156 research outputs found
Inferring epidemiological links from deep sequencing data: a statistical learning approach for human, animal and plant diseases
Pathogen sequence data have been exploited to infer who infected whom, by using empirical and model-based approaches. Most of these approaches exploit one pathogen sequence per infected host (e.g. individual, household, field). However, modern sequencing techniques can reveal the polymorphic nature of within-host populations of pathogens. Thus, these techniques provide a subsample of the pathogen variants that were present in the host at the sampling time. Such data are expected to give more insight on epidemiological links than a single sequence per host. In general, a mechanistic viewpoint to transmission and micro-evolution has been followed to infer epidemiological links from these data. Here, we investigate an alternative approach grounded on statistical learning. The idea consists of learning the structure of epidemiological links with a pseudo-evolutionary model applied to training data obtained from contact tracing, for example, and using this initial stage to infer links for the whole dataset. Such an approach has the potential to be particularly valuable in the case of a risk of erroneous mechanistic assumptions, it is sufficiently parsimonious to allow the handling of big datasets in the future, and it is versatile enough to be applied to very different contexts from animal, human and plant epidemiology. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'. This issue is linked with the subsequent theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'
Yield of varieties of Cucurbita pepo preimmunized with mild strains of Papaya ringspot virus - type W and Zucchini yellow mosaic virus
Inheritance analysis and identification of SNP markers associated with ZYMV resistance in Cucurbita pepo
[EN] Cucurbit crops are economically important worldwide. One of the most serious threats to cucurbit production is Zucchini yellow mosaic virus (ZYMV). Several resistant accessions were identified in Cucurbita moschata and their resistance was introgressed into Cucurbita pepo. However, the mode of inheritance of ZYMV resistance in C. pepo presents a great challenge to attempts at introgressing resistance into elite germplasm. The main goal of this work was to analyze the inheritance of ZYMV resistance and to identify markers associated with genes conferring resistance. An Illumina GoldenGate assay allowed us to assess polymorphism among nine squash genotypes and to discover six polymorphic single-nucleotide polymorphisms (SNPs) between two near-isogenic lines, "True French" (susceptible to ZYMV) and Accession 381e (resistant to ZYMV). Two F-2 and three BC1 populations obtained from crossing the ZYMV-resistant Accession 381e with two susceptible ones, the zucchini True French and the cocozelle "San Pasquale," were assayed for ZYMV resistance. Molecular analysis revealed an approximately 90% association between SNP1 and resistance, which was confirmed using High Resolution Melt (HRM) and a CAPS marker. Co-segregation up to 72% in populations segregating for resistance was observed for two other SNP markers that could be potentially linked to genes involved in resistance expression. A functional prediction of proteins involved in the resistance response was performed on genome scaffolds containing the three SNPs of interest. Indeed, 16 full-length pathogen recognition genes (PRGs) were identified around the three SNP markers. In particular, we discovered that two nucleotide-binding site leucine-rich repeat (NBS-LRR) protein-encoding genes were located near the SNP1 marker. The investigation of ZYMV resistance in squash populations and the genomic analysis performed in this work could be useful for better directing the introgression of disease resistance into elite C. pepo germplasm.This work was supported by the Ministry of University and Research (GenHORT project).Capuozzo, C.; Formisano, G.; Iovieno, P.; Andolfo, G.; Tomassoli, L.; Barbella, M.; Picó Sirvent, MB.... (2017). Inheritance analysis and identification of SNP markers associated with ZYMV resistance in Cucurbita pepo. Molecular Breeding. 37(8). https://doi.org/10.1007/s11032-017-0698-5S378Addinsoft (2007) XLSTAT, Analyse de données et statistique avec MS Excel. Addinsoft, NYAndolfo G, Ercolano MR (2015) Plant innate immunity multicomponent model. Front Plant Sci 6:987Andolfo G, Sanseverino W, Rombauts S et al (2013) Overview of tomato (Solanum lycopersicum) candidate pathogen recognition genes reveals important Solanum R locus dynamics. 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Behavioral responses of terrestrial mammals to COVID-19 lockdowns
COVID-19 lockdowns in early 2020 reduced human mobility, providing an opportunity to disentangle its effects on animals from those of landscape modifications. Using GPS data, we compared movements and road avoidance of 2300 terrestrial mammals (43 species) during the lockdowns to the same period in 2019. Individual responses were variable with no change in average movements or road avoidance behavior, likely due to variable lockdown conditions. However, under strict lockdowns 10-day 95th percentile displacements increased by 73%, suggesting increased landscape permeability. Animals' 1-hour 95th percentile displacements declined by 12% and animals were 36% closer to roads in areas of high human footprint, indicating reduced avoidance during lockdowns. Overall, lockdowns rapidly altered some spatial behaviors, highlighting variable but substantial impacts of human mobility on wildlife worldwide.acceptedVersio
Behavioral responses of terrestrial mammals to COVID-19 lockdowns
COVID-19 lockdowns in early 2020 reduced human mobility, providing an opportunity to disentangle its effects on animals from those of landscape modifications. Using GPS data, we compared movements and road avoidance of 2300 terrestrial mammals (43 species) during the lockdowns to the same period in 2019. Individual responses were variable with no change in average movements or road avoidance behavior, likely due to variable lockdown conditions. However, under strict lockdowns 10-day 95th percentile displacements increased by 73%, suggesting increased landscape permeability. Animals' 1-hour 95th percentile displacements declined by 12% and animals were 36% closer to roads in areas of high human footprint, indicating reduced avoidance during lockdowns. Overall, lockdowns rapidly altered some spatial behaviors, highlighting variable but substantial impacts of human mobility on wildlife worldwide.acceptedVersio
Captive-born collared peccary (Pecari tajacu, Tayassuidae) fails to discriminate between predator and non-predator models
Captive animals may lose the ability to recognize their natural predators, making conservation programs more susceptible to
failure if such animals are released into the wild. Collared peccaries are American tayassuids that are vulnerable to local
extinction in certain areas, and conservation programs are being conducted. Captive-born peccaries are intended for release into
the wild in Minas Gerais state, southeastern Brazil. In this study, we tested the ability of two groups of captive-born collared
peccaries to recognize their predators and if they were habituated to humans. Recognition tests were performed using models of
predators (canids and felids) and non-predators animals, as well as control objects, such as a plastic chair; a human was also
presented to the peccaries, and tested as a separate stimulus. Anti-predator defensive responses such as fleeing and threatening
displayswere not observed in response to predator models. Predator detection behaviors both from visual and olfactory cues were displayed, although they were not specifically targeted at predator models. These results indicate that collared peccaries were unable to recognize model predators. Habituation effects, particularly on anti-predator behaviors, were observed both with a 1-h model presentation and across testing days. Behavioral responses to humans did not differ from those to other models. Thus, if these animals were to be released into the wild, they should undergo anti-predator training sessions to enhance their chances of survival
NEOTROPICAL XENARTHRANS: a data set of occurrence of xenarthran species in the Neotropics
Xenarthrans – anteaters, sloths, and armadillos – have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with 24 domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, ten anteaters, and six sloths. Our dataset includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data-paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the south of the USA, Mexico, and Caribbean countries at the northern portion of the Neotropics, to its austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records (n=5,941), and Cyclopes sp. has the fewest (n=240). The armadillo species with the most data is Dasypus novemcinctus (n=11,588), and the least recorded for Calyptophractus retusus (n=33). With regards to sloth species, Bradypus variegatus has the most records (n=962), and Bradypus pygmaeus has the fewest (n=12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other datasets of Neotropical Series which will become available very soon (i.e. Neotropical Carnivores, Neotropical Invasive Mammals, and Neotropical Hunters and Dogs). Therefore, studies on trophic cascades, hunting pressure, habitat loss, fragmentation effects, species invasion, and climate change effects will be possible with the Neotropical Xenarthrans dataset
Assessing parallel gene histories in viral genomes
Background: The increasing abundance of sequence data has exacerbated a long known problem: gene trees and species trees for the same terminal taxa are often incongruent. Indeed, genes within a genome have not all followed the same evolutionary path due to events such as incomplete lineage sorting, horizontal gene transfer, gene duplication and deletion, or recombination. Considering conflicts between gene trees as an obstacle, numerous methods have been developed to deal with these incongruences and to reconstruct consensus evolutionary histories of species despite the heterogeneity in the history of their genes. However, inconsistencies can also be seen as a source of information about the specific evolutionary processes that have shaped genomes.
Results: The goal of the approach here proposed is to exploit this conflicting information: we have compiled eleven variables describing phylogenetic relationships and evolutionary pressures and submitted them to dimensionality reduction techniques to identify genes with similar evolutionary histories. To illustrate the applicability of the method, we have chosen two viral datasets, namely papillomaviruses and Turnip mosaic virus (TuMV) isolates, largely dissimilar in genome, evolutionary distance and biology. Our method pinpoints viral genes with common evolutionary patterns. In the case of papillomaviruses, gene clusters match well our knowledge on viral biology and life cycle, illustrating the potential of our approach. For the less known TuMV, our results trigger new hypotheses about viral evolution and gene interaction.
Conclusions: The approach here presented allows turning phylogenetic inconsistencies into evolutionary information, detecting gene assemblies with similar histories, and could be a powerful tool for comparative pathogenomics.IGB was funded by the disappeared Spanish Ministry for Science and Innovation (CGL2010-16713). Work in Valencia was supported by grant BFU2012-30805 from the Spanish Ministry of Economy and Competitiveness (MINECO) to SFE. BMC is the recipient of an IDIBELL PhD fellowship.Mengual-Chuliá, B.; Bedhomme, S.; Lafforgue, G.; Elena Fito, SF.; Bravo, IG. (2016). Assessing parallel gene histories in viral genomes. BMC Evolutionary Biology. 16:1-15. https://doi.org/10.1186/s12862-016-0605-4S11516Hess J, Goldman N. Addressing inter-gene heterogeneity in maximum likelihood phylogenomic analysis: Yeasts revisited. PLoS ONE. 2011;6:e22783.Salichos L, Rokas A. Inferring ancient divergences requires genes with strong phylogenetic signals. 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Climate determines transmission hotspots of Polycystic Echinococcosis, a life-threatening zoonotic disease, across Pan-Amazonia
Polycystic Echinococcosis (PE), a neglected life-threatening zoonotic disease caused by the cestode is endemic in the Amazon. Despite being treatable, PE reaches a case fatality rate of around 29% due to late or missed diagnosis. PE is sustained in Pan-Amazonia by a complex sylvatic cycle. The hunting of its infected intermediate hosts (especially the lowland paca ) enables the disease to further transmit to humans, when their viscera are improperly handled. In this study, we compiled a unique dataset of host occurrences (~86000 records) and disease infections (~400 cases) covering the entire Pan-Amazonia and employed different modeling and statistical tools to unveil the spatial distribution of PE's key animal hosts. Subsequently, we derived a set of ecological, environmental, climatic, and hunting covariates that potentially act as transmission risk factors and used them as predictors of two independent Maximum Entropy models, one for animal infections and one for human infections. Our findings indicate that temperature stability promotes the sylvatic circulation of the disease. Additionally, we show how El Niño-Southern Oscillation (ENSO) extreme events disrupt hunting patterns throughout Pan-Amazonia, ultimately affecting the probability of spillover. In a scenario where climate extremes are projected to intensify, climate change at regional level appears to be indirectly driving the spillover of . These results hold substantial implications for a wide range of zoonoses acquired at the wildlife-human interface for which transmission is related to the manipulation and consumption of wild meat, underscoring the pressing need for enhanced awareness and intervention strategies
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