Genome-wide association insights into the genomic regions controlling vegetative and oil production traits in Acrocomia aculeata

BACKGROUND

Macauba (Acrocomia aculeata) is a non-domesticated neotropical palm that has been attracting attention for economic use due to its great potential for oil production comparable to the commercially used oil palm (Elaeis guineensis). The discovery of associations between quantitative trait loci and economically important traits represents an advance toward understanding its genetic architecture and can contribute to accelerating macauba domestication. Pursuing this advance, this study performs single-trait and multi-trait GWAS models to identify candidate genes associated with vegetative and oil production traits in macauba. Eighteen phenotypic traits were evaluated from 201 palms within a native population. Genotyping was performed with SNP markers, following the protocol of genotyping-by-sequencing. Given that macauba lacks a reference genome, SNP calling was performed using three different strategies: using i) de novo sequencing, ii) the Elaeis guineenses Jacq. reference genome and iii) the macauba transcriptome sequences. After quality control, we identified a total of 27,410 SNPs in 153 individuals for the de novo genotypic dataset, 10,444 SNPs in 158 individuals using the oil palm genotypic dataset, and 4,329 SNPs in 167 individuals using the transcriptome genotypic dataset. The GWAS analysis was then performed on these three genotypic datasets.

RESULTS

Statistical phenotypic analyses revealed significant differences across all studied traits, with heritability values ranging from 63 to 95%. This indicates that the population contains promising genotypes for selection and the initiation of breeding programs. Genetic correlations between the 18 traits ranged from -0.47 to 0.99. The total number of significant SNPs in the single-trait and multi-trait GWAS was 92 and 6 using the de novo genotypic dataset, 19 and 11 using the oil palm genotypic dataset, and 1 and 2 using the transcriptome genotypic dataset, respectively. Gene annotation identified 12 candidate genes in the single-trait GWAS and four in the multi-trait GWAS, across the 18 phenotypic traits studied, in the three genotypic datasets. Gene mapping of the macauba candidate genes revealed similarities with Elaeis guineensis and Phoenix dactylifera. The candidate genes detected are responsible for metal ion binding and transport, protein transportation, DNA repair, and other cell regulation biological processes.

CONCLUSIONS

We provide new insights into genomic regions that map candidate genes associated with vegetative and oil production traits in macauba. These potential candidate genes require confirmation through targeted functional analyses in the future, and multi-trait associations need to be scrutinized to investigate the presence of pleiotropic or linked genes. Markers linked to traits of interest could serve as valuable resources for the development of marker-assisted selection in macauba for its domestication and pre-breeding.