Search Results (5,920)

Tongue squamous cell carcinoma (TSCC) is clinically heterogeneous, and patients with a similar TNM stage can experience markedly different outcomes. We systematically reviewed omics-driven studies to identify prognostic TSCC biomarkers. Although fundamentally prognostic, we discussed their theoretical translational relevance regarding future clinical decisions—such as treatment stratification or surveillance intensity—while strictly framing them as preliminary, hypothesis-generating targets. PubMed, Scopus, Web of Science, and Cochrane were searched for original human studies published between 2014 and 2024 using high-throughput genomic or transcriptomic profiling. Study selection followed referred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), data were extracted with a structured workbook, and risk of bias was assessed using QUIPS and PROBAST, with reporting completeness appraised using REMARK. Seventeen studies were included, identifying 85 distinct biomarkers. Across biomarkers supported by multivariable overall survival analyses, higher-risk associations were reported for NELL2, PDE4D, CTTN, HBEGF, and CA9, whereas lower-risk associations were reported for AC139530.1, LINC01711, CCDC96, CYP2J2, and SPAG16. Recurrent biological themes included IL-17 signaling, ECM-receptor interaction, and focal adhesion. CA9 was the only biomarker reported in more than one included study, supporting its prioritization for validation. Although the evidence remains heterogeneous and largely hypothesis-generating, these markers may support the future validation of response-oriented therapeutic stratification in TSCC. Full article

Background/Objectives: NF2-related schwannomatosis (NF2-SWN) is a genetic tumor predisposition syndrome of the nervous system caused by pathogenic variants in NF2 encoding the merlin tumor suppressor. Truncating variants in NF2 cause severe phenotypes with higher tumor burden, early mortality, and a lifetime need for multiple surgeries due to lack of medications that control schwannoma growth. Methods: We developed a functional precision medicine (FPM)-inspired workflow to identify drug sensitivities in cells isolated from a pediatric severe NF2-SWN patient’s spinal and peripheral schwannomas. Transcriptomic profiling, high-content drug sensitivity assays, tissue and isolated cell immunostaining, flow cytometry, and capillary-based immunoblotting were used to study the available tissues. Results: Aberrant merlin-dependent pathway expression was conserved between the spinal schwannoma and its cultured primary cells. Drug sensitivity screens in 2- and 3-dimensional formats revealed cytotoxic effects of fimepinostat in primary cells; dasatinib with brigatinib was the most effective cytostatic combination. Ineffective therapies attempted in the patient were also ineffective ex vivo. Conclusions: These data support the idea of using the FPM workflow to improve and individualize the standard of care for severe NF2-SWN patients using surgical samples. Full article

Elm (Ulmus pumila), an ecologically and economically valuable tree, exhibits significant tolerance to abiotic stress. However, the physiological and molecular mechanisms underlying its stress adaptabilities are largely unknown. Here, two elm salt-tolerant cultivars (ST-Y and ST-Q) and two salt-sensitive cultivars (SS-J and SS-JX) were identified in the 13 elm accessions collected from Shandong province, China via phenotypic salt tolerance screening. The key salt tolerance mechanisms were explored in ST-Y and SS-J via transcriptomic (RNA-Seq) assays, and subsequently validated in ST-Q and SS-JX via quantitative real-time polymerase chain reaction (RT-qPCR) analyses. Under salt treatment, ST-Y maintained leaf intactness and enhanced activation of antioxidant enzymes with a reduction in reactive oxygen species (ROS) accumulation, while SS-J suffered leaf defoliation and showed compromised antioxidant capacity with higher ROS levels. KEGG pathway analysis revealed that ST-Y leaves exhibited a unique enrichment of differentially expressed genes (DEGs) in the “oxidative phosphorylation (OXPHOS)” pathway after salt stress treatment. Both ST-Y and SS-J exhibited significant enrichment in the “metabolic pathway”, but the number of DEGs in the “arachidonic acid (AA) metabolism” pathway was much higher in ST-Y than in SS-J. Further RT-qPCR analysis verified the accuracy of the RNA-Seq data and revealed that genes related to the “OXPHOS” pathway were significantly up-regulated in ST-Y and ST-Q, but down-regulated in SS-J and SS-JX. Our results suggested that OXPHOS efficiency is critical to antioxidant capacity in elm salt tolerance, suggesting new avenues for forest tree improvement for climate change. Full article

NAC (NAM, ATAF1/2 and CUC2) transcription factors constitute one of the largest plant-specific transcription factor families and play pivotal roles in plant growth, development, and responses to environmental stresses. Systematic characterization of NAC genes is essential for understanding regulatory networks underlying key agronomic and adaptive traits. As a conservation-priority woody species with distinctive biological and horticultural value, Sinojackia xylocarpa Hu lacks comprehensive knowledge of its NAC repertoire, and elucidating its NAC family will facilitate functional studies related to development and environmental adaptation. Based on whole-genome data of S. xylocarpa, we conducted a systematic survey and characterization of the NAC transcription factor family. In total, 115 SxyNAC genes encoding the conserved NAC domain were identified, and their loci were unevenly distributed across 12 chromosomes. Analyses of gene-duplication modes and collinearity indicated that whole-genome/segmental duplication events were the major driving force for the expansion of this family. Phylogenetic relationships, gene structures, and conserved motifs classified the SxyNAC members into 15 subfamilies, revealing a highly conserved N-terminal NAC domain and a markedly diversified C-terminal regulatory region with pronounced member- and lineage-specific differences. Promoter cis-element prediction showed extensive enrichment of light-responsive, phytohormone-responsive, and stress-related elements, suggesting that SxyNAC genes may participate in coordinated regulation of multiple environmental cues and endogenous hormone pathways. Transcriptome data from six fruit developmental stages, together with qRT-PCR validation of ten representative genes, demonstrated diverse temporal and tissue-specific expression patterns during fruit development and close associations with fruit growth regulation. Overall, our findings establish a framework for exploring the evolutionary trajectories and functional diversification of NAC genes in S. xylocarpa, and they offer a valuable resource for NAC-family research and conservation-focused functional genomics in other rare or threatened plant species. Full article

(1) Background: The “Bider” marking refers to the symmetrical black stripes distributed on the shoulder blades of Dun Mongolian horses, representing an ancestral trait of significant genetic value. However, the molecular mechanisms underlying its formation remain unclear. This study aims to elucidate the molecular basis of these markings by comparing transcriptomic differences in skin tissues from variously pigmented areas of Mongolian horses’ “Bider” patterns. (2) Methods: Using three Dun Mongolian horses as subjects, skin tissue samples were collected from their shoulders (dark-marked and light-marked areas), dorsal midline, and croup regions for transcriptome sequencing. Differentially expressed genes were identified based on sequencing data, followed by Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Key findings were validated through quantitative reverse transcription polymerase chain reaction (qRT-PCR). (3) Results: The sequencing yielded approximately 893 million high-quality clean reads, with an overall alignment rate exceeding 96%. A total of 140 to 775 differentially expressed genes were identified. GO enrichment analysis revealed that these genes were significantly enriched in biological processes related to pigment metabolism, skin and hair follicle development, signal transduction (including calcium and cyclic guanosine monophosphate (cGMP) signaling), and immune regulation. KEGG analysis further indicated that multiple pathways closely associated with pigment regulation, including the calcium signaling pathway, tyrosine metabolism, cyclic adenosine monophosphate (cAMP) signaling pathway, and melanoma pathway, were significantly enriched across different tissue comparison groups, suggesting their potential key roles in coat color phenotype formation. The reliability of the sequencing data was corroborated by the results of qRT-PCR validation. (4) Conclusions: This study conducted a transcriptome analysis of skin samples from various pigmented regions of the Dun Mongolian horse’s Bider marking, revealing that the formation of this marking is associated with the differential expression of numerous genes and is co-regulated by multiple pigment-related signaling pathways. Full article

Pinoresinol diglucoside (PDG), one of the major lignans isolated from E. ulmoides Oliver bark, has various pharmacological functions, including antihypertension and prevention of osteoporosis. However, the glycosyltransferase-encoding gene (GT) involved in regulating the glycosylation of pinoresinol to form PDG has not been reported in E. ulmoides. In this study, we screened and cloned the EuGT8 gene from E. ulmoides based on our transcriptome data. The expression pattern of the EuGT8 gene exhibited a strong positive correlation with dynamic changes in the PDG contents in three different organs of E. ulmoides. The expression level of the EuGT8 gene and PDG content were significantly decreased in asODN-EuGT8-treated shoot tips in comparison with the control group. Prokaryotic expression of the EuGT8 gene revealed that the purified EuGT8 protein could catalyze the conversion of pinoresinol into PDG. In addition, we performed transcriptional and metabolomic analyses to compare the differences between transgenic Arabidopsis and WT plants. A total of 1799 DEGs and 294 DEMs were identified in transgenic and WT plants. KEGG enrichment analysis showed that the DEGs were mainly enriched in phenylpropanoid biosynthesis, secondary metabolite biosynthesis, and starch/sucrose metabolism pathways. The DEMs were mainly enriched in ABC transporters, aminoacyl-tRNA biosynthesis, biosynthesis of amino acids, phenylpropanoid biosynthesis, and flavone and flavonol biosynthesis pathways. Correlation analysis between DEGs and DEMs identified a total of 231 DEGs associated with 38 DEMs, which were mainly distributed in multiple metabolic pathways. This finding provides both theoretical insights and genetic resources for breeding high-PDG E. ulmoides varieties, facilitating marker-assisted selection (MAS) and promoting sustainable E. ulmoides production in Guizhou. Full article

Background/Objectives: The significant negative correlation between protein and oil content in soybean seeds is a long-standing bottleneck for conventional breeding. Its root cause lies in insufficient understanding of related molecular regulatory processes. Methods: We selected the CSSL_R19, a chromosome segment substitution line, to thoroughly investigate the intrinsic effects of the substituted segment on the high seed storage protein (SSP) and low fatty acid (FA) phenotype. Transcriptomic, proteomic, and metabolomic analyses were performed on the recurrent parent and R19. Results: A total of 1821 differentially expressed genes (DEGs), 12 differentially expressed proteins (DEPs), and 10 differentially accumulated metabolites (DEMs) were detected. Subsequently, an integrative examination of the data demonstrated that 28 DEGs, 5 DEPs, and 4 DEMs participated in biological processes such as carbohydrate metabolism, lipid degradation, as well as protein synthesis and transport. Mechanistically, down-regulation of PGM reduces the carbon source supply for FA synthesis; up-regulation of LOX, LACS, ACX, and KAT promotes FA degradation. SRP, SAR1, and HSP70 are involved in the synthesis and transport of SSP. Crucially, qRT-PCR validation performed on all 28 core DEGs showed that their expression trends were highly consistent with the transcriptome data, confirming the reliability of the findings. Conclusions: In conclusion, we propose a potential regulatory network that enhances SSP accumulation and reduces FA content. Altogether, these findings advance our understanding of storage compound accumulation in soybeans and guide future breeding strategies. Full article

Meat quality serves as a pivotal determinant of consumer purchasing behavior and of the economic viability of the livestock industry; as such, research into its regulatory mechanisms is of critical significance for the development of modern agriculture. Traditional investigations into meat quality have predominantly centered on sensory and physicochemical assessments of ultimate phenotypic traits, thereby facing inherent limitations in systematically deciphering the intricate molecular regulatory networks underlying meat quality formation. By contrast, an integrated analysis of the transcriptome and metabolome effectively connects the cascade of “gene transcription—metabolic regulation—phenotypic determination,” which has emerged as a core methodological paradigm in contemporary research on the molecular mechanisms governing meat quality. This review systematically delineates the evolutionary trajectory and principal technological frameworks of meat quality evaluation systems, with a focused synthesis of recent advances achieved through combined transcriptomic and metabolomic analyses in the field of meat quality regulation. The scope of this review encompasses core transcriptional regulatory networks associated with meat quality attributes, pivotal metabolic pathways, signal transduction mechanisms, and protein degradation dynamics. Furthermore, the regulatory impacts exerted by genetic variation among breeds, nutritional modulation, rearing environments, and stress responses on meat quality characteristics are comprehensively elucidated. Integrative analysis reveals that combined transcriptome–metabolome approaches transcend the inherent limitations of single-omics investigations, systematically unraveling the hierarchical regulatory mechanisms governing fundamental meat quality traits, such as muscle fiber type differentiation, postmortem glycolytic progression, intramuscular fat deposition, and flavor compound accumulation. Such integrative strategies have facilitated the identification of functional genes and metabolic biomarkers with potential utility for the early prediction of meat quality outcomes. Concurrently, this review acknowledges persistent challenges confronting the field, including the absence of standardized protocols for multi-omics data integration, insufficient functional causal validation, and a discernible disconnect between research discoveries and practical industrial implementation. Building upon this comprehensive assessment, prospective directions for future multi-omics research in meat quality are proposed, accompanied by the formulation of an integrated end-to-end improvement framework spanning fundamental research, technological innovation, and industrial application. Collectively, this review provides a systematic theoretical foundation for the in-depth elucidation of mechanisms that determine meat quality and the precision-oriented regulation of quality-determining traits in livestock production practices, thereby offering substantial scientific guidance for quality improvement initiatives within the animal husbandry sector. Full article

Transcriptome profiling is a cornerstone of functional genomics, enabling the detailed characterization of gene expression in health and disease. Bulk RNA sequencing (bulk RNAseq) remains the most widely used approach in clinical and large-cohort studies due to its cost-effectiveness, robustness, and comprehensive transcriptome coverage. However, bulk RNAseq inherently averages gene expression signals across heterogeneous cell populations, thereby masking cellular diversity and obscuring rare cell types. In contrast, single-cell RNA sequencing (scRNAseq) enables a high-resolution analysis of cellular heterogeneity, allowing the identification of distinct cell types, transitional states, and developmental trajectories. Nevertheless, scRNAseq is associated with higher cost, limited scalability, increased technical noise, sparse expression matrices, and protocol-dependent biases introduced during tissue dissociation or nuclear isolation. In this review, we summarize the conceptual and methodological foundations of integrating bulk RNAseq and scRNAseq data, emphasizing their complementary strengths and limitations. We discuss how scRNAseq-derived cell-type atlases can serve as reference matrices for computational reconstruction (deconvolution) of bulk RNAseq profiles and examine key sources of technical and biological variability. Furthermore, we outline major integration strategies, including reference-based deconvolution, pseudobulk aggregation, and Bayesian joint modeling to provide an overview of widely used analytical tools and essential components of scRNAseq data processing workflows. Full article

Proteomics represents a fundamental layer for understanding the molecular complexity of solid tumors by quantifying protein abundance and capturing proteoforms and post-translational modifications undetected in genomics or transcriptomics analyses. As mass spectrometry-based technologies and public proteomics repositories have expanded, opportunities for large-scale data reuse have grown accordingly. Nevertheless, data availability has not been translated into straightforward reuse: differences in experimental design, acquisition strategies, quantification workflows and metadata quality still limit the reproducibility and cross-study comparability. In this review, proteomics data reuse is defined as the systematic reanalysis and integration of publicly available datasets to support precision oncology applications such as biomarker assessment and antibody–drug conjugate target prioritization. We discuss reuse as an end-to-end analytical process, focusing on data analysis workflows, harmonization strategies, and the impact of heterogeneous experimental and analytical choices on interoperability. The increased application of artificial intelligence in proteomics data integration and reuse is also addressed, highlighting its analytical potential while underscoring the risks of overinterpretation when biological context and data structure are not adequately considered. Using colorectal and prostate cancer as representative examples, we illustrate how proteomics data reuse can support biological discovery and translational research, while critically examining the factors that limit robustness and clinical relevance. Full article

Background: A major technical challenge in single-cell transcriptomics is the absence of an integrative analytic pipeline that can simultaneously leverage gene regulatory network (GRN) architecture, AI-assisted gene panel discovery, and functional relevance analyses to generate coherent biological insights. Existing approaches often treat these components independently, focusing on clusters, marker genes, or predictive features without integrating them into a mechanistically grounded framework. Consequently, comprehensive screening that links regulatory association, gene signature screening, and functional interpretation within single-cell datasets remains limited, underscoring the need for an integrated strategy. Methods: We developed an integrative bioinformatics pipeline based on Gene regulatory network–AI–Functional Analysis (GAFA), combining latent-space integration, unsupervised clustering, diffusion pseudotime analysis, lineage-resolved generalized additive modeling, GRN inference, and machine learning-based gene panel discovery. This framework enables systematic mapping of cell-state structure, reconstruction of differentiation and effector trajectories, and identification of transcriptional and regulatory features strongly associated with clinical outcomes. As a case study, we applied the pipeline to NK cell transcriptomes from six CML patients (two early relapse, two late relapse, two durable treatment-free remission—TFR; 15 samples) collected at TKI discontinuation and 6–12 months after therapy cessation. Results: We reanalyzed publicly available scRNA-seq data from a previously published CML cohort to evaluate NK-cell transcriptional programs associated with treatment-free remission and relapse. We resolved six transcriptionally distinct NK cell states spanning CD56^bright-like cytokine-responsive, early activated, terminally mature, cytotoxic, lymphoid trafficking, and HLA-DR⁺ immunoregulatory populations, each exhibiting outcome-specific compositional differences. Pseudotime analysis revealed two major NK cell lineages—a maturation trajectory and a cytotoxic effector trajectory. TFR samples displayed balanced occupancy of both lineages, whereas early relapse samples showed marked depletion of the maturation branch and preferential accumulation in cytotoxic end states. AI-guided feature selection and random forest modeling identified an 18-gene panel that distinguished NK cells from TFR and relapse samples in an exploratory manner. Among them, CST7, FCER1G, GNLY, GZMA, and HLA-C were conventional NK-associated genes, whereas ACTB, CYBA, IFITM2, IFITM3, LYZ, MALAT1, MT2A, MYOM2, NFKBIA, PIM1, S100A8, S100B, and TSC22D3 were novel. The GRN inference further uncovered outcome-specific regulatory modules, with RUNX3, EOMES, ELK4, and REL regulons enriched in TFR, whereas FOSL2 and MAF regulons were enriched in relapse, and their downstream targets linked to IFN-γ signaling, metabolic reprogramming, and immunoregulatory feedback circuits. Conclusions: This AI-enabled single-cell analysis demonstrates how NK cell state composition, differentiation trajectories, and regulatory network rewiring collectively shape TFR versus relapse following TKI discontinuation in CML. The integrative pipeline provides a modular framework that could be extended to additional datasets for data-driven biomarker discovery and mechanistic stratification, and highlights candidate transcriptional regulators and NK cell programs that may be leveraged to improve remission durability, pending validation in larger patient cohorts. Full article

Undifferentiated sarcomas (USs), including undifferentiated pleomorphic sarcoma (UPS), are aggressive mesenchymal malignancies with limited molecular biomarkers for prognostic assessment and therapeutic stratification. Expression-based markers may provide insight into tumor aggressiveness and clinical outcomes. Here, we performed integrative transcriptomic and spatial analyses to identify differentially expressed genes (DEGs). By comparing normal tissues with sarcoma tumors and sarcoma tumors with cell lines. Intersection and clustering analyses were conducted to define shared expression programs, which revealed a subset of DEGs enriched in epithelial-mesenchymal transition (EMT)-related pathways. CosMx spatial transcriptomics was applied to xenograft tumors derived from two UPS cell lines to resolve tumor-intrinsic signatures. The National Cancer Center Cohort samples were used for validation, and immunohistochemistry confirmed the expression in thirty US tissues. Spatial transcriptomic profiling identified mesenchymal tissue–driven gene expression programs in UPS xenografts. Across bulk RNA-seq and spatial data, epithelial membrane protein 3 (EMP3) consistently emerged as highly expressed in US tissues and cell lines. EMP3 is a robust mesenchymal-associated biomarker linked to EMT, tumor progression, and clinical outcomes in USs, supporting its potential utility as a prognostic indicator and therapeutic target. Full article

Corolla movement is a typical plant movement behavior that enables plants to optimize pollination and adapt to environmental changes. Nevertheless, its molecular mechanism remains poorly understood. In the present study, we conduct a comprehensive transcriptome analysis of Mirabilis jalapa (Nyctaginaceae) corolla at five stages (AG-EG) to elucidate the regulatory networks underlying movement. The results showed that the differentially expressed genes (DEGs) were mainly associated with cellular processes, catalytic activity, MAPK signaling, plant hormone signal transduction, and photosynthesis-related pathways, highlighting their involvement in corolla dynamics. Transcriptome profiling further demonstrated that auxin, ethylene, and abscisic acid signaling pathways were key hormonal regulators of corolla movement. Moreover, Ca²⁺ transport genes (CNGCs and CMLs) and respiratory burst oxidase homologs (RBOHs) were significantly enriched, indicating that Ca²⁺–ROS signaling oscillations also play an important role in driving differential cell expansion and turgor changes. Transcription factor analysis also revealed the upregulation of WRKY2, WRKY22, and WRKY33, suggesting that WRKYs act as the critical transcriptional regulators linking ROS–Ca²⁺ signals with downstream gene expression. The reliability of RNA-Seq data was confirmed by RT-qPCR, which showed high consistency with transcriptome profiles. These findings suggested that corolla movement in M. jalapa is carried through the integration of hormonal pathways, Ca²⁺–ROS signaling, and WRKY-mediated transcriptional regulation. This research provided novel insights into the molecular basis of plant movement and established a foundation for further study on floral dynamics and adaptive strategies in angiosperms. Full article

Drought severely limits maize production. Basic helix-loop-helix (bHLH) transcription factors act as key regulators of plant drought responses; however, the precise regulatory networks they coordinate in maize remain largely unclear. Here, we functionally characterized ZmbHLH81, a drought- and abscisic acid (ABA)-responsive bHLH transcription factor in maize. Subcellular localization confirmed that ZmbHLH81 is a nuclear protein. Overexpression of ZmbHLH81 in Arabidopsis enhanced drought tolerance, whereas CRISPR/Cas9-mediated targeted mutagenesis in maize significantly increased plant sensitivity to drought stress. Physiologically, these mutant lines exhibited accelerated water loss, delayed stomatal closure, compromised antioxidant enzyme activities and elevated malondialdehyde (MDA) accumulation under drought stress. DAP-seq analysis demonstrated that ZmbHLH81 specifically recognizes the conserved G-box motif (CACGTG). Furthermore, integrating DAP-seq and transcriptomic data successfully identified the key downstream targets governed by ZmbHLH81. Molecular assays confirmed that ZmbHLH81 directly targets and transactivates the core ABA signaling kinase gene ZmSnRK2.9 and stress-responsive transcription factor genes ZmNAC20 and ZmHDZ4. Taken together, ZmbHLH81 positively regulates maize drought tolerance by directly activating a specific regulatory module that orchestrates ABA-mediated stomatal closure and reactive oxygen species (ROS) scavenging, providing a promising genetic target for breeding climate-resilient crops. Full article

Background: Chlorophyll degradation is a characteristic sign of fruit ripening. However, the chlorophyll degradation pathway during pitaya fruit development remains unexplored. Methods and Results: Here, chlorophyll contents showed a downward trend across the five developmental stages of ‘Jindu No.1’ pitaya peels. Based on the pitaya genome data, twenty chlorophyll degradation genes were identified, including two NYCs, three CLHs, five SGRs, six PAOs, and four RCCRs, spread across eight pitaya chromosomes. In addition, their phylogenetic relationships, conserved motifs, and domains were analyzed using homologous genes from beet and Arabidopsis species. Transcriptomic data and RT-qPCR analyses of these genes suggested that three HuSGRs demonstrated a significant upward trend during pitaya peel maturation. Indeed, the HuSGR1 has the complete gene structure, including the chloroplast transit peptide, SGR domain, and variable C-terminal region. However, HuSGR2 and HuSGR3 contained the N- and C-terminal sequences, respectively, of HuSGR1. They were separated by a 690 bp distance on chromosome 8, forming a gene cluster. Overexpressed HuSGR2 or HuSGR3 alone resulted in a significant decrease in chlorophyll contents in tobacco leaves. Notably, a more obvious reduction of chlorophyll contents was observed when overexpressing them together. Conclusions: Our results show that HuSGR2 and HuSGR3 were involved in accelerating the chlorophyll degradation process, providing new insights into the molecular basis of color formation in pitaya peels. Full article