Genome-Wide Association Mapping for Intelligence in Military Working Dogs: Canine Cohort, Canine Intelligence Assessment Regimen, Genome-Wide Single Nucleotide Polymorphism (SNP) Typing, and Unsupervised Classification Algorithm for Genome-Wide Association Data Analysis

摘要

This seedling project aimed to genetically map intelligence in the military working dog (MWD) population. A total of 199 canine subjects were recruited from United States working dog contractors. Of the recruited subjects, 153 were tested using the Canine Intelligence Testing Protocol (CITP), developed by Dr. Karen Overall (UPENN) to specifically analyze canine intelligence. CITP allows quantitative assessment of intelligence in individual dogs using a scoring system based on the latency to response, success-in-effort time, attentiveness, interest in novelty exploration, response to signaling and showing, observational learning, problem solving/boldness, and handedness. Blood samples were collected from the canines, and genomic DNA prepared. A total of 117 dogs, belonging to three breeds (German Shepherds, Belgian Malinois, Labrador Retrievers) were down-selected and successfully genotyped for whole genome (WG) single nucleotide polymorphism (SNP) markers by means of the Affymetrix Canine SNP Array v2. A 'proof-of-concept' advanced data mining algorithm for unsupervised analysis of the genome-wide association study (GWAS) dataset was successfully developed. Using this algorithm, canine subjects were successfully clustered into the correct breeds with an accuracy ranging from 89% - 100%, solely based on the WG SNP profiles. The details of the algorithm are described in the Technical Report AFRL-RH-WP-TR-2011-0081, entitled 'Development of Advanced Classification Algorithm for Genome-Wide Single Nucleotide Polymorphism (SNP) Data Analysis.' While not initially part of the seedling proposal, this project did receive IACUC permission to test DoD MWDs for follow-on studies, a unique and significant accomplishment.