For the transcriptome, previously published single-gene expression profiling-based query and eFP functions in BnTIR were incorporated^[1]. In eFP, we redesigned the page to greatly improve the speed of user's searching and integrate more datasets including totally 931 libraries under 7 biotic and 31 abiotic stress conditions. The user can view the gene expression difference between the treatment and the control under multiple treatment conditions. Since these gene expression data are all from ZS11, an Asian semi-winter double-low accession, we collected the transcriptome data of 2,385 libraries from public databases to obtain more and more comprehensive gene expression data,. After processing, gene expression datasets are integrated into the metalibrary module, and users can easily query the expression levels of genes of interest in different tissues in all libraries.