Microsatellites behaving badly: empirical evaluation of genotyping errors and subsequent impacts on population studies

• Published in: Genetics and molecular research Vol. 10; no. 4; pp. 2534 - 2553
• Main Authors: Kelly, A C, Mateus-Pinilla, N E, Douglas, M, Shelton, P, Novakofski, J
• Format: Journal Article
• Language: English
• Published: Brazil 19.10.2011
• Subjects: Animals; Deer - genetics; DNA Mutational Analysis - methods; DNA Primers - genetics; Female; Genetic Loci - genetics; Genetics, Population - methods; Genotype; Male; Microsatellite Repeats - genetics; Mutation; Polymerase Chain Reaction - methods
• ISSN: 1676-5680; 1676-5680
• DOI: 10.4238/2011.October.19.1

Microsatellites are useful tools for ecological studies because they can be used to discern population structure, dispersal patterns and genetic relationships among individuals. However, they can also yield inaccurate genotypes that, in turn, bias results, promote biological misinterpretations, and create repercussions for population management and conservation programs. We used empirical data from a large-scale microsatellite DNA study of white-tailed deer (Odocoileus virginianus) to identify sources of genotyping error, evaluate corrective measures, and provide recommendations to prevent bias in population studies. We detected unreported mutations that led to erroneous genotypes in five of 13 previously evaluated microsatellites. Of the five problematic markers, two contained mutations that resulted in null alleles, and three contained mutations that resulted in imperfect repeats. These five microsatellites had error rates that were four times greater on average than those observed in the remaining eight. Methodological corrections, such as primer redesign, reduced errors up to 5-fold in two problematic loci, although analytical corrections (computational adjustment for errors) were unable to fully prevent bias and, consequently, measures of genetic differentiation and kinship were negatively impacted. Our results demonstrate the importance of error evaluation during all stages of population studies, and emphasize the need to standardize procedures for microsatellite analyses. This study facilitates the application of microsatellite technology in population studies by examining common sources of genotyping error, identifying unreported problems with microsatellites, and offering solutions to prevent error and bias in population studies.