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Population Genetic Structuring in Acanthopagrus butcheri (Pisces: Sparidae): Does Low Gene Flow Among Estuaries Apply to Both Sexes?

Marine Biotechnology volume 9, pages 33–44 (2007)Cite this article

Abstract

Acanthopagrus butcheri completes its entire life history within estuaries and coastal lakes of southern Australia, although adults occasionally move between estuaries via the sea. Consequently, it is expected that populations of A. butcheri in different estuaries will be genetically distinct, with the magnitude of genetic divergence increasing with geographic isolation. However, previous genetic studies of A. butcheri from southeast Australia yielded conflicting results; allozyme variation exhibited minimal spatial structuring (θ = 0.012), whereas mitochondrial DNA distinguished the majority of populations analyzed (θ = 0.263) and genetic divergence was positively correlated with geographic isolation. This discrepancy could reflect high male gene flow, which impacts nuclear but not mitochondrial markers. Here we estimated allele frequencies at five nuclear microsatellite loci across 11 southeast Australian populations (595 individuals). Overall structuring of microsatellite variation was weaker (θ = 0.088) than that observed for mitochondrial DNA, but was able to distinguish a greater number of populations and was positively correlated with geographic distance. Therefore, we reject high male gene flow and invoke a stepping-stone model of infrequent gene flow among estuaries for both sexes. Likewise, management of A. butcheri within the study range should be conducted at the scale of individual or geographically proximate estuaries for both sexes. The lack of allozyme structuring in southeast Australia reflects either the large variance in structuring expected among loci under neutral conditions and the low number of allozymes surveyed or a recent colonization of estuaries such that some but not all nuclear loci have approached migration-drift equilibrium.

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Acknowledgments

Funding for the project was provided via a School of Life and Environmental Sciences grant to CPB. Prof. Chris Austin (Charles Darwin University) initiated genetic research of this species at Deakin University. We thank Patrick Coutin (Primary Industries Research Victoria) and Adrian Arkinstall, VICTAG Coordinator, Australian National Sportfishing Association, for assistance with the collection of samples. Devon Keeney (Otago University) and past and present members of the Molecular Ecology and Biodiversity Laboratory, Deakin University, made comments that improved the manuscript. Peter Unmack (University of Oklahoma) generously provided the template for Figure 1. The experiments described herein comply with the current Australian laws, and were approved by the Animal Ethics Committee of Deakin University.

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  1. Christopher P. Burridge

    Present address: Department of Zoology, University of Otago, 340 Great King Street, Dunedin, New Zealand

Authors and Affiliations

  1. School of Life and Environmental Sciences, Deakin University, PO Box 423, Warrnambool, Victoria, 3280, Australia

    Christopher P. Burridge & Vincent L. Versace

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Correspondence to Christopher P. Burridge.

Appendix

Appendix

Frequencies of microsatellite alleles and mitochondrial haplotypes at 11 populations of Acanthopagrus butcheri from southeast Australia

Locus/allele

Port Adelaide

Onkaparinga

Hindmarsh

Glenelg

Surrey

Hopkins

Painkalac

Thomson

Yarra

Gippsland

Sydenham

Asc21–218

(124)

(106)

(120)

(142)

(74)

(108)

(80)

(100)

(100)

(108)

(82)

222

–

–

–

–

–

–

–

–

0.010

0.019

–

234

–

–

–

–

–

0.009

–

–

–

–

–

240

0.024

0.019

–

0.197

0.216

0.102

0.188

0.140

0.090

0.093

0.183

244

0.016

0.009

–

–

–

0.009

0.013

0.050

–

–

–

246

0.016

–

0.017

0.014

0.095

0.065

0.050

0.070

0.100

0.176

0.195

248

0.032

0.019

–

0.092

0.108

0.019

–

0.010

0.010

0.019

0.085

250

0.903

0.943

0.933

0.627

0.446

0.731

0.650

0.560

0.730

0.537

0.463

252

–

–

0.017

0.007

–

0.009

–

0.020

0.010

0.065

0.049

254

0.008

0.009

0.033

0.063

0.135

0.046

0.087

0.110

0.050

0.083

0.012

256

–

–

–

–

–

0.009

0.013

0.040

–

0.009

0.012

Pab1H1

(110)

(106)

(116)

(140)

(56)

(104)

(80)

(96)

(100)

(108)

(84)

151

–

–

–

–

–

–

–

–

–

–

0.012

153

–

–

–

–

–

–

0.013

–

–

–

0.024

155

–

–

–

0.007

–

–

–

–

–

0.009

0.012

157

–

–

–

–

–

–

–

–

–

–

0.012

159

0.009

–

–

0.007

–

–

–

–

–

–

–

161

0.964

1.000

0.974

0.964

1.000

0.981

0.988

1.000

0.970

0.870

0.869

163

–

–

–

0.007

–

0.010

–

–

–

0.019

0.024

165

0.027

–

0.009

0.014

–

–

–

–

–

0.046

0.012

167

–

–

–

–

–

0.010

–

–

0.020

0.037

0.024

169

–

–

0.017

–

–

–

–

–

0.010

0.019

0.012

Pab2D11

(126)

(132)

(120)

(144)

(80)

(108)

(80)

(100)

(102)

(108)

(84)

122

–

–

–

0.021

–

–

–

–

–

–

–

126

0.968

0.955

0.900

0.938

1.000

0.843

0.837

0.870

0.990

0.306

0.369

128

–

–

–

0.028

–

0.046

0.063

0.100

0.010

0.130

0.119

130

0.032

0.045

0.100

0.014

–

0.111

0.100

0.030

–

0.537

0.500

132

–

–

–

–

–

–

–

–

–

0.019

0.012

134

–

–

–

–

–

–

–

–

–

0.009

–

Pab2A5

(126)

(132)

(120)

(144)

(78)

(108)

(78)

(100)

(102)

(108)

(84)

108

–

–

–

–

–

–

–

–

0.010

–

–

110

–

–

–

–

–

0.046

–

–

–

0.056

0.071

114

–

–

–

–

–

0.009

–

–

–

0.019

–

116

0.460

0.598

0.758

0.701

0.731

0.741

0.603

0.620

0.667

0.713

0.690

118

–

–

0.025

–

–

–

–

–

–

–

–

120

0.540

0.402

0.217

0.299

0.269

0.204

0.397

0.380

0.314

0.213

0.238

122

–

–

–

–

–

–

–

–

0.010

–

–

Pma1n

(124)

(128)

(114)

(142)

(70)

(108)

(80)

(92)

(98)

(108)

(84)

151

–

–

–

–

0.029

–

–

–

–

–

–

153

0.008

–

–

–

–

–

–

–

–

–

0.012

157

0.742

0.742

0.518

0.796

0.714

0.685

0.637

0.587

0.612

0.639

0.595

159

–

–

–

0.028

0.029

0.028

0.013

0.033

0.031

0.056

0.024

161

0.105

0.070

0.193

0.035

0.114

0.074

0.087

0.087

0.061

0.046

0.083

163

–

–

0.035

0.007

0.014

0.037

0.038

0.033

0.020

0.120

0.119

165

–

0.016

–

–

–

–

–

–

–

0.009

0.024

167

–

–

–

0.007

–

0.046

0.013

0.011

0.041

0.037

0.012

169

–

–

–

–

–

0.019

–

–

–

0.009

0.036

171

–

–

0.009

–

–

0.009

–

–

0.010

0.028

0.036

173

0.145

0.164

0.237

0.127

0.071

0.093

0.213

0.228

0.224

0.056

0.060

175

–

0.008

0.009

–

–

0.000

–

–

–

–

–

177

–

–

–

–

–

0.009

–

0.011

–

–

–

179

–

–

–

–

0.029

–

–

0.011

–

–

–

MtDNA

(52)

(54)

(52)

(72)

(40)

(52)

(40)

(48)

(51)

(53)

(41)

AA

0.904

0.870

0.712

0.542

0.350

0.308

0.525

0.250

0.412

0.226

0.268

AB

0.077

0.037

0.173

0.042

–

0.096

–

0.042

0.078

0.076

0.073

AC

–

–

–

–

–

0.038

–

–

–

–

–

BA

–

–

–

–

0.050

0.077

–

–

0.059

–

–

BB

0.019

0.093

0.077

0.347

0.525

0.192

0.200

0.250

0.294

0.075

–

BD

–

–

0.038

0.028

0.025

–

–

–

–

–

–

CA

–

–

–

–

–

0.039

–

–

–

0.019

–

CB

–

–

–

0.042

0.050

0.250

0.275

0.458

0.157

0.604

0.659

  1. Populations are ordered from west to east. Total numbers of alleles surveyed are given in parentheses, and microsatellite allele names represent their size in base pairs. Mitochondrial data were derived from Burridge et al. (2004) except for Glenelg, Painkalac, and Thomson.

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Burridge, C.P., Versace, V.L. Population Genetic Structuring in Acanthopagrus butcheri (Pisces: Sparidae): Does Low Gene Flow Among Estuaries Apply to Both Sexes?. Mar Biotechnol 9, 33–44 (2007). https://doi.org/10.1007/s10126-006-6023-7

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  • DOI: https://doi.org/10.1007/s10126-006-6023-7

Keywords

  • Isolation by distance
  • microsatellite
  • migration-drift equilibrium
  • sea level
  • selection
  • stepping stone