma(F)- and sigma(E)-dependent sporulation proteins at later time points in ammonium-starved cells was accompanied by an increased sporulation frequency. The specific response to tryptophan starvation includes the TRAP-regulated tryptophan biosynthesis genes, some RelA-dependent genes (e.g. adeC, ald) as well as spo0E. Furthermore, we recognized overlapping responses between ammonium and tryptophan starvation (e.g. dat, maeN) as well as the common induction of the CodY and sigma(H) general starvation regulons and the RelA-dependent stringent response. Many genes encoding proteins of so far unknown functions could be assigned to specifically or commonly induced genes.

Ammonium Sulfate↗

PubMed2021

Comparative cellular analysis of motor cortex in human, marmoset and mouse.

The primary motor cortex (M1) is essential for voluntary fine-motor control and is functionally conserved across mammals1. Here, using high-throughput transcriptomic and epigenomic profiling of more than 450,000 single nuclei in humans, marmoset monkeys and mice, we demonstrate a broadly conserved cellular makeup of this region, with similarities that mirror evolutionary distance and are consistent between the transcriptome and epigenome. The core conserved molecular identities of neuronal and non-neuronal cell types allow us to generate a cross-species consensus classification of cell types, and to infer conserved properties of cell types across species. Despite the overall conservation, however, many species-dependent specializations are apparent, including differences in cell-type proportions, gene expression, DNA methylation and chromatin state. Few cell-type marker genes are conserved across species, revealing a short list of candidate genes and regulatory mechanisms that are responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allows us to use patch-seq (a combination of whole-cell patch-clamp recordings, RNA sequencing and morphological characterization) to identify corticospinal Betz cells from layer 5 in non-human primates and humans, and to characterize their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell-type diversity in M1 across mammals, and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations.

Animals↗

PubMed2005

Pattern profiling and mapping of the fat body transcriptome in Drosophila melanogaster.

In Drosophila, the fat body is a collective name for the masses and sheets of adipose tissue that are distributed throughout the fly body. Thus far, >386,000 Drosophila expressed sequence tags (ESTs) have been deposited to the GenBank database, including 10,443 derived from fat body in flies (data accessed on October 7, 2004). The objective of this study was to map the transcriptome of the fat body in flies and thus provide genomics and bioinformatics tools for developing a Drosophila model for addressing the genetic complexity of obesity in humans. The gene-EST Basic Local Alignment Search Tool (BLAST) matches revealed that these ESTs could represent 12,188 coding genes in the Drosophila genome. Among them, at least 2,261 are expressed in the fat body, including 41 identified as preferentially expressed genes with logarithm of odds >3.0. Self-organizing map analysis revealed a cluster of 290 genes favorably expressed in the fat body compared with genes expressed in five other tissues. Mapping of the fat body transcriptome identified a 1.7-Mb domain on 3L containing 35 genes that were expressed at a much higher level than in other tissues (transcript density factor = 1.0 approximately 2.3).

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↗

PubMed2007

Molecular portrait of high productivity in recombinant NS0 cells.

Many important therapeutic proteins are produced in recombinant mammalian cells. Upon the introduction of the product gene, the isolated clones typically exhibit a wide range of productivity and high producers are subsequently selected for use in production. Using DNA microarray, two-dimensional gel electrophoresis (2DE), and iTRAQ as global surveying tools, we examined the transcriptome and proteome profiles of 11 lines of NS0 cells producing the same antibody molecule. Genes that are significantly differentially expressed between high and low producer groups statistically fall into a number of functional classes. Their distribution among the functional classes differs somewhat between transcriptomic and proteomic results. Overall, a high degree of consistency between transcriptome and proteome analysis are seen, although some genes exhibiting inconsistent trends between transcript and protein levels were observed as expected. In a novel approach, functional gene networks were retrieved using computational pathway analysis tools and their association with productivity was tested by physiological comprehension of the possible pathways involved in high recombinant protein production. Network analysis indicates that protein synthesis pathways were altered in high producers at both transcriptome and proteome levels, whereas the effect on cell growth/death pathways was more prominent only at the transcript level. The results suggest a common mechanism entailing the alteration of protein synthesis and cell growth control networks leading to high productivity. However, alternate routes with different sets of genes may be invoked to give rise to the same mechanistic outcomes. Such systematic approaches, combining transcriptomic and proteomic tools to examine high and low producers of recombinant mammalian cells will greatly enhance our capability to rationally design high producer cells. This work is a first step towards shedding a new light on the global physiological landscape of hyper productivity of recombinant cells.

Animals↗

PubMed2006

Protein/DNA interaction profiling reveals novel regulators of the pineal transcriptome.

The rat pineal gland transcriptome exhibits dynamic daily variation that reflects nocturnally restricted hormone production. Here we have used a protein/DNA interaction array to screen for day-night changes in DNA binding activity that are associated with transcriptional rhythms. Overall, 47 of 54 potential consensus binding sequence activities were detected, and of these, 29 (62%) were found to exhibit day:night differences in level. In addition to known, rhythmic pineal DNA binding activities (CRE and AP-1), multiple novel activities were observed including nocturnally elevated AP-2 consensus sequence binding activity. This array result was validated using conventional DNA binding assays, and we have also demonstrated AP-2beta and AP-2gamma proteins in the pineal gland, in addition to a nocturnally elevated AP-2alpha isoform. Our results have confirmed the presence of a complex assembly of transcriptional rhythms in the rat pineal gland and have provided details of more factors that contribute to this aspect of circadian neuroendocrine function.

Animals↗

PubMed2025

Transcript-guided targeted cell enrichment for scalable single-nucleus RNA sequencing.

Large-scale single-cell atlases have revealed many aging- and disease-associated cell types, yet these populations are often underrepresented in heterogeneous tissues, limiting detailed molecular analyses. To address this, we developed EnrichSci-a scalable, microfluidics-free platform that combines hybridization chain reaction RNA fluorescence in situ hybridization (FISH) with combinatorial indexing to profile single-nucleus transcriptomes of target cell types with full gene-body coverage. Applied to oligodendrocytes in the aging mouse brain, EnrichSci uncovered aging-associated molecular dynamics across distinct oligodendrocyte subtypes, revealing both shared and subtype-specific gene expression changes. Additionally, we identified aging-associated exon-level signatures missed by conventional gene-level analyses, highlighting post-transcriptional regulation as a critical dimension of cell-state dynamics in aging. By coupling transcript-guided enrichment with a scalable sequencing workflow, EnrichSci provides a versatile approach to decode dynamic regulatory landscapes in diverse cell types from complex tissues.

Animals↗