Department of Soil, Plant and Food Sciences, Genetics and Plant Breeding Section, University of Bari, Bari, Italy.
Department of Agricultural and Environmental Science, Research Unit of "Genetics and Plant Biotechnology", University of Bari, Bari, Italy.
Planta. 2019 Apr;249(4):1157-1175. doi: 10.1007/s00425-018-03075-1. Epub 2019 Jan 2.
Stable QTL for grain protein content co-migrating with nitrogen-related genes have been identified by the candidate genes and genome-wide association mapping approaches useful for marker-assisted selection. Grain protein content (GPC) is one of the most important quality traits in wheat, defining the nutritional and end-use properties and rheological characteristics. Over the years, a number of breeding programs have been developed aimed to improving GPC, most of them having been prevented by the negative correlation with grain yield. To overcome this issue, a collection of durum wheat germplasm was evaluated for both GPC and grain protein deviation (GPD) in seven field trials. Fourteen candidate genes involved in several processes related to nitrogen metabolism were precisely located on two high-density consensus maps of common and durum wheat, and six of them were found to be highly associated with both traits. The wheat collection was genotyped using the 90 K iSelect array, and 11 stable quantitative trait loci (QTL) for GPC were detected in at least three environments and the mean across environments by the genome-wide association mapping. Interestingly, seven QTL were co-migrating with N-related candidate genes. Four QTL were found to be significantly associated to increases of GPD, indicating that selecting for GPC could not affect final grain yield per spike. The combined approaches of candidate genes and genome-wide association mapping led to a better understanding of the genetic relationships between grain storage proteins and grain yield per spike, and provided useful information for marker-assisted selection programs.
通过候选基因和全基因组关联图谱的方法，已经鉴定出与氮相关基因共迁移的稳定的籽粒蛋白质含量（GPC）的 QTL，这对于标记辅助选择非常有用。籽粒蛋白质含量（GPC）是小麦最重要的品质特性之一，决定了营养和用途特性以及流变学特性。多年来，已经开发了许多旨在提高 GPC 的育种计划，其中大多数都因与籽粒产量的负相关而受阻。为了克服这个问题，对硬粒小麦种质资源进行了 GPC 和籽粒蛋白偏差（GPD）的评估，在七个田间试验中进行了评估。与氮代谢相关的几个过程涉及的 14 个候选基因被精确定位在普通小麦和硬粒小麦的两个高密度共识图谱上，其中 6 个基因与这两个性状高度相关。利用 90K iSelect 阵列对小麦进行了基因型分析，并通过全基因组关联图谱在至少三个环境和环境平均值中检测到 11 个稳定的 GPC 数量性状位点（QTL）。有趣的是，有 7 个 QTL 与 N 相关的候选基因共迁移。发现 4 个 QTL 与 GPD 的增加显著相关，这表明选择 GPC 不会影响每个穗粒的最终产量。候选基因和全基因组关联图谱的综合方法有助于更好地理解谷物贮藏蛋白和每个穗粒产量之间的遗传关系，并为标记辅助选择计划提供了有用的信息。
