Potential of Genome-Wide Association Studies and Genomic Selection to Improve Productivity and Quality of Commercial Timber Species in Tropical Rainforest, a Case Study of Shorea platyclados

horea platyclados (Dark Red Meranti) is a commercially important timber tree species in
Southeast Asia. However, its stocks have dramatically declined due, inter alia, to excessive logging,
insufficient natural regeneration and a slow recovery rate. Thus, there is a need to promote enrichment
planting and develop effective technique to support its rehabilitation and improve timber production
through implementation of Genome-Wide Association Studies (GWAS) and Genomic Selection (GS).
To assist such efforts, plant materials were collected from a half-sib progeny population in Sari Bumi
Kusuma forest concession, Kalimantan, Indonesia. Using 5900 markers in sequences obtained from
356 individuals, we detected high linkage disequilibrium (LD) extending up to >145 kb, suggesting
that associations between phenotypic traits and markers in LD can be more easily and feasibly
detected with GWAS than with analysis of quantitative trait loci (QTLs). However, the detection
power of GWAS seems low, since few single nucleotide polymorphisms linked to any focal traits were
detected with a stringent false discovery rate, indicating that the species’ phenotypic traits are mostly
under polygenic quantitative control. Furthermore, Machine Learning provided higher prediction
accuracies than Bayesian methods. We also found that stem diameter, branch diameter ratio and
wood density were more predictable than height, clear bole, branch angle and wood stiffness traits.
Our study suggests that GS has potential for improving the productivity and quality of S. platyclados,
and our genomic heritability estimates may improve the selection of traits to target in future breeding
of this species.
Keywords: Shorea platyclados; GWAS; GS; growth; wood quality traits; genomic heritability