Latest Articles

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  Section: Mathematical & Computational Biology ; Topics: Agricultural sciences, Computer sciences, Statistics ; Conference: JOBIM

  Simulating transgenerational hologenomes under selection with RITHMS

  Pety, Solène;   David, Ingrid;   Rau, Andrea;   Mariadassou, Mahendra  

  10.24072/pcjournal.666 - Peer Community Journal, Volume 5 (2025), article no. e142

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  A holobiont is made up of a host organism together with its microbiota. In the context of animal breeding, the holobiont can be viewed as the single unit upon which selection operates. Therefore, integrating microbiota data into genomic prediction models may be a promising approach to improve predictions of phenotypic and genetic values. Nevertheless, there is a paucity of hologenomic transgenerational data to address this hypothesis, and thus to fill this gap, we propose a new simulation framework. Our approach, an R Implementation of a Transgenerational Hologenomic Model-based Simulator (RITHMS) is an open-source package. It builds upon simulated transgenerational genotypes from the Modular Breeding Program Simulator (MoBPS) package and incorporates distinctive characteristics of the microbiota, notably vertical and horizontal transmission as well as modulation due to the environment and host genetics. In addition, RITHMS can account for a variety of selection strategies and is adaptable to different genetic architectures. We simulated transgenerational hologenomic data using RITHMS under a wide variety of scenarios, varying heritability, microbiability, and microbiota transmissibility. We found that simulated data accurately preserved key characteristics across generations, notably microbial diversity metrics, exhibited the expected behavior in terms of correlation between taxa and of modulation of vertical and horizontal transmission, response to environmental effects and the evolution of phenotypic values depending on selection strategy. Our results support the relevance of our simulation framework and illustrate its possible use for building a selection index balancing genetic gain and microbial diversity and for evaluating the impact of partially observed microbiota data. RITHMS is an advanced, flexible tool for generating transgenerational hologenomes under selection that incorporate the complex interplay between genetics, microbiota and environment.

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

  localScore: an R package to highlight optimal and suboptimal segments in a sequence with associated p-values computation

  Robelin, David;   Déjean, Sébastien;   Mercier, Sabine

  10.24072/pcjournal.650 - Peer Community Journal, Volume 5 (2025), article no. e141

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  Highlighting atypical segments of a sequence is an important goal in very diverse domains. In the case where no prior information on the length of the segment to be highlighted is known, Karlin and Altschul defined, in 1990, the local score for biological sequence analysis, and an asymptotic approximation of its distribution was proposed in 1992. There are now many other theoretical results that can be used to establish the p-value of the local score in different contexts. We have developed an R package bringing together these results for a sequence modelled by independent and identically or Markovian distributed variables. It calculates the local score, the sub-optimal scores and their positions, and proposes to establish the $p$-value of the local score using the various theoretical methods available to date. An automatic analysis is also proposed to apply the most appropriate method depending on the sequence analyzed. Here we present the software package and various application examples. Comparisons with other tools used depending on the context of the application are also given. The localScore package is available on CRAN under the GPL-2 license (core program) and various licenses for the embedded Eigen library.

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  Section: Archaeology ; Topics: Archaeology, Environmental sciences

  Digital surface models of crops used in archaeological feature detection – a case study of Late Neolithic site Tomašanci-Dubrava in Eastern Croatia

  Sosic Klindzic , Rajna; Vuković, Miroslav; Kalafatić, Hrvoje ; Šiljeg, Bartul  

  10.24072/pcjournal.665 - Peer Community Journal, Volume 5 (2025), article no. e140

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  This paper presents the results of a study on the Neolithic landscape of the Sopot culture in the area of Đakovština in Eastern Slavonija. A vast network of settlements was uncovered using aerial archaeology, which was further confirmed and chronologically determined by magnetometry, excavations, and field surveys. The study focuses on the site Tomašanci-Dubrava, where a drone was used to acquire vertical photographs to capture a detailed orthophoto of the feature in a maturing crop. The captured data revealed the subsurface archaeological features that affect the rate of plant growth, as observed on detailed digital surface models. The implications of this observation are discussed in the paper, including its potential use on a larger level with ALS data or aerial photographs taken by the state geodesic service to create DSM models of wider areas.

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  Section: Evolutionary Biology ; Topics: Biology of interactions, Ecology, Evolution

  The effects of host phylogenetic coverage and congruence metric on Monte Carlo-based null models of phylosymbiosis

  DuBose, James G.

  10.24072/pcjournal.667 - Peer Community Journal, Volume 5 (2025), article no. e139

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  Variation in host-associated microbial communities often parallels patterns of phylogenetic divergence between hosts, a pattern known as phylosymbiosis. Understanding of this phenomenon relies initially on quantifying phylosymbiotic signals from across a broad range of host taxa. Quantifying signals of phylosymbiosis is typically achieved by calculating how congruent a host’s phylogenetic tree is with a dendrogram that represents patterns of dissimilarity in their associated microbial communities. To statistically assess the degree of congruence, several studies have constructed null models using a Monte Carlo approach to randomly sample trees. Although this approach is becoming more common, it has several features that warrant benchmarking to advise its further use. This approach relies on quantification of congruence between a host’s phylogenetic tree its microbial community dendrogram. Therefore, it is important to establish how choice of congruence metric influences null model-based inferences. Furthermore, phylosymbiotic signals may manifest at different scales of host divergence, and it is important to establish the extent of host phylogenetic breadth needed to reliably detect a phylosymbiotic signal. To help improve our study of phylosymbiosis, here I examine how power and type 1 error (false positive) rates associated with this approach varies with choice of congruence metric and host phylogenetic coverage. Furthermore, I examine variation in sensitivity given uncertainty in tree estimation, as well as how well null congruence models align with expectations of community assembly that is completely neutral with respect to host phylogeny. I generally found that model performance increased rapidly with increasing tree sizes, suggesting lower limits on the host phylogenetic breadth needed to reliably detect phylosymbiotic signals with this approach. Furthermore, I found several notable variations in performance between congruence metrics, which translated into different inferences regarding signal detection. Overall, these findings suggest that Monte Carlo sampling across tree space can be an effective way to quantify phylosymbiotic signals and highlight key considerations for its implementation.