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Updated: Sep 30, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
Published on: July 3, 2020
Metadata analysis indicates biased estimation of genetic parameters and gains using conventional pedigree information
Jean Beaulieu1, Patrick Lenz2,3, Jean Bousquet2
1Canada Research Chair in Forest Genomics, Institute of Systems and Integrative Biology and Centre for Forest Research, Université Laval, 1030 Avenue de la Médecine, Quebec, QC, G1V 0A6, Canada. jean.beaulieu@sbf.ulaval.ca.
Abstract:
Forest tree improvement helps provide adapted planting stock to ensure growth productivity, fibre quality and carbon sequestration through reforestation and afforestation activities. However, there is increasing doubt that conventional pedigree provides the most accurate estimates for selection and prediction of performance of improved planting stock. When the additive genetic relationships among relatives is estimated using pedigree information, it is not possible to take account of Mendelian sampling due to the random segregation of parental alleles. The use of DNA markers distributed genome-wide (multi-locus genotypes) makes it possible to estimate the realized additive genomic relationships, which takes account of the Mendelian sampling and possible pedigree errors. We reviewed a series of papers on conifer and broadleaf tree species in which both pedigree-based and marker-based estimates of genetic parameters have been reported. Using metadata analyses, we show that for heritability and genetic gains, the estimates obtained using only the pedigree information are generally biased upward compared to those obtained using DNA markers distributed genome-wide, and that genotype-by-environment (GxE) interaction can be underestimated for low to moderate heritability traits. As high-throughput genotyping becomes economically affordable, we recommend expanding the use of genomic selection to obtain more accurate estimates of genetic parameters and gains.
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