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Iron (Fe) deficiency is a pressing global health concern, particularly affecting vulnerable groups like women and children in resource-limited areas. Addressing this challenge requires innovative solutions, and biofortified crops, like Fe-enriched wheat, can offer a sustainable solution to improve nutrition in cereal-based diets. While conventional breeding methods have yielded competitive Fe-biofortified wheat varieties across various nations, the imminent challenges in securing food and nutritional security for the future necessitate a delicate balance: maintaining genetic progress in grain yield while concurrently elevating grain Fe content. Despite substantial strides in elucidating the intricacies of Fe homeostasis, there remains a substantial knowledge gap, especially in the context of wheat and similar crop species. It is paramount to gain a comprehensive understanding of the hurdles impeding Fe enrichment in plant tissues and delve into the diverse mechanisms governing Fe uptake, translocation, transport, and storage within wheat. To surmount these challenges, researchers have explored a multitude of strategies, including mutagenesis, QTL mapping, meta-QTL analysis, GWAS, transgenesis, and genome editing. Furthermore, harnessing the potential of microorganisms, particularly engineered endophytes coupled with plant genes associated with Fe accumulation, emerges as a promising and pragmatic tool for augmenting Fe biofortification in wheat. This comprehensive review underscores the significant advancements made in unravelling the genetic and genomic aspects of Fe accumulation in wheat, while also delineating the future research directions in this field. By synergistically deploying these multifaceted approaches, scientists hold the potential to develop wheat varieties characterized by enhanced grain Fe content, improved bioavailability, and reduced anti-nutritional factors. Such innovations can play a pivotal role in advancing nutrition and health outcomes for populations reliant on wheat-based diets, particularly in resource-scarce regions.

Grain protein content (GPC) is an important quality trait that effectively modulates end-use quality and nutritional characteristics of wheat flour-based food products. The Gpc-B1 gene is responsible for the higher protein content in wheat grain. In addition to higher GPC, the Gpc-B1 is also generally associated with reduced grain filling period which eventually causes the yield penalty in wheat. The main aim of the present study was to evaluate the effect of foliar application of potassium nitrate (PN) and salicylic acid (SA) on the physiological characteristics of a set of twelve genotypes, including nine isogenic wheat lines carrying the Gpc-B1 gene and three elite wheat varieties with no Gpc-B1 gene, grown at wheat experimental area of the Department of Plant Breeding and Genetics, PAU, Punjab, India. The PN application significantly increased the number of grains per spike (GPS) by 6.42 grains, number of days to maturity (DTM) by 1.03 days, 1000-grain weight (TGW) by 1.97 g and yield per plot (YPP) by 0.2 kg/plot. As a result of PN spray, the flag leaf chlorophyll content was significantly enhanced by 2.35 CCI at anthesis stage and by 1.96 CCI at 10 days after anthesis in all the tested genotypes. Furthermore, the PN application also significantly increased the flag leaf nitrogen content by an average of 0.52% at booting stage and by 0.35% at both anthesis and 10 days after anthesis in all the evaluated genotypes. In addition, the yellow peduncle colour at 30 days after anthesis was also increased by 19.08% while the straw nitrogen content was improved by 0.17% in all the genotypes. The preliminary experiment conducted using SA demonstrated a significant increase in DTM and other yield component traits. The DTM increased by an average of 2.31 days, GPS enhanced by approximately 3.17 grains, TGW improved by 1.13g, and YPP increased by 0.21 kg/plot. The foliar application of PN and SA had no significant effect on GPC itself. The findings of the present study suggests that applications of PN and SA can effectively mitigate the yield penalty associated with Gpc-B1 gene by extending grain filling period in the wheat.

Abstract In wheat, a meta-analysis was performed using previously identified QTLs associated with drought stress (DS), heat stress (HS), salinity stress (SS), water-logging stress (WS), pre-harvest sprouting (PHS), and aluminium stress (AS) which predicted a total of 134 meta-QTLs (MQTLs) that involved at least 28 consistent and stable MQTLs conferring tolerance to five or all six abiotic stresses under study. Seventy-six MQTLs out of the 132 physically anchored MQTLs were also verified with genome-wide association studies. Around 43% of MQTLs had genetic and physical confidence intervals of less than 1 cM and 5 Mb, respectively. Consequently, 539 genes were identified in some selected MQTLs providing tolerance to 5 or all 6 abiotic stresses. Comparative analysis of genes underlying MQTLs with four RNA-seq based transcriptomic datasets unravelled a total of 189 differentially expressed genes which also included at least 11 most promising candidate genes common among different datasets. The promoter analysis showed that the promoters of these genes include many stress responsiveness cis-regulatory elements, such as ARE, MBS, TC-rich repeats, As-1 element, STRE, LTR, WRE3, and WUN-motif among others. Further, some MQTLs also overlapped with as many as 34 known abiotic stress tolerance genes. In addition, numerous ortho-MQTLs among the wheat, maize, and rice genomes were discovered. These findings could help with fine mapping and gene cloning, as well as marker-assisted breeding for multiple abiotic stress tolerances in wheat.

The high performance and stability of wheat genotypes for yield, grain protein content (GPC), and other desirable traits are critical for varietal development and food and nutritional security. Likewise, the genotype by environment (G × E) interaction (GEI) should be thoroughly investigated and favorably utilized whenever genotype selection decisions are made. The present study was planned with the following two major objectives: 1) determination of GEI for some advanced wheat genotypes across four locations (Ludhiana, Ballowal, Patiala, and Bathinda) of Punjab, India; and 2) selection of the best genotypes with high GPC and yield in various environments. Different univariate [Eberhart and Ruessll’s models; Perkins and Jinks’ models; Wrike’s Ecovalence; and Francis and Kannenberg’s models], multivariate (AMMI and GGE biplot), and correlation analyses were used to interpret the data from the multi-environmental trial (MET). Consequently, both the univariate and multivariate analyses provided almost similar results regarding the top-performing and stable genotypes. The analysis of variance revealed that variation due to environment, genotype, and GEI was highly significant at the 0.01 and 0.001 levels of significance for all studied traits. The days to flowering, plant height, spikelets per spike, grain per spike, days to maturity, and 1000-grain weight were specifically affected by the environment, whereas yield was mainly affected by the environment and GEI. Genotypes, on the other hand, had a greater impact on the GPC than environmental conditions. As a result, a multi-environmental investigation was necessary to identify the GEI for wheat genotype selection because the GEI was very significant for all of the evaluated traits. Yield, 1000-grain weight, spikelet per spike, and days to maturity were observed to have positive correlations, implying the feasibility of their simultaneous selection for yield enhancement. However, GPC was observed to have a negative correlation with yield. Patiala was found to be the most discriminating environment for both yield and GPC and also the most effective representative environment for GPC, whereas Ludhiana was found to be the most effective representative environment for yield. Eventually, two NILs (BWL7508, and BWL7511) were selected as the top across all environments for both yield and GPC.

As a staple food crop, rice has gained mainstream attention in genome engineering for its genetic improvement. Genome engineering technologies such as transgenic and genome editing have enabled the significant improvement of target traits in relation to various biotic and abiotic aspects as well as nutrition, for which genetic diversity is lacking. In comparison to conventional breeding, genome engineering techniques are more precise and less time-consuming. However, one of the major issues with biotech rice commercialization is the utilization of selectable marker genes (SMGs) in the vector construct, which when incorporated into the genome are considered to pose risks to human health, the environment, and biodiversity, and thus become a matter of regulation. Various conventional strategies (co-transformation, transposon, recombinase systems, and MAT-vector) have been used in rice to avoid or remove the SMG from the developed events. However, the major limitations of these methods are; time-consuming, leftover cryptic sequences in the genome, and there is variable frequency. In contrast to these methods, CRISPR/Cas9-based marker excision, marker-free targeted gene insertion, programmed self-elimination, and RNP-based delivery enable us to generate marker-free engineered rice plants precisely and in less time. Although the CRISPR/Cas9-based SMG-free approaches are in their early stages, further research and their utilization in rice could help to break the regulatory barrier in its commercialization. In the current review, we have discussed the limitations of traditional methods followed by advanced techniques. We have also proposed a hypothesis, “DNA-free marker-less transformation” to overcome the regulatory barriers posed by SMGs.