The pulse of the tree is under genetic control: eucalyptus as a case study

The pulse of the tree (diurnal cycle of stem radius fluctuations) has been widely studied as a way of analyzing tree responses to the environment, including the phenotypic plasticity of tree–water relationships in particular. However, the genetic basis of this daily phenotype and its interplay with the environment remain largely unexplored. We characterized the genetic and environmental determinants of this response, by monitoring daily stem radius fluctuation (dSRF) on 210 trees from a Eucalyptus urophylla × E. grandis full‐sib family over 2 years. The dSRF signal was broken down into hydraulic capacitance, assessed as the daily amplitude of shrinkage (DA), and net growth, estimated as the change in maximum radius between two consecutive days (ΔR). The environmental determinants of these two traits were clearly different: DA was positively correlated with atmospheric variables relating to water demand, while ΔR was associated with soil water content. The heritability for these two traits ranged from low to moderate over time, revealing a time‐dependent or environment‐dependent complex genetic determinism. We identified 686 and 384 daily quantitative trait loci (QTL) representing 32 and 31 QTL regions for DA and ΔR, respectively. The identification of gene networks underlying the 27 major genomics regions for both traits generated additional hypotheses concerning the biological mechanisms involved in response to water demand and supply. This study highlights that environmentally induced changes in daily stem radius fluctuation are genetically controlled in trees and suggests that these daily responses integrated over time shape the genetic architecture of mature traits.     

Disentangling the assembly mechanisms of ant cuticular bacterial communities of two Amazonian ant species sharing a common arboreal nest

Bacteria living on the cuticle of ants are generally studied for their protective role against pathogens, especially in the clade of fungus‐growing ants. However, little is known regarding the diversity of cuticular bacteria in other ant host species, as well as the mechanisms leading to the composition of these communities. Here, we used 16S rRNA gene amplicon sequencing to study the influence of host species, species interactions and the pool of bacteria from the environment on the assembly of cuticular bacterial communities on two phylogenetically distant Amazonian ant species that frequently nest together inside the roots system of epiphytic plants, Camponotus femoratus and Crematogaster levior. Our results show that (a) the vast majority of the bacterial community on the cuticle is shared with the nest, suggesting that most bacteria on the cuticle are acquired through environmental acquisition, (b) 5.2% and 2.0% of operational taxonomic units (OTUs) are respectively specific to Ca. femoratus and Cr. levior, probably representing their respective core cuticular bacterial community, and (c) 3.6% of OTUs are shared between the two ant species. Additionally, mass spectrometry metabolomics analysis of metabolites on the cuticle of ants, which excludes the detection of cuticular hydrocarbons produced by the host, were conducted to evaluate correlations among bacterial OTUs and m/z ion mass. Although some positive and negative correlations are found, the cuticular chemical composition was weakly species‐specific, suggesting that cuticular bacterial communities are prominently environmentally acquired. Overall, our results suggest the environment is the dominant source of bacteria found on the cuticle of ants.     

The phylogenetic range of bacterial and viral pathogens of vertebrates

Many major human pathogens are multihost pathogens, able to infect other vertebrate species. Describing the general patterns of host–pathogen associations across pathogen taxa is therefore important to understand risk factors for human disease emergence. However, there is a lack of comprehensive curated databases for this purpose, with most previous efforts focusing on viruses. Here, we report the largest manually compiled host–pathogen association database, covering 2,595 bacteria and viruses infecting 2,656 vertebrate hosts. We also build a tree for host species using nine mitochondrial genes, giving a quantitative measure of the phylogenetic similarity of hosts. We find that the majority of bacteria and viruses are specialists infecting only a single host species, with bacteria having a significantly higher proportion of specialists compared to viruses. Conversely, multihost viruses have a more restricted host range than multihost bacteria. We perform multiple analyses of factors associated with pathogen richness per host species and the pathogen traits associated with greater host range and zoonotic potential. We show that factors previously identified as important for zoonotic potential in viruses—such as phylogenetic range, research effort, and being vector‐borne—are also predictive in bacteria. We find that the fraction of pathogens shared between two hosts decreases with the phylogenetic distance between them. Our results suggest that host phylogenetic similarity is the primary factor for host‐switching in pathogens.     

Reproductives and eggs trigger worker vibration in a subterranean termite

In insect societies, the presence of reproductives or eggs has been shown to shape several biological traits in the colony members. Social interactions are one of these traits that involve modification of the communication system of the entire colony. Many studies described the role of chemical compounds and dominance behaviors in the presence of reproductive but vibratory behaviors received very few investigations. Yet, vibratory behaviors are ideal candidates, particularly for subterranean species like termites, as they could be quickly transmitted through the substrate and could be very diversified (origin, modulation). Here, we investigated whether the presence of reproductives/eggs affects the vibratory behavior (body‐shaking) of workers in the subterranean termite Reticulitermes flavipes. Our results reveal that the presence of reproductives or eggs triggers an increase of workers' body‐shaking, independent of their colony of origin after 24 hr. We hypothesize that vibratory communication could be used to transfer information about the presence of reproductives and eggs to the entire colony, suggesting that vibratory behaviors could serve as an important yet neglected mediator of social regulation.     

Contrasting Gene Decay in Subterranean Vertebrates: Insights from Cavefishes and Fossorial Mammals

Evolution sometimes proceeds by loss, especially when structures and genes become dispensable after an environmental shift relaxes functional constraints. Subterranean vertebrates are outstanding models to analyze this process, and gene decay can serve as a readout. We sought to understand some general principles on the extent and tempo of the decay of genes involved in vision, circadian clock, and pigmentation in cavefishes. The analysis of the genomes of two Cuban species belonging to the genus Lucifuga provided evidence for the largest loss of eye-specific genes and nonvisual opsin genes reported so far in cavefishes. Comparisons with a recently evolved cave population of Astyanax mexicanus and three species belonging to the Chinese tetraploid genus Sinocyclocheilus revealed the combined effects of the level of eye regression, time, and genome ploidy on eye-specific gene pseudogenization. The limited extent of gene decay in all these cavefishes and the very small number of loss-of-function mutations per pseudogene suggest that their eye degeneration may not be very ancient, ranging from early to late Pleistocene. This is in sharp contrast with the identification of several vision genes carrying many loss-of-function mutations in ancient fossorial mammals, further suggesting that blind fishes cannot thrive more than a few million years in cave ecosystems.     

Convolutional neural networks improve species distribution modelling by capturing the spatial structure of the environment

Convolutional Neural Networks (CNNs) are statistical models suited for learning complex visual patterns. In the context of Species Distribution Models (SDM) and in line with predictions of landscape ecology and island biogeography, CNN could grasp how local landscape structure affects prediction of species occurrence in SDMs. The prediction can thus reflect the signatures of entangled ecological processes. Although previous machine-learning based SDMs can learn complex influences of environmental predictors, they cannot acknowledge the influence of environmental structure in local landscapes (hence denoted “punctual models”). In this study, we applied CNNs to a large dataset of plant occurrences in France (GBIF), on a large taxonomical scale, to predict ranked relative probability of species (by joint learning) to any geographical position. We examined the way local environmental landscapes improve prediction by performing alternative CNN models deprived of information on landscape heterogeneity and structure (“ablation experiments”). We found that the landscape structure around location crucially contributed to improve predictive performance of CNN-SDMs. CNN models can classify the predicted distributions of many species, as other joint modelling approaches, but they further prove efficient in identifying the influence of local environmental landscapes. CNN can then represent signatures of spatially structured environmental drivers. The prediction gain is noticeable for rare species, which open promising perspectives for biodiversity monitoring and conservation strategies. Therefore, the approach is of both theoretical and practical interest. We discuss the way to test hypotheses on the patterns learnt by CNN, which should be essential for further interpretation of the ecological processes at play.