Soybean miR159-GmMYB33 Regulatory Network Involved in Gibberellin-Modulated Resistance to Heterodera glycines

Soybean cyst nematode (SCN, Heterodera glycines) is an obligate sedentary biotroph that poses major threats to soybean production globally. Recently, multiple miRNAome studies revealed that miRNAs participate in complicated soybean-SCN interactions by regulating their target genes. However, the functional roles of miRNA and target genes regulatory network are still poorly understood. In present study, we firstly investigated the expression patterns of miR159 and targeted GmMYB33 genes. The results showed miR159-3p downregulation during SCN infection; conversely, GmMYB33 genes upregulated. Furthermore, miR159 overexpressing and silencing soybean hairy roots exhibited strong resistance and susceptibility to H. glycines, respectively. In particular, miR159-GAMYB genes are reported to be involve in GA signaling and metabolism. Therefore, we then investigated the effects of GA application on the expression of miR159-GAMYB module and the development of H. glycines. We found that GA directly controls the miR159-GAMYB module, and exogenous GA application enhanced endogenous biologically active GA1 and GA3, the abundance of miR159, lowered the expression of GmMYB33 genes and delayed the development of H. glycines. Moreover, SCN infection also results in endogenous GA content decreased in soybean roots. In summary, the soybean miR159-GmMYB33 module was directly involved in the GA-modulated soybean resistance to H. glycines.

Rhizobium Symbiotic Capacity Shapes Root-Associated Microbiomes in Soybean

Root-microbiome interactions are of central importance for plant performance and yield. A distinctive feature of legumes is that they engage in symbiosis with N2-fixing rhizobia. If and how the rhizobial symbiotic capacity modulates root-associated microbiomes are still not yet well understood. We determined root-associated microbiomes of soybean inoculated with wild type (WT) or a noeI mutant of Bradyrhizobium diazoefficiens USDA 110 by amplicon sequencing. UPLC-MS/MS was used to analyze root exudates. The noeI gene is responsible for fucose-methylation of Nod factor secreted by USDA 110 WT strain. Soybean roots inoculated with the noeI mutant showed a significant decrease in nodulation and root-flavonoid exudation compared to roots inoculated with WT strain. The noeI mutant-inoculated roots exhibited strong changes in microbiome assembly in the rhizosphere and rhizoplane, including reduced diversity, changed co-occurrence interactions and a substantial depletion of root microbes. Root exudates and soil physiochemical properties were significantly correlated with microbial community shift in the rhizosphere between different rhizobial treatments. These results illustrate that rhizobial symbiotic capacity dramatically alters root-associated microbiomes, in which root exudation and edaphic patterns play a vital role. This study has important implications for understanding the evolution of plant-microbiome interactions.

Effects of manganese toxicity on the growth of soybean (Glycine max L.) at the seedling stage

Effects of manganese (Mn) toxicity stress on the growth of soybean, the number of Mn spots on leaves and the absorption of iron and magnesium were studied by nutrient solution hydroponics. The results showed that the presence of Mn spots on leaves was the main symptom of Mn toxicity in soybean. When the concentration of exogenous Mn was 25 μmol/l, the leaf generated obvious Mn oxidation spots; when the concentration of exogenous Mn exceeded 50 μmol/l, the growth of soybean was inhibited, and the number of Mn spots increased significantly. With the increase in exogenous Mn concentration, the Mn concentration in the roots, young leaves and old leaves of soybean increased significantly. When the concentration of exogenous Mn reached 200 μmol/l, the number of Mn spots on primary leaves, old leaves and young leaves increased significantly. Although the iron concentration in the roots remained the same, the iron content in the old and young leaves decreased significantly. On the other hand, although Mn toxicity significantly reduced the concentration of magnesium in soybean roots, it increased the concentration of magnesium in old and young leaves. Bangladesh J. Bot. 50(3): 803-811, 2021 (September) Special

Comparative root transcriptome analysis of two soybean cultivars with different cadmium sensitivities reveals the underlying tolerant mechanisms

The soybean can provide rich protein and fat and has great economic value worldwide. Cadmium (Cd) is a toxic heavy metal to organisms. It can accumulate in plants and be transmitted to the human body via food chain. Cd is a serious threat to soybean development, especially to root growth. Some soybean cultivars present tolerant symptoms under Cd stress; however, the potential mechanisms are not fully understood. Here, we optimized RNA-seq to identify the differentially expressed genes (DEGs) in Cd-sensitive (KUAI) and Cd-tolerant (KAIYU) soybean roots and compared the DEGs between KAIYU and KUAI. A total of 1,506 and 1,870 DEGs were identified in the roots of KUAI and KAIYU, respectively. Through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and gene function analyses, we found that genes related to antioxidants and sequestration were responsible for Cd tolerance in KAIYU. In addition, overexpression of Glyma11g02661, which encodes a heavy metal transporting ATPase, significantly improved Cd tolerance in transgenic hairy roots. These results provide a preliminary understanding of the tolerance mechanisms in response to Cd stress in soybean root development and are of great importance in developing Cd-resistant soybean cultivars by using the identified DEGs through genetic modification.

Effects of Irrigation and Bioproducts of Microbial Origin on Nematode Community and Mycorrhizal Root Colonization in Soybean

Soybean (Glycine max L. Merr) is the most important legume and threaten by diverse pests and diseases. Complex interactions among rhizosphere organisms are found in all agro-ecosystems. Results of these interactions can be positive and/or negative in terms of plant production. Soil nematode community consists of different trophic groups of nematodes. Nematodes are the most abundant soil invertebrates. Several nematode species penetrate soybean roots as parasites, and can cause loss in yields. Arbuscular mycorrhiza fungi are obligate plant symbionts that colonize soybean roots naturally. The aim of the study was to evaluate effects of irrigation and amendments of bioproducts containing beneficial soil microorganisms (ABM) on nematode community and mycorrhizal root colonization in soybean. Field experiments were conducted in soybean in 2013 in Osijek, Croatia. The plots were either rain fed or irrigated to 60-100% field water capacity (FWC). We tested soil amendments and soil + foliar amendments of three commercial products containing beneficial organisms. Average number of nematodes per soil sample varied from 186,67 (soil ABM in non-irrigated plots) to 297,57 (soil+foliar ABM in plots with 60-100% FWC), and there were no significant differences between the treatments. Bacterial feeding nematodes were the most abundant, while plant parasitic genus Pratylenchus was the most abundant among other plant parasitic nematodes. There was no clear influence of any of the treatments on soil nematode community. Amendments of the bioproducts increased mycorrhizal root colonization in rain fed plots, while it decreased the mycorrhizal root colonization when soybeans were irrigated. Irrigation increased mycorrhizal root colonization in plots without amendments of the bioproducts, and mycorrhizal colonization differed significantly between the sampling dates. Further research is needed to determine if irrigation alters the potential of mycorrhiza to colonize the roots.

Cover crop increases soybean yield cropped after degraded pasture in sandy soil

ABSTRACT Soybean cropping has been growing in recent years in environments with sandy soils and with climatic risk, but yield is low, especially in the early years. The objective of this study was to evaluate the effect of cover crops and nitrogen management in a sandy soil previously under degraded pastures on soybean yield. The study was conducted in Western São Paulo state, Brazil. The experimental design was randomized blocks, with four replicates, and the treatments were: black oats; black oats + 50 kg ha-1 of N in black oats; black oats + 50 kg ha-1 of N in soybean; black oats + lupine; black oats + lupine + 50 kg ha-1 of N in soybean; lupine; fallow; fallow + 50 kg ha-1 of N in soybean. Nitrogen concentration of the microbial biomass was higher with oats + N in soybean applied at the beginning of flowering (R1). The number of nodules in soybean roots increased by 2.3 times with oats and oats + N in soybean as compared to fallow. Soybean yield was higher in treatments with oats + N in oats (2,130 kg ha-1), oats (2,038 kg ha-1) and oats + N in soybean (1,872 kg ha-1). In the absence of cover crops, N fertilization in soybean increased yield by 19% (262 kg ha-1) compared to fallow. Black oats are the best option to increase soybean yield. However, in the absence of cover crops, nitrogen fertilization in soybean is necessary.

Using Machine Learning to Develop a Fully Automated Soybean Nodule Acquisition Pipeline (SNAP)

Nodules form on plant roots through the symbiotic relationship between soybean (Glycine max L. Merr.) roots and bacteria (Bradyrhizobium japonicum) and are an important structure where atmospheric nitrogen (N2) is fixed into bioavailable ammonia (NH3) for plant growth and development. Nodule quantification on soybean roots is a laborious and tedious task; therefore, assessment is frequently done on a numerical scale that allows for rapid phenotyping, but is less informative and suffers from subjectivity. We report the Soybean Nodule Acquisition Pipeline (SNAP) for nodule quantification that combines RetinaNet and UNet deep learning architectures for object (i.e., nodule) detection and segmentation. SNAP was built using data from 691 unique roots from diverse soybean genotypes, vegetative growth stages, and field locations and has a good model fit (R2=0.99). SNAP reduces the human labor and inconsistencies of counting nodules, while acquiring quantifiable traits related to nodule growth, location, and distribution on roots. The ability of SNAP to phenotype nodules on soybean roots at a higher throughput enables researchers to assess the genetic and environmental factors, and their interactions on nodulation from an early development stage. The application of SNAP in research and breeding pipelines may lead to more nitrogen use efficiency for soybean and other legume species cultivars, as well as enhanced insight into the plant-Bradyrhizobium relationship.

Effects of Rhizophagus intraradices on Plant Growth and the Composition of Microbial Communities in the Roots of Continuous Cropping Soybean at Maturity

Soybean is the major food and oil crop in the world. However, soybean continuous cropping can significantly reduce soybean yield. In this study, the effects of Rhizophagus intraradices on soybean growth and the composition of microbial communities in soybean roots under different continuous cropping regimes were investigated at maturity. The results showed that the mycorrhizal colonization rate was affected by R. intraradices and soybean continuous cropping. The mycorrhizal colonization rate was the highest in the inoculated soybean plants under 1 year of continuous cropping. Inoculation of R. intraradices significantly increased soybean plant growth. The greatest biomass parameters were obtained from the soybean plants inoculated with R. intraradices under 0 years of continuous cropping. Bacterial diversity was decreased by soybean continuous cropping, while the opposite result occurred for fungal diversity. Moreover, inoculation of R. intraradices could increase and decrease the diversity of bacteria and fungi in soybean roots, respectively. It also indicated that R. intraradices and soybean continuous cropping had significant effects on the composition of microbial communities in soybean roots. Proteobacteria and Ascomycota were the most dominant bacterial and fungal phylum in all samples, respectively. It would contribute to developing a biocontrol strategy to alleviate the soybean continuous cropping obstacles.