Apr 3, 2018

Accuracy of genomic selection for growth and wood quality traits in two control-pollinated progeny trials using exome capture as genotyping platform in Norway spruce

BioRxiv : the Preprint Server for Biology
Zhiqiang ChenHarry X. Wu


Background: Genomic selection (GS) can increase genetic gain by reducing the length of breeding cycle in forest trees. Here we genotyped 1370 control-pollinated progeny trees from 128 full-sib families in Norway spruce (Picea abies (L.) Karst.), using exome capture as a genotyping platform. We used 116,765 high quality SNPs to develop genomic prediction models for tree height and wood quality traits. We assessed the impact of different genomic prediction methods, genotype-by-environment interaction (GxE), genetic composition, size of the training and validation set, relatedness, and the number of SNPs on the accuracy and predictive ability (PA) of GS. Results: Using G matrix slightly altered heritability estimates relative to pedigree-based method. GS accuracies were about 11-14% lower than those based on pedigree-based selection. The efficiency of GS per year varied from 1.71 to 1.78, compared to that of the pedigree-based model if breeding cycle length was halved using GS. Height GS accuracy decreased more than 30% using one site as training for GS prediction to the second site, indicating that GxE for tree height should be accommodated in model fitting. Using half-sib family structure instead of full-sib led a significant re...Continue Reading

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Mentioned in this Paper

Biological Markers
Trees (plant)
Picea excelsa
Genetic Pedigree
Whole Exome Sequencing

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