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Cited by 595

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

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

Open access
Persson, Staffan, Wei, Hairong, Milne, Jennifer, Page, Grier P., Somerville, Christopher R.·2005·Proceedings of the National Academy of Sciences

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.

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Metadata

Authors
Persson, S., Wei, H., Milne, J., Page, G. P., & Somerville, C. R.
Venue
Proceedings of the National Academy of Sciences
Published
2005-06-02
Volume
102
Issue
24
Pages
8633-8638
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2074403192
Cited by
595
References
1
FWCI
44.74
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Identification of genes required for cellulose synthesis by regression analysis of public microarray data sets. https://app.cochat.ai/papers/10.1073/pnas.0503392102
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Persson, S., Wei, H., Milne, J., Page, G. P., & Somerville, C. R. (2005). Identification of genes required for cellulose synthesis by regression analysis of public microarray data sets. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.0503392102

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