Determining the promoter motifs involved in regulating transcription, the first process of gene expression, is critical for synthetic promoter engineering. A gene’s promoter contains cis-regulatory elements, or motifs, which are binding sites for transcription factors (TFs) to initiate and drive transcription. Many bioinformatic tools have been developed for determining statistically overrepresented regions, representing sites of potential cis-regulatory elements, that are shared across groups of promoters. Combining the results produced by multiple bioinformatic tools can lead to improved detection accuracy of motifs conferring biological activity. In the present study, we compiled a set of 11 known soybean constitutive gene promoters under the assumption that some of the promoters are regulated by the same transcription factor(s). Seven bioinformatic tools capable of de novo motif discovery were used to determine potentially shared motifs within the promoters, which were then mapped back to the original promoter sequences. A total of 64 overlapping motif regions (OMRs) were commonly detected amongst the 11 constitutive promoters, and each OMR was cloned individually in front of the minimal CaMV 35S promoter driving GUSPlus reporter gene expression. Transient tobacco leaf agroinfiltration and subsequent quantitative GUS activity assays were used to determine each OMR’s ability to drive reporter gene expression. We found that 20 of the 64 bioinformatically-determined OMRs drove functional gene expression significantly higher than the basal levels conferred by the minimal 35S promoter. Of the 20 functional OMRs, 11 drove GUSPlus expression at levels from just twice that of the minimal 35S promoter up to nearly half of the full-length 35S promoter. We also transformed these 20 functional OMRs individually into Arabidopsis. While GUS staining is still ongoing, we identified a few OMRs which showed strong promoter strength in single-copied homozygous Arabidopsis seedlings. These functional OMRs are strong candidates for further characterization and can be used for crop improvement.
