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. 2026 Oct 5;127(6):e71141. doi: 10.1111/tpj.71141

SDR3.1 negatively regulates seed dormancy in Poaceae crops

Naihui Guo 1, Ruihu An 1, Mengxue Xu 2, Yuanyuan Li 1, Zongliang Ren 1, Jun Jiang 1, Bonian Cai 1, Xinzhu Huang 1, Shikai Hu 1, Gaoneng Shao 1, Guiai Jiao 1, Lihong Xie 1, Ling Wang 1, Fengli Zhao 1, Yujun Zhu 1, Shaoqing Tang 1,✉, Zhonghua Sheng 1,✉, Peisong Hu 1,✉
PMCID: PMC13639105  PMID: 42834486

SUMMARY

Elucidating the molecular mechanisms that govern seed dormancy is important for developing crops with improved resistance to preharvest sprouting (PHS). A series of seed dormancy genes have been cloned, but the connections among different seed dormancy genes remain poorly understood. Here, we have revealed the relationship between two important dormancy quantitative trait loci (QTLs): SDR3.1 and Sdr4. SDR3.1 formed complexes with ABI3 and ABI5 and suppressed their activation of Sdr4 transcription. Haplotype analysis showed that the germination rate of SDR3.1 L‐type and Sdr4 n‐ or K‐type combinations was low, and the parents of modern core breeding do not contain l‐type. Analysis of transgenic plants confirmed that orthologs of SDR3.1 have conserved functions in controlling seed dormancy in rice (Oryza sativa L.), foxtail millet (Setaria italica (L.) P. Beauv.), and maize (Zea mays), but they have different molecular regulatory mechanisms. This study uncovers the OsSDR3.1‐ABI3/ABI5‐Sdr4 regulatory module conferring improved PHS resistance, while establishing an effective approach to characterize core functional genes for important agronomic traits across Poaceae species with rice as a model.

Keywords: rice, SDR3.1, Sdr4, seed dormancy, preharvest sprouting, Poaceae crops

Significance statement

For staple crops in the Poaceae family, such as wheat, barley, and maize, yield losses occur due to preharvest sprouting (PHS), in which seeds germinate on the mother plant directly before harvest when they encounter high temperature and humidity. This study uncovers the OsSDR3.1‐ABI3/ABI5‐Sdr4 regulatory module conferring improved PHS resistance, while establishing an effective approach to characterize core functional genes for important agronomic traits across Poaceae species with rice as a model.

INTRODUCTION

Improvements in crop yield are getting smaller each year. Consequently, with the decreasing availability of arable land and the outbreak of extreme climate, the goal of ending global hunger by 2030 is becoming increasingly challenging (Hodson, 2017). As such, reducing yield losses is an important goal of current agricultural research. For staple crops in the Poaceae family, such as wheat, barley, and maize, yield losses occur due to preharvest sprouting (PHS), in which seeds germinate on the mother plant directly before harvest when they encounter high temperature and humidity (Xu et al., 2019). In addition, PHS can reduce seed quality and the lodging resistance of large panicle varieties. Rice, belonging to the Poaceae family, is an important cereal crop worldwide and an ideal model system due to its morphological and genetic characteristics (Kim et al., 2014). The PHS of rice is similar to that of other major crops in the Poaceae family and the Fabaceae family, such as maize, wheat, and soybean. Investigations on G and Seed Dormancy 6 (SD6) are examples that extend knowledge on seed dormancy from rice to wheat and soybean (Wang et al., 2018; Xu et al., 2022). Therefore, rice is a good model for seed dormancy research for the Poaceae family, even for the Fabaceae family.

Seed dormancy refers to the phenomenon where viable seeds cannot germinate under suitable environmental conditions such as temperature, water, light, and oxygen. Notably, PHS is closely related to seed dormancy, and varieties with strong dormancy have stronger resistance to PHS. Therefore, enhancing seed dormancy is an effective means of inhibiting PHS. However, to accelerate the breeding process, breeders have eliminated some dormant germplasm during breeding, resulting in high‐yield varieties often experiencing PHS. Thus, cloning seed dormancy genes is essential for ensuring high yields and achieving food security worldwide.

So far, 7 QTLs for seed dormancy have been cloned in rice, including Sdr4(LOC_Os07g39700) (Sugimoto et al., 2010), qSD7‐1 (LOC_Os07g11020) (Gu et al., 2011), qSD1‐2 (LOC_Os01g66110) (Ye et al., 2015), qsd‐1‐1 (LOC_Os01g20030) (Wang, Lin, et al., 2020), SD6 (LOC_Os06g06900) (Xu et al., 2022), SDR3.1 (LOC_Os03g11550) (Guo et al., 2024), and qPSR8 (LOC_os08g42440) (Fan et al., 2025). However, there is still a lack of understanding of the relationship between different dormant genes. Moreover, research on using cloned dormant genes for improving PHS resistance is still relatively scarce.

Abscisic acid (ABA) and gibberellins (GA) are the primary hormones that antagonize and regulate seed dormancy (Penfield, 2017; Sajeev et al., 2024; Sano & Marion‐Poll, 2021; Shu et al., 2016). ABA promotes seed dormancy, while GA releases seed dormancy. Notably, ABA regulation of dormancy involves its content and signal transduction. Additionally, several factors regulating ABA signal transduction in seeds have recently been identified, such as PHS8 (Du et al., 2018), PHS9 (Xu et al., 2019), SDR3.1 (Guo et al., 2024), OsFTIP1 (Shen et al., 2024), and qPSR8 (Fan et al., 2025). The ABA signaling pathway involves many transcription factors, among which ABI3 and ABI5 are more critical. ABI5 enhances seed dormancy (Du et al., 2018; Guo et al., 2024; Zou et al., 2008), and several factors can inhibit the activity of ABI5 or degrade the ABI5 protein to promote seed germination (Du et al., 2018; Guan et al., 2014; Ju et al., 2019; Pan et al., 2020; Piskurewicz et al., 2008; Zhao et al., 2019). In comparison, several factors can promote ABI5 expression and maintain its protein stability to enhance seed dormancy (Hu & Yu, 2014; Yang et al., 2021). Relatively speaking, there is limited research on the regulation of seed dormancy by ABI3. ABI3 interacts with TRAB1 to regulate ABA‐induced transcriptional responses, thus playing an important role in regulating rice seed dormancy (Hobo et al., 1999). The interaction among ABI3, Rc, and OsC1 enhances seed sensitivity to ABA, leading to increased seed dormancy and inhibited PHS (Wang, Deng, et al., 2020). Furthermore, ABI3 can positively regulate seed dormancy by activating the expression of Sdr4 (Chen et al., 2021), which can positively regulate seed dormancy (Zhao et al., 2022).

In our prior research, the dormancy gene SDR3.1 was cloned from Mengjialaxiaoli, which negatively regulates seed dormancy and mediates seed dormancy differentiation between Xian and Geng. SDR3.1 interacts directly with ABI5 and inhibits the activation of EM1/LEA3 by ABI5/ABI3 (Guo et al., 2024). Therefore, we intend to explore further the relationship between SDR3.1, ABI3, and Sdr4 using experimental techniques such as AlphaFold3 prediction, Y2H, BiFC, pull‐down, luciferase (LUC), and transgenic technology. Using gene editing technology to knock out the homologous gene SDR3.1 in foxtail millet and maize, we can elucidate its common role in seed dormancy of cereal crops and preliminarily explore its molecular mechanism. Moreover, using germplasm resources to analyze the effects of different allele combinations of SDR3.1 and Sdr4 on rice dormancy will provide theoretical support and effective gene resources for improving crop PHS traits.

RESULTS

SDR3.1 physically interacts with ABI3

Our previous study demonstrated that SDR3.1 represses ABI3 transcriptional activation in rice (Guo et al., 2024). To determine whether SDR3.1 could directly interact with ABI3, we performed AlphaFold3 prediction. The result showed that SDR3.1 could bind tightly to ABI3 (Figure S1a), and their interaction involves a 3‐bond method, with a total of 16 binding sites (Figure S1b,c). This interaction was validated by yeast two‐hybrid (Y2H) assays (Figure 1A), in vitro pull‐down (Figure 1B), and co‐immunoprecipitation (Co‐IP) assays in rice protoplasts (Figure 1D). Furthermore, bimolecular fluorescence complementation (BiFC) assays confirmed that the interaction between SDR3.1 and ABI3 occurred in the nucleus (Figure 1C).

Figure 1.

Figure 1

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SDR3.1 interacts with ABI3.

(A) The Y2H showed that SDR3.1 interacted with ABI3.

(B) Pull‐down assays showed that SDR3.1 interacted with ABI3.

(C) BiFC assays showed that SDR3.1 interacted with ABI3. Bar = 10 μm.

(D) Co‐IP assays showed that SDR3.1 interacted with ABI3.

(E) Germination rate of ZH11, sdr3.1, abi3, and sdr3.1/abi3 (n = 3 independent experiments).

(F) PHS phenotypes of ZH11, sdr3.1, abi3, and sdr3.1/abi3 35 DAH. Data are presented as the mean ± SD.

To elucidate the regulatory relationship between SDR3.1 and ABI3, we generated the sdr3.1/abi3 double mutant in the ZH11 background (Figure S2a,b). Phenotypic analysis revealed that the germination rate of the sdr3.1/abi3 double mutant was comparable to that of the single mutants abi3‐1 and abi3‐2 (Figure 1E,F). The results also implied that SDR3.1 may act upstream of ABI3.

Transcriptome analysis of SDR3.1 knockout plants

RNA sequencing (RNA‐seq) was performed to characterize the transcriptomic differences in fresh seeds between ZH11 and the sdr3.1 mutant. A total of 9886 differentially expressed genes (DEGs) were identified with a significance threshold of P < 0.05. Compared with ZH11, 34.0% of these DEGs (3364 genes) were up‐regulated, while 66.0% (6522 genes) were down‐regulated in the sdr3.1 mutant (Figure 2A).

Figure 2.

Figure 2

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SDR3.1 negatively regulates the expression of Sdr4.

(A) Volcano plot of DEGs between sdr3.1 and ZH11.

(B) KEGG pathway enrichment analysis of DEGs. Sdr4 enrichment in the “plant hormone signal transduction” pathway.

(C) The expression of Sdr4 in sdr3.1 and ZH11.

(D) Pattern diagram of carrier in LUC experiment.

(E) SDR3.1 repressed ABI3 to activate Sdr4 treated with 5 μM ABA.

(F) Germination rate of ZH11, sdr3.1, sdr4, and sdr3.1/sdr4 (n = 3 independent experiments).

(G) PHS phenotypes of ZH11, sdr3.1, sdr4, and sdr3.1/sdr4 35 DAH. Data are presented as the mean ± SD.

Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that DEGs were significantly enriched in 8 pathways, including plant hormone signal transduction, zeatin biosynthesis, and phenylpropanoid biosynthesis (Figure 2B). Interestingly, the first cloned rice seed dormancy gene Sdr4 was in plant hormone signal transduction pathway (Figure 2B). Additionally, combining RNA‐seq and qRT‐PCR analyzed, we found that the expression level of Sdr4 was significantly higher in sdr3.1 than in ZH11 (Figure 2C). Thus, the results indicated that SDR3.1 may inhibit the expression of Sdr4.

SDR3.1 inhibits the expression of Sdr4

To further explore the relationship between SDR3.1 and Sdr4, we performed AlphaFold3 prediction. The result showed that ABI3 could bind to 3 bases in the Sdr4 promoter (Figure S3a). However, SDR3.1 disrupts the binding capability of ABI3, reducing the binding site to 1 (Figure S3b). Next, the LUC gene was ligated to the promoter region of Sdr4 to construct the reporter plasmid. For trans‐acting experiments, SDR3.1, ABI3, and green fluorescent protein (GFP) genes were expressed under the regulation of the CaMV 35S promoter (Figure 2D). When the samples were treated with 5 μM ABA, the Sdr4 reporter showed a marked activation effect in the presence of the ABI3 effector, in contrast to the GFP effector used as a control (Figure 2E). Nevertheless, the concurrent expression of SDR3.1 and ABI3 impaired the activation of LUC expression induced by ABI3 (Figure 2E). As such, these observations suggest that SDR3.1 exerts an inhibitory effect on Sdr4 expression by suppressing the transcriptional activity of ABI3.

To further elucidate the regulatory relationship between SDR3.1 and Sdr4, we generated the sdr3.1/sdr4 double mutant in the ZH11 background (Figure S4a,b). Phenotypic analysis revealed that the germination rate of the sdr3.1/sdr4 double mutant was comparable to that of the single mutants sdr4‐1 and sdr4‐2 (Figure 2F,G). Notably, the results verified that SDR3.1 inhibited the expression of Sdr4.

Because SDR3.1 interacted with ABI5 (Guo et al., 2024), ABI5 may also bind to the Sdr4 promoter like ABI3. The yeast one‐hybrid (Y1H) assay showed that ABI5 could bind to the promoter of Sdr4 (Figure S5a). The qRT‐PCR results also showed that the expression level of Sdr4 was significantly reduced in abi5 compared with ZH11 (Figure S5b). This indicates that ABI5 promotes the expression of Sdr4. In addition, we used a LUC experiment to explore the relationship among SDR3.1, ABI5, and Sdr4. To do so, the LUC gene was ligated to the promoter region of Sdr4 to construct the reporter plasmid. SDR3.1 and ABI5 were expressed under the regulation of the CaMV 35S promoter (Figure S5c). The concurrent expression of SDR3.1 and ABI5 impaired the activation of LUC expression induced by ABI5 (Figure S5d), indicating that SDR3.1 inhibited the expression of Sdr4 via repressing the transcriptional activity of ABI5.

Because SDR3.1 interacted with ABI5 and ABI3, we tested whether the 3 genes could form a complex by a yeast three‐hybrid (Y3H) assay. The results showed that ABI5 could interact with ABI3 and the 3 genes could form a complex (Figure 3A). This interaction was further validated by Co‐IP assays in rice protoplasts (Figure 3B). Furthermore, we have created a triple mutation (TM) of SDR3.1, ABI3, and ABI5 via CRISPR/Cas9 (Figure S6). The germination rate of the TM was similar to abi3‐1 (Figure 3C).

Figure 3.

Figure 3

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SDR3.1 can form complexes with ABI3 and ABI5.

(A) The Y3H showed that SDR3.1 interacted with ABI3 and ABI5.

(B) Co‐IP assays showed that SDR3.1 interacted with ABI3 and ABI5.

(C) Germination rate of ZH11, sdr3.1–1, abi3‐1, abi5‐1, and TM (n = 3 independent experiments).

(D) PHS phenotypes of ZH11, sdr3.1–1, abi3‐1, abi5‐1, and TM 35 DAH. Data are presented as the mean ± SD.

In all, these results indicated that SDR3.1 inhibits the expression of Sdr4.

The effect of different allele combinations of SDR3.1 and Sdr4 on dormancy

Given that SDR3.1 and Sdr4 are major dormant QTLs, we analyzed different allele combinations of SDR3.1 and Sdr4 in 273 natural rice populations. Based on the difference bases at positions 305 and 3399, we classified SDR3.1 into three allele types: m, h, and l (Figure 4A); similarly, based on the difference bases at positions 596 and 606, we classified Sdr4 into two allele types: n and k (Figure 4B). The average germination rate of h‐n (64.4%) was the highest, followed by those of m‐n (38.9%) and m‐k (14.5%), and the average germination rate of l‐n (7.7%) and l‐k (2.4%) was the lowest (Figure 4C). Correspondingly, we investigated the paddy field PHS situation of different haplotype combinations. The results showed that varieties containing l‐type had the lowest PHS phenomenon, with almost no sprouting (Figure S7). Among the 273 rice accessions, 77 were Xian/indica, and 77 were Geng/japonica. Xian/indica was mainly m‐n and m‐k, accounting for 57% and 36%, respectively. Geng/japonica was mainly h‐n, accounting for 87% (Figure 4D). Based on the above findings, the best method to improve the PHS resistance of Geng/japonica is to replace the h‐type of SDR3.1 with the l‐type. There are two ways to improve the PHS resistance of Xian/indica: one is to replace the n‐type of Sdr4 with the k‐type, and the other is to replace the m‐type of SDR3.1 with the l‐type.

Figure 4.

Figure 4

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The effect of different allele combinations of SDR3.1 and Sdr4 on dormancy.

(A) Haplotypes of SDR3.1 in 273 accessions according to two SNPs in the coding sequence region.

(B) Haplotypes of Sdr4 in 273 accessions according to two SNPs in the coding sequence region.

(C) The 7‐day germination rate of the five haplotype combinations (273 rice accessions) 35 DAH.

(D) Rice subspecies distribution of each haplotype combination.

(E) Geographic distribution of the three haplotype combinations among 87 accessions of core breeding parents. N: North latitude; E: East longitude.

(F) The 7‐day germination rate of the three haplotype combinations (87 accessions of core breeding parents) 35 DAH.

The lower case letters above the bars indicated significant differences based on ANOVA analysis (p < 0.05).

Furthermore, we collected core breeding parents (87 accessions) from southern China's rice‐growing regions (Figure 4E) and conducted germination experiments. These 87 rice varieties are divided into three types, with m‐n accounting for 42.5%, m‐k accounting for 5.8%, and h‐n accounting for 51.7% (Figure 4F). The average germination rates of the three types were 59.3%, 63.5%, and 64.3% (Figure 4F), respectively, all of which showed high germination rates. Among these parents, no l‐type parent showed a low germination rate. Therefore, introducing l‐type allele genes into breeding parents is a feasible method to improve PHS resistance.

SDR3.1 functions conservatively in major crops of the Poaceae family

Previous research indicated that the SDR3.1 gene encodes a Mediator of OsbZIP46 deactivation and degradation, which contains an EAR domain, a NINJA_B domain, and a TDBD domain (Guo et al., 2024). Phylogenetic analysis indicated that SDR3.1 shares an orthologous relationship with SiSDR3.1 (Seita.9G490900) from Setaria italica (Figure S8a), recorded as a Ninja‐family protein 1 isoform X1 in the foxtail millet gene repository (https://111.203.21.71:8000/search.html). Moreover, based on the phylogenetic tree (Figure S8a) and BLAST sequence identity results (Figure S8b), two SDR3.1 orthologs were identified within the Poaceae family, namely ZmSDR3.1 (Zm00001eb400170) in Zea mays and SorSDR3.1 (SORBI_3001G456400) in Sorghum bicolor.

To verify whether the function of SDR3.1 in regulating seed dormancy is conserved among Poaceae species, we used the CRISPR/Cas9 system to knock out SiSDR3.1 in the Ci846 genotype. Sequencing verification confirmed the acquisition of two homozygous mutant lines, Sisdr3.1‐1 and Sisdr3.1‐2, both of which carried a 1‐bp frameshift insertion in the first exon (Figure 5A). Consistent with our expectations, the germination rates of these two mutant lines were significantly lower than that of Ci846 (Figure 5B,C). Additionally, we generated two homozygous mutants in the B104 genotype via CRISPR/Cas9‐mediated genome editing (Figure 5D). Importantly, the Zmsdr3.1 mutants in maize also displayed a marked decrease in germination rates (Figure 5E,F). Taken together, the results of these transgenic experiments demonstrate that SDR3.1 plays a conserved role in regulating seed dormancy across Poaceae species.

Figure 5.

Figure 5

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SDR3.1 regulates seed dormancy in major cereal crops.

(A) Generation of Sisdr3.1‐1 and Sisdr3.1‐2.

(B) Germination phenotypes of Ci846 and the two mutants.

(C) Germination rate of Ci846 and the two mutants (n = 3 independent experiments).

(D) Generation of Zmsdr3.1‐1 and Zmsdr3.1‐2.

(E) Germination phenotypes of B104 and the two mutants.

(F) Germination rate of B104 and the two mutants (n = 3 independent experiments). Data are presented as the mean ± SD.

To explore whether the molecular mechanism of SDR3.1 regulating dormancy in different crops is the same, we first found the homologous gene of ABI3. Phylogenetic analysis suggests that ABI3 is orthologous to SiABI3 (Seita.5G423900), SorABI3 (Sobic.003G398200), and ZmABI3 (Zm00001eb143690) (Figure S9a), which all contain a Bfil_C_EcoRII_N_B3 domain (Figure S9b). We also found that SiSDR3.1 could interact with SiABI3 in Setaria italica via using Y2H assays (Figure 6A; Figure S10a). Subsequently, the in vivo interaction between the SiSDR3.1 protein and the SiABI3 protein in the nucleus was confirmed by luciferase complementation imaging (LCI) and Co‐Immunoprecipitation(Co‐IP) experiments (Figure 6B,C). In maize, the Y2H results of ZmABI3 (BD) and ZmSDR3.1 (AD) showed that they can interact (Figure S10b), but ZmSDR3.1 (BD) and ZmABI3 (AD) do not interact with each other (Figure 6D). Further, LCI and Co‐IP also prove that ZmSDR3.1 cannot interact with ZmABI3 (Figure 6E,F). Therefore, the above results indicate that SDR3.1 has different mechanisms in regulating seed dormancy in different crops.

Figure 6.

Figure 6

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SDR3.1 has different mechanisms in regulating seed dormancy in different crops.

(A) The Y2H showed that SiSDR3.1 interacted with SiABI3.

(B) The LCI assay showed that SiSDR3.1 interacted with SiABI3.

(C) The Co‐IP assay showed that SiSDR3.1 interacted with SiABI3.

(D) The Y2H assay showed that ZmSDR3.1 did not interact with ZmABI3.

(E) The LCI assay showed that ZmSDR3.1 did not interact with ZmABI3.

(F) The Co‐IP assay showed that ZmSDR3.1 did not interact with ZmABI3.

DISCUSSION

From seed dormancy to germination is an initial and important stage; this transition is governed by complex regulatory networks (Wang, Zhang, et al., 2025). Specifically, seed dormancy—a quantitative trait associated with plant domestication—is jointly controlled by multiple genes and modulated by diverse environmental factors (Graeber et al., 2012; Penfield & MacGregor, 2017; Xu et al., 2022). This characteristic renders the identification of seed dormancy‐related genes extremely challenging. Sdr4, which positively regulates rice seed dormancy, is the first gene cloned from the indica cultivar Kasalath (Sugimoto et al., 2010). ABI3 can directly bind to the Sdr4 promoter and thereby activate its transcription (Chen et al., 2021). In our prior research, SDR3.1 interacts directly with ABI5 and inhibits the activation of EM1/LEA3 by ABI5/ABI3 (Guo et al., 2024). In this study, we found the relationship between two seed dormancy QTLs, SDR3.1 and Sdr4, and provide AI, molecular, biochemical, and genetic evidence supporting the signaling network in which they work alongside ABI5 and ABI3. Thus, we propose the following network: SDR3.1, ABI3, and ABI5 form a complex; then SDR3.1 inhibits the transcriptional activation function of ABI3 and ABI5, leading to decreased expression of the downstream gene Sdr4 of ABI3/ABI5, ultimately resulting in seed germination (Figure 7).

Figure 7.

Figure 7

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Proposed working model for SDR3.1 in rice.

SDR3.1, ABI3, and ABI5 interact to form a complex. In contrast, SDR3.1 inhibits ABI3‐ and ABI5‐mediated activation of Sdr4, ultimately leading to seed germination.

Domestication can be considered the earliest form of breeding (Wang et al., 2018); this process has resulted in the loss of many elite haplotype genes. Therefore, identifying and utilizing elite haplotype genes has become a hot topic in current agricultural research. For example, as a high‐NUE haplotype, OsGATA8‐H promoted nitrogen uptake and increased the proportion of productive tillers (Wu et al., 2024). The elite allele SBRR1‐R is preferentially distributed in indica rice varieties; its introduction into japonica rice varieties notably alleviated yield loss under conditions of severe sheath blight disease stress (Feng et al., 2025). Introducing the elite CSP haplotype of Aegilops tauschii into wheat could significantly increase grain yields (Wang, Guo, et al., 2025). In addition, this could help identify a large number of elite haplotype genes in areas such as crop drought tolerance (Hou et al., 2025; Li, Yang, et al., 2025; Liu et al., 2025; Sinha et al., 2020; Sun et al., 2022; Xiang et al., 2025), grain shape (Ang et al., 2025; He et al., 2025; Zhao et al., 2025), heat stress tolerance (Lu et al., 2024; Zhang et al., 2022), cold tolerance (Gao et al., 2025; Zeng et al., 2025), seed dormancy (Guo et al., 2024; Zhang et al., 2026), etc. However, a strong dormancy haplotype may lead to poor field emergence and thus hinder the popularization of direct seeding cultivation.

Therefore, the combined analysis of multiple dormant gene haplotypes can provide more choices for PHS resistance breeding, just like the trait regulatory haplotypes (TRHs) established in the study of heat‐tolerant genes (Li, Zhu, et al., 2025). In this study, we found the effects of different allele combinations of SDR3.1 and Sdr4 on rice dormancy and proposed strategies for improving PHS resistance in indica and japonica rice; furthermore, in the process of half a century of southern and northern breeding, to accelerate the breeding process and ensure rapid germination of seeds, breeders have eliminated dormant germplasm. As a result, elite dormant haplotypes are extremely rare in current core breeding parents. Therefore, introducing elite dormant haplotypes is an effective strategy for improving PHS resistance of core breeding parents. However, as recently reported, maintaining an appropriate level of bioactive GA is key to improving rice stress tolerance (Guo et al., 2025). As such, further research is required to clarify the optimal level of seed dormancy that is beneficial for both PHS resistance and direct‐seeded cultivation (Xu et al., 2025).

A few seed dormancy genes exhibited parallel selection across different families. G gene maintains conserved regulatory roles in modulating seed dormancy across soybean, rice, and Arabidopsis (Wang et al., 2018), while SD6 is conserved in rice and wheat (Xu et al., 2022). In this study, SDR3.1 negatively regulates seed dormancy in cereal crops such as rice, foxtail millet, and maize. The identification of parallel selection genes will facilitate the domestication of new crops (Wang et al., 2018). Interestingly, SDR3.1 has different molecular mechanisms for regulating seed dormancy in different crops. SDR3.1 in rice and foxtail millet regulates seed dormancy through ABI3, while SDR3.1 in maize does not. We speculate that such divergence in molecular mechanisms might be related to the homology relationship: Compared to maize, foxtail millet has a closer homologous relationship with rice (Figures S8a, S9a). Moreover, previous studies have shown that Sdr4 in Arabidopsis negatively regulates seed dormancy (Liu et al., 2020), while Sdr4 in rice positively regulates seed dormancy (Sugimoto et al., 2010). Such divergence in function might be related to different molecular mechanisms and sequence variation in their coding sequences (Liu et al., 2020). Therefore, the different molecular mechanisms of SDR3.1 might be related to the function of downstream genes; this requires further research.

METHODS

Plant material and growth conditions

The mutants sdr3.1‐1 and sdr3.1‐2 were obtained from previous research (Guo et al., 2024). Foxtail millet transgenic plants (sisdr3.1‐1 and sisdr3.1‐2) were obtained from the Ci846 variety. Maize transgenic plants (zmsdr3.1‐1 and zmsdr3.1‐2) were generated from the B104 variety. All rice transgenic plants were developed using the ZH11 genotype as the background. For haplotype combination analysis, a population consisting of 273 rice accessions (Guo et al., 2024) and 87 core breeding parents (materials collected and preserved by our research group, Table S1) was used. In terms of field trials, foxtail millet was cultivated in the experimental field of Shanxi Agricultural University, China (37°25′N, 112°35′E). Meanwhile, maize and rice were grown in Hangzhou and Hainan, respectively.

Evaluation of seed germination

Rice seed germination was performed following the method previously reported (Guo et al., 2024). For foxtail millet germination assays, 100 seeds were placed in each 90‐mm petri dish lined with two layers of filter paper, and these dishes were then incubated in a dark chamber at 25°C for 48 h to facilitate seed germination. For maize, 50 seeds were placed in each 150‐mm petri dish covered with two layers of filter paper, and the dishes were incubated in a dark incubator at 25°C for 5 days to induce germination.

AI predicts interaction results

On the AlphaFold3 website (https://alphafoldserver.com/), we input the gene sequence to be validated for prediction. We then opened the prediction results using Visual Studio Code software and selected model_0 for binding site analysis.

Y1H assay

The CDS of ABI5 was cloned into the pB42AD vector, while the promoter region of Sdr4 was inserted into the pLacz vector. These two recombinant plasmids were co‐transformed into the EGY48 yeast strain, which was then cultured on SD‐Ura‐Trp selective medium at 28°C for 3 days. Subsequently, several colonies were randomly picked and spotted onto SD‐Leu‐Trp‐His‐Ade/X‐gal medium supplemented with 2% (w/v) galactose, 1% (w/v) raffinose, 1 × salt buffer (7 g/L Na2HPO4·PH2O, 3 g/L Na2HPO4, pH 7.0), and 80 mg/L 5‐bromo‐4‐chloro‐3‐indolyl‐β‐d‐galactopyranoside acid and incubated for 1 day.

Y2H assay

The CDS of SDR3.1 or ABI3 was cloned into the pGBKT7 or pGADT7 vector, respectively. The recombinant vectors were then co‐transformed into the Y2Hgold yeast strain, which was cultured on SD‐Leu‐Trp medium at 28°C for 2–4 days. Subsequently, several colonies were randomly selected and spotted onto SD‐Leu‐Trp‐His‐Ade/X‐gal medium, followed by incubation for 3 days.

Y3H assay

The CDS of SDR3.1 was inserted into the pGADT7 vector, while the CDS of ABI3 and ABI5 was separately integrated into the pBridge backbone. These recombinant constructs were co‐transformed into the AH109 yeast strain and cultivated on SD‐Leu‐Trp medium at 28°C for 3 days. Following growth, independent single colonies were randomly collected and inoculated onto two types of selective media containing X‐α‐gal, namely SD‐Trp‐Leu‐His‐Ade and SD‐Trp‐Leu‐His‐Ade‐Met. All plates were finally incubated for an additional 3 days.

Pull‐down assay

The SDR3.1 gene cloned from rice cDNA was linked to the pGEX‐4 T‐1 vector. The ABI3 gene cloned from rice cDNA was linked to the pET28a vector to create a fusion protein with a His tag. A pull‐down assay was performed using Glutathione Agarose beads (Solarbio, P2020). The mouse monoclonal anti‐GST, anti‐His, and HRP‐goat anti‐mouse antibodies were obtained from Proteintech or YEASEN at a dilution of 1:10000 (YEASEN: 30901ES50; Proteintech: 66005‐1‐Ig and SA00001‐1).

BiFC assay

The CDS of SDR3.1 was ligated into the pSPYCE vector, and the CDS of ABI3 was inserted into the pSPYNE vector to construct recombinant plasmids. The two recombinant plasmids were then co‐transfected into rice protoplasts. Finally, a Zeiss LSM 710 NLO confocal microscope was used to detect fluorescence signals to verify their interaction.

Co‐IP assay

The CDS of SDR3.1 was ligated to pCAMBIA1305 containing a GFP tag, and the CDS of ABI3 was ligated to pCAMBIA1300 containing a MYC tag. The combined plasmids were introduced into rice protoplasts and incubated for 22 h. Co‐IP assay was performed using GFP‐Nanoab‐Agarose (Lablead, GNA‐250‐5K). The mouse monoclonal anti‐GFP, rabbit monoclonal anti‐MYC, HRP‐goat anti‐rabbit antibodies, and HRP‐goat anti‐mouse antibodies were obtained from Roche, Abclonal, or Proteintech at a dilution of 1:5000 (Roche: 11814460001; Abclonal: AE070 and AS003; Proteintech: SA00001‐2).

LCI assay

The CDS of SiSDR3.1 or ZmSDR3.1 was ligated to nLUC, and the CDS of SiABI3 or ZmSDR3.1 was ligated to cLUC. The two plasmids of Si or Zm were transformed into the EHA105 Agrobacterium strain. Mix nLUC or cLUC fusion plasmids and infiltrate them into tobacco leaves. Three days after inoculation, the luciferase luminescence signal was imaged using a live plant imaging system (Tanon 5200).

Transient transactivation assay

We constructed the pGreenII 0800‐LUC recombinant vector for the Sdr4 promoter to form the reporter vector and constructed the pGreenII 62‐SK recombinant vectors for ABI3, ABI5, SDR3.1, and GFP to form the effector vector. We then transferred the recombinant vector into rice protoplasts, treated them with 5 μM ABA at 28°C for 22 h, and detected LUC activity.

Expression analysis

Total RNA was extracted using a MolPure® Plant Plus RNA Kit (YEASEN, 19292ES50). RNA reverse transcription was performed using TaqMan™ MicroRNA (Applied Biosystems: 4366596). qRT‐PCR was performed with ABI QuantStudio6 FLEX Q6.

RNA‐seq analysis

Seeds of ZH11 and sdr3.1 at 35 days after heading were harvested and immediately frozen in liquid nitrogen. The cDNA libraries were constructed in accordance with Illumina standard protocols and sequenced on the Illumina NovaSeq 6000 platform by Biorun (Wuhan, China). Thresholds of P < 0.05 and |log2foldchange| >1 were set to screen for significantly differentially expressed genes. The clusterProfiler R package (version 3.8.1) was used for GO enrichment and KEGG enrichment analyses.

Author Contributions

HP and SZ designed the research; GN, AR, XM, LY, RZ, JJ, CB, HX, HS, SG, JG, XL, WL, ZF, ZY and TS performed the experiments; SZ and GN analyzed the results and wrote the manuscript.

Conflict of Interest

The authors declare that they have no conflict of interest.

Supporting information

Figure S1. AI predicts the interaction between SDR3.1 and ABI3. (a) SDR3.1 and ABI3 interaction pattern diagram. (b, c) The binding sites of SDR3.1 and ABI3. The red arrow indicates the specific combination position.

Figure S2. The mutant sites of the sdr3.1/abi3 double knockout line. (a) SDR3.1 mutant sites of sdr3.1/abi3 double knockout line; red arrows indicated knockout sites. (b) ABI3 mutant sites of sdr3.1/abi3 double knockout line; red arrows indicated knockout sites.

Figure S3. AI predictions of the interaction between SDR3.1, ABI3, and Sdr4. (a) ABI3 binds to three sites in the Sdr4 promoter region. (b) SDR3.1 reduces the binding sites of ABI3 to the Sdr4 promoter region.

Figure S4. The mutant sites of the sdr3.1/sdr4 double knockout line. (a) SDR3.1 mutant sites of sdr3.1/sdr4 double knockout line; red arrows indicated the knockout sites. (b) Sdr4 mutant sites of sdr3.1/sdr4 double knockout line; red arrows indicated the knockout sites.

Figure S5. SDR3.1 inhibits the expression level of Sdr4 by ABI5. (a) Yeast one‐hybrid assay showed that ABI5 bound to the Sdr4 promoter. (b) Expression levels of Sdr4 in abi5 and ZH11. (c) Schematic of the effectors and reporter used in the transient transactivation assays. (d) SDR3.1 repressed ABI5 to activate Sdr4 in response to 5 μM ABA.

Figure S6. The mutant sites of the TM line. (a) SDR3.1 mutant sites of the TM knockout line; red arrows indicated the knockout sites. (b) ABI3 mutant sites of the TM knockout line; red arrows indicated the knockout sites. (c) ABI5 mutant sites of the TM knockout line; red arrows indicated the knockout sites.

Figure S7. PHS of different haplotype combinations. Five varieties were investigated for each combination, and the survey was conducted 4 days after rain.

Figure S8. Homologous analysis of SDR3.1. (a) Evolutionary tree analysis of SDR3.1. (b) Multi‐sequence alignment result of SDR3.1.

Figure S9. Homologous analysis of ABI3. (a) Evolutionary tree analysis of ABI3. (b) Multi‐sequence alignment result of ABI3.

Figure S10. Y2H verification of SDR3.1 interaction proteins in foxtail millet and maize. (a) The Y2H showed that SiABI3 interacted with SiSDR3.1. (b) The Y2H assay showed that ZmABI3 interacted with ZmSDR3.1.

Table S1. Germination rate of core parents.

TPJ-127-0-s001.docx (1.5MB, docx)

Acknowledgments

We thank Yinpei Liang (Shanxi Agricultural University) for the valuable suggestions and revisions. This work was supported by the China National Key Research and Development Program (2023YDF1201200), Postdoctoral Fellowship Program and China Postdoctoral Science Foundation (BX20250025, 2025M782866), the Zhejiang Province Postdoctoral Research Optimal Funding Project (ZJ2025035), the Zhejiang Science and Technology Major Program on Agricultural New Variety Breeding (2021C02063‐2), Zhejiang Provincial Natural Science Foundation of China (LDQ23C130001), Zhejiang Provincial Science and Technology Project (2020R51007), the Key Research and Development Program of Zhejiang Province (2022C02011), Local Financial Funds of National Agricultural Science and Technology Center, Chengdu (No. NASC2024KY17).

Contributor Information

Shaoqing Tang, Email: sqtang@126.com.

Zhonghua Sheng, Email: shengzhonghua666@163.com.

Peisong Hu, Email: hupeisong@caas.cn.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Figure S1. AI predicts the interaction between SDR3.1 and ABI3. (a) SDR3.1 and ABI3 interaction pattern diagram. (b, c) The binding sites of SDR3.1 and ABI3. The red arrow indicates the specific combination position.

Figure S2. The mutant sites of the sdr3.1/abi3 double knockout line. (a) SDR3.1 mutant sites of sdr3.1/abi3 double knockout line; red arrows indicated knockout sites. (b) ABI3 mutant sites of sdr3.1/abi3 double knockout line; red arrows indicated knockout sites.

Figure S3. AI predictions of the interaction between SDR3.1, ABI3, and Sdr4. (a) ABI3 binds to three sites in the Sdr4 promoter region. (b) SDR3.1 reduces the binding sites of ABI3 to the Sdr4 promoter region.

Figure S4. The mutant sites of the sdr3.1/sdr4 double knockout line. (a) SDR3.1 mutant sites of sdr3.1/sdr4 double knockout line; red arrows indicated the knockout sites. (b) Sdr4 mutant sites of sdr3.1/sdr4 double knockout line; red arrows indicated the knockout sites.

Figure S5. SDR3.1 inhibits the expression level of Sdr4 by ABI5. (a) Yeast one‐hybrid assay showed that ABI5 bound to the Sdr4 promoter. (b) Expression levels of Sdr4 in abi5 and ZH11. (c) Schematic of the effectors and reporter used in the transient transactivation assays. (d) SDR3.1 repressed ABI5 to activate Sdr4 in response to 5 μM ABA.

Figure S6. The mutant sites of the TM line. (a) SDR3.1 mutant sites of the TM knockout line; red arrows indicated the knockout sites. (b) ABI3 mutant sites of the TM knockout line; red arrows indicated the knockout sites. (c) ABI5 mutant sites of the TM knockout line; red arrows indicated the knockout sites.

Figure S7. PHS of different haplotype combinations. Five varieties were investigated for each combination, and the survey was conducted 4 days after rain.

Figure S8. Homologous analysis of SDR3.1. (a) Evolutionary tree analysis of SDR3.1. (b) Multi‐sequence alignment result of SDR3.1.

Figure S9. Homologous analysis of ABI3. (a) Evolutionary tree analysis of ABI3. (b) Multi‐sequence alignment result of ABI3.

Figure S10. Y2H verification of SDR3.1 interaction proteins in foxtail millet and maize. (a) The Y2H showed that SiABI3 interacted with SiSDR3.1. (b) The Y2H assay showed that ZmABI3 interacted with ZmSDR3.1.

Table S1. Germination rate of core parents.

TPJ-127-0-s001.docx (1.5MB, docx)

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

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