Open Access

Genetic effects and genotype × environment interactions govern seed oil content in Brassica napus L.

BMC GeneticsBMC series – open, inclusive and trusted201718:1

Received: 4 June 2016

Accepted: 20 December 2016

Published: 5 January 2017



As seed oil content (OC) is a key measure of rapeseed quality, better understanding the genetic basis of OC would greatly facilitate the breeding of high-oil cultivars. Here, we investigated the components of genetic effects and genotype × environment interactions (GE) that govern OC using a full diallel set of nine parents, which represented a wide range of the Chinese rapeseed cultivars and pure lines with various OCs.


Our results from an embryo-cytoplasm-maternal (GoCGm) model for diploid seeds showed that OC was primarily determined by genetic effects (VG) and GE (VGE), which together accounted for 86.19% of the phenotypic variance (VP). GE (VGE) alone accounted for 51.68% of the total genetic variance, indicating the importance of GE interaction for OC. Furthermore, maternal variance explained 75.03% of the total genetic variance, embryo and cytoplasmic effects accounted for 21.02% and 3.95%, respectively. We also found that the OC of F1 seeds was mainly determined by maternal effect and slightly affected by xenia. Thus, the OC of rapeseed was simultaneously affected by various genetic components, including maternal, embryo, cytoplasm, xenia and GE effects. In addition, general combining ability (GCA), specific combining ability (SCA), and maternal variance had significant influence on OC. The lines H2 and H1 were good general combiners, suggesting that they would be the best parental candidates for OC improvement. Crosses H3 × M2 and H1 × M3 exhibited significant SCA, suggesting their potentials in hybrid development.


Our study thoroughly investigated and reliably quantified various genetic factors associated with OC of rapeseed by using a full diallel and backcross and reciprocal backcross. This findings lay a foundation for future genetic studies of OC and provide guidance for breeding of high-oil rapeseed cultivars.


Seed oil content Diallel Genetic effects Brassica napus


The seed oil content (OC) is a key measure of rapeseed quality and is also a complicated quantitative trait easily affected by the environment and difficult to investigate [13]. Previous studies have demonstrated that the OC of rapeseed is mainly controlled by genotype and genotype × environment interactions (GE) [46]; in addition, it is governed by multiple genes mainly through additive effect, and thus can be altered through breeding and selection [710].

A previous study on summer rapeseed has suggested that OC might be primarily controlled by maternal factors or embryo genotype or xenia [4]. The strong influence of maternal effect on the OC of F1 seeds is usually accompanied by weak xenia [1113]. For maternal effect, several forms have been proposed, including the maternal inheritance of plastid, endosperm, seed coat, and maternal provision of nutrients [14, 15]. Seed lipid synthesis is independent of the leaf photosynthesis and the phloem transport of photosynthate [16], but mainly requires the supply of photosynthate from the silique wall [6, 12]. Photosynthesis of the silique wall, sugar transport in the seed coat, and the expression of fatty acid synthesis-related genes in the embryo can significantly influence the OC [17, 18]. In addition, the storage substance in seed is determined not only by the availability of assimilates (source strength), but also by the intrinsic traits of the seed (sink strength), which are controlled by the embryo genotype [19]. Therefore, variation in OC of rapeseed may be governed by multiple genetic components, including embryo, cytoplasmic, xenia, maternal, and GE effects [1113, 20, 21].

Xenia, which represents the effect of pollen on the development and characters of seed, can be demonstrated by analyzing the differences between seeds fertilized using different pollen sources from the same plant [22, 23]. The maternal effect on OC can be investigated using reciprocal crosses [24, 25], and ancillary data from backcross progeny can be used to separate cytoplasmic effect from maternal effect [26, 27]. A significant difference between reciprocal backcrosses is strongly indicative of cytoplasmic effect. Cytoplasmic effect and maternal effect may also be distinguished by comparing reciprocal F2 seeds [28]. In contrast, a difference between reciprocal F1 hybrids that does not exist between reciprocal F2 hybrids would indicate that OC is determined by maternal effect without cytoplasmic effect [11].

Diallel mating designs have been frequently used to investigate the genetic effects of parents or to determine which cultivars are the best combiners for favorable alleles in hybrids. Diallel analysis provides information on the genetic behaviors of these attributes in the F1 generation [29]. The four methods of Griffing have usually been used to obtain genetic information on the basis of data from only one year or one location [30]; however, it has been suggested that considering multiple types of environment data could provide more reliable genetic information on the material tested [31]. The variance of general combining ability (GCA) incorporates additive epistasis, whereas that of specific combining ability (SCA) incorporates dominance epistasis [30, 32]. The observation of high additive effect for a specific trait indicates higher heritability and less environmental influence and will facilitate the selection of this trait [33]. Additive effect efficiently responds to selection, whereas non-additive effects, such as dominance and epistatic components, increase hybrid vigor in the cross combinations of cultivars. These facts suggest that the evaluation of GCA of a specific trait can guide the breeders to select the parents that can be used in breeding program for that trait, while SCA indicates the heterosis of a specific trait, and significant SCA of a cross suggests the presence of non-additive gene action [34].

In the present study, we investigated whether OC is determined by embryo, maternal, cytoplasmic, xenia or GE effects, or a combination of these factors. To this end, we estimated the components of different genetic systems and their corresponding GE. In addition, we investigated the roles of GCA, SCA, and reciprocal effect in the inheritance of OC. An improved understanding of the genetic components of OC and the combining abilities of inbred lines will help breeders to develop high-oil rapeseed cultivars and hybrids for particular geographic locations.


Materials and field experiments

The experiments were carried out from September of 2009 to May of 2012. Nine semi-winter rapeseed lines with differences in seed oil content (OC) were selected as parental lines from the Rapeseed Laboratory of Huazhong Agricultural University (Table 1). Three high-oil lines (HO; H1, H2, H3), three medium-oil lines (MO; M1, M2, M3), and three low-oil lines (LO; L1, L2, L3), were crossed in a 9 × 9 diallel mating scheme to produce 72 F1 hybrids (F1 seeds from maternal plants), including 36 crosses and 36 of their reciprocals in March of 2010. These 72 crosses were performed again in March of 2012, and these F1 seeds were only analyzed for maternal effect and xenia on the OC of rapeseed.
Table 1

Parents and their seed oil contents (%) in 2011 (Mean ± SE)








Pure line

High erucic acid low GSL

44.61 ± 0.55



Pure line

High erucic acid low GSL

47.17 ± 0.18



Pure line

Double Lowa

45.46 ± 1.28



Registered Cultivar

High erucic acid high GSL

38.74 ± 1.36



Registered Cultivar

High erucic acid high GSL

41.04 ± 0.51



Registered Cultivar

Double Low

40.85 ± 1.13



Registered Cultivar

Double Low

37.99 ± 0.55



Registered Cultivar

Double Low

34.86 ± 1.20



Registered Cultivar

Double Low

35.13 ± 0.48

GSL glucosinolate, SE standard error, % percentage

aDouble low means that the content of erucic acid and total glucosinolates in seeds are below 2% and 30 mmol/g seeds, respectively

A total of 81 genetic entries (72 F1 hybrids from maternal plants and 9 parents) obtained from the complete diallel cross of the nine parents in May of 2010, were directly sown in the field at Huazhong Agricultural University, Wuhan, China around September 27th of both 2010 and 2011. The parental and F1 seeds were planted in a randomized block design with three replications over two consecutive growing seasons, and each block contained two rows with 10 plants in each row at a space of 30 cm × 15 cm. The OC of self-pollinated parents and F2 generation (F2 seeds from F1 plants) plants was calculated as the mean value of 20–56 individually harvested plants in both 2011and 2012, and that of the open-pollinated F2 generation was calculated as the mean value of 13–50 individually harvested plants in 2011.

Environmental factors, such as temperature, light, and weather during seed development and difference in flowering time, could influence OC and the results of the study. Therefore, since F1 plants have the same developmental timing, backcross using an F1 plant as the maternal parent could be used to solve these problems [27]. HO (H2, H3) and LO (L1, L2) were selected for producing backcross (BC) and reciprocal backcross (RBC) generations. The four parents and their eight F1 hybrids produced in March of 2010 were directly sown in the field at Huazhong Agricultural University, Wuhan, China around September 27th of both 2010 and 2011. In the spring of both 2011 and 2012, a total of 32 BC and RBC combinations were produced, including eight BC1s, eight BC2s (with F1 plants as female parents), eight RBC1s, and eight RBC2s (with F1 plants as male parents), and each of the combinations was repeated three times and used to study the maternal, xenia and cytoplasmic effects on OC.

All plants were isolated by paper bags at the beginning of flowering to ensure self-pollination of parents and F2 seeds, and the bags were removed at the end of full flowering. All plants were harvested and threshed at early May in 2010, 2011 and 2012. The total OC was measured using the Foss NIR-Systems 5000 near-infrared reflectance spectroscope (NIR-Systems, Inc., Silver Spring, MD, USA) [35], with the parameters described by Gan et al. [36].

Statistical analysis

Data were analyzed using a general linear model (GLM) [37]. Based on the GLM, least-square means were used to compute the combining ability based on Griffing’s diallel analysis with Method 1 (full diallel set), Model 1 [30]. All variance analyses and combining ability (GCA, SCA, reciprocal) estimation were performed using the SAS codes published by Zhang and Kang [31]. On the basis of Cong [38] and Duan et al. [39], the method proposed by Wang et al. [11] was used to estimate the genetic components of maternal effect and xenia in rapeseed. The OC of F1 seeds was calculated as F1 = MP1 + XP2, where M was the value of maternal effect and X was the value of xenia (X = 1–M).

The partitions of embryo, maternal, cytoplasmic effects as well as the corresponding GE were estimated using the embryo-cytoplasm-maternal (GoCGm) model [40, 41] for diploid seeds in QGAStation1.0 ( The genetic variance components were estimated using the minimum norm quadratic unbiased estimation (MINQUE) (0/1) method [42], and the genetic effects of each parent were investigated using the adjusted unbiased prediction (AUP) method [43]. Standard errors of the estimated variance and predicted genetic effects were then analyzed using a Jackknife procedure [44], and t-tests were used to test for significant differences in the traits examined.


Phenotypic variation

We found that the self-pollinated seeds from nine parents, including HO (H1, H2, and H3), MO (M1, M2, and M3), and LO (L1, L2, and L3), exhibited significant differences in OC, and that the differences between the parents with the highest and lowest OC in each year was about 12.00% (Tables 1, 2). The OC of the 72 F1 hybrids was strongly influenced by the maternal parent. In 2012, the mean OC of the eight F1 lines with H1 as the female parent was 42.01%, which was comparable to that of H1 (42.79%), whereas that of the eight F1 lines with H1 as the male parent was 38.04% (Table 2). Similarly, the mean OC of the eight F1 lines with L3 as the female parent was 32.44%, which was comparable to that of L3 (29.63%), and that of the eight F1 lines with L3 as the male parent was 37.10%, which was much higher than that of L3. Similar trends were observed in the other sets of crosses in both 2010 and 2012. Thus, the OC of F1 hybrids was similar to that of maternal parent, even with different male parents.
Table 2

Oil contents (%) of the complete diallel crosses F1 seeds harvested in 2010 and 2012 (Mean ± SE)






F1(F)   a

F1(M)    b


F1(F)   a

F1(M)    b


49.21 ± 1.42

48.35 ± 1.54

40.00 ± 4.35

42.79 ± 0.40

42.01 ± 2.16

38.04 ± 6.09


49.26 ± 1.62

49.43 ± 1.24

42.08 ± 3.63

45.80 ± 1.83

44.65 ± 2.06

40.19 ± 3.50


42.20 ± 2.20

39.42 ± 3.69

40.74 ± 5.64

40.99 ± 1.36

42.05 ± 1.65

37.08 ± 5.12


40.66 ± 0.45

39.87 ± 2.03

41.50 ± 5.78

37.37 ± 1.93

38.17 ± 2.19

39.11 ± 5.22


40.03 ± 0.45

38.50 ± 1.92

42.11 ± 5.69

39.43 ± 1.60

39.82 ± 1.76

39.49 ± 4.89


36.81 ± 0.43

38.70 ± 1.95

39.76 ± 4.41

37.00 ± 2.50

38.40 ± 1.66

38.14 ± 5.32


37.84 ± 2.65

39.00 ± 2.63

40.26 ± 4.80

35.27 ± 3.53

36.16 ± 3.50

37.27 ± 6.15


35.73 ± 1.67

35.75 ± 2.48

40.66 ± 5.39

27.26 ± 3.70

30.55 ± 4.18

39.48 ± 4.44


36.50 ± 0.67

38.85 ± 1.28

39.54 ± 5.27

29.63 ± 0.84

32.44 ± 3.70

37.10 ± 4.91

% percentage, SE standard error

aMean value of the F1 derived from the line as female crossed with other 8 lines

bMean value of the F1 derived from the line as male crossed with other 8 lines

The results in Table 3 showed that the mean OC of open-pollinated F2 seeds was about 2% higher than that of self-pollinated F2 seeds, and the mean values for most of the F2 seeds from reciprocal crosses were more or less similar, despite a small amount of inbreeding depression. In addition, differences between the F1 reciprocal crosses disappeared in the F2 generation for most combinations, thus demonstrating a maternal effect and little or no cytoplasmic effect (Tables 2, 3). The analysis of backcrosses confirmed the predominant influence of maternal parent on OC, even with the elimination of differences in flowering time (Fig. 1). Furthermore, the mean OCs of (H2/L1)H2 and (H2/L1)L1 were similar (Fig. 1a, e), and it was the same case for (L1/H2)H2 and (L1/H2)L1 (Fig. 1a, e). However, when H2 was used as the maternal parent to cross with four F1 hybrid lines (L1/H2, H2/L1, H2/L2, L2/H2), the various backcrosses exhibited different OCs, indicating the presence of a slight xenia (Fig. 1a, b, e, f). Similar trends were observed in other three sets of backcrosses, confirming that maternal effect was the main determinant of OC and that the influence of pollen source was minor (Fig. 1).
Table 3

Oil contents (%) of F2 seeds harvested from F1 plants grown in the field in 2011 (Mean ± SE)








H1 × H2

44.24 ± 1.69(32)a

45.71 ± 2.17(40)

46.31 ± 1.61(24)

47.81 ± 2.00(34)

H1 × H3

44.68 ± 2.36(37)

43.98 ± 2.13(47)

46.76 ± 1.66(28)

45.06 ± 2.36(33)

H1 × M1

44.12 ± 2.48(45)

42.61 ± 2.18(50)

45.35 ± 2.34(32)

44.58 ± 2.07(45)

H1 × M2

44.36 ± 1.73(48)

44.08 ± 1.85(48)

45.99 ± 1.29(35)

45.73 ± 1.44(41)

H1 × M3

45.41 ± 2.69(44)

43.57 ± 3.44(32)

46.84 ± 2.46(30)

45.63 ± 1.93(31)

H1 × L1

43.74 ± 2.33(41)

44.34 ± 2.81(54)

45.22 ± 1.88(25)

45.79 ± 2.02(35)

H1 × L2

43.92 ± 2.99(48)

43.15 ± 2.10(43)

45.35 ± 2.65(24)

44.69 ± 2.05(23)

H1 × L3

42.23 ± 2.12(38)

42.44 ± 2.16(51)

45.53 ± 1.71(25)

45.01 ± 1.93(29)

H2 × H3

46.89 ± 1.53(48)

46.61 ± 1.66(54)

49.25 ± 1.47(41)

48.23 ± 1.80(49)

H2 × M1

43.58 ± 1.71(51)

43.29 ± 1.93(48)

45.94 ± 1.39(41)

45.55 ± 1.50(44)

H2 × M2

46.92 ± 1.45(50)

46.82 ± 1.89(46)

48.84 ± 1.27(40)

48.30 ± 2.02(36)

H2 × M3

42.08 ± 2.36(47)

41.96 ± 2.29(42)

44.48 ± 1.56(31)

44.57 ± 1.37(32)

H2 × L1

42.73 ± 2.21(47)

43.09 ± 2.68(52)

45.37 ± 1.15(36)

45.03 ± 2.01(36)

H2 × L2

44.26 ± 1.82(49)

44.52 ± 2.20(56)

46.35 ± 1.57(28)

46.31 ± 1.99(33)

H2 × L3

40.76 ± 2.64(42)

42.53 ± 2.09(49)

42.83 ± 2.17(27)

44.18 ± 1.97(35)

H3 × M1

40.27 ± 1.70(52)

41.14 ± 2.30(38)

42.59 ± 1.53(43)

43.16 ± 1.61(31)

H3 × M2

45.97 ± 1.81(51)

46.24 ± 1.76(45)

47.67 ± 1.63(46)

48.50 ± 1.33(36)

H3 × M3

39.98 ± 2.32(49)

42.17 ± 1.77(31)

42.52 ± 2.54(33)

44.54 ± 0.98(21)

H3 × L1

40.47 ± 1.63(55)

41.22 ± 2.01(48)

42.00 ± 1.60(43)

43.26 ± 1.78(34)

H3 × L2

41.58 ± 1.57(42)

41.48 ± 1.83(29)

43.08 ± 1.56(35)

44.22 ± 2.01(18)

H3 × L3

39.12 ± 1.93(48)

39.38 ± 2.65(49)

41.69 ± 1.87(38)

41.68 ± 2.42(36)

M1 × M2

40.99 ± 2.27(41)

41.48 ± 1.46(54)

42.41 ± 2.14(34)

43.47 ± 1.10(48)

M1 × M3

40.62 ± 2.17(55)

40.90 ± 2.00(47)

42.66 ± 1.74(50)

43.01 ± 1.44(38)

M1 × L1

38.75 ± 2.83(23)

41.74 ± 1.59(36)

39.81 ± 1.44(13)

43.35 ± 1.67(30)

M1 × L2

40.48 ± 1.96(37)

39.19 ± 2.60(51)

42.85 ± 1.32(28)

41.40 ± 2.60(36)

M1 × L3

37.86 ± 1.99(51)

38.16 ± 2.36(48)

40.15 ± 1.60(40)

41.36 ± 1.64(42)

M2 × M3

41.24 ± 1.49(50)

41.66 ± 1.25(46)

43.02 ± 1.37(41)

43.29 ± 1.26(47)

M2 × L1

42.02 ± 1.37(53)

41.47 ± 1.65(34)

43.23 ± 1.69(43)

43.18 ± 1.19(30)

M2 × L2

40.03 ± 1.73(53)

39.58 ± 3.19(41)

41.59 ± 1.47(30)

42.06 ± 2.79(34)

M2 × L3

38.71 ± 2.04(44)

39.33 ± 1.64(53)

40.52 ± 1.74(33)

41.54 ± 1.20(36)

M3 × L1

39.59 ± 2.72(46)

39.76 ± 3.08(48)

41.03 ± 2.21(36)

41.67 ± 1.85(38)

M3 × L2

39.09 ± 2.34(44)

39.54 ± 2.06(33)

41.18 ± 2.12(26)

41.88 ± 1.08(14)

M3 × L3

37.61 ± 2.44(46)

37.11 ± 2.51(47)

40.96 ± 1.54(39)

40.36 ± 2.15(39)

L1 × L2

38.90 ± 2.15(50)

37.88 ± 2.43(48)

39.45 ± 2.25(33)

40.08 ± 1.75(32)

L1 × L3

37.85 ± 1.81(47)

37.58 ± 2.28(55)

40.52 ± 1.36(29)

40.31 ± 1.58(34)

L2 × L3

37.58 ± 2.11(45)

36.72 ± 2.02(47)

40.05 ± 2.62(25)

39.74 ± 1.77(30)

% percentage, SE standard error

aplant number of F1 plants

Fig. 1

Average values of seed oil content (%) in 4 parents and 10 reciprocal generations within 6 cross-combinations. a, e The mean seed oil contents of H2, L1 and reciprocal F1, BC1 and BC2 combinations were tested in 2011 and 2012, respectively. b, f The mean seed oil contents of H2, L2 and reciprocal F1, BC1 and BC2 combinations were tested in 2011 and 2012, respectively. c, g The mean seed oil contents of H3, L1 and reciprocal F1, BC1 and BC2 combinations were tested in 2011 and 2012, respectively. d, h The mean seed oil contents of H3, L2 and reciprocal F1, BC1 and BC2 combinations were tested in 2011 and 2012, respectively

Variance analysis of means and gene action

A combined analysis of variance also indicated significant differences in OC among genotypes (Table 4). The significant mean squares of GE for OC indicated that the magnitude of the trait in different genotypes varied over the two years, and the differences between plants in different blocks were also significant, indicating that OC was easily affected by the environment. GCA and SCA also significantly contributed to the OC variation over the years, indicating the importance of both additive and non-additive effects on OC (Table 4). Further partitioning of reciprocal sum squares indicated that maternal effect was significant, whereas non-maternal effect was not, suggesting that OC was not under strict nuclear control and could also be influenced by cytoplasm. The GCA × Environment showed significant effect on OC, suggesting that the additive variances were influenced by the environment. However, the SCA × Environment did not show any effect. Therefore, the effect of environment on non-additive components of genetic variance was not significant.
Table 4

9 × 9 diallel analysis of variance for the oil content of rapeseed (Griffing’s Method 1)



Sum of squares

Mean squares


P > F

Environment (E)












Genotype (G)




































G × E
























M × E






NM × E











DF degree of freedom, GCA general combining ability, M maternal, NM non-maternal component, REC reciprocal

SCA specific combining ability

**indicate significance at the 0.01 level

Combining ability

The GCA was significant for all parents even though some parents had positive values and other had negative values, whereas no parental line exhibited significant maternal effect (Table 5). H2 (3.21**) and H1 (2.87**) had the highest GCA for OC, whereas L3 (−3.06**) and L2 (−2.06**) were negative combiners with reduced OC in F1. The SCA in several crosses was significant, and reciprocal effect was only significant in two crosses. Lines H3 and M2 showed significantly positive GCA, whereas M1, M3 and L1 exhibited significantly negative GCA. Crosses H1 × M3, H1 × L1, H1 × L3, H2 × H3, H2 × M2 and H3 × M2 exhibited significantly positive SCA and were the best specific combiners for improvement of OC (Table 5), The negative SCA of H1 × H2, H1 × H3, H1 × M2, H3 × M1 and L2 × L3 observed with lower OC suggested that they were poor parental combinations for breeding. The reciprocal effect was estimated to be not significant in most reciprocal crosses, except for the reciprocals of L3 × M3 and L1 × H3. The cross L3 × M3 showed significant positive reciprocal effect indicating a negative cytoplasmic effect from the maternal parent L3. The negative reciprocal effect of L1 × H3 indicated a positive cytoplasmic effect from maternal parent L1. Therefore, L3 and L1 should be respectively exploited as male and maternal parent in crosses for OC improvement.
Table 5

Estimates of GCA, SCA, reciprocal effect and maternal effect (Griffing’s Method 1)

























































































































GCA general combining ability, SCA specific combining ability

a,bSignificantly different from zero at the 0.05 and 0.01 probability levels, respectively

Maternal effect and xenia

Based on the 54 F1 hybrids (HO × MO, HO × LO, MO × HO, MO × LO, LO × HO, LO × MO) harvested in 2010 and 2012, the mean estimated value of maternal effect was 0.84 in 2010 and 0.89 in 2012, and that of xenia was 0.16 in 2010 and 0.11 in 2012 (Table 6). On average across the two years, maternal effect accounted for 0.87 of the observed variation, whereas xenia accounted for only 0.13 of it, confirming a very strong maternal effect on the OC of F1 seeds and a weak effect of xenia. Some crosses (H1 × MO and M3 × LO) exhibited values of maternal effect around 1 consistently across the two years, suggesting 100% maternal influence. Some crosses (H3 × LO and M1 × LO) showed maternal effect and xenia varying markedly between two years and also had large standard errors (SE), suggesting that these crosses had relatively weak maternal effects.
Table 6

Estimated values of maternal effect and xenia on F1 hybrid oil contents in 2010 and 2012






Maternal (M)

Xenia (X)

Maternal (M)

Xenia (X)


H1 × LO

0.81 ± 0.11

0.09 ± 0.11

0.86 ± 0.18

0.14 ± 0.18


H1 × MO

1.03 ± 0.01

−0.03 ± 0.01

1.12 ± 0.19

−0.12 ± 0.19


H2 × LO

0.96 ± 0.10

0.04 ± 0.10

1.04 ± 0.08

0.09 ± 0.14


H2 × MO

1.17 ± 0.02a

−0.17 ± 0.02

0.95 ± 0.27

0.05 ± 0.27


H3 × LO

0.42 ± 0.16

0.58 ± 0.16

0.82 ± 0.17

0.18 ± 0.17


H3 × MO

0.84 ± 0.93

0.16 ± 0.93

1.06 ± 0.27

−0.06 ± 0.27


M1 × HO

0.81 ± 0.20

0.19 ± 0.20

0.82 ± 0.22

0.18 ± 0.22


M1 × LO

0.59 ± 0.69

0.41 ± 0.69

1.09 ± 0.54

−0.09 ± 0.54


M2 × HO

1.58 ± 0.86

−0.58 ± 0.86

0.89 ± 0.19

0.11 ± 0.19


M2 × LO

0.70 ± 0.64

0.30 ± 0.64

1.02 ± 0.10

−0.02 ± 0.10


M3 × HO

0.59 ± 0.39

0.41 ± 0.39

0.74 ± 0.26

0.26 ± 0.26


M3 × LO

1.16 ± 3.12

−0.16 ± 3.12

1.17 ± 0.27

−0.17 ± 0.27


L1 × HO

0.80 ± 0.37

0.20 ± 0.37

0.89 ± 0.22

0.11 ± 0.22


L1 × MO

0.66 ± 1.02

0.34 ± 1.02

0.76 ± 0.75

0.24 ± 0.75


L2 × HO

0.74 ± 0.06

0.26 ± 0.06

0.75 ± 0.12

0.25 ± 0.12


L2 × MO

1.24 ± 0.33

−0.24 ± 0.33

0.74 ± 0.14

0.26 ± 0.14


L3 × HO

0.70 ± 0.04

0.30 ± 0.04

0.89 ± 0.39

0.11 ± 0.39


L3 × MO

0.35 ± 0.10

0.65 ± 0.10

0.49 ± 0.42

0.51 ± 0.42







aThe maternal effect >1 was primarily due to the existence of ultra-high or ultra-low oil content parental individuals

Cytoplasmic effect

Analyses of backcrosses revealed the minor or negligible influence of cytoplasmic effect, although the backcrosses also displayed some variations between 2011 and 2012 (Fig. 1), which demonstrated that environment might have some influence on cytoplasmic effect. In 2011, for example, the average OC of (H3/L2)H3 was higher than that of (L2/H3)H3, and that of (H3/L2)L2 was higher than that of (L2/H3)L2 as well. However, in 2012, the mean OC of (H3/L2)L2 was higher than that of (L2/H3)L2, which might be owing to positive cytoplasmic effect, whereas that of (H3/L2)H3 was lower than that of (L2/H3)H3, which might be due to negative cytoplasmic effect. The mean OC of (H2/L2)L2 was higher than that of (L2/H2)L2, and that of (H2/L2)H2 was higher than that of (L2/H2)H2, which could be attributed to the positive cytoplasmic effect (Fig. 1b, f). The average OC of (H2/L1)H2 was higher than that of (L1/H2)H2, whereas that of (H2/L1)L1 was similar to that of (L1/H2)L1 in both 2011 and 2012. In contrast, the mean OCs of (H3/L1)H3 and (L1/H3)H3 were comparable, and it was the same case for (H3/L1)L1 and (L1/H3)L1, which again suggested the lack of cytoplasmic effect.

Components of total genetic variance

The results from GoCGm model showed that 13.81% of the phenotypic variance (VP) in OC could be attributed to environmental variations and experimental errors, whereas the rest (86.19%) was attributable to genetic (VG) and GE (VGE) components (Table 7). Genetic and GE variance components respectively accounted for 48.32% and 51.68% of the total genetic variance (VG + VGE). Embryo additive (VA), embryo additive interaction (VAE), maternal additive (VAm) and maternal dominant interaction (VDmE) variance components were significant, whereas embryo dominant interaction (VDE), cytoplasm interaction (VCE), maternal additive (VAmE), and maternal dominant (VDm) variance components were not. Maternal variances (VAm + VDm + VAmE + VDmE) explained 75.03% of the total genetic variance, whereas embryo and cytoplasmic effects accounted for only 21.02% and 3.95% of it, respectively. Overall, these results indicated that OC was predominantly influenced by maternal effect, followed by embryo and cytoplasmic effects.
Table 7

Estimation of genetic variance components of the seed oil content in rapeseed






Variance (%)





V G + V GE /V P






V e /V P






V GE /V G + V GE


V Am




V G /V G + V GE


V Dm




V A + V D + V AE + V DE /V G + V GE



V e


V C + V CE /V G + V GE



V Am + V Dm + V AmE + V DmE /V G + V GE


aindicates significance at the 0.01 level, % percentage

Estimation of genetic components of parents

H2 showed the highest additive effect, whereas L3 displayed the lowest additive effect, and we also found that H1, H2, H3, M1 and L1 exhibited significant positive maternal additive effect, whereas other parents showed significant negative maternal additive effect (Table 8). L2 exhibited the lowest maternal additive effect, whereas H1 showed the highest maternal additive effect. Cytoplasmic effects were positive in H1, H2, M1, M3 and L1, whereas the cytoplasmic effects of the remaining four lines were insignificantly or significantly negative. According to our estimated values, H1 exhibited the highest cytoplasmic effect (1.79 ± 0.86) among the nine parents, indicating the high probability of generating high-oil rapeseed with this line being used as the maternal parent. In addition, H2, M1, M2, and L2 displayed negative homozygous dominance, whereas the remaining five lines exhibited positive homozygous dominance (Table 8). L3 showed the highest homozygous dominance effect, indicating that it is more likely produce high heterosis. Moreover, all of the genetic effects of H1 were positive, suggesting that it might be an ideal maternal parent for breeding high-oil rapeseed.
Table 8

Estimation of genetic effects for seed oil content in rapeseed


Cytoplasm effect

Additive effect

Maternal Additive



1.79 ± 0.86a

0.80 ± 0.06b

2.88 ± 0.13b

3.50 ± 1.00b


1.08 ± 0.24b

1.68 ± 0.09b

1.32 ± 0.05b

−2.18 ± 0.62b


−0.09 ± 0.02b

−0.37 ± 0.02b

2.25 ± 0.09b

0.45 ± 0.04b


0.16 ± 0.03b

0.75 ± 0.03b

0.94 ± 0.05b

−4.94 ± 2.24a


−0.39 ± 0.03b

0.68 ± 0.05b

−0.09 ± 0.00b

−0.69 ± 0.45


0.10 ± 0.03b

0.02 ± 0.01b

−1.52 ± 0.07b

2.39 ± 0.28b


0.49 ± 0.24a

−1.09 ± 0.03b

0.16 ± 0.01b

0.75 ± 0.04b


−1.19 ± 0.42b

0.17 ± 0.06b

−3.48 ± 0.17b

−0.50 ± 0.07b


−1.96 ± 1.88

−1.14 ± 0.03b

−2.46 ± 0.14b

4.33 ± 0.28b

asignificant at 0.05, bsignificant at 0.01


Investigation of the influence of different genetic systems can facilitate a better understanding of the nature of gene interactions that could influence OC. Our study demonstrates that the variation of OC is mainly determined by genetic and GE components (Table 7), though the environment also has a significant influence [7, 8]. However, the influence of GE should not be neglected, since GE accounted for 51.68% of the total genetic variance. Significant interactions have been observed between male or female and the environment [13]. GE is a critical factor for developing varieties with wide geographical adaptability and should be taken into account in genetic model and breeding process. Data from the genetic model clearly demonstrated that OC was mainly controlled by the maternal parent, with the maternal effect accounting for 75% of the genetic variance. Embryo effect accounted for 21% of the genetic variance and cytoplasmic effect was detectable only at a very low level (Table 7). The present study confirms the earlier findings that the OC of F1 seeds is mainly controlled by maternal effect, and xenia is weak [11, 13, 45]. Analysis of reciprocal backcrosses demonstrates that maternal, xenia, and cytoplasmic effect can all influence OC (Fig. 1). Therefore, our genetic analysis confirms that OC is determined by maternal, embryo, cytoplasm, xenia and GE effects.

Previous studies have shown that the photosynthesis in silique wall makes a crucial contribution to OC [6, 12, 16, 17], providing an explanation for the influence of maternal parent on OC. Therefore, the selection for high-oil rapeseed would be more effective based on the photosynthetic activity of silique wall than based on the performance of maternal parent. It should be noted that xenia has a direct genetic effect on OC in many crops [11, 12, 46, 47], and is applied not only in genetic and physiological research but also in crop breeding and production. Similar to the case of corn and soybean, controlling the pollen source and considering xenia are required in both breeding programs and investigation of OC in rapeseed. Therefore, decision on parents and cross direction are very important for hybrid rapeseed breeding and production.

The OC of self-pollinated seeds was lower than that of open-pollinated seeds harvested from the same plant in the F2 generation (Table 3). This result is similar to the finding of Hom et al. [48]. Earlier studies reported that the OC of F1 seeds was significantly lower than that of self-pollinated seeds when a HO female was crossed with a LO male, but it was significantly higher than that of self-pollinated seeds when a LO female was crossed with a HO male [11, 12]. Similar results were obtained for soybean [49]. Although xenia has a direct genetic effect on OC of rapeseed [11, 12, 45], different pollens may not actually be responsible for the difference in OC between self-pollinated and open-pollinated seeds. During seed development, self-pollinated seeds were isolated using paper bags, whereas open-pollinated seeds were not. Thus, the difference in microclimate may have influenced the OC. Concurrently elevated CO2 and temperature could reduce seed biomass by half and further reduce losses in fatty acids and OC [50]. Seeds grown in high-light environments tend to have higher OC [51]. Hua et al. [12] suggested that local and tissue-specific photosynthetic activity in the silique wall were the main determinant for OC, and factors of weather and temperature could also influence photosynthesis of the silique wall, thereby affecting OC. Thus, the influence of microclimate on the photosynthesis of silique wall might explain the lower OC of self-pollinated seeds.

Our analysis of combining ability indicated the presence of both additive and non-additive gene actions in the parental lines (Table 4). Additive effect is equivalent to GCA, parental lines with high GCA for a specific trait may be better candidates as parental lines [30, 32, 34, 52]. Lines that had positive additive and maternal additive effects, such as H1, H2 and M1, are desirable general combiners that can be used for OC improvement. Cytoplasmic genes can persist through generations and are also expressed as additive effect [52]. Therefore, lines with positive cytoplasmic effect, such as H1, H2 and L1, could be used as maternal parents. It is evident that H1 and H2 are good combiners and that the genotypes might be the best candidates as maternal parents for improvement of OC. Hybrids in both pol and mur cytoplasmic male sterility systems exhibited significantly lower OC (by 1.3% and 1.4%, respectively) than identical hybrids constructed in the cytoplasm (nap) common in rapeseed [53, 54]. Line H1, which had positive additive, maternal additive, homozygous maternal dominance, and cytoplasmic effects, would be a more effective parent for high-oil rapeseed breeding. Crosses such as H3 × M2 and H1 × M3, which exhibited significant SCA, could be used in the development of hybrid varieties.


Based on analyses of a 9 × 9 full diallel scheme and selected backcross and reciprocal backcross, we concluded that the OC is simultaneously controlled by genetic components of maternal, embryo, xenia, cytoplasmic, and GE effects in rapeseed. Maternal effect is the most important factor, accounting for 75% of the genetic variance, followed by embryo effect, which accounts for 21% of the genetic variance. Therefore, selection of maternal parents is paramount in the genetic improvement of OC in rapeseed. Together with previous studies, additional information regarding the role of genetic components in determining OC could help breeder to better manipulate the OC of rapeseed.



Adjusted unbiased prediction




General combining ability


Genotype × environment interactions


High-oil lines


Low-oil lines


Minimum norm quadratic unbiased estimation


Medium-oil lines


Near infrared reflectance spectroscopy


Seed oil content


Reciprocal backcross


Reciprocal effect


Specific combining ability


Standard error



We are grateful to J Gao, HM Wang, and YY Pu for help in data analysis and suggestions. The authors are grateful to Prof. Jun Zhu from Zhejiang University for providing the analysis software. We also shall thank Prof. Zuoxiong Liu for editing the English language of the manuscript.


This work was supported by the National Key Research and Development Program of China (No.2016YFD0101300), and the Program for Modern Agricultural Industrial Technology System of China (grant no. nycytx-00501).

Availability of data and materials

All relevant data are available within the manuscript.

Authors’ contributions

YLG mainly carried out the experiments and analyzed the data. JXS and PS conceived and supervised the study. JTZ, JXT, TDF and CZM participated in its design. NW participated in field experimentation. YLG and PS wrote the manuscript. YB and JW helped to revise the manuscript. All the authors discussed the results and contributed to the manuscript. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Not applicable.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University
Center for Plant Genetics and Breeding, School of Plant Biology, the University of Western Australia (M080)
National Research Council Canada


  1. Boem FHG, Lavado RS, Porcelli CA. Note on the effects of winter and spring waterlogging on growth, chemical composition and yield of rapeseed. Field Crops Res. 1996;47(2):175–9.View ArticleGoogle Scholar
  2. Jensen CR, Mogensen VO, Mortensen G, Fieldsend JK, Milford GFJ, Andersen MN, Thage JH. Seed glucosinolate, oil and protein contents of field-grown rape (Brassica napus L.) affected by soil drying and evaporative demand. Field Crops Res. 1996;47(2):93–105.Google Scholar
  3. Si P, Mailer RJ, Galwey N, Turner DW. Influence of genotype and environment on oil and protein concentrations of canola (Brassica napus L.) grown across southern Australia. Crop Pasture Sci. 2003;54(4):397–407.Google Scholar
  4. Grami B, Stefansson BR, Baker RJ. Genetics of protein and oil content in summer rape: heritability, number of effective factors, and correlations. Can J Plant Sci. 1977;57(3):937–43.View ArticleGoogle Scholar
  5. Brandle J, McVetty P. Effects of inbreeding and estimates of additive genetic variance within seven summer oilseed rape cultivars. Genome. 1989;32(1):115–9.View ArticleGoogle Scholar
  6. Baud S, Lepiniec L. Physiological and developmental regulation of seed oil production. Prog Lipid Res. 2010;49(3):235–49.PubMedView ArticleGoogle Scholar
  7. Pritchard FM, Eagles HA, Norton RM, Salisbury PA, Nicolas M. Environmental effects on seed composition of Victorian canola. Anim Prod Sci. 2000;40(5):679–85.View ArticleGoogle Scholar
  8. Zhao J, Becker HC, Zhang D, Zhang Y, Ecke W. Oil content in a European × Chinese rapeseed population. Crop Sci. 2005;45(1):51–9.Google Scholar
  9. Jiang C, Shi J, Li R, Long Y, Wang H, Li D, Zhao J, Meng J. Quantitative trait loci that control the oil content variation of rapeseed (Brassica napus L.). Theor Appl Genet. 2014;127(4):957–68.PubMedView ArticleGoogle Scholar
  10. Liu S, Fan C, Li J, Cai G, Yang Q, Wu J, Yi X, Zhang C, Zhou Y. A genome-wide association study reveals novel elite allelic variations in seed oil content of Brassica napus. Theor Appl Genet. 2016;129(6):1203–15.PubMedView ArticleGoogle Scholar
  11. Wang X, Liu G, Yang Q, Hua W, Liu J, Wang H. Genetic analysis on oil content in rapeseed (Brassica napus L.). Euphytica. 2010;173(1):17–24.Google Scholar
  12. Hua W, Li R, Zhan G, Liu J, Li J, Wang X, Liu G, Wang H. Maternal control of seed oil content in Brassica napus: the role of silique wall photosynthesis. Plant J. 2012;69(3):432–44.PubMedView ArticleGoogle Scholar
  13. Hom NH, Schierholt A, Möllers C, Becker HC. Pollen genotype effects on seed quality traits in winter oilseed rape. Crop Sci. 2015;55(2):493–500.View ArticleGoogle Scholar
  14. Donohue K. Completing the cycle: maternal effects as the missing link in plant life histories. Philos Trans R Soc Lond B Biol Sci. 2009;364(1520):1059–74.PubMedPubMed CentralView ArticleGoogle Scholar
  15. Roach DA, Wulff RD. Maternal effects in plants. Annu Rev Ecol S. 1987;18:209–35.View ArticleGoogle Scholar
  16. Tan H, Xie Q, Xiang X, Li J, Zheng S, Xu X, Guo H, Ye W. Dynamic metabolic profiles and tissu-specific source effects on the metabolome of developing seeds of Brassica napus. PLoS One. 2015;10(10):e0124794.PubMedPubMed CentralView ArticleGoogle Scholar
  17. Liu J, Hua W, Yang H, Guo T, Sun X, Wang X, Liu G, Wang H. Effects of specific organs on seed oil accumulation in Brassica napus L. Plant Sci. 2014;227:60–8.PubMedView ArticleGoogle Scholar
  18. Wang X, Long Y, Yin Y, Zhang C, Gan L, Liu L, Yu L, Meng J, Li M. New insights into the gentic networks affecting seed fatty acid concentrations in Brassica napus. BMC Plant Biol. 2015;15(1):1.View ArticleGoogle Scholar
  19. Gallardo K, Thompson R, Burstin J. Reserve accumulation in legume seeds. C R Biol. 2008;331(10):755–62.PubMedView ArticleGoogle Scholar
  20. Wu J, Shi C, Zhang H. Partitioning genetic effects due to embryo, cytoplasm and maternal parent for oil content in oilseed rape (Brassica napus L.). Genet Mol Biol. 2006;29(3):533–8.Google Scholar
  21. Weselake RJ, Taylor DC, Rahman MH, Shah S, Laroche A, Mcvetty PBE, Harwood JL. Increasing the flow of carbon into seed oil. Biotechnol Adv. 2009;27(6):866–78.PubMedView ArticleGoogle Scholar
  22. Pahlavani MH, Abolhasani K. Xenia effect on seed and embryo size in cotton (Gossypium hirsutum L.). J Appl Genet. 2006;47(4):331–5.Google Scholar
  23. East EM. Xenia and the endosperm of angiosperms. Bot Gaz. 1913;56(3):217–24.View ArticleGoogle Scholar
  24. Heerden Van HG. Analysis of seed components in upland cotton and their associations with lint percentage. College Station: Ph D Diss, Texas A and M University; 1969.Google Scholar
  25. Christiansen MN, Lewis C. Reciprocal differences in tolerance to seed-hydration chilling in F1 progeny of Gossypium hirsutum L. Crop Sci. 1973;13(2):210–2.View ArticleGoogle Scholar
  26. Mosjidis JA, Yermanos DM. Maternal effects and cytoplasmic inheritance of oleic and linoleic acid contents in sesame. Euphytica. 1984;33(2):427–32.View ArticleGoogle Scholar
  27. Dani RG, Kohel RJ. Maternal effects and generation mean analysis of seed-oil content in cotton (Gossypium hirsutum L.). Theor Appl Genet. 1989;77(4):569–75.PubMedView ArticleGoogle Scholar
  28. Knowles PF, Mutwakil A. Inheritance of low iodine value of safflower selections from India. Econ Bot. 1963;17(2):139–45.View ArticleGoogle Scholar
  29. Chowdhry M, Rafiq M, Alam K. Genetic architecture of grain yield and certain other traits in bread wheat. Pak J Agr Res. 1992;13(3):216–20.Google Scholar
  30. Griffing B. Concept of general and specific combining ability in relation to diallel crossing systems. Aust J Biol Sci. 1956;9(4):463–93.View ArticleGoogle Scholar
  31. Zhang Y, Kang MS. DIALLEL-SAS: A SAS program for Griffing's diallel analyses. Agron J. 1997;89(2):176–82.View ArticleGoogle Scholar
  32. Sprague GF, Tatum LA. General vs. specific combining ability in single crosses of corn. Agron J. 1942;34(10):923–32.View ArticleGoogle Scholar
  33. Tosun M, Güler M, Erem C, Uslu T, Miskioglu E. Intermittent polyarthritis due to propylthiouracil. Clin Rheumatol. 1995;14(5):574–5.PubMedView ArticleGoogle Scholar
  34. Barnard AD, Labuschagne MT, Van Niekerk HA. Heritability estimates of bread wheat quality traits in the Western Cape province of South Africa. Euphytica. 2002;127(1):115–22.View ArticleGoogle Scholar
  35. Shenk JS, Westerhaus MO. Analysis of agriculture and food products by near infrared reflectance spectroscopy. Port Matilda: Infrasoft International; 1993.Google Scholar
  36. Gan L, Sun X. Establishment of math models of NIRS analysis for oil and protein contents in seed of Brassica napus. Scientia Agricultura Sinica; 2003.Google Scholar
  37. Sas Institute. The SAS system for Windows. 2003.Google Scholar
  38. Cong Z. Study on the effect of maize kernel oil genes at the F1 embryo stage and its application, MS Dissertation of China Agricultural University.. 1996. in Chinese.Google Scholar
  39. Duan M, Song T, Wang L, Fan H, Zhao J. Study on the xenia effect of high oil corn. Acta Agron Sin. 2001;28(2):208–14. in Chinese with English abstract.Google Scholar
  40. Zhu J, Weir BS. Analysis of cytoplasmic and maternal effects I. A genetic model for diploid plant seeds and animals. Theor Appl Genet. 1994;89(2):153–9.PubMedGoogle Scholar
  41. Zhu J, Weir BS. Diallel analysis for sex-linked and maternal effects. Theor Appl Genet. 1996;92(1):1–9.PubMedView ArticleGoogle Scholar
  42. Rao CR. Estimation of variance and covariance components—MINQUE theory. J Multivariate Anal. 1971;1(3):257–75.View ArticleGoogle Scholar
  43. Zhu J. Methods of predicting genotype value and heterosis for offspring of hybrids. J Biomathmatics. 1993;8(1):32–44. in Chinese with English abstract.Google Scholar
  44. Miller RG. The jackknife-a review. Biometrika. 1974;61(1):1–15.Google Scholar
  45. Grami B, Stefansson BR. Paternal and maternal effects on protein and oil content in summer rape. Can J Plant Sci. 1977;57(3):945–9.View ArticleGoogle Scholar
  46. Letchworth MB, Lambert RJ. Pollen parent effects on oil, protein, and starch concentration in maize kernels. Crop Sci. 1998;38(2):363–7.View ArticleGoogle Scholar
  47. Pixley KV, Bjarnason MS. Pollen-parent effects on protein quality and endosperm modification of quality protein maize. Crop Sci. 1994;34(2):404–9.View ArticleGoogle Scholar
  48. Hom NH. Pollen genotype effects on seed quality and selection of single seeds by near-infrared reflectance spectroscopy (NIRS) in winter oilseed rape, Thesis. Göttingen: Georg-August-Universität; 2004.Google Scholar
  49. Singh BB, Hadely HH. Maternal control of oil synthesis in soybeans, Glycine max (L.). Merr Crop Sci. 1968;8(5):622–5.View ArticleGoogle Scholar
  50. Namazkar S, Stokmarr A, Frenck G, Egsgaard H, Terkelsen T, Mikkelsen T, Ingvordsen CH, Jørgensen RB. Concurrent elevation of CO2, O3 and temperature severely affects oil quanlity and quantity in rapeseed. J Exp Bot. 2016;67(14):4117–25.PubMedView ArticleGoogle Scholar
  51. Li Y, Beisson F, Pollard M, Ohlrogge J. Oil content of Arabidopsis seeds: the influence of seed anatomy, light and plant-to-plant variation. Phytochemistry. 2006;67(9):904–15.PubMedView ArticleGoogle Scholar
  52. Wu J, McCarty JC, Jenkins JN. Cotton chromosome substitution lines crossed with cultivars: genetic model evaluation and seed trait analyses. Theor Appl Genet. 2010;120(7):1473–83.PubMedView ArticleGoogle Scholar
  53. Riungu TC, McVetty PBE. Comparison of the effect of mur and nap cytoplasms on the performance of intercultivar summer rape hybrids. Can J Plant Sci. 2004;84(3):731–8.View ArticleGoogle Scholar
  54. McVetty PBE, Edie SA, Scarth R. Comparison of the effect of nap and pol cytoplasms on the performance of intercultivar summer oilseed rape hybrids. Can J Plant Sci. 1990;70(1):117–26.View ArticleGoogle Scholar


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