Use of robust-long serial analysis of gene expression to identify novel fungal and plant genes involved in host-pathogen interactions.
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.
Gowda
Malali
M
Department of Plant Pathology, The Ohio State University, Columbus, USA.
Venu
R C
RC
Jia
Yulin
Y
Stahlberg
Eric
E
Pampanwar
Vishal
V
Soderlund
Carol
C
Wang
Guo-Liang
GL
D001483:Base Sequence; D015152:Blotting, Northern; D018076:DNA, Complementary / Q000235:genetics; D030541:Databases, Genetic; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation / Q000235:genetics*; D015723:Gene Library; D005800:Genes, Fungal; D017343:Genes, Plant; D006790:Host-Parasite Interactions; D020082:Magnaporthe / Q000235:genetics* / Q000472:pathogenicity / Q000502:physiology; D008969:Molecular Sequence Data; D025282:Mycelium; D012275:Oryza / Q000382:microbiology*; D018515:Plant Leaves / Q000382:microbiology; D012331:RNA, Fungal / Q000302:isolation & purification; D012333:RNA, Messenger / Q000302:isolation & purification; D012232:Rhizoctonia / Q000235:genetics* / Q000472:pathogenicity / Q000502:physiology; D012984:Software
D018076:DNA, Complementary; D012331:RNA, Fungal; D012333:RNA, Messenger