Suresh Ravindran*, A. Ramar, Senthamizh Selvi Balaraman, Murali P. Sankar, Mohamed A. A. Ahmed and Ehab A. A. Salama*,
{"title":"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","authors":"Suresh Ravindran*, A. Ramar, Senthamizh Selvi Balaraman, Murali P. Sankar, Mohamed A. A. Ahmed and Ehab A. A. Salama*, ","doi":"10.1021/acsagscitech.3c00326","DOIUrl":null,"url":null,"abstract":"<p >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.</p>","PeriodicalId":93846,"journal":{"name":"ACS agricultural science & technology","volume":"4 1","pages":"63–71"},"PeriodicalIF":2.3000,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Testing the Genetic Variability of Turmeric (Curcuma longa L.) Genotypes through Simple Sequence Repeats Genomic-Based Microsatellite Markers\",\"authors\":\"Suresh Ravindran*, A. Ramar, Senthamizh Selvi Balaraman, Murali P. Sankar, Mohamed A. A. Ahmed and Ehab A. A. Salama*, \",\"doi\":\"10.1021/acsagscitech.3c00326\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >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.</p>\",\"PeriodicalId\":93846,\"journal\":{\"name\":\"ACS agricultural science & technology\",\"volume\":\"4 1\",\"pages\":\"63–71\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2023-12-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS agricultural science & technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://pubs.acs.org/doi/10.1021/acsagscitech.3c00326\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AGRICULTURE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS agricultural science & technology","FirstCategoryId":"1085","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acsagscitech.3c00326","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
Testing the Genetic Variability of Turmeric (Curcuma longa L.) Genotypes through Simple Sequence Repeats Genomic-Based Microsatellite Markers
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.