Use of robust-long serial analysis of gene expression to identify novel fungal and plant genes involved in host-pathogen interactions.
Methods Mol Biol
; 354: 131-44, 2007.
Article
em En
| MEDLINE
| ID: mdl-17172751
ABSTRACT
Identification of important transcripts from fungal pathogens and host plants is indispensable for full understanding the molecular events occurring during fungal-plant interactions. Recently, we developed an improved LongSAGE method called robust-long serial analysis of gene expression (RL-SAGE) for deep transcriptome analysis of fungal and plant genomes. Using this method, we made 10 RL-SAGE libraries from two plant species (Oryza sativa and Zea maize) and one fungal pathogen (Magnaporthe grisea). Many of the transcripts identified from these libraries were novel in comparison with their corresponding EST collections. Bioinformatic tools and databases for analyzing the RL-SAGE data were developed. Our results demonstrate that RL-SAGE is an effective approach for large-scale identification of expressed genes in fungal and plant genomes.
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Base de dados:
MEDLINE
Assunto principal:
Rhizoctonia
/
Oryza
/
Regulação da Expressão Gênica
/
Genes de Plantas
/
Magnaporthe
/
Perfilação da Expressão Gênica
/
Genes Fúngicos
Idioma:
En
Ano de publicação:
2007
Tipo de documento:
Article