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PubMed2024

Haplotype-resolved genome assembly and implementation of VitExpress, an open interactive transcriptomic platform for grapevine.

Haplotype-resolved genome assemblies were produced for Chasselas and Ugni Blanc, two heterozygous Vitis vinifera cultivars by combining high-fidelity long-read sequencing and high-throughput chromosome conformation capture (Hi-C). The telomere-to-telomere full coverage of the chromosomes allowed us to assemble separately the two haplo-genomes of both cultivars and revealed structural variations between the two haplotypes of a given cultivar. The deletions/insertions, inversions, translocations, and duplications provide insight into the evolutionary history and parental relationship among grape varieties. Integration of de novo single long-read sequencing of full-length transcript isoforms (Iso-Seq) yielded a highly improved genome annotation. Given its higher contiguity, and the robustness of the IsoSeq-based annotation, the Chasselas assembly meets the standard to become the annotated reference genome for V. vinifera. Building on these resources, we developed VitExpress, an open interactive transcriptomic platform, that provides a genome browser and integrated web tools for expression profiling, and a set of statistical tools (StatTools) for the identification of highly correlated genes. Implementation of the correlation finder tool for MybA1, a major regulator of the anthocyanin pathway, identified candidate genes associated with anthocyanin metabolism, whose expression patterns were experimentally validated as discriminating between black and white grapes. These resources and innovative tools for mining genome-related data are anticipated to foster advances in several areas of grapevine research.

Vitis↗

PubMed2002

Functional transcriptomes: comparative analysis of biological pathways and processes in eukaryotes to infer genetic networks among transcripts.

Microarray technology enables us to monitor large changes in transcripts at any given time. The compilation of these data makes possible the comparison of such gene expression data on a genome-wide scale. As comparisons of genome sequence data yield new biological insights, comparative analyses of transcriptome data also promise new discoveries regarding metabolic pathways and cellular processes. The coordinated expression of genes shows that these genes physically interact with each other or are part of the same cascade. We have produced one of the largest expression profiles of adult mice and developmental tissues. These data, as well as the data on yeast from previous reports, were used to see whether coordinated expression (with high correlation coefficient) is closely coupled to the actual cascade on the pathway map.

Animals↗

PubMed2025

Genomic and Transcriptomic Profiling of Radiation-Resistant, Locally Recurrent Prostate Cancer.

PURPOSE: The biology of locally radiorecurrent prostate cancer (LRR-PCa) is poorly understood. METHODS AND MATERIALS: We sought to explore the genomic and transcriptomic landscape of LRR-PCa with targeted DNA sequencing and RNA expression analysis from 41 biopsy-proven LRR-PCa tumors from 36 unique patients who had a recurrence at a median interval of 84 months (IQR, 70-124 months). Genomic alteration frequencies and transcriptomic data were compared between the LRR-PCa cohort and treatment-naïve patients from the Cancer Genome Atlas (genomic; n = 496) and Gleason grade-at-recurrence-matched patients from the Decipher Genomics Resource for Intelligent Discovery (transcriptomic; n = 22,320). RESULTS: Twenty-five patients (69%) had pathologic upgrading at recurrence (17% vs 64% with Gleason grade 4-5 disease; P < .001). The LRR-PCa cohort demonstrated significantly greater single-nucleotide variations in 29 genes known to be associated with prostate cancer, including several associated with increased aggressiveness and DNA repair: FAT1 (58.5% vs 1.0%), RAD51B (36.6% vs 0.4%), POLQ (34.1% vs 1.4%), KMT2C (34.1% vs 4.9%), BRCA2 (29.3% vs 1.8%), ATRX (26.8% vs 0.8%), and BRCA1 (24.4% vs 0.4%) (Pvalues < .001 for all). The LRR-PCa cohort had a significantly higher Decipher score (median, 0.80 vs 0.66; P = .05) and demonstrated significantly greater basal subtype based on PAM50 (56% vs 20%; P < .001) and lower androgen receptor activity (61% for LRR vs 9%; P < .001). CONCLUSIONS: Overall, these results suggest that LRR-PCa has a distinct genomic and transcriptomic landscape from de novo prostate cancer. Specifically, LRR-PCa has an enrichment in SNVs in genes associated with tumor aggressiveness and/or DNA repair, has higher Decipher scores, a more basal subtype, and has transcriptomic evidence of lower androgen receptor activity and loss of tumor suppressor genes.

Humans↗

PubMed2026

Mycosis Fungoides-Like Atopic Dermatitis Represents a Th22-Dominant Inflammatory Endotype.

BACKGROUND: Early-stage mycosis fungoides (MF) often presents diagnostic challenges because of its clinical overlap with atopic dermatitis (AD). In clinical practice, we encountered a subset of patients with severe AD who fulfilled the MF diagnostic criteria yet remained clinically indistinguishable from AD and presented refractoriness to advanced therapies. We termed this ambiguous entity "mycosis fungoides-like AD" (mfAD) and sought to determine whether it represents malignant transformation or a distinct inflammatory endotype of AD. METHODS: Skin biopsies were obtained from 7 patients with AD and 11 patients with mfAD. We performed paired single-cell RNA sequencing and single-cell T-cell receptor sequencing analyses. Publicly available MF and AD datasets were integrated for comparative analysis. Spatial transcriptomic profiling was used to contextualize single-cell findings within the tissue architecture. RESULTS: Comparative transcriptomic analysis revealed that T cells in mfAD were aligned with those in AD and lacked genomic instability. High-resolution profiling showed that mfAD was characterized by oligoclonal Th22 expansion rather than a single dominant malignant clone. Notably, all patients with mfAD achieved rapid clinical remission with selective JAK1 inhibition, indicating the therapeutic response characteristics of inflammatory dermatoses. CONCLUSION: Our findings demonstrate that mfAD is not a true malignancy, but rather a Th22-driven inflammatory endotype of AD. These results redefine mfAD as an inflammatory subtype within the AD spectrum, providing a mechanistic explanation for both the "pseudo-monoclonality" that leads to MF misdiagnosis and the failure of dupilumab. This study establishes a rationale for the use of JAK inhibitors in precision medicine for this patient population.

JAK inhibitor↗

PubMed2026

Dynamic evolution of chaperone-mediated autophagy is associated with tumor microenvironment remodeling and prognostic stratification in lung adenocarcinoma: insights from single-cell transcriptomics, ensemble machine learning, and experimental validation.

BACKGROUND: Lung adenocarcinoma (LUAD) shows prognostic heterogeneity, and tumor-node-metastasis (TNM) staging is limited for individualized management. Chaperone-mediated autophagy (CMA) maintains proteostasis, but its role during adenocarcinoma in situ (AIS)-minimally invasive adenocarcinoma (MIA)-invasive adenocarcinoma (IAC) progression remains unclear. METHODS: Single-cell RNA sequencing (scRNA-seq) data from GSE189357 and bulk transcriptomes from The Cancer Genome Atlas (TCGA)-LUAD and Gene Expression Omnibus (GEO) cohorts were integrated. CMA activity, cell-cell communication, weighted gene co-expression network analysis (WGCNA), tumor-normal differential expression, machine-learning survival modeling, tumor microenvironment (TME) features, drug sensitivity, and EPC1 function were analyzed. RESULTS: CMA-high tumor epithelial cells increased from AIS (58.1%) to MIA (65.7%) but declined in IAC (44.4%; p < 0.001). CMA-low cells preferentially received fibroblast-derived extracellular matrix cues. A CMA-negatively correlated module identified 69 core genes. Random survival forest (RSF) performed best among 117 machine-learning combinations (mean concordance index > 0.873). High-risk patients had worse survival across cohorts, and the risk score was independently associated with overall survival (hazard ratio = 16.013, 95% confidence interval: 9.579-26.768, p < 0.001). High-risk tumors showed proliferative activation and M0 macrophage enrichment, whereas low-risk tumors showed stronger immune-related signaling. EPC1 overexpression suppressed malignant phenotypes in A549 cells. CONCLUSION: CMA dynamics are associated with stromal and immune remodeling during LUAD progression. A CMA-based model provides robust prognostic stratification and may offer a basis for future TME-guided studies.

Chaperone-mediated autophagy↗

PubMed2026

Decoding the landscape of cell-type-specific co-expressed transcription factors in soybean.

Soybean (Glycine max) is an essential source of protein and oil with high nutritional value for human and animal consumption. To enhance our understanding of soybean biology, it is essential to have accurate information regarding the expression of each of its protein-coding genes. Here, we present Tabula Glycine max, a soybean single-cell resolution transcriptome atlas. This atlas comprises single-nucleus RNA-sequencing data from ten different G. max organs and morphological structures constituting the entire soybean plant. These nuclei are grouped into 156 different clusters based on their transcriptomic profiles. The breadth of various organs, tissues and cell types represented in Tabula Glycine max reveals that the pattern of co-expressed transcription factor genes is sufficient to define most cell types based on their function and organ of origin. Defining cell-type-specific co-expressed transcription factor genes offers a new perspective to engineer cell-type-specific programmes and enhance the biology of unique soybean cell types. This cellular resolution and breadth make the Tabula Glycine max an exceptional resource for the plant and soybean communities.

Journal Article↗

PubMed2026

Oncogenic Mutations and Tumor Microenvironment Alterations in Diffuse Large B-Cell Lymphoma With Bulky Disease.

BACKGROUND: Bulky disease represents a clinically aggressive subset of diffuse large B-cell lymphoma (DLBCL) associated with adverse clinical outcomes. The aim of this study was to investigate the influence of oncogenic mutations and tumor microenvironment alterations on bulky disease in DLBCL. METHODS: We analyzed a cohort of 939 patients with newly diagnosed DLBCL. Using DNA (n = 934) and RNA (n = 524) sequencing, we compared oncogenic mutations and tumor microenvironment (TME) alterations based on tumor diameter, with cutoff values at 5.0 cm and 10.0 cm. Further stratification by mutations in key genes (CD58, STAT6, EBF1) correlated with tumor diameter revealed distinct transcriptomic and immunologic profiles. Subsequent single-cell RNA sequencing, guided by these mutational signatures, resolved the cellular heterogeneity within the TME. RESULTS: Integrative analysis revealed that tumor diameter correlated with increased incidence of mutations in CD58, STAT6, and EBF1; adverse genetic subtypes such as EZB-like MYC+ and TP53Mut; activation of oncogenic pathways (JAK/STAT, BCR, PI3K, and MYC); and an immunosuppressive tumor microenvironment. Notably, immune checkpoint molecules varied across the bulky stages, with CTLA-4, TIGIT, ICOS, and CD28 expression inversely correlated with tumor diameter, while CD70 and 4-1BBL expression positively correlated. Single-cell RNA sequencing further revealed mutation-specific tumor microenvironment insights. CD58-mutated tumor exhibited a profoundly immune-deserted microenvironment dominated by malignant B cells with minimal immune infiltration, whereas STAT6-mutated tumor was associated with increased fibroblasts and CD4 + T cells, particularly regulatory T cells (Treg) and Th1-like cells; EBF1-mutated tumor was characterized by increased proportions of malignant B cells. CONCLUSIONS: Collectively, our findings highlight the biological complexity of bulky disease, identifying candidate molecular targets and providing a biological framework for future therapeutic hypothesis generation in this clinically aggressive subset of DLBCL.

Humans↗

PubMed2002

Human prostate epithelial cell-type cDNA libraries and prostate expression patterns.

BACKGROUND: Transcriptome analysis is a powerful approach to uncovering genes responsible for diseases such as prostate cancer. Ideally, one would like to compare the transcriptomes of a cancer cell and its normal counterpart for differences. METHODS: Prostate luminal and basal epithelial cell types were isolated and cell-type-specific cDNA libraries were constructed. Sequence analysis of cDNA clones generated 505 luminal cell genes and 560 basal cell genes. These sequences were deposited in a public database for expression analysis. RESULTS: From these sequences, 119 unique luminal expressed sequence tags (ESTs) were extracted and assembled into a luminal-cell transcriptome set, while 154 basal ESTs were extracted and assembled into a basal-cell set. Interlibrary comparison was performed to determine representation of these sequences in cDNA libraries constructed from prostate tumors, PIN, cell lines. CONCLUSIONS: Our analysis showed that a significant number of epithelial cell genes were not represented in the various transcriptomes of prostate tissues, suggesting that they might be underrepresented in libraries generated from tissue containing multiple cell types. Although both luminal and basal cell types are epithelial, their transcriptomes are more divergent from each other than expected, underscoring their functional difference (secretory vs. nonsecretory). Tumor tissues show different expression of luminal and basal genes, with perhaps a trend towards expression of basal genes in advanced diseases.

DNA, Complementary↗

PubMed2000

Transcriptome analysis of channel catfish (Ictalurus punctatus): genes and expression profile from the brain.

Expressed sequence tag (EST) analysis was conducted using a complementary DNA (cDNA) library made from the brain mRNA of channel catfish (Ictalurus punctatus). As part of our transcriptome analysis in catfish to develop molecular reagents for comparative functional genomics, here we report analysis of 1201 brain cDNA clones. Of the 1201 clones, 595 clones (49.5%) were identified as known genes by BLAST searches and 606 clones (50.5%) as unknown genes. The 595 clones of known gene products represent transcripts of 251 genes. These known genes were categorized into 15 groups according to their biological functions. The largest group of known genes was the genes involved in translational machinery (21.4%) followed by mitochondrial genes (6.2%), structural genes (3.1%), genes homologous to sequences of unknown functions (2.3%), enzymes (2.7%), hormone and regulatory proteins (2.5%), genes involved in immune systems (2.1%), genes involved in sorting, transport, and metal metabolism (1.8%), transcriptional factors and DNA repair proteins (1.6%), proto-oncogenes (1.2%), lipid binding proteins (1.2%), stress-induced genes (0.7%), genes homologous to human genes involved in mental diseases (0.6%), and development or differentiation-related genes (0.3%). The number of genes represented by the 606 clones of unknown genes is not known at present, but the high percentage of clones showing no homology to any known genes in the GenBank databases may indicate that a great number of novel genes exist in teleost brain.

Animals↗

PubMed2024

Bioinformatic approaches for accurate assessment of A-to-I editing in complete transcriptomes.

A-to-I RNA editing is an RNA modification that alters the RNA sequence relative to the its genomic blueprint. It is catalyzed by double-stranded RNA-specific adenosine deaminase (ADAR) enzymes, and contributes to the complexity and diversification of the proteome. Advancement in the study of A-to-I RNA editing has been facilitated by computational approaches for accurate mapping and quantification of A-to-I RNA editing based on sequencing data. In this chapter we review some of the main computational approaches currently used, describe potential hurdles, challenges and pitfalls, and discuss possible ways to mitigate them.

RNA Editing↗

PubMed2024

Protocol to decode the role of transcriptionally active microbes in SARS-CoV-2-positive patients using an RNA-seq-based approach.

The elucidation of the role of microorganisms in human infections has been hindered by difficulties using conventional culture-based techniques. Here, we present a protocol for the investigation of transcriptionally active microbes (TAMs) using an RNA sequencing (RNA-seq)-based approach. We describe the steps for RNA isolation, viral genome sequencing, RNA-seq library preparation, and metatranscriptomic and transcriptomic analysis. This protocol permits a comprehensive evaluation of TAMs' contributions to the differential severity of infectious diseases, with a particular focus on diseases such as COVID-19. For complete details on the use and execution of this protocol, please refer to Devi et al.1.

Humans↗

PubMed2025

Single-cell profiling of trabecular meshwork identifies mitochondrial dysfunction in a glaucoma model that is protected by vitamin B3 treatment.

Since the trabecular meshwork (TM) is central to intraocular pressure (IOP) regulation and glaucoma, a deeper understanding of its genomic landscape is needed. We present a multimodal, single-cell resolution analysis of mouse limbal cells (includes TM). In total, we sequenced 9,394 wild-type TM cell transcriptomes. We discovered three TM cell subtypes with characteristic signature genes validated by immunofluorescence on tissue sections and whole-mounts. The subtypes are robust, being detected in datasets for two diverse mouse strains and in independent data from two institutions. Results show compartmentalized enrichment of critical pathways in specific TM cell subtypes. Distinctive signatures include increased expression of genes responsible for 1) extracellular matrix structure and metabolism (TM1 subtype), 2) secreted ligand signaling to support Schlemm's canal cells (TM2), and 3) contractile and mitochondrial/metabolic activity (TM3). ATAC-sequencing data identified active transcription factors in TM cells, including LMX1B. Mutations in LMX1B cause high IOP and glaucoma. LMX1B is emerging as a key transcription factor for normal mitochondrial function and its expression is much higher in TM3 cells than other limbal cells. To understand the role of LMX1B in TM function and glaucoma, we single-cell sequenced limbal cells from Lmx1b V265D/+ mutant mice (2,491 TM cells). In V265D/+ mice, TM3 cells were uniquely affected by pronounced mitochondrial pathway changes. Mitochondria in TM cells of V265D/+ mice are swollen with a reduced cristae area, further supporting a role for mitochondrial dysfunction in the initiation of IOP elevation in these mice. Importantly, treatment with vitamin B3 (nicotinamide), to enhance mitochondrial function and metabolic resilience, significantly protected Lmx1b mutant mice from IOP elevation.

Journal Article↗

PubMed2026

REACTOR: REgulon Activity analysis and Comparison Tool for single-cell transcriptOmics Research.

SUMMARY: We introduce REACTOR, a computational tool designed to detect differential activity of transcriptional regulators and their target genes (regulons) in single-cell RNA-sequencing data. It expands the currently available framework for regulon analysis by introducing a robust statistical test to detect differential regulon activity between conditions, such as disease versus control, with multiple replicates. By contrasting different conditions, REACTOR enables identification of key condition- and cell type-specific regulons. To demonstrate the use of REACTOR, we illustrate its performance in a publicly available COVID-19 dataset. AVAILABILITY: REACTOR R-package together with an implementation vignette are available at https://www.github.com/elolab/REACTOR.

Regulon↗

PubMed2026

Multi-omics approaches in idiopathic pulmonary fibrosis: from molecular mechanisms to therapeutic targets and precision medicine.

Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease with limited therapeutic options and marked molecular heterogeneity. Despite available antifibrotic therapies, disease progression remains poorly predictable, highlighting the need for improved mechanistic understanding and therapeutic targeting. This review summarizes recent advances in multi-omics research to elucidate the molecular mechanisms underlying IPF and to identify potential biomarkers and pharmacological targets. Multi-omics studies, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiome profiling, and single-cell sequencing, have revealed key pathogenic mechanisms in IPF. Genetic susceptibility factors such as MUC5B promoter variants and telomere-related genes contribute to disease risk. Epigenetic regulation, including DNA methylation, histone modifications, and non-coding RNAs, plays a central role in fibrotic remodeling. Transcriptomic and proteomic analyses have identified dysregulated signaling pathways, including TGF-β, mTOR, cellular senescence, and extracellular matrix remodeling. Metabolomic alterations indicate disrupted lipid and amino acid metabolism. Importantly, integration of multi-omics datasets enables the identification of molecular endotypes, candidate biomarkers, and potential therapeutic targets. However, challenges including data integration, tissue heterogeneity, limited cohort size, and the need for functional validation remain important barriers to clinical translation. Continued development of multi-omics approaches may facilitate more accurate disease classification and support the development of personalized therapeutic strategies for IPF.

biomarkers↗

PubMed2025

LINNAEUS: Simultaneous Single-Cell Lineage Tracing and Cell Type Identification.

A key goal of biology is to understand the origin of the many cell types that can be observed during diverse processes such as development, regeneration, and disease. Single-cell RNA-sequencing (scRNA-seq) is commonly used to identify cell types in a tissue or organ. However, organizing the resulting taxonomy of cell types into lineage trees to understand the origins of cell states and relationships between cells remains challenging. Here we present LINNAEUS (Spanjaard et al, Nat Biotechnol 36:469-473. https://doi.org/10.1038/nbt.4124 , 2018; Hu et al, Nat Genet 54:1227-1237. https://doi.org/10.1038/s41588-022-01129-5 , 2022) (LINeage tracing by Nuclease-Activated Editing of Ubiquitous Sequences)-a strategy for simultaneous lineage tracing and transcriptome profiling in thousands of single cells. By combining scRNA-seq with computational analysis of lineage barcodes, generated by genome editing of transgenic reporter genes, LINNAEUS can be used to reconstruct organism-wide single-cell lineage trees. LINNAEUS provides a systematic approach for tracing the origin of novel cell types, or known cell types under different conditions.

Single-Cell Analysis↗

PubMed2026

Beyond the gene: isoform diversity as a key contributor to human brain disorders.

The human brain exhibits exceptional transcriptomic complexity, with alternative splicing, promoter usage, and polyadenylation generating extensive transcript-isoform diversity. Isoform dysregulation is increasingly implicated in neurodevelopmental and psychiatric disorders (NPDs), yet the landscape, function, and genetic regulation of brain isoforms remain poorly understood due to limitations of short-read RNA sequencing. Advances in long-read sequencing (LR-seq) enable scalable full-length transcriptome profiling with single-cell and spatial resolution across developmental stages. Here, we review recent progress in isoform discovery, quantification, functional annotation, and genetic regulation, highlighting emerging links to human neurodevelopment and disease. LR-seq studies have uncovered tens of thousands of previously unannotated brain isoforms, with neuronal maturation characterized by increased exon inclusion and progressive 3' untranslated region (3' UTR) lengthening. Isoform-resolved genetic mapping outperforms gene-level analyses for NPD gene discovery and mechanistic interpretation. We argue that a shift from gene-centric to isoform-centric frameworks is essential to fully capture regulatory complexity in human neurogenetics. Together, these advances establish isoform diversity as a fundamental yet underappreciated axis of brain gene regulation and a key entry point for dissecting NPD biology.

Humans↗

PubMed2003

Identification and analysis of chromodomain-containing proteins encoded in the mouse transcriptome.

The chromodomain is 40-50 amino acids in length and is conserved in a wide range of chromatic and regulatory proteins involved in chromatin remodeling. Chromodomain-containing proteins can be classified into families based on their broader characteristics, in particular the presence of other types of domains, and which correlate with different subclasses of the chromodomains themselves. Hidden Markov model (HMM)-generated profiles of different subclasses of chromodomains were used here to identify sequences encoding chromodomain-containing proteins in the mouse transcriptome and genome. A total of 36 different loci encoding proteins containing chromodomains, including 17 novel loci, were identified. Six of these loci (including three apparent pseudogenes, a novel HP1 ortholog, and two novel Msl-3 transcription factor-like proteins) are not present in the human genome, whereas the human genome contains four loci (two CDY orthologs and two apparent CDY pseudogenes) that are not present in mouse. A number of these loci exhibit alternative splicing to produce different isoforms, including 43 novel variants, some of which lack the chromodomain. The likely functions of these proteins are discussed in relation to the known functions of other chromodomain-containing proteins within the same family.

Acetyltransferases↗

PubMed2026

Molting in Pancrustacea Is Characterized by Both Deeply Conserved and Recently Evolved Gene Modules.

Arthropods such as insects and crustaceans, which together form the monophyletic group Pancrustacea, possess a rigid chitinous exoskeleton that must be periodically shed through molting to allow growth and morphological change. Although molting is a deeply conserved developmental process across Arthropoda, our understanding of its molecular mechanisms is still largely derived from insect model species. Lineage-specific innovations and losses of molting-related genes raise fundamental questions about the extent of its conservation outside noninsect arthropods. Here, we investigate the evolutionary conservation of molting gene expression across five representative pancrustacean species using publicly available transcriptomic datasets. Changes in gene expression during molting are characterized by both deeply conserved and lineage-specific gene modules. Temporal gene expression analyses reveal that these lineage-specific signatures are not uniformly distributed across the molting process: the middle transitional phase is more lineage-specific, thereby exhibiting an inverse hourglass pattern. This is likely due to life-history-specific processes, development of the cuticle, and specialized structures of the exoskeleton. Overall, this study provides evidence for both the evolutionary conservation and divergence of this key postembryonic developmental process and highlights the modular architecture of the molting program.

Animals↗