Testing the Genetic Variability of Turmeric (Curcuma longa L.) Genotypes through Simple Sequence Repeats Genomic-Based Microsatellite Markers

IF 2.3 Q1 AGRICULTURE, MULTIDISCIPLINARY ACS agricultural science & technology Pub Date : 2023-12-19 DOI:10.1021/acsagscitech.3c00326
Suresh Ravindran*, A. Ramar, Senthamizh Selvi Balaraman, Murali P. Sankar, Mohamed A. A. Ahmed and Ehab A. A. Salama*, 
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Abstract

Turmeric plants produce a wide range of important and unique chemical compounds, such as curcumin, oleoresin, and essential oils, which are all the most important sources for turmeric-based industrial products. In this respect, the assessment of genetic diversity among available turmeric genotypes and germplasm core collections is an essential step to accelerate the genetic improvement process of production of its compounds and productivity. To this end, 22 turmeric genotypes selected from the germplasm collected from different regions were examined in the current study using the DNA-based simple sequence repeat (SSR) marker technique to investigate their genetic diversity, relation, and geographical distribution. Hence, 22 turmeric genotypes were evaluated by 26 SSR markers to determine the genetic variability. Among them, 5 primers showed 100% polymorphism, viz., CuMiSat 19, CuMiSat 24, Clon 1, CSSR 14, and CSSR 18. On the other hand, among the studied turmeric genotypes, CL 258, CL 202, and CL 125 were identified as the most deviating and potentially useful genotypes for any further breeding program of turmeric plants. In addition to that, the linkage and divergence of these genotypes were further designed with unweighted pair group method with arithmetic mean (UPGMA) cluster analysis and obtained SSR primer data. As a result, based on the analysis of SHAN matrix using UPGMA, the estimated turmeric genotypes were divided into several clusters due to the significant relationships as well as the considerable genetic diversity among them. Then, the comprehensive UPGMA dendrogram was generated using Jaccard’s similarity index based on SSR data. Notably, cluster-I and cluster-II shared a common node with a coefficient of 0.82%. Collectively, the obtained results of this investigation demonstrated that the SSR markers could be a useful tool in the introduction process of new and modern turmeric cultivars possessing tailor-made essential traits such as better adaptation and resilience to current climatic change scenarios along with high performance in terms of productivity as well as production of curcumin, oleoresin, and essential oil compounds which together make turmeric a promising industrial crop in the near future.

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通过基于基因组的简单序列重复微卫星标记检测姜黄(Curcuma longa L.)基因型的遗传变异性
姜黄植物能产生多种重要而独特的化学物质,如姜黄素、精油和香精油,它们都是姜黄工业产品最重要的来源。在这方面,评估现有姜黄基因型和种质核心收集的遗传多样性是加快其化合物生产和生产力遗传改良进程的必要步骤。为此,本研究采用基于 DNA 的简单序列重复(SSR)标记技术,对从不同地区收集的种质中筛选出的 22 个姜黄基因型进行了研究,以调查它们的遗传多样性、关系和地理分布。因此,通过 26 个 SSR 标记对 22 个姜黄基因型进行了评估,以确定其遗传变异性。其中,5 个引物表现出 100% 的多态性,即 CuMiSat 19、CuMiSat 24、Clon 1、CSSR 14 和 CSSR 18。另一方面,在所研究的姜黄基因型中,CL 258、CL 202 和 CL 125 被鉴定为偏差最大的基因型,可能对进一步的姜黄育种计划有用。此外,利用算术平均非加权配对组法(UPGMA)聚类分析和 SSR 引物数据,进一步设计了这些基因型的联系和差异。结果,根据 UPGMA 对 SHAN 矩阵的分析,估算出的姜黄基因型被分为几个聚类,因为它们之间存在显著的关系和相当大的遗传多样性。然后,利用基于 SSR 数据的 Jaccard 相似度指数生成了综合 UPGMA 树枝图。值得注意的是,群组Ⅰ和群组Ⅱ共享一个共同节点,系数为 0.82%。总之,本次研究的结果表明,SSR 标记可作为一种有用的工具,用于引进新的现代姜黄栽培品种,这些品种具有量身定制的基本性状,如对当前气候变化情景具有更好的适应性和抗逆性,同时在生产率以及姜黄素、精油和精油化合物的产量方面具有较高的表现,这些共同使姜黄在不久的将来成为一种前景广阔的工业作物。
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