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.

We dissected the genetic basis of total spikelet number (TSN) along with other traits, viz. spike length (SL) and flowering time (FT) in a panel of 518 elite European winter wheat varieties. Genome-wide association studies (GWAS) based on 39,908 SNP markers revealed highly significant quantitative trait loci (QTL) for TSN on chromosomes 2D, 7A, and 7B, for SL on 5A, and FT on 2D, with 2D-QTL being the functional marker for the gene Ppd-D1. The physical region of the 7A-QTL for TSN revealed the presence of a wheat ortholog (TaAPO-A1) to APO1–a rice gene that positively controls the spikelet number on the panicles. Interspecific analyses of the TaAPO-A1 orthologs showed that it is a highly conserved gene important for floral development and present in a wide range of terrestrial plants. Intraspecific studies of the TaAPO-A1 across wheat genotypes revealed a polymorphism in the conserved F-box domain, defining two haplotypes. A KASP marker developed on the polymorphic site showed a highly significant association of TaAPO-A1 with TSN, explaining 23.2% of the total genotypic variance. Also, the TaAPO-A1 alleles showed weak but significant differences for SL and grain yield. Our results demonstrate the importance of wheat sequence resources to identify candidate genes for important traits based on genetic analyses.

Grain quality traits determine the classification of registered wheat (Triticum aestivumL.) varieties. Although environmental factors and crop management practices exert a considerable influence on wheat quality traits, a significant proportion of the variance is attributed to the genetic factors. To identify the underlying genetic factors of wheat quality parameters viz., grain protein content (GPC), grain starch content (GSC), and grain hardness (GH), we evaluated 372 diverse European wheat varieties in replicated field trials in up to eight environments. We observed that all of the investigated traits hold a wide and significant genetic variation, and a significant negative correlation exists between GPC and GSCplusgrain yield. Our association analyses based on 26,694 high-quality single nucleotide polymorphic markers revealed a strong quantitative genetic nature of GPC and GSC with associations on groups 2, 3, and 6 chromosomes. The identification of knownPuroindoline-bgene for GH provided a positive analytic proof for our studies. We report that a locusQGpc.ipk-6Acontrols both GPC and GSC with opposite allelic effects. Based on wheat's reference and pan-genome sequences, the physical characterization of two loci viz.,QGpc.ipk-2BandQGpc.ipk-6Afacilitated the identification of the candidate genes for GPC. Furthermore, by exploiting additive and epistatic interactions of loci, we evaluated the prospects of predictive breeding for the investigated traits that suggested its efficient use in the breeding programs.

Septoria tritici blotch (STB) caused by the fungus Zymoseptoria tritici is a devastating foliar disease of wheat ( Triticum aestivum L.) that can lead to substantial yield losses. Quantitative genetic resistance has been proposed as a durable strategy for STB control. In this study, we dissected the genetic basis of STB infection in 371 European wheat varieties based on 35k and 90k single nucleotide polymorphism marker arrays. The phenotypic data analyses suggested that large genetic variance exists for STB infection with a broad‐sense heritability of 0.78. Genome‐wide association studies (GWAS) propose the highly quantitative nature of STB infection with potential associations on chromosomes 1A, 1B, 2D, 4A, 5A, 6A, 6D, 7A, and 7B. Increased marker density in GWAS by combining markers from both arrays helped to detect additional markers explaining increased genotypic variance. Linkage disequilibrium analyses revealed genes with a possible role in disease resistance. The potential of genomic prediction (GP) assessed via two models accounting for additive effects and additive plus epistatic interactions among the loci suggested the possibility of genomic selection for improved STB resistance. Genomic prediction results also indicated that the higher‐order epistatic interactions are not abundant and that both marker platforms are equally suitable for GP of STB infection. Our results provide further understanding of the quantitative genetic nature of STB infection, serve as a resource for marker‐assisted breeding, and highlight the potential of genomic selection for improved STB resistance.

Hybrid wheat breeding is gaining prominence worldwide because it ensures higher and more static yield than conventionally bred varieties. The cleistogamous floral architecture of wheat (Triticum aestivum L.) impedes anthers inside the floret, making it largely an inbreeder. For hybrid seed production, high anther extrusion is needed to promote cross pollination and to ensure a high level of pollen availability for the seed plant. This study, therefore, aimed at the genetic dissection of anther extrusion (AE) in panels of spring (SP) and winter wheat (WP) accessions by genome wide association studies (GWAS). We performed GWAS to identify the SNP markers potentially linked with AE in each panel separately. Phenotypic data were collected for three years for each panel. The average levels of Pearson’s correlation (r) among all years and their best linear unbiased estimates (BLUEs) within both panels were high (r (SP) = 0.75, P 3.0) marker trait associations (MTAs) were detected in both panels (SP = 11; WP = 12). Anther extrusion behaved as a complex trait with significant markers having either favourable or unfavourable additive effects and imparting minor to moderate levels of phenotypic variance (R2 (SP) = 9.75 – 14.24%; R2 (WP) = 9.44 – 16.98%). All mapped significant markers as well as the markers within their significant linkage disequilibrium (r2 ≥0.3) regions were blasted against wheat genome assembly (IWGSC1+popseq) to find the corresponding genes and their high confidence descriptions were retrieved. These genes and their orthologues in Hordeum vulgare, Brachypodium distachyon, Oryza sativa and Sorghum bicolor revealed syntenic genomic regions potentially involved in flowering-related traits. Moreover, the expression data of these genes suggested potential candidates for AE. Our results suggest that the use of significant markers can help to introduce AE in high yielding varieties to increase cross fertilization rates and improve hybrid-seed production in wheat.

In a number of crop species hybrids are able to outperform line varieties. The anthers of the autogamous bread wheat plant are normally extruded post anthesis, a trait which is unfavourable for the production of F1 hybrid grain. Higher anther extrusion (AE) promotes cross fertilization for more efficient hybrid seed production. Therefore, this study aimed at the genetic dissection of AE by genome wide association studies (GWAS) and determination of the main effect QTL. We applied GWAS approach to identify DArT markers potentially linked to AE to unfold its genetic basis in a panel of spring wheat accessions. Phenotypic data were collected for three years and best linear unbiased estimate (BLUE) values were calculated across all years. The extent of the AE correlation between growing years and BLUE values ranged from r = +0.56 (2013 vs 2015) to 0.91 (2014 vs BLUE values). The broad sense heritability was 0.84 across all years. Six accessions displayed stable AE >80% across all the years. Genotyping data included 2,575 DArT markers (with minimum of 0.05 minor allele frequency applied). AE was influenced both by genotype and by the growing environment. In all, 131 significant marker trait associations (MTAs) (|log₁₀ (P)| >FDR) were established for AE. AE behaved as a quantitative trait, with five consistently significant markers (significant across at least two years with a significant BLUE value) contributing a minor to modest proportion (4.29% to 8.61%) of the phenotypic variance and affecting the trait either positively or negatively. For this reason, there is potential for breeding for improved AE by gene pyramiding. The consistently significant markers linked to AE could be helpful for marker assisted selection to transfer AE to high yielding varieties allowing to promote the exploitation of hybrid-heterosis in the key crop wheat.