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Wang, S.-Y.

Publications and source records attributed to Wang, S.-Y..

2 recordsLinked to original sources

AhRLK1, a CLAVATA1-like leucine-rich repeat receptor-like kinase of peanut, confers increased resistance to bacterial wilt in tobacco

Bacterial wilt caused by Ralstonia solanacearum is a devastating disease that infects hundreds of plant species. Host factors involved in disease resistance and pathogenesis remain poorly characterized. An up regulated and leucine-rich repeat receptor-like kinase characterized as CLAVATA1 and named AhRLK1 was obtained by microarray analysis in response to R. solanacearum in peanut. AhRLK1 contained presumably, a signal peptide, ten leucine-rich repeat (LRR) domains and conserved motifs of intracellular kinases. For subcellular localization, the AhRLK1 protein was visualized only in the plasma membrane. After inoculation with R. solanacearum, AhRLK1 was constantly up regulated in the susceptible variety Xinhuixiaoli but showed little changed in the resistant cultivar Yueyou92. Different hormones, including salicylic acid, abscisic acid, methyl jasmonate, and ethephon, induced expression, but expression was completely down regulated under cold and drought treatments. Transient overexpression provoked a hypersensitive response (HR) in Nicotiana benthamiana following agro-infiltration. Furthermore, in transgenic tobacco with overexpression of the gene, the resistance to R. solanacearum increased significantly. By contrast, most representative defense-responsive genes in HR, SA, JA and ET signal pathways such as NtHIN1, NtPR2, NtLOX1, and NtACS6, among others, were considerably up regulated in the AhRLK1 transgenic lines. Additionally, the EDS1 and PAD4 in the R gene signal were also up regulated in transgenic plants, but the NDR1 and NPR1 genes were down regulated. Accordingly, we suggest that AhRLK1 increases the defense response to R. solanacearum via HR and hormone defense signalling, associated with the EDS1 pathway of R gene signalling. The results provide new understanding of CLV1 function and will contribute to genetic enhancement of peanut.

plant biology

Construction and analysis of mRNA, miRNA, lncRNA, and TF regulatory networks reveal the key genes in prostate cancer

Purpose: Prostate cancer (PCa) causes a common male urinary system malignant tumour, and the molecular mechanisms of PCa remain poorly understood. This study aims to investigate the underlying molecular mechanisms of PCa with bioinformatics.\n\nMethods: Original gene expression profiles were obtained from the GSE64318 and GSE46602 datasets in the Gene Expression Omnibus (GEO). We conducted differential screens of the expression of genes (DEGs) between two groups using the R software limma package. The interactions between the differentially expressed miRNAs, mRNAs and lncRNAs were predicted and merged with the target genes. Co-expression of the miRNAs, lncRNAs and mRNAs were selected to construct the mRNA-miRNA and-lncRNA interaction networks. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed for the DEGs. The protein-protein interaction (PPI) networks were constructed, and the transcription factors were annotated. The expression of hub genes in the TCGA datasets was verified to improve the reliability of our analysis.\n\nResults: The results demonstrated that 60 miRNAs, 1578 mRNAs and 61 lncRNAs were differentially expressed in PCa. The mRNA-miRNA-lncRNA networks were composed of 5 miRNA nodes, 13 lncRNA nodes, and 45 mRNA nodes. The DEGs were mainly enriched in the nuclei and cytoplasm and were involved in the regulation of transcription, related to sequence-specific DNA binding, and participated in the regulation of the PI3K-Akt signalling pathway. These pathways are related to cancer and focal adhesion signalling pathways. Furthermore, we found that 5 miRNAs, 6 lncRNAs, 6 mRNAs and 2 TFs play important regulatory roles in the interaction network. The expression levels of EGFR, VEGFA, PIK3R1, DLG4, TGFBR1 and KIT were significantly different between PCa and normal prostate tissue.\n\nConclusion: Based on the current study, large-scale effects of interrelated mRNAs, miRNAs, lncRNAs, and TFs were revealed and a model for predicting the mechanism of PCa was provided. This study provides new insight for the exploration of the molecular mechanisms of PCa and valuable clues for further research.

bioinformatics