Back

Novel Fusarium Wilt Resistance Genes Uncovered in the Wild Progenitors and Heirloom Cultivars of Strawberry

Pincot, D. D. A.; Feldmann, M. J.; Hardigan, M. A.; Vachev, M. V.; Henry, P. M.; Gordon, T. R.; Rodriguez, A.; Cobo, N.; Cole, G. S.; Coaker, G. L.; Knapp, S. J.

2021-12-09 plant biology
10.1101/2021.12.07.471687 bioRxiv
Show abstract

Fusarium wilt, a soilborne disease caused by Fusarium oxysporum f. sp. fragariae, poses a significant threat to strawberry (Fragaria x ananassa) production in many parts of the world. This pathogen causes wilting, collapse, and death in susceptible genotypes. We previously identified a dominant gene (FW1) on chromosome 2B that confers resistance to race 1 of the pathogen and hypothesized that gene-for-gene resistance to Fusarium wilt was widespread in strawberry. To explore this, a genetically diverse collection of heirloom and modern cultivars and wild octoploid ecotypes were screened for resistance to Fusarium wilt races 1 and 2. Here we show that resistance to both races is widespread and that resistance to race 1 is mediated by dominant genes (FW1, FW2, FW3, FW4, and FW5) on three non-homoeologous chromosomes (1A, 2B, and 6B). The resistance proteins encoded by these genes are not yet known; however, plausible candidates were identified that encode pattern recognition receptor or other proteins known to mediate gene-for-gene resistance in plants. High-throughput genotyping assays for SNPs in linkage disequilibrium with FW1-FW5 were developed to facilitate marker-assisted selection and accelerate the development of race 1 resistant cultivars. This study laid the foundation for identifying the genes encoded by FW1-FW5, in addition to exploring the genetics of resistance to race 2 and other races of the pathogen, as a precaution to averting a Fusarium wilt pandemic. Key MessageSeveral race-specific resistance genes were identified and rapidly deployed via marker-assisted selection to develop strawberry cultivars resistant to Fusarium wilt, a devastating soil-borne disease.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.