Grain length (GL) directly affects the yield and quality of rice. Very few cloned GL-related genes are applied in production because their yield-increasing effects are not obvious, and the overall regulatory networks underlying the associated processes remain poorly understood. DNA samples from two bulk DNA pools (L-pool and S-pool) and their parents (KJ01 and Huaye 3) were subjected to high-throughput sequencing. Using bulked segregant analysis (BSA), qGL3.5 was mapped to a 0.34-Mb “hotspot” region on chromosome 3 that contains 37 genes related to various traits. Then, qGL3.5 was mapped to the genomic interval between the flanking markers M2 and M3 using 2786 BC4F2 individuals. Because the region from B5 to B6 was not the associated region under BSA-seq analysis, qGL3.5 was narrowed down to the interval between B6 and M3, which spanned 24.0-kb. Of all 37 genes with non-synonymous single-nucleotide polymorphisms (SNPs) between KJ01 and Huaye 3 based on BSA-seq analysis, only one complete annotated gene, ORF18 (Gene ID: LOC_Os03g42790.1) was found. ORF18 encodes an IBR-RING zinc-finger-related protein, with one really interesting new gene (RING) and two in between ring finger (IBR) domains. The knockout of ORF18 derived from Huaye 3 using clustered, regularly interspaced, short palindromic repeat (CRISPR)/CRISPR-associated 9 (Cas9) editing technology increased the GL of the mutant by approximately 2.2 mm. The novel locus qGL3.5 negatively regulated GL by promoting elongation of the longitudinal cell of the grain outer glume. These results provide a new genetic resource for rice grain shape breeding and a starting point for the functional characterization of the wild rice GL gene.

Asynchrony widely exists in microgrids (MGs), such as non-identical sampling rates and communication delays, which challenges the MG control. This paper addresses the asynchronous distributed power control problem of hybrid microgrids, considering different kinds of asynchrony, such as non-identical sampling rates and random time delays. To this end, we first formulate the economic dispatch problem of MGs and devise a synchronous algorithm. Then, we analyze the impact of asynchrony and propose an asynchronous iteration algorithm based on the synchronous version. By introducing a random clock at each iteration, different types of asynchrony are fitted into a unified framework, where the asynchronous algorithm is converted into a fixed-point iteration problem with a nonexpansive operator, leading to a convergence proof. We further provide an upper bound estimation of the time delay of the communication. Moreover, the real-time implementation of the proposed algorithm in both AC and DC MGs is introduced. By measuring the frequency/voltage, the controller is simplified by reducing one order and adapt to the fast varying load demand. Finally, simulations on a benchmark MG and experiments are utilized to verify the effectiveness and advantages of the proposed algorithm. Index Terms-Asynchronous control, distributed control, multi-agent system, multi-microgrid networks, time delay. I. INTRODUCTION Multi-Microgrid systems or Microgrids (MGs) are clusters of distributed generators (DGs), energy storage systems and loads, which are generally categorized into three types: AC, DC and hybrid AC/DC MGs [1], [2]. A hybrid AC/DC MG has the advantage of reducing processes of multiple inverse conversions in the involved individual AC or DC grid [3]. Recently, the distributed power control for MGs has attracted more and more attention due to its fast response speed, privacy

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