SummaryWe have developed a novel procedure for the rapid classi®cation and identi®cation of Arabidopsis mutants with altered cell wall architecture based on Fourier-Transform Infrared (FT-IR) microspectroscopy. FT-IR transmission spectra were sampled from native 4-day-old dark-grown hypocotyls of 46 mutants and the wild type treated with various drugs. The Mahalanobis distance between mutants, calculated from the spectral information after compression with the Discriminant Variables Selection procedure, was used for a hierarchical cluster analysis. Despite the completely unsupervised nature of the classi®cation procedure, we show that all mutants with cellulose defects appeared in the same cluster. In addition, mutant alleles of similar strength for several unrelated loci were also clustered, which demonstrates the sensitivity of the method to detect a wide array of cell wall defects. Comparing the cellulose-de®cient cluster with the cluster that contained wild-type controls led to the identi®cation of wave numbers that were diagnostic for altered cellulose content in the context of an intact cell wall. The results show that FT-IR spectra can be used to identify different classes of mutants and to characterize cell wall changes at a microscopic level in unknown mutants. This procedure signi®cantly accelerates the identi®cation and classi®cation of cell wall mutants, which makes cell wall polysaccharides more accessible to functional genomics approaches.
FT-IR microspectroscopy can be used to study the global composition and architecture of plant cell walls and it allows cell wall mutants to be identified. Our aim is to define a distance between cell wall mutants in the model species Arabidopsis based on FT-IR spectra. Since the number of data points that constitute a spectrum exceeds the number of samples analysed, it is essential to reduce first the dimension of the dataset. We present a comparison of several compression methods, including linear discriminant analysis using a non-canonical covariance matrix. The calculated distances were used to define clusters of mutants that appeared to be biologically meaningful.
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