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PubMed2026

Estimating protein isoform abundances with [Formula: see text].

A single gene can encode multiple versions of a protein, dubbed isoforms, with varying functionality. Cellular control of isoform abundances is critical for multiple aspects of biology and is only partially regulated by transcript levels. While long-read sequencing facilitates transcript quantification, quantifying the resulting protein isoforms on a large scale is a major challenge, complicating biological interpretation of transcript alterations. Standard "bottom up" mass spectrometry can assess only short portions of isoforms called peptides, and these peptides often map onto more than one isoform. We introduce [Formula: see text] (Protein isoform Abundance Quantification), a Bayesian method that leverages multiomic information from the peptidome and transcriptome to provide accurate estimates of isoform abundance even when peptide mapping is ambiguous. [Formula: see text] offers several advantages over existing methods in a unified framework. It provides uncertainty quantification, integrates multiomic information for improved accuracy, and provides a rigorous framework for hypothesis testing. Extensive simulations show that [Formula: see text] consistently outperforms competing methods in detecting differentially abundant protein isoforms and estimating their abundances. We use [Formula: see text] to investigate differences in isoform abundance levels between people with schizophrenia and control subjects, confirming a long-held hypothesis that levels of the C4A isoform of Complement Component 4 are increased in schizophrenia while C4B is not. These results demonstrate that [Formula: see text] can identify significant variations in isoform abundance levels not previously possible.

Protein Isoforms↗
PubMed2003

Quantitative assessment of transcriptome differences between brain territories.

Transcriptome analysis of mammalian brain structures is a potentially powerful approach in addressing the diversity of cerebral functions. Here, we used a microassay for serial analysis of gene expression (SAGE) to generate quantitative mRNA expression profiles of normal adult mouse striatum, nucleus accumbens, and somatosensory cortex. Comparison of these profiles revealed 135 transcripts heterogeneously distributed in the brain. Among them, a majority (78), although matching a registered sequence, are novel regional markers. To improve the anatomical resolution of our analysis, we performed in situ hybridization and observed unique expression patterns in discrete brain regions for a number of candidates. We assessed the distribution of the new markers in peripheral tissues using quantitative RT-PCR, Northern hybridization, and published SAGE data. In most cases, expression was higher in the brain than in peripheral tissues. Because the markers were selected according to their expression level, without reference to prior knowledge, our studies provide an unbiased, comprehensive molecular signature for various mammalian brain structures that can be used to investigate their plasticity under a variety of circumstances.

Animals↗
PubMed2004

Negative transcriptional regulation of the ilv-leu operon for biosynthesis of branched-chain amino acids through the Bacillus subtilis global regulator TnrA.

The Bacillus subtilis ilv-leu operon is involved in the synthesis of branched-chain amino acids (valine, isoleucine, and leucine). The two- to threefold repression of expression of the ilv-leu operon during logarithmic-phase growth under nitrogen-limited conditions, which was originally detected by a DNA microarray analysis to compare the transcriptomes from the wild-type and tnrA mutant strains, was confirmed by lacZ fusion and Northern experiments. A genome-wide TnrA box search revealed a candidate box approximately 200 bp upstream of the transcription initiation base of the ilv-leu operon, the TnrA binding to which was verified by gel retardation and DNase I footprinting analyses. Deletion and base substitution of the TnrA box sequence affected the ilv-leu promoter activity in vivo, implying that TnrA bound to the box might be able to inhibit the promoter activity, possibly through DNA bending. The negative control of the expression of the ilv-leu operon by TnrA, which is considered to represent rather fine-tuning (two- to threefold), is a novel regulatory link between nitrogen and amino acid metabolism.

Amino Acids, Branched-Chain↗
PubMed2004

SAGE is far more sensitive than EST for detecting low-abundance transcripts.

BACKGROUND: Isolation of low-abundance transcripts expressed in a genome remains a serious challenge in transcriptome studies. The sensitivity of the methods used for analysis has a direct impact on the efficiency of the detection. We compared the EST method and the SAGE method to determine which one is more sensitive and to what extent the sensitivity is great for the detection of low-abundance transcripts. RESULTS: Using the same low-abundance transcripts detected by both methods as the targeted sequences, we observed that the SAGE method is 26 times more sensitive than the EST method for the detection of low-abundance transcripts. CONCLUSIONS: The SAGE method is more efficient than the EST method in detecting the low-abundance transcripts.

3' Untranslated Regions↗
PubMed2005

Systems toxicology: applications of toxicogenomics, transcriptomics, proteomics and metabolomics in toxicology.

Toxicogenomics can facilitate the identification and characterization of toxicity, as illustrated in this review. Toxicogenomics, the application of the functional genomics technologies (transcriptomics, proteomics and metabolomics) in toxicology enables the study of adverse effects of xenobiotic substances in relation to structure and activity of the genome. The advantages and limitations of the different technologies are evaluated, and the prospects for integration of the technologies into a systems biology or systems toxicology approach are discussed. Applications of toxicogenomics in various laboratories around the world show that the crucial steps and sequence of events at the molecular level can be studied to provide detailed insights into mechanisms of toxic action. Toxicogenomics allowed for more sensitive and earlier detection of adverse effects in (animal) toxicity studies. Furthermore, the effects of exposure to mixtures could be studied in more detail. This review argues that in the (near) future, human health risk assessment will truly benefit from toxicogenomics (systems toxicology).

Animals↗
PubMed2002

A partial transcriptome of human epidermis.

Serial analysis of gene expression (SAGE) is a powerful technique for global expression profiling without prior knowledge of the genes of interest. We carried out SAGE analysis of purified keratinocytes derived from human skin biopsy specimens, resulting in a partial transcriptome of human epidermis. We identified 7645 unique SAGE tags with quantitative information from 15,131 collected SAGE tags obtained from approximately 3 x 10(6) epidermal cells. This catalog contains a large number of genes that were not previously known to be expressed by human epidermis. Comparison with the databases of all known human SAGE tags allowed us to identify a number of keratinocyte-specific tags that putatively correspond to formerly unknown genes. Surprisingly, human epidermal keratinocytes in vivo show relatively low expression levels of genes typically associated with epidermal differentiation, whereas the expression levels of housekeeping genes are considerably higher than in cultured keratinocytes. This study provides a first step toward a transcriptome of human epidermis and, as such, harbors a wealth of information to identify genes involved in skin function, and candidate genes for genetic skin disorders.

Base Sequence↗
PubMed2026

Multilevel genomic, transcriptomic, and epidemiologic evidence linking diabetic retinopathy to Alzheimer disease.

BACKGROUND: Diabetic retinopathy (DR) and Alzheimer disease (AD) share metabolic and vascular dysfunctions, but the extent to which they reflect overlapping genetic susceptibility and neurovascular-metabolic regulatory pathways remains unclear. We combined multi-omics analyses with population-based data to examine the genetic convergence, cellular pathways, and longitudinal association between DR and AD. METHODS: We performed a two-sample Mendelian randomisation (MR) to estimate the association between genetically predicted DR liability and AD risk. We used Bayesian colocalisation analysis to identify shared genomic loci, and summary-data-based MR (SMR) to detect expression-mediated genes jointly associated with DR and AD. We analysed single-cell RNA sequencing data to characterise shared cellular features and related biological pathways. We also conducted an MR-based mediation analysis to explore whether lipid-related, metabolic, or inflammatory traits mediated the observed DR-AD association, and a longitudinal analysis of the UK Biobank cohort to assess the association between DR and incident AD. RESULTS: With the MR analysis, we found that genetically predicted liability to DR was associated with a modest increase in AD risk. Colocalisation analysis supported a shared genetic signal. We identified three genes with shared expression-mediated associations across DR and AD through SMR. Functional enrichment analyses revealed partially overlapping neurovascular and metabolic pathways. Using MR-based mediation analysis, we found no significant intermediary traits linking DR and AD. Findings from the UK Biobank cohort were directionally consistent with the genetic analyses. CONCLUSIONS: Genetic liability to DR is associated with an increased risk of AD and is accompanied by shared expression-mediated effects and convergent neurovascular-metabolic pathways. These findings support the possibility that DR may serve as a clinically accessible indicator of increased neurodegenerative vulnerability.

Humans↗
PubMed2005

Combined transcriptome profiling reveals a novel family of arbuscular mycorrhizal-specific Medicago truncatula lectin genes.

The large majority of plants are capable of undergoing a tight symbiosis with arbuscular mycorrhizal (AM) fungi. During this symbiosis, highly specialized new structures called arbuscules are formed within the host cells, indicating that, during interaction with AM fungi, plants express AM-specific genetic programs. Despite increasing efforts, the number of genes known to be induced in the AM symbiosis is still low. In order to identify novel AM-induced genes which have not been listed before, 5,646 expressed sequence tags (ESTs) were generated from two Medicago truncatula cDNA libraries: a random cDNA library (MtAmp) and a suppression subtractive hybridization (SSH) library (MtGim), the latter being designed to enhance the cloning of mycorrhiza-upregulated genes. In silico expression analysis was applied to identify those tentative consensus sequences (TCs) of The Institute for Genomic Research M. truncatula gene index (MtGI) that are composed exclusively of ESTs deriving from the MtGim or MtAmp library, but not from any other cDNA library of the MtGI. This search revealed 115 MtAmp- or MTGim-specific TCs. For the majority of these TCs with sequence similarities to plant genes, the AM-specific expression was verified by quantitative reverse-transcription polymerase chain reaction. Annotation of the novel genes induced in mycorrhizal roots suggested their involvement in different transport as well as signaling processes and revealed a novel family of AM-specific lectin genes. The expression of reporter gene fusions in transgenic roots revealed an arbuscule-related expression of two members of the lectin gene family, indicating a role for AM-specific lectins during arbuscule formation or functioning.

Amino Acid Sequence↗
PubMed2006

A novel R2R3 MYB transcription factor NtMYBJS1 is a methyl jasmonate-dependent regulator of phenylpropanoid-conjugate biosynthesis in tobacco.

Target metabolic and large-scale transcriptomic analyses of tobacco (Nicotiana tabacum L.) Bright Yellow-2 (BY-2) cells were employed to identify novel gene(s) involved in methyl jasmonate (MJ)-dependent function in plants. At the metabolic level, we describe the specific accumulation of several phenylpropanoid-polyamine conjugates in MJ-treated BY-2 cells. Furthermore, global gene expression analysis of MJ-treated cells using a 16K cDNA microarray containing expressed sequence tags (ESTs) from BY-2 cells revealed 828 genes that were upregulated by MJ treatment within 48 h. Using time-course expression data we identified a novel MJ-inducible R2R3 MYB-type transcription factor (NtMYBJS1) that was co-expressed in a close temporal pattern with the core phenylpropanoid genes phenylalanine ammonia-lyase (PAL) and 4-coumarate:CoA ligase (4CL). Overexpression of NtMYBJS1 in tobacco BY-2 cells caused accumulation of specific phenylpropanoid conjugates in the cells. Subsequent microarray analysis of NtMYBJS1 transgenic lines revealed that a limited number of genes, including PAL and 4CL, were specifically induced in the presence of the NtMYBJS1 transgene. These results, together with results of both antisense expression analysis and of gel mobility shift assays, strongly indicate that the NtMYBJS1 protein functions in tobacco MJ signal transduction, inducing phenylpropanoid biosynthetic genes and the accumulation of phenylpropanoid-polyamine conjugates during stress.

Acetates↗
PubMed2026

SCMO: a deep learning model integrating the single-cell resolution TME ecosystem and multi-omics for survival prediction in CRC patients.

BACKGROUND: Colorectal cancer (CRC) remains a leading cause of global cancer mortality, highlighting the need for precise survival prediction to guide clinical decisions. Although tissue-level multi-omics is widely utilized for survival prediction, its limited resolution cannot capture tumor heterogeneity. Single-cell RNA sequencing (scRNA-seq) enables dissection of the tumor microenvironment (TME) at cellular resolution, supporting personalized prognostic assessment. METHODS: We collected 213 CRC scRNA-seq samples and established a CRC-specific TME atlas comprising 339,060 cells. Using this atlas as a reference, we deconvolved bulk RNA-seq data from TCGA-CRC cohort with the EcoTyper algorithm to reconstruct TME features. Clinical, genomic, and transcriptomic data were obtained from the Xena platform; microbial data were sourced from the BIC database. We integrated TME and multi-omics features through a self-normalizing neural network to construct a deep learning model (single-cell resolution TME ecosystem with multi-omics data [SCMO]) for survival prediction. To enhance interpretability, we utilized the Integrated Gradients algorithm and spatial transcriptomic data to analyze multi-omics and TME features. We performed anticancer drug screening with tumor necrosis factor receptor-associated protein 1 (TRAP1), a critical feature according to the Integrated Gradients algorithm, as a potential target. RESULTS: We identified 13 survival-related TME features from the CRC-specific atlas: 12 cell states and one multi-cellular ecosystem. SCMO, which combined TME and multi-omics features, improved survival prediction and outperformed existing methods, achieving a concordance index of 0.762. The SCMO demonstrated robust performance for long-term predictions, achieving areas under the curve (AUCs) of 0.752, 0.772, and 0.869 for 1-, 3-, and 5-year predictions in the training set, with corresponding test set AUCs of 0.639, 0.756, and 0.772. TME features from the SCMO model revealed that ecosystem density increased with CRC malignancy. Multi-omics features included TRAP1 as a potential drug target. Drug screening identified saikosaponin A as a novel TRAP1 inhibitor, and its anticancer activity was validated in vitro. We developed SCMO-Lite, a simplified model incorporating 12 high-attribution-weight multi-omics features, which demonstrated robust risk stratification. CONCLUSIONS: SCMO combines analytical precision with biological interpretability, offering novel insights for oncology survival prediction.

Humans↗
PubMed2006

Global transcriptomic analysis of Desulfovibrio vulgaris on different electron donors.

Whole-genome microarrays of Desulfovibrio vulgaris were used to determine relative transcript levels in cells grown to exponential or stationary phase on a medium containing either lactate or formate as electron donor. The results showed that 158 and 477 genes were differentially expressed when comparing exponential to stationary phase in lactate- or formate-based media, respectively; and 505 and 355 genes were responsive to the electron donor used at exponential or stationary phase, respectively. Functional analyses suggested that the differentially regulated genes were involved in almost every aspect of cellular metabolism, with genes involved in protein synthesis, carbon, and energy metabolism being the most regulated. The results suggested that HynBA-1 might function as a primary periplasmic hydrogenase responsible for oxidation of H2 linked to the proton gradient in lactate-based medium, while several periplasmic hydrogenases including HynBA-1 and Hyd might carry out this role in formate-based medium. The results also indicated that the alcohol dehydrogenase and heterodisulfide reductase catalyzed pathway for proton gradient formation might be actively functioning for ATP synthesis in D. vulgaris. In addition, hierarchical clustering analysis using expression data across different electron donors and growth phases allowed the identification of the common electron donor independent changes in gene expression specifically associated with the exponential to stationary phase transition, and those specifically associated with the different electron donors independent of growth phase. The study provides the first global description and functional interpretation of transcriptomic response to growth phase and electron donor in D. vulgaris.

Bacterial Proteins↗
PubMed2004

Evidence that functional transcription units cover at least half of the human genome.

Transcriptome analyses have revealed that a large proportion of the human genome is transcribed. However, many of these transcripts might be functionless. To distinguish functional transcription units (FTUs) from spurious transcripts, we searched for the hallmarks of selective pressure against mutations that impair transcription. We analyzed the distribution of transposable elements, which are counter selected within FTUs. We show that these features are sufficiently informative to predict whether a sequence is transcribed and, if transcribed, in which orientation. Our results indicate that FTUs constitute at least 50% of the genome and that approximately one-third of these transcripts apparently do not encode proteins.

DNA Transposable Elements↗
PubMed2003

Target validation in hypoxia-induced vascular remodeling using transcriptome/metabolome analysis.

The present study describes combined transcriptome and metabolome analysis for therapeutic target validation in hypoxia-induced vascular remodeling. Exposure to hypoxic conditions resulted in the upregulation of S100C mRNA and increased taurine (2-aminoethanesulfonic acid) content in the rat lung, as demonstrated by differential display and amino-acid content analysis. Hypoxia resulted in transcriptional activation of the S100C promoter through hypoxia-inducible factor-1 (HIF-1). Taurine suppressed HIF-1-mediated increases in S100C transcription. Moreover, oral taurine administration attenuated vascular remodeling in hypoxic rat lung, whereas depletion of endogenous taurine by administration of beta-alanine resulted in increased vascular remodeling. Inhibition of HIF transcription by taurine may be of therapeutic benefit in preventing hypoxia-induced vascular remodeling. In conclusion, we used transcriptome and metabolome analysis to identify a therapeutic low-molecular-weight ligand that plays a critical role in hypoxia-induced vascular remodeling. These techniques provided an excellent strategy for screening and validation of targets.

Animals↗
PubMed2006

Nitric oxide-sensing mechanisms in Escherichia coli.

Exposure of Escherichia coli to nitric oxide (NO) or nitrosating agents causes significant changes in patterns of gene expression. Three recent studies have used microarrays to analyse the response of the E. coli transcriptome to NO and nitrosative stress. Drawing on the array data, I review our current understanding of the E. coli regulatory systems that are involved.

Bacterial Proteins↗
PubMed2006

Global alterations in mRNA polysomal recruitment in a cell model of colorectal cancer progression to metastasis.

Tumour onset and progression are due to the accumulation of genomic lesions, which alter gene expression and ultimately proteome activities. These lesions are thought to affect primarily the transcriptional control of gene expression. In the present study, we aimed at evaluating the genome-wide occurrence of alterations in the translational control exploiting an isogenic, phenotypically validated cellular model of colorectal cancer (CRC) transition from invasive carcinoma to metastasis. In this model, microarray profiling shows that changes in the level of messenger ribonucleic acid (mRNA) association with polysomes occur more than 2-fold than changes in the level of total cellular mRNA. When common to both the total and polysomal compartments, these changes are also homodirectional, being amplified in magnitude at the polysomal level. Comparison between the transcriptional and the translational fluctuations revealed distinct signatures of statistically over-represented gene functions, involving the program of cell proliferation for both levels of analysis, while the apoptosis and the translation programs were affected mainly at translation. Looking for an upstream determinant of translational deregulation, we found an increase in the hyperphosphorylated form of the 4E-BP1 protein in the metastatic cell line, possibly resulting in an increased activation of cap-dependent translation due to increased activity of the eIF4E protein. Analysis of the distribution profiles for the 5' untranslated region (5'-UTR) length of the changed genes showed an association between longer 5'-UTRs and the probability for the relevant gene to be altered translationally, consistent with enhanced eIF4E function. This genome-wide analysis is in favour of a model of profound alteration of translational control in late CRC progression. It also suggests polysomal mRNA profiles as a new, informative dimension for the study of transcriptome imbalance in cancer.

Adaptor Proteins, Signal Transducing↗
PubMed2026

Natural variants of CsSHN1 orchestrate a temporal regulatory cascade driving fruit skin netting in cucumber.

Fruit skin netting (russeting, Rs) forms when epidermal microcracks are sealed by a suberized periderm, reducing marketability. We previously identified the Rs locus (CsSHN1), which encodes an AP2/ERF transcription factor, as a major determinant of cucumber skin netting, but how fruit growth is temporally coupled to periderm formation remains unclear. Here, we integrated population genomics, time-series multiomics, DNA affinity purification sequencing (DAP-seq), and transgenic assays to decode the CsSHN1-mediated regulatory network. Six functionally relevant CsSHN1 variants were identified across 325 cucumber accessions. Allele distribution and selective sweep analyses revealed breeding-driven selection for smooth fruit skin. Overexpression of a netted allele in a smooth background induced epidermal fissures, altered cell geometry, and increased fruit size, demonstrating a dosage-sensitive effect. Time-series transcriptomics and metabolomics of near-isogenic lines (NILs) defined 3 developmental phases of netting: early suppression of lignin and trehalose genes preceding cracks, growth-driven fissuring accompanied by cell-wall remodeling and defense activation, and maturation-stage cell-wall degradation with strong induction of ligno-suberin biosynthesis. Across the cucumber genome, DAP-seq identified approximately 8,000 in vitro CsSHN1 binding sites. These binding sites were significantly enriched for the GCC-box motif and included genes involved in cutin and suberin biosynthesis. Together, these results show that CsSHN1 orchestrates fruit skin netting through a growth-coupled temporal regulatory cascade, providing a mechanistic framework for manipulating fruit epidermal properties.

Cucumis sativus↗
PubMed2005

Selection-driven transcriptome polymorphism in Escherichia coli/Shigella species.

To explore the role of transcriptome polymorphism in adaptation of organisms to their environment, we evaluated this parameter for the Escherichia coli/Shigella bacterial species, which is composed of well-characterized phylogenetic groups that exhibit characteristic life styles ranging from commensalism to intracellular pathogenicity. Both the genomic content and the transcriptome of 10 strains representative of the major E. coli/Shigella phylogenetic groups were evaluated using macroarrays displaying the 4290 K12-MG1655 open reading frames (ORFs). Although Shigella and enteroinvasive E. coli (EIEC) are not monophyletic, phylogenetic analysis of the binary coded (presence/absence) gene content data showed that these organisms group together due to similar patterns of undetectable K12-MG1655 genes. The variation in transcript abundance was then analyzed using a core genome of 2880 genes present in all strains, after adjusting RNA hybridization signals for DNA hybridization signals. Nonrandom changes in gene expression during the evolution of the E. coli/Shigella species were evidenced. Phylogenetic analysis of transcriptome data again showed that Shigella and EIEC strains group together in terms of gene expression, and this convergence involved groups of genes displaying biologically coherent patterns of functional divergence. Unlike the other E. coli strains evaluated, Shigella and EIEC are intracellular pathogens, and therefore face similar selective pressures. Thus, within the E. coli/Shigella species, strains exhibiting a particular life style have converged toward a specific gene expression pattern in a subset of genes common to the species, revealing the role of selection in shaping transcriptome polymorphism.

Caco-2 Cells↗
PubMed2018

Convergent evolution of gene expression in two high-toothed stickleback populations.

Changes in developmental gene regulatory networks enable evolved changes in morphology. These changes can be in cis regulatory elements that act in an allele-specific manner, or changes to the overall trans regulatory environment that interacts with cis regulatory sequences. Here we address several questions about the evolution of gene expression accompanying a convergently evolved constructive morphological trait, increases in tooth number in two independently derived freshwater populations of threespine stickleback fish (Gasterosteus aculeatus). Are convergently evolved cis and/or trans changes in gene expression associated with convergently evolved morphological evolution? Do cis or trans regulatory changes contribute more to gene expression changes accompanying an evolved morphological gain trait? Transcriptome data from dental tissue of ancestral low-toothed and two independently derived high-toothed stickleback populations revealed significantly shared gene expression changes that have convergently evolved in the two high-toothed populations. Comparing cis and trans regulatory changes using phased gene expression data from F1 hybrids, we found that trans regulatory changes were predominant and more likely to be shared among both high-toothed populations. In contrast, while cis regulatory changes have evolved in both high-toothed populations, overall these changes were distinct and not shared among high-toothed populations. Together these data suggest that a convergently evolved trait can occur through genetically distinct regulatory changes that converge on similar trans regulatory environments.

Alleles↗