PhylteR: Efficient Identification of Outlier Sequences in Phylogenomic Datasets.

In phylogenomics, incongruences between gene trees, resulting from both artifactual and biological reasons, can decrease the signal-to-noise ratio and complicate species tree inference. The amount of data handled today in classical phylogenomic analyses precludes manual error detection and removal. However, a simple and efficient way to automate the identification of outliers from a collection of gene trees is still missing. Here, we present PhylteR, a method that allows rapid and accurate detection of outlier sequences in phylogenomic datasets, i.e. species from individual gene trees that do not follow the general trend. PhylteR relies on DISTATIS, an extension of multidimensional scaling to 3 dimensions to compare multiple distance matrices at once. In PhylteR, these distance matrices extracted from individual gene phylogenies represent evolutionary distances between species according to each gene. On simulated datasets, we show that PhylteR identifies outliers with more sensitivity and precision than a comparable existing method. We also show that PhylteR is not sensitive to ILS-induced incongruences, which is a desirable feature. On a biological dataset of 14,463 genes for 53 species previously assembled for Carnivora phylogenomics, we show (i) that PhylteR identifies as outliers sequences that can be considered as such by other means, and (ii) that the removal of these sequences improves the concordance between the gene trees and the species tree. Thanks to the generation of numerous graphical outputs, PhylteR also allows for the rapid and easy visual characterization of the dataset at hand, thus aiding in the precise identification of errors. PhylteR is distributed as an R package on CRAN and as containerized versions (docker and singularity).

Larval density in the invasive Drosophila suzukii: Immediate and delayed effects on life-history traits.

The effects of density are key in determining population dynamics, since they can positively or negatively affect the fitness of individuals. These effects have great relevance for polyphagous insects for which immature stages develop within a single site of finite feeding resources. Drosophila suzukii is a crop pest that induces severe economic losses for agricultural production; however, little is known about the effects of density on its life-history traits. In the present study, we (i) investigated the egg distribution resulting from females' egg-laying strategy and (ii) tested the immediate (on immatures) and delayed (on adults) effects of larval density on emergence rate, development time, potential fecundity, and adult size. The density used varied in a range between 1 and 50 larvae. We showed that 44.27% of the blueberries used for the oviposition assay contained between 1 and 11 eggs in aggregates. The high experimental density (50 larvae) has no immediate effect in the emergence rate but has effect on larval developmental time. This trait was involved in a trade-off with adult life-history traits: The time of larval development was reduced as larval density increased, but smaller and less fertile females were produced. Our results clearly highlight the consequences of larval crowding on the juveniles and adults of this fly.

rbioacc: An R-package to analyze toxicokinetic data.

The R-package rbioacc allows to analyse experimental data from bioaccumulation tests where organisms are exposed to a chemical (exposure) then put into clean media (depuration). Internal concentrations are measured over time during the experiment. rbioacc provides turnkey functions to visualise and analyse such data. Under a Bayesian framework, rbioacc fits a generic one-compartment toxicokinetic model built from the data. It provides TK parameter estimates (uptake and elimination rates) and standard bioaccumulation metrics. All parameter estimates, bioaccumulation metrics and predictions of internal concentrations are delivered with their uncertainty. Bioaccumulation metrics are provided in support of environmental risk assessment, in full compliance with regulatory requirements required to approve market release of chemical substances. This paper provides worked examples of the use of rbioacc from data collected through standard bioaccumulation tests, publicly available within the scientific literature. These examples constitute step-by-step user-guides to analyse any new data set, uploaded in the right format.

Taking full advantage of modelling to better assess environmental risk due to xenobiotics-the all-in-one facility MOSAIC.

In the European Union, more than 100,000 man-made chemical substances are awaiting an environmental risk assessment (ERA). Simultaneously, ERA of these chemicals has now entered a new era requiring determination of risks for physiologically diverse species exposed to several chemicals, often in mixtures. Additionally, recent recommendations from regulatory bodies underline a crucial need for the use of mechanistic effect models, allowing assessments that are not only ecologically relevant, but also more integrative, consistent and efficient. At the individual level, toxicokinetic-toxicodynamic (TKTD) models are particularly encouraged for the regulatory assessment of pesticide-related risks on aquatic organisms. In this paper, we first briefly present a classical dose-response model to showcase the on-line MOSAIC tool, which offers all necessary services in a turnkey web platform, whatever the type of data analyzed. Secondly, we focus on the necessity to account for the time-dimension of the exposure by illustrating how MOSAIC can support a robust calculation of bioaccumulation metrics. Finally, we show how MOSAIC can be of valuable help to fully complete the EFSA workflow regarding the use of TKTD models, especially with GUTS models, providing a user-friendly interface for calibrating, validating and predicting survival over time under any time-variable exposure scenario of interest. Our conclusion proposes a few lines of thought for an easier use of modelling in ERA.

Sex-specific actuarial and reproductive senescence in zoo-housed tiger (Panthera tigris): The importance of sub-species for conservation.

A fifth of all known species are currently classified as threatened in the wild: the rate of biodiversity loss is rapid, continuous, and mostly due to anthropogenic activities. To slow down this decline, the accurate estimation of demographic parameters for threatened species is critical. With this aim, zoo institutions play an important role, giving access to data on zoo-housed animals, which aids researchers working on species life-history traits and intrinsic factors influencing the fitness of both sexes, such as age. While tigers (Panthera tigris) are particularly threatened in their natural environment, few of their demographic parameters have been determined because of their solitary and elusive nature as well as low population density. Using individual-based information for more than 9200 tigers (from 1938 to 2018) recorded in the International Tiger Studbook 2018, we aimed to determine sub-species and sex-specific variability of survival and reproductive parameters with age. No significant sex-difference in actuarial senescence (i.e., decline of survival probabilities with age) was observed but males tended to have a higher juvenile mortality and a faster senescence than females. Reproductive senescence (i.e., decline of reproductive parameters with age) was more pronounced in females than males. Moreover, we observed sub-species-specific variation in mortality and reproductive patterns, pointing out the necessity to consider them independently for conservation goals. Our findings can provide meaningful improvements to the husbandry of zoo-housed tigers, emphasizing the importance of adult breeding females of 7-9 years-old to control zoo-housed population size, but also providing accurate demographic estimates, crucial to set up effective conservation plans.

Lifespan decreases with proportion of sons in males but not females of zoo-housed tigers and lemurs.

Several studies have shown higher costs of rearing sons than daughters in mammals where males are larger than females. These studies typically focus on females by examining how the offspring sex ratio during a single reproductive event affected mothers' subsequent reproduction or survival probability. Here, we examine relationships between offspring sex ratio during single or multiple reproductive events and several survival metrics in mothers and fathers, using data from zoo-housed tigers (Panthera tigris) and ruffed lemurs (Varecia sp.). Our analyses failed to reveal an overall cost of reproduction or a higher cost of sons to mothers. In male ruffed lemurs, the proportion of sons produced during early life (before 10 years old) was negatively correlated with lifespan later in life. In tigers, males with a higher proportion of sons during their lifetime had shorter lifespans. One likely mechanism is the difference in testosterone levels between males: a high concentration of testosterone can increase the proportion of sons and compromise immune function. Our results suggest studies in wild populations should address the outstanding challenge of understanding consequences of sex allocation for males, and open an opportunity to predict lifespan in an applied conservation context.

Pollen limitation as a main driver of fruiting dynamics in oak populations.

In many perennial wind-pollinated plants, the dynamics of seed production is commonly known to be highly fluctuating from year to year and synchronised among individuals within populations. The proximate causes of such seeding dynamics, called masting, are still poorly understood in oak species that are widespread in the northern hemisphere, and whose fruiting dynamics dramatically impacts forest regeneration and biodiversity. Combining long-term surveys of oak airborne pollen amount and acorn production over large-scale field networks in temperate areas, and a mechanistic modelling approach, we found that the pollen dynamics is the key driver of oak masting. Mechanisms at play involved both internal resource allocation to pollen production synchronised among trees and spring weather conditions affecting the amount of airborne pollen available for reproduction. The sensitivity of airborne pollen to weather conditions might make oak masting and its ecological consequences highly sensitive to climate change.

DRomics: A Turnkey Tool to Support the Use of the Dose-Response Framework for Omics Data in Ecological Risk Assessment.

Omics approaches (e.g., transcriptomics, metabolomics) are promising for ecological risk assessment (ERA) since they provide mechanistic information and early warning signals. A crucial step in the analysis of omics data is the modeling of concentration-dependency which may have different trends including monotonic (e.g., linear, exponential) or biphasic (e.g., U shape, bell shape) forms. The diversity of responses raises challenges concerning detection and modeling of significant responses and effect concentration (EC) derivation. Furthermore, handling high-throughput data sets is time-consuming and requires effective and automated processing routines. Thus, we developed an open source tool (DRomics, available as an R-package and as a web-based service) which, after elimination of molecular responses (e.g., gene expressions from microarrays) with no concentration-dependency and/or high variability, identifies the best model for concentration-response curve description. Subsequently, an EC (e.g., a benchmark dose) is estimated from each curve, and curves are classified based on their model parameters. This tool is especially dedicated to manage data obtained from an experimental design favoring a great number of tested doses rather than a great number of replicates and also to handle properly monotonic and biphasic trends. The tool finally provides restitution for a table of results that can be directly used to perform ERA approaches.

Maternal reproductive senescence shapes the fitness consequences of the parental age difference in ruffed lemurs.

In humans, pronounced age differences between parents have deleterious fitness consequences. In particular, the number of children is lower when mothers are much older than fathers. However, previous analyses failed to disentangle the influence of differential parental age per se from a direct age effect of each parent. In this study, we analyse the fitness consequences of both parental age and parental age differences on litter size and offspring survival in two closely related species of lemurs living in captivity. As captive lemurs do not choose their reproductive partner, we were able to measure litter size and offspring survival across breeding pairs showing a wide range of parental age differences. However, we demonstrated that the effect of the parental age difference on litter size was fully accounted for by female reproductive senescence because females mating with much younger males were old females. On the other hand, both parental age difference and female reproductive senescence influenced offspring survival. Our results emphasize the importance of teasing apart the effect of parental reproductive senescence when investigating the health and fitness consequences of parental age differences and also provide new insights for conservation programmes of endangered species.

MareyMap Online: A User-Friendly Web Application and Database Service for Estimating Recombination Rates Using Physical and Genetic Maps.

Given the importance of meiotic recombination in biology, there is a need to develop robust methods to estimate meiotic recombination rates. A popular approach, called the Marey map approach, relies on comparing genetic and physical maps of a chromosome to estimate local recombination rates. In the past, we have implemented this approach in an R package called MareyMap, which includes many functionalities useful to get reliable recombination rate estimates in a semi-automated way. MareyMap has been used repeatedly in studies looking at the effect of recombination on genome evolution. Here, we propose a simpler user-friendly web service version of MareyMap, called MareyMap Online, which allows a user to get recombination rates from her/his own data or from a publicly available database that we offer in a few clicks. When the analysis is done, the user is asked whether her/his curated data can be placed in the database and shared with other users, which we hope will make meta-analysis on recombination rates including many species easy in the future.

Fruiting Strategies of Perennial Plants: A Resource Budget Model to Couple Mast Seeding to Pollination Efficiency and Resource Allocation Strategies.

Masting, a breeding strategy common in perennial plants, is defined by seed production that is highly variable over years and synchronized at the population level. Resource budget models (RBMs) proposed that masting relies on two processes: (i) the depletion of plant reserves following high fruiting levels, which leads to marked temporal fluctuations in fruiting; and (ii) outcross pollination that synchronizes seed crops among neighboring trees. We revisited the RBM approach to examine the extent to which masting could be impacted by the degree of pollination efficiency, by taking into account various logistic relationships between pollination success and pollen availability. To link masting to other reproductive traits, we split the reserve depletion coefficient into three biological parameters related to resource allocation strategies for flowering and fruiting. While outcross pollination is considered to be the key mechanism that synchronizes fruiting in RBMs, our model counterintuitively showed that intense masting should arise under low-efficiency pollination. When pollination is very efficient, medium-level masting may occur, provided that the costs of female flowering (relative to pollen production) and of fruiting (maximum fruit set and fruit size) are both very high. Our work highlights the powerful framework of RBMs, which include explicit biological parameters, to link fruiting dynamics to various reproductive traits and to provide new insights into the reproductive strategies of perennial plants.

Unknown age in health disorders: A method to account for its cumulative effect and an application to feline viruses interactions.

Parasite interactions have been widely evidenced experimentally but field studies remain rare. Such studies are essential to detect interactions of interest and access (co)infection probabilities but face methodological obstacles. Confounding factors can create statistical associations, i.e. false parasite interactions. Among them, host age is a crucial covariate. It influences host exposition and susceptibility to many infections, and has a mechanical effect, older individuals being more at risk because of a longer exposure time. However, age is difficult to estimate in natural populations. Hence, one should be able to deal at least with its cumulative effect. Using a SI type dynamic model, we showed that the cumulative effect of age can generate false interactions theoretically (deterministic modeling) and with a real dataset of feline viruses (stochastic modeling). The risk to wrongly conclude to an association was maximal when parasites induced long-lasting antibodies and had similar forces of infection. We then proposed a method to correct for this effect (and for other potentially confounding shared risk factors) and made it available in a new R package, Interatrix. We also applied the correction to the feline viruses. It offers a way to account for an often neglected confounding factor and should help identifying parasite interactions in the field, a necessary step towards a better understanding of their mechanisms and consequences.