A wide variety of edible plant species exist worldwide, but people predominantly rely on just three traditional cereal grains (wheat, rice, and maize). This over-dependence on a small set of crops poses a threat to global agriculture, as these crops are highly susceptible to climate change and related weather extremes. Amaranth is one of the neglected pseudocereals with strong potential to combat food insecurity and environmental challenges. This review focuses on employing genomics, web resources, and genotyping platforms in amaranth to provide a picture and a way forward to sustainable agriculture. With the advent of genomic tools and molecular breeding, the future of genetic enhancement in amaranth looks increasingly promising. This review provides nutritional context of amaranth, while also outlining the potential applications of genome assemblies, sequencing, molecular markers, Genome-wide association studies, high density genotyping arrays, web resources, databases, pangenomics and machine-learning based resources in amaranth improvement. Further, we discussed development and use of 64 K SNP array ‘AmahySNP’ for Affymetrix Axiom technology designed using 64,069 high-density SNPs from 8879 genes across 16 scaffolds. This genotyping tool has been commercialized and used for structure analysis, diversity studies, core development, and association studies. Their integration in breeding could enhance the nutritional content, improve climate resilience, isolate and identify nutritionally important genes and agronomic traits from Amaranth, which can be used for biofortification and genetic improvement of grain amaranth crop. • Amaranth is recognised as a superfood with ability to thrive harsh climates. • Amaranth grain is rich in proteins, dietary fibers, lipids, minerals and vitamins. • Proposes use of nutritionally important Amaranth genes in biofortification programs. • A novel SNP array ‘AmahySNP’ for future genetic advancements in amaranth. • Genetic technologies to sustainably combat malnutrition and climatic challenges.
Das et al. (Fri,) studied this question.