Genetically optimizing soybean nodulation improves yield and protein content.

Symbiotic nitrogen fixation in legume nodules requires substantial energy investment from host plants, and soybean (Glycine max (L.) supernodulation mutants show stunting and yield penalties due to overconsumption of carbon sources. We obtained soybean mutants differing in their nodulation ability, among which rhizobially induced cle1a/2a (ric1a/2a) has a moderate increase in nodule number, balanced carbon allocation, and enhanced carbon and nitrogen acquisition. In multi-year and multi-site field trials in China, two ric1a/2a lines had improved grain yield, protein content and sustained oil content, demonstrating that gene editing towards optimal nodulation improves soybean yield and quality.

A critical suppression feedback loop determines soybean photoperiod sensitivity.

Photoperiod sensitivity is crucial for soybean flowering, adaptation, and yield. In soybean, photoperiod sensitivity centers around the evening complex (EC) that regulates the transcriptional level of the core transcription factor E1, thereby regulating flowering. However, little is known about the regulation of the activity of EC. Our study identifies how E2/GIGANTEA (GI) and its homologs modulate photoperiod sensitivity through interactions with the EC. During long days, E2 interacts with the blue-light receptor flavin-binding, kelch repeat, F box 1 (FKF1), leading to the degradation of J/ELF3, an EC component. EC also suppresses E2 expression by binding to its promoter. This interplay forms a photoperiod regulatory loop, maintaining sensitivity to photoperiod. Disruption of this loop leads to losing sensitivity, affecting soybean's adaptability and yield. Understanding this loop's dynamics is vital for molecular breeding to reduce soybean's photoperiod sensitivity and develop cultivars with better adaptability and higher yields, potentially leading to the creation of photoperiod-insensitive varieties for broader agricultural applications.

The Myb73-GDPD2-GA2ox1 transcriptional regulatory module confers phosphate deficiency tolerance in soybean.

Phosphorus is indispensable in agricultural production. An increasing food supply requires more efficient use of phosphate due to limited phosphate resources. However, how crops regulate phosphate efficiency remains largely unknown. Here, we identified a major quantitative trait locus, qPE19, that controls seven low-phosphate (LP)-related traits in soybean (Glycine max) through linkage mapping and genome-wide association studies. We identified the gene responsible for qPE19 as GLYCEROPHOSPHORYL DIESTER PHOSPHODIESTERASE2 (GmGDPD2), and haplotype 5 represents the optimal allele favoring LP tolerance. Overexpression of GmGDPD2 significantly affects hormone signaling and improves root architecture, phosphate efficiency and yield-related traits; conversely, CRISPR/Cas9-edited plants show decreases in these traits. GmMyb73 negatively regulates GmGDPD2 by directly binding to its promoter, thus GmMyb73 negatively regulates LP tolerance. GmGDPD2 physically interacts with GA 2-oxidase 1 (GmGA2ox1) in the plasma membrane, and overexpressing GmGA2ox1 enhances LP-associated traits, similar to GmGDPD2 overexpression. Analysis of double mutants for GmGDPD2 and GmGA2ox1 demonstrated that GmGDPD2 regulates LP tolerance likely by influencing auxin and gibberellin dose-associated cell division in root. These results reveal a regulatory module that plays a major role in regulating LP tolerance in soybean and is expected to be utilized to develop phosphate-efficient varieties to enhance soybean production, particularly in phosphate-deficient soils.

Identification of the domestication gene GmCYP82C4 underlying the major quantitative trait locus for the seed weight in soybean.

KEY MESSAGE: A major quantitative trait locus (QTL) for the hundred-seed weight (HSW) was identified and confirmed in the two distinct soybean populations, and the target gene GmCYP82C4 underlying this locus was identified that significantly associated with soybean seed weight, and it was selected during the soybean domestication and improvement process. Soybean is a major oil crop for human beings and the seed weight is a crucial goal of soybean breeding. However, only a limited number of target genes underlying the quantitative trait loci (QTLs) controlling seed weight in soybean are known so far. In the present study, six loci associated with hundred-seed weight (HSW) were detected in the first population of 573 soybean breeding lines by genome-wide association study (GWAS), and 64 gene models were predicted in these candidate QTL regions. The QTL qHSW_1 exhibits continuous association signals on chromosome four and was also validated by region association study (RAS) in the second soybean population (409 accessions) with wild, landrace, and cultivar soybean accessions. There were seven genes in qHSW_1 candidate region by linkage disequilibrium (LD) block analysis, and only Glyma.04G035500 (GmCYP82C4) showed specifically higher expression in flowers, pods, and seeds, indicating its crucial role in the soybean seed development. Significant differences in HSW trait were detected when the association panels are genotyped by single-nucleotide polymorphisms (SNPs) in putative GmCYP82C4 promoter region. Eight haplotypes were generated by six SNPs in GmCYP82C4 in the second soybean population, and two superior haplotypes (Hap2 and Hap4) of GmCYP82C4 were detected with average HSW of 18.27 g and 18.38 g, respectively. The genetic diversity of GmCYP82C4 was analyzed in the second soybean population, and GmCYP82C4 was most likely selected during the soybean domestication and improvement process, leading to the highest proportion of Hap2 of GmCYP82C4 both in landrace and cultivar subpopulations. The QTLs and GmCYP82C4 identified in this study provide novel genetic resources for soybean seed weight trait, and the GmCYP82C4 could be used for soybean molecular breeding to develop desirable seed weight in the future.

Dt1 inhibits SWEET-mediated sucrose transport to regulate photoperiod-dependent seed weight in soybean.

Soybean is a photoperiod-sensitive short-day crop whose reproductive period and yield are markedly affected by day-length changes. Seed weight is one of the key traits determining the soybean yield; however, the prominent genes that control the final seed weight of soybean and the mechanisms underlying the photoperiod's effect on this trait remain poorly understood. In this study, we identify SW19 as a major locus controlling soybean seed weight by QTL mapping and determine Dt1, an orthologous gene of Arabidopsis TFL1 that is known to govern the soybean growth habit, as the causal gene of the SW19 locus. We showed that Dt1 is highly expressed in developing seeds and regulates photoperiod-dependent seed weight in soybean. Further analyses revealed that the Dt1 protein physically interacts with the sucrose transporter GmSWEET10a to negatively regulate the import of sucrose from seed coat to the embryo, thus modulating seed weight under long days. However, Dt1 does not function in seed development under short days due to its very low expression. Importantly, we discovered a novel natural allelic variant of Dt1 (H4 haplotype) that decouples its pleiotropic effects on seed size and growth habit; i.e., this variant remains functional in seed development but fails to regulate the stem growth habit of soybean. Collectively, our findings provide new insights into how soybean seed development responds to photoperiod at different latitudes, offering an ideal genetic component for improving soybean's yield by manipulating its seed weight and growth habit.

Genome-wide identification and expression analysis of the WNK kinase gene family in soybean.

WNK kinases are a unique class of serine/threonine protein kinases that lack a conserved catalytic lysine residue in the kinase domain, hence the name WNK (with no K, i.e., lysine). WNK kinases are involved in various physiological processes in plants, such as circadian rhythm, flowering time, and stress responses. In this study, we identified 26 WNK genes in soybean and analyzed their phylogenetic relationships, gene structures, chromosomal distribution, cis-regulatory elements, expression patterns, and conserved protein motifs. The soybean WNK genes were unevenly distributed on 15 chromosomes and underwent 21 segmental duplication events during evolution. We detected 14 types of cis-regulatory elements in the promoters of the WNK genes, indicating their potential involvement in different signaling pathways. The transcriptome database revealed tissue-specific and salt stress-responsive expression of WNK genes in soybean, the second of which was confirmed by salt treatments and qRT-PCR analysis. We found that most WNK genes were significantly up-regulated by salt stress within 3 h in both roots and leaves, except for WNK5, which showed a distinct expression pattern. Our findings provide valuable insights into the molecular characteristics and evolutionary history of the soybean WNK gene family and lay a foundation for further analysis of WNK gene functions in soybean. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-024-01440-5.

Mechanisms underlying key agronomic traits and implications for molecular breeding in soybean.

Soybean (Glycine max [L.] Merr.) is an important crop that provides protein and vegetable oil for human consumption. As soybean is a photoperiod-sensitive crop, its cultivation and yield are limited by the photoperiodic conditions in the field. In contrast to other major crops, soybean has a special plant architecture and a special symbiotic nitrogen fixation system, representing two unique breeding directions. Thus, flowering time, plant architecture, and symbiotic nitrogen fixation are three critical or unique yield-determining factors. This review summarizes the progress made in our understanding of these three critical yield-determining factors in soybean. Meanwhile, we propose potential research directions to increase soybean production, discuss the application of genomics and genomic-assisted breeding, and explore research directions to address future challenges, particularly those posed by global climate changes.

SoyMD: a platform combining multi-omics data with various tools for soybean research and breeding.

Advanced multi-omics technologies offer much information that can uncover the regulatory mechanisms from genotype to phenotype. In soybean, numerous multi-omics databases have been published. Although they cover multiple omics, there are still limitations when it comes to the types and scales of omics datasets and analysis methods utilized. This study aims to address these limitations by collecting and integrating a comprehensive set of multi-omics datasets. This includes 38 genomes, transcriptomes from 435 tissue samples, 125 phenotypes from 6686 accessions, epigenome data involving histone modification, transcription factor binding, chromosomal accessibility and chromosomal interaction, as well as genetic variation data from 24 501 soybean accessions. Then, common analysis pipelines and statistical methods were applied to mine information from these multi-omics datasets, resulting in the successful establishment of a user-friendly multi-omics database called SoyMD (https://yanglab.hzau.edu.cn/SoyMD/#/). SoyMD provides researchers with efficient query options and analysis tools, allowing them to swiftly access relevant omics information and conduct comprehensive multi-omics data analyses. Another notable feature of SoyMD is its capability to facilitate the analysis of candidate genes, as demonstrated in the case study on seed oil content. This highlights the immense potential of SoyMD in soybean genetic breeding and functional genomics research.

Natural variation in Fatty Acid 9 is a determinant of fatty acid and protein content.

Soybean is one of the most economically important crops worldwide and an important source of unsaturated fatty acids and protein for the human diet. Consumer demand for healthy fats and oils is increasing, and the global demand for vegetable oil is expected to double by 2050. Identification of key genes that regulate seed fatty acid content can facilitate molecular breeding of high-quality soybean varieties with enhanced fatty acid profiles. Here, we analysed the genetic architecture underlying variations in soybean seed fatty acid content using 547 accessions, including mainly landraces and cultivars from northeastern China. Through fatty acid profiling, genome re-sequencing, population genomics analyses, and GWAS, we identified a SEIPIN homologue at the FA9 locus as an important contributor to seed fatty acid content. Transgenic and multiomics analyses confirmed that FA9 was a key regulator of seed fatty acid content with pleiotropic effects on seed protein and seed size. We identified two major FA9 haplotypes in 1295 resequenced soybean accessions and assessed their phenotypic effects in a field planting of 424 accessions. Soybean accessions carrying FA9H2 had significantly higher total fatty acid contents and lower protein contents than those carrying FA9H1 . FA9H2 was absent in wild soybeans but present in 13% of landraces and 26% of cultivars, suggesting that it may have been selected during soybean post-domestication improvement. FA9 therefore represents a useful genetic resource for molecular breeding of high-quality soybean varieties with specific seed storage profiles.

A novel miR160a-GmARF16-GmMYC2 module determines soybean salt tolerance and adaptation.

Salt stress is a major challenge that has a negative impact on soybean growth and productivity. Therefore, it is important to understand the regulatory mechanism of salt response to ensure soybean yield under such conditions. In this study, we identified and characterized a miR160a-GmARF16-GmMYC2 module and its regulation during the salt-stress response in soybean. miR160a promotes salt tolerance by cleaving GmARF16 transcripts, members of the Auxin Response Factor (ARF) family, which negatively regulates salt tolerance. In turn, GmARF16 activates GmMYC2, encoding a bHLH transcription factor that reduces salinity tolerance by down-regulating proline biosynthesis. Genomic analysis among wild and cultivated soybean accessions identified four distinct GmARF16 haplotypes. Among them, the GmARF16H3 haplotype is preferentially enriched in localities with relatively saline soils, suggesting GmARF16H3 was artificially selected to improve salt tolerance. Our findings therefore provide insights into the molecular mechanisms underlying salt response in soybean and provide valuable genetic targets for the molecular breeding of salt tolerance.

Soybean reduced internode 1 determines internode length and improves grain yield at dense planting.

Major cereal crops have benefitted from Green Revolution traits such as shorter and more compact plants that permit high-density planting, but soybean has remained relatively overlooked. To balance ideal soybean yield with plant height under dense planting, shortening of internodes without reducing the number of nodes and pods is desired. Here, we characterized a short-internode soybean mutant, reduced internode 1 (rin1). Partial loss of SUPPRESSOR OF PHYA 105 3a (SPA3a) underlies rin1. RIN1 physically interacts with two homologs of ELONGATED HYPOCOTYL 5 (HY5), STF1 and STF2, to promote their degradation. RIN1 regulates gibberellin metabolism to control internode development through a STF1/STF2-GA2ox7 regulatory module. In field trials, rin1 significantly enhances grain yield under high-density planting conditions comparing to its wild type of elite cultivar. rin1 mutants therefore could serve as valuable resources for improving grain yield under high-density cultivation and in soybean-maize intercropping systems.

UV-B irradiation-activated E3 ligase GmILPA1 modulates gibberellin catabolism to increase plant height in soybean.

Plant height is a key agronomic trait that affects yield and is controlled by both phytohormone gibberellin (GA) and ultraviolet-B (UV-B) irradiation. However, whether and how plant height is modulated by UV-B-mediated changes in GA metabolism are not well understood. It has not been reported that the E3 ubiquitin ligase Anaphase Promoting Complex/Cyclosome (APC/C) is involved in the regulation of plant growth in response to environmental factors. We perform a forward genetic screen in soybean and find that a mutation in Glycine max Increased Leaf Petiole Angle1 (GmILPA1), encoding a subunit of the APC/C, lead to dwarfism under UV-B irradiation. UV-B promotes the accumulation of GmILPA1, which ubiquitinate the GA catabolic enzyme GA2 OXIDASE-like (GmGA2ox-like), resulting in its degradation in a UV-B-dependent manner. Another E3 ligase, GmUBL1, also ubiquitinate GmGA2ox-like and enhance the GmILPA1-mediated degradation of GmGA2ox-like, which suggest that GmILPA1-GmGA2ox-like module counteract the UV-B-mediated reduction of bioactive GAs. We also determine that GmILPA1 is a target of selection during soybean domestication and breeding. The deletion (Indel-665) in the promoter might facilitate the adaptation of soybean to high UV-B irradiation. This study indicates that an evolutionary GmILPA1 variant has the capability to develop ideal plant architecture with soybean cultivars.

PH13 improves soybean shade traits and enhances yield for high-density planting at high latitudes.

Shading in combination with extended photoperiods can cause exaggerated stem elongation (ESE) in soybean, leading to lodging and reduced yields when planted at high-density in high-latitude regions. However, the genetic basis of plant height in adaptation to these regions remains unclear. Here, through a genome-wide association study, we identify a plant height regulating gene on chromosome 13 (PH13) encoding a WD40 protein with three main haplotypes in natural populations. We find that an insertion of a Ty1/Copia-like retrotransposon in the haplotype 3 leads to a truncated PH13H3 with reduced interaction with GmCOP1s, resulting in accumulation of STF1/2, and reduced plant height. In addition, PH13H3 allele has been strongly selected for genetic improvement at high latitudes. Deletion of both PH13 and its paralogue PHP can prevent shade-induced ESE and allow high-density planting. This study provides insights into the mechanism of shade-resistance and offers potential solutions for breeding high-yielding soybean cultivar for high-latitude regions.

SoyDNGP: a web-accessible deep learning framework for genomic prediction in soybean breeding.

Soybean is a globally significant crop, playing a vital role in human nutrition and agriculture. Its complex genetic structure and wide trait variation, however, pose challenges for breeders and researchers aiming to optimize its yield and quality. Addressing this biological complexity requires innovative and accurate tools for trait prediction. In response to this challenge, we have developed SoyDNGP, a deep learning-based model that offers significant advancements in the field of soybean trait prediction. Compared to existing methods, such as DeepGS and DNNGP, SoyDNGP boasts a distinct advantage due to its minimal increase in parameter volume and superior predictive accuracy. Through rigorous performance comparison, including prediction accuracy and model complexity, SoyDNGP represents improved performance to its counterparts. Furthermore, it effectively predicted complex traits with remarkable precision, demonstrating robust performance across different sample sizes and trait complexities. We also tested the versatility of SoyDNGP across multiple crop species, including cotton, maize, rice and tomato. Our results showed its consistent and comparable performance, emphasizing SoyDNGP's potential as a versatile tool for genomic prediction across a broad range of crops. To enhance its accessibility to users without extensive programming experience, we designed a user-friendly web server, available at http://xtlab.hzau.edu.cn/SoyDNGP. The server provides two features: 'Trait Lookup', offering users the ability to access pre-existing trait predictions for over 500 soybean accessions, and 'Trait Prediction', allowing for the upload of VCF files for trait estimation. By providing a high-performing, accessible tool for trait prediction, SoyDNGP opens up new possibilities in the quest for optimized soybean breeding.

The NAC transcription factors SNAP1/2/3/4 are central regulators mediating high nitrogen responses in mature nodules of soybean.

Legumes can utilize atmospheric nitrogen via symbiotic nitrogen fixation, but this process is inhibited by high soil inorganic nitrogen. So far, how high nitrogen inhibits N2 fixation in mature nodules is still poorly understood. Here we construct a co-expression network in soybean nodule and find that a dynamic and reversible transcriptional network underlies the high N inhibition of N2 fixation. Intriguingly, several NAC transcription factors (TFs), designated as Soybean Nitrogen Associated NAPs (SNAPs), are amongst the most connected hub TFs. The nodules of snap1/2/3/4 quadruple mutants show less sensitivity to the high nitrogen inhibition of nitrogenase activity and acceleration of senescence. Integrative analysis shows that these SNAP TFs largely influence the high nitrogen transcriptional response through direct regulation of a subnetwork of senescence-associated genes and transcriptional regulators. We propose that the SNAP-mediated transcriptional network may trigger nodule senescence in response to high nitrogen.

Genome-wide identification and functional prediction of BYPASS1-related (BPS1) homologs in soybean.

The BYPASS1-related gene (BPS1) encodes a protein with an unknown functional domain that regulates plant organ growth and development by inhibiting the continuous production of a root-derived long-distance signaling molecule called bypass (bps). We conducted a comprehensive study to investigate the BPS gene family in soybean and identified twenty-three BPS genes in Glycine max and twenty BPS genes in Glycine soja (wild soybean). Collinearity analysis revealied the existence of multiple orthologs of soybean BPS genes in wild soybean, indicating incomplete conservation between the BPS genes of soybean and wild soybean. Phylogenetic analysis successfully categorized all BPS genes into five distinct groups. We further scrutinized their chromosomal locations, gene structures, conserved motifs, cis-acting elements, and expression patterns. Leveraging publicly available data on genetic variation, phenotypic variation, and single-cell transcriptome sequencing of root nodules, we discovered a potential association between BPS genes and multiple soybean traits, particularly those related to the root nodule phenotype. This pioneering study provides a systematic and comprehensive examination of the BPS gene family in soybean. The findings establish a robust foundation for future investigations into the functional roles of BPS genes in plant growth and development. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01403-2.