Bridging the genotype-phenotype gap for a Mediterranean pine by semi-automatic crown identification and multispectral imagery

Abstract

Progress in high-throughput phenotyping and genomics provides the potential to under-stand the genetic basis of plant functional differentiation. We developed a semi-automaticmethodology based on unmanned aerial vehicle (UAV) imagery for deriving tree-level pheno-types followed by genome-wide association study (GWAS).

An RGB-based point cloud was used for tree crown identification in a common garden of Pinus halepensis in Spain. Crowns were combined with multispectral and thermal orthomo-saics to retrieve growth traits, vegetation indices and canopy temperature. Thereafter, GWASwas performed to analyse the association between phenotypes and genomic variation at 235single nucleotide polymorphisms (SNPs).

Growth traits were associated with 12 SNPs involved in cellulose and carbohydratemetabolism. Indices related to transpiration and leaf water content were associated with sixSNPs involved in stomata dynamics. Indices related to leaf pigments and leaf area were associ-ated with 11 SNPs involved in signalling and peroxisome metabolism. About 16–20% of traitvariance was explained by combinations of several SNPs, indicating polygenic control of mor-pho-physiological traits.

Despite a limited availability of markers and individuals, this study is provides a successfulproof-of-concept for the combination of high-throughput UAV-based phenotyping withcost-effective genotyping to disentangle the genetic architecture of phenotypic variation in awidespread conifer