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Genetic Resources and Crop Evolution

, Volume 59, Issue 7, pp 1449–1464 | Cite as

Molecular diversity, genetic structure and mating system of Calopogonium mucunoides Desv.

  • A. C. B. Sousa
  • M. A. Carvalho
  • T. Campos
  • D. A. Sforça
  • M. I. Zucchi
  • L. Jank
  • A. P. SouzaEmail author
Research Article

Abstract

Calopogonium mucunoides Desv. is a species native of South and Central America that is used as green manure and a pasture crop. The molecular genetic diversity was characterized in 195 C. mucunoides accessions from a germplasm collection using 17 microsatellite markers. Outcrossing rate was estimated after the evaluation of six microsatellite loci in 200 genotypes originated from 10 open-pollinated progenies (20 genotypes per progeny). Six genetic clusters were identified in the germplasm collection by the STRUCTURE software analysis, neighbor-joining tree comparisons and principal component analysis, which highly correlated with the geographic locations where these accessions were originated or collected. These results were confirmed using AMOVA. The largest portion of the genetic variation was observed among clusters (64.38%). The results indicated that: multilocus outcrossing rate (t m ) was 16.3%, suggesting a mixed mating system with a predominance of autogamy; single locus outcrossing rate (t s ) was 11%; difference (t m t s ) was 0.054, indicating that only 5.4% of outcrossing occurred among related individuals; paternity correlation (r p ) was 33% suggesting a low probability of finding full sibs among the progeny; parental coefficient of inbreeding (F m ) was 5.0%, indicating a low degree of inbreeding in each parent. A core collection for C. mucunoides was assembled to capture the allelic diversity found in this study. The complete allelic diversity was represented by only 15 accessions. These results should be useful for exploiting the genetic resources of C. mucunoides and could influence future conservation efforts and breeding programs.

Keywords

Allelic diversity Autogamy Calopogonium mucunoides Germplasm collection Microsatellite markers Outcrossing rate 

Notes

Acknowledgments

The authors are grateful to the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) for financial support (Project 05/51010-0) and a graduate fellowship to A. C. B. Sousa (06/52953-8) and, to the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for research fellowships awarded to A. P. Souza and L. Jank.

References

  1. Blouin MS, Parsons M, Lacaille V, Lotz S (1996) Use of microsatellite loci to classify individuals by relatedness. Mol Ecol 7:393–401Google 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 32:314–331PubMedGoogle Scholar
  3. Brookfield JFY, Jin L (1993) Use of single-locus DNA probes in the establishment of relatedness in wild populations. Heredity 70:660–663CrossRefGoogle Scholar
  4. Brown AHD (1989) Core collection: a practical approach to genetic resources management. Genome 31:818–824CrossRefGoogle Scholar
  5. Carvalho-Okano RM, Leitão Filho HF (1985) Revisão taxonômica do gênero Calopogonium Desv. (Leguminosae–Lotoideae) no Brasil. Revista Brasileira de Botânica 8:31–45Google Scholar
  6. Chen CP, Aminah A (1992) Calopogonium mucunoides. In: Mannetje L, Jones RM (eds) Plant resources of South-East Asia No. 4. Forages. Pudoc Scientific Publishers, Wageningen, pp 72–74Google Scholar
  7. Chen YW, Nelson LR (2005) Relationship between origin and genetic diversity in Chinese soybean germplasm. Crop Sci 45:1645–1652CrossRefGoogle Scholar
  8. Cipriani G, Spadotto A, Jurman I, Gaspero GD, Crespan M, Meneghetti S, Frare E, Vignani R, Cresti M, Morganti M, Pezzotti M, Pe E, Policriti A, Testolin R (2010) The SSR-based molecular profile of 1005 grapevine (Vitis vinifera L.) accessions uncovers new synonymy and parentages, and reveals a large admixture amongst varieties of different geographic origin. Theor Appl Genet 121:1569–1585PubMedCrossRefGoogle Scholar
  9. Coelho ASG, Boo D (2002) Avaliação dos erros associados a estimativas de distâncias/similaridades genéticas através do procedimento de bootstrap com número variável de marcadores. Laboratório de Genética Vegetal, Instituto de Ciências biológicas, Universidade Federal de Goiás, GoiâniaGoogle Scholar
  10. Creste S, Tulmann Neto A, Figueira A (2001) Detection of single sequence repeat polymorphisms in denaturing polyacrylamide sequencing gels by silver staining. Plant Mol Biol Repor 19:299–306CrossRefGoogle Scholar
  11. Cruz Filho AB, Jorge EMP, Alvin MJ (1983) Comparação entre populações de Calopogonium mucunoides Desv. Revista de Zootecnia 21:61–70Google Scholar
  12. Degen B, Bandou E, Caron H (2004) Limited pollen dispersal and biparental inbreeding in Symphonia globulifera in French Guiana. Heredity 93:585–591PubMedCrossRefGoogle Scholar
  13. Don RH, Cox PT, Wainwright BJ, Baker K, Mattick JS (1991) “Touchdown” PCR to circumvent spurious priming during gene amplification. Nucleic Acids Res 19:4008PubMedCrossRefGoogle Scholar
  14. Doyle JJ, Doyle JL (1990) Isolation of plant DNA from fresh tissue. Focus 12:13–15Google Scholar
  15. Escribano P, Viruel MA, Hormaza JI (2008) Comparison of different methods to construct a core germplasm collection in Woody perennial species with simple sequence repeat markers. A case study in cherimoya (Annona cherimola, Annonaceae), an underutilized subtropical fruit tree species. Ann Appl Biol 153:25–32CrossRefGoogle Scholar
  16. Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 18:2611–2620CrossRefGoogle Scholar
  17. Excoffier L, Laval G, Schneider S (2005) Arlequin ver. 3.0: an integrated software package for population genetics data analysis. Evol Bioinform Online 1:47–50Google Scholar
  18. Franceschinelli EV, Bawa KS (2000) The effect of ecological factors on the mating system of a South American shrub species (Helicteres brevispira). Heredity 84:116–123PubMedCrossRefGoogle Scholar
  19. Francimary SC, Sebbenn AM, Kanashiro M, Degen B (2007) Low interannual variation of mating system and gene flow of Symphonia globulifera in the Brazilian Amazon. Biotropica 39:628–636CrossRefGoogle Scholar
  20. Gaitán-Solís E, Duque MC, Edwards KJ, Tohme J (2003) Microsatellite in common bean (Phaseolus vulgaris): isolation, characterization, and cross-species amplification in Phaseolus ssp. Crop Sci 42:2128–2136CrossRefGoogle Scholar
  21. Gouesnard B, Bataillon TM, Decoux G, Rozale C, Schoen DJ, David JL (2001) MSTRAT: an algorithm for building germplasm core collections by maximizing allelic or phenotypic richness. J Hered 92:93–94PubMedCrossRefGoogle Scholar
  22. Gupta PK, Varshney RK (2000) The development and use of microsatellite markers for genetics analysis and plant breeding with special emphasis on bread wheat. Euphytica 113:163–185CrossRefGoogle Scholar
  23. Hamrich J, Godt M (1996) Effects of life history traits on genetic diversity in plant species. Philos Trans Royal Soc 351:1291–1298CrossRefGoogle Scholar
  24. Hao CY, Zhang XY, Wang LF, Dong YS, Shang XW, Jia JZ (2006) Genetic diversity and core collection evaluations in common wheat germplasm from the Northwestern spring wheat region in China. Mol Breed 17:69–77CrossRefGoogle Scholar
  25. Hijmans RJ, Guarino L, Cruz M, Rojas E (2001) Computer tools for spatial analysis of plant genetic resources data: 1. DIVA-GIS. Plant Genet Resour 127:15–19Google Scholar
  26. Kapila RK, Yadav RS, Plaha P, Rai KN, Yadav OP, Hash CT, Howarth CJ (2008) Genetic diversity among pearl millet maintainers using microsatellite markers. Plant Breed 127:33–37Google Scholar
  27. Lewis P, Zaykin D (2002) Genetic data analysis (GDA): computer program for the analysis of allelic of allelic data (software), version 1.1 (d12). http://alleyn.eeb.uconn.edu/gda/
  28. McSweeney CS, Wesley-Smith RN (1986) Factors affecting the intake by sheep of the tropical legume, Calopogonium mucunoides. Aust J Exp Agric 26:659–664CrossRefGoogle Scholar
  29. Miller MP (1997) Tools for population genetic analysis (TFPGA) 1.3. A windows program for the analysis of allozyme and molecular population genetic data. Computer software distributed by authorGoogle Scholar
  30. Moretzsohn MC, Hopkins MS, Mitchell SE, Kresovich S, Valls JFM, Ferreira ME (2004) Genetic diversity of peanut (Arachis hypogaea L.) and its wild relatives based on the analysis of hypervariable regions of the genome. BMC Plant Biol 4:11CrossRefGoogle Scholar
  31. Ozkan H, Kafkas S, Ozer M, Brandolini A (2005) Genetic relationships among South-East Turkey wild barley populations and sampling strategies of Hordeum spontaneum. Theo Appl Gene 112:12–20Google Scholar
  32. Parzies HK, Fosung Nke C, Abdel-Ghani AH, Geiger HH (2008) Outcrossing rate of barley genotypes with different floral characteristics in drought-stressed environments in Jordan. Plant Breed 127:536–538CrossRefGoogle Scholar
  33. Peralta A, Teledo JM (1991) Establecimiento y renovación de pasturas. Conceptos, experiências y enfoque de La investigación. In: Lascano CE, Spain JM (eds) La problemática Del establecimiento y La recuperación de pasturas. Sexta Reunión Del Comité Asesor de La RIEPT. International Center for Tropical Agriculture (CIAT), Veracruz, pp 1–15Google Scholar
  34. Perrier X, Jacquemound-Collet JP (2006) DARwin software. Available from http://www.darwin.cirad.fr/darwin
  35. Pizarro EA, Carvalho MA (1997) Evaluation of a collection of Calopogonium mucunoides Desv. for the Cerrado Ecosystem, Brazil. Agronomists 15:17–21Google Scholar
  36. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959PubMedGoogle Scholar
  37. Ritland K (1989) Correlated matings in the partial selfer Mimulus guttatus. Evolution 43:849–859CrossRefGoogle Scholar
  38. Ritland K (2002) Extensions of models for the estimation of mating system using an independent loci. Heredity 88:221–228PubMedCrossRefGoogle Scholar
  39. Ritland K, Jain S (1981) A model for the estimation of outcrossing rate and gene frequencies using an independent loci. Heredity 47:35–52CrossRefGoogle Scholar
  40. Santos-Garcia MO, Resende RMS, Chiari L, Zucchi MI, Souza AP (2011) Mating systems in tropical forages: Stylosanthes capitata Vog. and Stylosanthes guianensis (Aubl.) Sw. Euphytica 178:185–193CrossRefGoogle Scholar
  41. Schoen DJ, Brown AHD (1993) Conservation of allelic richness in wild crop relatives is aided by assessment of genetic-markers. Proc Natl Acad Sci USA 90:10623–10627PubMedCrossRefGoogle Scholar
  42. Sivaramakrishnan S, Seetha K, Reddy LJ (2002) Diversity in selected wild and cultivated species of pigeonpea using RFLP of mtDNA. Euphytica 125:21–28CrossRefGoogle Scholar
  43. Sousa ACB, Carvalho MA, Ramos AKB, Sforça DA, Campos T, Jungmann L, Zucchi MI, Jank L, Souza AP (2010) Development and characterization of microsatellite loci for Calopogonium mucunoides Desv. Mol Ecol Resour Primer Dev Consortium Mol Ecol Resour 10:576–579Google Scholar
  44. Sousa ACB, Carvalho MA, Ramos AKB, Sforça DA, Campos T, Zucchi MI, Jank L, Souza AP (2011) Genetic studies in Centrosema pubescens Benth, a tropical forage legume: the mating system, genetic variability and genetic relationships between Centrosema species. Euphytica. doi: 10.1007/s10681-011-0415-0 (Online first)
  45. Tautz D, Trick M, Dover GA (1986) Cryptic simplicity in DNA is a major source of genetic variation. Nature 322:652–656PubMedCrossRefGoogle Scholar
  46. Tessier C, David J, This P, Boursiquot JM, Charrier A (1999) Optimization of the choice of molecular markers for varietal identification in Vitis vinifera L. Theor Appl Genet 98:171–177CrossRefGoogle Scholar
  47. van Hintum TJL, Brown AHD, Spilane G, Hodgkin T (2000) Core collections of plants genetic resources. IPGRI. (Technical Bulletin, 3), Rome, p 48Google Scholar
  48. Varela VP, Gurgel ESC (2001) Tratamentos pré-germinativos em sementes de Calopogônio (Calopogonium mucunoides Desv.)–Leguminosae, Papilionoideae. Revista Ciências Agrárias 35:89–96Google Scholar
  49. Varshney RK, Graner A, Sorrells ME (2005) Genic microsatellite markers in plants: features and applications. Trends Biotechnol 23:48–55PubMedCrossRefGoogle Scholar
  50. Veasey EA, Werner JC, Colozza MT, Freitas JCT, Lucena MAC, Beisman DA, Gerdes L (1999) Evaluation of morphological, phenological and agronomic characters of tropical forage legumes in relation to seed production. Boletim de Industria Animal 56:109–125Google Scholar
  51. Wang LX, Guan RX, Li YH, Lin FY, Luan WJ, Li W, Ma YS, Liu ZX, Chang RZ, Qiu LJ (2008) Genetic diversity of Chinese spring soybean germplasm revealed by SSR markers. Plant Breed 127:56–61Google Scholar
  52. Wu KS, Tanksley SD (1993) Abundance, polymorphism and genetic mapping of microsatellites in rice. Mol Gen Genet 241:225–235PubMedCrossRefGoogle Scholar
  53. Xiao J, Li J, Yuan L, McCouch SR, Tanksley SD (1996) Genetic diversity and its relationship to hybrid performance and heterosis in rice as revealed by PCR-based markers. Theor Appl Genet 92:637–643CrossRefGoogle Scholar
  54. Zane L, Bargelloni L, Patarnello T (2002) Strategies for microsatellite isolation: a review. Mol Ecol 11:1–16PubMedCrossRefGoogle Scholar
  55. Zhao W, Miao X, Jia S, Pan Y, Huang Y (2005) Isolation and characterization of microsatellite loci from the mulberry, Morus L. Plant Sci 168:519–525CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • A. C. B. Sousa
    • 1
    • 7
  • M. A. Carvalho
    • 2
  • T. Campos
    • 3
  • D. A. Sforça
    • 1
  • M. I. Zucchi
    • 4
  • L. Jank
    • 5
  • A. P. Souza
    • 1
    • 6
    Email author
  1. 1.Genetic Engineering and Molecular Biology Center (CBMEG)University of Campinas (UNICAMP)CampinasBrazil
  2. 2.Brazilian Agricultural Research Corporation, Embrapa CerradosPlanaltinaBrazil
  3. 3.Brazilian Agricultural Research Corporation, Embrapa AcreRio BrancoBrazil
  4. 4.São Paulo Agency of Technology and Agro-BusinessPólo Apta Centro SulPiracicabaBrazil
  5. 5.Forage Breeding DepartmentBrazilian Agricultural Research Corporation, Embrapa Beef CattleCampo GrandeBrazil
  6. 6.Plant Biology Department (DBV)Biology Institute, University of Campinas (UNICAMP)CampinasBrazil
  7. 7.Vegetal Biology Department (PPGBVeg)Universidade do Estado da Bahia (UNEB)Paulo AfonsoBrazil

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