QTL mapping of drought-tolerance-related traits of wheat see

c Indian Academy of Sciences

RESEARCH ARTICLE

Conditional and unconditional QTL mapping

of drought-tolerance-related traits of wheat seedling using two

related RIL populations

HONG ZHANG1,2,FA CUI1,3,LIN WANG4,JUN LI1,ANMING DING1,CHUNHUA ZHAO1,YINGUANG BAO1,

QIUPING YANG1and HONGGANG WANG1?

1State Key Laboratory of Crop Biology,Shandong Key Laboratory of Crop Biology,Taian Subcenter of National Wheat Improvement Center,College of Agronomy,Shandong Agricultural University,Taian271018,People’s Republic of China 2Department of Agronomy,Dezhou University,Dezhou253023,People’s Republic of China 3Center for Agricultural Resources Research,Institute of Genetics and Developmental Biology,Chinese Academy

of Sciences,Shijiazhuang,050021,Hebei,People’s Republic of China

4Municipal Academy of Agricultural Sciences,Jining272031,Shandong,People’s Republic of China

Abstract

For discovering the quantitative trait loci(QTLs)contributing to early seedling growth and drought tolerance during germi-nation,conditional and unconditional analyses of12traits of wheat seedlings:coleoptile length,seedling height,longest root length,root number,seedling fresh weight,stem and leaves fresh weight,root fresh weight,seedling dry weight,stem and leaves dry weight,root dry weight,root to shoot fresh weight ratio,root-to-shoot dry weight ratio,were conducted under two water conditions using two F8:9recombinant inbred line(RIL)populations.The results of unconditional analysis are as follows:88QTLs accounting for3.33–77.01%of the phenotypic variations were detected on chromosomes1A,1B,1D,2A, 2B,2D,3A,3B,4A,4B,4D,5A,5B,5D,6A,6B,6D,7A,7B and7D.Among these QTLs,19were main-effect QTLs with

a contribution rate greater than10%.The results of the conditional QTL analysis of12traits under osmotic stress on nor-

mal water conditions were as follows:altogether22QTLs concerned with drought tolerance were detected on chromosomes 1B,2A,2B,3B,4A,5D,6A,6D,7B,and7D.Of these QTLs,six were main-effect QTLs.These22QTLs were all special loci directly concerned with drought tolerance and most of them could not be detected by unconditional analysis.The?nding of these QTLs has an important signi?cance for?ne-mapping technique,map-based cloning,and molecular marker-assisted selection of early seedling traits,such as growth and drought tolerance.

[Zhang H.,Cui F.,Wang L.,Li J.,Ding A.,Zhao C.,Bao Y.,Yang Q.and Wang H.2013Conditional and unconditional QTL mapping of drought-tolerance-related traits of wheat seedling using two related RIL populations.J.Genet.92,xx–xx]

Introduction

Seed germination and early seedling growth are considered the most critical stages for wheat establishment,especially under stress(Blum1996).The improvement of drought toler-ance of wheat seedlings can overcome the in?uence of water in the soil,ensure both the basic seedling number and estab-lishment of the photosynthetic population,and provide a solid base for obtaining high and stable yield.Therefore,the drought tolerance during seed germination and early seedling growth is an important trait that should not be neglected. Drought tolerance is particularly complex,controlled by ?For correspondence.E-mail:hgwang@af1175104b35eefdc8d333f3.multiple genes,with each gene having only a relatively small effect.The conventional method for identi?cation of drought tolerance has been the yield obtained under drought conditions(Sio-Se Mardeh et al.2006;Atefeh et al.2011). This method involves a complex process,the workload is heavy and the ef?ciency is low.High-molecular-mass polyethylene glycol(PEG)has been widely used to mimic osmotic stress in culture solutions(Almansouri et al.2001), because this approach avoids much of the environmen-tal noise associated with?eld experiments and induces a plant response similar to that induced by natural drought, for example causing a depression in both seed germination and growth of the root and shoots(Blum et al.1980;Dhanda et al.2004;Mujtaba et al.2005).

Keywords.drought tolerance of wheat seedling;unconditional QTL;conditional QTL.

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Hong Zhang et al.

The quantitative trait loci(QTL)mapping approach (Collard et al.2005)has been successfully applied as a tool for the genetic analysis of numerous important agronomi-cal traits(Sourdille et al.1996,2000;Perretant et al.2000; Borner et al.2002;Lohwasser et al.2005),disease toler-ance(Nelson et al.1997;Anderson et al.2001;Simón et al. 2004;Faris and Friesen2005;Schmolke et al.2005),and abi-otic stress tolerance(Galiba et al.2005;Bálint et al.2007) in wheat.Zhu(1995)introduced the new methodology for conditional genetic analysis considering the developmental behaviour of traits.Based on this methodology,it is possi-ble to reveal that the gene expression for a complex trait may be contributed by its different causal genes expression at dif-ferent levels.Multivariate conditional analysis can estimate the conditional phenotypic values of a target trait given the component trait,through two steps.First,conditional vari-ance components of the conditional distribution of target trait given the component trait are estimated,which is indepen-dent of the component trait.Then,the proportion of variance of conditional target random genetic effects to unconditional target trait genetic effects is calculated and the contribution ratio can be used to measure the contribution of the compo-nent trait to the target trait(Zhu1995;Wen and Zhu2005). This method has been widely used to identify QTL expressed at certain stages of the life cycle(Zhu1995;Yan et al. 1998a,b;Cao et al.2001;Atchley and Zhu1997)or anal-yse contributions of component traits to a complex trait(Guo et al.2005;Liu et al.2008;Cui et al.2011,2012).Recently, this method was proposed for analysing the in?uence on traits of different agronomic measures and discovering spe-cial QTL that are preferentially expressed in stress environ-ments,as opposed to unstressed environments.Austin and Lee(1998)and Jiang et al.(2008)used this method to deter-mine those genes that are only expressed in low nitrogen stress environments.Until now,there is no report regarding the conditional analysis method to detect QTLs that are only expressed in drought-stress conditions.

In this study,we carried out unconditional and conditional analyses of the traits of wheat seedlings using two related recombinant inbred line(RIL)populations to dissect the net QTL expression under two water conditions and examined the speci?c expression of traits in wheat seedlings subjected to drought stress.Our study sought to understand the mech-anism of differential expression of genes affecting the traits of wheat seedlings under different water conditions and to provide an insight into the genetic basis of drought toler-ance.This approach is very signi?cant for genetic studies of drought tolerance and breeding new varieties of wheat.

Materials and methods

Experimental material

Two F8:9RIL populations derived from crosses between three common Chinese wheat varieties,namely,between Weimai8and Luohan2(WL);and between Weimai8and Yannong19(WY),comprising229(seven lines are missed) and302(11lines are missed)lines,respectively,were used in the present study.Weimai8is a drought susceptible vari-ety,and it was released by the Weifang Municipal Academy of Agricultural Sciences,Shandong,China,in2003;Luo-han2is a drought resistance variety,and it was released by the Crop Research Institute,Luoyang Municipal Academy of Agricultural Sciences,Henan,China,in2001;Yannong19is a save-water variety,and it was released by the Yantai Muni-cipal Academy of Agricultural Sciences,Shandong,China, in2001.

Introduction of the genetic map

Various molecular markers,including genomic simple sequence repeats(G-SSR),expressed sequence tag-SSR (EST-SSR),inter-simple sequence repeats(ISSR),sequence-tagged sites(STS),sequence-related ampli?ed polymor-phism(SRAP),and randomly ampli?ed polymorphic DNA (RAPD),were used to genotype the three parents and their derived lines.The genetic map deduced from the two popula-tions was constructed in2010in our laboratory.The genetic map established using the WY population consisted of338 loci distributed in27linkage groups with six linkage gaps, and it covered3010.70cM of the whole genome,with an average distance of8.45cM between adjacent loci(Cui et al.2011).The genetic map constructed based on the WL population included344loci on the wheat chromosomes and spanned2855.5cM,with an average density of one marker per8.30cM.There were six linkage gaps with linkage dis-tances of50cM.The distribution of markers ranged from45 on chromosome4A to three on chromosomes4D and7D. Osmotic stress tests

One hundred seeds per RIL and their parents were packed in gauze,dipped in3%H2O2for10min to sterilize,then washed2–3times using pure water,and initiated shoot for one day(24h)at25?C.Sixty growth-coincident seeds were picked and uniformly placed in six beakers(6cm wide) spread over two layers of?lter paper,with10grains in every beaker.Subsequently,5mL of10%PEG-6000solution or pure water was added to three beakers each.All the beakers were placed in a plastic box,covered with a thin plastic?lm, and cultured at25?C in the dark for three days.On the fourth day,5mL of water was added to every beaker with concur-rent illumination.On the eighth day,?ve growth-coincident plants were picked out from every beaker to measure coleop-tile length(CL),seedling height(SH),longest root length (RL),root number(RN),seedling fresh weight(SFW),stem and leaves fresh weight(SLFW),and root fresh weight (RFW).The seedlings were placed in an oven for20min at100?C,and then dried to constant weight at80?C.The following parameters were subsequently measured:seedling dry weight(SDW),stem and leaves dry weight(SLDW), and root dry weight(RDW).Then,the root to shoot fresh

Journal of Genetics V ol.92,No.2,August2013

QTL mapping of drought-tolerance-related traits in wheat

weight ratio(RSFWR)and the root to shoot dry weight ratio

(RSDWR)were calculated.

QTL analysis

Statistical analysis of the phenotypic data from the two RIL

populations was carried out using the software SPSS13.0

(SPSS,Chicago,USA).If both absolute skewness and kurto-

sis were less than1.0,the trait was assumed to follow a nor-

mal distribution in the RIL population.The estimated broad-

sense heritability of the corresponding traits was calculated

using the formula h2=σ2G/(σ2G+σ2e),whereσ2G is the genetic variance andσ2e is the experimental error.The QTL

screening was conducted using inclusive composite interval

mapping by IciMapping3.0based on the stepwise regres-

sion of the simultaneous consideration of all marker-related

information(Li et al.2007;af1175104b35eefdc8d333f3/).The

missing phenotype was deleted using the‘deletion’com-

mand.The walking speed chosen for all the QTLs was

1.0cM,and the probability in the stepwise regression was

0.001.The threshold logarithms of odds ratio(LOD)scores

were calculated using1000permutations,the type1error

being0.05.An LOD score of2.5was set as a threshold for

declaring the presence of a QTL.However,we ignored the

QTLs with LOD values<2.5to render the QTLs reported

herein authentic and reliable.Conditional genetic analysis

was conducted based on the phenotypic mean values of12

traits,which were obtained by the method described by Zhu

(1995),observed in wheat seedlings grown under osmotic

stress conditioned on each of the corresponding trait in plants

grown under normal water condition by software QGAS-

tation1.0(Zhu1995).Then,the conditional QTL screen-

ing was conducted using conditional phenotypic value of12

traits by IciMapping3.0as mentioned above.The assign-

ment of a QTL name was based on the following rules:itali-

cized uppercase‘Q’denotes QTL;letters following it before

the?rst period are the abbreviations of the corresponding

trait;the next uppercase letters before the second period indi-

cate the population in which the corresponding QTL was

detected;next,a numeral plus an uppercase letter,‘A,’‘B,’

or‘D,’indicate the wheat chromosome on which the corre-

sponding QTL was detected;the last number after the third

period denote different QTLs for the same trait on the same

chromosome.

Results

Analysis of phenotypic data

The?nal12traits for the two RIL populations and their par-

ents under the two water conditions are shown in table1.

The results of analysis of variance(ANOV A)showed that

the variance for treatment effects on CL of three parents was

signi?cant at P<0.01;the variance for treatment effects

on CL showed signi?cance at P<0.05in WY population,but nonsigni?cant in WL.The other investigated traits were signi?cant at the P<0.01level under the two water condi-tions among the three parents,as also in the two populations (table1).In both mapping populations,CL,RL,RN,SFW and SDW showed a good?t to normal distribution under the two water conditions.Phenotypic distributions of SH,SFW, SLFW,RFW,SLDW,RDW,RSFWR and RSDWR showed inconsistency over population or treatment,either normal or non-normal,indicating that they were in?uenced by the treat-ment to some extent.Strong transgressing segregations were observed for each trait under both osmotic stress and nor-mal water conditions,with some lines being bigger than the bigger parent or smaller than the smaller parent in WY and WL,respectively,indicating that alleles with positive effects are distributed among the parents.The estimated broad-sense heritabilities of the12seedling-related traits ranged from 24.52%to87.66%.Of these,CL had the highest heritabil-ity in both populations,next to RN,RSFWR,and RSDWR; further,SFW,SLFW,and RFW had the lowest heritabil-ity,next to SH,RDW,SLDW and SDW.Every trait seg-regated continuously in WY and WL,indicating that these traits were all typical quantitative traits controlled by a few minor genes and that the data were suitable for QTL analysis (?gure1).

A preliminary analysis indicated that the12traits involved in the experiments under two different water conditions in the two populations had a very signi?cantly positive correlation (table2).Correlation coef?cients ranged from0.485–0.886, and the consistency was very high in the two populations. The relativity of CL was the highest,with correlation coef-?cients of0.88and0.89,respectively,in the WY and WL populations.Second,the correlation coef?cients of SH,RN, SFW,RFW,RDW,and so on were greater than6.00in the two populations.The correlation coef?cients of RL,SLFW, SDW,SLDW,RSFWR,RSDWR,and so on were smaller. Larger correlation coef?cients indicated a smaller in?uence from osmotic stress.The correlations of all the traits under two water conditions is most signi?cant,so we can remove the effect derived from traits present under normal water con-ditions by conditional QTL analysis and examine the speci?c expression of traits in wheat seedlings subjected to drought stress.

Unconditional QTL mapping of traits in wheat seedlings

Up to88QTLs distributed throughout the20wheat chromo-somes,except for the chromosome3D,were identi?ed by unconditional QTL analysis for12traits of wheat seedlings (table3).Together,these QTLs explained3.32–77.01%of the phenotypic variation in the inpidual traits.Further,16 QTLs were detected under both water conditions,only38 QTLs under normal water condition and only34QTLs under osmotic stress.In WY and WL populations,48and40QTLs were detected respectively.The additive effects of18and 30QTLs observed in the WY population respectively came from Weimai8made as female parent and Yannong19

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Hong Zhang et al.

T a b l e 1.P h e n o t y p i c v a l u e s f o r 12s e e d l i n g t r a i t s o f t h r e e p a r e n t s a n d t h e t w o R I L p o p u l a t i o n s u n d e r t w o w a t e r c o n d i t i o n s .

T r a i t (h 2%)P a r e n t s W Y c

W L (P v a l u e )a T r e a t b W e i m a i 8e

Y a n n o n g 19e L u o h a n 2e M e a n e

S t d d M i n –m a x

S k e w n e s s K u r t o s i s M e a n e S t d M i n –m a x

S k e w n e s s K u r t o s i s

C L (c m )(87.66/79.45)C 3.15a A 2.74a A 2.82a A 2.62a A 0.401.65–3.860.350.172.80a A 0.381.75–3.88?0.11?0.28(0.03/0.01)T 3.46b B 3.21b B 3.46b B 2.54b A 0.391.79–5.590.650.522.83a A 0.411.74–3.860.03?0.38S H (c m )(37.92/39.86)C 11.27a A 10.89a A 12.58a A 10.24a A 1.466.24–14.87?0.070.3112.69a A 1.189.17–16.57?1.280.09(0.85/0.65)T 8.90b B 8.58b B 10.33b B 8.35b B 1.284.35–11.32?0.130.0811.21b B 1.297.66–14.4?0.330.11R L (c m )(31.91/34.35)C 10.57a A 8.64a A 9.19a A 7.66a A 1.986.24–14.87?0.04?0.429.31a A 1.794.47–14.060.08?0.27(0.40/0.80)T 8.02b B 6.16b B 9.35b B 5.83b B 1.132.91–8.820.26?0.357.48b B 1.293.43–10.970.11?0.06R N (67.25/68.10)C 3.00a A 4.60a A 4.20a A 4.71a A 0.553.3–6.1?0.27?0.085.37a A 0.483.9–6.8?0.010.30(0.01/0.02)T 3.60b B 5.40b B 5.80b B 4.87b B 0.493.4–5.9?0.440.705.57b B 0.563.8–7.30.120.24S F W (m g )(34.46/24.52)C 121.58a A 121.68a A 163.14a A 100.86a A 19.8645.54–166.120.180.53145.66a A 19.9093.31–205.410.940.18(0.84/0.51)T 68.89b B 84.05b B 116.90b B 76.35b B 14.3141.21–125.730.300.72110.73b B 16.8261.43–164.800.360.36S L F W (m g )(42.57/27.32)C 74.64a A 79.60a A 98.2a A 64.34a A 11.4225.35–86.12?0.04?0.0489.53a A 12.4060.21–145.500.581.14(0.89/0.62)T 44.21b B 54.56b B 65.18b B 51.51b B 8.9618.65–68.690.110.1170.39b B 10.9530.14–108.310.000.46R F W (m g )(39.49/28.75)C 46.94a A 42.08a A 64.94a A 36.48a A 10.0911.15–83.320.350.3556.31a A 11.5828.34–127.320.574.18(0.809/0.402)T 24.68b B 29.49b B 51.78b B 24.83b B 6.7910.43–75.210.671.5040.34b B 8.3717.13–79.430.151.22S

D W (m g )(34.14/41.04)C 18.54a A 18.89a A 24.36a A 15.04a A 3.086.30–2610.180.4821.32a A 2.5415.11–9.560.06?0.22(0.737/0.267)T 14.24b B 16.94b B 20.06b B 12.51b B 2.516.43–20.910.280.4218.56b B 3.149.32–27.31?0.050.35S L D W (m g )(43.48/36.71)C 11.83a A 12.85a A 15.23a A 10.03a A 2.333.54–19.800.591.8014.14a A 1.710.14–20.580.270.11(0.407/0.317)T 9.41b B 11.30b B 12.23b B 8.47b B 1.672.34–13.660.110.0212.47b B 2.156.44–20.810.151.01R D W (m g )(44.73/52.55)C 6.71a A 6.04a A 9.13a A 4.96a A 1.261.64–13.710.270.597.19a A 1.314.16–10.21?0.19?0.28(0.553/0.203)T 4.83b B 5.64b B 7.83b B 4.04b B 1.111.50–12.510.982.556.09b B 1.333.66–10.28?0.04?0.05R S F W R (%)50.61/58.38)C 62.89a A 52.86a A 66.09a A 56.56a A 11.731.12–89.340.28?0.2863.28a A 12.1833.6–99.900.120.19(0.734/0.324)T 55.82b B 54.05b B 79.42b B 48.21b B 10.2725.77–86.180.731.6857.86b B 12.5630.11–94.010.300.55R S D W R (%)(46.48/54.16)C 56.72a A 47.00a A 59.87a A 50.78a A 12.4610.10–90.290.421.0951.11a A 8.9926.17–82.200.130.33(0.051/0.133)T 51.33b B 49.91b B 63.93b B 47.91b B 10.2221.52–89.470.832.3049.22b B 8.9222.81–78.570.240.45

a A r a

b i c

n u m e r a l s i n t h e ?r s t p a r e n t h e s e s a r e t h e e s t i m a t e d b r o a d s e n s e h e r i t a b i l i t y o f t h e c o r r e s p o n d i n g t r a i t s a n d t h a t i n t h e s e c o n d p a r e n t h e s e s a r e P v a l u e s f o r t h e s i g n i ?c a n c e o f d i f f e r e n c e b e t w e e n t h e p a r e n t s ,o f w h i c h ,t h e ?r s t n u m e r a l r e f e r s t o W Y ,a n d t h e s e c o n d r e f e r s t o W L .b C a n d T p r e s e n t t h e n o r m a l w a t e r c o n d i t i o n a n d o s m o t i c s t r e s s ,r e s p e c t i v e l y .c W Y a n d W L r e p r e s e n t t h e p o p u l a t i o n s d e r i v e d f r o m t h e c r o s s e s b e t w e e n W e i m a i 8a n d Y a n n o n g 19a n d b e t w e e n W e i m a i 8a n d L u o h a n 2,r e s p e c t i v e l y .d S t d ,s t a n d a r d d e v i a t i o n .e S m a l l l e t t e r s ‘a ’a n d ‘b ’m e a n s s i g n i ?c a n c e o f d i f f e r e n c e w h e n P <0.05,a n d c a p i t a l l e t t e r s ‘A ’a n d ‘B ’m e a n s s i g n i ?c a n c e o f d i f f e r e n c e w h e n P<0.01.

Journal of Genetics V ol.92,No.2,August 2013

QTL mapping of drought-tolerance-related traits in wheat

1234

5678

9101112

13141516

17181920

Figure1.(contd.)

Journal of Genetics V ol.92,No.2,August2013

Hong Zhang et al.

21222324

25262728

29303132

33343536

37383940

Figure1.(contd.)

Journal of Genetics V ol.92,No.2,August2013

QTL mapping of drought-tolerance-related traits in

wheat

41424344

454647

48

Figure1.Frequency distribution graphs of12investigated traits of WY and WL population under two water conditions.Note:CLC, SHC,RLC,RNC,SFWC,SLFWC,RFWC,SDWC,SLDWC,RDWC,RSFWRC,RSDWRC separately means the coleoptile length(CL), seedling height(SH),longest root length(RL),root number(RN),seedling fresh weight(SFW),stem and leaves fresh weight(SLFW), root fresh weight(RFW),seedling dry weight(SDW),stem and leaves dry weight(SLDW),root dry weight(RDW),root to shoot fresh weight ratio(RSFWR),root to shoot dry weight ratio(RSDWR)under normal water condition,and CLT,SHT,RLT,RNT,SFWT,SLFWT, RFWT,SDWT,SLDWT,RDWT,RSFWRT,RSDWET separately means that under osmotic stress.The graphs from number1to24are trait-distribution of WY population,and from number25to48are trait distribution of WL population.

made as male parent,and the additive effects of17and23

QTLs observed in the WL population respectively came from

Weimai8made as female parent and Luohan2made as male

parent.

QTLs concerned with CL

Six QTLs concerned with CL were detected in the WY pop-

ulation.Of these,only one QTL was detected under both

water conditions,three QTLs only under normal water con-

dition,and two QTLs only under osmotic stress.These QTLs

were located on the chromosomes1A,2B,4A,5D,and

6B and accounted for5.43–16.53%of the phenotypic vari-

ation(table2).A main-effect QTL between Xgdm99.2and

Xcfd29of chromosome5D with positive additive effects,

derived from Weimai8,was detected under the two water

conditions,which accounted for16.53%and11.76%of the

phenotypic variation,respectively,under normal water con-

dition and osmotic stress.Under osmotic stress,two QTLs

with positive additive effects,from Weimai8and Yan-

nong19,respectively,were detected between Xgdm99.2and

Xcfd295D of chromosome5D.The absolute size was only

15cM.

Five QTLs concerned with CL were detected in the WL

population.Of these,two QTLs were detected under both

water conditions,two QTLs under normal water condition,

and one QTL only under osmotic stress.These QTLs were

located on chromosomes2B,3B,4D and5B and accounted

for 4.53–12.25%of the phenotypic variation(table2).

A main effect QTL between Xmag3356and Xbarc158

of chromosome3B with positive additive effects,derived

from Weimai8,was detected under both water conditions,

which accounted for11.44%and12.25%of the phenotypic

Table2.Phenotypic correlations of wheat seedling traits under normal water condition and under osmotic stress in both WJ and WY populations.

Population CL SH RL RN SFW SLFW RFW SDW SLDW RDW RSFWR RSDWR

WY0.88**0.74**0.60**0.68**0.71**0.54**0.70**0.43**0.65**0.61**0.70**0.69** WL0.89**0.66**0.56**0.74**0.65**0.59**0.68**0.58**0.49**0.67**0.52**0.55**

**Correlation is signi?cant at P<0.01level.

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Hong Zhang et al.

T a b l e 3.S u m m a r y o f u n c o n d i t i o n a l Q T L f o r w h e a t s e e d l i n g t r a i t s u n d e r t w o w a t e r c o n d i t i o n s .

T r a i t P o p u l a t i o n Q T L n a m e s

P o s i t i o n a M a r k e r i n t e r v a l b L O D v a l u e R 2%c C h r o m o s o m e d A d d i t i v e e T r e a t f

C L W Y

Q C L .W Y .1A 28B E 470813.3–X w e s 226.25.81/6.3416.53/11.761A 0.16/0.15C /T Q C L .W Y .2B 120X g w m 547–X c i n a u 119.25.4710.062B 0.14T Q C L .W Y .4A 123X w m c 420.2–X c f e 89.43.326.524A ?0.10C Q C L .W Y .5D .1223X g d m 99.2–X c f d 266.23.165.435D 0.11T Q C L .W Y .5D .2238X c f d 266.2–X c f d 293.646.835D ?0.12T Q C L .W Y .6B 152X w m c 737–X c w m 29.14.629.556B ?0.12C W L

Q C L .W L .2B 176X c f e 140–W W 7.12.627.072B 0.11T Q C L .W L .3B .1109X w m c 236–X b a r c 1763.024.533B 0.12C Q C L .W L .3B .2153X m a g 3356–X b a r c 1588.7511.443B 0.15C /T Q C L .W L .4D 29K s u m 195–X i s s r 8442.94/3.708.86/8.094D ?0.11/?0.12C /T Q C L .W L .5B 5X g w m 234.3–X g w m 544.23.756.965B ?0.10C S H W Y

Q S H .W Y .1A 28B E 470813.3–X w e s 226.25.48/6.1713.59/11.421A 0.52/0.43C /T Q S H .W Y .2D .120X w m c 181.1–X c f d 534.1710.062D ?0.51T Q S H .W Y .2D .238X b a r c 11–X c f d 168.23.739.302D 0.41T Q S H .W Y .4A 249X w m c 161–X b a r c 61.15.5211.264A 0.43T Q S H .W Y .4B 14X g w m 66.2–X g w m 66.13.689.374B 0.71C Q S H .W Y .6B 102X w m c 473–X b a r c 1464.858.776B ?0.43C Q S H .W Y .7A 24X i s s r 847–X g w m 604.447.537A ?0.40C W L

Q S H .W L .6A 54X m e 3e m 3.3–X m e 7e m 7.23.198.356A 0.37T Q S H .W L .7A .141X m a g 828.2–X m e 9e m 255.3177.017A 4.85C R L W Y

Q R L .W Y .1A 63X i s s r 845–G l u -a 13.018.891A ?0.70C Q R L .W Y .4A 252X w m c 161–X b a r c 61.14.0411.564A 0.39T Q R L .W Y .6B 1X s w e s 131.3–X s w e s 131.43.21/3.026.23/6.416B 0.48/0.28C /T W L

Q R L .W L .3B 96X b a r c 268–X b a r c 0753.156.753B ?0.36T Q R L .W L .4A 18X k s u e 18.2–X w m c 5162.996.554A ?0.34T Q R L .W L .4B 14X g w m 495–X c f d 545.1418.71744B ?0.77C Q R L .W L .6A 53X m e 3e m 3.3–X m e 7e m 7.22.535.396A 0.30T Q R L .W L .6D 212X c f e 277.1–X c f e 806.1915.676D 0.55T Q R L .W L .7B .185X w m c 475–X m g w 682.65/4.375.71/8.707B 0.51/0.40C /T Q R L .W L .7B .298X w m c 488.1–X g w m 350.13.788.287B 0.51C R N W Y

Q R N .W Y .2D 119X m e 3e m 2.5–X m e 3e m 2.34.1312.562D 0.23C Q R N .W Y .3B 62X b a r c 084–X b a r c 3443.136.723B ?0.1322T Q R N .W Y .4D 15X c a u 17.1–X c f d 718.0621.27/5.384D ?0.27/?0.12C /T W L

Q R N .W L .2B 223W W 86–X m a g 35123.525.712B ?0.12C Q R N .W L .3B 131X b a r c 101.1–X c f t 3417.15.066.533B ?0.12C Q R N .W L .5A 158X m a g 1681.2–X m a g 3794.13.498.175A 0.14C Q R N .W L .5B 112X g w m 540–X g w m 213.24.556.015B 0.12C Q R N .W L .6D 163X c f e 100.2–T S M 4225.15/4.107.54/7.496D ?0.13/?0.15C /T Q R N .W L .7B .163X g p w 5187–X m e 4e m 9.32.57/3.954.60/7.367B 0.13/0.19C /T Q R N .W L .7B .274X b a r c 346.3–W W 1544.817.827B ?0.16T

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T a b l e 3(c o n t d .)T r a i t P o p u l a t i o n Q T L n a m e s

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Q S L F W .W Y .7A .118X i s s r 847–X g w m 606.31/4.7822.53/6.617A ?6.24/?4.60C /T Q S L F W .W Y .7A .291X c f e 284–w w 160.22.7613.777A ?5.63T W L Q S L F W .W L .3B 121X b a r c 176–X b a r c 101.12.566.523B ?2.92T R F W

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Q R F W .W Y .1D 22X w e s 226.1–X c f d 48.23.5411.921D ?3.70C Q R F W .W Y .5A 111X c w m 17.1–X m a g 32732.5513.815A ?4.33C W L Q R F W .W L .3B 96X b a r c 268–X b a r c 0752.63/3.816.22/7.873B ?3.12/?2.51C /T S D W

W Y

Q S D W .W Y .2D 109X c w m 70.1–X c w m 834.719.442D ?0.82T Q S D W .W Y .4A 263X w m c 161–X b a r c 61.14.2212.254A ?0.91T Q S D W .W Y .7A 18X i s s r 847–X g w m 602.76/2.549.86/8.137A ?1.01/?0.80C /T Q S D W .W Y .7B 145w w 121–X w m c 517.23.088.277B ?0.92C Q S D W .W Y .7D 565X c f d 4–X g w m 442.875.487D ?0.63T W L

Q S D W .W L .2A 57X g w m 496–X b a r c 0153.016.152A ?0.70C Q S D W .W L .2A 84X b a r c 010–X c f a 2263.22.574.762A ?0.63T Q S D W .W L .3A 84X w m c 415–X m a g 4194.13.667.713A ?0.71C S L D W W Y

Q S L D W .W Y .1B 219X m a g 972.1–X m a g 972.22.896.321B ?0.51C Q S L D W .W Y .3B 83X b a r c 344–X c f e 32922.517.933B ?0.83C Q S L D W .W Y .4A 121X w m c 420.2–X c f e 89.42.725.864A ?0.52C Q S L D W .W Y .6D 82X s w e s 123.9–X c f e 87.24.6814.416D ?1.11C Q S L D W .W Y .7A 19X i s s r 847–X g w m 602.569.357A ?0.80C R D W

W Y Q R D W .W Y .2D 23X c f d 53–X c f d 168.13.138.612D ?0.52C W L

Q R D W .W L .1D 0X m e 2e m 1.2–X c f d 832.803.531D ?0.21T Q R D W .W L .2B 44X w m c 154–X g d m 993.826.652B ?0.34C Q R D W .W L .3A 84X w m c 415–X m a g 4194.13.32/3.277.01/7.533A ?0.44/?0.37C /T Q R D W .W L .3B .177X g p w 1146–X m a g 2916.22.513.333B ?0.20C Q R D W .W L .3B .295X b a r c 102–X b a r c 2682.953.813B ?0.26T Q R D W .W L .4A 53X c f e 65.2–X w m c 7302.854.394A ?0.30T Q R D W .W L .6D 50X c f e 100.2–T S M 4223.566.886D ?0.39T Q R D W .W L .7A 96X b a r c 049–X g w m 2735.587.917A ?0.45C R S F W R W Y

Q R S F W R .W Y .2D 25X c f d 168.1–X b a r c 113.247.812D ?7.59C Q R S F W R .W Y .3B 88X b a r c 344–X c f e 32922.956.293B 11.80T Q R S F W R .W Y .5A 115X c w m 17.1–X m a g 32733.059.695A ?9.24C W L

Q R S F W R .W L .3B 96X b a r c 268–X b a r c 0752.82/4.624.46/6.853B ?2.51/?3.39C /T Q R S F W R .W L .5A 80X m a g 694–X b a r c 3192.854.155A ?2.56T R S D W R W Y

Q R S D W R .W Y .2D 148X g w m 210–X g d m 352.588.862D ?13.20T Q R S D W R .W Y .5D 49X b a r c 28.2–X c w m 3624.1575.555D 68.25T Q R S D W R .W Y .7D 37X m a g 2934.1–m a g 2934.22.746.397D ?7.38C

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T a b l e 3(c o n t d .)T r a i t P o p u l a t i o n Q T L n a m e s P o s i t i o n a M a r k e r i n t e r v a l b

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X b a r c 049–X g w m 273

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f f e c t s .d C h r o m o s o m e o n w h i c h t h e Q T L w a s d e t e c t e d .e E s t i m a t e s o f t h e a d d i t i v e e f f e c t o f t h e Q T L .P o s i t i v e v a l u e s i n d i c a t e t h a t W e i m a i 8a l l e l e s i n c r e a s e t h e t r a i t v a l u e s .N e

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variation under normal water condition and osmotic stress,respectively.

QTLs concerned with SH

Eight QTLs concerned with SH were detected in the WY population;four QTLs each were detected under normal water condition and osmotic stress,respectively.These QTLs were located on chromosomes 1A,2D,4A,4B,6B,and 7A and accounted for 7.53–13.59%of the phenotypic varia-tion (table 2).Among these QTLs,four QTLs could account for more than 10%of the phenotypic variation;accord-ingly,these should be main effect QTLs.A main effect QTL between BE470813.3and Xwes226.2of chromosome 1A with positive additive effects,derived from Weimai 8was detected under the two water conditions,which accounted for 13.59%and 11.42%of the phenotypic variation under normal water condition and osmotic stress,respectively.This location was the same as that of the QTL for CL on chro-mosome 1A;hence,it should be a location with pleiotropic effects.Under osmotic stress,two QTLs were detected on chromosome 2D with positive additive effects,which were derived from Weimai 8and Yannong 19and accounted for 10.06%and 9.30%of the phenotypic variation,respectively.The absolute size of the two QTLs was 18cM.

Two QTLs concerned with SH were detected in the WL population.Of these,a main effect QTL between Xmag828.2and Xcfa2040,with positive additive effect and derived from Weimai 8,was detected under normal water condition,which accounted for 77.01%of the phenotypic variation.A QTL with positive additive effects from Weimai 8on chromosome 6A was detected under osmotic stress,which accounted for 8.35%of the phenotypic variation.

QTLs concerned with RL

Two QTLs concerned with RL were detected under normal water condition and osmotic stress,respectively.These QTLs were located on chromosomes 1A,4A,and 6B (table 2).A QTL with positive additive effects derived from Weimai 8and located between Xswes131.3and Xswes131.4on chro-mosome 6B,was detected under both the water conditions,and it accounted for 6.23%and 6.41%of the phenotypic variation respectively.Under osmotic stress,a main-effect QTL from Weimai 8,with positive additive effects,was detected on chromosome 4A.It accounted for 11.56%of the phenotypic variation.

Nine QTLs concerned with RL were detected in the WL population:three QTLs were detected under normal water condition,and six QTLs under osmotic stress.Under nor-mal water conditions,a main-effect QTL with negative addi-tive effects,derived from Yannong 19and located between Xgwm495and Xcfd54of chromosome 4B,accounted for 18.72%of the phenotypic variation under osmotic stress.A main-effect QTL with positive additive effects from Weimai 8,located between Xcfe277.1and Xcfe80of

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QTL mapping of drought-tolerance-related traits in wheat

chromosome6D,accounted for15.67%of the phenotypic variation.Similarly,three QTLs with positive additive effects from Weimai8were detected on chromosome7B.Of these QTLs,two QTLs were detected under normal water conditions and one QTL under osmotic stress.

QTLs concerned with RN

Two QTLs concerned with RN were detected under nor-mal water condition and osmotic stress,respectively,in the WY population.A main-effect QTL with negative additive effects from Yannong19was detected between Xcau17.1 and Xcfd71of chromosome4D.It accounted for21.28% and5.38%of the phenotypic variation under normal water condition and osmotic stress respectively.In addition,a main-effect QTL with positive additive effects,derived from Weimai8,was detected on chromosome2D.It accounted for 12.6%of the phenotypic variation.

Nine RN-related QTLs were detected in the WL popu-lation.Of these,six QTLs were expressed under normal water condition,and three under osmotic stress.All the QTLs accounted for less than10%of the phenotypic vari-ation;therefore,they were genes with minor effects.A common QTL was detected on chromosomes6D and7B respectively under two water conditions.The QTL on chro-mosome6D between Xcfe100.2and TSM422with a neg-ative additive effect accounted for7.54%and7.49%of the phenotypic variations under normal water condition and osmotic stress,respectively.The QTL on chromosome7B between Xcfe100.2and TSM422with a positive additive effect accounted for4.60%and7.36%of the variation under normal water condition and osmotic stress,respectively.In addition,a QTL with negative additive effect from Luohan2 was detected under osmotic stress at a location11cM away from the QTL locus on chromosome7B.It accounted for 7.82%of the phenotypic variation.

QTLs concerned with SFW

Five QTLs concerned with SFW were detected in the WY population.These QTLs were located on chromo-somes2D,6B,7A,and7B and accounted for4.99–11.31% of the phenotypic variation(table2).Of these,two were detected under normal water condition,and three under osmotic stress.A common QTL with additive effect from Yannong19was detected between Xmag3023and Xgwm60 of chromosome7A.It accounted for11.31%and9.93% of the phenotypic variation under the two water conditions respectively.No QTL for SFW was detected in the WL population.

QTLs concerned with SLFW

Two QTLs related to SLFW were detected in the WY pop-ulation.One was detected under both the water conditions, and the other was found only under osmotic stress.These two QTLs were located on chromosome7A and were main-effect QTLs with negative additive effect,derived from Yan-nong19.They accounted for13.7–22.53%of the phenotypic variation.

In the WL population,only one SLFW-related QTL located on chromosome3B,with positive additive effect and derived from Weimai8,was detected under osmotic stress.It accounted for6.52%of the phenotypic variation.

QTLs concerned with RFW

Only two main-effect QTLs concerned with RFW were detected in the WY population.Of these QTLs,one with neg-ative additive effect from Yannong19was located between Xwes226.1and Xcfd48.2of chromosome1D,accounting for11.92%of phenotypic variation.The other with a pos-itive additive effect,from Weimai8was located between Xcwm17.1and Xmag3273of chromosome1D,accounted for13.81%of phenotypic variation.

A common QTL with negative additive effect from Luo-han2was detected under both water conditions in the WL population.It was located between Xbarc268and Xbarc075 of chromosome3

B and accounted for6.22%and7.87% of phenotypic variation under the two water conditions respectively.

QTLs concerned with SDW

Six QTLs concerned with SDW were detected in the WY population.Of these QTLs,two were detected under nor-mal water condition and four under osmotic stress.These QTLs were located on chromosomes2D,4A,7A,7B,and 7D and accounted for5.48–12.25%of the phenotypic varia-tion(table2).A common QTL with negative additive effect derived from Yannong19was detected between Xmag847 and Xgwm60of chromosome7A under the two water condi-tions and accounted for9.86%and8.13%of the phenotypic variation,respectively.

Three QTLs with negative additive effect were detected in the WL population.These QTLs accounted for4.76–7.71% of the phenotypic variation.Of these QTLs,two located on chromosomes2A and3A,respectively,were detected under normal water condition.One QTL located on chromosomes 2A and3A was detected only under osmotic stress.

QTLs concerned with SLDW

Five QTLs concerned with SLDW were detected only under normal water condition in the WY population.These QTLs, located on chromosomes1B,3B,4A,6D,and7A,accounted for5.86–14.41%of the phenotypic variation(table2).A main-effect QTL with positive additive effect,from Weimai 8,accounted for14.41%of phenotypic variation and was detected between Xswes123.9and Xcfe87.2of chromosome 6D.The additive effects of all other QTLs were derived from

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Yannong19.No QTL concerned with SLDW was detected in the WL population.

QTLs concerned with RDW

Only one QTL with positive additive effect,derived from Weimai8,was detected under normal water condition in the WY population.It was located between Xcfd53and Xcfd168.1of chromosome2D and accounted for8.61%of phenotypic variation.

Nine QTLs were detected in the WL population,account-ing for3.32–8.61%of the phenotypic variation.Of these QTLs,four were detected under normal water condition and ?ve under osmotic stress.The additive effect of two QTLs resulted from Weimai8,whereas that of seven QTLs was derived from Luohan2.A common QTL with negative addi-tive effect,derived from Luohan2,was detected between Xwmc415and Xmag4194.1of chromosome3A.It accounted for7.01%and7.53%of the phenotypic variation under two water conditions.One QTL was detected on each of the fol-lowing chromosomes:on2B,3B and7A under normal water condition;and on2B,3B,and7A under osmotic stress. QTLs concerned with RSFWR

Three QTLs concerned with RSFWR were detected in the WY population:two were detected under normal water con-dition,and one under osmotic stress.These QTLs were located on chromosomes2D,5A,and3B and accounted for 6.29%and9.69%of phenotypic variation in the two water conditions,respectively.The additive effect of one QTL was derived from Yannong19,and other was derived from Weimai8.

Three QTLs concerned with RSFWR were detected in the WL population.Of these,one was detected under normal water condition,and two under osmotic stress.These QTLs were located on chromosomes3B and5A and accounted for 4.46%and6.85%of phenotypic variation in the two con-ditions,respectively.The additive effect of all QTLs came from Yannong19.A QTL located between Xbarc102and Xbarc268of chromosome3B was detected under the two water conditions.

QTLs concerned with RSDWR

Three QTLs concerned with RSDWR were detected in the WY population.One QTL was detected under normal water condition,and two under osmotic stress.These QTLs were located on chromosomes2D,5D,and7D.A main-effect QTL with a positive additive effect that was derived from Weimai8,located between Xbarc28.2and Xcwm36of chromosome5D,accounted for75.55%of the phenotypic variation.

Nine QTLs concerned with RSDWR were detected in the WL population.Of these,four were detected under normal water condition,and?ve under osmotic stress.These QTLs,located on chromosomes3B,4D,5A,6A,and6D,accounted for3.63–11.98%of phenotypic variation.The additive effect of seven QTLs came from Luohan2,and the additive effect of two QTLs came from Weimai8.A QTL with negative additive effect from Luohan2,located between Xbarc102 and Xbarc268of3B was detected under both the water condi-tions and accounted for3.63%and6.47%of the phenotypic variation.

QTLs with multiple effects were detected in the two populations Seven QTLs with multiple effects were detected in WY pop-ulation(?gure2).A main-effect QTL with multiple effects related to both CL and SH was found between BE470813.3 and Xwes226.2of chromosome1A.A QTL with positive additive effect from Weimai8was detected simultaneously under two water conditions for the two traits and accounted for more than10%of the phenotypic variation.A QTL with multiple effects concerned with SFW,SLFW,SDW,SLFW and SH was detected between Xissr847and Xgwm60of chro-mosome7A.This QTL accounted for11.31%and9.93% of the phenotypic variation in SFW,22.53%and16.61%in SLFW,and9.86%and8.13%in SDW under normal water condition and osmotic stress,respectively.In addition,this QTL accounted for9.36%and7.53%of the phenotypic vari-ation of SLDW and SH,respectively,under normal water condition.The additive effect of this QTL was derived from Yannong19.A QTL concerned with SLDW and CL was detected between Xwmc420.2and Xcfe89.4of chromosome 4A.This QTL with negative additive effect and derived from Yannong19accounted for5.86%and6.52%of the phenotypic variation of SLDW and CL,respectively. Seven QTLs with multiple effects were detected in the WL population(?gure2).A QTL located between Xbarc268 and Xbarc075on chromosome3B was detected for RL, RFW and RDW under osmotic stress;and for RSFWR and RSDWR under both water conditions.The additive effect of this QTL originated from Luohan2.This QTL should be an important locus concerned with root growth.A QTL with the additive effect from Luohan2located between Xwmc415 and Xmag4194.1of chromosome3A was detected for SDW under normal water condition and for RDW under the two water conditions.Under osmotic stress,a QTL concerned with SH and RL was detected on chromosome4A.A QTL with the additive effect from Weimai8located on chro-mosome6A was detected for SH and RL under osmotic stress.

Conditional QTL

When12seedling trait values surveyed under osmotic stress was conditioned QTL analysis on those surveyed under nor-mal water condition,altogether22conditional QTLs were detected(table4).These QTLs were located on chromo-somes1B,2A,2D,4A,6A and6D in the WY popula-tion;and on chromosomes2A,2B,3B,5D,6D,7B,and

Journal of Genetics V ol.92,No.2,August2013

QTL mapping of drought-tolerance-related traits in wheat

Figure2.(contd.)

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al.

Figure2.Locations of QTLs for wheat seedling traits that detected by unconditional QTL analysis.QTLs are indicated on the right side of each chromosome.QTL intervals were LOD≥2.0with LOD peak values more than2.5.

7D in the WL population.Of these QTLs,six were main-effect QTLs,with a contribution rate>10%.Two common loci were detected in the WL population,one located on chromosome2B between ww7.1and ww86was detected simultaneously when the in?uence of SFWC(shoot fresh weight under normal water condition)on SFWCT(shoot fresh weight under osmotic stress)and that of SDWC on SDWT were excluded,and the other QTL located on chro-mosome3B between Xbarc268and Xbarc075was detected when the in?uence of RSFWRC(root to shoot fresh weight ratio under normal water condition)on RSFWRT(root to shoot fresh weight ratio under osmotic stress)and that of RSDWRC(root to shoot dry weight ratio under normal water condition)on RSDWRT(root to shoot dry weight ratio under osmotic stress)were excluded.The QTL on chromosome 3B was also detected by unconditional analysis of RSFWRT and RSDWRT,and it showed reduced and enhanced addi-tive effects,respectively,when the in?uence of RSFWRC on RSFWRT and RSDWRC on RSDWRT were disregarded.In addition,a QTL between Xcfe277.1and Xcfe80of chromo-some6D,accounting for15.31%of the phenotypic variation, was detected when the in?uence of RLC(root length under normal water condition)on RLT(root length under osmotic stress)was excluded;it was also detected by unconditional analysis of RLT with a similar additive effect. Moreover,eight conditional QTLs accounting for6.73–14.23%of the phenotypic variance in the inpidual traits were detected in the WY population.Of these QTLs,the additive effect of three QTLs was derived from Yannong 19,and?ve were derived from Weimai8.All the QTLs were not detected by the unconditional analysis method. When the in?uence of SHC(shoot height under normal water condition)on SHT(shoot height under osmotic stress)was excluded,two QTLs were detected on chromosomes2A and 6D.These two QTLs accounted for8.77%and6.84%of the phenotypic variation,with the additive effect derived from Yannong19and Weimai8,respectively.When the in?u-ence of RLC on RLT was excluded,two main-effect QTLs were detected on chromosomes4D and6D.These two QTLs accounted for14.18%and11.59%of the phenotypic vari-ation,respectively,with the additive effect being derived from Weimai8.When the in?uence of SFWC(shoot fresh weight under normal water condition)on SFWT(shoot fresh weight under osmotic stress)was excluded,one QTL was detected on chromosome6A.When the in?uence of RFWC on RFWT was excluded,two QTLs were detected on chro-mosomes2D and6A,respectively.Of these two,the QTL located between Xgwm210and Xgdm35of chromosome2D was a main-effect QTL that accounted for14.24%of the phenotypic variation.When the in?uence of RSFWRC on RRFWRT was excluded,a main-effect QTL was detected between Xgwm11and Xbarc61.2on chromosome1B,which accounted for11.72%of the phenotypic variation;further, the additive effect was derived from Weimai8.

Totally,14conditional QTLs were detected in WL pop-ulation;of these QTLs,six had the additive effect derived from Weimai8,and eight possessed the additive effect derived from Luohan 2.When the in?uence of CLC (coleoptile length under normal water condition)on CLT (coleoptile length under osmotic stress)was excluded,four

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QTL mapping of drought-tolerance-related traits in wheat

Table4.Summary of conditional QTL for seedling traits of wheat.

LOD Contribution Additive Population Trait T|Trait C a QTL name Location Marker interval value rate(%)effect WY SHT|SHC QSHT|SHC.WY.2A151Xcfe87.3–Xbarc071 4.698.77?0.257

QSHT|SHC.WY.6D28Xswes123.7–Xissr841.2 2.85 6.840.2550 RLT|RLC QRLT|RLC.WY.4A241Xbarc1047–Xwmc161 6.2214.180.3537 QRLT|RLC.WY.6D88Xcfe87.1–Xissr841.1 4.0911.590.3111 SFWT|SFWC QSFWT|SFWC.WY.6A167Xcfe179.3–Xcfe87.1 3.057.830.0029 QSFWT|SFWC.WY.2D152Xgwm210–Xgdm35 2.8314.24?0.0029

QSFWT|SFWC.WY.6A94Xcfe179.1–Xgwm169 2.62 6.74?0.0019 RSFWRT|RSFWRC QRSFWRT|RSFWRC.WY.1B149Xgwm11–Xbarc61.2 3.5711.720.0571 WL CLT|CLC QCLT|CLC.WL.2B211WW86–Xmag3512 4.0010.360.0634 QCLT|CLC.WL.3B108Xcau6.1–Xwmc236 4.968.68?0.0900

QCLT|CLC.WL.5D50Xcau18.1–Xcfd13 3.58 6.38?0.0586

QCLT|CLC.WL.7B104Xcfe148.1–Xpsp3065.2 3.03 4.51?0.0447 RLT|RLC QRLT|RLC.WL.2A14Xme10em5.3–Xme1em8.2 3.02 4.38?0.2366 QRLT|RLC.WL.3B72Xmag2916.1–Xgwm285.2 3.00 4.190.2235

QRLT|RLC.WL.6D11Xcfe277.1–Xcfe80 6.4015.310.4469 SFWT|SFWC QSFWT|SFWC.WL.2A92Xcfa2263.2–Xcfa2263.3 3.40 5.39?0.0031 QSFWT|SFWC.WL.2B183WW7.1–WW86 2.55 3.820.0025 RFWT|RFWC QRFWT|RFWC.WL.7D66Xgpw2327.2–Xgpw2327.1 2.72 6.480.0016 SDWT|SDWC QSDWT|SDWC.WL.2B183WW7.1–WW86 2.59 4.060.0005 RDWT|RDWC QRDWT|RDWC.WL.6D39Xcfe277.2–Xcfd49 3.40 6.92?0.0003 RSFWRT|RSFWRC QRSFWRT|RSFWRC.WL.3B96Xbarc268–Xbarc075 2.60 5.07?0.0258 RSDWRT|RSDWRC QRSDWRT|RSDWRC.WL.3B96Xbarc268–Xbarc075 3.407.65?0.0219 a The trait value observed under osmotic stress was conditioned on that under normal water condition.

conditional QTLs were detected on chromosomes2B,3B, 5B and7B respectively.Of these QTLs,a main-effect QTL with an additive effect,derived from Weimai8and located between ww86and Xmag3512of chromosome2B, accounted for10.36%of the phenotypic variation.When the in?uence of RLC on RLT was excluded,three QTLs were detected on chromosomes2A,3B,and6D,respec-tively.When the in?uence of SFWC on SFWT was excluded, another minor-effect QTL was detected on chromosome2A. When the in?uence of RFWC(root fresh weight under nor-mal water condition)on RFWT(root fresh weight under osmotic stress)and RDWC(root dry weight under normal water condition)on RDWT(root dry weight under osmotic stress)was excluded,a minor-effect QTL was detected on chromosomes7D and6D respectively.The other four QTLs have been mentioned above;so they are not repeated here.

Discussion

Comparison of the QTL analysis between two related populations The results of the QTL detection show that genes controlling some traits are expressed under special genetic background and environmental conditions.The QTLs detected in differ-ent populations had quite a large difference because of the in?uence of all types of factors,such as genetic composition of the parents,size of the population,interaction between genotype and environment,style of genetic maps,and so on (Beavis1998).With the rapid development of quantitative genetics,research on QTL effects in more than one genetic backgrounds,either different or related,is warranted.Kumar et al.(2007)have used two independent RIL populations to conduct QTL analysis;however,only a solitary QTL for spikelets per spike was common between the two popula-tions.Ma et al.(2007)identi?ed a large number of common QTLs using RILs and RIL-derived IF2populations.Buckler et al.(2009)used a set of5000RILs(maize nested asso-ciation mapping population,NAM),comprising25related inpidual RIL populations to dissect the QTLs for?owering time in maize;they identi?ed numerous minor-effect QTLs that were shared among families.Cui et al.(2011)conducted conditional and unconditional QTL analysis for plant height using two related populations and found11pairwise common QTLs.

In this report,two related RIL populations with a com-mon parent were subjected to unconditional and condi-tional QTL mapping to identify the QTLs for various traits in wheat seedlings.The two molecular marker maps had 19common molecular markers.The QTLs of12breed-ing traits had different distributions on the chromosomes in the two populations under the two water conditions.By the unconditional analysis method,a common locus concerned with CL was detected on chromosome2B,with the com-mon linkage marker wmc441.By the conditional analysis method,a common QTL concerned with drought tolerance was detected on chromosome2A,with the common linkage marker Xbarc071.In addition,a QTL for RSFWR on chro-mosome3B,a QTL for SH on chromosome7A,and two QTLs concerned with drought tolerance on chromosome6D were detected in the two populations;however,because there

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Hong Zhang et al.

was no common marker on these chromosomes,con?rming whether they were common loci was dif?cult.Although these two populations had a common parent,because of the vari-ations in the different loci of the two parents,a few com-mon QTLs were detected.Nevertheless,without doubt,a greater number of QTLs could be detected using two related populations than by using a single population.The next work involves using other markers to decrease the interval in genetic maps,to increase the number of common mark-ers,and to recombine the two related maps to improve the authenticity of QTL detection.

Comparison of conditional and unconditional QTLs

Drought tolerance of plants is a complex trait represented by different phenotypic traits in different growth periods;there-fore,establishment of screening standards for evaluation is dif?cult.QTL analysis of conventional drought tolerance is generally aimed at analysing expression of phenotypic traits under osmotic stress(Zhou et al.2005).Discovering the genetic relation between these phenotypic traits and drought tolerance;and?nding the loci concerned with drought tolerance are extremely dif?cult.Although some indexes for drought resistance have been used to detect QTLs related to drought resistance,the stability of such QTLs is very low under different conditions.For example,of the36 genomic regions reported to harbour root trait-related QTLs (Yue et al.2006a),only four had positional correspondence with previously identi?ed QTLs for root or other drought tolerance-related traits(Courtois et al.2009;Yonemaru et al. 2010).Expression of special loci under osmotic stress can be found by conditional QTL mapping after excluding the in?uence of traits expressed under normal water condition. When conducting conditional QTL analysis of traits in wheat seedlings grown under osmotic stress on the corresponding traits under normal water condition,four results are possi-ble:(i)a QTL detected by the unconditional method can be identi?ed with a similar or equal effect indicating that this QTL is the special locus concerned with only drought toler-ance;(ii)a QTL detected by the unconditional method can be identi?ed with either a greatly reduced or a greatly enhanced effect suggesting that this QTL for trait expression is par-tially but not completely associated with drought tolerance; (iii)a QTL detected by the unconditional method cannot be identi?ed meaning that this QTL is not entirely concerned with drought tolerance;and(vi)an additional QTL can be detected by the conditional mapping method,which means that the expression of the QTL for these traits under osmotic stress is completely suppressed by the traits expressed under normal water condition and that these effects could only be identi?ed by eliminating the in?uence of the traits expressed under normal water condition.This suggests that the addi-tional QTL has an opposite additive effect on trait expression under the two water conditions.

Of the50unconditional QTLs studied for the12traits of wheat seedlings detected in the two populations,only three QTLs with similar,reduced,and enhanced additive effects,respectively,were detected by the conditional anal-ysis method,and47QTLs were not detected.This result indicated that most of the QTLs concerned with drought tolerance were not detected by unconditional QTL analysis under osmotic stress.Further,19new QTLs were detected by the conditional analysis method,which means that the expression of these QTLs concerned with drought tolerance is completely suppressed,and the effects could only be iden-ti?ed by eliminating the in?uence of the traits expressed under normal water condition.The results described above show that some unconditional QTLs for the traits of wheat seedlings grown under osmotic stress were contributed by the traits of seedlings grown under normal water condition.This ?nding further con?rmed the results of the correlation anal-ysis between traits of seedlings grown under normal water condition and osmotic stress(table2).

In QTL mapping,the likelihood of detecting a QTL is dependent on the ratio between the variation caused by the QTL’s effect and the total variation of the trait as well as the size of the mapping population(Lander and Botstein 1989).In conditional QTL analysis,the effects on QTLs con-tributed by a conditional trait are reduced,and the QTLs with effects lower than a certain threshold become virtually unde-tectable.Thus,observation of the results described herein is reasonable,which indicates that the unconditional QTLs for traits of seedlings grown under osmotic stress was strongly in?uenced by the conditional-trait representation and that the QTLs directly concerned with drought tolerance were detected only by conditional QTL analysis after excluding the in?uence of normal-trait representation;therefore,carry-ing out conditional analysis for stress-tolerance trait such as drought tolerance is both necessary and viable.

Distribution characteristics of QTLs

In this study,we found that the QTL distribution of traits on every chromosome of wheat seedlings was uneven.The chromosome3B had the most number of QTLs.Altogether 21QTLs controlling different traits in the seedlings were detected on chromosome3B in the two populations;of these QTLs,17were detected by the unconditional analy-sis method,and four were detected by the conditional anal-ysis method.In addition,14QTLs with multiple effects, which controlled many growth traits at the same time,were detected by unconditional analysis.Especially,a main-effect QTL with pleiotropic effects detected between Xissr847and Xgwm60on chromosome7A was related to the growth traits of upland seedlings.A QTL with pleiotropic effects,detected between Xbarc268and Xbarc075on chromosome3B was related to the growth of many root traits,and this locus was also detected by conditional analysis of RSFWRT|RSFWRC and RSDWRT|RSDWRC and should be an important locus concerned with drought tolerance.In addition,many QTLs controlling two different traits were detected on many sec-tions of different chromosomes in the two populations.This

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QTL mapping of drought-tolerance-related traits in wheat

indicated that some of the related traits can be in?uenced by a gene with pleiotropic effects which is consistent with the study results of Cui et al.(2003).

Comparison of the present study with previous studies

Traits of wheat seedlings have been investigated by QTL analysis in many other reports(Matsui et al.1998; Rebetzke et al.2001,2007;Hao et al.2003;Zhou et al. 2005;Spielmeyer et al.2007;Li et al.2007;Landjeva et al. 2010;Alhosein et al.2012;Liu et al.2013)however,in most reported QTL experiments,the number and size of the pop-ulation were limited.Limited population sizes can lead to an underestimation of QTL number,overestimation of QTL effects,and failure to quantify QTL interactions(Vales et al. 2005).Beavis(1998)suggested that as many as200indi-viduals might still be too few for reliable QTL detection. To our knowledge,there has been no report on QTL anal-ysis for traits of wheat seedlings with two related mapping populations of more than200progenies.The present WY mapping population included229F8:9RILs;and the WL mapping population included302F8:9RILs,enhancing the accuracy and precision of QTL detection of traits of the seedlings and increasing the number of QTLs being detected. Matsui et al.(1998)have reported that the?nal CL is controlled by genes on chromosomes1A,4A,4D,5A, and5B,with a major in?uence of group5chromosomes. Rebetzke et al.(2007)have detected QTLs for CL on chro-mosomes1A,2B,2D,3B,4A,4B,4D,5A,5D,6B and7A. In this experiment,11QTLs for CL were detected on chro-mosomes1A,2B,3B,4A,4D,5B,5D and6B.Only three QTLs reported here correspond to that of previous research based on comparison of information of the corresponding ?anking adjacent markers(table5).

According to loci information published on GrainGenes 2.0(af1175104b35eefdc8d333f3/GG2/index.shtml),we con-cluded that QSH.WY.4B were located at a position similar to that of Rht.A QTL for SH reported by Landjeva et al.(2008) on chromosome2D are located in an interval similar to that of QSH.WY.2D.1,Cui et al.(2011)have mapped the QTLs for the plant height of wheat at the mature stage.A QTL on chromosome1A for plant height has also been detected for shoot height and CL under two water conditions in this study,which further con?rmed that there was a QTL con-cerned with plant height on chromosome1A near the marker Xwes226.2.This also indicated that the early shoot height and height of mature plant are related to some extent;thus, we can carry out early selection for plant height.

Using a doubled haploid population of wheat with150 lines under two water conditions,Zhou et al.(2005)detected three QTLs for RN on chromosomes2B,7A,and7B,three for RL on chromosomes1D,2B and6B,two for RFW on chromosomes5B and7A,two for RDW on chromosomes 2A and5B,and one QTL for RSDWR on chromosome5D. Hamada et al.(2012)detected one QTL for seminal root length on chromosome5A.Liu et al.(2013)reported QTLs for root length on chromosomes1B,2D,3A,5B,5D,7B, and for root number on chromosomes2B,3B,3D,5A,7A under two different water af1175104b35eefdc8d333f3ndjeva et al.(2008) detected a QTL for root length on chromosome5B under normal water condition and six QTLs on1A,6D,7D under osmotic stress.To our knowledge,no QTLs for SFW,SDW, SLFW,SLDW,and RSFWR under osmotic stress have been reported so far.We detected nine QTLs for RN on chro-mosomes2D,2B,3B,4D,5A,5B,6D and7B,10for RL on chromosomes1A,3B,4A,4B,6A,6B,6D and7B.By comparing with the previous research results we found that only two QTLs for RL were oriented on the same chromo-some region(table5)which could be caused by the different genetic backgrounds and trial designs.

Considering all the traits evaluated for drought tolerance, Luigi et al.(2002)reported that the most important genomic regions for drought tolerance were identi?ed on the homol-ogous linkage groups6and7in wheat at different stages of growth ranging from germination to maturity.In addition, some QTLs found in a conserved region of the homologous group7had a major effect on drought tolerance(Luigi et al. 2002).Nelson et al.(1995)found an RFLP marker related to abscisic acid response on chromosomes2A,2B,and2D under drought af1175104b35eefdc8d333f3ponents of drought–tolerance

af1175104b35eefdc8d333f3parison of the QTL location between previous studies and this study.

QTLs in this study QTLs detected in previous studies

Chromosome Marker Related trait(treatment)Related trait(treatment)Reference

1A BE470813.3QCL(C/T),QSH(C/T)Plant height(normal water Cui et al.(2011)

condition in?eld trial)

1A Glu-1A QRL(C)RL(osmotic stress)Landjeva et al.(2008) 2B Xgwm547QCL(T)CL(three soil temperatures)Rebetzke et al.(2007) 2D Xcfd53QSH(T),QRSFWR(C),SH,root/shoot(control Landjeva et al.(2008) QRDW(C)and osmotic stress)

3B Xbarc268QRL(T),QRFW(C/T),RN,RL,(under water stress)Liu et al.(2013)

QRDW(T),QRSFWR(C/T),Potential quantum ef?ciency of photosystem,Kumar et al.(2012)

QRSDWR(C/T)Chlorophyll content(under water stress)

4B xgwm66QSH(C)CL(three soil temperatures)Rebetzke et al.(2007) 6B Xwmc473QSH(C)CL(osmotic stress)Landjeva et al.(2008)

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traits have been mapped to various regions of the group2 chromosomes(both the short arm and the distal part of the long arm)(Cattivelli et al.2002).In this study,altogether11 conditional QTLs were detected on chromosomes6A,6D, 7B,7D,2A,2B,and2D.Of these QTLs,four were main-effect QTLs;four were detected on the6D chromosome;two on the6A chromosome;one each on chromosomes7B,7D, and2D;and two each on chromosomes2A and2B.The results were in accordance with those from former studies, which further validated that the conditional analysis method was feasible and necessary for the analysis of traits control-ling resistance to stresses,such as drought,salty soil,lower or higher temperatures and so on.

In summary,we detected88QTLs concerned with12gen-eral traits of wheat seedlings and22special QTLs concerned with drought tolerance of the seedlings by conditional and unconditional QTL analyses.Thus,these QTLs would be of great value for marker-assisted selection in breeding pro-grammes.The conditional analysis method has been applied to the genetic research on drought tolerance of wheat for the ?rst time which has a great instructional signi?cance for the genetic study of stress tolerance traits.

Acknowledgements

This research was supported by the National Basic Research Pro-gramme of China(863Programme,2011AA100103)and Cre-ation and Utilization of Agriculture-Biology Resource of Shandong Province,China.

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Received9January2012,in revised form3February2013;accepted11March2013

Published on the Web:12August2013

Journal of Genetics V ol.92,No.2,August2013

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