CROP SCIENCE, VOL. 52, JULY– AUGUST 2012 1583
RESEARCH
A
biotic stresses are becoming the major limiting factors for
crop production especially under globally changing climatic
conditions. Among them, drought and salinity are considered as
the two of the major abiotic stresses (Brown and Halwei, 1998;
Pandey et al., 2000). Drought is a serious problem in rainfed rice
area, which occupies 50% of total rice acreage in the world. In
Identiication of Genetic Overlaps for Salt
and Drought Tolerance Using Simple Sequence
Repeat Markers on an Advanced Backcross
Population in Rice
Yun Wang, Jinping Zang, Yong Sun, Jauhar Ali, Jianlong Xu,* and Zhikang Li
ABSTRACT
Salinity and drought are two of the major
abiotic stresses that affect rice (Oryza sativa
L.) production especially in Asia. Quantitative
trait loci (QTL) for salt tolerance (ST) at
seedling stage and drought tolerance (DT) at
reproductive stage were identiied using 77
BC
2
F
8
advanced backcross introgression lines
(ILs) derived from a cross of Teqing × Binam in
Teqing background. Ten ST QTL were identiied
governing days to seedlings survival (DSS),
score on salt toxicity symptoms on leaves (SST),
shoot K
+
concentration (SKC), and shoot Na
+
concentration (SNC) at seedling stage, and 23
QTL were identiied under reproductive stage
drought and irrigated conditions for panicle
number per plant (PN), thousand grain weight
(TGW), seed fertility (SF), plant height (PH), and
grain yield per plant (GYP). Most QTL detected at
reproductive stage showed obvious differential
expression to drought stress. In addition,
another eight QTL were detected by trait ratio
of the stress to the irrigation; the alleles at all
loci except QSf3 showed increasing trait values
to be associated with Binam, indicating Binam
alleles at these loci could improve DT under
drought stress. Upon comparison of identiied
ST and DT QTL we found 14 QTL shared the
same genome regions with similar gene actions,
clearly suggesting that genetic overlap existed
between the two abiotic stress tolerances.
Pyramiding of favorable alleles from Binam into
Teqing background should allow us to develop
superior ILs with higher levels of ST and DT.
Y. Wang, Shenyang Agricultural Univ. /Key Lab. for Northern Japonica
Rice Genetics and Breeding of Ministry of Education, Shenyang
110866, China; Y. Wang, J. Zang, Y. Sun, J. Xu, and Z. Li, Institute
of Crop Sciences/National Key Facility for Crop Gene Resources and
Genetic Improvement, Chinese Academy of Agricultural Sciences, 12
South Zhong-Guan-Cun Street, Beijing 100081, China; J. Ali and Z.
Li, International Rice Research Institute, DAPO Box 7777, Metro
Manila, Philippines. Yun Wang and Jinping Zang equally contributed
to this work. Received 1 Dec. 2011. *Corresponding author (xujlcaas@
yahoo.com.cn or xujl@caas.net.cn).
Abbreviations: DSS, days to seedling survival; DT, drought tolerance;
GYP, grain yield per plant; IL, introgression line; MAS, marker-assisted
selection; PH, plant height; PN, panicle number per plant; QTL,
quantitative trait loci/locus; RGYP, ratio of grain yield per plant under
drought stress to control condition; RPN, ratio of panicle number
per plant under drought stress to control condition; RSF, ratio of seed
fertility under drought stress to control condition; RTGW, ratio of
thousand grain weight under drought stress to control condition; SF,
seed fertility; SGYP, grain yield per plant under drought stress condition;
SKC, shoot K
+
concentration; SNC, shoot Na
+
concentration; SSF, seed
fertility under drought stress condition; SSR, simple sequence repeat;
SST, score on salt toxicity symptoms on leaves; ST, salt tolerance;
STGW, thousand grain weight under drought stress condition; TGW,
thousand grain weight.
Published in Crop Sci. 52:1583–1592 (2012).
doi: 10.2135/cropsci2011.12.0628
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