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Cytological Study of the Expression of Soybean Partial Resistance, Rps2, and Root resistance to Phytophthora sojae

Please use this identifier to cite or link to this item: http://hdl.handle.net/1811/6143

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Title: Cytological Study of the Expression of Soybean Partial Resistance, Rps2, and Root resistance to Phytophthora sojae
Creators: Mideros Mora, Santiago
Contributors: Dorrance, Anne E.
Keywords: Glycine max
host resistance
incomplete resistance
Issue Date: 2006-04-17
Series/Report no.: Plant Pathology. Graduate student poster competition, 2006
Abstract: Phytophthora root and stem rot caused by Phytophthora sojae, is a serious limitation to soybean production in the US. Partial resistance to P. sojae in soybeans is effective against all races of the pathogen and is a form of incomplete resistance where the plant reduces the rate of colonization of the pathogen. In addition to partial resistance other types of incomplete resistance have also been described. Rps2 (a single dominant gene) and root resistance (which is thought to be quantitatively inherited) are race specific and as partial resistance reduce the rate of pathogen colonization. In order to differentiate partial resistance from the other types of incomplete resistance that are race specific bright field and epifluorescent microscopy were used to study P. sojae inoculated root samples at three time points. Different responses to infection were observed: i) the resistance phenotype (Rps1a) contained the pathogen biotrophic growth from between 0 to 24 hours after inoculation (hai) in a hypersensitive response; ii) Rps2 and root resistance phenotypes, also stopped growth of the pathogen but this occurred in a delayed hypersensitive response between 24 and 48 hai and iii) partial resistance and the susceptible phenotypes allowed biotrophic colonization of P. sojae throughout the studied time course. The different types of incomplete resistance to P. sojae in soybean can be differentiated based on the number of dead cells and extent of colonization at 48 hai.
URI: http://hdl.handle.net/1811/6143
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