European Journal of Sustainable Agroecosystems

The problem of nitrogen deficiency remains one of the key limiting factors in the overall productivity of maize (Zea mays L.) all around the world, as it is very important to follow how certain root cell types "see" and react to nitrogen deficiency for the sake of improving nitrogen-use efficiency (NUE) in such crops that utilize huge amounts of nitrogen fertilizers. The technique of single-cell RNA sequencing (scRNAseq) is widely used for the purpose of obtaining data concerning the cell type-specific expression of genes which cannot be done with the help of bulk transcriptomic techniques because of their averaging of information received from a mixed root tissue. The review gathered data from the scientific literature concerning single-cell transcriptomic studies of maize and other plants in relation to root development and nitrogen deficiency response. It was actively pointed to in the previous studies that nine to eleven different root cell types have been identified thanks to maize root scRNAseq methods such as the epidermis, root hair, cortex, endodermis, pericycle, and vascular tissue with different types of marker gene expression. It was shown that the information concerning the expression of genes linked to nitrate transception and transport, components epidermal cells. The review also highlights important shortcomings, such as the dominance of many basic scRNA-seq techniques in Arabidopsis as opposed to maize, relatively few studies of maize root scRNA-seq that examine effects specifically related to nitrogen deficiency despite the huge amount of available literature regarding nitrate's impact, and limited success in converting potentially useful candidate genes identified in scRNA-seq studies into breeding targets for the enhancement of nitrogen-use efficiency. It is emphasized, therefore, that single-cell transcriptomics can provide a valid and increasingly practical scientific framework for the investigation of cell type-related reactions to nitrogen in maize roots, and several key points have been identified for application of scRNA-seq data to developing actual breeding targets based on identified genes and other candidate genes.