Hostname: page-component-78c5997874-dh8gc Total loading time: 0 Render date: 2024-11-18T15:18:38.588Z Has data issue: false hasContentIssue false

Do Mediterranean crickets Gryllus bimaculatus De Geer (Orthoptera: Gryllidae) come from the Mediterranean? Largescale phylogeography and regional gene flow

Published online by Cambridge University Press:  27 March 2009

M. Ferreira
Affiliation:
Centre for Environmental Studies, Department of Zoology and Entomology, University of Pretoria, Pretoria0002, South Africa
J.W.H. Ferguson*
Affiliation:
Centre for Environmental Studies, Department of Zoology and Entomology, University of Pretoria, Pretoria0002, South Africa
*
*Author for correspondence Fax: +27 12 420 3210 E-mail: willemferguson@zoology.up.ac.za

Abstract

We investigate the degree of between-population genetic differentiation in the Mediterranean field cricket Gryllus bimaculatus, as well as the possible causes of such differentiation. Using cytochrome b mtDNA sequences, we estimate genetic variation in G. bimaculatus from seven South African and two Mediterranean populations. Within-population genetic variation in Europe (two haplotypes, one unique to a single individual) suggest low effective population size and strong bottlenecks with associated founder effects, probably due to cold winter environments in Europe that limit reproduction to a short part of the summer. The likely cause for this is the daily maxima in winter temperatures that fall below the critical level of 16°C (enabling normal calling and courtship behaviour) in Mediterranean Europe, whereas the equivalent temperatures in southern Africa are above this limit and enable reproduction over a large part of the year. European genetic variants were either shared with Africa or closely related to African haplotypes. For survival, European populations are probably dependent on immigration from other areas, including Africa. South African populations have low but measurable gene flow with Europe and show significant between-population genetic differentiation (30 haplotypes). Isolation-by-distance is not sufficient to explain the degree of between-population genetic differences observed, and a large degree of dispersal is also required in order to account for the observed patterns. Differences in morphology and calling behaviour among these populations are underlied by these genetic differences.

Type
Research Paper
Copyright
Copyright © 2009 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Arctander, P. (1995) Comparison of a mitochondrial gene and a corresponding nuclear pseudogene. Proceedings of the Royal Society of London B 262, 1319.Google Scholar
Beerli, P. (2004) Comparison of Bayesian and maximum-likelihood inference of population genetic parameters. Bioinformatics 22, 341345.CrossRefGoogle Scholar
Bensasson, D., Zhang, D.-X. & Hewitt, G.M. (2000) Frequent assimilation of mitochondrial DNA by grasshopper nuclear genomes. Molecular Biology and Evolution 17, 406415.CrossRefGoogle ScholarPubMed
Bretman, A.J., Wedell, N. & Tregenza, T. (2004) Molecular evidence of post-copulatory inbreeding avoidance in the field cricket Gryllus bimaculatus. Proceedings of the Royal Society of London. Series B: Biological Sciences 271, 159164.CrossRefGoogle ScholarPubMed
Broughton, R.E. & Harrison, R.G. (2003) Nuclear gene genealogies reveal historical, demographic and selective factors associated with speciation in field crickets. Genetics 163, 13891401.CrossRefGoogle ScholarPubMed
Business Monitor International (2008) The South Africa Freight Transport Report 2008. Business Monitor Inernational. London, Blackfriars.Google Scholar
Castelloe, J. & Templeton, A.R. (1994) Root probabilities for intraspecific gene trees under neutral coalescent theory. Molecular Phylogenetics and Evolution 3, 102113.CrossRefGoogle ScholarPubMed
Clement, M. & Posada, D. & Crandall, K.A. (2000) TCS: a computer program to estimate gene genealogies. Molecular Ecology 9, 16571660.CrossRefGoogle ScholarPubMed
Donnelly, P. & Tavarè, S. (1986) The ages of alleles and a coalescent. Advances in Applied Probability 18, 119.CrossRefGoogle Scholar
Excoffier, L., Smouse, P.E. & Quattro, J.M. (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131, 479491.CrossRefGoogle ScholarPubMed
Ferreira, M. (2006) Evolutionary implications of variation in the calling song of the cricket Gryllus bimaculatus De Geer (Orthoptera: Gryllidae). MSc thesis, University of Pretoria. Pretoria, South Africa.Google Scholar
Ferreira, M. & Ferguson, J.W.H. (2002) Geographic variation in the calling song of the field cricket Gryllus bimaculatus (Orthoptera: Gryllidae) and its relevance to mate recognition and mate choice. Journal of Zoology, London 257, 163170.CrossRefGoogle Scholar
Harley, E.H. (2000) Dapsa: A program for DNA and protein sequence analysis, version 4.9. Department of Chemical Pathology, University of Cape Town, South Africa.Google Scholar
Harrison, R.G. & Bogdanowicz, S.M. (1995) Mitochondrial DNA phylogeny of North American field crickets: perspectives on the evolution of life cycles, songs, and habitat associations. Journal of evolutionary Biology 8, 209232.CrossRefGoogle Scholar
Ji, Y.-J., Zhang, D.-X. & He, L.-J. (2003) Evolutionary conservation and versatility of a new set of primers for amplifying the ribosomal internal transcribed spacer regions in insects and other invertebrates. Molecular Ecology Notes 3, 581585.CrossRefGoogle Scholar
Lansman, R.A., Shade, R.O., Shapira, J.F. & Avise, J.C. (1981) The use of restriction endonucleases to measure mitochondrial DNA sequence relatedness in natural populations. III. Techniques and potential applications. Journal of Molecular Evolution 17, 214226.CrossRefGoogle ScholarPubMed
Liedloff, A. (1999) Mantel nonparametric test calculator for Windows, version 2.0. School of Natural Resource Sciences, Queensland University of Technology, Brisbane, Australia.Google Scholar
Mantel, N. (1967) The detection of disease clustering and a generalised regression approach. Cancer Research 27, 209220.Google Scholar
McCarthy, C. (1996) Chromas, version 1.45. School of Biomolecular and Biomedical Science, Griffith University, Southport, Queensland, Australia.Google Scholar
Panchal, M. & Beaumont, M.A. (2007) The automation and evaluation of nested clade phylogeographic analysis. Evolution 61, 14661480.CrossRefGoogle ScholarPubMed
Posada, D. & Crandall, K.A. (1998) Modeltest: testing the model of DNA substitution. Bioinformatics 14, 817818.CrossRefGoogle ScholarPubMed
Posada, D., Crandall, K.A. & Templeton, A.R. (2000) GeoDis: a program for the cladistic nested analysis of the geographical distribution of genetic haplotypes. Molecular Ecology 9, 487488.CrossRefGoogle ScholarPubMed
Preston-Whyte, R.A. & Tyson, P.D. (1988) The Atmosphere and Meather of Southern Africa. 374Cape Town, South Africa, Oxford University Press.Google Scholar
Ragge, D.R. (1972) An unusual case of mass migration by flight in Gryllus bimaculatus DeGeer (Orthoptera Gryllidae). Bulletin de l'Instution fond d'Afrique noire A 34, 869878.Google Scholar
Roff, D.A. & Bentzen, P. (1989) The statistical analysis of mitochondrial DNA polymorphisms: χ2 and the problem of small samples. Molecular Biology and Evolution 6, 539545.Google Scholar
Ryan, M.J., Rand, A.S. & Weigt, L.A. (1996) Allozyme and advertisement call variation in the túngara frog, Physalaemus pustulosus. Evolution 50, 24352447.Google ScholarPubMed
Schneider, S., Roessli, D. & Excoffier, L. (2000) Arlequin, version 2.000. A software for population genetics data analysis. Genetics and Biometry Laboratory, University of Geneva. Geneva, Switzerland.Google Scholar
Schulze, B.R. (1994) Climate of South Africa. Part 8: General survey. South African Weather Service, Department of Environment affairs, Pretoria, South Africa.Google Scholar
Tamura, K. & Nei, M. (1993) Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees. Molecular Biology and Evolution 10, 512526.Google ScholarPubMed
Templeton, A.R. (2004) Statistical phylogeography: methods of evaluating and minimizing inference errors. Molecular Ecology 13, 789809.CrossRefGoogle ScholarPubMed
Templeton, A.R. (2008) Nested clade analysis: an extensively validated method for strong phylogeographic inference. Molecular Ecology 17, 18771880.CrossRefGoogle ScholarPubMed
Templeton, A.R. & Sing, C.F. (1993) A cladistic analysis of phenotypic associations with haplotypes inferred from restriction endonuclease mapping. IV. Nested analyses with cladogram uncertainty and recombination. Genetics 134, 659669.CrossRefGoogle ScholarPubMed
Templeton, A.R., Crandall, K.A. & Sing, C.F. (1992) A cladistic analysis of phenotypic associations with haplotypes inferred from restriction endonuclease mapping and DNA sequence data. III. Cladogram estimation. Genetics 132, 619633.CrossRefGoogle ScholarPubMed
van Wyk, W.J. & Ferguson, J.W.H. (1995) Communicatory constraints on field crickets Gryllus bimaculatus calling at low ambient temperatures. Journal of Insect Physiology 41, 837841.CrossRefGoogle Scholar
Walsh, P.S., Metzger, D.A. & Higuchi, R. (1991) Chelex® 100 as a medium for simple extraction of DNA for PCR-based typing from forensic material. BioTechniques 10, 506513.Google ScholarPubMed
Whitlock, M.C. & McCauley, D.E. (1999) Indirect measures of gene flow and migration: F ST≠1/(4Nm+1). Heredity 82, 117125.CrossRefGoogle Scholar
Willett, C.S., Ford, M.J. & Harrison, R.G. (1997) Inferences about the origin of a field cricket hybrid zone from a mitochondrial DNA phylogeny. Heredity 79, 484494.CrossRefGoogle ScholarPubMed
Zhang, D.-X. & Hewitt, G.M. (1996) Highly conserved nuclear copies of the mitochondrial control region in the desert locust Schistocerca gregaria: some implications for population studies. Molecular Ecology 5, 295300.CrossRefGoogle ScholarPubMed