22
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Identification of genes required for cellulose synthesis by regression analysis of public microarray data sets.

      Proceedings of the National Academy of Sciences of the United States of America

      Arabidopsis, genetics, Arabidopsis Proteins, Cellulose, biosynthesis, metabolism, Computational Biology, methods, DNA Mutational Analysis, Databases, Genetic, Genes, Plant, Glucosyltransferases, Glycosyltransferases, Oligonucleotide Array Sequence Analysis, Phenotype, Regression Analysis

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Coexpression patterns of gene expression across many microarray data sets may reveal networks of genes involved in linked processes. To identify factors involved in cellulose biosynthesis, we used a regression method to analyze 408 publicly available Affymetrix Arabidopsis microarrays. Expression of genes previously implicated in cellulose synthesis, as well as several uncharacterized genes, was highly coregulated with expression of cellulose synthase (CESA) genes. Four candidate genes, which were coexpressed with CESA genes implicated in secondary cell wall synthesis, were investigated by mutant analysis. Two mutants exhibited irregular xylem phenotypes similar to those observed in mutants with defects in secondary cellulose synthesis and were designated irx8 and irx13. Thus, the general approach developed here is useful for identification of elements of multicomponent processes.

          Related collections

          Author and article information

          Journal
          15932943
          1142401
          10.1073/pnas.0503392102

          Comments

          Comment on this article