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Shoot apical meristem activity is controlled by complex regulatory networks in which components such as transcription factors, miRNAs, small peptides, hormones, enzymes and epigenetic marks all participate. Many key genes that determine the inherent characteristics of the shoot apical meristem have been identified through genetic approaches. Recent advances in genome-wide studies generating extensive transcriptomic and DNA-binding datasets have increased our understanding of the interactions within the regulatory networks that control the activity of the meristem, identifying new regulators and uncovering connections between previously unlinked network components. In this review, we focus on recent studies that illustrate the contribution of whole genome analyses to understand meristem function.
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http://dx.doi.org/10.1093/jxb/erw058 | DOI Listing |
Blood Adv
September 2025
BC Cancer, Vancouver, British Columbia, Canada.
Classical Hodgkin Lymphoma (CHL) is characterized by a complex tumor microenvironment (TME) that supports disease progression. While immune cell recruitment by Hodgkin and Reed-Sternberg (HRS) cells is well-documented, the role of non-malignant B cells in relapse remains unclear. Using single-cell RNA sequencing (scRNA-seq) on paired diagnostic and relapsed CHL samples, we identified distinct shifts in B-cell populations, particularly an enrichment of naïve B cells and a reduction of memory B cells in early-relapse compared to late-relapse and newly diagnosed CHL.
View Article and Find Full Text PDFPlant J
September 2025
College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, 310058, China.
Genome imbalance, resulting from varying the dosage of individual chromosomes (aneuploidy), has a more detrimental effect than changes in complete sets of chromosomes (haploidy/polyploidy). This imbalance is likely due to disruptions in stoichiometry and interactions among macromolecular assemblies. Previous research has shown that aneuploidy causes global modulation of protein-coding genes (PCGs), microRNAs, and transposable elements (TEs), affecting both the varied chromosome (cis-located) and unvaried genome regions (trans-located) across various taxa.
View Article and Find Full Text PDFAm J Reprod Immunol
September 2025
Department of Laboratory Animal Science, Kunming Medical University, Kunming, China.
Objective: To explore B cell infiltration-related genes in endometriosis (EM) and investigate their potential as diagnostic biomarkers.
Methods: Gene expression data from the GSE51981 dataset, containing 77 endometriosis and 34 control samples, were analyzed to detect differentially expressed genes (DEGs). The xCell algorithm was applied to estimate the infiltration levels of 64 immune and stromal cell types, focusing on B cells and naive B cells.
Sci Signal
September 2025
Department of Pathology, Microbiology and Immunology, New York Medical College, Valhalla, NY, USA.
Replication of HIV-1 requires the coordinated action of host and viral transcription factors, most critically the viral transactivator Tat and the host nuclear factor κB (NF-κB). This activity is disrupted in infected cells that are cultured with extracellular vesicles (EVs) present in human semen, suggesting that they contain factors that could inform the development of new therapeutics. Here, we explored the contents of semen-derived EVs (SEVs) from uninfected donors and individuals with HIV-1 and identified host proteins that interacted with HIV Tat and the NF-κB subunit p65.
View Article and Find Full Text PDFPLoS One
September 2025
Institute of Computational Science and Technology, Guangzhou University, Guangzhou, China.
MicroRNAs (miRNAs) are critical regulators of gene expression in cancer biology, yet their spatial dynamics within tumor microenvironments (TMEs) remain underexplored due to technical limitations in current spatial transcriptomics (ST) technologies. To address this gap, we present STmiR, a novel XGBoost-based framework for spatially resolved miRNA activity prediction. STmiR integrates bulk RNA-seq data (TCGA and CCLE) with spatial transcriptomics profiles to model nonlinear miRNA-mRNA interactions, achieving high predictive accuracy (Spearman's ρ > 0.
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