Rhizoctonia crown and root rot (Rcrr) is one of the most common limiting factor for the sugar beet production. Efforts made towards breeding for resistance to infection with Rcrr has gained little achievements with traditional selection methods. In the present study, a number of 96 sugar beet individual plants, inoculated with a highly aggressive isolate of Rhizoctonia solani, were used to identify single nucleotide polymorphisms (SNPs) markers linked to disease resistance. 15,966 SNPs were discovered using diversity array technology (DArTseq) sequencing method. The data for rating disease and SNPs discovery were used for step-wise regression analysis and the results indicated that four SNPs markers explained 43.49% of the total variation of disease resistance. The surrounding sequence of a candidate SNP marker with the highest coefficient of determination (R2 = 17.58%) was used for primer design and further validation through high resolution melting (HRM) analysis. In HRM difference plot, the two reference rhizoctonia- resistant genotypes (Melinda-KWS and FC709) were clearly discriminated from susceptible individual plants derived from Marinella. The linked-SNP marker can be efficiently used for the detection of resistant Rcrr plants and marker-assisted breeding for resistant cultivar release
A candidate single nucleotide polymorphism (SNP) marker linked to resistance to infection with rhizoctonia in sugar beet
Bahram Heidari;Piergiorgio Stevanato;Chiara Broccanello;Giuseppe Concheri;
2018
Abstract
Rhizoctonia crown and root rot (Rcrr) is one of the most common limiting factor for the sugar beet production. Efforts made towards breeding for resistance to infection with Rcrr has gained little achievements with traditional selection methods. In the present study, a number of 96 sugar beet individual plants, inoculated with a highly aggressive isolate of Rhizoctonia solani, were used to identify single nucleotide polymorphisms (SNPs) markers linked to disease resistance. 15,966 SNPs were discovered using diversity array technology (DArTseq) sequencing method. The data for rating disease and SNPs discovery were used for step-wise regression analysis and the results indicated that four SNPs markers explained 43.49% of the total variation of disease resistance. The surrounding sequence of a candidate SNP marker with the highest coefficient of determination (R2 = 17.58%) was used for primer design and further validation through high resolution melting (HRM) analysis. In HRM difference plot, the two reference rhizoctonia- resistant genotypes (Melinda-KWS and FC709) were clearly discriminated from susceptible individual plants derived from Marinella. The linked-SNP marker can be efficiently used for the detection of resistant Rcrr plants and marker-assisted breeding for resistant cultivar release
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