Discovery of Genomic Regions Associated With Resistance to Late Wilt Disease Caused by Harpophora Maydis (Samra, Sabet and Hing) in Maize (Zea mays L.)

Late wilt disease (LWD) caused by Harpophora maydis (Samra, Sabet and Hing) is emerging as major production constraint in maize across the world. As a prelude to develop maize hybrids resistance to LWD, genetic basis of resistance was investigated. Two F2:3 mapping populations (derived from CV156670 × 414-33 (P-1) and CV156670 × CV143587 (P-2)) were challenged with LWD at two locations (Kallinayakanahalli and Muppadighatta) during 2017 post-rainy season. Wider range of LWD scores were observed at both locations in both the populations. LWD response was influenced by significant Genotype × location interaction. Six and 56 F2:3 progeny families showed resistance level better than resistant parent. 150 and 199 polymorphic SNP markers were used to genotype P-1 and P-2, respectively. Inclusive composite interval mapping was performed to detect significant QTL, QTL × QTL, QTL × Location interaction effects. Three major and four minor QTL controlling LWD resistance were detected on chromosome-1. Position and effect of the QTL varied with the location. Significant di-QTL interactions involving QTL (with significant and/or non-significant effects) located within and between all the ten chromosomes were detected. Five of the seven detected QTL in our study showed significant QTL × location interaction. Though two major QTL (q-lw-1.5 and q-lw-1.6) with lower Q×L interaction effects could be considered as stable, their phenotypic variance is not large enough to deploy them in MAS. Based on these results, strategies to breed maize for resistance to LWD are discussed.

Harpophora maydis (late wilt of maize).

H. maydis is a soilborne and apparently seedborne fungus, related to the root-infecting species in the genus Gaeumannomyces. It is known from only a few scattered countries, where it can cause significant losses, but may have been unobserved in others in which the primary host, maize [Zea mays], is grown. This fungus was reported recently from Portugal and Spain (Molinero-Ruiz et al., 2010). No dispersal by fungal propagules has been demonstrated, so that, other than in soil, its likely means of spread over borders would be in seed. Importation of the fungus with seed is considered to be the source in Hungary (Pécsi and Németh, 1998). Although research has been carried out on chemical and biological control methods, the development and use of resistant varieties is the most practical means of control. Regulation and testing of imported seed should prevent transport of the pathogen to new regions.

Evaluating Azoxystrobin Seed Coating Against Maize Late Wilt Disease Using a Sensitive qPCR-Based Method

Harpophora maydis, a phytopathogenic fungus, causes late wilt, a severe vascular maize disease characterized by relatively rapid wilting of maize plants near fertilization. The disease is currently controlled using resistant varieties. Here, we evaluated seed coating efficiency with azoxystrobin against H. maydis in a series of in vitro and in vivo trials. A real-time polymerase chain reaction (qPCR)-based method was developed and proved to be a sensitive, accurate tool for monitoring H. maydis DNA inside infected seeds, sprouts, and tissues of mature plants. In the early growth stages, the chemical coating drastically reduced the pathogen DNA prevalence in host tissues and minimized the suppressing effect on the plants’ biomass and development. In an infested field, the qPCR assay identified the pathogen 20 days after seeding, up to a month before conventional PCR detection. In the resistant fodder maize cultivar 32D99, which showed only minor disease symptoms, the seed coating blocked fungal progression and increased cob and plant weight by 39 and 60%, respectively. Nevertheless, this treatment was unable to protect a sensitive maize hybrid, cultivar Prelude, at the disease wilting breakout (60 days after sowing). These results encourage further examination of azoxystrobin and other fungicides in the field using the qPCR detection method to evaluate their efficiency.