Biology subjects

Pilet-Nayel, M.-L.

Publications and source records attributed to Pilet-Nayel, M.-L..

4 recordsLinked to original sources

bioRxiv2026

Intraspecific variation at the free-living stage of a soil-borne pathogen is organized into an exploration syndrome associated with infectivity

Many pathogens spend a substantial portion of their life cycle outside the host tissues. During its free-living stage, the root legume-plant pathogen Aphanomyces euteiches persists in soil either as non-motile resting oospores or actively explores the environment through mycelium and motile zoospores. These two latter stages are critical for survival, dispersal and host encounter. However, the extent of intraspecific variation during these phases remains poorly explored, and it is still unknown whether they are organized into phenotypic syndromes contributing to infection success. Here, we measured eight free-living phenotypic traits associated with mycelial and zoospore stages across 23 A. euteiches strains from distinct geographic regions (USA, Europe) whose genomes were sequenced. We tested whether traits are organized into a phenotypic syndrome linked to either geographic origin, genomic diversity or infectivity. The microbial strains exhibited substantial intraspecific phenotypic variation that we proposed as an 'exploration syndrome' linked to host search. Beyond this general syndrome, we detected sub-structure according to strains' infectivity, geographic origin and genetic group. This suggests that the free-living stage of pathogens may contribute to disease potential. Our results highlight the importance of integrating functional trait approaches into plant pathology and suggest that the identified "exploration syndrome" may serve as a predictor of infectivity in soilborne oomycete pathogens.

ecology↗

bioRxiv2025

QTL combinations associated with field partial resistance to aphanomyces root rot in pea Near-Isogenic Lines

Aphanomyces root rot, caused by Aphanomyces euteiches, is one of the most-important diseases of pea (Pisum sativum L.) worldwide. The development of resistant varieties is a major objective to manage the disease. Consistent quantitative trait loci (QTL) controlling partial resistance were discovered from linkage mapping and genome-wide association studies. This study aimed to validate the resistance QTL effects and identify effective QTL combinations under contaminated field conditions, by exploiting Near-Isogenic Lines (NILs) carrying resistance alleles at individual or combined consistent QTL in different genetic backgrounds. A total of 157 NILs previously created were fingerprinted using 10,494 SNP markers from the GenoPea Infinium(R) BeadChip, which made it possible to confirm the QTL introgression sizes in the NILs. All NILs were phenotyped for resistance in field contaminated nurseries over two years at six locations in France. NILs carrying resistance alleles from PI180693 or 90-2131 at the major-effect QTL Ae-Ps7.6, individually or in combination with minor-effect QTL (Ae-Ps4.1 or Ae-Ps5.1), showed significantly increased levels of partial resistance in different environments and genetic backgrounds. At other QTL combinations (Ae-Ps1.2 or AePs7.6 + Ae-Ps2.2 + Ae-Ps3.1), alleles from PI180693 or 552 also showed significant effects on partial resistance in some NIL genetic backgrounds. At these QTL combinations, the PI180693 resistance alleles also contributed to late flowering. This study provides tools and information for the choice of resistance QTL to combine in breeding, to increase partial resistance to A. euteiches in pea varieties.

genetics↗

bioRxiv2022

SNP discovery by exome capture and resequencing in a pea genetic resource collection

Background & SummaryIn addition to being the model plant used by Mendel1 to establish genetic laws, pea (Pisum sativum L., 2n=14) is a major pulse crop cultivated in many temperate regions of the world. In order to face new challenges imposed particularly by global climate change and new regulations targeted at reducing chemical inputs, pea breeders have to take advantage of the genetic diversity present in the Pisum genepool to develop improved, resilient varieties. The aim of this study was to assess the genetic diversity of a pea germplasm collection and allow genome-wide association studies using this collection. To be able to perform genome-wide association approaches with high resolution, genotyping with a large set of genetic markers such as Single Nucleotide Polymorphism (SNP) markers well-spread over the genome is required. Rapid advances in second-generation sequencing technologies and the development of bioinformatic tools have revolutionized the access to and the characterization of available genetic diversity. High-density, high-throughput genotyping has been possible for a large number of species, including those with large and complex genomes2 such as pea (2n=14) which genome size is estimated to be 4.45 Gb3. In this study, which is part of the PeaMUST project4, we used a target capture technology based on pea transcriptome sequences to generate exome-enriched genomic libraries that were further subjected to Illumina sequencing in paired-end mode. This methodology was chosen because whole-genome resequencing is relatively expensive for species with large genomes and because capturing genetic variations in repeated non-coding regions is difficult to achieve or to interpret5. Whole-exome sequencing represented an interesting alternative that focused on coding regions only6,7. Mapping the obtained reads on the reference pea genome sequence enabled the discovery of an abundant set of SNPs. The development of this resource is a crucial cornerstone in research and breeding projects towards boosting the improvement of pea production and quality.

genomics↗

bioRxiv2021

The quasi-universality of nestedness in the structure of quantitative plant-parasite interactions

AO_SCPLOWBSTRACTC_SCPLOWUnderstanding the relationships between host range and pathogenicity for parasites, and between the efficiency and scope of immunity for hosts are essential to implement efficient disease control strategies. In the case of plant parasites, most studies have focused on describing qualitative interactions and a variety of genetic and evolutionary models has been proposed in this context. Although plant quantitative resistance benefits from advantages in terms of durability, we presently lack models that account for quantitative interactions between plants and their parasites and the evolution of these interactions. Nestedness and modularity are important features to unravel the overall structure of host-parasite interaction matrices. Here, we analysed these two features on 32 matrices of quantitative pathogenicity trait data gathered from 15 plant-parasite pathosystems consisting of either annual or perennial plants along with fungi or oomycetes, bacteria, nematodes, insects and viruses. The performance of several nestedness and modularity algorithms was evaluated through a simulation approach, which helped interpretation of the results. We observed significant modularity in only six of the 32 matrices, with two or three modules detected. For three of these matrices, modules could be related to resistance quantitative trait loci present in the host. In contrast, we found high and significant nestedness in 30 of the 32 matrices. Nestedness was linked to other properties of plant-parasite interactions. First, pathogenicity trait values were explained in majority by a parasite strain effect and a plant accession effect, with no or minor parasite-plant interaction term. Second, correlations between the efficiency and scope of the resistance of plant genotypes, and between the host range breadth and pathogenicity level of parasite strains were overall positive. This latter result questions the efficiency of strategies based on the deployment of several genetically-differentiated cultivars of a given crop species in the case of quantitative plant immunity.

pathology↗