Cost-efficient selection of a marker panel in genetic studies

Jamie S. Sanderlin, Nicole Lazar, Michael J. Conroy, Jaxk Reeves

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Genetic techniques are frequently used to sample and monitor wildlife populations. The goal of these studies is to maximize the ability to distinguish individuals for various genetic inference applications, a process which is often complicated by genotyping error. However, wildlife studies usually have fixed budgets, which limit the number of genetic markers available for inclusion in a study marker panel. Prior to our study, a formal algorithm for selecting a marker panel that included genotyping error, laboratory costs, and ability to distinguish individuals did not exist. We developed a constrained nonlinear programming optimization algorithm to determine the optimal number of markers for a marker panel, initially applied to a pilot study designed to estimate black bear abundance in central Georgia. We extend the algorithm to other genetic applications (e.g., parentage or population assignment) and incorporate possible null alleles. Our algorithm can be used in wildlife pilot studies to assess the feasibility of genetic sampling for multiple genetic inference applications. © 2011 The Wildlife Society.

Original languageEnglish (US)
Pages (from-to)88-94
Number of pages7
JournalJournal of Wildlife Management
Volume76
Issue number1
DOIs
StatePublished - Jan 2012

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Ecology
  • Nature and Landscape Conservation

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