A mutation in CsGME encoding GDP-mannose 3,5-epimerase results in little and wrinkled leaf in cucumber.

KEY MESSAGE: Map-based cloning revealed that a mutation in a highly conserved amino acid of the CsGME gene encoding GDP-mannose 3,5-epimerase, causes the phenotype of little and wrinkled leaves in cucumbers. Leaf size is a critical determinant of plant architecture in cucumbers, yet only a few genes associated with this trait have been mapped or cloned. Here, we identified and characterized a mutant with little and wrinkled leaves, named lwl-1. Genetic analysis revealed that the phenotype of the lwl-1 was controlled by a single recessive gene. Through map-based cloning, the lwl-1 locus was narrowed down to a 12.22-kb region exclusively containing one fully annotated gene CsGME (CsaV3_2G004170). CsGME encodes GDP-mannose 3,5-epimerase, which is involved in the synthesis of ascorbic acid (ASA) and one of the components of pectin, RG-II. Whole-length sequencing of the 12.22 kb DNA fragment revealed the presence of only a non-synonymous mutation located in the sixth exon of CsGME in lwl-1, resulting in an amino acid alteration from Pro363 to Leu363. This mutation was unique among 118 inbred lines from cucumber natural populations. CsGME expression significantly reduced in various organs of lwl-1, accompanied by a significant decrease in ASA and pectin content in leaves. Both CsGME and Csgme proteins were localized to the cytoplasm. The mutant phenotype exhibited partial recovery after the application of exogenous boric acid. Silencing CsGME in cucumber through VIGS confirmed its role as the causal gene for lwl-1. Transcriptome profiling revealed that CsGME greatly affected the expression of genes related to the cell division process and cell plate formation. This study represents the first report to characterize and clone the CsGME in cucumber, indicating its crucial role in regulating leaf size and development.

Sensor fault diagnosis and fault tolerant control for the multiple manipulator synchronized control system.

In this paper, a fault diagnosis (FD) and fault tolerant control (FTC) scheme is proposed for the leader-follower based multiple manipulator system with sensor fault under network communication topology. The learning observer is designed to obtain the fault information when the time-varying sensor fault occurs in follower manipulators. The synchronization error between the leader manipulator and the follower manipulator is defined based on the graph theory. The distributed multiple manipulator synchronization controller is designed for each follower manipulator which contains the value of fault estimation and RBF neural network based approximator. Correspondingly, the stability analysis of the error system is analyzed by the Lyapunov stability theorem. Finally, a simulation example is given to prove the effectiveness of the algorithm.

Fault Diagnosis and Minimum Rational Entropy Fault Tolerant Control of Stochastic Distribution Collaborative Systems.

In this paper, a fault-tolerant control scheme is presented for a class of stochastic distribution collaborative control systems, which are composed of three subsystems connected in series to complete the control target. The radial basis function neural network is used to approximate the output probability density function of the third subsystem, which is also the output of the entire system. When fault occurs in the first subsystem, an adaptive diagnostic observer is designed to estimate the value of fault. However, the first subsystem does not have the ability of self-recovery, minimum rational entropy controllers are designed in the latter subsystems to compensate the influence of the fault and minimize the entropy of the system output. A numerical simulation is given to verify the effectiveness of the proposed scheme.