Safflower is an important oilseed crop mainly grown in the arid and semi-arid regions of the world. The aim of this study was to explore phenotypic and genetic diversity, population structure, and marker-trait association for 100-seed weight in 94 safflower accessions originating from 26 countries using silicoDArT markers. Analysis of variance revealed statistically significant genotypic effects (p < 0.01), while Turkey samples resulted in higher 100-seed weight compared to Pakistan samples. A Constellation plot divided the studied germplasm into two populations on the basis of their 100-seed weight. Various mean genetic diversity parameters including observed number of alleles (1.99), effective number of alleles (1.54), Shannon’s information index (0.48), expected heterozygosity (0.32), and unbiased expected heterozygosity (0.32) for the entire population exhibited sufficient genetic diversity using 12232 silicoDArT markers. Analysis of molecular variance (AMOVA) revealed that most of the variations (91%) in world safflower panel are due to differences within country groups. A model-based structure grouped the 94 safflower accessions into populations A, B, C and an admixture population upon membership coefficient. Neighbor joining analysis grouped the safflower accessions into two populations (A and B). Principal coordinate analysis (PCoA) also clustered the safflower accessions on the basis of geographical origin. Three accessions; Egypt-5, Egypt-2, and India-2 revealed the highest genetic distance and hence might be recommended as candidate parental lines for safflower breeding programs. The mixed linear model i.e., the Q + K model, demonstrated that two DArTseq markers (DArT-45483051 and DArT-15672391) had significant association (p < 0.01) for 100-seed weight. We envisage that identified DArTseq markers associated with 100-seed weight will be helpful to develop high-yielding cultivars of safflower through marker-assisted breeding in the near future.

中文翻译：

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使用 SilicoDArT 标记信息研究国际红花小组 100 粒种子重量的遗传多样性、群体结构和标记性状关联。

红花是重要的油料作物，主要种植在世界干旱、半干旱地区。本研究的目的是使用 silicoDArT 标记探索来自 26 个国家的 94 个红花种质的表型和遗传多样性、群体结构以及 100 粒种子重量的标记-性状关联。方差分析显示具有统计显着性的基因型效应 ( p < 0.01)，而土耳其样品的 100 粒种子重量高于巴基斯坦样品。星座图根据 100 颗种子的重量将所研究的种质分为两个群体。整个种群的各种平均遗传多样性参数，包括观察到的等位基因数（1.99）、有效等位基因数（1.54）、香农信息指数（0.48）、预期杂合度（0.32）和无偏预期杂合度（0.32）表现出足够的遗传多样性使用 12232 个 silicoDArT 标记。分子方差分析 (AMOVA) 显示，世界红花小组的大部分变异 (91%) 是由于国家组内的差异造成的。基于模型的结构根据隶属系数将 94 个红花种质分为群体 A、B、C 和混合群体。邻接分析将红花种质分为两个群体（A 和 B）。主坐标分析（PCoA）还根据地理起源对红花种质进行了聚类。三个加入品；Egypt-5、Egypt-2 和 India-2 显示出最高的遗传距离，因此可能被推荐作为红花育种计划的候选亲本系。混合线性模型，即 Q + K 模型，证明两个 DArTseq 标记（DArT-45483051 和 DArT-15672391）与 100 粒种子重量具有显着相关性 ( p < 0.01)。我们预计，与百粒重相关的 DArTseq 标记将有助于在不久的将来通过标记辅助育种开发红花高产品种。