宁麦9号/扬麦158重组自交系群体产量性状的遗传解析

doi:10.3724/SP.J.1006.2021.01051

Abstract

Abstract:

Ningmai 9 and Yangmai 158 are the main commercial wheat varieties, as well as the backbone parents in wheat breeding programs in the middle and lower reaches of the Yangtze River in China. Both of them have high yield potential, while they showed significant difference in yield components. To understand the genetic mechanism of their high yield potential, 282 recombinant inbred lines (RILs) derived from the cross between Ningmai 9 and Yangmai 158 were genotyped with the Illumina iSelect 90K wheat single nucleotide polymorphism (SNP) assay to construct a high-density genetic map. Yield (YD) and yield-related traits including spike number (SN), kernel number per spike (KN), and 1000-kernel weight (TKW) were evaluated for three consecutive growing seasons. The results indicated that the KN of Ningmai 9 was higher than that of Yangmai 158, while TKW was lower than that of Yangmai 158. In total, 9, 8, 10, and 12 QTLs associated with SN, KN, TKW and YD were identified by QTL mapping, respectively. Among these traits, TKW possessed the highest heritability, and three QTL associated with TKW were identified repetitively. The markers related to such QTLs were then transferred to Kompetitive Allele Specific PCR (KASP) markers for high throughput selection in 139 wheat accessions. It was indicated that pyramiding 2 or 3 QTLs was more effective than single QTL for TKW improvement. The results in this study could provide more information for marker assisted selection in wheat yield breeding program.

Key words: wheat (Triticum aestivum L.), Ningmai 9, Yangmai 158, yield, KASP marker

JIANG Peng, ZHANG Xu, WU Lei, HE Yi, ZHANG Ping-Ping, MA Hong-Xiang, KONG Ling-Rang. Genetic analysis for yield related traits of wheat (Triticum aestivum L.) based on a recombinant inbred line population from Ningmai 9 and Yangmai 158[J].Acta Agronomica Sinica, 2021, 47(5): 869-881.

Figures/Tables 9

Table 1

Table 2

Table 3

Table 4

QTL analysis of yield and its components"

性状 Traits	序号No.	QTL	环境 Environment	遗传位置 Genetic position (cM)	物理区间 Physical interval (Mb)	区间 Interval	LOD	表型贡献率 PVE^a(%)	加性效应 AE^b	前人研究中的产量相关性状 Yield-related traits in previous studies
穗数 Spike number	1	Qsn-1A	2018	101.45-101.95	543-574	Tdurum_contig96086_74-RFL_Contig3683_1784	4.85	7.54	-27.00	产量、穗粒数、单穗产量、收获指数^[19] Yield, kernel number per spike, kernel weight per spike, harvest index^[19]
	2	Qsn-1B.1	2016	6.35-11.15	614-616	wsnp_BE590634B_Ta_2_5-Tdurum_contig10362_555	4.03	5.11	19.22	产量^[20] Yield^[20]
	3	Qsn-1B.2	2016	15.95-20.55	630-641	BS00069044_51-wsnp_Ex_rep_c78209_74462664	7.40	10.39	-29.21	穗长、千粒重、穗粒数^[21,22] Spike length, 1000-kernel weight, kernel number per spike^[21,22]
	4	Qsn-1B.3	2017	97.75-98.25	678-680	BobWhite_c4482_73-Tdurum_contig52086_342	2.97	3.45	-19.25	千粒重^[23] 1000-kernel weight^[23]
	5	Qsn-2B	2017	78.05-79.35	781-783	Ku_c2936_1987-RAC875_c18928_455	3.21	3.68	19.78	—
	6	Qsn-4B	2016	14.95-15.95	603-620	BS00039402_51-Excalibur_rep_c109675_738	3.44	3.62	14.41	—
	7	Qsn-5A	2017	49.45-50.35	505-520	tplb0056b09_1000-BS00085826_51	6.27	7.56	28.32	千粒重、穗粒数^[23] 1000-kernel weight, kernel number per spike^[23]
	8	Qsn-7A.1	2017	38.25-39.45	688-697	Tdurum_contig31699_276-wsnp_Ku_c4035_7363089	3.18	4.48	24.15	千粒重^[23] 1000-kernel weight^[23]
	9	Qsn-7A.2	2017	108.35-111.1	730-735	BS00069019_51-BS00022284_51	3.74	4.66	-22.28	—
穗粒数 Kernel number per spike	10	Qkn-2B	2016	68.25-69.35	768-776	Kukri_c24939_378-RAC875_rep_c83950_222	3.69	5.84	-1.75	—
	12	Qkn-3B.1	2018	105.45-105.85	146-151	RAC875_c45525_131-IAAV1079	6.10	8.66	-3.41	—
	11	Qkn-3B.2	2017	62.95-65.35	724-742	BobWhite_c2937_1426-BS00040739_51	3.08	4.42	-1.88	穗数、产量^[5] Spike number, yield^[5]
	13	Qkn-4A	2017	4.05-14.95	664-683	BS00066066_51-IAAV5722	2.76	5.03	1.76	穗粒数、穗数、千粒重^[23,24] Kernel number per spike, spike number, 1000-kernel weight^[23,24]
	14	Qkn-5B.1	2018	91.25-93.35	615-618	Tdurum_contig85060_121-Kukri_rep_c101622_604	3.78	5.30	1.60	产量^[25] Yield^[25]
	15	Qkn-5B.2	2017	129.35-130.05	682-698	Excalibur_c6346_266-IAAV8023	3.06	4.40	-1.77	千粒重、穗粒数^[23] 1000-kernel weight, kernel number per spike^[23]
	16	Qkn-6B	2016	49.35-50.95	96-141	RAC875_c23812_187-wsnp_Ku_c12559_20252463	3.02	5.18	1.64	—
	17	Qkn-7A	2018	0-7.05	670-680	Ku_c62742_888-wsnp_Ku_c42539_50247333	2.68	3.76	-1.40	千粒重、穗粒数、穗数^[23] 1000-kernel weight, kernel number per spike, spike number^[23]
千粒重 1000-kernel weight	18	Qtkw-1A	2016	47.05-48.95	31-33	BS00084022_51-wsnp_Ex_c31983_40709866	3.08	3.60	0.76	千粒重、单穗产量、穗粒数^[23,26] 1000-kernel weight, kernel weight per spike, kernel number per spike^[23,26]
	19	Qtkw-1B	2017/2018	35.25-39.55	640-653	IAAV1683-IAAV565	3.68	5.80	-1.15	穗长、千粒重、穗粒数^[21] Spike length, 1000-kernel weight, kernel number per spike^[21]
	20	Qtkw-2B	2018	51.45-52.05	748-750	CAP8_c8516_542-BS00094578_51	8.09	9.43	1.06	千粒重^[24] 1000-kernel weight^[24]
	21	Qtkw-3A	2016	0-6.15	9-10	Excalibur_c10014_307-RAC875_c36922_829	3.29	3.71	0.88	—
	22	Qtkw-4A	2016/2017	3.75-19.75	661-683	BS00066066_51-BS00066891_51	5.55	6.42	-1.02	穗粒数、穗数、千粒重^[23,24] Kernel number per spike, spike number, 1000-kernel weight^[23,24]
	23	Qtkw-4B	2018	4.85-5.05	427-428	GENE-2847_1060-wsnp_Ex_rep_c70265_69211592	7.90	8.82	-1.02	千粒重^[27] 1000-kernel weight^[27]
	24	Qtkw-5A	2016	55.85-56.55	537-539	BS00096758_51-RAC875_c103967_76	7.51	8.85	1.20	千粒重、穗粒数^[23] 1000-kernel weight, kernel number per spike^[23]
	25	Qtkw-5B	2018	67.15-70.95	586-587	Kukri_c45964_273-RAC875_c43383_483	2.88	3.10	-0.65	穗粒数^[28] Kernel number per spike^[28]
	26	Qtkw-7A	2017/2018	48.55-49.55	261-285	RFL_Contig428_290-RAC875_c16624_970	4.21	4.57	-0.79	—
	27	Qtkw-7B	2016	0-4.95	15-25	wsnp_CAP7_c44_26549-Ex_c101666_634	4.74	5.99	-0.99	产量、小穗数^[20,28] Yield, the spikelet number per spike^[20,28]
产量 Yield	28	Qyd-1B.1	2017	37.55-38.65	236-433	BobWhite_c4147_1429-BS00033681_51	5.40	5.33	441.75	千粒重、单穗产量、产量^[29,30] 1000-kernel weight, kernel weight per spike, yield^[29,30]
	29	Qyd-1B.2	2017	65.55-73.25	480-498	Ra_c68984_1882-Tdurum_contig81102_102	4.27	4.17	-611.83	—
	30	Qyd-2A	2018	47.85-55.05	653-706	BS00090569_51-BS00029332_51	3.87	6.19	332.86	单株产量、小穗数、千粒重、穗粒数^[31] Kernel weight per plant, the spikelet number per spike, 1000-kernel weight, kernel number per spike^[31]
	31	Qyd-4B	2017	68.85-70.45	101-168	BS00071792_51-Tdurum_contig28490_463	3.26	3.23	337.82	穗粒数、单穗产量、千粒重^[5,23,32] Kernel number per spike, kernel weight per spike, 1000-kernel weight^[5,23,32]
	32	Qyd-5A.1	2016	13.35-14.55	389-420	BS00086963_51-BS00001322_51	4.11	7.91	242.37	千粒重、穗粒数^[23] 1000-kernel weight, kernel number per spike^[23]
	33	Qyd-5A.2	2017	53.35-54.45	511-540	wsnp_Ex_c49211_53875575-CAP7_c1404_72	10.88	11.79	642.73	千粒重、穗粒数^[23] 1000-kernel weight, kernel number per spike^[23]
	34	Qyd-5B.1	2018	45.15-46.15	545-547	Tdurum_contig25513_195-wsnp_Ex_c8659_14515623	3.59	4.45	-418.08	产量^[27] Yield^[27]
	35	Qyd-5B.2	2017	113.05-113.85	663-665	BobWhite_c36154_81-Kukri_c41_858	4.87	4.80	-285.41	—
	36	Qyd-6A	2017	35.35-38.2	609-617	Excalibur_c96749_512-Excalibur_c98257_136	3.82	3.88	-408.26	产量、千粒重^[20,23] Yield, 1000-kernel weight^[20,23]
	37	Qyd-6B	2018	53.35-53.75	144-148	BobWhite_c1905_98-wsnp_Ku_c5891_10414090	3.08	3.88	-281.40	—
	38	Qyd-7A	2018	33.25-34.25	83-109	Excalibur_rep_c101407_222-BS00011072_51	2.92	3.60	-256.01	穗重、千粒重、穗粒数、穗数^[23,33-34] Ear weight per tiller, 1000-kernel weight, kernel number per spike, spike number^[23,33-34]
	39	Qyd-7B	2018	133.15-133.95	743-745	Tdurum_contig51105_1538-tplb0040b02_681	4.36	5.48	313.01	产量、千粒重^[20,23] Yield, 1000-kernel weight^[20,23]

Table 4

Fig. 1

Table 5

Table S1

Fig. S1

Table 6

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性状 Trait	年份 Year	宁麦9号 Ningmai 9	扬麦158 Yangmai 158	重组自交系群体 RIL population					遗传力 Heritability
性状 Trait	年份 Year	宁麦9号 Ningmai 9	扬麦158 Yangmai 158	最大值 Max.	最小值 Min.	平均值 Mean	标准差 SD	变异系数 CV (%)	遗传力 Heritability
穗数 Spike number (×10⁴ hm^-2)	2016	197.30	292.21	729.27	137.36	343.77	84.10	24.46	0.13
	2017	549.45	412.09	779.22	252.25	497.33	96.53	19.41
	2018	479.52	534.47	816.68	249.75	495.31	94.39	19.06
穗粒数 Kernel number per spike	2016	69.00	53.33	75.14	32.00	52.53	7.18	13.68	0.37
	2017	65.00	58.40	82.80	37.60	63.31	7.98	12.60
	2018	52.20	46.60	74.00	31.00	44.17	6.36	14.40
千粒重 1000-kernel weight (g)	2016	32.55	35.48	47.63	21.75	34.98	3.90	11.16	0.60
	2017	30.98	32.94	51.96	25.37	35.55	4.50	12.67
	2018	40.40	47.01	50.62	31.51	41.79	3.27	7.82
产量 Yield (kg hm^-2)	2016	3238.43	3887.78	7251.08	1506.83	3903.92	940.63	24.09	0.18
	2017	6018.98	4920.08	11,163.83	2006.33	6492.86	1752.69	26.99
	2018	6993.00	8658.00	12,321.00	3330.00	7128.55	1420.14	19.92

项目 Item	穗数 Spike number (×10⁴ hm^-2)	穗粒数 Kernel number per spike	千粒重 1000-kernel weight (g)	产量 Yield (kg hm^-2)
基因型 Genotype	0.78	1.92^**	2.64^**	0.86
年份 Year	214.54^**	754.62^**	415.05^**	320.18^**
基因型×年份 Genotype×Year	0.64	1.21	1.06	0.64

性状 Trait	环境 Environment	穗数 Spike number (×10⁴ hm^-2)	穗粒数 Kernel number per spike	千粒重 1000-kernel weight (g)	产量 Yield (kg hm^-2)
穗数 Spike number (×10⁴ hm^-2)	2016	(0.136^*)
	2017	(0.128^*)
	2018	(-0.042)
穗粒数 Kernel number per spike	2016	-0.154^**	(0.081)
	2017	-0.157^**	(0.344^**)
	2018	-0.054	(-0.014)
千粒重 1000-kernel weight (g)	2016	-0.004	-0.131^*	(0.316^**)
	2017	-0.025	-0.284^**	(0.364^**)
	2018	-0.171^**	-0.146^**	(0.288^**)
产量 Yield (kg hm^-2)	2016	0.169^**	-0.077	0.289^**	(0.242^**)
	2017	0.418^**	-0.201^**	0.439^**	(0.052)
	2018	0.312^**	0.306^**	0.085	(0.120^*)

QTL	环境 Environment	优势等位变异 Favorable alleles (g)	非优势等位变异 Unfavorable alleles (g)	差值 Difference (g)	t值 t-value	P值 P-value
Qtkw-1B	2016	35.21 (121)	34.56 (133)	0.65	1.36	0.18
	2017	36.47 (121)	34.62 (133)	1.85	3.31	<0.01
	2018	42.37 (121)	40.95 (133)	1.42	3.56	<0.01
Qtkw-4A	2016	35.68 (110)	33.71 (98)	1.97	3.86	<0.01
	2017	36.48 (110)	34.41 (98)	2.07	3.41	<0.01
	2018	42.38 (110)	40.68 (98)	1.7	3.94	<0.01
Qtkw-7A	2016	34.78 (168)	35.03 (78)	-0.25	-0.47	0.64
	2017	36.31 (168)	34.46 (78)	1.85	2.97	<0.01
	2018	42.02 (168)	41.30 (78)	0.72	1.38	0.17
Qtkw-1B+Qtkw-4A	2016	36.62 (46)	33.48 (51)	3.14	4.22	<0.01
	2017	37.03 (46)	33.59 (51)	3.44	4.11	<0.01
	2018	43.32 (46)	40.56 (51)	2.76	4.24	<0.01
Qtkw-1B+Qtkw-7A	2016	35.42 (74)	35.48 (34)	-0.06	-0.09	0.93
	2017	37.51 (74)	33.58 (34)	3.93	4.26	<0.01
	2018	42.82 (74)	40.79 (34)	2.03	2.98	<0.01
Qtkw-4A+Qtkw-7A	2016	35.46 (68)	33.73 (34)	1.73	2.11	0.04^*
	2017	37.42 (68)	34.56 (34)	2.86	3.04	<0.01
	2018	42.27 (68)	40.51 (34)	1.76	2.85	<0.01
Qtkw-1B+Qtkw-4A+Qtkw-7A	2016	36.55 (26)	33.73 (12)	2.82	2.14	0.04^*
	2017	38.42 (26)	33.08 (12)	5.34	5.22	<0.01
	2018	43.10 (26)	41.16 (12)	1.94	1.55	0.14

SNP	QTL	F1 (5°-3°)	F2 (5°-3°)	R (5°-3°)
Kukri_c18109_682	Qtkw-1B	AACGACGCCTGGTTTTCCTCA	CGACGCCTGGTTTTCCTCG	TCCGAGATGGACGAGGAACTG
IAAV1683	Qtkw-1B	TGTTCTTACCTGAACTTGTGTGACA	GTTCTTACCTGAACTTGTGTGACG	CTGAAGCTCTGATATCATCATCATCC
Kukri_c42354_263	Qtkw-1B	TCGACGATACTGGCGGTGTA	TCGACGATACTGGCGGTGTG	TGATCGCAAAGTGCATTATGTT
BS00066891_51	Qtkw-4A	TGGACGGATGGTTGATGGCTCG	ATGGACGGATGGTTGATGGCTCA	TATAAGCTACTACCGCTCCGGC
IAAV5722	Qtkw-4A	AGCTGCAACCCATCCTCT	AGCTGCAACCCATCCTCC	TGTGACCTACTCGATGTTCATAAC
Excalibur_rep_c70004_275	Qtkw-7A	GGTGTTCTCCCTGGTAGCTCA	GGTGTTCTCCCTGGTAGCTCG	CTTCTGGCACCTGCTTTCATCG
RFL_Contig428_290	Qtkw-7A	GGATGTCCCGGTTGGAGAAGAC	GGATGTCCCGGTTGGAGAAGAT	GACAAGTACGGCCCCATCTTCT
IACX1477	Qtkw-7A	CCAAAATGGCTTGTCAAATGAGATA	CCAAAATGGCTTGTCAAATGAGA TG	GCTTGACCCTTAGCTCATGA

Genetic analysis for yield related traits of wheat (Triticum aestivum L.) based on a recombinant inbred line population from Ningmai 9 and Yangmai 158

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QTL	优势等位变异 Favorable alleles (g)	非优势等位变异 Unfavorable alleles (g)	差值 Difference (g)	t值 t-value	P值 P-value
Qtkw-1B	48.32 (62)	45.92 (77)	2.40	-3.79	<0.01
Qtkw-4A	47.67 (100)	45.26 (39)	2.41	3.40	<0.01
Qtkw-7A	47.47 (122)	43.53 (17)	3.95	-4.15	<0.01
Qtkw-1B+Qtkw-4A	48.73 (49)	44.49 (26)	4.23	4.61	<0.01
Qtkw-1B+Qtkw-7A	48.43 (60)	43.32 (15)	5.11	-4.73	<0.01
Qtkw-4A+Qtkw-7A	47.67 (98)	43.01 (15)	4.66	-4.59	<0.01
Qtkw-1B+Qtkw-4A+Qtkw-7A	48.73 (49)	42.69 (13)	6.03	-5.27	<0.01

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