Journal of Applied Genetics最新文献

Multiple sclerosis (MS) is a central nervous system (CNS) disorder defined by inflammation, demyelination, and neuronal damage. Several independent studies have confirmed the prevalence of EBV infection in MS and the presence of elevated anti-EBV antibody titers in serum prior to and throughout the clinical period of MS. EBV stands out from other human-infecting viruses in that it can activate, infect, and clone the B cells and remain a latent infection inside them. The prevalence of EBV-positive B cell lymphoproliferative diseases in immunocompromised individuals demonstrates the critical significance of immune surveillance in managing EBV infection. It has also been postulated that a deficiency in EBV-specific CD8⁺ T cell regulation predisposes to MS by allowing EBV-infected autoreactive B cells and plasma cells to concentrate in the CNS. Thus, EBV-specific T-cell therapy might have the potential to eradicate B lymphocytes infected by EBV in the CNS, preventing disease development and leading to enhanced clinical outcomes. One of the effective approaches for treating MS patients is application of EBV-specific T cells. In this method, peripheral blood mononuclear cells (PBMCs) are isolated from patients and expanded with EBV-specific antigens, resulting in antiviral cytotoxic response. This review discusses the significance of EBV in the pathogenesis of MS, the impact of disease-modifying T-cell treatments targeting EBV, therapeutic implications to target EBV in MS pathogenesis, and several novel EBV-targeting gene therapies.

The Sieve Element Occlusion (SEO) proteins are subunits that assemble into structural filamentous phloem proteins, commonly referred to as P-proteins. These proteins in Arabidopsis play a structural role and contribute to plant defense by reversible sieve plate (SP) sealing. This mechanism could be particularly important also in Citrus trees affected by Huanglongbing (HLB), as SEO genes are highly induced in susceptible species C. sinensis upon Candidatus Liberibacter asiaticus (CLas) colonization. Given the limited information on this gene family in Citrus, we analyzed 27 SEO genes within the Rutaceae family, with a focus on genera closely related to Citrus, to better understand their potential roles in HLB tolerance. Genomic sequences revealed conserved exon-intron structures similar to Arabidopsis thaliana, while promoter regions contained a higher number of light-responsive Cis-elements, along with elements associated with growth, development, stress responses, and phloem-specific gene expression. Subcellular localization identified the cytoplasm as the primary site, with additional predictions for the plasma membrane and mitochondria. Phylogenetic analysis categorized SEO proteins into five subgroups, refining their classification in Citrus. Lately, protein interaction networks indicated strong connections with proteins involved in coordinated immune responses. These findings improve the understanding of SEO protein dynamics and evolutionary conservation, highlighting their role in phloem biology. Further investigation of these SEO genes and their promoters in the plant response to HLB could help identify specific targets for developing disease-tolerant Citrus varieties through genetic engineering.

Meeting the projected 70% rise in agricultural output by 2050 to sustain a global population of 9.6 billion poses a formidable challenge amid intensifying biotic and abiotic stresses. Traditional breeding methods, although foundational, are limited in their ability to improve complex polygenic traits such as yield, stress tolerance, and disease resistance. Genomic selection (GS) has emerged as a transformative approach that leverages genome-wide markers to predict breeding values with higher accuracy and efficiency. Unlike marker-assisted selection (MAS) and genome-wide association studies (GWAS), which emphasize major-effect loci, GS captures the cumulative contribution of numerous small-effect loci, enabling faster genetic gains for complex traits. This review outlines the conceptual framework, evolution, and integration of GS with cutting-edge technologies such as high-throughput genotyping, phenomics, multi-omics, and machine learning. It also discusses key achievements, implementation strategies, and the potential of GS to enhance selection accuracy, shorten breeding cycles, and develop climate-resilient, high-yielding cultivars. The integration of GS within modern breeding pipelines represents a paradigm shift toward sustainable crop improvement and global food security in an era of climatic uncertainty.

Non-small-cell lung cancer treatment relies greatly on immunotherapy, especially in individuals without targetable mutations enabling the use of molecularly targeted therapies. Negative immune checkpoint inhibitors significantly contribute to improving patients' survival and quality of life. Both programmed death ligand 1 expression on tumour cells and tumour mutational burden are used to predict the response to such treatment and qualify patients for therapy; however, in some cases, these biomarkers do not perform sufficiently well. Discovering new markers indicating resistance or response to immunotherapy would therefore enable clinicians to tailor the therapy course to the patient's benefit. This paper aims to describe the genetic and immunological background of immunotherapy courses and identify factors potentially related to clinical benefit or lack of response to immunotherapy, using next-generation sequencing of tumour tissue and flow cytometry analysis of lymphocyte subpopulations in the peripheral blood of non-small cell lung cancer patients in a preliminary study.

The aim of this study was to apply DArTseq technology to analyze T. spelta L. (spelt wheat) genotypes in order to eliminate duplicates in the gene bank and ensure the high quality and purity of the stored material. The research included the analysis of genetic similarity, the construction of dendrograms, and association mapping, which enabled the identification of specific molecular diagnostic markers for spelt wheat. Spelt is an ancient cereal species gaining popularity, especially in organic farming. It is characterized by natural resistance to biotic factors and tolerance to environmental stress. Spelt is a valuable material in plant resistance breeding aimed at developing varieties resistant to diseases and well adapted to unfavourable environmental conditions. In this study, molecular characterization of 27 spelt genotypes was carried out using high-throughput DArTseq technology, enabling simultaneous analysis of SilicoDArT and SNP markers. A total of 96,136 markers were identified, of which 16,712 met the quality criteria and were used for genetic similarity and association mapping. Based on similarity coefficients, a dendrogram was created, distinguishing four main genotype groups. Association mapping revealed over 2,600 markers significantly associated with the virulence level of the B. graminis f. sp. tritici pathogen. Particular attention was paid to SilicoDArT 7,492,586 and SNP 1,126,088 markers, showing significant associations with plant response to three of the five analyzed isolates. Chromosomal regions (1D, 3D, 5B, 6 A) associated with resistance were also identified, confirming the polygenic nature of this trait. Results indicate high genetic variability of the analyzed material and the usefulness of DArTseq technology in identifying markers for resistance breeding. The presented markers can be used in marker-assisted breeding programs, especially considering the growing interest in spelt as a cereal for organic farming. These findings provide a valuable basis for further improvement of spelt resistance and sustainable cereal breeding.

Plasmalemma vesicle-associated protein (PLVAP) plays a pivotal role in regulating endothelial permeability and maintaining blood-brain barrier (BBB) integrity. As a cellular receptor for the Japanese Encephalitis Virus (JEV) envelope protein, PLVAP significantly influences viral neuroinvasion and central nervous system entry. This study employed computational approaches to investigate the functional impact of non-synonymous single-nucleotide polymorphisms (nsSNPs) in the PLVAP gene and their potential effects on JEV-host interactions. We retrieved 11,883 SNPs from the NCBI dbSNP database and identified 403 unique nsSNPs for comprehensive analysis. Approximately 50% of these variants resulted in alterations to amino acid charge or polarity, indicating potential functional consequences. Stability analysis revealed 43 nsSNPs that significantly destabilized PLVAP structure (ΔΔG ≤ -1 kcal/mol), with several variants also affecting local protein disorder. Conservation analysis identified 29 deleterious nsSNPs, emphasizing their evolutionary importance and functional relevance. Five critical variants (R26H, I35T, E175G, V44G, and I39S) were prioritized based on their pronounced destabilizing effects on PLVAP structure and function. Molecular docking studies demonstrated that these mutations substantially altered PLVAP-JEV envelope protein binding interactions, potentially modifying viral entry efficiency and host susceptibility. These findings suggest clinical applications, including the use of PLVAP variants as biomarkers for risk stratification and guiding vaccination strategies in endemic regions. Moreover, insights into PLVAP-JEV interactions open avenues for therapeutic interventions, such as small-molecule inhibitors targeting viral entry. This computational framework may be extended to other flavivirus-host interactions, advancing antiviral drug discovery and personalized medicine approaches for JEV prevention.

Undifferentiated pleomorphic sarcoma (UPS) is a diagnosis of exclusion; given limited effective treatments and marked heterogeneity, there is a need to identify therapeutic targets, a task facilitated by next-generation sequencing (NGS) in clinical practice. We report 2 STS pts with the diagnosis of UPS, G3 - each treated in a clinical trial (NCT03651374) with UNRESARC protocol consisting of neoadjuvant chemotherapy (CHT), radiotherapy, and surgical resection. Biopsy samples from each patient were subjected to NGS with the TruSight™ Oncology 500 assay (Illumina) and analysed in PierianDX (commercial software). 5 pathogenic alterations were identified: Case A: CCNE1 (6 copies) and MYC (3 copies) amplifications; Case B: CCND1 (3 copies), EGFR (3 copies) and FGFR1 (4 copies) amplifications. Amplifications of cell-cycle associated (CCNE1, CCND1) and apoptosis-related (MYC) genes contribute to uncontrolled proliferation and resistance to apoptosis, while amplifications in receptor tyrosine kinases (EGFR and FGFR1) activate pathways (RAS/MAPK and PI3K/AKT), involved in tumour growth and metastasis. In both patients, a poor pathological response, early local recurrence (LRFS of 9 months in both patients) and progressive disease (PD) when treated with first-line palliative CHT (PFS of 5 months in A and 4 months in B) were noted. All tumours demonstrated a low tumour mutation burden (TMB) (1.6-3.9 mut/Mb) and no microsatellite instability (MSI), explaining no sensitivity to immune checkpoint inhibitors. NGS assays may enable accurate diagnosis and identify predictive biomarkers and novel therapeutic targets - of particular importance in poor-prognosis entities such as UPS. Our report is consistent with the literature classifying UPS as malignancy with a high frequency of CNAs and low TBM.

Background: Colorectal cancer (CRC) is a major global health concern with increasing incidence. Current treatments, though improved, require novel biomarkers for better diagnosis and management. Disulfidptosis, a recently characterized form of cell death, may play a critical role in CRC progression.

Methods: Utilizing summary-data-based Mendelian randomization (SMR), we identified RNH1 as a gene linked to CRC and disulfidptosis. The expression and intercellular communication of RNH1 in CRC were analyzed using single-cell RNA sequencing (scRNA-seq) and spatial transcriptome sequencing (stRNA-seq). A prognostic model was built using a Deep Learning Survival Neural Network (DeepSurv). Additionally, we performed RNA sequencing (RNA-seq) analysis to analyze the function of RNH1. Validation was performed through qPCR on CRC and normal tissue samples.

Results: RNH1 was identified as a gene linked to disulfidptosis and positively correlated with CRC risk. scRNA-seq analysis revealed that RNH1 + malignant cells showed distinct metabolic pathways and greater cell interactions. stRNA-seq analysis confirmed these interactions, especially with endothelial cells. DeepSurv analysis produced a prognostic model, showing different survival outcomes between high-risk and low-risk groups. RNA-seq analysis showed that the RNH1 + high expression group had higher immune cell abundance scores and tumor microenvironment scores, and RNH1 was positively correlated with most immune checkpoints. Drug sensitivity analysis suggested that CRC patients with high RNH1 expression were more sensitive to certain therapeutic agents. qPCR showed that the expression level of RNH1 in cancer tissues of CRC patients was significantly higher than that in normal tissues.

Conclusion: RNH1 acts as a biomarker for CRC, influencing tumor growth via disulfidptosis, tumor microenvironment alterations, and metabolic pathways. Its high expression correlates with immune escape. This study suggests RNH1 as a potential therapeutic target for CRC, warranting further exploration of its mechanistic roles and treatment potential.