Sheath blight of rice is a destructive disease that could be calamitous to rice cultivation. The significant objective of this study is to contemplate the proteomic analysis of the high virulent and less virulent isolate of using a quantitative LC-MS/MS-based proteomic approach to identify the differentially expressed proteins promoting higher virulence. Across several rice-growing regions in Odisha, Eastern India, 58 isolates were obtained. All the isolates varied in their pathogenicity. The isolate RS15 was found to be the most virulent and RS22 was identified as the least virulent. The PCR amplification confirmed that the RS15 and RS22 belonged to the subgroup of AG1-IA with a specific primer. The proteomic information generated has been deposited in the PRIDE database with PXD023430. The virulent isolate consisted of 48 differentially abundant proteins, out of which 27 proteins had higher abundance, while 21 proteins had lower abundance. The analyzed proteins acquired functionality in fungal development, sporulation, morphology, pathogenicity, detoxification, antifungal activity, essential metabolism and transcriptional activities, protein biosynthesis, glycolysis, phosphorylation and catalytic activities in fungi. A Quantitative Real-Time PCR (qRT-PCR) was used to validate changes in differentially expressed proteins at the mRNA level for selected genes. The abundances of proteins and transcripts were positively correlated. This study provides the role of the proteome in the pathogenicity of AG1-IA in rice and underpins the mechanism behind the pathogen's virulence in causing sheath blight disease.
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http://dx.doi.org/10.3390/jof8040370 | DOI Listing |
RNA Biol
December 2025
Biorepository and Omics Research Group, Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Pakistan.
This study aimed to identify differentially expressed non-coding RNAs (ncRNAs) associated with preterm birth (PTB) and determine biological pathways being influenced in the context of PTB. We processed cell-free RNA sequencing data and identified seventeen differentially expressed (DE) ncRNAs that could be involved in the onset of PTB. Per the validation via customized RT-qPCR, the recorded variations in expressions of eleven ncRNAs were concordant with the analyses.
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January 2025
Graduate School of Qinghai University, Xining, 810000, Qinghai Province, People's Republic of China.
The occurrence and progression of breast cancer (BCa) are complex processes involving multiple factors and multiple steps. The tumor microenvironment (TME) plays an important role in this process, but the functions of immune components and stromal components in the TME require further elucidation. In this study, we obtained the RNA-seq data of 1086 patients from The Cancer Genome Atlas (TCGA) database.
View Article and Find Full Text PDFSleep Breath
January 2025
Department of Respiratory and Critical Care Medicine, Medical School of Nantong University, Nantong Key Laboratory of Respiratory Medicine, Affiliated Hospital of Nantong University, Nantong, 226001, China.
Background: The pathophysiology of obstructive sleep apnea (OSA) and diabetes mellitus (DM) is still unknown, despite clinical reports linking the two conditions. After investigating potential roles for DM-related genes in the pathophysiology of OSA, our goal is to investigate the molecular significance of the condition. Machine learning is a useful approach to understanding complex gene expression data to find biomarkers for the diagnosis of OSA.
View Article and Find Full Text PDFDiscov Oncol
January 2025
Department of Medical Imaging, Shenzhen Longhua District Key Laboratory of Neuroimaging, Shenzhen Longhua District Central Hospital, Shenzhen, 518110, China.
Background: Glioblastoma multiforme (GBM) is a highly aggressive brain cancer with poor prognosis and limited treatment options. Despite advances in understanding its molecular mechanisms, effective therapeutic strategies remain elusive due to the tumor's genetic complexity and heterogeneity.
Methods: This study employed a comprehensive analysis approach integrating 113 machine learning algorithms with Mendelian Randomization (MR) analysis to investigate the molecular underpinnings of GBM.
Dev Psychol
January 2025
Department of Psychology, New York University.
Adults hold a broad range of beliefs about intellectual ability. Key examples include beliefs about its malleability, its distribution in the population, whether high levels of it ("brilliance") are necessary for success, its origins, and its responsiveness to intervention. Here, we examined the structure and motivational significance of this network of consequential beliefs in a sample of elementary school-age children (5- to 11-year-olds, = 231; 116 girls, 112 boys, three gender nonbinary children; predominantly White and Asian children from relatively high-income backgrounds).
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