GENOMIC PREDICTION OF GROWTH AND WOOD TRAITS OF Shorea platyclados , COMMERCIAL TIMBER IN SOUTHEAST ASIA

抄録

Shorea platyclados is a commercial timber in Southeast Asia. Its stock has been declined due to excessive logging, insufficient regeneration and slow recovery rate. We need to promote enrichment planting and develop techniques to support its rehabilitation and improve timber production through molecular breeding (GWAS and Genomic Selection). Plant materials were collected from half-sib population (332 individuals from 77 mother trees) in Indonesia. Using 5,412 markers, we detected strong LD (> 110 kb). In GWAS, few SNPs linked to any traits were detected with a stringent FDR, indicating that they are under polygenic quantitative control. GS using Machine Learning provided higher prediction accuracies than Bayesian regression methods. Height, wood density and wood stiffness were more predictable than diameter and branch shape. Genomic heritability help to select potential traits in future breeding and GS is promising to improve the yield and quality of timber.