Combining US and Brazilian microsatellite data for a meta-analysis of sheep (Ovis aries) breed diversity: facilitating the FAO Global Plan of Action for Conserving Animal Genetic Resources.
Microsatellites are commonly used to understand genetic diversity among livestock populations. Nevertheless, most studies have involved the processing of samples in one laboratory or with common standards across laboratories. Our objective was to identify an approach to facilitate the merger of microsatellite data for cross-country comparison of genetic resources when samples were not evaluated in a single laboratory. Eleven microsatellites were included in the analysis of 13 US and 9 Brazilian sheep breeds (N = 706). A Bayesian approach was selected and evaluated with and without a shared set of samples analyzed by each country. All markers had a posterior probability of greater than 0.5, which was higher than predicted as reasonable by the software used. Sensitivity analysis indicated no difference between results with or without shared samples. Cluster analysis showed breeds to be partitioned by functional groups of hair, meat, or wool types (K = 7 and 12 of STRUCTURE). Cross-country comparison of hair breeds indicated substantial genetic distances and within breed variability. The selected approach can facilitate the merger and analysis of microsatellite data for cross-country comparison and extend the utility of previously collected molecular markers. In addition, the result of this type of analysis can be used in new and existing conservation programs.
EMBRAPA Recursos Genéticos e Biotecnologia, Laboratório de Genética Animal, Parque Estação Biológica, Brasília, DF 70770-917, Brazil. samuel@cenargen.embrapa.br
Samuel Rezende
SR
Paiva
Arthur da Silva
Ada S
Mariante
Harvey D
HD
Blackburn
D000483:Alleles; D000818:Animals; D001499:Bayes Theorem; D001938:Brazil; D001947:Breeding; D016000:Cluster Analysis; D003247:Conservation of Natural Resources / Q000706:statistics & numerical data; D030541:Databases, Genetic; D005819:Genetic Markers; D014644:Genetic Variation; D005828:Genetics, Population / Q000379:methods* / Q000706:statistics & numerical data; D006197:Hair; D008460:Meat; D018895:Microsatellite Repeats; D012756:Sheep / Q000235:genetics*; D012984:Software; D014481:United States; D014935:Wool
D005819:Genetic Markers