白菜型油菜分枝角度主基因+多基因混合遗传模型分析

doi:10.3969/j.issn.1004-1524.20240262

浙江农业学报 ›› 2025, Vol. 37 ›› Issue (4): 745-753.DOI: 10.3969/j.issn.1004-1524.20240262

白菜型油菜分枝角度主基因+多基因混合遗传模型分析

裴大妹(), 赵洪平, 王龙, 李华欣, 赵志, 肖麓^*()

青海大学农林科学院,青海西宁 810016

收稿日期:2024-03-20 出版日期:2025-04-25 发布日期:2025-05-09
作者简介:裴大妹(2000—),女,甘肃敦煌人,硕士研究生,研究方向为春油菜分子育种。E-mail:pdm2022@163.com
通讯作者: *肖麓,E-mail:xlu2005@aliyun.com
基金资助:
青海省“帅才科学家负责制”课题计划(2022-NK-170);国家现代农业产业技术体系(CARS-12);青海省自然科学基金计划—创新团队(2022-ZJ-902)

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

摘要/Abstract

摘要： 分枝角度是决定油菜株型的重要性状之一,与油菜产量密切相关。为揭示白菜型油菜(Brassica rapa L.)分枝角度的遗传规律,本研究选用青海大黄为母本,浩油11和No.952为父本分别配置杂交组合,采用主基因+多基因混合遗传模型分析的方法对2个组合各世代(P₁、P₂、F₁、F₂)单株的顶端连续3个分枝的夹角进行遗传分析。结果表明:西宁组合Ⅰ分枝角度的最适模型为2MG-EAD模型(2对完全显性主基因模型),主基因遗传率为84.61%,组合Ⅱ分枝角度的最适模型为2MG-A(2对加性主基因模型),主基因遗传率为80.71%;云南组合Ⅰ的最适模型为2MG-EA(2对等加性主基因模型),组合Ⅱ的最适模型为2MG-EAD(2对完全显性主基因模型),主基因遗传率均为86.05%。以上结果表明,白菜型油菜分枝角度明显受2对主基因遗传因素控制,且主基因间具有加性效应或显性效应;2个组合具有较高的主基因遗传力,说明油菜在分枝角度调控过程中,受多基因与环境因素影响较小,所以应在早期群体里进行选择。同时,这些结果可以为理想株型的构建和后续分枝角度数量性状基因座(QTL)定位和育种提供理论指导。

关键词: 白菜型油菜, 遗传效应, 主基因+多基因, 分枝角度, 主基因遗传率

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

中图分类号:

S565.4

裴大妹, 赵洪平, 王龙, 李华欣, 赵志, 肖麓. 白菜型油菜分枝角度主基因+多基因混合遗传模型分析[J]. 浙江农业学报, 2025, 37(4): 745-753.

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.

图/表 6

表1 大黄×浩油11和大黄×No.952 4个世代分枝角度的表型数据统计

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

图1 组合Ⅰ和Ⅱ F2群体分枝角度的频次分布

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

表2 各组合的遗传分析备选模型

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

表3 最适遗传模型的适合性检验

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)

表3 最适遗传模型的适合性检验

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)

表4 最适遗传模型的一阶遗传参数估计

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

表5 最适遗传模型的二阶遗传参数估计

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

表5 最适遗传模型的二阶遗传参数估计

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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白菜型油菜分枝角度主基因+多基因混合遗传模型分析

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

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