Stavridou Evangelia, Lagiotis Georgios, Kalaitzidou Parthena, Grigoriadis Ioannis, Bosmali Irini, Tsaliki Eleni, Tsiotsiou Stiliani, Kalivas Apostolos, Ganopoulos Ioannis, Madesis Panagiotis
Institute of Applied Biosciences, Centre for Research and Technology, Thermi, GR-57001 Thessaloniki, Greece.
Institute of Plant Breeding and Genetic Resources, Hellenic Agricultural Organization Demeter, Thermi, GR-57001 Thessaloniki, Greece.
Plants (Basel). 2021 Mar 30;10(4):656. doi: 10.3390/plants10040656.
A selection of sesame ( L.) landraces of different eco-geographical origin and breeding history have been characterized using 28 qualitative morpho-physiological descriptors and seven expressed sequence tag-simple sequence repeat (EST-SSR) markers coupled with a high-resolution melting (HRM) analysis. The most variable qualitative traits that could efficiently discriminate landraces, as revealed by the correlation analyses, were the plant growth type and position of the branches, leaf blade width, stem pubescence, flowering initiation, capsule traits and seed coat texture. The agglomerative hierarchical clustering analysis based on a dissimilarity matrix highlighted three main groups among the sesame landraces. An EST-SSR marker analysis revealed an average polymorphism information content (PIC) value of 0.82, which indicated that the selected markers were highly polymorphic. A principal coordinate analysis and dendrogram reconstruction based on the molecular data classified the sesame genotypes into four major clades. Both the morpho-physiological and molecular analyses showed that landraces from the same geographical origin were not always grouped in the same cluster, forming heterotic groups; however, clustering patterns were observed for the Greek landraces. The selective breeding of such traits could be employed to unlock the bottleneck of local phenotypic diversity and create new cultivars with desirable traits.
利用28个定性形态生理描述符和7个表达序列标签-简单序列重复(EST-SSR)标记结合高分辨率熔解(HRM)分析,对不同生态地理起源和育种历史的芝麻(L.)地方品种进行了特征鉴定。相关性分析表明,最具变异性且能有效区分地方品种的定性性状是植株生长类型和分枝位置、叶片宽度、茎毛、开花起始、蒴果性状和种皮质地。基于差异矩阵的凝聚层次聚类分析突出了芝麻地方品种中的三个主要类群。EST-SSR标记分析显示平均多态性信息含量(PIC)值为0.82,表明所选标记具有高度多态性。基于分子数据的主坐标分析和树状图重建将芝麻基因型分为四个主要分支。形态生理和分子分析均表明,来自同一地理起源的地方品种并不总是聚在同一类群中,而是形成了杂种优势群;然而,希腊地方品种呈现出聚类模式。对这些性状进行选择性育种可用于突破当地表型多样性的瓶颈,并培育出具有理想性状的新品种。