Omics technologies, namely genomics, transcriptomics, proteomics, metabolomics, and phenomics, are becoming an integral part of virtually every commercial cereal crop breeding program, as they provide substantial dividends per unit time in both pre-breeding and breeding phases. Continuous advances in omics assure time efficiency and cost benefits to improve cereal crops. This review provides a comprehensive overview of the established omics methods in five major cereals, namely rice, sorghum, maize, barley, and bread wheat. We cover the evolution of technologies in each omics section independently and concentrate on their use to improve economically important agronomic as well as biotic and abiotic stress-related traits. Advancements in the (1) identification, mapping, and sequencing of molecular/structural variants; (2) high-density transcriptomics data to study gene expression patterns; (3) global and targeted proteome profiling to study protein structure and interaction; (4) metabolomic profiling to quantify organ-level, small-density metabolites, and their composition; and (5) high-resolution, high-throughput, image-based phenomics approaches are surveyed in this review.

Tan spot, caused by the fungus Pyrenophoratritici-repentis (Ptr), is a severe foliar disease of wheat (Triticumaestivum L.). Improving genetic resistance is a durable strategy to reduce Ptr-related losses. Here, we dissected Ptr-infection’s genetic basis in 372 European wheat varieties via simple sequence repeats (SSRs) plus 35k and 90k single nucleotide polymorphism (SNP) marker platforms. In our phenotypic data analyses, Ptr infection showed a significant genotypic variance and a significant negative correlation with plant height. Genome-wide association studies revealed a highly quantitative nature of Ptr infection and identified two quantitative trait loci (QTL), viz., QTs.ipk-7A and QTs.ipk-7B, which imparted 21.23 and 5.84% of the genotypic variance, respectively. Besides, the Rht-D1 gene showed a strong allelic influence on the infection scores. Due to the complex genetic nature of the Ptr infection, the potential of genome-wide prediction (GP) was assessed via three different genetic models on individual and combined marker platforms. The GP results indicated that the marker density and marker platforms do not considerably impact prediction accuracy (~40–42%) and that higher-order epistatic interactions may not be highly pervasive. Our results provide a further understanding of Ptr-infection’s genetic nature, serve as a resource for marker-assisted breeding, and highlight the potential of genome-wide selection for improved Ptr resistance.

Sustainable production and improved genetic gains can be achieved by broadening the genetic window of elite wheat germplasm. Here, we induced mutations in two spring wheat varieties, viz., NN-Gandum-1 (NN-1) and Punjab-11 (Pb-11), by exposing their seeds to ethyl methane sulfonate (EMS) and γ-rays, respectively. We characterized >3500 lines of each NN-1 and Pb-11 derived population in three consecutive generations, viz., M₅, M₆, and M₇, for important traits, e.g., plant height, heading date, spike morphology and rust resistance. We observed significant genetic variation and correlations in both populations for all investigated traits. We observed differences in terms of number of mutants between NN-1 (22.76%) and Pb-11 (26.18%) which could be ascribed to the genotype-by-mutagen interaction. High broad-sense heritability (H²) estimates, that are vital for higher genetic gains, were observed for all of the investigated traits in both populations (H² = 0.69–0.91 in NN-1 and 0.84–0.98 in Pb-11). Particularly, to breed for rust resistance, we selected a subset (n = 239) of M₇ lines that also showed phenotypic variation for other traits. Our studies (1) show the relevance to artificial mutagenesis to create genetic variation in elite germplasm for their immediate use in current breeding programs, and (2) provide material for downstream identification of genes associated with traits of high agronomic importance.

Spikelet abortion is a phenomenon where apical spikelet primordia on an immature spike abort. Regardless of the row-type, both apical and basal spikelet abortion occurs, and their extent decides the number of grain-bearing spikelets retained on the spike—thus, affecting the yield potential of barley. Reducing spikelet abortion, therefore, represents an opportunity to increase barley yields. Here, we investigated the variation for apical spikelet abortion along with 16 major spike, shoot, and grain traits in a panel of 417 six-rowed spring barleys. Our analyses showed a significantly large genotypic variation resulting in high heritability estimates for all the traits. Spikelet abortion (SA) varies from 13 to 51% depending on the genotype and its geographical origin. Among the seven spike traits, SA was negatively correlated with final spikelet number, spike length and density, while positively with awn length. This positive correlation suggests a plausible role of the rapidly growing awns during the spikelet abortion process, especially after Waddington stage 5. In addition, SA also showed a moderate positive correlation with grain length, grain area and thousand-grain weight. Our hierarchical clustering revealed distinct genetic underpinning of grain traits from the spike and shoot traits. Trait associations showed a geographical bias whereby European accessions displayed higher SA and grain and shoot trait values, whereas the trend was opposite for the Asian accessions. To study the observed phenotypic variation of SA explained by 16 other individual traits, we applied linear, quadratic, and generalized additive regression models (GAM). Our analyses of SA revealed that the GAM generally performed superior in comparison to the other models. The genetic interactions among traits suggest novel breeding targets and easy-to-phenotype “proxy-traits” for high throughput on-field selection for grain yield, especially in early generations of barley breeding programs.