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Genet Mol Res. 2007 Oct 5;6(4):866-89.

Abundance and diversity of resistance genes in the sugarcane transcriptome revealed by in silico analysis.

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1
Departamento de Genética, Laboratório de Genética e Biotecnologia Vegetal, Centro de Ciências Biológicas, Universidade Federal de Pernambuco, Recife, PE, Brasil.

Abstract

Resistance genes (R-genes) are responsible for the first interaction of the plant with pathogens being responsible for the activation (or not) of the defense response. Despite their importance and abundance, no tools for their automatic annotation are available yet. The present study analyzed R-genes in the sugarcane expressed sequence tags database which includes 26 libraries of different tissues and development stages comprising 237,954 expressed sequence tags. A new annotation routine was used in order to avoid redundancies and overestimation of R-gene number, common mistakes in previous evaluations. After in silico screening, 280 R-genes were identified, with 196 bearing the complete domains expected. Regarding the alignments, most of the sugarcane's clusters yielded best matches with proteins from Oryza sativa, probably due to the prevalence of sequences of this monocot in data banks. All R-gene classes were found except the subclass LRR-NBS-TIR (leucine-rich repeats, nucleotide-binding site, including Toll interleukin-1 receptors), with prevalence of the kinase (Pto-like) class. R-genes were expressed in all libraries, but flowers, transition root to shoot, and roots were the most representative, suggesting that in sugarcane the expression of R-genes in non-induced conditions prevails in these tissues. In leaves, only low level of expression was found for some gene classes, while others were completely absent. A high allelic diversity was found in all classes of R-genes, sometimes showing best alignments with dicotyledons, despite the great number of genes from rice, maize and other grasses deposited in data banks. The results and future possibilities regarding R-genes in sugarcane research and breeding are further discussed.

PMID:
18058709
[Indexed for MEDLINE]
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