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In plants, nucleotide-binding site and leucine-rich repeat proteins (NLRs) play pivotal roles in effector-triggered immunity (ETI). However, the precise mechanisms underlying NLR-mediated disease resistance remain elusive. Previous studies have demonstrated that the NLR gene pair Pik-H4 confers resistance to rice blast disease by interacting with the transcription factor OsBIHD1, consequently leading to the upregulation of hormone pathways. In the present study, we identified an RNA recognition motif (RRM) protein, OsRRM2, which interacted with Pik1-H4 and Pik2-H4 in vesicles and chloroplasts. OsRRM2 exhibited a modest influence on Pik-H4-mediated rice blast resistance by upregulating resistance genes and genes associated with chloroplast immunity. Moreover, the RNA-binding sequence of OsRRM2 was elucidated using systematic evolution of ligands by exponential enrichment. Transcriptome analysis further indicated that OsRRM2 promoted RNA editing of the chloroplastic gene ndhB. Collectively, our findings uncovered a chloroplastic RRM protein that facilitated the translocation of the NLR gene pair and modulated chloroplast immunity, thereby bridging the gap between ETI and chloroplast immunity.

The intricate regulatory process governing rice immunity against the blast fungus Magnaporthe oryzae remains a central focus in plant–pathogen interactions. In this study, we investigated the important role of Osa-miR11117, an intergenic microRNA, in regulating rice defense mechanisms. Stem-loop qRT-PCR analysis showed that Osa-miR11117 is responsive to M. oryzae infection, and overexpression of Osa-miR11117 compromises blast resistance. Green fluorescent protein (GFP)-based reporter assay indicated OsPAO4 is one direct target of Osa-miR11117. Furthermore, qRT-PCR analysis showed that OsPAO4 reacts to M. oryzae infection and polyamine (PA) treatment. In addition, OsPAO4 regulates rice resistance to M. oryzae through the regulation of PA accumulation and the expression of the ethylene (ETH) signaling genes. Taken together, these results suggest that Osa-miR11117 is targeting OsPAO4 to regulate blast resistance by adjusting PA metabolism and ETH signaling pathways.

Objective To investigate the association between DNA methylation and the stable warfarin dose through genome-wide DNA methylation analysis and pyrosequencing assay. Method This study included 161 patients and genome-wide DNA methylation analysis was used to screen potential warfarin dose-associated CpGs through Illumina Infinium HumanMethylation 450 K BeadChip; then, the pyrosequencing assay was used to further validate the association between the stable warfarin dose and alterations in the methylation of the screened CpGs. GenomeStudio Software and R were used to analyze the differentially methylated CpGs. Results The methylation levels of CpGs surrounding the xenobiotic response element (XRE) within the CYP1A1 promoter, differed significantly between the different dose groups (P 0, P

Background We used bioinformatic analysis and quantitative reverse transcription polymerase chain reaction (RT-qPCR) assays to investigate the association between plasma microRNAs (miRNAs) and stable warfarin dosage in a Chinese Han population. Methods Bioinformatics analysis was used to screen out potential warfarin dose-associated miRNAs. Three plasma miRNAs were validated in 99 samples by RT-qPCR. Kruskal–Wallis test and multivariate logistic regression were used to compare differences in plasma miRNAs expression levels between three warfarin dosage groups. Results There were significant between-group differences among the three dose groups for hsa-miR-133b expression (p = 0.005), but we observed an “n-shaped” dose-dependent curve rather than a linear relationship. Expression levels of hsa-miR-24-3p (p = 0.475) and hsa-miR-1276 (p = 0.558) were not significantly different in the multivariate logistic regression. Conclusion miRNAs have received extensive attention as ideal biomarkers and possible therapeutic targets for various diseases. However, they are not yet widely used in precision medicine. Our results indicate that hsa-miR-133b may be a possible reference factor for the warfarin dosage algorithm. These findings emphasize the importance of a comprehensive evaluation of complex relationships in warfarin dose prediction models and provide new avenues for future pharmacogenomics studies.