Journal of Agronomy and Field Innovations

Background: Wheat (Triticum aestivum L.) is known as a basic food crop whose productivity relies heavily on nitrogen (N) fertilization, but a significant amount of used N is not absorbed by the crop. This results in inefficiency and environmental damage. Consequently, improving nitrogen use efficiency (NUE) is a key goal of modern wheat breeding. However, the complexity of both genetic and physiological structure of these characteristic limits the power of traditional studies in solving the problems connected with wheat breeding.
Objective: The aim of this research is to demonstrate the application of a multi-omics approach based upon genomics, transcriptomics, proteomics and metabolomics in solving the issues surrounding molecular basis of NUE in divergent wheat genotypes and translating this into useful information for breeding programs.
Methods framework: Wheat genotypes characterized by varying efficiency levels of nitrogen utilization were studied under different nitrogen conditions in the field and a controlled greenhouse environment. Various phenotypic, genomic, transcriptomic, proteomic, and metabolomic parameters were obtained and subsequently analyzed using several statistical tools like ANOVA, principal components analysis, weighted gene co-expression network analysis, and multi-omic factor integration.
Results: According to the combined evaluation, genomic locations, genes that have different expressions, various kinds of proteins and products related to nitrogen have gathered in certain biological groups in charge of the operations of nitrate transportation and absorption, ammonia assimilation, amino acid synthesis, regulation of carbon and nitrogen balance, and processes of remobilization in old plants. Noteworthy regulatory genes responsible for nitrate transportation, forms of glutamine synthetase, NAC and bZIP transcription factors, and asparagine synthetase appeared to be basic links, confirmed by the available proofs.
Significance and conclusion: In conclusion, it is clear that multi-omics integration has allowed us to gain the resolution necessary to prioritize candidate genes for NUE improvement better than could be accomplished by any individual omics layer alone. The approach we developed can be used to design genomic selection panels and breeding strategies, and for gene editing to produce environmentally friendly, nitrogen-efficient wheat.