SEARCH · PubMed Health

Results for “comparative transcriptomics”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,351 records · Page 75Linked to original sources

PubMed2006

Predicting cis-acting elements of Lactobacillus plantarum by comparative genomics with different taxonomic subgroups.

Cis-acting elements in Lactobacillus plantarum were predicted by comparative analysis of the upstream regions of conserved genes and predicted transcriptional units (TUs) in different bacterial genomes. TUs were predicted for two species sets, with different evolutionary distances to L.plantarum. TUs were designated 'cluster of orthologous transcriptional units' (COT) when >50% of the genes were orthologous in different species. Conserved DNA sequences were detected in the upstream regions of different COTs. Subsequently, conserved motifs were used to scan upstream regions of all TUs. This method revealed 18 regulatory motifs only present in lactic acid bacteria (LAB). The 18 LAB-specific candidate regulatory motifs included 13 that were not described previously. These LAB-specific different motifs were found in front of genes encoding functions varying from cold shock proteins to RNA and DNA polymerases, and many unknown functions. The best-described LAB-specific motif found was the CopR-binding site, regulating expression of copper transport ATPases. Finally, all detected motifs were used to predict co-regulated TUs (regulons) for L.plantarum, and transcriptome profiling data were analyzed to provide regulon prediction validation. It is demonstrated that phylogenetic footprinting using different species sets can identify and distinguish between general regulatory motifs and LAB-specific regulatory motifs.

Base Sequence↗

PubMed2025

Genomic insights into the population history of fat-tailed sheep and identification of two mutations that contribute to fat tail adipogenesis.

INTRODUCTION: Since their domestication, domestic sheep (Ovis aries) have been culturally and economically significant farming animals worldwide. Fat-tailed sheep serve as a unique genetic resource for understanding adipogenesis and adaptive evolution in livestock. OBJECTIVES: Several genomic analyses have been conducted on various sheep breeds to elucidate the genome and regulation mechanism of the fat tail trait, prior genomic studies have failed to reconcile conflicting evidence about the genetic basis of tail morphology, particularly regarding the roles of PDGFD and BMP2. METHODS: Here, we conducted whole-genome resequencing of 283 sheep, encompassing 66 domestic breeds and 5 wild ovine species, to investigate the domestication history and selection signatures of fat-tailed sheep. Additionally, we performed transcriptome sequencing on adipose tissue to identify differentially expressed genes and cellular assays to validate these results. RESULTS: Demographic analysis revealed that domestic sheep descended from Asiatic mouflon and fat-tailed sheep began to diverge from thin-tailed sheep approximately 4.4-7.5 thousand years ago in East Asia. Chinese indigenous sheep were classified into Mongolian, Kazakh, Tibetan, and Yunnan populations. The Yunnan population may have experienced more recent genetic introgression from wild species, rather than an independent domestication event. Moreover, many potential regions associated with the fat-tailed phenotype (DDI1, PDGFD, and BMP2) were identified by selective sweep and genome-wide association analyses. Additionally, a fine-scale analysis of fat-tailed and thin-tailed sheep revealed two novel mutations: a G/A missense variant of PDGFD (Chr15: 3900312) and a C/T missense variant of BMP2 (Chr13: 48462350), both of which were significantly associated with tail adiposity. Functional validation demonstrated that mutant A-PDGFD significantly activated PFGFD expression and reduced fat deposition compared to wildtype. The C-BMP2 mutant activated BMP2 expression and promoted preadipocyte fat deposition. CONCLUSION: Our study provides the first evidence that these genes jointly regulate fat tail development through complementary mechanisms: PDGFD promotes adipose expansion, whereas BMP2 modulates energy partitioning. These findings offer new insights into the evolutionary history of fat-tailed sheep and identify potential targets for precision breeding in small ruminants.

Animals↗

PubMed2003

Peptidomics: A new approach to affinity protein microarrays.

Protein microarrays for diagnostic and proteomic analyses are being developed using a number of different techniques for each of the steps required including immobilisation methods, assay and detection systems. This is extremely different to the development of DNA microarrays which is now a well established technology that has demonstrated the capabilities of transcriptomics to deliver validated differential transcripts. As mRNA and protein levels do not always correlate, protein microarrays would seem to be an obvious successor to DNA arrays. Unlike nucleic acids, however, protein targets are typically nonhomogeneous in physicochemical properties and affinity capture agents are often poorly characterised making the experiments difficult to perfect and reproduce. Moreover, running multiple affinity assays in parallel (multiplexing) is compromised by the heterogeneity of antibody affinities to their protein targets. In the peptidomic approach presented here the assayed mixture of proteins is enzymatically digested prior to affinity capture to form a mixture of short peptides that are more similar in their physicochemical properties than intact proteins. These peptides can be predicted by in silico digestion of individual proteins, e.g. from protein databases allowing design of nonhomologous reagents for the screening of affinity agent libraries. The use of mass spectrometry (e.g. matrix-assisted laser desorption/ionization-time of flight mass spectrometry) for a direct confirmation of the identity of the species captured, provides a further advantage compared to the more usual method of detection in which fluorescently labelled captured species are scanned to give a spatially resolved image of the array.

Peptides↗

PubMed2005

Differential gene expression profile between cord blood progenitor-derived and adult progenitor-derived human mast cells.

In order to better understand the mechanisms governing the display of mast cell characteristics in human mast cells (MCs), such as cord blood (CB)-derived cultured mast cells, peripheral blood (PB)-derived cultured MCs, and differentiated adult-lung cultured MCs, we examined the transcriptomes of these three types MCs using oligonucleotide microarray (GeneChip) and hierarchical clustering analysis. The expression profile of CB-derived MCs substantially differed from those of PB- and lung-derived MCs. In CB-derived MCs, we identified 132 up-regulated transcripts, such as MARCKS, KRT1, TIMP2, SERPINA1, and TLR2, and 428 down-regulated transcripts, such as LTBP3, CDC42BPA, DDO, DICER1, and FCER1A. Moreover, using RT-PCR and FACS analysis, we confirmed the expression of TLR2, which plays an important role in innate immunity, in CB-derived MCs but not in PB-derived MCs. In addition, it was observed that CB-derived MCs uniquely release histamine and CCL1, which are produced by human MCs but not by human monocytes, in response to peptidoglycan (PGN), although it had been controversy issue whether CB-derived MCs could, in fact, induce degranulation in response to PGN. These results indicated that in innate immunity MCs derived from neonatal hemopoietic cells might have unique functions compared to their adult counterparts because of different gene profiles.

Adult↗

PubMed2006

MACSIMS: multiple alignment of complete sequences information management system.

BACKGROUND: In the post-genomic era, systems-level studies are being performed that seek to explain complex biological systems by integrating diverse resources from fields such as genomics, proteomics or transcriptomics. New information management systems are now needed for the collection, validation and analysis of the vast amount of heterogeneous data available. Multiple alignments of complete sequences provide an ideal environment for the integration of this information in the context of the protein family. RESULTS: MACSIMS is a multiple alignment-based information management program that combines the advantages of both knowledge-based and ab initio sequence analysis methods. Structural and functional information is retrieved automatically from the public databases. In the multiple alignment, homologous regions are identified and the retrieved data is evaluated and propagated from known to unknown sequences with these reliable regions. In a large-scale evaluation, the specificity of the propagated sequence features is estimated to be >99%, i.e. very few false positive predictions are made. MACSIMS is then used to characterise mutations in a test set of 100 proteins that are known to be involved in human genetic diseases. The number of sequence features associated with these proteins was increased by 60%, compared to the features available in the public databases. An XML format output file allows automatic parsing of the MACSIM results, while a graphical display using the JalView program allows manual analysis. CONCLUSION: MACSIMS is a new information management system that incorporates detailed analyses of protein families at the structural, functional and evolutionary levels. MACSIMS thus provides a unique environment that facilitates knowledge extraction and the presentation of the most pertinent information to the biologist. A web server and the source code are available at http://bips.u-strasbg.fr/MACSIMS/.

Algorithms↗

PubMed2005

An atlas of human gene expression from massively parallel signature sequencing (MPSS).

We have used massively parallel signature sequencing (MPSS) to sample the transcriptomes of 32 normal human tissues to an unprecedented depth, thus documenting the patterns of expression of almost 20,000 genes with high sensitivity and specificity. The data confirm the widely held belief that differences in gene expression between cell and tissue types are largely determined by transcripts derived from a limited number of tissue-specific genes, rather than by combinations of more promiscuously expressed genes. Expression of a little more than half of all known human genes seems to account for both the common requirements and the specific functions of the tissues sampled. A classification of tissues based on patterns of gene expression largely reproduces classifications based on anatomical and biochemical properties. The unbiased sampling of the human transcriptome achieved by MPSS supports the idea that most human genes have been mapped, if not functionally characterized. This data set should prove useful for the identification of tissue-specific genes, for the study of global changes induced by pathological conditions, and for the definition of a minimal set of genes necessary for basic cell maintenance. The data are available on the Web at http://mpss.licr.org and http://sgb.lynxgen.com.

Algorithms↗

PubMed2005

Insights on the evolution of metabolic networks of unicellular translationally biased organisms from transcriptomic data and sequence analysis.

Codon bias is related to metabolic functions in translationally biased organisms, and two facts are argued about. First, genes with high codon bias describe in meaningful ways the metabolic characteristics of the organism; important metabolic pathways corresponding to crucial characteristics of the lifestyle of an organism, such as photosynthesis, nitrification, anaerobic versus aerobic respiration, sulfate reduction, methanogenesis, and others, happen to involve especially biased genes. Second, gene transcriptional levels of sets of experiments representing a significant variation of biological conditions strikingly confirm, in the case of Saccharomyces cerevisiae, that metabolic preferences are detectable by purely statistical analysis: the high metabolic activity of yeast during fermentation is encoded in the high bias of enzymes involved in the associated pathways, suggesting that this genome was affected by a strong evolutionary pressure that favored a predominantly fermentative metabolism of yeast in the wild. The ensemble of metabolic pathways involving enzymes with high codon bias is rather well defined and remains consistent across many species, even those that have not been considered as translationally biased, such as Helicobacter pylori, for instance, reveal some weak form of translational bias for this genome. We provide numerical evidence, supported by experimental data, of these facts and conclude that the metabolic networks of translationally biased genomes, observable today as projections of eons of evolutionary pressure, can be analyzed numerically and predictions of the role of specific pathways during evolution can be derived. The new concepts of Comparative Pathway Index, used to compare organisms with respect to their metabolic networks, and Evolutionary Pathway Index, used to detect evolutionarily meaningful bias in the genetic code from transcriptional data, are introduced.

Ammonia↗

PubMed2006

Quantitative proteomic and genomic profiling reveals metastasis-related protein expression patterns in gastric cancer cells.

Gastric cancer is a leading cause of death worldwide, and patients have an overall 5-year survival rate of less than 10%. Using quantitative proteomic techniques together with microarray chips, we have established comprehensive proteome and transcriptome profiles of the metastatic gastric cancer TMC-1 cells and the noninvasive gastric cancer SC-M1 cell. Our qualitative protein profiling strategy offers the first comprehensive analysis of the gastric cancer cell proteome, identifying 926 and 909 proteins from SC-M1 and TMC-1 cells, respectively. Cleavable isotope-coded affinity tagging analysis allows quantitation of a total of 559 proteins (with a protein false-positive rate of <0.005), and 240 proteins were differentially expressed (>1.3-fold) between the SC-M1 and TMC-1 cells. We identified numerous proteins not previously associated with gastric cancer. Notably, a large subset of differentially expressed proteins was associated with tumor metastasis, including proteins functioning in cell-cell and cell-extracellular matrix (cell-ECM) adhesion, cell motility, proliferation, and tumor immunity. Gene expression profiling by DNA microarray revealed differential expression (of >2-fold) of about 1000 genes. The weak correlation observed between protein and mRNA profiles highlights the important complementarities of DNA microarray and proteomics approaches. These comparative data enabled us to map the disease-perturbed cell-cell and cell-ECM adhesion and Rho GTPase-mediated cytoskeletal pathways. Further validation of a subset of genes suggests the potential use of vimentin and galectin 1 as markers for metastasis. We demonstrate that combining proteomic and genomic approaches not only provides a rapid, robust, and sensitive platform to elucidate the molecular mechanisms underlying gastric cancer metastasis but also may identify candidate diagnostic markers and therapeutic targets.

Biomarkers, Tumor↗

PubMed2004

Transcriptomic changes in human breast cancer progression as determined by serial analysis of gene expression.

INTRODUCTION: Genomic and transcriptomic alterations affecting key cellular processes such us cell proliferation, differentiation and genomic stability are considered crucial for the development and progression of cancer. Most invasive breast carcinomas are known to derive from precursor in situ lesions. It is proposed that major global expression abnormalities occur in the transition from normal to premalignant stages and further progression to invasive stages. Serial analysis of gene expression (SAGE) was employed to generate a comprehensive global gene expression profile of the major changes occurring during breast cancer malignant evolution. METHODS: In the present study we combined various normal and tumor SAGE libraries available in the public domain with sets of breast cancer SAGE libraries recently generated and sequenced in our laboratory. A recently developed modified t test was used to detect the genes differentially expressed. RESULTS: We accumulated a total of approximately 1.7 million breast tissue-specific SAGE tags and monitored the behavior of more than 25,157 genes during early breast carcinogenesis. We detected 52 transcripts commonly deregulated across the board when comparing normal tissue with ductal carcinoma in situ, and 149 transcripts when comparing ductal carcinoma in situ with invasive ductal carcinoma (P < 0.01). CONCLUSION: A major novelty of our study was the use of a statistical method that correctly accounts for the intra-SAGE and inter-SAGE library sources of variation. The most useful result of applying this modified t statistics beta binomial test is the identification of genes and gene families commonly deregulated across samples within each specific stage in the transition from normal to preinvasive and invasive stages of breast cancer development. Most of the gene expression abnormalities detected at the in situ stage were related to specific genes in charge of regulating the proper homeostasis between cell death and cell proliferation. The comparison of in situ lesions with fully invasive lesions, a much more heterogeneous group, clearly identified as the most importantly deregulated group of transcripts those encoding for various families of proteins in charge of extracellular matrix remodeling, invasion and cell motility functions.

Apoptosis↗

PubMed2024

An easy-to-use pipeline to analyze amplicon-based Next Generation Sequencing results of human mitochondrial DNA from degraded samples.

Genome and transcriptome examinations have become more common due to Next-Generation Sequencing (NGS), which significantly increases throughput and depth coverage while reducing costs and time. Mitochondrial DNA (mtDNA) is often the marker of choice in degraded samples from archaeological and forensic contexts, as its higher number of copies can improve the success of the experiment. Among other sequencing strategies, amplicon-based NGS techniques are currently being used to obtain enough data to be analyzed. There are some pipelines designed for the analysis of ancient mtDNA samples and others for the analysis of amplicon data. However, these pipelines pose a challenge for non-expert users and cannot often address both ancient and forensic DNA particularities and amplicon-based sequencing simultaneously. To overcome these challenges, a user-friendly bioinformatic tool was developed to analyze the non-coding region of human mtDNA from degraded samples recovered in archaeological and forensic contexts. The tool can be easily modified to fit the specifications of other amplicon-based NGS experiments. A comparative analysis between two tools, MarkDuplicates from Picard and dedup parameter from fastp, both designed for duplicate removal was conducted. Additionally, various thresholds of PMDtools, a specialized tool designed for extracting reads affected by post-mortem damage, were used. Finally, the depth coverage of each amplicon was correlated with its level of damage. The results obtained indicated that, for removing duplicates, dedup is a better tool since retains more non-repeated reads, that are removed by MarkDuplicates. On the other hand, a PMDS = 1 in PMDtools was the threshold that allowed better differentiation between present-day and ancient samples, in terms of damage, without losing too many reads in the process. These two bioinformatic tools were added to a pipeline designed to obtain both haplotype and haplogroup of mtDNA. Furthermore, the pipeline presented in the present study generates information about the quality and possible contamination of the sample. This pipeline is designed to automatize mtDNA analysis, however, particularly for ancient samples, some manual analyses may be required to fully validate results since the amplicons that used to be more easily recovered were the ones that had fewer reads with damage, indicating that special care must be taken for poor recovered samples.

DNA, Mitochondrial↗

PubMed2026

engGNN: a dual-graph neural network for omics-based disease classification and feature selection.

Omics data, such as transcriptomics, proteomics, and metabolomics, provide critical insights into disease mechanisms and clinical outcomes. However, their high dimensionality, small sample sizes, and intricate biological networks pose major challenges for reliable prediction and meaningful interpretation. Graph neural networks offer a promising way to integrate prior knowledge by encoding feature relationships as graphs. Yet, existing methods typically rely solely on either an externally curated feature graph or a data-driven generated graph, which limits their ability to capture complementary information. To address this, we propose the external and generated Graph Neural Network (engGNN), a dual-graph framework that jointly leverages both external biological networks and data-driven generated graphs. Specifically, engGNN constructs a biologically informed undirected feature graph from established network databases and complements it with a directed feature graph derived from tree-ensemble models. This dual-graph design produces more comprehensive representations, thereby improving predictive performance and interpretability. Through extensive simulation studies and real-world applications to three independent gene expression datasets, engGNN consistently demonstrates strong classification performance compared with competitive baselines. Beyond classification, engGNN provides feature- and source-level interpretability, enabling biologically meaningful analyses such as pathway enrichment analysis. Taken together, these results highlight engGNN as a robust, flexible, and interpretable framework for disease classification and biomarker discovery in high-dimensional omics contexts.

Graph Neural Networks↗

PubMed2006

Insights into the immune transcriptome of the shrimp Litopenaeus vannamei: tissue-specific expression profiles and transcriptomic responses to immune challenge.

Infectious disease constitutes a major obstacle to the sustainability of shrimp aquaculture worldwide and a significant threat to natural populations of shrimp and other crustacea. The study of the shrimp immune system, including the response to viral infection, has been hampered by a relative lack of molecular genetic information and of tools suitable for high-throughput assessment of gene expression. In this report, the generation of a cDNA microarray encompassing 2,469 putative unigenes expressed in gills, circulating hemocytes, and hepatopancreas of Litopenaeus vannamei is described. The unigenes printed on the microarray were derived from the analyses of 7,021 expressed sequence tags obtained from standard cDNA libraries as well as from libraries generated by suppression subtractive hybridization, after challenging shrimp with a variety of immune stimuli. The general utility of the cDNA microarray was demonstrated by interrogating the array with labeled RNA from four different shrimp tissues (gills, hemocytes, hepatopancreas, and muscle) and by analyzing the transcriptomic response of shrimp to a lethal challenge with white spot syndrome virus. Our results indicate that white spot syndrome virus infection upregulates (in the hepatopancreas) genes encoding known and potential antimicrobial effectors, while some genes involved in protection from oxidative stress were found to be downregulated by the virus.

Animals↗

PubMed2025

Genotype by Environment Interactions in Gene Regulation Underlie the Response to Soil Drying in the Model Grass Brachypodium distachyon.

Gene expression is a quantitative trait under the control of genetic and environmental factors and their interaction, so-called genotype and environment (G × E). Understanding the mechanisms driving G × E is fundamental for ensuring stable crop performance across environments and for predicting the response of natural populations to climate change. Gene expression is regulated through complex molecular networks, yet the interactions between genotype and environment in gene regulation are rarely considered, particularly at the genome scale. Current frameworks and experimental designs often lack power to explicitly test network rewiring or to systematically compare regulatory networks. Here, we leverage a highly replicated RNA-sequencing dataset to model genome-scale gene expression variation between two natural accessions of the model grass Brachypodium distachyon and their response to soil drying. We first identified genotypic, environmental, and G × E effects on physiological, metabolic, and gene expression traits. We identify patterns of conservation-or variation-in gene coexpression networks and link these coexpression features to physiological traits. We further develop predictions of gene-gene interactions using causal inference and screen for interactions specific to-or with higher affinity in-a single genotype, treatment, or their interaction, G × E. Our analyses identify variation in candidate gene regulatory networks that may shape the evolution of environmental response in B. distachyon. We highlight the environmentally dependent regulatory control of several metabolic traits shown previously to play a role in drought acclimation. The framework presented here provides a scalable approach for more complex comparisons, particularly with the growing availability of large datasets from technologies such as single-cell transcriptomics.

Brachypodium↗

PubMed2004

FlyGEM, a full transcriptome array platform for the Drosophila community.

We have constructed a DNA microarray to monitor expression of predicted genes in Drosophila. By using homotypic hybridizations, we show that the array performs reproducibly, that dye effects are minimal, and that array results agree with systematic northern blotting. The array gene list has been extensively annotated and linked-out to other databases. Incyte and the NIH have made the platform available to the community via academic microarray facilities selected by an NIH committee.

Animals↗

PubMed2004

Identification of lineage-specific zygotic transcripts in early Caenorhabditis elegans embryos.

During Caenorhabditis elegans embryogenesis, a maternally supplied transcription factor, SKN-1, is required for the specification of the mesendodermal precursor, EMS, in the 4-cell stage embryo. When EMS divides, it gives rise to a mesoderm-restricted precursor, MS, and an endoderm-restricted precursor, E. To systematically identify genes that function as key regulators of MS and/or E-derived tissues, we identified, by microarray analyses, genes that are newly transcribed within a short developmental window (approximately 30 min) encompassing the generation and fate specification of the MS and E blastomeres. By comparing total cDNAs generated from individual, carefully staged embryos, we identified 275 genes up-regulated in 12-cell embryos compared to 4-cell embryos. Fifty of these 275 genes are down-regulated in 12-cell skn-1 mutant embryos and are designated skn-1-dependent zygotic (sdz) genes. The spatial and temporal expression patterns in C. elegans embryos of 10 randomly selected sdz genes were analyzed by a nuclear GFP reporter driven by the endogenous 5' regulatory sequence of each gene. GFP expression, although absent at the 4-cell stage, was detected at the 12- to 16-cell stage for all 10 genes and was restricted to EMS-derived lineages for 7 of the 10. Among the seven lineage-specific genes, three genes are expressed equally in both MS and E lineages, two are expressed exclusively or predominantly in the MS lineage, and two are expressed exclusively in the E lineage. Depletion of skn-1 by RNAi abolishes the expression of all seven reporter transgenes in vivo, confirming that these genes are indeed skn-1 dependent. These results demonstrate the successful combination of single-staged embryo cDNAs, genetic mutants, and whole transcriptome microarray analysis to identify stage- and lineage-specific transcripts in early C. elegans embryos.

Animals↗

PubMed2003

Aldosteronism and peripheral blood mononuclear cell activation: a neuroendocrine-immune interface.

Aldosteronism eventuates in a proinflammatory/fibrogenic vascular phenotype of the heart and systemic organs. It remains uncertain whether peripheral blood mononuclear cells (PBMCs) are activated before tissue invasion by monocytes/macrophages and lymphocytes, as is the case for responsible pathogenic mechanisms. Uninephrectomized rats treated for 4 weeks with dietary 1% NaCl and aldosterone (ALDOST, 0.75 microg/h) with or without spironolactone (Spi, 100 mg/kg per daily gavage) were compared with unoperated/untreated and uninephrectomized/salt-treated controls. Before intramural coronary vascular lesions appeared at week 4 of ALDOST, we found (1) a reduction of PBMC cytosolic free [Mg2+]i, together with intracellular Mg2+ and Ca2+ loading, whereas plasma and cardiac tissue Mg2+ were no different from controls; (2) increased H2O2 production by monocytes and lymphocytes together with upregulated PBMC gene expression of oxidative stress-inducible tyrosine phosphatase and Mn2+-superoxide dismutase and the presence of 3-nitrotyrosine in CD4+ and ED-1-positive inflammatory cells that had invaded intramural coronary arteries; (3) B-cell activation, including transcription of immunoglobulins, intracellular adhesion molecule-1, and CC and CXC chemokines and their receptors; (4) expansion of B lymphocyte subset and myosin heavy chain class II-expressing lymphocytes; and (5) autoreactivity with gene expression for antibodies to acetylcholine receptors and a downregulation of RT-6.2, which is in keeping with cell activation and associated with autoimmunity. Spi cotreatment attenuated the rise in intracellular Ca2+, the appearance of oxidative/nitrosative stress in PBMCs and invading inflammatory cells, and alterations in PBMC transcriptome. Thus, aldosteronism is associated with an activation of circulating immune cells induced by iterations in PBMC divalent cations and transduced by oxidative/nitrosative stress. ALDO receptor antagonism modulates this neuroendocrine-immune interface. The full text of this article is available online at http://www.circresaha.org.

Aldosterone↗

PubMed2004

Generation of a bovine oocyte cDNA library and microarray: resources for identification of genes important for follicular development and early embryogenesis.

The oocyte is a key regulator of ovarian folliculogenesis and early embryonic development. However, the composition of the oocyte transcriptome and identities and functions of key oocyte-specific genes involved in the above processes are relatively unknown. Using a PCR-based cDNA amplification method (SMART technology), we constructed a bovine oocyte cDNA library. Analysis of 230 expressed sequence tags (ESTs) from this library identified 102 unique sequences. Although some correspond to housekeeping genes (e.g., ribosomal protein L15) and some represent genes previously known to be expressed in oocytes and other tissues, most encode for genes whose expression in mammalian oocytes has not been reported previously (e.g., cocaine- and amphetamine-regulated transcript) or genes of unknown function. Sixteen did not show significant sequence similarity to any entries in the GenBank database and were classified as novel. Using over 2,000 unsequenced, randomly selected cDNA clones from the library, we constructed an oocyte microarray and performed experiments to identify genes preferentially expressed in fetal ovary (an enriched source of oocytes) relative to somatic tissues. Eleven clones were identified by microarray analysis with consistently higher expression in fetal ovaries (collected from animals at days 210-260 of gestation) compared with spleen and liver. DNA sequence analysis of these clones revealed that two correspond to JY-1, a novel bovine oocyte-specific gene. The remaining nine clones represent five identified genes and one additional completely novel gene. Increased abundance of mRNA in fetal ovary for five of the six genes identified was confirmed by real-time PCR. Results demonstrate the potential utility of these unique resources for identification of oocyte-expressed genes potentially important for reproductive function.

Animals↗

PubMed2026

Construction of molecular signatures based on the co-expression network of NECSO-related gene TRPM4 and its prognostic value in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) demonstrates significant prognostic variability that is not entirely accounted for by traditional staging systems. Necrosis by sodium overload (NECSO) is an emerging programmed cell death pathway, but its clinical relevance in HCC remains undefined. Therefore, this study aimed to identify TRPM4-associated core genes, develop and validate a prognostic signature, and investigate its relationship with the tumor immune microenvironment, tumor mutational burden, and single-cell expression patterns in HCC. METHODS: We integrated transcriptomic, clinical, and mutational datasets from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) (n=421) and Gene Expression Omnibus (GEO) cohorts (n=115) to identify genes co-expressed with TRPM4-a key NECSO mediator-and those differentially expressed in HCC. A prognostic signature was developed using least absolute shrinkage and selection operator (LASSO)-Cox regression and validated through survival analysis, time-dependent receiver operating characteristic (ROC) curves, and multivariate Cox regression analysis. The immune landscape was characterized using CIBERSORT, somatic mutation data were used to calculate tumor mutational burden (TMB) and assess its correlation with the risk score, and single-cell RNA sequencing (scRNA-seq) resolved cell-type-specific expression patterns. RESULTS: From 294 TRPM4-associated core genes, we identified an 11-gene signature (BRSK1, MMP1, GRIN2D, GP6, MYOM2, N4BP3, CCDC112, TSEN54, MAP3K9, SPP1, B3GNT4) that independently predicted overall survival (OS) (hazard ratio =5.419, P<0.001) with areas under the curve (AUCs) of 0.779, 0.693, and 0.701 at 1, 3, and 5 years. These values were superior or comparable to conventional clinicopathologic variables after direct comparison. High-risk patients exhibited an immunosuppressive microenvironment, characterized by enrichment of M0 macrophage, a higher M2/M1 ratio (P<0.001) and distinct immune checkpoint profiles. When integrated with TMB, the prognostic stratification was further refined: high-TMB/high-risk patients had poorest outcomes (median OS, 15.3 months), while low-TMB/low-risk patients had the most favorable survival (median OS, 68.7 months). Single-cell analysis revealed that MMP1 was induced in cancer-associated fibroblasts (CAFs) and SPP1 was downregulated in macrophages, single-cell risk scores confirmed TAFs and macrophages as the main contributors to the prognostic model. CONCLUSIONS: The TRPM4-centered 11-gene signature provides robust and independent prognostic stratification in HCC by integrating immune, mutational, and single-cell features. This signature serves as a potential tool for prognostic evaluation and may help inform immunotherapeutic strategies for HCC.

Hepatocellular carcinoma (HCC)↗