Reconstructing a Genetic Network from Gene Perturbations in Secretory Pathway of Cancer Cell Lines

Marina Piccirillo (), Kumar Parijat Tripathi, Sonali Gopichand Chavan, Alessandra Varavallo, Seetharaman Parashuraman and Mario Rosario Guarracino
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Marina Piccirillo: High Performance Computing and Networking Institute (ICAR), National Research Council (CNR), Laboratory for Genomics, Transcriptomics and Proteomics (Lab-GTP)
Kumar Parijat Tripathi: High Performance Computing and Networking Institute (ICAR), National Research Council (CNR), Laboratory for Genomics, Transcriptomics and Proteomics (Lab-GTP)
Sonali Gopichand Chavan: National Research Council (CNR-IBP), Institute of Protein Biochemistry
Alessandra Varavallo: National Research Council (CNR-IBP), Institute of Protein Biochemistry
Seetharaman Parashuraman: National Research Council (CNR-IBP), Institute of Protein Biochemistry
Mario Rosario Guarracino: High Performance Computing and Networking Institute (ICAR), National Research Council (CNR), Laboratory for Genomics, Transcriptomics and Proteomics (Lab-GTP)

A chapter in Dynamics of Mathematical Models in Biology, 2016, pp 65-77 from Springer

Abstract: Abstract Gene perturbation studies play an important role in the reconstruction of genetic networks and in determining the influence of genes on each other activities. According to this hypothesis, we planned to develop new analysis methods, based on novel algorithms, to reconstruct genetic networks by incorporating gene expression datasets, containing profiles of cell lines that have been exposed to genetic perturbations. In the present work, we focus on a list of genes, localized in secretory pathway. These genes and their products are responsible for the delivery of different kind of proteins from their site of synthesis to their proper cellular location and they are essential for cellular functions and multicellular development. Using data from high-throughput experiments, gene expression profiles are collected from 33 genes perturbations (knockdown and over-expressed) experiments in four cancer cell lines. Data have been downloaded from the Library of Integrated Network-Based Cellular Signatures. We characterized gene regulatory networks of secretory pathway, and we provided some empirical results of the network modular organization. The interesting observation is that all these regulatory genes are also connected with each other through hub nodes. It means that interactions do not have a separate entity and are not regulated by independent behavior of perturbed genes, but probably, there is a global effect of all these perturbations on all subnetworks present in an interaction network.

Keywords: Perturbation; Genetic network; Algorithm; Secretory pathway (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-45723-9_6

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DOI: 10.1007/978-3-319-45723-9_6

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