SSRs, SNPs and DArTs comparison on estimation of relatedness and genetic parameters’ precision from a small half-sib sample population of Eucalyptus grandis

Simple sequence repeats (SSR) are the most widely used molecular markers for relatedness inference due to their multi-allelic nature and high informativeness. However, there is a growing trend toward using high-throughput and inter-specific transferable single-nucleotide polymorphisms (SNP) and Diversity Arrays Technology (DArT) in forest genetics owing to their wide genome coverage. We compared the efficiency of 15 SSRs, 181 SNPs and 2816 DArTs to estimate the relatedness coefficients, and their effects on genetic parameters’ precision, in a relatively small data set of an open-pollinated progeny trial of Eucalyptus grandis (Hill ex Maiden) with limited relationship from the pedigree. Both simulations and real data of Eucalyptus grandis were used to study the statistical performance of three relatedness estimators based on co-dominant markers. Relatedness estimates in pairs of individuals belonging to the same family (related) were higher for DArTs than for SNPs and SSRs. DArTs performed better compared to SSRs and SNPs in estimated relatedness coefficients in pairs of individuals belonging to different families (unrelated) and showed higher ability to discriminate unrelated from related individuals. The likelihood-based estimator exhibited the lowest root mean squared error (RMSE); however, the differences in RMSE among the three estimators studied were small. For the growth traits, heritability estimates based on SNPs yielded, on average, smaller standard errors compared to those based on SSRs and DArTs. Estimated relatedness in the realized relationship matrix and heritabilities can be accurately inferred from co-dominant or sufficiently dense dominant markers in a relatively small E. grandis data set with shallow pedigree.Fil: Cappa, Eduardo Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires; ArgentinaFil: Klápště, Jaroslav. Czech University Of Life Sciences Prague; República Checa. University of British Columbia; Canadá. New Zealand Forest Research Institute Ltd.; Nueva ZelandaFil: Garcia, Martín Nahuel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Investigación En Ciencias Veterinarias y Agronómicas; ArgentinaFil: Villalba, Pamela Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Investigación En Ciencias Veterinarias y Agronómicas; ArgentinaFil: Marcucci Poltri, Susana Noemí. Investigación En Ciencias Veterinarias y Agronómicas; Argentin