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3 Biotech

, 9:252 | Cite as

Assessment of morphological and genetic variability through genic microsatellite markers for essential oil in Sandalwood (Santalum album L.)

  • Tanzeem FatimaEmail author
  • Ashutosh Srivastava
  • P. V. Somashekar
  • Vageeshbabu S. Hanur
  • M. Srinivasa Rao
  • Surendra Singh Bisht
Original Article
  • 26 Downloads

Abstract

Sandalwood (Santalum album L; family Santalaceae) is a highly significant aromatic oil yielding tree. It is valued for two important traits, heartwood and essential oil obtained from the heartwood. This study was proposed to assess the morphological and genetic variability of sandalwood accessions. For this, genotypes were randomly selected (n = 177) from the 14 populations from three states in southern India. The total heartwood oil content and quality was estimated by UV method and GC–MS. Total 14 oil-specific genic SSR markers were procured to evaluate the genetic diversity among the sandalwood accessions. Total core size, heartwood content, and oil of S. album ranged from 4.4 to 19.1 cm; 0.0 to 17.3 cm; and 0.0 to 5.96% with covariance 27.61, 85.25, and 73.12% followed by mean 9.74, 3.77, and 2.71, respectively. Genetic diversity estimates were highly polymorphic in terms of Na 7.28, Ne 5.89, He 8.0 PIC 0.891, with little Ho, and F-0.922. AMOVA revealed that minimal genetic variation among populations and highest variation was found among individuals with Nm (58.4). The UPGMA reveals the cluster favored the grouping pattern by the PCA analysis. Structure and PCA analysis clustered the entire populations into two major groups with FST 0.046 in which population of Kerala and Karnataka were pure and Telangana accessions were found admixtures. No significant correlation (r2 = 0.23, P = 0.00) was observed between heartwood oil and genetic structures. A high degree of transferability of genic markers would facilitate the assessment of novel genotypes for future tree improvement and conservation of Sandalwood populations.

Keywords

GC–MS Genic SSRs Genetic variability Heartwood oil PIC Santalum album 

Abbreviations

F

Inbreeding coefficient

GC–MS

Gas Chromatography–Mass spectrometry

He

Expected heterozygosity

Ho

Observed heterozygosity

Na

Number of alleles

Ne

Effective number of alleles

Nm

Gene flow

PIC

Polymorphic information content

PCA

Principal component analysis

UPGMA

Unweighted Pair Group Method with Arithmetic mean

Notes

Acknowledgements

Authors are thankful to the Director, IWST, Group co-ordinator Research, Head-Genetics and Tree Improvement Division, Dr. D. Annapurna GTI Division, Head-Chemistry of Forest Product Division, Institute of Wood Science and Technology. The authors also wish to thank Hassan DFO, Dharwad DFO, Director, Institute of Forest Biodiversity Hyderabad, State farmers of Suryapet Khammam Telangana, and their assistance on field trips, tree identification, and sample collection.

Author contributions

All authors contributed equally. All authors read, reviewed, agreed, and approved the final manuscript.

Compliance with ethical standards

Conflict of interest

All authors declare that they have no conflict of interest.

Supplementary material

13205_2019_1758_MOESM1_ESM.docx (3.2 mb)
Supplementary material 1 (DOCX 3254 kb)

References

  1. Arbeiter AB, Hladnik M, Jakse J, Bandelj D (2017) Identification and validation of novel EST-SSR markers in olives. Sci Agric 74:215–225CrossRefGoogle Scholar
  2. ArunKumar AN, Srinivasa YB, Joshi G, Seetharam A (2011) Variability in and relation between tree growth, heartwood and oil content in sandalwood (Santalum album). Curr Sci 6:827–830Google Scholar
  3. Arunkumar AN, Dhyani A, Joshi G (2019) Santalum album. The IUCN red list of threatened species 2019:e.T31852A2807668Google Scholar
  4. Bernard A, Barreneche T, Lheureux F, Dirlewanger E (2018) Analysis of genetic diversity and structure in a worldwide walnut (Juglans regia L.) germplasm using SSR markers. PLoS One 13:e0208021PubMedPubMedCentralCrossRefGoogle Scholar
  5. Bisht SS, Hemanthraj KPM (2014) Gas Chromatography–Mass spectrometry (GC–MS) profiling of heartwood oil composition from 15 years old Sandalwood. Int J Pharm Phytol Res 6:387–392Google Scholar
  6. 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 32:314–331PubMedPubMedCentralGoogle Scholar
  7. Doran J, Thomson L, Brophy J, Goldsack B, Bulai P, Fakaosi T, Mokoia T (2005) Variation in heartwood oil composition of young sandalwood trees in the South Pacific (S. yasi, S. album and F1 hybrids in Fiji, and S. yasi in Tonga and Niue). Sandal Res Newsle 3–4Google Scholar
  8. Earl DA, Vonholt BM (2012) STRUCTURE HARVESTER: a website and program A for visualizing STRUCTURE output and implementing the Evanno method. Cons Gen Resour 4:359–361CrossRefGoogle Scholar
  9. Evanno G, Regnaut S, Goudet J (2005) Detectin the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611–2620PubMedCrossRefGoogle Scholar
  10. Fatima T, Srivastava A, Hanur VS, Rao SM (2018) An effective wood DNA extraction protocol for three economic important timber species of India. Am J Plant Sci 9:139–149CrossRefGoogle Scholar
  11. Fu N, Wang PY, Liu XD, Shen HL (2014) Use of EST-SSR markers for evaluating genetic diversity and fingerprinting celery (Apium graveolens L.) cultivars. Molecules 19:1939–1955PubMedPubMedCentralCrossRefGoogle Scholar
  12. Guimaraes AG, Junior ATDA, Filho EDA, Pena GF, Vittorazzi C, Pereira MG (2018) Population structure and impact of recurrent selection on popcorn EST-SSR markers. Gen Plant Breed 40:E35218Google Scholar
  13. Hettiarachchi DS, Gamage M, Subasinghe U (2010) Oil content analysis of sandalwood: a novel approach for core sample analysis. Sandal Res Newsl 1–4Google Scholar
  14. International Organisation for Standardisation (2002) second ed., ISO 3518Google Scholar
  15. Jain SH, Angadi VG, Shankaranarayana KH (2003) Edaphic environmental and genetic factors associated with growth ana adaptability of sandal (Santalum album L.) in provenances. Sandal Res Newsl 17:6–7Google Scholar
  16. Jia B, Lin Q, Zhang L, Tan X, Lei X, Hu X, Shao F (2014) Development of 15 Genic-SSR markers in oil-tea tree (camellia oleifera) based on transcriptome sequencing. Genet 46(3):789–797CrossRefGoogle Scholar
  17. Jia H, Yang H, Sun P, Li J, Zhang J, Guo Y, Han X, Zhang G, Lu M, Hu J (2016) De novo transcriptome assembly, development of EST-SSR markers and population genetic analyses for the desert biomass willow (Salix psammophila). Sci Rep 6:39591PubMedPubMedCentralCrossRefGoogle Scholar
  18. Jones CG, Ghisalberti EL, Plummer JA, Barbour EL (2006) Quantitative co-occurrence of sesquiterpenes; a tool for elucidating their biosynthesis in Indian sandalwood, Santalum album. J Phytochem 67:2463–2468CrossRefGoogle Scholar
  19. Jones CG, Keeling CI, Ghisalberti EL, Barbour EL, Plummer JA, Bohlmann J (2008) Isolation of cDNA and functional characterization of two multi-product terpene synthase enzymes from sandalwood from sandalwood, Sandalwood, Santlum album L. Arch Biochem Biophys 477:121–130PubMedCrossRefGoogle Scholar
  20. Jones CG, Moniodis J, Zulak GK, Scaffidi A, Plummer JA, Ghisalberti EL, Barbour EL, Bohlmann J (2011) Sandalwood fragrance biosynthesis involves sesquiterpene synthases of both the terpene synthase TPS-a and TPS-b subfamilies, including santalene synthases. J Biol Chem 286:17445–17454PubMedPubMedCentralCrossRefGoogle Scholar
  21. Lin Z, Wang Y, Zhang X, Zhang J (2012) Functional Markers for cellulose synthase and their comparison to SSRs in cotton. Plant Mole Biol Rep 30:1270–1275CrossRefGoogle Scholar
  22. Misra BB, Dey S (2013) Developmental variations in sesquiterpenoid biosynthesis in East Indian sandalwood (Santalum album L). Trees 27:1071–1086CrossRefGoogle Scholar
  23. Moniodis J, Renton M, Jones CG, Barbour EL, Byrne M (2018) Genetic environment parameters show associations with essential oil composition in Western sandalwood (Santalum spicatum). Aust J Bot 66:48–58CrossRefGoogle Scholar
  24. Peakall R, Smouse PE (2012) GENALEX 6.5: genetic analysis in excel. Genetic analysis in excel. Population genetic software for teaching and research—an update. Bioinfo 28:2537–2539CrossRefGoogle Scholar
  25. Postolache D, Leonarduzzi C, Piotti A, Spanu I, Roig A, Fady B, Roschanski A, Liepelt S, Vendramin GG (2014) Transcriptome versus genomic microsatellite markers: highly informative multiplexes for genotyping Abies alba mill and congeneric species. Plant Mol Biol Rep 32:750–760CrossRefGoogle Scholar
  26. Pritchard JK, Stephens M, Donelly P (2000) Inference of population structure using multilocus genotype data. Genet 155:945–959Google Scholar
  27. Purohit PM (2018) Reviving the royal tree Santalum album Linn.: Santalaceae. J Med Plants Stu 6(2):273–276Google Scholar
  28. Rani A, Ravikumar P, Reddy MD, Kush A (2013) Molecular regulation of santalol Biosynthesis in Santalum album L. Gene 527:642–648PubMedCrossRefGoogle Scholar
  29. Rao NM, Ravikanth G, Ganeshaiah KN, Rathore TS, Shaanker RU (2007) assessing threats and identifying the ecological niche of sandal resources to identify ‘hot-spots’ for in situ conservation in Southern India. Sandal Proc Natl Semin 23–31Google Scholar
  30. Rosenberg NA, Burke T, Elo K, Feldman MW, Freidlin PJ, Groenen MAM, Hillel J, Maki-Tanila A, Tixier-Biochard M, Vignal A, Wimmers K, Weigend S (2001) Empirical evaluation of genetic clustering methods using multilocus genotypes from 20 chicken breeds. G E N 159:699–713Google Scholar
  31. Shams M, Ramezani M, Esfahan SZ, Esfahan EZ, Dursun A, Yildirim A (2016) Effects of climatic factors on the quantity of essential oil and dry matter yield of coriander (Coriandrum sativum L.). J Sci Technol 9:6Google Scholar
  32. Shankaranarayna KH, Angadi VG, Rajeevalochan KS, Sharma CR, Rangaswamy CR (1997) A rapid method of estimating essential oil content in heartwood of Santalum album Linn. Curr Sci 72:41–242Google Scholar
  33. Song YP, Jinag XB, Zhang M, Wang ZL, Bo WH, An XM, Zhang DQ, Zhang ZY (2012) Differences of EST-SSR and genomic markers in assessing genetic diversity in poplar. For Stud China 14(1):1–7CrossRefGoogle Scholar
  34. Sreenivasan VV, Shivaramakrishnana VR, Rangaswamy CR, Ananthapadmanabha HS, Shankaranarayana KH (1992) Sandal. ICFRE, Dehradun, p 233Google Scholar
  35. Subasinghe SMCUP (2013) Sandalwood research: a global perspective. J Trop For Environ 3:1–8Google Scholar
  36. Takezaki N, Nei M, Tamura K (2010) POPTREE2: software for constructing population trees from allele frequency data and computing other population statistics with Windows interface. Mol Biol Evol 27(4):747–752PubMedCrossRefGoogle Scholar
  37. Thatikunta R, Sankar AS, Sreelakshmi J, Palle G, Leela C, Rani CVD, Shankar VG, Lavanya B, Reddy PN, Dudhe MY (2016) Utilization of in silico EST–SSR markers for diversity studies in castor (Ricinus communis L.). Phys Mol Biol Plants 4:535–545CrossRefGoogle Scholar
  38. Varshney RK, Graner A, Sorrells ME (2005) Genetic microsatellite markers in plants: features and applications. Trends Biotechnol 23:48–55PubMedCrossRefGoogle Scholar
  39. Wen M, Wang H, Xia Z, Zou M, Lu C, Wang W (2010) Development of EST-SSR and genomic SSR markers to assess genetic diversity in Jatropha curcas L. BMC Res Notes 3:42PubMedPubMedCentralCrossRefGoogle Scholar
  40. Williams JGK, Kubelik AR, Livak KJ, Rafalski JA, Tingey SV (1990) DNA Polymorphisms amplifies by arbitrary primers are useful as genetic markers. Nucleic Acid Res 313:101–105Google Scholar
  41. Wright S (1978) Variability within and among natural populations. Evol and the Gen of Pop, 4, University of Chicago Press, ChicagoGoogle Scholar
  42. Zhijiao S, Heyu Y, Qijie W, Changpin Z, Fagen L, Mei L, Wanhong L, Jianzhong L, Siming G (2016) Genetic diversity and selective loci in Eucalyptus tereticornis populations. Sci Sil Sini 52(9):40–47Google Scholar

Copyright information

© King Abdulaziz City for Science and Technology 2019

Authors and Affiliations

  1. 1.Genetics and Tree Improvement Division Institute of Wood Science and TechnologyBangaloreIndia
  2. 2.Division of BiotechnologyIndian Institute of Horticultural ResearchBangaloreIndia
  3. 3.Woodworking DivisionInstitute of Wood Science and TechnologyBangaloreIndia
  4. 4.Chemistry and Bio Prospecting DivisionInstitute of Wood Science and TechnologyBangaloreIndia

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