Literature DB >> 22033936

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

A C Kelly1, N E Mateus-Pinilla, M Douglas, M Douglas, P Shelton, J Novakofski.   

Abstract

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.

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Year:  2011        PMID: 22033936     DOI: 10.4238/2011.October.19.1

Source DB:  PubMed          Journal:  Genet Mol Res        ISSN: 1676-5680


  7 in total

1.  Discovery of novel variants in genotyping arrays improves genotype retention and reduces ascertainment bias.

Authors:  John P Didion; Hyuna Yang; Keith Sheppard; Chen-Ping Fu; Leonard McMillan; Fernando Pardo-Manuel de Villena; Gary A Churchill
Journal:  BMC Genomics       Date:  2012-01-19       Impact factor: 3.969

Review 2.  Challenges in analysis and interpretation of microsatellite data for population genetic studies.

Authors:  Alexander I Putman; Ignazio Carbone
Journal:  Ecol Evol       Date:  2014-10-30       Impact factor: 2.912

3.  Genotyping-by-sequencing of genome-wide microsatellite loci reveals fine-scale harvest composition in a coastal Atlantic salmon fishery.

Authors:  Ian R Bradbury; Brendan F Wringe; Beth Watson; Ian Paterson; John Horne; Robert Beiko; Sarah J Lehnert; Marie Clément; Eric C Anderson; Nicholas W Jeffery; Steven Duffy; Emma Sylvester; Martha Robertson; Paul Bentzen
Journal:  Evol Appl       Date:  2018-03-11       Impact factor: 5.183

4.  Identification and evaluation of a core microsatellite panel for use in white-tailed deer (Odocoileus virginianus).

Authors:  William L Miller; Jessie Edson; Peter Pietrandrea; Cassandra Miller-Butterworth; W David Walter
Journal:  BMC Genet       Date:  2019-06-06       Impact factor: 2.797

5.  Imputation of microsatellite alleles from dense SNP genotypes for parental verification.

Authors:  Matthew McClure; Tad Sonstegard; George Wiggans; Curtis P Van Tassell
Journal:  Front Genet       Date:  2012-08-14       Impact factor: 4.599

6.  Assessment of population genetic structure in the arbovirus vector midge, Culicoides brevitarsis (Diptera: Ceratopogonidae), using multi-locus DNA microsatellites.

Authors:  Maria G Onyango; Nigel W Beebe; David Gopurenko; Glenn Bellis; Adrian Nicholas; Moses Ogugo; Appolinaire Djikeng; Steve Kemp; Peter J Walker; Jean-Bernard Duchemin
Journal:  Vet Res       Date:  2015-09-25       Impact factor: 3.683

7.  Delineation of the population genetic structure of Culicoides imicola in East and South Africa.

Authors:  Maria G Onyango; George N Michuki; Moses Ogugo; Gert J Venter; Miguel A Miranda; Nohal Elissa; Appolinaire Djikeng; Steve Kemp; Peter J Walker; Jean-Bernard Duchemin
Journal:  Parasit Vectors       Date:  2015-12-24       Impact factor: 3.876

  7 in total

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