Impact of heat and drought stresses on grain nutrient content in chickpea: Genome-wide marker-trait associations for protein, Fe and Zn
Srinivasan Samineni, Mahesh D. Mahendrakar, N. P. S. De Silva V. G. Shankar, Avinalappa Hotti, Uttam Chand, Abhishek Rathore, Pooran M. Gaur
Abstract
Chickpea is a cheap source of protein and micronutrients to the poor and vegetarian population living in south-Asia and sub-Saharan Africa. Due to changes in climatic conditions and cropping systems, the crop is being exposed to severe drought and heat stress during its reproductive period, which leads to significant yield losses and fluctuations in grain nutrient accumulation. The study was conducted with 140 diverse genotypes under non-stress, drought, and heat stress conditions to estimate their effects on grain nutrient (protein, Fe and Zn) contents and identify the marker-trait associations. Analysis of variance revealed highly significant differences among genotypes for nutrient content under respective planting conditions. The seed yield was negatively associated with the grain Fe (r = −0.37, −0.25, 0.11) and Zn (r = −0.49, −0.35, −0.72) under respective planting conditions. The PCA indicated that PC1 was positively associated with grain Fe in non-stress and heat, while Zn in all planting conditions, whereas PC2 was positively influenced by protein content followed by grain yield. Cluster analysis identified eight clusters, of which cluster VI showed maximum cluster means for Fe (73 mg kg-1) and Zn (48.1 mg kg-1). The Genome-wide association study revealed, a total of 181 MTAs for grain Fe, Zn, and protein content in all three growing conditions. A total of 4, 2, and 48 SNPs for grain Fe and Zn content, whereas, 66, 46, 15 SNPs for grain protein content have shown significant association under non-stress, drought, and heat stress, respectively. One SNP each on chr1 (S1_35622241; P ≤ 3.47 ×10-6) and chr4 (S4_44607232; P ≤ 1.35 ×10-5) was co-associated under drought and non-stress conditions for protein and Fe, respectively. The identified robust MTAs will be validated and used in marker-assisted selection towards the rapid development of nutrient-rich varieties.