Ethylene promotes ripening in fruits as well as the biosynthesis of anthocyanins in plants. However, the question of which ethylene response factors (ERFs) interact with the genes along the anthocyanin biosynthesis pathway is yet to be answered. Herein, we conduct an integrated analysis of transcriptomes and metabolome on fruits of two mulberry genotypes (‘Zijin’, ZJ, and ‘Dashi’, DS, with high and low anthocyanin abundance, respectively) at different post-flowering stages. In total, 1035 upregulated genes were identified in ZJ and DS, including MYBA in the MBW complex and anthocyanin related genes such as F3H. A KEGG analysis suggested that flavonoid biosynthesis and plant hormone signaling transduction pathways were significantly enriched in the upregulated gene list. In particular, among 103 ERF genes, the expression of ERF5 showed the most positive correlation with the anthocyanin change pattern across both genotypes and in the post-flowering stages, with a Pearson correlation coefficient (PCC) of 0.93. Electrophoresis mobility shift assay (EMSA) and luciferase assay suggested that ERF5 binds to the promoter regions of MYBA and F3H and transcriptionally activates their gene expression. We elucidated a potential mechanism by which ethylene enhances anthocyanin accumulation in mulberry fruits and highlighted the importance of the ERF5 gene in controlling the anthocyanin content in mulberry species. This knowledge could be used for engineering purposes in future mulberry breeding programs.

Identifying the early predictive biomarkers or compounds represents a pivotal task for guiding a targeted agricultural practice. Despite the various available tools, it remains challenging to define the ideal compound combination and thereby elaborate an effective predictive model fitting that. Hence, we employed a stepwise feature selection approach followed by a maximum relevance and minimum redundancy (MRMR) on the untargeted metabolism in four mulberry genotypes at different fruit developmental stages (FDSs). Thus, we revealed that 7 out of 226 differentially abundant metabolites (DAMs) explained up to 80% variance of anthocyanin based on linear regression model and stepwise feature selection approach accompanied by an MRMR across the genotypes over the FDSs. Among them, the phosphoenolpyruvate, d-mannose and shikimate show the top 3 attribution indexes to the accumulation of anthocyanin in the fruits of these genotypes across the four FDSs. The obtained results were further validated by assessing the regulatory genes expression levels and the targeted metabolism approach. Taken together, our findings provide valuable evidences on the fact that the anthocyanin biosynthesis is somehow involved in the coordination between the carbon metabolism and secondary metabolic pathway. Our report highlights as well the importance of using the feature selection approach for the predictive biomarker identification issued from the untargeted metabolomics data.