Identification of QTL for Grain Weight and Grain Shape Using Populations Derived from Residual Heterozygous Lines of indica Rice

doi:10.16819/j.1001-7216.2019.8120

Abstract

Abstract:

【Objective】Grain weight and grain shape are important factors influencing grain yield and quality in rice. There are quantitative traits controlled by a large number of quantitative trait loci (QTL) that vary greatly in effect, but not much attention has been paid to minor QTL. This study was conducted to detect minor QTL for grain weight and shape in the absence of major-QTL segregation. 【Method】 Following results of a previous QTL mapping study, a residual heterozygous plant was identified from the original population. The new population derived was homozygous in regions where major QTL for grain weight and shape were detected in the previous study, but segregated in 13 segments of other genomic regions. The population was planted in Hangzhou, Zhejiang and Lingshui, Hainan. Thousand-grain weight, grain length and grain width were tested and used for QTL analysis using Windows QTL Cartographer 2.5. 【Result】A total of 22 QTL were detected, distributing on 12 intervals of 10 chromosomes. Ten of them were significant in both locations, and the other two were detected in Hangzhou only. One plant that was only heterozygous in four of the 12 QTL regions was identified, from which one new population was constructed and tested. The QTL effects of the four regions were well validated. 【Conclusion】Our results indicate that the power of detecting minor QTL could be efficiently increased by eliminating the influence of major-QTL segregation. It is also suggested that minor QTL could have a stable effect though it is believed that they are generally subjected to large influence of the genetic background and environmental conditions. Our results also lay a foundation for fine mapping, cloning and marker-assisted selection of minor QTL for grain weight and grain shape in rice.

Key words: quantitative trait locus, 1000-grain weight, grain shape, residual heterozygous line, rice

摘要：

【目的】粒重粒形是影响水稻产量和品质的重要因素,由大量数量性状座位(QTL)控制,其作用变异极大,但以往研究主要着眼于效应大的QTL。本研究在剔除主效QTL影响的基础上,开展微效粒重粒形QTL分析。【方法】在前期研究基础上,从原群体挑选出1个剩余杂合体单株,构建了在主效QTL区间纯合、在其余区域中13个区间分离的群体,种植于浙江杭州和海南陵水,测定千粒重、粒长和粒宽。【结果】采用Windows QTL Cartographer 2.5,检测到22个QTL,分布于10条染色体的12个区间,其中,10个区间在两地均呈显著作用,2个区间仅在杭州试验中呈显著作用。进一步从该群体筛选出1个只在其中4个QTL区间杂合的单株,自交构建分离群体,验证了这4个区间对粒重粒形的效应。【结论】排除主效QTL有利于提高微效粒重粒形QTL的检测功效;虽然微效QTL可能易受环境和遗传背景影响,但仍可具有稳定表现。这些结果为进一步开展粒重粒形QTL的精细定位、克隆和分子标记辅助选择奠定了基础。

关键词: 数量性状座位, 千粒重, 粒形, 剩余杂合体, 水稻

CLC Number:

Andong ZHU, Zhichao SUN, Yujun ZHU, Hui ZHANG, Xiaojun NIU, Yeyang FAN, Zhenhua ZHANG, Jieyun ZHUANG. Identification of QTL for Grain Weight and Grain Shape Using Populations Derived from Residual Heterozygous Lines of indica Rice[J]. Chinese Journal OF Rice Science, 2019, 33(2): 144-151.

朱安东, 孙志超, 朱玉君, 张荟, 牛小军, 樊叶杨, 张振华, 庄杰云. 应用剩余杂合体衍生群体定位水稻粒重粒形QTL[J]. 中国水稻科学, 2019, 33(2): 144-151.

Figures/Tables 4

References 40

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性状 Trait	群体 Population	地点 Location	株系数 No. of lines	平均值 Mean	标准差 SD	变异系数 CV	变异范围 Range	偏度 Skewness	峰度 Kurtosis	亲本Parent
性状 Trait	群体 Population	地点 Location	株系数 No. of lines	平均值 Mean	标准差 SD	变异系数 CV	变异范围 Range	偏度 Skewness	峰度 Kurtosis	特青Teqing	IRBB52
千粒重	Ti52-2	陵水 Lingshui	251	24.98	0.51	0.020	23.77-26.32	-0.03	-0.21	25.53	24.87
TGW / g	Ti52-2	杭州 Hangzhou	251	21.83	0.42	0.019	20.78-23.00	0.25	-0.46	23.55	23.14
	ZC8	杭州 Hangzhou	179	22.18	0.27	0.012	21.46-22.93	0.29	0.09	22.95	23.52
粒长	Ti52-2	陵水 Lingshui	251	8.009	0.104	0.013	7.742-8.382	0.21	0.21	7.541	9.026
GL / mm	Ti52-2	杭州 Hangzhou	251	7.821	0.094	0.012	7.567-8.053	0.14	-0.29	7.417	8.911
	ZC8	杭州 Hangzhou	179	8.137	0.053	0.007	8.016-8.342	0.22	0.36	7.650	9.122
粒宽	Ti52-2	陵水 Lingshui	251	2.890	0.039	0.013	2.777-2.997	-0.11	0.00	3.216	2.720
GW / mm	Ti52-2	杭州 Hangzhou	251	2.579	0.028	0.011	2.491-2.652	0.05	-0.09	2.891	2.395
	ZC8	杭州 Hangzhou	179	2.688	0.016	0.006	2.646-2.728	0.20	-0.34	2.917	2.510

性状 Trait	群体 Population	地点 Location	株系数 No. of lines	平均值 Mean	标准差 SD	变异系数 CV	变异范围 Range	偏度 Skewness	峰度 Kurtosis	亲本Parent
性状 Trait	群体 Population	地点 Location	株系数 No. of lines	平均值 Mean	标准差 SD	变异系数 CV	变异范围 Range	偏度 Skewness	峰度 Kurtosis	特青Teqing	IRBB52
千粒重	Ti52-2	陵水 Lingshui	251	24.98	0.51	0.020	23.77-26.32	-0.03	-0.21	25.53	24.87
TGW / g	Ti52-2	杭州 Hangzhou	251	21.83	0.42	0.019	20.78-23.00	0.25	-0.46	23.55	23.14
	ZC8	杭州 Hangzhou	179	22.18	0.27	0.012	21.46-22.93	0.29	0.09	22.95	23.52
粒长	Ti52-2	陵水 Lingshui	251	8.009	0.104	0.013	7.742-8.382	0.21	0.21	7.541	9.026
GL / mm	Ti52-2	杭州 Hangzhou	251	7.821	0.094	0.012	7.567-8.053	0.14	-0.29	7.417	8.911
	ZC8	杭州 Hangzhou	179	8.137	0.053	0.007	8.016-8.342	0.22	0.36	7.650	9.122
粒宽	Ti52-2	陵水 Lingshui	251	2.890	0.039	0.013	2.777-2.997	-0.11	0.00	3.216	2.720
GW / mm	Ti52-2	杭州 Hangzhou	251	2.579	0.028	0.011	2.491-2.652	0.05	-0.09	2.891	2.395
	ZC8	杭州 Hangzhou	179	2.688	0.016	0.006	2.646-2.728	0.20	-0.34	2.917	2.510

染色体 Chr	区间 Interval	QTL	杭州 Hangzhou				陵水 Lingshui
染色体 Chr	区间 Interval	QTL	LOD	A	D	R²/%	LOD	A	D	R²/%
1	RM12210	qGL1	5.69	0.029	-0.004	4.51	4.55	0.033	0.004	4.76
3	RM14302-RM14383	qGL3.1	4.90	0.025	0.003	3.52	8.12	0.044	0.013	9.22
		qGW3	ns				5.29	-0.015	0.001	6.93
3	RM232	qGL3.2	5.21	0.029	-0.004	3.79	ns
4	RM16252-RM335	qTGW4	6.65	-0.150	0.090	6.66	5.03	-0.200	-0.030	7.14
		qGW4	9.78	-0.014	0.003	11.50	6.79	-0.017	0.001	9.02
5	RM18927-RM3321	qTGW5	22.38	0.340	-0.040	27.44	ns
		qGL5	38.86	0.092	-0.022	40.16	6.84	0.044	0.004	7.72
6	RM469-RM587	qTGW6.1	ns				2.91	0.130	0.110	3.98
		qGL6	13.27	0.047	0.001	11.20	10.50	0.055	0.001	11.93
		qGW6.1	12.63	-0.016	0.006	14.78	ns
6	RM20731	qTGW6.2	4.64	-0.140	0.040	4.62	ns
		qGW6.2	5.65	-0.011	0.002	6.31	5.78	-0.015	-0.006	7.31
8	RM22755-RM210	qTGW8	3.84	0.120	0.020	3.55	4.49	0.170	-0.090	6.29
		qGL8	5.45	0.028	0.005	4.09	5.15	0.027	-0.030	5.70
9	RM5688-RM219	qTGW9	12.30	0.230	0.050	14.23	ns
		qGW9	10.54	0.014	0.004	13.16	ns
10	RM6704-RM6100	qTGW10	6.54	0.160	-0.050	6.44	ns
		qGL10	9.17	0.037	-0.001	7.47	6.43	0.030	0.029	6.24
11	RM1233-RM5926	qTGW11	ns				4.08	-0.170	0.090	6.13
		qGW11	4.41	-0.008	-0.005	4.79	7.46	-0.020	0.003	10.09
12	RM3246-Pita	qGL12	3.33	-0.021	-0.002	2.31	10.36	-0.051	-0.010	11.67

染色体 Chr	区间 Interval	QTL	杭州 Hangzhou				陵水 Lingshui
染色体 Chr	区间 Interval	QTL	LOD	A	D	R²/%	LOD	A	D	R²/%
1	RM12210	qGL1	5.69	0.029	-0.004	4.51	4.55	0.033	0.004	4.76
3	RM14302-RM14383	qGL3.1	4.90	0.025	0.003	3.52	8.12	0.044	0.013	9.22
		qGW3	ns				5.29	-0.015	0.001	6.93
3	RM232	qGL3.2	5.21	0.029	-0.004	3.79	ns
4	RM16252-RM335	qTGW4	6.65	-0.150	0.090	6.66	5.03	-0.200	-0.030	7.14
		qGW4	9.78	-0.014	0.003	11.50	6.79	-0.017	0.001	9.02
5	RM18927-RM3321	qTGW5	22.38	0.340	-0.040	27.44	ns
		qGL5	38.86	0.092	-0.022	40.16	6.84	0.044	0.004	7.72
6	RM469-RM587	qTGW6.1	ns				2.91	0.130	0.110	3.98
		qGL6	13.27	0.047	0.001	11.20	10.50	0.055	0.001	11.93
		qGW6.1	12.63	-0.016	0.006	14.78	ns
6	RM20731	qTGW6.2	4.64	-0.140	0.040	4.62	ns
		qGW6.2	5.65	-0.011	0.002	6.31	5.78	-0.015	-0.006	7.31
8	RM22755-RM210	qTGW8	3.84	0.120	0.020	3.55	4.49	0.170	-0.090	6.29
		qGL8	5.45	0.028	0.005	4.09	5.15	0.027	-0.030	5.70
9	RM5688-RM219	qTGW9	12.30	0.230	0.050	14.23	ns
		qGW9	10.54	0.014	0.004	13.16	ns
10	RM6704-RM6100	qTGW10	6.54	0.160	-0.050	6.44	ns
		qGL10	9.17	0.037	-0.001	7.47	6.43	0.030	0.029	6.24
11	RM1233-RM5926	qTGW11	ns				4.08	-0.170	0.090	6.13
		qGW11	4.41	-0.008	-0.005	4.79	7.46	-0.020	0.003	10.09
12	RM3246-Pita	qGL12	3.33	-0.021	-0.002	2.31	10.36	-0.051	-0.010	11.67

染色体Chr	区间 Interval	QTL	LOD	A	D	R²/%
6	RM20731	qTGW6.2	2.52	-0.080	0.010	5.08
		qGW6.2	4.31	-0.006	-0.000	8.03
8	RM22755-RM210	qTGW8	6.52	0.160	-0.010	16.32
		qGL8	5.71	0.026	-0.013	11.92
10	RM1108-RM7300	qGL10	4.70	0.024	0.000	9.27
12	RM3246-Pita	qTGW12	2.75	0.080	0.050	5.49
		qGL12	3.58	-0.019	0.008	6.79
		qGW12	3.70	0.006	0.001	6.85