Central American and Caribbean population history of the Pseudocercospora fijiensis fungus responsible for the latest worldwide pandemics on banana

Revisiting the historical scenario of a disease dissemination using genetic data and Approximate Bayesian Computation methodology: The case of Pseudocercospora fijiensis invasion in Africa

The reconstruction of geographic and demographic scenarios of dissemination for invasive pathogens of crops is a key step toward improving the management of emerging infectious diseases. Nowadays, the reconstruction of biological invasions typically uses the information of both genetic and historical information to test for different hypotheses of colonization. The Approximate Bayesian Computation framework and its recent Random Forest development (ABC-RF) have been successfully used in evolutionary biology to decipher multiple histories of biological invasions. Yet, for some organisms, typically plant pathogens, historical data may not be reliable notably because of the difficulty to identify the organism and the delay between the introduction and the first mention. We investigated the history of the invasion of Africa by the fungal pathogen of banana Pseudocercospora fijiensis, by testing the historical hypothesis against other plausible hypotheses. We analyzed the genetic structure of eight populations from six eastern and western African countries, using 20 microsatellite markers and tested competing scenarios of population foundation using the ABC-RF methodology. We do find evidence for an invasion front consistent with the historical hypothesis, but also for the existence of another front never mentioned in historical records. We question the historical introduction point of the disease on the continent. Crucially, our results illustrate that even if ABC-RF inferences may sometimes fail to infer a single, well-supported scenario of invasion, they can be helpful in rejecting unlikely scenarios, which can prove much useful to shed light on disease dissemination routes.

The Vulnerability of Bananas to Globally Emerging Disease Threats

Banana cultivation has increased significantly over the last century to meet the growing demand for this popular fruit. Originating in Southeast Asia, bananas are now produced in >135 different countries in tropical and subtropical regions of the world. Most of this expansion of production is based on a single banana variety, Cavendish, which makes up almost all the export trade grown in large-scale monocultures and a large part of the local trade and represents >40% of all bananas grown globally. Over the last century several major diseases of the banana have emerged and widely expanded their geographic ranges. Cultivars within the Cavendish variety are highly susceptible to these diseases, including yellow Sigatoka, black leaf streak, Eumusae leaf spot, freckle, Fusarium wilt tropical race 4, banana bunchy top, and the bacterial wilts Moko, Xanthomonas wilt, and banana Blood disease. This review graphically illustrates the emergence and rapid intercontinental spread of these diseases and discusses several major disease epidemics in bananas. Evidently, the large-scale monoculture based on the single variety Cavendish has resulted in an extreme level of genetic vulnerability. The resistance to diversification in the Cavendish production chain and the lack of investment in genetics and plant breeding in the recent past means that currently limited genetic solutions are available to replace the Cavendish banana with a set of market acceptable resistant varieties from a range of different genetic backgrounds.

Complex adaptive architecture underlies adaptation to quantitative host resistance in a fungal plant pathogen

Plant pathogens often adapt to plant genetic resistance so characterization of the architecture underlying such an adaptation is required to understand the adaptive potential of pathogen populations. Erosion of banana quantitative resistance to a major leaf disease caused by polygenic adaptation of the causal agent, the fungus Pseudocercospora fijiensis, was recently identified in the northern Caribbean region. Genome scan and quantitative genetics approaches were combined to investigate the adaptive architecture underlying this adaptation. Thirty-two genomic regions showing host selection footprints were identified by pool sequencing of isolates collected from seven plantation pairs of two cultivars with different levels of quantitative resistance. Individual sequencing and phenotyping of isolates from one pair revealed significant and variable levels of correlation between haplotypes in 17 of these regions with a quantitative trait of pathogenicity (the diseased leaf area). The multilocus pattern of haplotypes detected in the 17 regions was found to be highly variable across all the population pairs studied. These results suggest complex adaptive architecture underlying plant pathogen adaptation to quantitative resistance with a polygenic basis, redundancy, and a low level of parallel evolution between pathogen populations. Candidate genes involved in quantitative pathogenicity and host adaptation of P. fijiensis were identified in genomic regions by combining annotation analysis with available biological data.