Mapping QTLs provides insights in the inheritance mechanisms of the quantitative traits in plants and animals [11]. The mapping populations used for QTL analysis could be divided into permanent populations and temporary populations [11]. In the QTL analysis of salt tolerance in rice, the permanent populations included recombinant inbred lines (RILs) and introgression lines (ILs). RIL population–parent combinations included Kolajoha×Ranjit [12], Jiucaiqing× IR26 ^[13][14][13,14], Changbai10×Dongnong425 [15], Tesanai 2×CB, (Nona Bokra×Pokkali)×(IR4630-22-2-5-1-3×IR10167-129-3-4) [16], IR4630×IR15324 [17], Co39×Moroberekan [18], Milyang23×Gihobyeo ^[19][20][19,20], H359×Acc8558 [21], IR29×Pokkali B [22], Yiai1×Lishuinuo [23], CSR11×MI48 [24], CSR27×MI48 [25], and Dongxiang×NJ16 [7]. IL population–parent combinations included IR64×Tarom Molaii [26], Ilpumbyeo×Moroberekan [27], Minghui86×ZDZ057, Minghui86×Teqing Shuhui527×ZDZ057, Shuhui527×Teqing [28], Lemont×Teqing [29], Pokkali×IR29 ^[30][31][30,31], Teqing×Oryza rufipogon [32], Ce258×IR758 62 [33], Tarome-Molaei×Tiqing [34], Xiushui 09×IR2061 [35], IR64×Binam [36], and Nipponbare×Kasalath [37]. In addition, there are doubled haploid (DH) groups that include IR64×Aucena [38] and Zhaiyeqing 8×Jingxi 17 ^[39][40][39,40]. Some studies also used a set of chromosome segment substitution lines (CSSLs) to detect salt tolerance in seedlings [41]. Mapped salt-tolerant QTLs that have permanent populations could analyze phenotypic variation at multiple points over multiple years. In this way, the identified salt-tolerant QTLs are more stable and not affected by the environment, which was of benefit to map-based cloning and molecular breeding applications. However, most of the permanent populations in the studies were not used for salt tolerance analysis. There was a lack of highly salt-tolerant or salt-sensitive parental varieties. The salt tolerance difference between the parents was small, which was not conducive to the identification of major salt-tolerant sites. Only a few populations were constructed that had salt-tolerant varieties as their parents and used for salt tolerance research, such as Kolajoha×Ranjit [12], Jiucaiqing×IR26 ^[13][14][13,14], (Nona Bokra×Pokkali)×(IR4630-22-2-5-1-3×IR10167-129-3-4) [16], IR29×Pokkali [22], CSR11×MI48 [24], and CSR27×MI48 [25].

Most of the salt-tolerant QTL mapping of rice has used temporary populations. Most of these populations were F₂ and F₃ populations, and a few were F₄, BC₁F₁, BC₁F_2:3, and BC₂F_2:3 populations. The parent populations included Gharib×Sepidroud ^[42][43][42,43], Nona Bokra×Koshihikari [44], Tarommahali×Khazar ^[45][46][45,46], Pokkali×Shaheen Basmati [47], BRRI Dhan40×IR61920-3B-22-2-1 [48], Dongnong425×Changbai10 ^[15][49][15,49], Jiucaiqing×IR36 [50], Sadri×FL478 [51], NERICA-L-19×Hasawi, Sahel 108×Hasawi, and BG90-2×Hasawi [52], IR36×Pokkali ^[53][54][53,54], CSR27×MI48 [55], Cheriviruppu×Pusa Basmati1 [56], and Peta×Pokkali [57]. These populations were used for QTL analysis of salt-tolerant materials such as Gharib, Nona Bokra, Tarommahali, Pokkali, Jiucaiqing, FL478, Hasawi, IR61920-3B-22-2-1, Cheriviruppu, Changbai10, and CSR27 ^{[42][43][44][45][46][47][48][49][50][51][52][55][56]}[42,43,44,45,46,47,48,49,50,51,52,55,56].

Some studies used two or more populations simultaneously for salt tolerance QTL analysis. Tiwari et al. [24] identified the salt-tolerant QTLs that had two RIL populations CSR11×MI48 and CSR27×MI48; Cheng et al. and Yang et al. ^[29][35][29,35] used the two-way combination of Xiushui09×IR2061 and Lemont×Teqing; Qian et al. [28] selected Shuhui 527×ZDZ057, Minghui 86×ZDZ057, Shuhui 527×teqing, and Minghui 86×teqing for salt tolerance QTL analysis; Sun et al. [49] used F₃ and BC₁F_2:3 populations of Dongnong 425×Changbai 10 to analyze the dynamic QTL that controls the ion content in rice roots; Bimpong et al. [52] used F₂ populations of NERICA-L-19×Hasawi, Sahel 108×Hasawi and BG90-2×Hasawi to identify QTLs for salt tolerance in Hasawi. QTL analysis and comparison with multiple mapped populations were conducive to finding salt-tolerant sites that could be stably expressed and less affected by genetic background.

2.2. Period and Method of Salt Tolerance Identification

Rice has different tolerances to salt stress at different growth stages [7]. The seedling stage and the reproductive growth stage are salt-sensitive, while the seed germination stage and the vegetative growth stage are more salt-tolerant [7]. Therefore, most of the studies of salt tolerance QTL analysis in rice have been conducted during the seedling and reproductive growth stages [58].

More than half of the QTL studies on rice salt tolerance have used the seedling stage. The methods used for the identification of salt tolerance at the seedling stage were uniform. Rice seedlings were cultivated by hydroponics, and treated with salt at, or near, the three-leaf stage ^{[13][14][16][17][19][20][21][22][23][26][28][29][30][34][35][36][40][43][44][45][46]}[13,14,16,17,19,20,21,22,23,26,28,29,30,34,35,36,40,43,44,45,46]. For the reproductive growth stage, most rice studies used plants in artificial salt ponds. A small number of studies used rice planted in soil and treated with salt water ^{[24][25][40][51][52][53][54][55][56]}[24,25,40,51,52,53,54,55,56]. The initial and final salt treatments were different in different studies. Most of the studies transplanted rice to salt ponds in the seedling or tillering stage, where they were grown to maturity. The plants were then scored for agronomic traits and physiological indicators of salt tolerance ^{[24][25][40][51][52][53][54][57]}[24,25,40,51,52,53,54,57]. A few studies analyzed salt tolerance QTL in the seed germination stage, and conducted the germination in a medium with salt as a treatment ^[13][38][42][13,38,42].

Some studies simultaneously analyzed salt tolerance QTL in two or more growth and development stages. Gu et al. and Pandit et al. ^[25][57][25,57] identified the salt tolerance QTL in the vegetative and reproductive growth stages of rice; Zang et al. [36] identified tolerance in the seedling stage and vegetative growth stage; Ammar et al. [55] analyzed salt tolerance QTLs in seedling, vegetative growth, and reproductive growth stages. These studies helped to identify the genes that control salt tolerance in multiple growth and development stages of rice.

To analyze the influence of plant developmental differences on salt tolerance, some studies used a control group. They analyzed the salt tolerance of the mapping population under the salt and the control treatments at the same time ^{[13][14][24][27][28][36][37][38][40][49][52][53][54][57]}[13,14,24,27,28,36,37,38,40,49,52,53,54,57]. Most of the studies used permanent populations that are homozygous for each strain. A few studies used different tillers from F₂ populations for different treatments.

2.3. Salt Tolerance Evaluation Parameter

The salt tolerance of rice is a complex and comprehensive trait that has various evaluations that differ between development stages. In QTL analysis of rice salt tolerance, the evaluation parameters at the seedling stage can be divided into three categories: morphological, growth and physiological. Morphological parameter analysis evaluates the salt tolerance of the seedlings (score of salt tolerance, SST) by observing the blade tips, leaves, tillers, and the growth inhibition and death of plants after salt stress, and also investigating the survival days of seedling (SDS) after salt stress ^{[14][15][18][19][20][22][23][26][27][28][29][30][33][35][36][43][44][46][47][48][55][59]}[14,15,18,19,20,22,23,26,27,28,29,30,33,35,36,43,44,46,47,48,55,59]. Most studies have used the standard evaluation system (SES) proposed by the International Rice Research Institute (IRRI) to evaluate the salt damage level [60]. Some studies modified the evaluation criteria based on experimental materials and experimental design ^{[19][22][26][28][29][30][33][35][36][43][46][47][55][59]}[19,22,26,28,29,30,33,35,36,43,46,47,55,59]. The growth indicators used to evaluate the salt tolerance during the seedling stage include plant height and the fresh and dry weight of shoots and roots ^{[14][17][22][27][43][45][46][47]}[14,17,22,27,43,45,46,47]. There are many physiological parameters for evaluating the salt tolerance of rice, and the indicators for QTL analysis include plant ion content, the concentration of shoot Na⁺ (SNC) and K⁺ (SKC), shoot Na⁺/K⁺ ratio (SNKR), the concentrations of root Na⁺ (RNC) and K⁺ content (RKC), and root Na⁺/K⁺ ratio (RNKR) ^{[14][15][16][17][21][22][26][29][33][34][35][43][44][45][46][47][59]}[14,15,16,17,21,22,26,29,33,34,35,43,44,45,46,47,59]. Some studies also analyzed QTL with the chlorophyll content of seedlings after salt stress ^[22][43][45][22,43,45].

The evaluation parameters for the salt tolerance of rice seeds during germination include germination rate and germination vigor. Some studies further analyzed growth of the embryo and the radicle of seedlings after germination ^[13][38][42][13,38,42]. The evaluation parameters during the vegetative growth stage included plant growth and physiological indicators. Most studies analyzed the growth and ion content of the shoot rather than the root ^{[18][25][36][49][50][55][57]}[18,25,36,49,50,55,57]. The evaluation during reproductive growth included yield-related agronomic traits, such as the heading date, plant height, tiller number panicles per plant, grains per panicle, seed setting rate, 1000-seed weight, and yield per plant ^{[24][25][40][51][52][55][56][57]}[24,25,40,51,52,55,56,57]. Some studies analyzed the content of Na⁺, K⁺, Ca²⁺, and Cl⁻ in rice leaves or straw after salt treatment in the reproductive growth stage ^{[25][51][53][55]}[25,51,53,55]. Some studies included control groups, and they used the absolute value of each evaluation parameter for QTL analysis between the control and comparison groups. They also used the relative value of each salt tolerance trait (treatment/control) or decrease rate ((control–treatment)/control) as an indicator, which was beneficial in reducing the influence of individual plant differences ^{[24][27][49][53][54][57]}[24,27,49,53,54,57].

2.4. Salt Tolerance QTL

AuthorsWe found 52 salt tolerance QTL studies in rice, as shown in Table 1. More than half of the salt-tolerant QTLs were in the seedling stage. Salt-tolerant QTLs at each growth stage were distributed on the 12 rice chromosomes.

Table 1.

Identified QTL for salt tolerance in rice.

Stage	Parents for Cross	Population Type	Evaluation Parameter for Salt Tolerance	PVE%	QTL	High-PVE QTL	Reference
Germination stage	IR64×Azucena	DH	GR, seedling root length, seedling dry mass, seedling vigor	13.5–19.5	7	0	[38]
	Jiucaiqing×IR26	RIL	GR, RL, SH	6.5–43.7	7	4	[13]
	Gharib×Sepidroud	F2/F2:4	GR, germination percentage, radicle length, plumule length, coleoptile length, radicle fresh weight, plumule fresh weigh, radicle dry weight, plumule dry weight, coleoptile fresh weight, coleoptile dry weight	10.0–21.9	17	2	[42]
	9311×japonica	CSSL	Survival rate	5.1–93.2	4	-	[41]
Seedling stage	Dongnong425×Changbai10	BC2F2/BC2F2:3	SST, SNC, SKC, RNC, RKC	6.45–17.95	13	0	[63]
	O. rufipogon×O. Sative	ILs	SDS, STT	2–8	10	-	[64]
	(Nona Bokra×Pokkali)×(IR4630-22-2-5-1-3×IR10167-129-3-4)	RIL	SNC, SKC, SNKR	-	4	-	[16]
	IR4630×IR15324	RIL	SNC, SKC, SNKR, total Na+ and K+, SDW	6.4–19.6	11	0	[17]
	Milyang 23×Gihobyeo	RIL	SST	9.2–27.8	2	1	[19]
	Milyang 23×Gihobyeo	RIL	SST	9.1–27.8	2	1	[20]
	H359×Acc 8558	RIL	SNC	1.68–45.39	13	3	[21]
	IR29×Pokkali	RIL	SNC, SKC, RKC, RNKC, SH, chlorophyll content, seedling survival rate, initial and final SST	6–67	27	16	[22]
	Yiai1×Lishuinuo	RIL	Dead rate of leaf and seedling	8.65–27.20	6	1	[23]
	IR64×Tarom Molaii	IL	SST, SDS, SKC, SNC, RKC, RNC	-	23	-	[26]
	Ilpumbyeo×Moroberekan	IL	The reduction rate of fresh and dry weight, leaf area and SH	10.2–13.9	8	0	[27]
	Shuhui527×ZDZ057, Minghui86×Teqing, Minghui86×ZDZ057, Shuhui527×Teqing	IL	SST, SDS	8.17–42.18	43	12	[28]
	Lemont×Teqing	IL	SST, SDS, SKC, SNC	-	36	-	[29]
	Pokkali×IR29	IL	SST	4.00-18.42	6	0	[30]
	Ce258×IR75862, ZGX1×IR75862	IL	SST, SDS, SKC, SNC	5.13–13.75/3.73–8.26 *	18/2 *	0	[33]
	Tarome-Molaei×Tiqing	IL	SNC, SKC, SNKR, RNC, RKC, RNKR	9.0–30.0	14	5	[34]
	Xiushui 09×IR2061-520-6-9	IL	SST, SDS, SKC, SNC, SKNR	5.14–18.89/2.60–14.30 *	26/21 *	0	[35]
	Zaiyeqing8×Jingxi17	DH	SDS	10.2–38.4	10	2	[39]
	Nona Bokra×Koshihikari	F2/F3	SDS, SNC, SKC, RNC, RKC, Na+ and K+ in root, SDW	12.4–48.5	11	3	[44]
	Tarommahalli×Khazar	F2/F3	Survival rate, chlorophyll content, SH, RL, leaf area, the weight of stem and root, total Na+ and K+ in shoot, SNKR	9.03–38.22	32	14	[45]
	Tarommahali×Khazar	F2/F3	STR, DM, Na+ content, K+ content, Na+/K+	9.03–20.90	14	1	[46]
	Pokkali×Shaheen Basmati	F2/F3	SST, SH, SDW, SFW, SNC, SKC, SNKR, RNC, RKC, RNKR	4.89–10.55	22	0	[47]
	BRRI Dhan40×IR61920-3B-22-2-l	F2	SST	12.5–29.0	3	2	[48]
	Jiucaiqing×IR26	RIL	RNKR, SH, SDW, RDW	7.8–23.9/- *	15/5 *	2	[14]
	Jiucaiqing×IR26	RIL	RKC, SNC, SKC, SST	8.5–18.9/- *	13/9 *	0	[59]
	Tesanai 2×CB	RIL	SDS	1.5–11.6	4	0	[61]
	Tesanai 2×CB	RIL	SDS, SDW, RDW, SNC, SKC, SKNR	4.4–15.0	31	0	[62]
	Teqing×Oryza rufipogon	IL	SST, relative SDW, RDW and total plant dry weight	8–26	15	3	[32]
Vegetative growth stage	Co39×Moroberekan	RIL	Content of Na+ in shoot, SNKR, fresh weight of stem, moisture content of leaf	11.0–26.3	14	3	[18]
	Nipponbare×Kasalath	IL	SH, SDW, number of tillers	12–41	31	11	[37]
	Dongnong425×Changbai10	BC1F2/BC1F2:3, F2/F3	RNC, RKC, RNKR, relative RNC, relative RKC, relative RNKR	3.61–27.9	50	4	[49]
	CSR10×Taraori Basmati	F3	Relative growth rate, SNKR, visual salt-injury symptoms	25.6–31.3	14	-	[65]
	Jiucaiqing×IR26	F2	SST, SNKR, SDW	6.7–19.3	7	0	[50]
Reproductive growth stage	CSRll×MI48, CSR27×MI48	RIL	Sensitivity index of grain yield stress	-	55	-	[24]
	Zhaiyeqing 8×Jingxi 17	DH	Effective tiller number, thousand-grain weight, PH, heading date, number of grains per panicle	7.9–40.1	24	3	[40]
	Sadri×FL478	F2	Heading date, PH, length and number of panicles, dry weight of straw, number of fertile and sterile spikelets per plant, total number of spikelets per plant, yield per plant, spikelet fertility, thousand grain weight	4.2–30.0	37	1	[51]
	NERICA-L-19×Hasawi, Sahel108×Hasawi, BG90-2×Hasawi	F2	SST, PH, TN, heading date, panicle number per plant, panicle sterility rate, grain number per ear, thousand-grain weight, yield per plant	6.5–49.5	75	37	[52]
	IR36×Pokkali	F2	Content of Na+ and Ca2+, absorption rate of Ca2+, relative content of Na+, K+ and Ca2+, relative ion content, relative absorption rate of Na+, K+, Ca2+ and Na+/K+	7.69–26.33	14	3	[53]
	IR36×Pokkali	F2	PH, TN, number of effective tillers, panicle weight, panicle length, number of spikelets panicle, number of unfilled grains panicle, number of grains panicle, panicle fertility, days of 50% flowering, days to maturity, grain length, grain width, grain length–width ratio, grain yield, thousand-grain weight, straw yield, harvest index	11.52–81.56	6	1	[54]
	Cheriviruppu×Pusa Basmati 1	F2	PH, TN, panicle length, yield, biomass, pollen fertility, Na+ content in flag leaf, Na+/K+	3.8–48.7	24	5	[56]
	HHZ×Budda, HHZ×Gang46B	BC2F5	Grain weight, spikelet number, thousand-grain weight, seed fertility	4.7–90.6	22	1	[66]
	Sahel108×Hasawi, NERICA-L-19×Hasawi, BG90-2×Hasawi	F2	Days to flowering/heading, PH, TN, panicle sterility, grain yield, yield per plant, yield-component data for each plot, salt tolerance score	7.3–31.9	75	-	[52]
	Tarommahalli×Khazar	F2/F3	PH, TN, number of full grains, number of empty grains, length and number of panicle, biomass	8.76–26.83	12	3	[56]
Multiple growth stages	CSR27×MI48	RIL	Vegetative growth period: content of Na+ in stem, content of K+ and Cl− content in leaf	5.86–8.55	4	0	[25]
			Reproductive growth period: content of Na+, K+ in straw, Na+/K+ in straw, spikelet fertility stress sensitivity index	7.22–14.05	5	0
	IR64×Binam	IL	Seedling stage: SST, SDS, SKC, SNC	-	13	-	[36]
			Vegetative growth period: PH, panicle number, fresh weight	-	22	-
	CSR27×MI48	F2/F3	Seedling stage: SST	14.38	1	0	[55]
		F2	Vegetative growth period: Na+, Cl− content in leaf and stem, K+ content in stem, Na+/K+ in leaf and stem	11.13–55.72	17	15
		F2	Reproductive growth period: content of Na+, K+ and Cl− in leaf, Na+/K+ in leaf	26.26–52.63	7	7
	Peta×Pokkali	BC1F1	Vegetative growth stage: SST, SFW, SDW, Na+ content	-	4	-	[57]
			Reproductive growth stage: weight of stem and leaf, PH, TL, effective panicle, number, panicle weight, main panicle length, grain weight, seed setting rate	-	11	-

The phenotypic contribution rate of a single QTL ranged from 0.02% to 81.56%. A total of 167 QTLs had a contribution greater than 20% and these occupied 22.0% of the total QTLs (Table 1). Salt-tolerant QTLs that have a large contribution to the phenotype were found in the studies that follow. Thomson et al. [22] detected 16 salt-tolerant QTLs which explained more than 20% of the phenotypic variation in the seedling stage. Of these, five QTLs had a contribution exceeding 50%. Qian et al. [28] used four mapping populations and detected 43 QTLs that control SST or SDS in seedlings. The contributions of 12 QTLs were more than 20%. Sabouri et al. [45] identified 32 QTLs that control different growth and physiological indicators of salt tolerance in rice seedlings. Among them, 14 QTLs explained more than 20% of the phenotypic variation. Bimpong et al. [52] detected 75 salt tolerance QTLs in three mapping populations during the reproductive stage, of which about half of the QTLs (37) explained more than 20% of the phenotypic variation. Ammar et al. [55] detected 25 QTLs that had a contribution greater than 10% in the seedling, vegetative growth, or reproductive growth stage, and 22 QTLs among these had a contribution rate over 20%. In these studies, there were 101 salt-tolerant QTLs that had a phenotypic contribution rate exceeding 20%. There were only a few QTLs that had large effects in other studies, and 13 studies had no salt-tolerant QTLs that exceeded a 20% variation. ^{[5][15][17][25][27][30][33][38][47][50][59][61][62]}[5,15,17,25,27,30,33,38,47,50,59,61,62].

We constructed a framework genetic map using 70 QTLs with high PVE in the reports ^{[13][14][19][20][21][34][39][40][42][44][45][48][51]}[13,14,19,20,21,34,39,40,42,44,45,48,51] (Figure 1). Figure 1 showed that QTLs related to salt tolerance are distributed on 12 chromosomes, but less on chromosomes 11 and 12.

Figure 1. Genetic linkage map showing the location of QTLs for salt tolerance-related traits detected in reports.

2.5. Fine Mapping and Map-Based Cloning of QTLs for Salt Tolerance in Rice

Because many salt-tolerant rice QTLs have a low phenotypic contribution rate and are difficult to fine-map and clone, relevant research has progressed slowly. However, two QTLs located on the first chromosome, qSKC-1 and Saltol, are suitable for fine-mapping or map-based cloning.

qSKC-1 is a major QTL that controls the K⁺ content in the shoot. It was detected in the F₂ population that was constructed by the salt-tolerant variety Nona Bokra and the salt-sensitive variety Koshihikari, and it explained 40.1% of the total phenotypic variation [44]. Ren et al. ^[63][67] used the map-based cloning method, followed by fine-mapping of the BC₂F₂ population and high-precision linkage analysis of the BC₃F₂ population, and they restricted qSKC-1 within the 7.4 kb chromosome interval and isolated the qSKC-1 gene. This gene encoded an ion transporter (OsHKT1;5) of the HKT (high-affinity K⁺ transporter) family, which exists in the parenchyma cells of the xylem of rice roots and has the function of specifically transporting Na⁺. This transporter could transport Na⁺ out of the xylem, and transport Na⁺ from the phloem back to the root where it was excreted from the plant through the action of other Na⁺ transporters. This process reduced the Na⁺ content in the shoot, regulated the Na⁺/K⁺ balance in the shoots, and improved rice salt tolerance ^[64][68].

Gregorio ^[65][69] used AFLP markers to analyze the salt tolerance QTL of the F₈ recombinant inbred line population of the Pokkali/IR29 combination, and detected a major QTL on rice chromosome 1 that simultaneously controls the Na⁺, K⁺ content and Na⁺/K⁺ ratio in rice. This QTL was named Saltol. In the population, the LOD value of the Saltol site was greater than 14.5, and the phenotypic contribution rate was 64.3–80.2%. Subsequently, Bonilla et al. ^[66][70] used the same population to map Saltol to the chromosome between SSR markers RM23 and RM140, and they found that the contribution rates of Saltol sites to the Na⁺, K⁺ content and Na⁺/K⁺ ratio were 39.2%, 43.9%, and 43.2%, respectively. Niones and Thomson et al. ^[22][67][22,71] used the near-isogenic lines BC₃F₄ and BC₃F₅ with IR29 as the background and Pokkali as the donor to confirm the position of the Saltol locus. Since the positions of Saltol and qSKC-1 were nearby on the chromosome, and both were responsible for regulating the Na⁺/K⁺ balance of rice under salt stress, Thomson et al. [22] speculated that Saltol and qSKC-1 may encode the same gene (OsHKT1;5).

Some studies conducted fine mapping and cloning on salt-tolerant and salt-sensitive mutants. Lan et al. ^[68][72] fine-mapped the seedling salt-tolerant mutant gene SST to the 17 kb interval on chromosome 6, and the only predicted gene in this interval is OsSPL10, which might be a candidate gene for SST. Ogawa et al. ^[69][73] and Toda et al. ^[70][74] used the salt-sensitive mutants rss1 and rss3 to clone the salt-tolerant-related genes RSS1 and RSS3, respectively. RSS1 participated in the regulation of the cell cycle and was an important factor for maintaining the viability and vigor of meristematic cells under salt stress; RSS3 regulated the expression of the jasmonic acid-responsive gene, and was involved in maintaining root cell elongation at an appropriate rate under salt stress. Deng et al. ^[71][72][75,76] analyzed the salt-tolerant and salt-sensitive mutants rst1, rss2 and rss4. They detected two QTLs (qSNC-1 and qSNC-6) that control the Na⁺ content of aerial parts on chromosomes 1 and 6, which explained 14.5% and 53.3% of the phenotypic variation, respectively. The synergistic alleles were derived from rss2.