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QTL analysis for agronomic traits in a barley doubled haploids population grown in Iran
Plant Science 169 (2005) 1008–1013 www.elsevier.com/locate/plantsci
QTL analysis for agronomic traits in a barley doubled haploids population grown in Iran Sayed Ali Peighambari a, Bahman Yazdi Samadi a, Alireza Nabipour a, Gills Charmet b, Ahmad Sarrafi c,* a
Department of Agronomy and Plant Breeding, Faculty of Agriculture, University of Tehran, Karaj, Iran b INRA Clermont-Ferrand, 234 Av. du Brezet, 63039 Clermont-ferrand, Cedex France c Department of Biotechnology and Plant Breeding, BAP-IFR 40-ENSAT–INP,18 Chemin de Borde Rouge, BP 32607-31326 Castanet France Received 15 December 2004; received in revised form 4 May 2005; accepted 10 May 2005 Available online 13 June 2005
Abstract Seventy-two doubled haploid (DH) barley lines and their two parents ‘Steptoe’ and ‘Morex’ were planted in a randomized complete block design with three replications at the research farm of the University of Tehran, Faculty of Agriculture, Karaj, Iran, for two growing seasons. Each plot consisted of a 2 m row and was scored for 10 agronomic traits. Analysis of variance showed that the main effects of genotype and environment (year) were significant for all studied traits. Genotype by environment interaction was also significant for all the traits except for plant height and seed/spike. Heritability estimates were more than 0.6 for all of the traits. A genetic map comprising 327 molecular markers was recovered from Grain Gene and used for quantitative trait loci (QTL) mapping. This map is fairly saturated with a total length of 1226 cM and an average marker spacing of 3.75 cM. Twenty-three QTLs controlling different studied traits were identified. Phenotypic variance explained by these QTLs varies from 11.9 to 61.1%. QTLs were identified for all traits on all chromosomes except chromosome 6H. Highest LOD scores were obtained for the dates of spike initiation and flowering on chromosome 2H, and for plant height and spike length on chromosome 3H. QTLs for 1000-seed weight, an indicator of drought tolerance, were found on chromosomes 1H and 5H, with positive alleles from ‘Morex’, and on chromosome 7H with positive alleles from ‘Steptoe’. The specificity of the QTLs for Iranian conditions as well as their usefulness for marker-assisted selection in dry conditions is discussed. # 2005 Elsevier Ireland Ltd. All rights reserved. Keywords: Doubled haploid; Drought tolerance; Heritability; Barley; QTL; Transgressive variation
1. Introduction Barley (Hordeum vulgare L.) ranks fourth among the cereals in worldwide production. It is grown as a source of malt for beer [1] as well as for direct human consumption and for animal feed [2]. The main objectives of barley breeding programmes are the development of cultivars with high-grain yield and high-malt quality. Protein content is a determinant of malt quality, too high or low grain protein content would not be suitable for malting [3]. Malting yield is determined by the product of grain yield per unit area and * Corresponding author. Tel.: +33 5 62193580; fax: +33 5 62193581. E-mail address: [email protected] (A. Sarrafi).
malt extract in the grain. Therefore, consideration of both components is important when breeding for malting [4]. Seed yield in barley, as in other crops, depends on many characters especially yield components, which are controlled by several genes, their effects being modified by environmental factors [5–9]. Identification of the genetic loci contributing to variation in traits, which are quantitative in nature, such as yield and yield components, has great importance in plant breeding. The knowledge of the number and effects of quantitative trait loci (QTL) can help breeders to understand the genetic control of these traits and to design more efficient selection strategies to improve the traits [10]. Mapping quantitative trait loci in plants is usually conducted using a population derived from a cross between two lines.
0168-9452/$ – see front matter # 2005 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.plantsci.2005.05.018
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Thus, the QTLs found represent only a small part of the genetic picture and represent limited economic interests in a marker-assisted selection (MAS) programme. The power of such QTL detection and mapping strategies and the estimation of the effects depend to a large extent on the initial choice of the two parental lines. Most experiments aimed at identifying QTLs use progenies from single crosses between fixed breeding lines that contrast for the trait of interest. QTL analysis has been undertaken in virtually all plant species with molecular marker linkage maps available [11]. The development of molecular marker techniques has allowed the construction of high-density genome linkage maps for a range of crops including barley (Hordeum Vulgare L.) [12–15]. A barley genetic map from the cross ‘Steptoe’ ‘Morex’ consisting of 327 loci was constructed by the North American Barley Genome Mapping Project [14,15]. This map has been employed to identify, locate and estimate the phenotypic effects of QTLs that determine economically important traits such as grain yield [6,7,16], malting quality [6,7] and disease resistance [17,18]. Breeding populations typically exhibit genotype by environment (G E) interaction when tested in diverse environments. In the case of such interactions, at least some of the genes underlying QTLs would also show G E interaction. QTL E interaction would be expressed as significant effects detected only in a subset of the total number of environments or changes in the magnitude of significant effects of QTL across environments. The potential of QTL analysis for introgression of alleles from exotic germplasm with minimum linkage drag has been discussed [19]. The utility of marker-assisted selection for traits such as yield and quality in barley has been demonstrated [20,21]. This study summarizes QTL analyses based on the evaluation of a population of 72 F1-derived doubled haploid (DH) lines from the cross of ‘Steptoe’ ‘Morex’ in dry land environments in Karaj, Iran for 2 years.
randomized complete block with three replications. Each doubled haploid or parental line was sown in a 2 m long row (40 seeds per row) and scored for days to flowering (flo), spike initiation (spi), and maturity (mat), plant height (hei) (cm), spike length (spl) (mm), spikes per plant (spp), seeds per spike (sps), 1000-seed weight (tsw) (g), protein percentage (prp) and seed yield (syi) (g). Analysis of variance (ANOVA) was performed on the combined data from both years. Approximate heritability across years was estimated from h2 ¼ s 2g =ðs 2g þ s 2GE =n þ s 2e =nÞ, where s 2g is the genotypic variance, s 2GE the G E variance component and n is the number of environments [5,8,9]. Variance components were computed by equating mean squares to their expectations. Covariance analysis was performed for seed yield, seeds per spike, spike number per plant and spike length using number of plants per row as covariate, and significant differences were found for these traits. ANOVAs of the adjusted data were performed using MSTATC software for seed per spike, spike number per plant and spike length, and significant differences were found for all of them. Pair-wise Pearson correlations were computed using SPSS software. The genetic map of this population comprises 327 markers with an average density of 3.75 cM [14,15]. Current mapping and QTL on-line data sets are available in Grain Genes through the Gopher Server. QTL analyses were first conducted separately for each trait in each year and as genotype environment interaction was detected, we have reported QTLs based on multi-environment means. Analyses were performed using MULTIQTL software [23,24]. QTL effects were considered significant if they exceeded a LOD score of 2.23 ( p 0.027) for a sparse map case [25]. LOD significance was also tested against its empirical distribution as established through 1000-permutation with MULTIQTL. The LOD peaks were considered the most likely position of QTL effects. 95% confidence intervals were calculated by 1000-bootstrap re-sampling [26], as proposed in the MULTIQTL package.
2. Materials and methods
3. Results and discussion
Seventy-two doubled haploid barley lines from the barley ‘Steptoe’ (CI15229) ‘Morex’ (CI15773) cross population [6,7] were used in this study. The population was derived from an F1 hybrid of this cross by a modified ‘Hordeum bulbosum’ method [22]. The DHs were developed by the Oregon State University Barley Breeding Programme and kindly provided by Dr. Hayes (Department of Crop and Soil Science, Oregon State University, Corvallis, OR 973314501, USA). ‘Steptoe’ is a high yielding, broadly adapted, six-rowed, spring feed-type and drought sensitive variety, whereas ‘Morex’ is a drought tolerant, six-rowed and spring malting barley [1]. The seeds were sown in the field of the Faculty of Agriculture, University of Tehran, under dry conditions in fall. The experimental design was a
Analysis of variance of the 72 doubled haploid lines and their parents (‘Steptoe’ and ‘Morex’) showed a highly significant genotype effect for all the studied traits and also a significant year (environment) effect for 5 characters out of 10 studied, namely: plant height (hei), spike length (spl), seeds per spike (sps), percentage of protein (ppr) and seed yield (syi) (Table 1). Genotype environment (G E) interaction was also significant for all the traits, except plant height (hei), seeds per spike (sps) and seed yield (syi) (Table 1). Previous studies have also reported significant genotype and genotype-environment effect for different traits in this population [27–29]. ‘Morex’ showed significantly higher values when compared with ‘Steptoe’ for traits: flo, spi, spp, tsw and syi (Table 2). The difference
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Table 1 Results of combined analysis of variance for 10 agronomic traits in a population of 72 DH barley and their two parents Source of variation
Df
Year Error Genotype EG Covariate Error
1 4 73 73 1 291
Mean squares flo
spi
mat
hie
spl
spp
sps
tsw
prp
syi
475.89 ns 468.35 66.34** 34.01** 5.67 10.97
897.82 ns 144.42 81.04** 33.84** 120.08 17.4
263.84 ns 1530.65 17.02** 11.97** 2.06 7.32
6885.25* 558.281 222.20** 38.17 ns 214.5 45.43
2648.99** 66.64 265.25** 120.72** 208.44 33.16
69.47 ns 26.72 3.87* 3.75* 55.42 2.73
7796.79* 438.08 112.29** 65.24 ns 445.34 67.34
707.22 ns 752.73 42.12** 17.99* 1.88 13.28
201.13* 20.66 1.53** 0.92** 0.4 0.42
878.18** 286570 10257.66** 8815.93 ns 205084 6747.75
flo, days to flowering; spi, spike initiation; mat, days to maturity; hei, plant height (cm); spl, spike length (cm); spp, spike per plant; sps, seeds per spike; tsw, 1000-seed weight (g); prp, protein percentage; syi, seed yield. * and **, significant at 0.05 and 0.01 probability level; ns, non significant.
between the mean of doubled haploids (XDHs) and their midparent was not significant, indicating that the 72 DHs in this experiment are representative of the total possible DHs from the cross ‘Steptoe’ ‘Morex’ and that the studied traits are mostly controlled by additive gene effect (Table 2). The best DH when compared with the best parent showed significantly higher values for four traits, which are mat (earliness), hei, spl and sps. Bregitzer and Campbell [30] in a study to determine the QTLs associated with plant regeneration in this population also reported that transgressive segregation occurred. This phenomenon of ‘‘transgressive variation’’ could be interpreted as favourable alleles being dispersed between the two parental lines. Narrowsense heritabilities (h2) presented in Table 2 showed high values ranging from 62.42 to 89.29% for all traits. Positive correlations were observed between seed yield (syi) and plant height (hei), spike per plant (spp), seed per spike (sps) and 1000-seed weight (tsw) (Table 3). The coefficients of determination (R2) for hei, spp, sps and tsw were 11, 10, 20 and 9%, respectively. The highest variations for all traits were observed for syi and spp and the lowest ones were recorded for mat and flo. The multiple regression analysis showed that 71% of seed yield variation (X) was expressed through spp (x1), tsw (x2), sps (x3) and hei (x4). The best fitted equation for seed yield based on stepwise regression analysis was X = 428.8 + 17.22x1 +
5.82x2 + 3.52x3 + 1.70x4. Using Hotelling’s T-test for comparing trait means (years 1 and 2), the T2 and F-values were 178.5 and 16.8, respectively, indicating a strong environmental effect on seed yield. These results also suggest that traits like number of seeds per spike and 1000-seed weight could be used as selection indices for improving grain yield of the studied barley genotypes. From one to four QTLs were detected for each of the 10 traits studied using the ‘QTL E’ option in MULTIQTL programme (Table 4). A region with QTLs having positive alleles from ‘Morex’ for late flowering (flo-1H-1), late maturity (mat-1H-1) and high number of seed per spike (sps1H-1) were identified on chromosome 1H. The positive allele for the QTL of 1000-seed weight (tsw-1H-1) in this region comes from ‘Steptoe’. The QTL for 1000-seed weight (tsw-1H-1) does not show any difference for additive effects with year (stable QTL) (Table 4). Six QTLs are located on chromosome 2H, controlling date of flowering, spike initiation, plant height, spike length, percentage of protein and seed yield. These QTLs appear to be quite stable between years, their phenotypic variance as well as their additive effects being of the same magnitude in 2001 and 2002. Han and Ullrich [31] reported that QTLs of grain protein and kernel weight located on chromosome 2H were consistent over years. They also found two QTLs for grain protein with different signs in this group. Our QTL on
Table 2 Genetic gain and heritability for 10 agronomic traits in a population of 72 DH barley and their two parents Item
flo
spi
mat
hei
spl
spp
sps
tsw
prp
syi
Steptoe (P1) Morex (P2) P1–P2 Xp = (P1 + P2)/2 XDHsa XDHs Xp Best DH GGc = BDH BPb h2d
174.57 182.30 7.93* 178.44 179.45 1.01 ns 172.41 2.16 ns 77.89
158.22 169.78 11.56* 164.00 164.82 0.82 ns 157.52 0.7 ns 75.99
206.27 207.93 1.66 ns 207.10 206.58 0.52 ns 201.98 4.29* 70.15
91.27 93.67 0.24 ns 92.47 87.45 5.02 ns 103.37 9.70* 89.29
91.27 93.67 0.24 ns 92.47 87.45 5.02 ns 103.37 9.70* 80.01
4.40 6.71 2.31* 5.57 5.67 0.1 ns 7.42 0.71 ns 62.42
52.75 53.91 1.16 ns 53.33 52.40 0.93 ns 64.61 10.70* 71.92
31.08 39.60 8.52* 35.34 33.15 2.19 ns 38.84 0.76 ns 78.98
12.50 11.21 1.29* 11.85 11.24 0.61 ns 12.25 0.25 ns 74.24
202.06 321.93 119.87* 262.00 227.57 34.43 ns 348.60 26.67 ns 65.94
ns, nonsignificant. flo, days to flowering; spi, spike initiation; mat, days to maturity; hei, plant height (cm); spl, spike length (cm); spp, spike per plant; sps, seed per spike; tsw, 1000-seed weight (g); prp, protein percentage; syi, seed yield. a Mean of doubled haploids. b Best parent. c Genetic gain. d Heritability estimated from 2 years experiment taking into account s 2GE . * Significant at the 0.05 probability level.
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Table 3 Simple phenotypic correlations among characters in a population of 72 DH barley and their two parents from data combined across environments Trait
flo
spi
mat
hei
spl
spp
sps
tsw
prp
syi
flo spi mat hei spl spp sps tsw prp syi
1 0.755** 0.421** 0.398* 0.116 0.286* 0.164 0.227 0.432** 0.037
1 0.399** 0.267 0.057 0.283* 0.19 0.174 0.438** 0.002
1 0.162 0.067 0.259* 0.189 0.022 0.091 0.122
1 0.569** 0.175 0.055 0.113 0.210 0.325**
1 0.114 0.106 0.226 0.008 0.058
1 0.119 0.172 0.151 0.447**
1 0.119 0.064 0.324**
1 0.041 0.307**
1 0.208
1
flo, days to flowering; spi, spike initiation; mat, days to maturity; hei, plant height (cm); spl, spike length (cm); spp, spike per plant; sps, seed per spike; tsw, 1000-seed weight (g); prp, protein percentage; syi, seed yield. * Significant at the 0.05 probability level. ** Significant at the 0.01 probability level.
affecting grain protein were observed in only 9 environments out of 16 and on 5 chromosomes. However, four of them were consistently expressed on chromosomes 2H (two), 4H and 5H. The QTL that we have found in our experiment on chromosome 2H (prp-2H-1) is located in the same map position as one of the two QTLs they reported in 2H. The other protein QTL identified in our conditions (prp4H-1) is also located very close to a corresponding QTL in Hayes and Iyambo [27]. Hayes and Iyambo [27] also reported that 11 QTLs for plant height were non-consistently
chromosome 2H concerning percentage of protein (prp-2H1) is in agreement with the above-mentioned works. Hayes and Iyambo [27], following a series of experiments involving 16 environments, reported that QTLs affecting yield were present in all of the environments and on all seven chromosomes, but only two of them detected on chromosomes 3H and 1H were consistent. Despite not being completely consistent over the environments, five out of nine yield QTLs identified were later confirmed in other studies [21,28,29,32]. Hayes and Iyambo [27] reported that QTLs
Table 4 Map positions and effect of QTLs detected for 10 agronomic traits in a population of 72 DH and their two parents, in 2001–2002 Trait
QTL
Linkage group
Position a
LOD
P.E.V.b
Additive effect
2001 (1)
2002 (2)
2001
2002
Date of flowering (day)
flo-1H-1 flo-2H-1 flo-3H-1
1H 2H 3H
141 80 109
3.32 8.49 3.71
0.153 0.205 0.141
0.140 0.307 0.181
1.54 1.93 1.42
3.37 5.57 4.10
Date of spike initiation (day)
spi-1H-1 spi-2H-1 spi-5H-1 spi-7H-1
1H 2H 5H 7H
100 75 50 105
3.08 6.97 5.15 2.83
0.143 0.183 0.191 0.124
0.149 0.263 0.155 0.121
1.52 1.85 1.91 1.25
3.83 5.43 3.67 3.31
Date of maturity (day)
mat-1H-1 mat-3H-1
1H 3H
144 61
3.46 4.27
0.222 0.120
0.056 0.269
1.44 0.95
0.48 2.65
Plant height (cm)
hei-2H-1 hei-3H-1 hei-4H-1
2H 3H 4H
186 70 59
3.96 10.62 3.72
0.161 0.309 0.119
0.128 0.342 0.153
3.99 7.75 3.94
2.89 6.75 3.95
Spike length (mm)
spl-2H-1 spl-3H-1
2H 3H
80 77
4.79 15.8
0.141 0.611
0.208 0.208
6.49 17.40
2.87 3.26
Spike per plant
spp-1H-1 spp-5H-1
1H 5H
118 50
2.70 6.02
0.202 0.299
0.051 0.125
1.12 1.48
0.04 0.42
Seed per spike
sps-1H-1
1H
75
6.22
0.249
0.247
5.00
5.48
Thousand-seeds weight (g)
tsw-1H-1 tsw-5H-1 tsw-7H-1
1H 5H 7H
118 66 146
5.39 5.74 2.86
0.198 0.202 0.139
0.209 0.196 0.146
2.98 3.02 2.43
2.02 1.90 1.55
Protein percentage
prp-2H-1 prp-4H-1
2H 4H
65 134
4.80 2.23
0.260 0.186
0.102 0.088
0.63 0.53
0.26 0.25
Seed yield (g)
syi-2H-1
2H
72
3.6
0.215
0.069
4.02
1.92
a b
Expressed, in Kosambi cM, from origin of the linkage group (end of short arm). Proporation expected variance (r2) ‘‘value determinted by MULTIQTL-Version 2.4’’.
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present in all 16 environments and on all chromosomes (except 1H). Kandemir et al. [33] found a plant height QTL on chromosome 3H. According to Hayes and Iyambo [27], the plant height QTL on chromosome 3H is very consistent, because it was expressed in 12 environments out of 16. The QTL we have identified on chromosome 3H for plant height (hei-3H-1) is located in the same region. Our QTL on chromosome 2H (hei-2H-1) is also located in the vicinity of the QTL presented by Hayes and Iyambo [27]. Hayes and Iyambo [27] also reported that QTLs on chromosomes 7H, 2H, 3H and 4H for days to heading were non-consistently observed in all 16 environments. However, the only stable one that they detected was located on chromosome 2H. The QTL that we found for date of flowering on the same chromosome (flo-2H-1) is located at about 30 cM away from their QTL. In our experiment chromosome 3H harbours QTLs for four traits. The first two, with positive alleles from ‘Steptoe’ for days to flowering and maturity (flo-3H-1 and mat-3H-1), had more pronounced effects in 2002 than in 2001. Another region on chromosome 3H shows positive alleles from ‘Morex’ for spike length and plant height, with relatively stable effect on the latter trait (Table 4). The other three chromosomes bear QTLs for only two or three different traits: plant height and protein percentage on chromosome 4H; days to spike initiation, spike number and 1000-seed weight on chromosome 5H (Table 4). These QTLs showed rather stable effects among years. Finally, two QTLs for days to spike initiation and 1000-seed weight were identified on chromosome 7H. Most QTLs already reported from previous studies using the ‘Steptoe’ ‘Morex’ population focused on disease tolerance and malting quality and related enzyme activities [6,7,17,18]. As we have demonstrated, some of the QTLs detected in our experiment confirm those presented in previous reports. Our study thus represents a contribution to the knowledge of QTLs segregating in the DH population of ‘Steptoe’ ‘Morex’. The most important ones, with regard to their effects, their environmental stability and their potential for plant breeding, are those for flowering date on chromosome 2H and for plant height and spike length on chromosome 3H. Some QTLs for grain yield have been reported in this cross [21,34]. They are located on chromosomes 1H, 2H, 3H and 5H. In the present study, we found only one QTL located on chromosome 2H. However, in our study, QTLs for yield components were found on chromosomes 1H and 5H (tsw1H-1 for 1000-seed weight and spp-5H-1 for spike per plant). Several QTL co-locations confirm the observed correlations among the traits. For example, the correlations between seeds per spike and seed yield (positive) and between seed yield and protein percentage (negative) are consistent with the co-location observed on chromosome 2H (Tables 3 and 4). If a combination of high yield and highprotein content is sought, as for example in fodder barley, QTL pyramiding can be followed using a set of markers
spanning the confidence interval of the QTL position, as suggested by Charmet et al. [35] and Hospital and Charcosset [36]. Thousand-seed weight is controlled by three stable QTLs, which do not co-locate with any QTL for protein. QTLs on chromosomes 1H and 5H for 1000-seed weight have positive alleles from ‘Morex’, while the one on chromosome 7H has positive allele from ‘Steptoe’. Markerassisted selection could be successfully employed to have a desirable combination at all three loci, which could be of interest in breeding programmes for malting quality. Moreover, the favourable alleles for 1000-seed weight at QTL tsw-1H-1 can be associated with desirable alleles for early flowering and maturity, giving a good combination to escape drought. Han and Ullrich [31] also reported several co-locations for different traits, for example, QTLs for kernel weight and grain protein were located in the same region on 2H. These co-locations could be either because of linkage between two genes or the pleiotropy effect of one gene. In the latter case, the correlation between traits will never be broken. This study is the first report of QTL analysis in barley evaluated in Iran under dry versus irrigated management. Despite the small sample size used for technical reasons, a total of 23 significant QTLs were found for the 10 studied traits. We had focused on grain yield, protein content and developmental traits, which were supposed to be associated with drought adaptation. However, most QTLs showed remarkable stability over management practices and over years (Table 4). Although the detected regions need to be more precisely mapped, the information obtained should help in marker-assisted selection.
Acknowledgment The authors thank professor Catherine Carter (South Dakota State University) for English corrections.
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[20] M. Ayoub, E. Armstrong, G. Bridger, M.G. Fortin, D.E. Mather, Marker-based selection in barley for a QTL region affecting alphaamylase activity of malt, Crop Sci. 43 (2003) 556–561. [21] H. Zhu, G. Briceno, R. Dovel, P.M. Hayes, B.H. Liu, C.T. Liu, S.E. Ullrich, Molecular breeding for grain yield in barley: an evaluation of QTL effects in a spring barley cross, Theor. Appl. Genet. 98 (1999) 772–779. [22] F. Chen, P.M. Hayes, A comparison of Hordeum bulbosum-mediated haploid production efficiency in barley using in vitro floret and tiller culture, Theor. Appl. Genet. 77 (1989) 701–704. [23] A.B. Korol, Y.I. Ronin, E. Nevo, P. Hayes, Multi-interval mapping of correlated trait complexes, Heredity 80 (1998) 273–284. [24] A.B. Korol, Y.I. Ronin, F. Nevo, Approximated analysis of QTLenvironmental interaction with no limits on the number of environments, Genetics 148 (1998) 2015–2028. [25] E.S. Lander, D. Botstein, Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps, Genetics 121 (1989) 185–199. [26] C.M. Lebreton, P.M. Visscher, C.S. Haley, A. Semikhodskii, S.A. Quarrie, A nonparametric bootstrap method for testing close linkage vs. pleiotropy on coincident quantitative trait loci, Genetics 150 (1998) 931–943. [27] P.M. Hayes, O.E. Iyambo, Summary of QTL effects in the Steptoe Morex population, Barley Genet. Newsl. 23 (1994) 98–143. [28] I. Romagosa, F. Han, S. Ullrich, P.M. Hayes, D. Wesenberg, Verification of QTL through realized molecular marker-assisted selection responses in a barley cross, Mol. Breed. 5 (1999) 143–152. [29] I. Romagosa, S.E. Ullrich, F. Han, P.M. Hayes, Use of the additive main effects and multiplicative interaction model in QTL mapping for adaptation in barley, Theor. Appl. Genet. 93 (1996) 30–37. [30] P. Bregitzer, R.D. Campbell, Genetic markers associated with green and albino plant regeneration from embryogenic barley callus, Crop Sci. 41 (2001) 173–179. [31] F. Han, S.E. Ullrich, Mapping of quantitative trait loci associated with malting quality in barley, Barley Genet. Newsl. 23 (1994) 84–97. [32] S.R. Larson, D. Kadyrzhanova, C. McDonald, M. Sorrells, T.K. Blake, Evaluation of barley chromosome 3 yield QTL in a backcross F2 population using PCR-STS markers, Theor. Appl. Genet. 93 (1996) 618–625. [33] N. Kandemir, A. Kleinhofs, D.A. Kudrna, S.E. Ullrich, Molecular marker assisted analysis of two yield QTL in barley, in: Plant & Animal Genome VII Conference, Town & Country Hotel, San Diego, CA, January 17–21, 1999. [34] N. Kandemir, B.L. Jones, D.M. Wesenberg, S.E. Ullrich, A. Kleinhofs, Marker-assisted analysis of three grain yield QTL in barley (Hordeum vulgare L.) using near isogenic lines, Mol. Breed. 6 (2000) 157–167. [35] G. Charmet, N. Robert, M.R. Perretant, G. Gay, P. Sourdille, C. Groos, M. Bernard, Marker assisted recurrent selection for cumulating additive and interactive QTLs in recombinant inbred line, Theor. Appl. Genet. 99 (1999) 1143–1148. [36] F. Hospital, A. Charcosset, Marker assisted introgression of quantitative trait loci, Genetics 147 (1997) 1469–1485.
QTL analysis for agronomic traits in a barley doubled haploids population grown in Iran Sayed Ali Peighambari a, Bahman Yazdi Samadi a, Alireza Nabipour a, Gills Charmet b, Ahmad Sarrafi c,* a
Department of Agronomy and Plant Breeding, Faculty of Agriculture, University of Tehran, Karaj, Iran b INRA Clermont-Ferrand, 234 Av. du Brezet, 63039 Clermont-ferrand, Cedex France c Department of Biotechnology and Plant Breeding, BAP-IFR 40-ENSAT–INP,18 Chemin de Borde Rouge, BP 32607-31326 Castanet France Received 15 December 2004; received in revised form 4 May 2005; accepted 10 May 2005 Available online 13 June 2005
Abstract Seventy-two doubled haploid (DH) barley lines and their two parents ‘Steptoe’ and ‘Morex’ were planted in a randomized complete block design with three replications at the research farm of the University of Tehran, Faculty of Agriculture, Karaj, Iran, for two growing seasons. Each plot consisted of a 2 m row and was scored for 10 agronomic traits. Analysis of variance showed that the main effects of genotype and environment (year) were significant for all studied traits. Genotype by environment interaction was also significant for all the traits except for plant height and seed/spike. Heritability estimates were more than 0.6 for all of the traits. A genetic map comprising 327 molecular markers was recovered from Grain Gene and used for quantitative trait loci (QTL) mapping. This map is fairly saturated with a total length of 1226 cM and an average marker spacing of 3.75 cM. Twenty-three QTLs controlling different studied traits were identified. Phenotypic variance explained by these QTLs varies from 11.9 to 61.1%. QTLs were identified for all traits on all chromosomes except chromosome 6H. Highest LOD scores were obtained for the dates of spike initiation and flowering on chromosome 2H, and for plant height and spike length on chromosome 3H. QTLs for 1000-seed weight, an indicator of drought tolerance, were found on chromosomes 1H and 5H, with positive alleles from ‘Morex’, and on chromosome 7H with positive alleles from ‘Steptoe’. The specificity of the QTLs for Iranian conditions as well as their usefulness for marker-assisted selection in dry conditions is discussed. # 2005 Elsevier Ireland Ltd. All rights reserved. Keywords: Doubled haploid; Drought tolerance; Heritability; Barley; QTL; Transgressive variation
1. Introduction Barley (Hordeum vulgare L.) ranks fourth among the cereals in worldwide production. It is grown as a source of malt for beer [1] as well as for direct human consumption and for animal feed [2]. The main objectives of barley breeding programmes are the development of cultivars with high-grain yield and high-malt quality. Protein content is a determinant of malt quality, too high or low grain protein content would not be suitable for malting [3]. Malting yield is determined by the product of grain yield per unit area and * Corresponding author. Tel.: +33 5 62193580; fax: +33 5 62193581. E-mail address: [email protected] (A. Sarrafi).
malt extract in the grain. Therefore, consideration of both components is important when breeding for malting [4]. Seed yield in barley, as in other crops, depends on many characters especially yield components, which are controlled by several genes, their effects being modified by environmental factors [5–9]. Identification of the genetic loci contributing to variation in traits, which are quantitative in nature, such as yield and yield components, has great importance in plant breeding. The knowledge of the number and effects of quantitative trait loci (QTL) can help breeders to understand the genetic control of these traits and to design more efficient selection strategies to improve the traits [10]. Mapping quantitative trait loci in plants is usually conducted using a population derived from a cross between two lines.
0168-9452/$ – see front matter # 2005 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.plantsci.2005.05.018
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Thus, the QTLs found represent only a small part of the genetic picture and represent limited economic interests in a marker-assisted selection (MAS) programme. The power of such QTL detection and mapping strategies and the estimation of the effects depend to a large extent on the initial choice of the two parental lines. Most experiments aimed at identifying QTLs use progenies from single crosses between fixed breeding lines that contrast for the trait of interest. QTL analysis has been undertaken in virtually all plant species with molecular marker linkage maps available [11]. The development of molecular marker techniques has allowed the construction of high-density genome linkage maps for a range of crops including barley (Hordeum Vulgare L.) [12–15]. A barley genetic map from the cross ‘Steptoe’ ‘Morex’ consisting of 327 loci was constructed by the North American Barley Genome Mapping Project [14,15]. This map has been employed to identify, locate and estimate the phenotypic effects of QTLs that determine economically important traits such as grain yield [6,7,16], malting quality [6,7] and disease resistance [17,18]. Breeding populations typically exhibit genotype by environment (G E) interaction when tested in diverse environments. In the case of such interactions, at least some of the genes underlying QTLs would also show G E interaction. QTL E interaction would be expressed as significant effects detected only in a subset of the total number of environments or changes in the magnitude of significant effects of QTL across environments. The potential of QTL analysis for introgression of alleles from exotic germplasm with minimum linkage drag has been discussed [19]. The utility of marker-assisted selection for traits such as yield and quality in barley has been demonstrated [20,21]. This study summarizes QTL analyses based on the evaluation of a population of 72 F1-derived doubled haploid (DH) lines from the cross of ‘Steptoe’ ‘Morex’ in dry land environments in Karaj, Iran for 2 years.
randomized complete block with three replications. Each doubled haploid or parental line was sown in a 2 m long row (40 seeds per row) and scored for days to flowering (flo), spike initiation (spi), and maturity (mat), plant height (hei) (cm), spike length (spl) (mm), spikes per plant (spp), seeds per spike (sps), 1000-seed weight (tsw) (g), protein percentage (prp) and seed yield (syi) (g). Analysis of variance (ANOVA) was performed on the combined data from both years. Approximate heritability across years was estimated from h2 ¼ s 2g =ðs 2g þ s 2GE =n þ s 2e =nÞ, where s 2g is the genotypic variance, s 2GE the G E variance component and n is the number of environments [5,8,9]. Variance components were computed by equating mean squares to their expectations. Covariance analysis was performed for seed yield, seeds per spike, spike number per plant and spike length using number of plants per row as covariate, and significant differences were found for these traits. ANOVAs of the adjusted data were performed using MSTATC software for seed per spike, spike number per plant and spike length, and significant differences were found for all of them. Pair-wise Pearson correlations were computed using SPSS software. The genetic map of this population comprises 327 markers with an average density of 3.75 cM [14,15]. Current mapping and QTL on-line data sets are available in Grain Genes through the Gopher Server. QTL analyses were first conducted separately for each trait in each year and as genotype environment interaction was detected, we have reported QTLs based on multi-environment means. Analyses were performed using MULTIQTL software [23,24]. QTL effects were considered significant if they exceeded a LOD score of 2.23 ( p 0.027) for a sparse map case [25]. LOD significance was also tested against its empirical distribution as established through 1000-permutation with MULTIQTL. The LOD peaks were considered the most likely position of QTL effects. 95% confidence intervals were calculated by 1000-bootstrap re-sampling [26], as proposed in the MULTIQTL package.
2. Materials and methods
3. Results and discussion
Seventy-two doubled haploid barley lines from the barley ‘Steptoe’ (CI15229) ‘Morex’ (CI15773) cross population [6,7] were used in this study. The population was derived from an F1 hybrid of this cross by a modified ‘Hordeum bulbosum’ method [22]. The DHs were developed by the Oregon State University Barley Breeding Programme and kindly provided by Dr. Hayes (Department of Crop and Soil Science, Oregon State University, Corvallis, OR 973314501, USA). ‘Steptoe’ is a high yielding, broadly adapted, six-rowed, spring feed-type and drought sensitive variety, whereas ‘Morex’ is a drought tolerant, six-rowed and spring malting barley [1]. The seeds were sown in the field of the Faculty of Agriculture, University of Tehran, under dry conditions in fall. The experimental design was a
Analysis of variance of the 72 doubled haploid lines and their parents (‘Steptoe’ and ‘Morex’) showed a highly significant genotype effect for all the studied traits and also a significant year (environment) effect for 5 characters out of 10 studied, namely: plant height (hei), spike length (spl), seeds per spike (sps), percentage of protein (ppr) and seed yield (syi) (Table 1). Genotype environment (G E) interaction was also significant for all the traits, except plant height (hei), seeds per spike (sps) and seed yield (syi) (Table 1). Previous studies have also reported significant genotype and genotype-environment effect for different traits in this population [27–29]. ‘Morex’ showed significantly higher values when compared with ‘Steptoe’ for traits: flo, spi, spp, tsw and syi (Table 2). The difference
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Table 1 Results of combined analysis of variance for 10 agronomic traits in a population of 72 DH barley and their two parents Source of variation
Df
Year Error Genotype EG Covariate Error
1 4 73 73 1 291
Mean squares flo
spi
mat
hie
spl
spp
sps
tsw
prp
syi
475.89 ns 468.35 66.34** 34.01** 5.67 10.97
897.82 ns 144.42 81.04** 33.84** 120.08 17.4
263.84 ns 1530.65 17.02** 11.97** 2.06 7.32
6885.25* 558.281 222.20** 38.17 ns 214.5 45.43
2648.99** 66.64 265.25** 120.72** 208.44 33.16
69.47 ns 26.72 3.87* 3.75* 55.42 2.73
7796.79* 438.08 112.29** 65.24 ns 445.34 67.34
707.22 ns 752.73 42.12** 17.99* 1.88 13.28
201.13* 20.66 1.53** 0.92** 0.4 0.42
878.18** 286570 10257.66** 8815.93 ns 205084 6747.75
flo, days to flowering; spi, spike initiation; mat, days to maturity; hei, plant height (cm); spl, spike length (cm); spp, spike per plant; sps, seeds per spike; tsw, 1000-seed weight (g); prp, protein percentage; syi, seed yield. * and **, significant at 0.05 and 0.01 probability level; ns, non significant.
between the mean of doubled haploids (XDHs) and their midparent was not significant, indicating that the 72 DHs in this experiment are representative of the total possible DHs from the cross ‘Steptoe’ ‘Morex’ and that the studied traits are mostly controlled by additive gene effect (Table 2). The best DH when compared with the best parent showed significantly higher values for four traits, which are mat (earliness), hei, spl and sps. Bregitzer and Campbell [30] in a study to determine the QTLs associated with plant regeneration in this population also reported that transgressive segregation occurred. This phenomenon of ‘‘transgressive variation’’ could be interpreted as favourable alleles being dispersed between the two parental lines. Narrowsense heritabilities (h2) presented in Table 2 showed high values ranging from 62.42 to 89.29% for all traits. Positive correlations were observed between seed yield (syi) and plant height (hei), spike per plant (spp), seed per spike (sps) and 1000-seed weight (tsw) (Table 3). The coefficients of determination (R2) for hei, spp, sps and tsw were 11, 10, 20 and 9%, respectively. The highest variations for all traits were observed for syi and spp and the lowest ones were recorded for mat and flo. The multiple regression analysis showed that 71% of seed yield variation (X) was expressed through spp (x1), tsw (x2), sps (x3) and hei (x4). The best fitted equation for seed yield based on stepwise regression analysis was X = 428.8 + 17.22x1 +
5.82x2 + 3.52x3 + 1.70x4. Using Hotelling’s T-test for comparing trait means (years 1 and 2), the T2 and F-values were 178.5 and 16.8, respectively, indicating a strong environmental effect on seed yield. These results also suggest that traits like number of seeds per spike and 1000-seed weight could be used as selection indices for improving grain yield of the studied barley genotypes. From one to four QTLs were detected for each of the 10 traits studied using the ‘QTL E’ option in MULTIQTL programme (Table 4). A region with QTLs having positive alleles from ‘Morex’ for late flowering (flo-1H-1), late maturity (mat-1H-1) and high number of seed per spike (sps1H-1) were identified on chromosome 1H. The positive allele for the QTL of 1000-seed weight (tsw-1H-1) in this region comes from ‘Steptoe’. The QTL for 1000-seed weight (tsw-1H-1) does not show any difference for additive effects with year (stable QTL) (Table 4). Six QTLs are located on chromosome 2H, controlling date of flowering, spike initiation, plant height, spike length, percentage of protein and seed yield. These QTLs appear to be quite stable between years, their phenotypic variance as well as their additive effects being of the same magnitude in 2001 and 2002. Han and Ullrich [31] reported that QTLs of grain protein and kernel weight located on chromosome 2H were consistent over years. They also found two QTLs for grain protein with different signs in this group. Our QTL on
Table 2 Genetic gain and heritability for 10 agronomic traits in a population of 72 DH barley and their two parents Item
flo
spi
mat
hei
spl
spp
sps
tsw
prp
syi
Steptoe (P1) Morex (P2) P1–P2 Xp = (P1 + P2)/2 XDHsa XDHs Xp Best DH GGc = BDH BPb h2d
174.57 182.30 7.93* 178.44 179.45 1.01 ns 172.41 2.16 ns 77.89
158.22 169.78 11.56* 164.00 164.82 0.82 ns 157.52 0.7 ns 75.99
206.27 207.93 1.66 ns 207.10 206.58 0.52 ns 201.98 4.29* 70.15
91.27 93.67 0.24 ns 92.47 87.45 5.02 ns 103.37 9.70* 89.29
91.27 93.67 0.24 ns 92.47 87.45 5.02 ns 103.37 9.70* 80.01
4.40 6.71 2.31* 5.57 5.67 0.1 ns 7.42 0.71 ns 62.42
52.75 53.91 1.16 ns 53.33 52.40 0.93 ns 64.61 10.70* 71.92
31.08 39.60 8.52* 35.34 33.15 2.19 ns 38.84 0.76 ns 78.98
12.50 11.21 1.29* 11.85 11.24 0.61 ns 12.25 0.25 ns 74.24
202.06 321.93 119.87* 262.00 227.57 34.43 ns 348.60 26.67 ns 65.94
ns, nonsignificant. flo, days to flowering; spi, spike initiation; mat, days to maturity; hei, plant height (cm); spl, spike length (cm); spp, spike per plant; sps, seed per spike; tsw, 1000-seed weight (g); prp, protein percentage; syi, seed yield. a Mean of doubled haploids. b Best parent. c Genetic gain. d Heritability estimated from 2 years experiment taking into account s 2GE . * Significant at the 0.05 probability level.
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Table 3 Simple phenotypic correlations among characters in a population of 72 DH barley and their two parents from data combined across environments Trait
flo
spi
mat
hei
spl
spp
sps
tsw
prp
syi
flo spi mat hei spl spp sps tsw prp syi
1 0.755** 0.421** 0.398* 0.116 0.286* 0.164 0.227 0.432** 0.037
1 0.399** 0.267 0.057 0.283* 0.19 0.174 0.438** 0.002
1 0.162 0.067 0.259* 0.189 0.022 0.091 0.122
1 0.569** 0.175 0.055 0.113 0.210 0.325**
1 0.114 0.106 0.226 0.008 0.058
1 0.119 0.172 0.151 0.447**
1 0.119 0.064 0.324**
1 0.041 0.307**
1 0.208
1
flo, days to flowering; spi, spike initiation; mat, days to maturity; hei, plant height (cm); spl, spike length (cm); spp, spike per plant; sps, seed per spike; tsw, 1000-seed weight (g); prp, protein percentage; syi, seed yield. * Significant at the 0.05 probability level. ** Significant at the 0.01 probability level.
affecting grain protein were observed in only 9 environments out of 16 and on 5 chromosomes. However, four of them were consistently expressed on chromosomes 2H (two), 4H and 5H. The QTL that we have found in our experiment on chromosome 2H (prp-2H-1) is located in the same map position as one of the two QTLs they reported in 2H. The other protein QTL identified in our conditions (prp4H-1) is also located very close to a corresponding QTL in Hayes and Iyambo [27]. Hayes and Iyambo [27] also reported that 11 QTLs for plant height were non-consistently
chromosome 2H concerning percentage of protein (prp-2H1) is in agreement with the above-mentioned works. Hayes and Iyambo [27], following a series of experiments involving 16 environments, reported that QTLs affecting yield were present in all of the environments and on all seven chromosomes, but only two of them detected on chromosomes 3H and 1H were consistent. Despite not being completely consistent over the environments, five out of nine yield QTLs identified were later confirmed in other studies [21,28,29,32]. Hayes and Iyambo [27] reported that QTLs
Table 4 Map positions and effect of QTLs detected for 10 agronomic traits in a population of 72 DH and their two parents, in 2001–2002 Trait
QTL
Linkage group
Position a
LOD
P.E.V.b
Additive effect
2001 (1)
2002 (2)
2001
2002
Date of flowering (day)
flo-1H-1 flo-2H-1 flo-3H-1
1H 2H 3H
141 80 109
3.32 8.49 3.71
0.153 0.205 0.141
0.140 0.307 0.181
1.54 1.93 1.42
3.37 5.57 4.10
Date of spike initiation (day)
spi-1H-1 spi-2H-1 spi-5H-1 spi-7H-1
1H 2H 5H 7H
100 75 50 105
3.08 6.97 5.15 2.83
0.143 0.183 0.191 0.124
0.149 0.263 0.155 0.121
1.52 1.85 1.91 1.25
3.83 5.43 3.67 3.31
Date of maturity (day)
mat-1H-1 mat-3H-1
1H 3H
144 61
3.46 4.27
0.222 0.120
0.056 0.269
1.44 0.95
0.48 2.65
Plant height (cm)
hei-2H-1 hei-3H-1 hei-4H-1
2H 3H 4H
186 70 59
3.96 10.62 3.72
0.161 0.309 0.119
0.128 0.342 0.153
3.99 7.75 3.94
2.89 6.75 3.95
Spike length (mm)
spl-2H-1 spl-3H-1
2H 3H
80 77
4.79 15.8
0.141 0.611
0.208 0.208
6.49 17.40
2.87 3.26
Spike per plant
spp-1H-1 spp-5H-1
1H 5H
118 50
2.70 6.02
0.202 0.299
0.051 0.125
1.12 1.48
0.04 0.42
Seed per spike
sps-1H-1
1H
75
6.22
0.249
0.247
5.00
5.48
Thousand-seeds weight (g)
tsw-1H-1 tsw-5H-1 tsw-7H-1
1H 5H 7H
118 66 146
5.39 5.74 2.86
0.198 0.202 0.139
0.209 0.196 0.146
2.98 3.02 2.43
2.02 1.90 1.55
Protein percentage
prp-2H-1 prp-4H-1
2H 4H
65 134
4.80 2.23
0.260 0.186
0.102 0.088
0.63 0.53
0.26 0.25
Seed yield (g)
syi-2H-1
2H
72
3.6
0.215
0.069
4.02
1.92
a b
Expressed, in Kosambi cM, from origin of the linkage group (end of short arm). Proporation expected variance (r2) ‘‘value determinted by MULTIQTL-Version 2.4’’.
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present in all 16 environments and on all chromosomes (except 1H). Kandemir et al. [33] found a plant height QTL on chromosome 3H. According to Hayes and Iyambo [27], the plant height QTL on chromosome 3H is very consistent, because it was expressed in 12 environments out of 16. The QTL we have identified on chromosome 3H for plant height (hei-3H-1) is located in the same region. Our QTL on chromosome 2H (hei-2H-1) is also located in the vicinity of the QTL presented by Hayes and Iyambo [27]. Hayes and Iyambo [27] also reported that QTLs on chromosomes 7H, 2H, 3H and 4H for days to heading were non-consistently observed in all 16 environments. However, the only stable one that they detected was located on chromosome 2H. The QTL that we found for date of flowering on the same chromosome (flo-2H-1) is located at about 30 cM away from their QTL. In our experiment chromosome 3H harbours QTLs for four traits. The first two, with positive alleles from ‘Steptoe’ for days to flowering and maturity (flo-3H-1 and mat-3H-1), had more pronounced effects in 2002 than in 2001. Another region on chromosome 3H shows positive alleles from ‘Morex’ for spike length and plant height, with relatively stable effect on the latter trait (Table 4). The other three chromosomes bear QTLs for only two or three different traits: plant height and protein percentage on chromosome 4H; days to spike initiation, spike number and 1000-seed weight on chromosome 5H (Table 4). These QTLs showed rather stable effects among years. Finally, two QTLs for days to spike initiation and 1000-seed weight were identified on chromosome 7H. Most QTLs already reported from previous studies using the ‘Steptoe’ ‘Morex’ population focused on disease tolerance and malting quality and related enzyme activities [6,7,17,18]. As we have demonstrated, some of the QTLs detected in our experiment confirm those presented in previous reports. Our study thus represents a contribution to the knowledge of QTLs segregating in the DH population of ‘Steptoe’ ‘Morex’. The most important ones, with regard to their effects, their environmental stability and their potential for plant breeding, are those for flowering date on chromosome 2H and for plant height and spike length on chromosome 3H. Some QTLs for grain yield have been reported in this cross [21,34]. They are located on chromosomes 1H, 2H, 3H and 5H. In the present study, we found only one QTL located on chromosome 2H. However, in our study, QTLs for yield components were found on chromosomes 1H and 5H (tsw1H-1 for 1000-seed weight and spp-5H-1 for spike per plant). Several QTL co-locations confirm the observed correlations among the traits. For example, the correlations between seeds per spike and seed yield (positive) and between seed yield and protein percentage (negative) are consistent with the co-location observed on chromosome 2H (Tables 3 and 4). If a combination of high yield and highprotein content is sought, as for example in fodder barley, QTL pyramiding can be followed using a set of markers
spanning the confidence interval of the QTL position, as suggested by Charmet et al. [35] and Hospital and Charcosset [36]. Thousand-seed weight is controlled by three stable QTLs, which do not co-locate with any QTL for protein. QTLs on chromosomes 1H and 5H for 1000-seed weight have positive alleles from ‘Morex’, while the one on chromosome 7H has positive allele from ‘Steptoe’. Markerassisted selection could be successfully employed to have a desirable combination at all three loci, which could be of interest in breeding programmes for malting quality. Moreover, the favourable alleles for 1000-seed weight at QTL tsw-1H-1 can be associated with desirable alleles for early flowering and maturity, giving a good combination to escape drought. Han and Ullrich [31] also reported several co-locations for different traits, for example, QTLs for kernel weight and grain protein were located in the same region on 2H. These co-locations could be either because of linkage between two genes or the pleiotropy effect of one gene. In the latter case, the correlation between traits will never be broken. This study is the first report of QTL analysis in barley evaluated in Iran under dry versus irrigated management. Despite the small sample size used for technical reasons, a total of 23 significant QTLs were found for the 10 studied traits. We had focused on grain yield, protein content and developmental traits, which were supposed to be associated with drought adaptation. However, most QTLs showed remarkable stability over management practices and over years (Table 4). Although the detected regions need to be more precisely mapped, the information obtained should help in marker-assisted selection.
Acknowledgment The authors thank professor Catherine Carter (South Dakota State University) for English corrections.
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