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.
Flowering plants with indeterminate inflorescences often produce more floral structures than they require. We found that floral primordia initiations in barley ( Hordeum vulgare L.) are molecularly decoupled from their maturation into grains. While initiation is dominated by flowering-time genes, floral growth is specified by light signaling, chloroplast, and vascular developmental programs orchestrated by barley CCT MOTIF FAMILY 4 ( HvCMF4 ), which is expressed in the inflorescence vasculature. Consequently, mutations in HvCMF4 increase primordia death and pollination failure, mainly through reducing rachis greening and limiting plastidial energy supply to developing heterotrophic floral tissues. We propose that HvCMF4 is a sensory factor for light that acts in connection with the vascular-localized circadian clock to coordinate floral initiation and survival. Notably, stacking beneficial alleles for both primordia number and survival provides positive implications on grain production. Our findings provide insights into the molecular underpinnings of grain number determination in cereal crops.
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 single sequence repeats (SSR) in addition to 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 resistance 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.
The potential to increase barley grain yield lies in the indeterminate nature of its inflorescence meristem (IM). The IM produces spikelets, the basic reproductive unit in grasses, which are linked to reproductive success. During early reproductive growth, barley spikes pass through the maximum yield potential—a stage after which no new spikelet ridges are produced. Subsequently, spikelet abortion (SA), a phenomenon in which spikelets abort during spike growth, imposes a bottleneck on increasing the grain yield potential. Here, we studied the potential of main culm spikes by counting potential spikelet number (PSN), final spikelet number (FSN) and computed the corresponding SA (%) in a panel of 417 six-rowed spring barleys. Our phenotypic data analyses showed a significantly large within- and across-years genotypic variation with high broad-sense heritability estimates for all the investigated traits, including SA. Asian accessions displayed the lowest SA indicating the presence of favorable alleles that may be exploited in breeding programs. A significantly negative Pearson’s product-moment correlation was observed between FSN and SA. Our path analysis revealed that PSN and FSN explain 93% of the observed phenotypic variability for SA with PSN behaving as a suppressor trait magnifying the effect. Based on a large set of diverse barley accessions, our results provide a deeper phenotypic understanding of the quantitative genetic nature of SA, its association with traits of high agronomic importance, and a resource for further genetic analyses.
Omics technologies, viz., genomics, transcriptomics, proteomics, metabolomics, and phenomics, are becoming an integral part of virtually every commercial cereal breeding program because they provide substantial dividends per unit time in both pre-breeding and breeding phases. Continuous advances in cereal-omics promise—in combination with time efficiency—the cost benefits. In this review, we provide a comprehensive overview of the established cereal-omics methods in five major cereals, viz., 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.
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