Skip to main content

Advertisement

SpringerLink
Log in

Variability for Seed-based Economic Traits and Genetic Diversity Analysis in Mucuna pruriens Population of Northeast India

  • Full-Length Research Article
  • Published:
Agricultural Research Aims and scope Submit manuscript

Abstract

The tropical legume Mucuna pruriens (L.) DC. is one of the protein-rich crops well suited for the arid regions of the world, which suffers from low soil fertility and protein-energy malnutrition. Though thought to have originated in Southern China or Eastern India, which includes parts of Northeast (NE) India, the genetic diversity of M. pruriens from this region is poorly documented. In this study, we used 25 species-specific genic-microsatellite markers to investigate the diversity and population structure of sixty (60) M. pruriens accessions from Northeast India alongside assessing variability for the six seed-based economic traits. The study revealed high genetic diversity (I = 0.496), poor population differentiation (GST = 0.038 and FST = 0.061), extensive gene flow (Nm = 7.48), and admixture genotypes in addition to good variability for the seed-based economic traits. These findings will provide a strong basis for future studies on association mapping in addition to broadening the germplasm base for breeding programs in this lesser-known legume crop.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Arora KR (1991) Native food plants of northeastern India. Scientific Publishers, Jodhpur India, pp 137–152

    Google Scholar 

  2. 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 32:314–331

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Bradford MM (1976) A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein dye binding. Anal Biochem 72:248–254

    Article  CAS  PubMed  Google Scholar 

  4. Buckles D (1995) M. pruriens: A “new” plant with a history. Econ Bot 49:13–25

    Article  Google Scholar 

  5. Burkill IH (1966) A Dictionary of the economic products of the Malay Peninsula. Kuala Lumpur, Malaysia, Ministry of Agriculture and Cooperatives

  6. Chinapolaiah A, Bindu HH, Khadke GN, Manjesh GN, Rao NH, Kumar SS, Suthar MK (2018) Genetic diversity analysis in underutilized medicinal climber Mucuna pruriens (L) DC germplasm revealed by inter simple sequence repeats markers. Legume Res. https://doi.org/10.18805/LR-3954

    Article  Google Scholar 

  7. Doyle JJ, Doyle JL (1990) Isolation of plant DNA from fresh tissue. Focus 12:13–15

    Google Scholar 

  8. Duke JA (1981) Handbook of legumes of world economic importance. USA, Plenum Press, New York

    Book  Google Scholar 

  9. Earl DA (2012) Structure Harvester: a website and program for visualizing structure output and implementing the Evanno method. Conser Genet Resour 4:359–361

    Article  Google Scholar 

  10. Eilitta M, Carsky RJ (2003) Efforts to improve the potential of Mucuna as a food and feed crop: background to the workshop. Trop Subtrop Agroecosyst 1:47–55

    Google Scholar 

  11. Eilitta M, Bressani R, Carew LB, Carsky RJ, Flores M, Gilbert R, Huyck L, St. Laurent L and Szabo NJ (2002) Mucuna as a food and feed crop: An overview. In: Flores BM, Eilittä M, Myhrman R, Carew LB and Carsky RJ (eds) Food and Feed from Mucuna: Current uses and the Way Forward, Workshop, (April 26–29, 2000) Tegucigalpa, Honduras: CIDICCO, CIEPCA and World Hunger Research Center, pp. 18–47

  12. Eltaher S, Sallam A, Belamkar V, Emara HA, Nower AA, Salem KFM et al (2018) Genetic diversity and population structure of F3:6 nebraska winter wheat genotypes using genotyping-by-sequencing. Front Genet 9:76. https://doi.org/10.3389/fgene.2018.00076

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Frankham R, Ballou JD, Briscoe DA (2002) Introduction to Conservation Genetics. Cambridge University Press, Cambridge. https://doi.org/10.1017/CBO9780511808999

    Book  Google Scholar 

  14. Gurumoorthi P, Kumar SS, Vadivel V, Janardhanan K (2003) Studies on agrobotanical characters of different accessions of velvet bean collected from Western Ghats, South India. Trop SubtropAgroecosyst 2:105–115

    Google Scholar 

  15. Hallingback HR, Fogelqvist J, Powers SJ, Turrion-Gomez J, Rossiter R, AmeyJ MT et al (2015) Association mapping in Salix viminalis L. (Salicaceae) - identification of candidate genes associated with growth and phenology. GCB Bioenergy 8:670–685. https://doi.org/10.1111/gcbb.12280

    Article  CAS  PubMed  Google Scholar 

  16. Hammer O, Harper DAT, Ryan RD (2001) PAST: Paleontological statistics software package for education and data analysis. Palaeontol Electron 4:1–9

    Google Scholar 

  17. Hedge JE, Hofreiter BT (1962) Determination of reducing sugars and carbohydrates. Academic Press, New York, pp 380–394

    Google Scholar 

  18. Hira CK, Chopra N (1995) Effects of roasting on protein quality of chickpea (Cicer arietinum) and pea-nut (Arachis hypogaea). J Food Sci Technol 32:501–503

    CAS  Google Scholar 

  19. Janardhanan K, Gurumoorthi P, Pugalenthi M (2003) Nutritional potential of five accessions of a South Indian tribal pulse, Mucuna pruriens var. utilis I, The effect of processing methods on the content of L-Dopa, phytic acid and oligosaccharides. Trop Subtrop Agroecosyst 1:141–152

    Google Scholar 

  20. Jorge MA, Eilitta M, Proud FJ, Barbara Maasdorp V, Beksissa H, Ashok Sarial K, Hanson J (2007) Mucuna species: recent advances in application of biotechnology. Fruit Veg Cereal Sci Biotech 2:80–94

    Google Scholar 

  21. Kalia RK, Rai MK, Kalia S, Singh R, Dhawan AK (2011) Microsatellite markers: an overview of the recent progress in plants. Euphytica 177:309–334

    Article  CAS  Google Scholar 

  22. Kalidass C, Mahapatra AK (2014) Evaluation of the proximate and phytochemical compositions of an underexploited legume Mucuna pruriens var. utilis (Wall ex Wight) Baker ex Burck. Int Food Res J 21:303–308

    Google Scholar 

  23. Kalidass C, Mohan VR (2011) Nutritional and antinutritional composition of itching bean [Mucuna pruriens (L.) DC. var. pruriens]: An underutilized tribal pulse in Western Ghats Tamil Nadu. Trop Subtrop Agroecosyst 14:279–293

    Google Scholar 

  24. Kamei RG, Mauro DS, Gower DJ, vanBocxlaer I, Sherratt E, Thomas A, Babu S, Bossuyt F, Wilkinson Z, Biju SD (2012) Discovery of a new family of amphibians from northeast India with ancient links to Africa. Proc Royal Soc: Biol Sci 279:2396–2401

    Google Scholar 

  25. Kumar S, Singh GK, Kumar R, Bhatia NK, Awasthi CP (1991) Variation in quality traits of Pigeon pea (Cajanus cajan) (Mill sp) varieties. J Food Sci Tech 28:173–174

    Google Scholar 

  26. Kumar PR, Sundeep S, Sathyanarayana N (2019) Microsatellite analysis reveals low interpopulation differentiation in velvet bean (Mucuna pruriens var. utilis) of India. Nucleus. https://doi.org/10.1007/s13237-019-00276-1

    Article  Google Scholar 

  27. Lampariello LR, Cortelazzo A, Guerranti R, Sticozzi C, Valacchi G (2012) The magic velvet bean of Mucuna pruriens. J Tradit Complement Med 2:331–339. https://doi.org/10.1016/s2225-4110(16)30119-5

    Article  PubMed  PubMed Central  Google Scholar 

  28. Leelambika M, Mahesh S, Jaheer M, Sathyanarayana N (2010) Comparative evaluation of genetic diversity among Indian Mucuna species using morphometric, biochemical and molecular approaches. World J Agric Sci 6:568–578

    CAS  Google Scholar 

  29. Li L, Chokchai W, Xianqun H, Tuan H, Qiyi L, Yi P, Guimin H (2011) Comparison of AFLP and SSR for genetic diversity analysis of Brassica napus hybrids. J Agric Sci 3:101–110

    Google Scholar 

  30. Liu K, Muse SV (2005) PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics 21:2128–2129

    Article  CAS  PubMed  Google Scholar 

  31. Luo ZA, Iaffaldano BJ, Zhuang XF, Fresnedo-Ramirez J, Cornish K (2017) Analysis of the first Taraxacum kok-saghyz transcriptome reveals potential rubber yield related SNPs. Sci Rep 7:9939. https://doi.org/10.1038/s41598-017-09034-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Mang YD, Njintang YN, Abdou BA, Scher J, Bernard C, Mbofung MC (2016) Dehulling reduces toxicity and improves in vivo biological value of proteins in vegetal milk derived from two Mucuna (Mucuna pruriens L.) seeds varieties. J Food Sci Technol 53:2548–2557. https://doi.org/10.1007/s13197-016-2211-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Mittermeier RA, Gils PR, Hoffman M, Pilgrim J, Brooks T, Mittermeier CG, Lamoreaux J, Da Fonseca, GAB (eds) (2004) Hotspots revisited: Earth’s biologically richest and most endangered terrestrial eco-regions. Mexico City: CEMEX

  34. Muinga RW, Saha HM, Mureithi JG (2003) The effect of Mucuna (Mucuna pruriens) forage on the performance of lactating cows. Trop Subtrop Agroecosyst 1:87–91

    Google Scholar 

  35. Nei M (1990) Heterozygosity and genetic-distance - a citation classic commentary on estimation of average heterozygosity and genetic-distance from a small number of individuals. Genetics 89:583–590

    Article  Google Scholar 

  36. Pathania R, Chawla P, Khan H, Kaushik R, Khan MA (2020) An assessment of potential nutritive and medicinal properties of Mucuna pruriens: a natural food legume. Biotech 10:261. https://doi.org/10.1007/s13205-020-02253-x

    Article  Google Scholar 

  37. Peakall R, Smouse PE (2012) GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics 28:2537–2539

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Perrier X, Jacquemoud-collet JP (2006) DARwin Software, version 5.0.158. Montpellier: Department Systems Biologiques (BIOS), CIRAD

  39. Poornachandra MN, Khanam S, Shivananda BGTN, Shivananda TN, Dris R (2005) Mucuna pruriens (LDDC) - A novel drug for learning and memory retrieval. J Food Agric Environ 3:13–15

    Google Scholar 

  40. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Pugalenthi M, Vadivel V, Siddhuraju P (2005) Alternative food/ feed perspectives of an underutilized legume Mucuna pruriens var. utilis – a review. Plant Foods Hum Nutr 60:201–218

    Article  CAS  PubMed  Google Scholar 

  42. Rao VR (2002) Hodgkin T (2002) Genetic diversity and conservation and utilization of plant genetic resources. Plant Cell Tiss Org 68:1–19

    Article  Google Scholar 

  43. Rao BSN, Deosthale YG, Pant KC (1989) Nutritive value of Indian foods. Hyderabad, India: National Institute of Nutrition, Indian Council of Medical Research, pp. 47 – 91

  44. SPSS Inc. Released 2008. SPSS Statistics for Windows, Version 17.0. Chicago: SPSS Inc.

  45. Salem KFM, Sallam A (2016) Analysis of population structure and genetic diversity of Egyptian and exotic rice (Oryza sativa L.) genotypes. C R Biol 339:1–9. https://doi.org/10.1016/j.crvi.2015.11.003

    Article  PubMed  Google Scholar 

  46. Sathiyanarayanan L, Arulmozhi S (2007) Mucuna pruriens-A comprehensive review. Pharmacognosy Rev 1:157–162

    CAS  Google Scholar 

  47. Sathyanarayana N, Leelambika M, Mahesh S, Jaheer M (2011) AFLP assessment of genetic diversity among Indian Mucuna Accessions. Physiol Mol Biol Plants 17:171–180

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Sathyanarayana N, Mahesh S, Jaheer M, Leelambika M (2012) Genetic diversity of wild and cultivated Mucuna pruriens (L.) DC. accessions analyzed using thirty morpho-agronomical characters. Trop Subtrop Agroecosyst 15:249–259

    Google Scholar 

  49. Sathyanarayana N, Mahesh S, Leelambika M, Jaheer M, Chopra R, Rashmi KV (2016) Role of genetic resources and molecular markers in M. pruriens (L.) DC improvement. Plant Genet Resour 14:270–282

    Article  CAS  Google Scholar 

  50. Sathyanarayana N, Pittala RK, Tripathi PK, Chopra R, Singh HR, Belamkar V, Bhardwaj PK, Doyle JJ, Egan AN (2017) Transcriptomic resources for the medicinal legume Mucuna pruriens: de novo transcriptome assembly, annotation, identification and validation of EST-SSR markers. BMC Genom. https://doi.org/10.1186/s12864-017-3780-9

    Article  Google Scholar 

  51. Shete S, Tiwari H, Elston RC (2000) On estimating the heterozygosity and polymorphism information content value. Theor Popul Biol 57:265–271. https://doi.org/10.1006/tpbi.2000.1452

    Article  CAS  PubMed  Google Scholar 

  52. Shetty P, Sharma S, Sathyanarayana N (2015) Exploiting legume EST databases for the development of gene-derived SSR-markers in medicinal legume Mucuna pruriens L. (DC.). Electron J Plant Breed 6:1041–1051

    Google Scholar 

  53. Siddhuraju P, Becker K, Makkar HP (2000) Studies on the nutritional composition and antinutritional factors of three different germplasm seed materials of an under-utilized tropical legume, Mucuna pruriens var. utilis. J Agric Food Chem 48:6048–6060

    Article  CAS  PubMed  Google Scholar 

  54. Slatkin M, Barton NH (1989) A comparison of three indirect methods for estimating average levels of gene flow. Evolution 43:1349–1368

    Article  PubMed  Google Scholar 

  55. Soares AR, Marchiosi R, Soares RCS, de Lima RB, dos Santos WD, Ferrarese-Filho O (2014) The role of L-Dopa in plants. Plant Signal Behav 9(3):e28275

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  56. Szabo NJ, Tebbett IR (2002) The chemistry and toxicity of Mucuna species. In: Flores BM, Eilitta M, Myhrman R, Carew LB, Carsky RJ (eds) Food and feed from Mucuna: current uses and the way forward. Proceedings of the Centro Internacional de Informacion sobre Cultivos de Cobertura (CIDICCO) Workshop, Tegucigalpa, Honduras, pp 120–141

  57. Tautz D (1989) Hypervariability of simple sequences as a general source for polymorphic DNA markers. Nucleic Acid Res 17:6463–6471

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Tripathi PK, Jena SN, Rana TS, Sathyanarayana N (2018) High levels of gene flow constraints population structure in Mucuna pruriens L. (DC.) of northeast India. Plant Gene 15:6–14

    Article  Google Scholar 

  59. Vadivel V, Janardhanan K (2000) Nutritional and anti-nutritional composition of velvet bean: an under-utilized food legume in south India. Int J Food Sci Nutr 51:279–287

    Article  CAS  PubMed  Google Scholar 

  60. Wilmot-Dear CM (1984) A revision of Mucuna (Leguminosae- Phaseoleae) in China and Japan. Kew Bull 39:23–65

    Article  Google Scholar 

  61. Wilmot-Dear CM (1987) A revision of Mucuna (Leguminosae- Phaseolae) in the Indian Subcontinent and Burma. Kew Bull 42:23–46

    Article  Google Scholar 

  62. Wright S (1965) The interpretation of population structure by F-statistics with special regard to systems of mating. Evolution 19:395–420. https://doi.org/10.1111/j.1558-5646.1965.tb01731.x

    Article  Google Scholar 

  63. Yeh FC, Yang RC, Boyle T, Ye ZH, Mao JX (1999) POPGENE, Version 1.32: The User Friendly Software for Population Genetic Analysis. Edmonton, AB: Molecular Biology and Biotechnology Centre, University of Alberta

Download references

Acknowledgements

Authors acknowledge the Ministry of Tribal Affairs (MoTA), Government of India fellowship to PL under National Fellowship for Higher Education of ST Students (NFST-2015-17-ST-SIK-1633 dated 01/04/2016).

Author information

Authors and Affiliations

  1. Department of Botany, Sikkim University, 6th Mile, Samdur, Tadong-737102, Gangtok, East Sikkim, 737102, Sikkim, India

    Patrush Lepcha & N. Sathyanarayana

Authors
  1. Patrush Lepcha
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. N. Sathyanarayana
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to N. Sathyanarayana.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 52 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lepcha, P., Sathyanarayana, N. Variability for Seed-based Economic Traits and Genetic Diversity Analysis in Mucuna pruriens Population of Northeast India. Agric Res 11, 1–11 (2022). https://doi.org/10.1007/s40003-021-00568-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40003-021-00568-6

Keywords

Search

Navigation