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Parental Selection of Hybrid Breeding Based On Maternal and Paternal Inheritance of Traits in Rapeseed (Brassica napus L.).
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Parental selection is crucial for hybrid breeding, but the methods available for such a selection are not very effective. In this study, a 6×6 incomplete diallel cross was designed using 12 rapeseed germplasms, and a total of 36 hybrids together with their parental lines were planted in 4 environments. Four yield-related traits and seed oil content (OC) were evaluated. Genetic distance (GD) was estimated with 359 simple sequence repeats (SSRs) markers. Heterosis levels, general combining ability (GCA) and specific combining ability (SCA) were evaluated. GD was found to have a significant correlation with better-parent heterosis (BPH) of thousand seed weight (TSW), SCA of seeds per silique (SS), TSW, and seed yield per plant (SY), while SCA showed a statistically significant correlation with heterosis levels of all traits at 1% significance level. Statistically significant correlations were also observed between GCA of maternal or paternal parents and heterosis levels of different traits except for SS. Interestingly, maternal (TSW, SS, and OC) and paternal (siliques per plant (SP) and SY) inheritance of traits was detected using contribution ratio of maternal and paternal GCA variance as well as correlations between GCA and heterosis levels. Phenotype and heterosis levels of all the traits except TSW of hybrids were significantly correlated with the average performance of parents. The correlations between SS and SP, SP and OC, and SY and OC were statistically significant in hybrids but not in parents. Potential applications of parental selection in hybrid breeding were discussed.
Authors:
Nailin Xing; Chuchuan Fan; Yongming Zhou
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Type:  JOURNAL ARTICLE     Date:  2014-7-25
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Title:  PloS one     Volume:  9     ISSN:  1932-6203     ISO Abbreviation:  PLoS ONE     Publication Date:  2014  
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Journal ID (nlm-ta): PLoS One
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ISSN: 1932-6203
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Received Day: 30 Month: 4 Year: 2014
Accepted Day: 26 Month: 6 Year: 2014
collection publication date: Year: 2014
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DOI: 10.1371/journal.pone.0103165

Parental Selection of Hybrid Breeding Based On Maternal and Paternal Inheritance of Traits in Rapeseed (Brassica napus L.) Alternate Title:Parental Selection of Hybrid Breeding in Rapeseed
Nailin Xingaff1
Chuchuan Fanaff1
Yongming Zhouaff1*
Meng-xiang Sunedit1 Role: Editor
National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
Wuhan University, China
Correspondence: * E-mail: ymzhou@mail.hzau.edu.cn
[conflict] Competing Interests: The authors have declared that no competing interests exist.
Contributed by footnote: Conceived and designed the experiments: YMZ. Performed the experiments: NLX. Analyzed the data: NLX. Contributed reagents/materials/analysis tools: YMZ CCF NLX. Contributed to the writing of the manuscript: NLX YMZ.

Introduction

Plant breeding currently faces the daunting task of meeting the challenges posed by global climate change and a growing need for food supply and bioenergy. Heterosis has proven to be an efficient way to improve yield and environmental adaptability, and has been used in breeding of many crops [1][3]. Rapeseed (Brassica napus), an important oilseed crop worldwide, is one of the most successful crops in application of heterosis [4][7]. So far, the vast majority of the hybrid cultivars has been developed through extensive selection of F1 hybrid combinations, thus involving high cost and a lengthy turn-around period. Therefore, it is necessary to explore efficient methods that could predict hybrid performance in the parental generation.

In the past two decades, a number of studies have been reported that investigated methods for hybrid performance prediction in rapeseed. Riaz et al. and Tan et al. found a significant correlation between genetic distance (GD) and yield heterosis through molecular markers [8][9]. Ali et al. found significant correlations between GD and yield-component traits, but no significant correlation was identified for the number of branches per plant [10]. However, Yu et al. found significant correlations between some agronomic traits, but not for seed yield [11]. Diers et al. reported that GD was significantly correlated only with heterosis of seed yield in inbred diallel combinations, but not with cultivar diallel [12]. Qian et al. found no significant correlations between heterosis and GD, but significant correlations between general combining abilities (GCA) and hybrid performance [13]. Similarly, Teklewold and Becker, and Devi and Singh both found significant correlations between combining abilities and hybrid performance [14][15]. However, no effective method of parental selection has been proposed through GD and combining abilities in hybrid breeding.

A thorough understanding of the inheritance mode of traits is essential to establish an effective method for parental selection. Inheritances of traits have been analyzed widely in bi-parent populations and diallel crosses in rapeseed, and additive, dominance and epistasis effects have been identified for a wide array of traits [16][20]. In addition, maternal and paternal inheritances of traits have been studied using reciprocal crosses in many crops [21][23]. Maternal and paternal effects of heterosis have been identified only through analyzing GCA variance contributed by different parents [24]. However, no report is available about different correlations between traits in parents and hybrids, together with the correlations between heterosis levels and GCA of different parents.

The objectives of the current study are to investigate: (1) the relationships between GD, combining abilities, and heterosis levels, (2) maternal and paternal contribution to hybrid performances through analysis of GCA variance and correlations between heterosis levels and GCA of different parents, and (3) correlations between traits with parents as homozygous genotypes and hybrids as heterozygous genotypes. Our results provide novel information for parental selection in hybrid breeding of rapeseed.


Materials and Methods
Plant materials and field experiments

The experimental materials used in this study comprised 12 semi-winter rapeseed germplasms including 5 cultivars and 7 inbred lines whose characteristics was described in Table S1. With the parental lines listed in Table S1, a total of 36 hybrids were developed using a 6×6 incomplete diallel cross design (Table 1).

The hybrids along with the parents were grown in 4 natural environments at 3 different locations. They were planted in a winter rapeseed crop area at the experimental farm of Huazhong Agricultural University, Wuhan, China in the season of 2009–2010 and 2010–2011, and Huanggang Academy of Agricultural Sciences, Huanggang, China in the season of 2010–2011 [25], and in a spring rapeseed crop area in Hezheng, Gansu, China in the season of 2010. The field experiments of Huanggang were granted permission by the administrative board of the Huanggang Academy of Agricultural Sciences. The experiment location of Gansu was the experiment base of Huazhong Agricultural University, and no specific permission was required for the field trial. All parents and hybrids were used for all the environments and growing seasons and were grown for the evaluation of phenotype traits at the mature plant stage. All the field trials in this study did not involve endangered or protected species.

All the field experiments followed a randomized block design with 3 replications, and each replication comprised parents and hybrids that were planted in 4 rows with 48 plants for each plot. The crop was cultivated with standard agronomic practices. Ten mature plants in the middle of each plot were randomly selected for trait evaluation, and the mean value of each trait was used for analysis. Seed yield per plant (SY), seeds per silique (SS), siliques per plant (SP), thousand seed weight (TSW), and oil content in seeds (OC) were evaluated as described by Shi et al. [19].

Genetic diversity

Genomic DNA was isolated following the standard procedure [26]. A total of 359 simple sequence repeats (SSRs) including all the markers mapped on the linkage groups constructed by Fan et al. [27] were used to analyze the genetic diversity of parents. Genetic diversity was estimated on the basis of polymorphism generated by SSR primers. Amplification profiles of test genotypes were compared with each other and bands of DNA fragments were scored as ‘1’ for present and ‘0’ for absent. The genetic distance was computed using UPGMA method by NTSYSPC Version 2.10e [28].

Statistical analysis

The mid-parent heterosis (MPH), better-parent heterosis (BPH), general combining ability (GCA), specific combining ability (SCA) and correlation coefficients were calculated using SAS v9.3 software (SAS Institute, Cary, North Carolina, USA) using the GLM procedure [29][30].

The MPH was calculated as: MPH (%)  =  (F1 – MP)/MP ×100, BPH (%)  =  (F1 – BP)/BP ×100. where MP is the mean of the two parents, and BP the value of the better parent.

For combining ability analyses, the GCA for parents and SCA for hybrids were calculated using the following formula, respectively:

[Formula ID: pone.0103165.e001]

Here, , , and represent the GCA of female and male parent, and SCA of the hybrid, respectively; represents the mean value of all the hybrids; represents the value of the hybrid produced with the fth female parent and the mth male parent; n represent the number of female or male parents. The variance of additive effect (A), dominant effect (D), additive by additive effect (AA), and their interaction with environment (AE, DE, and AAE) were estimated using QGA Station Version 1.0 software [31]. The broad sense of heritability (h2b), narrow sense heritability (h2n), variance of GCA, variance of SCA, and ANOVA analysis were conducted using DPS software [32]. Heritability was calculated using the following formula:

[Formula ID: pone.0103165.e007]

Here, is the genotypic variance, is the additive variance, and is the phenotypic variance [24]. MPH and BPH of hybrids, and GD of the parents between the hybrids, as well as GCA and SCA of the parents and hybrids were correlated with each other to assess the relationship between these genetic parameters and parental diversity.

The maternal and paternal inheritances were analyzed by calculating the correlation coefficients between the hybrids and their parents and comparing the contribution of female and male genotypic variance to total genotypic variance for each trait [24]. The correlation coefficients between the traits investigated were computed through phenotypic performance of parents and hybrids, respectively. The correlation coefficients between the hybrids and their maternal or paternal lines were computed through phenotypic performance of each trait.


Results
Estimation of variance and covariance components

Variances of genetic effect (G), environment effect (E), and G×E were statistically significant for all traits in parents, hybrids, and all the plant materials including parents and hybrids at the 1% significance level, except for the environment effect of SY in hybrids and SP in all the plant materials (Table 2). In addition, the additive, dominant and additive by additive interaction effects were statistically significant for all traits at the 1% significance level, except for the additive effect of SY, dominant effect of SS and AA of SP and TSW (Table 3). For the genetic and environment interaction effect, AE of TSW and OC, and AAE of SY, SS, and SP were not significant. For SP, the dominant effect was greater than the additive effect. On the contrary, the additive effect was higher than the dominant effect for TSW and OC. These results indicated that SY of hybrid was mainly controlled by the dominant and epistasis effects, SS was mainly controlled by the additive and epistasis effects, SP was mainly controlled by the dominant effect, and TSW and OC were mainly controlled by the additive effect. Furthermore, the SY of hybrids had stronger environment adaptability than parents did, which was consistent with prior research [33].

Heterosis performance of hybrids

The MPH ranged from −12.88% of SP for P6×P8 to 96.17% of SY for P2×P11, and SY showed the highest average MPH (45.41%) among the 5 traits (Table 4). The BPH ranged from −22.78% of SS for P5×P8 to 64.64% of SY for P2×P11, and SY also had the highest average BPH (26.07%) among the 5 traits. The average MPH and BPH showed a positive direction for all the traits, except for the average BPH of SS and TSW. This result was consistent with prior research [9].

Heritability, combining abilities and GD

For the 5 traits, h2b and h2n ranged from 68.27% to 93.05%, and 18.61% to 74.88% respectively (Table 5). TSW showed the highest heritability, whether h2b or h2n, followed by SS, while the h2n of SY was only 18.61%.

The variance of GCA was higher than that of SCA for all traits except for SY. Additionally, TSW showed the highest GCA variance of 80.47% among the 5 traits while SY showed the lowest GCA variance of 25.71%. Furthermore, maternal genotypic variance was found to contribute more to total genotypic variance than paternal one for SS, TSW, and OC, but less for SY and SP. The maternal and paternal contributions to TSW showed the greatest difference among the 5 traits (Table 5).

A total of 359 SSR markers were used to estimate the genetic diversity of the parents. The number of polymorphic alleles generated by the markers ranged from 1 to 11 with an average of 3. The genetic distances between both parents of the hybrids ranged from 0.21 for P3×P7 and P1×P8 to 0.72 for P4×P7 (Table 1).

Relationships of GD, combining abilities, and heterosis levels

No significant relationship was found between GD and MPH for all 5 traits (Table 6), which was consistent with prior reports [1], [13]. However, a negative and statistically significant correlation was detected between GD and BPH of TSW at the 1% significance level. In addition, statistically significant correlations were detected between GD and SCA of SS, TSW, and SY at the 1% and 5% significance level, respectively. Each trait had a positive and statistically significant correlation between SCA and the heterosis levels at the 1% significance level.

The relationships between heterosis level and GCA of the maternal or paternal parent were computed (Table 6). OC and TSW showed statistically significant correlations between heterosis level and GCA of maternal parents at the 5% and 1% significance level, respectively. SP and SY displayed positive and statistically significant correlations between heterosis levels and GCA of both parents at the 5% or 1% significance level. SS showed no significant correlation between heterosis levels and GCA of both parents.

Performances of hybrids are closely related to parents

Correlation coefficients between performance of hybrids and their parents were found to be positive and statistically significant at the 1% significance level (Table 7). In addition, the correlations between performance of hybrids and the average performance of the two parents were also statistically significant at the 1% significance level. However, the correlations between heterosis levels and the average performance of their parents were negative and statistically significant at the 1% or 5% significance level, except for TSW (Figure 1, Table 8).

Correlations of phenotypes among the 5 traits were computed with parents as the homozygous genotype and hybrids as the heterozygous genotype, respectively (Table 9). Positive and statistically significant correlations were detected between SY and SP, and between SS and OC at the 1% significance level in both homozygous and heterozygous genotypes, while a negative correlation were found between SS and TSW. However, negative and statistically significant correlations were detected only in heterozygous genotypes between SY and OC, and between SP and two other traits (SS and OC) at the 5% and 1% significance level, respectively.


Discussion

In this study, all 5 traits appeared to have high heterosis levels and a wide variations (Table 4), which is consistent with previous studies [12][13]. This result suggests great potential for improving yield-related traits in rapeseed through hybrid breeding.

Though heterosis of rapeseed appears to be strong, it has not been utilized fully in hybrid breeding. One of the reasons is the difficulty in predicting heterosis level from parental generation [1], [14]. To explore an effective way to heterosis prediction, relationships of GD with combining abilities and heterosis levels were extensively studied, and significant correlations were detected in some traits in the previous studies [1], [8], [10], [34]. However, contradictory results for correlations between GD and heterosis of seed yield and some agronomic traits were also reported [10][11]. In our study, GD was significantly correlated only with BPH of TSW, and SCA of SY, TSW, and SS (Table 6), which suggested that GD is a valuable genetic parameter for predicting heterosis levels based on the molecular markers [27], [35], but should be used with cautions and with other parameters together.

Another way to hybrid prediction is to use the estimates of combining ability. Qian et al. and Rameeh found significant correlations between heterosis levels and combining abilities in rapeseed [13], [36]. However, no significant correlation was found between GD and heterosis levels in prior research [13]. In maize, significant correlations were found between heterosis levels and combining abilities [15], [37]. Similarly, our study found significantly positive correlations between combining abilities and heterosis levels in all 5 traits except for GCA of SS. Our results together with previous studies indicate that combining ability may be considered a more effective parameter than GD in heterosis prediction of rapeseed.

Thus far, the contributions of GCA variance of different parents together with maternal and paternal effects to hybrid performance have been rarely studied, especially in rapeseed [24]. In our study, the contribution ratios of the two parental GCA variances as well as the correlations between heterosis levels and GCA of parents showed that TSW was mainly controlled by the maternal genotype, and the maternal effect was 55.22% higher than paternal effect. Furthermore, our study showed that heterosis levels had a statistically significant and positive correlation with GCA of maternal parent (Tables 5 and 6). SS was also controlled by maternal genotype, while for OC, the contribution of maternal parent was slightly higher than that of paternal parent, which was different from Wang et al. [38]. The maternal effect of various seed traits including seed size was shown in many other crops to be correlated with parental environmental effects (e.g. availability of light, temperature, water, and nutrients) and cytoplasmic effects [39][40]. Based on the contribution ratio of GCA variance and correlation between heterosis levels and GCA of parents, paternal parent contributed more than maternal parent for SY, which provided valuable information for SY improvement in hybrid breeding of rapeseed. For SP, paternal parent contributed slightly more than maternal parent. Higher paternal effect on inheritance was also found in the leaflet area and other traits in carrot [41]. This paternal effect is likely contributed by epigenetic mechanisms [42], and plays an important role in the expression of polyphenic traits [43].

To the best of our knowledge, no report has to date has explored the relationships between traits in parental lines and their hybrids of rapeseed. Our study revealed that the correlations between SS and TSW, SS and OC, and SY and SP are statistically significant in both parents and hybrids (Table 9). In contrast, correlations between SS and SP, SP and OC, and SY and OC only appeared to be statistically significant in hybrids. The relationships between traits that are different from those obtained from homozygous genotypes or homozygous genotypes mixed with heterozygous genotypes provide valuable information for hybrid breeding.

Previously, additive, dominant, and epistasis effects were all detected for yield and yield related traits in rapeseed hybrids [19]. Zhang et al. found that SS was mainly controlled by the additive effect [44], which was similar to the results from our study (Table 2, and 5). In contrast to the result of Amiri-Oghan et al. [17], we found SY was mainly controlled by the additive by additive effect (Table 3). However, dominant effect was also detected for SY inheritance by Shen et al. and Radoev et al. [45][46]. Interestingly, traits primarily controlled by maternal parent were mainly additive inheritance, and traits primarily controlled by paternal parents were mainly dominant inheritance in our study. The reason for this phenomenon is unknown, and further studies are needed to understand the mechanism underlying this phenomenon.

In conclusion, hybrid performance in hybrid breeding might be predicted by combining ability supplemented with GD. Furthermore, the selection of maternal and paternal parents should be based on the maternal or paternal control of traits in hybrid breeding. For example, parents with a higher combining ability of TSW should be selected as a female parent, while parents with a higher combining ability of SY as a male parent. Our study provides useful information for parental selection in hybrid breeding of rapeseed and other crops.


Supporting Information Table S1

Major characteristics of the parental lines used for incomplete diallel crosses.

(DOC)


Click here for additional data file (pone.0103165.s001.doc)


References
1. Melchinger AE (1999) Genetic diversity and heterosis. J.G. Coors, S. Pandey (Eds.), Genetics and Exploitation of Heterosis in Crops, ASA/CSSA/SSSA, Madison, WI, pp. 99–118.
2. Sellis D,, Callahan BJ,, Petrov DA,, Messer PW, (Year: 2011) Heterozygote advantage as a natural consequence of adaptation in diploids. Proc Natl Acad Sci USA108: 20666–2067122143780
3. Schnable PS,, Springer NM, (Year: 2013) Progress toward understanding heterosis in crop plants. Annu Rev Plant Biol64: 71–8823394499
4. Thurling N, (Year: 1991) Application of the ideotype concept in breeding for higher yield in the oilseed brassicas. Field Crop Res26: 201–219
5. Shen JX,, Wang HZ,, Fu TD,, Tian BM, (Year: 2008) Cytoplasmic male sterility with self-incompatibility, a novel approach to utilizing heterosis in rapeseed (Brassica napus L.). Euphytica162: 109–115
6. Tochigi T,, Udagawa H,, Li F,, Kitashiba H,, Nishio T, (Year: 2011) The self-compatibility mechanism in Brassica napus L. is applicable to F1 hybrid breeding. Theor Appl Genet123: 475–48221544575
7. Chen SY,, Guan CY,, Wang GH,, Li X,, Liu ZS, (Year: 2012) Breeding of Xiangzayou 763, a new double-low and high oil content rapeseed cultivar. Crop Res26: 40–42
8. Riaz A,, Li G,, Quresh Z,, Swati M,, Quiros C, (Year: 2001) Genetic diversity of oilseed Brassica napus inbred lines based on sequence- related amplified polymorphism and its relation to hybrid performance. Plant Breed120: 411–415
9. Tan Z,, Li Y,, Hu Q,, Mei D,, Li Y,, et al. (Year: 2007) Heterosis prediction based on genetic distance estimated by molecular markers in rapeseed. Chinese J. Oil Crop Sci29: 126
10. Ali M,, Copeland L,, Elias S,, Kelly J, (Year: 1995) Relationship between genetic distance and heterosis for yield and morphological traits in winter canola (Brassica napus L.). Theor Appl Genet91: 118–12124169676
11. Yu C,, Hu S,, Zhao H,, Guo A,, Sun G, (Year: 2005) Genetic distances revealed by morphological characters, isozymes, proteins and RAPD markers and their relationships with hybrid performance in oilseed rape (Brassica napus L.). Theor Appl Genet110: 511–51815578151
12. Diers B,, McVetty P,, Osborn T, (Year: 1996) Relationship between heterosis and genetic distance based on restriction fragment length polymorphism markers in oilseed rape (Brassica napus L.). Crop Sci36: 79–83
13. Qian W,, Sass O,, Meng J,, Li M,, Frauen M,, et al. (Year: 2007) Heterotic patterns in rapeseed (Brassica napus L.): I. Crosses between spring and Chinese semi-winter lines. Theor Appl Genet115: 27–3417453172
14. Teklewold A,, Becker HC, (Year: 2006) Comparison of phenotypic and molecular distances to predict heterosis and F1 performance in Ethiopian mustard (Brassica carinata A. Braun). Theor Appl Genet112: 752–75916365759
15. Devi P,, Singh N, (Year: 2011) Heterosis, molecular diversity, combining ability and their interrelationships in short duration maize (Zea mays L.) across the environments. Euphytica178: 71–81
16. Ramsay L,, Bradshaw J,, Griffiths D,, Kearsey M, (Year: 2001) The inheritance of quantitative traits in Brassica napus ssp. rapifera (swedes): Augmented triple test cross analyses of production characters. Euphytica121: 65–72
17. Amiri-Oghan H,, Fotokian M,, Javidfar F,, Alizadeh B, (Year: 2009) Genetic analysis of grain yield, days to flowering and maturity in oilseed rape (Brassica napus L.) using diallel crosses. Int J Plant Prod3: 19–26
18. Chen W,, Zhang Y,, Yao J,, Ma C,, Tu J,, et al. (Year: 2011) Quantitative trait loci mapping for two seed yield component traits in an oilseed rape (Brassica napus) cross. Plant Breed130: 640–646
19. Shi J,, Li R,, Zou J,, Long Y,, Meng J, (Year: 2011) A dynamic and complex network regulates the heterosis of yield-correlated traits in rapeseed (Brassica napus L.). PloS One6: e2164521747942
20. Zhang L,, Yang G,, Liu P,, Hong D,, Li S,, et al. (Year: 2011) Genetic and correlation analysis of silique-traits in Brassica napus L. by quantitative trait locus mapping. Theor Appl Genet122: 21–3120686746
21. Hua W,, Li RJ,, Zhan GM,, Liu J,, Li J,, et al. (Year: 2012) Maternal control of seed oil content in Brassica napus: the role of silique wall photosynthesis. Plant J69: 432–44421954986
22. Nodine MD,, Bartel DP, (Year: 2012) Maternal and paternal genomes contribute equally to the transcriptome of early plant embryos. Nature482: 94–9722266940
23. Debes P,, Fraser D,, McBride M,, Hutchings J, (Year: 2013) Multigenerational hybridisation and its consequences for maternal effects in Atlantic salmon. Heredity111: 238–24723652564
24. Lou XY,, Hu QS,, Bao MZ,, Ye YM, (Year: 2010) Analysis of combining ability of two-types of male sterile and four restorer lines of Zinnia elegans. Euphytica174: 91–103
25. Wu J,, Cai G,, Tu J,, Li L,, Liu S,, et al. (Year: 2013) Identification of QTLs for resistance to Sclerotinia stem rot and BnaC. IGMT5. a as a candidate gene of the major resistant QTL SRC6 in Brassica napus. PloS One8: e6774023844081
26. Murray M,, Thompson WF, (Year: 1980) Rapid isolation of high molecular weight plant DNA. Nucleic Acids Res8, 4321–43267433111
27. Fan C,, Cai G,, Qin J,, Li Q,, Yang M,, et al. (Year: 2010) Mapping of quantitative trait loci and development of allele-specific markers for seed weight in Brassica napus. Theor Appl Genet121: 1289–130120574694
28. Rohlf F (2000) Multivariate Analysis System, Version 2.10 e, Applied Biostatistics. Inc, New York.
29. Goffman FD,, Becker HC, (Year: 2001) Diallel analysis for tocopherol contents in seeds of rapeseed. Crop Sci41: 1072–1079
30. Valdiani A,, Kadir MA,, Saad MS,, Talei D,, Tan SG, (Year: 2012) Intra-specific hybridization: Generator of genetic diversification and heterosis in Andrographis paniculata Nees. A bridge from extinction to survival. Gene505: 23–3622683537
31. Zhu J,, Weir BS, (Year: 1994) Analysis of cytoplasmic and maternal effects. I. A genetic model for diploid plant seeds and animals. Theor Appl Genet89: 153–15924177822
32. Tang Q, Feng M (2002) DPS data processing system for practical statistics. Science, Beijing.
33. Haussmann BIG,, Obilana AB,, Ayiecho PO,, Blum A,, Schipprack W,, et al. (Year: 2000) Yield and yield stability of four population types of grain Sorghum in a semi-arid area of Kenya. Crop Sci40: 319–329
34. Bansal P,, Banga S,, Banga S, (Year: 2012) Heterosis as investigated in terms of polyploidy and genetic diversity using designed Brassica juncea amphiploid and its progenitor diploid species. PloS One7: e2960722363404
35. Shen JX,, Fu TD,, Yang GS,, Tu JX,, Ma CZ, (Year: 2006) Prediction of heterosis using QTLs for yield traits in rapeseed (Brassica napus L.). Euphytica151: 165–171
36. Rameeh V, (Year: 2010) Combining ability and factor analysis in F2 diallel crosses of rapeseed varieties. Plant Breed Seed Sci62: 73–83
37. Balestre M,, Machado J,, Lima J,, Souza J,, Nóbrega-Filho L, (Year: 2008) Genetic distance estimates among single cross hybrids and correlation with specific combining ability and yield in corn double cross hybrids. Genet Mol Res7: 65–7318273821
38. Wang X,, Liu G,, Yang Q,, Hua W,, Liu J,, et al. (Year: 2010) Genetic analysis on oil content in rapeseed (Brassica napus L.). Euphytica173: 17–24
39. Xu Y,, Li HN,, Li GJ,, Wang X,, Cheng LG,, et al. (Year: 2011) Mapping quantitative trait loci for seed size traits in soybean (Glycine max L. Merr.). Theor Appl Genet122: 581–59420981403
40. Marty C,, BassiriRad H, (Year: 2014) Seed germination and rising atmospheric CO2 concentration: a meta-analysis of parental and direct effects. New Phytologist202: 401–414
41. Grebenstein C,, Kos SP,, Jong TJ de,, Tamis WLM,, Snoo GR de, (Year: 2013) Morphological markers for the detection of introgression from cultivated into wild carrot (Daucus carota L.) reveal dominant domestication traits. Plant Biol15: 531–54023173917
42. Curley JP,, Mashoodh R,, Champagne FA, (Year: 2011) Epigenetics and the origins of paternal effects. Horm Behav59: 306–31420620140
43. Buzatto BA,, Simmons LW,, Tomkins JL, (Year: 2012) Paternal effects on the expression of a male polyphenism. Evolution66: 3167–317823025606
44. Zhang LW,, Liu PW,, Hong DF,, Huang AQ,, Li SP,, et al. (Year: 2010) Inheritance of seeds per silique in Brassica napus L. using joint segregation analysis. Field Crops Res116: 58–67
45. Shen JX,, Fu TD,, Yang GS,, Ma CZ,, Tu JX, (Year: 2005) Genetic analysis of rapeseed self-incompatibility lines reveals significant heterosis of different patterns for yield and oil content traits. Plant Breed124: 111–116
46. Radoev M,, Becker HC,, Ecke W, (Year: 2008) Genetic analysis of heterosis for yield and yield components in rapeseed (Brassica napus L.) by quantitative trait locus mapping. Genetics179: 1547–155818562665

Figures

[Figure ID: pone-0103165-g001]
doi: 10.1371/journal.pone.0103165.g001.
Figure 1  Relationships between average performances of parents and their hybrids for heterosis levels of seed yield.

(A) relationship with MPH. (B) relationship with BPH. * Significant at p = 0.05; ** significant at p = 0.01; n = 36



Tables
[TableWrap ID: pone-0103165-t001] doi: 10.1371/journal.pone.0103165.t001.
Table 1  Genetic distance between parental lines used for 6×6 incomplete diallel crosses.
Parental lines P1 P2 P3 P4 P5 P6
P7 0.36 0.38 0.21 0.72 0.44 0.61
P8 0.21 0.40 0.40 0.66 0.43 0.61
P9 0.41 0.50 0.58 0.33 0.53 0.44
P10 0.37 0.41 0.44 0.53 0.40 0.46
P11 0.46 0.45 0.54 0.57 0.45 0.46
P12 0.47 0.49 0.56 0.50 0.52 0.46

P1 to P6: maternal parents; P7 to P12: paternal parents.

P1, P2, P3, P7, and P8: cultivars (P1: ZS5; P2: ZS7; P3: ZS10; P7: ZS9; P8: HS5). P4 to P6, and P9 to P12: inbred lines.

See also Table S1 for detailed characteristics of the parental lines.


[TableWrap ID: pone-0103165-t002] doi: 10.1371/journal.pone.0103165.t002.
Table 2  Double factors variance analysis of traits.
DF SY SS SP TSW OC
Parent G 11 191.54** 110.15** 59614.20** 2.36** 34.29**
E 3 104.47** 24.01** 32519.32** 0.78** 71.83**
G×E 33 29.79** 65.05** 8293.86** 0.75** 14.77**
Hybrid G 35 300.44** 98.26** 70730.35** 2.86** 30.89**
E 3 5.68 126.44** 6482.04** 2.90** 28.71**
G×E 105 21.50** 12.80** 7499.03** 0.22** 5.65**
Total G 47 326.60** 107.03** 71818.80** 2.76** 48.46**
E 3 34.52** 61.92** 923.54 1.57** 66.22**
G×E 141 24.59** 26.64** 8335.66** 0.39** 10.17**

G: genotype; E: environment; G×E: interaction of genotype and environment; DF: degree of freedom.

SS: seeds per silique; SP: siliques per plant; SY: seed yield per plant; TSW: thousand seed weight; OC: oil content in seeds; MPH: middle parent heterosis; BPH: better parent heterosis. The same abbreviations were used below.

** Significant at P = 0.01


[TableWrap ID: pone-0103165-t003] doi: 10.1371/journal.pone.0103165.t003.
Table 3  Variance analysis of traits (By QGA station).
SY SS SP TSW OC
A 0 1.76** 592.14** 0.24** 1.15**
D 0.45** 0 961.36** 0.13** 0.29**
AA 6.46** 2.59** 0 0 0.38**
AE 2.89** 3.11** 1423.52** 0 0
DE 8.66** 3.65** 2695.86** 0.02** 0.23**
AAE 0 0 0 0.03** 0.56**

A: additive effect; D: dominant effect; AA: interaction of additive and additive effect; AE: interaction between additive and environment effect; DE: interaction between dominant and environment effect; AAE: interaction of epistasis of additive and additive effect and environment effect.

** Significant at P = 0.01.


[TableWrap ID: pone-0103165-t004] doi: 10.1371/journal.pone.0103165.t004.
Table 4  Heterosis level of incomplete diallel crosses.
Traits MPH (%) BPH (%)
Mean ±SD Range Mean ±SD Range
SY 45.41±0.21 8.10∼96.17 26.07±0.17 −3.35∼64.64
SS 9.79±0.08 −11.29∼22.59 −2.07±0.07 −22.78∼10.51
SP 18.75±0.14 −12.88∼45.76 7.53±0.15 −19.98∼36.93
TSW 6.39±0.07 −9.00∼21.94 −2.66±0.09 −23.22∼16.71
OC 3.95±0.02 0.06∼7.23 0.63±0.02 −5.02∼3.88

[TableWrap ID: pone-0103165-t005] doi: 10.1371/journal.pone.0103165.t005.
Table 5  Genetic parameters of heritability and combining ability.
Traits VG (%) VS (%) Vgf (%) Vgm (%) Vgfm (%) h2b (%) h2n (%)
SY 25.71 74.30 10.32 13.70 75.98 68.77 18.61
SS 68.56 31.44 42.96 26.47 30.58 89.67 61.66
SP 66.13 33.87 29.97 39.26 30.78 75.12 40.06
TSW 80.47 19.53 69.52 11.30 19.18 93.05 74.88
OC 70.39 29.61 35.80 34.83 29.37 68.27 48.18

VG: variance of general combining ability (GCA); VS: variance of specific combining ability (SCA); Vgf: contribution ratio of the female GCA variance to the total variance; Vgm: contribution ratio of the male GCA variance to the total variance; Vgfm: contribution ratio of the SCA variance to the total variance; h2b: broad sense heritability; h2n: narrow sense heritability.


[TableWrap ID: pone-0103165-t006] doi: 10.1371/journal.pone.0103165.t006.
Table 6  Correlation coefficients between GD, heterosis levels, and combining abilities of each trait.
Trait GD SCA MPH BPH
MPH BPH SCA MPH BPH GCAf GCAm GCAf GCAm
SY 0.05 0.06 0.19* 0.43** 0.49** 0.36** 0.19* 0.35** 0.27**
SS 0.13 0.08 0.43** 0.34** 0.31** 0.16 −0.09 0.15 −0.07
SP −0.11 −0.13 0.04 0.55** 0.53** 0.37** 0.18* 0.34** 0.27**
TSW −0.12 −0.32** −0.35** 0.54** 0.70** 0.34** 0.05 0.59** 0.11
OC −0.01 0.08 −0.08 0.53** 0.54** 0.05 −0.04 −0.17* −0.12

GD: genetic distance; GCAf: GCA of female parents; GCAm: GCA of male parents.

* Significant at p = 0.05; ** significant at p = 0.01.


[TableWrap ID: pone-0103165-t007] doi: 10.1371/journal.pone.0103165.t007.
Table 7  Correlation coefficients of each trait between hybrid and its parental lines.
Trait Hybrid and female parent Hybrid and male parent Hybrids and two parents
SY 0.69** 0.65** 0.76**
SS 0.53** 0.62** 0.74**
SP 0.60** 0.77** 0.75**
TSW 0.76** 0.50** 0.81**
OC 0.55** 0.65** 0.77**

** Significant at p = 0.01.


[TableWrap ID: pone-0103165-t008] doi: 10.1371/journal.pone.0103165.t008.
Table 8  Correlation coefficients between heterosis level and average performance of parents.
Heterosis level Traits
SY SS SP TSW OC
MPH −0.43** −0.52** −0.35** −0.16 −0.46**
BPH −0.35** −0.30** −0.32** 0.09 −0.42**

** Significant at p = 0.01; n = 36.


[TableWrap ID: pone-0103165-t009] doi: 10.1371/journal.pone.0103165.t009.
Table 9  Phenotypic correlations between traits in hybrids and parents.
Trait SY SS SP TSW OC
SY −0.12 0.75** 0.11 −0.18*
SS 0.16 −0.41** −0.60** 0.36**
SP 0.73** −0.14 −0.03 −0.44**
TSW 0.07 −0.66** −0.08 0.06
OC −0.00 0.47** −0.24 −0.06

The numbers in the upper or lower triangle are correlation coefficients between traits in hybrids, or between traits in parental lines.

* Significant at p = 0.05; ** significant at p = 0.01; n = 144.



Article Categories:
  • Research Article
Article Categories:
  • Biology and Life Sciences
    • Agriculture
      • Agronomy
        • Plant Breeding
    • Genetics
      • Phenotypes
        • Quantitative Traits
      • Plant Genetics
        • Crop Genetics
    • Organisms
      • Plants
        • Flowering Plants
          • Rapeseed
    • Plant Science
      • Plant Genetics
        • Crop Genetics


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