Plant Breeding 132, 10–20 (2013)
© 2012 Blackwell Verlag GmbH

doi:10.1111/pbr.12000

Review
Crop breeding for salt tolerance in the era of molecular markers and
marker-assisted selection
M U H A M M A D A S H R A F 1 and M A J I D R . F O O L A D 2,

3

1

Department of Botany, University of Agriculture, Faisalabad, Pakistan; 2Department of Plant Science and The Intercollege Graduate
Degree Programs in Plant Biology and Genetics, The Pennsylvania State University, University Park, PA 16802, USA;
3
Corresponding author, E-mail:
With 2 tables
Received March 2, 2012/Accepted July 10, 2012
Communicated by R. Tuberosa

Abstract
Crop salt tolerance (ST) is a complex trait affected by numerous genetic
and non-genetic factors, and its improvement via conventional breeding
has been slow. Recent advancements in biotechnology have led to the
development of more efficient selection tools to substitute phenotypebased selection systems. Molecular markers associated with genes or
quantitative trait loci (QTLs) affecting important traits are identified,
which could be used as indirect selection criteria to improve breeding
efficiency via marker-assisted selection (MAS). While the use of MAS
for manipulating simple traits has been streamlined in many plant breeding programmes, MAS for improving complex traits seems to be at

infancy stage. Numerous QTLs have been reported for ST in different
crop species; however, few commercial cultivars or breeding lines with
improved ST have been developed via MAS. We review genes and
QTLs identified with positive effects on ST in different plant species and
discuss the prospects for developing crop ST via MAS. With the current
advances in marker technology and a better handling of genotype by
environment interaction effects, the utility of MAS for breeding for ST
will gain momentum.

Key words: abiotic stress — breeding for stress resistance —
molecular breeding — quantitative trait loci — salinity — stress
tolerance

In arid and semi-arid regions of the world, with insufficient
annual precipitation, agriculture depends mainly on irrigation
water. Irrigation agriculture poses a serious problem, that of
accumulation of high concentrations of soluble salts in the soil
where the plant roots normally grow. High salinity in the root
zone severely impedes normal plant growth and development.
This impairment could be due to (i) water stress arising from the
more negative water potential of the rooting medium, (ii) adverse
specific ion effects (toxicity), usually associated with either
excessive sodium or chloride intake that may disturb membrane
integrity and function, and (iii) nutrient ion imbalance, when
the excess of sodium or chloride leads to either a diminished
uptake of potassium, nitrate or phosphate, or impaired internal
distribution of one or more of these ions (Shannon 1984,
Gorham et al. 1985, Ashraf et al. 2008, Lenis et al. 2011). Irrespective of the cause, plant productivity may be reduced partially
or completely depending on the intensity of the salt stress.
The various strategies proposed to overcome the threat of

salinity stress can be deciphered from a number of comprehensive reviews published on plant salt tolerance (ST; Epstein et al.

1980, Flowers 2004, Chinnusamy et al. 2005, Yamaguchi and
Blumwald 2005, Munns et al. 2006, Ashraf et al. 2008, Ashraf
and Akram 2009, Rai et al. 2011). However, generally, there are
two major approaches/strategies to minimize the deleterious
effects of high soil or water salinity and both must be applied to
achieve sustainable crop production in the presence of excessive
salts (Epstein et al. 1980). One is a technological approach, that
is, implementing large engineering schemes for reclamation,
drainage and irrigation with high-quality water. Although these
practices have had continuing success in some areas, the associated costs are high and often provide only a temporary solution
to the problem. The second approach, that is a complement to
technological approach, entails biological strategies focused upon
the exploitation or development of plants capable of tolerating
excessive levels of salts. This approach includes (i) diversifying
cropping systems to include crops that are known to be salt
tolerant (e.g. by crop substitution); (ii) exploiting wild or feral
species that are adapted to saline environments (e.g. by domestication); and/or (iii) genetically modifying domesticated crops by
breeding and selection to develop cultivars with enhanced ST.
Breeding for salt-tolerant genotypes that can grow more
efficiently than the conventional varieties under high salinity
stress is a fundamental approach which is considered economically feasible (Blum 1988, Ashraf et al. 2008).
The possibility and desirability of selection and breeding for
salt-tolerant plants was first discussed by Lyon (1941), Dewey
(1962) and Epstein (1963). Dewey (1962) was actually the first
to conduct a systematic study of the ST of 60 strains of Agropyron desertorum and to outline a breeding programme for improving plant ST. Further reports (Epstein and Jefferies 1964) also
emphasized the importance of breeding for salt-tolerant crops. In
the early 1970s, genetic investigations were sporadically introduced into applied research on salinity for the first time (Epstein
1976), and in 1980, Epstein et al. (1980) advocated the development of crops tolerant to salinity as a strategy to overcome this

enduring problem. Since then, there have been numerous reports
and reviews dealing with the development of salt-tolerant crops
(Epstein 1983, Richards 1983, Shannon and Qualset 1984, Staple
and Toennissen 1984, Shannon 1985, Foolad 1999a, 2005, 2007,
Munns et al. 2006, Ashraf et al. 2008, Ashraf and Akram 2009,
Azzedine et al. 2011, Rai et al. 2011).
Development of a breeding programme for improved ST
requires (i) efficient screening techniques for the selection and

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Crop breeding for salt tolerance in the era of molecular markers

evaluation of specified characters, (ii) identification of genetic
variability, (iii) knowledge of the inheritance of tolerance trait(s)
at specific developmental stages, (iv) knowledge of biological
mechanisms underlying tolerance, (v) reliable direct or indirect
selection criteria, and (vi) designing the most appropriate breeding methodologies/strategies to transfer the tolerance trait(s) into
improved genetic backgrounds. Among these, the identification
of genetic variability, attainment of genetic knowledge of STrelated traits and development of reliable selection criteria are
most crucial for the establishment of a successful breeding programme. Accumulating evidence in different crop species has
indicated that ST is a developmentally regulated, stage-specific
phenomenon. Tolerance at one stage of plant development may
be poorly correlated with tolerance at other developmental stages
(Foolad 1999a, Zhang and Blumwald 2001, Ashraf and Akram
2009, Uddin et al. 2011). Specific stages throughout the ontogeny of the plant such as germination and emergence, seedling
survival and growth, and vegetative and reproductive growth
should be evaluated separately for the assessment of ST and
identification of contributing genetic components. Formal genetic

analysis of ST at specific developmental stages may simplify the
underlying genetic components and therein facilitate breeding
efforts by introgressing each component trait into superior
genetic backgrounds. Subsequent integration of differential tolerance at specific stages into a single highly tolerant cultivar might
then be accomplished faster than selection strategies based on
yield performance, which is the ultimate objective. Reducing ST
into developmental units may also facilitate the identification of
individual genes or quantitative trait loci (QTLs), amenable to
manipulation with current molecular genetic techniques.
Direct selection in field sites for quantitative traits, such as
ST, is difficult because uncontrollable environmental factors
adversely affect the precision and repeatability of such trials.
One suggested approach to improve the efficiency of the breeding programmes is adoption of new selection criteria based on
the knowledge of the physiological processes limiting crop production under conditions of stress (Ashraf 2004) and of their
genetic control (Tal 1985). Some of the physiological responses
to high salinity, which may be used as indirect selection criteria
for improving crop ST, are tissue water potential, tissue ion content, K+/Na+ ratio, succulence, water-use efficiency, chlorophyll
fluorescence, content of chlorophyll, contents of proline, phenolics and sugars, and activities and levels of enzymatic and nonenzymatic antioxidants. Whether these physiological responses
are correlated with ST or there is variation in these responses in
the plant species of interest must be elucidated before the question of genetic control can be addressed.
A contemporary approach to improving the efficiency of selection and breeding for complex traits such as ST is to discover
genetic markers that are associated with the trait(s) of interest
and which could be used as indirect selection criteria for the
evaluation of large breeding populations. A common method for
the identification of associated genetic markers is the detection
of linkage between genetic markers already mapped on the chromosomes and the loci or gene complexes (e.g. QTLs) that control quantitative variation and are inherited as major hereditary
factors. This technique entails the identification of QTL-linked
markers in controlled environment, using appropriate genetic
material, and then introgressing marker-linked QTLs into desirable genetic backgrounds by a process known as marker-assisted
selection (MAS). Because often several traits and mechanisms

are involved in plant ST, pyramiding traits of interest via MAS
may be an effective approach to substantial improvement in

11

plant ST. Furthermore, MAS may allow early selection for trait
(s) of interest, multiple cycles of selection in a year, and pyramiding of tolerance components from different genetic resources.
These advantages may facilitate the development of crops with
improved ST, compared to traditional methods of field evaluation and phenotypic selection (Foolad 2004, Collins et al. 2008,
Witcombe et al. 2008). For example, it has been estimated that
breeding rice cultivars for tolerance to salinity stress and phosphorus deficiency via MAS may be accelerated by 3–6 years
compared with the conventional breeding, leading to a saving of
US$ 50–900 million over a 25-year period (Alpuerto et al.
2009).
Since the advent of molecular markers and MAS technology,
numerous studies have been conducted to identify genes or
QTLs affecting ST in different plant species and during different
developmental stages. These studies have been conducted with
the promise of using marker-linked QTLs or genes in MAS
breeding for ST. However, limited progress has been made in
developing salt-tolerant cultivars via the use of MAS technology.
This is in contrast to the extensive application of MAS for
breeding for many simple traits in numerous crop species. In this
article, we review and summarize the genes and QTLs that have
been identified with positive effects on ST in different plant species and discuss their use in MAS breeding for improving plant
ST. Further, we discuss challenges and opportunities for developing crop ST via the use of MAS technology.

QTLs Associated with Salt Tolerance
It has been known that salt stress imposes two primary effects
on plants, osmotic and ionic, and both reduce plant growth and

final yield to varying extents in different crop species. In addition, salt stress imposes secondary effects such as nutrient imbalances, generation of oxidative stresses and hormonal imbalances
(Ashraf et al. 2008). To counteract such salt-induced adverse
effects, plants respond in different ways, including ion exclusion/accumulation to provide ion homoeostasis, accumulation of
organic osmolytes to establish osmoregulation, production of
antioxidants to counteract salt-induced generation of reactive
oxygen species (ROS), and changes in uptake and accumulation
of essential mineral nutrients (Mittler 2002, Byrt et al. 2007,
Ashraf et al. 2008). During the past two decades, numerous
studies have been undertaken in different crop species to identify
QTLs that directly or indirectly affect the various plant responses
to salt stress at different developmental stages, including seed
germination, seedling and vegetative growth and reproduction.
These studies are summarized in Table 1, and in the following
paragraphs, we review and discuss some of the major findings.
QTLs for ion uptake and accumulation
The key transport systems involved in ion homoeostasis in
plants grown under saline conditions are regulated by the salt
overly sensitive (SOS) signal pathway (Hasegawa et al. 2000,
Zhu 2000). The SOS2, a serine/threonine protein kinase, regulates SOS1 (plasma membrane Na+/H+ antiporter)-mediated Na+
efflux from the cytosol, as well as regulating vacuolar Na+/H+
antiporter-mediated Na+ sequestration into the vacuole (Shi et al.
2000, Qiu et al. 2003). In addition to this mechanism of ion homoeostasis, the high-affinity K+ transporters (HKT), which
mediate Na+-specific transport or Na+/K+ co-transport, play an
important role in maintaining Na+ homoeostasis in plants under
saline conditions. An important locus (Kna1) in hexaploid bread


12

M. ASHRAF and M.R. FOOLAD


Table 1: Identification of quantitative trait loci (QTLs) for salt tolerance (ST) in different plant species
Crop plants
Wheat
(Triticum
aestivum L.)

Arabidopsis
thaliana L.

Rice (Oryza
sativa L.)

Barley
(Hordeum
vulgare)

Molecular
markers

Traits governed

ESTs

TmHKT7-A2

SSR

Kna1


Reduces Na+ concentration in leaf blades by
retaining Na+ in the sheaths
Controls the selectivity of Na+ and K+
transport from root to shoot and maintains
high K+/Na+ ratio

SSR

Nax1

Both are involved in decreasing Na+ uptake
and enhancing K+ loading into the xylem

EST

Nax2

Not
mentioned
in the
article
AFLPs

Xglk683–Xcdo460 and Xfbb168–Xbcd147

Not
mentioned
in the
article
SSRs


RAS1

QTL1, QTL2, QTL3, QTL5

qRL-7, qDWRO-9a and qDWRO-9b qBI-1a and
qBI-1b

Increase biomass, shoot length, root length,
chlorophyll and proline contents at both the
germination and seedling stages under saline
conditions
Functions as a negative regulator of ST during
seed germination and early seedling growth
by enhancing ABA sensitivity and its loss of
function contributes to increased ST
Control germination under salt stress

Play important roles in root length and root
dry weight at seedling stage under saline
conditions
Affect shoot Na+ and K+ concentrations,
respectively

ESTs

qSNC-7 and qSKC-1

SSRs


QNa, QNa:K, SKC1/OsHKT8

Regulate K+ / Na+ homoeostasis

AFLPs

QNa, QK1, QK2 and QNaK

SSRs

qDM-3 and qDM-8, qSTR-6

Improve Na+, K+ and discrimination of Na+ or
K+ uptake
Improve Na+/K+ ratio under saline conditions

RFLPs,
SSRs,
AFLPs
and
isozymes
SSRs

qST1 and qST3

Enhance ST in shoots

qNAK-2 and qNAK-6

Improve Na+/K+ ratio


SSRs

Saltol

Controls shoot Na+/K+ homoeostasis

SSRs

Saltol and non-Saltol

Control shoot Na+/K+ homoeostasis

SSRs

QKr1.2

Controls K+ content in root

SSRs

bPb-1278 and bPb-8437

RFLPs

QFv2H, QCh7Ha, Qch2Ha and QWSC2H

Associated with tiller number, plant height,
spikes per line and spikes per plant (SPP)
Enhance ST by improving chlorophyll content,

fluorescence and proline content

SSR

Five QTL for ST were identified on
chromosomes 1H, 2H, 5H, 6H and 7H, which
accounted for more than 50% of the
phenotypic variation
A locus HvNax3 on the short arm of
chromosome 7H in wild barley (Hordeum
vulgare ssp. spontaneum) accession CPI71284-48
HvNax4 was fine-mapped on the long arm of
barley (Hordeum vulgare) chromosome 1H.
ORS674, ORS784, ORS235, ORS681

RFLPs
Sunflower
(Helianthus
annuus L.)

Locus

ESTs, SNPs

Enhance vegetative growth under saline stress

References
Huang et al.
(2006)
Dubcovsky

et al. (1996),
Gorham et al.
(1990)
Huang et al.
(2006),
Lindsay et al.
(2004)
Byrt et al.
(2007)
Ma et al.
(2007)
Ren et al.
(2010)
Galpaz and
Reymond
(2010)
Sabouri and
Sabouri
(2008)
Lin et al.
(2004),
Pushparajan
et al. (2011)
Ren et al.
(2005)
Flowers et al.
(2000)
Sabouri et al.
(2009)
Lee et al.

(2007)

Ming-zhe et al.
(2005)
Thomson et al.
(2010)
Alam et al.
(2011)
Ahmadi and
Fotokian
(2011)
Xue et al.
(2010)
Siahsar and
Narouei
(2010)
Zhou et al.
(2012)

Reduces shoot Na+ content by 10–25% in
plants grown under salt stress (150 mM
NaCl)

Shavrukov
et al. (2010)

Promotes shoot Na+ exclusion up to %59

Rivandi et al.
(2011)

Lexer et al.
(2003)

Enhance ST by increasing Ca2+ uptake,
coupled with greater exclusion of Na+

(continued)


Crop breeding for salt tolerance in the era of molecular markers

13

Table 1. (continued)

Crop plants
Tomato
(Solanum
lycopersicum
L.)

White clover
(Trifolium
repens L.)
Soybean
(Glycine max
(L.) Merr.)

Molecular
markers

RFLPs

Locus

Traits governed

RFLPs

Five QTLs on chromosomes 1, 3, 5 and 9

Contribute to rapid germination under salt
stress (in crosses with Solanum pennellii)
Contribute to rapid germination under salt
stress (in crosses with Solanum
pimpinellifolium
Affect ST during vegetative stage

RFLPs

Five QTLs on chromosomes 1, 3, 5, 6 and 11

Affect ST during vegetative stage

RFLPs

Several QTLs for ST–related traits

Affect ST during reproductive stage

SSR and

SNPs

Several QTLs for ST, some at common
locations, but each of low scale

Affect ST during vegetative stage

RFLP and
SSR
SSR

A major QTL for ST was identified near the
Sat091 SSR marker on linkage group (LG) N
Eight QTLs for ST were detected

Maintains healthy growth under salt stress
Maintains growth under salt stress

SSR

A major QTL for ST was detected

Maintains growth under saline stress

RFLPs

Seven QTLs on chromosomes 1, 2, 3, 7, 8 9
and 12
Seven QTLs on chromosomes 1, 2, 5, 7, 9 and
12


wheat (Triticum aestivum) has been reported to control the
selectivity of Na+ and K+ transport from root to shoot, thereby
maintaining a high K+/Na+ ratio in leaves (Gorham et al. 1987,
1990, Dubcovsky et al. 1996, Luo et al. 1996). However, Na+
exclusion mechanism in durum wheat (Triticum turgidum L.
ssp. durum Desf.) was found to be linked to Nax1 (Na+ exclusion 1) and Nax2 loci, which most probably relate to the Na+
transporters HKT1;4 (HKT7) and HKT1;5 (HKT8), respectively
(Huang et al. 2006, 2008, Byrt et al. 2007). The Nax1 and
Nax2 loci have been reported to effectively decrease Na+ transport from root to shoot, thereby maintaining reasonably low
Na+ content as well as high level of K+ in the leaf blades of
durum wheat plants by excluding Na+ from, and loading K+
into, the xylem (James et al. 2006). Ming-zhe et al. (2005) identified two QTLs for root Na+/K+ ratio in rice (Oryza sativa),
which were mapped to chromosomes 2 and 6 using an F2 population of a cross between japonica rice cultivar ‘Jiucaiqing’ and
indica rice cultivar ‘IR36’. Many other QTLs for ST traits have
been identified in rice, including Saltol on chromosome 1,
which explains most of the variation for ion uptake under salt
stress (Bonilla et al. 2002, Gregorio et al. 2002), QNa for high
Na+ uptake on chromosome 1 (Flowers et al. 2000), QNa:K for
Na+/K+ discrimination on chromosome 4 (Singh et al. 2001),
SKC1/OsHKT8 on chromosome 1, which regulates K+/Na+ homoeostasis in salt-tolerant indica variety ‘Nona Bokra’ (Lin
et al. 2004, Ren et al. 2005), several QTLs on all but chromosome 9 for Na+/K+ ratio in the root (Sabouri and Sabouri
2008), three QTLs for ion exchange on chromosomes 3 and 10
(Sabouri and Sabouri 2008), and one QTL each for Na+ and K+
uptake and four QTLs for tissue Na+/K+ ratio on different
chromosomes (Lang et al. 2001). Furthermore, Ahmadi and
Fotokian (2011) identified 14 QTLs for root and shoot Na+, K+
and K+/Na+ ratio on different rice chromosomes. Among them,
a QTL (QKr1.2) for root K+ content identified on chromosome
1 was found to be most promising as it explained approximately 30% of the variation observed for ST in rice. Furthermore, Islam et al. (2011) identified two novel QTLs on rice


References
Foolad et al.
(1997)
Foolad et al.
(1998)
Foolad and
Chen (1999)
Foolad et al.
(2001)
Breto et al.
(1994),
Monforte
et al. (1996)
Wang et al.
(2010)
Lee et al.
(2004)
Chen et al.
(2008)
Hamwieh et al.
(2011)

chromosomes 8 and 10 based on an F2 population of a cross
between a moderately salt-tolerant (BRRI-dhan40) line and a
highly salt-tolerant (IR61920-3B-22-2-1) line.
Similar to that in rice, numerous studies have identified QTLs
for ST-related traits in barley (Hordeum vulgare L.; Table 1).
For example, Xue et al. (2010) identified 30 QTLs for 10 different traits, including shoot Na+, K+ and Na+/K+ ratio, and several
growth and yield-related attributes in populations grown under

salt-stress and non-stress conditions. This research determined
that the QTLs for ion-uptake traits observed under saline stress
were different from those under non-stress conditions, suggesting
that specific genes related to ion uptake and facilitating plant
adaptation to salt stress were expressed only under salt-stress
conditions. The authors suggested that only the QTLs expressed
under saline stress were associated with ST, which could potentially be useful for developing salt-tolerant barley genotypes.
QTL analysis of mineral ion-uptake traits in three species of
sunflower (Helianthus sp.), Helianthus paradoxus (from highly
saline habitat – salt marshes) and its putative parents Helianthus
annuus and Helianthus petiolaris (both usually categorized as
salt sensitive), resulted in the identification of 14 QTLs for ion
uptake (Lexer et al. 2003). The researchers also reported that ST
in Helianthus was achieved through enhanced Ca2+ uptake and
Na+ exclusion. In follow-up studies, using sunflower expressed
sequence tags (EST) database and single-nucleotide polymorphism (SNP) mapping strategy, several candidate genes were
detected that co-localized with QTLs for some of the vital adaptive traits (Lexer et al. 2004, Lai et al. 2005). For example, the
genes encoding Ca2+ and K+ transporters as well as a calciumdependent protein kinase (CDPK) co-localized with the QTLs
for ion uptake and survival under salt stress. In a different study
using H. paradoxus, transgressive expression of genes encoding
K+ and Ca2+ transport system was detected, suggesting that these
genes play important roles in the adaptation of H. paradoxus to
high saline conditions.
It is apparent that many studies have identified QTLs for
ion uptake and/or accumulation in different crop species grown


14

under salt stress. However, the utility of these QTL information for improving plant ST via MAS has not been verified.

Additional work is necessary to determine the utility of such
QTLs for use in crop breeding for improved ST. First, the
actual relationship between ion accumulation (or lack thereof)
and ST has to be clearly determined in crop species of interest. Ion accumulation or exclusion may only be a small component of the overall response of plants to salt stress, and
thus, such QTLs may not play a major role in plant ST. Second, most studies have identified QTLs for ion uptake/accumulation at one stage of plant development. It has been reported
that the extent of operation of ion-uptake mechanism varies
considerably at different stages of plant development (Ashraf
and O’Leary 1994, Chartzoulakis and Klapaki 2000, Qasim
and Ashraf 2006). Thus, it needs to be determined whether
ion accumulation at any specific stage of plant development
would affect the overall plant response to salt stress. Third, as
for many other agriculturally important traits, the QTLs for ion
accumulation are originally described in genetic populations
distantly related from or irrelevant to a given breeder’s germplasm and/or in different agricultural environments from a
given breeder’s target climatic region. Such information may
not be easily transferable to populations used in practical plant
breeding programmes. Thus, before these issues are addressed,
the value of the identified QTLs for improving plant ST cannot be easily determined.
QTLs for oxidative defence system
Under saline stress, similar to that under a variety of other
stress conditions, reduction of oxygen (O2) frequently takes
place in plants, which leads to the production of different types
of ROS, including superoxide (OÁÀ
2 ), hydrogen peroxide (H2O2)
and hydroxyl radical (˙OH). ROS are known to adversely interact with a number of metabolites, which may result in the
impairment of normal functioning of the cell (Mittler 2002,
Ashraf 2009, Mittler et al. 2011). However, plants have the
ability to generate a variety of enzymatic and non-enzymatic
compounds that act as antioxidants to detoxify the ROS. The
type of antioxidants depends on plant species. Some key enzymatic antioxidants include superoxide dismutase, catalase,

ascorbate peroxidase (APX), dehydroascorbate reductase
(DHAR), monodehydroascorbate reductase (MDHAR) and glutathione reductase (GR; Mittler 2002, Ashraf 2009). Important
non-enzymatic antioxidants include glutathione (GSH), ascorbate (AsA), carotenoids, tocopherols, phenolics and flavonoids
(Mittler 2002, Mateo et al. 2004, Gupta et al. 2005, Ashraf
2009). Overexpression of these antioxidants has been reported
to be associated with ST in many plant species (Lopez et al.
1996, Shalata et al. 2001, Ashraf 2009, Zhou et al. 2011).
Furthermore, up-regulation of the genes for different antioxidants has been reported in plants under stress conditions (Zhu
et al. 2005). Thus, attempts have been made to identify QTLs
underlying the expression of various antioxidants in different
plant species. For example, Frary et al. (2010) reported that
Solanum pennellii accession LA716 (a salt-tolerant wild
accession of tomato) had considerably more accumulation of
antioxidants, such as total phenolics, flavonoids and some other
key antioxidant enzymes, than the salt-sensitive cultivated
species, Solanum lycopersicum. In this research, a total of 125
QTLs for antioxidants were identified under saline and nonsaline conditions. Among these, some antioxidant QTLs were
identified under both saline and non-saline conditions, while

M. ASHRAF and M.R. FOOLAD

other QTLs were more specific to one or the other condition.
However, the authors contemplated that the identification of
QTLs for enhanced synthesis of antioxidants under salt stress
would be beneficial to breeding programme for developing
salt-tolerant cultivars of tomato.
Because very few reports on the identification of QTLs related
to oxidative defence system are available, it is difficult to draw
any conclusion as to whether the detection of QTLs for such
traits would be useful for improving plant ST via MAS. In fact,

the regulation of oxidative defence mechanism in plants is considered to be one of the secondary responses of plants to saline
stress (Ashraf 2009), so it needs to be determined how relevant
QTLs for antioxidants and their overexpression would be in relation to plant ST.
QTLs for organic osmolytes and osmoprotectants
When subjected to stress conditions, including salt stress, most
plants accumulate a variety of organic osmolytes (osmoprotectants), including sugar alcohols, proline and quaternary ammonium compounds such as glycine betaine. Such organic solutes
not only contribute to osmoregulation in stressed plants, but also
provide protection to very many enzymes that are active in the
cytosol (Bohnert et al. 1995, Ashraf and Foolad 2007). There
are great variations within and among plant species in the accumulation of organic osmolytes in response to saline conditions.
In general, plants accumulating higher levels of these osmolytes
are more salt tolerant than those accumulating lower amounts
(Ashraf and Harris 2004). However, limited research has been
conducted to identify putative QTLs underlying various osmoprotectants, besides a few reports related to proline. For example,
two putative proline QTLs were identified in barley on chromosomes 2 and 4 ( and
recently, Siahsar and Narouei (2010) identified 29 QTLs for a
number of physiological traits including proline content under
saline conditions in barley. Unlike the QTL approach, transgenic
approaches have been used frequently to engineer plants with
overproduction of different types of osmoprotectants, including
glycine betaine, proline and trehalose (Hussain et al. 2011). For
example, Ziaf et al. (2011) transferred an early responsive-todehydration gene (SpERD15) from a drought- and salt-tolerant
wild tomato S. pennellii to tobacco (Nicotiana tobacum L.). The
resultant transgenic tobacco line showed improved drought and
ST because of high accumulation of proline and soluble sugars,
which occurred because of the overexpression of their respective
genes, P5CS and sucrose synthase. Similarly, a transgenic line
of potato (Solanum tuberosum L.), recently developed by the
insertion of a bacterial mannitol 1-phosphate dehydrogenase
(mtlD) gene, showed enhanced ST that was associated with

increased accumulation of mannitol in both shoot and root
(Rahnama et al. 2011).
The above-mentioned studies clearly demonstrate that ST can
be improved by engineering gene(s) controlling enhanced osmolyte synthesis and that the overaccumulation of a specific
organic osmolyte depends on the species used. For example, in
some plant species, high proline synthesis is a useful characteristic related to ST, whereas in others, it may not be. The same is
true for other osmolytes. Because different osmolytes play
important roles in conferring ST, it is prudent to conduct
research to discern the genetic control of osmolyte production in
different plant species. Such knowledge may facilitate the development of plants with improved ST via breeding for osmolyte
accumulation.


Crop breeding for salt tolerance in the era of molecular markers

QTLs for growth-related traits under salt stress
Quantitative trait loci have been identified for growth-related
traits as well as physiological and biochemical attributes related
to ST during different plant development stages, including seed
germination, early and late seedling growth and vegetative
growth and reproduction (Foolad and Jones 1993, Foolad et al.
1997, 1998, Mano and Takeda 1997, Foolad and Chen 1998,
1999, Foolad 2004; Table 1). For example, QTLs for ST during
the germination stage have been identified in different plant species, including tomato (Foolad and Jones 1993, Foolad et al.
1997, 1998), rice (Prasad et al. 2000, Cheng et al. 2008),
Arabidopsis (Ren et al. 2010, Vallejo et al. 2010), barley (Mano
and Takeda 1997) and wheat (Ma et al. 2007). Similarly, QTLs
for ST at the seedling stage (i.e. vegetative growth under salt
stress) have been detected in a number of plant species, including rice (Ming-zhe et al. 2005, Yao et al. 2005, Lee et al. 2007,
Sabouri and Sabouri 2008, Thomson et al. 2010, Ahmadi and

Fotokian 2011, Alam et al. 2011), Arabidopsis (Ren et al.
2010), barley (Mano and Takeda 1997, Ellis et al. 2002, Zhou
et al. 2012), soybean (Lee et al. 2004, Chen et al. 2008,
Hamwieh et al. 2011), white clover (Wang et al. 2010), tomato
(Bolarin et al. 1991, Asins et al. 1993, Foolad and Chen 1999,
Foolad et al. 2001) and wheat (Ma et al. 2007). Furthermore,
QTLs for ST during reproductive stage (e.g. grain or fruit yield
under salt stress) have been identified in different plant species,
including rice (Takehisa et al. 2004, Manneh et al. 2007), barley
(Ellis et al. 2002, Xue et al. 2010) and tomato (Breto et al.
1994, Monforte et al. 1999, Villalta et al. 2007). Many of these
studies have indicated the complexity of the genetics of ST
across plant species. However, most studies have also suggested
that this complexity could be simplified by looking at tolerance
at individual developmental stages. Specific ontogenetic stages,
including seed germination and emergence, seedling survival and
growth, and vegetative growth and reproduction, may have to be
evaluated separately for the assessment of tolerance and the
identification and characterization of useful genetic components.
Partitioning of the tolerance into its component traits related to
ontogenic stages would facilitate a better understanding of the
genetic basis of tolerance and the development of salt-tolerant
genotypes.

QTL Expression at Different Growth Stages and
under Different Conditions
Although many QTLs for ST at different phases of plant growth
have been identified and mapped in different plant species,
a major concern is that the ability to withstand salt stress is a
developmentally regulated, stage-specific phenomenon, so that

tolerance at one stage of plant development is not necessarily
correlated with tolerance at other developmental stages (Kumar
et al. 1983, Caro et al. 1991, Johnson et al. 1992, Foolad and
Lin 1997, Pearen et al. 1997, Shannon 1997, Almansouri et al.
2001, Foolad 2004). Thus, often ST QTLs identified at one stage
of plant development are different from those identified at other
developmental stages (Mano and Takeda 1997, Foolad 1999a,
Foolad et al. 1999, Zhang et al. 2003). For example, Mano and
Takeda (1997) reported that in barley, the QTLs identified for
ST at the germination stage were different from those contributing to ST at the seedling stage, suggesting that different genes
or physiological mechanisms control ST at the two stages. Similar observations have been reported in tomato (Foolad and Lin
1997, Foolad 1999a, 2004, Zhang et al. 2003) and other plant

15

species (Walia et al. 2007, Khan 2011). Similar results have
been reported for other abiotic stresses, including cold tolerance
(Foolad and Lin 2000, 2001). The overall conclusion from these
studies is that to gain a better understanding of the genetic control of stress tolerance (including ST) and to improve plant tolerance, specific ontogenetic stages throughout the plant life cycle
should be evaluated separately for the assessment of tolerance
and identification, characterization and utilization of useful
genetic components. This approach is expected to simplify the
complexity of stress tolerance and facilitate the development of
plants with improved tolerance throughout the plant ontogeny.
For example, once genetic components of ST at individual
developmental stages are tagged with molecular markers, the
MAS technology can facilitate transferring of such genetic components to desirable genetic backgrounds leading to the development of plants with enhanced ST throughout the plant life cycle.
In addition to be stage specific, QTLs have been reported to
be environmental and population specific. For example, a QTL
(fwTG48-TG180) that accounted for 58% of the variation in fruit

weight of tomato under non-saline conditions could explain only
14% of the variation under saline stress (Monforte et al. 1997).
And when the same QTL studied in a different tomato population, it accounted for 17% of the variation under control conditions and 8% of the variation under saline conditions (Monforte
et al. 1997). These observations suggest the presence of significant genotype 9 genotype and genotype 9 environment interactions when it comes to the expression of genes/QTLs affecting
plant ST (Tsuruta et al. 2002). Realizing considerable effects of
environment on the expression of QTLs, Collins et al. (2008)
suggested the presence of two types of QTLs, constitutive,
which appear in all environments, and adaptive, which normally
are detected only in specific environments or show varying
expressions with the change in environmental conditions. Similar
observations and classifications have been made when QTLs
were compared under different stress (e.g. salt, cold and drought)
and non-stress conditions in tomato (Foolad 1999b, 2000, Foolad
et al. 1999, 2003, 2007). In these studies, it was determined that
some QTLs were expressed under both stress and non-stress
conditions, whereas other QTLs were detected only under stress
conditions. Additionally, there were QTLs that were expressed
under various stress conditions, whereas others were more stress
specific, that is, they were expressed only under certain stress
conditions. However, depending on breeding goals and target
environment(s), constitutive and adaptive QTLs may have
different values.

Improvement in Crop Salt Tolerance through
Marker-assisted Selection
As described earlier, numerous studies have identified QTLs
contributing to ST at different developmental stages and for different ST attributes (Table 1). The challenge, however, has been
the utilization of the marker-QTL information in breeding programmes for improving crop ST. In general, unlike the situation
with simple/qualitative traits where marker information has been
frequently and successfully utilized in breeding programmes, for

complex/quantitative traits, including ST, which are often controlled by more than one gene (QTL) and exhibit low heritability
and strong G 9 E interactions, such information is underutilized.
The limited use of molecular markers for complex traits is
because of various reasons, including QTLs being unreliable or
population and environment specific, QTLs not strong enough in
terms of linkage to warrant their use for marker-assisted


16

M. ASHRAF and M.R. FOOLAD

breeding, lack of marker validation or marker polymorphism in
breeding populations, and problems associated with linkage
drag.
In the case of ST, however, a few studies can be deciphered
from the literature where gene or QTL information has been
used to develop lines or cultivars with improved ST through
marker-assisted breeding (Table 2). One example is the recent
development of a highly salt-tolerant cultivar of durum wheat by
R. Munns and her research team at CSIRO, Australia (Munns
et al. 2012). Durum wheat is generally known for its more sensitivity to salt stress compared with the common bread wheat, and
this has been attributed to its inherent lower ability of excluding
Na+ from the leaf blade (Gorham et al. 1990). In an earlier
study, Munns et al. (2000) had identified a durum line (known
as Line 149) with Na+ exclusion ability similar to that of bread
wheat. In a genetic analysis of a cross between Line 149 and a
durum wheat accession (Tamaroi) with normal Na+ exclusion
ability, two genes, Nax1 and Nax2, were identified for controlling Na+ exclusion (Munns et al. 2003). Nax1 was mapped to
the distal region of chromosome 2AL (Lindsay et al. 2004), and

Nax2 was mapped to chromosome 5AL (Byrt et al. 2007). In
subsequent studies, these two genes were introduced into various
durum wheat lines through marker-assisted breeding. The newly
developed durum wheat lines were tested under natural saline
fields in northern New South Wales, Australia, and the lines possessing particularly Nax2 were able to produce approximately
25% more yield than the control durum wheat lines under such
saline conditions (Munns et al. 2012). The findings of this
research are encouraging and provide confidence to the use of
MAS for breeding plants for improved ST. In a similar study in
rice, scientists at the International Rice Research Institute (IRRI)
identified a single major QTL (Saltol) on the short arm of chromosome 1, which explained much of the variation for ST in a
segregating rice population (Bonilla et al. 2002). In subsequent
studies conducted at the Bangladesh Rice Research Institute
(BRRI), attempts have been made to transfer Saltol to two highyielding popular commercial rice varieties, BR11 and BR28
(Rahman et al., />In this study, various markers closely linked to Saltol were identified and used to transfer the QTL to the two commercial varieties via marker-assisted backcrossing. In tomato, MAS was
employed to develop salt-tolerant breeding lines using an F2
population of a cross between the cultivated tomato (salt-sensitive) and a salt-tolerant accession of the tomato wild species
Solanum pimpinellifolium (Monforte et al. 1996). In this study, a
combination of phenotypic selection and MAS was used to
develop lines with improved ST. However, despite the development of advanced filial generations, which contained the QTLs
for ST, there is no report of the evaluation of these lines under

field conditions to verify their ST behaviour or agricultural
value.
In summary, despite the extensive efforts made to identify
QTLs contributing to ST in different crop species, limited
attempts have been made to use such QTL information for marker-assisted breeding for improved ST. This situation is similar
to that for most other complex traits across crop species. However, the limited use of markers for improving crop ST is attributable to various reasons, including (i) generally limited efforts
that have been made by breeders to develop plants with
improved ST, compared to efforts devoted to other economically

important traits such as disease resistance and improved quality
and quantity of yield, (ii) limited familiarity of many plant
breeders with the marker technology, (iii) insufficient reliability
of the identified QTLs or lack of QTL confirmation and (iv)
population specificity of the reported QTLs and their associated
markers. However, with the new advancement in marker technology and trait phenotyping and the greater need in crop plants
with improved ST, it is expected that more progress will be
made in developing new cultivars with improved ST in particular
via using marker-assisted breeding approaches. Furthermore,
once QTLs have been verified for use in MAS, efforts must be
made to clone and characterize important QTLs. Cloning of
QTLs conferring ST will not only enhance the functional understanding of the tolerance and the underlying genes and mechanisms (Salvi and Tuberosa 2005), but also provide breeders with
precise markers for both breeding purposes and exploitation of
allelic variations present in germplasm collections. The latter is
particularly crucial for further identification and characterization
of desirable genetic resources and enhancement of crop ST.

Conclusion and Future Prospects
Most modern cultivars of major crop species are highly or moderately sensitive to salt stress and thus do no perform well under
field saline conditions. Fortunately, genetic sources of ST have
been identified in most crop species, which could be utilized for
breeding purposes. However, most of the identified germplasms
with ST characteristics have been identified within the related
wild or feral species, which could not be utilized in breeding
programmes without inherent difficulties. The advent of molecular markers and mapping technology has promised opportunities
to identify genes or QTLs of interest for complex traits such as
ST and transfer them more precisely from unadapted genetic
backgrounds into modern cultivars via the process of MAS. One
of the advantages of MAS when using wild germplasm as
genetic resources is to reduce the problems associated with

linkage drag. With this promise in mind, considerable efforts
have been made and many genes or QTLs have been identified

Table 2: Improving salinity tolerance in different crop lines/varieties using marker-assisted selection
Crop

QTL
used

QTL donor
line/cultivar

Recipient
line/cultivar

Line/cultivar
developed

Durum wheat (Triticum
turgidum L.)

Nax1
and
Nax2

Line 149

Tamaroi

Durum wheat


Rice (Oryza sativa L.)

Saltol

FL378

BR11 or BR28

BR11

Tomato (Solanum
lycopersicum L.)

TG24

Solanum
pimpinellifolium
(wild tomato)

S. lycopersicum
(cultivated
tomato)

F3 population of
S. lycopersicum

Traits improved
Improved 25% yield by
enhancing Na+

exclusion from the
leaf blade
Higher yield under
saline conditions
Improved total fruit
weight under salinity

References
Munns et al. (2000)

Rahman et al. (2008)
Monforte et al. (1996)


Crop breeding for salt tolerance in the era of molecular markers

contributing to ST in different plant species. However, despite
such progress, currently, there are few examples of successful
development of cultivars or breeding lines with improved ST via
the use of molecular markers and MAS technology. This is in
sharp contrast to the extensive and efficient use of molecular
markers for improving simple traits, which are often controlled
by one or few genes with independent effects and free of environmental influence.
The limited use of markers for improving complex traits has
been attributable to various reasons as discussed in this article;
however, this does not mean that the marker technology will not
be useful for developing crops with improved ST. Theoretically,
it should be possible to use markers for improving complex traits
such as ST, assuming that efforts are made to identify reliable
QTLs and associated genetic markers. However, the development of reliable marker information for quantitative traits necessitates additional efforts, including: (i) Conducting mapping

experiments under field production conditions where all factors
affecting the expression of the quantitative trait of interest are
accounted for. Often QTL mapping experiments are conducted
under controlled greenhouse conditions, where the environment
is different from field conditions. For example, most experiments
to identify QTLs for ST have been conducted under greenhouse
conditions with little or no transpiration. Such settings would not
impose the kinds of stress that plants may experience under field
conditions, which certainly affect gene expression and QTL
identification. Furthermore, plants respond to various stresses in
a coordinated and interactive manner and cross-tolerance exists
against such stresses, which make the mechanisms much more
complex (Orsini et al. 2010). Under field saline conditions, there
are always other stresses that plants have to deal with and
respond to in order to survive or produce economic yield. Thus,
the identification of QTLs for ST under confined greenhouse
conditions may not be useful for developing plants with
improved ST under field conditions. At least the QTLs identified
under controlled conditions must be re-examined and confirmed
under field saline conditions before using them in markerassisted breeding. (ii) Repeating screening experiments in multiple environments to minimize the environmental effects on trait
expression and maximize the relationship between phenotype
and genotype (i.e. increasing heritability of the trait). Generally,
QTLs identified in multiple environments are more reliable. (iii)
Minimizing other environmental variation to increase the heritability of the trait, for example by increasing the number of replications in space and using larger population size. (iv) Breaking
complex traits into their simpler individual components and identifying QTLs and linked markers for such individual components, instead of studying the trait as a whole. For example, ST
is a developmentally regulated phenomenon, which differs with
changes in plant age and developmental stages. Tolerance at one
stage of plant development may not be correlated with tolerance
at other developmental stages or with the overall performance of
the plant during its life cycle. QTLs must be identified for

individual developmental stages as well as for individual physiological parameters contributing to ST. Pyramiding of such QTLs
may lead to the development of plants with improved ST.
Although the proposed approach seems challenging, it is certainly doable assuming devoted efforts and is expected to pave
the way for the use of marker technology for improving complex
traits such as ST. Furthermore, with the recent advances in genome sequencing, the development of highly polymorphic and
informative molecular markers such as single-nucleotide polymorphisms (SNPs), and high-throughput genotyping capabilities,

17

it is expected that the use of markers in large breeding populations will be streamlined which in turn will facilitate employing
MAS for crop breeding for improved ST. Moreover, as more
molecular markers and saturated maps are becoming available
and larger number of major and minor QTLs are identified for
ST, it may be more effective to improve crop ST via genomic
selection, that is selection solely based on the genotypes of all
markers associated with ST (Bernardo and Yu 2007, Heffner
et al. 2009, Jannink et al. 2010). Because genomic selection
employs complete data for all trait-associated markers as predictors of performance, it would provide a more accurate estimate/
prediction of the breeding value of individuals in the population
and thus may be more effective in improving crop ST.

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