American Journal of Plant Sciences, 2011, 2, 190-201
doi:10.4236/ajps.2011.22021 Published Online June 2011 (http://www.SciRP.org/journal/ajps)
Copyright © 2011 SciRes. AJPS
Molecular Mapping of QTLs for Drought Related
Traits at Seedling Stage under PEG Induced Stress
Conditions in Rice
Akkareddy Srividhya1#, Lakshminarayana R. Vemireddy1*,#, Puram Venkata Ramanarao1, Sakile
Sridhar1, Mudduluru Jayaprada1, Ghanta Anuradha1, Battiprolu Srilakshmi1, Hariprasad K. Reddy2,
Arramsetty Subramanyam Hariprasad3, Ebrahimali Abubackar Siddiq1
1Institute of Biotechnology, Acharya NG Ranga Agricultural University, Rajendranagar, Hyderabad, India; 2Department of Genetics
and Plant Breeding S. V. Agricultural College, Tirupati, India; 3Directorate of Rice Research, Rajendranagar, Hyderabad, India.
Email: *vlnreddi@gmail.com
Received February 15th, 2011; revised March 11th, 2011; accepted March 18th, 2011.
ABSTRACT
Differential response of seedling characteristics under water stress conditions is known to be associated with drought
resistance in rice and elucidation of its genetics could b e of help in breeding for tolerance to the stress. A recombinant
inbred population derived from the cross between a semi-dwarf variety IR64 and landrace INRC10192 was grown in
hydroponic culture and phenotyped for varied responses of seedlings to water deficit imposed by poly ethylene glycol
(PEG). The ratio between mean value of seedling trait under stress and control conditions was used for assessing
drought tolerance. In all 19 putative QTLs relating to five seedling traits viz., shoo t length, maximum root length, shoot
dry weight, root dry weight and root to shoot dry weight ratio under PEG induced stress conditio ns were id entified con -
firms that the traditional tall landraces as the one chosen for the study posses hitherto unexploited drought tolerant
genes and utiliza tion o f them as poten tial don ors in br eeding fo r yield en han cement wou ld be rewarding. They might be
useful for improving drought resistance of rice by marker assisted selection/breeding.
Keywords: Ory z a Sat iva L., QTL Mapping, RIL Population, Seedling Morphology, PEG, Hydroponic Culture
1. Introduction
Over one half of the world’s rice area is rainfed and
breeding for drought resistance has been the research
priority in these areas [1,2]. Many morpho-physiological
traits of seedlings have been reported to influence the
performance of the crop under rainfed upland condition.
Root and shoot systems, for instance, affect growth and
development of seedlings. In rice, several root character-
istics viz., root length, depth of rooting, root thickness
and root to shoot ratio are considered to play an impor-
tant role in resisting water deficit. Earlier studies showed
varieties with longer, thicker and bigger ro ot systems are
to be drought resistant and associated, in some cases,
with higher grain yield under drought [1,3,4]. As re-
ported by O’Toole (1982) [5] greater rooting depth and
density could result in more available soil water and
hence better resistance to moisture stress.
Molecular marker technology has now been found to
facilitate better understanding of the genetic basis of the
indices of tolerance, most of which are quantitatively
inherited. Quantitative trait loci (QTL) approach has
helped to identify QTL for the stress tolerance related
traits including length, weight and thickness of root and
shoot height, leaf rolling and osmotic adjustment under
hydroponics [6-8] and other artificially created stress
conditions [7,9-16]. The root-related characters have
recently been used in breeding for tolerance to the stress
[17,18] using marker assisted selection.
Although all such investigation enriched our under-
standing of plant response to water deficit, genetic mecha-
nisms underlying the expression of drought resistance are
poorly unders tood because of incons istency in the choice
of testing environ ments and cu ltiv ars, timing and sev erity
of the stress imposed and difficulties in measuring
root-related traits. In field grown experiments, screening
for responses of root-related traits to the stress is not easy
besides being time-consuming and imprecise. The Poly
ethylene glycol (PEG ) of higher molecular weight (4000 -
#These authors contributed equally to this work.
Molecular Mapping of QTLs for Drought Related Traits at Seedling Stage under PEG Induced Stress Conditions in Rice191
8000) is quite commonly used in hydroponics as an al-
ternative for judging the performance of plants against
water stress under field conditions [19]. Generally high
molecular weight PEG absorbed by the plants is accu-
mulated in roots and leaves results in osmotic adju stment
besides imposing water-de ficit conditions [16]. Although
water stress induced by the PEG-6000 develops faster in
creating an osmotic shock, the responses of plants to
such osmotic treatment is ind icative of the relative po ten-
tial of the different rice varieties to tolerate water stress
at physiological and biochemical level [20]. Reports of
Yoshida and Hasegawa (1982) [21] show response of root
related traits viz., overall size and maximum depth of the
system and individual root thickness in plants grown
under field and hydroponic condition to be positively
related to the level of drought resistance. Price et al. (1997)
[3] too confirmed that root-related traits of rice grown
hydroponically viz., maximum root length and adventi-
tious root thickness were related to resistance to water-
deficit in the field. Therefore, hydroponic culture has been
employed to study root related traits in the present study.
As of now, most reported drought-related QTL map-
ping experiments in rice has employed only five popula-
tions [7]. Many of the upland parents used in these
populations (e.g., CT9993-5-10-1-M and Azucena) are
not considered to be highly drought-tolerant in terms of
grain yield under severe drought conditions. Many tradi-
tional and improved cultivars from drought-prone areas
on the other hand are known to be tolerant to the stress
[22]. But they too have rarely been used as parents in
mapping studies. Recent studies at IRRI and elsewhere
suggest the possibilities of d etecting stress tolerance QTL
in parental sources not known to be tolerant [23,24].
Keeping the foregoing, the present study was initiated
with the objective of detecting hidden drought response
QTLs in mapping population derived from the cross in-
volving the primitive landrace INRC10192 which is not
known to possess drought tolerance and IR64 as the par-
ents. The mapping population consisting of 140 recom-
binant inbred lines derived from the cross was used to
assess the response of the lines and parents to water defi-
cit induced by PEG and map genetic regions associated
with seedling traits.
2. Materials and Methods
2.1. Choice of Parents and Development of
Mapping Population
The popular semi-dwarf high yielding variety IR64 was
used as female parent while INRC10192 a tall, lodging
prone, photosensitive, medium duration and long root
landrace accession from the Assam Rice Collection
(ARC), India as male parent. Recombinant inbred lines
(RILs) comprising 140 lines derived from the cross by
selfing and advancing to F7 generation at the Biotech-
nology Unit (BTU), ARI, Acharya N G Ranga Agricul-
tural University (ANGRAU), Hyderabad, India by Single
Seed Descent method f ormed the mapping pop ula ti on .
2. 2 . Phen otypic Evaluation
Approximately 150 seeds each of the 140 RILs along
with parents and IR20 and Moroberekan as drought sus-
ceptible and drought tolerant checks respectively, were
sown on moistened filter paper in petri dishes (5 cm di-
ameter and 2 cm depth) and kept in an incubator main-
tained at 30˚C for 48 h. The germinated seeds were re-
moved from the incubator and kept under room tempera-
ture (27˚C ± 1˚C) for three days. The seedlings were al-
lowed then to grow in Yoshida’s nutrient solution [25]
under greenhouse conditions for three days. The seed-
lings of each of the lines were evenly distributed in four
petri dishes, two of which for water deficit (stress) treat-
ment and two for control. The random complete block
design (RCBD) with two rep lications was followed. Wa-
ter deficit was created by using half-strength Yoshida’s
nutrient solution containing 15% PEG-6000 (W/W) with
osmotic potential (OP) of –2.36 to –2.95 bars at 25˚C -
30˚C, while the control was continued with normal nu-
trient solution. Five days later, OP level of the stress
treatment was increased to –4.04/–4.91 bars by replacing
15% with 20% PEG-6000 to the nutrient solution and
maintained for two weeks. Though this is considered to
be the critical concentration for early seedling stage
screening of rice for drought tolerance [16,26,27], the
seedlings were subjected to still higher stress level the
range being –6.15/–7.35 bars (PEG-6000 at 25% of nu-
trient solution) for four days. The nutrient solution was
replenished once a week in control; while for keeping the
water potential stable, the solution containing PEG was
changed on alternate days in the stress treatment. The pH
of both the treatments was adjusted to 5.0 by adding 1
mol/l HCl or NaOH solution ever y 24 hours. Response to
the treatment was observed 29 days after sowing (DAS).
Immediately after removing from nutrient solution, the
seedlings were thoroughly washed with distilled water
and blotted with tissue paper to remove excess water
before observing for root and shoot length (Figure 1).
The same root and shoot samples were used for measur-
ing root and shoot dry weights, after drying them at 70˚C
for 48 h [23,28]. For study of secondary traits related to
drought tolerance, observations were made on six seed-
lings per replication and averaged them under control (C)
and stress (S) conditions and of their relative parameters
(R) (Ratio of the parameter under stress to the control).
Standard procedures were followed for recording the
observations as follows: shoot length (SL)—length (cm)
Copyright © 2011 SciRes. AJPS
Molecular Mapping of QTLs for Drought Related Traits at Seedling Stage under PEG Induced Stress Conditions in Rice
192
Figure 1. Root and shoot pictures of parents (INRC10192
and IR64) and control (Azucena and MTU1061). The age of
the seedlings was 18 days.
from node/collar region to the tip of the shoot, maximum
root length (MRL)—length (cm) of the seminal root
(Seminal root is the longest root at early seedling stage),
shoot dry weight (SDW)—weight (mg) of shoot after
oven-drying at 70˚C for 48 h and for 24 h, root dry
weight (RDW)—weight (mg) of root after oven-drying at
70˚C for 48 h and root shoot weight ratio (RS)—ratio of
root dry weight to the shoot dry w e ight.
2.3. Construction of Linkage Map and QTL
Mapping
DNA was isolated from fresh leaf samples of tagged
plants using the modified CTAB method [29]. The PCR
was performed with 10 µl final volume containing 25 -
50 ng of genomic DNA, 10X buffer, 0.125 mM final
concentration of each dNTPs, 0.2 µM of each forward
and reverse primer and 1U of Biogene Taq DNA Poly-
merase. The PCR was set up with an initial denaturation
of 94˚C for 5 min, followed by 35 cycles of denaturation
at 94˚C for 45 secs, annealing at 55˚C for 45 secs, exten-
sion at 72˚C for 1 min, followed by the final extension of
72˚C for 10 min. PCR samples were run on a 3% agarose
gel containing ethidium bromide along with the marker
50 bp ladder (MBI Fermentas, Canada) at 5.3 V/cm
(BioRad Power Pack 300) for an hour in 0.5x Tris Ace-
tic acidEDTA (TAE) buffer. The resolved PCR bands
were documented using BioRad Molecular Imager Gel
Doc XR System. Linkage map was constructed using
MAPMAKER/EXP v.3. QTLs were identified using
Simple Interval Mapping (SIM) and Composite Interval
Mapping (CIM) methods of QTL Cartographer 2.5 [30]
(Wang et al., 2007). The significant threshold was esti-
mated by performing 1000 permutations of each meas-
urement (p < 0.05) using QTL cartographer [31].
3. Results
3.1. Phenotypic Performance
Under both control and stress conditions, the parents,
IR64 and INRC10192 manifested significant differences
in respect of all the traits studied, except RDW in the
control (Table 1). Significant differences in RDW and
RS were however observed between the two treatments
in the case of both the parents. In respect of SDW and
MRL, INRC10192 only showed significant differences
under the stress. Relative parameters measured under
stress revealed significant differences between parents
for MRL(R), RDW(R) and RS(R).
INRC10192 show ed higher mean values than IR 64 for
all the traits studied (Supl Table 1). Study of RILs under
controlled conditions revealed transgressive segregants
ranging from 48.5% (MRL) to 93.3% (RS), while under
stress it ranged from 49.4% (RDW) to 99.8% (RS). The
relative parameters showed the range to be between
69.4% (RDW) and 92.2% (RS). All the traits showed
continuous variation fitting well normal distribution ex-
cept relative SDW and RDW (Supl Table 1, Figure 2).
Those traits which are not distributed normally were
subjected to transformation using skew-normal interval
mapping method developed by Fernandez et al. (2007)
[32].
Correlation coefficients revealed that maximum root
length (MRL) under control had significant positive cor-
relation with shoot length and shoo t dry weig ht (Tab le 2 ),
while under stress it had highly significant positive cor-
relation with both SL and SDW. In contrast, MRL
showed significant negative correlation with RDW and
RS under stress. Root dry weight under control, had
strong significant positive asso ciation with SL and SDW,
but under stress, it had significant negative association
with SL, MRL and SDW. As expected, RS had strong
Table 1. Test of significance of the parents for shoot and
root traits and of their relative parameters measured in
control and stress treatments.
IR IN IR/IN IR/IN Rel. par.
Trait C/S C/S C S S
SL 0.19 0.55 0.02 0.01 0.37
MRL 0.73 0.02 0.01 0.05 0.03
SDW 0.06 0.03 0.04 0.01 0.22
RDW 0.05 0.01 0.20 0.01 0.02
RS 0.09 0.01 0.04 0.001 0.01
C-Control; S-Stress; Rel. par. = relative parameter. Note: Values in bold are
ignificant probabil ity levels, IR-IR64; IN-INRC10 1 92. s
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Molecular Mapping of QTLs for Drought Related Traits at Seedling Stage under PEG Induced Stress Conditions in Rice
Copyright © 2011 SciRes. AJPS
193
Figure 2. Phenotypic distribution of seedling traits in 140 RILs under greenhouse conditions; IN-INRC10192 and IR-IR64.
significant negative association with SL and SDW under
both control and stress conditions, respectively. Under
stress, still RS exhibited significant negative and positiv e
association with MRL and RDW, respectively. Identical
traits showed positive significant association, when cor-
related between the means of control and stress for all the
traits viz., SL, MRL, SDW, and RS, except RDW, which
showed negative correlation (highlighted as bold figures
in Table 2). Relative parameters measured under the
stress were negatively correlated with all the traits under
control and in contrast, with traits meas- ured under the
stress, showing significant positive correlation (highlighted
Molecular Mapping of QTLs for Drought Related Traits at Seedling Stage under PEG Induced Stress Conditions in Rice
194
as bold figures in Table 2).
3.2. Construction of Linkage Map and QTL
Mapping
Of 412 rice microsatellite primers used to screen the
parents, 113 found to be polymorphic and they are dis-
tributed throughout the rice genome. The linkage map
covered 1978.9 cM employing Kosambi mapping func-
tion, resulting in an averag e marker interval of 31.41 cm.
The linear order of microsatellite markers reported in the
present genetic map is not in total agreement with the
physical map.
Such observed discrepancies in the map distances are
most likely to occur on account of different parental
strains, number of markers, differences in the size and
type of mapping populations and levels of polymorphism.
Nevertheless, for exploratory mapping, resolution and
genome coverage of the present linkage map may be
adequate at least for some of the chromosomes to detect
QTLs relating to drought related traits. A total of 19 pu-
tative QTLs associated with the five seedling traits were
detected (Figure 3). Chromosomes 1 and 8 harbor most
of the QTLs. Phenotypic variance of the detected QTLs
ranged from 7.9% to 29.8%. For most of the QTLs the
increasing effect was contributed by the landrace
INRC10192 (68.4 %).
A single QTL designated as qsl1.1 on chromosome
1was identified for sho ot length under control con dition s.
It was located in the marker interval of RM1-RM495
with a LOD score of 4.24, explai ning 18. 4% of phenotypic
variance. The allele effect was contributed by INRC10192.
Two QTLs of minor effect qmrl3.1 and qmrl3.2 influ-
encing maximum root length on chromosome 3 were
identified only under control condition. They had same
LOD value of 2.52 and explained comparable phenotypic
variance 11.74% and 11.51% QTL. The increased allele
effect of these QTLs was contributed by INRC10192.
For shoot dry weight, in all four QTLs were identified,
of which three viz., qsdw2.1, qsdw2.2 and qsdw9.1 were
identified on chromosomes 2 and 9 under stress condi-
tions. The LOD score and phenotypic variance explained
by individual QTLs ranged from 2.51 to 3.03, and 18.7%
to 23.7%, respectively. One QTLs, qsdw1.1 identified on
chromosome 1 in the marker interval of RM1-RM495
with a LOD score of 3.48 explained a phenotypic vari-
ance of 13.69%. INRC10192 had allele effect for qsdw1.1,
qsdw2.1 and qsdw2.2, while IR64 contributed at qsdw9.1
locus.
Five QTLs for root dry weight were identified on three
chromosomes under the stress condition and for relative
parameter. Four QTLs, (qrdw1.1, qrdw1.2, qrdw8.1 and
qrdw8.2) mapped two each on chromosomes 1 and 8,
explained phenotypic variation ranging from 7.9 to
25.9% and LOD score in the range of 2.74 - 6.33. Three
QTLs (qrdw1.1, qrdw7.1 and qrdw8.2) were identified
for relative root dry weight with LOD score of 3.89 -
5.79 and phenotypic variation explaining 13.62% -
29.29%. Of these, two qrdw1.1 and qrdw8.2 were identi-
fied simultaneously for root dry weight under the stress
and for relative root dry weight measured under the stress.
IR64 contributed positive allele effect for qrdw1.1 and
qrdw1.2; while, for the remaining three QTLs, INRC10192
contributed favorable allele effect.
Seven QTLs were found associated with root shoot r a-
tio. Of them, five namely qrs1.1, qrs1.2, qrs2.1, qrs8.1
and qrs8.2 were detected under the stress condition,
while qrs1.2 and qrs8.2 were found as well for relative
root shoot ratio measured under the stress condition.
Further, qrs1.3 and qrs7.1 were also found for relative
RS under the stress. Besides, under the stress, the QTL
qrs8.1 was as well detected under control condition with
main effect. All these QTLs showed LOD score in the
Table 2. Correlation coefficients between the traits under control (C) and stress (S) conditions and of the relative parameters
(R) (* = p < 0.05; **= p < 0.01).
Copyright © 2011 SciRes. AJPS
Molecular Mapping of QTLs for Drought Related Traits at Seedling Stage under PEG Induced Stress Conditions in Rice195
Figure 3. Distribution of QTLs for drought related traits in the molecular linkage map of IR64/INRC10192. QTLs are indi-
cated right side of the linkage map. Names of the markers represented left side of the linkage map. Numbers in parenthesis
are relative genetic distances from one end of the chromosomes in centimorgans (cM).
range of 2.71 - 5.26 and explained phenotypic variance
ranging from 11.9% to 29.8%.
4. Discussion
Considering the fact that the parents used for identifying
the genomic regions/QTLs controlling drought tolerance
is very few and scope for exploiting traditional cultivars,
the present study was initiated to identify the genomic
regions related to drought tolerance from the cross of a
landrace INRC10192, not known for drought tolerance
and a semi dwarf variety IR64.
In the pr esent study, both the parents h ave been found
to differ in their response to the stress induced by PEG
with IR64 showing significantly low response in respect
of SL and MRL while INRC10192 showing significant
difference for MRL only (Table 1). In agreement with
the findings of Cui et al. (2008) [16], who have reported
water deficit to inhibit shoot characteristics (plant height
and shoot fresh weight) while promoting that of root
(maximum root length, root fresh weight, root number
and root/shoot ratio) in a hydroponic experiment, in the
present study also showed more decrease in SL and SDW
and increase in MRL, RDW and RS under the stress as
compared to the response under control condition. The
relative parameters of measured traits showed wide
variation, ranging far from 1 (1 = similar performance
under control and stress conditions) in both the directions
(Supl Table 1). For instance, relative MRL ranged from
0.26 to 1.74, while relative RDW from 0.23 to 5.79,
suggesting either inhibition or enhancement of root
growth by water deficit. Varied levels of response to the
stress was observed among the lines could be attributed
to their genotype. Only three lines showed higher maxi-
mum root length than Moroberekan (data not shown)
under the stress. Transgressive segregants observed in
both the directions among the measured traits in the RILs
(Supl Table 1 and Figure 2) indicate the hidden variabil-
ity present in the landrace could be used for broadening
the cultivated gen e poo l by reintroduction.
Significant correlations observed among most of the
trait pairs studied, suggest the parameters of shoot and
root morphology measured in this population were in-
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Molecular Mapping of QTLs for Drought Related Traits at Seedling Stage under PEG Induced Stress Conditions in Rice
196
ter-related. SL, MRL, and SDW showing positive and
significant correlation with each other under control and
stress conditions indicate indirect selection of one by the
other trait possible. These results are in conformity with
the earlier findings [10,33,34]. Whereas under control
condition, MRL was positively correlated with RDW,
while under the stress it showed negative correlation with
RDW. These results are in agreement with those of Asch
et al. (2005) [33], on the basis of “quantification of the
effects of different levels of drought stress on dry matter
partitioning and root development in rice”. They con-
cluded assimilate partitioning between root and shoot
was affected under low moisture stress conditions but not
to affect under severe stress by drastically decreasing the
partitioning to the root as in the present study. Thus MRL
showed negative correlation with RDW under stress.
Shoot length and shoot dry weight show significant
positive association with many of the traits and selection
based on these two could greatly help simultaneous se-
lection of other traits governing drought tolerance. Since
the root trait MRL has been found to be significant and
positively correlated with SL and SDW under both con-
trol and stress conditions selection based on the shoot
traits would enable selection of genotypes with MRL,
without taking the trouble of observing the roots as re-
ported by Mane et al. (2003) and Zheng et al. (2003)
[14,35].
Relative parameters used for different indices or
drought tolerance under stress showed significant nega-
tive associations with their respective characters under
control, indicating that the lines that performed under
control need not to do so under the stress. On the con-
trary relative parameters measured under the stress had
strong positive and significant correlation with traits
measured.
The region RM1-RM495 on chromosome 1 found in
the present study to harbor five QTLs for shoot and root
related traits which has been reported by many earlier
workers. For instance, Li et al. (2005) [13] have repo rted
QTLs for root thickness, root number and root dry
weight, while length of mesocotyl by Redona and Mack-
ill (1996) [36] in the same region. Further, Xu et al.
(2004) [37] and Price et al. (2000) [38] have reported
QTLs for PH and root number, respectively in the same
region. Cui et al. (2008) [16] have identified a QTLs
cluster in the same region for plant height and shoot fresh
weight under well watered conditions. Interestingly, in
the present study also under well-watered conditions,
QTLs for shoot length and shoot dry weight have been
mapped to the same region. Thus, this region appears to
be a good candidate for breeding for drought tolerance
through MAS as well as for fine mapping and positional
cloning of the un derlying ge ne(s).
Two QTLs for shoot dry weigh t under stress condition
have been located at the interval RM106-RM5897 on
chromosome 2. In a study by Cui et al. (2008) [16] the
region near RM262 on the same chromosome has been
detected to harbor QTL for shoot fresh weight. However,
Xu et al. (2001) [39] have detected a QTL for root
weight in the same region. The vicinity of RM570-
RM251 on chromosome 3 was observed to harbor two
QTLs for MRL under control conditions. The region,
RM38-RM331 on chromosome 8 was observed to have
effects on RDW under stress conditions and RS under
control conditions and of its relative parameter measured
under stress. Another region i.e., RM404-RM547 on
chromosome 8 controlled RDW and RS under stress
conditions and of their relative parameters measured un-
der stress. It is noteworthy that alleles at 5 of 6 regions
were contributed by the parent INRC10192 (Table 3).
Among six intervals on four chromosomes identified
to harbor multiple QTLs, two interv als (RM1-RM495 on
chromosome 1 and RM38-RM331 on chromosome 5)
were found to affect related traits under the two water
supply conditions and one interval (RM570-RM251 on
chromosome 3) to affect traits under well watered condi-
tions. Three intervals (RM493-RM302 on chromosome 1,
RM106-RM5897 on chromosome 2 and RM404-RM547
on chromosome 8) were observed to be water sup-
ply-specific regions and had effects only under stress
conditions, suggesting that water supply-specific regions
or QTLs might be closely associated with the responses
of lines to water deficit. Particularly, this also suggests
that water deficit promoted the expression of QTLs lo-
cated in these regions.
It is assumed that inductive expression of new genes
would permit adaptation to stresses. Several studies have
documented that gene expression is induced by stresses
[40-42]. For instance, Rabbani et al. (2003) [42] have
found 62 genes were induced by drought in rice. Salek-
deh et al. (2002) [43] have shown concentrations of sev-
eral leaf proteins have been increased significantly dur-
ing drought and declined on re-watering. Genes induced
in drought stress generally involved in protection of cells
from water deficit by producing metabolic proteins and
regulation of genes for signal transduction [44]. Very
recently, Rabello et al. (2008) [45] identified drought
responsive genes in roots of upland rice and observed
that the genes exclusively expressed in the tolerant
genotypes were related to the maintenance of turgor and
cell integrity. Hence it can be interpreted that QTLs de-
tected only under drought or well-watered conditions
perhaps involved in the responses of plants to stress.
Some of the candidate genes controlling drought stress
were identified based on previous reports in the marker
intrval of RM1 and RM495 on chromosome1 which e
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Molecular Mapping of QTLs for Drought Related Traits at Seedling Stage under PEG Induced Stress Conditions in Rice
Copyright © 2011 SciRes. AJPS
197
Table 3. QTLs for drought related traits and of the relative parameters under stress (PEG) and control conditions.
Chr, refers to Chromosome number. LOD, refers to log10-Likelihood value PVE, Phenotypic variance explained by single QTL. a0, Additive effect. Al.ef.,
Allele effect of substituting a single allele from one parent to another. Positive values show that allelic contribution is from IR64 and negative values from
INRC10192. asignificant only in composite interval mapping. bsignificant only in simple interval mapping. *Repeated/Stable QTLs across control/stress treat-
ments. P-Pos ition of the QTL fr o m left flanking marker in cM.
harbours important QTLs for SL, SDW, RDW and RS
(Suppl Table 2).
Related traits are often due to pleiotropic effect of a
gene(s) or QTLs, which may enable selection for a com-
plex trait via an easily observable related trait. In the
present study, six loci distributed over chromosomes 1, 2,
3 and 8 have been found to harbor multiple QTLs affect-
ing the same or different traits (Ta ble 4). The number of
QTLs in each of the clusters ranges from 2 to 5.
Out of 24 QTLs detected, only five have been identi-
fied as stable (Table 3), while the remaining have been
detected either under stress (10 QTLs) or control (7
QTLs) conditions only. Among these five stable QTLs
also, only one QTL viz., qrs8.1 has been identified under
control as well as stress conditions, while the remaining
four QTLs viz., qrdw1.1, qrdw8.2, qrs1.2 and qrs8.2 for
traits measured under stress and of their relative parame-
ters measured under the stress. Very low percentage of
common (stable) QTLs detected across water supply con-
ditions is in agreement with the significant responses of
RILs to water deficit strong ly suggesting QTLs detection
is depend on specific environment and water deficit to
induce or inhibit some new genes to express simultane-
ously [13,16]. This lower coincidence of QTLs across
two water regimes has as well been reported by Ka-
moshita et al. (2002a and 2002b) [12,46]. They could
find only two stable QTLs among 31 detected for seven
traits in two experiments with different sowing dates
under anaerobic conditions, suggesting a large effect
of the phenotyping environment as defined by tempera-
ture and solar radiation on QTsL identification for root
traits. Further, Zhang et al. (2001b) [47] showed that
QTLs and epistatic loci for seminal root length detected
in solution culture were different from those detected in
paper culture and revealed a different genetic system
responsible for seminal root growth under different water
supply conditio ns.
Recently, MacMillan et al. (2006) [48] mapped QTL
for six root- and shoot-related traits in four treatment
environments (a control, low light, low soil nitrogen and
low soil water), and most QTLs for an iden tical trait in th e
four environments were different. Generally, it is consid
ered that QTLs × environment interaction is an important
Table 4. QTL clusters identified for shoot and root related
traits.
S.No.Marker interval Chr Traits No. of QTLs
1 RM1-RM495 1
SL, SDW,
RDW(2), RS 5
2 RM493-RM3021 RS(3) 3
3 RM106-RM58972 SDW(2) 2
4 RM570-RM2513 MRL(2) 2
5 RM38-RM331 8 RDW, RS(2) 3
6 RM404-RM5478 RDW(2),
RS(2) 4
Values in parenthesis indicates no. of QTLs for the respective traits.
Molecular Mapping of QTLs for Drought Related Traits at Seedling Stage under PEG Induced Stress Conditions in Rice
198
component for genetic determination of root growth
[13,48]. Similar results were observed by Zheng et al.
(2003) [14], who used flooding and upland as different
water supply conditions, and by Li et al. (2005) [13],
who carried out phenotype scoring under lowland
(flooded), upland (aerobic soil) and polyvinyl chloride
(PVC)-pipe aerobic conditions. The differences in the
experimental conditions and mapping populations em-
ployed often result in marked differences in resistance
traits and consistency of QTLs [12].
No QTL was detected for some of the traits like shoot
length and maximum root length under stress cond itions,
although segregation for these traits was obvious in the
RILs. Earlier studies have found epistasis and G × E in-
teractions plays major role in determining yield and its
components and most of the phenology traits, especially
under drought conditions [49-52]. This finding probably
explains why no QTL could be detected for such traits. In
the present study, no epistatic interaction was found for
shoot length and maximu m root length ind icating th e G ×
E play crucial role to determine QTLs for these traits.
Keeping in view the objective of the present investig a-
tion i.e., discovering new QTLs of promise, it is impor-
tant to identify QTLs with enhancing favorable alleles
from the landrace for introducing in the crop improve-
ment program. Though the landrace is agronomically
unattractive, the results suggested to con tribute favorable
alleles for 65.86% of the QTLs, by enhancing the level of
tolerance to drought through various seedling indices.
These findings are in agreement with those of earlier
workers many who had detected QTLs with trait value
enhancing alleles in agronomically phenotypically infe-
rior parental sources in rice [53-55]. McCouch and Do-
erge (1995) [56] have identified more than 50% of the
QTLs for root morphology in the RIL population of the
cross CO39/ Moroberekan and all the alleles that had
positive effect were from Moroberekan, the japonica
donor parent. It is thus possible to detect more number of
novel and major QTLs with favorable alleles in mapping
populations derived of crosses involving primitive land-
races.
It is encouraging that a high percentage of transgres-
sive segregants could be detected for nearly all the
drought tolerance related traits in the mapping popu lation
involving a pa rent i.e., the landrace INRC10192 which is
not known for its superior agronomic traits. Recovery,
however, of useful transgressive segregants in such
population could be due to result of interaction between
the trait enhancing alleles of the landrace INRC10192
with those of the high yielding variety IR64. The ge-
nomic regions harboring drought tolerant QTLs could be
of great targets to identify the candidate genes by fine-
mapping. However, further investigations are required to
identify the promising candidate genes underlying the
major drought tolerant QTLs and the tightly linked or
gene specific markers can be used for development of
drought resistance rice cultivars through marker-assisted
selection. Pyramiding of the stress tolerance QTL/gene(s)
coupled with genes governing high yield might help to
evolve high yielding varieties ideally suited to drought
prone rainfed rice ecologies.
5 Acknowledgements
We thank DRR for maintaining the rice material under
National Professors Project. Thanks to the Biotechnology
unit, ANGRAU for supporting the research work and
fellowship supported by CSIR, New Delhi to AS.
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