Browsing by Author "Ashraf, Nasheeman"

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    Comparative analyses of genotype dependent expressed sequence tags and stress-responsive transcriptome of chickpea wilt illustrate predicted and unexpected genes and novel regulators of plant immunity
    (BioMed Central, 2009) Ashraf, Nasheeman; Ghai, Deepali; Barman, Pranjan; Basu, Swaraj; Gangisetty, Nagaraju; Mandal, Mihir K; Chakraborty, Niranjan; Datta, Asis; Chakraborty, Subhra
    Background: The ultimate phenome of any organism is modulated by regulated transcription of many genes. Characterization of genetic makeup is thus crucial for understanding the molecular basis of phenotypic diversity, evolution and response to intra- and extra-cellular stimuli. Chickpea is the world's third most important food legume grown in over 40 countries representing all the continents. Despite its importance in plant evolution, role in human nutrition and stress adaptation, very little ESTs and differential transcriptome data is available, let alone genotype-specific gene signatures. Present study focuses on Fusarium wilt responsive gene expression in chickpea. Results: We report 6272 gene sequences of immune-response pathway that would provide genotype- dependent spatial information on the presence and relative abundance of each gene. The sequence assembly led to the identification of a CaUnigene set of 2013 transcripts comprising of 973 contigs and 1040 singletons, two-third of which represent new chickpea genes hitherto undiscovered. We identified 209 gene families and 262 genotype-specific SNPs. Further, several novel transcription regulators were identified indicating their possible role in immune response. The transcriptomic analysis revealed 649 non- cannonical genes besides many unexpected candidates with known biochemical functions, which have never been associated with pathostress-responsive transcriptome. Conclusion: Our study establishes a comprehensive catalogue of the immune-responsive root transcriptome with insight into their identity and function. The development, detailed analysis of CaEST datasets and global gene expression by microarray provide new insight into the commonality and diversity of organ-specific immune-responsive transcript signatures and their regulated expression shaping the species specificity at genotype level. This is the first report on differential transcriptome of an unsequenced genome during vascular wilt.
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    Integrative network analyses of wilt transcriptome in chickpea reveal genotype dependent regulatory hubs in immunity and susceptibility
    (Springer Nature, 2018) Ashraf, Nasheeman; Basu, Swaraj; Narula, Kanika; Ghosh, Sudip; Tayal, Rajul; Gangisetty, Nagaraju; Biswas, Sushmita; Aggarwal, Pooja R.; Chakraborty, Niranjan; Chakraborty, Subhra
    Host specific resistance and non-host resistance are two plant immune responses to counter pathogen invasion. Gene network organizing principles leading to quantitative differences in resistant and susceptible host during host specific resistance are poorly understood. Vascular wilt caused by root pathogen Fusarium species is complex and governed by host specific resistance in crop plants, including chickpea. Here, we temporally profiled two contrasting chickpea genotypes in disease and immune state to better understand gene expression switches in host specific resistance. Integrative gene-regulatory network elucidated tangible insight into interaction coordinators leading to pathway determination governing distinct (disease or immune) phenotypes. Global network analysis identified five major hubs with 389 co-regulated genes. Functional enrichment revealed immunome containing three subnetworks involving CTI, PTI and ETI and wilt diseasome encompassing four subnetworks highlighting pathogen perception, penetration, colonization and disease establishment. These subnetworks likely represent key components that coordinate various biological processes favouring defence or disease. Furthermore, we identified core 76 disease/immunity related genes through subcellular analysis. Our regularized network with robust statistical assessment captured known and unexpected gene interaction, candidate novel regulators as future biomarkers and first time showed system-wide quantitative architecture corresponding to genotypic characteristics in wilt landscape.