Metagenomic study reveals hidden relationships among fungal diversity, variation of plant disease, and genetic distance in Cornus florida (Cornaceae).

Introduction: Understanding patterns of plant-microbe interactions across plant species and populations is a critical yet poorly characterized aspect in the field of plant pathology. Microbial DNA sequences present as contaminants in omics data of plants obtained using next-generation sequencing methods provide a valuable source to explore the relationships among endophytic microbial diversity, disease and genetic differentiation of host plants, and environmental variation, but few such studies have been conducted. The flowering dogwood tree (Cornus florida L.), an ecologically important species in North America, is threatened by powdery mildew and dogwood anthracnose diseases, and knowledge of the microbial diversity harbored within genetically and environmental distinct populations of this species remains largely unknown. Methods: We conducted a metagenomics study utilizing the sequences of RAD-tag/genotype-by-sequence libraries from leaf tissues of C. florida to examine such host-fungus interactions across the dogwood's US range. We performed various combinations of alignments to both host and pathogen genomes to obtain filtered sets sequences for metagenomics analysis. Taxonomic assignments were determined on each filtered set of sequences, followed by estimation of microbial diversity and correlation to environment and host-genetic variation. Results: Our data showed that microbial community composition significantly differed between visually healthy and diseased sites. Several microbial taxa known to interact with dogwood were identified from these sequences. We found no correlation between microbial diversity and relative abundances of sequences aligning to draft genomes of either pathogen causing powdery mildew or dogwood anthracnose. We found a significant relationship between differences of fungal communities and geographic distances of plant populations, suggesting roles of environments in shaping fungal communities in leaf tissues. Significant correlations between the genetic differentiation of plant samples and fungal community dissimilarity (beta diversity) were also observed in certain sets of our analyses-suggesting the possibility of a relationship between microbial community composition and plant genetic distance. This relationship persisted in significance even after controlling for significant effects of geographic-bioclimatic variation of microbial diversity. Discussion: Our results suggest that both genetics and the environment play a significant role in shaping foliar fungal communities. Our findings underscore the power of leveraging hidden microbial sequences within datasets originally collected for plant genetic studies to understand plant-pathogen interactions.

Discovering variation of secondary metabolite diversity and its relationship with disease resistance in Cornus florida L.

Understanding intraspecific relationships between genetic and functional diversity is a major goal in the field of evolutionary biology and is important for conserving biodiversity. Linking intraspecific molecular patterns of plants to ecological pressures and trait variation remains difficult due to environment-driven plasticity. Next-generation sequencing, untargeted liquid chromatography-mass spectrometry (LC-MS) profiling, and interdisciplinary approaches integrating population genomics, metabolomics, and community ecology permit novel strategies to tackle this problem. We analyzed six natural populations of the disease-threatened Cornus florida L. from distinct ecological regions using genotype-by-sequencing markers and LC-MS-based untargeted metabolite profiling. We tested the hypothesis that higher genetic diversity in C. florida yielded higher chemical diversity and less disease susceptibility (screening hypothesis), and we also determined whether genetically similar subpopulations were similar in chemical composition. Most importantly, we identified metabolites that were associated with candidate loci or were predictive biomarkers of healthy or diseased plants after controlling for environment. Subpopulation clustering patterns based on genetic or chemical distances were largely congruent. While differences in genetic diversity were small among subpopulations, we did observe notable similarities in patterns between subpopulation averages of rarefied-allelic and chemical richness. More specifically, we found that the most abundant compound of a correlated group of putative terpenoid glycosides and derivatives was correlated with tree health when considering chemodiversity. Random forest biomarker and genomewide association tests suggested that this putative iridoid glucoside and other closely associated chemical features were correlated to SNPs under selection.

Resolving relationships and phylogeographic history of the Nyssa sylvatica complex using data from RAD-seq and species distribution modeling.

Nyssa sylvatica complex consists of several woody taxa occurring in eastern North America. These taxa were recognized as two or three species including three or four varieties by different authors. Due to high morphological similarities and complexity of morphological variation, classification and delineation of taxa in the group have been difficult and controversial. Here we employ data from RAD-seq to elucidate the genetic structure and phylogenetic relationships within the group. Using the genetic evidence, we evaluate previous classifications and delineate species. We also employ Species Distribution Modeling (SDM) to evaluate impacts of climatic changes on the ranges of the taxa and to gain insights into the relevant refugia in eastern North America. Results from Molecular Variance Analysis (AMOVA), STRUCTURE, phylogenetic analyses using Maximum likelihood, Bayesian Inference, and Splittree methods of RAD-seq data strongly support a two-clade pattern, largely separating samples of N. sylvatica from those of N. biflora-N. ursina mix. Divergence time analysis with BEAST suggests the two clades diverged in the mid Miocene. The ancestor of the present trees of N. sylvatica was suggested to be in the Pliocene and that of N. biflora-N. ursina mix in the end of the Miocene. Results from SDM predicted a smaller range in the southern part of the species present range of each clade during the Last Glacial Maximum (LGM). A northward expansion of the ranges during interglacial period and a northward shift of the ranges in the future under a model of global warming were also predicted. Our results support the recognition of two species in the complex, N. sylvatica and N. biflora, following the phylogenetic species concept. We found no genetic evidence supporting recognitions of intraspecific taxa. However, we propose subsp. ursina and subsp. biflora within N. biflora due to their distinction in habits, distributions, and habitats. Our results further support movements of trees in eastern North America in response to climatic changes. Finally, our study demonstrates that RAD-seq data and a combination of population genomics and SDM are valuable in resolving relationship and biogeographic history of closely related species that are taxonomically difficult.

Ecological genomics of local adaptation in Cornus florida L. by genotyping by sequencing.

Discovering local adaptation, its genetic underpinnings, and environmental drivers is important for conserving forest species. Ecological genomic approaches coupled with next-generation sequencing are useful means to detect local adaptation and uncover its underlying genetic basis in nonmodel species. We report results from a study on flowering dogwood trees (Cornus florida L.) using genotyping by sequencing (GBS). This species is ecologically important to eastern US forests but is severely threatened by fungal diseases. We analyzed subpopulations in divergent ecological habitats within North Carolina to uncover loci under local selection and associated with environmental-functional traits or disease infection. At this scale, we tested the effect of incorporating additional sequencing before scaling for a broader examination of the entire range. To test for biases of GBS, we sequenced two similarly sampled libraries independently from six populations of three ecological habitats. We obtained environmental-functional traits for each subpopulation to identify associations with genotypes via latent factor mixed modeling (LFMM) and gradient forests analysis. To test whether heterogeneity of abiotic pressures resulted in genetic differentiation indicative of local adaptation, we evaluated Fst per locus while accounting for genetic differentiation between coastal subpopulations and Piedmont-Mountain subpopulations. Of the 54 candidate loci with sufficient evidence of being under selection among both libraries, 28-39 were Arlequin-BayeScan Fst outliers. For LFMM, 45 candidates were associated with climate (of 54), 30 were associated with soil properties, and four were associated with plant health. Reanalysis of combined libraries showed that 42 candidate loci still showed evidence of being under selection. We conclude environment-driven selection on specific loci has resulted in local adaptation in response to potassium deficiencies, temperature, precipitation, and (to a marginal extent) disease. High allele turnover along ecological gradients further supports the adaptive significance of loci speculated to be under selection.