Engines of change: Transposable element mutation rates are high and variable within Daphnia magna.

Transposable elements (TEs) represent a major portion of most eukaryotic genomes, yet little is known about their mutation rates or how their activity is shaped by other evolutionary forces. Here, we compare short- and long-term patterns of genome-wide mutation accumulation (MA) of TEs among 9 genotypes from three populations of Daphnia magna from across a latitudinal gradient. While the overall proportion of the genome comprised of TEs is highly similar among genotypes from Finland, Germany, and Israel, populations are distinguishable based on patterns of insertion site polymorphism. Our direct rate estimates indicate TE movement is highly variable (net rates ranging from -11.98 to 12.79 x 10-5 per copy per generation among genotypes), differing both among populations and TE families. Although gains outnumber losses when selection is minimized, both types of events appear to be highly deleterious based on their low frequency in control lines where propagation is not limited to random, single-progeny descent. With rate estimates 4 orders of magnitude higher than base substitutions, TEs clearly represent a highly mutagenic force in the genome. Quantifying patterns of intra- and interspecific variation in TE mobility with and without selection provides insight into a powerful mechanism generating genetic variation in the genome.

Resolving intergenotypic Striga resistance in sorghum.

Genetic underpinnings of host-pathogen interactions in the parasitic plant Striga hermonthica, a root parasitic plant that ravages cereals in sub-Saharan Africa, are unclear. We performed a comparative transcriptome study on five genotypes of sorghum exhibiting diverse resistance responses to S. hermonthica using weighted gene co-expression network analysis (WGCNA). We found that S. hermonthica elicits both basal and effector-triggered immunity-like a bona fide pathogen. The resistance response was genotype specific. Some resistance responses followed the salicylic acid-dependent signaling pathway for systemic acquired resistance characterized by cell wall reinforcements, lignification, and callose deposition, while in others the WRKY-dependent signaling pathway was activated, leading to a hypersensitive response. In some genotypes, both modes of resistance were activated, while in others either mode dominated the resistance response. Cell wall-based resistance was common to all sorghum genotypes but strongest in IS2814, while a hypersensitive response was specific to N13, IS9830, and IS41724. WGCNA further allowed for pinpointing of S. hermonthica resistance causative genes in sorghum, including glucan synthase-like 10 gene, a pathogenesis-related thaumatin-like family gene, and a phosphoinositide phosphatase gene. Such candidate genes will form a good basis for subsequent functional validation and possibly future resistance breeding.

Genomics of sorghum local adaptation to a parasitic plant.

Host-parasite coevolution can maintain high levels of genetic diversity in traits involved in species interactions. In many systems, host traits exploited by parasites are constrained by use in other functions, leading to complex selective pressures across space and time. Here, we study genome-wide variation in the staple crop Sorghum bicolor (L.) Moench and its association with the parasitic weed Striga hermonthica (Delile) Benth., a major constraint to food security in Africa. We hypothesize that geographic selection mosaics across gradients of parasite occurrence maintain genetic diversity in sorghum landrace resistance. Suggesting a role in local adaptation to parasite pressure, multiple independent loss-of-function alleles at sorghum LOW GERMINATION STIMULANT 1 (LGS1) are broadly distributed among African landraces and geographically associated with S. hermonthica occurrence. However, low frequency of these alleles within S. hermonthica-prone regions and their absence elsewhere implicate potential trade-offs restricting their fixation. LGS1 is thought to cause resistance by changing stereochemistry of strigolactones, hormones that control plant architecture and below-ground signaling to mycorrhizae and are required to stimulate parasite germination. Consistent with trade-offs, we find signatures of balancing selection surrounding LGS1 and other candidates from analysis of genome-wide associations with parasite distribution. Experiments with CRISPR-Cas9-edited sorghum further indicate that the benefit of LGS1-mediated resistance strongly depends on parasite genotype and abiotic environment and comes at the cost of reduced photosystem gene expression. Our study demonstrates long-term maintenance of diversity in host resistance genes across smallholder agroecosystems, providing a valuable comparison to both industrial farming systems and natural communities.

Physiological and ecological warnings that dodders pose an exigent threat to farmlands in Eastern Africa.

Invasive holoparasitic plants of the genus Cuscuta (dodder) threaten African ecosystems due to their rapid spread and attack on various host plant species. Most Cuscuta species cannot photosynthesize and hence rely on host plants for nourishment. After attachment through a peg-like organ called a haustorium, the parasites deprive hosts of water and nutrients, which negatively affects host growth and development. Despite their rapid spread in Africa, dodders have attracted limited research attention, although data on their taxonomy, host range, and epidemiology are critical for their management. Here, we combine taxonomy and phylogenetics to reveal the presence of field dodder (Cuscuta campestris) and C. kilimanjari (both either naturalized or endemic to East Africa), in addition to the introduction of the giant dodder (C. reflexa), a south Asian species, in continental Africa. These parasites have a wide host range, parasitizing species across 13 angiosperm orders. We evaluated the possibility of C. reflexa to expand this host range to tea (Camelia sinensis), coffee (Coffea arabica), and mango (Mangifera indica), crops of economic importance to Africa, for which haustorial formation and vascular-bundle connections in all three crops revealed successful parasitism. However, only mango mounted a successful postattachment resistance response. Furthermore, species distribution models predicted high habitat suitability for Cuscuta spp. across major tea- and coffee-growing regions of Eastern Africa, suggesting an imminent risk to these crops. Our findings provide relevant insights into a poorly understood threat to biodiversity and economic wellbeing in Eastern Africa, and provide critical information to guide development of management strategies to avert Cuscuta spp. spread.

Genome-wide polymorphism and signatures of selection in the symbiotic sea anemone Aiptasia.

BACKGROUND: Coral reef ecosystems are declining in response to global climate change and anthropogenic impacts. Yet patterns of standing genetic variation within cnidarian species, a major determinant of adaptive potential, are virtually unknown at genome-scale resolution. We explore patterns of genome-wide polymorphism and identify candidate loci under selection in the sea anemone Aiptasia, an important laboratory model system for studying the symbiosis between corals and dinoflagellate algae of the genus Symbiodinium. RESULTS: Low coverage genome sequencing revealed large genetic distances among globally widespread lineages, novel candidate targets of selection, and considerably higher heterozygosity than previously reported for Aiptasia. More than 670,000 single nucleotide polymorphisms were identified among 10 Aiptasia individuals including two pairs of genetic clones. Evolutionary relationships based on genome-wide polymorphism supported the current paradigm of a genetically distinct population from the US South Atlantic that harbors diverse Symbiodinium clades. However, anemones from the US South Atlantic demonstrated a striking lack of shared derived polymorphism. Heterozygosity was an important feature shaping nucleotide diversity patterns: at any given SNP site, more than a third of individuals genotyped were heterozygotes, and heterozygosity within individual genomes ranged from 0.37-0.58%. Analysis of nonsynonymous and synonymous sites suggested that highly heterozygous regions are evolving under relaxed purifying selection compared to the rest of the Aiptasia genome. Genes previously identified as having elevated evolutionary rates in Aiptasia compared to other cnidarians were found in our study to be under strong purifying selection within Aiptasia. Candidate targets of selection, including lectins and genes involved in Rho GTPase signalling, were identified based on unusual signatures of nucleotide diversity, Tajima's D, and heterozygosity compared to genome-wide averages. CONCLUSIONS: This study represents the first genome-wide analysis of Tajima's D in a cnidarian. Our results shed light on patterns of intraspecific genome-wide polymorphism in a model for studies of coral-algae symbiosis and present genetic targets for future research on evolutionary and cellular processes in early-diverging metazoans.

Predicting gene expression responses to environment in Arabidopsis thaliana using natural variation in DNA sequence.

The evolution of gene expression responses are a critical component of adaptation to variable environments. Predicting how DNA sequence influences expression is challenging because the genotype to phenotype map is not well resolved for cis regulatory elements, transcription factor binding, regulatory interactions, and epigenetic features, not to mention how these factors respond to environment. We tested if flexible machine learning models could learn some of the underlying cis-regulatory genotype to phenotype map. We tested this approach using cold-responsive transcriptome profiles in 5 diverse Arabidopsis thaliana accessions. We first tested for evidence that cis regulation plays a role in environmental response, finding 14 and 15 motifs that were significantly enriched within the up- and down-stream regions of cold-responsive differentially regulated genes (DEGs). We next applied convolutional neural networks (CNNs), which learn de novo cis-regulatory motifs in DNA sequences to predict expression response to environment. We found that CNNs predicted differential expression with moderate accuracy, with evidence that predictions were hindered by biological complexity of regulation and the large potential regulatory code. Overall, DEGs between specific environments can be predicted based on variation in cis-regulatory sequences, although more information needs to be incorporated and better models may be required.

Climate biogeography of Arabidopsis thaliana: linking distribution models and individual variation.

AIM: Patterns of individual variation are key to testing hypotheses about the mechanisms underlying biogeographic patterns. If species distributions are determined by environmental constraints, then populations near range margins may have reduced performance and be adapted to harsher environments. Model organisms are potentially important systems for biogeographical studies, given the available range-wide natural history collections, and the importance of providing biogeographical context to their genetic and phenotypic diversity. LOCATION: Global. TAXON: Arabidopsis thaliana ("Arabidopsis"). METHODS: We fit occurrence records to climate data, and then projected the distribution of Arabidopsis under last glacial maximum, current, and future climates. We confronted model predictions with individual performance measured on 2,194 herbarium specimens, and we asked whether predicted suitability was associated with life-history and genomic variation measured on ~900 natural accessions. RESULTS: The most important climate variables constraining the Arabidopsis distribution were winter cold in northern and high elevation regions and summer heat in southern regions. Herbarium specimens from regions with lower habitat suitability in both northern and southern regions were smaller, supporting the hypothesis that the distribution of Arabidopsis is constrained by climate-associated factors. Climate anomalies partly explained interannual variation in herbarium specimen size, but these did not closely correspond to local limiting factors identified in the distribution model. Late-flowering genotypes were absent from the lowest suitability regions, suggesting slower life histories are only viable closer to the center of the realized niche. We identified glacial refugia farther north than previously recognized, as well as refugia concordant with previous population genetic findings. Lower latitude populations, known to be genetically distinct, are most threatened by future climate change. The recently colonized range of Arabidopsis was well-predicted by our native-range model applied to certain regions but not others, suggesting it has colonized novel climates. MAIN CONCLUSIONS: Integration of distribution models with performance data from vast natural history collections is a route forward for testing biogeographical hypotheses about species distributions and their relationship with evolutionary fitness across large scales.

Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning.

Unmanned aerial vehicles (UAVs) equipped with multispectral sensors offer high spatial and temporal resolution imagery for monitoring crop stress at early stages of development. Analysis of UAV-derived data with advanced machine learning models could improve real-time management in agricultural systems, but guidance for this integration is currently limited. Here we compare two deep learning-based strategies for early warning detection of crop stress, using multitemporal imagery throughout the growing season to predict field-scale yield in irrigated rice in eastern Arkansas. Both deep learning strategies showed improvements upon traditional statistical learning approaches including linear regression and gradient boosted decision trees. First, we explicitly accounted for variation across developmental stages using a 3D convolutional neural network (CNN) architecture that captures both spatial and temporal dimensions of UAV images from multiple time points throughout one growing season. 3D-CNNs achieved low prediction error on the test set, with a Root Mean Squared Error (RMSE) of 8.8% of the mean yield. For the second strategy, a 2D-CNN, we considered only spatial relationships among pixels for image features acquired during a single flyover. 2D-CNNs trained on images from a single day were most accurate when images were taken during booting stage or later, with RMSE ranging from 7.4 to 8.2% of the mean yield. A primary benefit of convolutional autoencoder-like models (based on analyses of prediction maps and feature importance) is the spatial denoising effect that corrects yield predictions for individual pixels based on the values of vegetation index and thermal features for nearby pixels. Our results highlight the promise of convolutional autoencoders for UAV-based yield prediction in rice.

Genomics of natural history collections for understanding evolution in the wild.

A long-standing question in biology is how organisms change through time and space in response to their environment. This knowledge is of particular relevance to predicting how organisms might respond to future environmental changes caused by human-induced global change. Usually researchers make inferences about past events based on an understanding of current static genetic patterns, but these are limited in their capacity to inform on underlying past processes. Natural history collections (NHCs) represent a unique and critical source of information to provide temporally deep and spatially broad time-series of samples. By using NHC samples, researchers can directly observe genetic changes over time and space and link those changes with specific ecological/evolutionary events. Until recently, such genetic studies were hindered by the intrinsic challenges of NHC samples (i.e. low yield of highly fragmented DNA). However, recent methodological and technological developments have revolutionized the possibilities in the novel field of NHC genomics. In this Special Feature, we compile a range of studies spanning from methodological aspects to particular case studies which demonstrate the enormous potential of NHC samples for accessing large genomic data sets from the past to advance our knowledge on how populations and species respond to global change at multiple spatial-temporal scales. We also highlight possible limitations, recommendations and a few opportunities for future researchers aiming to study NHC genomics.

Seeds attached to refrigerated shipping containers represent a substantial risk of nonnative plant species introduction and establishment.

The initial processes for successful biological invasions are transport, introduction, and establishment. These can be directly influenced or completely avoided through activities that reduce the number and frequency of entering nonnative propagules. Economic and environmental benefits through preventative monitoring programs at early stages of invasion far outweigh the long-term costs associated with mitigating ecological and economic impacts once nonnative species establish and spread. In this study, we identified 30 taxa of hitchhiking plant propagules on the air-intake grilles of refrigerated shipping containers arriving into a United States seaport from a port on the Pacific coast of South America. The four monocotyledonous taxa with the highest number of seeds collected were analyzed; we estimated propagule pressure, germination, and survivorship of these taxa, and we used the estimates to determine likelihood of establishment. At the levels of propagule pressure estimated here, non-zero germination and survival rates resulted in high establishment probabilities even when escape rates from shipping containers were modelled to be exceedingly low. Our results suggest high invasion risk for nonnative taxa including Saccharum spontaneum L., a listed Federal Noxious Weed. Currently, not all shipping containers arriving at USA ports are thoroughly inspected due to limited personnel and funding for biological invasion prevention. Our results indicate that there is a significant risk from only a few propagules escaping into the environment from this source, and we propose possible solutions for reducing this risk.

Genomic history and ecology of the geographic spread of rice.

Rice (Oryza sativa) is one of the world's most important food crops, and is comprised largely of japonica and indica subspecies. Here, we reconstruct the history of rice dispersal in Asia using whole-genome sequences of more than 1,400 landraces, coupled with geographic, environmental, archaeobotanical and paleoclimate data. Originating around 9,000 yr ago in the Yangtze Valley, rice diversified into temperate and tropical japonica rice during a global cooling event about 4,200 yr ago. Soon after, tropical japonica rice reached Southeast Asia, where it rapidly diversified, starting about 2,500 yr BP. The history of indica rice dispersal appears more complicated, moving into China around 2,000 yr BP. We also identify extrinsic factors that influence genome diversity, with temperature being a leading abiotic factor. Reconstructing the dispersal history of rice and its climatic correlates may help identify genetic adaptations associated with the spread of a key domesticated species.

Molecular signatures of host specificity linked to habitat specialization in Exaiptasia sea anemones.

Rising ocean temperatures associated with global climate change induce breakdown of the symbiosis between coelenterates and photosynthetic microalgae of the genus Symbiodinium. Association with more thermotolerant partners could contribute to resilience, but the genetic mechanisms controlling specificity of hosts for particular Symbiodinium types are poorly known. Here, we characterize wild populations of a sea anemone laboratory model system for anthozoan symbiosis, from contrasting environments in Caribbean Panama. Patterns of anemone abundance and symbiont diversity were consistent with specialization of holobionts for particular habitats, with Exaiptasia pallida/S. minutum (ITS2 type B1) abundant on vertical substrate in thermally stable, shaded environments but E. brasiliensis/Symbiodinium sp. (ITS2 clade A) more common in shallow areas subject to high temperature and irradiance. Population genomic sequencing revealed a novel E. pallida population from the Bocas del Toro Archipelago that only harbors S. minutum. Loci most strongly associated with divergence of the Bocas-specific population were enriched in genes with putative roles in cnidarian symbiosis, including activators of the complement pathway of the innate immune system, thrombospondin-type-1 repeat domain proteins, and coordinators of endocytic recycling. Our findings underscore the importance of unmasking cryptic diversity in natural populations and the role of long-term evolutionary history in mediating interactions with Symbiodinium.

Natural Variation in Responses to Acute Heat and Cold Stress in a Sea Anemone Model System for Coral Bleaching.

Rising ocean temperatures disrupt the symbiosis between corals and their microalgae, accelerating global decline of coral reef ecosystems. Because of the difficulty of performing laboratory experiments with corals, the sea anemone Aiptasia has emerged as an important model system for molecular studies of coral bleaching and symbiosis. Here, we investigate natural variation in bleaching responses among different genetic lineages of Aiptasia. Both heat- and cold-induced paths to symbiosis breakdown were analyzed. Significant genetic variation in response to acute heat stress was observed, with severe bleaching of two Aiptasia strains from Hawaii but minimal bleaching of strains from the U.S. South Atlantic, including the strain used to generate the Aiptasia reference genome. Both strains from Hawaii hosted Symbiodinium type B1, whereas strains from the U.S. South Atlantic hosted type A4 or B2. In contrast to the results from exposures to acute heat stress, negligible variation was observed in response to a pulsed cold shock despite moderate bleaching across all strains. These results support our hypothesis that bleaching responses to distinct stressors are independent. Our findings emphasize the role of stress regime when predicting adaptive responses of symbiotic cnidarians to changing climates, because genetic variation may exist for some forms of stress-induced bleaching but not others.