小麦穗部性状的主基因+多基因混合遗传模型分析

doi:10.3864/j.issn.0578-1752.2019.24.001

Abstract

Abstract:

【Objective】 Panicle traits are important yield traits of wheat, occupying an important position and role in wheat yield composition. Carrying out genetic research on wheat panicle traits and analyzing its genetic mechanism provide theoretical and practical guidance for formulating high-yield breeding strategies and improving breeding efficiency. 【Method】 Based on the length of the main stem, the number of spikelets, the number of grains per spike, and the number of spikelets, the main gene + polygene mixed genetic model of quantitative traits was used to obtain the parental product 34 and the male parent under different ecological conditions. BARRAN and its derived F_7:8, F_8:9 generation recombinant inbred line population (RIL) were used for genetic model analysis and genetic parameter estimation of panicle traits to determine the number of genes controlling various traits, and to estimate genetic effect values and heritability. 【Result】The best genetic model for panicle length and spikelet number were B-2-1 (PG-AI), which was consistent with two pairs of linked major genes + additive-epistasis polygene genetic model. The polygenic heritability of spike length was 90.64%, the polygenic heritability of spikelet number was 89.52%, the average of environmental variation of spike length accounted for 9.39% in phenotypic variation, and the average of environmental variation of spikelet number accounted for 10.50% in phenotypic variation; Major gene heritability was 69.39%, Polygenes heritability rate was 29.94%, and the average environmental variation accounted for 2.18% in phenotypic variation. Additive effect value of the first pair of main genes controlling the number of spikes and the additive effect value of the third pair of major genes are equal, and the same was 4.56, which has a positive effect. The additive effect value of the second pair of major genes was the same as the additive effect of the first pair of major genes × the second pair of major genes × the third pair of major genes, both of which were -1.44, and are negative effects. The additive and additive × additive epistasis interaction values were equal to the additive and the second pair of major gene additions × the third pair of major gene additive epistatic interactions, both of which were -6.02. Additive and the first pair of major gene additive × the third pair of main gene additive epistatic interaction effect value is 0.18, the multi-gene additive effect value is 0.15, showing a lower positive genetic effect; H-1(4MG-AI) was best-fitting genetic model for the spikelet number traits, which showed that their inheritance was controlled by incorporating four major genes additive-epistasis genetic model. The heritability of the main gene was 81.50%. The additive effect values of the main genes in the first to fourth pairs were 0.22, 0.18, -0.20, and 0.24, respectively, the additive and epistatic interactions of the first pair of major genes × the first pair of major genes were -0.170, the additive effect value of the additive and the first pair of major genes × the third pair of major genes was 0.240. the additive effect value of the additive and the first pair of major genes × the fourth pair of major genes was -0.200, additive and the second pair of major genes × the third pair of major genes × additive effect value and additive and the second pair of major gene additive × fourth pair of major gene additive epistatic interaction value absolute value, the effect in contrast, the former value was 0.030, and the latter value was -0.030. The additive effect value of the additive and the third pair of major genes × the fourth pair of major genes was 0.060. 【Conclusion】The panicle traits of wheat are mainly polygenic genetic effects, which are in line with quantitative genetic characteristics and are susceptible to environmental influences. The number of spikelet grains has the genetic characteristics of the main gene. The main gene has high heritability and is affected by the environment. The number of spikelets can be used as a direct indicator to effectively improve the early selection of panicle traits, achieving single plant directional selection and improving breeding efficiency.

Key words: wheat, panicle traits, major gene + polygene, genetic effect

SongFeng XIE,WanQuan JI,ChangYou WANG,WeiGuo HU,Jun LI,YaoYuan ZHANG,XiaoXi SHI,JunJie ZHANG,Hong ZHANG,ChunHuan CHEN. Genetic Analysis of Panicle Related Traits in Wheat with Major Gene Plus Polygenes Mixed Model[J].Scientia Agricultura Sinica, 2019, 52(24): 4437-4452.

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Figures/Tables 5

Table 1

Fig. 1

Table 2

Akaike information criterion(AIC) and Maximum likelihood values (MLV) of thirty-eight genetic models for panicle traits in joint segregation analysis on the F8, F9 population between Pindong34 and Barran"

环境Environment	^a模型代码Model Code	^b模型含义Implication of model	AIC值AIC value				极大似然函数值log_Max_likelihood_value
环境Environment	^a模型代码Model Code	^b模型含义Implication of model	穗长 SL(cm)	小穗数 SME	单穗粒数GME	小穗粒数GSE	穗长 SL(cm)	小穗数 SME	单穗粒数GME	小穗粒数GSE
2016SY	B-1-9	2MG-IE	2008.766	2202.984	3630.920	568.647	-1001.383	-1098.492	-1812.460	-281.323
2017SY			2042.412	1871.954	3892.716	836.451	-1018.206	-932.977	-1943.358	-415.226
2017HY			2005.506	2264.683	3068.409	-151.936	-999.753	-1129.341	-1531.204	78.968
2017SG			2280.090	2518.826	3905.365	831.225	-1137.045	-1256.413	-1949.683	-412.612
平均值Average			2084.194	2214.612	3624.353	521.097	-1039.097	-1104.306	-1809.176	-257.548
2016SY	B-2-1	PG-AI	1991.08	2184.541	3649.384	554.133	-990.540	-1087.271	-1819.692	-272.066
2017SY			2016.217	1855.786	3899.482	920.279	-1003.108	-922.893	-1944.741	-455.140
2017HY			1965.160	2256.652	3074.416	-88.404	-977.58	-1123.326	-1532.208	49.202
2017SG			2260.751	2507.815	3890.493	905.074	-1125.375	-1248.908	-1940.246	-447.537
平均值Average			2058.302	2201.199	3628.444	572.771	-1024.151	-1095.599	-1809.222	-281.385
2016SY	E-2-5	MX2-ER-A	1993.659	2204.400	3631.760	557.823	-990.83	-1096.200	-1809.880	-272.911
2017SY			2037.382	1872.533	3888.241	841.737	-1012.691	-930.267	-1938.120	-414.868
2017HY			1975.250	2264.573	3074.295	-155.919	-981.625	-1126.287	-1531.147	83.960
2017SG			2179.590	2509.166	3879.773	825.033	-1083.795	-1248.583	-1933.887	-406.517
平均值Average			2046.470	2212.668	3618.517	517.168	-1017.235	-1100.334	-1803.259	-252.584
2016SY	E-2-6	MX2-AE-A	1984.375	2205.064	3681.667	558.402	-986.188	-1096.532	-1834.834	-273.201
2017SY			2035.499	1870.327	3888.148	924.373	-1011.749	-929.163	-1938.074	-456.187
2017HY			1964.365	2264.534	3076.497	-156.411	-976.183	-1126.267	-1532.248	84.206
2017SG			2190.648	2510.324	3892.530	907.513	-1089.324	-1249.162	-1940.265	-447.756
平均值Average			2043.722	2212.562	3634.711	558.469	-1015.861	-1100.281	-1811.355	-273.235
2016SY	E-2-7	MX2-CE-A	2008.310	2206.715	3681.548	558.968	-999.155	-1098.357	-1835.774	-274.484
2017SY			2038.900	1871.419	3886.283	925.424	-1014.450	-930.710	-1938.141	-457.712
2017HY			1992.014	2265.186	3074.897	-157.747	-991.007	-1127.593	-1532.449	83.874
2017SG			2212.174	2508.126	3891.372	908.553	-1101.087	-1249.063	-1940.686	-449.276
平均值Average			2062.850	2212.862	3633.525	558.799	-1026.425	-1101.431	-1811.763	-274.400
2016SY	F-1	3MG-AI	1985.792	2203.003	3578.592	500.386	-983.896	-1092.501	-1780.296	-241.193
2017SY			2050.987	1865.838	3896.524	837.993	-1016.493	-923.919	-1939.262	-409.997
2017HY			1967.168	2268.794	3076.632	-170.353	-974.584	-1125.397	-1529.316	94.177
2017SG			2164.521	2523.808	3889.178	812.895	-1073.26	-1252.904	-1935.589	-397.447
平均值Average			2042.117	2215.361	3610.232	495.230	-1012.058	-1098.68	-1796.116	-238.615
2016SY	F-2	3MG-A	2061.739	2303.912	3654.398	428.251	-1025.870	-1146.956	-1822.199	-209.126
2017SY			2115.129	1856.02	3931.771	838.167	-1052.565	-923.01	-1960.885	-414.084
2017HY			2116.900	2370.007	3175.847	-166.145	-1053.45	-1180.003	-1582.924	88.073
2017SG			2263.549	2451.369	3917.213	822.204	-1126.775	-1220.685	-1953.606	-406.102
平均值Average			2139.329	2245.327	3669.807	480.619	-1064.665	-1117.663	-1829.904	-235.310
2016SY	G-1	MX3-AI-A	1985.729	2203.538	3562.874	487.927	-981.865	-1090.769	-1770.437	-232.963
2017SY			2034.889	1869.268	3892.910	841.503	-1006.444	-923.634	-1935.455	-409.751
2017HY			1963.325	2267.739	3081.815	-178.949	-970.663	-1122.870	-1529.907	100.474
2017SG			2172.129	2518.193	3883.909	826.033	-1075.064	-1248.096	-1930.954	-402.017
平均值Average			2039.018	2214.685	3605.377	494.128	-1008.509	-1096.342	-1791.688	-236.064
2016SY	H-1	4MG-AI	1804.726	2198.415	3572.438	572.548	-891.363	-1088.207	-1775.219	-275.274
2017SY			2048.989	1873.771	3893.070	822.622	-1013.495	-925.885	-1935.535	-400.311
2017HY			1960.836	2268.425	3079.402	-244.665	-969.418	-1123.212	-1528.701	133.332
2017SG			2164.815	2518.811	3885.512	805.103	-1071.407	-1248.406	-1931.756	-391.552
平均值Average			1994.842	2214.856	3607.606	488.902	-986.421	-1096.428	-1792.803	-233.451

Table 2

Table 3

Table 4

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环境Environment	性状 Trait	亲本Parent		重组自交系群体 RIL
环境Environment	性状 Trait	品冬34 Pin- Dong34	Warran	最小值 Minimum	最大值 Maximum	平均数 Average	标准差 SD	变异系数 Coefficient of variation/CV (%)	遗传力 Heritability	偏度系数 Skewness	峰度系数 Kurtosis
2016SY	穗长 SL (cm）	9.00	5.00	4.00	14.00	8.44	1.92	0.23	0.92	0.08	-0.53
2017SY		9.00	5.25	4.00	26.20	8.45	1.92	0.23	0.91	1.58**	14.10**
2017HY		9.78	6.13	4.88	14.90	9.43	1.80	0.19	0.90	0.02	-0.45
2017SG		10.67	5.17	3.77	14.17	9.00	2.48	0.27	0.97	-0.16	-0.98
平均 Average		9.61	5.39	4.16	17.32	8.83	2.03	0.23	0.92	0.38**	3.03**
2016SY	小穗数SME	19.00	14.00	11.00	27.00	18.39	2.34	0.13	0.88	0.27**	0.58**
2017SY		19.00	15.75	12.60	22.33	17.19	1.59	0.09	0.34	0.21*	0.14*
2017HY		17.25	15.00	9.25	39.50	17.48	2.37	0.14	0.62	1.66**	5.36**
2017SG		21.00	21.00	13.33	59.00	20.58	3.11	0.15	0.95	1.77**	3.71**
平均值 Average		19.06	16.44	11.55	36.96	18.41	2.35	0.13	0.70	0.98**	2.45**
2016SY	单穗粒数 GME	50.00	39.00	27.00	104.00	56.32	10.92	0.19	0.92	0.92**	2.31**
2017SY		44.25	39.25	26.00	69.60	43.01	5.86	0.14	0.40	0.48**	1.05**
2017HY		33.75	35.75	15.25	55.50	37.11	5.35	0.14	0.80	0.15*	0.68**
2017SG		48.33	52.00	8.33	94.00	45.14	12.70	0.28	0.92	-0.35	0.36**
平均 Average		44.08	41.50	19.15	80.78	45.39	8.71	0.19	0.76	0.30**	1.10**
2016SY	小穗粒数 GSE	2.63	2.79	2.00	9.00	3.07	0.44	0.14	0.85	5.67**	12.24**
2017SY		2.32	2.53	1.73	8.78	2.62	0.77	0.29	0.81	5.72**	17.04**
2017HY		1.95	2.38	1.62	31.25	2.21	1.35	0.61	0.90	2.03**	5.58**
2017SG		2.30	2.48	0.20	3.71	2.15	0.62	0.29	0.97	-0.92	0.95**
平均 Average		2.30	2.54	1.39	13.18	2.51	0.80	0.32	0.88	3.13**	8.95**

性状 Traits	环境 Environment	模型代码 Modelcode	模型含义 Implication of model	世代 Generation	统计量Statistic
性状 Traits	环境 Environment	模型代码 Modelcode	模型含义 Implication of model	世代 Generation	U₁²	U₂²	U₃²	nW²	D_n
穗长 SL(cm)	2017SY	B-2-1	PG-AI	P₁	0.5511(0.4579)	0.3309(0.5651)	0.3297(0.5659)	0.5036(0.0397)	0.4948(0.0088)
				P₂	0.0268(0.8701)	0.0993(0.7527)	0.3929(0.5308)	0.151(0.3881)	0.4143(0.3929)
				RIL	0.0577(0.8102)	0.3641(0.5463)	2.1999(0.1380)	0.0854(0.6733)	0.0354(0.5748)
小穗数 SME	2016SY	B-2-1	PG-AI	P₁	0(0.9998)	0(0.9968)	0.0003(0.9865)	0.0541(0.8519)	0.25(0.9062)
				P₂	0(1)	0.0245(0.8756)	0.392(0.5312)	0.0385(0.9405)	0.24(0.9810)
				RIL	0.1318(0.7166)	0.2995(0.5842)	0.6132(0.4336)	1.8464(2.98E-05)	0.154(2.51E-10)
穗粒数 GME	2016SY	G-1	MX3-AI-A	P₁	0.4341(0.5100)	0.3268(0.5676)	0.0704(0.7908)	0.0678(0.771)	0.3233(0.8155)
				P₂	0.4341(0.5100)	0.3268(0.5676)	0.0704(0.7908)	0.0678(0.771)	0.3233(0.8155)
				RIL	0.0455(0.8311)	0.0049(0.9440)	1.2258(0.2682)	1.428(2.52E-04)	0.1279(3.00E-07)
小穗粒数 GSE	2017SY	H-1	4MG-AI	P₁	0.1133(0.7364)	0.5279(0.4675)	2.5687(0.1090)	0.1469(0.4011)	0.3086(0.2420)
				P₂	0.0564(0.8122)	0.0075(0.9312)	1.6016(0.2057)	0.0937(0.6285)	0.3291(0.7942)
				RIL	0.0036(0.9519)	0.0086(0.9261)	0.0188(0.8908)	0.0394(0.9364)	0.0315(0.7159)
	2017HY	H-1	4MG-AI	P₁	1.9215(0.1657)	0.1336(0.7148)	15.2622(9.36E-05)	0.5132(0.0375)	0.457(0.0199)
				P₂	0.0427(0.8363)	0.0469(0.8286)	2.7766(0.0957)	0.1411(0.4202)	0.2822(0.4653)
				RIL	0.0016(0.9677)	0.2173(0.6411)	4.0874(0.0432)	0.1458(0.4046)	0.0501(0.1760)
	2017SG	H-1	4MG-AI	P₁	0.2727(0.6015)	0.1454(0.7029)	0.247(0.6192)	0.1503(0.3902)	0.2221(0.4761)
				P₂	0.0023(0.9615)	0.0588(0.8083)	1.3396(0.2471)	0.0813(0.6955)	0.346(0.7437)
				RIL	0(0.9954)	0.0001(0.9917)	0.0004(0.9844)	0.0344(0.9596)	0.0275(0.8516)

性状Traits		穗长SL(cm)	小穗数SME	穗粒数GME	小穗粒数GSE
环境Environment		2017SY	2016SY	2016SY	2017SY	2017HY	2017SG
模型含义Implication of model		PG-AI	PG-AI	MX3-AI-A	4MG-AI	4MG-AI	4MG-AI
一阶参数估计值1^st order parameter Estimate (%)	m(m¹)	8.70	17.00	56.22	2.16	2.19	2.18
	m²	5.25	13.00	—	—	—	—
	m³	8.45	18.40	—	—	—	—
	d(da)	—	—	4.56	0.22	-0.12	-0.33
	db	—	—	-1.64	0.18	-0.12	0.16
	dc	—	—	4.56	-0.20	-0.07	0.06
	dd	—	—	—	0.24	-0.09	0.24
	iab (i*)	—	—	-6.02	-0.17	0.08	0.01
	iac	—	—	0.18	0.24	0.06	0.11
	iad	—	—	—	-0.20	0.08	0.19
	ibc	—	—	-6.02	0.03	0.06	-0.09
	ibd	—	—	—	-0.03	0.08	-0.03
	icd	—	—	—	0.06	0.03	-0.17
	iabc	—	—	-1.64	—	—	—
	[d]	—	—	0.15	—	—	—
二阶参数估计值2^nd order parameter Estimate (%)	σ²_e	0.35	0.57	0.80	0.07	0.01	0.06
	σ²_p	3.70	5.46	36.44	0.07	0.01	0.06
	σ²_mg	—	—	82.59	0.31	0.04	0.33
	h²_mg(%)	—	—	69.39	81.50	71.36	85.49
	σ²_pg	3.36	4.90	35.64	—	—	—
	h²_pg(%)	90.64	89.52	29.94	—	—	—

Genetic Analysis of Panicle Related Traits in Wheat with Major Gene Plus Polygenes Mixed Model

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