Using answer set programming to integrate RNA expression with signalling pathway information to infer how mutations affect ageing.

A challenge of systems biology is to integrate incomplete knowledge on pathways with existing experimental data sets and relate these to measured phenotypes. Research on ageing often generates such incomplete data, creating difficulties in integrating RNA expression with information about biological...

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Autores principales:	Irene Papatheodorou, Matthias Ziehm, Daniela Wieser, Nazif Alic, Linda Partridge, Janet M Thornton
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/d33dc7059f154716bc11f6c07d81d475
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spelling	oai:doaj.org-article:d33dc7059f154716bc11f6c07d81d4752021-11-18T08:05:50ZUsing answer set programming to integrate RNA expression with signalling pathway information to infer how mutations affect ageing.1932-620310.1371/journal.pone.0050881https://doaj.org/article/d33dc7059f154716bc11f6c07d81d4752012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23251396/?tool=EBIhttps://doaj.org/toc/1932-6203A challenge of systems biology is to integrate incomplete knowledge on pathways with existing experimental data sets and relate these to measured phenotypes. Research on ageing often generates such incomplete data, creating difficulties in integrating RNA expression with information about biological processes and the phenotypes of ageing, including longevity. Here, we develop a logic-based method that employs Answer Set Programming, and use it to infer signalling effects of genetic perturbations, based on a model of the insulin signalling pathway. We apply our method to RNA expression data from Drosophila mutants in the insulin pathway that alter lifespan, in a foxo dependent fashion. We use this information to deduce how the pathway influences lifespan in the mutant animals. We also develop a method for inferring the largest common sub-paths within each of our signalling predictions. Our comparisons reveal consistent homeostatic mechanisms across both long- and short-lived mutants. The transcriptional changes observed in each mutation usually provide negative feedback to signalling predicted for that mutation. We also identify an S6K-mediated feedback in two long-lived mutants that suggests a crosstalk between these pathways in mutants of the insulin pathway, in vivo. By formulating the problem as a logic-based theory in a qualitative fashion, we are able to use the efficient search facilities of Answer Set Programming, allowing us to explore larger pathways, combine molecular changes with pathways and phenotype and infer effects on signalling in in vivo, whole-organism, mutants, where direct signalling stimulation assays are difficult to perform. Our methods are available in the web-service NetEffects: http://www.ebi.ac.uk/thornton-srv/software/NetEffects.Irene PapatheodorouMatthias ZiehmDaniela WieserNazif AlicLinda PartridgeJanet M ThorntonPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 12, p e50881 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Irene Papatheodorou Matthias Ziehm Daniela Wieser Nazif Alic Linda Partridge Janet M Thornton Using answer set programming to integrate RNA expression with signalling pathway information to infer how mutations affect ageing.
description	A challenge of systems biology is to integrate incomplete knowledge on pathways with existing experimental data sets and relate these to measured phenotypes. Research on ageing often generates such incomplete data, creating difficulties in integrating RNA expression with information about biological processes and the phenotypes of ageing, including longevity. Here, we develop a logic-based method that employs Answer Set Programming, and use it to infer signalling effects of genetic perturbations, based on a model of the insulin signalling pathway. We apply our method to RNA expression data from Drosophila mutants in the insulin pathway that alter lifespan, in a foxo dependent fashion. We use this information to deduce how the pathway influences lifespan in the mutant animals. We also develop a method for inferring the largest common sub-paths within each of our signalling predictions. Our comparisons reveal consistent homeostatic mechanisms across both long- and short-lived mutants. The transcriptional changes observed in each mutation usually provide negative feedback to signalling predicted for that mutation. We also identify an S6K-mediated feedback in two long-lived mutants that suggests a crosstalk between these pathways in mutants of the insulin pathway, in vivo. By formulating the problem as a logic-based theory in a qualitative fashion, we are able to use the efficient search facilities of Answer Set Programming, allowing us to explore larger pathways, combine molecular changes with pathways and phenotype and infer effects on signalling in in vivo, whole-organism, mutants, where direct signalling stimulation assays are difficult to perform. Our methods are available in the web-service NetEffects: http://www.ebi.ac.uk/thornton-srv/software/NetEffects.
format	article
author	Irene Papatheodorou Matthias Ziehm Daniela Wieser Nazif Alic Linda Partridge Janet M Thornton
author_facet	Irene Papatheodorou Matthias Ziehm Daniela Wieser Nazif Alic Linda Partridge Janet M Thornton
author_sort	Irene Papatheodorou
title	Using answer set programming to integrate RNA expression with signalling pathway information to infer how mutations affect ageing.
title_short	Using answer set programming to integrate RNA expression with signalling pathway information to infer how mutations affect ageing.
title_full	Using answer set programming to integrate RNA expression with signalling pathway information to infer how mutations affect ageing.
title_fullStr	Using answer set programming to integrate RNA expression with signalling pathway information to infer how mutations affect ageing.
title_full_unstemmed	Using answer set programming to integrate RNA expression with signalling pathway information to infer how mutations affect ageing.
title_sort	using answer set programming to integrate rna expression with signalling pathway information to infer how mutations affect ageing.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/d33dc7059f154716bc11f6c07d81d475
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Using answer set programming to integrate RNA expression with signalling pathway information to infer how mutations affect ageing.

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