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Transcriptional and histopathological profiling of skeletal muscle in Bla/J mice at the stage of dysferlinopathy manifestation.

Dysferlinopathy is a rare muscular dystrophy characterized by chronic muscle damage and ineffective regeneration. While late-stage morphological changes, such as fibroadipose replacement, are well described, the early molecular mechanisms driving muscle fiber loss and regenerative failure at the onset of the disease remain largely uncharacterized. To address this gap, we investigated the skeletal muscles of dysferlin-deficient Bla/J mice during the early manifestation stage (3 months of age). This exploratory study aimed to identify primary pathomorphogenetic events by correlating the transcriptomic profile of the tissue with its specific histopathological and ultrastructural alterations. We performed a comparative analysis of the m. gastrocnemius in 3-month-old Bla/J mice versus wild-type controls using RNA sequencing, RT-qPCR, histomorphometry and transmission electron microscopy. The results revealed atrophy and muscle fiber necrosis without the expected induction of Fbxo32 and Trim63 ubiquitin ligases, suggesting ubiquitin-proteasome system-independent muscle mass loss. Furthermore, the absence of Casp3, Bak1, and Bad induction, confirmed by the lack of active caspase-3, excluded apoptosis as the primary death mechanism. A differentiation block in satellite cells was confirmed by the lack of Myf5, Myod1, and Myog induction and a trend toward Tead4 suppression, pointing to an early failure of the reparative program. Exploratory RNA sequencing also identified a suppression of Prkn expression accompanied by LC3B-II-positive autophagosome accumulation. Immunohistochemical and immunofluorescent evaluation of the mitochondrial network (TOMM20) revealed abnormal accumulations and dense clumping, indicating impaired organelle clearance. Furthermore, ultrastructural analysis demonstrated internal organelle damage and the presence of myelin-like structures, consistent with a state of stalled mitophagy. Collectively, this exploratory study demonstrates that early muscle atrophy and myofiber necrosis in dysferlinopathy occur independently of canonical ubiquitin-proteasome and apoptotic pathways. Instead, the disease manifestation stage is structurally characterized by stalled mitochondrial clearance and a delayed regenerative response.

Animals↗

Uncovering hidden complexity in the Apis mellifera mitotranscriptome: a polyadenylation-centered perspective.

Mitochondrial transcription is gaining increasing attention as researchers seek to better understand the full coding potential of mitochondrial DNA (mtDNA). Emerging evidence suggests that mtDNA may encode additional elements beyond classical oxidative phosphorylation genes, pointing to a more complex transcriptional architecture than previously recognized. In this study, we explored the mitochondrial transcriptome of Apis mellifera (Insecta: Hymenoptera), with a particular focus on polyadenylation-associated features. Our analysis revealed that both sense and antisense transcripts undergo polyadenylation, although transcript abundance and poly(A) tail lengths varied markedly across mitochondrial genes. Several transcripts exhibited alternative isoforms, either extended or truncated, frequently including intergenic regions. These regions may represent functional non-coding elements or structural variants rather than conventional untranslated regions (UTRs). Interestingly, some transcripts also contained non-templated nucleotide additions particularly cytosine residues immediately upstream of the poly(A) tails. Monocistronic units that included portions of downstream intergenic regions were among the most abundantly represented, suggesting a possible regulatory role for these sequences. To experimentally validate our in silico findings, we performed RT-qPCR to assess relative gene expression and applied 3' RACE-PCR to define transcript boundaries. These approaches confirmed the presence of multiple transcript isoforms and supported the involvement of polyadenylation in shaping mitochondrial RNA diversity. Together, our findings reveal a previously underappreciated level of complexity in the A. mellifera mitochondrial transcriptome and highlight the potential regulatory significance of polyadenylation dynamics and intergenic region transcription.

Animals↗

The expanding transcriptome: the genome as the 'Book of Sand'.

The central dogma of molecular biology inspired by classical work in prokaryotic organisms accounts for only part of the genetic agenda of complex eukaryotes. First, post-transcriptional events lead to the generation of multiple mRNAs, proteins and functions from a single primary transcript, revealing regulatory networks distinct in mechanism and biological function from those controlling RNA transcription. Second, a variety of populous families of small RNAs (small nuclear RNAs, small nucleolar RNAs, microRNAs, siRNAs and shRNAs) assemble on ribonucleoprotein complexes and regulate virtually all aspects of the gene expression pathway, with profound biological consequences. Third, high-throughput methods of genomic analysis reveal that RNAs other than non-protein-coding RNAs (ncRNAs) represent a major component of the transcriptome that may perform novel functions in gene regulation and beyond. Post-transcriptional regulation, small RNAs and ncRNAs provide an expanding picture of the transcriptome that enriches our views of what genes are, how they operate, evolve and are regulated.

Animals↗

Global correlation of genome and transcriptome changes in classical Hodgkin lymphoma.

To identify genes involved in the pathogenesis of classical Hodgkin lymphoma (cHL), we performed serial analysis of gene expression (SAGE) and array-based comparative genomic hybridization (aCGH). Comparison of SAGE libraries of cHL cell lines L428 and L1236 with that of germinal centre B cells revealed consistent overexpression of only 14 genes. In contrast, 141 genes were downregulated in both cHL cell lines, including many B cell and HLA genes. aCGH revealed gain of 2p, 7p, 9p, 11q and Xq and loss of 4q and 11q. Eighteen percent of the differentially expressed genes mapped to regions with loss or gain and a good correlation was observed between underexpression and loss or overexpression and gain of DNA. Remarkably, gain of 2p and 9p did not correlate with increased expression of the proposed target genes c-REL and JAK2. Downregulation of many genes within the HLA region also did not correlate with loss of DNA. FSCN1 and IRAK1 mapping at genomic loci (7p and Xq) that frequently showed gain were overexpressed in cHL cell lines and might be involved in the pathogenesis of cHL.

Carrier Proteins↗

Comparative analysis of expressed sequence tags (ESTs) of ginseng leaf.

The expressed sequence tags (ESTs) referenced in this report are the first transcriptomes in a leaf from a half-shade ginseng plant. A cDNA library was constructed from samples of the leaves of 4-year-old Panax ginseng plants, which were cultured in a field. The 2,896 P. ginseng cDNA clones represent 1,576 unique sequences, consisting of 1,167 singletons and 409 contig sequences. BLAST comparisons of the cDNAs in GenBank's non-redundant databases revealed that 2,579 of the 2,896 cDNAs (89.1%) exhibited a high degree of sequence homology to genes from other organisms. The majority of the identified transcripts were found to be genes related with energy, metabolism, subcellular localization, and protein synthesis and transport. The chlorophyll a/b-binding protein ESTs in the ginseng leaf samples manifested a substantially higher level of expression than was observed in other plant leaves. The ESTs involved in ginsenoside biosynthesis were also identified and discussed.

Expressed Sequence Tags↗

Hyperstructures, genome analysis and I-cells.

New concepts may prove necessary to profit from the avalanche of sequence data on the genome, transcriptome, proteome and interactome and to relate this information to cell physiology. Here, we focus on the concept of large activity-based structures, or hyperstructures, in which a variety of types of molecules are brought together to perform a function. We review the evidence for the existence of hyperstructures responsible for the initiation of DNA replication, the sequestration of newly replicated origins of replication, cell division and for metabolism. The processes responsible for hyperstructure formation include changes in enzyme affinities due to metabolite-induction, lipid-protein affinities, elevated local concentrations of proteins and their binding sites on DNA and RNA, and transertion. Experimental techniques exist that can be used to study hyperstructures and we review some of the ones less familiar to biologists. Finally, we speculate on how a variety of in silico approaches involving cellular automata and multi-agent systems could be combined to develop new concepts in the form of an Integrated cell (I-cell) which would undergo selection for growth and survival in a world of artificial microbiology.

Algorithms↗

Genome-wide detection of tissue-specific alternative splicing in the human transcriptome.

We have developed an automated method for discovering tissue-specific regulation of alternative splicing through a genome-wide analysis of expressed sequence tags (ESTs). Using this approach, we have identified 667 tissue-specific alternative splice forms of human genes. We validated our muscle-specific and brain-specific splice forms for known genes. A high fraction (8/10) were reported to have a matching tissue specificity by independent studies in the published literature. The number of tissue-specific alternative splice forms is highest in brain, while eye-retina, muscle, skin, testis and lymph have the greatest enrichment of tissue-specific splicing. Overall, 10-30% of human alternatively spliced genes in our data show evidence of tissue-specific splice forms. Seventy-eight percent of our tissue-specific alternative splices appear to be novel discoveries. We present bioinformatics analysis of several tissue-specific splice forms, including automated protein isoform sequence and domain prediction, showing how our data can provide valuable insights into gene function in different tissues. For example, we have discovered a novel kidney-specific alternative splice form of the WNK1 gene, which appears to specifically disrupt its N-terminal kinase domain and may play a role in PHAII hypertension. Our database greatly expands knowledge of tissue-specific alternative splicing and provides a comprehensive dataset for investigating its functional roles and regulation in different human tissues.

Alternative Splicing↗

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↗

GIMS: an integrated data storage and analysis environment for genomic and functional data.

Effective analyses in functional genomics require access to many kinds of biological data. For example, the analysis of upregulated genes in a microarray experiment might be aided by information concerning protein interactions or proteins' cellular locations. However, such information is often stored in different formats at different sites, in ways that may not be amenable to integrated analysis. The Genome Information Management System (GIMS) is an object database that integrates genomic data with data on the transcriptome, protein-protein interactions, metabolic pathways and annotations, such as gene ontology terms and identifiers. The resulting system supports the running of analyses over this integrated data resource, and provides comprehensive facilities for handling and interrelating the results of these analyses. GIMS has been used to store Saccharomyces cerevisiae data, and we demonstrate how the integrated storage of diverse types of data can be beneficial for analysis, using combinations of complex queries. As an example, we describe how GIMS has been used to analyse a collection of aryl alcohol dehydrogenase gene deletion mutants. The GIMS database can be accessed remotely using a Java application that can be downloaded from http://img.cs.man.ac.uk/gims.

Computational Biology↗

A Multi-omics Exploration Revealing SLIT2 as a Prime Therapeutic Target for Peripheral Facial Paralysis: Integrating Single-Cell Transcriptomics and Plasma Proteome Data.

Peripheral facial paralysis (PFP) is a common neurological disorder characterized by facial-nerve dysfunction. Identifying therapeutic targets and understanding the molecular and cellular mechanisms underlying PFP are crucial for developing effective treatment strategies. This study combined Mendelian randomization (MR) analysis and single-cell RNA sequencing (scRNA-seq) to explore potential therapeutic candidates and their roles in PFP pathophysiology. The MR analysis included 1925 publicly available plasma protein cis-heritability instruments. Instrumental variables were selected for MR analysis to identify plasma proteins associated with PFP, followed by colocalization analysis to evaluate shared genetic variants between the identified proteins and PFP. After the initial identification of plasma proteins associated with Bell's palsy using MR analysis, a rat model of facial-nerve injury was established to further dissect underlying mechanisms at cellular and molecular levels. Using scRNA-seq technology, we delved deeply into cellular Heterogeneity and dynamic changes in gene expression in the facial-nerve nucleus tissues under both injured and control conditions, thereby achieving a systematic study ranging from macroscopic genetic associations to microscopic cellular functions. Finally, expression patterns were preliminarily validated by performing in vitro immunofluorescence analysis on the facial-nerve nucleus samples of SD rats. The MR analysis results identified 30 plasma proteins significantly associated with PFP, with nine target genes showing differential expression in the scRNA-seq data. Colocalization analysis demonstrated that slit guidance Ligand 2 (SLIT2), semaphorin 4D (SEMA4D), EGF containing fibulin extracellular matrix protein 1 (EFEMP1), and sprouty related EVH1 domain containing 2 (SPRED2) shared causal variants with PFP. SLIT2 was highly expressed in the microglia and inhibitory neurons in the experimental group, whereas SEMA4D showed elevated expression across multiple glial cell types in the same group. In contrast, EFEMP1 and SPRED2 showed distinct expression patterns in fibroblasts and oligodendrocytes. The role of SLIT2 has been previously well-documented in many central nervous system diseases. However, for the first time, this study detected SLIT2 alteration after facial-nerve injury. Altered intercellular signaling, particularly enhanced SLIT2-ROBO signaling between neurons and glial cells, was observed in the PFP group. Pseudotime analysis revealed dynamic SLIT2 expression during microglia and inhibitory neuron differentiation, mirroring changes in ROBO1 expression. Immunofluorescence analysis of rat facial-nerve nucleus samples verified that SLIT2 protein levels were significantly increased in the facial-nerve nuclei of injured samples. In conclusion, despite the fact that this study is primarily founded on animal models and despite notable differences existing between animals and humans in terms of the facial motor nucleus, this study successfully identified SLIT2 as potential therapeutic targets for PFP. The SLIT2-ROBO axis stands out as a particularly promising candidate. SLIT2 may play a role in modulating neuroimmune interactions and promoting nerve repair. These findings provide a foundation for future clinical studies and targeted interventions to enhance recovery from PFP. Future research should focus on human sample validation to enhance clinical translation.

Animals↗

Silencing in yeast: identification of clr4 targets.

Efficient handling of multiple reactions is a crucial prerequisite for productive RNA differential display (DD) analysis. To identify transcriptional targets of the histone H3 Lys9-specific methyltransferase Clr4, we applied a multiformat modification of DD to compare between clr4+ and clr4- transcriptomes of Schizosaccaromyces pombe. As a result, 14 differentially expressed bands were identified among 720 polymerase chain reaction (PCR) studied. The content of these bands was then analyzed by cloning, sequencing, and Northern analysis. In the final stage of verification, four Clr4 targets were isolated based on their expression in six Clr4 chromo and SET domain mutant strains. The step-by-step description of the multiformat DD provided below includes RNA purification, cDNA synthesis, 96-well PCR, electrophoretic separation of PCR products, isolation of DNA fragments from differentially expressed bands, and verification of candidate genes by Northern analysis.

Blotting, Northern↗

Kinesin superfamily proteins (KIFs) in the mouse transcriptome.

In the post genomic era where virtually all the genes and the proteins are known, an important task is to provide a comprehensive analysis of the expression of important classes of genes, such as those that are required for intracellular transport. We report the comprehensive analysis of the Kinesin Superfamily, which is the first and only large protein family whose constituents have been completely identified and confirmed in silico and at the cDNA, mRNA level. In FANTOM2, we have found 90 clones from 33 Kinesin Superfamily Protein (KIF) gene loci. The clones were analyzed in reference to sequence state, library of origin, detection methods, and alternative splicing. More than half of the representative transcriptional units (TU) were full length. The FANTOM2 library also contains novel splice variants previously unreported. We have compared and evaluated various protein classification tools and protein search methods using this data set. This report provides a foundation for future research of the intracellular transport along microtubules and proves the significance of intracellular transport protein transcripts as part of the transcriptome.

Alternative Splicing↗

Dietary Polyphenol Acteoside-Related Molecular Signatures in Clear Cell Renal Cell Carcinoma: Multi-Omics Profiling and Functional Validation of IMPDH1.

Clear cell renal cell carcinoma (ccRCC) is characterized by substantial metabolic and molecular heterogeneity, but the disease-relevant programs associated with acteoside, a dietary polyphenol, remain poorly understood. We integrated predicted acteoside targets with bulk, single-cell, and spatial transcriptomic data from ccRCC and combined molecular subtyping with cross-cohort machine-learning analysis. Acteoside-related signatures were preferentially enriched in malignant compartments and increased with tumor grade and stage. Consensus clustering identified two molecular subtypes with distinct biological and clinical features. C1 was associated with immune activation, metabolic activity, and more favorable survival, whereas C2 showed greater genomic instability, reduced renal epithelial differentiation, and poorer outcomes. We further benchmarked multiple machine-learning strategies and established a 10-gene prognostic model that retained predictive performance across independent cohorts, with IMPDH1 emerging as the strongest risk-associated feature. Functional experiments confirmed the biological relevance of IMPDH1: its knockdown suppressed ccRCC cell proliferation, DNA synthesis, colony formation, and migration, whereas overexpression produced the opposite effects. Together, these findings indicate that acteoside-related molecular signatures capture clinically relevant heterogeneity in ccRCC and provide a framework for linking dietary-polyphenol-related molecular space with tumor biology. The identification and functional validation of IMPDH1 further highlight its potential importance in ccRCC progression.

IMPDH1↗

CRISPR-Enabled functional genomics in hPSCs-derived neural models for autism spectrum disorder.

Autism Spectrum Disorder (ASD) is a genetically heterogeneous neurodevelopmental condition in which hundreds of individually rare risk variants converge on a small number of shared biological pathways, including synaptic scaffolding, chromatin remodeling, excitation-inhibition balance, and cellular energy metabolism. Translating this genetic heterogeneity into mechanistic insight requires experimental systems capable of interrogating individual gene functions in human-relevant neural contexts at scale. CRISPR-enabled functional genomics in human pluripotent stem cell (hPSC)-derived neural models, spanning neural progenitors, cortical and inhibitory neurons, astrocytes, microglia, and brain organoids, provides precisely this capability. By integrating pooled perturbation screens with multimodal readouts including single-cell and spatial transcriptomics, chromatin accessibility profiling, proximity labeling proteomics, multi-electrode array electrophysiology, and metabolic flux analysis, these platforms enable systematic, causal mapping of ASD gene function at system resolution. Early applications have already revealed convergent mechanisms: BAF complex disruption expands the ventral progenitor pool and biases its fate toward oligodendrocyte and interneuron lineages; ADNP loss impairs microglial synaptic pruning through altered endocytic trafficking; and mTOR pathway dysregulation in PTEN- and TSC2-perturbed models links genetic risk directly to metabolic and mitochondrial dysfunction. Computational frameworks including MIMOSCA and SCEPTRE enable causal network reconstruction and pseudotime inference from these datasets, moving the field from gene lists toward pathway-level models of ASD pathobiology. Translational applications leverage isogenic iPSC panels and variant-level base and prime editing to stratify ASD variants by functional impact, informing gene therapy design for haploinsufficient targets such as CHD8 and SCN2A via AAV or antisense oligonucleotide delivery. Remaining challenges, including model developmental immaturity, batch variability, and the difficulty of modeling polygenic risk, are addressed by a roadmap integrating spatial perturbomics, AI-driven causal inference, and population-scale standardized biobanks. This review synthesizes the current state of CRISPR-based functional genomics in human stem cell neural models as a coherent experimental framework for converting ASD genetic associations into mechanistic understanding and therapeutic opportunity.

Humans↗

Pathway-driven target prioritisation in drug discovery.

Genome-scale association studies and functional screens routinely implicate hundreds of candidate genes per disease, yet only a few will be clinically validated as drug targets. Choosing which to pursue is a central drug-discovery decision that depends on interpreting each candidate in its biological context. Curated pathway databases provide this context, while enrichment analysis applies it at scale, turning gene-level signals from genome-wide association, transcriptomic, proteomic and CRISPR studies into mechanistic hypotheses for prioritisation. This review examines how pathway-based methods inform target prioritisation, the databases and tools available for this purpose, and why pathway co-membership should be viewed as a starting point for validation rather than as evidence of causal involvement.

CRISPR↗

Genomic and transcriptomic quality control for an autologous iPSC-derived cell therapy for Parkinson's disease.

Toward development of an autologous, induced pluripotent stem cell (iPSC)-based cell therapy for Parkinson's disease (PD), we demonstrate successful, reproducible genomic and transcriptomic qualification of patient-derived dopaminergic neuron precursor cells (DANPCs) across multiple donors. Our analysis includes whole-genome sequencing data from fibroblasts, iPSCs, and DANPCs and the development of NeuriTest, an RNAseq-based bioinformatic analysis of DANPCs designed to predict cell quality based on empirical animal data. Autologous cell therapies are immune matched to the patient, potentially augmenting durability of benefit compared to allogeneic cells while negating the need for immunosuppression and accompanying side effects. Patient-specific iPSCs are an autologous cell source that can be differentiated to dopaminergic neurons, the cell type lost in PD. We report here our preclinical manufacturing strategy and results demonstrating efficacy in a PD rodent model and safety in a 9-month GLP toxicology study.

Parkinson’s disease↗

What is the relevance of bioinformatics to pharmacology?

Although bioinformatics achieved prominence because of its central role in genome data storage, management and analysis, its focus has shifted as the life sciences exploit these data. In pharmacology, genomic, transcriptomic and proteomic data are being used in the quest for drugs that fulfill unmet medical needs, are disease modifying or curative and are more effective and safer than current drugs. Bioinformatics is used in drug target identification and validation and in the development of biomarkers and toxicogenomic and pharmacogenomic tools to maximize the therapeutic benefit of drugs. Now that the 'parts list' of cellular signalling pathways is available, integrated computational and experimental programmes are being developed, with the goal of enabling in silico pharmacology by linking the genome, transcriptome and proteome to cellular pathophysiology.

Computational Biology↗

The transcriptome's drugable frequenters.

Microarray studies are widely employed in the exploratory phase of the drug discovery process. Expectations raised by the genomics revolution led to the belief that they would rapidly lead to the identification of novel drug targets. However, a few basic questions were often overlooked. Are members of drugable gene families properly represented in the transcriptome? Or are they poorly expressed and below the detection limit of the microarray technology? This review explores the representation of drug targets and components of downstream cellular signaling pathways in the transcriptome. It appears that members of drugable gene families are underrepresented in the transcriptomes of non-pathological human tissues. But, they are represented at or above the expected frequency in the differential transcriptome (i.e. the set of genes that changes expression upon a change in cellular environment). Analysis of differential gene expression on a genome-wide scale will therefore give a comprehensive overview of cellular pathways and possible drug targets.

Drug Design↗