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Biochemical Genetics

, Volume 57, Issue 4, pp 522–539 | Cite as

Population Genetics of Calotropis gigantea, a Medicinal and Fiber Resource Plant, as Inferred from Microsatellite Marker Variation in two Native Countries

  • Md. Rabiul Islam
  • Zhi-Zhong Li
  • Andrew W. Gichira
  • Mohammad Nur Alam
  • Peng-Cheng Fu
  • Guang-Wan Hu
  • Qing-Feng WangEmail author
  • Ling-Yun ChenEmail author
Original Article

Abstract

Calotropis gigantea is well known for its aesthetic, medicinal, pharmacological, fodder, fuel, and fiber production potential. Unfortunately, this plant species is still undomesticated, and the genetic information available for crop improvement is limited. For this study, we sampled 21 natural populations of C. gigantea from two key areas of its natural distribution range (Bangladesh and China) and genotyped 379 individuals using nine nuclear microsatellite markers. Population genetic diversity was higher in Bangladesh than that observed in Chinese populations. Overall, a moderate level of genetic diversity was found (Na = 3.73, HE = 0.466), with most of the genetic variation detected within populations (65.49%) and substantial genetic differentiation (FST = 0.345) between the study regions. We observed a significant correlation between genetic and geographic distances (r  =  0.287, P  =  0.001). The Bayesian clustering, UPGMA tree, and PCoA analyses yielded three distinct genetic pools, but the number of migrants per generation was high (NM = 0.52–2.78) among them. Our analyses also revealed that some populations may have experienced recent demographic bottlenecks. Our study provides a baseline for exploitation of the genetic resources of C. gigantea in domestication and breeding programs as well as some insights into the germplasm conservation of this valuable plant.

Keywords

Calotropis gigantea Domestication Genetic diversity Gene flow Microsatellites Population bottleneck 

Notes

Acknowledgements

We acknowledged Professor Dr. Md. Abu Hasan, Hajee Mohammad Danesh Science and Technology University, Bangladesh, and Xu Zhun for helping during sample collection; Shu-Ying Zhao for assistance in data analyses; and John Mulinge Nzei and Mwanzia Virginia M. for language editing of the manuscript. This project financially supported by National Natural Science Foundation of China (31670226) and CAS-TWAS President’s PhD Fellowship Program, University of Chinese Academy of Sciences, China.

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

10528_2019_9904_MOESM1_ESM.docx (618 kb)
Supplementary file1 (DOCX 619 kb)
10528_2019_9904_MOESM2_ESM.xlsx (46 kb)
Supplementary file2 (XLSX 46 kb)

References

  1. Abbas B, Eltayeb AE, Sulleiman YR (1992) Calotropis procera- feed potential for arid zones. Vet Rec 131:132.  https://doi.org/10.1136/vr.131.6.132-a CrossRefPubMedGoogle Scholar
  2. Ali T, Ali SI (1989) Pollination biology of Calotropis procera subsp. Hamiltonii (Asclepiadaceae). Phyton 29:175–188Google Scholar
  3. Angelo D, Agossou Yao R, Sprycha Y, Porembski S, Horn R (2015) AFLP assessment of the genetic diversity of Calotropis procera (Apocynaceae) in the West Africa region (Benin). Genet Resour Crop Evol 62:863–878.  https://doi.org/10.1007/s10722-014-0197-z CrossRefGoogle Scholar
  4. Ashori A, Bahreini Z (2009) Evaluation of Calotropis gigantea as a promising raw material for fiber-reinforced composite. J Compos Mater 43(11):1297–1304.  https://doi.org/10.1177/0021998308104526 CrossRefGoogle Scholar
  5. Babu GD, Babu KS, Kishore PN (2014) Tensile and wear behavior of Calotropis gigantea fruit fiber reinforced polyester composites. Procedia Eng 97:531–535CrossRefGoogle Scholar
  6. Barbosa MO, de Almeida-Cortez JS, da Silva SI, de Oliveira AFM (2014) Seed oil content and fatty acid composition from different populations of Calotropis procera (Aiton) W. T. Aiton (Apocynaceae). J Am Oil Chem Soc 91:1433–1441.  https://doi.org/10.1007/s11746-014-2475-5 CrossRefGoogle Scholar
  7. Beerli P (2006) Comparison of Bayesian and maximum-likelihood inference of population genetic parameters. Bioinformatics 22:341–345.  https://doi.org/10.1093/bioinformatics/bti803 CrossRefPubMedGoogle Scholar
  8. Beerli P, Felsenstein J (1999) Maximum-likelihood estimation of migration rates and effective population numbers in two populations using a coalescent approach. Genetics 152:763–773PubMedPubMedCentralGoogle Scholar
  9. Beerli P, Palczewski M (2010) Unified framework to evaluate panmixia and migration direction among multiple sampling locations. Genetics 185:313–326.  https://doi.org/10.1534/genetics.109.112532 CrossRefPubMedPubMedCentralGoogle Scholar
  10. Beerli P (2012) Migrate Documentation Version 3.2.1. Florida State University, Tallahassee FLGoogle Scholar
  11. Bertoni BW, de Souza AV, Biondo R, SdeC França, Telles MPC, Pereira AMS (2010) Genetic diversity among natural populations of Mandevilla velutina. Hortic Bras 28:209–213.  https://doi.org/10.1590/S0102-05362010000200012 CrossRefGoogle Scholar
  12. Blanquart F, Gandon S (2011) Evolution of migration in a periodically changing environment. Am Nat 177:188–201.  https://doi.org/10.1086/657953 CrossRefPubMedGoogle Scholar
  13. 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
  14. Boylan J, Valle FL, Kang Y (2009) Determination of genetic relationships among populations of Asclepias tuberosa (Asclepiadaceae) based on ISSR polymorphisms. BIOS 80:25–34CrossRefGoogle Scholar
  15. Carlsson J (2008) Effects of microsatellite null alleles on assignment testing. J Hered 99:616–623.  https://doi.org/10.1093/jhered/esn048 CrossRefPubMedGoogle Scholar
  16. Cavalli-Sforza LL, Edwards AWF (1967) Phylogenetic analysis: models and estimation procedures. Am J Hum Genet 19:233–257PubMedPubMedCentralGoogle Scholar
  17. Chapuis MP, Estoup A (2007) Microsatellite null alleles and estimation of population differentiation. Mol Biol Evol 24:621–631CrossRefGoogle Scholar
  18. Chen Y, Shi MM, Ai B, Gu JM, Chen XY (2008) Genetic variation in island and mainland populations of Ficus pumila (Moraceae) in eastern Zhejiang of China. Symbiosis 45:1–9Google Scholar
  19. Chybicki IJ, Burczyk J (2009) Simultaneous estimation of null alleles and inbreeding coefficients. J Hered 100:106–113.  https://doi.org/10.1093/jhered/esn088 CrossRefPubMedGoogle Scholar
  20. Comer JR (2009) An assessment of genetic variation within Missouri populations of Asclepias meadii Torr. ex Grey (Apocynaceae) and a comparison with three widespread Asclepias species. MSU Graduate Theses, Missouri State UniversityGoogle Scholar
  21. Cornuet JM, Luikart G (1996) Description and power analysis of two tests for detecting recent population bottlenecks from Allele Frequency Data. Genetics 144:2001–2014PubMedPubMedCentralGoogle Scholar
  22. Dakin EE, Avise JC (2004) Microsatellite null alleles in parentage analysis. Heredity 93:504–509CrossRefPubMedGoogle Scholar
  23. Dias EF, Moura M, Schaefer H, Silva L (2016) Geographical distance and barriers explain population genetic patterns in an endangered island perennial. AoB Plants 8:plw072CrossRefPubMedPubMedCentralGoogle Scholar
  24. Doyle JJ, Doyle JL (1987) A rapid isolation procedure for small quantities of fresh leaf tissue. Phytochem Bull 19:11–15Google Scholar
  25. Earl DA, vonHoldt BM (2012) STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv Genet Resour 4:359–361.  https://doi.org/10.1007/s12686-011-9548-7 CrossRefGoogle Scholar
  26. eFloras (2008) Flora of China. Missouri Botanical Garden, St. Louis, MO and Harvard University Herbaria, Cambridge, MA. http://www.efloras.org. Accessed 25 Feb 2018
  27. El-Bakry AA, Hammad IA, Rafat FA (2014) Polymorphism in Calotropis procera: preliminary genetic variation in plants from different phytogeographical regions in Egypt. Rend Fis Acc Lincei 25:471–477.  https://doi.org/10.1007/s12210-014-0316-y CrossRefGoogle Scholar
  28. Ellstrand NC, Elam DR (1993) Population genetic consequences of small population size: implications for plant conservation. Annu Rev Ecol Syst 24:217–242CrossRefGoogle Scholar
  29. Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611–2620.  https://doi.org/10.1111/j.1365-294X.2005.02553.x CrossRefPubMedGoogle Scholar
  30. Excoffier L, Laval G, Schneider S (2005) Arlequin (version 3.0): an integrated software package for population genetics data analysis. Evol Bioinform Online 1:47–50CrossRefGoogle Scholar
  31. Fan LN, Deng HH, Luo QW, He HY, Li Y, Wang QN, Huang ZX, Wu JT, Li QW, Liu SM, Qi YW (2013) Genetic diversity of Saccharum spontaneum from geographical regions of China assessed by simple sequence repeats. Genet Mol Res 12:5916–5925.  https://doi.org/10.4238/2013 CrossRefPubMedGoogle Scholar
  32. Francis JK (2003) Calotropis procera. U.S. Department of Agriculture, Forest Service, International Institute of Tropical Forestry, Puerto RicoGoogle Scholar
  33. García-Verdugo C, Sajeva M, La Mantia T, Harrouni C, Msanda F, Caujapé-Castells J (2015) Do island plant populations really have lower genetic variation than mainland populations? Effects of selection and distribution range on genetic diversity estimates. Mol Ecol 24:726–741.  https://doi.org/10.1111/mec.13060 CrossRefPubMedGoogle Scholar
  34. García-Verdugo C, Caujapé-Castells J, Mairal M, Monroy P (2018) How repeatable is microevolution on islands? Patterns of dispersal and colonization-related plant traits in a phylogeographical context. Ann Bot. https://dx.doi.org/10.1093/aob/mcy191
  35. Goudet J (2001) FSTAT, a program to estimate and test gene diversities and fixation indices (version 2.9.3). https://www2.unil.ch/popgen/softwares/fstat.htm
  36. Hamrick JL, Godt MJW, Sherman-Broyles SL (1992) Factors influencing levels of genetic diversity in woody plant species. New For 6:95–124CrossRefGoogle Scholar
  37. Hartl DL, Clark AG (1980) Principles of Population Genetics, 4th edn. Sinauer Associates, Inc., Publishers Sunderland, MassachusettsGoogle Scholar
  38. Hauser L, Seamons TR, Dauer M, Naish KA, Quinn TP (2006) An empirical verification of population assignment methods by marking and parentage data: hatchery and wild steelhead (Oncorhynchus mykiss) in Forks Creek, Washington, USA. Mol Ecol 15:3157–3173CrossRefPubMedGoogle Scholar
  39. IBM Corp. Released (2015) IBM SPSS Statistics for Windows, Version 23.0. Armonk, NY: IBM CorpGoogle Scholar
  40. Jimenez HJ, Martins LSS, Montarroyos AVV, Silva Junior JF, Alzate-Marin AL, Moraes Filho RM (2015) Genetic diversity of the Neotropical tree Hancornia speciosa Gomes in natural populations in Northeastern Brazil. Genet Mol Res 14:17749–17757.  https://doi.org/10.4238/2015 CrossRefPubMedGoogle Scholar
  41. Kabat SM, Dick CW, Hunter MD (2010) Isolation and characterization of microsatellite loci in the common milkweed, Asclepias syriaca (Apocynaceae). Am J Bot 97:37–38CrossRefGoogle Scholar
  42. Kalinowski ST, Taper ML, Marshall TC (2007) Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Mol Ecol 16:1099–1106.  https://doi.org/10.1111/j.1365-294X.2007.03089.x CrossRefGoogle Scholar
  43. Kumar S, Stecher G, Tamura K (2016) MEGA7: Molecular evolutionary genetics analysis version 7.0 for biggest datasets. Mol Biol Evol 33:1870–1874.  https://doi.org/10.1093/molbev/msw054 CrossRefPubMedGoogle Scholar
  44. Lienert J, Fischer M (2003) Habitat fragmentation affects the common wetland specialist Primula farinosa in north-east Switzerland. J Ecol 9:587–599CrossRefGoogle Scholar
  45. Luikart G, Cornuet JM (1998) Empirical evaluation of a test for identifying recently bottlenecked populations from allele frequency data. Conserv Biol 12:228–237CrossRefGoogle Scholar
  46. Maebe K, Meeus I, Maharramov J, Grootaert P, Michez D, Rasmont P, Smagghe G (2013). Microsatellite analysis in museum samples reveals inbreeding before the regression of Bombus veteranus . Apidologie 44:188–197. https://doi.org/10.1007/s13592-012-0170-9 CrossRefGoogle Scholar
  47. Maki' M, Morita H (1998) Genetic diversity in island and mainland populations of Aster spathulifolius (Asteraceae). Int J Plant Sci 159:148–152CrossRefGoogle Scholar
  48. Menge EO, Greenfield ML, Mcconchie CA, Bellairs SM, Lawes MJ (2017) Density-dependent reproduction and pollen limitation in an invasive milkweed, Calotropis procera (Ait.) R. Br. (Apocynaceae). Austral Ecol 42:61–71.  https://doi.org/10.1111/aec.12401 CrossRefGoogle Scholar
  49. Motaleb MA, Hossain MK, Sobhan I, Alam MK, Khan NA, Firoz R (2011) Selected Medicinal Plants of Chittagong Hill Tracts. IUCN (International Union for Conservation of Nature), Dhaka, BangladeshGoogle Scholar
  50. Moura NF, Chaves LJ, Venkovsky R, Naves RV, Aguiar AV, Moura MF (2011) Genetic structure of mangaba (Hancornia speciosa Gomes) populations in the cerrado region of central Brazil. Bioscience Journal 27:473–481Google Scholar
  51. Muchugi A, Gachuiri A, Gacheri N, Mutiso F, Kimiti J, Jamnadass R and Xu J (2017) Calotropis procera: a new investment for African drylands. Future Agriculture: socio-ecological transitions and bio-cultural shifts. Tropentag, 20–22 September, BonnGoogle Scholar
  52. Muriira NG, Xu W, Muchugi A, Xu J, Liu A (2015) De novo sequencing and assembly analysis of transcriptome in the Sodom apple (Calotropis gigantea). BMC Genom 16:1–14.  https://doi.org/10.1186/s12864-015-1908-3 CrossRefGoogle Scholar
  53. Muriira NG, Muchugi A, Yu A, Xu J, Liu A (2018) Genetic diversity analysis reveals genetic differentiation and strong population structure in Calotropis plants. Sci Rep 8:7832.  https://doi.org/10.1038/s41598-018-26275-x CrossRefPubMedPubMedCentralGoogle Scholar
  54. Nakahama N, Kaneko S, Hayano A, Isagi Y, Inoue-Murayama M, Tominaga T (2012) Development of microsatellite markers for the endangered grassland species Vincetoxicum pycnostelma (Apocynaceae) using next-generation sequencing technology. Conserv Genet Resour 4:669–671CrossRefGoogle Scholar
  55. Nei M, Maruyama T, Chakraborty R (1975) The bottleneck effect and genetic variability in populations. Evolution 29:1–10CrossRefPubMedGoogle Scholar
  56. Nybom H (2004) Comparison of different nuclear DNA markers for estimating intraspecific genetic diversity in plants. Mol Ecol 13:1143–1155CrossRefPubMedGoogle Scholar
  57. Pandeya SC, Chandra A, Pathak PS (2007) Genetic diversity in some perennial plant species with-in short distances. J Environ Biol 28:83–86PubMedGoogle Scholar
  58. Parhira S, Yang ZF, Zhu GY, Chen QL, Zhou BX (2014) In vitro anti-influenza virus activities of a new lignan glycoside from the latex of Calotropis gigantea. PLoS ONE 9:e104544.  https://doi.org/10.1371/journal.pone.0104544 CrossRefPubMedPubMedCentralGoogle Scholar
  59. Parhira S, Zhu GY, Li T, Liu L, Bai LP, Jiang ZH (2016) Inhibition of IKK-β by epidioxysterols from the flowers of Calotropis gigantea (Niu jiao gua). Chin Med 11:1–8.  https://doi.org/10.1186/s13020-016-0081-1 CrossRefGoogle Scholar
  60. 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.  https://doi.org/10.1093/bioinformatics/bts460 CrossRefPubMedPubMedCentralGoogle Scholar
  61. Piry S, Luikart G, Cornuet JM (1999) Bottleneck: a computer program for detecting recent reductions in the effective population size using allele frequency data. J Hered 90:502–503CrossRefGoogle Scholar
  62. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959PubMedPubMedCentralGoogle Scholar
  63. Priya TA, Manimekalai V, Ravichandran P (2015) Intraspecific genetic diversity studies on Calotropis gigantea (L) R. Br. using RAPD markers. European J Biotechnol Biosci 3:7–9Google Scholar
  64. Rahman MA, Wilcock CC (1991) A taxonomic revision of Calotropis (Asclepiadaceae). Nord J Bot 11:301–308CrossRefGoogle Scholar
  65. Ramadan A, Sabir JSM, Alakilli SYM, Shokry AM, Gadalla NO, Edris S, Al-Kordy MA, Al-Zahrani HS, El-Domyati FM, Bahieldin A, Baker NR, Willmitzer L, Irgang S (2014) Metabolomic response of Calotropis procera growing in the desert to changes in water availability. PLoS ONE 9:e87895.  https://doi.org/10.1371/journal.pone.0087895 CrossRefPubMedPubMedCentralGoogle Scholar
  66. Rathore PK, Madihalli S, Hegde S, Hegde HV, Bhagwat RM, Gupta VS, Kholkute SD, Jha TB, Roy S (2016) Assessment of genetic diversity of Gymnema sylvestre (Retz.) R.Br. from Western Ghats and Eastern India. India. J Bio Env Sci 9:82–92Google Scholar
  67. Reddy N, Yang Y (2009) Extraction and characterization of natural cellulose fibers from common milkweed stems. Polym Eng Sci 49:2212–2217.  https://doi.org/10.1002/pen.21469 CrossRefGoogle Scholar
  68. Rousset F (2008) Genepop 007: a complete re-implementation of the Genepop software for Windows and Linux. Mol Ecol Resour 8:103–106.  https://doi.org/10.1111/j.1471-8286.2007.01931.x CrossRefPubMedGoogle Scholar
  69. Slatkin M (1985) Gene flow in natural populations. Annu Rev Ecol Syst 16:393–430CrossRefGoogle Scholar
  70. Smith JM (1999) Evolutionary genetics. Oxford University Press, OxfordGoogle Scholar
  71. Su Z, Richardson BA, Zhuo L, Jiang X, Li W, Kang X (2017) Genetic diversity and structure of an endangered desert shrub and the implications for conservation. AoB Plants 9:plx016. https://doi.org/10.1093/aobpla/plx016 CrossRefPubMedPubMedCentralGoogle Scholar
  72. Szczecińska M, Sramko G, Wołosz K, Sawicki J (2016) Genetic diversity and population structure of the rare and endangered plant species Pulsatilla patens (L.) Mill in East Central Europe. PLoS ONE 11: e0151730. https://doi.org/10.1371/journal.pone.0151730 CrossRefPubMedPubMedCentralGoogle Scholar
  73. Tabkhkar N, Rabiei B, Samizadeh Lahiji H, Hosseini Chaleshtori M (2018) Genetic variation and association analysis of the SSR markers linked to the major drought-yield QTLs of rice. Biochem Genet 56:356–374.  https://doi.org/10.1007/s10528-018-9849-6 CrossRefPubMedGoogle Scholar
  74. Tanuj Kanchan MD, Alok Atreya MD (2016) Calotropis gigantea. Wild. Environ Med 27:350–351.  https://doi.org/10.1016/j.wem.2015.12.011 CrossRefGoogle Scholar
  75. Tariq A, Sadia S, Pan K, Ullah I, Mussarat S, Sun F, Abiodun OO, Batbaatar A, Li Z, Song D, Xiong Q, Ullah R, Khan S, Basnet BB, Kumar B, Islam R, Adnan M (2017) A systematic review on ethnomedicines of anti-cancer plants. Phytother Res 31:202–264.  https://doi.org/10.1002/ptr.5751 CrossRefPubMedGoogle Scholar
  76. Torezan JMD, Souza RFD, Ruas PM, Ruas CDF, Camargo EH, Vanzela ALL (2005) Genetic variability of pre and post-fragmentation cohorts of Aspidosperma polyneuron Muell. Arg. (Apocynaceae). Braz Arch Biol Technol 48:171–180.  https://doi.org/10.1590/S1516-89132005000200002 CrossRefGoogle Scholar
  77. Turchetto C, Segatto ALA, Beduschi J, Bonatto SL, Freitas LB (2015). Genetic differentiation and hybrid identification using microsatellite markers in closely related wild species. AoB Plants 7:plv084. https://dx.doi.org/10.1093/aobpla/plv084 CrossRefPubMedPubMedCentralGoogle Scholar
  78. van Oosterhout C, Hutchinson WF, Wills DPM, Shipley P (2004). MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data. Mol Ecol Notes 4:535–538. https://doi.org/ 10.1111/j.1471-8286.2004.00684.xCrossRefGoogle Scholar
  79. Wei ZZ, Du QZ, Zhang JF, Li BL, Zhang DQ (2013) Genetic diversity and population structure in Chinese indigenous poplar (Populus simonii) populations using microsatellite markers. Plant Mol Biol Rep 31:620–632.  https://doi.org/10.1007/s11105-012-0527-2 CrossRefGoogle Scholar
  80. Worldometers (2018) Bangladesh population (LIVE). https://www.worldometers.info/world-population/bangladesh-population/. Accessed on 29 July 2018
  81. Yamashiro T, Yamashiro A, Inoue M, Maki M (2016) Genetic diversity and divergence in populations of the threatened grassland perennial Vincetoxicum atratum (Apocynaceae-Asclepiadoideae) in Japan. J Hered 107:455–462.  https://doi.org/10.1093/jhered/esw034 CrossRefPubMedGoogle Scholar
  82. Zhao AL, Chen XY, Zhang X, Zhang D (2006) Effects of fragmentation of evergreen broad-leaved forests on genetic diversity of Ardisia crenata var. bicolor (Myrsinaceae). Biodivers Conserv 15:1339–1351CrossRefGoogle Scholar
  83. Zhao J, Solís-Montero L, Lou A, Vallejo-Marín M (2013) Population structure and genetic diversity of native and invasive populations of Solanum rostratum (Solanaceae). PLoS ONE 8:e79807.  https://doi.org/10.1371/journal.pone.0079807 CrossRefPubMedPubMedCentralGoogle Scholar

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Authors and Affiliations

  • Md. Rabiul Islam
    • 1
    • 2
    • 3
    • 4
  • Zhi-Zhong Li
    • 1
    • 3
  • Andrew W. Gichira
    • 1
    • 3
  • Mohammad Nur Alam
    • 1
    • 3
  • Peng-Cheng Fu
    • 5
  • Guang-Wan Hu
    • 1
    • 2
  • Qing-Feng Wang
    • 1
    • 2
    Email author
  • Ling-Yun Chen
    • 1
    • 2
    Email author
  1. 1.Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical GardenChinese Academy of SciencesWuhanChina
  2. 2.Sino-Africa Joint Research CenterChinese Academy of SciencesWuhanChina
  3. 3.University of Chinese Academy of SciencesBeijingChina
  4. 4.Department of Crop Physiology and EcologyHajee Mohammad Danesh Science and Technology UniversityDinajpurBangladesh
  5. 5.Life Science CollegeLuoyang Normal UniversityLuoyangChina

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