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Color is a crucial feature to consider when breeding and improving strains of Auricularia cornea. To uncover the mechanism of white strain formation in A. cornea, this study selected parental strains that were homozygous for the color trait and analyzed the genetic laws of A. cornea color through genetic population construction, such as test-cross, back-cross, and self-cross populations, and the statistical analysis of color trait segregation. Moreover, the study developed SSR molecular markers to construct a genetic linkage map, perform the fine mapping the color-controlling genetic locus, and verify candidate genes using yeast two-hybrid, transcriptome analysis, and different light treatments. The results of the study indicated that the color trait of A. cornea is controlled by two pairs of alleles. When both pairs of loci are dominant, the fruiting body is purple, while when both pairs of loci are recessive or one pair of loci is recessive, the fruiting body is white. Based on the linkage map, the study finely mapped the color locus within Contig9_29,619bp-53,463bp in the A. cornea genome and successfully predicted the color-controlling locus gene A18078 (AcveA), which belongs to the Velvet factor family protein and has a conserved structure domain of the VeA protein. It can form a dimer with the VelB protein to inhibit pigment synthesis in filamentous fungi. Lastly, the study validated the interaction between AcVeA and VelB (AcVelB) in A. cornea at the gene, protein, and phenotype levels, revealing the mechanism of inhibition of pigment synthesis in A. cornea. Under dark conditions, dimerization occurs, allowing it to enter the nucleus and inhibit pigment synthesis, leading to a lighter fruiting body color. However, under light conditions, the dimer content is low and cannot enter the nucleus to inhibit pigment synthesis. In summary, this study clarified the mechanism of white strain formation in A. cornea, which could aid in improving white strains of A. cornea and studying the genetic basis of color in other fungi. [ABSTRACT FROM AUTHOR]

Large-scale wind farms and wind farm clusters with many installed wind turbines are increasingly built around the world, and especially in offshore regions. The reliability and availability of these assets are critically important for cost-effective wind power generation. This requires effective solutions for online fault detection, diagnosis and fault accommodation to improve the overall reliability and availability of wind turbines and entire wind farms. To meet this requirement, this paper proposes a novel active fault-tolerant cooperative control (FTCC) scheme for large-scale wind farms and wind farm clusters (WFCs). The proposed scheme is based on a signal correction method at wind turbine level that is augmented with two innovative "control reallocation" mechanisms at wind farm and network operator levels. Applied to a WFC, this scheme detects, identifies and accommodates the effects of both mild and severe power-loss faults in wind turbines. Various simulation studies on an advanced WFC benchmark indicate the high efficiency and effectiveness of the proposed solutions. [ABSTRACT FROM AUTHOR]