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Both human and animals, for their nutritional requirements, mainly rely on the plant-based foods, which provide a wide range of nutrients. Minerals, proteins, vitamins are among the nutrients which are essential and need to be available in adequate amount in edible portion of the staple crops. Increasing nutritional content in staple crops either through agronomic biofortification or through conventional plant-breeding strategies continue to be a huge task for scientists around the globe. Although some success has been achieved in recent past, in most cases, we have fallen short of expected targets. To maximize the nutrient uptake and partitioning to different economic part of plants, scientists have employed and tailored several biofortification strategies. But in present agricultural and environmental concerns, these approaches are not much effective. Henceforth, we are highlighting the recent developments and promising aspects of microbial-assisted and genomic-assisted breeding as candidate biofortification approach, that have contributed significantly in increasing nutritional content in grains of different crops. The methods used to date to accomplish nutrient enrichment with recently emerging strategies that we believe could be the most promising and holistic approach for future biofortification program. Results are encouraging, but for future perspective, the existing knowledge about the strategies needs to be confined. Concerted scientific investment are required to widen up these biofortification strategies, so that it could play an important role in ensuring nutritional security of ever-growing population in growing agricultural and environmental constraints.

Pigeonpea, a tropical photosensitive crop, harbors significant diversity for days to flowering, but little is known about the genes that govern these differences. Our goal in the current study was to use genome wide association strategy to discover the loci that regulate days to flowering in pigeonpea. A single trait as well as a principal component based association study was conducted on a diverse collection of 142 pigeonpea lines for days to first and fifty percent of flowering over 3 years, besides plant height and number of seeds per pod. The analysis used seven association mapping models (GLM, MLM, MLMM, CMLM, EMLM, FarmCPU and SUPER) and further comparison revealed that FarmCPU is more robust in controlling both false positives and negatives as it incorporates multiple markers as covariates to eliminate confounding between testing marker and kinship. Cumulatively, a set of 22 SNPs were found to be associated with either days to first flowering (DOF), days to fifty percent flowering (DFF) or both, of which 15 were unique to trait based, 4 to PC based GWAS while 3 were shared by both. Because PC1 represents DOF, DFF and plant height (PH), four SNPs found associated to PC1 can be inferred as pleiotropic. A window of ± 2 kb of associated SNPs was aligned with available transcriptome data generated for transition from vegetative to reproductive phase in pigeonpea. Annotation analysis of these regions revealed presence of genes which might be involved in floral induction like Cytochrome p450 like Tata box binding protein, Auxin response factors, Pin like genes, F box protein, U box domain protein, chromatin remodelling complex protein, RNA methyltransferase. In summary, it appears that auxin responsive genes could be involved in regulating DOF and DFF as majority of the associated loci contained genes which are component of auxin signaling pathways in their vicinity. Overall, our findings indicates that the use of principal component analysis in GWAS is statistically more robust in terms of identifying genes and FarmCPU is a better choice compared to the other aforementioned models in dealing with both false positive and negative associations and thus can be used for traits with complex inheritance.

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