Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen, AB24 3UU, UK.
National Omics Center, National Science and Technology Development Agency (NSTDA), Pathum Thani, 12120, Thailand.
Heredity (Edinb). 2021 Mar;126(3):505-520. doi: 10.1038/s41437-020-00390-w. Epub 2020 Nov 24.
Manganese (Mn) is an essential trace element for plants and commonly contributes to human health; however, the understanding of the genes controlling natural variation in Mn in crop plants is limited. Here, the integration of two of genome-wide association study approaches was used to increase the identification of valuable quantitative trait loci (QTL) and candidate genes responsible for the concentration of grain Mn across 389 diverse rice cultivars grown in Arkansas and Texas, USA, in multiple years. Single-trait analysis was initially performed using three different SNP datasets. As a result, significant loci could be detected using the high-density SNP dataset. Based on the 5.2 M SNP dataset, major QTLs were located on chromosomes 3 and 7 for Mn containing six candidate genes. In addition, the phenotypic data of grain Mn concentration were combined from three flooded-field experiments from the two sites and 3 years using multi-experiment analysis based on the 5.2 M SNP dataset. Two previous QTLs on chromosome 3 were identified across experiments, whereas new Mn QTLs were identified that were not found in individual experiments, on chromosomes 3, 4, 9 and 11. OsMTP8.1 was identified in both approaches and is a good candidate gene that could be controlling grain Mn concentration. This work demonstrates the utilisation of multi-experiment analysis to identify constitutive QTLs and candidate genes associated with the grain Mn concentration. Hence, the approach should be advantageous to facilitate genomic breeding programmes in rice and other crops considering QTLs and genes associated with complex traits in natural populations.
锰(Mn)是植物必需的微量元素,通常对人类健康有益;然而,对于控制作物中天然锰变异的基因的理解是有限的。在这里,整合了两种全基因组关联研究方法,用于增加对控制美国阿肯色州和德克萨斯州 389 个不同水稻品种中粒锰浓度的有价值的数量性状位点(QTL)和候选基因的识别,这些品种在多年来进行了多次种植。首先使用三种不同的 SNP 数据集进行单性状分析。结果表明,使用高密度 SNP 数据集可以检测到显著的位点。基于 5.2M SNP 数据集,在第 3 和第 7 号染色体上定位到包含六个候选基因的 Mn 主要 QTL。此外,使用基于 5.2M SNP 数据集的多实验分析,将来自两个地点和 3 年的三个淹水田间实验的粒锰浓度表型数据进行了组合。在跨实验中鉴定到了三个染色体 3 上的先前 QTL,而在新的染色体 3、4、9 和 11 上鉴定到了在个别实验中未发现的新的 Mn QTL。在这两种方法中都鉴定到了 OsMTP8.1,它是一个控制粒锰浓度的候选基因。这项工作展示了利用多实验分析来鉴定与粒锰浓度相关的组成性 QTL 和候选基因的方法。因此,该方法应该有利于促进水稻和其他作物的基因组育种计划,考虑与自然群体中复杂性状相关的 QTL 和基因。