Combining Genome-Wide Association and Genomic Prediction to unravel the Genetic Architecture of Carotenoid Accumulation in Carrot

Authors: Rolling, William; ELLISON, SHELBY - University Of Wisconsin; COE, KEVIN - University Of Wisconsin; MASSIMO, IORIZZO - North Carolina State University; DAWSON, JULIE - University Of Wisconsin; Senalik, Douglas; Simon, Philipp

Submitted to: The Plant Genome
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/23/2024
Publication Date: 1/2/2025
Citation: Rolling, W.R., Ellison, S., Coe, K., Massimo, I., Dawson, J., Senalik, D.A., Simon, P.W. 2025. Combining Genome-Wide Association and Genomic Prediction to unravel the Genetic Architecture of Carotenoid Accumulation in Carrot. The Plant Genome. 18:e20560.(2025). https://doi.org/10.1002/tpg2.20560.
DOI: https://doi.org/10.1002/tpg2.20560

Interpretive Summary: Carotenoids account for the red, yellow, and orange colors of carrots and orange carrots are a rich source of the provitamin A carotenoids, a- and ß-carotene. Understanding which genes contribute to carrot color will improve carrot breeders’ ability to produce varieties with the most vibrant colors and highest nutrition. We visually scored the color of carrots and directly measured the concentration of carotenoids in a collection of different carrot accessions (varieties) from around the world. We also sequenced DNA of these carrots to identify genes responsible for carotenoids production, finding three regions of the genome that were associated with carotenoid biosynthesis. We also determined if we could use the DNA sequence to predict the concentration of carotenoids in different carrot accessions. We found that predictions were only moderately accurate, likely because carotenoid concentration is affected by the environment carrots are grown. These results are of interest to carrot growers, carrot genetics and breeding researchers, and nutritionists.

Technical Abstract: Carrots are a rich source of provitamin A, namely a- and ß-carotene. Breeding programs prioritize increasing ß-carotene content for improved color and nutritional value. Understanding the genetic basis of carotenoid accumulation is crucial for implementing genomic-assisted selection to develop high-carotenoid lines. While previous genetic mapping identified loci (Y2, Y, Or, and REC) associated with carrot color and carotenoid content, this study employed genome-wide association analysis (GWAS) to refine positions. Additionally, we discovered a novel locus harboring a candidate gene encoding Phytoene Synthase, a key enzyme in carotenoid biosynthesis. Interestingly, these loci are mostly fixed in orange carrot varieties, yet considerable variation in carotenoid concentration persists. This suggests complex trait architecture influenced by environmental factors. GWAS of carotenoid concentration identified a quantitative trait locus for total carotenoids and a-carotene on Chr04. We also explored the accuracy of genomic prediction (GP) models to predict carotenoid concentration. We determined the optimal number of plants and plots required for accurate carotenoid phenotyping, finding eight plants per plot and three plots per site as the minimum effective sample per accession. GP models achieved accuracies ranging from 0.06 to 0.40 depending on the specific carotenoid. This study presents a novel carotenoid loci and demonstrates the potential of GP for future breeding efforts.