Polyploidy is a key factor influencing traits such as chloroplast number, stomatal size, and leaf yield. In mulberry (Morus spp.), triploids are well known to be superior over other ploidies in terms of yield traits. However, the cellular and molecular processes driving these benefits remain unclear. Transcriptome analysis is a powerful tool used to understand the molecular mechanisms underlying various plant traits, which requires coding skills and high-performance computers that hinder the utilization of publicly available huge RNA-Seq datasets. To address this issue, repository RNA-Seq datasets were analyzed using Galaxy to decode the genetic basis of the superior functionality of triploid mulberry. Leaf transcriptome datasets of diploids and triploids were retrieved and analyzed in Galaxy, where the genome of M. indica K2 was used as a reference. A variety of tools, including Trimmomatic, HISAT2, Stringtie, StringtieMerge, Featurecount, DEseq2, and WGCNA, were employed to identify differentially expressed genes, which were further analyzed using iDEP tools. For data interpretation, a PCA, volcano plot, heatmap, dendrogram, and bubble diagram were generated. The analysis revealed that triploid mulberry germplasm yielded a considerable number of up- and downregulated genes compared to diploids. Notably, the upregulated genes were associated with photosynthesis, chlorophyll biosynthesis, and carbon fixation, which in turn relay the molecular basis of the advantageous effect of triploids over diploids. These transcriptome studies indicate that polyploidization enhances photosynthetic capacity and other metabolic attributes. Therefore, this methodology helps to decipher the molecular basis of the advantageous effect of triploids over diploids without coding skills and high-performance computers.