The economic value of wheat grain is determined by the kernel morphology which is an important parameter for manufacturing different food products requiring specific grain characteristics. Although kernel size and shape have emerged as important breeding objectives, not much information is available about the number or location of associated gene(s)/quantitative trait loci. In the present study, a recombinant inbred line population of 106 plants (F 7 ) was phenotyped for four traits, namely kernel length, width, weight and factor form density (FFD) and genotyped with different polymerase chain reaction-based markers. Transgressive segregants were observed for all the traits and genetic correlation studies showed positive correlations between the majority of the traits. The number of markers associated with each trait ranged from two to nine and the phenotypic contribution by an individual marker ranged from 3.3 to 16.6%. Many of the markers showed linkage to more than one trait. Strategies for improving the wheat grain quality traits and the utility of such markers in marker-assisted selection (MAS) efforts are discussed.
SummaryMolecular changes elicited by plants in response to fungal attack and how this affects plant–pathogen interaction, including susceptibility or resistance, remain elusive. We studied the dynamics in root metabolism during compatible and incompatible interactions between chickpea and Fusarium oxysporum f. sp. ciceri (Foc), using quantitative label‐free proteomics and NMR‐based metabolomics. Results demonstrated differential expression of proteins and metabolites upon Foc inoculations in the resistant plants compared with the susceptible ones. Additionally, expression analysis of candidate genes supported the proteomic and metabolic variations in the chickpea roots upon Foc inoculation. In particular, we found that the resistant plants revealed significant increase in the carbon and nitrogen metabolism; generation of reactive oxygen species (ROS), lignification and phytoalexins. The levels of some of the pathogenesis‐related proteins were significantly higher upon Foc inoculation in the resistant plant. Interestingly, results also exhibited the crucial role of altered Yang cycle, which contributed in different methylation reactions and unfolded protein response in the chickpea roots against Foc. Overall, the observed modulations in the metabolic flux as outcome of several orchestrated molecular events are determinant of plant's role in chickpea–Foc interactions.
Insect pests remain a major reason for crop loss worldwide despite extensive use of chemical insecticides. More than 50% of all insecticides are organophosphates, followed by synthetic pyrethroids, organochlorines, carbamates, and biopesticides, and their continued use may have many environmental, agricultural, medical, and socioeconomic issues. Importantly, only a countable number of insects have acquired the status of crop pests, mostly due to monoculture of crop plants and polyphagous nature of the insects. We focus on adaptations of Lepidopteran insects to phytochemicals and synthetic pesticides in native and modern agricultural systems. Because of heavy use of chemical insecticides, a strong selection pressure is imposed on insect populations, resulting in the emergence of resistance against candidate compound(s). Current knowledge suggests that insects generally implement a three-tier system to overcome the effect of toxic compounds at physiological, biochemical, and genetic levels. Furthermore, we have discussed whether the adaptation to phytochemicals provides an advantage to the insect while encountering synthetic insecticide molecules. Specific metabolic pathways employed by insects to convert deterrents into less toxic forms or their removal from the system are highlighted. Using the proteomics approach, insect proteins interacting with insecticides can be identified, and their modification in resistant insects can be characterized. Also, systems biology studies can offer useful cues to decipher the molecular networks participating in the metabolism of detrimental compounds.
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