Resistance is a key determinant in interactions between hosts and their parasites. Understanding the amount and distribution of variation in this trait between strains can provide insights into (co)evolutionary processes and their potential to shape patterns of diversity in natural populations. Using controlled inoculation in experimental mass cultures, we investigated the quantitative variation in resistance to the bacterial parasite Holospora undulata across a worldwide collection of strains of its ciliate host Paramecium caudatum. We combined the observed variation with available information on the phylogeny and biogeography of the strains. We found substantial variation in resistance among strains, with upper-bound values of broad-sense heritability >0.5 (intraclass correlation coefficients). Strain estimates of resistance were repeatable between laboratories and ranged from total resistance to near-complete susceptibility. Early (1 week post inoculation) measurements provided higher estimates of resistance heritability than did later measurements (2–3 weeks), possibly due to diverging epidemiological dynamics in replicate cultures of the same strains. Genetic distance (based on a neutral marker) was positively correlated with the difference in resistance phenotype between strains (r = 0.45), essentially reflecting differences between highly divergent clades (haplogroups) within the host species. Haplogroup A strains, mostly European, were less resistant to the parasite (49% infection prevalence) than non-European haplogroup B strains (28%). At a smaller geographical scale (within Europe), strains that are geographically closer to the parasite origin (Southern Germany) were more susceptible to infection than those from further away. These patterns are consistent with a picture of local parasite adaptation. Our study demonstrates ample natural variation in resistance on which selection can act and hints at symbiont adaptation producing signatures in geographic and lineage-specific patterns of resistance in this model system. © Copyright © 2020 Weiler, Zilio, Zeballos, Nørgaard, Conce Alberto, Krenek, Kaltz and Bright.