Relationship between the genetic characteristics of Botrytis sp. airborne inoculum and meteorological parameters, seasons and the origin of air masses
Grey mould is a worldwide disease on many economically important crops. It is caused by two fungal species, Botrytis cinerea and B. pseudocinerea, which are mainly airborne dispersed. Although several studies have considered the abundance of airborne inoculum of B. cinerea in models forecasting the risk of grey mould epidemics, the genetic characteristics of this inoculum are poorly known. In the present study, airborne inoculum of B. cinerea and B. pseudocinerea was collected on 29 dates over a 2.5-year period on a site in south-eastern France. The 683 sampled isolates were genotyped with nine microsatellites markers, and 616 were identified as B. cinerea. The genetic structure of B. cinerea airborne inoculum was inferred with Bayesian assignment tests. Eight genetic clusters were identified. Cluster abundance showed temporal variation and was statistically linked to the season (P = 0.0009) and the origin of air masses (P < 0.0001). The proportion of isolates belonging to the species B. pseudocinerea was equal to 9.8 % on average, but it showed temporal variation; it tended to be higher in winter. This study is the first to provide information about the genetic characteristics of airborne inoculum of B. cinerea and B. pseudocinerea and to bring evidence of relationship with seasons, meteorological parameters and with the origin of air masses.
KeywordsSpores Grey mould Genetic clusters Diversity Botrytis
This study was partially supported by a grant of the INRA department of Plant Health and Environment. The authors gratefully acknowledge the National Oceanic and Atmospheric Administration (NOAA) Air Resources Laboratory (ARL) for the provision of the HYSPLIT transport and dispersion model and READY website (http://www.arl.noaa.gov/ready.php) used in this publication. The authors also thank M. Duffaud for her excellent technical support.
- Berrie, A. M., Harris, D. C., Xu, X.-M., & Burgess, C. M. (2002). A potential system for managing Botrytis and powdery mildew in main season strawberries. ISHS Acta Horticulturae (ISHS), 567, 647–649.Google Scholar
- Draxler, R. R. & Rolph, G. D. (2011). HYSPLIT (HYbrid Single-Particle Lagrangian Integrated Trajectory) Model access via NOAA ARL READY Website (http://ready.arl.noaa.gov/HYSPLIT.php). NOAA Air Resources Laboratory, Silver Spring, MD.
- Elad, Y., Williamson, B., Tudzynski, P., & Delen, N. (2004). Botrytis spp. and diseases they cause in agricultural systems—An introduction. In Y. Elad, B. Williamson, P. Tudzynski, & N. Delen (Eds.), Botrytis: biology, pathology and control (pp. 1–6). Dordrecht: Kluwer Academic Publishers.Google Scholar
- Excoffier, L., Laval, G., & Schneider, S. (2005). Arlequin ver. 3.0: An integrated software package for population genetics data analysis. Evolutionary Bioinformatics Online, 1, 47–50.Google Scholar
- Fournier, E., & Giraud, T. (2008). Sympatric genetic differentiation of a generalist pathogenic fungus, Botrytis cinerea, on two different host plants, grapevine and bramble. Journal of Evolutionary Biology, 21, 122–132.Google Scholar
- Leyronas, C., Duffaud, M., & Nicot, P. C. (2012). Compared efficiency of the isolation methods for Botrytis cinerea. Mycology: An International Journal on Fungal Biology, 3, 221–225.Google Scholar
- Leyronas, C., Bryone, F., Duffaud, M., Troulet, C., & Nicot, P. C. (2015a). Assessing host specialization of Botrytis cinerea on lettuce and tomato by genotypic and phenotypic characterization. Plant Pathology, 64, 119–127.Google Scholar
- Oliveira, M., Guerner-Moreira, J., Mesquita, M. M., & Abreu, I. (2009). Important phytopathogenic airborne fungal spores in a rural area: incidence of Botrytis cinerea and Oidium spp. AAEM, 16, 197–204.Google Scholar
- Rasiukevièiûtë, N., Valiuðkaitë, A., Survilienë-Radzevièë, E., & Supronienë, S. (2013). Investigation of Botrytis cinerea risk forecasting model of strawberry in Lithuania. Proceedings of the Latvian academy of sciences, 67(195), 198.Google Scholar
- Raymond, M., & Rousset, F. (1995). GENEPOP (version 1.2): Population genetics software for exact tests and ecumenicism. Journal of Heredity, 86, 248–249.Google Scholar
- Rolph, G.D. (2011) Real-time Environmental Applications and Display sYstem (READY). http://ready.arl.noaa.gov. NOAA Air Resources Laboratory, Silver Spring, MD.
- Shtienberg, D., & Elad, Y. (1997). Incorporation of weather forecasting in integrated, biological-chemical management of Botrytis cinerea. Phytopathology, 87(332), 340.Google Scholar
- Walker, A. S., Gladieux, P., Decognet, V., Fermaud, M., Confais, J., Roudet, J., et al. (2014). Population structure and temporal maintenance of the multihost fungal pathogen Botrytis cinerea: causes and implications for disease management. Environmental Microbiology,. doi: 10.1111/1462-2920.12563.Google Scholar