Soil salinity negatively impacts plant function, development, and yield. To overcome this impediment to agricultural productivity, variation in morphological and physiological response to salinity among genotypes of important crops should be explored. Sorghum bicolor is a staple crop that has adapted to a variety of environmental conditions and contains a significant amount of standing genetic diversity, making it an exemplary species to study variation in salinity tolerance.

Methods

Twenty-one diverse Sorghum accessions were treated with nonsaline water or 75 mM sodium chloride. Salinity tolerance was assessed via changes in biomass between control and salt-treated individuals. Accessions were first rank-ordered for salinity tolerance, and then individuals spanning a wide range of responses were analyzed for foliar proline and ion accumulation. Tolerance rankings were then overlaid on a neighbor-joining tree.

Results

We found that, while proline is often a good indicator of osmotic adjustment and is historically associated with increased salt tolerance in many species, proline accumulation in sorghum reflects a stress response injury rather than acclimation. When combining ion profiles with stress tolerance indices, the variation observed in tolerance was not a sole result of Na⁺ accumulation, but rather reflected accession-specific mechanisms.

Conclusions

We identified significant variation in salinity tolerance among Sorghum accessions that may be a result of the domestication history of Sorghum. When we compared our results with known phylogenetic relationships within sorghum, the most parsimonious explanation for our findings is that salinity tolerance was acquired early during domestication and subsequently lost in accessions growing in areas varying in soil salinity.

Soil salinity is a major constraint to agricultural crop productivity, limiting the provision of food, fuel, and fiber to large portions of the world's population (Munns and Tester, 2008; Qadir et al., 2014; Morton et al., 2019). Soil salinity, defined as concentrations of soluble salts above 40 mM sodium chloride (NaCl) or greater than 4 dS m^–1 electrical conductivity (Jamil et al., 2011; Shrivastava and Kumar, 2015), is a global problem affecting more than 20% of the irrigated land used for agriculture (Qadir et al., 2014). Salts increase in soils naturally through the rise and ingression of sea water (Abrol et al., 1988; Singh, 2015; Liu et al., 2017), weathering of soil parent material (Abrol et al., 1988), and high surface evaporation associated with low precipitation (Chhabra, 1996; Shrivastava and Kumar, 2015; Singh, 2015). Anthropogenic factors, such as irrigation with saline water, inadequate field drainage, and over-application of animal waste, also result in increased soluble salts in agricultural soils (Munns and Tester, 2008; Thomson et al., 2010; Singh, 2015; Lemanowicz and Bartkowiak, 2017).

Increased salinity negatively impacts plant function and development through both osmotic and ionic effects (Munns and Tester, 2008; Negrão et al., 2017). In the osmotic phase, salinity impedes plant water acquisition. Water uptake is disrupted even when soils contain adequate moisture due to lower soil water potential compared to plant osmotic potential. This imbalance inhibits water extraction by plant roots, simulating drought-like conditions (Munns and Tester, 2008; Negrão et al., 2017). In response to osmotic stress, leaf emergence and growth rate is reduced, stomata close resulting in decreased/inhibited photosynthesis, and leaf temperature increases (Munns and Tester, 2008; Alqahtani et al., 2019). In the ion-dependent phase, ions such as Na⁺ and Cl^– enter the plant, accumulate to toxic levels in the cytoplasm, and disrupt normal metabolic function (Munns and Tester, 2008).

Various plant responses result from both ion-independent and -dependent phases. Key growth responses to osmotic stress include decreased leaf and root growth due to lack of turgor (Munns, 2005). Leaf growth is affected to a greater extent than root growth, resulting in a decreased shoot to root ratio (Negrão et al., 2017). Toxic ions accumulate in leaves and affect ion homeostasis and photosynthesis, resulting in premature leaf senescence (Munns, 1993, 2002). As ions accumulate, Na⁺ specifically disrupts the uptake and distribution of K⁺, an essential ion for basic biological functions such as stomatal opening, enzymatic activity (Tari et al., 2013), or cellular metabolism (Zhu, 2003).

Sorghum bicolor (L.) Moench is an African grass that is cultivated for food, fuel, and fiber. There are five landraces of sorghum (bicolor, kafir, guinea, caudatum, and durra) that are classified based on morphology (Shehzad et al., 2009) and reflect the genetic diversity associated with different geographical regions of adaptation (Price et al., 2005; Morris et al., 2013; Mace et al., 2013; Mullet et al., 2014; Smith et al., 2019). There are also 10 intermediate landraces that are a combination of the five landraces (de Oliveira et al., 1996; Price et al., 2005). Worldwide, sorghum ranks fifth as a contributor to grain production and second as a biofuel feedstock (Wiersema and Dahlberg, 2007). Sorghum thrives in areas that are often not suitable for other crops and requires minimal human input while delivering high yields (Mullet et al., 2014). Given these traits, sorghum provides a model system for studying the complex basis of salt tolerance because it is relatively drought tolerant (Mullet et al., 2014; Fracasso et al., 2016; McCormick et al., 2018), and as with drought stress, salt stress results in osmotic imbalance (Munns and Tester, 2008).

Here, we evaluated the variation in whole-plant response to salt exposure in a diverse panel of sorghum accessions that are representative of a diversity of sorghum landraces and species. Specifically, we included a hybrid species, three wild progenitors, and a variety of cultivated landraces to evaluate the association between standing genotypic and phenotypic diversity and salinity tolerance. Because Sorghum bicolor was originally domesticated >8000 years ago in eastern Africa and has since adapted to a variety of geographical regions (Wendorf et al., 1992; Mace et al., 2013; Winchell et al., 2017; Smith et al., 2019), we hypothesized that variation in salt tolerance may be a result of post-domestication adaptation to areas varying in soil salinity. Therefore, we expected to observe landraces that adapted in regions with high soil salt content to have increased salinity tolerance compared to landraces that adapted in low soil salt content.

Materials and Methods

Plant material

Seeds for 21 diverse Sorghum accessions representative of the different landraces were obtained from the Germplasm Resources Information Network (GRIN; ars-grin.gov). Landrace information was provided by GRIN, and arbitrary codes were assigned and used to reference specific accessions throughout this study (Table 1).

Table 1. Summary of Sorghum accessions. Sorghum accessions and associated information (identification code used to reference accessions throughout the study and landrace). Accession information and landrace information was supplied by GRIN.

Accession	ID	Landrace	Sorghum Association Panel
PI33027204SD	D-1	drummondii
subsp. propinquum	P-1	subsp. propinquum
PI57112801SD	Sb-1	caudatum
PI53412801SD	Sb-2	durra	SAP-208
PI52569503SD	Sb-3	guinea-margaritiferum
PI57613001SD	Sb-4	kafir	SAP-65
PI53391004SD	Sb-5	caudatum	SAP-268
PI53383401SD	Sb-6	caudatum
PI53379202SD	Sb-7	caudatum	SAP-140
PI65606902SD	Sb-8	intermediate (unknown)
PI58643001SD	Sb-9	guinea-margaritiferum
PI58574902SD	Sb-10	durra
PI56512103SD	Sb-11	caudatum	SAP-80
PI53413301SD	Sb-12	durra	SAP-233
PI53375201SD	Sb-13	caudatum	SAP-127
PI65361702SD	Sb-14	intermediate (unknown)	SAP-73
PI61353602SD	Sb-15	durra-caudatum	SAP-74
PI56351602SD	Sb-16	durra-caudatum
PI60933601SD	Sb-17	intermediate (unknown)
PI65602902SD	Sb-18	durra	SAP-37
Tx7000	Tx-1	durra
PI22609603SD	V-1	subsp. verticilliflorum
PI30011903SD	V-2	subsp. verticilliflorum

Note

Tx-1 and Sb-6 were excluded from the study.

NaCl exposure

A pilot study, in which five randomly selected accessions were exposed to increasing salt concentrations, was used to determine an appropriate experimental treatment level. Replicates were treated with 0 mM, 25 mM, 75 mM, 125 mM, 150 mM, or 200 mM NaCl beginning at the third leaf stage of development and for 4 weeks. There was a clear reduction in growth and biomass as NaCl increased (Appendix S1). Because soil is considered to be saline at concentrations greater than 40 mM (Shrivastava and Kumar, 2015) and we observed growth reduction without mortality at 75 mM NaCl, we used 75 mM NaCl as our treatment.

Twenty seeds of each accession (10 replicates per treatment and a total of two treatments) were germinated in Metro-mix 360 (Sun Gro Horticulture, Agawam, MA, USA) in 5 × 5 × 5 cm planting plugs in a controlled greenhouse. Target germination conditions were 29°C day/24°C night, 60% humidity, and 14 h ambient daylight/day. During germination, all seedlings were misted regularly with nonsaline tap water and watered with a 20-10-20 N-P-K fertilizer (J.R. Peters, Allentown, PA, USA) diluted to 200 mg N L^–1 once a week. When 90% of the seedlings were at the third leaf stage of development, seedlings were transplanted into 5 × 5 × 25 cm tree pots (Stuewe and Sons, Tangent, OR, USA) filled with a 1:1 mix of #2 and #4 silica sand. Seedlings were watered with tap water for 1-week post-transplant to provide a period of establishment.

At the 4–6 leaf stage of development, and well before flowering, plants were watered to saturation daily with tap water (nonsaline water, control) or tap water containing 75 mM NaCl solution (treatment). Twice each week, all plants were additionally watered to saturation with the 20-10-20 N-P-K fertilizer at a rate of 200 mg N L^–1. Treatment was carried out for a total of 12 weeks.

Biomass measurements

At 12 weeks post-treatment, five of the 10 replicates were collected for biomass measurements. At harvest, plants were separated into roots and shoots. Roots were brushed free of adhering sand. The biomass of each plant was dried in five categories: roots, main stem, live leaves (>50% green), dead leaves (<50% green), and tillers (shoots from the base of the stem). All biomass samples were dried at 65°C for a minimum of 72 h.

Throughout this study, the following terms were used to describe specific tissues: live aboveground biomass was the sum of the live stem, live leaves, and live tillers. Dead aboveground biomass was the sum of the dead stem, dead leaves, and dead tillers. Total aboveground biomass was the sum of live and dead aboveground biomass. Percentage of live aboveground biomass was the ratio of live aboveground biomass by the total aboveground biomass as a fraction of 100.

Phenotypic measurements

The remaining five replicates were used for phenotypic measurements. The following variables were recorded after 12 weeks of treatment: total number of leaves, total number of live leaves, percentage live leaves (calculated from live leaves and total leaves), mortality (defined as 1 for alive and 0 for dead), and height (cm). Height was measured from the base of the main stem to the tip of the newest emerged leaf.

Physiological measurements

Physiological measurements were taken at 12 weeks post treatment on the third leaf from the top because it was the oldest living leaf across all plants. The same five replicates used for phenotypic measurements were used for quantifying chlorophyll content (SPAD 502 Plus Chlorophyll Meter, Konica Minolta, Osaka, Japan) and proline concentration. Leaf ion profiles were measured on the same five replicates used for biomass measurements. Proline and ion concentrations were quantified on a subset of accessions that showed variation in phenotypic responses.

Foliar sodium and potassium concentrations were determined for microwave-assisted acid digests (MARSXpress, CEM Corp., Matthews, NC, USA). Leaf tissue was dried for 72 h at 70°C, ground in a CyclotecTM 1093 sample mill (FOSS, Hilleroed, Denmark), and digested in 4 mL of 70% v/v HNO₃ and 1 mL of 30% v/v H₂O₂ (Carrilho et al., 2002). Digests were analyzed for elemental concentrations by inductively coupled plasma optical emission spectrometry (ICP-OES) by the Pennsylvania State University Analytical Laboratory (State College, PA, USA). Elemental yields were obtained using ground apple leaves from the National Institute of Standards and Technology and were used to calculate elemental content from the ICP-OES data.

Quantification of proline was determined colorimetrically by comparisons with standards. Following harvest, samples were flash frozen and immediately stored at −80°C. Tissue was ground to a fine powder, and 2 mL of 70% v/v ethanol was added to each sample. Samples were incubated at room temperature with continuous agitation for 24 h, then centrifuged at 16,000 × g for 10 s, and the supernatant was transferred to a new tube. The ground tissue was then re-suspended in 2 mL of fresh 70% ethanol for an additional 24 h at room temperature with agitation. After the second extraction, both 2 mL extracts were combined. Samples were then incubated at 95°C for 20 min with a 1% w/v ninhydrin and 60% v/v acetic acid reaction mix and quantified on a Tecan Infinite 200 PRO plate reader (Tecan, Grödig, Austria) at 520 nm.

Tolerance indices

Salinity tolerance in plants is often defined as the ability of a plant to sustain growth in the presence of salts (Munns, 2010). In our study, several traits were evaluated, and tolerance was defined by the ability to maintain biomass (live and total) when comparing salt exposure to control conditions.

Stress tolerance (ST)

The stress tolerance value was calculated for SPAD of the oldest living leaf across all plants, percentage of live leaves, height (cm), mortality, live aboveground biomass (dry mass in g), dead aboveground biomass (dry mass in g), and root biomass (dry mass in g) as (Negrão et al., 2017):

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where Y is a growth-related trait measured at the end of the experiment (T₂) under control and salt treatments as indicated. The ST value normalizes performance by accession.

Relative decrease in plant biomass (RDPB)

The sum of biomass for all tissues separated during a destructive harvest was used to determine the relative decrease in plant biomass (RDPB; Negrão et al., 2017) for each accession and landrace. The RDPB describes the reduction of growth in stressed conditions compared to control conditions. The RDPB is calculated as:

$urn:x-wiley:00029122:media:ajb21506:ajb21506-math-0002$

where M_f is plant mass under control and salt treatments as indicated. Lower RDPB values indicate less reduction in biomass under stress conditions and are representative of higher degrees of tolerance. RDPB was converted to percentage of plant biomass retained (1 − RDPB). Tolerant genotypes were individuals with high amounts of biomass retained, while sensitive individuals retained less biomass in response to treatment.

Stress tolerance index (STI)

The stress tolerance index (STI; Negrão et al., 2017) was calculated for biomass traits (live aboveground biomass, dead aboveground biomass, root biomass). The STI was calculated as:

$urn:x-wiley:00029122:media:ajb21506:ajb21506-math-0003$

where Y_control and Y_salt are measured traits for control and salt treatments for each accession, and Y_{control average} is the trait response under control conditions for the entire population evaluated. A greater STI for an accession indicates higher degrees of salt tolerance. The STI accounts for genotypic response to salinity stress and compares it to a population response to reveal accessions that are performing superior to others. Raw STI values for live aboveground biomass, dead aboveground biomass, and root biomass (Appendix S2) were converted to a rank order. STI was rank-ordered with 0 indicating missing data, 1 indicating the lowest STI, and 21 indicating the highest possible STI.

Statistical analyses

Treatment effects

Nonmetric multidimensional scaling (NMDS) (Julkowska et al., 2019), performed in R v. 3.6.0 (R Core Team, 2013), was used to evaluate plant response to salt exposure and to determine groupings among accessions across treatments. The dimcheckMDS function in the geoveg package generated the associated stress value with each reduction in dimension. A lower stress value indicates higher conformity between the true multivariate distance between samples and the distance between samples in reduced dimensions. Two dimensions were deemed appropriate. NMDS was paired with analysis of similarity (ANOSIM), which statistically tests clusters and ordination results from the NMDS. The ANOSIM determines whether the dissimilarity matrix used in the NMDS ordination is significantly different. Using an ANOSIM, we tested whether accessions were more similar within a treatment compared to among treatments. Dissimilarities were determined using a Bray–Curtis dissimilarity index.

Landrace and accession effects

To determine whether plant response to increased salt was a result of genetic mechanisms (accession response or landrace structure), a NMDS was coupled with ANOSIM. The Bray–Curtis dissimilarity coefficients for ST values were used in the NMDS to visualize patterns in the data. Two dimensions were specified. NMDS was paired with ANOSIM to statistically test clusters and ordination results. We tested whether individuals were more similar within an accession compared to among accessions; we tested whether individuals were more similar within a landrace compared to among landraces.

Treatment effects on growth

A one-way analysis of variance (ANOVA) was used to determine whether there was a statistical difference among accessions for live aboveground biomass STI values, dead aboveground biomass STI values, and root biomass STI values in response to salt exposure. An ANOVA was used to evaluate differences between landraces in response to salt exposure. When significant differences were found, a Tukey's honestly significant difference (HSD) was used to separate accession/landrace means.

In R v. 3.6.0 (R Core Team, 2013), Shapiro–Wilk tests were used to test population response normality, and Levene's test in the car package (Fox and Weisberg, 2019) was used to test homogeneity of variance. Response variables that did not pass a threshold of α = 0.05 in the Shapiro–Wilk tests were transformed before the ANOVA. For the accession ANOVA, STI values for live aboveground biomass, dead aboveground biomass, and root biomass were square-root-transformed. For the landrace ANOVA, STI values for live aboveground biomass and dead aboveground biomass were log-transformed; STI values for root biomass were square-root-transformed.

Treatment effects on sodium and potassium accumulation

To determine whether there was significant variation among treatments and accessions with respect to Na⁺ content, K⁺ content, and the potassium to sodium ratio (K⁺/Na⁺), a two-way ANOVA was performed in R v. 3.6.0 (R Core Team, 2013). When a significant difference was found (P < 0.05), Tukey's honestly significant difference (HSD) test was performed to determine which treatments and accessions were responsible for the significant difference.

Treatment effects on proline accumulation

To determine whether there was significant variation among treatments and accessions for proline accumulation, a two-way ANOVA was performed on proline values that were log-transformed using R v. 3.6.0 (R Core Team, 2013). When a significant difference was found (P < 0.05), Tukey's HSD was performed to determine which treatments and accessions were responsible for the significant difference.

Results

Treatment effects

Salt exposure reduced the live aboveground biomass, the root biomass, the shoot-to-root ratio, height, the percentage of live leaves, and the foliar SPAD across all accessions and landraces, while the dead aboveground biomass and mortality increased (Appendix S3). We observed a differential response to NaCl exposure among accessions indicating that variation in salt tolerance exists within our tested population.

Landrace and accession effects

Based on accession and landrace ST values calculated for the measured growth parameters, plants were more similar within an accession rather than across accessions, and within a landrace rather than across landraces (Fig. 1) when exposed to salt.

Details are in the caption following the image — **Figure 1**
Open in figure viewer PowerPoint

Nonmetric multidimensional scaling using Bray–Curtis dissimilarity coefficient to two-dimensionally visualize plant response to treatment. For the NaCl treatment, accessions were ordinated in two-dimensional space. The following measurements were analyzed for dissimilarity among individuals: SPAD, percentage of live leaves (live leaf count/total leaf count), height (cm), mortality, live aboveground biomass (dry mass in g), dead aboveground biomass (dry mass in g), and root biomass (dry mass in g). Shapes indicate the landrace grouping for each accession. The analysis of similarity revealed plants were more similar within a landrace than among landraces (R = 0.31, P < 0.001).

Relative decrease in plant biomass (RDPB)

The percentage of biomass retained in response to NaCl ranged from 98% to 3% across accessions (Fig. 2). Accessions with sustained growth included V-1 (subsp. verticilliflorum), Sb-18 (durra), Sb-7 (caudatum), Sb-9 (guinea-margaritiferum), Sb-10 (durra), and Sb-3 (guinea-margaritiferum). These six accessions retained >90% of live aboveground biomass when exposed to NaCl. The RDPB values within the NaCl treatment also varied among landraces (F_{8, 83} = 5.22, P < 0.001; Appendix S4).

Stress tolerance index (STI)

The STI values for live aboveground biomass, dead aboveground biomass, and root biomass differed among accessions (F_{20, 66} = 3.82, F_{17, 56} = 61.65, F_{20, 60} = 30.36, respectively, P < 0.001 for each). The STI values ranged from 0.01 to 1.51 for live aboveground biomass, 0.10 to 3.35 for dead aboveground biomass, and 0.05 to 1.97 for root biomass. Some accessions ranked high for all three traits, while others ranked high for only one or two of the traits. For example, P-1 ranked low for live aboveground biomass (1^st of 21) but ranked 17^th of 21 for root biomass (Fig. 3). The largest overall scores (additive rank score for live aboveground biomass, dead aboveground biomass, and root biomass) were observed for the accessions Sb-10, V-1, Sb-9, Sb-3, Sb-2, and Sb-12, indicating overall better performance compared to other accessions (Fig. 3).

When the STI values were compared among landraces, differences were observed for live aboveground biomass, dead aboveground biomass, and root biomass (F_{8, 83} = 38.93, F_{7, 72} = 4.68, F_{8, 71} = 32.87, respectively, P < 0.001 for each; Appendix S5). The STI values ranged from 0.01 to 1.28 for live aboveground biomass. Sorghum propinquum had the lowest STI for live aboveground biomass with a mean of 0.01, and landrace durra had the highest STI for live aboveground biomass with a mean of 1.28. The STI values ranged from 0.32 to 2.08 for dead aboveground biomass with the intermediate landraces displaying the least STI values and the landrace guinea-margaritiferum displaying the highest. The STI values ranged from 0.11 to 1.69 for root biomass. The landrace guinea-margaritiferum had the highest STI for root biomass (1.69), while most other landraces averaged about 0.2 to 0.5 (Appendix S2).

Sodium and potassium accumulation

A subset of accessions that varied in growth under salt treatment were evaluated for ion accumulation. Variation in Na⁺ content was found among treatment and accessions (F_{11, 87} = 3.04, P < 0.01). Foliar Na⁺ under control conditions was low but varied 35-fold across accessions (Table 2). When exposed to NaCl, Sb-3 and Sb-4 accumulated the least amount of Na⁺, while P-1 and V-2 accumulated the most (Table 2).

Table 2. Summary of ion profiles for the third leaf from the top in a subset of Sorghum accessions that varied in phenotypic responses to 75 mM NaCl. A two-way ANOVA was used to test for significant variation among treatments and accessions with respect to Na⁺ content, K⁺ content, and K⁺/Na⁺ content. Different letters after the SE represent significant differences among accessions (P < 0.05).

Accession	Mean (±SE)				Mean (±SE)				Mean (±SE)
	Na⁺ mg/g				K⁺ mg/g				K⁺/Na⁺
	Control		75 mM NaCl		Control		75 mM NaCl		Control		75 mM NaCl
P-1	0.13	(0.03)^bcdefg	2.58	(0.48)^gh	14.32	(1.54)^bcde	3.06	(1.08)^a	81.98	(25.47)^cdefg	0.67	(0.12)^a
Sb-1	0.02	(0.01)^abc	0.59	(0.16)^efgh	17.89	(1.27)^ef	18.18	(3.03)^ef	564.71	(122.52)^gh	23.72	(6.36)^bcde
Sb-3	0.19	(0.14)^abcde	0.15	(0.07)^abcde	9.45	(0.29)^b	14.52	(0.82)^cde	124.51	(46.12)^cdefg	142.67	(45.08)^defg
Sb-4	0.17	(0.10)^abcdef	0.22	(0.11)^bcdefg	13.05	(0.69)^bcde	17.11	(0.96)^def	147.21	(85.36)^cdefg	74.87	(20.78)^cdefg
Sb-7	0.03	(0.01)^abc	0.22	(0.08)^cdefg	22.54	(1.34)^f	22.84	(0.62)^f	806.73	(240.01)^gh	108.48	(41.20)^cdefg
Sb-8	0.04	(0.01)^abcd	0.92	(0.27)^efgh	17.06	(0.80)^def	18.85	(0.90)^ef	246.46	(41.32)^fgh	14.55	(4.68)^abcde
Sb-9	0.03	(0.01)^abc	0.51	(0.12)^efgh	10.93	(0.85)^bc	16.70	(0.81)^def	235.69	(30.71)^fgh	24.12	(4.75)^bcde
Sb-10	0.02	(0.01)^ab	0.60	(0.23)^defgh	10.28	(0.68)^bc	11.43	(0.92)^bcd	703.49	(466.73)^fgh	18.92	(5.44)^bcd
Sb-15	0.09	(0.07)^abc	1.95	(0.64)^gh	18.68	(0.81)^ef	19.34	(2.23)^ef	936.91	(475.01)^fgh	25.15	(20.61)^abc
Sb-16	0.01	(0.01)^a	0.13	(0.06)^abcde	17.86	(1.22)^ef	23.22	(1.07)^f	1569.94	(674.41)^h	351.98	(179.91)^efgh
Sb-17	0.35	(0.24)^bcdefgh	1.79	(0.74)^fgh	14.88	(0.91)^bcdef	18.28	(0.64)^def	94.21	(65.45)^cdefg	9.46	(4.46)^abc
V-2	0.32	(0.20)^bcdefg	3.47	(1.19)^h	11.28	(1.52)^bcd	12.28	(1.72)^bcde	56.12	(22.40)^cdef	2.80	(0.74)^ab
SEM	0.45				0.08				0.45
P _Accession	P < 0.001				P < 0.001				P < 0.001
P _Treatment	P < 0.001				P < 0.050				P < 0.001
P _Interaction	P < 0.001				P < 0.001				P < 0.001

As with Na⁺, foliar K⁺ concentrations also varied among accessions, and these differed in response to treatments (F_{11, 87} = 13.83, P < 0.001). For example, P-1 exhibited similar K⁺ content to the tested population mean under control conditions and then declined more than other accessions under NaCl exposure (79% decline), whereas K⁺ increased significantly in Sb-3 and Sb-9 under NaCl exposure (Table 2).

We found variation among treatments and accessions for the K⁺/Na⁺ ratio (F_{11, 87} = 4.44, P < 0.001). Under control conditions, V-2 had the lowest K⁺/Na⁺ ratio, and Sb-16 the greatest (Table 2). The ratio declined (49% to 99%) in many accessions under NaCl exposure, most notably in P-1 (99%) and Sb-15 (97%), while the ratio did not change in Sb-3.

Proline accumulation

In response to salt exposure, proline accumulation in sorghum foliage increased, with the magnitude of increase depending on the accession (F_{11, 87} = 4.44, P < 0.001; Fig. 4). Proline accumulation ranged from 0.07 to 0.26 g fw^–1 in the control treatment and 0.07 to 2.63 g fw^–1 in the salt treatment (Appendix S6).

Discussion

Phenotypic responses to salinity stress

Salinity tolerance is a product of maintenance mechanisms that occur during both the osmotic and ionic phases of salinity stress (Munns and Tester, 2008). During the osmotic phase, continued growth of aboveground biomass indicates the ability to overcome osmotic stress, since sensitivity to water deprivation typically results in decreased growth (Munns and Tester, 2008).

During the ionic phase, mechanisms of tolerance include compartmentalization of toxic ions into vacuoles and/or extrusion of Na⁺ from cells and the removal of Na⁺ from the xylem stream, which reduces potential exposure in the leaf. Therefore, the accumulation of dead aboveground biomass can be used as a proxy for evaluating compartmentalization and extrusion efficiency (Munns and Tester, 2008; Deinlein et al., 2014). We found that accessions with high STI values for dead aboveground biomass included both tolerant (Sb-10, Sb-9, and V-1) and sensitive (Sb-16 and V-2) accessions. These results, combined with the results for live aboveground biomass, suggest that tolerance in sorghum is correlated to a greater extent with the plant's ability to overcome the osmotic phase via continued growth rather than exclusion and/or compartmentalization of ions during the ionic phase. This tolerance is most evident for accessions such as Sb-10, Sb-9, and V-1. These tolerant accessions accumulated large amounts of both live and dead aboveground biomass (Fig. 3), reflecting the ability to maintain continued growth under salt exposure. The ability to continue new growth aids in the dilution of Na⁺ in leaves, and if new growth exceeds the rate of leaf senescence, plants can continue photosynthesizing and producing enough carbon to support overall plant growth (Munns and Tester, 2008; Carillo et al., 2011).

Plants may exhibit limited root growth as a result of low soil water potential, or conversely, increased growth as a search response for non-saline water (Rahnama et al., 2011; Jung and McCouch, 2013; Munns and Gilliham, 2015; Hanin et al., 2016). In our study, we found that three of the overall most-tolerant accessions (Sb-10, Sb-9, Sb-3) ranked in the top five highest STIs for root biomass (Fig. 3), suggesting that maintenance of root biomass in response to treatment is associated with salinity tolerance (Galvan-Ampudia et al., 2013; Munns and Gilliham, 2015). Sorghum propinquum, one of the most sensitive accessions, had the largest RDPB and the lowest live aboveground biomass STI, yet had the fifth highest overall STI for root biomass (Fig. 2 and Fig. 3, respectively). The larger STI for root biomass in S. propinquum is most likely a product of its naturally more extensive root system compared to S. bicolor, rather than tolerance, per se.

In our study, we assessed tolerance using the relative decrease in plant biomass (RDPB) and the stress tolerance index (STI) (Negrão et al., 2017). We observed that some accessions had less than a 10% decrease in plant biomass (RDPB) but ranked low in the STI analysis. For example, V-1 and Sb-10 had a 2% and 10% decrease in plant biomass, respectively (or 98% and 90% retained biomass, respectively), in response to treatment and ranked in the top five most-tolerant accessions in the STI analysis for live aboveground biomass, dead aboveground biomass, and root biomass. However, Sb-18, which lost only 4% of its biomass (retained 96% of its biomass) in response to treatment, ranked 16^th, 1^st, and 14^th for live aboveground biomass, dead aboveground biomass, and root biomass, respectively. The discordance between a high rank in the RDPB analysis versus STI analysis suggests that different modes of tolerance may exist in sorghum. Different modes of tolerance may reflect reductions in Na⁺ accumulation achieved by multiple mechanisms, such as reduction in root uptake, reduction in xylem loading, increased extrusion, and increased retrieval from aboveground tissue (Munns and Tester, 2008; Deinlein et al., 2014; Wu et al., 2019). Each of these mechanisms results in reduced Na⁺ in the cytoplasm. Regardless of the mechanism, reduced Na⁺ typically results in increased tolerance. Therefore, we propose that the RDPB analysis is the better indicator of tolerance because it depicts the outcome of NaCl exposure regardless of the mechanism operating in tolerant genotypes.

Physiological responses to salinity stress

Historically, proline accumulation under salt and/or osmotic stress has been used as an indicator of tolerance (Iqbal et al., 2014). When comparing proline accumulation across accessions, we found that leaf proline increased between the control and NaCl treatment, although this increase was accession dependent (Fig. 4). V-1 and Sb-10, two of our most-tolerant accessions according to RDPB and STI analysis, displayed low amounts of proline in both control and treatment conditions. In contrast, Sb-7 and Sb-17 exhibited large NaCl-induced increases in proline content but were only moderately salt tolerant. The lack in correlation of proline accumulation with the rank score of tolerant accessions (Appendix S7) suggests that, in sorghum, proline accumulation may reflect stress injury rather than osmotic adjustment/osmoprotection for increased tissue tolerance (Munns and Tester, 2008; Roy et al., 2014). Further, the quantitative trait loci (QTLs) for proline accumulation under salinity stress and for stress tolerance are not linked in barley (Fan et al., 2015), and in rice, salt-sensitive accessions accumulated higher levels of Na⁺ and proline compared to salt-tolerant accessions (Lutts et al., 1999; Vaidyanathan et al., 2003; Theerakulpisut et al., 2005). Therefore, although sorghum does accumulate proline in response to NaCl (Weimberg et al., 1982; Surender Reddy et al., 2015), our results suggest that proline is not an accurate predictor of protective capacity against stress injury.

Significant variation in sodium and potassium concentrations among accessions suggests that differences in the mechanisms responsible for sodium uptake and distribution and/or regulation of potassium concentration exist in sorghum (Table 2). When comparing the variation in Na⁺ accumulation with tolerance categories, we did not observe patterns suggestive of a unifying mechanism of sorghum response to excess Na⁺ (Appendix S8 and Appendix S7). For example, Sb-1 and Sb-10, a sensitive and a tolerant accession, respectively, did not significantly differ in foliar Na⁺ accumulation. In control conditions, both accessions averaged approximately 0.02 mg Na⁺ g^–1, and in treatment conditions, both averaged about 0.59 mg Na⁺ g^–1; however, in terms of relative decreases in plant biomass, Sb-10 had less than a 10% loss in live aboveground biomass, while Sb-1 had greater than 50% loss. Although our analysis of foliar Na⁺ by ICP cannot be used to assess subcellular localization, Sb-10 may have elevated tissue tolerance as a result of better compartmentalization of Na⁺ ions into vacuoles, resulting in less cell death due to ionic imbalance.

Salt sensitivity is often associated with changes in K⁺ uptake resulting from competition between Na⁺ and K⁺ (Deinlein et al., 2014). In sorghum, we observed variation in K⁺ among accessions and NaCl treatments. Most variation in K⁺ was observed between accessions and not between treatments. The only accession with a decline in K⁺ between the control and NaCl treatments was P-1, whereas exposure led to an increase in K⁺ in Sb-3 and Sb-9. Sb-3 and Sb-9 are both from the landrace guinea-margaritiferum, and both had low RDPB. In contrast, P-1 had a high RDPB. These patterns suggest that, at least in the sorghum accessions included in this study, the loss of K⁺ homeostasis may not underlie NaCl toxicity in S. bicolor, but rather may represent the basis of salt sensitivity in the wild relative, S. propinquum.

Evolution, domestication, and adaptation of salt-tolerant sorghum accessions

Where population structure and geographic distribution of sorghum has been studied, landraces show genetic diversity and racial structure with strong geographical patterning (Mace et al., 2013; Morris et al., 2013). We found, however, that salinity tolerance was not solely associated with landrace, suggesting that accessions exposed to high local and regional soil salt contents may have adapted mechanisms to overcome the stresses associated with NaCl exposure. We initially hypothesized that the driving force of variation in salt tolerance may be a result of post domestication adaptation to saline environments; however, when we evaluated our findings within the phylogenetic framework presented by Mace et al. (2013), the most-tolerant S. bicolor accessions were those that originated shortly after the domestication event, particularly those accessions within the durra clade (Fig. 5). Further, the two S. verticilliflorum accessions included here, and in the Mace et al. (2013) study, differed significantly in their responses to salinity. V-1 (PI226096), which had the lowest RDPB and ranked 5^th highest for live aboveground biomass STI, dead aboveground biomass STI, and root biomass STI, is positioned in the first post domestication clade; however, V-2 (PI300119), which lost approximately 70% of its biomass in response to treatment and ranked in the 3^rd to last position for live aboveground biomass and the last position for root biomass, is placed in the clade before the domestication event (Appendix S9). This placement, combined with the observations for the durra accessions, suggests that salinity tolerance was gained during or shortly after sorghum domestication. In contrast, accessions from the landrace caudatum, which displayed a diversity of stress tolerance rankings, are not monophyletic and are found in diverse positions throughout the tree (Fig. 5). Interpretation of these results within this phylogenetic context suggests that, during further selection and improvement, salinity tolerance was lost in lineages that were no longer subjected to continued environmental salt exposure. Lastly, given that S. bicolor and especially the landrace durra (Smith et al., 2019) are known to be relatively drought tolerant (Mullet et al., 2014; Fracasso et al., 2016; McCormick et al., 2018; Guo et al., 2018) and, as with drought stress, salt stress has an initial osmotic component, we propose that salinity tolerance in sorghum originated in combination with, or as a by-product of, drought tolerance during domestication.

Conclusions

With more than 500 million people relying on food, fuel, and fiber production from sorghum (Mace et al., 2013), the standing genetic diversity of this staple crop should be utilized to maximize production needs, especially in adverse soils. Because of its ability to thrive in environments associated with high degrees of abiotic stressors, it is imperative that the genetic, physiological, and morphological responses to salt exposure in sorghum are understood and utilized to enhance production on saline soils. We identified significant variation in response to salinity exposure among a diverse group of sorghum accessions, and we conclude that the variation in tolerance is not due to landrace alone, but rather a by-product of domestication and improvement. Given our results, and in combination with results of Mace et al. (2013), we propose that accessions from the landrace durra would serve as valuable resources for genetic improvement of sorghum salinity tolerance in agriculture.

Acknowledgments

We thank Dr. Jeffrey Bennetzen for providing Sorghum propinquum seed, Dr. Stephen DiFazio for guidance in project design, Dr. Sandra Simon for guidance in data analysis, and Janna Kleinsasser, Natalie Nedley, Rachel Bainbridge, and Margo Folwick for their assistance in data collection. We also thank two anonymous reviewers and the associate editor for their insightful comments on this manuscript. We acknowledge the Pennsylvania State University Analytical Laboratory, State College PA, the U.S. National Plant Germplasm System for supplying seed, and the West Virginia University Evansdale Greenhouse for supplying space. This work was partially funded by the Eberly College of Arts and Sciences research award (West Virginia University), the Biology Graduate Student Association graduate student research award (West Virginia University), both awarded to A.N.H., and the United States Department of Agriculture National Institute of Food and Agriculture (grant number 2018-67014-27469).

Author Contributions

A.N.H. and J.S.H. designed experiments; A.N.H. and J.S.H. managed the project; A.N.H., P.M.C, J.R.C., and J.S.H. prepared the samples; A.N.H, J.R.C., and J.S.H. led the data analysis; A.N.H, J.R.C., and J.S.H. wrote the manuscript with contributions from P.M.C.

Supporting Information

Filename	Description
ajb21506-sup-0001-AppendixS1.pdfPDF document, 38.6 MB	APPENDIX S1. Pilot study showing the effect of increasing concentrations of NaCl on biomass accumulation.
ajb21506-sup-0002-AppendixS2.docxWord document, 44.5 KB	APPENDIX S2. (A) Accession stress tolerance index (STI) values. (B) Growth variation in response to NaCl. Data are means ± SE. Different letters represent significant differences when comparing accessions (P < 0.05).
ajb21506-sup-0003-AppendixS3.pdfPDF document, 295.7 KB	APPENDIX S3. Nonmetric multidimensional scaling using Bray–Curtis dissimilarity coefficient for two-dimensionally visualizing plant response to 0 mM and 75 mM NaCl. The analysis of similarity revealed that plants were more similar within a treatment than across treatments (R = 0.11; P < 0.001). Gray triangles represent individuals within the control treatment; black circles represent individuals within the 75 mM NaCl treatment.
ajb21506-sup-0004-AppendixS4.docxWord document, 18.4 KB	APPENDIX S4. Relative decrease in plant biomass (RDPB) for each landrace. Data shown are means ± SE of RDPB values for each landrace. Different letters represent significant differences when comparing landraces (P < 0.05).
ajb21506-sup-0005-AppendixS5.docxWord document, 29.6 KB	APPENDIX S5. (A) Landrace stress tolerance index (STI) values and (B) growth variation in response to NaCl. Data shown are means ± SE. Different letters represent significant differences when comparing landraces (P < 0.05).
ajb21506-sup-0006-AppendixS6.docxWord document, 20.1 KB	APPENDIX S6. Mean proline content for control and NaCl conditions. Data shown are means ± SE of proline (g fw-1) for a subset of accessions. Different letters represent significant differences when comparing accessions and treatment (P < 0.05).
ajb21506-sup-0007-AppendixS7.pdfPDF document, 1.5 MB	APPENDIX S7. Pearson correlation matrix (75 mM NaCl).
ajb21506-sup-0008-AppendixS8.pdfPDF document, 612.1 KB	APPENDIX S8. Correlation between (A) Na⁺ accumulation and relative decrease in plant biomass (RDPB) (B) Na⁺ accumulation and live aboveground biomass stress tolerance index (STI).
ajb21506-sup-0009-AppendixS9.pdfPDF document, 295.6 KB	APPENDIX S9. Neighbor-joining tree constructed by Mace et al. (2013) using single nucleotide polymorphism (SNP) data. STI rank scores for (A) live aboveground biomass, (B) dead aboveground biomass, and (C) root biomass overlaid on neighbor-joining tree. Lower STI rank scores (yellow) indicate sensitivity, whereas higher STI rank scores (red) indicates tolerance. Figure modified by permission from Mace, E., Tai, S., Gilding, E. et al. Whole-genome sequencing reveals untapped genetic potential in Africa's indigenous cereal crop sorghum. Nature Communications 4: 2320 (2013), https://doi.org/10.1038/ncomms3320.

Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

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Citing Literature

Volume107, Issue7

July 2020

Pages 983-992

Phenotypic and physiological responses to salt exposure in Sorghum reveal diversity among domesticated landraces

Abstract

Premise

Methods

Results

Conclusions

Materials and Methods

Plant material

Note

NaCl exposure

Biomass measurements

Phenotypic measurements

Physiological measurements

Tolerance indices

Stress tolerance (ST)

Relative decrease in plant biomass (RDPB)

Stress tolerance index (STI)

Statistical analyses

Treatment effects

Landrace and accession effects

Treatment effects on growth

Treatment effects on sodium and potassium accumulation

Treatment effects on proline accumulation

Results

Treatment effects

Landrace and accession effects

Relative decrease in plant biomass (RDPB)

Stress tolerance index (STI)

Sodium and potassium accumulation

Proline accumulation

Discussion

Phenotypic responses to salinity stress

Physiological responses to salinity stress

Evolution, domestication, and adaptation of salt-tolerant sorghum accessions

Conclusions

Acknowledgments

Author Contributions

Supporting Information

Literature Cited

Citing Literature

Figures

References

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