MicroRNAs (miRNAs) control expression of endogenous target genes through transcript cleavage or translational inhibition. Legume plants can form a specialized organ, the nodule, through interaction with nitrogen fixing soil bacteria. To understand the regulatory roles of miRNAs in the nodulation process, we functionally validated gma-miR171o and gma-miR171q and their target genes in soybean. These two miRNA sequences are identical in sequence but their miRNA genes are divergent and show unique, tissue-specific expression patterns. The expression levels of the two miRNAs are negatively correlated with that of their target genes. Ectopic expression of these miRNAs in transgenic hairy roots resulted in a significant reduction in nodule formation. Both gma-miR171o and gma-miR171q target members of the GRAS transcription factor superfamily, namely GmSCL-6 and GmNSP2. Transient interaction of miRNAs and their target genes in tobacco cells further confirmed their cleavage activity. The results suggest that gma-miR171o and gma-miR171q regulate GmSCL-6 and GmNSP2, which in turn, influence expression of the Nodule inception (NIN), Early Nodulin 40 (ENOD40), and Ethylene Response Factor Required for Nodulation (ERN) genes during the Bradyrhizobium japonicum-soybean nodulation process. Collectively, our data suggest a role for two miRNAs, gma-miR171o and gma-miR171q, in regulating the spatial and temporal aspects of soybean nodulation.

[This corrects the article DOI: 10.3389/fpls.2019.00475.].

The Soybean Gene Atlas project provides a comprehensive map for understanding gene expression patterns in major soybean tissues from flower, root, leaf, nodule, seed, and shoot and stem. The RNA-Seq data generated in the project serve as a valuable resource for discovering tissue-specific transcriptome behavior of soybean genes in different tissues. We developed a computational pipeline for Soybean context-specific network (SoyCSN) inference with a suite of prediction tools to analyze, annotate, retrieve, and visualize soybean context-specific networks at both transcriptome and interactome levels. BicMix and Cross-Conditions Cluster Detection algorithms were applied to detect modules based on co-expression relationships across all the tissues. Soybean context-specific interactomes were predicted by combining soybean tissue gene expression and protein-protein interaction data. Functional analyses of these predicted networks provide insights into soybean tissue specificities. For example, under symbiotic, nitrogen-fixing conditions, the constructed soybean leaf network highlights the connection between the photosynthesis function and rhizobium-legume symbiosis. SoyCSN data and all its results are publicly available via an interactive web service within the Soybean Knowledge Base (SoyKB) at http://soykb.org/SoyCSN. SoyCSN provides a useful web-based access for exploring context specificities systematically in gene regulatory mechanisms and gene relationships for soybean researchers and molecular breeders.

Target leaf spot (TLS) of sorghum, a foliar disease caused by the necrotrophic fungus Bipolaris cookei (also known as Bipolaris sorghicola), can affect grain yield in sorghum by causing premature drying of leaves and defoliation. Two sorghum recombinant inbred line (RIL) populations, BTx623/BTx642 and BTx623/SC155-14E, were assessed for TLS resistance in replicated trials. Using least square mean trait data, four TLS resistance QTL were identified, two in each population. Of these, three were previously unidentified while a major QTL on chromosome 5 in the BTx623/BTx642 RIL population corresponded to the previously identified TLS resistance gene ds1. A set of sorghum lines were assessed for production of reactive oxygen species induced by treatment with the microbe-associated molecular pattern (MAMP) flg22 (a derivative of flagellin). Flg22-induced ROS production varied between lines in a consistent fashion. One QTL associated with variation in the flg22 response was detected in the RIL populations. No evidence was found to link variation in the MAMP response to variation in TLS resistance.

Plants have the capacity to respond to conserved molecular features known as microbe-associated molecular patterns (MAMPs). The goal of this work was to assess variation in the MAMP response in sorghum, to map loci associated with this variation, and to investigate possible connections with variation in quantitative disease resistance. Using an assay that measures the production of reactive oxygen species, we assessed variation in the MAMP response in a sorghum association mapping population known as the sorghum conversion population (SCP). We identified consistent variation for the response to chitin and flg22-an epitope of flagellin. We identified two SNP loci associated with variation in the flg22 response and one with the chitin response. We also assessed resistance to Target Leaf Spot (TLS) disease caused by the necrotrophic fungus Bipolaris cookei in the SCP. We identified one strong association on chromosome 5 near a previously characterized disease resistance gene. A moderately significant correlation was observed between stronger flg22 response and lower TLS resistance. Possible reasons for this are discussed.

Plants and seeds are the main dietary sources of zinc, iron, manganese, and copper, but are also the main entry point for toxic elements such as cadmium into the food chain. We report here that an Arabidopsis oligopeptide transporter mutant, opt3-2, over-accumulates cadmium (Cd) in seeds and roots but, unexpectedly, under-accumulates Cd in leaves. The cadmium distribution in opt3-2 differs from iron, zinc, and manganese, suggesting a metal-specific mechanism for metal partitioning within the plant. The opt3-2 mutant constitutively up-regulates the Fe/Zn/Cd transporter IRT1 and FRO2 in roots, indicative of an iron-deficiency response. No genetic mutants that impair the shoot-to-root signaling of iron status in leaves have been identified. Interestingly, shoot-specific expression of OPT3 rescues the Cd sensitivity and complements the aberrant expression of IRT1 in opt3-2 roots, suggesting that OPT3 is required to relay the iron status from leaves to roots. OPT3 expression was found in the vasculature with preferential expression in the phloem at the plasma membrane. Using radioisotope experiments, we found that mobilization of Fe from leaves is severely affected in opt3-2, suggesting that Fe mobilization out of leaves is required for proper trace-metal homeostasis. When expressed in yeast, OPT3 does not localize to the plasma membrane, precluding the identification of the OPT3 substrate. Our in planta results show that OPT3 is important for leaf phloem-loading of iron and plays a key role regulating Fe, Zn, and Cd distribution within the plant. Furthermore, ferric chelate reductase activity analyses provide evidence that iron is not the sole signal transferred from leaves to roots in leaf iron status signaling.

The plant rhizosphere harbors a diverse population of microorganisms, including beneficial plant growth-promoting bacteria (PGPB), that colonize plant roots and enhance growth and productivity. In order to specifically define bacterial traits that contribute to this beneficial interaction, we used high-throughput transposon mutagenesis sequencing (TnSeq) in two model root-bacterium systems associated with Setaria viridis: Azoarcus olearius DQS4^T and Herbaspirillum seropedicae SmR1. This approach identified ∼100 significant genes for each bacterium that appeared to confer a competitive advantage for root colonization. Most of the genes identified specifically in A. olearius encoded metabolism functions, whereas genes identified in H. seropedicae were motility related, suggesting that each strain requires unique functions for competitive root colonization. Genes were experimentally validated by site-directed mutagenesis, followed by inoculation of the mutated bacteria onto S. viridis roots individually, as well as in competition with the wild-type strain. The results identify key bacterial functions involved in iron uptake, polyhydroxybutyrate metabolism, and regulation of aromatic metabolism as important for root colonization. The hope is that by improving our understanding of the molecular mechanisms used by PGPB to colonize plants, we can increase the adoption of these bacteria in agriculture to improve the sustainability of modern cropping systems.IMPORTANCE There is growing interest in the use of associative, plant growth-promoting bacteria (PGPB) as biofertilizers to serve as a sustainable alternative for agriculture application. While a variety of mechanisms have been proposed to explain bacterial plant growth promotion, the molecular details of this process remain unclear. The current research supports the idea that PGPB use in agriculture will be promoted by gaining more knowledge as to how these bacteria colonize plants, promote growth, and do so consistently. Specifically, the research seeks to identify those bacterial genes involved in the ability of two, PGPB strains, Azoarcus olearius and Herbaspirillum seropedicae, to colonize the roots of the C4 model grass Setaria viridis. Applying a transposon mutagenesis (TnSeq) approach, we assigned phenotypes and function to genes that affect bacterial competitiveness during root colonization. The results suggest that each bacterial strain requires unique functions for root colonization but also suggests that a few, critical functions are needed by both bacteria, pointing to some common mechanisms. The hope is that such information can be exploited to improve the use and performance of PGPB in agriculture.

Background

The circadian clock regulates plant metabolic functions and is an important component in plant health and productivity. Rhizosphere bacteria play critical roles in plant growth, health, and development and are shaped primarily by soil communities. Using Illumina next-generation sequencing and high-resolution mass spectrometry, we characterized bacterial communities of wild-type (Col-0) Arabidopsis thaliana and an acyclic line (OX34) ectopically expressing the circadian clock-associated cca1 transcription factor, relative to a soil control, to determine how cycling dynamics affected the microbial community. Microbial communities associated with Brachypodium distachyon (BD21) were also evaluated.

Results

Significantly different bacterial community structures (P = 0.031) were observed in the rhizosphere of wild-type plants between light and dark cycle samples. Furthermore, 13% of the community showed cycling, with abundances of several families, including Burkholderiaceae, Rhodospirillaceae, Planctomycetaceae, and Gaiellaceae, exhibiting fluctuation in abundances relative to the light cycle. However, limited-to-no cycling was observed in the acyclic CCAox34 line or in soil controls. Significant cycling was also observed, to a lesser extent, in Brachypodium. Functional gene inference revealed that genes involved in carbohydrate metabolism were likely more abundant in near-dawn, dark samples. Additionally, the composition of organic matter in the rhizosphere showed a significant variation between dark and light cycles.

Conclusions

The results of this study suggest that the rhizosphere bacterial community is regulated, to some extent, by the circadian clock and is likely influenced by, and exerts influences, on plant metabolism and productivity. The timing of bacterial cycling in relation to that of Arabidopsis further suggests that diurnal dynamics influence plant-microbe carbon metabolism and exchange. Equally important, our results suggest that previous studies done without relevance to time of day may need to be reevaluated with regard to the impact of diurnal cycles on the rhizosphere microbial community.

We report reference-quality genome assemblies and annotations for two accessions of soybean (Glycine max) and for one accession of Glycine soja, the closest wild relative of G. max. The G. max assemblies provided are for widely used US cultivars: the northern line Williams 82 (Wm82) and the southern line Lee. The Wm82 assembly improves the prior published assembly, and the Lee and G. soja assemblies are new for these accessions. Comparisons among the three accessions show generally high structural conservation, but nucleotide difference of 1.7 single-nucleotide polymorphisms (snps) per kb between Wm82 and Lee, and 4.7 snps per kb between these lines and G. soja. snp distributions and comparisons with genotypes of the Lee and Wm82 parents highlight patterns of introgression and haplotype structure. Comparisons against the US germplasm collection show placement of the sequenced accessions relative to global soybean diversity. Analysis of a pan-gene collection shows generally high conservation, with variation occurring primarily in genomically clustered gene families. We found approximately 40-42 inversions per chromosome between either Lee or Wm82v4 and G. soja, and approximately 32 inversions per chromosome between Wm82 and Lee. We also investigated five domestication loci. For each locus, we found two different alleles with functional differences between G. soja and the two domesticated accessions. The genome assemblies for multiple cultivated accessions and for the closest wild ancestor of soybean provides a valuable set of resources for identifying causal variants that underlie traits for the domestication and improvement of soybean, serving as a basis for future research and crop improvement efforts for this important crop species.

High-throughput RNA sequencing (RNA-seq) has recently become the method of choice to define and analyze transcriptomes. For the model moss Physcomitrella patens, although this method has been used to help analyze specific perturbations, no overall reference dataset has yet been established. In the framework of the Gene Atlas project, the Joint Genome Institute selected P. patens as a flagship genome, opening the way to generate the first comprehensive transcriptome dataset for this moss. The first round of sequencing described here is composed of 99 independent libraries spanning 34 different developmental stages and conditions. Upon dataset quality control and processing through read mapping, 28 509 of the 34 361 v3.3 gene models (83%) were detected to be expressed across the samples. Differentially expressed genes (DEGs) were calculated across the dataset to permit perturbation comparisons between conditions. The analysis of the three most distinct and abundant P. patens growth stages - protonema, gametophore and sporophyte - allowed us to define both general transcriptional patterns and stage-specific transcripts. As an example of variation of physico-chemical growth conditions, we detail here the impact of ammonium supplementation under standard growth conditions on the protonemal transcriptome. Finally, the cooperative nature of this project allowed us to analyze inter-laboratory variation, as 13 different laboratories around the world provided samples. We compare differences in the replication of experiments in a single laboratory and between different laboratories.