The Use of “Genotyping-by-Sequencing” to Recover Shared Genealogy in Genetically Diverse Eucalyptus Populations
Klápště, Jaroslav | Ashby, Rachael L. | Telfer, Emily J. | Graham, Natalie J. | Dungey, Heidi S. | Brauning, Rudiger | Clarke, Shannon M. | Dodds, Ken G.
The recovery of genealogy in both natural and captive populations is critical for any decision in the management of genetic resources. It allows for the estimation of genetic parameters such as heritability and genetic correlations, as well as defining an optimal mating design that maintains a large effective population size. We utilised “genotyping-by-sequencing” (GBS) in combination with bioinformatics tools developed specifically for GBS data to recover genetic relatedness, with a focus on parent-offspring relationships in a Eucalyptus nitens breeding population as well as recognition of individuals representing other Eucalyptus species and putative hybrids. We found a clear advantage on using tools specifically designed for data of highly variable sequencing quality when recovering genetic relatedness. The parent-offspring relatedness showed a significant response to data filtering from 0.05 to 0.3 when the standard approach (G1) was used, while it oscillated around 0.4 when the specifically designed method (G5) was implemented. Additionally, comparisons with commonly used tools demonstrated vulnerability of the relatedness estimates to incorrect imputation of missing data when shallow sequencing information and genetically distant individuals are present in the population. In turn, these biased imputed genotypes negatively affected the estimation of genetic relatedness between parents and offspring. Careful filtering for both genetic outliers and shallowly sequenced markers led to improvements in estimations of genetic relatedness. Alternatively, a method that avoided missing data imputation and took sequence depth into consideration improved the accuracy of parent-offspring relationship coefficients where sequencing data quality was highly variable.
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