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Analysis of Plant Cell Walls Using High-Throughput Profiling Techniques with Multivariate Methods

Lookup NU author(s): Professor William WillatsORCiD

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Abstract

Plant cell walls are composed of a number of coextensive polysaccharide-rich networks (i.e., pectin, hemicellulose, protein). Polysaccharide-rich cell walls are important in a number of biological processes including fruit ripening, plant-pathogen interactions (e.g., pathogenic fungi), fermentations (e.g., winemaking), and tissue differentiation (e.g., secondary cell walls). Applying appropriate methods is necessary to assess biological roles as for example in putative plant gene functional characterization (e.g., experimental evaluation of transgenic plants). Obtaining datasets is relatively easy, using for example gas chromatography-mass spectrometry (GC-MS) methods for monosaccharide composition, Fourier transform infrared spectroscopy (FT-IR) and comprehensive microarray polymer profiling (CoMPP); however, analyzing the data requires implementing statistical tools for large-scale datasets. We have validated and implemented a range of multivariate data analysis methods on datasets from tobacco, grapevine, and wine polysaccharide studies. Here we present the workflow from processing samples to acquiring data to performing data analysis (particularly principal component analysis (PCA) and orthogonal projection to latent structure (OPLS) methods).

Publication metadata

Author(s): Moore JP, Gao Y, Zietsman AJJ, Fangel JU, Trygg J, Willats WGT, Vivier MA

Publication type: Article

Publication status: Published

Journal: The Plant Cell Wall

Year: 2020

Volume: 2149

Pages: 327-337

Online publication date: 03/07/2020

Acceptance date: 02/04/2016

Publisher: Springer

URL: https://doi.org/10.1007/978-1-0716-0621-6_18

DOI: 10.1007/978-1-0716-0621-6_18

PubMed id: 32617943

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