Latest Articles

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  Section: Genomics ; Topics: Genetics/genomics ; Conference: JOBIM

  rnaends: an R package to study exact RNA ends at nucleotide resolution

  Caetano, Tomas;   Redder, Peter;   Fichant, Gwennaele;   Barriot, Roland  

  10.24072/pcjournal.724 - Peer Community Journal, Volume 6 (2026), article no. e49

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  5’ and 3’ RNA-end sequencing protocols have unlocked new opportunities to study aspects of RNA metabolism such as synthesis, maturation and degradation, by enabling the quantification of exact ends of RNA molecules in vivo. From RNA-Seq data that have been generated with one of the specialized protocols, it is possible to identify transcription start sites (TSS) and/or endoribonucleolytic cleavage sites, and even, in some cases, co-translational 5’ to 3’ degradation dynamics. Furthermore, post-transcriptional addition of ribonucleotides at the 3’ end of RNA can be studied at the nucleotide resolution. While different RNA-end sequencing library protocols exist that have been adapted to a specific organism (prokaryote or eukaryote) or specific biological question, the generated RNA-Seq data are very similar and share common processing steps. Most importantly, the major aspect of RNA-end sequencing is that only the 5’ or 3’ end mapped location is of interest, contrary to conventional RNA sequencing that considers genomic ranges for gene expression analysis. This translates to a simple representation of the quantitative data as a count matrix of RNA-end location on the reference sequences. This representation seems under-exploited and is, to our knowledge, not available in a generic package focused on the analyses on the exact transcriptome ends. Here, we present the rnaends R package which is dedicated to RNA-end sequencing analysis. It offers functions for raw read pre-processing, RNA-end mapping and quantification, RNA-end count matrix post-processing, and further downstream count matrix analyses such as TSS identification, fast Fourier transform for signal periodic pattern analysis, or differential proportion of RNA-end analysis. The use of rnaends is illustrated here with applications in RNA metabolism studies through selected rnaends workflows on published RNA-end datasets: (i) TSS identification, (ii) ribosome translation speed and co-translational degradation, (iii) post-transcriptional modification analysis and differential proportion analysis.

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  Section: Archaeology ; Topics: Archaeology, Computer sciences, Engineering

  A multimodal approach to heritage preservation in the context of climate change

  Roqui, David; Cormier, Adèle; Grozavu, Nistor; Bourges, Ann

  10.24072/pcjournal.723 - Peer Community Journal, Volume 6 (2026), article no. e48

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  Cultural heritage sites face accelerating degradations due to climate change, yet traditional monitoring relies on unimodal analysis (visual inspection or environmental sensors alone) that fails to capture the complex interplay between environmental stressors and material deterioration. We propose a lightweight multimodal architecture that fuses sensor data (temperature, humidity) with visual imagery to predict degradation severity at heritage sites. Our approach adapts PerceiverIO with two key innovations: (1) simplified encoders (64D latent space) that prevent overfitting on small datasets (37 samples for training, 555 with data augmentation; 13 for validation, and 13 for testing), and (2) Adaptive Barlow Twins loss that encourages modality complementarity rather than redundancy. On data from Strasbourg Cathedral, our model achieves 76.9% accuracy and 77.0% weighted-F1 score on the test set, a 43% improvement over standard multimodal architectures (VisualBERT, Transformer) and 25% over vanilla PerceiverIO. Ablation studies reveal that sensor-only achieves 61.5% while image-only reaches 46.2%, confirming successful multimodal synergy. A systematic hyperparameter study identifies an optimal moderate correlation target (τ = 0.3) that balances alignment and complementarity, achieving 69.2% accuracy compared to other τ values (τ = 0.1/0.5/0.7: 53.8%, τ = 0.9: 61.5%). This work demonstrates that architectural simplicity combined with contrastive regularization enables effective multimodal learning in data-scarce heritage monitoring contexts, providing a foundation for AI-driven conservation decision support systems.

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  Section: Infections ; Topics: Agricultural sciences, Health sciences

  Phenology of Hyalomma marginatum: a longitudinal study in a site of southern France

  Stachurski, Frédéric;   Duhayon, Maxime; Appelgren, Anaïs; Balança, Gilles; Giupponi, Carla; Pollet, Thomas;   Vial, Laurence  

  10.24072/pcjournal.726 - Peer Community Journal, Volume 6 (2026), article no. e47

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  Hyalomma marginatum tick establishment has been recorded in southern mainland France for around ten years. This two-host species is one of the main vectors of the Crimean-Congo haemorrhagic fever (CCHF) virus. Knowing the phenology of the tick is a prerequisite for a better understanding of its spread and of CCHF virus dispersal. A longitudinal study was carried out between 2016 and 2022 in a horse herd to determine the seasonal variations of H. marginatum infestation. In the study site, adult ticks started infesting their hosts from the beginning of March. Infestation peaked during the first weeks of May. At that period, on average, up to 4 or 5 ticks attached daily to each horse. Then, the infestation steadily decreased until the end of August. In this site, birds are parasitised by H. marginatum immatures (larvae and nymphs) in summer, from mid/late June to the end of September. The larvae are therefore not yet active when the migratory birds pass through in spring. Blackbird, Turdus merula, was the most heavily infested bird species: nearly two-thirds of the blackbirds examined in summer were parasitised by H. marginatum. It is suggested that this bird species could be a good sentinel host for monitoring the establishment of the tick in currently H. marginatum-free areas. To complete these surveys, an experimental study was carried out in quasi-natural conditions with engorged ticks placed in cages in the garrigue. It was shown that the nymphs moulted into adults within 3-4 weeks in July-August. However, they remain completely immobile in the litter, undergoing a behavioural diapause, until the following spring. On the other hand, almost all the nymphs released later, in September or October, died during the cold and rainy season. It was also observed that engorged females were able to survive the cold conditions up to 6-8 months before laying eggs. The study also suggested that there were predators of H. marginatum, likely ants and spiders, in the study site. The hosts monitored over all these years were not only infested by H. marginatum. The phenology of other tick species parasitizing horses (Dermacentor marginatus, Haemaphysalis punctata, Rhipicephalus bursa) and birds (Ixodes frontalis, I. ricinus, H. punctata) was also highlighted for this study site.

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  Section: Mathematical & Computational Biology ; Topics: Evolution, Genetics/genomics, Population biology

  SelNeTime: a python package inferring effective population size and selection intensity from genomic time series data

  Uhl, Mathieu;   Bunel, Paul; de Navascués, Miguel;   Boitard, Simon;   Servin, Bertrand  

  10.24072/pcjournal.708 - Peer Community Journal, Volume 6 (2026), article no. e46

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  Genomic samples collected from a single population over several generations provide direct access to the genetic diversity changes occurring within a specific time period. This provides information about both demographic and adaptive processes acting on the population during that period. A common approach to analyze such data is to model observed allele counts in finite samples using a Hidden Markov Model (HMM) where hidden states are true allele frequencies over time (i.e. a trajectory). The HMM framework allows one to compute the full likelihood of the data, while accounting both for the stochastic evolution of population allele frequencies along time and for the noise arising from sampling a limited number of individuals at possibly spread out generations. Several such HMM methods have been proposed so far, differing mainly in the way they model the transition probabilities of the Markov chain. Following Paris et al. (2019a), we consider here the Beta with Spikes approximation, which avoids the computational issues associated to the Wright-Fisher model while still including fixation probabilities, in contrast to other standard approximations of this model like the Gaussian or Beta distributions. To facilitate the analysis and exploitation of genomic time series data, we present an improved version of Paris et al. (2019a) ‘s approach, denoted SelNeTime, whose computation time is drastically reduced and which accurately estimates effective population size (assuming no selection) or the selection intensity at each locus (given a previously estimated value of N). We also evaluate the performance of this method in realistic situations where selection is present and both demography and selection need to be inferred. SelNeTime is implemented in a user friendly python package, which can also easily simulate genomic time series data under a user-defined evolutionary model and sampling design.