Background: The CLV3/ESR-RELATED (CLE) gene family encodes small secreted peptides (SSPs) and plays vital roles in plant growth and development by promoting cell-to-cell communication. The prediction and classification of CLE genes is challenging because of their low sequence similarity. Results: We developed a machine learning-aided method for predicting CLE genes by using a CLE motif-specific residual score matrix and a novel clustering method based on the Euclidean distance of 12 amino acid residues from the CLE motif in a site-weight dependent manner. In total, 2156 CLE candidates—including 627 novel candidates—were predicted from 69 plant species. The results from our CLE motif-based clustering are consistent with previous reports using the entire pre-propeptide. Characterization of CLE candidates provided systematic statistics on protein lengths, signal peptides, relative motif positions, amino acid compositions of different parts of the CLE precursor proteins, and decisive factors of CLE prediction. The approach taken here provides information on the evolution of the CLE gene family and provides evidence that the CLE and IDA/IDL genes share a common ancestor. Conclusions: Our new approach is applicable to SSPs or other proteins with short conserved domains and hence, provides a useful tool for gene prediction, classification and evolutionary analysis.

Background: The CLV3/ESR-RELATED (CLE) gene family encodes small secreted peptides (SSPs) and plays vital roles in plant growth and development by promoting cell-to-cell communication. The prediction and classification of CLE genes is challenging because of their low sequence similarity. Results: We developed a machine learning-aided method for predicting CLE genes by using a CLE motif-specific residual score matrix and a novel clustering method based on the Euclidean distance of 12 amino acid residues from the CLE motif in a site-weight dependent manner. In total, 2156 CLE candidates—including 627 novel candidates—were predicted from 69 plant species. The results from our CLE motif-based clustering are consistent with previous reports using the entire pre-propeptide. Characterization of CLE candidates provided systematic statistics on protein lengths, signal peptides, relative motif positions, amino acid compositions of different parts of the CLE precursor proteins, and decisive factors of CLE prediction. The approach taken here provides information on the evolution of the CLE gene family and provides evidence that the CLE and IDA/IDL genes share a common ancestor. Conclusions: Our new approach is applicable to SSPs or other proteins with short conserved domains and hence, provides a useful tool for gene prediction, classification and evolutionary analysis.

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As a member of the CLAVATA3 (CLV3)/EMBRYO SURROUNDING REGION (CLE) family, the dodecapeptide tracheary element differentiation inhibitory factor (TDIF) has a major impact on vascular development in plants. However, the influence of polymorphisms in the TDIF peptide motif on activity remains poorly understood. The model plant, Arabidopsis provides a fast and effective tool for assaying the activity of TDIF homologs. Five TDIF homologs from a group of 93 CLE genes in switchgrass (Panicum virgatum), a perennial biomass crop, named PvTDIF-like (PvTDIFL) genes were studied. The expression levels of PvTDIFL1, PvTDIFL3MR3, and PvTDIFL3MR2 were relatively high and all of them were expressed at the highest levels in the rachis of switchgrass. The precursor proteins for PvTDIFL1, PvTDIFL3MR3, and PvTDIFL3MR2 contained one, three, and two TDIFL motifs, respectively. Treatments with exogenous PvTDIFL peptides increased the number of stele cells in the hypocotyls of Arabidopsis seedlings, with the exception of PvTDIFL_4p. Heterologous expression of PvTDIFL1 in Arabidopsis strongly inhibited plant growth, increased cell division in the vascular tissue of the hypocotyl, and disrupted the cellular organization of the hypocotyl. Although heterologous expression of PvTDIFL3MR3 and PvTDIFL3MR2 also affected plant growth and vascular development, PvTDIFL activity was not enhanced by the multiple TDIFL motifs encoded by PvTDIFL3MR3 and PvTDIFL3MR2. These data indicate that in general, PvTDIFLs are functionally similar to Arabidopsis TDIF but that the processing and activities of the PvTDIFL peptides are more complex.

Protein phylogenetic analysis focuses on the evolutionary relationships among related protein sequences and can help researchers infer protein functions and developmental trajectories. With the advent of the big data era, the existing protein phylogenetic methods, including distance matrix and character-based methods, are facing challenges in both running time and application scope. Here, we developed an R package that we call CProtMEDIAS that is useful for protein phylogenetic analysis. In contrast to existing phylogenetic analysis methods, CProtMEDIAS utilizes dimensionality reduction algorithms to digitize multiple sequence alignments and quickly conduct phylogenetic analysis with a large number of amino acid sequences from similarly distant protein families and species. We used CProtMEDIAS to perform a dimensionality reduction, clustering, pseudotime, specific residue and evolutionary trajectory analysis of the plant homeobox superfamily. We found that CProtMEDIAS delivers consistent clustering, fast running and elegant presentation and thus provides powerful new tools and methods for protein clustering and evolutionary analysis.