Latest Articles
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Section: Genomics ; Topics: Genetics/genomics
Sequencing, de novo assembly of Ludwigia plastomes, and comparative analysiswithin the Onagraceae family
10.24072/pcjournal.536 - Peer Community Journal, Volume 5 (2025), article no. e43.
Get full text PDFThe Onagraceae family, which belongs to the order Myrtales, consists of approximately 657 species and 17 genera. This family includes the genus Ludwigia L., which is comprised of 82 species. In this study, we focused on the two aquatic invasive species Ludwigia grandiflora subsp. hexapetala (Lgh) and Ludwigia peploides subsp. montevidensis (Lpm) largely distributed in aquatic environments in North America and in Europe. Both species have been found to degrade major watersheds leading ecological and economical damages. Genomic resources for Onagraceae are limited, with only Ludwigia octovalvis (Lo) plastid genome available for the genus Ludwigia L. at the time of our study. This scarcity constrains phylogenetic, population genetics, and genomic studies. To brush up genomic ressources, new complete plastid genomes of Ludwigia grandiflora subps. hexapetala (Lgh) and Ludwigia peploides subsp. montevidensis (Lpm) were generated using a combination of MiSeq (Illumina) and GridION (Oxford Nanopore) sequencing technologies. These plastomes were then compared to the published Ludwigia octovalvis (Lo) plastid genome, which was re-annotated by the authors. We initially sequenced and assembled the chloroplast (cp) genomes of Lpm and Lgh using a hybrid strategy combining short and long reads sequences. We observed the existence of two Lgh haplotypes and two potential Lpm haplotypes. Lgh, Lpm, and Lo plastomes were similar in terms of genome size (around 159 Kb), gene number, structure, and inverted repeat (IR) boundaries, comparable to other species in the Myrtales order. A total of 45 to 65 SSRs (simple sequence repeats), were detected, depending on the species, with the majority consisting solely of A and T, which is common among angiosperms. Four chloroplast genes (matK, accD, ycf2 and ccsA) were found under positive selection pressure, which is commonly associated with plant development, and especially in aquatic plants such as Lgh, and Lpm. Our hybrid sequencing approach revealed the presence of two Lgh plastome haplotypes which will help to advance phylogenetic and evolutionary studies, not only specifically for Ludwigia, but also the Onagraceae family and Myrtales order. To enhance the robustness of our findings, a larger dataset of chloroplast genomes would be beneficial.
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Section: Archaeology ; Topics: Archaeology, History
First evidence of a Palaeolithic occupation of the Po plain in Piedmont: the case of Trino (north-western Italy)
10.24072/pcjournal.551 - Peer Community Journal, Volume 5 (2025), article no. e42.
Get full text PDFThe Trino hill is an isolated relief located in north-western Italy, close to Trino municipality. The hill was subject of multidisciplinary studies during the 1970s, when, because of quarrying and agricultural activities, five concentrations of lithic artefacts were recognized and referred to a Palaeolithic occupation of the area. During the 1980s and the 1990s, surface collections continued, but the lithic finds have never been subject of specific studies. Even if most of the lithic assemblages count a few lithic implements, four collection areas (3, 13 E, 13 W and 14) have significative lithic assemblages, representing the most important evidence of a Palaeolithic frequentation of the Po plain in north-western Italy. The present work, in the limits imposed by a surface and not systematic collection, propose a technological study of the lithic artefacts from the Trino hill, with the aim to define the main features of the technological behaviour of the human groups that occupied the area. The results obtained allow to clearly identify a Middle Palaeolithic occupation of the Trino hill, characterized by the exploitation of vein quartz and other local raw materials; allochthonous varieties of chert were used in the next frequentation phases to produce blades and bladelets. Even if part of the laminar production can be referred to Neolithic, most of that remains of indeterminate chronology and could be the result of both an Upper Palaeolithic and Neolithic human presence. The systematic and inclusive approach to the study of the Paleolithic of the Piedmont region proposed here has made it possible to obtain a first and realistic overview of the Paleolithic of the region. The methods used for the technological study are similar to those used for other sites in the region and have made it possible to link Trino's surface collections with data from sites systematically investigated in recent years.
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Section: Animal Science ; Topics: Agricultural sciences, Computer sciences
A pipeline with pre-processing options to detect behaviour from accelerometer data using Machine Learning tested on dairy goats
10.24072/pcjournal.545 - Peer Community Journal, Volume 5 (2025), article no. e41.
Get full text PDFAnimal behaviour is a significant component in the evaluation of animal welfare. Conducting continuous observations of animal behaviour is a time-consuming task and may not be feasible over extended periods for all animals. Thus, new technologies like sensors and cameras can be used to assess individual behaviour continuously. Combined with Artificial Intelligence (AI), accelerometers are promising to continuously and individually detect animal behaviour from the acceleration signals and characteristics of the behaviour. Such devices are commercialised for cattle but they have not been widely developed for small ruminants. Being able to automatically monitor behaviour at an individual scale represents a crucial step towards an objective assessment of animal welfare. This paper aims to present the use of a pipeline called ACT4Behav (Accelerometer-based Classification Tool for identifying Behaviours) involving a supervised classification algorithm for automatically characterising specific animal behaviours using accelerometer data, and to explore the best pre-processing steps for each behaviour. This algorithm is designed to be general-purpose and applicable with different species, behaviours and accelerometers. This paper presents the use of this pipeline with eight indoor-housed goats equipped with ear-mounted accelerometers. Rumination, head in the feeder, standing and lying behaviours were continuously sampled from camera recordings for 11 consecutive hours for each goat using The Observer software. The developed pipeline was used to identify optimal descriptive features and data preparation steps for each prediction model, one for each behaviour. A sensitivity analysis was conducted to assess the impact of the processing techniques and parameter value on the resulting AUC (Area Under the Curve) score, used as the performance score of the models. This analysis allowed the identification of the adequate filtering techniques, time-window segmentations, application of various transformations to raw data, and feature selections for each behaviour. Tuning the data pre-processing for each behaviour enhanced the ability to predict rumination (AUC score=0.800), head in the feeder (AUC score=0.819), lying (AUC score=0.829) and standing (AUC score=0.823) behaviours. When the application of the models on goats that did not participate in the training was tested by training the models on six goats and testing it on the two other goats, the AUC score for the four behaviours decreased (0.644, 0.733, 0.741 and 0.749 respectively for rumination, head in the feeder, lying and standing).
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Section: Evolutionary Biology ; Topics: Evolution, Genetics/genomics, Population biology
On the potential for GWAS with phenotypic population means and allele-frequency data (popGWAS)
10.24072/pcjournal.544 - Peer Community Journal, Volume 5 (2025), article no. e40.
Get full text PDFIt is vital to understand the genomic basis of differences in ecologically important traits if we are to understand the impact of global change on biodiversity and enhance our ability for targeted intervention. This study explores the potential of a novel genome-wide association study (GWAS) approach for identifying loci underlying quantitative polygenic traits in natural populations, based on phenotypic population means and genome-wide allele frequency data as obtained e.g. by PoolSeq approaches. Extensive population genetic forward simulations demonstrate that the approach is generally effective for oligogenic and moderately polygenic traits and relatively insensitive to low heritability. However, applicability is limited for highly polygenic architectures and pronounced population structure. The required sample size is moderate with very good results being obtained already for a few dozen populations scored. When combined with machine learning for feature selection, the method performs very well in predicting population means. The data efficiency of the method, particularly when using pooled sequencing and bulk phenotyping, makes GWAS studies more accessible for research in biodiversity genomics. Moreover, in a direct comparison to individual based GWAS, the proposed method performed constistently better with regard to the number of true positive loci identified and prediction accuracy. Overall, this study highlights the promise of popGWAS for dissecting the genetic basis of complex traits in natural populations.
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