Identification of Avramr1 from Phytophthora infestans using long read and cDNA pathogen-enrichment sequencing (PenSeq)

Potato late blight, caused by the oomycete pathogen Phytophthora infestans, significantly hampers potato production. Recently, a new Resistance to Phytophthora infestans (Rpi) gene, Rpi-amr1, was cloned from a wild Solanum species, Solanum americanum. Identification of the corresponding recognized effector (Avirulence or Avr) genes from P. infestans is key to elucidating their naturally occurring sequence variation, which in turn informs the potential durability of the cognate late blight resistance. To identify the P. infestans effector recognized by Rpi-amr1, we screened available RXLR effector libraries and used long read and cDNA pathogen-enrichment sequencing (PenSeq) on four P. infestans isolates to explore the untested effectors. Using single-molecule real-time sequencing (SMRT) and cDNA PenSeq, we identified 47 highly expressed effectors from P. infestans, including PITG_07569, which triggers a highly specific cell death response when transiently coexpressed with Rpi-amr1 in Nicotiana benthamiana, suggesting that PITG_07569 is Avramr1. Here we demonstrate that long read and cDNA PenSeq enables the identification of full-length RXLR effector families and their expression profile. This study has revealed key insights into the evolution and polymorphism of a complex RXLR effector family that is associated with the recognition by Rpi-amr1.     

Mixed company: a framework for understanding the composition and organization of mixed‐species animal groups

Mixed‐species animal groups (MSGs) are widely acknowledged to increase predator avoidance and foraging efficiency, among other benefits, and thereby increase participants' fitness. Diversity in MSG composition ranges from two to 70 species of very similar or completely different phenotypes. Yet consistency in organization is also observable in that one or a few species usually have disproportionate importance for MSG formation and/or maintenance. We propose a two‐dimensional framework for understanding this diversity and consistency, concentrating on the types of interactions possible between two individuals, usually of different species. One axis represents the similarity of benefit types traded between the individuals, while the second axis expresses asymmetry in the relative amount of benefits/costs accrued. Considering benefit types, one extreme represents the case of single‐species groups wherein all individuals obtain the same supplementary, group‐size‐related benefits, and the other extreme comprises associations of very different, but complementary species (e.g. one partner creates access to food while the other provides vigilance). The relevance of social information and the matching of activities (e.g. speed of movement) are highest for relationships on the supplementary side of this axis, but so is competition; relationships between species will occur at points along this gradient where the benefits outweigh the costs. Considering benefit amounts given or received, extreme asymmetry occurs when one species is exclusively a benefit provider and the other a benefit user. Within this parameter space, some MSG systems are constrained to one kind of interaction, such as shoals of fish of similar species or leader–follower interactions in fish and other taxa. Other MSGs, such as terrestrial bird flocks, can simultaneously include a variety of supplementary and complementary interactions. We review the benefits that species obtain across the diversity of MSG types, and argue that the degree and nature of asymmetry between benefit providers and users should be measured and not just assumed. We then discuss evolutionary shifts in MSG types, focusing on drivers towards similarity in group composition, and selection on benefit providers to enhance the benefits they can receive from other species. Finally, we conclude by considering how individual and collective behaviour in MSGs may influence both the structure and processes of communities.     

Review: Helicobacter pylori infection in children

Helicobacter pylori infection in children and adolescents differs in comparison to adults with respect to epidemiology, host responses, and disease manifestations. Furthermore, treatment options are limited in this population and antibiotic resistance rates continue to increase. Therefore, ongoing research is vital to understand disease pathogenesis and provide optimal management of children with infection. This review summarizes relevant publications from April 2019 to March 2020. Similar to adults, recent studies show a decreasing prevalence of infection in the pediatric population. Studies of pathogenesis investigated serum immune responses and the potential inverse association of infection and allergy. Several studies investigated the effect of H pylori and related inflammation on the gut microbiome. The recommendation of endoscopy‐based testing to identify the cause of symptoms and not just H pylori, reserving noninvasive UBT or stool antigen tests for post‐eradication follow‐up, was supported by the current literature.     

Incorporating intraspecific variation into species distribution models improves distribution predictions,but cannot predict species traits for a wide-spread plant species

The most common approach to predicting how species ranges and ecological functions will shift with climate change is to construct correlative species distribution models (SDMs). These models use a species’ climatic distribution to determine currently suitable areas for the species and project its potential distribution under future climate scenarios. A core, rarely tested, assumption of SDMs is that all populations will respond equivalently to climate. Few studies have examined this assumption, and those that have rarely dissect the reasons for intraspecific differences. Focusing on the arctic-alpine cushion plant Silene acaulis, we compared predictive accuracy from SDMs constructed using the species’ full global distribution with composite predictions from separate SDMs constructed using subpopulations defined either by genetic or habitat differences. This is one of the first studies to compare multiple ways of constructing intraspecific-level SDMs with a species-level SDM. We also examine the contested relationship between relative probability of occurrence and species performance or ecological function, testing if SDM output can predict individual performance (plant size) and biotic interactions (facilitation). We found that both genetic- and habitat-informed SDMs are considerably more accurate than a species-level SDM, and that the genetic model substantially differs from and outperforms the habitat model. While SDMs have been used to infer population performance and possibly even biotic interactions, in our system these relationships were extremely weak. Our results indicate that individual subpopulations may respond differently to climate, although we discuss and explore several alternative explanations for the superior performance of intraspecific-level SDMs. We emphasize the need to carefully examine how to best define intraspecific-level SDMs as well as how potential genetic, environmental, or sampling variation within species ranges can critically affect SDM predictions. We urge caution in inferring population performance or biotic interactions from SDM predictions, as these often-assumed relationships are not supported in our study.     

Multispectral canopy reflectance improves spatial distribution models of Amazonian understory species

Species distribution models are required for the research and management of biodiversity in the hyperdiverse tropical forests, but reliable and ecologically relevant digital environmental data layers are not always available. We here assess the usefulness of multispectral canopy reflectance (Landsat) relative to climate data in modelling understory plant species distributions in tropical rainforests. We used a large dataset of quantitative fern and lycophyte species inventories across lowland Amazonia as the basis for species distribution modelling (SDM). As predictors, we used CHELSA climatic variables and canopy reflectance values from a recent basin-wide composite of Landsat TM/ETM+ images both separately and in combination. We also investigated how species accumulate over sites when environmental distances were expressed in terms of climatic or surface reflectance variables. When species accumulation curves were constructed such that differences in Landsat reflectance among the selected plots were maximised, species accumulated faster than when climatic differences were maximised or plots were selected in a random order. Sixty-nine species were sufficiently frequent for species distribution modelling. For most of them, adequate SDMs were obtained whether the models were based on CHELSA data only, Landsat data only or both combined. Model performance was not influenced by species’ prevalence or abundance. Adding Landsat-based environmental data layers overall improved the discriminatory capacity of SDMs compared to climate-only models, especially for soil specialist species. Our results show that canopy surface reflectance obtained by multispectral sensors can provide studies of tropical ecology, as exemplified by SDMs, much higher thematic (taxonomic) detail than is generally assumed. Furthermore, multispectral datasets complement the traditionally used climatic layers in analyses requiring information on environmental site conditions. We demonstrate the utility of freely available, global remote sensing data for biogeographical studies that can aid conservation planning and biodiversity management.     

Sierra Nevada mountain lake microbial communities are structured by temperature,resources and geographic location

Warming, eutrophication (nutrient fertilization) and brownification (increased loading of allochthonous organic matter) are three global trends impacting lake ecosystems. However, the independent and synergistic effects of resource addition and warming on autotrophic and heterotrophic microorganisms are largely unknown. In this study, we investigate the independent and interactive effects of temperature, dissolved organic carbon (DOC, both allochthonous and autochthonous) and nitrogen (N) supply, in addition to the effect of spatial variables, on the composition, richness, and evenness of prokaryotic and eukaryotic microbial communities in lakes across elevation and N deposition gradients in the Sierra Nevada mountains of California, USA. We found that both prokaryotic and eukaryotic communities are structured by temperature, terrestrial (allochthonous) DOC and latitude. Prokaryotic communities are also influenced by total and aquatic (autochthonous) DOC, while eukaryotic communities are also structured by nitrate. Additionally, increasing N availability was associated with reduced richness of prokaryotic communities, and both lower richness and evenness of eukaryotes. We did not detect any synergistic or antagonistic effects as there were no interactions among temperature and resource variables. Together, our results suggest that (a) organic and inorganic resources, temperature, and geographic location (based on latitude and longitude) independently influence lake microbial communities; and (b) increasing N supply due to atmospheric N deposition may reduce richness of both prokaryotic and eukaryotic microbes, probably by reducing niche dimensionality. Our study provides insight into abiotic processes structuring microbial communities across environmental gradients and their potential roles in material and energy fluxes within and between ecosystems.     

Age‐related variation in the trophic characteristics of a marsupial carnivore,the Tasmanian devil Sarcophilus harrisii

Age‐related changes in diet have implications for competitive interactions and for predator–prey dynamics, affecting individuals and groups at different life stages. To quantify patterns of variation and ontogenetic change in the diets of Tasmanian devils Sarcophilus harrisii, a threatened marsupial carnivore, we analyzed variation in the stable isotope composition of whisker tissue samples taken from 91 individual devils from Wilmot, Tasmania from December 2014 to February 2017. Both δ¹³C and δ¹⁵N decreased with increasing age in weaned Tasmanian devils, indicating that as they age devils rely less on small mammals and birds, and more on large herbivores. Devils <12 months old had broader group isotopic niches, as estimated by Bayesian standard ellipses (SEA_B mode = 1.042) than devils from 12 to 23 months old (mode = 0.541) and devils ≥24 months old (mode = 0.532). Devils <24 months old had broader individual isotopic niches (SEA_B mode range 0.492–1.083) than devils ≥24 months old (mode range 0.092–0.240). A decrease in δ¹⁵N from the older whisker sections to the more recently grown sections in devils <24 months old likely reflects the period of weaning in this species, as this pattern was not observed in devils ≥24 months old. Our data reveal changes in the isotopic composition of devil whiskers with increasing age, accompanied by a reduction in isotopic variation both among population age classes and within individuals, reflecting the effect of weaning in early life, and a likely shift from an initially diverse diet of small mammals, birds, and invertebrates towards increasing consumption of larger herbivores in adulthood.     

Tool for genomic selection and breeding to evolutionary adaptation: Development of a 100K single nucleotide polymorphism array for the honey bee

High‐throughput high‐density genotyping arrays continue to be a fast, accurate, and cost‐effective method for genotyping thousands of polymorphisms in high numbers of individuals. Here, we have developed a new high‐density SNP genotyping array (103,270 SNPs) for honey bees, one of the most ecologically and economically important pollinators worldwide. SNPs were detected by conducting whole‐genome resequencing of 61 honey bee drones (haploid males) from throughout Europe. Selection of SNPs for the chip was done in multiple steps using several criteria. The majority of SNPs were selected based on their location within known candidate regions or genes underlying a range of honey bee traits, including hygienic behavior against pathogens, foraging, and subspecies. Additionally, markers from a GWAS of hygienic behavior against the major honey bee parasite Varroa destructor were brought over. The chip also includes SNPs associated with each of three major breeding objectives—honey yield, gentleness, and Varroa resistance. We validated the chip and make recommendations for its use by determining error rates in repeat genotypings, examining the genotyping performance of different tissues, and by testing how well different sample types represent the queen's genotype. The latter is a key test because it is highly beneficial to be able to determine the queen's genotype by nonlethal means. The array is now publicly available and we suggest it will be a useful tool in genomic selection and honey bee breeding, as well as for GWAS of different traits, and for population genomic, adaptation, and conservation questions.