Browsing by Author "Katari, Manpreet S."

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    An integrated genetic, genomic and systems approach defines gene networks regulated by the interaction of light and carbon signaling pathways in Arabidopsis
    (2008) Thum, Karen E.; Shin, Michael J.; Gutiérrez Ilabaca, Rodrigo Antonio; Mukherjee, Indrani; Katari, Manpreet S.; Nero, Damion; Shasha, Dennis; Coruzzi, Gloria M.
    Abstract Background Light and carbon are two important interacting signals affecting plant growth and development. The mechanism(s) and/or genes involved in sensing and/or mediating the signaling pathways involving these interactions are unknown. This study integrates genetic, genomic and systems approaches to identify a genetically perturbed gene network that is regulated by the interaction of carbon and light signaling in Arabidopsis. Results C arbon and l ight i nsensitive (cli) mutants were isolated. Microarray data from cli186 is analyzed to identify the genes, biological processes and gene networks affected by the integration of light and carbon pathways. Analysis of this data reveals 966 genes regulated by light and/or carbon signaling in wild-type. In cli186, 216 of these light/carbon regulated genes are misregulated in response to light and/or carbon treatments where 78% are misregulated in response to light and carbon interactions. Analysis of the gene lists show that genes in the biological processes "energy" and "metabolism" are over-represented among the 966 genes regulated by carbon and/or light in wild-type, and the 216 misregulated genes in cli186. To understand connections among carbon and/or light regulated genes in wild-type and the misregulated genes in cli186, the microarray data is interpreted in the context of metabolic and regulatory networks. The network created from the 966 light/carbon regulated genes in wild-type, reveals that cli186 is affected in the light and/or carbon regulation of a network of 60 connected genes, including six transcription factors. One transcription factor, HAT22 appears to be a regulatory "hub" in the cli186 network as it shows regulatory connections linking a metabolic network of genes involved in "amino acid metabolism", "C-compound/carbohydrate metabolism" and "glycolysis/gluconeogenesis". Conclusion The global misregulation of gene networks controlled by light and carbon signaling in cli186 indicates that it represents one of the first Arabidopsis mutants isolated that is specifically disrupted in the integration of both carbon and light signals to control the regulation of metabolic, developmental and regulatory genes. The network analysis of misregulated genes suggests that CLI186 acts to integrate light and carbon signaling interactions and is a master regulator connecting the regulation of a host of downstream metabolic and regulatory processes.
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    Integrated RNA-seq and sRNA-seq analysis identifies novel nitrate-responsive genes in Arabidopsis thaliana roots
    (2013) Vidal, Elena A.; Moyano, Tomas C.; Krouk, Gabriel; Katari, Manpreet S.; Tanurdzic, Milos; McCombie, W. Richard; Coruzzi, Gloria M.; Gutierrez, Rodrigo A.
    Background: Nitrate and other nitrogen metabolites can act as signals that regulate global gene expression in plants. Adaptive changes in plant morphology and physiology triggered by changes in nitrate availability are partly explained by these changes in gene expression. Despite several genome-wide efforts to identify nitrate-regulated genes, no comprehensive study of the Arabidopsis root transcriptome under contrasting nitrate conditions has been carried out.
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    Sungear
    (2007) Poultney, Christopher S.; Gutierrez, Rodrigo A.; Katari, Manpreet S.; Gifford, Miriam L.; Paley, W. Bradford; Coruzzi, Gloria M.; Shasha, Dennis E.
    Sungear is a software system that supports a rapid, visually interactive and biologist-driven comparison of large datasets. The datasets can come from microarray experiments (e.g. genes induced in each experiment), from comparative genomics (e.g. genes present in each genome) or even from non-biological applications (e.g. demographics or baseball statistics). Sungear represents multiple datasets as vertices in a polygon. Each possible intersection among the sets is represented as a circle inside the polygon. The position of the circle is determined by the position of the vertices represented in the intersection and the area of the circle is determined by the number of elements in the intersection. Sungear shows which Gene Ontology terms are over-represented in a subset of circles or anchors. The intuitive Sungear interface has enabled biologists to determine quickly which dataset or groups of datasets play a role in a biological function of interest.