Genomic basis of seed colour in quinoa inferred from variant patterns using extreme gradient boosting

Abstract

Quinoa is an agriculturally important crop species originally domesticated in the Andes of central South America. One of its most important phenotypic traits is seed colour. Seed colour variation is determined by contrasting abundance of betalains, a class of strong antioxidant and free radicals scavenging colour pigments only found in plants of the order Caryophyllales. However, the genetic basis for these pigments in seeds remains to be identified. Here we demonstrate the application of machine learning (extreme gradient boosting) to identify genetic variants predictive of seed colour. We show that extreme gradient boosting outperforms the classical genome-wide association approach. We provide re-sequencing and phenotypic data for 156 South American quinoa accessions and identify candidate genes potentially controlling betalain content in quinoa seeds. Genes identified include novel cytochrome P450 genes and known members of the betalain synthesis pathway, as well as genes annotated as being involved in seed development. Our work showcases the power of modern machine learning methods to extract biologically meaningful information from large sequencing data sets.

Keywords: betalain synthesis pathway; genome sequencing; genotype‐phenotype relationships; machine learning; quinoa; seed colour.

Figure 1

Representative quinoa seeds classified as white (a), beige (b), greenish‐red (c, d), yellow (e), orange (f), red (g) and black (h) at 50‐fold magnification.

Figure 2

Principal component analysis (PCA) and linear discriminant analysis (LDA) of 129 SNP positions that increased the quality of at least nine independent XGBoost models using accessions with beige, orange and white seeds.

Figure 3

(a) Principal component analysis (PCA) and (b) linear discriminant analysis (LDA) of 129 SNP positions that increased the quality of at least nine independent XGBoost models using accessions with beige, orange, white and yellow seeds.

Figure 4

Hierarchical clustering of the genotypes at 129 variant positions discriminating beige‐, orange‐ and white‐seeded accessions. Dark blue: homozygous alternative; turquoise: heterozygous; light green: homozygous reference; black: missing data.

Figure 5

Linear discriminant analysis (LDA) of 129 SNP positions that increased the quality of at least nine independent XGBoost models. In addition to the four larger seed groups (beige, orange, white and yellow) we also included data from quinoa accessions with red, black, brown and greenish‐red seeds.