Zou Jun, Semagn Kassa, Iqbal Muhammad, Chen Hua, Asif Mohammad, N'Diaye Amidou, Navabi Alireza, Perez-Lara Enid, Pozniak Curtis, Yang Rong-Cai, Randhawa Harpinder, Spaner Dean
Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, Canada.
National Institute for Genomics and Advanced Biotechnology, National Agricultural Research Centre, Islamabad, Pakistan.
PLoS One. 2017 Feb 3;12(2):e0171528. doi: 10.1371/journal.pone.0171528. eCollection 2017.
Recently, we investigated the effect of the wheat 90K single nucleotide polymorphic (SNP) array and three gene-specific (Ppd-D1, Vrn-A1 and Rht-B1) markers on quantitative trait loci (QTL) detection in a recombinant inbred lines (RILs) population derived from a cross between two spring wheat (Triticum aestivum L.) cultivars, 'Attila' and 'CDC Go', and evaluated for eight agronomic traits at three environments under organic management. The objectives of the present study were to investigate the effect of conventional management on QTL detection in the same mapping population using the same set of markers as the organic management and compare the results with organic management. Here, we evaluated 167 RILs for number of tillers (tillering), flowering time, maturity, plant height, test weight (grain volume weight), 1000 kernel weight, grain yield, and grain protein content at seven conventionally managed environments from 2008 to 2014. Using inclusive composite interval mapping (ICIM) on phenotypic data averaged across seven environments and a subset of 1203 informative markers (1200 SNPs and 3 gene specific markers), we identified a total of 14 QTLs associated with flowering time (1), maturity (2), plant height (1), grain yield (1), test weight (2), kernel weight (4), tillering (1) and grain protein content (2). Each QTL individually explained from 6.1 to 18.4% of the phenotypic variance. Overall, the QTLs associated with each trait explained from 9.7 to 35.4% of the phenotypic and from 22.1 to 90.8% of the genetic variance. Three chromosomal regions on chromosomes 2D (61-66 cM), 4B (80-82 cM) and 5A (296-297 cM) harbored clusters of QTLs associated with two to three traits. The coincidental region on chromosome 5A harbored QTL clusters for both flowering and maturity time, and mapped about 2 cM proximal to the Vrn-A1 gene, which was in high linkage disequilibrium (0.70 ≤ r2 ≤ 0.75) with SNP markers that mapped within the QTL confidence interval. Six of the 14 QTLs (one for flowering time and plant height each, and two for maturity and kernel weight each) were common between the conventional and organic management systems, which suggests issues in directly utilizing gene discovery results based on conventional management to make in detail selection (decision) for organic management.
最近，我们研究了小麦90K单核苷酸多态性（SNP）芯片以及三个基因特异性（Ppd - D1、Vrn - A1和Rht - B1）标记对一个重组自交系（RILs）群体数量性状位点（QTL）检测的影响，该群体源自两个春小麦（Triticum aestivum L.）品种‘Attila’和‘CDC Go’的杂交，并在有机管理的三种环境下对八个农艺性状进行了评估。本研究的目的是使用与有机管理相同的一组标记，研究常规管理对同一作图群体QTL检测的影响，并将结果与有机管理进行比较。在此，我们在2008年至2014年的七个常规管理环境下，对167个RILs的分蘖数（分蘖）、开花时间、成熟度、株高、容重（谷物体积重量）、千粒重、籽粒产量和籽粒蛋白质含量进行了评估。利用对七个环境的表型数据进行平均，并结合1203个信息性标记（1200个SNP和3个基因特异性标记）的子集，通过包容性复合区间作图（ICIM），我们总共鉴定出14个与开花时间（1个）、成熟度（2个）、株高（1个）、籽粒产量（1个）、容重（2个）、粒重（4个）、分蘖（1个）和籽粒蛋白质含量（2个）相关的QTL。每个QTL单独解释了6.1%至18.4%的表型变异。总体而言，与每个性状相关的QTL解释了9.7%至35.4%的表型变异和22.1%至90.8%的遗传变异。2D染色体（61 - 66 cM）、4B染色体（80 - 82 cM）和5A染色体（296 - 297 cM）上的三个染色体区域含有与两到三个性状相关的QTL簇。5A染色体上的巧合区域含有开花和成熟时间的QTL簇，并且定位在Vrn - A1基因近端约2 cM处，该区域与位于QTL置信区间内的SNP标记处于高度连锁不平衡（0.70≤r2≤0.75）。14个QTL中的6个（每个开花时间和株高各1个，每个成熟度和粒重各2个）在常规和有机管理系统中是共同的，这表明在直接利用基于常规管理的基因发现结果进行有机管理的详细选择（决策）时存在问题。
