Genetic diversity in the candidate trees of Madhuca indica J. F. Gmel. (Mahua) revealed by inter-simple sequence repeats (ISSRs)
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Madhuca indica provides livelihood to several tribal people in India, where the flowers are used for extraction of sweet juices having multiple applications. Certain trees have more value as judged by the tribal people mainly based on yield and quality performance of the trees, and these trees were selected for the genetic diversity analyses. Genetic diversity of 48 candidate Mahua trees from Etapalli, Dadagaon, and Jawhar, Maharashtra, India, was assessed using ISSR markers. Fourteen ISSR primers revealed a total of 132 polymorphic bands giving overall 92% polymorphism. Genetic diversity, in terms of expected number of alleles (Ne), the observed number of alleles (Na), Nei’s genetic diversity (H), and Shannon’s information index (I) was 1.921, 1.333, 0.211, and 0.337, respectively, and suggested lower genetic diversity. Region wise analysis revealed higher genetic diversity for site Etapalli (H = 0.206) and lowest at Dhadgaon (H = 0.140). Etapalli area possesses higher forest cover than Dhadgaon and Jawhar. Additionally, in Dhadgaon and Jawhar M. indica trees are restricted to field bunds; both reasons might contribute to lower genetic diversity in these regions. The dendrogram and the principal coordinate analyses showed no region-specific clustering. The clustering patterns were supported by AMOVA where higher genetic variance was observed within trees and lower variance among regions. Long-distance dispersal and/or higher human interference might be responsible for low diversity and higher genetic variance within the candidate trees.
KeywordsGenetic diversity ISSR markers People’s perception Human interference
We thank Lilesh Chavan, Nana Pawara and Giri Gurudas from BISLD, Nasik, India, for their field support. Authors also thank Dr. Monali Rahalkar (Agharkar Research Institute, Pune) for critical reading suggestions for improvement of the manuscript.
SDN, VKK, and SA gave technical guidance and were involved in documentation, identification, and collection of plant samples. SSJ and RAB executed the laboratory experiments and RAB interpreted and wrote the draft manuscript. All the authors scrutinized and reviewed the manuscript, and approved the final version.
Received funding for Maharashtra Gene Bank project from Rajiv Gandhi Science and Technology Commission, Mumbai and IISER Pune, India.
Compliance with ethical standards
In present work, human participation was limited to identification of plants by local tribal people and, therefore, formal consent was not required.
Conflict of interest
The authors declare no conflict of interests.
- Aabd NA, Msanda F, Mousadik AE (2015) Genetic diversity of the endangered argan tree (Argania spinosa L.) (sapotaceae) revealed by ISSR analysis. Basic Res J Agri Sci Rev 4:176–186Google Scholar
- Apte GS, Bahulikar RA, Kulkarni RS, Lagu MD, Kulkarni BG, Suresh HS, Rao PSN, Gupta VS (2006) Genetic diversity analysis in Gaultheria fragrantissima Wall. (Ericaceae) from the two biodiversity hotspots in India using ISSR markers. Curr Sci 91(12):1634–1640Google Scholar
- Austerlitz F, Mariette S, Machon N, Gouyon P-H, Godelle B (2000) Effects of colonization processes on genetic diversity: differences between annual plants and tree species. Genetics 154(3):1309–1321Google Scholar
- Bachmann K (1994) Molecular markers in plant ecology. New Phytol 126(3):403–418. https://doi.org/10.1111/j.1469-8137.1994.tb04242.x CrossRefGoogle Scholar
- Bahulikar RA, Lagu MD, Kulkarni BG, Pandit SS, Suresh HS, Rao MKV, Ranjekar PK, Gupta VS (2004a) Genetic diversity among spatially isolated populations of Eurya nitida Korth. (Theaceae) based on inter-simple sequence repeats. Curr Sci 86(6):824–831Google Scholar
- Chaudhary A, Bhandari A, Pandurangan A, Koul S (2015) Madhuca indica J. F. Gmel. (Sapotaceae): an overview. Int J Pharma Sci Let 5(2):539–545Google Scholar
- Deshpande AU, Apte GS, Bahulikar RA, Lagu MD, Kulkarni BG, Suresh HS, Singh NP, Rao MKV, Gupta VS, Pant A, Ranjekar PK (2001) Genetic diversity across natural populations of three montane plant species from the Western Ghats, India revealed by intersimple sequence repeats. Mol Ecol 10(10):2397–2408. https://doi.org/10.1046/j.0962-1083.2001.01379.x CrossRefGoogle Scholar
- Hammer Ø, Harper DAT, Ryan PD (2001) Past: paleontological statistics software package for education and data analysis. Palaeontol Electronica 4(1):4–9Google Scholar
- Idris AE, Hamza NB, Yagoub SO, Ibrahim AIA, El-Amin HKA (2012) Maize (Zea mays L.) genotypes diversity study by utilization of Inter-Simple Sequence Repeat (ISSR) markers. Aust J Basic Appl Sci 6(10):42–47Google Scholar
- Joshi SP, Ranjekar PK, Gupta VS (1999) Molecular markers in plant genome analysis. Curr Sci 77(2):230–241Google Scholar
- Kulkarni PS, Sharanappa G, Ramesh MR (2013) Mahua (Madhuca indica) as a source of biodiesel in India. Int J Eng Res Appl 4(7):2319–2329Google Scholar
- Morikawa M, Muto T, Santos-Guerrra A, Kondo K (2014) Identifying, discriminating and isolating cultivars of ‘Marguerites’ originated from Argyranthemum frutescens parentages and their intergeneric and interspecific hybridities by DNA markers amplified by RAPD (Random Amplified Polymorphic DNA) and ISSR (inter-simple sequence repeat). Chromosome Bot 9:97–112CrossRefGoogle Scholar
- Nagaraju J, Kathirvel M, Kumar RR, Siddiq EA, Hasnain SE (2002) Genetic analysis of traditional and evolved Basmati and non-Basmati rice varieties by using fluorescence-based ISSR-PCR and SSR markers. Proc Natl Acad Sci USA 99(9):5836–5841. https://doi.org/10.1073/pnas.042099099 CrossRefGoogle Scholar
- Patel M, Naik SN (2010) Flowers of Madhuca indica, present status and future prospective. Indian J Nat Prod Resour 1(4):438–443Google Scholar
- Patel PK, Prajapati NK, Dubey BK (2012) Madhuca indica: a review of its medicinal property. Int J Pharm Sci Rev Res 3(5):1285–1293Google Scholar
- Wani MS, Wani A, Mughal A (2015) Estimation of divergence to genetic variation in half-sib families of Madhuca indica GMEL. Under greenhouse and open field environmental conditions. Indian J Agr Sci 141(1):35–40Google Scholar
- Yeh FC, Yang RC, Boyle T, Ye ZH, Mao JX (1999) POPGENE, version 1.32: the user friendly software for population genetic analysis. Molecular Biology and Biotechnology Centre, University of Alberta, Edmonton, AB, CanadaGoogle Scholar