Sequence Variants of the Phytophthora sojae RXLR Effector Avr3a/5 Are Differentially Recognized by Rps3a and Rps5 in Soybean

The perception of Phytophthora sojae avirulence (Avr) gene products by corresponding soybean resistance (Rps) gene products causes effector triggered immunity. Past studies have shown that the Avr3a and Avr5 genes of P. sojae are genetically linked, and the Avr3a gene encoding a secreted RXLR effector protein was recently identified. We now provide evidence that Avr3a and Avr5 are allelic. Genetic mapping data from F2 progeny indicates that Avr3a and Avr5 co-segregate, and haplotype analysis of P. sojae strain collections reveal sequence and transcriptional polymorphisms that are consistent with a single genetic locus encoding Avr3a/5. Transformation of P. sojae and transient expression in soybean were performed to test how Avr3a/5 alleles interact with soybean Rps3a and Rps5. Over-expression of Avr3a/5 in a P. sojae strain that is normally virulent on Rps3a and Rps5 results in avirulence to Rps3a and Rps5; whereas silencing of Avr3a/5 causes gain of virulence in a P. sojae strain that is normally avirulent on Rps3a and Rps5 soybean lines. Transient expression and co-bombardment with a reporter gene confirms that Avr3a/5 triggers cell death in Rps5 soybean leaves in an appropriate allele-specific manner. Sequence analysis of the Avr3a/5 gene identifies crucial residues in the effector domain that distinguish recognition by Rps3a and Rps5

Fault diagnosis of transformer based on random forest

Conference Name:2011 4th International Conference on Intelligent Computation Technology and Automation, ICICTA 2011. Conference Address: Shenzhen, Guangdong, China. Time:March 28, 2011 - March 29, 2011.Hunan University; Changsha University of Science and Technology; Hunan University of Science and Technology; Intelligence Computation Technology and Automation SocietyFault diagnosis of transformer in power system is studied in this paper. Considering the excellent performances of Random Forest (RF) in pattern recognition, we apply RF to construct a diagnosis model to predict the situation of transformer. The experiments of fault diagnosis for some real transformers show that RF obtains a better result in prediction accuracy and stability than traditional Back Propagation neural network does. In addition, the order of influence factors given by RF is helpful in fault diagnosis. ? 2011 IEEE

Genetic Diversity, Population Structure and Mating Type Distribution of <i>Setosphaeria turcica</i> on Corn in Midwestern China

Setosphaeria turcica is the causal agent of northern corn leaf blight (NCLB), which is a destructive foliar disease of corn around the world. To date, limited information is available on the genetic diversity, population structure, and mating type distribution of the pathogen in the mid-west of China. In this study, based on single nucleotide polymorphism (SNP) markers and mating type-specific primers, we characterized 117 S. turcica isolates collected from Henan, Hebei, Shanxi, and Shaanxi provinces in China. Based on the developed 33 SNP markers, all isolates can be categorized into two genetic groups. Each group consisted of isolates from all four provinces. The Nei’s gene diversity of four populations ranged from 0.328 to 0.419 with a mean of 0.391. The analysis of fixation index (Fst) and gene flow (Nm) suggested that low genetic differentiation and high gene flow existed among four geographic populations. The analysis of molecular variance (AMOVA) demonstrated that the principal molecular variance existed within populations (98%) rather than among populations (2%). The analysis of mating type loci revealed that two mating types (MAT1-1 and MAT1-2) were basically in equilibrium in all four populations. These findings advance our understanding of the genetic diversity, population structure and mating type distribution of S. turcica on corn in the mid-west of China and will aid in developing efficient strategies to control NCLB

Identification of a C2H2 Transcription Factor (PsCZF3) Associated with RxLR Effectors and Carbohydrate-Active Enzymes in Phytophthora sojae Based on WGCNA

Phytophthora sojae is a destructive soybean pathogen that orchestrates various secreted proteins (effectors) to modulate plant immunity and facilitate infection. Although a number of effectors have been identified and functionally studied in P. sojae, the way these molecules are regulated is marginally known. In this study, we performed a weighted gene correlation network analysis (WGCNA) based on digital RNA-seq, which enabled the identification of a transcription factor (PsCZF3) in P. sojae. This transcription factor is a C2H2-type zinc finger protein that regulates the transcription of 35 RxLR effectors during the early infection stage. Phylogenetic analysis revealed that PsCZF3 is a highly conserved protein across oomycetes, suggesting that this regulation mechanism may broadly exist in oomycete species. In addition, by building a subnetwork of PsCZF3 and correlated genes, we also found that PsCZF3 contributed to the transcriptional regulation of carbohydrate-active enzymes. Our findings suggest that the activation of PsCZF3 facilitates P. sojae infection by up-regulating RxLR effectors and carbohydrate-active enzymes

Effects of Microstructure, Mechanical and Physical Properties on Machinability of Graphite Cast Irons

Flake (FGI) and spheroidal (SGI) graphite cast irons are often used to produce workpieces, which often need to be machined. Machinability differences under various machining methods are the basis for choosing machining equipment and technology. In this work, FGI and SGI were used to produce tractor front brackets, and the machinability of both materials under turning and drilling processes was compared. The machinability (turning and drilling ability) has been evaluated in terms of machining load, chips shape, surface roughness, and tool temperature. The influence of materials microstructure and thermal conductivity on the machinability was analyzed. In the turning process, the cutting force and its standard deviation of the FGI were larger than the SGI due to the higher volume fraction of pearlite. The surface roughness was similar in both materials. In the drilling process, the even action of the friction and cutting force on the bit turned into similar drilling loads for both materials. Higher friction and lower thermal conductivity caused a higher bit temperature in SGI drilling compared to FGI. The chip breaking was worse in SGI drilling, where the longer chips scratched the internal surface of the holes, resulting in the higher surface roughness

MOESM1 of siRNAs regulate DNA methylation and interfere with gene and lncRNA expression in the heterozygous polyploid switchgrass

Additional file 1: Table S1. Information on bisulfite sequencing data in switchgrass

MOESM3 of siRNAs regulate DNA methylation and interfere with gene and lncRNA expression in the heterozygous polyploid switchgrass

Additional file 3: Figure S1. Sequencing depth and saturation analysis of in leaf (a) and root (b) tissues of switchgrass. The x-axis represents the sequencing depth. The y axis represents the percentage for cytosine with a sequencing depth over a specific depth of the whole genome cytosine

MOESM23 of siRNAs regulate DNA methylation and interfere with gene and lncRNA expression in the heterozygous polyploid switchgrass

Additional file 23: Table S12. Prediction of lncRNA families in switchgrass

MOESM20 of siRNAs regulate DNA methylation and interfere with gene and lncRNA expression in the heterozygous polyploid switchgrass

Additional file 20: Table S10. The correlation analysis between gene methylation and siRNA expression

MOESM24 of siRNAs regulate DNA methylation and interfere with gene and lncRNA expression in the heterozygous polyploid switchgrass

Additional file 24: Table S13. Annotation of targets of miR169 and miR171