Improvement of Rice Salt Tolerance by Pyramiding Two Genes in Xian and Geng Backgrounds Through CRISPR-Cas9 System

Abstract

Salinity is one of the main environmental factors influencing rice production. Many genes affecting salt tolerance (ST) have been cloned in rice so far. In the present study, four genes negatively regulating ST, including HST1, LRRK1, STRK2, and PC1, were edited by CRISPR-Cas9 technology in six rice varieties (three in indica (xian) and three in japonica (geng) backgrounds), and three two-gene editing combinations, including hst1-lrrk1, hst1-strk2, and hst1-pc1, were created. All combinations of hst1-pc1, hst1-lrrk1, and hst1-strk2 significantly improved the ST of all the tested materials in both xian and geng backgrounds and had much better ST than single-gene editing lines. The combination of hst1-pc1 had the poorest ST in CH70 and 8TX23 backgrounds but showed almost the same level of ST as the combinations of hst1-strk2 and hst1-lrrk1 in the C199S background for 17 days after salinization, which clearly brought out the background effect on ST and its utilization in ST breeding. As a comparison of the recipient varieties, almost all gene-edited lines except hst1-pc1 in the CH70 background showed significantly reduced grain weight owing to reduced seed setting rate in normal conditions. The hst1-strk2 showed the highest level of ST at the seedling stage and a relatively higher grain yield among all the lines; thus, it is feasible to enhance the ST of high-yielding rice varieties by simultaneously gene-editing against the two loci or pyramiding these two alleles with the other major ST genes of rice. Our results provide valuable gene resources and germplasms for improving rice salt tolerance and high yield.

1. Introduction

Rice (Oryza sativa) is an important staple food crop worldwide. As the global population continues to rise, rice production also needs to increase [1]. According to statistics, approximately 7% of the world’s land (more than 900 million hectares) is threatened by saline-alkalization, and there are no effective measures by which to control its spread [2]. The area of saline-alkali land in China has reached 100 million hectares [3]. With the increasingly scarce arable land resources, enhancing the utilization rate of saline-alkali land and the yield of crops grown on it is an important measure to increase the total grain output. The rice is defined as a salt-sensitive crop [4]. The sensitivity to salt was different in different growth stages, different organ parts, and different varieties. Younger seedlings are more susceptible to salinity than older seedlings, and root growth is more susceptible than shoot growth [5]. The salt tolerance (ST) of indica (xian) rice was generally higher than that of japonica (geng) rice [6]. Creating and cultivating new salt-tolerant germplasm resources is an important measure to improve and utilize saline-alkali land and increase grain yield.

ST traits of rice belong to quantitative traits, controlled by polygenes, easily affected by the environment, etc. [7]. In previous studies, many genes related to ST in rice have been identified [8,9,10,11,12,13,14,15,16,17,18]. Among them, the genes DST [8], HST1 [9], PC1 [10], LRRK1 [11], and STRK2 [11] negatively regulate ST in rice. Loss of DST function increases stomatal closure and reduces stomatal density, consequently resulting in enhanced drought and ST in rice [8]. OsRR22 (HST1) is a negatively regulated ST gene in rice identified by MutMap from 6000 ethyl methylate mutants [9]. The hst1 gene reduced Na⁺ ions, lipid peroxidation, and H₂O₂ content and improved proline and antioxidant enzyme activities under salt stress [12]. As a negatively regulated ST gene in rice, it has been widely used in modern crop breeding by CRISPR/Cas9 technology, and the gene-edited lines have shown greater ST than parents [13,14]. PC1 is a manganese (Mn²⁺)-dependent protein phosphatase; it acts as a molecular switch to dephosphorylate and deactivate CatC and negatively regulate H₂O₂ homeostasis and ST in rice [10]. LRRK1 and STRK2 participate in negative regulation of ST of rice, and STRK2 acts as the upstream of LRRK1 to transmit signals through phosphorylation [11]. The genes P5CS, SKC1, NHX1, and HAK1 positively regulate ST in rice [15,16,17,18]. Expression of the P5CS transgene under the control of a stress-inducible promoter led to stress-induced overproduction of the P5CS enzyme and proline accumulation in transgenic rice plants [15]. SKC1 encoded a member of HKT-type transporters; it is involved in regulating K/Na homeostasis under salt stress [16]. The OsNHX1 gene encodes vacuole (Na⁺, K⁺/H⁺) reverse transporters, and overexpression of OsNHX1 can improve ST in rice [17]. The expression of the OsHAK1 (K⁺ transporter) gene is significantly upregulated, and overexpression of this gene in rice can improve the tolerance of transgenic plants to salt stress [18].

Conventional breeding technologies, such as natural cross-hybridization, are often used to enhance crop production. However, these breeding methods are sometimes laborious and complicated [19]. Recently, molecular breeding technology made the agronomic character improvement more efficient. The CRISPR-Cas9 system, a convenient and efficient genome editing technology, has been widely utilized to study genetic modification of plants and animals [20]. Gene editing technology can regulate various biological processes by targeted knockout of target genes, which can be quickly applied in rice breeding through gene editing techniques [21]. To date, CRISPR/Cas9 has been widely applied to the genetic improvement of major crops such as rice, maize, oilseed rape, and soybeans [22]. TMS5 is the most widely applied thermo-sensitive genic male sterility gene in China. CRISPR/Cas9 was used for targeted editing to create a new sterile line and accelerate the crossbreeding process [23]. Genome editing techniques can edit several sites at the same time to get mutants that combine multiple genes, which might have greater impacts on related traits than a single gene. Three genes related to grain weight (GW2, GW5, and TGW6) were simultaneously edited to achieve rapid gene aggregation in rice [24]. The researchers used a CRISPR-Cas9-based genome editing strategy to generate new alleles in the cis-regulated regions of three major heading date genes, Hd1, Ghd7, and DTH8. By editing promoter regions and regulating the expression levels of these genes, a series of germplasm resources with quantitative variation at the heading stage were obtained. Field trials were conducted to screen the best strains suitable for different regions [25].

The purpose of this study was to use the CRISPR/Cas9 gene editing system to combine HST1 with LRRK1, STRK2, and PC1, respectively, to improve the ST of existing varieties through two-gene editing and evaluate the performances of ST and yield-related traits for different editing combinations in different variety backgrounds. The results will provide the valuable information of interaction effects of different gene combinations on ST and create excellent salt-tolerant materials for future rice breeding programs.

2. Materials and Methods

2.1. Generation of hst1-lrrk1, hst1-strk2 and hst1-pc1

The Cas9 plant expression vector (pYLCRISPR/Cas9Pubi-H) and the sgRNA expression vector (pYLgRNA) were provided by Prof. Yao-Guang Liu of the South China Agricultural University, Guangzhou, China. In order to measure the salt tolerance of pyramid genes under different subgroups and different varieties of the same subgroup, three xian cultivars (including Changhui 70 (CH70), 8TX23, and Chun 199S (C199S)) and three geng cultivars (including Zhongnonggeng 11 (ZNG11), Huhan 6220 (HH6220), and Haidao 6 (HD6)) with different levels of salt tolerance as parents in breeding were selected for experiments in this study. Embryogenic calluses of these cultivars were used for Agrobacterium-mediated transformation with CRISPR vectors targeting hst1, lrrk1, strk2, and pc1.

2.2. Identification of Mutant Transgenic Plants

Four pairs of specific primers, including HST1, LRRK1, STRK2, and PC1, were designed for the editing target sites of the four salt-tolerance-related genes, including HST1, LRRK1, STRK2, and PC1, respectively (

Table 1. Primers used in this study.

Primer Name	Primer Sequence (5′-3′)	Purpose
HST1-F	AGGTGCTTCAGTTTCAGTTGC	Target site sequencing
HST1-R	GTGCACCATAGTAGGCATATT	Target site sequencing
LRRK1-F	AAGCTGCGAGGCTGTTCTCCGC	Target site sequencing
LRRK1-R	GTTCCAAAACTAAACCAAGATT	Target site sequencing
STRK2-F	TGAAGGGGTTCAGGAAGTAGAG	Target site sequencing
STRK2-R	CTGGGATTGCTCCAGTTAATTT	Target site sequencing
PC1-F	GAGAACATGGACTGGGTGC	Target site sequencing
PC1-R	AAGCCGAGACGGACAAGA	Target site sequencing
HPT-F	GAGCATATACGCCCGGAGTC	Transgenic analysis
HPT-R	CAAGACCTGCCTGAAACCGA	Transgenic analysis

). Sequencing for the samples was performed after PCR amplification. PCR amplification system: The 20 µL reaction system selected for molecular marker amplification included 2 × Taq PCR MasterMix 10 μL (Vazyme), 1.0 µL (10 µM) of each forward and reverse primer, ddH₂O 6.5 μL, and 1.5 µL DNA template (50 ng/µL). The amplification process was as follows: (1) predenaturation at 98 °C for 5 min, (2) denaturation at 98 °C for 30 s, (3) denaturation at 55 °C for 30 s, (4) extension at 72 °C for 40 s with 35 cycles in total, and (5) extension at 72 °C for 5 min. From T₀ to T₃, all types of homozygous mutants were selected, and the mutants causing protein changes were used to measure the salt tolerance. Finally, we selected 1–2 homozygous lines of two-gene pyramiding lines, including hst1-lrrk1 (h-l), hst1-strk2 (h-s), and hst1-pc1 (h-p), representing the entire population for the salt tolerance study of each type of pyramid gene.

To identify T-DNA-free plants from homozygous lines, the plants were analyzed via PCR using the HPT-specific primer HPT (Table 1) in combination with agarose gel electrophoresis. The pYLCRISPR/Cas9 Pubi-H plasmids were selected as positive controls. And the HPT- plants were considered as T-DNA-free plants.

2.3. Identification and Evaluation of Salt Tolerance (ST) for Mutant Plants

To evaluate the ST of plants at the seedling stage, seedlings were placed in an artificial climate box to grow. A total of 100 seeds of each accession were placed in an oven at 50 °C for 3 days to break dormancy, then disinfected with 3% NaClO for 30 min and washed three times with sterile water. Next, the seeds were soaked in water for 36 h and germinated for 12 h. For each accession, 16 uniformly germinated seeds were sown in a 96-well plate with holes at the bottom per replicate, and all the accessions were arranged in a randomized block design with three replicates. Then, the seeds were floated in a plastic box containing tap water and cultured in an artificial climate chamber with controlled conditions with 70% relative humidity and a photoperiod of 13 h of light at 28 °C and 11 h of darkness at 25 °C. After 7 days, the seeds were transferred to Yoshida solution (pH 5.8–6.0) [26]. Three-leaf stage seedlings were treated with 140 mM NaCl solution (pH = 7), and the nutrient solution was changed every 5 days [27]. The survival rates (SR) and survival days (SD) were used to evaluate the ST of the accessions used in this study. The survival days were calculated every two days, and the average survival days were used to evaluate ST. Based on the different ST of the materials, the SRs of geng varieties ZNG11, HH6220, and HD6 were calculated after 9 and 17 days under salt stress, respectively. While for xian varieties CH70, 8TX23, and C199S, the survival rates were calculated on the 15th and 21st days after salt stress, respectively.

2.4. Investigation of Yield-Related Traits

We selected the two-gene pyramiding lines without transgenic vectors and their wildtypes to measure the yield-related traits. These accessions were grown in Beijing (40.2° N, 116.2° E), China, from May 2024 to October 2024. In the field, 200 kg N ha⁻¹ in the form of urea was applied (50% used as basal, 30% applied 7 days after transplanting, and the remaining 20% applied at the panicle initiation). Phosphorus (90 kg ha⁻¹ of P₂O₅ in the form of calcium superphosphate) and potassium (90 kg ha⁻¹ of K₂O in the form of potassium chloride) fertilizers were applied as basal before transplanting. The paddy soil field for the experiment had a pH of 6, organic matter of 10.9 g kg⁻¹, available N of 41.7 mg kg⁻¹, available P of 116.5 mg kg⁻¹, and available K of 98.8 mg kg⁻¹. The field was irrigated after transplanting with a depth of 3–5 cm until the tillering stage, drained at the maximum tillering stage to control unproductive tillers, and irrigated again at the booting stage with the water layer of 3–5 cm until the heading stage, then wetting–drying alternation irrigation was performed during the grain-filling duration, and finally, it was drained a week before maturity. Weeds, pests, and diseases were controlled by a combination of chemical and manual methods, and there were no potential environmental pressures such as pests and diseases in the field after following regular field management of weeds, pests and diseases. Each accession was planted in five rows with eight individuals in each row at a spacing of 25 cm between rows and 17 cm between plants for three replications. Whole plots were harvested at maturity for grain yield measurement based on a 14% moisture content after air-drying, and we calculated the grain yield per plant (GY). Fifteen uniform plants in the middle rows were sampled and dried in an oven at 50 °C for 5 days for yield-related traits investigation, including effective panicle number (EPN), grain number per panicle (GNP), seed setting rate (SSR), and thousand grains weight (TGW).

2.5. Data Analysis

Microsoft 365 (v16.0.17328.20000, https://www.microsoft.com/excel; accessed on 31 January 2024), IBM SPSS Statistics 29.0 (https://www.ibm.com/spss; accessed on 6 October 2023), SnapGene 6.3.2 (https://www.snapgene.com; accessed on 10 January 2023) and GraphPad Prism 10 (https://www.graphpad.com/; accessed on 12 July 2023) were used to analyze all data. Differences in the phenotypic values between the accessions were examined by a one-way ANOVA or Student’s t-test. Duncan’s multiple range test was conducted to determine the significance of any differences (p < 0.05). Student’s t-test (two-tailed) was used to determine exact p-values.

3. Results

3.1. ST of Wildtype

To evaluate ST of the three geng accessions (ZNG11, HH6220, and HD6) and three xian accessions (CH70, 8TX23, and C199S) at the seedling stage, we measured two traits including SR and SD under salt stress (Figure 1). After 9 days of salt stress, the SR of the three geng varieties showed obvious differences. Among them, the survival rates of HD6 (85.42%) and ZNG11 (8.33%) were the highest and lowest, respectively (Figure 1a). With the increase of salt stress time, the survival rate of ZNG11, HH6220 and HD6 decreased significantly, and nearly all ZNG11 died after 17 days of salt stress (Figure 1a). The survival rates of the three xian varieties showed significant differences until 15 days after salt stress. And the survival rate of C199S (81.25%) was significantly higher than CH70 (16.67%) and 8TX23 (14.58%) (Figure 1b). With the increase of salt stress time, the survival rate of CH70, 8TX23 and C199S decreased significantly, and nearly all of CH70 and 8TX23 died after 21 days of salt stress (Figure 1a). The average survival days of xian accession C199S (17.73 days) was the highest, and that of geng accession ZNG11 (6.83 days) was the lowest among the six materials used in this study (Figure 1c).

3.2. Acquisition of Transgenic Seedlings and Identification of Homozygotes

To evaluate the ST of different gene pyramiding lines, we selected different homozygous gene pyramiding lines from the mutants created by the CRISPR/Cas9 system. And then, 2 homozygous lines (1 line only for a few mutants) were selected for each gene-pyramiding material by sequencing and analysis of the editing sites of the 4 target genes (Figure 2).

3.3. ST of Gene Mutant Lines

To evaluate the ST phenotype of the line with the hst1-lrrk1 (h-l), hst1-strk2 (h-s), and hst1-pc1 (h-p) in different backgrounds, the ST-related traits, including SR and SD of xian and geng accessions, were measured (Figure 3 and Figure 4).

After salt stress for 15 days, the SRs of different gene pyramiding lines under the three xian backgrounds (CH70, 8TX23, and C199S) were all significantly higher than that of the wildtypes (Figure 3a–c). Under the background of CH70, the SR of hst1 (h) was significantly higher than wildtype CH70, while it was significantly lower than the five two-gene pyramiding lines, including h-l, h-s-1, h-s-2, h-p-1, and h-p-2 (Figure 3a). Among the two-gene pyramiding lines, the SR of h-p was the lowest under the background of CH70 and 8TX23 (Figure 3a,b). While there were no differences in SR among h-l, h-s, and h-p under the C199S background (Figure 3c).

To further evaluate the difference in ST among different two-gene pyramiding lines under the C199S background, these materials were continuously subjected to salt stress for 21 days (Figure 3d–f). By this time, almost all of CH70’s and 8TX23’s plants had died (Figure 3d,e). Under the C199S background, the SRs of h-l, h-s, and h-p were all significantly higher than wildtype C199S, which were consistent with those of 15 days on salt stress (Figure 3f). The SR of h-s and h-p was the highest and lowest, respectively, which were consistent with those of 15 days on salt stress under the 8TX23 background (Figure 3b,f).

Further, we evaluated the ST of the materials by the average survival days (SD), and the SRs of the h-l, h-s-1, h-s-2, h-p-1, and h-p-2 were all significantly higher than wildtypes (Figure 3g–i). Under the CH70 background, hst1 was significantly higher than wildtype CH70, while it was significantly lower than the five two-gene pyramiding lines, including h-l, h-s-1, h-s-2, h-p-1, and h-p-2, suggesting that pyramiding multiple ST genes could further improve the ST of rice (Figure 3g). The SD of h-s was significantly higher than h-l and h-p, both under 8TX23 and C199S backgrounds (Figure 3h,i).

We further evaluated the effect of different gene aggregations on the ST of rice at the seedling stage under the geng background, including ZNG11, HH6220, and HD6 (Figure 4). The survival rates of different two-gene pyramiding lines under the three geng backgrounds were all significantly higher than that of the wildtypes after salt stress for 9 and 17 days (Figure 4a–f). Under the background of ZNG11, the survival rate of lrrk1 (l) was significantly higher than wildtype ZNG11, while it was significantly lower than the two-gene pyramiding lines, including h-l-1 and h-l-2 (Figure 4a). And under the background of HH6220, the survival rate of hst1 (h) was significantly higher than wildtype HH6220, while it was significantly lower than the two-gene pyramiding lines including h-l-1, h-l-2, h-s-1, h-s-2, h-p-1, and h-p-2 (Figure 4b). Among the two-gene pyramiding lines, the SRs of h-s-1 and h-s-2 were higher than h-l-1 and h-l-2 under the background of ZNG11 (Figure 4a), while there were no differences in SR among h-l, h-s, and h-p under HH6220 and HD6 backgrounds (Figure 4b,c).

To further distinguish the difference in ST among different two-gene pyramiding lines under HH6220 and HD6 backgrounds, SR was evaluated when these materials were subjected to salt stress for 17 days (Figure 4d–f). By this time almost all of ZNG11’s plants had died (Figure 4d). Under the HH6220 background, the survival rate of hst1 (h) was significantly higher than wildtype HH6220, while it was significantly lower than the two-gene pyramiding lines including h-l-1, h-l-2, h-s-1, h-s-2, h-p-1, and h-p-2 (Figure 4e), which were consistent with those of 9 days on salt stress (Figure 4b). The SRs of h-l, h-s, and h-p were all significantly higher than wildtype, and the h-s-1 was the highest both under HH6220 and HD6 backgrounds (Figure 4e,f).

Further, we evaluated the ST of the materials by the average survival days (SD), and the SRs of the h-l-1, h-l-2, h-s-1, h-s-2, h-p-1, and h-p-2 were all significantly higher than wildtypes (Figure 4g–i). Under the ZNG11 background, lrrk1 was significantly higher than wildtype, while it was significantly lower than the h-l-1 and h-l-2 (Figure 4g). Under HH6220 background, hst1 was significantly higher than wildtype, while it was significantly lower than the six two-gene pyramiding lines, including h-l-1, h-l-2, h-s-1, h-s-2, h-p-1, and h-p-2 (Figure 4h). These results suggested that pyramiding multiple ST genes could further improve the ST of rice. The SD of h-s-1 was the highest under all of the ZNG11, HH6220, and HD6 backgrounds (Figure 4h,i).

3.4. Identification of Transgenic Vector

In order to evaluate their agronomic traits and apply the superior gene pyramiding lines to rice breeding, T-DNA detections were carried out on the selected lines in the T₃ generation. And the T-DNA-free plants were chosen in the editing combination of all the two-gene pyramiding lines under the three xian backgrounds except for h-p-2 under the 8TX23 background (Figure 5b). The T-DNA-free plants were chosen in the editing combinations of h-l-1, h-s-1, and h-p-1 under both ZNG11 and HD6 backgrounds (Figure 5a). While under the HH6220 background, the T-DNA-free plants were only detected in h-l-1, h-p-1, and h-p-2 (Figure 5a), indicating that no T-DNA-free plants were detected in the two-gene pyramiding lines of h-s under the HH6220 background.

3.5. Morphological Features and Agronomic Traits of the Transgenic Plants

We selected the two-gene pyramiding lines without transgenic vectors and their wildtypes to measure the yield-related traits. Then the h-l-1, h-s-1, and h-p-1 under the three geng varieties (ZNG11, HH6220, and HD6) and two xian varieties (CH70 and 8TX23) and their wildtypes were grown in Beijing (40.2° N, 116.2° E), China, from May 2024 to October 2024 (Figure 6).

Under the geng variety ZNG11 background, there were no significant differences in effective panicle number (EPN) and grain number per panicle (GNP) of h-l-1, h-s-1 and h-p-1 compared with the wildtype ZNG11 (

Table 2. Performance of agronomic traits for h-l-1, h-s-1, and h-p-1 under geng varieties backgrounds.

Lines	Effective Panicle Number	Grain Number Per Panicle	Seed Setting Rate (%)	1000-Grain Weight (g)	Grain Yield Per Plant (g)
ZNG11	10.17 ± 1.47 a	130.92 ± 11.20 a	91.22 ± 1.05 a	21.58 ± 0.38 b	27.21 ± 1.69 a
ZNG11_h-l-1	9.33 ± 1.67 a	127.92 ± 7.18 a	87.83 ± 2.73 b	21.08 ± 0.4 c	22.71 ± 2.04 b
ZNG11_h-s-1	9.25 ± 1.28 a	140.39 ± 12.87 a	83.91 ± 2.48c	21.91 ± 0.45 b	21.8 ± 2.41 b
ZNG11_h-p-1	9.67 ± 1.63 a	129.89 ± 18.42 a	83.79 ± 2.52 c	22.91 ± 0.6 a	23.22 ± 1.89 b
HH6220	16.88 ± 1.55 ab	55.34 ± 3.89 a	89.97 ± 4.88 a	23.9 ± 0.55 a	19.06 ± 2.83 a
HH6220_h-l-1	15.75 ± 1.58 b	46.31 ± 3.51 b	77.64 ± 5.56 c	21.37 ± 1.09 c	11.54 ± 2.02 c
HH6220_h-s-1	17.5 ± 2.07 ab	44.96 ± 8.15 b	82.32 ± 4.05 b	22.83 ± 0.61 b	15.98 ± 2.74 b
HH6220_h-p-1	17.8 ± 0.84 a	42.49 ± 4.83 b	85.73 ± 2.44 b	23.81 ± 0.87 a	18.03 ± 2.18 ab
HD6	10.9 ± 1.79 ab	143.1 ± 19.84 a	93.81 ± 1.4 a	24.64 ± 0.61 a	36.39 ± 4.13 a
HD6_h-l-1	9.71 ± 0.76 b	141.56 ± 12.87 a	87.8 ± 1.9 b	24.79 ± 0.66 a	26.7 ± 5.93 b
HD6_h-s-1	11.75 ± 1.49 a	135.41 ± 7.72 a	76.1 ± 2.58 c	23.39 ± 0.5 b	28.08 ± 4.42 b
HD6_h-p-1	10.86 ± 2.04 ab	135.04 ± 9.13 a	86.12 ± 3.95 b	24.58 ± 0.65 a	30.27 ± 5.93 b

All data were based on mean values ± standard deviation. Different letters indicated significance difference at 0.05 level by Duncan’s multiple range test for multiple comparisons.

). The seed setting rate (SSR) in h-l-1, h-s-1 and h-p-1 were all significantly lower than that in wildtype ZNG11. Interestingly, compared with wildtype ZNG11, the 1000-grain weight (TGW) of h-p-1 increased significantly (+6.16%), while the 1000-grain weight of h-l-1 decreased significantly (-2.32%), and there was no significant difference in h-s-1. Finally, the grain yield per plant (GY) of h-l-1, h-s-1, and h-p-1 was significantly reduced by 16.54%, 19.88%, and 14.66%, respectively (Table 2).

There were no significant differences in EPN between the wildtype and h-l-1, h-s-1 and h-p-1 under the HH6220 background (Table 2). The yield-related traits of GNP, SSR and TGW in h-l-1 (h-s-1) were significantly decreased by 16.32% (18.76%), 13.70% (8.0%), and 10.59% (4.48%), respectively, resulting in a significantly decreased GY of 39.45%/16.16% compared to wildtype HH6220. Compared with the wildtype HH6220, although the GNP and SSR in h-p-1 were significantly reduced by 23.22% and 4.71%, respectively, the GY did not decrease significantly due to a slight increase in EPN (+5.40%) (Table 2).

Under the xian variety CH70 background, there were no significant differences in EPN and GNP of h-l-1, h-s-1, and h-p-1 compared with wildtype CH70 (

Table 3. Performance of agronomic traits for h-l-1, h-s-1, and h-p-1 under xian varieties backgrounds.

Lines	Effective Panicle Number	Grain Number Per Panicle	Seed Setting Rate (%)	1000-Grain Weight (g)	Grain Yield Per Plant (g)
CH70	7.25 ± 0.96 a	194.05 ± 15.33 a	86.69 ± 6.57 a	18.04 ± 0.43 b	20.01 ± 2.28 a
CH70_h-l-1	7.29 ± 1.8 a	180.33 ± 18.86 a	75.94 ± 3.04 c	17.76 ± 0.37 b	17.00 ± 4.51 a
CH70_h-s-1	7.50 ± 1.05 a	177.13 ± 38.36 a	77.71 ± 2.69 bc	17.05 ± 0.39 c	16.79 ± 2.66 a
CH70_h-p-1	6.80 ± 0.84 a	195.19 ± 20.4 a	81.81 ± 4.91 b	19.50 ± 0.33 a	20.60 ± 4.63 a
8TX23	8.50 ± 1.29 a	157.17 ± 13.9 a	87.87 ± 3.17 a	15.75 ± 0.45 b	16.85 ± 3.16 a
8TX23_h-l-1	8.0 ± 1.15 a	128.79 ± 19.13 b	80.75 ± 5.80 b	15.40 ± 0.63 bc	12.05 ± 3.15 b
8TX23_h-s-1	8.57 ± 1.40 a	132.56 ± 16.49 b	86.28 ± 2.11 ab	15.04 ± 0.21 c	13.83 ± 2.26 ab
8TX23_h-p-1	8.33 ± 1.21 a	149.83 ± 16.56 ab	82.30 ± 6.83 ab	17.35 ± 0.25 a	16.23 ± 3.17 ab

All data were based on mean values ± standard deviation. Different letters indicated significance difference at 0.05 level by Duncan’s multiple range test for multiple comparisons.

). The SSR in h-l-1, h-s-1, and h-p-1 were all significantly lower than that in wildtype CH70. Interestingly, compared with wildtype CH70, the TGW of h-p-1 increased significantly (+8.10%), while the TGW of h-s-1 decreased significantly (-5.49%), and there was no significant difference in h-l-1. Finally, although the GY of h-l-1, h-s-1 and h-p-1 all did not change significantly, the GY of h-l-1 and h-s-1 had a slight reduction of 15.04% and 16.09%, respectively (Table 3).

There were no significant differences in EPN between the wildtype and h-l-1, h-s-1, and h-p-1 under the 8TX23 background (Table 3). The yield-related traits of GNP and SSR in h-l-1 were significantly decreased by 18.06% and 8.10%, respectively, resulting in a significantly decreased GY of 28.49% compared to wildtype 8TX23. Compared with the wildtype 8TX23, although the TGW in h-p-1 was significantly increased by 10.16%, the GY did not increase significantly due to a slight reduction in GNP (−4.67%) and SSR (−6.34%) (Table 3). In the h-s-1 line, the significant reduction in GNP (−15.66%) and TGW (−4.51%) resulted in a slight decrease in GY of 17.92%, but did not reach the significant level of 0.05 (Table 3).

4. Discussion

In this study, the three geng accessions (ZNG11, HH6220, and HD6) and three xian accessions (CH70, 8TX23, and C199S) were used as the recipient materials for salt-tolerant gene editing. These rice varieties had different ST (Figure 1). After 9 days of salt stress, the three geng varieties showed obvious differences in ST. With the increase in salt stress time, the survival rate of ZNG11, HH6220, and HD6 decreased significantly, and nearly all ZNG11 died after 17 days of salt stress (Figure 1a). For the three xian varieties, there were obvious differences when they were subjected to salt stress for 15 days, and nearly all CH70 and 8TX23 died until they were on salt stress for 21 days (Figure 1b). These results suggest that the ST of three xian accessions was higher than that of geng accessions. Oryza sativa are known to be genetically organized into two major groups (xian and geng) and several minor groups [28]. There were broader genetic variations of ST in different subspecies, and both specific genetic loci and broader genetic variations were important factors that made xian more tolerant to salt stress than geng [29,30]. Although most ST accessions previously identified were from xian, such as Pokkali (Sri Lanka) and Nona Bokra (India), it was very important to understand the relationships between varietal groups and phenotypic variation for ST, as it was particularly important to know where to mine for interesting alleles [31]. Although we selected three xian accessions and three geng accessions with different levels of ST in this study, limited genetic background might affect the generalizability of the results. Next, we will select more breeding varieties for gene editing and pyramid ST genes.

When we edited a single gene, HST1, in the xian variety CH70 and the geng variety HH6220, the ST of gene-edited lines were significantly improved. On the basis of hst1 mutant, we further edited LRRK1, STRK2, and PC1 to get two-gene pyramiding mutants for further evaluation of the ST. We found that the ST of two-gene pyramiding lines was much better than that of single-gene edited lines in all xian and geng variety backgrounds, indicating that the three genes lrrk1, strk2, and pc1 have positively synergetic ST effects with gene hst1. It was shown that the multi-gene pyramiding is an effective method to further improve the ST of rice, as indicated in the previous reports [32,33]. Although combinations of hst1-pc1, hst1-lrrk1, and hst1-strk2 could improve the ST of all the tested materials in both xian and geng backgrounds in this study, the combination of hst1-strk2 had much better ST than that of the other two combinations of hst1-lrrk1 and hst1-pc1. The combination of hst1-pc1 had the worst ST in CH70 and 8TX23 backgrounds but showed almost the same level of ST as the combinations of hst1-strk2 and hst1-lrrk1 in the C199S background for 17 days after salinization. And the hst1-lrrk1 showed the strongest ST in the CH70 background than in the other two combinations. The above observations clearly bring out the background effect on ST and its utilization in ST breeding. Therefore, to improve the ST of rice by gene-editing technology, we need to cautiously select a recipient variety, which is directly related to the success or failure of gene-editing breeding.

To evaluate the breeding value of different pyramiding genes, we selected the lines without transgenic vectors to be planted in normal conditions in Beijing in 2024 to measure their yield-related traits. There was a tradeoff between ST and yield of rice, and the salt stress could affect the normal growth of rice. Compared with the wildtypes, the grain yield per plant of all gene-edited materials was reduced, except for hst1-pc1-1 in the CH70 background. The two-gene pyramiding mutant hst1-strk2 had the strongest ST at the seedling stage and had the higher grain yield in normal conditions (Figure 3 and Figure 4), suggesting that it could balance the relationship between yield and ST better than hst1-lrrk1 and hst1-pc1. In the previous reports, salt stress produced the accumulation of osmotic substance proline and lipid peroxidation, which inhibits plant growth [34,35]. And it has been reported that rice plant growth, photosynthetic pigment, and enzyme activities are affected under salt stress [36]. So, the decrease in rice yield was the result of multiple yield-related traits. It took a lot of time to create the gene-pyramided lines, and we lacked the time to measure yield-related traits under salt stress up to now. Therefore, the performances of ST and yield of the three salt-tolerant gene-edited double-gene polymers still need to be further observed under salt stress conditions in different locations for at least two years.

Conventional backcross breeding is the primary method used to develop high-ST rice cultivars, but it requires a lot of time to transfer one or more genes into the cultivar to improve ST [37,38]. CRISPR/Cas9 is a new targeted gene-editing technology with high efficiency and high specificity. To date, CRISPR/Cas9 has been widely applied to the genetic improvement of major crops such as rice, maize, oilseed rape, and soybeans [22]. In China, the administration of gene-editing products is referred to as genetically modified organisms. Therefore, the release of gene-editing varieties must be approved by the Ministry of Agriculture and Rural Affairs of the People’s Republic of China prior to application in production. Fortunately, gene-editing rice varieties are more easily approved than transgenic rice varieties, owing to their non-involvement of exogenous genes. Given that a co-regulation mechanism has been discovered between rice ST and yield components such as grain length [39,40], plant growth [41], and flowering [42], gene editing for genes with co-regulation of rice yield-related traits and ST or implementing marker-assisted selection for these may be one of the effective strategies for improving ST of rice varieties in the future. In this study, we demonstrated that pyramiding of hst1-strk2 showed the strongest ST in all rice varieties except for Changhui 70 and had the higher grain yield among the two-gene edited lines in the xian and geng backgrounds under normal conditions. Therefore, after allele analysis of recipient variety at hst1 and strk2, we can enhance ST of high-yielding rice variety by simultaneously gene-editing against the two loci or pyramiding these two alleles with the other major ST genes such as Saltol [43] and qST1.1 [44] by marker-assisted section.

Finally, we acknowledged that not measuring yield-related traits under salt stress was a weakness of this study. Next, we will simultaneously evaluate the ST of all gene-edited lines both in the normal and the saline conditions to analyze pyramiding effects of the four negative regulating ST genes on ST and grain yield and its related traits.

5. Conclusions

Four genes (HST1, LRRK1, STRK2, and PC1), negatively regulating salt tolerance (ST), were edited by CRISPR-Cas9 technology in three xian varieties and three geng varieties backgrounds, and three two-gene edited combinations, including hst1-lrrk1, hst1-strk2, and hst1-pc1, were created. All combinations of hst1-pc1, hst1-lrrk1, and hst1-strk2 significantly improved the ST at the seedling stage better than a single gene on all the tested backgrounds. The combination of hst1-pc1 had the poorest ST in CH70 and 8TX23 backgrounds but showed almost the same level of ST as the combinations of hst1-strk2 and hst1-lrrk1 in the C199S background for 17 days after salinization, which clearly brought out the background effect on ST and its utilization in ST breeding. Almost all gene-edited lines except hst1-pc1 in the CH70 background showed significantly reduced grain yield per plant in normal conditions. The hst1-strk2 showed the highest level of ST and a relatively higher grain yield among all the lines; thus, it is feasible to enhance ST of high-yielding rice varieties by simultaneously gene-editing against the two loci or pyramiding these two alleles with the other major ST genes of rice.