Cargando…

Reconstruction of gene regulatory modules from RNA silencing of IFN-α modulators: experimental set-up and inference method

BACKGROUND: Inference of gene regulation from expression data may help to unravel regulatory mechanisms involved in complex diseases or in the action of specific drugs. A challenging task for many researchers working in the field of systems biology is to build up an experiment with a limited budget...

Descripción completa

Detalles Bibliográficos
Autores principales: Grassi, Angela, Di Camillo, Barbara, Ciccarese, Francesco, Agnusdei, Valentina, Zanovello, Paola, Amadori, Alberto, Finesso, Lorenzo, Indraccolo, Stefano, Toffolo, Gianna Maria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4788926/
https://www.ncbi.nlm.nih.gov/pubmed/26969675
http://dx.doi.org/10.1186/s12864-016-2525-5
_version_ 1782420792880922624
author Grassi, Angela
Di Camillo, Barbara
Ciccarese, Francesco
Agnusdei, Valentina
Zanovello, Paola
Amadori, Alberto
Finesso, Lorenzo
Indraccolo, Stefano
Toffolo, Gianna Maria
author_facet Grassi, Angela
Di Camillo, Barbara
Ciccarese, Francesco
Agnusdei, Valentina
Zanovello, Paola
Amadori, Alberto
Finesso, Lorenzo
Indraccolo, Stefano
Toffolo, Gianna Maria
author_sort Grassi, Angela
collection PubMed
description BACKGROUND: Inference of gene regulation from expression data may help to unravel regulatory mechanisms involved in complex diseases or in the action of specific drugs. A challenging task for many researchers working in the field of systems biology is to build up an experiment with a limited budget and produce a dataset suitable to reconstruct putative regulatory modules worth of biological validation. RESULTS: Here, we focus on small-scale gene expression screens and we introduce a novel experimental set-up and a customized method of analysis to make inference on regulatory modules starting from genetic perturbation data, e.g. knockdown and overexpression data. To illustrate the utility of our strategy, it was applied to produce and analyze a dataset of quantitative real-time RT-PCR data, in which interferon-α (IFN-α) transcriptional response in endothelial cells is investigated by RNA silencing of two candidate IFN-α modulators, STAT1 and IFIH1. A putative regulatory module was reconstructed by our method, revealing an intriguing feed-forward loop, in which STAT1 regulates IFIH1 and they both negatively regulate IFNAR1. STAT1 regulation on IFNAR1 was object of experimental validation at the protein level. CONCLUSIONS: Detailed description of the experimental set-up and of the analysis procedure is reported, with the intent to be of inspiration for other scientists who want to realize similar experiments to reconstruct gene regulatory modules starting from perturbations of possible regulators. Application of our approach to the study of IFN-α transcriptional response modulators in endothelial cells has led to many interesting novel findings and new biological hypotheses worth of validation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-2525-5) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-4788926
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-47889262016-03-13 Reconstruction of gene regulatory modules from RNA silencing of IFN-α modulators: experimental set-up and inference method Grassi, Angela Di Camillo, Barbara Ciccarese, Francesco Agnusdei, Valentina Zanovello, Paola Amadori, Alberto Finesso, Lorenzo Indraccolo, Stefano Toffolo, Gianna Maria BMC Genomics Research Article BACKGROUND: Inference of gene regulation from expression data may help to unravel regulatory mechanisms involved in complex diseases or in the action of specific drugs. A challenging task for many researchers working in the field of systems biology is to build up an experiment with a limited budget and produce a dataset suitable to reconstruct putative regulatory modules worth of biological validation. RESULTS: Here, we focus on small-scale gene expression screens and we introduce a novel experimental set-up and a customized method of analysis to make inference on regulatory modules starting from genetic perturbation data, e.g. knockdown and overexpression data. To illustrate the utility of our strategy, it was applied to produce and analyze a dataset of quantitative real-time RT-PCR data, in which interferon-α (IFN-α) transcriptional response in endothelial cells is investigated by RNA silencing of two candidate IFN-α modulators, STAT1 and IFIH1. A putative regulatory module was reconstructed by our method, revealing an intriguing feed-forward loop, in which STAT1 regulates IFIH1 and they both negatively regulate IFNAR1. STAT1 regulation on IFNAR1 was object of experimental validation at the protein level. CONCLUSIONS: Detailed description of the experimental set-up and of the analysis procedure is reported, with the intent to be of inspiration for other scientists who want to realize similar experiments to reconstruct gene regulatory modules starting from perturbations of possible regulators. Application of our approach to the study of IFN-α transcriptional response modulators in endothelial cells has led to many interesting novel findings and new biological hypotheses worth of validation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-2525-5) contains supplementary material, which is available to authorized users. BioMed Central 2016-03-12 /pmc/articles/PMC4788926/ /pubmed/26969675 http://dx.doi.org/10.1186/s12864-016-2525-5 Text en © Grassi et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Grassi, Angela
Di Camillo, Barbara
Ciccarese, Francesco
Agnusdei, Valentina
Zanovello, Paola
Amadori, Alberto
Finesso, Lorenzo
Indraccolo, Stefano
Toffolo, Gianna Maria
Reconstruction of gene regulatory modules from RNA silencing of IFN-α modulators: experimental set-up and inference method
title Reconstruction of gene regulatory modules from RNA silencing of IFN-α modulators: experimental set-up and inference method
title_full Reconstruction of gene regulatory modules from RNA silencing of IFN-α modulators: experimental set-up and inference method
title_fullStr Reconstruction of gene regulatory modules from RNA silencing of IFN-α modulators: experimental set-up and inference method
title_full_unstemmed Reconstruction of gene regulatory modules from RNA silencing of IFN-α modulators: experimental set-up and inference method
title_short Reconstruction of gene regulatory modules from RNA silencing of IFN-α modulators: experimental set-up and inference method
title_sort reconstruction of gene regulatory modules from rna silencing of ifn-α modulators: experimental set-up and inference method
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4788926/
https://www.ncbi.nlm.nih.gov/pubmed/26969675
http://dx.doi.org/10.1186/s12864-016-2525-5
work_keys_str_mv AT grassiangela reconstructionofgeneregulatorymodulesfromrnasilencingofifnamodulatorsexperimentalsetupandinferencemethod
AT dicamillobarbara reconstructionofgeneregulatorymodulesfromrnasilencingofifnamodulatorsexperimentalsetupandinferencemethod
AT ciccaresefrancesco reconstructionofgeneregulatorymodulesfromrnasilencingofifnamodulatorsexperimentalsetupandinferencemethod
AT agnusdeivalentina reconstructionofgeneregulatorymodulesfromrnasilencingofifnamodulatorsexperimentalsetupandinferencemethod
AT zanovellopaola reconstructionofgeneregulatorymodulesfromrnasilencingofifnamodulatorsexperimentalsetupandinferencemethod
AT amadorialberto reconstructionofgeneregulatorymodulesfromrnasilencingofifnamodulatorsexperimentalsetupandinferencemethod
AT finessolorenzo reconstructionofgeneregulatorymodulesfromrnasilencingofifnamodulatorsexperimentalsetupandinferencemethod
AT indraccolostefano reconstructionofgeneregulatorymodulesfromrnasilencingofifnamodulatorsexperimentalsetupandinferencemethod
AT toffologiannamaria reconstructionofgeneregulatorymodulesfromrnasilencingofifnamodulatorsexperimentalsetupandinferencemethod