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Computational Integration of Homolog and Pathway Gene Module Expression Reveals General Stemness Signatures
The stemness hypothesis states that all stem cells use common mechanisms to regulate self-renewal and multi-lineage potential. However, gene expression meta-analyses at the single gene level have failed to identify a significant number of genes selectively expressed by a broad range of stem cell typ...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2011
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3084730/ https://www.ncbi.nlm.nih.gov/pubmed/21559491 http://dx.doi.org/10.1371/journal.pone.0018968 |
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author | Koeva, Martina Forsberg, E. Camilla Stuart, Joshua M. |
author_facet | Koeva, Martina Forsberg, E. Camilla Stuart, Joshua M. |
author_sort | Koeva, Martina |
collection | PubMed |
description | The stemness hypothesis states that all stem cells use common mechanisms to regulate self-renewal and multi-lineage potential. However, gene expression meta-analyses at the single gene level have failed to identify a significant number of genes selectively expressed by a broad range of stem cell types. We hypothesized that stemness may be regulated by modules of homologs. While the expression of any single gene within a module may vary from one stem cell type to the next, it is possible that the expression of the module as a whole is required so that the expression of different, yet functionally-synonymous, homologs is needed in different stem cells. Thus, we developed a computational method to test for stem cell-specific gene expression patterns from a comprehensive collection of 49 murine datasets covering 12 different stem cell types. We identified 40 individual genes and 224 stemness modules with reproducible and specific up-regulation across multiple stem cell types. The stemness modules included families regulating chromatin remodeling, DNA repair, and Wnt signaling. Strikingly, the majority of modules represent evolutionarily related homologs. Moreover, a score based on the discovered modules could accurately distinguish stem cell-like populations from other cell types in both normal and cancer tissues. This scoring system revealed that both mouse and human metastatic populations exhibit higher stemness indices than non-metastatic populations, providing further evidence for a stem cell-driven component underlying the transformation to metastatic disease. |
format | Text |
id | pubmed-3084730 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-30847302011-05-10 Computational Integration of Homolog and Pathway Gene Module Expression Reveals General Stemness Signatures Koeva, Martina Forsberg, E. Camilla Stuart, Joshua M. PLoS One Research Article The stemness hypothesis states that all stem cells use common mechanisms to regulate self-renewal and multi-lineage potential. However, gene expression meta-analyses at the single gene level have failed to identify a significant number of genes selectively expressed by a broad range of stem cell types. We hypothesized that stemness may be regulated by modules of homologs. While the expression of any single gene within a module may vary from one stem cell type to the next, it is possible that the expression of the module as a whole is required so that the expression of different, yet functionally-synonymous, homologs is needed in different stem cells. Thus, we developed a computational method to test for stem cell-specific gene expression patterns from a comprehensive collection of 49 murine datasets covering 12 different stem cell types. We identified 40 individual genes and 224 stemness modules with reproducible and specific up-regulation across multiple stem cell types. The stemness modules included families regulating chromatin remodeling, DNA repair, and Wnt signaling. Strikingly, the majority of modules represent evolutionarily related homologs. Moreover, a score based on the discovered modules could accurately distinguish stem cell-like populations from other cell types in both normal and cancer tissues. This scoring system revealed that both mouse and human metastatic populations exhibit higher stemness indices than non-metastatic populations, providing further evidence for a stem cell-driven component underlying the transformation to metastatic disease. Public Library of Science 2011-04-29 /pmc/articles/PMC3084730/ /pubmed/21559491 http://dx.doi.org/10.1371/journal.pone.0018968 Text en Koeva et al. 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 Koeva, Martina Forsberg, E. Camilla Stuart, Joshua M. Computational Integration of Homolog and Pathway Gene Module Expression Reveals General Stemness Signatures |
title | Computational Integration of Homolog and Pathway Gene Module Expression Reveals General Stemness Signatures |
title_full | Computational Integration of Homolog and Pathway Gene Module Expression Reveals General Stemness Signatures |
title_fullStr | Computational Integration of Homolog and Pathway Gene Module Expression Reveals General Stemness Signatures |
title_full_unstemmed | Computational Integration of Homolog and Pathway Gene Module Expression Reveals General Stemness Signatures |
title_short | Computational Integration of Homolog and Pathway Gene Module Expression Reveals General Stemness Signatures |
title_sort | computational integration of homolog and pathway gene module expression reveals general stemness signatures |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3084730/ https://www.ncbi.nlm.nih.gov/pubmed/21559491 http://dx.doi.org/10.1371/journal.pone.0018968 |
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