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PubMed2026

Convergent mitochondrial impairment and apoptosis driven by simultaneous down-regulation of multiple genes at 11p11.2 in Alzheimer's disease.

Genome-wide association studies (GWAS) and multi-omics analyses have identified numerous risk loci and thousands of potential causal genes associated with Alzheimer's disease (AD). However, the synergistic pathogenic contributions of multiple low-risk causal genes within a single locus remain poorly understood. Polygenic synergism at the 11p11.2 locus was systematically examined in AD pathogenesis. Three causal genes (MTCH2, NDUFS3, and PSMC3) exhibited coordinated down-regulation in both AD patients and AD mouse models. Individual knockdown in cultured cells altered mitochondrial function and disrupted AD-associated pathways, as revealed by transcriptomic profiling. Integrated RNA-seq analysis and experimental validation demonstrated that the concurrent down-regulation of all three genes synergistically enhanced mitochondrial reactive oxygen species (ROS) generation and activated the caspase-7-mediated apoptotic pathway. Notably, pharmacological caspase inhibition with Q-VD-OPh attenuated neuronal apoptosis, ameliorated memory deficits, and reduced Aβ plaque deposition in APP/PS1 mice. Simultaneous down-regulation of multiple genes at the 11p11.2 locus contributed to mitochondrial dysfunction and apoptosis in AD, highlighting polygenic synergism as a key pathogenic mechanism.

Animals↗

PubMed2026

Methyltransferase METTL1 regulates MSC mRNA stability via m7G modification in acute pancreatitis.

Acute pancreatitis (AP) is a serious inflammatory disease with significant morbidity, yet its underlying molecular mechanisms remain incompletely understood. This study reveals a novel epitranscriptomic pathway in AP pathogenesis centered on METTL1-mediated N7-methylguanosine (m7G) RNA modification. We found that METTL1 expression and global m7G levels were significantly elevated in serum from AP patients, pancreatic tissues of sodium taurocholate-induced AP mice, and in vitro models of LPS-polarized macrophages and STC-injured pancreatic acinar cells. Through integrated multi-omics analysis combining m7G methylome mapping and transcriptome profiling, we identified Musculin (MSC) as a key target whose mRNA stability is enhanced by METTL1-mediated m7G modification. Functional experiments demonstrated that MSC upregulation activates TNF signaling through phosphorylation of NF-κB, JNK, and MAPK proteins, thereby promoting macrophage M1 polarization and pancreatic acinar cell injury. The pathological significance of this pathway was confirmed in vivo, where pancreas-targeted knockdown of Mettl1 significantly attenuated AP severity. Furthermore, mechanistic studies using a catalytic-dead METTL1 mutant established that both the methyltransferase activity of METTL1 and subsequent TNF signaling activation are essential for driving inflammatory responses. Our findings delineate a previously unrecognized METTL1-m7G-MSC-TNF signaling axis that promotes AP progression, highlighting the therapeutic potential of targeting METTL1-mediated epitranscriptomic modification in inflammatory diseases.

Animals↗

PubMed2024

Progressive cardiomyopathy with intercalated disc disorganization in a rat model of Becker dystrophy.

Becker muscular dystrophy (BMD) is an X-linked disorder due to in-frame mutations in the DMD gene, leading to a less abundant and truncated dystrophin. BMD is less common and severe than Duchenne muscular dystrophy (DMD) as well as less investigated. To accelerate the search for innovative treatments, we developed a rat model of BMD by deleting the exons 45-47 of the Dmd gene. Here, we report a functional and histopathological evaluation of these rats during their first year of life, compared to DMD and control littermates. BMD rats exhibit moderate damage to locomotor and diaphragmatic muscles but suffer from a progressive cardiomyopathy. Single nuclei RNA-seq analysis of cardiac samples revealed shared transcriptomic abnormalities in BMD and DMD rats and highlighted an altered end-addressing of TMEM65 and Connexin-43 at the intercalated disc, along with electrocardiographic abnormalities. Our study documents the natural history of a translational preclinical model of BMD and reports a cellular mechanism for the cardiac dysfunction in BMD and DMD offering opportunities to further investigate the organization role of dystrophin in intercellular communication.

Animals↗

PubMed2005

Embryonic endothelial progenitor cells expressing a broad range of proangiogenic and remodeling factors enhance vascularization and tissue recovery in acute and chronic ischemia.

Clonal embryonic endothelial progenitor cells (eEPCs) isolated from embryonic day 7.5 mice home specifically to hypoxic areas in mouse tumor metastases but spare normal organs and do not form carcinomas. Based on these results, we assessed the potential of eEPCs to enhance vascularization and limit organ dysfunction after ischemia in syngenic and xenotypic organisms. The angiogenic potential of eEPCs was evaluated in chronic ischemic rabbit hindlimbs after regional application by retroinfusion. eEPC treatment improved limb perfusion, paralleled by an increase in capillary density and collateral blood vessel number. Systemic eEPC infusion into mice after ischemic cardiac insult increased postischemic heart output measured by a marked improvement in left ventricle developed pressure and both systolic and diastolic functions. In vitro, eEPCs strongly induced vascular outgrowths from aortic rings. To address the molecular basis of this intrinsic angiogenic potential, we investigated the eEPC transcriptome. Genome-wide Affymetrix GeneChip analysis revealed that the eEPCs express a wealth of secreted factors known to induce angiogenesis, tissue remodeling, and organogenesis that may contribute to the eEPC-mediated beneficial effects. Our findings show that eEPCs induce blood vessel growth and cardioprotection in severe ischemic conditions providing a readily available source to study the mechanisms of neovascularization and tissue recovery.

Animals↗

PubMed2026

Genomic Structural Equation Modeling Identifies a Shared Inflammatory Genetic Dimension Across Inflammatory Arthritis Phenotypes and Biomarkers.

BACKGROUND: Inflammatory arthritis (IA), including rheumatoid arthritis (RA), psoriatic arthritis (PsA) and gout, shares systemic inflammatory features indexed by C-reactive protein (CRP) and interleukin-6 (IL-6), yet the extent of their common genetic basis remains unclear. AIMS: We aimed to delineate the shared genetic architecture across IA phenotypes and inflammatory biomarkers. MATERIALS AND METHODS: We applied genomic structural equation modelling (Genomic SEM) to GWAS summary statistics for RA, PsA, gout, CRP and IL-6, fitted a single common factor, and performed multivariate GWAS followed by fine-mapping, transcriptome-wide association, gene-based analysis, pathway enrichment, and cell-type and spatial mapping. RESULTS: A single common factor was fitted (CFI = 0.990, SRMR = 0.045). The multivariate GWAS identified 56 genome-wide significant SNPs across 10 independent lead loci, including one novel signal. Fine-mapping prioritized high-confidence variants near PTPN22, the CRP gene cluster and a urate-associated locus. Gene-level analyses converged on DCLRE1B, PTPN22, IL6R, NLRP3 and HNF1A, with pathway enrichment implicating inflammasome assembly and metabolic-inflammatory overlap. Cell-type enrichment highlighted myeloid populations, and spatial mapping localized signals to lung, kidney, mucosal epithelium and gastrointestinal tissues. DISCUSSION: These results delineate a shared inflammatory genetic dimension across IA phenotypes and biomarkers, anchored in immune, inflammasome, cytokine-receptor and metabolic pathways. CONCLUSION: Together, these findings provide a valuable framework for prioritizing candidate genes and cellular contexts for future investigation.

TWAS↗

PubMed2025

Defining the networks that connect RNase III and RNase J-mediated regulation of primary and specialized metabolism in Streptomyces venezuelae.

UNLABELLED: RNA metabolism involves coordinating RNA synthesis with RNA processing and degradation. Ribonucleases play fundamental roles within the cell, contributing to the cleavage, modification, and degradation of RNA molecules, with these actions ensuring appropriate gene regulation and cellular homeostasis. Here, we employed RNA sequencing to explore the impact of RNase III and RNase J on the transcriptome of Streptomyces venezuelae. Differential expression analysis comparing wild-type and RNase mutant strains at distinct developmental stages revealed significant changes in transcript abundance, particularly in pathways related to multicellular development, nutrient acquisition, and specialized metabolism. Both RNase mutants exhibited dysregulation of the BldD regulon, including altered expression of many cyclic-di-GMP-associated enzymes. We also observed precocious chloramphenicol production in these RNase mutants and found that in the RNase III mutant, this was associated with PhoP-mediated regulation. We further found that RNase III directly targeted members of the PhoP regulon, suggesting a link between RNA metabolism and a regulator that bridges primary and specialized metabolism. We connected RNase J function with translation through the observation that RNase J directly targets multiple ribosomal protein transcripts for degradation. These findings establish distinct but complementary roles for RNase III and RNase J in coordinating the gene expression dynamics critical for S. venezuelae development and specialized metabolism. IMPORTANCE: RNA processing and metabolism are mediated by ribonucleases and are fundamental processes in all cells. In the morphologically complex and metabolically sophisticated Streptomyces bacteria, RNase III and RNase J influence both development and metabolism through poorly understood mechanisms. Here, we show that both ribonucleases are required for the proper expression of the BldD developmental pathway and contribute to the control of chloramphenicol production, with an interesting connection to phosphate regulation for RNase III. Additionally, we show that both RNases have the potential to impact translation through distinct mechanisms and can function cooperatively in degrading specific transcripts. This study advances our understanding of RNases in Streptomyces biology by providing insight into distinct contributions made by these enzymes and the intriguing interplay between them.

Streptomyces↗

PubMed2005

In silico analysis of 2085 clones from a normalized rat vestibular periphery 3' cDNA library.

The inserts from 2400 cDNA clones isolated from a normalized Rattus norvegicus vestibular periphery cDNA library were sequenced and characterized. The Wackym-Soares vestibular 3' cDNA library was constructed from the saccular and utricular maculae, the ampullae of all three semicircular canals and Scarpa's ganglia containing the somata of the primary afferent neurons, microdissected from 104 male and female rats. The inserts from 2400 randomly selected clones were sequenced from the 5' end. Each sequence was analyzed using the BLAST algorithm compared to the Genbank nonredundant, rat genome, mouse genome and human genome databases to search for high homology alignments. Of the initial 2400 clones, 315 (13%) were found to be of poor quality and did not yield useful information, and therefore were eliminated from the analysis. Of the remaining 2085 sequences, 918 (44%) were found to represent 758 unique genes having useful annotations that were identified in databases within the public domain or in the published literature; these sequences were designated as known characterized sequences. 1141 sequences (55%) aligned with 1011 unique sequences had no useful annotations and were designated as known but uncharacterized sequences. Of the remaining 26 sequences (1%), 24 aligned with rat genomic sequences, but none matched previously described rat expressed sequence tags or mRNAs. No significant alignment to the rat or human genomic sequences could be found for the remaining 2 sequences. Of the 2085 sequences analyzed, 86% were singletons. The known, characterized sequences were analyzed with the FatiGO online data-mining tool (http://fatigo.bioinfo.cnio.es/) to identify level 5 biological process gene ontology (GO) terms for each alignment and to group alignments with similar or identical GO terms. Numerous genes were identified that have not been previously shown to be expressed in the vestibular system. Further characterization of the novel cDNA sequences may lead to the identification of genes with vestibular-specific functions. Continued analysis of the rat vestibular periphery transcriptome should provide new insights into vestibular function and generate new hypotheses. Physiological studies are necessary to further elucidate the roles of the identified genes and novel sequences in vestibular function.

Afferent Pathways↗

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↗

PubMed2005

[Overview: application of DNA chips to clinical immunology].

DNA microarrays or DNA chips are rapidly evolved technologies. Hybridization of labeled cDNA or cRNA to DNA probes on the solid phases enables analyses of transcriptome of particular cells. Storage and analysis of microarray data are also important factors. Several studies have been published on the gene expression in the immune cells during immune responses and immune mediated diseases.

Cytokines↗

PubMed2026

Single-cell sequencing reveals synovial fluid γδ T-cell expansion in equine experimental osteoarthritis.

OBJECTIVE: Define temporal cellular changes following joint injury using single-cell RNA sequencing in experimental equine posttraumatic osteoarthritis (PTOA). METHODS: PTOA was induced in 4 Quarter Horses (3 to 5 years) via carpal osteochondral fragmentation and high-speed treadmill exercise. Synovial fluid (SF) cells and synovium were sampled over 18 weeks (November 2023 to April 2024). Single-cell suspensions were processed (10x Genomics Chromium iX), then aligned to the equine genome (Cell Ranger). Downstream analysis was completed in the R Seurat package. Differential gene expression (log2[fold change] > 1; P < .05) and differential abundance analyses were performed (P < .1). RESULTS: Cartilage injury had a modest impact on gene expression changes and cell abundance shifts in SF. Integrated analysis of 90,323 SF cells across 4 time points revealed 9 distinct cell types, primarily T cells (73 ± 19%) followed by myeloid cells (20 ± 13%). Subcluster analysis of T cells revealed 9 transcriptomically distinct subtypes (3 CD8, 2 CD4, 3 γδ, and 1 cycling). Differential abundance analyses of temporal changes identified increased γδ T and decreased CD4+ T-cell subsets in joints over time. Expanded populations of IL-23 receptor-positive γδ T cells exhibited increased T-helper 17 signatures. CONCLUSIONS: IL-23 receptor-positive γδ T-cell expansion, associated with joint inflammation, occurred in PTOA. Limitations include small sample size and individual heterogeneity; further investigation over extended timeframe is necessary to confirm whether later stages of the experimental model reflect natural chronic OA. CLINICAL RELEVANCE: Cellular immunotherapy targeting γδ T cells and IL-23/IL-17 blockade may warrant investigation to mitigate equine OA progression.

equine↗

PubMed2026

Nested co-expression network analysis identifies compact gene clusters in a black box.

MOTIVATION: Digital analysis of biological systems requires methods capable of identifying both broad and nested gene modules reflecting complex biological processes. Existing transcriptomic methods often miss compact gene sets corresponding to subprocesses in specialized cell types, limiting insights into functional heterogeneity. RESULTS: We present Nested-WGCNA, a two-stage unsupervised network analysis algorithm designed to identify coarse-grained and fine-grained gene modules. Applied to bulk RNA-Seq data, Nested-WGCNA reveals stable modules reproducible across datasets. When validated against scRNA-Seq data, these modules correspond to both major and minor immune cell subtypes. Application to immunotherapy response datasets uncovers predictive and prognostic biomarkers, highlighting its utility in treatment stratification and biomarker discovery. AVAILABILITY: The NestedWGCNA source code and analysis pipeline are available on GitHub (https://github.com/ilyada/NestedWGCNA) and archived on Zenodo (https://doi.org/10.5281/zenodo.18959244).

Algorithms↗

PubMed2026

The evolution of Ca2+-ATPases across plants with profiles in Rhododendron and the function of key members in alleviating high calcium stress.

Ca2+-ATPase (CAP) is a key Ca2+ efflux protein in plants. Our previous research suggests that CAPs may play a crucial role in the adaptation of rhododendrons to high calcium environments. However, the evolution, variation, characteristic expression, and subfunctionalization of this gene family in Rhododendron remain unknown. Through the analysis of pan-genomes and pan-transcriptomes, we elucidated the systematic evolution of CAPs in plants, as well as their characteristic expression patterns in Rhododendron. During the evolutionary process from lower to higher plants, CAPs can be divided into six clades and exhibit structural conservation. CAPs have emerged and differentiated in lower plants such as algae, and they have undergone significant amplification in Eudicots plants like rhododendrons. Three Rhododendron species (Rhododendron bailiense, R. delavayi, and R. irroratum) located in the karst province of Guizhou in Southwest China exhibit the highest copies of CAPs, suggesting a strong association between CAP copy number variation and habitat, particularly in high calcium environments. Through multiple transcriptome analyses, we revealed that CAPs are induced under various environmental/developmental conditions (e.g. karst environments, high altitude, early flower development, hormones, etc.). Co-expression network analysis highlighted key members of calcineurin B-like protein (CBL) and CBL-interacting protein kinases (CIPK) that are associated with the high expression of CAPs. Experimental validation demonstrated that CAPb1 and CAPd1 significantly alleviate high calcium stress, and the CAPb1-CIPK1-CBL1 and CAPd1-CIPK2-CBL1 modules can further enhance the alleviation. These findings provide new insights into the evolution, characteristic expression, and function of CAPs, as well as new perspectives on the high calcium adaptability of rhododendrons.

Journal Article↗

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 °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↗

PubMed2006

Establishment of the epithelial-specific transcriptome of normal and malignant human breast cells based on MPSS and array expression data.

INTRODUCTION: Diverse microarray and sequencing technologies have been widely used to characterise the molecular changes in malignant epithelial cells in breast cancers. Such gene expression studies to identify markers and targets in tumour cells are, however, compromised by the cellular heterogeneity of solid breast tumours and by the lack of appropriate counterparts representing normal breast epithelial cells. METHODS: Malignant neoplastic epithelial cells from primary breast cancers and luminal and myoepithelial cells isolated from normal human breast tissue were isolated by immunomagnetic separation methods. Pools of RNA from highly enriched preparations of these cell types were subjected to expression profiling using massively parallel signature sequencing (MPSS) and four different genome wide microarray platforms. Functional related transcripts of the differential tumour epithelial transcriptome were used for gene set enrichment analysis to identify enrichment of luminal and myoepithelial type genes. Clinical pathological validation of a small number of genes was performed on tissue microarrays. RESULTS: MPSS identified 6,553 differentially expressed genes between the pool of normal luminal cells and that of primary tumours substantially enriched for epithelial cells, of which 98% were represented and 60% were confirmed by microarray profiling. Significant expression level changes between these two samples detected only by microarray technology were shown by 4,149 transcripts, resulting in a combined differential tumour epithelial transcriptome of 8,051 genes. Microarray gene signatures identified a comprehensive list of 907 and 955 transcripts whose expression differed between luminal epithelial cells and myoepithelial cells, respectively. Functional annotation and gene set enrichment analysis highlighted a group of genes related to skeletal development that were associated with the myoepithelial/basal cells and upregulated in the tumour sample. One of the most highly overexpressed genes in this category, that encoding periostin, was analysed immunohistochemically on breast cancer tissue microarrays and its expression in neoplastic cells correlated with poor outcome in a cohort of poor prognosis estrogen receptor-positive tumours. CONCLUSION: Using highly enriched cell populations in combination with multiplatform gene expression profiling studies, a comprehensive analysis of molecular changes between the normal and malignant breast tissue was established. This study provides a basis for the identification of novel and potentially important targets for diagnosis, prognosis and therapy in breast cancer.

Biomarkers, Tumor↗

PubMed2005

In vivo transcriptome of Plasmodium falciparum reveals overexpression of transcripts that encode surface proteins.

Infections with the human parasite Plasmodium falciparum continue to present a great challenge to global health. Fundamental questions regarding the molecular basis of virulence and immune evasion in P. falciparum have been only partially answered. Because of the parasite's intracellular location and complex life cycle, standard genetic approaches to the study of the pathogenesis of malaria have been limited. The present study presents a novel approach to the identification of the biological processes involved in host-pathogen interactions, one that is based on the analysis of in vivo P. falciparum transcripts. We demonstrate that a sufficient quantity of P. falciparum RNA transcripts can be derived from a small blood sample from infected patients for whole-genome microarray analysis. Overall, excellent correlation was observed between the transcriptomes derived from in vivo samples and in vitro samples with ring-stage P. falciparum 3D7 reference strain. However, gene families that encode surface proteins are overexpressed in vivo. Moreover, this analysis has identified a new family of hypothetical genes that may encode surface variant antigens. Comparative studies of the transcriptomes derived from in vivo samples and in vitro 3D7 samples may identify important strategies used by the pathogen for survival in the human host and highlight, for vaccine development, new candidate antigens that were not previously identified through the use of in vitro cultures.

Adaptation, Physiological↗

PubMed2025

BMDx2: A Tool for Integrating Toxicogenomics-Based Dose-Dependency Analysis and AOP-Based Mechanistic Insights.

Despite the advent of mechanistic toxicology using omics data to link molecular perturbations with systemic outcomes, regulatory toxicology still lacks the application of mechanism-anchored metrics from such data. This is partially because traditional gene-centric analysis often falls short of linking molecular changes to adverse outcomes. To address this gap, BMDx2, an open-source tool that transforms multi-dose toxicogenomics datasets into quantitative, mechanistic evidence for human chemical safety assessment is developed. BMDx2 couples benchmark-dose modeling with Adverse Outcome Pathway (AOP) enrichment to derive transcriptomic-based points of departure, enabling potency ranking, chemical prioritization, and mechanistically anchored explanations of the effect of chemical exposures. BMDx2 can process a broad range of data, including DNA microarray and RNA sequencing studies. Here, case studies are used to illustrate the versatility of BMDx2 in characterizing the mechanism of action of chemicals. An initial case study on carbon nanotubes exposure applies integrative analysis of transcriptomics and genome-wide DNA methylation data, uncovering cellular reprogramming processes underlying fibrosis. A second case study on bleomycin exposure demonstrate how transcriptomic data alone can be mapped to fibrosis-related AOPs in a standardized, regulatory appropriate manner. Together, these examples show how BMDx2 supports the regulatory application of toxicogenomics and accelerates mechanism-based chemical safety evaluation.

Toxicogenetics↗

PubMed2005

Conversion of cDNA differential display results (DDRT-PCR) into quantitative transcription profiles.

BACKGROUND: Gene expression studies on non-model organisms require open-end strategies for transcription profiling. Gel-based analysis of cDNA fragments allows to detect alterations in gene expression for genes which have neither been sequenced yet nor are available in cDNA libraries. Commonly used protocols for gel-based transcript profiling are cDNA differential display (DDRT-PCR) and cDNA-AFLP. Both methods have been used merely as qualitative gene discovery tools so far. RESULTS: We developed procedures for the conversion of cDNA Differential Display data into quantitative transcription profiles. Amplified cDNA fragments are separated on a DNA sequencer and detector signals are converted into virtual gel images suitable for semi-automatic analysis. Data processing consists of four steps: (i) cDNA bands in lanes corresponding to samples treated with the same primer combination are matched in order to identify fragments originating from the same transcript, (ii) intensity of bands is determined by densitometry, (iii) densitometric values are normalized, and (iv) intensity ratio is calculated for each pair of corresponding bands. Transcription profiles are represented by sets of intensity ratios (control vs. treatment) for cDNA fragments defined by primer combination and DNA mobility. We demonstrated the procedure by analyzing DDRT-PCR data on the effect of secondary metabolites of oilseed rape Brassica napus on the transcriptome of the pathogenic fungus Leptosphaeria maculans. CONCLUSION: We developed a data processing procedure for the quantitative analysis of amplified cDNA fragments separated by electrophoresis. The system utilizes common software and provides an open-end alternative to DNA microarray analysis of the transcriptome. It is expected to work equally well with DDRT-PCR and cDNA-AFLP data and be useful particularly in research on organisms for which microarray analysis is not available or economical.

Brassica napus↗

PubMed2025

Integration of multiple omics reveals key targets and cellular mechanisms for intervention in sarcopenia.

BACKGROUND: Sarcopenia, an age-related syndrome characterized by progressive loss of muscle mass, strength, and function, presents a significant global health burden with limited therapeutic interventions. This study integrates genomic causality, multi-tissue omics, and cellular mediation analyses to identify and prioritize mechanistically grounded therapeutic targets. METHODS: A multi-tiered analytical framework was applied, beginning with two-sample Mendelian randomization (MR) to infer causal relationships between 4907 plasma proteins (cis-pQTLs from 35,559 individuals) and sarcopenia traits in Pan-UK Biobank participants. Bayesian colocalization and transcriptomic validation in human sarcopenia muscle biopsies were employed to prioritize targets. Cellular mediation analysis quantified contributions of immune and stromal cell subtypes to protein-trait pathways using transcriptomic deconvolution. RESULTS: MR identified 1237 plasma proteins causally associated with sarcopenia traits, with six targets (HGFAC, GATM, HMOX2, F2, LMAN2L, HPGDS) validated through colocalization, transcriptomic expression, and sarcopenia-related dysregulation. Cellular mediation revealed immune mechanisms underlying HGFAC's effects, with CD4+ regulatory T cells mediating 3.49 % of its impact on sarcopenia traits. Prothrombin exhibited muscle-protective effects independent of coagulation. CONCLUSION: This study establishes a causal map linking plasma proteins to sarcopenia through immune-stromal interactions. The integration of MR, multi-omics validation, and cellular mediation prioritizes six proteins as actionable targets, supporting repurposing of thrombin inhibitors and development of immunometabolic therapies. The framework bridges genomic causality with cellular pathophysiology, advancing precision strategies for age-related muscle decline.

Humans↗