Metabolomics is an emerging branch of “omics” and it involves identification and quantification of metabolites and chemical footprints of cellular regulatory processes in different biological species. The metabolome is the total metabolite pool in an organism, which can be measured to characterize genetic or environmental variations. Metabolomics plays a significant role in exploring environment–gene interactions, mutant characterization, phenotyping, identification of biomarkers, and drug discovery. Metabolomics is a promising approach to decipher various metabolic networks that are linked with biotic and abiotic stress tolerance in plants. In this context, metabolomics-assisted breeding enables efficient screening for yield and stress tolerance of crops at the metabolic level. Advanced metabolomics analytical tools, like non-destructive nuclear magnetic resonance spectroscopy (NMR), liquid chromatography mass-spectroscopy (LC-MS), gas chromatography-mass spectrometry (GC-MS), high performance liquid chromatography (HPLC), and direct flow injection (DFI) mass spectrometry, have sped up metabolic profiling. Presently, integrating metabolomics with post-genomics tools has enabled efficient dissection of genetic and phenotypic association in crop plants. This review provides insight into the state-of-the-art plant metabolomics tools for crop improvement. Here, we describe the workflow of plant metabolomics research focusing on the elucidation of biotic and abiotic stress tolerance mechanisms in plants. Furthermore, the potential of metabolomics-assisted breeding for crop improvement and its future applications in speed breeding are also discussed. Mention has also been made of possible bottlenecks and future prospects of plant metabolomics.

Stripe rust caused by the pathogen Puccinia striiformis f. sp. tritici (Pst) is a major threat for wheat, resulting in low yield and grain quality loss in many countries. Genetic resistance is a prevalent method to combat the disease. Mapping the resistant loci and their association with traits is highly exploited in this era. A panel of 465 Pakistani spring wheat genotypes were evaluated for their phenotypic response to stripe rust at the seedling and adult plant stages. A total of 765 single nucleotide polymorphism (SNP) markers were applied on 465 wheat genotypes to evaluate their stripe rust response against nine races during the seedling test and in three locations for the field test. Currently, twenty SNPs dispersed on twelve chromosomal regions (1A, 1B, 1D, 2A, 2B, 4A, 4B, 5B, 6A, 6B, 6D and 7B) have been identified that were associated with rust race-specific resistance at the seedling stage. Thirty SNPs dispersed on eighteen chromosomal regions (1A, 1B, 1D, 2A, 2B, 2D, 3A, 3B, 3D, 4B, 5A, 5B, 6A, 6B, 6D, 7A, 7B and 7D) are associated with adult plant resistance. SNP loci IWB3662 was linked with all three Pakistani races, and likewise IWA2344 and IWA4096 were found to be linked with three different USA races. The present research findings can be applied by wheat breeders to increase their resistant capability and yield potential of their cultivars, through marker-assisted selection.

The success of plant breeding is based on the accessibility of genetic variation, information about desired traits with well-organized approach that make it likely to develop existing genetic resources. Food security demands to break the yield barrier through increasing new cultivars which can adapt to wide range of environment. It is especially important to observe the character association for yield along with its components before recognizing novel technique to break the yield barrier. There are numerous methods for improved exploiting of the inherent genetic makeup of crops with heritable variations. It is recommended that recognized parental resources can also be induced to mutate for unmasking novel alleles of genes that organize the traits suitable for the crop varieties of the 21st century world. Chemical mutagens have extensively been applied to make genetic changes in crop plants for breeding investigation as well as genetic studies. Ethyl methane sulphonate (EMS) is the most frequently applied as chemical agents in plants. EMS normally induces GC → AT transitions in the genome causing mutated protein that performed different functions rather than normal. It is exposed that the utilization of EMS is an efficient approach for developing novel gene pool.

Nonrenewable energy resources deplete with the passage of time due to rapid increase in industrialization and population. Hence, countries worldwide are investing dearly in substitute energy resources like biofuel from miscellaneous set of feedstocks. Among the energy crops, sorghum serves as a model crop due to its drought tolerance, small genome size (730 Mb), high biomass, dry matter contents, quick growth, wide adaptability to diverse climatic and soil conditions and C4 photosynthesis. Sweet sorghum with high sugar content in stalk is an efficient feedstock for advanced biofuels and other bio-based products from sugars. However, high biomass sorghum has the utility as a feedstock for cellulosic biofuels. The enhanced yield of monomeric carbohydrates is a key to cheap and efficient biofuel production. The efficiency of lignocellulosic biofuels is compromised by recalcitrance to cell wall digestion, a trait that cannot be efficiently improved by traditional breeding. Therefore, scientists are looking for solutions to such problems in biomass crop genomes. Sorghum genome has been completely sequenced and hence this crop qualifies for functional genomics analysis by fast forward genetic approaches. This chapter documents the latest efforts on advancement of sorghum for biomass potential at morphological and molecular level by exploiting genomics approaches.

For centuries, crop improvement has served as the basis of food security of ever increasing human population. Though vast germplasm collections are available; their exploitation for crop improvement still depends upon efficient assessment of genetic diversity. Genetic variability is the key element in adaptation of plants to varying climates. While crops with narrow genetic diversity are vulnerable to stresses. The estimation of extent and pattern of genetic variability is a prerequisite for generating superior varieties. Genetic diversity analysis generates key information to dissect genetic variations in crop germplasm with the help of morphometrical, biochemical and molecular tools. Among these, DNA markers provide a reliable and detailed insight into the similarities and differences among crops. In this chapter, we discuss the applications of phenotypic and molecular markers to probe genetic divergence in crops and present case studies that describe the significance of these tools to characterize sorghum germplasm. Furthermore, we spotlight sorghum biodiversity exploration efforts worldwide and propose future directions.

Introduction: Sweet sorghum is a C4 tropical grass species that has gained importance quickly as a major bioenergy crop.Methods: This genome-wide association study (GWAS) utilized a sweet sorghum panel (SSP) of 183 diverse sweet sorghum accessions genotyped by 14,819 high-quality single-nucleotide polymorphism (SNP) markers to identify novel genetic loci that are associated with major agronomic traits and sugars (Brix units, %).Results: Population stratification revealed a clear separation of the accessions based on geographical origins. The initial 50% linkage disequilibrium (LD) decay was approximately 5 kb, and the background level was approximately 80 kb, similar to that of the previously reported sorghum association panel (SAP), indicating the panel's effectiveness and reliability for GWAS. This study identified 21 significant quantitative trait nucleotides (QTNs) for the studied traits using the three (compressed)-variance component multi-locus random- SNP-effect mixed linear model (3VmrMLM), which were colocalized with previously reported quantitative trait loci (QTLs). The phenotypic variance (R2) explained by these QTNs ranged from 5.11% to 13.86%.Discussion: Additionally, haplotype analysis revealed significant phenotypic differences between haplotypes for four candidate genes, namely, Sobic.006G128200 (a threonine-specific protein kinase gene) for days to flowering, Sobic.001G387600 (an ethylene-insensitive gene) for Brix, Sobic.003G069950 (a protein kinase domain gene), and Sobic.003G214400 (an amino acid transporter gene) for fresh biomass.