Trilat. Project: Mango malformation: Epidemiology and simultaneous transcriptome analyses of host and fungal pathogen
Final Report Abstract
(1) Main objective of the project was and is to unravel the molecular basis of the socalled Mango malformation disease of the Mango tree Mangifera indica, caused by the ascomycete Fusarium mangiferae, which infects the tree in an as yet not completely known way and leads to the generation of symptoms like crippled inflorescences. The consequence, the prevention of flower maturation and fruit formation, has a severe impact on fruit yield, and therefore on consumption and export, and is presently a negative economic factor in Israel. (2) Whereas the fungus and its distribution in Israel are already known, the project added a map of mango orchards and tentative Fusarium mangiferae distribution on the West Bank. Phytopathology research additionally widened our insight into the influence of a series of environmental parameters on fungal growth and virulence. (3) Conidia of Fusarium mangiferae, isolated from infected panicles, served to reproducibly infect Mango trees. Airborne dispersal of inoculum was proven, and disease incidence and severity could be linked to the capacity of sporulation. A PCR diagnostic tool for the detection of the pathogen in planta is now available, based on specific primers complementary to rDNA sequences. (4) More than 23,000 tags were identified in in vitro grown Fusarium mycelium. However, most of the tags that were detected from the infected tissue were also detected in non-infected plants, suggesting contamination with common powdery mildew (Oidium mangiferae). (5) The transcriptomes (the entirety of transcript RNAs of the fungus and host separately as well as during their interaction in planta were characterized quantitatively by deepSuperSAGE, a technology based on the isolation of small sequence tags (each diagnostic for one specific messenger RNA), their sequencing by next-generation sequencing technologies in a massively parallel fashion and their annotation to existing databases. Even very low abundant transcripts, not visible on microarrays, were discovered from both fungus and plant. Some were identified as being involved in flower development of the plant (as e.g. gene AP1). (6) The transcriptome analyses unexpectedly revealed, that even control plants (not infected with Fusarium mangiferae) were in a reactive state very similar to plants infected by the mango malformation fungus. Many transcripts in control and experiment were identical, which finally lead to the conclusion of a potential superinfection. In fact, it was detected, that Oidium mangiferae, a relative of powdery mildew, was present in all plants, though no symptoms of infection were visible. Therefore, the deepSuperSAGE results were corrupted, since they did not represent the response of the host towards Fusarium alone, but a mixed response to Fusarium and Oidium. (7) As a perspective, the consortium will submit an extension proposal to continue unraveling the system Fusarium mangiferae/Mangifera indica in molecular detail, using genome sequencing to improve the annotation base and an advanced version of deepSuperSAGE to study the transcriptomes of pathogen and host plant separately and during their interaction.
Publications
- High-Throughput SuperSAGE for Digital Gene Expression Analysis of Multiple Samples Using Next Generation Sequencing. PLoS ONE 5, Issue 8, e12010 (2010)
Matsumura H., Yoshida K., Luo S., Kimura E., Fujibe T., Albertyn Z., Barrero R.A., Krüger D.H., Kahl G., Schroth G.P., Terauchi R.
- DeepSuperSAGE: Hightthroughput Transcriptome Sequencing with Now- and Next-Generation Sequencing Technologies. In: Tag-based Next Generation Sequencing, ed. Matthias Harbers and Günter Kahl, Wiley-Blackwell, December 2011
Matsumura H., Molina C, Krüger D.H., Terauchi R., Kahl, G.
- Tag-based Next Generation Sequencing. Wiley-Blackwell, 581 pages (2011)
Harbers M., G. Kahl
- The salt-responsive transcriptome of chickpea roots and nodules via deepSuperSAGE. BMC Plant Biology 11:31 (2011)
Molina C., Zaman-Allah M., Khan F., Fatnassi N., Horres R., Rotter B., Steinhauer D., Amenc L, Drevon J.J., Winter P., G. Kahl
