Open Access Open Badges Research article

Molecular pedigree reconstruction and estimation of evolutionary parameters in a wild Atlantic salmon river system with incomplete sampling: a power analysis

Tutku Aykanat1*, Susan E Johnston15, Deirdre Cotter2, Thomas F Cross3, Russell Poole2, Paulo A Prodőhl4, Thomas Reed3, Ger Rogan2, Philip McGinnity3 and Craig R Primmer1

Author Affiliations

1 Division of Genetics and Physiology, Department of Biology, University of Turku, Turku, Finland

2 Marine Institute, Furnace, Newport, Co., Mayo, Ireland

3 Aquaculture & Fisheries Development Centre, School of Biological, Earth & Environmental Sciences, University College Cork, Cork, Ireland

4 Institute for Global Food Security, School of Biological Science, Medical Biology Centre, Queen’s University, Belfast, Northern Ireland

5 Present address: Institute of Evolutionary Biology, University of Edinburgh, West Mains Road, Edinburgh, UK

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BMC Evolutionary Biology 2014, 14:68  doi:10.1186/1471-2148-14-68

Published: 31 March 2014



Pedigree reconstruction using genetic analysis provides a useful means to estimate fundamental population biology parameters relating to population demography, trait heritability and individual fitness when combined with other sources of data. However, there remain limitations to pedigree reconstruction in wild populations, particularly in systems where parent-offspring relationships cannot be directly observed, there is incomplete sampling of individuals, or molecular parentage inference relies on low quality DNA from archived material. While much can still be inferred from incomplete or sparse pedigrees, it is crucial to evaluate the quality and power of available genetic information a priori to testing specific biological hypotheses. Here, we used microsatellite markers to reconstruct a multi-generation pedigree of wild Atlantic salmon (Salmo salar L.) using archived scale samples collected with a total trapping system within a river over a 10 year period. Using a simulation-based approach, we determined the optimal microsatellite marker number for accurate parentage assignment, and evaluated the power of the resulting partial pedigree to investigate important evolutionary and quantitative genetic characteristics of salmon in the system.


We show that at least 20 microsatellites (ave. 12 alleles/locus) are required to maximise parentage assignment and to improve the power to estimate reproductive success and heritability in this study system. We also show that 1.5 fold differences can be detected between groups simulated to have differing reproductive success, and that it is possible to detect moderate heritability values for continuous traits (h2 ~ 0.40) with more than 80% power when using 28 moderately to highly polymorphic markers.


The methodologies and work flow described provide a robust approach for evaluating archived samples for pedigree-based research, even where only a proportion of the total population is sampled. The results demonstrate the feasibility of pedigree-based studies to address challenging ecological and evolutionary questions in free-living populations, where genealogies can be traced only using molecular tools, and that significant increases in pedigree assignment power can be achieved by using higher numbers of markers.

Atlantic salmon; Heritability; Incomplete sampling; MasterBayes; Parentage assignment; Power analysis; Reproductive success