## 1 Introduction
multiple sequence alignment with functionally characterized _trans_-PTs because of the fact that the predominant product chain length may change dramatically upon replacement of a single amino acid [10; 13]. Moreover, with the fast development of genome sequencing, the number of uncharacterized _trans_-PT sequences in the National Center for Biotechnology Information (NCBI) protein database has increased exponentially. Accordingly, in silico function prediction methods for _trans_-PTs are urgently needed, and several efforts have been made through different approaches. One method in a previous study tried to make predictions of chain length specificity using a ligand-docking method that evaluates the steric complementarity between different polyprenyl pyrophosphate products and the elongation tunnel [14]. The prediction accuracy of this method is around 60% which is higher than TrEMBL (an automated annotation method from UniProt Knowledgebase/Translated EMBL Nucleotide Sequence Data Library, with 45% prediction accuracy) [15]. However, the method using the structural modeling and docking algorithm requires huge computational resources and may hardly be applied in the annotation for such a large number of sequences from the _trans_-PTs family. In our previous work, by solving the crystal structures of three different _trans_-PTs from _Arabidopsis thaliana_, we revealed the product chain length determination mechanism of _trans_-SC-PTs and interpreted it as a \"three floors\" model [10]. Using this model, we successfully identified a novel GFPPS clade distributed in Brassicaceae plants which formed GFPPS-TPS gene clusters in their genomes [10]. These findings finally led to the discovery of a series of sesquterreponoids in plants [16; 17; 18; 19]. However, it is unclear whether the \"three floors\" model could also be applied to other species, and whether there are more GFPPSs beyond the Brassicaceae clade in plants is unknown. Thus, in this study, we designed an automatic algorithm named PTS-Pre (Prenyltransferases Prediction tool) for predicting the function of _trans_-PTs using the updated \"three floors\" model. This program gave 86% prediction accuracy for an experimental dataset including 141 _trans_-PTs from Archaea, Bacteria, and Eukarya and achieved the best prediction performance in Eukarya (95% prediction accuracy). The program was also tested by blind prediction using randomly selected _trans_-PTs sequences which were verified in subsequent in vitro enzymatic assays. All these results indicate that PTS-Pre could be extended to other species and could achieve not only high accuracy but also fast (several seconds per sequence) predictions. We further carried out a systematic search of 7870 _trans_-PTs sequences, spanning all domains of life, to mine the potential GFPPS genes. Finally, nine uncharacterized _trans_-PTs from Nestocaceae, Malvacae, Musaceae, and Ranunculaceae families were predicted and confirmed with GFPPS activities suggesting the evolutionary lineage specific for GFPPS. In summary, our work sheds light on the genome-wide functional prediction of _trans_-PTs and would be of further benefit to terpenoid metabolism pathway elucidation and production engineering.