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PubMed2026

Metabolism pathway-based subtyping in pancreatic adenocarcinoma: an integrated study by bulk RNA-sequence and machine learning algorithms.

BACKGROUND: Pancreatic adenocarcinoma (PAAD) is highly aggressive, and its tumor microenvironment has significant metabolic and immune microenvironment complexity and genomic instability. In this study, by integrating the metabolic pathway activity score and clinical data, we constructed a novel risk assessment model to reveal the unique biological behavior and clinical significance behind different PAAD subtypes. METHODS: In this study, the transcriptome and clinical data of TCGA and GSE57495 databases were integrated to explore the interaction between metabolic pathways. Based on unsupervised clustering analysis of pathway activity and survival prognosis, patients with PAAD were classified into metabolic subtypes with significant prognostic differences. Subsequently, we assessed the heterogeneity of these subtypes in terms of clinical outcomes, genomic characteristics, and immune microenvironment composition. Based on the differentially expressed genes (DEGs) among metabolic subtypes, a clinical prognostic risk model and nomogram were constructed, which were double-validated by GSE57495-independent cohort and GSE57495 + TCGA-PAAD combined cohort. Finally, the correlations between risk scores (RSs) and signaling pathway activity and tumor immune microenvironment characteristics were evaluated. RESULTS: Based on metabolic pathway correlation and prognostic information, 240 patients in the TCGA-PAAD and GSE57495 datasets were divided into three subgroups. There were significant differences between subgroups in gene expression, pathway activity, clinical prognosis, and immune infiltration characteristics among the subtypes. Using machine learning algorithms, an RS model was constructed from DEGs among the subgroups, with the random forest method showing the best performance. A nomogram integrating the RS and clinical indicators demonstrated excellent predictive accuracy for 1-, 3-, and 5-year survival rates, confirming the RS as an independent prognostic factor. High- and low-risk groups exhibited significant differences in immune infiltration, pathway activity, and gene mutations. Drug sensitivity analysis showed that the high-risk group was more sensitive to AZD6244, ABT737, and other drugs. CONCLUSION: This study stratified patients with PAAD into three subgroups based on metabolic pathways and prognostic information, revealing significant differences in clinical outcomes, immune characteristics, and genetic mutations. The robust RS model developed from these findings demonstrated strong predictive power for patient survival and identified promising therapeutic strategies, providing valuable insights for advancing precision medicine in PAAD.

immune microenvironment↗
PubMed2003

Protein arrays: the current state-of-the-art.

The completion of projects for sequencing whole genomes such as those of human, Saccaromyces cerevisiae and Caenorhabditis elegans has led to a rapid increase in the availability of genetic information. The technology by which such information is acquired is having a major impact on the way we think about analysing the RNA and protein products of the gene transcription. Transcriptome analysis has, via microarray technology, managed to achieve a near genomic scale quantitative analysis of mRNA levels. Several other technologies such as quantitative reverse transcriptase polymerase chain reaction and representational differential analysis are also available for analysing gene products. Traditionally, protein analysis has been performed by assaying one particular protein at a time, with very little parallel analysis. As protein function is a direct consequence of the protein product of the gene and as mRNA levels do not always correlate well with protein, it is desirable to analyse the entire protein complement of a cell etc. on a similar scale to mRNA. Despite the clear interest in analysing the expression, structure and function of proteins at a genomic scale, they have proven less amenable to such generic, high-throughput approaches. This review highlights the current thinking in the area of proteome analysis and considers the potential for future technology development in the area of protein arrays.

Animals↗
PubMed2002

Impact of genomics approaches on plant genetics and physiology.

Comprehensive analysis of genetic information in higher plants is under way for several plants of biological and agronomical importance. Among them, Arabidopsis thaliana, a member of Brassica family, and Oryza sativa(rice) have been chosen as model plants most suitable for genome analysis. Sequencing of the genome of A. thaliana was completed in December 2000, and rice genome sequencing is in progress. The accumulated genome sequences, together with the hundreds of thousands of ESTs from several tens of plant species, have drastically changed the strategy of plant genetics. By utilizing the information on the genome and gene structures, comprehensive approaches for genome-wide functional analysis of the genes, including transcriptome analysis using microarray systems and a comprehensive analysis of a large number of insertion mutant lines, have been widely adopted. As a consequence, a large quantity of information on both the structure and function of genes in these model plants has been accumulated. However, other plant species may have their own characteristics and advantages to study individual phenomena. Application of knowledge from the model plants to other plant species and vice versa through the common language, namely the genome information, should facilitate understanding of the genetic systems underlying a variety of biological phenomena. Introduction of this common language may not be very simple, especially in the case of complex pathways such as a process of cell-covering formation. Nevertheless, it should be emphasized that genomics approaches are the most promising way to understand these processes.

Journal Article↗
PubMed2006

Connexin43 and the brain transcriptome of newborn mice.

Our previously reported cDNA array datasets from neonatal wild-type and Cx43-/- (approved gene symbol Gja1) mouse brains were further analyzed to identify underlying interlinkages in the brain transcriptome. The analysis revealed that no gene cohort sharing either primary function or chromosomal location was significantly altered (up-and down-regulation were roughly balanced) in Cx43-/- brains, but each cohort exhibited significant perturbation of transcript abundance proportions and reduced expression variability and coordination. By comparing pairwise expression correlations of all genes with one another in wild-type brains, we found genes exhibiting remarkable similarity or opposition to the coordination profile (set of synergistically, antagonistically, and independently expressed partners) of Cx43, one of the most similar being pannexin1, a vertebrate homolog of invertebrate gap junction proteins. This study indicates striking redundancy of expression controls over functional pathways and suggests that certain genes may play roles similar to or opposite that of Cx43 in organizing the brain transcriptome.

Animals↗
PubMed2005

Microarrays: new tools to unravel parasite transcriptomes.

The ability to monitor the expression levels of thousands of genes in a single microarray experiment is a huge progression from conventional Northern blot analysis or PCR-based techniques. Microarrays can play a pivotal role in the mass screening of genes in a wide range of fields including parasitology. The relatively few parasites that can be readily cultured or isolated from a host, as compared with cell lines or tissue sources, makes microarray technology ideal for maximizing experimental results from a limiting source of starting material. Khan et al. (1999 a) commented in an early review of microarray technology " With this system in place, one can anticipate a time when data from thousands of gene expression experiments will be available for meta-analysis........leading to more robust results and subtle conclusions". Now in 2005, microarrays represent a very powerful resource that can play an important role in the characterization and annotation of the transcriptomes of many parasites of medical and veterinary importance.

Animals↗
PubMed2002

The xanthomonas type III effector protein AvrBs3 modulates plant gene expression and induces cell hypertrophy in the susceptible host.

Xanthomonas campestris pv. vesicatoria bacteria expressing the type III effector protein AvrBs3 induce a hypersensitive response in pepper plants carrying the resistance gene Bs3. Here, we report that infection of susceptible pepper and tomato plants leads to an AvrBs3-dependent hypertrophy of the mesophyll tissue. Agrobacterium-mediated transient expression of the avrBs3 gene in tobacco and potato plants resulted in a similar phenotype. Induction of hypertrophy was shown to depend on the repeat region, nuclear localization signals, and acidic transcription activation domain (AAD) of AvrBs3, suggesting that the effector modulates the host's transcriptome. To search for host genes regulated by AvrBs3 in an AAD-dependent manner, we performed a cDNA-amplified fragment length polymorphism analysis of pepper mRNA populations. Thirteen AvrBs3-induced transcripts were identified and confirmed by reverse transcriptase-polymerase chain reaction. Sequence analysis revealed homologies to auxin-induced and expansinlike genes, which play a role in cell enlargement. These results suggest that some of the AvrBs3-induced genes may be involved in hypertrophy development and that xanthomonads possess type III effectors that steer host gene expression.

Bacterial Proteins↗
PubMed2005

Reduced expression of antigenic proteins MPB70 and MPB83 in Mycobacterium bovis BCG strains due to a start codon mutation in sigK.

Mycobacterium bovis Bacille Calmette-Guerin (BCG) strains are genetically and phenotypically heterogeneous. Expression of the antigenic proteins MPB70 and MPB83 is known to vary considerably across BCG strains; however, the reason for this phenotypic difference has remained unknown. By immunoblot, we separated BCG into high- and low-producing strains. By quantitative reverse transcription polymerase chain reaction (RT-PCR), we determined that transcription of the antigen-encoding genes, mpb70 and mpb83, follows the same strain pattern with mRNA levels reduced over 50-fold in low-producing strains. Transcriptome comparison of the same BCG strains by DNA microarray revealed two gene regions consistently downregulated in low-producing strains compared with high-producing strains, one including mpb70 (Rv2875) and mpb83 (Rv2873) and a second that includes the predicted sigma factor, sigK. DNA sequence analysis revealed a point mutation in the start codon of sigK in all low-producing BCG strains. Complementation of a low-producing strain, BCG Pasteur, with wild-type sigK fully restored MPB70 and MPB83 production. Microarray-based analysis and confirmatory RT-PCR of the complemented strains revealed an upregulation in gene transcription limited to the sigK and the mpb83/mpb70 gene regions. These data demonstrate that a mutation of sigK is responsible for decreased expression of MPB70 and MPB83 in low-producing BCG strains and provide clues into the role of Mycobacterium tuberculosis SigK.

Antigens, Bacterial↗
PubMed2002

Speculations on the role of natural antisense transcripts in mammalian X chromosome evolution.

Recent comprehensive transcriptome analyses in mice have revealed tremendous numbers of natural antisense transcripts in a hitherto ignored category of genes in eukaryotes. We discuss the possible biological roles of these transcripts and their relationships with mammalian sex chromosome evolution. Of 60,770 full-length cDNA sequences, as many as 2,500 pairs of sense-antisense transcripts (SATs) with the potential to form RNA duplex via their complementary sequences have been identified. This high number of antisense transcripts indicates their generic roles in gene expression regulation. These SATs are almost evenly distributed along the chromosomes, with the exception of the X chromosome. The rate of occurrence of SATs on the X chromosome is one-third to one-half that on the autosomes, and this under-representation must be related to a property intrinsic to the X chromosome. Here we hypothesize that monoallelically expressed antisense RNA regulates its sense partner, but that this regulatory system cannot operate on the mammalian X chromosome, as the mammalian X chromosome is effectively in a hemizygous state in both sexes. Loss of such regulation may be involved in the evolution of the X chromosome itself.

Animals↗
PubMed2005

SREBP-1 as a transcriptional integrator of circadian and nutritional cues in the liver.

The act of feeding in mammals can generate such powerful cues for peripheral organs that, under certain conditions, they can override the entraining signals coming from the clock in the brain. Restricting the feeding time to the inactivity period, for example, can completely and quickly reverse the rhythms of gene expression in the liver. This manipulation does not affect the central oscillator in the suprachiasmatic nucleus, which is phase-locked to the light-dark cycle, but does release the peripheral oscillations in the liver from central control. It seems reasonable to predict the existence of one or more immediate response systems designed to sense the need to acutely reverse the sequence of absorptive and postabsorptive phases in the liver. In this study, the authors monitored the posttranslational activation of the sterol response element binding proteins from a circadian point of view to evaluate the role they might play in the circadian organization of the liver transcriptome as well as in the reversal of hepatic physiology that accompanies diurnal restricted feeding. This study highlights a possible direct link between the immediate effects of food consumption on the level of key membrane and humoral factors and the expression status of a set of coordinately regulated target genes in the liver.

Animals↗
PubMed2026

Cyclin-dependent kinase 4 and 6 inhibitors and the breast cancer immune ecosystem: immune remodeling, resistance, and therapeutic reprogramming.

Cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6 inhibitors) combined with endocrine therapy have become a therapeutic backbone for hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer, yet durable disease control is frequently limited by intrinsic and acquired resistance. Canonical tumor-cell mechanisms, including retinoblastoma-pathway escape, cyclin E-cyclin-dependent kinase 2 (CDK2) activation, endocrine adaptation, and phosphoinositide 3-kinase (PI3K)-AKT-mechanistic target of rapamycin (mTOR) signaling, explain only part of this failure because they do not fully capture dynamic immune and stromal remodeling. Preclinical and translational studies indicate that early CDK4/6 inhibition can enhance antigen presentation, activate interferon-related programs, restrain regulatory T cells, and promote a T-cell-inflamed state. These effects are conditional and may not persist during prolonged treatment. Sustained therapy can instead drive heterogeneous resistant niches characterized by stromal remodeling, myeloid recruitment, checkpoint adaptation, and T-cell dysfunction. This immune-state dependence provides a rationale for immune checkpoint blockade, although clinical combinations have shown mixed efficacy and clinically relevant hepatic, pulmonary, and hematologic toxicities. Sequential or lead-in strategies therefore warrant prospective evaluation. Oxidative phosphorylation (OXPHOS) and redox adaptation may sustain selected resistant states and expose context-dependent ferroptotic vulnerabilities. Ferroptosis may connect tumor-cell killing with immune regulation, whereas nanomedicine may improve tumor-selective delivery. Both strategies remain largely preclinical and require further evaluation of pharmacokinetics, biodistribution, toxicity, manufacturability, and immune-cell safety. This Review distinguishes intrinsic from acquired resistance across interpatient, intratumoral, spatial, and temporal dimensions. It integrates tumor-cell escape with cytokine, immune, stromal, vascular, and metabolic remodeling and summarizes emerging therapeutic strategies. We further propose a candidate biomarker-informed framework that integrates genomic profiling, spatial immune architecture, circulating biomarkers, T-cell receptor (TCR) dynamics, transcriptomic and single-cell analyses, artificial intelligence (AI)-assisted multimodal integration, and longitudinal sampling. This framework is intended to support biomarker development and prospective trial design rather than current clinical decision-making, providing a translational basis for testing state-informed and sequence-aware therapeutic strategies.

Humans↗
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↗
PubMed1999

Serial microanalysis of renal transcriptomes.

Large-scale gene expression studies can now be routinely performed on macroamounts of cells, but it is unclear to which extent current methods are valuable for analyzing complex tissues. In the present study, we used the method of serial analysis of gene expression (SAGE) for quantitative mRNA profiling in the mouse kidney. We first performed SAGE at the whole-kidney level by sequencing 12,000 mRNA tags. Most abundant tags corresponded to transcripts widely distributed or enriched in the predominant kidney epithelial cells (proximal tubular cells), whereas transcripts specific for minor cell types were barely evidenced. To better explore such cells, we set up a SAGE adaptation for downsized extracts, enabling a 1, 000-fold reduction of the amount of starting material. The potential of this approach was evaluated by studying gene expression in microdissected kidney tubules (50,000 cells). Specific gene expression profiles were obtained, and known markers (e.g., uromodulin in the thick ascending limb of Henle's loop and aquaporin-2 in the collecting duct) were found appropriately enriched. In addition, several enriched tags had no databank match, suggesting that they correspond to unknown or poorly characterized transcripts with specific tissue distribution. It is concluded that SAGE adaptation for downsized extracts makes possible large-scale quantitative gene expression measurements in small biological samples and will help to study the tissue expression and function of genes not evidenced with other high-throughput methods.

Animals↗
PubMed2003

Open architecture expression profiling of plant transcriptomes and gene discovery using GeneCalling technology.

The recent rapid developments in genomics tools, technologies, and bioinformatics have revolutionized gene expression analysis. It is now routine to measure gene expression modulation at the genomic level. GeneCalling technology is an open architecture system capable of assaying more than 95% of genes expressed in a tissue. Unlike the closed systems, GeneCalling is not dependent upon an existing sequence or clone database. GeneCalling uses as low as 50 pg of the cDNA from samples and identifies cDNA fragments that are differentially modulated within a set of samples. With the use of 96 pairs of restriction enzymes, more than 30,000 cDNA fragments are routinely assayed to identify those that are differentially modulated. Specific processes, such as SeqCalling, Trace Poisoning, and GeneCall Poisoning, are set up to not only confirm the known genes, but also to clone and analyze unknown and novel genes that have an interesting expression profile. GeneCalling has been successfully applied to expression profiling of several plant and fungal species, and resulted in identification and characterization of genes that are useful in commercial applications towards improving agriculturally important traits in plants.

DNA, Complementary↗
PubMed2006

Genetic algorithm learning as a robust approach to RNA editing site prediction.

BACKGROUND: RNA editing is one of several post-transcriptional modifications that may contribute to organismal complexity in the face of limited gene complement in a genome. One form, known as C --> U editing, appears to exist in a wide range of organisms, but most instances of this form of RNA editing have been discovered serendipitously. With the large amount of genomic and transcriptomic data now available, a computational analysis could provide a more rapid means of identifying novel sites of C --> U RNA editing. Previous efforts have had some success but also some limitations. We present a computational method for identifying C --> U RNA editing sites in genomic sequences that is both robust and generalizable. We evaluate its potential use on the best data set available for these purposes: C --> U editing sites in plant mitochondrial genomes. RESULTS: Our method is derived from a machine learning approach known as a genetic algorithm. REGAL (RNA Editing site prediction by Genetic Algorithm Learning) is 87% accurate when tested on three mitochondrial genomes, with an overall sensitivity of 82% and an overall specificity of 91%. REGAL's performance significantly improves on other ab initio approaches to predicting RNA editing sites in this data set. REGAL has a comparable sensitivity and higher specificity than approaches which rely on sequence homology, and it has the advantage that strong sequence conservation is not required for reliable prediction of edit sites. CONCLUSION: Our results suggest that ab initio methods can generate robust classifiers of putative edit sites, and we highlight the value of combinatorial approaches as embodied by genetic algorithms. We present REGAL as one approach with the potential to be generalized to other organisms exhibiting C --> U RNA editing.

Algorithms↗
PubMed2026

Construction and validation of a β-hydroxybutyrylation-related molecular model for predicting prognosis of papillary thyroid carcinoma.

BACKGROUND: Papillary thyroid carcinoma (PTC) usually has a favorable prognosis, yet a subset of patients develops persistent, recurrent, or biologically aggressive disease. The clinical relevance of lysine β-hydroxybutyrylation (Kbhb)-related transcriptional programs in PTC remains unclear. Accordingly, this study aimed to characterize Kbhb-related molecular heterogeneity in PTC, construct a prognostic signature, and explore its association with the tumor microenvironment (TME). METHODS: Transcriptomic and clinical data from PTC samples within The Cancer Genome Atlas Thyroid Carcinoma (TCGA-THCA) cohort were analyzed to identify Kbhb-related differentially expressed genes (DEGs), define molecular subtypes, construct a prognostic signature, and characterize tumor microenvironmental features. Single-cell RNA-sequencing data from PTC were further used to explore the cellular distribution of representative genes. RESULTS: We identified 51 Kbhb-related DEGs in PTC and defined two Kbhb molecular subtypes. The Kbhb_C2 subtype showed shorter progression-free interval (PFI) and a more immune- and stroma-enriched microenvironment. A six-gene prognostic signature comprising TARID, CDSN, PIMREG, KLRC1, SYT13, and NPR3 was then established. High-risk patients had significantly worse PFI in the full, training, and testing cohorts, with 1-, 3-, and 5-year areas under the curve (AUCs) of 0.715, 0.793, and 0.771, respectively, in the full cohort. High-risk tumors also exhibited higher stromal, immune, and ESTIMATE scores, altered immune infiltration, and increased expression of multiple immune checkpoint molecules. Single-cell analysis confirmed distinct cell-type-specific expression patterns of representative genes. CONCLUSIONS: Kbhb-related transcriptional programs define clinically relevant molecular heterogeneity in PTC and are closely associated with prognosis and TME remodeling. The identified six-gene signature provides a biologically interpretable framework for risk stratification in PTC.

Papillary thyroid carcinoma (PTC)↗
PubMed2026

Placenta-derived Exosomes Mitigate Hypoxia-Induced Trophoblast Apoptosis and Inflammatory Progression via SASH1.

SASH1 is a signal adaptor protein involved in cell growth, apoptosis, and immune regulation, and has been increasingly studied in tumor and immune cells. Emerging evidence suggests that SASH1 plays an important role in inflammatory responses and cellular homeostasis, processes that are closely associated with the development of PE. This study aimed to determine whether SASH1 contributes to trophoblast apoptosis and inflammatory responses in PE and whether P-EXOS exerts protective effects through SASH1 regulation. In this study, three PE-related transcriptomic datasets (GSE75010, GSE10588, and GSE60438) were analyzed to identify shared differentially expressed genes (DEGs), followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Machine learning algorithms were further applied to screen key candidate genes, and single-cell RNA sequencing data were used to characterize cellular heterogeneity in placental tissue and to determine cell type-specific expression patterns. SASH1 was identified as a consensus candidate gene and was significantly upregulated in trophoblast cells from PE samples. In vitro, a hypoxia-treated HTR-8/SVneo trophoblast cell model was established, combined with SASH1 knockdown, SASH1 overexpression, and co-culture with P-EXOS. Functional experiments showed that knockdown of SASH1 significantly suppressed hypoxia-induced trophoblast apoptosis and reduced the secretion of pro-inflammatory cytokines, including IL-6, IL-1β, and TNF-α, whereas SASH1 overexpression promoted apoptosis and inflammatory responses. In addition, P-EXOS treatment markedly reduced SASH1 expression at both mRNA and protein levels and attenuated hypoxia-induced trophoblast injury, while SASH1 overexpression largely abolished these protective effects. Taken together, these findings indicate that SASH1 plays a critical role in trophoblast apoptosis and inflammatory responses in PE. P-EXOS may alleviate hypoxia-induced trophoblastic injury by suppressing SASH1 expression, providing new insights into the molecular mechanisms and potential therapeutic targets for PE.

Trophoblasts↗
PubMed2026

Identifying Co-Expressed lncRNAs Correlated With Traits of Interest in an Animal Model for Metabolic Diseases in Humans.

Nutrigenomics investigates how nutrients modulate gene expression. Among them, fatty acids (FA) play important roles in regulating gene transcription, while long non-coding RNAs (lncRNAs) may be associated with gene regulation and metabolic diseases. This study aimed to analyze the hepatic transcriptome of pigs, a species frequently used as a model for nutrigenomic studies, to identify novel lncRNAs and their potential target genes in response to diets containing different sources of FA. Seventy-two pigs were fed four diets supplemented with 1.5% soybean oil (control), 3% canola oil, 3% fish oil, and 3% soybean oil. RNA sequencing of liver samples was performed to identify novel lncRNAs. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify modules associated with phenotypic traits related to lipid metabolism and inflammation. Functional enrichment analyses were then conducted to annotate genes within these modules using Gene Ontology (GO) terms and to assess overlap with Quantitative Trait Loci (QTL). The results revealed 106 novel lncRNAs potentially regulating genes associated with lipid metabolism and immune responses in pigs fed diets with different FA sources. These findings enhance understanding of the regulatory role of lncRNAs in pigs and reinforce their relevance as models for human metabolic diseases.

Animals↗
PubMed2006

Molecular properties of adult mouse gastric and intestinal epithelial progenitors in their niches.

We have sequenced 36,641 expressed sequence tags from laser capture microdissected adult mouse gastric and small intestinal epithelial progenitors, obtaining 4031 and 3324 unique transcripts, respectively. Using Gene Ontology (GO) terms, each data set was compared with cDNA libraries from intact adult stomach and small intestine. Genes in GO categories enriched in progenitors were filtered against genes in GO categories represented in hematopoietic, neural, and embryonic stem cell transcriptomes and mapped onto transcription factor networks, plus canonical signal transduction and metabolic pathways. Wnt/beta-catenin, phosphoinositide-3/Akt kinase, insulin-like growth factor-1, vascular endothelial growth factor, integrin, and gamma-aminobutyric acid receptor signaling cascades, plus glycerolipid, fatty acid, and amino acid metabolic pathways are among those prominently represented in adult gut progenitors. The results reveal shared as well as distinctive features of adult gut stem cells when compared with other stem cell populations.

Animals↗