Liu Guifu, Zhang Zemin, Zhu Haitao, Zhao Fangming, Ding Xiaohua, Zeng Ruizhen, Li Wentao, Zhang Guiquan
Guangdong Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou 510642, People's Republic of China.
Theor Appl Genet. 2008 May;116(7):923-31. doi: 10.1007/s00122-008-0724-4. Epub 2008 Feb 15.
A novel population consisting of 35 single-segment substitution lines (SSSLs) originating from crosses between the recipient parent, Hua-jing-xian 74 (HJX74), and 17 donor parents was evaluated in six cropping season environments to reveal the genetic basis of genetic main effect (G) and genotype-by-environment interaction effect (GE) for panicle number (PN) in rice. Subsets of lines were grown in up to six environments. An indirect analysis method was applied, in which the total genetic effect was first partitioned into G and GE by using the mixed linear-model approach, and then QTL (quantitative trait locus) analyses on these effects were conducted separately. At least 18 QTLs for PN in rice were detected and identified on 9 of 12 rice chromosomes. A single QTL effect (a + ae) ranging from -1.5 to 1.2 was divided into two components, additive effect (a) and additive x environment interaction effect (ae). A total number of 9 and 16 QTLs were identified with a ranging from -0.4 to 0.6 and ae ranging from -1.0 to 0.6, respectively, the former being stable but the latter unstable across environments. Three types of QTLs were suggested according to their effects expressed. Two QTLs (Pn-1b and Pn-6d) expressed stably across environments due to the association with only a, nine QTLs (Pn-1a, Pn-3c, Pn-3d, Pn-4, Pn-6a, Pn-6b, Pn-8, Pn-9 and Pn-12) with only ae were unstable, and the remaining seven of QTLs were identified with both a and ae, which also were unstable across environments. This is the first report on the detection of QE (QTL-by-environment interaction effect) of QTLs with SSSLs. Our results illustrate the efficiency of characterizing QTLs and analyzing action of QTLs through SSSLs, and further demonstrate that QE is an important property of many QTLs. Information provided in this paper could be used in the application of marker-assisted selection to manipulate PN in rice.
一个由35个单片段代换系(SSSLs)组成的新型群体源自受体亲本华粳籼74(HJX74)与17个供体亲本的杂交,在六个种植季节环境中进行评估,以揭示水稻穗数(PN)的遗传主效应(G)和基因型与环境互作效应(GE)的遗传基础。部分品系在多达六个环境中种植。采用间接分析方法,首先利用混合线性模型方法将总遗传效应分解为G和GE,然后分别对这些效应进行QTL(数量性状位点)分析。在水稻12条染色体中的9条上检测并鉴定出至少18个控制水稻穗数的QTL。单个QTL效应(a + ae)范围为-1.5至1.2,分为两个组分,即加性效应(a)和加性×环境互作效应(ae)。共鉴定出9个和16个QTL,a范围为-0.4至0.6,ae范围为-1.0至0.6,前者在不同环境中稳定,后者不稳定。根据其表达效应提出了三种类型的QTL。两个QTL(Pn-1b和Pn-6d)因仅与a相关而在不同环境中稳定表达,9个QTL(Pn-1a、Pn-3c、Pn-3d、Pn-4、Pn-6a、Pn-6b、Pn-8、Pn-9和Pn-12)仅与ae相关,不稳定,其余7个QTL同时具有a和ae,在不同环境中也不稳定。这是关于利用SSSLs检测QTL的QE(QTL与环境互作效应)的首次报道。我们的结果说明了通过SSSLs表征QTL和分析QTL作用的效率,并进一步证明QE是许多QTL的重要特性。本文提供的信息可用于应用标记辅助选择来调控水稻的穗数。