Biology subjects

De Mita, S.

Publications and source records attributed to De Mita, S..

6 recordsLinked to original sources

bioRxiv2026

Population structure of the rice blast fungus Pyricularia oryzae in the context of elevated host heterogeneity

In a context where pathogen emergence threatens global food security, crop resistance to pathogens is crucial for preventing and controlling epidemics. Agrosystems with high intraspecific cultivated diversity are expected to better mitigate infectious diseases compared with homogeneous ones. However, the long-term impact of cultivated genotypic heterogeneity on pathogen populations is still under debate. The 1,300-year-old traditional agrosystem of the Yuanyang Terraces (YYT) in China exhibits an outstanding level of rice diversity. The rice blast fungus Pyricularia oryzae has been recorded in the area, making this area ideal for studying the impact of long term heterogeneous cultivation on plant-pathogen coevolution. In this study, we analysed 94 P. oryzae genomes from the YYT and compared them to 198 genomes representative of the worldwide diversity. We report elevated levels of genomic diversity of P. oryzae in the YYT. Whereas the worldwide diversity of this species is organized in four lineages, we detected seven lineages within the YYT, four of which are restricted to this area. The sampling dates of the YYT isolates (2009 to 2017) provided sufficient temporal signal to date nodes of the phylogenetic tree of isolates. Endemic lineages appeared to have arisen several centuries ago but later than the origin of the YYT themselves. We also detected recent introductions of worldwide lineages. Linkage disequilibrium analyses and in vitro cross experiments suggest that P. oryzae reproduces asexually in the YYT. These results suggest that long-term intraspecific crop diversity in the YYT has promoted the emergence and maintenance of a highly diverse, locally adapted pathogen population.

evolutionary biology↗

bioRxiv2024

Long-distance gene flow and recombination shape the evolutionary history of a maize pathogen

The evolutionary history of crop pathogens is shaped by a complex interaction of natural and anthropogenic factors. The ascomycete fungus Colletotrichum graminicola causes maize anthracnose. The disease can result in significant yield losses and is also an important model for genetic studies. We conducted a comprehensive investigation into the evolutionary genomics of C. graminicola using a collection of 212 isolates from 17 countries. Genomic analyses supported the existence of three geographically isolated genetic lineages, with a significant pattern of isolation by distance. We identified two distinct gene flow patterns, driven by short and long-distance dispersion, likely resulting from the natural spread of the pathogen and the exchange of contaminated seeds. We present evidence of genetic introgression between lineages, suggesting a long history of recombination. We identified significant recombination events coalescing at distinct points in time, with the North American lineage displaying evidence of most ancient recombination. Demographic modeling indicated that North America is an intermediate between Brazil, Europe and an ancestral, unsampled source population, hypothesized to be Mesoamerican. Our analyses revealed that the global genomic structure of C. graminicola is shaped by geographic differentiation driven by long-distance migration and a long history of recombination and introgression. We show historical relationships among these lineages, identifying a potential route for fungal spread, with the North American population emerging ancestrally, followed sequentially by the Brazilian and European populations. Our research indicates that the European lineage is more virulent, which has implications for the potential emergence of new outbreaks of maize anthracnose in Europe.

genomics↗

bioRxiv2024

Population genomics of the rice landrace Acuce reveals exceptional dynamics of immune receptors

In cultivated plants such as Oryza sativa, landraces harbour high levels of diversity, in sharp contrast with genetically uniform modern varieties. The Yuanyang terraces (China) are renowned for traditional farming involving landraces and low disease incidence. To understand the molecular basis of these resistance levels, we explored the genomic diversity of Acuce, one of the oldest landraces in the region. Based on whole-genome resequencing of over 200 Acuce plants, we evaluated the diversity of immunity and agronomical genes with respect to the rest of the genome. In parallel, we analysed the genetic basis of pathogen resistance and agronomical traits. Acuce exhibits high levels of diversity, reaching 38% of the worldwide levels. We uncovered an excess of diversity and signatures of directional selection associated with immunity genes, in contrast with agricultural traits. Furthermore, cultures of mixed genotypes exhibited superior performances for both pathogen resistance and agricultural traits. We showed that, within one single landrace, traditional farmer practices selected optimal agricultural traits while maintaining diversity enabling pathogen resistance. This study elucidates the complex interplay between genetic diversity, natural selection related to pathogens, and selection for agricultural traits within traditional landraces, providing insights into sustainable agricultural practices in diverse cropping systems.

genomics↗

bioRxiv2021

Impact of ploidy and pathogen life cycle on resistance durability

The breeding of resistant hosts based on the gene-for-gene interaction is crucial to address epidemics of plant pathogens in agroecosystems. Resistant host deployment strategies are developed and studied worldwide to decrease the probability of resistance breakdown and increase the resistance durability in various pathosystems. A major component of deployment strategies is the proportion of resistant hosts in the landscape. However, the impact of this proportion on resistance durability remains unclear for diploid pathogens with complex life cycles. In this study, we modelled pathogen population dynamics and genetic evolution at the virulence locus to assess the impact of the ploidy (haploid or diploid) and the pathogens life cycle (with or without host alternation) on resistance durability. Ploidy has a strong impact on evolutionary trajectories, with much greater stochasticity and delayed times of resistance breakdown for diploids. This result emphasises the importance of genetic drift in this system: as the virulent allele is recessive, positive selection on resistant hosts only applies to homozygous (virulent) individuals, which may lead to population collapse at low frequencies of the virulent allele. We also observed differences in the effect of host deployment depending on the pathogens life cycle. With host alternation, the probability that the pathogen population collapses strongly increases with the proportion of resistant hosts in the landscape. Therefore, resistance breakdown events occurring at high proportions of resistant hosts frequently amount to evolutionary rescue. Last, life cycles correspond to two selection regimes: without host alternation (soft selection) the resistance breakdown is mainly driven by the migration rate. Conversely, host alternation (hard selection) resembles an all-or-nothing game, with stochastic trajectories caused by the recurrent allele redistributions on the alternate host.

evolutionary biology↗

bioRxiv2021

Genomic signatures of a major adaptive event in the pathogenic fungus Melampsora larici-populina

BackgroundThe recent availability of genome-wide sequencing techniques has allowed systematic screening for molecular signatures of adaptation, including in non-model organisms. Host-pathogen interactions constitute good models due to the strong selective pressures that they entail. We focused on an adaptive event which affected the poplar rust fungus Melampsora larici-populina when it overcame a resistance gene borne by its host, cultivated poplar. Based on 76 virulent and avirulent isolates framing narrowly the estimated date of the adaptive event, we examined the molecular signatures of selection. ResultsUsing an array of genome scan methods, we detected a single locus exhibiting a consistent pattern suggestive of a selective sweep in virulent individuals (excess of differentiation between virulent and avirulent samples, linkage disequilibrium, genotype-phenotype statistical association and long-range haplotypes). Our study pinpoints a single gene and further a single amino acid replacement which may have allowed the adaptive event. Although the selective sweep occurred only four years earlier, it does not seem to have affected genome diversity further than the immediate vicinity of the causal locus. ConclusionsOur results suggest that M. larici-populina under-went a soft selective sweep and possibly a prominent effect of outbreeding and recombination, which we speculate have increased the efficiency of selection.

evolutionary biology↗

bioRxiv2021

Joint inference of adaptive and demographic history from temporal population genomic data

Disentangling the effects of selection and drift is a long-standing problem in population genetics. Simulations show that pervasive selection may bias the inference of demography. Ideally, models for the inference of demography and selection should account for the interaction between these two forces. With simulation-based likelihood-free methods such as Approximate Bayesian Computation (ABC), demography and selection parameters can be jointly estimated. We propose to use the ABC-Random Forests framework to jointly infer demographic and selection parameters from temporal population genomic data (e.g. experimental evolution, monitored populations, ancient DNA). Our framework allowed the separation of demography (census size, N) from the genetic drift (effective population size, Ne) and the estimation of genome-wide parameters of selection. Selection parameters informed us about the adaptive potential of a population (the scaled mutation rate of beneficial mutations,{theta} b), the realized adaptation (the number of mutation under strong selection), and population fitness (genetic load). We applied this approach to a dataset of feral populations of honey bees (Apis mellifera) collected in California, and we estimated parameters consistent with the biology and the recent history of this species.

evolutionary biology↗