Expressed sequence tags from the flower pathogen Claviceps purpurea

The ascomycete Claviceps purpurea (ergot) is a biotrophic flower pathogen of rye and other grasses. The deleterious toxic effects of infected rye seeds on humans and grazing animals have been known since the Middle Ages. To gain further insight into the molecular basis of this disease, we generated about 10 000 expressed sequence tags (ESTs)—about 25% originating from axenic fungal culture and about 75% from tissues collected 6–20 days after infection of rye spikes. The pattern of axenic vs. in planta gene expression was compared. About 200 putative plant genes were identified within the in planta library. A high percentage of these were predicted to function in plant defence against the ergot fungus and other pathogens, for example pathogenesis-related proteins. Potential fungal pathogenicity and virulence genes were found via comparison with the pathogen–host interaction database (PHI-base; http://www.phi-base.org ) and with genes known to be highly expressed in the haustoria of the bean rust fungus. Comparative analysis of Claviceps and two other fungal flower pathogens (necrotrophic Fusarium graminearum and biotrophic Ustilago maydis ) highlighted similarities and differences in their lifestyles, for example all three fungi have signalling components and cell wall-degrading enzymes in their arsenal. In summary, the analysis of axenic and in planta ESTs yielded a collection of candidate genes to be evaluated for functional roles in this plant–microbe interaction.     

Serial Analysis of Gene Expression (SAGE) of<Emphasis Type="Italic"> Magnaporthe grisea</Emphasis>: genes involved in appressorium formation

Treatment with cyclic AMP (cAMP) induces appressorium formation in the phytopathogenic fungus Magnaporthe grisea, the causative agent of rice blast disease. In a search for the M. grisea genes responsible for appressorium formation and host invasion, SAGE (Serial Analysis of Gene Expression) was carried out using mRNA isolated from fungal conidia germinating in the presence and absence of cAMP. From cAMP-treated conidia 5087 tags including 2889 unique tags were isolated, whereas untreated conidia yielded 2342 unique tags out of total of 3938. cAMP treatment resulted in up- and down-regulation of genes corresponding to 57 and 53 unique tags, respectively. Upon consultation of EST/cDNA databases, 22 tags with higher representation in cAMP-treated conidia were annotated with putative gene names. Furthermore, 28 tags corresponding to cAMP-induced genes could be annotated with the help of the recently published genome sequence of M. grisea. cAMP-induced genes identified by SAGE included many genes that have not been described so far, as well as a number of genes known to be involved in pathogenicity, e.g. MPG1, MAS1 and MAC1. RT-PCR of 13 randomly selected genes confirmed the SAGE results, verifying the fidelity of the SAGE data.Electronic Supplementary Material Supplementary material is available in the online version of this article at Communicated by E. Cerdá-Olmedo     

The pattern of gene expression in mouse Gr-1(+) myeloid progenitor cells

To understand the pattern of gene expression in mouse myeloid progenitor cells, we carried out a genome-wide analysis of gene expression in mouse bone marrow Gr-1(+) cells using SAGE and GLGI techniques. We identified 22,033 unique SAGE tags with quantitative information from 73,869 collected SAGE tags. Among these unique tags, 64% match known sequences, including many genes important for myeloid differentiation, and 36% have no matches to known sequences and are likely to represent novel genes. We compared the expression of mouse Gr-1(+) and human CD15(+) myeloid progenitor cells and showed that the pattern of gene expression of these two cell populations had some similarities. We also compared the expression of mouse Gr-1(+) myeloid progenitor cells with that of mouse brain tissue and found a highly tissue-specific manner of gene expression in these two samples. Our data provide a basis for studying altered gene expression in myeloid disorders using mouse models.     

Analysis of allelic differential expression in the human genome using allele-specific serial analysis of gene expression tags

Recent reports have demonstrated that a significant proportion of human genes display allelic differential expression (ADE). ADE is associated with phenotypic variability and may contribute to complex genetic diseases. Here, we present a computational analysis of ADE using allele-specific serial analysis of gene expression (SAGE) tags representing 1295 human genes. We identified 472 genes for which unequal representation (>3-fold) of allele-specific SAGE tags was observed in at least one SAGE library, suggesting the occurrence of ADE. For 235 out of these 472 genes, the difference in the expression level between both allele-specific SAGE tags was statistically significant (p < 0.05). Eleven candidate genes were then subjected to experimental validation and ADE was confirmed for 8 out of these 11 genes. Our results suggest that at least 25% of the human genes display ADE and that allele-specific SAGE tags can be efficiently used for the identification of such genes.