Genome-wide association mapping of nutritional traits for designing superior chickpea varieties

FRONTIERS IN PLANT SCIENCE(2022)

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摘要
Micronutrient malnutrition is a serious concern in many parts of the world; therefore, enhancing crop nutrient content is an important challenge. Chickpea (Cicer arietinum L.), a major food legume crop worldwide, is a vital source of protein and minerals in the vegetarian diet. This study evaluated a diverse set of 258 chickpea germplasm accessions for 12 key nutritional traits. A significant variation was observed for several nutritional traits, including crude protein (16.56-24.64/100 g), beta-Carotene (0.003-0.104 mg/100 g), calcium (60.69-176.55 mg/100 g), and folate (0.413-6.537 mg/kg). These data, combined with the available whole-genome sequencing data for 318,644 SNPs, were used in genome-wide association studies comprising single-locus and multi-locus models. We also explored the effect of varying the minor allele frequency (MAF) levels and heterozygosity. We identified 62 significant marker-trait associations (MTAs) explaining up to 28.63% of the phenotypic variance (PV), of which nine were localized within genes regulating G protein-coupled receptor signaling pathway, proteasome assembly, intracellular signal transduction, and oxidation-reduction process, among others. The significant effect MTAs were located primarily on Ca1, Ca3, Ca4, and Ca6. Importantly, varying the level of heterozygosity was found to significantly affect the detection of associations contributing to traits of interest. We further identified seven promising accessions (ICC10399, ICC1392, ICC1710, ICC2263, ICC1431, ICC4182, and ICC16915) with superior agronomic performance and high nutritional content as potential donors for developing nutrient-rich, high-yielding chickpea varieties. Validation of the significant MTAs with higher PV could identify factors controlling the nutrient acquisition and facilitate the design of biofortified chickpeas for the future.
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关键词
biofortification, micronutrient, malnutrition, trait-mapping, genomics, GWAS
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