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Title: QTL mapping and candidate gene discovery in potato for resistance to the Verticillium wilt pathogen Verticillium dahliae

Author
item KUMAR, ARUN - University Of Wisconsin
item Jansky, Shelley
item ENDELMAN, JEFFREY - University Of Wisconsin

Submitted to: American Phytopathological Society
Publication Type: Abstract Only
Publication Acceptance Date: 3/24/2017
Publication Date: 8/5/2017
Citation: Kumar, A., Jansky, S.H., Endelman, J., Halterman, D.A. 2017. QTL mapping and candidate gene discovery in potato for resistance to the Verticillium wilt pathogen Verticillium dahliae. American Phytopathological Society. Paper No. 262-P.

Interpretive Summary:

Technical Abstract: Verticillium wilt (VW) of potato (Solanum tuberosum), caused by fungal pathogens, Verticillium dahliae and V. albo atrum, is a disease of major significance throughout the potato growing regions in the world. In the past, researchers have focused on the Ve gene, which is a major dominant gene that confers resistance to VW in tomato. Using Ve sequence information from tomato, orthologues in potato were sequenced to develop functional molecular markers. However, the use of such markers was complicated by gene duplication. Also, the association between phenotypic and marker data was weak. These studies suggested that there might be other genetic determinants of VW resistance in potato. However, difficulties in disease phenotyping along with the complicated genetics of tetraploid potato cultivars have limited the progress in this direction and no major resistance gene from potato has been reported so far. We developed an F2 mapping population by selfing an F1 individual, which was derived from a cross between two homozygous diploid parents, S. tuberosum DM1-3 (susceptible to VW) and S. chacoense M6 (resistant to VW). This population was SNP genotyped and phenotyped using a rooted cutting protocol developed in our lab. Using R/qtl software, a QTL in chromosome 1 was identified, which explains 31% of phenotypic variation. Using SNP marker data, 22 genes were found in the QTL region, among which, based on bioinformatic analysis, two genes have been selected for further functional validation studies.