Bioinformatics prediction and evolution analysis of arabinogalactan proteins in the plant kingdom

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Abstract

Arabinogalactan proteins (AGPs) are a family of extracellular glycoproteins implicated in plant growth and development. With a rapid growth in the number of genomes sequenced in many plant species, the family members of AGPs can now be predicted to facilitate functional investigation. Building upon previous advances in identifying Arabidopsis AGPs, an integrated strategy of systematical AGP screening for “classical” and “chimeric” family members is proposed in this study. A Python script named Finding-AGP is compiled to find AGP-like sequences and filter AGP candidates under the given thresholds. The primary screening of classical AGPs, Lys-rich classical AGPs, AGP-extensin hybrids, and non-classical AGPs was performed using the existence of signal peptides as a necessary requirement, and BLAST searches were conducted mainly for fasciclin-like, phytocyanin-like and xylogen-like AGPs. Then glycomodule index and partial PAST (Pro, Ala, Ser, and Thr) percentage are adopted to identify AGP candidates. The integrated strategy successfully discovered AGP gene families in 47 plant species and the main results are summarized as follows: (i) AGPs are abundant in angiosperms and many “ancient” AGPs with Ser-Pro repeats are found in Chlamydomonas reinhardtii; (ii) Classical AGPs, AG-peptides, and Lys-rich classical AGPs first emerged in Physcomitrella patens, Selaginella moellendorffii, and Picea abies, respectively; (iii) Nine subfamilies of chimeric AGPs are introduced as newly identified chimeric subfamilies similar to fasciclin-like, phytocyanin-like, and xylogen-like AGPs; (iv) The length and amino acid composition of Lys-rich domains are largely variable, indicating an insertion/deletion model during evolution. Our findings provide not only a powerful means to identify AGP gene families but also probable explanations of AGPs in maintaining the plant cell wall and transducing extracellular signals into the cytoplasm.

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Ma, Y., Yan, C., Li, H., Wu, W., Liu, Y., Wang, Y., … Ma, H. (2017). Bioinformatics prediction and evolution analysis of arabinogalactan proteins in the plant kingdom. Frontiers in Plant Science, 8. https://doi.org/10.3389/fpls.2017.00066

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