Mixed genetic model analysis of major gene + polygene of branch angle in Brassica rapa L.

doi:10.3969/j.issn.1004-1524.20240262

Acta Agriculturae Zhejiangensis ›› 2025, Vol. 37 ›› Issue (4): 745-753.DOI: 10.3969/j.issn.1004-1524.20240262

• Crop Science • Previous Articles Next Articles

Mixed genetic model analysis of major gene + polygene of branch angle in Brassica rapa L.

PEI Damei(), ZHAO Hongping, WANG Long, LI Huaxin, ZHAO Zhi, XIAO Lu^*()

Academy of Agriculture and Forestry Sciences, Qinghai University, Xining 810016, China

Received:2024-03-20 Online:2025-04-25 Published:2025-05-09

Abstract

Abstract:

Branch angle serves as a crucial trait in determining the plant architecture of Brassica napus and is intimately linked to its yield potential. To elucidate the genetic mechanisms underlying branch angle in Brassica rapa L., this study used a genetic analysis approach involving the configuration of hybrid combinations. Qinghai Dahuang was chosen as the female parent, while Haoyou 11 and No.952 served as the male parents. Genetic analysis was conducted on the angle between the top three consecutive branches of individual plants across various generations (P₁, P₂, F₁, F₂) within the two combinations, utilizing a combined major gene and polygene genetic model. The findings revealed that the most appropriate genetic model for the branch angle of Xining combination I was the 2MG-EAD model (two pairs of completely dominant major genes), with a significant major gene heritability of 84.61%; Conversely, for combination II, the most fitting model was the 2MG-A model( two pairs of additive major genes), exhibiting a major gene heritability of 80.71%. In the case of Yunnan combination I, the most suitable model was the 2MG-EA model(two pairs of equally additive major genes), on the other hand, combination II adhered to the 2MG-EAD model(two pairs of completely dominant major genes), both combinations exhibiting a major gene heritability of 86.05%. These results suggest that the branch angle in B. rapa is predominantly controlled by two pairs of major genetic factors, exhibiting either additive effects or dominance interactions among these genes. Notably, the high heritability of major genes observed in both combinations implies that B. rapa is relatively insensitive to the influence of polygenes and environmental factors in regulating branch angle. Consequently, early population selection is recommended to capitalize on these genetic traits. Furthermore, these findings provide valuable theoretical insights for the development of ideal plant types, as well as for subsequent quantitative trait locus(QTL) mapping and breeding efforts aimed at optimizing branch angle in B. rapa.

Key words: Brassica rapa L., genetic effect, main gene+polygenes, branch angle, heritability of main gene

CLC Number:

S565.4

PEI Damei, ZHAO Hongping, WANG Long, LI Huaxin, ZHAO Zhi, XIAO Lu. Mixed genetic model analysis of major gene + polygene of branch angle in Brassica rapa L.[J]. Acta Agriculturae Zhejiangensis, 2025, 37(4): 745-753.

Figures/Tables 6

Table 1 Phenotype data statistics of branch angle in four generations from Dahuang×Haoyou 11 and Dahuang×No.952

环境 Environ- ment	世代 Gene- ration	Ⅰ组合Combination Ⅰ						Ⅱ组合Combination Ⅱ
		单株数 No. of plants	分枝角度Branch angle					单株数 No. of single plant	分枝角度Branch angle
		单株数 No. of plants	最大值 Maximum/ (°)	最小值 Minimun/ (°)	平均数 Mean/ (°)	标准差 SD	变异系数 CV/%	单株数 No. of single plant	最大值 Maximum/ (°)	最小值 Minimun/ (°)	平均数 Mean/ (°)	标准差 SD	变异系数 CV/%
西宁	P₁	20	25.15	15.23	23.05	2.97	12.89	20	25.15	15.23	23.05	2.97	12.89
Xining	P₂	20	54.54	21.53	33.37	7.22	21.64	10	36.76	23.90	30.10	5.58	18.54
	F₁	17	41.54	24.15	30.34	4.72	15.56	17	37.54	21.25	29.19	4.62	15.83
	F₂	197	51.25	10.03	30.37	7.37	24.27	190	43.78	9.07	26.86	6.58	24.50
云南	P₁	20	29.71	17.42	22.44	3.79	16.89	20	29.71	17.42	22.44	3.79	16.89
Yunnan	P₂	20	48.70	25.31	33.94	9.06	26.69	20	50.44	20.21	38.91	8.14	20.92
	F₁	17	44.74	21.08	31.97	4.57	14.29	17	47.23	28.80	34.39	5.20	15.12
	F₂	185	65.36	16.20	35.11	9.29	26.46	188	57.18	10.01	32.82	9.61	29.28

Fig.1 Frequency distribution of branch angle in F2 population of combination Ⅰ and Ⅱ

Table 2 Alternative models for genetic analysis of each combination

环境 Environment	组合Ⅰ Combination Ⅰ			组合Ⅱ Combination Ⅱ
环境 Environment	模型含义 Implication of model	AIC值 AIC value	极大似然函数值 Maximum likelihood function value	模型含义 Implication of model	AIC值 AIC value	极大似然函数值 Maximum likelihood function value
西宁Xining	1MG-AD	1 654.77	-821.39	1MG-AD	1 441.82	-714.91
	1MG-A	1 653.22	-821.61	1MG-A	1 440.13	-715.06
	1MG-EAD	1 653.30	-821.65	1MG-EAD	1 439.97	-714.98
	1MG - NCD	1 652.41	-821.20	1MG-NCD	1 440.02	-715.01
	2MG-ADI	1 672.71	-825.35	2MG-ADI	1 456.28	-717.14
	2MG-AD	1 668.77	-827.39	2MG-AD	1 451.66	-718.83
	2MG-A	1 679.56	-834.78	2MG - A	1 431.33	-710.67
	2MG-EA	1 652.47	-822.24	2MG - EA	1 431.86	-711.93
	2MG-CD	1 694.88	-842.44	2MG-CD	1 448.50	-719.25
	2MG - EAD	1 651.54	-821.77	2MG-EAD	1 440.52	-716.26
云南Yunnan	1MG-AD	1 088.24	-538.12	1MG-AD	1 090.69	-539.34
	1MG-A	1 086.77	-538.39	1MG-A	1 088.70	-539.35
	1MG-EAD	1 086.63	-538.32	1MG-EAD	1 089.08	-539.54
	1MG-NCD	1 087.79	-538.90	1MG-NCD	1 090.24	-540.12
	2MG-ADI	1 106.72	-542.36	2MG-ADI	1 108.64	-543.32
	2MG-AD	1 100.32	-543.16	2MG-AD	1 103.81	-544.90
	2MG-A	1 109.01	-549.51	2MG-A	1 110.38	-550.19
	2MG - EA	1 083.34	-537.67	2MG - EA	1 085.71	-538.85
	2MG-CD	1 112.02	-551.01	2MG-CD	1 135.54	-562.77
	2MG - EAD	1 084.36	-538.18	2MG - EAD	1 085.50	-538.75

Table 3 Goodness-of-fit test of the optimal genetic model

环境 Environment	组合 Combination	模型 Model	世代 Generation	$U 1 2$	$U 2 2$	$U 3 2$	_nW²	D_n
西宁Xining	Ⅰ	2MG-EAD	P₁	0.021(0.884)	0.041(0.840)	0.060(0.807)	0.002(0.933)	0.119(0.909)
			P₂	0.289(0.591)	0.833(0.361)	2.465(0.116)	0.023(0.384)	0.190(0.418)
			F₁	0.128(0.720)	0.117(0.732)	0.000 3(0.986)	0.005(0.735)	0.167(0.637)
			F₂	0.002(0.966)	0.001(0.981)	0.005(0.947)	0.002(0.937)	0.042(0.885)
	Ⅱ	2MG-A	P₁	0.021(0.884)	0.041(0.840)	0.060(0.807)	0.002(0.933)	0.119(0.909)
			P₂	0.004(0.949)	0.001(0.972)	0.011(0.916)	0.004(0.784)	0.284(0.726)
			F₁	0.002(0.961)	0.118(0.732)	2.430(0.119)	0.005(0.771)	0.153(0.850)
			F₂	0.001(0.971)	0.001(0.971)	0(0.995)	0(1.000)	0.025(1.000)
云南Yunnan	Ⅰ	2MG-EA	P₁	0.040(0.842)	0.011(0.917)	0.126(0.723)	0.003(0.839)	0.176(0.866)
			P₂	0.064(0.801)	0.049(0.825)	0.008(0.928)	0.008(0.666)	0.281(0.470)
			F₁	0.002(0.961)	0.043(0.836)	0.413(0.520)	0.002(0.899)	0.116(0.965)
			F₂	0(0.998)	0(0.994)	0.001(0.980)	0.001(0.984)	0.048(0.943)
	Ⅱ	2MG-EAD	P₁	0.040(0.842)	0.011(0.917)	0.126(0.723)	0.004(0.839)	0.176(0.865)
			P₂	0.228(0.633)	0.062(0.804)	0.732(0.392)	0.022(0.393)	0.296(0.407)
			F₁	0.022(0.882)	0.007(0.932)	0.056(0.813)	0.005(0.759)	0.195(0.516)
			F₂	0(0.993)	0(0.998)	0.002(0.965)	0(0.985)	0.047(0.952)

Table 3 Goodness-of-fit test of the optimal genetic model

环境 Environment	组合 Combination	模型 Model	世代 Generation	$U 1 2$	$U 2 2$	$U 3 2$	_nW²	D_n
西宁Xining	Ⅰ	2MG-EAD	P₁	0.021(0.884)	0.041(0.840)	0.060(0.807)	0.002(0.933)	0.119(0.909)
			P₂	0.289(0.591)	0.833(0.361)	2.465(0.116)	0.023(0.384)	0.190(0.418)
			F₁	0.128(0.720)	0.117(0.732)	0.000 3(0.986)	0.005(0.735)	0.167(0.637)
			F₂	0.002(0.966)	0.001(0.981)	0.005(0.947)	0.002(0.937)	0.042(0.885)
	Ⅱ	2MG-A	P₁	0.021(0.884)	0.041(0.840)	0.060(0.807)	0.002(0.933)	0.119(0.909)
			P₂	0.004(0.949)	0.001(0.972)	0.011(0.916)	0.004(0.784)	0.284(0.726)
			F₁	0.002(0.961)	0.118(0.732)	2.430(0.119)	0.005(0.771)	0.153(0.850)
			F₂	0.001(0.971)	0.001(0.971)	0(0.995)	0(1.000)	0.025(1.000)
云南Yunnan	Ⅰ	2MG-EA	P₁	0.040(0.842)	0.011(0.917)	0.126(0.723)	0.003(0.839)	0.176(0.866)
			P₂	0.064(0.801)	0.049(0.825)	0.008(0.928)	0.008(0.666)	0.281(0.470)
			F₁	0.002(0.961)	0.043(0.836)	0.413(0.520)	0.002(0.899)	0.116(0.965)
			F₂	0(0.998)	0(0.994)	0.001(0.980)	0.001(0.984)	0.048(0.943)
	Ⅱ	2MG-EAD	P₁	0.040(0.842)	0.011(0.917)	0.126(0.723)	0.004(0.839)	0.176(0.865)
			P₂	0.228(0.633)	0.062(0.804)	0.732(0.392)	0.022(0.393)	0.296(0.407)
			F₁	0.022(0.882)	0.007(0.932)	0.056(0.813)	0.005(0.759)	0.195(0.516)
			F₂	0(0.993)	0(0.998)	0.002(0.965)	0(0.985)	0.047(0.952)

Table 4 Estimation of the 1st genetic parameter for the optimal genetic model

环境 Environment	组合 Combination	一阶遗传参数1st order genetic parameter/%
环境 Environment	组合 Combination	群体均方m	第1对主基因的加性效应da	第2对主基因的加性效应db
西宁Xining	Ⅰ(2MG-EAD)	28.68	-1.10	0
	Ⅱ(2MG-A)	27.50	-5.65	2.54
云南Yunnan	Ⅰ(2MG-EA)	30.82	-2.89	0
	Ⅱ(2MG-EAD)	32.69	-4.12	0

Table 5 Estimation of 2nd genetic parameter for the optimal genetic model

环境 Environment	组合 Combination	二阶遗传参数 2nd order genetic parameter/%
环境 Environment	组合 Combination	主基因方差 $σ m g 2$	主基因遗传率 $h m g 2$
西宁Xining	Ⅰ(2MG-EAD)	46.00	84.61
	Ⅱ(2MG-A)	35.01	80.71
云南Yunnan	Ⅰ(2MG-EA)	79.52	86.05
	Ⅱ(2MG-EAD)	79.52	86.05

Table 5 Estimation of 2nd genetic parameter for the optimal genetic model

环境 Environment	组合 Combination	二阶遗传参数 2nd order genetic parameter/%
环境 Environment	组合 Combination	主基因方差 $σ m g 2$	主基因遗传率 $h m g 2$
西宁Xining	Ⅰ(2MG-EAD)	46.00	84.61
	Ⅱ(2MG-A)	35.01	80.71
云南Yunnan	Ⅰ(2MG-EA)	79.52	86.05
	Ⅱ(2MG-EAD)	79.52	86.05

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Mixed genetic model analysis of major gene + polygene of branch angle in Brassica rapa L.

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