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At least 1,531 records · Page 85Linked to original sources
PubMed2005

Protein encoding genes in an ancient plant: analysis of codon usage, retained genes and splice sites in a moss, Physcomitrella patens.

BACKGROUND: The moss Physcomitrella patens is an emerging plant model system due to its high rate of homologous recombination, haploidy, simple body plan, physiological properties as well as phylogenetic position. Available EST data was clustered and assembled, and provided the basis for a genome-wide analysis of protein encoding genes. RESULTS: We have clustered and assembled Physcomitrella patens EST and CDS data in order to represent the transcriptome of this non-seed plant. Clustering of the publicly available data and subsequent prediction resulted in a total of 19,081 non-redundant ORF. Of these putative transcripts, approximately 30% have a homolog in both rice and Arabidopsis transcriptome. More than 130 transcripts are not present in seed plants but can be found in other kingdoms. These potential "retained genes" might have been lost during seed plant evolution. Functional annotation of these genes reveals unequal distribution among taxonomic groups and intriguing putative functions such as cytotoxicity and nucleic acid repair. Whereas introns in the moss are larger on average than in the seed plant Arabidopsis thaliana, position and amount of introns are approximately the same. Contrary to Arabidopsis, where CDS contain on average 44% G/C, in Physcomitrella the average G/C content is 50%. Interestingly, moss orthologs of Arabidopsis genes show a significant drift of codon fraction usage, towards the seed plant. While averaged codon bias is the same in Physcomitrella and Arabidopsis, the distribution pattern is different, with 15% of moss genes being unbiased. Species-specific, sensitive and selective splice site prediction for Physcomitrella has been developed using a dataset of 368 donor and acceptor sites, utilizing a support vector machine. The prediction accuracy is better than those achieved with tools trained on Arabidopsis data. CONCLUSION: Analysis of the moss transcriptome displays differences in gene structure, codon and splice site usage in comparison with the seed plant Arabidopsis. Putative retained genes exhibit possible functions that might explain the peculiar physiological properties of mosses. Both the transcriptome representation (including a BLAST and retrieval service) and splice site prediction have been made available on http://www.cosmoss.org, setting the basis for assembly and annotation of the Physcomitrella genome, of which draft shotgun sequences will become available in 2005.

Alternative Splicing↗
PubMed2005

Floral gene resources from basal angiosperms for comparative genomics research.

BACKGROUND: The Floral Genome Project was initiated to bridge the genomic gap between the most broadly studied plant model systems. Arabidopsis and rice, although now completely sequenced and under intensive comparative genomic investigation, are separated by at least 125 million years of evolutionary time, and cannot in isolation provide a comprehensive perspective on structural and functional aspects of flowering plant genome dynamics. Here we discuss new genomic resources available to the scientific community, comprising cDNA libraries and Expressed Sequence Tag (EST) sequences for a suite of phylogenetically basal angiosperms specifically selected to bridge the evolutionary gaps between model plants and provide insights into gene content and genome structure in the earliest flowering plants. RESULTS: Random sequencing of cDNAs from representatives of phylogenetically important eudicot, non-grass monocot, and gymnosperm lineages has so far (as of 12/1/04) generated 70,514 ESTs and 48,170 assembled unigenes. Efficient sorting of EST sequences into putative gene families based on whole Arabidopsis/rice proteome comparison has permitted ready identification of cDNA clones for finished sequencing. Preliminarily, (i) proportions of functional categories among sequenced floral genes seem representative of the entire Arabidopsis transcriptome, (ii) many known floral gene homologues have been captured, and (iii) phylogenetic analyses of ESTs are providing new insights into the process of gene family evolution in relation to the origin and diversification of the angiosperms. CONCLUSION: Initial comparisons illustrate the utility of the EST data sets toward discovery of the basic floral transcriptome. These first findings also afford the opportunity to address a number of conspicuous evolutionary genomic questions, including reproductive organ transcriptome overlap between angiosperms and gymnosperms, genome-wide duplication history, lineage-specific gene duplication and functional divergence, and analyses of adaptive molecular evolution. Since not all genes in the floral transcriptome will be associated with flowering, these EST resources will also be of interest to plant scientists working on other functions, such as photosynthesis, signal transduction, and metabolic pathways.

Biodiversity↗
PubMed2005

Application of Affymetrix array and Massively Parallel Signature Sequencing for identification of genes involved in prostate cancer progression.

BACKGROUND: Affymetrix GeneChip Array and Massively Parallel Signature Sequencing (MPSS) are two high throughput methodologies used to profile transcriptomes. Each method has certain strengths and weaknesses; however, no comparison has been made between the data derived from Affymetrix arrays and MPSS. In this study, two lineage-related prostate cancer cell lines, LNCaP and C4-2, were used for transcriptome analysis with the aim of identifying genes associated with prostate cancer progression. METHODS: Affymetrix GeneChip array and MPSS analyses were performed. Data was analyzed with GeneSpring 6.2 and in-house perl scripts. Expression array results were verified with RT-PCR. RESULTS: Comparison of the data revealed that both technologies detected genes the other did not. In LNCaP, 3,180 genes were only detected by Affymetrix and 1,169 genes were only detected by MPSS. Similarly, in C4-2, 4,121 genes were only detected by Affymetrix and 1,014 genes were only detected by MPSS. Analysis of the combined transcriptomes identified 66 genes unique to LNCaP cells and 33 genes unique to C4-2 cells. Expression analysis of these genes in prostate cancer specimens showed CA1 to be highly expressed in bone metastasis but not expressed in primary tumor and EPHA7 to be expressed in normal prostate and primary tumor but not bone metastasis. CONCLUSION: Our data indicates that transcriptome profiling with a single methodology will not fully assess the expression of all genes in a cell line. A combination of transcription profiling technologies such as DNA array and MPSS provides a more robust means to assess the expression profile of an RNA sample. Finally, genes that were differentially expressed in cell lines were also differentially expressed in primary prostate cancer and its metastases.

Cell Line, Tumor↗
PubMed2004

In vivo transcriptional profiling of Plasmodium falciparum.

BACKGROUND: Both host and pathogen factors contribute to disease outcome in Plasmodium falciparum infection. The feasibility of studying the P. falciparum in vivo transcriptome to understand parasite transcriptional response while it resides in the human host is presented. METHODS: A custom made oligonucleotide array with probes based on the P. falciparum 3D7 laboratory strain chromosome 2 sequence was used to detect in vivo P. falciparum transcripts. This study analyzed transcripts from total RNA derived from small blood samples of P. falciparum infected patients and compared the in vivo expression profile to the in vitro cultivated 3D7 strain transcriptome. RESULTS: The data demonstrated that in vivo transcription can be studied from a small blood sample, despite the abundance of human RNA. The in vivo transcriptome is similar to the 3D7 ring stage transcriptome, but there are significant differences in genes encoding a sexual stage antigen and surface proteins. CONCLUSIONS: Whole genome transcription analysis of P. falciparum can be carried out successfully and further studies in selected patient cohorts may provide insight into parasite in vivo biology and defense against host immunity.

Animals↗
PubMed2006

Serum circulating human mRNA profiling and its utility for oral cancer detection.

PURPOSE: The purpose of this study is to explore the presence of informative RNA biomarkers from human serum transcriptome, and evaluate the serum transcriptome diagnostics for disease detection. Oral squamous cell carcinoma (OSCC) was selected as the proof-of-concept disease. PATIENTS AND METHODS: Blood samples were collected from patients (n = 32) with primary T1/T2 OSCC and matched healthy patients (n = 35). Circulating RNA was isolated from serum and linearly amplified using T7 polymerase. Microarrays were applied for profiling transcriptome in serum from 10 cancer patients and controls. The differential gene expression was analyzed by combining the present calls, t tests, and fold-change statistics. Quantitative polymerase chain reaction (PCR) was used to validate the selected candidate RNA markers identified by microarray. Receiver operating characteristic curve and classification models were exploited to evaluate the diagnostic power of these markers for OSCC. RESULTS: Human serum circulating mRNAs were presented by reverse transcriptase PCR. Microarray identified 2,623 +/- 868 probes assigned present calls in OSCC (n = 10) versus 1,792 +/- 165 in healthy patients (n = 10), indicating a higher complexity of serum transciptome in OSCC patients (P = .002, Wilcoxon test). Three hundred thirty-five serum RNAs exhibited significantly differential expression level between the two groups (P < .05, t test; fold > or = 2). Five cancer-related gene transcripts were consistently validated by quantitative PCR on serum from OSCC patients (n = 32) and controls (n = 35). The best combination of biomarkers yielded a receiver operating characteristic curve value of 88%, sensitivity (91%), and specificity (71%) in distinguishing OSCC. CONCLUSION: The utility of serum transcriptome diagnostics is successfully demonstrated for OSCC detection. This novel concept could be developed as an adjunctive tool for disease diagnosis.

Biomarkers↗
PubMed2005

Validation of RNA arbitrarily primed PCR probes hybridized to glass cDNA microarrays: application to the analysis of limited samples.

BACKGROUND: The applicability of microarray-based transcriptome massive analysis is often limited by the need for large amounts of high-quality RNA. RNA arbitrarily primed PCR (RAP-PCR) is an unbiased fingerprinting PCR technique that reduces both the amount of initial material needed and the complexity of the transcriptome. The aim of this study was to evaluate the feasibility of using hybridization of RAP-PCR products as transcriptome representations to analyze differential gene expression in a microarray platform. METHODS: RAP-PCR products obtained from samples with limited availability of biological material, such as experimental metastases, were hybridized to conventional cDNA microarrays. We performed replicates of self-self hybridizations of RAP-PCR products and mathematical modeling to assess reproducibility and sources of variation. RESULTS: Gene/slide interaction (47.3%) and the PCR reaction (33.8%) accounted for the majority of the variability. From these observations, we designed a protocol using two pools of three independent RAP-PCR reactions coming from two independent reverse transcription reactions hybridized in duplicate and evaluated them in the analyses of paired xenograft-metastases samples. Using this approach, we found that HER2 and MMP7 may be down-regulated during distal dissemination of colorectal tumors. CONCLUSION: RAP-PCR glass array hybridization can be used for transcriptome analysis of small samples.

Acetyltransferases↗
PubMed2004

Expression genomics and cancer biology.

Expression genomics is a term that is used to describe the investigation of transcription in a whole-genome manner and includes the investigation of gene regulation. Characteristic of this approach is its comprehensiveness and the highly multiplexed nature of its analysis. Thus, the range of technologies used include microarrays, tag library approaches, such as serial analysis of gene expression (SAGE), full-length cDNA cloning and sequencing, and chromatin immunoprecipitation coupled with cloning/sequencing or applied to genomic chips. These technologies are all complementary since they have different capabilities and attack different components of the transcriptome: transcriptional regulation, promoter usage, differential splicing, and gene expression. Unlike genome sequencing, the combinatorial complexity of the transcriptome is immense, making its complete characterization impossible. Instead, the strategy has shifted to the analysis of the whole transcriptome in a context-driven, cell biological framework where the fundamental truths emerge through multiple comparisons and pharmacological challenges. The density of non-redundant data generated with any experiment allows for the assessment of higher order relationships. This comprehensive data, in turn, permits information convergence across different experiments, organisms, and data sets. Surprising concordance in the underlying conclusions is observed with data of such complexity. Since microarrays have been the most widely used technology in expression genomics for the study of cancer biology, this paper will focus on studies using expression arrays, but will also touch on other transcriptome-directed technologies. The experience with these approaches is sufficiently mature to arrive at some generalizable observations. First, although expression genomics is a useful approach for the discovery of individual candidate genes, its greatest power is in defining class distinctions using the collective behavior of gene clusters. Therefore, expression genomic output can effectively uncover hierarchies of molecular importance. Second, in the hierarchy of factors that determine the expression footprint within a cell, cell lineage is the most important, followed by the activity of specific biochemical pathways and further followed by the effect of individual genes. Lastly, expression profiling is an effective clinical tool that can discern prognostic and therapeutic classes. The importance of these gene lists is that not only do they describe potential therapeutic targets, but they are effective monitors of therapeutic efficacy.

Animals↗
PubMed2026

A Computational Workflow for Prioritizing Microbial Metabolite-Associated Host Genes in Constipation-Predominant Irritable Bowel Syndrome.

No standardized computational pipeline exists for systematically prioritizing microbial metabolite-associated host genes and protein-ligand complexes from publicly available chemical, genomic, and structural databases. This article describes an eight-stage workflow that accepts a user-defined set of gut microbiota-derived metabolites and produces a ranked shortlist of candidate metabolite-associated host genes, enriched biological pathways, and structurally prioritized protein-ligand complexes for experimental follow-up. The pipeline integrates (i) chemoinformatic metabolite profiling; (ii) multi-database candidate target prediction using protein-chemical interaction and ligand-based target-prediction tool and a molecular docking program; (iii) differential gene expression analysis of publicly available transcriptomic data; (iv) target-differentially expressed gene overlap; (v) protein-protein interaction network construction and pathway enrichment; (vi) molecular docking with a molecular docking program; (vii) 200 ns molecular dynamics simulation using a molecular dynamics engine with a protein force field used for molecular dynamics simulations; and (viii) MM-PBSA binding free-energy estimation. As a worked example, nine gut microbiota-derived or microbiota-modified metabolites representing short-chain fatty acids, bile acids, tryptophan-derived metabolites, and urolithin A were processed using the public IBS-C rectal mucosal transcriptomic dataset GSE36701. The workflow ranked 17 unique predicted metabolite-associated genes that were differentially expressed in this dataset. Docking, molecular dynamics simulation, and MM-PBSA analyses structurally prioritized five metabolite-protein complexes: lithocholic acid-VDR, lithocholic acid-NR1H4/FXR, ursodeoxycholic acid-NR1H4/FXR, tryptamine-HTR2A (simulated in an explicit 1-Palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) lipid bilayer), and urolithin A-CASP3. The protocol is designed to be adaptable to other metabolite sets, disease transcriptomic datasets, and target classes; all outputs are hypothesis-generating computational predictions that require independent transcriptomic replication, protein-level validation, and functional ligand-response assays before causal or therapeutic conclusions can be drawn.

Irritable Bowel Syndrome↗
PubMed2002

[Pharmacogenomics and pharmainformatics].

Pharmacogenomics is defined to identify the genes which are involved in determining the responsiveness and to distinguish 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 clue 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, et al), mRNA display (differential display, fluorescent differential display, RNA arbitraly primed PCR, molecular indexing, gene expression fingerprinting, et al) and differential hybridization(cDNA high density filter, cDNA microarray, oligomicrochip, et al). We used transcriptome analysis to identify therapeutic target genes by studying change of gene expression in animal models of cerebral vasospasm (1) and of hypoxia/ischemia and found novel drug target candidates through this pharmacogenomic strategy (2). We found remarkable up-regulation of heme oxygenase-1(HO-1) mRNA in the basilar artery and it might be closely related to the occurrence of delayed vasospasm after subarachnoid hemorrhage. In this report, we clearly demonstrate that intrathecal administration of antisense HO-1 oligodeoxynucleotide aggravates vasospasm, suggesting HO-1 gene induction has spasmolytic effects. Furthermore, we found the protective effects of HO-1 gene induction by endogenous or clinical compounds in cerebral vasospasm. Therapeutic gene induction of HO-1 could be a novel strategy for the prevention and treatment of Hb-induced pathologic conditions including delayed cerebral vasospasm. Our results suggest that the pharmacogenomic transcriptome analysis and pharmainformatics has the potential for strategy to define novel drug targets in various diseases (3). (1) J Clin Invest 104: 59-66, 1999. (2) J Biol Chem 276: 19921-19928, 2001. (3) J Cardiovasc Pharm 36: S1-S4, 2000.

Animals↗
PubMedDate not supplied

Large-scale analysis of gene expression: methods and application to the kidney.

Characterization of tissue-specific gene expression profiles, or transcriptomes, may serve two purposes: a) establishing relationships between cell transcriptomes and functions (i.e. molecular and physiological phenotypes) under physiological and pathophysiological conditions serves to elucidate gene functions, and b) determination of the totality of genes expressed in a cell seems a prerequisite for understanding cell functions, because the properties of proteins vary with their environment. Sophisticated methods are now available for transcriptome analysis. They are based on serial, partial sequencing of cDNAs (sequencing of expressed sequenced tags (ESTs) and serial analysis of gene expression (SAGE)), or on parallel hybridization of labeled cDNAs to specific probes immobilized on a grid (macro- and microarrays and DNA chips). Some methods were designed specifically to compare gene expression under different conditions (substractive hybridization, glass microarrays). However, all these methods require several microg of mRNA as starting material, making impossible, in most tissues, to analyse gene expression in homogeneous cell populations. To get around this limitation, we developed a scaled-down SAGE method (SAGE adaptation to downsized extracts: SADE) in our laboratory. SAGE is based on the following: a) each cDNA is characterized by a 10-bp informative sequence called tag, b) the information from several transcripts is condensed into a single DNA molecule by concatenation of several tags, c) sequencing of individual clones from the library of concatemers, computer analysis of sequences and interrogation of sequence databases allow quantitative gene expression profiling. Applied to microdissected mouse nephron segments, SADE made it possible to determine segment-specific transcriptomes.

Animals↗
PubMed2005

Paracoccidioides brasiliensis translation and protein fate machineries revealed by functional genome analysis.

The translational and post-translational modification machineries of Paracoccidioides brasiliensis were assessed by means of comparative analyses of PbAESTs (P. brasiliensis assembled expressed sequence tags) with sequences deposited on different databases. Of the 79 sequences corresponding to cytosolic ribosomal proteins, we were able to find 78 in the P. brasiliensis transcriptome. Nineteen of the 27 Saccharomyces cerevisiae genes related to translation initiation were also found. All eukaryotic elongation factors were detected in P. brasiliensis transcriptome, with eEF1A as one of the most expressed genes. Translation termination is performed, in eukaryotes, by factors 1 and 3 (eRF1, eRF3). In P. brasiliensis transcriptome it was possible to identify eRF3, but not eRF1. Sixteen PbAESTs showing aminoacyl-tRNA synthetase-predicted activities were found in our analyses, but no cysteinyl-, leucyl-, asparagyl- and arginyl-tRNA synthetases were detected. Among the mitochondrial ribosomal proteins, we have found 20 and 18 orthologs to S. cerevisiae large and small ribosomal subunit proteins, respectively. We have also found three PbAESTs similar to Neurospora crassa mitochondrial ribosomal genes, with no similarity with S. cerevisiae genes. Although orthologs to S. cerevisiae mitochondrial EF-Tu, EF-G and RF1 have been found in P. brasiliensis transcriptome, no sequences corresponding to functional EF-Ts were detected. In addition, 64 and 28 PbAESTs associated to protein modification and degradation, respectively, were found. These results suggest that these machineries are well conserved in P. brasiliensis, when compared to other organisms.

Expressed Sequence Tags↗
PubMed2026

Global downstream BMP15 pathway analysis in human ovarian granulosa cells reveals novel genetic variations associated with primary ovarian insufficiency.

OBJECTIVES: Primary ovarian insufficiency (POI) is a fertility disorder with a well-established genetic component, but many cases still remain idiopathic. Approximately 1.5-12% of patients with POI can carry a variant in the BMP15 gene, depending on the population and the diagnostic criteria. We hypothesize that genetic variations within pathways downstream of BMP15 activity in ovarian granulosa cells (GCs) may contribute to unexplained cases of POI. The main goal of this study is to identify novel variants associated with POI in genes induced by BMP15 in GCs. STUDY DESIGN: Primary cultures of human GCs were stimulated with recombinant human BMP15. Microarray analysis profiled the BMP15-induced transcriptome in GCs. Validation was achieved by qPCR and immunoblot. Further, target exome sequencing of the differentially expressed genes was performed on 64 women with early POI onset in search of novel variants. MAIN OUTCOME MEASURES: Transcriptome profiling of human GCs stimulated with BMP15 and target exome sequencing in women with early onset of POI. RESULTS: Transcriptome analysis revealed significant upregulation of 19 genes (p&#xa0;<&#xa0;0.05). Ontology analysis of these genes converged towards two main pathways: TGF-beta signaling and regulation of stem cell pluripotency. Target exome sequencing identified six novel rare variants in five BMP15-induced genes (SAMD11, SMAD6, ID1, USP35, GPCR137C) in 9 of the 64 women with early POI (14%). CONCLUSIONS: BMP15 action in human ovarian GCs defines TGF-beta signaling and pluripotency fate in ovarian follicles. In addition, this study uncovers new potential candidate genes for the pathogenesis of POI.

Humans↗
PubMed2025

Histology-Based Virtual RNA Inference Identifies Pathways Associated With Metastasis Risk in Colorectal Cancer.

Colorectal cancer (CRC) remains a major health concern, with >150,000 new diagnoses and >50,000 deaths annually in the United States, underscoring an urgent need for improved screening, prognostication, disease management, and therapeutic approaches. The tumor microenvironment (TME)-comprising cancerous and immune cells interacting within the tumor's spatial architecture-plays a critical role in disease progression and treatment outcomes, reinforcing its importance as a prognostic marker for metastasis and recurrence risk. However, traditional methods for TME characterization, such as bulk transcriptomics and multiplex protein assays, lack sufficient spatial resolution. Although spatial transcriptomics (ST) allows for the high-resolution mapping of whole transcriptomes at near-cellular resolution, current ST technologies (eg, Visium and Xenium) are limited by high costs, low throughput, and issues with reproducibility, preventing their widespread application in large-scale molecular epidemiology studies. In this study, we refined and implemented virtual RNA inference (VRI) to derive ST-level molecular information directly from hematoxylin and eosin (H&E)-stained tissue images. Our VRI models were trained on the largest matched CRC ST data set to date, comprising 45 patients and >300,000 Visium spots from primary tumors. Using state-of-the-art deep learning models (UNI, ResNet-50, Vision Transformer, and Vision Mamba), we achieved a median Spearman's correlation coefficient of 0.546 between predicted and measured spot-level expression. As validation, VRI-derived gene signatures linked to specific tissue regions (tumor, interface, submucosa, stroma, serosa, muscularis, and inflammation) showed strong concordance with signatures generated via direct ST, and VRI performed accurately in estimating cell-type proportions spatially from H&E slides. In an expanded CRC cohort controlling for tumor invasiveness and clinical factors, we further identified VRI-derived gene signatures significantly associated with key prognostic outcomes, including metastasis status. Although certain tumor-related pathways are not fully captured by histology alone, our findings highlight the ability of VRI to infer a wide range of "histology-associated" biological pathways at near-cellular resolution without requiring ST profiling. Future efforts will extend this framework to expand TME phenotyping from standard H&E tissue images, with the potential to accelerate translational CRC research at scale.

Humans↗
PubMed2026

CoxFormer enables spatial omics inference with multimodal generative modeling.

Gene co-expression maps transcriptome-wide gene-gene relationships, yet high-quality estimates cover less than half the genome. Meanwhile, spatial omics either profiles restricted in situ panels or lacks cellular resolution. Extending co-expression transcriptome-wide could overcome these limitations by inferring unassayed gene expression at subcellular resolution. Here we show that CoxFormer integrates literature-derived gene knowledge with co-expression networks from bulk tissues and large-scale single-cell atlases to learn 512-dimensional representations for 32,016 human genes. These embeddings capture functional gene relationships and serve as a generative prior for spatial inference across platforms and modalities. Without requiring a matched single-cell RNA-sequencing reference, CoxFormer supports four applications beyond measured genes: histology-based expression imputation, gene activity prediction from chromatin accessibility, subcellular super-resolution inference, and pathological region detection. Together, CoxFormer extends gene embedding from gene- and cell-level tasks to whole-transcriptome spatial inference, providing a unified framework for biological analysis beyond the limited gene coverage of current spatial omics technologies.

Humans↗
PubMed2024

A time-resolved single-cell roadmap of the logic driving anterior neural crest diversification from neural border to migration stages.

Neural crest cells exemplify cellular diversification from a multipotent progenitor population. However, the full sequence of early molecular choices orchestrating the emergence of neural crest heterogeneity from the embryonic ectoderm remains elusive. Gene-regulatory-networks (GRN) govern early development and cell specification toward definitive neural crest. Here, we combine ultradense single-cell transcriptomes with machine-learning and large-scale transcriptomic and epigenomic experimental validation of selected trajectories, to provide the general principles and highlight specific features of the GRN underlying neural crest fate diversification from induction to early migration stages using Xenopus frog embryos as a model. During gastrulation, a transient neural border zone state precedes the choice between neural crest and placodes which includes multiple converging gene programs. During neurulation, transcription factor connectome, and bifurcation analyses demonstrate the early emergence of neural crest fates at the neural plate stage, alongside an unbiased multipotent-like lineage persisting until epithelial-mesenchymal transition stage. We also decipher circuits driving cranial and vagal neural crest formation and provide a broadly applicable high-throughput validation strategy for investigating single-cell transcriptomes in vertebrate GRNs in development, evolution, and disease.

Animals↗
PubMed2025

Laboratory Evolution Reveals Transcriptional Mechanisms Underlying Thermal Adaptation of Escherichia coli.

Adaptive laboratory evolution is able to generate microbial strains, which exhibit extreme phenotypes, revealing fundamental biological adaptation mechanisms. Here, we use adaptive laboratory evolution to evolve Escherichia coli strains that grow at temperatures as high as 45.3 &#xb0;C, a temperature lethal to wild-type cells. The strains adopted a hypermutator phenotype and employed multiple systems-level adaptations that made global analysis of the DNA mutations difficult. Given the challenge at the genomic level, we were motivated to uncover high-temperature tolerance adaptation mechanisms at the transcriptomic level. We employed independently modulated gene set (iModulon) analysis to reveal five transcriptional mechanisms underlying growth at high temperatures. These mechanisms were connected to acquired mutations, changes in transcriptome composition, sensory inputs, phenotypes, and protein structures. They are as follows: (i) downregulation of general stress responses while upregulating the specific heat stress responses, (ii) upregulation of flagellar basal bodies without upregulating motility and upregulation fimbriae, (iii) shift toward anaerobic metabolism, (iv) shift in regulation of iron uptake away from siderophore production, and (v) upregulation of yjfIJKL, a novel heat tolerance operon whose structures we predicted with AlphaFold. iModulons associated with these five mechanisms explain nearly half of all variance in the gene expression in the adapted strains. These thermotolerance strategies reveal that optimal coordination of known stress responses and metabolism can be achieved with a small number of regulatory mutations and may suggest a new role for large protein export systems. Adaptive laboratory evolution with transcriptomic characterization is a productive approach for elucidating and interpreting adaptation to otherwise lethal stresses.

Escherichia coli↗
PubMed2016

Loss of neurogenesis in Hydra leads to compensatory regulation of neurogenic and neurotransmission genes in epithelial cells.

Hydra continuously differentiates a sophisticated nervous system made of mechanosensory cells (nematocytes) and sensory-motor and ganglionic neurons from interstitial stem cells. However, this dynamic adult neurogenesis is dispensable for morphogenesis. Indeed animals depleted of their interstitial stem cells and interstitial progenitors lose their active behaviours but maintain their developmental fitness, and regenerate and bud when force-fed. To characterize the impact of the loss of neurogenesis in Hydra, we first performed transcriptomic profiling at five positions along the body axis. We found neurogenic genes predominantly expressed along the central body column, which contains stem cells and progenitors, and neurotransmission genes predominantly expressed at the extremities, where the nervous system is dense. Next, we performed transcriptomics on animals depleted of their interstitial cells by hydroxyurea, colchicine or heat-shock treatment. By crossing these results with cell-type-specific transcriptomics, we identified epithelial genes up-regulated upon loss of neurogenesis: transcription factors (Dlx, Dlx1, DMBX1/Manacle, Ets1, Gli3, KLF11, LMX1A, ZNF436, Shox1), epitheliopeptides (Arminins, PW peptide), neurosignalling components (CAMK1D, DDCl2, Inx1), ligand-ion channel receptors (CHRNA1, NaC7), G-Protein Coupled Receptors and FMRFRL. Hence epitheliomuscular cells seemingly enhance their sensing ability when neurogenesis is compromised. This unsuspected plasticity might reflect the extended multifunctionality of epithelial-like cells in early eumetazoan evolution.

Animals↗
PubMed2025

Transcriptional benchmark dose modeling of ultraviolet radiation-induced genomic activation in mouse skin.

The in&#xa0;vivo transcriptional response of mouse skin to ultraviolet radiation (UV-R) exposure reveals key genomic alterations associated with UV-R-induced damage but it does not provide precise dose thresholds for these effects. These initial findings provided the impetus to advance dose-response characterization by integrating benchmark dose (BMD) modeling with transcriptomic data, aiming to identify biologically relevant points of departure for gene and pathway activation. To accomplish this, mice were exposed to five erythemally weighted UV-R doses (0-40&#x2009;mJ/cm2) emitted from a UV-emitting tanning device, across six post-exposure timepoints (0-96&#x2009;h). Four analytical methods were used to estimate BMDs, with the lowest consistent response dose (LCRD) approach yielding the most sensitive estimates (1.21-3.44&#x2009;mJ/cm2). Transcriptomic responses revealed activation of shared pathways related to DNA damage and cancer, oxidative stress and metabolism, inflammation and immunity, and hormonal disruption. Notably, the majority of LCRD BMD estimates (1.21-3.44&#x2009;mJ/cm2) were lower than the International Electrotechnical Commission standard actinic exposure limit (3&#x2009;mJ/cm2 (erythemally weighted)) for broadband UV-R (200-400&#x2009;nm) for unprotected skin and the eye for an 8&#x2009;h period. These findings suggest that transcriptomic BMD modeling can detect early biological responses to UV-R at doses lower than current exposure limits.

Animals↗