A combination of conserved and diverged responses underlies Theobroma cacao's defense response to Phytophthora palmivora.

BACKGROUND: Plants have complex and dynamic immune systems that have evolved to resist pathogens. Humans have worked to enhance these defenses in crops through breeding. However, many crops harbor only a fraction of the genetic diversity present in wild relatives. Increased utilization of diverse germplasm to search for desirable traits, such as disease resistance, is therefore a valuable step towards breeding crops that are adapted to both current and emerging threats. Here, we examine diversity of defense responses across four populations of the long-generation tree crop Theobroma cacao L., as well as four non-cacao Theobroma species, with the goal of identifying genetic elements essential for protection against the oomycete pathogen Phytophthora palmivora. RESULTS: We began by creating a new, highly contiguous genome assembly for the P. palmivora-resistant genotype SCA 6 (Additional file 1: Tables S1-S5), deposited in GenBank under accessions CP139290-CP139299. We then used this high-quality assembly to combine RNA and whole-genome sequencing data to discover several genes and pathways associated with resistance. Many of these are unique, i.e., differentially regulated in only one of the four populations (diverged 40 k-900 k generations). Among the pathways shared across all populations is phenylpropanoid biosynthesis, a metabolic pathway with well-documented roles in plant defense. One gene in this pathway, caffeoyl shikimate esterase (CSE), was upregulated across all four populations following pathogen treatment, indicating its broad importance for cacao's defense response. Further experimental evidence suggests this gene hydrolyzes caffeoyl shikimate to create caffeic acid, an antimicrobial compound and known inhibitor of Phytophthora spp. CONCLUSIONS: Our results indicate most expression variation associated with resistance is unique to populations. Moreover, our findings demonstrate the value of using a broad sample of evolutionarily diverged populations for revealing the genetic bases of cacao resistance to P. palmivora. This approach has promise for further revealing and harnessing valuable genetic resources in this and other long-generation plants.

Combining GWAS and population genomic analyses to characterize coevolution in a legume-rhizobia symbiosis.

The mutualism between legumes and rhizobia is clearly the product of past coevolution. However, the nature of ongoing evolution between these partners is less clear. To characterize the nature of recent coevolution between legumes and rhizobia, we used population genomic analysis to characterize selection on functionally annotated symbiosis genes as well as on symbiosis gene candidates identified through a two-species association analysis. For the association analysis, we inoculated each of 202 accessions of the legume host Medicago truncatula with a community of 88 Sinorhizobia (Ensifer) meliloti strains. Multistrain inoculation, which better reflects the ecological reality of rhizobial selection in nature than single-strain inoculation, allows strains to compete for nodulation opportunities and host resources and for hosts to preferentially form nodules and provide resources to some strains. We found extensive host by symbiont, that is, genotype-by-genotype, effects on rhizobial fitness and some annotated rhizobial genes bear signatures of recent positive selection. However, neither genes responsible for this variation nor annotated host symbiosis genes are enriched for signatures of either positive or balancing selection. This result suggests that stabilizing selection dominates selection acting on symbiotic traits and that variation in these traits is under mutation-selection balance. Consistent with the lack of positive selection acting on host genes, we found that among-host variation in growth was similar whether plants were grown with rhizobia or N-fertilizer, suggesting that the symbiosis may not be a major driver of variation in plant growth in multistrain contexts.

Discordant population structure among rhizobium divided genomes and their legume hosts.

Symbiosis often occurs between partners with distinct life history characteristics and dispersal mechanisms. Many bacterial symbionts have genomes comprising multiple replicons with distinct rates of evolution and horizontal transmission. Such differences might drive differences in population structure between hosts and symbionts and among the elements of the divided genomes of bacterial symbionts. These differences might, in turn, shape the evolution of symbiotic interactions and bacterial evolution. Here we use whole genome resequencing of a hierarchically structured sample of 191 strains of Sinorhizobium meliloti collected from 21 locations in southern Europe to characterize population structures of this bacterial symbiont, which forms a root nodule symbiosis with the host plant Medicago truncatula. S. meliloti genomes showed high local (within-site) variation and little isolation by distance. This was particularly true for the two symbiosis elements, pSymA and pSymB, which have population structures that are similar to each other, but distinct from both the bacterial chromosome and the host plant. Given limited recombination on the chromosome, compared to the symbiosis elements, distinct population structures may result from differences in effective gene flow. Alternatively, positive or purifying selection, with little recombination, may explain distinct geographical patterns at the chromosome. Discordant population structure between hosts and symbionts indicates that geographically and genetically distinct host populations in different parts of the range might interact with genetically similar symbionts, potentially minimizing local specialization.

Host-Associated Rhizobial Fitness: Dependence on Nitrogen, Density, Community Complexity, and Legume Genotype.

The environmental context of the nitrogen-fixing mutualism between leguminous plants and rhizobial bacteria varies over space and time. Variation in resource availability, population density, and composition likely affect the ecology and evolution of rhizobia and their symbiotic interactions with hosts. We examined how host genotype, nitrogen addition, rhizobial density, and community complexity affected selection on 68 rhizobial strains in the Sinorhizobium meliloti-Medicago truncatula mutualism. As expected, host genotype had a substantial effect on the size, number, and strain composition of root nodules (the symbiotic organ). The understudied environmental variable of rhizobial density had a stronger effect on nodule strain frequency than the addition of low nitrogen levels. Higher inoculum density resulted in a nodule community that was less diverse and more beneficial but only in the context of the more selective host genotype. Higher density resulted in more diverse and less beneficial nodule communities with the less selective host. Density effects on strain composition deserve additional scrutiny as they can create feedback between ecological and evolutionary processes. Finally, we found that relative strain rankings were stable across increasing community complexity (2, 3, 8, or 68 strains). This unexpected result suggests that higher-order interactions between strains are rare in the context of nodule formation and development. Our work highlights the importance of examining mechanisms of density-dependent strain fitness and developing theoretical predictions that incorporate density dependence. Furthermore, our results have translational relevance for overcoming establishment barriers in bioinoculants and motivating breeding programs that maintain beneficial plant-microbe interactions across diverse agroecological contexts. IMPORTANCE Legume crops establish beneficial associations with rhizobial bacteria that perform biological nitrogen fixation, providing nitrogen to plants without the economic and greenhouse gas emission costs of chemical nitrogen inputs. Here, we examine the influence of three environmental factors that vary in agricultural fields on strain relative fitness in nodules. In addition to manipulating nitrogen, we also use two biotic variables that have rarely been examined: the rhizobial community's density and complexity. Taken together, our results suggest that (i) breeding legume varieties that select beneficial strains despite environmental variation is possible, (ii) changes in rhizobial population densities that occur routinely in agricultural fields could drive evolutionary changes in rhizobial populations, and (iii) the lack of higher-order interactions between strains will allow the high-throughput assessments of rhizobia winners and losers during plant interactions.

The spatial scale of adaptation in a native annual plant and its implications for responses to climate change.

Spatial patterns of adaptation provide important insights into agents of selection and expected responses of populations to climate change. Robust inference into the spatial scale of adaptation can be gained through reciprocal transplant experiments that combine multiple source populations and common gardens. Here, we examine the spatial scale of local adaptation of the North American annual plant common ragweed, Ambrosia artemisiifolia, using data from four common gardens with 22 source populations sampled from across a ∼1200 km latitudinal gradient within the native range. We found evidence of local adaptation at the northernmost common garden, but maladaptation at the two southern gardens, where more southern source populations outperformed local populations. Overall, the spatial scale of adaptation was large-at the three gardens where distance between source populations and gardens explained variation in fitness, it took an average of 820 km for fitness to decline to 50% of its predicted maximum. Taken together, these results suggest that climate change has already caused maladaptation, especially across the southern portion of the range, and may result in northward range contraction over time.

Unraveling coevolutionary dynamics using ecological genomics.

Coevolutionary interactions, from the delicate co-dependency in mutualistic interactions to the antagonistic relationship of hosts and parasites, are a ubiquitous driver of adaptation. Surprisingly, little is known about the genomic processes underlying coevolution in an ecological context. However, species comprise genetically differentiated populations that interact with temporally variable abiotic and biotic environments. We discuss the recent advances in coevolutionary theory and genomics as well as shortcomings, to identify coevolving genes that take into account this spatial and temporal variability of coevolution, and propose a practical guide to understand the dynamic of coevolution using an ecological genomics lens.

Individual-based eco-evolutionary models for understanding adaptation in changing seas.

As climate change threatens species' persistence, predicting the potential for species to adapt to rapidly changing environments is imperative for the development of effective conservation strategies. Eco-evolutionary individual-based models (IBMs) can be useful tools for achieving this objective. We performed a literature review to identify studies that apply these tools in marine systems. Our survey suggested that this is an emerging area of research fuelled in part by developments in modelling frameworks that allow simulation of increasingly complex ecological, genetic and demographic processes. The studies we identified illustrate the promise of this approach and advance our understanding of the capacity for adaptation to outpace climate change. These studies also identify limitations of current models and opportunities for further development. We discuss three main topics that emerged across studies: (i) effects of genetic architecture and non-genetic responses on adaptive potential; (ii) capacity for gene flow to facilitate rapid adaptation; and (iii) impacts of multiple stressors on persistence. Finally, we demonstrate the approach using simple simulations and provide a framework for users to explore eco-evolutionary IBMs as tools for understanding adaptation in changing seas.

Genomic structural variants constrain and facilitate adaptation in natural populations of Theobroma cacao, the chocolate tree.

Genomic structural variants (SVs) can play important roles in adaptation and speciation. Yet the overall fitness effects of SVs are poorly understood, partly because accurate population-level identification of SVs requires multiple high-quality genome assemblies. Here, we use 31 chromosome-scale, haplotype-resolved genome assemblies of Theobroma cacao-an outcrossing, long-lived tree species that is the source of chocolate-to investigate the fitness consequences of SVs in natural populations. Among the 31 accessions, we find over 160,000 SVs, which together cover eight times more of the genome than single-nucleotide polymorphisms and short indels (125 versus 15 Mb). Our results indicate that a vast majority of these SVs are deleterious: they segregate at low frequencies and are depleted from functional regions of the genome. We show that SVs influence gene expression, which likely impairs gene function and contributes to the detrimental effects of SVs. We also provide empirical support for a theoretical prediction that SVs, particularly inversions, increase genetic load through the accumulation of deleterious nucleotide variants as a result of suppressed recombination. Despite the overall detrimental effects, we identify individual SVs bearing signatures of local adaptation, several of which are associated with genes differentially expressed between populations. Genes involved in pathogen resistance are strongly enriched among these candidates, highlighting the contribution of SVs to this important local adaptation trait. Beyond revealing empirical evidence for the evolutionary importance of SVs, these 31 de novo assemblies provide a valuable resource for genetic and breeding studies in Tcacao.

Comparative genomics reveals high rates of horizontal transfer and strong purifying selection on rhizobial symbiosis genes.

Horizontal transfer (HT) alters the repertoire of symbiosis genes in rhizobial genomes and may play an important role in the on-going evolution of the rhizobia-legume symbiosis. To gain insight into the extent of HT of symbiosis genes with different functional roles (nodulation, N-fixation, host benefit and rhizobial fitness), we conducted comparative genomic and selection analyses of the full-genome sequences from 27 rhizobial genomes. We find that symbiosis genes experience high rates of HT among rhizobial lineages but also bear signatures of purifying selection (low Ka : Ks). HT and purifying selection appear to be particularly strong in genes involved in initiating the symbiosis (e.g. nodulation) and in genome-wide association candidates for mediating benefits provided to the host. These patterns are consistent with rhizobia adapting to the host environment through the loss and gain of symbiosis genes, but not with host-imposed positive selection driving divergence of symbiosis genes through recurring bouts of positive selection.

Biased Gene Conversion Constrains Adaptation in Arabidopsis thaliana.

Reduction of fitness due to deleterious mutations imposes a limit to adaptive evolution. By characterizing features that influence this genetic load we may better understand constraints on responses to both natural and human-mediated selection. Here, using whole-genome, transcriptome, and methylome data from >600 Arabidopsis thaliana individuals, we set out to identify important features influencing selective constraint. Our analyses reveal that multiple factors underlie the accumulation of maladaptive mutations, including gene expression level, gene network connectivity, and gene-body methylation. We then focus on a feature with major effect, nucleotide composition. The ancestral vs. derived status of segregating alleles suggests that GC-biased gene conversion, a recombination-associated process that increases the frequency of G and C nucleotides regardless of their fitness effects, shapes sequence patterns in A. thaliana Through estimation of mutational effects, we present evidence that biased gene conversion hinders the purging of deleterious mutations and contributes to a genome-wide signal of decreased efficacy of selection. By comparing these results to two outcrossing relatives, Arabidopsis lyrata and Capsella grandiflora, we find that protein evolution in A. thaliana is as strongly affected by biased gene conversion as in the outcrossing species. Last, we perform simulations to show that natural levels of outcrossing in A. thaliana are sufficient to facilitate biased gene conversion despite increased homozygosity due to selfing. Together, our results show that even predominantly selfing taxa are susceptible to biased gene conversion, suggesting that it may constitute an important constraint to adaptation among plant species.

Pleiotropy facilitates local adaptation to distant optima in common ragweed (Ambrosia artemisiifolia).

Pleiotropy, the control of multiple phenotypes by a single locus, is expected to slow the rate of adaptation by increasing the chance that beneficial alleles also have deleterious effects. However, a prediction arising from classical theory of quantitative trait evolution states that pleiotropic alleles may have a selective advantage when phenotypes are distant from their selective optima. We examine the role of pleiotropy in regulating adaptive differentiation among populations of common ragweed (Ambrosia artemisiifolia); a species that has recently expanded its North American range due to human-mediated habitat change. We employ a phenotype-free approach by using connectivity in gene networks as a proxy for pleiotropy. First, we identify loci bearing footprints of local adaptation, and then use genotype-expression mapping and co-expression networks to infer the connectivity of the genes. Our results indicate that the putatively adaptive loci are highly pleiotropic, as they are more likely than expected to affect the expression of other genes, and they reside in central positions within the gene networks. We propose that the conditionally advantageous alleles at these loci avoid the cost of pleiotropy by having large phenotypic effects that are beneficial when populations are far from their selective optima. We further use evolutionary simulations to show that these patterns are in agreement with a model where populations face novel selective pressures, as expected during a range expansion. Overall, our results suggest that highly connected genes may be targets of positive selection during environmental change, even though they likely experience strong purifying selection in stable selective environments.

Context Dependence of Local Adaptation to Abiotic and Biotic Environments: A Quantitative and Qualitative Synthesis.

Understanding how spatially variable selection shapes adaptation is an area of long-standing interest in evolutionary ecology. Recent meta-analyses have quantified the extent of local adaptation, but the relative importance of abiotic and biotic factors in driving population divergence remains poorly understood. To address this gap, we combined a quantitative meta-analysis and a qualitative metasynthesis to (1) quantify the magnitude of local adaptation to abiotic and biotic factors and (2) characterize major themes that influence the motivation and design of experiments that seek to test for local adaptation. Using local-foreign contrasts as a metric of local adaptation (or maladaptation), we found that local adaptation was greater in the presence than in the absence of a biotic interactor, especially for plants. We also found that biotic environments had stronger effects on fitness than abiotic environments when ignoring whether those environments were local versus foreign. Finally, biotic effects were stronger at low latitudes, and abiotic effects were stronger at high latitudes. Our qualitative analysis revealed that the lens through which local adaptation has been examined differs for abiotic and biotic factors. It also revealed biases in the design and implementation of experiments that make quantitative results challenging to interpret and provided directions for future research.

Gene Expression Modularity Reveals Footprints of Polygenic Adaptation in Theobroma cacao.

Separating footprints of adaptation from demography is challenging. When selection has acted on a single locus with major effect, this issue can be alleviated through signatures left by selective sweeps. However, as adaptation is often driven by small allele frequency shifts at many loci, studies focusing on single genes are able to identify only a small portion of genomic variants responsible for adaptation. In face of this challenge, we utilize coexpression information to search for signals of polygenetic adaptation in Theobroma cacao, a tropical tree species that is the source of chocolate. Using transcriptomics and a weighted correlation network analysis, we group genes with similar expression patterns into functional modules. We then ask whether modules enriched for specific biological processes exhibit cumulative effects of differential selection in the form of high FST and dXY between populations. Indeed, modules putatively involved in protein modification, flowering, and water transport show signs of polygenic adaptation even though individual genes that are members of those groups do not bear strong signatures of selection. Modeling of demography, background selection, and the effects of genomic features reveal that these patterns are unlikely to arise by chance. We also find that specific modules are enriched for signals of strong or relaxed purifying selection, with one module bearing signs of adaptive differentiation and an excess of deleterious mutations. Our results provide insight into polygenic adaptation and contribute to understanding of population structure, demographic history, and genome evolution in T. cacao.

A Select and Resequence Approach Reveals Strain-Specific Effects of Medicago Nodule-Specific PLAT-Domain Genes.

Genetic studies of legume symbiosis with nitrogen-fixing rhizobial bacteria have traditionally focused on nodule and nitrogen-fixation phenotypes when hosts are inoculated with a single rhizobial strain. These approaches overlook the potential effect of host genes on rhizobial fitness (i.e. how many rhizobia are released from host nodules) and strain-specific effects of host genes (i.e. genome × genome interactions). Using Medicago truncatula mutants in the recently described nodule-specific PLAT domain (NPD) gene family, we show how inoculating plants with a mixed inoculum of 68 rhizobial strains (Ensifer meliloti) via a select-and-resequence approach can be used to efficiently assay host mutants for strain-specific effects of late-acting host genes on interacting bacteria. The deletion of a single NPD gene (npd2) or all five members of the NPD gene family (npd1-5) differentially altered the frequency of rhizobial strains in nodules even though npd2 mutants had no visible nodule morphology or N-fixation phenotype. Also, npd1-5 nodules were less diverse and had larger populations of colony-forming rhizobia despite their smaller size. Lastly, NPD mutations disrupt a positive correlation between strain fitness and wild-type host biomass. These changes indicate that the effects of NPD proteins are strain dependent and that NPD family members are not redundant with regard to their effects on rhizobial strains. Association analyses of the rhizobial strains in the mixed inoculation indicate that rhizobial genes involved in chromosome segregation, cell division, GABA metabolism, efflux systems, and stress tolerance play an important role in the strain-specific effects of NPD genes.

Does adaptation to historical climate shape plant responses to future rainfall patterns? A rainfall manipulation experiment with common ragweed.

Climate change is affecting both the volume and distribution of precipitation, which in turn is expected to affect the growth and reproduction of plant populations. The near ubiquity of local adaptation suggests that adaptive differentiation may have important consequences for how populations are affected by and respond to changing precipitation. Here, we manipulated rainfall in a common garden to examine how differentiation among populations of common ragweed, Ambrosia artemisiifolia (Asteraceae) affects responses to water availability expected under climate change. We collected seeds from 26 populations along gradients of historical rainfall and used event-based rainout shelters and watering additions to simulate drier summer conditions and more extreme rainfall events, respectively. Ambrosia artemisiifolia had higher fitness on average under reduced rainfall, suggesting it may spread and become more abundant in areas projected to become hotter and drier during the summer months. We also found strong evidence for phenotypic and fitness clines across both latitude and longitude, and that phenological responses and fitness effects of altered rainfall depended on seed source or historical climate. The effect of rainfall treatment on female fitness was highest in western and mid longitudes, but there was little effect on eastern populations. Across latitude, the effect of rainfall treatment on male fitness was highest in southern populations. These phenology and fitness clines suggest that adaptive differentiation across the species' range has the potential to shape future responses of A. artemisiifolia populations to climate change, particularly altered patterns of rainfall.

Climate change is predicted to disrupt patterns of local adaptation in wild and cultivated maize.

Climate change is one of the most important threats to biodiversity and crop sustainability. The impact of climate change is often evaluated on the basis of expected changes in species' geographical distributions. Genomic diversity, local adaptation, and migration are seldom integrated into future species projections. Here, we examine how climate change will impact populations of two wild relatives of maize, the teosintes Zea mays ssp. mexicana and Z. mays ssp. parviglumis. Despite high levels of genetic diversity within populations and widespread future habitat suitability, we predict that climate change will alter patterns of local adaptation and decrease migration probabilities in more than two-thirds of present-day teosinte populations. These alterations are geographically heterogeneous and suggest that the possible impacts of climate change will vary considerably among populations. The population-specific effects of climate change are also evident in maize landraces, suggesting that climate change may result in maize landraces becoming maladapted to the climates in which they are currently cultivated. The predicted alterations to habitat distribution, migration potential, and patterns of local adaptation in wild and cultivated maize raise a red flag for the future of populations. The heterogeneous nature of predicted populations' responses underscores that the selective impact of climate change may vary among populations and that this is affected by different processes, including past adaptation.

Legacy of prior host and soil selection on rhizobial fitness in planta.

Measuring selection acting on microbial populations in natural or even seminatural environments is challenging because many microbial populations experience variable selection. The majority of rhizobial bacteria are found in the soil. However, they also live symbiotically inside nodules of legume hosts and each nodule can release thousands of daughter cells back into the soil. We tested how past selection (i.e., legacies) by two plant genotypes and by the soil alone affected selection and genetic diversity within a population of 101 strains of Ensifer meliloti. We also identified allelic variants most strongly associated with soil- and host-dependent fitness. In addition to imposing direct selection on rhizobia populations, soil and host environments had lasting effects across host generations. Host presence and genotype during the legacy period explained 22% and 12% of the variance in the strain composition of nodule communities in the second cohort, respectively. Although strains with high host fitness in the legacy cohort tended to be enriched in the second cohort, the diversity of the strain community was greater when the second cohort was preceded by host rather than soil legacies. Our results indicate the potential importance of soil selection driving the evolution of these plant-associated microbes.

Species distribution models throughout the invasion history of Palmer amaranth predict regions at risk of future invasion and reveal challenges with modeling rapidly shifting geographic ranges.

Palmer amaranth (Amaranthus palmeri) is an annual plant native to the desert Southwest of the United States and Mexico and has become invasive and caused large economic losses across much of the United States. In order to examine the temporal and spatial dynamics of past invasion, and to predict future invasion, we developed a broad array of species distribution models (SDMs). In particular, we constructed sequential SDMs throughout the invasion history and asked how well those predicted future invasion (1970 to present). We showed that invasion occurred from a restricted set of environments in the native range to a diverse set in the invaded range. Spatial autocorrelation analyses indicated that rapid range expansion was facilitated by stochastic, long-distance dispersal events. Regardless of SDM approach, all SDMs built using datasets from early in the invasion (1970-2010) performed poorly and failed to predict most of the current invaded range. Together, these results suggest that climate is unlikely to have influenced early stages of range expansion. SDMs that incorporated data from the most recent sampling (2011-2017) performed considerably better, predicted high suitability in regions that have recently become invaded, and identified mean annual temperature as a key factor limiting northward range expansion. Under future climates, models predicted both further northward range expansion and significantly increased suitability across large portions of the U.S. Overall, our results indicate significant challenges for SDMs of invasive species far from climate equilibrium. However, our models based on recent data make more robust predictions for northward range expansion of A. palmeri with climate change.

Sex-biased gene expression in flowers, but not leaves, reveals secondary sexual dimorphism in Populus balsamifera.

Because sexual dimorphism in plants is often less morphologically conspicuous than in animals, studies of sex-biased gene expression may provide a quantitative metric to better address their commonality, molecular pathways, consistency across tissues and taxa, and evolution. The presence of sex-biased gene expression in tissues other than the androecium or gynoecium, termed secondary sexual characters, suggests that these traits arose after the initial evolution of dioecy. Patterns of sequence evolution may provide evidence of positive selection that drove sexual specialization. We compared gene expression in male and female flowers and leaves of Populus balsamifera to assess the extent of sex-biased expression, and tested whether sex-biased genes exhibit elevated rates of protein evolution. Sex-biased expression was pervasive in floral tissue, but nearly absent in leaf tissue. Female-biased genes in flowers were associated with photosynthesis, whereas male-biased genes were associated with mitochondrial function. Sex-biased genes did not exhibit elevated rates of protein evolution, contrary to results from other studies in animals and plants. Our results suggest that the ecological and physiological constraints associated with the energetics of flowering, rather than sexual conflict, have probably shaped the differences in male and female gene expression in P. balsamifera.