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PubMed2026

Time-Dependent Effects of Rapid-Acting Antidepressants in iPSC-Derived Neurons from Treatment-Resistant Depression and Healthy Volunteers.

UNLABELLED: Rapid-acting antidepressants like ketamine and serotonergic psychedelics show promise for treatment-resistant depression (TRD), but the molecular mechanisms that contribute to their therapeutic effects remain unclear. Induced pluripotent stem cells (iPSCs) offer a platform to model human cortical neurons and investigate drug effects in a human-relevant system. Here, iPSCs from individuals with TRD and healthy volunteers (HVs) were differentiated into mature cortical-like neurons and treated for six and 24 hours with agents being investigated as rapid-acting antidepressants, including (2R,6R)-hydroxynorketamine (HNK), psilocybin, lysergic acid diethylamide (LSD), and 2,5-Dimethoxy-4-iodoamphetamine (DOI). Bulk and single-cell RNA sequencing assessed global and cell-type-specific transcriptomic responses. Synaptic proteins were evaluated via Western blotting and immunocytochemistry. To validate translational relevance, transcriptomic results were compared to CSF proteomics from ketamine-treated HVs. Despite differing initial pharmacological targets, overall gene expression across all compounds was highly correlated at matched timepoints compared to vehicle control, suggesting shared downstream effects. Both glutamatergic and serotonergic drugs converged on pathways involving inflammation, mTORC1 signaling, and cellular growth. At the single-cell level, HNK showed distinct cell-type specific alterations: upregulation in excitatory neurons and concomitant downregulation of inhibitory neuron populations. Differentially expressed genes from HNK-treated neurons also overlapped with CSF proteomic signatures from ketamine-treated individuals, supporting the model's translational relevance. This study is the first to assess multiple putative rapid-acting antidepressants in parallel using an iPSC-derived neuron model. Both convergent and drug-specific changes in gene expression and pathway enrichment were observed across diverse compounds, supporting the use of human iPSC-derived neurons in antidepressant drug discovery. CLINICAL TRIAL REGISTRY: www.clinicaltrials.gov, NCT02484456.

Journal Article↗
PubMed2005

Accessing optimal primer distance from insert.

When building either DNA or cDNA libraries, a researcher looks at the vector multiple cloning site and chooses which restriction enzyme(s) will be used to clone the inserts. Although this procedure does not seem to be important, the accurate choosing of primer to insert distance can save time and money from genome and transcriptome projects. Here, 846 single-pool pUC18 sequences were produced and compared with the pUC18 consensus using local alignment tools. Data show that reads often contain 0-20 miscalled bases at the beginning of read and noise to signal transition is frequently found at 46-54 bases from the first 3' base downstream the sequencing primer. For SWAT-based approaches, 60 bases was the distance where over 90% of the sequences provided reliable information, presenting 13 vector bases on average. Looking at the data, it is possible to choose the most appropriate primer to insert distance for many applications.

Algorithms↗
PubMedDate not supplied

Transcriptomics and proteomics: tools for the identification of novel drug targets and vaccine candidates for tuberculosis.

The availability of the complete genome sequence of Mycobacterium tuberculosis has revolutionised many areas of tuberculosis research and facilitated functional genomics studies. Most notably, transcriptomics and proteomics have become important tools in gaining increased understanding of the biology of M. tuberculosis and offer the promise of being able to deliver novel drug targets and vaccine candidates.

Electrophoresis, Gel, Two-Dimensional↗
PubMed2001

Sequence and analysis of the Arabidopsis genome.

The comprehensive analysis of the genome sequence of the plant Arabidopsis thaliana has been completed recently. The genome sequence and associated analyses provide the foundations for rapid progress in many fields of plant research, such as the exploitation of genetic variation in Arabidopsis ecotypes, the assessment of the transcriptome and proteome, and the association of genome changes at the sequence level with evolutionary processes. Nevertheless, genome sequencing and analysis are only the first steps towards a new plant biology. Much remains to be done to refine the analysis of encoded genes, to define the functions of encoded proteins systematically, and to establish new generations of databases to capture and relate diverse data sets generated in widely distributed laboratories.

Arabidopsis↗
PubMed2025

Unsupervised multiscale clustering of single-cell transcriptomes to identify hierarchical structures of cell subtypes.

BACKGROUND: Cell clustering is an essential step in uncovering cellular architectures in single-cell RNA sequencing (scRNA-seq) data. However, the existing cell clustering approaches are not well designed to dissect complex structures of cellular landscapes at a finer resolution. RESULTS: Here, we develop a multiscale clustering (MSC) approach to construct a sparse cell-cell correlation network for unsupervised identification of de novo cell types and subtypes across multiple resolutions. Based upon simulated silver- and gold-standard data as well as real scRNA-seq data in diseases, MSC demonstrates significantly improved performance compared to established benchmark methods and reveals a biologically meaningful cell hierarchy to facilitate the discovery of novel disease-associated cell subtypes and mechanisms. CONCLUSIONS: We present MSC as a new single-cell multiscale clustering framework as a powerful tool for advancing discoveries in disease-associated cell populations using single-cell sequencing data.

Single-Cell Analysis↗
PubMed2003

Annotation and analysis of 10,000 expressed sequence tags from developing mouse eye and adult retina.

BACKGROUND: As a biomarker of cellular activities, the transcriptome of a specific tissue or cell type during development and disease is of great biomedical interest. We have generated and analyzed 10,000 expressed sequence tags (ESTs) from three mouse eye tissue cDNA libraries: embryonic day 15.5 (M15E) eye, postnatal day 2 (M2PN) eye and adult retina (MRA). RESULTS: Annotation of 8,633 non-mitochondrial and non-ribosomal high-quality ESTs revealed that 57% of the sequences represent known genes and 43% are unknown or novel ESTs, with M15E having the highest percentage of novel ESTs. Of these, 2,361 ESTs correspond to 747 unique genes and the remaining 6,272 are represented only once. Phototransduction genes are preferentially identified in MRA, whereas transcripts for cell structure and regulatory proteins are highly expressed in the developing eye. Map locations of human orthologs of known genes uncovered a high density of ocular genes on chromosome 17, and identified 277 genes in the critical regions of 37 retinal disease loci. In silico expression profiling identified 210 genes and/or ESTs over-expressed in the eye; of these, more than 26 are known to have vital retinal function. Comparisons between libraries provided a list of temporally regulated genes and/or ESTs. A few of these were validated by qRT-PCR analysis. CONCLUSIONS: Our studies present a large number of potentially interesting genes for biological investigation, and the annotated EST set provides a useful resource for microarray and functional genomic studies.

Aging↗
PubMed2005

Transcriptional profiling of mefloquine-induced disruption of calcium homeostasis in neurons in vitro.

Mefloquine is associated with adverse neurological effects that are mediated via unknown mechanisms. Recent in vitro studies have shown that mefloquine disrupts neuronal calcium homeostasis via liberation of the endoplasmic reticulum (ER) store and induction of calcium influx across the plasma membrane. In the present study, global changes in gene expression induced in neurons in response to mefloquine-induced disruption of calcium homeostasis and appropriate control agents were investigated in vitro using Affymetrix arrays. The mefloquine transcriptome was found to be enriched for important regulatory sequences of the unfolded protein response and the drug was also found to induce key ER stress proteins, albeit in a manner dissimilar to, and at higher equivalent concentrations than, known ER-tropic agents like thapsigargin. Mefloquine also down-regulated several important functional categories of genes, including transcripts encoding G proteins and ion channels. These effects may be related to intrusion of extracellular calcium since they were also observed after glutamate, but not thapsigargin, hydrogen peroxide, or low-dose mefloquine treatment. Mefloquine could be successfully differentiated from other treatments on the basis of principle component analysis of its "calcium-relevant" transcriptome. These data may aid interpretation of expression of results from future in vivo studies.

Animals↗
PubMed2001

Recent advances in computational genomics.

In the post-genomic era, the new discipline of functional genomics is now facing the challenge of associating a function (as well as estimating its relevance to industrial applications) to about 100,000 microbial, plant or animal genes of known sequence but unknown function. Besides the design of databases, computational methods are increasingly becoming intimately linked with the various experimental approaches. Consequently, bioinformatics is rapidly evolving into independent fields addressing the specific problems of interpreting i) genomic sequences, ii) protein sequences and 3D-structures, as well as iii) transcriptome and macromolecular interaction data. It is thus increasingly difficult for the biologist to choose the computational approaches that perform best in these various areas. This paper attempts to review the most useful developments of the last 2 years.

Computational Biology↗
PubMed2005

An algorithmic framework for genome-wide modeling and analysis of translation networks.

The sequencing of genomes of several organisms and advances in high throughput technologies for transcriptome and proteome analysis has allowed detailed mechanistic studies of transcription and translation using mathematical frameworks that allow integration of both sequence-specific and kinetic properties of these fundamental cellular processes. To understand how perturbations in mRNA levels affect the synthesis of individual proteins within a large protein synthesis network, we consider here a genome-scale codon-wide model of the translation machinery with explicit description of the processes of initiation, elongation, and termination. The mechanistic codon-wide description of the translation process and the large number of mRNAs competing for resources, such as ribosomes, requires the use of novel efficient algorithmic approaches. We have developed such an efficient algorithmic framework for genome-scale models of protein synthesis. The mathematical and computational framework was applied to the analysis of the sensitivity of a translation network to perturbation in the rate constants and in the mRNA levels in the system. Our studies suggest that the highest specific protein synthesis rate (protein synthesis rate per mRNA molecule) is achieved when translation is elongation-limited. We find that the mRNA species with the highest number of actively translating ribosomes exerts maximum control on the synthesis of every protein, and the response of protein synthesis rates to mRNA expression variation is a function of the strength of initiation of translation at different mRNA species. Such quantitative understanding of the sensitivity of protein synthesis to the variation of mRNA expression can provide insights into cellular robustness mechanisms and guide the design of protein production systems.

Algorithms↗
PubMed2026

A Molecularly Anchored Spatial Transcriptomic Framework for Precise CA1-Subiculum Parcellation and Region-Resolved Analysis in Alzheimer's Disease.

BACKGROUND: The precise molecular delineation of the interface between the Subiculum (Sub) and cornu ammonis 1 (CA1) is a challenge in hippocampal research, as conventional cytoarchitectural boundaries are often ambiguous and limit reproducible regional annotation. Here, we developed a molecularly anchored spatial transcriptomic framework to define CA1-Sub regional identities using high-definition spatial transcriptomics (Stereo-seq) and single-nucleus RNA sequencing (snRNA-seq) references. FINDINGS: Using a human hippocampal Stereo-seq dataset from 12 donors, we established a data-driven parcellation framework that defines reproducible molecular features distinguishing CA1 and Sub while capturing the transition between these regions. FN1 was identified as a Sub-enriched marker in a subset of EX_Sub and, together with ETV1 and additional regional markers, enabled molecular assignment of CA1 and Sub identities across datasets. The Sub association of FN1 and ETV1 was further supported by human 10X Genomics spatial transcriptomics, mouse in situ hybridization data, and a mouse spatial transcriptomic dataset. Applying this framework to Alzheimer's disease (AD) tissues revealed region-specific transcriptional alterations across CA1 and Sub, including enrichment of mitochondrial energy metabolism-related transcripts in the Sub, suggesting exploratory transcriptional associations of altered metabolic function. CONCLUSIONS: This study provides a molecularly anchored framework for human CA1-Sub parcellation that complements conventional annotation. By defining regional molecular states while preserving the biological continuum across CA1-Sub interface, this approach enables more consistent regional analysis of human hippocampus tissue across donors, datasets, and disease conditions.

Journal Article↗
PubMed2006

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↗
PubMed2006

Profiling of maternal and developmental-stage specific mRNA transcripts in Atlantic halibut Hippoglossus hippoglossus.

cDNA libraries were constructed from the following developmental stages (tissues) of the Atlantic halibut (Hippoglossus hippoglossus): 2-cell stage (embryos), 1 day-old yolk sac larvae (trunk) and juvenile (fast skeletal muscle). A total of 4249 high quality expressed sequence tags from the three libraries were clustered into a partial transcriptome of 2124 putative genes. A large proportion of the gene clusters (48.3%) had no significant matches against known proteins. The most abundant ESTs of nuclear transcripts in the 2-cell library included sequences with high identity to zebrafish H1M, a linker histone-like protein involved in primordial germ cell specification, zinc finger protein, rRNA external transcribed spacer, thymosin beta-4, cyclin B1 and several predicted peptides from the Tetraodon nigroviridis genome assembly with unknown functions. 170 and 123 ESTs represented ribosomal proteins in the larval and juvenile libraries respectively, compared with only two sequences in the 2-cell library, which may reflect an abundance of maternally inherited pre-formed ribosomes in the yolk. Even though some clusters were common to all three libraries, most putative genes showed a developmental-stage specific distribution with 72% (2-cell embryo), 59% (larval) and 57% (juvenile) sequences having no significant matches against the 8400 adult halibut sequences in the EMBL nucleotide database. Comparison between the predicted halibut peptide data set and the human, zebrafish, and pufferfishes (T. nigroviridis and Takifugu rubripes) proteomes revealed that, as expected, the halibut sequences were more similar to the other two fish species than to human proteins. However, no clear bias towards the pufferfishes was observed, suggesting significant sequence variation between orthologues within the clade Acanthomorpha. The sequence information generated in the present study will represent a significant new resource for future studies on normal and abnormal development in Atlantic halibut.

Animals↗
PubMed2004

FREP: a database of functional repeats in mouse cDNAs.

The FREP database (http://facts.gsc.riken.go.jp/FREP/) contains 31 396 RepeatMasker-identified non-redundant variant repeat sequences derived from 16,527 mouse cDNAs with protein-coding potential. The repeats were computationally associated with potential effects on transcriptional variation, translation, protein function or involvement in disease to identify Functional REPeats (FREPs). FREPs are defined by the (i) occurrence of exon-exon boundaries in repeats, (ii) presence of polyadenylation sites in 3'UTR-located repeats, (iii) effect on translation, (iv) position in the protein- coding region or protein domains or (v) conditional association with disease MeSH terms. Currently the database contains 9261 (29.5%) inferred FREPs derived from 6861 (41.5%) mouse cDNAs. Integrated evidence of the functional assignments and dynamically generated sequence similarity search results support the exploration and annotation of functional, ancestral or taxon-specific repeats. Keyword and pre-selected feature searches (e.g. coding sequence-repeat or splice site-repeat relations) support intuitive database querying as well as the retrieval of repeat sequences. Integrated sequence search and alignment tools allow the analysis of known or identification of new functional repeat candidates. FREP is a unique resource for illuminating the role of transposons and repetitive sequences in shaping the coding part of the mouse transcriptome and for selecting the appropriate experimental model to study diseases with suspected repeat etiology contributions.

Animals↗
PubMed2026

High-throughput single-cell proteomics and transcriptomics from same cells with a nanoliter-scale, spin-transfer approach.

Single-cell multiomic platforms provide a comprehensive snapshot of cellular states and cell types by offering critical insights into the spatiotemporal regulation of biomolecular networks at a systems level, thereby defining the basis of multicellularity. Here, we introduce nanoSPINS, an advanced platform that enables high-throughput profiling and integrative analysis of the transcriptome and proteome from the same single cells using RNA sequencing and isobaric labeling LC-MS-based proteomics, respectively. NanoSPINS can efficiently transfer mRNA-containing droplets across two microarrays via a centrifugation-based approach, while proteins are retained on the initial platform. Benchmarking of nanoSPINS on two cell lines demonstrates its ability to generate global proteomic and transcriptomic profiles that align well with previously established methodologies/platforms. The incorporation of isobaric TMTpro labeling into this single-cell multiomics platform significantly enhances the throughput of single-cell proteomic analyses. Through the high-throughput quantification of the proteome and transcriptome, nanoSPINS not only facilitates the identification of molecular features at both mRNA and protein level but also provides larger sample sizes for improved statistical power in clustering and differential abundance. Given the broad applicability of single-cell multiomics in biological research and clinical settings, we believe nanoSPINS represents a powerful platform for the characterization of heterogeneous cell populations.

Single-Cell Analysis↗
PubMed2025

Alternative Splicing in Mechanically Stretched Podocytes as a Model of Glomerular Hypertension.

KEY POINTS: Mechanical stretch induced over 3000 alternative splicing events in podocytes, affecting gene expression and protein abundance. Seventeen genes showed consistent splicing events across multiple analysis tools, with key isoform changes. Shroom3 and Myl6 underwent isoform switches under mechanical stretch, altering the C-terminal sequence and interaction properties of Myl6. BACKGROUND: Alterations in pre-mRNA splicing are crucial to the pathophysiology of various diseases. However, the effects of alternative splicing of mRNA on podocytes in hypertensive nephropathy are still unknown. The Sys_CARE project aimed to identify alternative splicing events involved in the development and progression of glomerular hypertension. METHODS: Murine podocytes were exposed to mechanical stretch, after which proteins and mRNA were analyzed by proteomics, RNA sequencing, and several bioinformatic alternative splicing tools. RESULTS: Using transcriptomic and proteomic analysis, we identified significant changes in gene expression and protein abundance because of mechanical stretch. RNA-Seq identified over 3000 alternative spliced genes after mechanical stretch, including all types of alternative splicing events. Among these, 17 genes exhibited an alternative splicing event across four different splicing analysis tools. From this group, we focused on Myl6, a component of the myosin protein complex, and Shroom3, an actin-binding protein essential for podocyte function. We identified two Shroom3 isoforms with significant expression changes under mechanical stretch, which was validated by quantitative RT-PCR and in situ hybridization. In addition, we observed an expression switch of two Myl6 isoforms after mechanical stretch, accompanied by an alteration in the C-terminal amino acid sequence. CONCLUSIONS: A comprehensive RNA-Seq analysis of mechanically stretched podocytes identified novel potential podocyte-specific biomarkers and highlighted significant alternative splicing events, notably in the mRNA of Shroom3 and Myl6.

podocyte↗
PubMed2026

HyLnc: a hybrid deep learning and feature-based approach for long non-coding RNA prediction.

Long non-coding RNAs (lncRNAs) play important roles in gene regulation, development and disease, yet accurate identification of lncRNAs from transcriptomic data remains a major computational challenge. Existing methods often rely either on handcrafted sequence features or deep learning approaches, each with their inherent limitations in capturing the full complexity of RNA sequences. In this study, we proposed HyLnc, a computational framework that integrates transformer-based contextual embeddings with biologically meaningful sequence features for improved lncRNA prediction. A custom BERT-based model was first pre-trained on a large corpus of metazoan RNA sequences using a masked language modelling strategy to learn contextual nucleotide dependencies. The model was subsequently fine-tuned on curated datasets of lncRNAs and protein-coding transcripts and 256-dimensional deep sequence embeddings were extracted. Parallelly, 348 handcrafted features, including ORF characteristics, untranslated region (UTR) properties, nucleotide composition and Fickett scores, were computed. A multi-stage feature selection strategy was applied to identify the most informative features, resulting in optimized hybrid feature sets. Multiple machine learning classifiers were evaluated, with the RF model achieving the best performance. The proposed framework attained an accuracy of 91.30%, F1-score of 91.23% and MCC of 82.60 on an independent validation dataset, outperforming several existing lncRNA prediction tools. Thus, HyLnc demonstrates that integrating deep contextual representations with biologically interpretable features enhances lncRNA prediction. This approach provides a robust and scalable solution for large-scale transcriptome annotation and can be extended to other sequence-based prediction.

RNA, Long Noncoding↗
PubMed2005

Floral gene resources from basal angiosperms for comparative genomics research.

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

Biodiversity↗
PubMed2026

NextLongIso: a comprehensive Nextflow pipeline for multi-dimensional long-read RNA-seq analysis.

SUMMARY: Long-read RNA sequencing technologies, including Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT), enable direct characterization of full-length transcripts and transcriptome complexity. However, analysis of long-read RNA-seq data remains fragmented across multiple tools, limiting the ability to obtain a unified view of transcript structure, expression, and regulatory variation in long-read transcriptomes. We present NextLongIso, a scalable and reproducible Nextflow pipeline that enables coordinated analysis of multiple layers of transcript regulation. Rather than focusing solely on transcript reconstruction, NextLongIso integrates transcript discovery with downstream regulatory analyses to jointly characterize alternative splicing, isoform switching, transcript boundary dynamics (including alternative promoters and polyadenylation), and transposable element-associated transcription from both PacBio and ONT datasets. By eliminating complex cross-tool data harmonization, this unified framework facilitates the transition from transcript identification to functional interpretation of transcriptomic variation. AVAILABILITY AND IMPLEMENTATION: NextLongIso is implemented in Nextflow and is freely available at github: https://github.com/YidanSunResearchLab/nf-LongIso.git and Zenodo: https://doi.org/10.5281/zenodo.21049837.

Software↗