Latest Articles

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  Section: Plants ; Topics: Plant biology, Biology of interactions, Systems biology

  Transcriptional responses of Solanum lycopersicum to three distinct parasites reveal host hubs and networks underlying parasitic successes

  Truch, Julia;   Jaouannet, Maelle; Da Rocha, Martine;   Kulhanek-Fontanille, Emmanuelle; Van Ghelder, Cyril;   Rancurel, Corinne;   Migliore, Olivier; Pere, Arthur; Jaubert, Stephanie;   Coustau, Christine; Galiana, Eric;   Favery, Bruno  

  10.24072/pcjournal.815 - Peer Community Journal, Volume 6 (2026), article no. e108

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  Crops face attacks from a wide range of pathogens and pests that deploy various parasitic strategies. All aggressors must manipulate major plant functions, such as immune signaling, hormone pathways, metabolism, and development, to successfully establish themselves and complete their life cycle. Here, we compared the tomato plant’s response to three evolutionary distant pathogens (nematodes, aphids and oomycetes) during compatible interactions using a transcriptomic approach. We identified differentially expressed genes and biological processes, and highlighted potential key host hubs associated with successful parasitism. By integrating recent published datasets, we refined our understanding of the global and tissue-specific mechanisms targeted during compatible interactions and, through co-expression analysis, identified clusters showing shared dysregulation patterns enriched in specific GO terms. Finally, model-to-crop translational analysis using the Arabidopsis interactome network, repositioned tomato candidates within larger interaction networks and emphasized the key positions occupied by some of them. Identifying these pivotal tomato targets is crucial to decipher processes underlying parasitism and, consequently, offers new opportunities to develop sustainable multi-pathogen control strategies.

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  Section: Evolutionary Biology ; Topics: Evolution, Population biology, Genetics/genomics

  The geometry of gametic dispersal in a flying mammal, Rhinolophus hipposideros

  Brazier, Thomas;   Zarzoso-Lacoste, Diane;   Lehnen, Lisa;   Jan, Pierre-Loup;   Puechmaille, Sebastien J.;   Petit, Eric J.  

  10.24072/pcjournal.811 - Peer Community Journal, Volume 6 (2026), article no. e107

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  Dispersal influences population and evolutionary dynamics, in a manner that depends on by which dispersal strategies gene flow occurs. In some species, mating partners move exclusively for mating, dispersing genes but not individuals. This is the case in many bat species, of which the lesser horseshoe bat (Rhinolophus hipposideros) shows a genetic structure at a fine spatial scale suggesting restricted dispersal. We investigated how natal and mating dispersal shape gene flow in this species in two metapopulations using paternity and population assignments. Half of the inferred paternities were intra-colonial and gave an estimate of the mean mating dispersal distance of around 11 km, explaining the observed genetic structure. Complete gametic dispersal distances were further estimated by combining natal with mating dispersal distances. The resulting gametic dispersal kernels showed a mean distance of around 20 km and a fat-tailed distribution typical of an excess of long-distance dispersal movements. It is the first time that natal and mating dispersal distances have been separately estimated and then combined in animals, documenting quantitatively how mating dispersal decorrelates gene and individual flows. It is important to consider this mechanism to explain dispersal evolution.

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  Section: Ecotoxicology & Environmental Chemistry ; Topics: Environmental sciences

  Combination of instrumental and biomonitoring approaches elucidate the contributions of multiple and contrasted sources of atmospheric exposure to polycyclic aromatic hydrocarbons

  Reuillard, Mathilde; Dron, Julien;   Durand, Amandine;   Gandolfo, Adrien;   Wortham, Henri; Wafo, Emmanuel; Austruy, Annabelle

  10.24072/pcjournal.813 - Peer Community Journal, Volume 6 (2026), article no. e106

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  A combined approach was implemented to investigate the origins of elevated PAH concentrations in a complex urban environment where numerous emission sources coexist. This approach integrated one year of atmospheric measurements  PM10 filters and continuous atmospheric monitoring), alongside lichen biomonitoring and soil analyses. Results revealed diffuse multi-source contamination, characterized by high PAH levels in both soils and lichens, with a major contribution from the resuspension of soil particles from contaminated brownfields. Pronounced seasonal variations, particularly in winter, reflected the influence of residential heating, with a minor and local contribution from agricultural stubble-burning. Current industrial and port activities were also identified as significant contributors notably through fine particle. The integration of these complementary spatial and temporal approaches enable the ranking of source as follows: (i) resuspension of contaminated soil particles, (ii) industrial and maritime emissions, (iii) residential heating, and (iv) stubble-burning. Combining biomonitoring with atmospheric monitoring provides a robust methodology for characterizing PAH exposure in complex multi-exposure atmospheric contexts, and for guiding environmental health risk management.

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  Section: Statistics & Machine Learning ; Topics: Statistics

  On Nonparanormal Likelihoods

  Hothorn, Torsten  

  10.24072/pcjournal.814 - Peer Community Journal, Volume 6 (2026), article no. e105

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  Nonparanormal models describe the joint distribution of multivariate responses via latent Gaussian, and thus parametric, copulae while allowing flexible nonparametric marginals. Some aspects of such distributions, for example conditional independence, are formulated parametrically. Other features, such as marginal distributions, can be formulated non- or semiparametrically. Such models are attractive when multivariate normality is questionable but interpretability paramount. Most estimation procedures perform two steps, first estimating the nonparametric part. The copula parameters come second, treating the marginal estimates as known. This is sufficient for some applications. For other applications, e.g. when a semiparametric margin features parameters of interest or when standard errors are important, a simultaneous estimation of all parameters might be more advantageous. We present suitable parameterisations of nonparanormal models, possibly including semiparametric effects, and define four novel nonparanormal log-likelihood functions. In general, the corresponding one-step optimisation problems are shown to be non-convex. In some cases, however, biconvex problems emerge. Several convex approximations are discussed. From a low-level computational point of view, the core contribution is the score function for multivariate normal log-probabilities computed via Genz’ procedure. As a demonstration for the versatility of the theoretical and computational framework, we present a series of nonparanormal models for transformation discriminant analysis when some biomarkers are subject to limit-of-detection problems. Possible empirical gains of full maximum likelihood estimation compared to two-step approaches are illustrated in a simulation study targeting semiparametric efficient polychoric correlation analysis where a theoretical benchmark is available.