Targeted improvement of plant‐based protein: Genome‐wide association mapping of a lentil (Lens culinaris Medik.) diversity panel

Abstract

The world is increasingly looking to plant‐based sources to meet its protein needs. Multiple factors are driving this progression, ranging from nutritional and ethical considerations to climate change and population growth. As a pulse crop, lentil is ideal to help meet this change in demand. However, plant‐based proteins have limiting amino acids and lower protein digestibility compared to animal‐based proteins. This research identifies genetic markers that can be used to accelerate breeding of protein quality traits in lentil to ultimately help meet the rising demand in high‐quality plant‐based protein and bolster global food and nutritional security. Lentil (Lens culinaris Medik.) contains ~25% high‐quality protein in addition to high concentrations of prebiotic carbohydrates and micronutrients, such as folate, iron, zinc, and selenium. As animal‐based protein's economic and environmental costs rise, plant‐based protein sources, such as lentil, will become increasingly important to global food systems. Consequently, evaluating and targeting protein quality traits for genomic‐assisted breeding is a valuable objective for lentil breeding programs. A diversity panel of 183 breeding lines was analyzed for protein quality traits, including amino acids and protein digestibility. Genotyping‐by‐sequencing (GBS) data were used to assess population structure and conduct genome‐wide association studies (GWAS). Genes in local linkage disequilibrium (LD) with significant single nucleotide polymorphism (SNP) markers were identified and categorized by homology. Protein quality traits showed a wide range of variation. Repeatability estimates were low to moderate across traits. Twelve traits were strongly correlated with each other (r > .7). Admixture analysis identified six ancestral subpopulations, which also demonstrated clustering in principal component analysis. Ten different traits had significant SNP associations; two loci were shared across multiple traits. Twenty‐seven candidate genes, including glutathione S‐transferase, protease family, and gibberellin 2‐beta‐dioxygenase genes, were identified. This paper identifies SNP markers associated with lentil protein quality traits. Once validated, these SNPs could accelerate lentil protein quality breeding efforts. By targeting lentil's limiting amino acids (methionine and cysteine) and protein digestibility through marker‐assisted selection, the nutritional value of lentil's protein content could be increased without the need to alter total protein content.