Power analyses for pedigree reconstructions, in populations with variable mating systems, and types and quantities of molecular and demographic data — ASN Events
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  2. CONCURRENT SESSION: Colour in nature: Conceptual and methodological challenges and emerging solutions (Symposium) / Behavioural thermoregulation: Mechanisms and consequences for ecthotherms in a changing world (Symposium)
  3. Power analyses for pedigree reconstructions, in populations with variable mating systems, and types and quantities of molecular and demographic data

Power analyses for pedigree reconstructions, in populations with variable mating systems, and types and quantities of molecular and demographic data (#291)

Anna M Kopps 1 2 , Jungkoo Kang 1 3 , Bill B Sherwin 2 4 , Per J Palsbøll 1
  1. Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, Netherlands
  2. Evolution & Ecology Research Centre, University of New South Wales, Sydney, NSW, Australia
  3. IceLab, Umeå University, Umeå, Sweden
  4. Murdoch University Cetacean Research Unit, Murdoch University, Murdoch, WA, Australia

As molecular techniques improve, the pedigree is being regarded as only an approximation to the true relatedness or identity by descent (rather than identity by state) that can be found in each part of the genome. However, cases remain where insights into the pedigree is important, such as niche inheritance, cultural inheritance, epigenetic inheritance. There is a need for power analyses that address a range of possible relationships. Nevertheless, such analyses are rarely applied, and studies using genetic-data-based-kinship inference often ignore the influence of intrinsic population characteristics. We investigated the power of relatedness category assignments (RCA) using an individual-based model with realistic life-history parameters. We investigated: the effects of the number of genetic markers; marker type (microsatellite, SNP, or both); minor allele frequency; typing error; mating system; and the number of overlapping generations under different demographic conditions. We found that (i) an increasing number of genetic markers increased the power of the RCA so that up to first cousins can be assigned with >80% power; (ii) the minimum number of genetic markers required for assignments with sufficient power differed between relatedness categories, mating systems and the number of overlapping generations; (iii) the power of an assignment was improved by adding additional relatedness categories and demographic data, and (iv) a combination of microsatellite and SNP data increased the power if <800 SNP loci were available. This study showed how intrinsic population characteristics, such as mating system, life history traits, and genetic marker characteristics can influence the power of a kinship study. So power analyses are essential.