Predicting and Clustering Plant CLE Genes with a New Method Developed Specifically for Short Amino Acid Sequences

Abstract

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.

The Sequenced Genomes of Non-Flowering Land Plants Reveal the (R)Evolutionary History of Peptide Signaling

“…In P. patens the R-type PpCLE peptide with its PpCLV receptor is involved 3D growth by determination of the orientation of stem cell division planes (Whitewoods et al, 2018). The function of the H-type CLE peptide recently detected in Anthoceros remains to be revealed (Li et al, 2020; Zhang et al, 2020b).…”

“…Queries with wildcards were generated based on consensus sequences from MUSCHLE alignments (Edgar, 2004) of mature peptides of Arabidopsis, A. trichopoda, P. glauba, M. polymorpha and S. moellendorffii, (DYxxxxPxPPLxxPxPF and PIPxSxPSKRHN, respectively) and used against protein libraries generated from gene-annotated Anthoceros genomes. Further options may be to test Machine Learning or Deep Learning methods that recently have been developed for peptide discovery (Plisson et al, 2020; Serrano, 2020; Zhang et al, 2020b).…”

“…Our focus, however, is different; it is to explore the evolutionary history of the group LRXI receptors known to interact with signaling peptides in angiosperms. One of the most plausible hypotheses of the land plant phylogeny proposes an early separation of both monophyletic bryophyte and vascular plant lineages (Figure 1) (2019; Li et al, 2020; Zhang et al, 2020b). We have therefore sampled putative LRXI receptors from A nthoceros hornworts, the liverwort M. polymorpha , the moss P. patens , and the lycophyte S. moellendorffii (hereafter collectively referred to as AMPS), which are extant species representing lineages that arose from ancient splits in land plant diversification before the emergence of angiosperms.…”