A 37 K SNP array for the management and conservation of Golden Eagles (Aquila chrysaetos)
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Abstract
We describe the development of a custom 37 K Affymetrix Axiom myDesign single nucleotide polymorphism (SNP) array for a culturally and ecologically important apex predator, the golden eagle (Aquila chrysaetos). Using this SNP array, we performed population genomic analysis on 154 individuals of known natal localities and detected three genetic clusters that we designated as Taiga/High Arctic, Great Basin, and Rocky Mountains/Great Plains. Each of these clusters appears to display clinal variation within these geographic regions. After determining genetic structure, we performed an assignment test of 32 individuals, five of which were siblings of individuals used in the assessment of genetic structure, three had associated telemetry data, and the remaining individuals were of unknown natal locations. Using this array, four siblings were correctly assigned to the same geographic region as their sibling and the genetic assignment of the radio telemetered birds agreed with the expected movement patterns displayed by these individuals. For the remaining individuals, we were able to assign all but five individuals to one of the three genetic clusters. Our genetic assignments illustrates the utility of this SNP array to accurately assign most individuals to predesignated geographical regions. While further compiling genetic and other data types, we can increase the power of this tool for identifying those breeding populations that may need assistance due to anthropogenic stressors that negatively impact their population viability. The use of this genetic resource will help substantiate decisions by multiple conservation groups that seek to preserve the natural population structure of the golden eagle.
Publication type | Article |
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Publication Subtype | Journal Article |
Title | A 37 K SNP array for the management and conservation of Golden Eagles (Aquila chrysaetos) |
Series title | Conservation Genetics |
DOI | 10.1007/s10592-023-01508-3 |
Volume | 24 |
Year Published | 2023 |
Language | English |
Publisher | Springer |
Contributing office(s) | Forest and Rangeland Ecosystem Science Center |
Description | 14 p. |
First page | 391 |
Last page | 404 |
Google Analytic Metrics | Metrics page |