川麦42和川农16抗穗发芽QTL定位及聚合效应分析

doi:10.3864/j.issn.0578-1752.2020.17.001

摘要/Abstract

摘要：

【目的】小麦穗发芽严重影响小麦产量和品质,是全球小麦生产面临的重大问题之一。通过鉴定挖掘抗穗发芽QTL,聚合穗发芽抗性位点,选育抗穗发芽小麦品种,为四川小麦穗发芽抗性改良提供技术和材料支撑。【方法】以川麦42/川农16重组自交系（RIL,F₈）为材料,于2016—2018年分别在2个环境下对RIL群体进行籽粒发芽指数（GI,2016和2018）、籽粒发芽率（GR,2016和2018）和整穗发芽率（SGR,2017和2018）3个穗发芽指标测定。利用90K SNP芯片构建的遗传图谱检测全基因组穗发芽相关QTL,并分析抗性QTL聚合效应。【结果】双亲间GI、GR和SGR指标值差异显著,亲本川农16穗发芽抗性明显优于亲本川麦42。共检测到11个与穗发芽抗性有关的QTL,主要分布在2B、2D、3A、3D、4A、5A、5B和6B染色体上。5B染色体上检测到的单个环境表达的整穗发芽QTL解释的表型变异率最大,达到29%;在2D和3A染色体上检测到的整穗发芽主效QTL,以及5A染色体上检测到的与种子休眠相关的籽粒发芽主效QTL,在2个环境下均能表达,其抗穗发芽等位变异均来源于川农16。基因型分析发现,RIL群体中不同株系聚合抗性QTL的数量变幅为1—9个,表现为抗穗发芽的株系均携带4—9个与穗发芽相关的抗性QTL。重组自交系群体中6个株系GI、GR和SGR值均在15%以下,表现出高抗穗发芽特性;这6个优异株系聚合了多个与穗发芽相关的抗性QTL,且均聚合了川麦42在4A染色体上的微效QTL（QGi.saas-4A和QGr.saas-4A）,以及川农16在2D和5B染色体上的主效QTL（QSgr.saas-2D和QSgr.saas-5B）;编号为104和125的优异株系已通过审定,定名为川麦104和川麦64。其中,川麦104于2012年同时通过国家和四川省审定,其抗穗发芽能力强,产量、品质、抗病等优良性状突出,聚合了7个正向穗发芽QTL,包括2B、2D和5B染色体上来源于川农16的4个抗性QTL（QGi.saas-2B、QGr.saas-2B、QSgr.saas-2D和QSgr.saas-5B）,以及4A和6B染色体上来源于川麦42的3个QTL（QGi.saas-4A、QGr.saas-4A和QGr.saas-6B）;近年来,川麦104已成为西南麦区小麦育种的核心亲本,育成小麦品种（系）18个。【结论】共检测到11个抗穗发芽QTL,其中3个来源于川麦42,8个来源于川农16;RIL群体中的抗穗发芽株系均携带4—9个抗性QTL,优异株系川麦104和川麦64高抗穗发芽,均聚合了7个穗发芽抗性QTL。

关键词: 小麦, 穗发芽, QTL定位, QTL聚合, 聚合效应

Abstract:

【Objective】Pre-harvest sprouting (PHS) is one of the serious problems for wheat production, which significantly reduces grain yield and end-use quality, especially in rainy or high humidity regions. The objective of this study is to identify and aggregate quantitative trait loci (QTLs) for traits associated with PHS resistance, which will provide a theoretical basis for improving PHS resistance in Sichuan wheat cultivars.【Method】A recombinant inbred line (RIL) population derived from Chuanmai 42 and Chuannong 16 was used to detect QTL and assess the new germplasm resources for PHS resistance. 127 lines in RIL population were analyzed by phenotypic and genetic identification for PHS-related traits. Seed germination index (GI), seed germination rate (GR) and seed germination rate of in each spike (SGR) in two different environments were used to evaluate PHS resistance. All QTLs for PHS resistance were mapped by an available high-density single nucleotide polymorphism (SNP, 90K). The pyramiding of the resistant QTL was also analyzed according to the genotype of every line in RILs. 【Result】There were significant difference in GI, GR and SGR between two parents. PHS resistance of Chuannong 16 was superior than that of Chuanmai 42. A total of 11 QTLs for PHS were detected on chromosomes 2B, 2D, 3A, 3D, 4A, 5A, 5B and 6B. QSgr.saas-5B was significantly associated with PHS resistance in single environment and explained 29.03% phenotypic variation. QSgr.saas-2D, QSgr.saas-3A, QGi.saas-5A and QGr.saas-5A could express stably in two environments, and the alleles of enhancing PHS resistance were from Chuannong 16. The results of genotype analysis showed that the number of resistant QTL in different lines ranged from one to nine. Six excellent lines in RILs with high resistance carried seven or eight additive QTLs for PHS resistance. These additive QTLs included the minor QTLs on chromosome 4A from Chuanmai 42 and the major QTLs on chromosomes 2D and 5B from Chuannong 16. No. 104 and No. 125 in RIL population were released in China or Sichuan province because of its high yield and PHS resistance, and were named Chuanmai 104 and Chuanmai 64, respectively. Chuanmai 104 showed high yield and good resistance for stripe rust, powdery mildew and PHS in the Sichuan provincial trials and the national trails for Upper and Middle Yangtze River region in 2010 and 2012. The QTL analysis for PHS resistance revealed that Chuanmai 104 carried seven QTLs, including four QTLs on chromosomes 2B, 2D and 5B from Chuannong 16 and three QTLs on chromosomes 4A and 6B from another parent Chuanmai 42. The pyramiding of these additive QTL alleles from each parent led directly to the character of high PHS resistance in Chuanmai 104. In recent years, Chuanmai 104 was widely used to wheat improvement in Southwest China, and 18 wheat varieties (lines) have been bred. 【Conclusion】Eleven QTLs for PHS resistance, including three QTLs from Chuanmai 42 and eight QTLs from chuannong16, were detected in this study. Four to nine resistant QTLs were generally carried by the resistant lines in RIL population. Two pyramiding lines (Chuanmai 104 and Chuanmai 64) with high PHS resistance carried seven resistant QTLs.

Key words: wheat, pre-harvest sprouting (PHS), QTL mapping, QTL pyramiding, pyramiding effect

王琴,刘泽厚,万洪深,魏会廷,龙海,李涛,邓光兵,李俊,杨武云. 川麦42和川农16抗穗发芽QTL定位及聚合效应分析[J]. 中国农业科学, 2020, 53(17): 3421-3431.

WANG Qin,LIU ZeHou,WAN HongShen,WEI HuiTing,LONG Hai,LI Tao,DENG GuangBing,LI Jun,YANG WuYun. Identification and Pyramiding of QTLs for Traits Associated with Pre-Harvest Sprouting Resistance in Two Wheat Cultivars Chuanmai 42 and Chuannong 16[J]. Scientia Agricultura Sinica, 2020, 53(17): 3421-3431.

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性状 Trait	环境 Environment	亲本Parents		RIL群体 RIL population
性状 Trait	环境 Environment	川麦42 Chuanmai 42	川农16 Chuannong 16	均值 Mean	标准差 SD	最小值 Min	最大值 Max	峰度 Kurtosis	偏度 Skewness	遗传力Heritability
GI	2016GH	0.74	0.11**	0.57	0.10	0.06	0.98	-0.02	-0.27	0.57
GI	2018CD	0.76	0.17**	0.59	0.20	0.05	0.87	-0.54	-0.66	0.49
GR	2016GH	0.83	0.24**	0.82	0.09	0.07	1.00	-0.09	-0.57	0.82
GR	2018CD	0.86	0.21**	0.79	0.23	0.06	1.00	0.68	-1.21	0.69
SGR	2017CD	0.62	0.15**	0.52	0.17	0.02	0.90	-0.35	-0.28	0.61
SGR	2018CD	0.51	0.09**	0.42	0.21	0.03	0.99	-0.70	0.12	0.51

性状Trait	GI-2018CD	GR-2016GH	GR-2018CD	SGR-2017CD	SGR-2018CD
GI-2016GH	0.091	0.892**	0.037	0.177*	0.266**
GI-2018CD		0.169	0.966**	0.239**	0.289**
GR-2016GH			0.114	0.247**	0.258**
GR-2018CD				0.201*	0.224*
SGR-2017CD					0.440**

性状 Trait	QTL	环境 Environment	标记区间 Marker interval	LOD	贡献率 PVE (%)	加性效应 Additive effect^a
GI	QGi.saas-2B	2016GH	IWB217—IWB12070	2.64	9.47	0.05
	QGi.saas-4A	2016GH	IWB32870—IWB43187	2.50	4.28	-0.03
	QGi.saas-5A	2016GH	IWB22536—IWB43493	2.51	5.88	0.09
	QGi.saas-5A	2018CD	IWB6853—IWB25919	3.98	14.72	0.13
GR	QGr.saas-2B	2016GH	IWB217—IWB12070	2.59	5.02	0.03
	QGr.saas-4A	2016GH	IWB32870—IWB43187	2.51	4.79	-0.04
	QGr.saas-5A	2016GH	IWB22536—IWB43493	2.65	4.87	0.06
	QGr.saas-5A	2018CD	IWB6853—IWB25919	5.10	18.80	0.15
	QGr.saas-6B	2016GR	IWB8673—IWB22066	11.02	14.26	-0.05
SGR	QSgr.saas-2D	2017CD	IWB62848—IWB56618	3.29	8.06	0.05
	QSgr.saas-2D	2018CD	IWB9680—IWB62848	2.54	5.73	0.05
	QSgr.saas-3A	2017CD	IWB10578—IWB30094	2.57	4.72	0.04
	QSgr.saas-3A	2018CD	IWB10578—IWB30094	3.60	10.86	0.07
	QSgr.saas-3D	2017CD	IWB30686—IWB38826	4.69	11.96	0.06
	QSgr.saas-5B	2018CD	IWB60217—IWB52109	12.36	29.03	0.16

株系 Lines	GI (%)		GR (%)		SGR (%)		QTL
株系 Lines	2016GH	2018CD	2016GH	2018CD	2017CD	2018CD	QTL
12	0.14	0.12	0.12	0.15	0.07	0.05	QGi.saas-2B, QGr.saas-2B, QSgr.saas-2D, QSgr.saas-3A, QSgr.saas-3D, QGi.saas-4A, QGr.saas-4A, QSgr.saas-5B
74	0.13	0.10	0.13	0.15	0.02	0.03	QGi.saas-2B, QGr.saas-2B, QSgr.saas-2D, QSgr.saas-3D, QGi.saas-4A, QGr.saas-4A, QSgr.saas-5B, QGr.saas-6B
82	0.09	0.05	0.12	0.13	0.14	0.07	QGi.saas-2B, QGr.saas-2B, QSgr.saas-2D, QSgr.saas-3A, QGi.saas-4A, QGr.saas-4A, QSgr.saas-5B
104	0.07	0.12	0.10	0.14	0.13	0.11	QGi.saas-2B, QGr.saas-2B, QSgr.saas-2D, QGi.saas-4A, QGr.saas-4A, QSgr.saas-5B, QGr.saas-6B
112	0.06	0.09	0.13	0.11	0.14	0.15	QSgr.saas-2D, QSgr.saas-3D, QGi.saas-4A, QGr.saas-4A, QSgr.saas-5B, QGi.saas-5A, QGr.saas-5A
125	0.08	0.10	0.07	0.11	0.09	0.07	QSgr.saas-2D, QSgr.saas-3A, QSgr.saas-3D, QGi.saas-4A, QGr.saas-4A, QSgr.saas-5B, QGr.saas-6B