绿豆5个产量相关性状的QTL分析

doi:10.11983/CBB22108

摘要/Abstract

摘要： 利用绿豆(Vigna radiata)品种苏绿16-10和潍绿11杂交构建的F₂和F₃群体发掘调控绿豆产量相关性状的遗传位点。同时对绿豆产量相关性状进行表型鉴定和相关性分析, 并利用构建的遗传连锁图谱进行QTL定位。结果表明, 单株产量与单株荚数、单荚粒数、百粒重和分枝数均呈正相关。单株产量与单株荚数的相关性最高, 这2个性状在F₂和F₃群体中的相关系数分别为0.950和0.914。在F₂群体中, 共检测到8个与产量性状相关的QTL位点, 其中与单株荚数、单荚粒数和单株产量相关的QTL位点各1个, 分别解释11.09% (qNPP3)、17.93% (qNSP3)和14.18% (qYP3)的表型变异; 2个与分枝数相关的QTL位点qBMS3和qBMS11, 分别解释18.51%和7.06%的表型变异; 3个与百粒重相关的QTL位点qHSW3、qHSW7和qHSW10, 分别解释5.33%、46.07%和4.24%的表型变异。在F₃群体中, qNSP3和qHSW7再次被检测到, 表明这2个QTLs有较好的遗传稳定性。同时, 开发了1个与百粒重主效QTL qHSW7紧密连锁的InDel标记R7-13.4, 并利用自然群体对该分子标记辅助筛选的有效性进行了验证。研究结果可为绿豆产量相关性状基因的定位、克隆及分子标记辅助育种提供参考。

关键词: 绿豆, 产量相关性状, 相关性分析, QTL定位

Abstract: The F₂ and F₃ populations derived from the cross between Sulv16-10 and Weilv11 were used to explore the genetic loci controlling yield-related traits in mungbean, and the phenotype identification and correlation analysis between yield-related traits were completed. The genetic linkage map was constructed and used for QTL analysis. The yield per plant was positively correlated with the number of pods per plant, the number of seeds per pod, hundred-seed weight and the number of branches on main stem. The correlation between the yield per plant and the number of pods per plant was the highest, and the correlation coefficient between these two traits were 0.950 and 0.914 in F₂ and F₃ population, respectively. A total of 8 QTLs for yield-related traits were detected in the F₂ population. Among them, three traits including the number of pods per plant, number of seeds per pod and yield per plant were found only on one related QTL, and each QTL accounting for 11.09% (qNPP3), 17.93% (qNSP3) and 14.18% (qYP3) of phenotype variance, respectively. Two QTLs, qBMS3 and qBMS11 related to the branch number on main stem were detected, which could explain 18.51% and 7.06% of phenotype variance, respectively. Three QTLs, qHSW3, qHSW7 and qHSW10 controlling hundred-seed weight were identified, which could explain 5.33%, 46.07% and 4.24% of phenotype variance, respectively. qNSP3 and qHSW7 were detected again in the F₃ population, demonstrating that the two QTLs were genetically stable. The InDel molecular marker R7-13.4 which closely linked to the major-effect QTL qHSW7 for hundred-seed weight was developed, and the validation of molecular marker-assisted selection was verified in natural populations. These studies provide reference for mapping, cloning of genes associated with yield-related traits as well as molecular marker-assisted selection in mungbean.

Key words: mungbean, yield-related traits, correlation analysis, QTL mapping

叶卫军, 张阴, 王沛然, 张玲玲, 田东丰, 吴泽江, 周斌. 绿豆5个产量相关性状的QTL分析. 植物学报, 2023, 58(1): 150-158.

Weijun Ye, Yin Zhang, Peiran Wang, Lingling Zhang, Dongfeng Tian, Zejiang Wu, Bin Zhou. QTLs Analysis for Five Yield-related Traits in Mungbean. Chinese Bulletin of Botany, 2023, 58(1): 150-158.

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https://www.chinbullbotany.com/CN/Y2023/V58/I1/150

图/表 8

参考文献 36

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Year	Traits	Parental lines		F₂ or F₃ population
Year	Traits	Weilv11	Sulv16-10	Means±SD	Range	CV (%)	Skewness	Kurtosis
2019 (F₂)	NPP	11.0	20.2 **	18.26±8.86	5.0-46.0	48.52	1.27	1.26
	NSP	10.1	12.0 **	10.62±0.98	9.6-14.3	7.77	-0.84	0.55
	HSW (g)	5.00	7.42 **	6.33±0.69	4.77-8.19	10.95	0.27	-0.45
	BMS	0.5	3.0 **	2.08±1.48	0.0-6.0	71.17	0.35	-0.45
	YP (g)	5.21	14.95 **	11.48±5.95	2.67-28.96	51.80	1.16	0.82
2020 (F₃)	NPP	9.4	23.2 **	16.94±8.65	5.0-48.0	51.05	1.38	2.01
	NSP	9.8	12.3 **	10.41±1.30	8.5-15.0	10.15	-0.73	0.80
	HSW (g)	5.06	7.02 **	5.47±0.68	3.40-7.20	12.51	-0.44	0.27
	BMS	0.5	3.6 **	1.71±1.39	0.0-6.0	81.68	-0.11	-1.17
	YP (g)	4.62	16.89 **	8.94±4.71	2.00-5.40	52.70	1.15	1.18

Year	Traits	Parental lines		F₂ or F₃ population
Year	Traits	Weilv11	Sulv16-10	Means±SD	Range	CV (%)	Skewness	Kurtosis
2019 (F₂)	NPP	11.0	20.2 **	18.26±8.86	5.0-46.0	48.52	1.27	1.26
	NSP	10.1	12.0 **	10.62±0.98	9.6-14.3	7.77	-0.84	0.55
	HSW (g)	5.00	7.42 **	6.33±0.69	4.77-8.19	10.95	0.27	-0.45
	BMS	0.5	3.0 **	2.08±1.48	0.0-6.0	71.17	0.35	-0.45
	YP (g)	5.21	14.95 **	11.48±5.95	2.67-28.96	51.80	1.16	0.82
2020 (F₃)	NPP	9.4	23.2 **	16.94±8.65	5.0-48.0	51.05	1.38	2.01
	NSP	9.8	12.3 **	10.41±1.30	8.5-15.0	10.15	-0.73	0.80
	HSW (g)	5.06	7.02 **	5.47±0.68	3.40-7.20	12.51	-0.44	0.27
	BMS	0.5	3.6 **	1.71±1.39	0.0-6.0	81.68	-0.11	-1.17
	YP (g)	4.62	16.89 **	8.94±4.71	2.00-5.40	52.70	1.15	1.18

Traits	NPP	NSP	HSW	BMS
NSP	0.362 **
NSP	0.357 **
HSW	-0.005	-0.049
HSW	0.149	0.125
BMS	0.403 **	0.190 *	0.174 *
BMS	0.708 **	0.423 **	0.311 **
YP	0.950 **	0.409 **	0.163	0.425 **
YP	0.914 **	0.464 **	0.318 **	0.701 **

Traits	NPP	NSP	HSW	BMS
NSP	0.362 **
NSP	0.357 **
HSW	-0.005	-0.049
HSW	0.149	0.125
BMS	0.403 **	0.190 *	0.174 *
BMS	0.708 **	0.423 **	0.311 **
YP	0.950 **	0.409 **	0.163	0.425 **
YP	0.914 **	0.464 **	0.318 **	0.701 **

Year	Traits	QTL name	Chromosome	Marker interval	Position (cM)	Likelihood of odd (LOD)	Add effect	Phenotype variance explained (%)
2019	NPP	qNPP3	3	ID3-8-ID3-9	30.60-31.34	3.47	4.62	11.09
	NSP	qNSP3	3	ID3-5-ID3-6	13.16-23.40	5.92	0.58	17.93
	HSW	qHSW3	3	ID3-7-ID3-9	29.12-31.34	3.78	0.26	5.33
		qHSW7	7	ID7-10-ID7-7	100.12-103.50	23.15	0.71	46.07
		qHSW10	10	ID10-3-ID10-4	6.84-9.08	2.90	-0.09	4.24
	BMS	qBMS3	3	ID3-8-ID3-9	30.60-31.34	6.44	1.03	18.51
	BMS	qBMS11	11	ID11-6-ID11-7	33.46-35.32	2.85	0.25	7.06
	YP	qYP3	3	ID3-8-ID3-9	30.60-31.34	4.60	3.67	14.18
2020	NPP	qNPP3_a	3	ID3-4-ID3-5	9.83-13.06	3.39	3.63	2.27
	NSP	qNSP3_a	3	R3-9-R3-12	20.88-22.23	6.37	0.66	19.93
	HSW	qHSW7_a	7	ID7-10-ID7-7	29.77-31.76	8.80	0.42	30.17