Effective disease management depends on timely and accurate diagnosis to guide control measures. The capacity to distinguish between individuals in a pathogen population with specific properties such as fungicide resistance, toxin production and virulence profiles is often essential to inform disease management approaches. The genomics revolution has led to technologies that can rapidly produce high-resolution genotypic information to define individual variants of a pathogen species. However, their application to complex fungal pathogens has remained limited due to the frequent inability to culture these pathogens in the absence of their host and their large genome sizes. Here, we describe the development of Mobile And Real-time PLant disEase (MARPLE) diagnostics, a portable, genomics-based, point-of-care approach specifically tailored to identify individual strains of complex fungal plant pathogens. We used targeted sequencing to overcome limitations associated with the size of fungal genomes and their often obligately biotrophic nature. Focusing on the wheat yellow rust pathogen, Puccinia striiformis f.sp. tritici (Pst), we demonstrate that our approach can be used to rapidly define individual strains, assign strains to distinct genetic lineages that have been shown to correlate tightly with their virulence profiles and monitor genes of importance. MARPLE diagnostics enables rapid identification of individual pathogen strains and has the potential to monitor those with specific properties such as fungicide resistance directly from field-collected infected plant tissue in situ. Generating results within 48 h of field sampling, this new strategy has far-reaching implications for tracking plant health threats.

Frequent emergence of new variants in the Puccinia graminis f. sp. tritici Ug99 race group in Kenya has made pathogen survey a priority. We analyzed 140 isolates from 78 P. graminis f. sp. tritici samples collected in Kenya between 2008 and 2014 and identified six races, including three not detected prior to 2013. Genotypic analysis of 20 isolates from 2013 and 2014 collections showed that the new races TTHST, TTKTK, and TTKTT belong to the Ug99 race group. International advanced breeding lines were evaluated against an isolate of TTKTT (Sr31, Sr24, and SrTmp virulence) at the seedling stage. From 169 advanced lines from Kenya, 23% of lines with resistance to races TTKSK and TTKST were susceptible to TTKTT and, from two North American regional nurseries, 44 and 91% of resistant lines were susceptible. Three lines with combined resistance genes were developed to facilitate pathogen monitoring and race identification. These results indicate the increasing virulence and variability in the Kenyan P. graminis f. sp. tritici population and reveal vulnerabilities of elite germplasm to new races.

The Ug99 race (TTKSK) of wheat stem rust was first detected in Uganda in 1998 (Pretorius et al. 2000) and since then seven additional variants have been reported, i.e., TTKSF, TTKST, TTTSK, TTKSP, PTKSK, PTKST, and TTKSF+ (Pretorius et al. 2012). In this study, 84 stem rust samples from the 2014 surveys of wheat fields in Africa (Kenya, 9; Uganda, 28; Rwanda, 41; and Egypt, 6) were sent to the Global Rust Reference Center (GRRC, Denmark) for race analysis. Puccinia graminis f. sp. tritici (Pgt) samples were recovered on cv. Morocco, and resulting urediniospores of 53 single-pustule isolates were inoculated onto 20 North American stem rust differential lines using standard procedures (Jin et al. 2008). The pathotyping was repeated in two or three independent experiments. Twelve of the derived isolates were also typed at the USDA-ARS Cereal Disease Laboratory (USA) for an independent confirmation. Among the Kenyan samples, four collected from Njoro (Central Rift, cvs. Robin and Kwale) and two from Ntulumeti...

Ethiopia is the largest wheat producer in sub-Saharan Africa yet remains a net importer. Increasing domestic wheat production is a national priority. Improved varieties provide an important pathway to enhancing productivity and stability of production. Reliably tracking varietal use and dynamics is a challenge, and the value of conventional recall surveys is increasingly questioned. We report the first nationally representative, large-scale wheat DNA fingerprinting study undertaken in Ethiopia. Plot level comparison of DNA fingerprinting with farmer recall from nearly 4000 plots in the 2016/17 season indicates that only 28% of farmers correctly named wheat varieties grown. The DNA study reveals that new, rust resistant bread wheat varieties are now widely adopted. Germplasm originating from CGIAR centres has made a significant contribution. Corresponding productivity gains and economic benefits have been substantial, indicating high returns to investments in wheat improvement. The study provides an accurate assessment of wheat varietal status and sets a benchmark for national policy-makers and donors. In recent decades, the Ethiopian wheat landscape has transformed from local tetraploid varieties to widespread adoption of high yielding, rust resistant bread wheat. We demonstrate that DNA fingerprinting can be applied at scale and is likely to transform future crop varietal adoption studies.

Wheat rusts are the key biological constraint to wheat production in Ethiopia—one of Africa’s largest wheat producing countries. The fungal diseases cause economic losses and threaten livelihoods of smallholder farmers. While it is known that wheat rust epidemics have occurred in Ethiopia, to date no systematic long-term analysis of past outbreaks has been available. We present results from one of the most comprehensive surveillance campaigns of wheat rusts in Africa. More than 13,000 fields have been surveyed during the last 13 years. Using a combination of spatial data-analysis and visualization, statistical tools, and empirical modelling, we identify trends in the distribution of wheat stem rust (Sr), stripe rust (Yr) and leaf rust (Lr). Results show very high infection levels (mean incidence for Yr: 44%; Sr: 34%; Lr: 18%). These recurrent rust outbreaks lead to substantial economic losses, which we estimate to be of the order of 10s of millions of US-D annually. On the widely adopted wheat variety, Digalu, there is a marked increase in disease prevalence following the incursion of new rust races into Ethiopia, which indicates a pronounced boom-and-bust cycle of major gene resistance. Using spatial analyses, we identify hotspots of disease risk for all three rusts, show a linear correlation between altitude and disease prevalence, and find a pronounced north-south trend in stem rust prevalence. Temporal analyses show a sigmoidal increase in disease levels during the wheat season and strong inter-annual variations. While a simple logistic curve performs satisfactorily in predicting stem rust in some years, it cannot account for the complex outbreak patterns in other years and fails to predict the occurrence of stripe and leaf rust. The empirical insights into wheat rust epidemiology in Ethiopia presented here provide a basis for improving future surveillance and to inform the development of mechanistic models to predict disease spread.