A novel resistance locus from an unexploited East Asian Vitis coignetiae confers resistance to grapevine downy mildew

A novel locus for grapevine resistance to Plasmopara viticola (Rpv32) was identified on chromosome 14 in the East Asian wild species Vitis coignetiae and compared with other resistances. One of the most devastating diseases in viticulture worldwide is downy mildew, caused by an obligate biotrophic oomycete, Plasmopara viticola. While fungicides are widely used to prevent yield losses, their environmental impact and decreasing social acceptance highlight the need for sustainable alternatives. Breeding and cultivating resistant grapevine varieties is an effective option for durable disease control, but requires the identification of novel genetic resistances. To minimize disease impact and pathogen adaptation, diverse genetic resistance mechanisms are essential. We conducted a QTL analysis to identify a new resistance locus in the unexploited East Asian wild species Vitis coignetiae. A biparental F1 population derived from 'Morio Muskat' × COxGT2 (V. coignetiae × 'Gewürztraminer') was evaluated using artificial infection assays over three consecutive years and genotyped with rhAmpSeq markers. A high-resolution genetic map comprising 639 markers spanned 1147.36 cM across 19 linkage groups, covering 96% of the physical genome. QTL mapping identified a highly significant and stable QTL on chromosome 14 in three years that explains up to 28.16% of the phenotypic variation. This novel resistance locus was named Rpv32. Microscopic analysis revealed restricted intracellular pathogen development in the resistant parent, and pathogen proliferation assays confirmed the strength of Rpv32-mediated resistance. An additional QTL for leaf hair density was detected on chromosome 5, but this trait does not appear to play a role in downy mildew resistance in this population. Markers tightly linked to Rpv32 have been developed, enabling the rapid utilization of this novel resistance in breeding through introgression and pyramiding using marker-assisted selection.