Genetic divergence among inbred lines in Cucurbita moschata from China

Scientia Horticulturae 127 (2011) 207–213

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Genetic divergence among inbred lines in Cucurbita moschata from China Xiaohua Du ∗ , Yongdong Sun, Xinzheng Li, Junguo Zhou, Xiaomei Li Henan Institute of Science and Technology, Xinxiang, Henan Province 453003, PR China

a r t i c l e

i n f o

Article history: Received 20 November 2009 Received in revised form 10 August 2010 Accepted 29 October 2010 Keywords: Cucurbita moschata Cluster analysis PCA Heterotic group

a b s t r a c t Knowledge of genetic divergence among inbred lines is essential for cross breeding. The objectives of this study were to (1) analyze the level and character of genetic diversity in C. moschata accessions, and (2) classify the genetic divergence among inbred lines in C. moschata to assist in selection of parent genotypes for genetic improvement. Twenty agronomic characters were investigated and rich diversities were demonstrated among 39 inbred lines of C. moschata from China. Various degree correlations among these characters made it possible to summarize the diversities of the twenty characters into 3 major principal components: leaf, fruit and flesh quality factor. Forty-one inbred lines of pumpkin were clustered into four groups based on principal component data, which is more distinct for classification that based on the original data of the 20 characters. However, parent inbred lines whose hybrids displayed significant heterosis in fruit weight, soluble solid and fruit shape were located in different clusters or sub-clusters based on standardized original data. It was suggested that genotypes in the same clusters may represent members of one heterotic group. © 2010 Elsevier B.V. All rights reserved.

1. Introduction China is the largest global producer of cultivated pumpkin species, including Cucurbita moschata Duch. Agricultural production of pumpkin and squash in China was about 30% of global production (FAO, 2007). However, a large proportion of the production is based on traditional local cultivars which have been maintained by farmers for centuries, as has occurred in Span and Latin America and Africa (Marˇııa Ferriol et al., 2003; Gwanama et al., 2000; Lira-Saade, 1995), since the species was introduced from America. During the period of cultivation in China, C. moschata showed adaptation to different agro-ecological conditions and displayed high variability for many agronomic characters, such as fruit shapes and colors, flowering habits, leaf characters, etc. (Zhang, 2005a). Collecting and determining the degree of variability within these cultivars is necessary prior to their use in breeding program. Up to now, most of the analyses of genetic variability involving in C. moschata from China have focused on the establishment of phylogenetic relationships with other Cucurbita species using genetic markers (Li et al., 2000; Sun et al., 2004; Zhang, 2005b; Li, 2006). Chu et al. (2007) analyzed genetic diversity of 70 C. moschata accessions collected from different agro-ecological zones of China using the morphological and RAPD marker. However, the heterozygous genotypes of the accessions caused by outcrossing limited the genetic

∗ Corresponding author. Tel.: +86 0373 304 0384/1583 605 9716. E-mail address: [email protected] (X. Du). 0304-4238/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.scienta.2010.10.018

relationship among accessions application in breeding programs directly. The pumpkin breeding center of Henan Institute of Science and Technology has spent years on the task of collecting and selfing available genotypes of C. moschata in China to establish the level of genetic diversity and inbred lines for breeding of F1 cultivars. Currently this center conserves over 1000 accessions of C. moschata from various regions of China and has obtained over 100 inbred lines. The genetic divergence of parents is the basis of cross breeding for most crops. Therefore we sought to determine the genetic divergence of inbred lines in C. moschata using Multivariate statistical methods to reveal the level of genetic diversity of the species and to provide a reference for hybrid breeding because of heterosis in pumpkin and squash (Sirohi and Behera, 2000; Gwanama et al., 2001). Simultaneously, clusters of inbred lines based on the data dealing with or without PCA were compared for choosing a feasible clustering method based on morphological characters.

2. Materials and methods 2.1. Plant material Forty-one inbred lines were included in our investigation, including 39 C. moschata and two of C. maxima, derived from 8 generations selfing of traditional local cultivars from various regions of China (Table 1). Meanwhile, 68 hybrids were also contained to preliminary realize the relationship between heterosis and genetic divergence among inbred lines.

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X. Du et al. / Scientia Horticulturae 127 (2011) 207–213

Table 1 Origin and fruit shape of pumpkin accessions in the analysis. Species

Inbred lines

Origin

Fruit shape a

b

C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata

114 149 381 002-2 387 001-10 396 456 072-2 046-1 360-3 367-2 048-1 053-1 012-2 009-2 058-1 151 328 112-2 042-1

Jiaozuo , Henan Jiaozuo, Henan Jiyuan, Henan Jiyuan, Henan Anyang, Henan Anyang, Henan Hebi, Henan Xinxiang, Henan Xinxiang, Henan Sanmenxia, Henan Luoyang, Henan Luoyang, Henan Luoyang, Henan Luoyang, Henan Luoyang, Henan Luoyang, Henan Zhengzhou, Henan Zhengzhou, Henan Xinyang, Henan Xinyang, Henan Xinyiang, Henan

Pyriform Pyriform Crookneck Crookneck Crookneck Crookneck Dumbbell Crookneck Crookneck Crookneck Crookneck Crookneck Crookneck pyriform Crookneck Crookneck Crookneck Crookneck Crookneck Crookneck Crookneck

C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. moschata C. maxima C. maxima

045-3 395-1 063-2 080-3 140-1 460-2 777-14 396-1 062-2 458-1 Chang2 450 002-9 017-3 041-1 467-1 Sweet Yunnan4 Beiguan Xuanfu

Zhumajian, Henan Pingdingshan, Henan Yanling, Henan Puyang, Henan Puyang, Henan Kaifeng, Henan Kaifeng, Henan Zhoukou, Henan Zhoukou, Henan Zhoukou, Henan Zhoukou, Hennan Yulin, Shanxi Ankang, Shanxi Weinan, Shanxi Wuhan, Hubei Yaan, Sichan Chengdu, Sichan Kunming, Yunnan Zhumajian, Henan Xinyang, Henan

Crookneck Crookneck Pyriform Crookneck Crookneck Crookneck Crookneck Dumbbell Crookneck Crookneck Crookneck Oval Crookneck Crookneck Crookneck Round Crookneck Flattened Flattened Flattened

a b

Stands for district. Stands for province.

Eigenvalues, as the correlation coefficients between the first three principal components (Fi ) and the morphological characters. Based on Fi data, the Euclidean distances among accessions showed the distance indicators between pairs of inbred lines, which were calculated according to formula, dij = ( (Xik − Xjk )2 )1/2 , where dij was the distance between the ith sample and the jth sample, Xik was the standard data of the kth character of the ith sample and Xjk was the standard data of the kth character of the jth sample (Reif et al., 2005). An unweighted pair group method with arithmetic mean (UPGMA) employed these distances to construct a dendrogram. The dendrogram based on standardized original data-matrix was also constructed as a comparison with that Fi based data. A Mantel test was outcome in order to study the correlation between two distance matrices. A correlation analysis, a linear regression and a nonlinear regression were adopted to examine the relationship between mid-parent heterosis and genetic distance among parent inbred lines. 3. Results 3.1. Variance of 20 morphological characters The investigated data showed a large range of variability of morphological characters among the 39 inbred lines of C. moschata (Table 2). Regarding qualitative characteristics leaf color ranged from light green (e.g., ‘387 ) to dark green (e.g., ‘328 ), flesh colors ranged from white (e.g., ‘046-1 ) to orange (e.g., ‘318 ), firmness of flesh from loose (e.g., ‘012-2 ) to compact (e.g., ‘063-2 ), flesh taste ranged from rough (e.g., ‘041-1 ) to fine (e.g., ‘396 ), flesh texture from smooth-firm (e.g., ‘367-2 ) to fibrous-gelatinous (e.g., ‘112-2 ), and flesh flavor from insipid (e.g., ‘149 ) to sweet (e.g., ‘072-2 ). A large variability in quantitative traits was also found among inbred lines of C. moschata from China. For example, fruit weight of the 39 inbred lines was from 1.7 kg to 5.4 kg. The fruit length of 39 inbred lines from 9.4 to 80.0 cm and the fruit width was from 10 to 24 cm. The average variation coefficient of 14 quantitative traits among C. moschata was 26.6%. The variations of 14 quantitative traits by ANOVA were all significant. Simultaneously, morphological traits with more variance were usually related to the fruit. For example, the variation coefficient of fruit length/width was 44.1%, and that of fruit length was 36.7%.

2.2. Morphological evaluation 3.2. Relationship between 20 morphological characters All inbred lines were examined for a set of 14 quantitative and 6 qualitative characters used as descriptors, recommended by the IPGRI (2003), with minor adaptations for addition of three character descriptors including number of nodes between female flower, taste and firmness of flesh. The nomenclature of mature fruit morphology of accessions used herein was previously articulated by Esquinas-Alcaˇızar and Gulick (1983). The flesh taste was sequenced to 4 grades from rougher to rough, medium and fine. The firmness of flesh was classified into 4 grades from loose to medium, compact and more compacter. Three characters of the hybrids, fruit weight, fruit shape (fruit length/width) and soluble solid, were investigated. The quantitative and qualitative data in plant and fruit were measured in 10 plants and 15 fruits per accession.

Positive and negative correlations were found between the 20 morphological characters by correlation analysis, some correlations varied significantly. For instance, leaf length was positively correlated with leaf width, leaf petiole length, stem thickness and fruit weight, but negatively correlated with soluble solid. Positive correlations were between flesh thickness and fruit width, fruit weight, stem thickness. A negative correlation was between flesh thickness and fruit length. There was a positive correlation between firmness, texture, favor of flesh and soluble solid (Table 3). The correlation between characters helped us determinate the most important morphological characters for an identification and comprehensive description of accession.

2.3. Statistical analysis

3.3. Principal components of morphological characters

Six qualitative characters of 41 accessions were quantified according to their graduations. An ANOVA (analysis of variance) was executed to provide the significant differences of quantitative characters between accessions. A PCA was used to estimate correlations between characters and reduce multidimensional data sets to lower dimensions with the standardized original data-matrix. The total of variation explained was calculated as the sum of extracted

PCA generalized 20 morphological characters to three principal components which explained 57.03% of the total variability. The first component accounted for 25.13% of the total variation, and was mainly defined by leaf length, leaf width and leaf petiole length. The second component accounted for 20.48% of the total variation and was correlated with fruit width, flesh thickness and fruit weight. The third component accounted for 11.43% and was associated with

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Table 2 Morphological characters statistics and their correlation with the first 3 principal components (Fi ). Character Cumulative contribution Number of nodes to the first fruit Number of nodes between female flowers Stem thickness (mm) Internode length (cm) Leaf petiole length (cm) Leaf width (cm) Leaf length (cm) Fruit weight (kg) Number of seeds per fruit Fruit length (cm) Fruit diameter (cm) Fruit length/width Flesh thickness (cm) Soluble solids (%) Leaf color Flesh color Firmness of flesh Flesh favor Flesh texture Flesh taste

Mean

Std

Max

Min

C.V. (%)

F test

F1 25.13%

F2 20.48%

F3 11.43%

23.54

6.11

39.60

14.60

25.94

14.02**

0.23

0.04

−0.07

3.30

1.19

6.80

1.40

35.99

2.92**

0.25

0.04

−0.22

1.1 2.05 5.16 4.08 3.57 1.08 98.06 18.74 3.54 1.74 0.74 1.35 0.88 1.39 0.98 0.98 1.04 0.82

14.6 22.51 41.84 45.04 34.86 5.43 504.00 80.00 24.40 7.34 4.50 15.00 4.00 6.00 4.00 5.00 5.00 4.00

9.9 14.17 20.36 27.40 18.18 1.37 79.00 9.43 10.00 0.51 1.55 8.20 1.00 1.00 1.00 1.00 1.00 1.00

9.87 10.97 17.49 10.70 12.78 36.67 33.07 40.98 25.18 48.46 29.12 11.68 29.97 42.93 35.70 32.04 30.99 28.86

4.06** 6.62** 9.60** 8.79** 7.57** 2.18** 4.56** 12.61** 9.56** 12.12** 5.66** 4.36** − − − − − −

0.24 0.22 0.33 0.36 0.38 0.28 −0.02 0.26 −0.02 0.20 0.01 −0.01 0.06 −0.17 −0.33 −0.13 −0.24 0.04

0.24 −0.22 −0.01 0.11 0.10 0.25 0.06 −0.35 0.44 −0.41 −0.09 0.46 0.10 0.14 0.02 −0.23 −0.05 0.12

0.20 0.15 0.05 0.16 0.19 0.04 −0.21 0.05 −0.04 0.08 0.34 0.05 0.20 0.37 0.09 0.32 0.40 0.44

11.7 18.65 29.50 38.16 27.94 2.936 296.52 45.74 14.06 3.58 2.53 11.58 2.93 3.24 2.73 3.07 3.37 2.85

*P < 0.05. ** P < 0.0l.

taste, texture and favor of flesh (Table 2). Therefore, three principal components could be called leaf factor, fruit factor and flesh quality factor, respectively. 3.4. Clustering of 41 inbred lines The genetic distances (GD) between every inbred lines (including 39 of C. moschata and 2 of C. maxima) were estimated based on the first 9 principle component (>85% of the total variability explained) data. The results showed the average GD between C. maxima accessions and C. moschata accessions were 7.55 greater than the average GD among C. moschata accessions (GD = 5.58) and GD between C. maxima accessions (GD = 4.18). However, the GDs among inbred lines of C. moschata were not shown to be relevant to criteria of geographic origin, e.g., the average GD between ‘Yunnan4 derived from Yunnan province and the accessions from Henan province was (GD = 5.98) not distinctly different from that of among accessions derived from Henan province (GD = 5.56). According to the Mantel test, the GD based on principle component data was correlated with that of original data, with a value of 98.7%. The dendrogram based on principle components data (D1 ) grouped 41 inbred lines in four major clusters morphologically (Fig. 1). Cluster I included two C. maxima accessions (‘Xuanfu’ and ‘Beiguan’), which have small leaf, short petiole, few nodes to the first female flower, small flattened fruit, insipid and mealy flesh. While cluster II, III and IV included those of C. moschata accessions. It reflected distinct difference between interspecies. In cluster II, ‘151 , ‘387 and ‘367-2 were grouped together, with uniform morphological characters such as big leaf, long petiole, many nodes to the first female flower, big and elongated fruit, sweet and smoothfirm texture flesh, morphologically contrast with the C. maxima accessions. The morphotypes of cluster III and cluster IV were between cluster I and cluster II. Cluster III included 10 inbred lines of C. moschata which were similar to those of cluster I morphologically. While cluster IV contained the remaining 26 inbred lines of C. moschata which were similar to those of cluster II morphologically. Moreover, Cluster III could be classified into two sub-clusters, one contained five inbred lines (‘396 , ‘Yunnan4 , ‘467-1 , ‘053-1 and ‘396-1 ), the other contained the remained five inbred lines (‘114 ,

‘063-2 , ‘149 , ‘Sweet’ and ‘450 ). Cluster IV could also be classified into two sub-clusters, one included seven inbred lines (‘001-10 , ‘460-2 , ‘012-2 , ‘046-1 , ‘062-2 , ‘395-1 and ‘458-1 ), one included the other nineteen inbred lines. The dendrogram based on standardized original data (D2 ) grouped 41 inbred lines in five major clusters (Fig. 2). Though

Fig. 1. Dendrogram of 41 inbred lines based on principle components data.

X. Du et al. / Scientia Horticulturae 127 (2011) 207–213

0.117 0.435** −0.081 0.134 0.468** −0.014 −0.355* −0.285 −0.435** 0.148 0.318* 0.147 0.209 0.152 0.175 −0.093 −0.560** −0.149 −0.276 0.241

Fig. 2. Dendrogram of 41 inbred lines based on original data.

0.533** −0.370* 0.521** 0.065 −0.391* −0.105 −0.390* 0.207 −0.097 0.140 −0.015 0.322* −0.117 0.082 0.445** −0.048 −0.252 −0.327* −0.081 0.413** −0.032 0.035 0.002 −0.128 0.203 0.152 0.093 −0.081 −0.025 0.331*

0.381* −0.048 0.300 0.074 −0.134 −0.087 −0.527** −0.272 −0.329* 0.039

0.313* 0.213 0.196 0.091 0.220 −0.117 −0.537** −0.103 −0.278 0.131

D2 was similar to D1 in many aspects, there were some differences between them. The differences between D1 and D2 were in three aspects. One was the sub-cluster of cluster III in D1 included five inbred lines (‘396 , ‘Yunnan4 , ‘467-1 ‘053-1 and ‘396-1 ) was become an independently cluster (cluster V) in D2 . While the other sub-cluster of cluster III except ‘063-2 and the sub-cluster of cluster IV except ‘460-2 formed cluster III in D2 , and became two subclusters of cluster III. The other sub-cluster of cluster IV included nineteen inbred lines in D1 incorporated with ‘063-2 and ‘4602 formed cluster IV in D2 . On the whole, the grouping of D2 was not more distinct than that of D1 morphologically. That maybe because the cluster based on the principal components extracted the major information of genetic divergence among inbred lines and ignored some minor information. Therefore, it is helpful to transform original data of characters into several principle components for classification (Huang and Wu, 2006).

0.129 −0.034 0.119 −0.076 0.091 −0.355* −0.273 −0.093 −0.122 −0.035

0.233 0.008 0.149 −0.184 0.055 −0.249 −0.340* −0.361* −0.365* −0.144

0.367* 0.268 0.372* 0.058 0.012 0.346* 0.193 0.231 0.139 0.125 0.166 0.481** 0.328* * 0.369 0.270 0.521** 0.426** 0.317* 0.553** 0.338* 0.342* 0.527** −0.013 −0.040 −0.044 0.160 −0.030 0.227 0.116 0.137 0.129 −0.258

**

P < 0.05. P < 0.0l.

3.5. Heterotic group

*

0.435** 0.122

Leaf color (lc) Number of nodes to the first fruit (nnf) Number of nodes between female flowers (nbf) Stem thickness (st) Internode length (il) Leaf petiole length (lpl) Leaf width (lw) Leaf length (ll) Fruit weight (fw) Number of seeds per fruit (ns) Fruit length (fl) Fruit width (fwd) Fruit length/width (fs) Flesh color (fc) Flesh thickness (ft) Firmness of flesh (ff) Soluble solid (ss) Flesh favor (ffr) Flesh texture (ftt) Flesh taste (fta)

−0.031

nnf lc Traits

Table 3 Correlation matrix of 20 morphological characters.

nbf

st

il

pl

lw

ll

0.576** 0.641** 0.925** 0.309* 0.568** 0.607** −0.059 −0.095 −0.006

fw

0.155

sn

−0.130 0.157 −0.197 0.071 0.004 0.003 0.041 −0.146 −0.156 −0.237

fl

−0.602** 0.940** 0.148 −0.637** −0.399** −0.423** 0.193 −0.224 −0.010

fwd

−0.777** −0.163 0.854** 0.203 0.034 −0.253 −0.120 0.088

fs

fc

0.167 −0.739** −0.214 −0.373* 0.307 −0.316* 0.059 0.270 0.333* −0.108 0.230 −0.028 0.054

ft

0.260 0.020 −0.275 0.001 0.305

ff

0.270 0.177 0.443** 0.261

ss

ffr

0.238 0.468** 0.509** 0.036 −0.048

ftt

0.297

210

Divergent genotypes may have good breeding value. Genotypes in the same cluster may represent members of one heterotic group. Maximum variability for selection in segregating populations may be achieved by utilising genotypes from different clusters as parents of crosses. For this reason, we examined the heterosis of three agricultural characters of 68 hybrids (Table 4). We found the parental inbred lines whose hybrids had mid-parents heterosis exceeded 10% in three characters were generally located in different clusters or sub-clusters in D2 , except those of three hybridized combinations “041-1 × 042–1” in soluble solid, “112–2 × 002–2” and “456 × 360–3” in fruit weight. While just some of those parents were in different clusters and some of them were in the same

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211

Table 4 Heterosis of 68 hybrids and distances between their parents. Hybridized combination

Fruit shape

Fruit weight (g)

Soluble solid (%)

Dis1

Dis2

F1

MPH

F1

MPH

F1

MPH

114 × 151 114 × 002-2 045-3 × 114 151 × 149 149 × 396 002-9 × 149 009-2 × 149 041-1 × 149 042-1 × 149 058-1 × 149 Sweet × 149 151 × 042-1 151 × 045-3 151 × 062-2 140-1 × 151 151 × 360-3 112-2 × 151 151 × Xuanfu 328 × 045-3 Chang2 × 328 381 × 450 396 × 001-10 002-2 × 396 045-3 × 396 396 × 063-2 450 × 002-9 450 × 009-2 041-1 × 450 450 × 058-1 450 × 063-2 467-1 × 450 450 × Sweet 450 × Chang2 456 × 360-3 001-10 × 042-1 001-10 × 045-3 001-10 × 062-2 001-10 × 112-2

3.21 3.29 2.34 2.23 2.51 2.54 2.54 2.46 2.40 2.32 2.02 3.31 3.30 4.20 2.39 4.54 4.42 1.19 3.43 3.45 3.78 3.09 2.33 2.36 2.41 3.19 2.67 2.73 2.73 1.85 0.93 1.86 2.61 5.14 4.46 4.45 5.19 3.85

0.01 0.06 −0.01 −0.09 0.09 −0.06 −0.02 −0.04 −0.04 −0.06 0.01 −0.04 −0.04 −0.04 −0.13 −0.01 0.04 −0.14 −0.04 −0.06 0.03 −0.04 −0.02 0.00 0.13 −0.03 −0.03 −0.03 −0.04 −0.05 −0.11 −0.04 −0.06 0.02 −0.02 −0.01 −0.02 −0.04

2790 2951 2200 3131 3233 1917 2467 2167 2467 2217 3167 3740 3088 3483 2880 3233 3352 2181 2000 1333 2983 4429 2750 2845 3233 2200 2575 2700 2183 2500 2800 2517 1467 4223 3538 3275 3196 3188

−0.059 0.049 −0.016 −0.068 −0.037 −0.077 −0.068 −0.073 −0.071 −0.053 −0.002 −0.025 −0.041 −0.038 −0.081 −0.047 −0.045 −0.085 −0.005 −0.062 −0.075 0.137 −0.042 −0.027 −0.004 −0.094 −0.094 −0.091 −0.097 −0.087 −0.085 −0.090 −0.144 0.102 0.101 0.147 0.074 0.174

9.75 7.50 11.30 11.60 13.2 15.0 15.5 12.1 14.4 12.3 13.1 11.05 9.10 9.60 9.85 10.20 10.90 10.70 15.0 13.9 14.1 7.40 10.40 10.35 15.0 14.2 16.7 15.3 14.2 12.9 12.7 15.0 14.1 8.40 12.10 10.85 9.95 10.00

−0.016 −0.104 0.008 0.022 0.024 0.072 0.064 0.014 0.044 0.021 0.026 0.003 −0.019 −0.027 0.001 −0.026 0.008 −0.030 0.103 0.056 0.052 −0.080 −0.051 −0.019 0.066 0.055 0.086 0.121 0.063 0.021 0.019 0.065 0.045 −0.088 0.021 0.019 −0.024 0.008

5.55 5.55 5.12 4.82 3.87 4.67 4.92 5.98 5.12 5.76 2.61 6.76 6.56 4.77 4.35 6.15 6.30 9.03 4.77 2.73 5.23 7.43 6.10 5.98 5.73 6.29 5.67 7.80 7.16 5.34 6.48 3.19 6.32 2.90 6.76 6.39 4.75 6.90

6.06 6.36 5.77 5.09 4.50 4.84 5.20 6.17 5.28 6.12 3.90 6.87 6.88 5.31 4.54 6.49 6.39 9.24 5.30 3.52 5.49 7.78 6.84 6.35 6.42 6.65 6.14 7.77 7.34 5.68 6.81 4.28 6.47 3.21 6.76 6.39 4.75 6.90

001-10 × 360-3 002-2 × 042-1 002-2 × 045-3 002-2 × 062-2 112-2 × 002-2 360-3 × 002-2 041-1 × 002-9 002-9 × 063-2 002-9 × Chang2 009-2 × 042-1 009-2 × 045-3 009-2 × Chang2 009-2 × 063-2 041-1 × 042-1 041-1 × 063-2 041-1 × 072-2 042-1 × 053-1 042-1 × 063-2 042-1 × 112-2 042-1 × 360-3 042-1 × 467-1 042-1 × Chang2 112-2 × 045-3 080-3 × 045-3 360-3 × 045-3 458-1 × 045-3 058-1 × 063-2 112-2 × 360-3 112-2 × Chang2 Sweet × 063-2 Sweet × Chang2

4.44 3.42 3.67 3.42 3.18 3.78 3.86 3.23 3.24 4.15 2.81 3.63 2.68 4.13 2.63 3.63 1.77 3.37 3.43 4.37 0.89 3.62 2.93 2.84 3.26 3.46 3.07 3.28 3.39 1.77 2.32

−0.05 −0.01 0.02 −0.06 −0.01 −0.03 −0.02 0.00 −0.07 0.06 −0.03 −0.01 0.02 0.04 −0.01 −0.03 −0.05 0.07 0.01 0.01 −0.14 −0.02 −0.02 −0.07 −0.05 −0.09 0.02 −0.04 −0.02 0.01 −0.06

3300 3225 2423 2081 4385 2624 2167 1800 2000 2300 2050 2800 2117 2500 2733 2267 3945 2467 3300 3700 3840 2467 3480 1833 3333 2333 2667 2616 2400 3300 3750

0.101 0.005 −0.008 −0.071 0.175 −0.010 −0.007 −0.051 0.014 −0.072 −0.065 0.030 −0.065 −0.035 0.018 −0.062 −0.011 −0.040 0.032 0.045 0.037 −0.010 0.103 −0.041 0.062 −0.049 0.040 −0.012 0.024 0.058 0.155

11.30 11.85 12.15 10.15 10.95 13.65 14.0 12.6 15.3 9.1 13.4 15.6 15.1 16.4 15.6 14.3 11.40 15.6 8.1 9.0 10.05 15.0 9.60 13.4 13.5 11.6 13.7 10.40 7.40 13.0 6.4

−0.008 −0.063 −0.002 −0.057 −0.044 −0.069 0.067 0.025 0.083 −0.069 0.040 0.067 0.059 0.100 0.095 0.075 −0.013 0.072 −0.088 −0.077 −0.057 0.058 −0.040 0.043 0.032 0.033 0.057 −0.050 −0.098 0.027 −0.114

6.01 4.64 5.15 5.81 6.35 5.53 4.36 4.52 2.80 2.38 3.27 3.45 3.70 3.89 4.76 5.21 7.82 4.76 3.85 4.00 7.03 3.95 5.85 5.92 6.08 6.89 4.26 3.33 5.06 4.17 4.53

6.01 4.42 5.15 5.81 6.35 5.53 4.84 4.88 3.78 3.13 4.23 4.21 4.19 4.19 4.96 5.65 7.82 5.08 3.86 4.23 7.03 4.59 5.85 6.08 6.21 7.10 4.73 3.33 5.47 4.63 4.96

Note: Dis1 is the distance based on PCA and Dis2 is the distance based original data. MPH stands for mid-parent heterosis.

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clusters in D1 . It was revealed that the clusters base on PCA data corresponded with heterotic groups was not better than those on original morphological data. For instance, the heterosis of “00110 × 045-3” in fruit weight was 14.7%, their parents were located in cluster III and cluster IV in D2 , respectively, while they were located in the same cluster IV in D1 . Similar instances were also found in hybridized combinations “467–1 × 450” and “396 × 0632” in fruit shape, “112-2 × 045–3” and “001-10 × 112-2” in fruit weight, and “328 × 045–3” in soluble solid. Therefore, it was suggested the cluster base on original data maybe more suitable for classification of heterotic groups than that on PCA. The heterosis of 68 hybridized combinations were significantly correlated with their parents distances in fruit shape (length/width ratio) (r = −0.33 on original data and r = −0.35 on PCA), but a linear and a non-linear relationship were not found between them by regression analysis. In fruit weight, the correlation between heterosis and the genetic distances was not significantly, as well as in soluble solid. 4. Discussion The great variation of C. moschata from China agreed with previous study using morphological and molecular markers. In some studies, greater genetic diversity was observed in C. moschata than in C. maxima. However, the results between C. moschata and C. pepo varied with the study (Sun et al., 2004; Liu et al., 2004; Zhang, 2005b). The genetic diversity in C. moschata was probably attribute to the genetic variability of the species for adapting to the diverse agro-ecological conditions in China since the species introduced 500 years ago (Shu, 1998). On the other hand, the variation from crossing between different types was the main cause. For example, the types of C. moschata introduced were only crookneck and round primitively, but currently a great diversity of types in China was found, such as round, oval, pear-shaped and dumbbell form, etc. (Chu et al., 2007). With the most genetic diversities (Mohanty and Mishra, 1999), pumpkin usually manifests itself in many ways, such as fruit shape, fruit weight, leaf size, etc. The rich of diversity provide more selection chances in breeding, but brings complexity in classification of germplasm resources and breeding selection. In our study, by the PCA, the diversities of 20 traits were summarized into 3 major factors represented by leaf factor (represented by leaf size), fruit factor (represented by fruit width) and flesh quality factor. These 3 major factors could be as the priority indexes in screening of germplasm and breeding selection. The greater GD between C. maxima accessions and C. moschata and firstly separating between interspecies in this study, were accorded with the previous studies that relationship between interspecies were more distant than that of intraspecies (Li, 2006). None of the classifications obtained clearly grouped the different accessions based on geographic origin in C. moschata, which was accord with previous grouping by DNA markers (Zhang, 2005b; Chu et al., 2007). Different factors could have led to this grouping. The out crossing in C. moschata may have contributed to similarities within regions. On the other hand, this grouping could also be due to the existence of seed exchanges among farmers. The same phenomenon seems to occur among farmers from Malawi and Zambia, where 40% of the C. moschata seeds are exchanged (Gwanama et al., 2000) and also in Mexico, where the percentage of C. moschata seed exchange is approximately 62% (Montes-Hernaˇındez and Eguiarte, 2002). On the contrary, the classifications on local varieties of C. moschata in Korean and that in Zambia and Malawi and Spain, were corresponds to the distribution areas of these pumpkins, suggesting that they were developed in isolated zones (Youn and Chung, 1998; Gwanama et al., 2000; Marıˇıa Ferriol et al., 2004). The prediction of heterosis could reduce blindness in hybridized combinations. It was believed by some researcher that a close corre-

lation between the magnitude of genetic divergence and heterosis (Ali et al., 1995; Gwanama et al., 2001). And genetic distance estimation has been adopted for predicting heterosis (Cheres et al., 2000; Joshi et al., 2001). However, genetic distances based on morphological data or molecular marker data have not always showed good correlation with specific combining ability or mid-parent heterosis (Heathcliffe Riday et al., 2003), including in our preliminary study about C. moschata. Fortunately, cluster analysis based on genetic distance matrix provides another way to predicting heterosis. Genotypes in the same cluster may represent members of one heterotic group. Clusters based on original data likely more suitable to classification of heterotic group than that on PCA. The minor information of genetic divergence ignored by PCA may have certain value for heterotic groups classifying. Sensible hybridized combinations may be achieved by utilising genotypes from different clusters as parents of crosses in C. moschata. Acknowledgements This research was financially supported by Henan Science & Technology Department of PR China within the Key Scientific and Technological Project (072102120006). Thanks are due to Ph. D. Zhengui Zheng, Howard Hughes Medical Institute and Katy Evans, for their editorial help. References Ali, M., Copeland, L.O., Elias, S.G., Kelly, J.D., 1995. Relationship between genetic distance and heterosis for yield and morphological traits in winter canola (Brassica napus L.). Theoretical and Applied Genetics 91 (1), 118–121. Cheres, M.T., Miller, J.F., Crane, J.M., Knapp, S.J., 2000. Genetic distance as a predictor of heterosis and hybrid performance within and between heterotic groups in sunflower. Theoretical and Applied Genetics 100 (6), 889–894. Chu, P.P., Xiang, C.P., Zhang, C.X., Liu, C.P., 2007. Genetic diversity of Cucurbita moschata genotypes revealed by RAPD markers and agronomic traits. Journal of Nuclear Agricultural Science 21 (5), 441–444. Esquinas-Alcaˇızar, J.T., Gulick, P.J., 1983. Genetic Resources of Cucurbitaceae – A Global Report. IBPGR Secretariat, Rome, Italy. FAO, 2007. http://faostat.fao.org. Gwanama, C., Botha, A.M., Labuschagne, M.T., 2001. Genetic effects and heterosis of flowering and fruit characteristics of tropical pumpkin. Plant Breeding 120 (3), 271–272. Gwanama, C., Labuschagne, M.T., Botha, A.M., 2000. Analysis of genetic variation in Cucurbita moschata by random amplified polymorphic DNA (RAPD) markers. Euphytica 113, 19–24. Heathcliffe Riday, E., Charles Brummer, T., Austin Campbell, D.L., Cazcarro Patricia, M., 2003. Comparisons of genetic and morphological distance with heterosis between Medicago sativa subsp. sativa and subsp. Falcate. Euphytica 131 (1), 37–45. Huang, Y., Wu, P., 2006. SAS (Statistical Analysis System) and its Application. China Machine Press, Beijing, pp. 293–296 (in Chinese). IPGRI, 2003. Descriptors for Melon (Cucumis melo L.). International Plant Genetic Resources Institute, Rome, Italy. Joshi, S.P., Bhave, S.G., Chowdari, K.V., Apte, G.S., Dhonukshe, B.L., Lalitha, K., Ranjekar, P.K., Gupta, V.S., 2001. Use of DNA markers in prediction of hybrid performance and heterosis for a three-line hybrid system in rice. Biochemical Genetics 39 (5–6), 179–200. Li, H.Y., 2006. Genetic Diversity Analysis of Germplasm Resource by RAPD. Xinjiang Agricultural University, Wulumuqi, China (in Chinese). Li, H.Z., Xu, Y., Wu, J.X., Wang, Y.J., Guo, J., Shou, S.Y., 2000. Studies on genetic relationship and molecular identification of three main cultivated species in Cucurbita. Journal of Agricultural Biotechnology 8 (2), 161–164 (in Chinese). Lira-Saade, R., 1995. Estudios taxonoˇımicos y ecogeograˇı ficos de las Cucurbitaceae latinoamericanas de importancia econoˇı mica. Systematic and Ecogeographic Studies on Crop Genepools, vol. 9. International Plant Genetic Resources Institute, Rome. Liu, X.J., Li, Y.J., Zhao, Y., Fang, C., Sun, Z.H., Wang, M.L., 2004. Analysis of genetic variation in some Chinese cultivated pumpkin and squash resources by random amplified polymorphic DNA (RAPD) markers. Southwest China Journal of Agricultural Sciences 17 (5), 567–571 (in Chinese). Marˇııa Ferriol, Maria Beleˇın Picoˇı, Fernando Nuez, 2003. Genetic diversity of some accessions of Cucurbita maxima from Spain using RAPD and SBAP markers. Genetic Resources and Crop Evolution 50, 227–238. Marıˇıa Ferriol, Beleˇın Picoˇı, Pascual Fernaˇındez de Coˇı rdova, Fernando Nuez, 2004. Molecular diversity of a germplasm collection of squash (Cucurbita moschata) determined by SRAP and AFLP markers. Crop Science 44, 653– 664.

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