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Phytophthora infestans causes the severe late blight disease of potato. During its infection process, P. infestans delivers hundreds of RXLR (Arg-x-Leu-Arg, x behalf of any one amino acid) effectors to manipulate processes in its hosts, creating a suitable environment for invasion and proliferation. Several effectors interact with host proteins to suppress host immunity and inhibit plant growth. However, little is known about how P. infestans regulates the host transcriptome. Here, we identified an RXLR effector, PITG_15718.2, which is upregulated and maintains a high expression level throughout the infection. Stable transgenic potato (Solanum tuberosum) lines expressing PITG_15718.2 show enhanced leaf colonization by P. infestans and reduced vegetative growth. We further investigated the transcriptional changes between three PITG_15718.2 transgenic lines and the wild type Désirée by using RNA sequencing (RNA-Seq). Compared with Désirée, 190 differentially expressed genes (DEGs) were identified, including 158 upregulated genes and 32 downregulated genes in PITG_15718.2 transgenic lines. Eight upregulated and nine downregulated DEGs were validated by real-time RT-PCR, which showed a high correlation with the expression level identified by RNA-Seq. These DEGs will help to explore the mechanism of PITG_15718.2-mediated immunity and growth inhibition in the future. [ABSTRACT FROM AUTHOR]

Based on density evolution analysis of the existing belief propagation (BP) algorithm, the Turbo Decoding Message Passing (TDMP) algorithm was analyzed from the perspective of density evolution and Gaussian approximation, and the theoretical analysis process of TDMP algorithm was given. When calculating the prior message of each layer of the TDMP algorithm, the check message of the previous iteration should be subtracted. Therefore, the result will not be convergent, if the TDMP algorithm is directly analyzed based on density evolution and Gaussian approximation. We researched the TDMP algorithm based on the symmetry conditions to obtain the convergent result. When using density evolution (DE) and Gaussian approximation to analyze the decoding convergence of the TDMP algorithm, we can provide a theoretical basis for proving the superiority of the algorithm. Then, based on the DE theory, we calculated the probability density function (PDF) of the check-to-variable information of TDMP and its simplified algorithm, and then gave it a calculation based on the process of the normalization factor. Simulation results show that the decoding convergence speed of the TDMP algorithm was faster and the iterations were smaller compared to the BP algorithm under the same conditions. [ABSTRACT FROM AUTHOR]