Rice blast (Magnaporthe oryzae) is a devastating disease affecting rice production globally. The development of cultivars with host resistance has been proved to be the best strategy for disease management. Several rice-resistance genes (R) have been recognized which induce resistance to blast in rice but R gene-mediated mechanisms resulting in defense response still need to be elucidated. Here, mutant lines generated through CRISPR/Cas9 based targeted mutagenesis to investigate the role of Pi21 against blast resistance and 17 mutant plants were obtained in T0 generation with the mutation rate of 66% including 26% bi-allelic, 22% homozygous, 12% heterozygous, and 3% chimeric and 17 T-DNA-free lines in T1 generation. The homozygous mutant lines revealed enhanced resistance to blast without affecting the major agronomic traits. Furthermore, comparative proteome profiling was adopted to study the succeeding proteomic regulations, using iTRAQ-based proteomic analysis. We identified 372 DEPs, among them 149 up and 223 were down-regulated, respectively. GO analysis revealed that the proteins related to response to stimulus, photosynthesis, carbohydrate metabolic process, and small molecule metabolic process were up-regulated. The most of DEPs were involved in metabolic, ribosomal, secondary metabolites biosynthesis, and carbon metabolism pathways. 40S ribosomal protein S15 (P31674), 50S ribosomal protein L4, L5, L6 (Q10NM5, Q9ZST0, Q10L93), 30S ribosomal protein S5, S9 (Q6YU81, Q850W6, Q9XJ28), and succinate dehydrogenase (Q9S827) were hub-proteins. The expression level of genes related to defense mechanism, involved in signaling pathways of jasmonic acid (JA), salicylic acid (SA), and ethylene metabolisms were up-regulated in mutant line after the inoculation of the physiological races of M. oryzae as compared to WT. Our results revealed the fundamental value of genome editing and expand knowledge about fungal infection avoidance in rice.

Duo1, a major component of the Dam1 complex which has been found in two species of yeast (the budding yeast Saccharomyces cerevisae and the fission yeast Schizosaccharomyces pombe), is involved in mitosis-related chromosome segregation, while its relevance to pathogenicity in filamentous fungi remains unclear. This report elucidated this very fact in the case of the rice blast fungus Magnaporthe oryzae. A gene designated MoDUO1 that encodes a Duo1-like homolog (MoDuo1) was discovered in the M. oryzae genome. Two types of MoDUO1 mutants were obtained using genetic approaches of Agrobacterium-mediated gene disruption and homologous recombination. Both disruption and deletion of MoDUO1 can exert profound effects on the formation pattern of conidiophores and conidial morphology, such as abnormal nucleic numbers in conidia and delayed extension of infectious hyphae. Intriguingly, plant infection assays demonstrated that inactivation of MoDUO1 significantly attenuates the virulence in its natural host rice leaves, and functional complementation can restore it. Subcellular localization assays showed that MoDuo1 is mainly distributed in the cytosol of fungal cells. Proteomics-based investigation revealed that the expression of four mitosis-related proteins is shut down in the MoDUO1 mutant, suggesting that MoDuo1 may have a function in mitosis. In light of the fact that Duo1 orthologs are widespread in plant and human fungal pathogens, our finding may represent a common mechanism underlying fungal virulence. To the best of our knowledge, this is the first example of linking a Duo1-like homolog to the pathogenesis of a pathogenic fungus, which might provide clues to additional studies on the role of Dam1 complex in M. oryzae and its interaction with rice.

Ralstonia solanacearum strain Rs-T02 was originally isolated from a bacterial wilt of tomato plant in Nanning City of Guangxi Province, China. It represents the most prevalent phylotype in Guangxi. Here, we present the draft genome sequence of this strain, which comprises 5,225 genes and 5,976,011 nucleotides with an average G+C content of 66.79%. There are 968 different genes between this isolate and the previously reported genome sequence of Ralstonia solanacearum GMl l000 (race l, biovar 3, phylotype I), and the genome sequence information of this isolate may be useful for comparative genomic studies to determine the genetic diversity in this species.

In recent years, marine autonomous surface vessels (MASS) have grown into a ship research issue to increase the level of autonomy of ship behavior decision-making and control while sailing at sea. This paper focuses on the MASS motion control module design that aims to improve the accuracy and reliability of ship steering control systems. Nevertheless, the stochastic sea and wind environment have led to the extensive use of filters and state observers for estimating the ship-motion-related parameters, which are important for ship steering control systems. In particular, the ship maneuverability Nomoto index, which primarily determines the designed ship steering controller’s performance, cannot be observed directly due to the model errors and the external environment disturbance in the process of sailing. Hence, an adaptive robust ship steering controller based on a closed-loop gain shaping (CGS) scheme and an extended Kalman filter (EKF) on-line identification method is explored in this paper. To verify the effectiveness of the proposed steering controller design scheme, the motor vessel YUKUN was taken as the control plant and a series of simulation experiments were carried out. The results show the advantages of the dynamic response performance of the proposed steering controller compared with the classical PD and traditional CGS controllers. Therefore, the proposed adaptive CGS steering controller would be a good solution for MASS motion control module design.

The increasing congestion of maritime traffic leads to frequent maritime traffic accidents. Unmanned search and rescue equipment provides a guarantee for rapid rescue operations. In marine accidents, the waiting time is short and the rescue risk factor is high. Unmanned surface vessel (USV) can transport rescue equipment to the accident site in the first time and carry out searching and rescuing, which will greatly improve rescue efficiency. With the development of technology, USV can autonomously conduct area exploration to assist in the discovery of survivors. This paper proposes a complex area exploration of multiple unmanned surface vessels based on the Proximal Policy Optimization algorithm (PPO). The PPO algorithm is used to improve training efficiency, achieve 100% search coverage in complex water surface areas, and make searching and rescuing operations safe, simple and efficient. Experimental simulations show that the algorithm can realize 100% area exploration, have high search efficiency, and consumes less energy. This is a new intelligent ship application that can complete 100% exploration without human involvement.