Fine-scale characterization of the soybean rhizosphere microbiome via synthetic long reads and avidity sequencing.

BACKGROUND: The rhizosphere microbiome displays structural and functional dynamism driven by plant, microbial, and environmental factors. While such plasticity is a well-evidenced determinant of host health, individual and community-level microbial activity within the rhizosphere remain poorly understood, due in part to the insufficient taxonomic resolution achieved through traditional marker gene amplicon sequencing. This limitation necessitates more advanced approaches (e.g., long-read sequencing) to derive ecological inferences with practical application. To this end, the present study coupled synthetic long-read technology with avidity sequencing to investigate eukaryotic and prokaryotic microbiome dynamics within the soybean (Glycine max) rhizosphere under field conditions. RESULTS: Synthetic long-read sequencing permitted de novo reconstruction of the entire 18S-ITS1-ITS2 region of the eukaryotic rRNA operon as well as all nine hypervariable regions of the 16S rRNA gene. All full-length, mapped eukaryotic amplicon sequence variants displayed genus-level classification, and 44.77% achieved species-level classification. The resultant eukaryotic microbiome encompassed five kingdoms (19 genera) of protists in addition to fungi - a depth unattainable with conventional short-read methods. In the prokaryotic fraction, every full-length, mapped amplicon sequence variant was resolved at the species level, and 23.13% at the strain level. Thirteen species of Bradyrhizobium were thereby distinguished in the prokaryotic microbiome, with strain-level identification of the two Bradyrhizobium species most reported to nodulate soybean. Moreover, the applied methodology delineated structural and compositional dynamism in response to experimental parameters (i.e., growth stage, cultivar, and biostimulant application), unveiled a saprotroph-rich core microbiome, provided empirical evidence for host selection of mutualistic taxa, and identified key microbial co-occurrence network members likely associated with edaphic and agronomic properties. CONCLUSIONS: This study is the first to combine synthetic long-read technology and avidity sequencing to profile both eukaryotic and prokaryotic fractions of a plant-associated microbiome. Findings herein provide an unparalleled taxonomic resolution of the soybean rhizosphere microbiota and represent significant biological and technological advancements in crop microbiome research.

Correction: Hale et al. Differential Expression Profiling Reveals Stress-Induced Cell Fate Divergence in Soybean Microspores. Plants 2020, 9, 1510.

In the original publication [...].

Gene regulatory network inference in soybean upon infection by Phytophthora sojae.

Phytophthora sojae is a soil-borne oomycete and the causal agent of Phytophthora root and stem rot (PRR) in soybean (Glycine max [L.] Merrill). Yield losses attributed to P. sojae are devastating in disease-conducive environments, with global estimates surpassing 1.1 million tonnes annually. Historically, management of PRR has entailed host genetic resistance (both vertical and horizontal) complemented by disease-suppressive cultural practices (e.g., oomicide application). However, the vast expansion of complex and/or diverse P. sojae pathotypes necessitates developing novel technologies to attenuate PRR in field environments. Therefore, the objective of the present study was to couple high-throughput sequencing data and deep learning to elucidate molecular features in soybean following infection by P. sojae. In doing so, we generated transcriptomes to identify differentially expressed genes (DEGs) during compatible and incompatible interactions with P. sojae and a mock inoculation. The expression data were then used to select two defense-related transcription factors (TFs) belonging to WRKY and RAV families. DNA Affinity Purification and sequencing (DAP-seq) data were obtained for each TF, providing putative DNA binding sites in the soybean genome. These bound sites were used to train Deep Neural Networks with convolutional and recurrent layers to predict new target sites of WRKY and RAV family members in the DEG set. Moreover, we leveraged publicly available Arabidopsis (Arabidopsis thaliana) DAP-seq data for five TF families enriched in our transcriptome analysis to train similar models. These Arabidopsis data-based models were used for cross-species TF binding site prediction on soybean. Finally, we created a gene regulatory network depicting TF-target gene interactions that orchestrate an immune response against P. sojae. Information herein provides novel insight into molecular plant-pathogen interaction and may prove useful in developing soybean cultivars with more durable resistance to P. sojae.

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.

Amelioration of AsV toxicity by concurrent application of ZnO-NPs and Se-NPs is associated with differential regulation of photosynthetic indexes, antioxidant pool and osmolytes content in soybean seedling.

Arsenic is a significant food safety and environmental concern due to its mutagenic and carcinogenic effect on living organism. Soybean (Glycine max [L.] Merrill) is a global staple crop grown intensively in arsenic-contaminated regions of the world (e.g., Southern Province of China). Therefore, the objective of this study was to investigate whether Se-NPs and/or ZnO-NPs could be used as an eco-friendly and efficient amendment to reduce arsenic uptake and toxicity in soybean. Ten-days-old seedling, grown in vermiculite, were transferred to hydroponic media and further grown till V2 growth stage appeared. AsV (25 µM Na2HAsO4) stressed plants were treated with ZnONP (25 µM ZnO) and SeNP (25 µM Se) separately and in combination, which were grown for another 10 d. The result demonstrated that arsenic-treated soybean plants displayed a reduction in photosynthetic efficiency, increased proline and glycine betaine accumulation in tissues, and altered antioxidant activity compared to an untreated control. The application of zinc oxide and selenium nanoparticles, both independently and in tandem, reduced arsenic stress in root and shoot tissues and rescued plant health. This was reflected through increased levels of reduced glutathione content, ascorbic acid, and various photosynthesis- and antioxidant-relevant enzymes. In addition, nanoparticle-treated soybean plants displayed higher expression of defense- and detoxification-related genes compared to controls. Cellular toxicants (i.e., oxidized glutathione, reactive oxygen species, and malondialdehyde) were reduced upon nanoparticle treatment. These data collectively suggest that selenium and zinc oxide nanoparticles may be a solution to ameliorate arsenic toxicity in agricultural soils and crop plants.

Androgenesis-Based Doubled Haploidy: Past, Present, and Future Perspectives.

Androgenesis, which entails cell fate redirection within the microgametophyte, is employed widely for genetic gain in plant breeding programs. Moreover, androgenesis-responsive species provide tractable systems for studying cell cycle regulation, meiotic recombination, and apozygotic embryogenesis within plant cells. Past research on androgenesis has focused on protocol development with emphasis on temperature pretreatments of donor plants or floral buds, and tissue culture optimization because androgenesis has different nutritional requirements than somatic embryogenesis. Protocol development for new species and genotypes within responsive species continues to the present day, but slowly. There is more focus presently on understanding how protocols work in order to extend them to additional genotypes and species. Transcriptomic and epigenetic analyses of induced microspores have revealed some of the cellular and molecular responses required for or associated with androgenesis. For example, microRNAs appear to regulate early microspore responses to external stimuli; trichostatin-A, a histone deacetylase inhibitor, acts as an epigenetic additive; ά-phytosulfokine, a five amino acid sulfated peptide, promotes androgenesis in some species. Additionally, present work on gene transfer and genome editing in microspores suggest that future endeavors will likely incorporate greater precision with the genetic composition of microspores used in doubled haploid breeding, thus likely to realize a greater impact on crop improvement. In this review, we evaluate basic breeding applications of androgenesis, explore the utility of genomics and gene editing technologies for protocol development, and provide considerations to overcome genotype specificity and morphogenic recalcitrance in non-model plant systems.

Differential Expression Profiling Reveals Stress-Induced Cell Fate Divergence in Soybean Microspores.

Stress-induced microspore embryogenesis is a widely employed method to achieve homozygosity in plant breeding programs. However, the molecular mechanisms that govern gametophyte de- and redifferentiation are understood poorly. In this study, RNA-Seq was used to evaluate global changes across the microspore transcriptome of soybean (Glycine max [L.] Merrill) as a consequence of pretreatment low-temperature stress. Expression analysis revealed more than 20,000 differentially expressed genes between treated and control microspore populations. Functional enrichment illustrated that many of these genes (e.g., those encoding heat shock proteins and cytochrome P450s) were upregulated to maintain cellular homeostasis through the mitigation of oxidative damage. Moreover, transcripts corresponding to saccharide metabolism, vacuolar transport, and other pollen-related developmental processes were drastically downregulated among treated microspores. Temperature stress also triggered cell wall modification and cell proliferation-characteristics that implied putative commitment to an embryonic pathway. These findings collectively demonstrate that pretreatment cold stress induces soybean microspore reprogramming through suppression of the gametophytic program while concomitantly driving sporophytic development.