Soil indigenous microbiome and plant genotypes cooperatively modify soybean rhizosphere microbiome assembly

Background: Plants have evolved intimate interactions with soil microbes for a range of beneficial functions including nutrient acquisition, pathogen resistance and stress tolerance. Further understanding of this system is a promising way to advance sustainable agriculture by exploiting the versatile benefits offered by the plant microbiome. The rhizosphere is the interface between plant and soil, and functions as the first step of plant defense and root microbiome recruitment. It features a specialized microbial community, intensive microbe-plant and microbe-microbe interactions, and complex signal communication. To decipher the rhizosphere microbiome assembly of soybean (Glycine max), we comprehensively characterized the soybean rhizosphere microbial community using 16S rRNA gene sequencing and evaluated the structuring influence from both host genotype and soil source. Results: Comparison of the soybean rhizosphere to bulk soil revealed significantly different microbiome composition, microbe-microbe interactions and metabolic capacity. Soil type and soybean genotype cooperatively modulated microbiome assembly with soil type predominantly shaping rhizosphere microbiome assembly while host genotype slightly tuned this recruitment process. The undomesticated progenitor species, Glycine soja, had higher rhizosphere diversity in both soil types tested in comparison to the domesticated soybean genotypes. Rhizobium, Novosphingobium, Phenylobacterium, Streptomyces, Nocardioides, etc. were robustly enriched in soybean rhizosphere irrespective of the soil tested. Co-occurrence network analysis revealed dominant soil type effects and genotype specific preferences for key microbe-microbe interactions. Functional prediction results demonstrated converged metabolic capacity in the soybean rhizosphere between soil types and among genotypes, with pathways related to xenobiotic degradation, plant-microbe interactions and nutrient transport being greatly enriched in the rhizosphere. Conclusion: This comprehensive comparison of the soybean microbiome between soil types and genotypes expands our understanding of rhizosphere microbe assembly in general and provides foundational information for soybean as a legume crop for this assembly process. The cooperative modulating role of the soil type and host genotype emphasizes the importance of integrated consideration of soil condition and plant genetic variability for future development and application of synthetic microbiomes. Additionally, the detection of the tuning role by soybean genotype in rhizosphere microbiome assembly provides a promising way for future breeding programs to integrate host traits participating in beneficial microbiota assembly

Soil indigenous microbiome and plant genotypes cooperatively modify soybean rhizosphere microbiome assembly

Background Plants have evolved intimate interactions with soil microbes for a range of beneficial functions including nutrient acquisition, pathogen resistance and stress tolerance. Further understanding of this system is a promising way to advance sustainable agriculture by exploiting the versatile benefits offered by the plant microbiome. The rhizosphere is the interface between plant and soil, and functions as the first step of plant defense and root microbiome recruitment. It features a specialized microbial community, intensive microbe-plant and microbe-microbe interactions, and complex signal communication. To decipher the rhizosphere microbiome assembly of soybean (Glycine max), we comprehensively characterized the soybean rhizosphere microbial community using 16S rRNA gene sequencing and evaluated the structuring influence from both host genotype and soil source. Results Comparison of the soybean rhizosphere to bulk soil revealed significantly different microbiome composition, microbe-microbe interactions and metabolic capacity. Soil type and soybean genotype cooperatively modulated microbiome assembly with soil type predominantly shaping rhizosphere microbiome assembly while host genotype slightly tuned this recruitment process. The undomesticated progenitor species, Glycine soja, had higher rhizosphere diversity in both soil types tested in comparison to the domesticated soybean genotypes. Rhizobium, Novosphingobium, Phenylobacterium, Streptomyces, Nocardioides,etc. were robustly enriched in soybean rhizosphere irrespective of the soil tested. Co-occurrence network analysis revealed dominant soil type effects and genotype specific preferences for key microbe-microbe interactions. Functional prediction results demonstrated converged metabolic capacity in the soybean rhizosphere between soil types and among genotypes, with pathways related to xenobiotic degradation, plant-microbe interactions and nutrient transport being greatly enriched in the rhizosphere. Conclusion This comprehensive comparison of the soybean microbiome between soil types and genotypes expands our understanding of rhizosphere microbe assembly in general and provides foundational information for soybean as a legume crop for this assembly process. The cooperative modulating role of the soil type and host genotype emphasizes the importance of integrated consideration of soil condition and plant genetic variability for future development and application of synthetic microbiomes. Additionally, the detection of the tuning role by soybean genotype in rhizosphere microbiome assembly provides a promising way for future breeding programs to integrate host traits participating in beneficial microbiota assembly

Development and Phenotypic Screening of an Ethyl Methane Sulfonate Mutant Population in Soybean

Soybean is an important oil-producing crop in the Fabaceae family and there are increasing demands for soybean oil and other soybean products. Genetic improvement of soybean is needed to increase its production. In order to provide genetic diversity and resources for identifying important genes, a new ethyl methane sulfonate (EMS) mutagenized soybean population was generated using the newly released germplasm, JTN-5203 (maturity group V). Treatment of soybean seeds with 60 mM EMS concentration was found to be suitable for inducing mutation. A total of 1,820 M1 individuals were produced from 15,000 treated seeds. The resulting M2 population was planted in the field for phenotyping. After harvest, seed traits including total oil, protein, starch, moisture content, fatty acid and amino acid compositions were measured by NIR. Phenotypic variations observed in this population include changes in leaf morphology, plant architecture, seed compositions, and yield. Of most interest, we identified plants with increased amounts of total protein (50% vs. 41% for control) and plants with higher amounts of total oil (25% vs. 21.2% control). Similarly, we identified plants with increases in oleic acid content and decreases in linoleic acid and linolenic acid. This EMS mutant population will be used for further studies including screening for various traits such as amino acid pathways, allergens, phytic acids, and other important soybean agronomic traits. In addition, these mutant individuals will be evaluated in the next generation to assess the heritability. Beneficial traits from these mutants can be exploited for future soybean breeding programs. This germplasm can also be used for discovering novel mutant alleles and for functional gene expression analysis using reverse genetics tools such as TILLING

The methylome of soybean roots during the compatible interaction with the soybean cyst nematode, Heterodera glycines

Soybean cyst nematode (SCN, Heterodera glycines) induces the formation of a multinucleated feeding site, or syncytium, whose etiology includes massive gene expression changes. Nevertheless, the genetic networks underlying gene expression control in the syncytium are poorly understood. DNA methylation is a critical epigenetic mark that plays a key role in regulating gene expression. To determine the extent to which DNA methylation is altered in soybean roots during the susceptible interaction with SCN, we generated whole-genome cytosine methylation maps at single nucleotide resolution. The methylome analysis revealed that SCN induces hypo-methylation to a much higher extent than hyper-methylation. We identified 2,465 differentially hyper-methylated regions and 4,692 hypo-methylated regions in the infected roots compared with the non-infected control. In addition, a total number of 703 and 1346 unique genes were identified as overlapping with hyper- or hypo-methylated regions, respectively. The differential methylation in genes apparently occurs independently of gene size and GC content but exhibits strong preference for recently duplicated paralogs. Furthermore, a set of 278 genes was identified as specifically syncytium differentially methylated genes. Of these, we found genes associated with epigenetic regulation, phytohormone signaling, cell wall architecture, signal transduction and ubiquitination. This study provides new evidence that differential methylation is part of the regulatory mechanisms controlling gene expression changes in the nematode-induced syncytium, which seems to be heavily influenced by the traditional well-known transcription factor-based regulatory mechanisms

Inheritance of Early Stomatal Closure Trait in Soybean: Ellis × N09-13890 Population

Drought conditions exhibit various physiological and morphological changes in crops and thus reduce crop growth and yield. In order to mitigate the negative impacts of drought stress on soybean (Glycine max L. Merr.) production, identification and selection of genotypes that are best adapted to limited water availability in a specific environmental condition can be an effective strategy. This study aimed to assess the inheritance of early stomatal closure traits in soybeans using a population of recombinant inbred lines (RILs) derived from a cross between N09-13890 and Ellis. Thirty soybean lines were subjected to progressive water-deficit stress using a dry-down experiment. The experiment was conducted from June to November 2022 at the West Tennessee Research and Education Center (WTREC), University of Tennessee in Jackson, TN, under controlled environment conditions. This study identified significant differences among soybean lines in their early stomatal closure thresholds. The fraction of transpirable soil water (FTSW) thresholds among 30 tested lines ranged from 0.18 to 0.80, at which the decline in transpiration with soil drying was observed. Almost 65% of the RILs had FTSW threshold values between 0.41 to 0.80. These results, indicating inheritance, are supportive of the expression of early stomatal closure trait in progeny lines at a high level in cultivar development for water-deficit stress conditions. Thus, identifying the differences in genotypes of water use and their response to water-deficit stress conditions can provide a foundation for selecting new cultivars that are best adapted to arid and semi-arid agricultural production systems

Recombination hotspots in soybean [\u3ci\u3eGlycine max\u3c/i\u3e (L.) Merr.]

Recombination allows for the exchange of genetic material between two parents, which plant breeders exploit to make improved cultivars. This recombination is not distributed evenly across the chromosome. Recombination mostly occurs in euchromatic regions of the genome and even then, recombination is focused into clusters of crossovers termed recombination hotspots. Understanding the distribution of these hotspots along with the sequence motifs associated with them may lead to methods that enable breeders to better exploit recombination in breeding. To map recombination hotspots and identify sequence motifs associated with hotspots in soybean [Glycine max (L.) Merr.], two biparental recombinant inbred lines populations were genotyped with the SoySNP50k Illumina Infinium assay. A total of 451 recombination hotspots were identified in the two populations. Despite being half-sib populations, only 18 hotspots were in common between the two populations. While pericentromeric regions did exhibit extreme suppression of recombination, 27% of the detected hotspots were located in the pericentromeric regions of the chromosomes. Two genomic motifs associated with hotspots are similar to human, dog, rice, wheat, drosophila, and arabidopsis. These motifs were a CCN repeat motif and a poly-A motif. Genomic regions spanning other hotspots were significantly enriched with the tourist family of mini-inverted-repeat transposable elements that resides i

Identification of QTL Associated with Regrowth Vigor Using the Nested Association Mapping Population in Switchgrass

Switchgrass (Panicum virgatum L.) is a warm-season perennial grass species that is utilized as forage for livestock and biofuel feedstock. The stability of biomass yield and regrowth vigor under changing harvest frequency would help manage potential fluctuations in the feedstock market and would provide a continuous supply of quality forage for livestock. This study was conducted to (i) assess the genetic variation and (ii) identify the quantitative trait loci (QTL) associated with regrowth vigor after multiple cuttings in lowland switchgrass. A nested association mapping (NAM) population comprising 2000 pseudo F2 progenies was genotyped with single nucleotide polymorphism (SNP) markers derived from exome-capture sequencing and was evaluated for regrowth vigor in 2017 and 2018. The results showed significant variation among the NAM families in terms of regrowth vigor (p < 0.05). A total of 10 QTL were detected on 6 chromosomes: 1B, 5A, 5B, 6B, 7B, and 8A, explaining the phenotypic variation by up to 4.7%. The additive genetic effects of an individual QTL ranged from −0.13 to 0.26. No single QTL showed a markedly large effect, suggesting complex genetics underlying regrowth vigor in switchgrass. The homologs of candidate genes that play a variety of roles in developmental processes, including plant hormonal signal transduction, nucleotide biosynthesis, secondary metabolism, senescence, and responses to both biotic and abiotic stresses, were identified in the vicinity of QTL

The development and use of a molecular model for soybean maturity groups

Abstract Background Achieving appropriate maturity in a target environment is essential to maximizing crop yield potential. In soybean [Glycine max (L.) Merr.], the time to maturity is largely dependent on developmental response to dark periods. Once the critical photoperiod is reached, flowering is initiated and reproductive development proceeds. Therefore, soybean adaptation has been attributed to genetic changes and natural or artificial selection to optimize plant development in specific, narrow latitudinal ranges. In North America, these regions have been classified into twelve maturity groups (MG), with lower MG being shorter season than higher MG. Growing soybean lines not adapted to a particular environment typically results in poor growth and significant yield reductions. The objective of this study was to develop a molecular model for soybean maturity based on the alleles underlying the major maturity loci: E1, E2, and E3. Results We determined the allelic variation and diversity of the E maturity genes in a large collection of soybean landraces, North American ancestors, Chinese cultivars, North American cultivars or expired Plant Variety Protection lines, and private-company lines. The E gene status of accessions in the USDA Soybean Germplasm Collection with SoySNP50K Beadchip data was also predicted. We determined the E allelic combinations needed to adapt soybean to different MGs in the United States (US) and discovered a strong signal of selection for E genotypes released in North America, particularly the US and Canada. Conclusions The E gene maturity model proposed will enable plant breeders to more effectively transfer traits into different MGs and increase the overall efficiency of soybean breeding in the US and Canada. The powerful yet simple selection strategy for increasing soybean breeding efficiency can be used alone or to directly enhance genomic prediction/selection schemes. The results also revealed previously unrecognized aspects of artificial selection in soybean imposed by soybean breeders based on geography that highlights the need for plant breeding that is optimized for specific environments

Development and Phenotypic Screening of an Ethyl Methane Sulfonate Mutant Population in Soybean

Soybean is an important oil-producing crop in the Fabaceae family and there are increasing demands for soybean oil and other soybean products. Genetic improvement of soybean is needed to increase its production. In order to provide genetic diversity and resources for identifying important genes, a new ethyl methane sulfonate (EMS) mutagenized soybean population was generated using the newly released germplasm, JTN-5203 (maturity group V). Treatment of soybean seeds with 60 mM EMS concentration was found to be suitable for inducing mutation. A total of 1,820 M1 individuals were produced from 15,000 treated seeds. The resulting M2 population was planted in the field for phenotyping. After harvest, seed traits including total oil, protein, starch, moisture content, fatty acid and amino acid compositions were measured by NIR. Phenotypic variations observed in this population include changes in leaf morphology, plant architecture, seed compositions, and yield. Of most interest, we identified plants with increased amounts of total protein (50% vs. 41% for control) and plants with higher amounts of total oil (25% vs. 21.2% control). Similarly, we identified plants with increases in oleic acid content and decreases in linoleic acid and linolenic acid. This EMS mutant population will be used for further studies including screening for various traits such as amino acid pathways, allergens, phytic acids, and other important soybean agronomic traits. In addition, these mutant individuals will be evaluated in the next generation to assess the heritability. Beneficial traits from these mutants can be exploited for future soybean breeding programs. This germplasm can also be used for discovering novel mutant alleles and for functional gene expression analysis using reverse genetics tools such as TILLING