The soybean ubiquitin-proteasome system: Current knowledge and future perspective

Abstract

Increasing soybean [Glycine max (L.) Merr.] yield has become a worldwide scientific problem in the world. Many studies have shown that ubiquitination plays a key role in stress response and yield formation. In the UniProtKB database, 2,429 ubiquitin-related proteins were predicted in soybean, however, <20 were studied. One key way to address this lack of progress in increasing soybean yield will be a deeper understanding of the ubiquitin-proteasome system (UPS) in soybean. In this review, we summarized the current knowledge about soybean ubiquitin-related proteins and discussed the method of combining phenotype, mutant library, transgenic system, genomics, and proteomics approaches to facilitate the exploration of the soybean UPS. We also proposed the strategy of applying the UPS in soybean improvement based on related studies in model plants. Our review will be helpful for soybean scientists to learn current research progress of the soybean UPS and further lay a theoretical reference for the molecular improvement of soybean in future research by use of this knowledge.

Abbreviations
• ABA
• abscisic acid
• ABI
• abscisic acid insensitive
• BR
• brassinosteroid
• DA
• big in Chinese
• DAR1
• DA1-related
• Dt
• determinate stem
• EOD1/BB
• enhancer of DA1/BIG BROTHER
• GA
• gibberellin
• GW2
• GRAIN WIDTH AND WEIGHT 2
• HY5
• LONG HYPOCOTYL 5
• RPT2
• 26S proteasome regulatory particle AAA-ATPase
• SCN
• soybean cyst nematode
• SL
• strigolactone
• SNP
• single nucleotide polymorphism
• UBP15
• UBIQUITIN-SPECIFIC PROTEASE15
• UBQ
• UBIQUITIN-SPECIFIC PROTEASES
• UPS
• ubiquitin-proteasome system
• WTG1
• deubiquitinating enzyme homologous to human OTUB1
• POZ
• Zinc finger of poxvirus
• BTB
• Broad-complex、Tramtrack and Bric-abrac

INTRODUCTION

Soybean [Glycine max (L.) Merr.] is one of the most economically important leguminous seed crops, which provides more than one-quarter of the total protein for food and animal feed (Zhang, Liu et al., 2022). In the past 50 yr, a dramatic yield increase has been achieved for rice (Oryza sativa L.), maize (Zea mays L.), and wheat (Triticum aestivum L.) (S. Liu et al., 2020). Due to the big difference between soybean and rice or maize of heterosis in increasing yield, although soybean yield in 2020 almost doubled compared with the yield in the 1960s, there was still a huge gap between soybean and rice or maize (Umburanas et al., 2022). In 2010, the reference genome of Williams 82 was published (Schmutz et al., 2010). Added to high-throughput technologies developed, the publications number on soybean have doubled in the last decade (Zhang, Liu et al., 2022). However, the yield of soybean has still increased slowly (Xu et al., 2020; Zhang, Liu et al., 2022). To meet the growing demand for soybean, the urgent need to further improve soybean yield and resistance to stresses has become a worldwide scientific problem (S. Liu et al., 2020; Ray et al., 2013).

The ubiquitin-proteasome system (UPS), including ubiquitin, ubiquitin-activating enzyme (E1), ubiquitin-conjugating enzyme (E2), ubiquitin ligase enzyme (E3), and 26S proteasome (Shu & Yang, 2017), is the main pathway for the protein degradations, which controls protein ability, activity, and localization to affect many cellular processes (Sadanandom et al., 2012). In these components, ubiquitin is a key protein post-translational modifier with 76 amino acids involved in signaling in plants (Zheng & Shabek, 2017). It was also worth noting that E3 ubiquitin ligase plays an important role in plant growth and development due to their different target proteins. Since the involvement of ubiquitination in protein degradation, and different target proteins of E3 ubiquitin ligase are involved in different pathways, there have been extensive reports on the plant architecture (Guo, Chen, Herrera-Estrella et al., 2020; Hill & Hollender, 2019; Huang et al., 2021; X. F. Liu et al., 2021; Luo et al., 2020; Maurya et al., 2020; Wang et al., 2018; Zheng & Shabek, 2017), stress response (Chen et al., 2020; Lee & Kim, 2011; Melo et al., 2021; Shu & Yang, 2017; Xu & Xue, 2019), hormone signaling, photo-morphological formation (Podolec & Ulm, 2018; N. X. Qin et al., 2020), and seed size (Hu et al., 2021; N. Li et al., 2019; Zhao et al., 2016) of crops. For example, the E3 ligase GmRNF1a interacts with GmAGL1 to regulate silique dehiscence in Arabidopsis (Yang et al., 2022). COP1 was a crucial repressor of photomorphogenesis (Hoecker, 2017; Podolec & Ulm, 2018). WG2 negatively regulates the grain width and weight in rice (Choi et al., 2018). GmARI1, GmPUB13, GmPUB6, and GmPUB8 were involved in aluminum, host immunity, and drought responses, respectively (Lin et al., 2021; Wang et al., 2020, 2016; Zhang et al., 2014). These factors are closely related to the formation of crop yields. It is indicated that the UPS plays an important role in crop yield formation.

However, few studies on the genes and proteins of soybean involved in UPS have been reported. In the UniProtKB database (https://www.uniprot.org/), 1,360 and 318 ubiquitin-related proteins were reviewed at the transcript or protein level in Arabidopsis and rice, respectively. Although about 2,429 ubiquitin-related proteins were found in soybean, <20 proteins were reviewed. Further study of the soybean UPS will be of great significance for the improvement of soybean yields. In this review, we summarized and compared the molecular mechanisms of ubiquitination systems in terms of yield formation between soybean and other plants. Meanwhile, a combination of phenotype, mutant library, genomics, and proteomics approaches is proposed for a deep exploration of the UPS for soybean yield.

Core Ideas

• Ubiquitination plays a key role in stress response and yield formation.
• The yield per unit area of soybean is an emerging study focus in the world.
• The ubiquitin-proteasome system can be used to increase the soybean yield or stress resistance.
• We proposed the strategy of applying the ubiquitin-proteasome system in soybean improvement based on model plants.

ROLE OF THE UBIQUITIN-PROTEASOME SYSTEM IN SOYBEAN YIELD

As a multifactorial trait, soybean yield is affected by many factors, such as seeds per pod, pod number per plant, plants per area, and seed size. Now, the UPS functions are better defined in seed size, plant architecture, and responses to stresses of Arabidopsis and rice, however, which are still lagging behind. Some useful information may be obtained by comparing the characteristics of UPS between soybean and other plants.

Ubiquitin-proteasome system in stress response

Stress tolerance is an important factor affecting the stable and high yield of soybean. Therefore, great efforts have been focused on genetic loci and genes responsible for the stress response in the past decade (Anderson et al., 2019), including in salt, temperature stress, drought, flooding, and disease (K. P. Li et al., 2021; Ramesh et al., 2019; Robison et al., 2019; Shu et al., 2020; Whitham et al., 2016; Widyasari et al., 2020). Several WRKY and NAC transcription factors were positive regulators in soybean drought tolerance, such as GmWRKY54 (Wei et al., 2019), GmWRKY20 (Luo et al., 2013), and GmNAC8 (Yang et al., 2020). The overexpression of GmWRKY20, GmWRKY54, or GmNAC8 exhibits significantly higher drought tolerance. Two circadian clock genes, GmLHY and GmLCL, were also involved in drought tolerance (K. Wang et al., 2021; Yuan et al., 2021). Both GmLCL and GmLHY negatively regulate abscisic acid (ABA) perception and signaling control in soybean drought tolerance. Salinity also has significant effects on soybean yield (A. L. Liu et al., 2019; S. Liu et al., 2020). Reducing the ion toxicity or balancing the ions can effectively enhance the salt resistance of genes such as GmSALT3, GmCDF1, and GmAKT1 (Guan et al., 2014; X. S. Wang et al., 2021; W. Zhang et al., 2019). GmSALT3 enhanced salt tolerance by limiting the accumulation of sodium ions in shoots of soybean. Several transcription factors and protein kinase, including GmNAC109 (X. F. Yang et al., 2019), GmSIN1 (S. Li et al., 2019), GmbZIP110 (Xu et al., 2016), GmNAC20 (Hao et al., 2011), GmMYB118 (Du et al., 2018), GmERF135, and GmCDPK3 (Wang et al., 2019), were also involved in the salt response. In addition, ABA and salicylic acid are two key phytohormones for stress resistance, and the knockdown of the synthase biosynthesis pathway can abrogate pathogen resistance (Shine et al., 2016). In soybean, it was also found that GmABAS1 functioned as a transcriptional repressor that enhances ABA sensitivity (Ku et al., 2020). For biotic stresses, the soybean cyst nematode (SCN) and stay-green disease are the most devastating soybean stresses. Rhg1 and Rhg4 are playing a key role in SCN resistance (Cook et al., 2012; Liu et al., 2012; McHale et al., 2012; Mitchum, 2016). Recent studies have shown that a new distinct geminivirus SoSGV causes soybean stay-green disease, which provides a solid foundation for the study of soybean stay-green disease (Cheng et al., 2022) (Table 1).

TABLE 1 The regulators of seed size, plant architecture and stress response in soybean

[Table omitted. See PDF]

a

Bold genes indicates ubiquitin-proteasome system-related genes.

Recently, ubiquitination has emerged as a target for the improvement of crop abiotic–biotic stress tolerance (Xu & Xue, 2019). The UPS selectively degrades specific target proteins, which plays an important role in the response to abiotic–biotic stress (Wang et al., 2022). In addition, the UBIQUITIN-SPECIFIC PROTEASES (UBQ) family and proteasome subunits are also involved in plant development and stress responses (Zhou et al., 2017). In rice, the E3 ligase OsPUB67 and its target proteins OsRZF34 and OsDIS1 (Q. Qin et al., 2020), as well as OsCTR1 and its target proteins OsRP1 and OsCP12, are jointly involved in drought stress (Lim et al., 2014). OsSADR1, OsMAR1, and OsSIRP2 and their targets (OsSNAC2, OsGRA44, OsOCP12, OsFKBP12, OsSaIT, OsCPA1, OsDH1, and OsTKL1) participate in regulating the salt stress response (Melo et al., 2021). The proteasome 19S subunits RPN10, RPN1a, RPN8a, RPN12a, and RPN6; 20S α subunits OgTT1, PAE1/2, and ARS5; and 20S β subunits PBA1, PBB1/2, and PBE1/2, are involved in salt, heat, drought, disease, and pathogen responses (Xu & Xue, 2019).

In soybean, two E2 ubiquitin-conjugating enzymes of GmUBC2 and GmUBC9 play an important role in the drought stress response, whereby the overexpression of GmUBC2 confers enhanced drought or salt tolerance in Arabidopsis (Chen et al., 2020; Zhou et al., 2010). For E3 ligases, U-box proteins GmPUB1, GmPUB6, GmPUB8, and GmPUB13 are involved in stress responses (S. Li et al., 2021; Lin et al., 2021; Wang et al., 2020, 2016). The expression of GmPUB8 induced by drought, NaCl, and exogenous ABA, whereas the overexpression of GmPUB8 in Arabidopsis results in decreased drought tolerance and inhibited mannitol- and ABA-mediated stomatal closure (Wang et al., 2016). Similar to GmPUB8, under drought stress, overexpression of GmPUB6 in Arabidopsis also results in decreased plant survival (Wang et al., 2020). Differing from GmPUB6 and GmPUB8, GmPUB1 and GmPUB13 participate in host immunity. The silencing of GmPUB13 decreases Phytophthora sojae (P. sojae) infection in soybean hairy roots, and the overexpression of GmPUB1-1 cause cell death (S. Li et al., 2021; Lin et al., 2021). Some RING-type E3 ligases such as GmRFP1 and GmCOI1 are also involved in soybean defense (Du et al., 2010; Wang et al., 2005). An RING-between RING-RING (RBR) type E3 ligase of GmARI1 may play a key role in tolerance to aluminum stress in soybean (Zhang et al., 2014). Soybean UBQs were also involved in stress responses. However, unlike in rice, overexpression of GsUBQ10 in alfalfa significantly improved the alkaline tolerance, and soybean UBQ10 plays a positive role in responses to alkaline stress (C. Chen et al., 2018). GmBTB/Zinc finger of poxvirus (POZ), a novel Broad-complex、Tramtrack and Bric-abrac (BTB)/POZ domain-containing nuclear protein, was located in the cell nucleus and up-regulated by P. sojae, functions as a positive regulator in the soybean response to P. sojae infection (C. Zhang et al., 2019): The GmBTB/POZ interacts with GmAP2 and GmLHP1 to regulate the defense response to P. sojae. GmAP2 and GmLHP1-RNAi exhibited enhanced resistance to P. sojae (Zhang, Cheng et al., 2021). In addition, GmSK1 might play a role in the crosstalk between ubiquitination and drought and salt stress responses (Y. P. Chen et al., 2018) (Table 1).

Although some genes associated with ubiquitination have been reported in response to stress in soybean, the depth and breadth of research are lacking compared with Arabidopsis or rice. More E3-ubiquitin ligases and their target proteins of abiotic stress responses need to be obtained by forward or reverse genetics.

Ubiquitin proteasome system in plant architecture

The plant architecture is an important trait that affects the stress resistance, yield, and crop growth, which is the primary factor underlying the “unit area yield”. Examples include the semi-dwarf phenotype of rice and wheat, the upright and sparsely branched phenotype of maize, and the greater node number phenotype of soybean (Guo, Chen, Chen et al., 2020; Tian et al., 2019; J. Wang et al., 2017; J. B. Yang et al., 2019; Zheng et al., 2020). Due to the important role of the plant architecture in yield, about 40 genes have been reported in recent years, including 17 genes in rice, six genes in soybean, four genes in wheat, and three genes in maize (Guo, Chen, Herrera-Estrella et al., 2020) (Table 1). Such as IPA1, a star gene of ideal plant architecture encodes OsSPL14. The IPA1's function was regulated by ubiquitination modifications at protein levels. The IPA1 stabilizes in shoot apexes and promotes the degradation in panicles through K63-linked and K48-linked polyubiquitination, respectively. So, the optimal high-yield plant architecture may be produced by fine-tuning IPA1's expression in crops (Jiao et al., 2010; M. M. Liu et al., 2019; Zhang et al., 2017). The stability of IPA1/OsSPL14 was also regulated by the rice ortholog of human OTUB1 (S. S. Wang et al., 2017). Furthermore, OsOTUB1 also regulates the plant architecture by promoting the degradation of rice SQUAMOSA promoter binding protein SPL14 (Yue et al., 2017). In addition, The E3 ubiquitin ligase of COP1 is also a crucial repressor of photomorphogenesis (Hoecker, 2017; Podolec & Ulm, 2018), which acts by regulating the stability of phyA, phyB, and HY5, the weak cop1 alleles with strong photomorphogenesis even in complete darkness (Podolec & Ulm, 2018).

In soybean, an APC8-like protein GmILPA1 was involved in plant architecture, and the petiole angle and leaf development were altered in the gmipla1 mutant (Gao et al., 2017). Dt1 and Dt2 are homologs of Arabidopsis TFL1 and a MADS-domain factor, respectively. Functional analyses have shown that Dt2 represses Dt1 transcription through bind to the promoter of Dt1, thereby controlling the plant height and growth (Liu et al., 2010, 2016; Ping et al., 2014). Overexpression of GmmiR156b can increase branch and node number to substantially improve the plant architecture and then affect the yield in soybean (Sun et al., 2019). In addition, the overexpression of GmPIP2;9 can increase the pod number and seed size (Lu et al., 2018). Recent studies have shown that the overexpression of GmWRI1b can increase the node number, stem diameter, pod number per plant, yield per plant, and branch number and decrease the internode length and plant height (Guo, Chen, Chen et al., 2020).

The elite phenotypes of the plant architecture can be changed by endogenous phytohormone contents. The most commonly studied hormones such as ABA, auxin, cytokinin, gibberellin (GA), strigolactone (SL), and brassinosteroid (BR), usually affect the plant architecture (Jiang et al., 2013; X. Zhang et al., 2019). The BR crosstalk with ABA, Gas, and auxin play important roles in the regulation of the leaf and tiller angles (Sang et al., 2014; Wang et al., 2018). The auxin, GAs, BRs, and SLs can promote plant height (Chen et al., 2022; Wang et al., 2018). In addition, SLs can decrease the tiller number, however, BRs can increase the tiller number. Furthermore, SLs also can regulate the tiller number coordinately with BRs and ABA (Burger, 2021; Chen et al., 2022; L. H. Liu et al., 2021; Waters et al., 2017). Numerous studies have shown that some proteins are crucial repressors of phytohormone signaling, such as ABIs for ABA, JAZs for jasmonic acid, DELLAs for GA, and SMXLs for SL, which are the target proteins of the E3 ligase in the UPS. Therefore, hormones mediated by the ubiquitination system play an important role in regulating the plant architecture of crop yield formation. However, there are few reports on the regulation of plant architecture by the ubiquitination pathway in soybean. So far, only one soybean RING family member of the E3 ubiquitin ligase GmRNF1a was observed, which exhibits higher promoter activity in soybean hairy roots as well as in Arabidopsis leaves, flowers, and siliques. Heterologous expression of GmRNF1a in Arabidopsis showed that the transgenic Arabidopsis siliques had a faster maturation rate and cracked earlier than the wild-type plants. Further study showed that GmRNF1a interacts with GmAGL1 to regulate silique dehiscence in Arabidopsis (Yang et al., 2022).

Differing from wheat and rice, the existence of no or only a few branches is ideal in soybean (S. Liu et al., 2020). The pattern of shoot branching is one of the most important factors in soybean yield, which is determined genetically. In Arabidopsis or rice, the genetic and chemical modulation of the SL pathway is recognized as a promising approach to modifying plant architecture, and the plants have attracted a great deal of attention due to their semi-dwarf and super multi-branched mutants. The mechanism of the SL-mediated ubiquitin pathway participating in the regulation of branches was reported in recent years, and the interaction hormones and potential targets were also explored, such as BES1 as MAX2 substrate to regulate the expression of SL-responsive gene in Arabidopsis (Wang et al., 2013). At present, there are few reports on the effects of SL on soybean branching. Understanding how SLs pathway genes regulate the plant architecture will lay the foundation for developing rational approaches toward improving soybean yield. Is only BES1 of the BR pathway involved in SL-mediated ubiquitination? Is only the transcriptional level of the regulation involved between SLs and ABA? Are other hormone-related proteins, such as DELLA and ABIs, involved in the regulation of plant height and secondary branching by SLs mediated ubiquitination pathway? Therefore, the deep study of the target proteins’ molecular functions related to SLs signaling in the ubiquitination pathway will be of great significance for the plant architecture and yield formation of soybean plants.

Ubiquitin-proteasome system in seed size

The size of a seed not only affects the nutritional aspects but also the yield, and many studies focusing on seed size genes have also been reported in plants, involving phytohormone signaling and homeostasis, G-protein signaling, the mitogen-activated protein kinase (MAPK) signaling pathway, the UPS, transcriptional regulators, and endosperm development. Among them, 40 genes are rice seed size-related gene and 35 are Arabidopsis seed size-related gene. Compared with them, there is only one soybean seed size gene (GmPP2C-1) involved in phytohormone signaling (Lu et al., 2017), and two soybean genes (GmCYP78A72 and GmCYP78A10) act as other regulators (Wang et al., 2015; Zhao et al., 2016), while no ubiquitination-pathway associated seed size gene has been discovered in soybean (Table 1).

Several star genes of the UPS were reported to increase yield by regulating the grain size, such as DA1, DA2, DAR1, and GW2. As a ubiquitin receptor, DA1 plays a negative role in the seed growth in Arabidopsis (Dong et al., 2017; Li et al., 2008). AtDAR1, a homologous gene of DA1, the seed and organ size were increased in DA1 and DAR1 double mutant. DA1interact with two RING-type E3 ligases DA2 and enhancer of DA1/BIG BROTHER (EOD1/BB) (Disch et al., 2006; Dong et al., 2017), to control the seed and organ size; like DA1, the seed and organ were also increased in DA2 or EOD1/BB mutant. AtUBP15, a target of DA1, promotes seed growth by regulating cell proliferation (Du et al., 2014). The seeds of the Atubp15 mutant are small, overexpressing AtUBP15 resulted in seed enlargement, further, unlike DA2 and EOD1, while UBP15 may have different targets that control seed/organ growth (N. Li et al., 2019).

In addition, the effect of DA1 on the seed size may be conserved in different species, such as BnDA1 in canola (Brassica napus L.) (J. L. Wang et al., 2017), ZmDA1 in maize (Xie et al., 2018), and TaDA1 in wheat (H. Liu et al., 2020). In maize, the kernel yield was increased in the ZmDA1 or ZmDAR1 overexpression plants, whereas ZmDA1 and ZmDAR1 play important roles in the embryo and endosperm development, respectively. The increased sugar and starch contents in the endosperm or embryo lead to an increase in grain weight. The results were different from the regulation of AtDA1/AtDAR1 in seed size, which was possibly due to the different substrate degradation pathways in the two species (Xie et al., 2018). TaDA1-A was mainly expressed in reproductive organs, whereas TaDA1-D and TaDA1-B were mainly expressed in vegetative organs. Both mutated TaDA1 and TaWG2 increased the grain size and weight of wheat, whereas the TaDA1 gene negatively regulates grain size by limiting the proliferation of maternal pericarp cells (H. Liu et al., 2020). Mutations of site 358 in DA1 inhibit the activity of DA1 and DAR1, resulting in increased seed sizes in Arabidopsis, canola, and maize; however, the mutation site has not been found for the natural variation, causing its limited application in breeding.

As a RING-type E3 ubiquitin ligase homolog to DA2, WG2 negatively regulates the grain width and weight in rice (Choi et al., 2018). It has great potential WG2 for yield improvement due to mutation GW2 can increase the grain yield without affecting the grain quality, and (Achary & Reddy, 2021; Rasheed et al., 2022; Yamaguchi et al., 2020). Further, ZmGW2-CHR4 and ZmGW2-CHR5 of maize, TaWG2-A1, TaWG2-B1, TaWG2-D1, and TaWG2-6A of wheat were also involved in grain size regulation. In addition, the 26S proteome and deubiquitinase also affect the seed size. Compared with wild type, the atrpt2a mutant contains larger and fewer cells, AtRPT2 was involved in seed size by restricting cell expansion (Kurepa et al., 2009). Different from WG2 regulating cell division to influence seed width, WTG1 controls the grain size and shape by affecting the cell expansion (Huang et al., 2017; S. S. Wang et al., 2017). Further, WTG1 promotes K48-linked ubiquitination and limits the K63-linked ubiquitination of OsSPL14, which may be a target of downstream cell-expansion regulators, and identifying novel targets of WTG1 would help to reveal its downstream mechanisms of seed size control.

In general, we expect these genes in wheat, corn, rice, and other crops to be used as references for soybean. However, compared with the wild type, there was no significant difference in the seed sizes of overexpressing soybean DA1 transgenics plants (Zhao et al., 2015), which was inconsistent with the results for DA1 in mouse-ear cress [Arabidopsis thaliana (L.) Heynh.] canola, maize, and wheat (Li et al., 2008; H. Liu et al., 2020; J. L. Wang et al., 2017; Xia et al., 2013; Xie et al., 2018). The DA1 gene may have multiple functions in plants, and the conserved functions of homologous genes are affected by the distance of the genetic relationship. In addition, GmGW2's regulation of the seed size in soybean also has not been reported. The seed size is a key trait affecting early growth, and also a key factor determining soybean yield. However, until now, only three soybean grain size regulatory factors have been reported, with no studies on the UPS pathway. So, is UPS not involved in soybean grain size regulation? As different target proteins are involved in different pathways, we believe that some target proteins that regulate grain size are involved in soybean UPS although it may be different from other species. Therefore, it is urgent to find the key genes regulating soybean grain through UPS. The molecular functions of the UPS in soybean yield formation need to be further explored.

IMPROVING SOYBEAN PRODUCTION THROUGH NEW DESIGN ASSOCIATED WITH THE UBIQUITIN-PROTEASOME SYSTEM

As model plants, mouse-ear cress and rice are the most intensively studied dicotyledons and monocots, whether in genome sequencing; mutant library establishment; or transcriptome, proteome, and functional studies. Learning from the model plants is also a more efficient way to gain more information for soybean research. Similar to rice, with the publication of the soybean reference genome and the development of sequencing technology, the population genetics of soybean has greatly advanced in the last decade. Compared with commercial soybean the wild soybean was much more genetically diverse, however, half of them has been lost in modern cultivars (Zhou et al., 2015), which has limited the development of new elite cultivars. It is essential to exploit to expand gene pools and novel sources of genetic diversity for soybean improvement. Using physical mutagenesis, chemical mutagenesis, and biological mutagenesis to increase genetic diversity was an effective method of learning from the model plants (Oladosu et al., 2016). So far, more than 6,000 soybean germplasm resources have been genotyped for breeding (Zhang, Liu et al., 2022), and a great number of single nucleotide polymorphism (SNP) markers have been generated via resequencing, which greatly increases the efficiency of gene mapping and facilitates the construction of haplotype maps (Patil et al., 2016; Torkamaneh et al., 2021). A genetic diversity pool can be obtained quickly using physical or chemistry methods; however, the utilization of these mutant populations in the soybean community was limited by the lack of genome-wide characterization of mutations (S. Liu et al., 2020; Zhang, Zhang et al., 2022). To advance this progress, recent studies involved the whole-genome sequencing of 1,044 mutant lines via ethyl methane sulphonate mutagenesis for characterization, and a total of 6,774,731 mutations were pinpointed, including 3,141,030 homozygous and 3,633,701 heterozygous mutations (Zhang, Zhang et al., 2022).

The above review indicates that the UPS plays an important role in crop stability and yield, however, there are few studies on the UPS in soybean. In the UniProtKB database, <20 soybean ubiquitin-associated proteins have been reviewed at the protein or transcription level. For the UPS in soybean, we can still refer to the molecular functions of ubiquitination-related genes in Arabidopsis or rice with stable and high yields, which could help us quickly understand the molecular function of soybean ubiquitination genes in yield formation. However, the function of homologous genes was affected by the distance of the genetic relationship; for example, for the star gene DA1, there was no significant difference in the seed sizes of overexpressing soybean DA1 transgenics plants, which was inconsistent with the results for DA1 in Arabidopsis, canola, maize, and common wheat. In addition, although genome editing has shown great advantages in terms of trait improvements, only a few genes controlling the soybean yield, such as seed size or plant architecture genes, have been characterized. Many studies of reverse genetics are not directly applicable to breeding (S. Liu et al., 2020). Meanwhile, forward genetics refers to the mapping of unknown genes regulated by a trait, then the further study of their pathways and interaction network, both of which have certain limitations or involve unpredictability.

Is there a way to explore one pathway gene at a time and use them in breeding? Here, taking the UPS in soybean as an example, we described potential approaches for combination with mutant libraries, genomics, proteomics, and phenotypic analyses for stable and high soybean yields.

The genes of 2,429 ubiquitin-related proteins in the UniProtKB database were searched in the iSoybean mutant library, and 2,078 genes with 22,067 nonsynonymous or stop gain mutations were retrieved (Supplemental Table S1). Among them, 373 E3 ubiquitin ligases were used for protein–protein interaction network predictive analysis using the STRING 11.0 program (https://cn.string-db.org/) (Gong et al., 2021; Xiong et al., 2022, 2021). The network showed that the E3 ubiquitin ligases GmARI1, GmARI2, GmARI3, and GmARI7 have multiple interacting proteins, which may be involved in multiple pathways. The results were consistent with a previous study that GmARI1 plays a key role in stress response (Zhang et al., 2014). Therefore, it can be inferred that those with more interacting proteins, may participate in more pathways affecting soybean growth and development, such as Glyma12G03640, Glyma12G05050, Glyma18G39750, Glyma07G15840, Glyma11G25680, and so on (Figure 1). The mutants of ubiquitin-related genes can be used for yield trait analyses or anti-stress screening. Furthermore, these mutants with important genetic traits such as their short internode length, appropriate plant height, few branches, moderate pod number of each node, higher ratio of four seeds per pod, moderate 100-seed weight, small petiole angle and short petiole length, can be used in breeding. Arabidopsis ALF4 was involved in regulating the ubiquitination process (Bagchi et al., 2018), meanwhile its homologous genes such as the Gyma.17G215800 mutant can be used for ubiquitination proteome and isobaric tags for relative and absolute quantification (iTRAQ) or label-free/MS proteome analyses. Some target proteins involved in the ubiquitination pathway can also be screened for their E3 ligases using yeast two-hybrid screening or Co-IP/MS approach, which also can enrich the ubiquitination pathway and molecular network of soybean plants. In addition, using these materials for transcriptome, metabolome and proteome studies can enrich the corresponding soybean database, which can provide an important basis for the study of soybean's molecular mechanism and of stable and high-yield varieties.

FIGURE 1. Protein-protein interaction network of soybean E3 ubiquitin ligases in iSoybean library

CONCLUSIONS

In this review, we discussed the role of the soybean ubiquitin-proteasome system in yield formation compared with other plants. Referring to Arabidopsis and rice, it is of great significance to expand the genetic diversity and establish a mutant library for soybean yield research. Furthermore, the combination of phenotype, mutant library, genomics and proteomics approaches is proposed to facilitate the exploration of the ubiquitin-proteasome system for stable and high-yielding soybean. In this new design, the use of transgenic technology and the establishment of a mutant library are two technical challenges. There is an urgent need to obtain a large number of mutants with clear backgrounds and to establish an effective mutant database based on sequencing methods. However, the recently developed graph-based soybean pangenome will revolutionize the functional studies in soybean, and the rapid development of new technologies, such as high-throughput analyses, genomic selection, and genome editing, will certainly accelerate the accomplishment of the proposed tasks. In addition, the efficiency of transgenic technologies is also more mature and improved. We firmly believe that soybean research will enter a period of rapid development in the next decade.

AUTHOR CONTRIBUTIONS

Erhui Xiong: Data curation; Resources; Writing-original draft; Writing-review & editing. Xuelian Qu: Data curation; Resources. Junfeng Li: Data curation; Resources. Hongli Liu: Data curation; Resources; Writing-original draft. Hui Ma: Resources. Dan Zhang: Writing-original draft. Shanshan Chu: Resources; Writing-original draft. Yongqing Jiao: Writing-review & editing.

ACKNOWLEDGMENTS

This research was funded by the National Natural Science Foundation of China (32101641, 32172418 and 31971971) and Henan Agricultural University (30500689).

CONFLICTS OF INTEREST

The authors declare no conflict of interest.