Genome-Wide Identification and Expression Profiling Suggest that Invertase Genes Function in Silique Development and the Response to Sclerotinia sclerotiorum in Brassica napus

Invertase(INV),a key enzyme in sucrose metabolism,irreversibly catalyzes the hydrolysis of sucrose to glucose and fructose,thus playing important roles in plant growth,development,and biotic and abiotic stress responses.In this study,we identified 27 members of the BnaINV family in Brassica napus.We constructed a phylogenetic tree of the family and predicted the gene structures,conserved motifs,cis-acting elements in promoters,physicochemical properties of encoded proteins,and chromosomal distribution of the BnaINVs.We also analyzed the expression of the BnaINVs in different tissues and developmental stages in the B.napus cultivar Zhongshuang 11 using qRT-PCR.In addition,we analyzed RNA-sequencing data to explore the expression patterns of the BnaINVs in four cultivars with different harvest indices and in plants inoculated with the pathogenic fungus Sclerotinia sclerotiorum.We used WGCNA(weighted coexpression network analysis)to uncover BnaINV regulatory networks.Finally,we explored the expression patterns of several BnaINV genes in cultivars with long(Zhongshuang 4)and short(Ningyou 12)siliques.Our results suggest that BnaINVs play important roles in the growth and development of rapeseed siliques and the defense response against pathogens.Our findings could facilitate the breeding of high-yielding B.napus cultivars with strong disease resistance.

Enhanced Butterfly Optimization Algorithm for Large-Scale Optimization Problems

To solve large-scale optimization problems,Fragrance coefficient and variant Particle Swarm local search Butterfly Optimization Algorithm(FPSBOA)is proposed.In the position update stage of Butterfly Optimization Algorithm(BOA),the fragrance coefficient is designed to balance the exploration and exploitation of BOA.The variant particle swarm local search strategy is proposed to improve the local search ability of the current optimal butterfly and prevent the algorithm from falling into local optimality.192000-dimensional functions and 201000-dimensional CEC 2010 large-scale functions are used to verify FPSBOA for complex large-scale optimization problems.The experimental results are statistically analyzed by Friedman test and Wilcoxon rank-sum test.All attained results demonstrated that FPSBOA can better solve more challenging scientific and industrial real-world problems with thousands of variables.Finally,four mechanical engineering problems and one ten-dimensional process synthesis and design problem are applied to FPSBOA,which shows FPSBOA has the feasibility and effectiveness in real-world application problems.