Genetic Diversity Analysis Reveals Strong Population Structure in Sorghum Germplasm Collection
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Population structure and genetic variability among seven groups of 44 parental lines of sorghum, including mid-season drought-tolerant, mid-season drought-susceptible, stay green lines, terminal drought-tolerant, saline-tolerant, saline-susceptible, high Fe–Zn lines and a wild genotype as an out-group were assessed using three dominant markers namely ISSR, RAPD, and DAMD. Wide range genome coverage of sorghum has been attained using these markers, which produced about 263 fragments of amplified products and the analysis accounted for a higher polymorphism (84.6%) and the polymorphic loci (72.65%) which produced a greater level of genetic distance among the genotypes. These findings are consistent with the UPGMA and neighbor-joining clustering of genotypes by individual markers. The existence of greater genetic variation at an intrapopulation level than at the interpopulation level was indicated by principal coordinate analysis and principal component analysis where the individuals of different groups failed to form distinct clusters rather mixed up along the axis. The Bayesian model-based structure analysis also identified the population structure with high admixture and diversity among the studied populations. The study also showed the non-existence of pure lines from this collection. Therefore, markers used in the study efficiently arrived at the phylogenetic relationships of 44 domesticated sorghum lines, and the obtained information can be implemented in breeding programs of this important food and forage resource for biofortification and the development of varieties with abiotic stress tolerance.
KeywordsAgronomic traits Heterogeneity Molecular markers Population structure Sorghum
One of the authors thanks the University Grants Commission, New Delhi, India for financial support in the form of UGC-BSR SRF (UGC Order No: F.25-1/2014-15 (BSR)/7-326/2011/BSR). The authors thank Dr. Are Ashok Kumar, Sorghum Breeding, International Crops Research Institute from the Semi-Arid Tropics (ICRISAT), Hyderabad, India, and Department of Millets, Tamil Nadu Agricultural University (TNAU), Coimbatore, India, for providing the seed material used in this study. They sincerely acknowledge the Computational and Bioinformatics facility provided by the Alagappa University Bioinformatics Infrastructure Facility (funded by DBT, GOI; File No. BT/BI/25/012/2012,BIF). The authors also thankfully acknowledge RUSA 2.0 [F. 24-51/2014-U, Policy (TN Multi-Gen), Dept of Edn, GOI], DST-FIST (Grant No. SR/FST/LSI-639/2015(C)), UGC-SAP (Grant No. F.5-1/2018/DRS-II (SAP-II)) and DST-PURSE (Grant No. SR/PURSE Phase 2/38 (G)) for providing instrumentation facilities.
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Conflict of interest
The authors declare that they have no conflict of interest to publish this manuscript.
- 2.Reddy BVS, Ramesh S, Reddy PS, Kumar AA (2009) Genetic enhancement for drought tolerance in sorghum. Plant Breed Rev 31:189–222Google Scholar
- 4.ICRISAT (1996) The world sorghum and millet economies: facts, trends and outlook, ICRISAT/FAO, Patancheru, India/Rome, Italy, pp 1–2Google Scholar
- 8.Basnet BR, Ali MB, Ibrahim AM, Payne T, Mosaad MG (2011) Evaluation of genetic bases and diversity of Egyptian wheat cultivars released during the last 50 years using coefficient of parentage. Commun Biom Crop Sci 6:31–47Google Scholar
- 9.Frankel OH, Brown AHD (1984) Plant genetic resources today: a critical appraisal. In: Holden JHW, Williams JT (eds) Crop genetic resources: conservation and evaluation. George Allen and Unwin, London, UK, pp 249–257Google Scholar
- 11.Van Esbroeck G, Bowman DT (1998) Cotton germplasm diversity and its importance in cultivar development. J Cot Sci 2:121–129Google Scholar
- 17.Akram Z, Khan MM, Shabbir G, Nasir F (2011) Assessment of genetic variability in sorghum genotypes for drought tolerance based on RAPD analysis. J Agric Res 49:455–464Google Scholar
- 18.Botstein D, White RL, Skolnick M, Davis RW (1980) Construction of a genetic linkage map in man using restriction fragment length polymorphisms. Am J Hum Genet 32:314–331Google Scholar
- 19.Hammer Ø, Harper DAT, Ryan PD (2001) PAST: paleontological statistics software package for education and data analysis. Palaeontol Electron 4:9Google Scholar
- 20.Rohlf FJ (1998) NTSYS-PC. Numerical taxonomy and multivariate analysis system, version 2.02. Exeter Software, Setauket, NYGoogle Scholar
- 21.Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959Google Scholar
- 28.Weerasooriya DK, Maulana FR, Bandara AY, Tirfessa A, Ayana A, Mengistu G, Nouh K, Tesso TT (2016) Genetic diversity and population structure among sorghum (Sorghum bicolor, L.) germplasm collections from Western Ethiopia. Afr J Biotechnol 15:1147–1158Google Scholar