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Bioinformatic Identification and Analysis of Hydroxyproline-rich Glycoproteins in Plants

Abstract Details

2017, Doctor of Philosophy (PhD), Ohio University, Molecular and Cellular Biology (Arts and Sciences).
Hydroxyproline-rich glycoproteins (HRGPs) are a superfamily of plant cell wall proteins that function in diverse aspects of plant growth and development. This superfamily consists of three members: arabinogalactan-proteins (AGPs), extensins (EXTs), and proline-rich proteins (PRPs). A bioinformatic software program, BIO OHIO 2.0, was developed to expedite the genome-wide identification and classification of HRGPs based on characteristic motifs and biased amino acid compositions. Principles of HRGPs identification and a stepwise tutorial for using this program with proteomic data was provided to facilitate and guide basic and applied research on HRGPs. Firstly, bioinformatic identification of EXTs was conducted in plants. A total of 758 EXTs were identified in 16 species, including 87 classical EXTs, 97 short EXTs, 61 leucine-rich repeat extensins (LRXs), 75 proline-rich extensin-like receptor kinases (PERKs), 54 formin-homolog EXTs (FHXs), 38 long chimeric EXTs, and 346 other chimeric EXTs. Classical EXTs were likely derived after the terrestrialization of plants; LRXs, PERKs, and FHXs were derived earlier than classical EXTs; monocots have fewer classical EXTs than eudicots; green algae have no classical EXTs but have a number of long chimeric EXTs that are absent in embryophytes. Phylogenetic analysis was conducted which shed light on the evolution of three EXT classes. In a second study, bioinformatic identification of HRGPs was conducted in poplar (Populus trichocarpa) which identified and classified 271 HRGPs including 162 AGPs, 60 EXTs, and 49 PRPs. Comparisons were made with Arabidopsis thaliana to facilitate the understanding of their respective structural and functional roles, including their possible applications in the areas plant biofuel and natural products for medicinal or industrial uses. In a third study, the bioinformatic identification and analysis of EXTs was conducted in Arabidopsis lyrata and Arabidopsis l, two close relatives of Arabidopsis thaliana. A total of 61 EXTs and 65 EXTs were identified in A. lyrata and A. halleri, respectively, compared with 69 EXTs in A. thaliana. Phylogenetic trees and cluster analysis revealed a number of potential orthologous and paralogous proteins among the three species. The identified EXTs and their homologous proteins provide insight into the evolution and functions of EXTs in related species within the same genus.
Allan Showalter (Advisor)
247 p.

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Citations

  • Liu, X. (2017). Bioinformatic Identification and Analysis of Hydroxyproline-rich Glycoproteins in Plants [Doctoral dissertation, Ohio University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou150037001088989

    APA Style (7th edition)

  • Liu, Xiao. Bioinformatic Identification and Analysis of Hydroxyproline-rich Glycoproteins in Plants. 2017. Ohio University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ohiou150037001088989.

    MLA Style (8th edition)

  • Liu, Xiao. "Bioinformatic Identification and Analysis of Hydroxyproline-rich Glycoproteins in Plants." Doctoral dissertation, Ohio University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou150037001088989

    Chicago Manual of Style (17th edition)