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Genetic Resources and Crop Evolution

, Volume 57, Issue 7, pp 995–1005 | Cite as

Investigation of recent population bottlenecks in Kenyan wild sorghum populations (Sorghum bicolor (L.) Moench ssp. verticilliflorum (Steud.) De Wet) based on microsatellite diversity and genetic disequilibria

  • M. M. Muraya
  • F. Sagnard
  • H. K. Parzies
Research Article

Abstract

Identifying populations that have recently suffered a severe reduction in size is particularly important for their conservation as they are likely to suffer an increased risk of genetic erosion. We investigated the presence of recent bottlenecks in two wild sorghum populations from different eco-geographical conditions in Kenya employing 18 microsatellite markers. Microsatellite analysis showed high allelic diversity in the two populations, with a mean of 4.11 and 6.94 alleles per locus in the North-West wild sorghum population (NWWSP) and the South-East wild sorghum population (SEWSP), respectively. The mean observed heterozygosity was 0.34 and 0.56 in NWWSP and SEWSP, respectively. A large long-term effective populations size for both populations was observed assuming either an infinite allele model or a stepwise mutation model. There was no apparent loss of genetic variability for either of the populations. Test of heterozygosity excess indicated that a recent bottleneck in the two populations is highly unlikely. Furthermore, analysis of the allele frequency distribution revealed an L-shaped distribution which would not have been observed in case a recent bottleneck had reduced genetic variability in the two populations. The fact that most loci displayed a significant heterozygosity deficiency could be explained by population subdivision and the mixed mating system exhibited by wild sorghum populations. Furthermore, the possibility of a historical expansion of wild sorghum populations and presence of null alleles could not be ruled out.

Keywords

Bottleneck Genetic diversity Linkage disequilibrium Microsatellite markers Null allele Sorghum bicolor ssp. verticilliflorum Wild sorghum population 

Notes

Acknowledgment

This study was funded by the United States Agency for International Development (USAID) Biotechnology and Biodiversity Interface Program (BBI), the Institute of Plant Breeding and Population Genetics at the University of Hohenheim, Germany, and Germany Academic Exchange Service (DAAD: A0523923). We are grateful to Kenya Agricultural Research Institute and Ben Kanyenji who supervised the collection of genetic materials in full compliance with regulations according to the Convention on Biological Diversity (CBD).

References

  1. Beaumont MA, Rannala B (2004) The Bayesian revolution in genetics. Nat Rev Genet 5:251–261CrossRefPubMedGoogle Scholar
  2. Brown SM, Hopkins MS, Mitchell SE, Senior ML, Wang TY, Duncan RR et al (1996) Multiple methods for identification of polymorphic simple sequence repeats (SSRs) in sorghum (Sorghum bicolor (L.) Moench). Theor Appl Genet 93:190–198CrossRefGoogle Scholar
  3. Chikhi L, Bruford MW (2005) Mammalian population genetics and genomics. In: Ruvinsky A, Marshall-Graves J (eds) Mammalian genomics. CABI Publishing, OxfordGoogle Scholar
  4. Cornuet JM, Luikart G (1997) Description and power analysis of two tests for detecting recent population bottlenecks from allele frequency data. Genetics 144:2001–2014Google Scholar
  5. de Wet JMJ (1978) Systematics and evolution of Sorghum sect. Sorghum (Gramineae). Amer J Bot 65:477–484CrossRefGoogle Scholar
  6. Dempster AP, Laird NM, Rubin DB (1977) Maximum likelihood from incomplete data via the EM algorithm. J R Stat Soc B 39:1–38Google Scholar
  7. Estoup A, Tailliez C, Cornuet JM, Solignac M (1995) Size homoplasy and mutational processes of interrupted microsatellites in two bee species, Apis mellifera and Bombus terrestris (Apidae). Mol Biol Evol 12:1074–1084PubMedGoogle Scholar
  8. Frankham R (1998) Inbreeding and extinction: island populations. Conserv Biol 12:665–675CrossRefGoogle Scholar
  9. Franklin IR (1980) Evolutionary changes in small populations. In: Soulé ME, Wilcox BA (eds) Conservation biology: an evolutionary-ecological perspective. Sinauer Associates, Sunderland, Massachusetts, pp 135–150Google Scholar
  10. Garnier-Gere P, Dillmann C (1992) A computer program for testing pairwise linkage disequilibria in subdivided populations. J Hered 83:239PubMedGoogle Scholar
  11. Goossens B, Chikhi L, Ancrenaz M, Lackman-Ancrenaz I, Andau P, Bruford MW (2006) Genetic signature of anthropogenic population collapse in orang-utans. PLoS Biol 4:285–291CrossRefGoogle Scholar
  12. Houlden BA, England PR, Taylor AC, Greville WD, Sherwin WB (1996) Low genetic variability of the koala Phascolarctos cinereus in south-eastern Australia following a severe population bottleneck. Mol Ecol 5:269–281PubMedGoogle Scholar
  13. Keller LF, Waller DM (2002) Inbreeding effects in wild populations. Trends Ecol Evol 17:230–241CrossRefGoogle Scholar
  14. Kimura M (1983) The neutral theory of molecular evolution. United Kingdom, Cambridge University PressCrossRefGoogle Scholar
  15. Kong L, Dong J, Hart GE (2000) Characteristics, linkage-map positions, and allelic differentiation of Sorghum bicolor (L.) Moench DNA simple-sequence repeats (SSRs). Theor Appl Genet 101:438–448CrossRefGoogle Scholar
  16. Kwok S, Kellog DE, McKinney N, Spasic D, Goda L, Levenson C et al (1990) Effects of primer-template mismatches on the polymerase chain reaction: human immunodeficiency virus 1 model studies. Nucleic Acids Res 18:999–1005CrossRefPubMedGoogle Scholar
  17. Lehmann T, Hawley WA, Grebert H, Collins FH (1998) The effective population size of Anopheles gambiae in Kenya: implications for population structure. Mol Biol Evol 15:264–276PubMedGoogle Scholar
  18. 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
  19. Luikart G, Allendorf FW, Cornuet JM, Sherwin WB (1998a) Distortion of allele frequency distributions provides a test for recent population bottlenecks. J Hered 89:238–247CrossRefPubMedGoogle Scholar
  20. Luikart G, Sherwin WB, Steele BM, Allendorf FW (1998b) Usefulness of molecular markers for detecting population bottlenecks via monitoring genetic change. Mol Ecol 7:963–974CrossRefPubMedGoogle Scholar
  21. Luikart G, England PR, Tallomon D, Jordan S, Taberlet P (2003) The power and promise of population genomics: from genotyping to genome typing. Nat Rev Genet 4:981–994CrossRefPubMedGoogle Scholar
  22. Mace ES, Buhariwalla HK, Crouch JH (2003) A high throughput DNA extraction protocol for molecular breeding programs. Plant Mol Biol Rep 21:459a–459hCrossRefGoogle Scholar
  23. Mann JA, Kimber CT, Miller FR (1983) The origin and early cultivation of sorghums in Africa. Texas Agricultural Experiment Station, Bulletin 1454Google Scholar
  24. Maruyama T, Fuerst PA (1985) Population bottlenecks and non equilibrium models in population genetics. II. Number of alleles in a small population that was formed by a recent bottleneck. Genetics 111:675–689PubMedGoogle Scholar
  25. Mills LS, Smouse PE (1994) Demographic consequences of inbreeding in remnant populations. Am Nat 144:412–431CrossRefGoogle Scholar
  26. Nei M (1987) Molecular evolutionary genetics. Columbia University Press, New YorkGoogle Scholar
  27. Nei M, Maruyama T, Chakraborty R (1975) The bottleneck effect and genetic variability in populations. Evolution 29:1–10CrossRefGoogle Scholar
  28. Raymond M, Rousset F (1995) An exact test for population differentiation. Evolution 49:1280–1283CrossRefGoogle Scholar
  29. Saillant E, Patton JC, Ross KE, Gold JR (2004) Conservation genetics and demographic history of the endangered Cape Fear shiner (Notropis mekistocholas). Mol Ecol 13:2947–2958CrossRefPubMedGoogle Scholar
  30. Schloss SJ, Mitchell SE, White GM, Kukatla R, Bowers JE, Paterson AH et al (2002) Characterization of RFLP probe sequences for gene discovery and SSR development in Sorghum bicolor (L.) Moench. Theor Appl Genet 105:912–920CrossRefPubMedGoogle Scholar
  31. Schwartz MK, Luikart G, Waples RS (2007) Genetic monitoring as a promising tool for conservation and management. Trends Ecol Evol 22:25–33CrossRefPubMedGoogle Scholar
  32. Slatkin M (1995) Hitchhiking and associative overdominance at a microsatellite locus. Mol Biol Evol 12:473–480PubMedGoogle Scholar
  33. Spencer CC, Neigel JE, Leberg PL (2000) Experimental evaluation of the usefulness of microsatellite DNA for detecting bottlenecks. Mol Ecol 9:1517–1528CrossRefPubMedGoogle Scholar
  34. Taramino G, Tarchini R, Ferrario S, Lee M, Pe’ ME (1997) Characterisation and mapping of simple sequence repeats (SSR) in Sorghum bicolor. Theor Appl Genet 95:66–72CrossRefGoogle Scholar
  35. Thuillet A-C, Bru D, David J, Roumet P, Santoni S, Sourdille P et al (2002) Direct estimation of mutation rate for 10 microsatellite loci in durum wheat, Triticum turgidum (L.) Thell. ssp. durum Desf. Mol Biol Evol 19:122–125PubMedGoogle Scholar
  36. Thuillet A-C, Bataillon T, Poirier S, Santoni S, David JL (2005) Estimation of long-term effective population sizes through the history of durum wheat using microsatellite data. Genetics 169:1589–1599CrossRefPubMedGoogle Scholar
  37. United Nations Environment Programme Convention on Biological Diversity (UNEPCD) SBSTTA (2003) Monitoring and indicators: designing national-level monitoring programmes and indicators, United NationsGoogle Scholar
  38. Waples RS (1991) Genetic methods for estimating the effective population size of cetacean populations. In: Hoelzel AR (ed) Genetic ecology of whales and dolphins. International Whaling Commission, Cambridge, pp 279–300 (Spec Issue No 13)Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.Institute of Plant Breeding, Seed Science and Population GeneticsUniversity of HohenheimStuttgartGermany
  2. 2.Leibniz Institute of Plant Genetics and Crop Plant ResearchGaterslebenGermany
  3. 3.CIRAD-UMR Développement et Amélioration des PlantesNairobiKenya
  4. 4.International Crops Research Institute for the Semi-Arid Tropics (ICRISAT-Nairobi)NairobiKenya

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