Cargando…

Decomposition of Gene Expression State Space Trajectories

Representing and analyzing complex networks remains a roadblock to creating dynamic network models of biological processes and pathways. The study of cell fate transitions can reveal much about the transcriptional regulatory programs that underlie these phenotypic changes and give rise to the coordi...

Descripción completa

Detalles Bibliográficos
Autores principales: Mar, Jessica C., Quackenbush, John
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2791157/
https://www.ncbi.nlm.nih.gov/pubmed/20041215
http://dx.doi.org/10.1371/journal.pcbi.1000626
_version_ 1782175164199337984
author Mar, Jessica C.
Quackenbush, John
author_facet Mar, Jessica C.
Quackenbush, John
author_sort Mar, Jessica C.
collection PubMed
description Representing and analyzing complex networks remains a roadblock to creating dynamic network models of biological processes and pathways. The study of cell fate transitions can reveal much about the transcriptional regulatory programs that underlie these phenotypic changes and give rise to the coordinated patterns in expression changes that we observe. The application of gene expression state space trajectories to capture cell fate transitions at the genome-wide level is one approach currently used in the literature. In this paper, we analyze the gene expression dataset of Huang et al. (2005) which follows the differentiation of promyelocytes into neutrophil-like cells in the presence of inducers dimethyl sulfoxide and all-trans retinoic acid. Huang et al. (2005) build on the work of Kauffman (2004) who raised the attractor hypothesis, stating that cells exist in an expression landscape and their expression trajectories converge towards attractive sites in this landscape. We propose an alternative interpretation that explains this convergent behavior by recognizing that there are two types of processes participating in these cell fate transitions—core processes that include the specific differentiation pathways of promyelocytes to neutrophils, and transient processes that capture those pathways and responses specific to the inducer. Using functional enrichment analyses, specific biological examples and an analysis of the trajectories and their core and transient components we provide a validation of our hypothesis using the Huang et al. (2005) dataset.
format Text
id pubmed-2791157
institution National Center for Biotechnology Information
language English
publishDate 2009
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-27911572009-12-30 Decomposition of Gene Expression State Space Trajectories Mar, Jessica C. Quackenbush, John PLoS Comput Biol Research Article Representing and analyzing complex networks remains a roadblock to creating dynamic network models of biological processes and pathways. The study of cell fate transitions can reveal much about the transcriptional regulatory programs that underlie these phenotypic changes and give rise to the coordinated patterns in expression changes that we observe. The application of gene expression state space trajectories to capture cell fate transitions at the genome-wide level is one approach currently used in the literature. In this paper, we analyze the gene expression dataset of Huang et al. (2005) which follows the differentiation of promyelocytes into neutrophil-like cells in the presence of inducers dimethyl sulfoxide and all-trans retinoic acid. Huang et al. (2005) build on the work of Kauffman (2004) who raised the attractor hypothesis, stating that cells exist in an expression landscape and their expression trajectories converge towards attractive sites in this landscape. We propose an alternative interpretation that explains this convergent behavior by recognizing that there are two types of processes participating in these cell fate transitions—core processes that include the specific differentiation pathways of promyelocytes to neutrophils, and transient processes that capture those pathways and responses specific to the inducer. Using functional enrichment analyses, specific biological examples and an analysis of the trajectories and their core and transient components we provide a validation of our hypothesis using the Huang et al. (2005) dataset. Public Library of Science 2009-12-24 /pmc/articles/PMC2791157/ /pubmed/20041215 http://dx.doi.org/10.1371/journal.pcbi.1000626 Text en Mar, Quackenbush. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Mar, Jessica C.
Quackenbush, John
Decomposition of Gene Expression State Space Trajectories
title Decomposition of Gene Expression State Space Trajectories
title_full Decomposition of Gene Expression State Space Trajectories
title_fullStr Decomposition of Gene Expression State Space Trajectories
title_full_unstemmed Decomposition of Gene Expression State Space Trajectories
title_short Decomposition of Gene Expression State Space Trajectories
title_sort decomposition of gene expression state space trajectories
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2791157/
https://www.ncbi.nlm.nih.gov/pubmed/20041215
http://dx.doi.org/10.1371/journal.pcbi.1000626
work_keys_str_mv AT marjessicac decompositionofgeneexpressionstatespacetrajectories
AT quackenbushjohn decompositionofgeneexpressionstatespacetrajectories