Enhancing genomic association studies in slash pine through close-range UAV-based morphological phenotyping.

Area of Science:

• Forestry genetics
• Plant phenotyping
• Conifer genomics

Background:

• Tree morphological traits are vital for forestry productivity.
• Traditional measurement methods lack efficiency and scalability.
• Advanced phenotyping is needed for large-scale forest assessments.

Purpose of the Study:

• Integrate Unmanned Aerial Vehicle (UAV) technology with Genome-Wide Association Studies (GWAS).
• Improve genomic association studies for slash pine (Pinus elliottii).
• Identify genetic associations for key morphological traits.

Main Methods:

• Utilized UAV-based phenotyping to identify seven morphological traits: canopy area (CA), crown base height (CBH), crown length (CL), canopy volume (CV), crown width (CW), crown width height (CWH), and tree height (H).
• Applied GWAS to analyze genetic associations with these traits.
• Assessed heritability using Single Nucleotide Polymorphism (SNP) and pedigree methods.

Main Results:

• Identified significant heritability for traits like CBH, CL, CV, and H, indicating strong genetic influence.
• GWAS revealed 28 associations, including 22 SNPs in 16 candidate genes.
• Discovered two candidate genes (DEAD-like helicase and ethylene-responsive element binding factor (ERF)) significantly associated with CW and CA.

Conclusions:

• UAV imaging facilitates comprehensive analysis of slash pine morphological growth.
• This approach aids in discovering informative alleles for complex phenotypic variation in conifers.
• The study highlights the genetic basis of key tree traits for improved forestry applications.