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Inheritance and molecular markers for aphid (Macrosiphoniella sanbourni) resistance in chrysanthemum (Chrysanthemum morifolium Ramat.)
Scientia Horticulturae 180 (2014) 220–226
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Inheritance and molecular markers for aphid (Macrosiphoniella sanbourni) resistance in chrysanthemum (Chrysanthemum morifolium Ramat.) Chuchu Wang, Fei Zhang, Zhiyong Guan, Sumei Chen, Jiafu Jiang, Weimin Fang, Fadi Chen ∗ College of Horticulture, Nanjing Agricultural University, No. 1, Weigang, Nanjing 210095, Jiangsu, PR China
a r t i c l e
i n f o
Article history: Received 2 July 2014 Received in revised form 15 October 2014 Accepted 17 October 2014 Available online 6 November 2014 Keywords: Chrysanthemum Aphid resistance Inheritance Molecular markers
a b s t r a c t Aphids have caused great damage to chrysanthemum production, and it’s crucial to breed new chrysanthemums with strong aphid resistance. However, little information is available regarding the inheritance of aphid resistance in chrysanthemum. The inheritance pattern of chrysanthemum aphid resistance within an F1 segregating population was dissected with the major gene plus polygene mixed inheritance model and molecular markers. The result showed that aphid resistance of chrysanthemum is a quantitative trait with a moderate coefficient of variation >50%. The mixed inheritance model based on a single segregating generation suggested the inheritance of aphid resistance was controlled by two pairs of major genes with additive effect 0.68 and 0.39, respectively. The heritability of major gene was calculated at 89.21%. Marker-trait analysis based on one-way variance analysis uncovered 11 markers significantly associated with phenotype, cumulatively explaining ∼74% variation. Bulked segregant analysis (BSA) based on the gene bulks of high resistant and susceptive genotypes in F1 population identified two SSR markers, SSR145-93 and SSR197-205, linked to high aphid resistance (r > 0.4). The QTL analysis detected 5 putative QTL for aphid resistance in two successive years, with individual QTL explaining the phenotypic variation of 14.30–28.00%. The inheritance model and molecular markers identified for aphid resistance facilitate the ongoing breeding activities in chrysanthemum. © 2014 Elsevier B.V. All rights reserved.
Introduction Chrysanthemum (Chrysanthemum morifolium Ramat.) is a traditionally famous flower in China and ranks the second in cut flower production worldwide. In 2011, the annual consumption of chrysanthemum in European, America and Japan reached up to 15, 8 and 20 billion branches, respectively. In chrysanthemum production, however, insects from different orders have negative impact on the quality of flower yield and require control. It is therefore particularly promising to develop sustainable insect pest management in ornamentals. The chrysanthemum aphid (Macrosiphoniella sanbourni) is one of the most major insect pests on chrysanthemum. Aphids directly injure leaves, shoots, and flowers, resulting in plant dwarf, leaf yellowing, and curling. Besides, while the release of honeydew fosters sooty mold infestation, aphids act as vectors for virus
∗ Corresponding author. Tel.: +86 25 84395592; fax: +86 25 84395266. E-mail address: [email protected] (F. Chen). http://dx.doi.org/10.1016/j.scienta.2014.10.038 0304-4238/© 2014 Elsevier B.V. All rights reserved.
transmission to infect chrysanthemum. To control insects, large amounts of chemical insecticides are needed to manage aphid pests, which are costly and often result in severe environment pollution. Additionally, it becomes more difficult to suppress the aphids that developed resistance to insecticide with the application of high-dose insecticides. With consideration given to economic and environmental reasons, integrated pest management programs in chrysanthemum production including natural enemies and insect proof net have been developed. However, these measures were found to be of minor importance for the suppression of the mentioned aphid species. Improving the host-plant resistance is an effective method for controlling aphid, since it does reduce the use of exogenous chemical insecticides or pecuniary loss, and the effect is stable and long-lasting (Jun et al., 2013; Sota et al., 2014). Thus breeding for resistant chrysanthemum cultivars is a further possibility to provide an efficient, economic and environmental friendly approach to reducing the losses caused by the injury of aphid. There has been a great effort to improve the aphid resistance in chrysanthemum. Transgenic plants with improved resistance to aphids
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have been reported in chrysanthemum (Wang et al., 2004; He et al., 2009), whereas there is a long way towards the commercial production of transgenic chrysanthemums. Recently, several authors have identified variable susceptibility of different chrysanthemum genotypes to aphids, and digged out some resistant chrysanthemums (He et al., 2010, 2011; Sun et al., 2012). Based on these observations, the resistant chrysanthemum produced thick palisade tissues, bushy trichomes, and dense wax on the lower leaf epidermis, and showed increased defense enzymes activities (He et al., 2011), and yielded more bioactive substance as terpene (Deng et al., 2010). These observations help understanding the mechanism of resistance to aphids in chrysanthemum. However, it is important to not only identify the resistant genotypes but also to improve chrysanthemum cultivars with increased aphid resistance by using these resistant germplasm. The latest finding suggested that hybridization between different resistant chrysanthemums conferred hybrids stronger resistance to aphid, but within a varied quantitative range (Zhu et al., 2014). The wide segregation of aphid resistance in hybrid progeny affords a genetic background for breeding resistant chrysanthemum. However, little information is available concerning the inheritance pattern of aphid resistance in chrysanthemum thus far. In order to better understand the inheritance of resistance to aphid, the present study was carried out to dissect the inheritance pattern of aphid resistance in chrysanthemum with the major gene plus polygene mixed inheritance model base on a single segregation analysis method, and to identify the putative molecular markers linked to aphid resistance. The findings from this study add an in-depth understanding to the genetic determinism of aphid resistance and aid in the ongoing breeding practices in improving aphid resistance of chrysanthemum. Materials and methods Plant materials Plant materials comprised 133 F1 progeny obtained from the cross between the two cultivars ‘Han 2’ (2n = 6x = 54) and ‘Nannong Gongfen’ (2n = 6x = 54). ‘Han 2’ is high resistant to aphid, and ‘Nannong Gongfen’ is susceptible. All the materials are maintained at the Chrysanthemum Germplasm Resource Preserving Center, Nanjing Agricultural University, China. Aphid resistance evaluation Evaluation of chrysanthemum aphid resistance was performed using artificial inoculation with aphids (M. sanbourni) in two consecutive years of 2011 and 2012. The chrysanthemum aphid used in this study was established in a growth chambers maintained at temperatures between 23 and 28 ◦ C with 80% relative humidity, by collecting aphids from a nearby chrysanthemum field. In this test, every seedling was grown in a 12 cm in diameter and 25 cm deep transparent plastic proof cage to prevent aphids from escaping and to restrict entry of predators in the cage from outside. Each plant was infested with five wingless adult aphids at the 6–8 leaves stage. Two parents were also included as checks. The chrysanthemum aphid resistance was evaluated by counting at 21 days after infestation (Deng et al., 2010). Individual plants were scored for ratio of aphid. Ratio of aphid was designated as the average of number of insect population in individual plant divided the average of number of insect population in all plants. The aphid resistance of chrysanthemum could be divided into five grades in terms of aphid number ratio, high resistance (aphid number ratio 0–0.25), moderate resistance (0.26–0.50), resistance (0.51–0.75), low resistance (0.76–1.25), and non-resistance (>1.25).
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Mixed inheritance model analysis The major gene plus polygene mixed inheritance model based on a single segregation generation described by Gai et al. (2003) was used to dissect the inheritance pattern of aphid resistance in chrysanthemum. Briefly, suppose under the modifications of polygene and environment, the effects of major gene in segregation generation display an independent normal distribution, then the whole segregation generation could be seen as a mixed distribution made up by many independent normal distributions. A joint maximum-likelihood function was derived to estimate the parameters of component distributions through the IECM (iterated expectation and conditional maximization) algorithm. Additionally, the Akaike’s information criterion (AIC), likelihood-ratio test (LRT), and a set of goodness-of-fit tests were used for model selection and test. Akaike (1977) suggested that the hypothesis maximizing the expected entropy should be selected as the most fitting model. For this purpose, based on goodness-of-fit and parsimony, the hypothesis that leads to the smallest AIC will be chosen. Here, the single generation segregation analysis may involve the two genetic model of null or one pair of major genes (A model) and two pairs of major genes (B model) in 11 kinds with special reference to major gene. The model with the least AIC value and best fitness was considered the best-fitting model. Genetic parameters were estimated with the method as detailed in Gai et al. (2003). DNA extraction and genotyping Total genomic DNA was isolated from young leaves using a modified CTAB protocol (Murray and Thompson, 1980). The F1 individuals together with the two parents was genotyped using three marker sets, including microsatellite (SSR), start codon targeted (SCoT) and sequence-related amplified polymorphism (SRAP). In this study, 200 SRAP, 300 SSR, and 18 SCoT primer combinations were screened for polymorphism across the two parents and eight randomly selected F1 individuals. The informative and polymorphic primer combinations were performed for later genotyping for marker-trait analysis and genetic mapping. All the primers were synthesized by Shanghai Sangon (Shanghai, China). PCR and electrophoretic procedures of SRAP, SSR and SCoT followed by Zhang et al. (2011a), Wang et al. (2013) and Li et al. (2013), respectively. Marker-trait analysis Marker profiles were scored by assigning ‘0’ for the absence and ‘1’ for the presence of each polymorphic fragment. Only reproducible and well-defined bands were scored. Each marker was identified by the primer pair used and a suffix was attached to the designation, where multiple fragments were identified from a single primer combination and molecular size. According to the marker-based method of Singh et al. (1991), for each marker, the segregating progeny were assigned into groups, formed by those scored as ‘0’ and those as ‘1’, and a one-way variance analysis was then performed for each marker in turn to detect any loci linked to aphid resistance. Bulked segregant analysis Bulked segregant analysis (BSA) method was also adopted to identify markers associated with aphid resistance. According to phenotype, each six radical aphid-resistance individuals for resistance bulk (RB) and extreme aphid-susceptible individuals for susceptible bulk (SB) were selected from the segregating F1 population. DNA bulk representing each extreme phenotype in a population was formed by mixing equal volume of DNA solution from each genotype in the bulk. DNA samples of the two parents and
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Fig. 1. Aphid density on seven plants at 21 days after aphid inoculation. (A): High resistance parent ‘Han 2’, (B): high resistant individual, (C): moderate resistant individual, (D): resistant individual, (E): low resistant individual, (F): non-resistant individual, (G): susceptive parent ‘Nannong Gongfen’.
the two bulks in each population were assayed using the selected polymorphic markers. The gels were scored for each marker used for the assay as described above and the polymorphic ones were selected for each population. A marker was regarded to be polymorphic at this stage when the different bands formed by the RB and SB bulks were similar to the bands formed by the RB and SB parents, respectively. Individual genotypes in the contrasting bulks of each population were then assayed using the markers found to be polymorphic between the two bulks to select the candidate markers. The genotypic data generated for each marker from screening of the individuals in the contrasting bulks of each population were correlated with the phenotypic data using Pearson correlation test in SPSS. Percent of presence or absence of band (RB parent band) among all the individuals in each phenotypic group was estimated for each polymorphic marker. A marker was regarded to be closely associated with aphid resistance genes when the correlation coefficient between phenotypic and genotypic data was ≥0.3 (Olasanmi et al., 2014). The genotypic and phenotypic data for each marker were subjected to regression analysis. Each candidate marker identified in a population was used to assay the remaining individuals in the population to identify the genotypes having the desirable marker(s).
by each QTL in proportion to the total phenotypic variance, which could be achieved from the CIM results.
Results Aphid resistance performance Aphid density at 21 days after inoculation is shown in Fig. 1. Aphid resistance of chrysanthemum segregated widely in the segregating F1 population with coefficient of variation 51.57% (Table 1). The skewness and kurtosis values and frequency distribution indicated that aphid resistance in the F1 population was compatible with a normal distribution (Table 1, Fig. 2). Therefore, aphid resistance of chrysanthemum is quantitatively inherited in nature.
Map construction and QTL screening The parental genetic maps were separately constructed based on the segregating polymorphic markers in the F1 population consisting of 133 individual plants. Linkage analysis with all markers in the F1 population was performed using Mapmaker/EXP3.0 (Lincoln et al., 1992). A minimum log likelihood of the odds (LOD) score of 3.0 and a maximum distance of 30 cM were use to group loci into linkage groups (LG). Genetic distances between loci were calculated using the Kosambi (1944) mapping function. Then two separate QTL mapping analyses were carried out by applying the composite interval mapping (CIM) method (Zeng, 1994) embedded in the Windows QTL Cartographer software (Wang et al., 2007). The window size was set at 10 cM and the walking speed at 1 cM. The LOD threshold to declare a putative QTL was 2.5. The contribution ratio (R2 ) by each QTL was estimated as the percentage of variance explained
Fig. 2. Frequent distributions for aphid resistance segregating in F1 population derived from a cross between ‘Han 2’ (P1 ) and ‘Nannong Gongfen’ (P2 ).
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Table 1 Phenotypic statistic values for aphid-resistance traits of chrysanthemum cultivars ‘Han 2’ (P1 ) and ‘Nannong Gongfen’ (P2 ) and their F1 mapping population in 2011 and 2012 seasons. F1 mapping population
Parent
Trait
P1 Aphid number of ratio 2012 0.05 2011 0.06
P2
Maximum
Minimum
Average
SD
Skewness
Kurtosis
1.33 1.37
2.42 2.50
0.06 0.05
1.00 1.00
1.29 1.40
0.71 0.73
0.4 0.5
Table 2 Akaike information criterion (AIC) values of various genetic models for aphid resistance traits in joint segregation analysis of F1 population derived from cross between ‘Han 2’ and ‘Nannong Gongfen’, and test for goodness-of-fit of selected genetic model. Model
AIC
A-0 A-1 A-2 A-3 A-4 B-1 B-2 B-3 B-4 B-5 B-6
166.83 160.13 158.15 170.83 180.33 166.24 164.13 140.48 155.34 170.83 168.83
U12
U22
U32
nW
Table 5 Percentage of presence of bands, correlation coefficients between the phenotypic and genotypic data individuals. Marker
Band present in resistant individuals (%)
Band present in susceptive individuals (%)
Correlation coefficient
SSR145-92.98 SSR197-204.15
88.9 91.9
42.9 28.6
0.41** 0.52**
D
** Indicates significant difference with the least significant difference (LSD) test at P < 0.01.
0.00(0.99)
0.00(0.99)
0.00(0.98)
0.02
0.04
0.39, respectively. The heritability of major gene was calculated at 89.21%. Molecular marker analysis
Table 3 Estimation of genetic parameters for aphid resistance traits of chrysanthemum at its optimal genetic model. Genetic parameter
m
da
db
p2
2 mg
h2mg (%)
Aphid number of ratio
1.20
0.68
0.39
0.27
0.31
89.21
m: Mean value of aphid number of ratio; da : the first major-gene additive effect; db : 2 : major-gene the second major-gene additive effect; 2 p: phenotypic variance; mg variance; h2mg : major-gene heritability.
Inheritance analysis The AIC values of various genetic models for aphid resistance traits in joint segregation analysis of F1 population and the goodness-of-fit test of selected genetic model are shown in Table 2. According to the assumption that the model with the least AIC value is the optimal model, the B-3 model that showed the smallest AIC value might be the preferred inheritance model for aphid resistance. After further goodness-of-fit tests, no significant differences were detected for this model (Table 2). Thus the optimal model for aphid resistance should be B-3, controlled by two pairs of major genes with additive effects. The estimated genetic parameters for aphid resistance at B-3 model are shown in Table 3. The additive effect values of the two pairs of major genes were 0.68 and
Screening against DNA of the two parental cultivars and 8 F1 individuals, 60, 53 and 6 polymorphic primer pairs respectively, for SRAP, SSR and SCoT were found to be informative and were used for genotyping the whole F1 population. As a result, a total of 763 (537 SRAP, 195 SSR and 31 SCoT) polymorphic fragments were yield, respectively. The marker-trait association analysis based on one-way variance method revealed seven SRAP markers and four SSR markers significantly associated with aphid-resistance (Table 4). These putative markers cumulatively explained 74.4% to the total phenotypic variation, but with a low contribution by individual markers to the phenotypic variance ranging from 6.3 to 8.9%. The SSR marker-based BSA method, revealed two SSR makers, SSR145-93 and SSR197 = 205, for the aphid resistance (Table 5). The marker-trait correlation coefficients were >0.3, indicating that SSR145-93 and SSR197-205 might be closely linked to aphid resistance genes. QTL mapping Of the 763 polymorphic markers, 386 testcross markers present in either parent were constructed genetic linkage maps for the two parents, ‘Han 2’ and ‘Nannong Gongfen’. Finally, 262 of 386 (67.9%) markers were grouped on the two parental maps, leaving 124 (32.1%) markers unlinked. 142 markers were placed on 30 linkage groups of ‘Han 2’ map, while ‘Nannong Gongfen’ linkage map
Table 4 The markers significantly associated with aphid-resistance in the F1 population detected by one-way ANOVA method. Marker name EM11ME13-919 EM12ME18-135 EM13ME24-226 EM14ME24-97 EM17ME5-80 EM19ME21-324 EM19ME21-437 SSR197-205 SSR147-232 SSR145-93 SSR52-143
Sum of squares between groups 67,629.62 58,308.37 67,639.55 61,875.33 57,487.64 77,885.44 71,319.06 61,671.60 78,169.99 34,765.98 80,457.69
Sum of squares within group 853,325.66 869,303.33 859,972.14 865,736.36 794,161.37 849,726.25 856,292.63 865,940.10 849,441.70 892,845.71 823,206.33
R2 indicates ratio of contribution to the total phenotypic variations explained by individual marker.
F value
P value
R2 (%)
7.846 6.775 7.944 7.219 6.877 9.258 8.412 7.193 9.295 3.933 9.774
0.006 0.011 0.006 0.008 0.01 0.003 0.005 0.009 0.003 0.05 0.002
7.34 6.29 7.29 6.67 6.75 8.40 7.69 6.65 8.43 3.75 8.90
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Table 6 QTL mapping for plant aphid-resistance of chrysanthemum in two years (environments), detected by WinQTL5.0. QTL
LG
Interval
Position (cM)
Range (cM)
LOD
A
R2 (%)
NoaE2G1 NoaE2G7 NoaE1H3 NoaE2H7 NoaE2H8
G1 G7 H3 H7 H8
SR149-268 E8M9-215 E12M18-99 E12M18-80 E16M6-383 SR197-113 S14-676 S16-370 S11-700 E16M18-109
36.44 80.12 54.78 28.92 87.68
1.0 2.0 6.0 4.0 8.0
2.60 2.58 3.35 3.94 2.74
−57.81 −40.00 −48.87 −62.04 −39.70
14.3 25.4 19.4 24.7 28.0
A is the additive genetic effects estimated at the testing points. Negative values mean that the corresponding parent has a negative effect on aphid density, that is, increasing aphid resistance. R2 indicates ratio of contribution to the total phenotypic variations explained by individual marker.
grouped 120 markers on 25 linkage groups. Both genetic maps have an adequate inter-marker distance ∼12 cM. The QTL analysis identified five QTLs closely associated with aphid resistance in 2011 and 2012 (Table 6), which mainly distributed on the linkage groups G1 and G7 of ‘Han 2’ map and H3, H7 and H8 of ‘Nannong Gongfen’ map (Fig. 3). Each of the five QTL explained >10% of the phenotypic variation within a range 14.30–28.00% (Table 6), thus these should be major QTL for aphid resistance. Discussion The performance of host-plant aphid resistance is resulted from the defense behavior of host plants, dependent on the morphological structure, biochemical and physiological response or the regulation of hormone signals (Li et al., 2008;Bos et al., 2010; Guo et al., 2012). For improving host-plant aphid resistance, it is crucial to understand the genetic determinism and to identify the molecular markers linked to aphid resistance genes. Inheritance of aphid resistance in chrysanthemum Identification of varieties and plant introductions that show resistance to aphids and characterization of the genes from the resistant sources are important early steps in the development of cultivars with resistance to aphid (Jun et al., 2013), so knowing the inheritance of aphid resistance is absolutely necessary. Previous researches suggested the inheritance of aphid resistance was more
quantitative rather than qualitative. Dominant and recessive genes were found to determine aphid resistance in many crops such as peach (Pascal et al., 2002), wheat (Liu et al., 2012), soybean (Hill et al., 2006; Mian et al., 2008; Xiao et al., 2013; Fox et al., 2014), and corn (So et al., 2010). In contrast, Julier et al. (2004) suggested a multigene inheritance with mainly additive effect for pea aphid resistance in lucerne, and the resistance level of lucerne cultivars was strongly correlated with their general combining abilities. Also, aphid resistance in soybean could also be quantitative (Zhang et al., 2009; Meng et al., 2011). Thus inheritance of aphid resistance varied with crops or genetic backgrounds, indicative of its complexity. As to chrysanthemum, it is largely self-incompatible and suffers from inbreeding depression (Anderson and Ascher, 2000). This makes it practically difficult to obtain advance generations of inbred lines of the sort used for genetic research in self-compatible species. The major gene plus polygene mixed inheritance model based a single segregating generation (F2 ) were successfully applied for genetic research using the F1 (pseudo-F2 ) population of heterozygous crops like chrysanthemum (Zhang et al., 2011b) and bromeliad (Wang et al., 2012), setting a good example for genetic dissection for aphid resistance in chrysanthemum. The present study suggested that aphid resistance varied quantitatively in the F1 progeny of chrysanthemum. Results from the mixed inheritance model analysis in this study demonstrated that aphid resistance in chrysanthemum was controlled by two major genes with additive effects and the heritability of major gene was as high as ∼89%. Thus, it should be relatively easy to select for aphid resistance in the early
Fig. 3. The significant quantitative trait loci (QTL) for chrysanthemum aphid resistance. NoaE1 and NoaE2 indicate the QTL for aphid resistance detected in 2011 and 2012, respectively.
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generations of breeding program. Also the detection of major genes is an important clue to the later research on identifying molecular markers associated with aphid resistance. The molecular markers for aphid resistance Current phenotyping methods including aphid density or abundancy for selection of plant resistant to aphid are cumbersome and cannot distinguish plants containing combinations of resistance genes from those carrying a single gene. To achieve durable resistance to aphid, it is therefore important to not only identify alternative sources of resistance but also to pyramid the resistance genes to effectively develop horizontal resistance. This is best achieved through the application of marker-assisted selection (MAS). MAS through the use of molecular markers closely linked to the resistance genes is a powerful selection tool that accelerates the breeding of new more durably resistant cultivars containing two or more pyramided resistance genes (Collard et al., 2005). Until present BSA (Olasanmi et al., 2014) and map-based QTL analysis (Stoeckli et al., 2008; Sauge et al., 2012; Kamphuis et al., 2013) were often adopted to find out the molecular markers associated with aphid resistance in previous publications. In the current study, the two methods together with marker-based variance analysis using three marker types of SRAP, SSR, and SCoT were attempted to identify markers linked to aphid resistance in chrysanthemum. The marker-trait association analysis by the method of one-way ANOVA detected 7 SRAP makers and 4 SSR markers significantly associated with aphid resistance with cumulative contribution ratio of ∼74%, but with a low individual contribution. This reinforces the quantitative nature of aphid resistance in chrysanthemum. Olasanmi et al. (2014) reported that a marker could be regarded to be closely associated with a gene when the correlation coefficient between phenotypic and genotypic data was ≥0.3, and identified 9 SSR markers closely linked to early bulking in cassava via BSA method. According to such mentioned assumption, in the present study, high correlation coefficients (r = 0.41–0.52, respectively; P < 0.01) between genotype and phenotype (i.e. aphid resistance here) were detected two SSR markers, SSR145-93 and SSR197205. Thus the two markers should be closely linked to the aphid resistance genes. The use of the SSR markers can aid in selecting with moderate precision for desired aphid resistance in chrysanthemum. Additionally, the marker SSR197-205 was detected by both marker-based variance analysis and BSA, and thus should be focused on in future MAS. Although molecular marker-based approaches to host-plant resistance against insects are common in annual crops (Wu and Huang, 2008; Ricciardi et al., 2010; Punnuri et al., 2013), and are intensively studied in chrysanthemum to dissect other horticultural traits (Zhang et al., 2011a, 2012, 2013), they have received little attention so far in chrysanthemum in connection with aphid suppression. In this study, the mapped-based QTL analysis identified five putative QTL for aphid resistance in two consecutive years of 2011 and 2012, distributing on both ‘Han 2’ and ‘Nannong Gongfen’ maps. All the QTL decreased ∼40 to ∼62 of the aphid density, that is, they had a positive effect on the aphid resistance. According to Falconer and Mackay (1996), QTL explaining >10% of phenotypic variation (R2 ) should be considered major QTL. Here, the R2 explained by individual QTL ranged from 14.30% to 28.00%, therefore indicative of that the five QTL should be of major QTL. However, it’s necessary to point out that the five QTL was not consecutively detected in different years. So we conclude that the QTL detected are readily influenced by environment, and should be further confirmed with more environment and genetic backgrounds before applied for MAS. Honestly, few common markers were detected between results from marker-based variance method and BSA with QTL mapping.
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This is probably because the genetic maps for the two chrysanthemum cultivars in this study were unsaturated and most of the detected markers by the former two methods were not grouped on the linkage maps. Though, findings from this research add a brand-new knowledge on the inheritance pattern and molecular markers for the aphid resistance in chrysanthemum. Moreover, the candidate markers should be a meaningful start to improving aphid-resistance with MAS in chrysanthemum. Acknowledgments The authors gratefully acknowledge the financial support provided by the National Natural Science Foundation of China (grant nos. 31272196, 31370699, 31372092, 31471900), 863 Project (2011AA100208), the Program for New Century Excellent Talents in University of the Chinese Ministry of Education (grant no. NCET12-0890), the Jiangsu Program for Hi-Tech Research (BE2012350), Fund for Independent Innovation of Agricultural Sciences in Jiangsu Province [CX(12)2020], and the Fundamental Research Funds for the Central Universities (KYTZ201401). References Anderson, N.O., Ascher, P.D., 2000. Fertility changes in inbred families of selfincompatible chrysanthemums (Dendranthema grandiflorum). J. Am. Soc. Hortic. Sci. 125, 619–625. Akaike, H., 1977. On entropy maximisation principle. In: Krishnaiah, P.R. (Ed.), Proceedings of the Symposium on Applications of Statistics. Amsterdam, The Netherlands, pp. 27–47. Bos, J.I.B., Prince, D., Pitino, M., Maffei, M.E., Win, J., Hogenhout, S.A., 2010. A functional genomics approach identifies candidate effectors from the aphid species Myzus persicae (green peach aphid). PLoS Genet 6, e1001216. Collard, B.C.Y., Jahufer, M.Z.Z., Brouwer, J.B., Pang, E.C.K., 2005. An introduction to markers, quantitative trait loci (QTL) mapping, and marker-assisted selection for crop improvement: The basic concepts. Euphytica 142, 169–196. Deng, Y., Chen, S., Lu, A., Chen, F., Tang, F., Guan, Z., Teng, N., 2010. Production and characterization of the intergeneric hybrids between Dendranthema morifolium and Artemisia vulgaris exhibiting enhances resistance to chrysanthemum aphid (Macrosiphoniella sanbourni). Planta 231, 693–703. Falconer, D.S., Mackay, T.F.C., 1996. Introduction to Quantitative Genetics, fourth ed. Longman Group Ltd, England. Fox, C.M., Kim, K.S., Cregan, P.B., Hill, C.B., Hartman, G.L., Diers, B.W., 2014. Inheritance of soybean aphid resistance in 21 soybean plant introductions. Theor. Appl. Genet. 127, 43–50. Gai, J.Y., Zhang, Y.M., Wang, J.K., 2003. Genetic System of Quantitative Traits in Plants. Science Press, Beijing, pp. 96–102. Guo, S.M., Kamphuis, L.G., Gao, L.L., Klingler, J.P., Lichtenzveig, J., Edwards, O., Singh, K.B., 2012. Identification of distinct quantitative trait loci associated with defence against the closely related aphids Acyrthosiphon pisum and A. Kondoi in Medicago truncatula. J. Exp. Bot. 63, 3913–3922. He, J., Chen, F., Chen, S., Fang, W., Miao, H., Luo, H., 2009. Transformation of Lycoris longtituba agglutinin gene to cut chrysanthemum and identification of aphid resistance in the transgenic plants. Acta Bot, Boreal.-Occident. Sin. 29, 2318–2325. He, J., Chen, F., Chen, S., Fang, W., 2010. Aphid-resistance of chrysanthemum cultivars. Chin. J. Ecol. 29, 1382–1386. He, J., Chen, F., Chen, S., Lv, G., Deng, Y., Fang, W., Liu, Z., Guan, Z., He, C., 2011. Chrysanthemum leaf epidermal surface morphology and antioxidant and defense enzyme activity in response to aphid infestation. J. Plant Physiol. 168, 687–693. Hill, C.B., Li, Y., Hartman, G.L., 2006. A single dominant gene for resistance to the soybean aphid in the soybean cultivar Dowling. Crop Sci. 46, 1601–1605. Julier, B., Bournoville, R., Landré, B., Ecalle, C., Carré, S., 2004. Genetic analysis of lucerne (Medicago sativa L.) seedling resistance to pea aphid (Acyrthosiphon pisum Harris). Euphytica 138, 133–139. Jun, T.H., Mian, M.A.R., Michel, A.P., 2013. Genetic mapping of three quantitative trait loci for soybean aphid resistance in PI567324. Heredity 111, 16–22. Kamphuis, L.G., Lichtenzveig, J., Peng, K., Guo, S.M., Klingler, J.P., Siddique, K.H., Gao, L.L., Singh, K.B., 2013. Characterization and genetic dissection of resistance to spotted alfalfa aphid (Therioaphis trifolii) in Medicago truncatula. J. Exp. Bot. 64, 5157–5172. Kosambi, D.D., 1944. The estimation of map distances from recombination values. Ann. Eugen. 12, 172–175. Li, Y., Zou, J.J., Li, M., Bilgin, D.D., Vodkin, L.O., Hartman, G.L., Clough, S.J., 2008. Soybean defense responses to the soybean aphid. New Phytol. 179, 185–195. Li, P., Jiang, J., Chen, S., Guan, Z., Liao, Y., Fang, W., Chen, F., 2013. Establishment and optimization of SCoT molecular marker system in chrysanthemum and its application of analysis on genetic diversity. Acta Hortic. Sin. 40, 2015–2025.
226
C. Wang et al. / Scientia Horticulturae 180 (2014) 220–226
Lincoln, S., Daly, M., Lander, E., 1992. Constructing gentic maps with mapmaker/EXP3.0. In: Whitehead Institute Techn. Rep, third ed. Whitehead Institute, Cambridge. Liu, X.L., Yang, X.F., Wang, C.Y., Wang, Y.J., Zhang, H., Ji, W.Q., 2012. Molecular mapping of resistance gene to English grain aphid (Sitobion avenae F.) in Triticum durum wheat line C273. Theor. Appl. Genet. 124, 287–293. Meng, F.L., Han, Y.P., Teng, W.L., Li, Y.G., Li, W.B., 2011. QTL underlying the resistance to soybean aphid (Aphis glycine Matsumura) through isoflavonemediated antibiosis in soybean cultivar ‘Zhongdou 27’. Theor. Appl. Genet. 123, 1459–1465. Mian, M.A.R., Kang, S.T., Beil, S.E., Hammond, R.B., 2008. Genetic linkage mapping of the soybean aphid resistance gene in PI 243540. Theor. Appl. Genet. 117, 955–962. Murray, M., Thompson, W.F., 1980. Rapid isolation of high molecular weight plant DNA. Nucleic Acids Res. 8, 4321–4325. Olasanmi, B., Akoroda, M.O., Okogbenin, E., Egesi, C., Kahya, S.S., Onyegbule, O., Ewa, F., Guitierrez, J., Ceballos, H., Tohme, J., Fregene, M., 2014. Bulked segregant analysis identifies molecular markers associated with early bulking in cassava (Manihot esculenta Crantz). Euphytica 195, 235–244. Pascal, T., Pfeiffer, F., Kervella, J., Lacroze, J.P., Saug, M.H., 2002. Inheritance of green peach aphid resistance in the peach cultivar ‘Rubira’. Plant Breed 121, 459–461. Punnuri, S., Huang, Y.H., Steets, J., Wu, Y.Q., 2013. Developing new markers and QTL mapping for greenbug resistance in sorghum [Sorghum bicolor (L.) Moench]. Euphytica 191, 191–203. Ricciardi, M., Tocho, E., Tacaliti, M.S., Vasicek, A., Gimenez, D.O., Paglione, A., Simmonds, J., Snape, J.W., Cakir, M., Castro, A.M., 2010. Mapping quantitative trait loci for resistance against Russian wheat aphid (Diuraphis noxia) in wheat (Triticum aestivum L.). Crop Pasture Sci. 61, 970–977. Sauge, M.H., Lambert, P., Pascal, T., 2012. Co-localisation of host plant resistance QTLs affecting the performance and feeding behaviour of the aphid Myzus persicae in the peach tree. Heredity 108, 292–301. Singh, P.S., Gutierrez, J.A., Molina, A., Urrea, C., Gepts, P., 1991. Genetic diversity in cultivated common bean: II Marker-base analysis of morphological and agronomic traits. Crop Sci. 31, 24–39. So, Y.-S., Ji, Y.C., Brewbaker, J.L., 2010. Resistance to corn leaf aphid (Rhopalosiphum maidis Fitch) in tropical corn (Zea mays L.). Euphytica 172, 373–381. Sota, T., Kagata, H., Ando, Y., Utsumi, S., Osono, T., 2014. Insect-Plant Interactions in Plant-Based Community/Ecosystem Genetics. Springer, Japan, pp. 25–43. Stoeckli, S., Mody, K., Gessler, C., Patocchi, A., Jermini, M., Dorn, S., 2008. QTL analysis for aphid resistance and growth traits in apple. Tree Genet. Genomes 4, 833–847.
Sun, Y., Guan, Z., Chen, S., Fang, W., Chen, F., 2012. Identification of aphid resistance in eleven species of Dendranthema and Artemisia at seedling stage. Acta Ecol. Sin. 32, 319–325. Wang, G., Liu, Y., Guo, S., Wang, Y., Ji, Y., Fang, H., 2004. Study on transformation of snowdrop lectin gene to chrysanthemum and aphid resistance of the transgenic plants. Acta Genet. Sin. 31, 1434–1438. Wang, S., Basten, J.C., Zeng, Z.B., 2007. Window QTL Cartographer Version 2.5. Statistical Genetics. North Carolina State University, USA. Wang, W., Zhang, F., Yu, X., Shen, X., Ge, Y., Zhang, Z., 2012. Genetic analysis and associated SRAP markers for horticultural traits of Aechmea bromeliads. Sci. Hortic. 147, 29–33. Wang, H., Jiang, J., Chen, S., Qi, X., Peng, H., Li, P., Song, A., Guan, Z., Fang, W., Liao, Y., Chen, F., 2013. Next-generation sequencing of the Chrysanthemum nankingense (Asteraceae) transcriptome permits large scale unigene assembly and SSR marker discovery. PLoS One 8, e62293. Wu, Y.Q., Huang, Y.H., 2008. Molecular mapping of QTLs for resistance to the greenbug Schizaphis graminum (Rondani) in Sorghum bicolor (Moench). Theor. Appl. Genet. 117, 117–124. Xiao, L., Hu, Y., Wang, B., Wu, T., 2013. Genetic mapping of a novel gene for soybean aphid resistance in soybean (Glycine max [L.] Merr.) line P203 from China. Theor. Appl. Genet. 126, 2279–2287. Zeng, Z.B., 1994. Precision mapping of quantitative trait loci. Genetics 136, 1457–1468. Zhang, F., Chen, S., Chen, F., Fang, W., Chen, Y., Li, F., 2011a. SRAP-based mapping and QTL detection for inflorescence-related traits in chrysanthemum (Dendranthema morifolium). Mol. Breed. 27, 11–23. Zhang, F., Chen, S., Chen, F., Fang, W., Deng, Y., Chang, Q., Liu, P., 2011b. Genetic analysis and associated SRAP markers for flowering traits of chrysanthemum (Chrysanthemum morifolium). Euphytica 177, 15–24. Zhang, F., Jiang, J., Chen, S., Chen, F., Fang, W., 2012. Mapping single-locus and epistatic quantitative trait loci for plant architectural traits in chrysanthemum. Mol. Breed. 30, 1027–1036. Zhang, F., Chen, S., Jiang, J., Guan, Z., Fang, W., Chen, F., 2013. Genetic mapping of quantitative trait loci underlying flowering time in chrysanthemum (Chrysanthemum morifolium). PLoS One 8, e83023. Zhang, G., Gu, C., Wang, D., 2009. Molecular mapping of soybean aphid resistance genes in PI 567541B. Theor. Appl. Genet. 118, 473–482. Zhu, W., Zhang, F., Chen, S., Xu, L., Wang, L., Wang, H., Qi, X., Li, H., Chen, F., 2014. Intergeneric hybrid between Chrysanthemum morifolium ‘Nannongxiaoli’ and Artermisia vulgaris ‘Variegata’ show enhanced resistance against both aphids and Alternaria leaf spot. Euphytica 197, 399–408.
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Scientia Horticulturae journal homepage: www.elsevier.com/locate/scihorti
Inheritance and molecular markers for aphid (Macrosiphoniella sanbourni) resistance in chrysanthemum (Chrysanthemum morifolium Ramat.) Chuchu Wang, Fei Zhang, Zhiyong Guan, Sumei Chen, Jiafu Jiang, Weimin Fang, Fadi Chen ∗ College of Horticulture, Nanjing Agricultural University, No. 1, Weigang, Nanjing 210095, Jiangsu, PR China
a r t i c l e
i n f o
Article history: Received 2 July 2014 Received in revised form 15 October 2014 Accepted 17 October 2014 Available online 6 November 2014 Keywords: Chrysanthemum Aphid resistance Inheritance Molecular markers
a b s t r a c t Aphids have caused great damage to chrysanthemum production, and it’s crucial to breed new chrysanthemums with strong aphid resistance. However, little information is available regarding the inheritance of aphid resistance in chrysanthemum. The inheritance pattern of chrysanthemum aphid resistance within an F1 segregating population was dissected with the major gene plus polygene mixed inheritance model and molecular markers. The result showed that aphid resistance of chrysanthemum is a quantitative trait with a moderate coefficient of variation >50%. The mixed inheritance model based on a single segregating generation suggested the inheritance of aphid resistance was controlled by two pairs of major genes with additive effect 0.68 and 0.39, respectively. The heritability of major gene was calculated at 89.21%. Marker-trait analysis based on one-way variance analysis uncovered 11 markers significantly associated with phenotype, cumulatively explaining ∼74% variation. Bulked segregant analysis (BSA) based on the gene bulks of high resistant and susceptive genotypes in F1 population identified two SSR markers, SSR145-93 and SSR197-205, linked to high aphid resistance (r > 0.4). The QTL analysis detected 5 putative QTL for aphid resistance in two successive years, with individual QTL explaining the phenotypic variation of 14.30–28.00%. The inheritance model and molecular markers identified for aphid resistance facilitate the ongoing breeding activities in chrysanthemum. © 2014 Elsevier B.V. All rights reserved.
Introduction Chrysanthemum (Chrysanthemum morifolium Ramat.) is a traditionally famous flower in China and ranks the second in cut flower production worldwide. In 2011, the annual consumption of chrysanthemum in European, America and Japan reached up to 15, 8 and 20 billion branches, respectively. In chrysanthemum production, however, insects from different orders have negative impact on the quality of flower yield and require control. It is therefore particularly promising to develop sustainable insect pest management in ornamentals. The chrysanthemum aphid (Macrosiphoniella sanbourni) is one of the most major insect pests on chrysanthemum. Aphids directly injure leaves, shoots, and flowers, resulting in plant dwarf, leaf yellowing, and curling. Besides, while the release of honeydew fosters sooty mold infestation, aphids act as vectors for virus
∗ Corresponding author. Tel.: +86 25 84395592; fax: +86 25 84395266. E-mail address: [email protected] (F. Chen). http://dx.doi.org/10.1016/j.scienta.2014.10.038 0304-4238/© 2014 Elsevier B.V. All rights reserved.
transmission to infect chrysanthemum. To control insects, large amounts of chemical insecticides are needed to manage aphid pests, which are costly and often result in severe environment pollution. Additionally, it becomes more difficult to suppress the aphids that developed resistance to insecticide with the application of high-dose insecticides. With consideration given to economic and environmental reasons, integrated pest management programs in chrysanthemum production including natural enemies and insect proof net have been developed. However, these measures were found to be of minor importance for the suppression of the mentioned aphid species. Improving the host-plant resistance is an effective method for controlling aphid, since it does reduce the use of exogenous chemical insecticides or pecuniary loss, and the effect is stable and long-lasting (Jun et al., 2013; Sota et al., 2014). Thus breeding for resistant chrysanthemum cultivars is a further possibility to provide an efficient, economic and environmental friendly approach to reducing the losses caused by the injury of aphid. There has been a great effort to improve the aphid resistance in chrysanthemum. Transgenic plants with improved resistance to aphids
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have been reported in chrysanthemum (Wang et al., 2004; He et al., 2009), whereas there is a long way towards the commercial production of transgenic chrysanthemums. Recently, several authors have identified variable susceptibility of different chrysanthemum genotypes to aphids, and digged out some resistant chrysanthemums (He et al., 2010, 2011; Sun et al., 2012). Based on these observations, the resistant chrysanthemum produced thick palisade tissues, bushy trichomes, and dense wax on the lower leaf epidermis, and showed increased defense enzymes activities (He et al., 2011), and yielded more bioactive substance as terpene (Deng et al., 2010). These observations help understanding the mechanism of resistance to aphids in chrysanthemum. However, it is important to not only identify the resistant genotypes but also to improve chrysanthemum cultivars with increased aphid resistance by using these resistant germplasm. The latest finding suggested that hybridization between different resistant chrysanthemums conferred hybrids stronger resistance to aphid, but within a varied quantitative range (Zhu et al., 2014). The wide segregation of aphid resistance in hybrid progeny affords a genetic background for breeding resistant chrysanthemum. However, little information is available concerning the inheritance pattern of aphid resistance in chrysanthemum thus far. In order to better understand the inheritance of resistance to aphid, the present study was carried out to dissect the inheritance pattern of aphid resistance in chrysanthemum with the major gene plus polygene mixed inheritance model base on a single segregation analysis method, and to identify the putative molecular markers linked to aphid resistance. The findings from this study add an in-depth understanding to the genetic determinism of aphid resistance and aid in the ongoing breeding practices in improving aphid resistance of chrysanthemum. Materials and methods Plant materials Plant materials comprised 133 F1 progeny obtained from the cross between the two cultivars ‘Han 2’ (2n = 6x = 54) and ‘Nannong Gongfen’ (2n = 6x = 54). ‘Han 2’ is high resistant to aphid, and ‘Nannong Gongfen’ is susceptible. All the materials are maintained at the Chrysanthemum Germplasm Resource Preserving Center, Nanjing Agricultural University, China. Aphid resistance evaluation Evaluation of chrysanthemum aphid resistance was performed using artificial inoculation with aphids (M. sanbourni) in two consecutive years of 2011 and 2012. The chrysanthemum aphid used in this study was established in a growth chambers maintained at temperatures between 23 and 28 ◦ C with 80% relative humidity, by collecting aphids from a nearby chrysanthemum field. In this test, every seedling was grown in a 12 cm in diameter and 25 cm deep transparent plastic proof cage to prevent aphids from escaping and to restrict entry of predators in the cage from outside. Each plant was infested with five wingless adult aphids at the 6–8 leaves stage. Two parents were also included as checks. The chrysanthemum aphid resistance was evaluated by counting at 21 days after infestation (Deng et al., 2010). Individual plants were scored for ratio of aphid. Ratio of aphid was designated as the average of number of insect population in individual plant divided the average of number of insect population in all plants. The aphid resistance of chrysanthemum could be divided into five grades in terms of aphid number ratio, high resistance (aphid number ratio 0–0.25), moderate resistance (0.26–0.50), resistance (0.51–0.75), low resistance (0.76–1.25), and non-resistance (>1.25).
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Mixed inheritance model analysis The major gene plus polygene mixed inheritance model based on a single segregation generation described by Gai et al. (2003) was used to dissect the inheritance pattern of aphid resistance in chrysanthemum. Briefly, suppose under the modifications of polygene and environment, the effects of major gene in segregation generation display an independent normal distribution, then the whole segregation generation could be seen as a mixed distribution made up by many independent normal distributions. A joint maximum-likelihood function was derived to estimate the parameters of component distributions through the IECM (iterated expectation and conditional maximization) algorithm. Additionally, the Akaike’s information criterion (AIC), likelihood-ratio test (LRT), and a set of goodness-of-fit tests were used for model selection and test. Akaike (1977) suggested that the hypothesis maximizing the expected entropy should be selected as the most fitting model. For this purpose, based on goodness-of-fit and parsimony, the hypothesis that leads to the smallest AIC will be chosen. Here, the single generation segregation analysis may involve the two genetic model of null or one pair of major genes (A model) and two pairs of major genes (B model) in 11 kinds with special reference to major gene. The model with the least AIC value and best fitness was considered the best-fitting model. Genetic parameters were estimated with the method as detailed in Gai et al. (2003). DNA extraction and genotyping Total genomic DNA was isolated from young leaves using a modified CTAB protocol (Murray and Thompson, 1980). The F1 individuals together with the two parents was genotyped using three marker sets, including microsatellite (SSR), start codon targeted (SCoT) and sequence-related amplified polymorphism (SRAP). In this study, 200 SRAP, 300 SSR, and 18 SCoT primer combinations were screened for polymorphism across the two parents and eight randomly selected F1 individuals. The informative and polymorphic primer combinations were performed for later genotyping for marker-trait analysis and genetic mapping. All the primers were synthesized by Shanghai Sangon (Shanghai, China). PCR and electrophoretic procedures of SRAP, SSR and SCoT followed by Zhang et al. (2011a), Wang et al. (2013) and Li et al. (2013), respectively. Marker-trait analysis Marker profiles were scored by assigning ‘0’ for the absence and ‘1’ for the presence of each polymorphic fragment. Only reproducible and well-defined bands were scored. Each marker was identified by the primer pair used and a suffix was attached to the designation, where multiple fragments were identified from a single primer combination and molecular size. According to the marker-based method of Singh et al. (1991), for each marker, the segregating progeny were assigned into groups, formed by those scored as ‘0’ and those as ‘1’, and a one-way variance analysis was then performed for each marker in turn to detect any loci linked to aphid resistance. Bulked segregant analysis Bulked segregant analysis (BSA) method was also adopted to identify markers associated with aphid resistance. According to phenotype, each six radical aphid-resistance individuals for resistance bulk (RB) and extreme aphid-susceptible individuals for susceptible bulk (SB) were selected from the segregating F1 population. DNA bulk representing each extreme phenotype in a population was formed by mixing equal volume of DNA solution from each genotype in the bulk. DNA samples of the two parents and
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Fig. 1. Aphid density on seven plants at 21 days after aphid inoculation. (A): High resistance parent ‘Han 2’, (B): high resistant individual, (C): moderate resistant individual, (D): resistant individual, (E): low resistant individual, (F): non-resistant individual, (G): susceptive parent ‘Nannong Gongfen’.
the two bulks in each population were assayed using the selected polymorphic markers. The gels were scored for each marker used for the assay as described above and the polymorphic ones were selected for each population. A marker was regarded to be polymorphic at this stage when the different bands formed by the RB and SB bulks were similar to the bands formed by the RB and SB parents, respectively. Individual genotypes in the contrasting bulks of each population were then assayed using the markers found to be polymorphic between the two bulks to select the candidate markers. The genotypic data generated for each marker from screening of the individuals in the contrasting bulks of each population were correlated with the phenotypic data using Pearson correlation test in SPSS. Percent of presence or absence of band (RB parent band) among all the individuals in each phenotypic group was estimated for each polymorphic marker. A marker was regarded to be closely associated with aphid resistance genes when the correlation coefficient between phenotypic and genotypic data was ≥0.3 (Olasanmi et al., 2014). The genotypic and phenotypic data for each marker were subjected to regression analysis. Each candidate marker identified in a population was used to assay the remaining individuals in the population to identify the genotypes having the desirable marker(s).
by each QTL in proportion to the total phenotypic variance, which could be achieved from the CIM results.
Results Aphid resistance performance Aphid density at 21 days after inoculation is shown in Fig. 1. Aphid resistance of chrysanthemum segregated widely in the segregating F1 population with coefficient of variation 51.57% (Table 1). The skewness and kurtosis values and frequency distribution indicated that aphid resistance in the F1 population was compatible with a normal distribution (Table 1, Fig. 2). Therefore, aphid resistance of chrysanthemum is quantitatively inherited in nature.
Map construction and QTL screening The parental genetic maps were separately constructed based on the segregating polymorphic markers in the F1 population consisting of 133 individual plants. Linkage analysis with all markers in the F1 population was performed using Mapmaker/EXP3.0 (Lincoln et al., 1992). A minimum log likelihood of the odds (LOD) score of 3.0 and a maximum distance of 30 cM were use to group loci into linkage groups (LG). Genetic distances between loci were calculated using the Kosambi (1944) mapping function. Then two separate QTL mapping analyses were carried out by applying the composite interval mapping (CIM) method (Zeng, 1994) embedded in the Windows QTL Cartographer software (Wang et al., 2007). The window size was set at 10 cM and the walking speed at 1 cM. The LOD threshold to declare a putative QTL was 2.5. The contribution ratio (R2 ) by each QTL was estimated as the percentage of variance explained
Fig. 2. Frequent distributions for aphid resistance segregating in F1 population derived from a cross between ‘Han 2’ (P1 ) and ‘Nannong Gongfen’ (P2 ).
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Table 1 Phenotypic statistic values for aphid-resistance traits of chrysanthemum cultivars ‘Han 2’ (P1 ) and ‘Nannong Gongfen’ (P2 ) and their F1 mapping population in 2011 and 2012 seasons. F1 mapping population
Parent
Trait
P1 Aphid number of ratio 2012 0.05 2011 0.06
P2
Maximum
Minimum
Average
SD
Skewness
Kurtosis
1.33 1.37
2.42 2.50
0.06 0.05
1.00 1.00
1.29 1.40
0.71 0.73
0.4 0.5
Table 2 Akaike information criterion (AIC) values of various genetic models for aphid resistance traits in joint segregation analysis of F1 population derived from cross between ‘Han 2’ and ‘Nannong Gongfen’, and test for goodness-of-fit of selected genetic model. Model
AIC
A-0 A-1 A-2 A-3 A-4 B-1 B-2 B-3 B-4 B-5 B-6
166.83 160.13 158.15 170.83 180.33 166.24 164.13 140.48 155.34 170.83 168.83
U12
U22
U32
nW
Table 5 Percentage of presence of bands, correlation coefficients between the phenotypic and genotypic data individuals. Marker
Band present in resistant individuals (%)
Band present in susceptive individuals (%)
Correlation coefficient
SSR145-92.98 SSR197-204.15
88.9 91.9
42.9 28.6
0.41** 0.52**
D
** Indicates significant difference with the least significant difference (LSD) test at P < 0.01.
0.00(0.99)
0.00(0.99)
0.00(0.98)
0.02
0.04
0.39, respectively. The heritability of major gene was calculated at 89.21%. Molecular marker analysis
Table 3 Estimation of genetic parameters for aphid resistance traits of chrysanthemum at its optimal genetic model. Genetic parameter
m
da
db
p2
2 mg
h2mg (%)
Aphid number of ratio
1.20
0.68
0.39
0.27
0.31
89.21
m: Mean value of aphid number of ratio; da : the first major-gene additive effect; db : 2 : major-gene the second major-gene additive effect; 2 p: phenotypic variance; mg variance; h2mg : major-gene heritability.
Inheritance analysis The AIC values of various genetic models for aphid resistance traits in joint segregation analysis of F1 population and the goodness-of-fit test of selected genetic model are shown in Table 2. According to the assumption that the model with the least AIC value is the optimal model, the B-3 model that showed the smallest AIC value might be the preferred inheritance model for aphid resistance. After further goodness-of-fit tests, no significant differences were detected for this model (Table 2). Thus the optimal model for aphid resistance should be B-3, controlled by two pairs of major genes with additive effects. The estimated genetic parameters for aphid resistance at B-3 model are shown in Table 3. The additive effect values of the two pairs of major genes were 0.68 and
Screening against DNA of the two parental cultivars and 8 F1 individuals, 60, 53 and 6 polymorphic primer pairs respectively, for SRAP, SSR and SCoT were found to be informative and were used for genotyping the whole F1 population. As a result, a total of 763 (537 SRAP, 195 SSR and 31 SCoT) polymorphic fragments were yield, respectively. The marker-trait association analysis based on one-way variance method revealed seven SRAP markers and four SSR markers significantly associated with aphid-resistance (Table 4). These putative markers cumulatively explained 74.4% to the total phenotypic variation, but with a low contribution by individual markers to the phenotypic variance ranging from 6.3 to 8.9%. The SSR marker-based BSA method, revealed two SSR makers, SSR145-93 and SSR197 = 205, for the aphid resistance (Table 5). The marker-trait correlation coefficients were >0.3, indicating that SSR145-93 and SSR197-205 might be closely linked to aphid resistance genes. QTL mapping Of the 763 polymorphic markers, 386 testcross markers present in either parent were constructed genetic linkage maps for the two parents, ‘Han 2’ and ‘Nannong Gongfen’. Finally, 262 of 386 (67.9%) markers were grouped on the two parental maps, leaving 124 (32.1%) markers unlinked. 142 markers were placed on 30 linkage groups of ‘Han 2’ map, while ‘Nannong Gongfen’ linkage map
Table 4 The markers significantly associated with aphid-resistance in the F1 population detected by one-way ANOVA method. Marker name EM11ME13-919 EM12ME18-135 EM13ME24-226 EM14ME24-97 EM17ME5-80 EM19ME21-324 EM19ME21-437 SSR197-205 SSR147-232 SSR145-93 SSR52-143
Sum of squares between groups 67,629.62 58,308.37 67,639.55 61,875.33 57,487.64 77,885.44 71,319.06 61,671.60 78,169.99 34,765.98 80,457.69
Sum of squares within group 853,325.66 869,303.33 859,972.14 865,736.36 794,161.37 849,726.25 856,292.63 865,940.10 849,441.70 892,845.71 823,206.33
R2 indicates ratio of contribution to the total phenotypic variations explained by individual marker.
F value
P value
R2 (%)
7.846 6.775 7.944 7.219 6.877 9.258 8.412 7.193 9.295 3.933 9.774
0.006 0.011 0.006 0.008 0.01 0.003 0.005 0.009 0.003 0.05 0.002
7.34 6.29 7.29 6.67 6.75 8.40 7.69 6.65 8.43 3.75 8.90
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Table 6 QTL mapping for plant aphid-resistance of chrysanthemum in two years (environments), detected by WinQTL5.0. QTL
LG
Interval
Position (cM)
Range (cM)
LOD
A
R2 (%)
NoaE2G1 NoaE2G7 NoaE1H3 NoaE2H7 NoaE2H8
G1 G7 H3 H7 H8
SR149-268 E8M9-215 E12M18-99 E12M18-80 E16M6-383 SR197-113 S14-676 S16-370 S11-700 E16M18-109
36.44 80.12 54.78 28.92 87.68
1.0 2.0 6.0 4.0 8.0
2.60 2.58 3.35 3.94 2.74
−57.81 −40.00 −48.87 −62.04 −39.70
14.3 25.4 19.4 24.7 28.0
A is the additive genetic effects estimated at the testing points. Negative values mean that the corresponding parent has a negative effect on aphid density, that is, increasing aphid resistance. R2 indicates ratio of contribution to the total phenotypic variations explained by individual marker.
grouped 120 markers on 25 linkage groups. Both genetic maps have an adequate inter-marker distance ∼12 cM. The QTL analysis identified five QTLs closely associated with aphid resistance in 2011 and 2012 (Table 6), which mainly distributed on the linkage groups G1 and G7 of ‘Han 2’ map and H3, H7 and H8 of ‘Nannong Gongfen’ map (Fig. 3). Each of the five QTL explained >10% of the phenotypic variation within a range 14.30–28.00% (Table 6), thus these should be major QTL for aphid resistance. Discussion The performance of host-plant aphid resistance is resulted from the defense behavior of host plants, dependent on the morphological structure, biochemical and physiological response or the regulation of hormone signals (Li et al., 2008;Bos et al., 2010; Guo et al., 2012). For improving host-plant aphid resistance, it is crucial to understand the genetic determinism and to identify the molecular markers linked to aphid resistance genes. Inheritance of aphid resistance in chrysanthemum Identification of varieties and plant introductions that show resistance to aphids and characterization of the genes from the resistant sources are important early steps in the development of cultivars with resistance to aphid (Jun et al., 2013), so knowing the inheritance of aphid resistance is absolutely necessary. Previous researches suggested the inheritance of aphid resistance was more
quantitative rather than qualitative. Dominant and recessive genes were found to determine aphid resistance in many crops such as peach (Pascal et al., 2002), wheat (Liu et al., 2012), soybean (Hill et al., 2006; Mian et al., 2008; Xiao et al., 2013; Fox et al., 2014), and corn (So et al., 2010). In contrast, Julier et al. (2004) suggested a multigene inheritance with mainly additive effect for pea aphid resistance in lucerne, and the resistance level of lucerne cultivars was strongly correlated with their general combining abilities. Also, aphid resistance in soybean could also be quantitative (Zhang et al., 2009; Meng et al., 2011). Thus inheritance of aphid resistance varied with crops or genetic backgrounds, indicative of its complexity. As to chrysanthemum, it is largely self-incompatible and suffers from inbreeding depression (Anderson and Ascher, 2000). This makes it practically difficult to obtain advance generations of inbred lines of the sort used for genetic research in self-compatible species. The major gene plus polygene mixed inheritance model based a single segregating generation (F2 ) were successfully applied for genetic research using the F1 (pseudo-F2 ) population of heterozygous crops like chrysanthemum (Zhang et al., 2011b) and bromeliad (Wang et al., 2012), setting a good example for genetic dissection for aphid resistance in chrysanthemum. The present study suggested that aphid resistance varied quantitatively in the F1 progeny of chrysanthemum. Results from the mixed inheritance model analysis in this study demonstrated that aphid resistance in chrysanthemum was controlled by two major genes with additive effects and the heritability of major gene was as high as ∼89%. Thus, it should be relatively easy to select for aphid resistance in the early
Fig. 3. The significant quantitative trait loci (QTL) for chrysanthemum aphid resistance. NoaE1 and NoaE2 indicate the QTL for aphid resistance detected in 2011 and 2012, respectively.
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generations of breeding program. Also the detection of major genes is an important clue to the later research on identifying molecular markers associated with aphid resistance. The molecular markers for aphid resistance Current phenotyping methods including aphid density or abundancy for selection of plant resistant to aphid are cumbersome and cannot distinguish plants containing combinations of resistance genes from those carrying a single gene. To achieve durable resistance to aphid, it is therefore important to not only identify alternative sources of resistance but also to pyramid the resistance genes to effectively develop horizontal resistance. This is best achieved through the application of marker-assisted selection (MAS). MAS through the use of molecular markers closely linked to the resistance genes is a powerful selection tool that accelerates the breeding of new more durably resistant cultivars containing two or more pyramided resistance genes (Collard et al., 2005). Until present BSA (Olasanmi et al., 2014) and map-based QTL analysis (Stoeckli et al., 2008; Sauge et al., 2012; Kamphuis et al., 2013) were often adopted to find out the molecular markers associated with aphid resistance in previous publications. In the current study, the two methods together with marker-based variance analysis using three marker types of SRAP, SSR, and SCoT were attempted to identify markers linked to aphid resistance in chrysanthemum. The marker-trait association analysis by the method of one-way ANOVA detected 7 SRAP makers and 4 SSR markers significantly associated with aphid resistance with cumulative contribution ratio of ∼74%, but with a low individual contribution. This reinforces the quantitative nature of aphid resistance in chrysanthemum. Olasanmi et al. (2014) reported that a marker could be regarded to be closely associated with a gene when the correlation coefficient between phenotypic and genotypic data was ≥0.3, and identified 9 SSR markers closely linked to early bulking in cassava via BSA method. According to such mentioned assumption, in the present study, high correlation coefficients (r = 0.41–0.52, respectively; P < 0.01) between genotype and phenotype (i.e. aphid resistance here) were detected two SSR markers, SSR145-93 and SSR197205. Thus the two markers should be closely linked to the aphid resistance genes. The use of the SSR markers can aid in selecting with moderate precision for desired aphid resistance in chrysanthemum. Additionally, the marker SSR197-205 was detected by both marker-based variance analysis and BSA, and thus should be focused on in future MAS. Although molecular marker-based approaches to host-plant resistance against insects are common in annual crops (Wu and Huang, 2008; Ricciardi et al., 2010; Punnuri et al., 2013), and are intensively studied in chrysanthemum to dissect other horticultural traits (Zhang et al., 2011a, 2012, 2013), they have received little attention so far in chrysanthemum in connection with aphid suppression. In this study, the mapped-based QTL analysis identified five putative QTL for aphid resistance in two consecutive years of 2011 and 2012, distributing on both ‘Han 2’ and ‘Nannong Gongfen’ maps. All the QTL decreased ∼40 to ∼62 of the aphid density, that is, they had a positive effect on the aphid resistance. According to Falconer and Mackay (1996), QTL explaining >10% of phenotypic variation (R2 ) should be considered major QTL. Here, the R2 explained by individual QTL ranged from 14.30% to 28.00%, therefore indicative of that the five QTL should be of major QTL. However, it’s necessary to point out that the five QTL was not consecutively detected in different years. So we conclude that the QTL detected are readily influenced by environment, and should be further confirmed with more environment and genetic backgrounds before applied for MAS. Honestly, few common markers were detected between results from marker-based variance method and BSA with QTL mapping.
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This is probably because the genetic maps for the two chrysanthemum cultivars in this study were unsaturated and most of the detected markers by the former two methods were not grouped on the linkage maps. Though, findings from this research add a brand-new knowledge on the inheritance pattern and molecular markers for the aphid resistance in chrysanthemum. Moreover, the candidate markers should be a meaningful start to improving aphid-resistance with MAS in chrysanthemum. Acknowledgments The authors gratefully acknowledge the financial support provided by the National Natural Science Foundation of China (grant nos. 31272196, 31370699, 31372092, 31471900), 863 Project (2011AA100208), the Program for New Century Excellent Talents in University of the Chinese Ministry of Education (grant no. NCET12-0890), the Jiangsu Program for Hi-Tech Research (BE2012350), Fund for Independent Innovation of Agricultural Sciences in Jiangsu Province [CX(12)2020], and the Fundamental Research Funds for the Central Universities (KYTZ201401). References Anderson, N.O., Ascher, P.D., 2000. Fertility changes in inbred families of selfincompatible chrysanthemums (Dendranthema grandiflorum). J. Am. Soc. Hortic. Sci. 125, 619–625. Akaike, H., 1977. On entropy maximisation principle. In: Krishnaiah, P.R. (Ed.), Proceedings of the Symposium on Applications of Statistics. Amsterdam, The Netherlands, pp. 27–47. Bos, J.I.B., Prince, D., Pitino, M., Maffei, M.E., Win, J., Hogenhout, S.A., 2010. A functional genomics approach identifies candidate effectors from the aphid species Myzus persicae (green peach aphid). PLoS Genet 6, e1001216. Collard, B.C.Y., Jahufer, M.Z.Z., Brouwer, J.B., Pang, E.C.K., 2005. An introduction to markers, quantitative trait loci (QTL) mapping, and marker-assisted selection for crop improvement: The basic concepts. Euphytica 142, 169–196. Deng, Y., Chen, S., Lu, A., Chen, F., Tang, F., Guan, Z., Teng, N., 2010. Production and characterization of the intergeneric hybrids between Dendranthema morifolium and Artemisia vulgaris exhibiting enhances resistance to chrysanthemum aphid (Macrosiphoniella sanbourni). Planta 231, 693–703. Falconer, D.S., Mackay, T.F.C., 1996. Introduction to Quantitative Genetics, fourth ed. Longman Group Ltd, England. Fox, C.M., Kim, K.S., Cregan, P.B., Hill, C.B., Hartman, G.L., Diers, B.W., 2014. Inheritance of soybean aphid resistance in 21 soybean plant introductions. Theor. Appl. Genet. 127, 43–50. Gai, J.Y., Zhang, Y.M., Wang, J.K., 2003. Genetic System of Quantitative Traits in Plants. Science Press, Beijing, pp. 96–102. Guo, S.M., Kamphuis, L.G., Gao, L.L., Klingler, J.P., Lichtenzveig, J., Edwards, O., Singh, K.B., 2012. Identification of distinct quantitative trait loci associated with defence against the closely related aphids Acyrthosiphon pisum and A. Kondoi in Medicago truncatula. J. Exp. Bot. 63, 3913–3922. He, J., Chen, F., Chen, S., Fang, W., Miao, H., Luo, H., 2009. Transformation of Lycoris longtituba agglutinin gene to cut chrysanthemum and identification of aphid resistance in the transgenic plants. Acta Bot, Boreal.-Occident. Sin. 29, 2318–2325. He, J., Chen, F., Chen, S., Fang, W., 2010. Aphid-resistance of chrysanthemum cultivars. Chin. J. Ecol. 29, 1382–1386. He, J., Chen, F., Chen, S., Lv, G., Deng, Y., Fang, W., Liu, Z., Guan, Z., He, C., 2011. Chrysanthemum leaf epidermal surface morphology and antioxidant and defense enzyme activity in response to aphid infestation. J. Plant Physiol. 168, 687–693. Hill, C.B., Li, Y., Hartman, G.L., 2006. A single dominant gene for resistance to the soybean aphid in the soybean cultivar Dowling. Crop Sci. 46, 1601–1605. Julier, B., Bournoville, R., Landré, B., Ecalle, C., Carré, S., 2004. Genetic analysis of lucerne (Medicago sativa L.) seedling resistance to pea aphid (Acyrthosiphon pisum Harris). Euphytica 138, 133–139. Jun, T.H., Mian, M.A.R., Michel, A.P., 2013. Genetic mapping of three quantitative trait loci for soybean aphid resistance in PI567324. Heredity 111, 16–22. Kamphuis, L.G., Lichtenzveig, J., Peng, K., Guo, S.M., Klingler, J.P., Siddique, K.H., Gao, L.L., Singh, K.B., 2013. Characterization and genetic dissection of resistance to spotted alfalfa aphid (Therioaphis trifolii) in Medicago truncatula. J. Exp. Bot. 64, 5157–5172. Kosambi, D.D., 1944. The estimation of map distances from recombination values. Ann. Eugen. 12, 172–175. Li, Y., Zou, J.J., Li, M., Bilgin, D.D., Vodkin, L.O., Hartman, G.L., Clough, S.J., 2008. Soybean defense responses to the soybean aphid. New Phytol. 179, 185–195. Li, P., Jiang, J., Chen, S., Guan, Z., Liao, Y., Fang, W., Chen, F., 2013. Establishment and optimization of SCoT molecular marker system in chrysanthemum and its application of analysis on genetic diversity. Acta Hortic. Sin. 40, 2015–2025.
226
C. Wang et al. / Scientia Horticulturae 180 (2014) 220–226
Lincoln, S., Daly, M., Lander, E., 1992. Constructing gentic maps with mapmaker/EXP3.0. In: Whitehead Institute Techn. Rep, third ed. Whitehead Institute, Cambridge. Liu, X.L., Yang, X.F., Wang, C.Y., Wang, Y.J., Zhang, H., Ji, W.Q., 2012. Molecular mapping of resistance gene to English grain aphid (Sitobion avenae F.) in Triticum durum wheat line C273. Theor. Appl. Genet. 124, 287–293. Meng, F.L., Han, Y.P., Teng, W.L., Li, Y.G., Li, W.B., 2011. QTL underlying the resistance to soybean aphid (Aphis glycine Matsumura) through isoflavonemediated antibiosis in soybean cultivar ‘Zhongdou 27’. Theor. Appl. Genet. 123, 1459–1465. Mian, M.A.R., Kang, S.T., Beil, S.E., Hammond, R.B., 2008. Genetic linkage mapping of the soybean aphid resistance gene in PI 243540. Theor. Appl. Genet. 117, 955–962. Murray, M., Thompson, W.F., 1980. Rapid isolation of high molecular weight plant DNA. Nucleic Acids Res. 8, 4321–4325. Olasanmi, B., Akoroda, M.O., Okogbenin, E., Egesi, C., Kahya, S.S., Onyegbule, O., Ewa, F., Guitierrez, J., Ceballos, H., Tohme, J., Fregene, M., 2014. Bulked segregant analysis identifies molecular markers associated with early bulking in cassava (Manihot esculenta Crantz). Euphytica 195, 235–244. Pascal, T., Pfeiffer, F., Kervella, J., Lacroze, J.P., Saug, M.H., 2002. Inheritance of green peach aphid resistance in the peach cultivar ‘Rubira’. Plant Breed 121, 459–461. Punnuri, S., Huang, Y.H., Steets, J., Wu, Y.Q., 2013. Developing new markers and QTL mapping for greenbug resistance in sorghum [Sorghum bicolor (L.) Moench]. Euphytica 191, 191–203. Ricciardi, M., Tocho, E., Tacaliti, M.S., Vasicek, A., Gimenez, D.O., Paglione, A., Simmonds, J., Snape, J.W., Cakir, M., Castro, A.M., 2010. Mapping quantitative trait loci for resistance against Russian wheat aphid (Diuraphis noxia) in wheat (Triticum aestivum L.). Crop Pasture Sci. 61, 970–977. Sauge, M.H., Lambert, P., Pascal, T., 2012. Co-localisation of host plant resistance QTLs affecting the performance and feeding behaviour of the aphid Myzus persicae in the peach tree. Heredity 108, 292–301. Singh, P.S., Gutierrez, J.A., Molina, A., Urrea, C., Gepts, P., 1991. Genetic diversity in cultivated common bean: II Marker-base analysis of morphological and agronomic traits. Crop Sci. 31, 24–39. So, Y.-S., Ji, Y.C., Brewbaker, J.L., 2010. Resistance to corn leaf aphid (Rhopalosiphum maidis Fitch) in tropical corn (Zea mays L.). Euphytica 172, 373–381. Sota, T., Kagata, H., Ando, Y., Utsumi, S., Osono, T., 2014. Insect-Plant Interactions in Plant-Based Community/Ecosystem Genetics. Springer, Japan, pp. 25–43. Stoeckli, S., Mody, K., Gessler, C., Patocchi, A., Jermini, M., Dorn, S., 2008. QTL analysis for aphid resistance and growth traits in apple. Tree Genet. Genomes 4, 833–847.
Sun, Y., Guan, Z., Chen, S., Fang, W., Chen, F., 2012. Identification of aphid resistance in eleven species of Dendranthema and Artemisia at seedling stage. Acta Ecol. Sin. 32, 319–325. Wang, G., Liu, Y., Guo, S., Wang, Y., Ji, Y., Fang, H., 2004. Study on transformation of snowdrop lectin gene to chrysanthemum and aphid resistance of the transgenic plants. Acta Genet. Sin. 31, 1434–1438. Wang, S., Basten, J.C., Zeng, Z.B., 2007. Window QTL Cartographer Version 2.5. Statistical Genetics. North Carolina State University, USA. Wang, W., Zhang, F., Yu, X., Shen, X., Ge, Y., Zhang, Z., 2012. Genetic analysis and associated SRAP markers for horticultural traits of Aechmea bromeliads. Sci. Hortic. 147, 29–33. Wang, H., Jiang, J., Chen, S., Qi, X., Peng, H., Li, P., Song, A., Guan, Z., Fang, W., Liao, Y., Chen, F., 2013. Next-generation sequencing of the Chrysanthemum nankingense (Asteraceae) transcriptome permits large scale unigene assembly and SSR marker discovery. PLoS One 8, e62293. Wu, Y.Q., Huang, Y.H., 2008. Molecular mapping of QTLs for resistance to the greenbug Schizaphis graminum (Rondani) in Sorghum bicolor (Moench). Theor. Appl. Genet. 117, 117–124. Xiao, L., Hu, Y., Wang, B., Wu, T., 2013. Genetic mapping of a novel gene for soybean aphid resistance in soybean (Glycine max [L.] Merr.) line P203 from China. Theor. Appl. Genet. 126, 2279–2287. Zeng, Z.B., 1994. Precision mapping of quantitative trait loci. Genetics 136, 1457–1468. Zhang, F., Chen, S., Chen, F., Fang, W., Chen, Y., Li, F., 2011a. SRAP-based mapping and QTL detection for inflorescence-related traits in chrysanthemum (Dendranthema morifolium). Mol. Breed. 27, 11–23. Zhang, F., Chen, S., Chen, F., Fang, W., Deng, Y., Chang, Q., Liu, P., 2011b. Genetic analysis and associated SRAP markers for flowering traits of chrysanthemum (Chrysanthemum morifolium). Euphytica 177, 15–24. Zhang, F., Jiang, J., Chen, S., Chen, F., Fang, W., 2012. Mapping single-locus and epistatic quantitative trait loci for plant architectural traits in chrysanthemum. Mol. Breed. 30, 1027–1036. Zhang, F., Chen, S., Jiang, J., Guan, Z., Fang, W., Chen, F., 2013. Genetic mapping of quantitative trait loci underlying flowering time in chrysanthemum (Chrysanthemum morifolium). PLoS One 8, e83023. Zhang, G., Gu, C., Wang, D., 2009. Molecular mapping of soybean aphid resistance genes in PI 567541B. Theor. Appl. Genet. 118, 473–482. Zhu, W., Zhang, F., Chen, S., Xu, L., Wang, L., Wang, H., Qi, X., Li, H., Chen, F., 2014. Intergeneric hybrid between Chrysanthemum morifolium ‘Nannongxiaoli’ and Artermisia vulgaris ‘Variegata’ show enhanced resistance against both aphids and Alternaria leaf spot. Euphytica 197, 399–408.