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Network Theory Inspired Analysis of Time-Resolved Expression Data Reveals Key Players Guiding P. patens Stem Cell Development
Transcription factors (TFs) often trigger developmental decisions, yet, their transcripts are often only moderately regulated and thus not easily detected by conventional statistics on expression data. Here we present a method that allows to determine such genes based on trajectory analysis of time-...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3630159/ https://www.ncbi.nlm.nih.gov/pubmed/23637751 http://dx.doi.org/10.1371/journal.pone.0060494 |
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author | Busch, Hauke Boerries, Melanie Bao, Jie Hanke, Sebastian T. Hiss, Manuel Tiko, Theodhor Rensing, Stefan A. |
author_facet | Busch, Hauke Boerries, Melanie Bao, Jie Hanke, Sebastian T. Hiss, Manuel Tiko, Theodhor Rensing, Stefan A. |
author_sort | Busch, Hauke |
collection | PubMed |
description | Transcription factors (TFs) often trigger developmental decisions, yet, their transcripts are often only moderately regulated and thus not easily detected by conventional statistics on expression data. Here we present a method that allows to determine such genes based on trajectory analysis of time-resolved transcriptome data. As a proof of principle, we have analysed apical stem cells of filamentous moss (P. patens) protonemata that develop from leaflets upon their detachment from the plant. By our novel correlation analysis of the post detachment transcriptome kinetics we predict five out of 1,058 TFs to be involved in the signaling leading to the establishment of pluripotency. Among the predicted regulators is the basic helix loop helix TF PpRSL1, which we show to be involved in the establishment of apical stem cells in P. patens. Our methodology is expected to aid analysis of key players of developmental decisions in complex plant and animal systems. |
format | Online Article Text |
id | pubmed-3630159 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-36301592013-05-01 Network Theory Inspired Analysis of Time-Resolved Expression Data Reveals Key Players Guiding P. patens Stem Cell Development Busch, Hauke Boerries, Melanie Bao, Jie Hanke, Sebastian T. Hiss, Manuel Tiko, Theodhor Rensing, Stefan A. PLoS One Research Article Transcription factors (TFs) often trigger developmental decisions, yet, their transcripts are often only moderately regulated and thus not easily detected by conventional statistics on expression data. Here we present a method that allows to determine such genes based on trajectory analysis of time-resolved transcriptome data. As a proof of principle, we have analysed apical stem cells of filamentous moss (P. patens) protonemata that develop from leaflets upon their detachment from the plant. By our novel correlation analysis of the post detachment transcriptome kinetics we predict five out of 1,058 TFs to be involved in the signaling leading to the establishment of pluripotency. Among the predicted regulators is the basic helix loop helix TF PpRSL1, which we show to be involved in the establishment of apical stem cells in P. patens. Our methodology is expected to aid analysis of key players of developmental decisions in complex plant and animal systems. Public Library of Science 2013-04-18 /pmc/articles/PMC3630159/ /pubmed/23637751 http://dx.doi.org/10.1371/journal.pone.0060494 Text en © 2013 Busch 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 Busch, Hauke Boerries, Melanie Bao, Jie Hanke, Sebastian T. Hiss, Manuel Tiko, Theodhor Rensing, Stefan A. Network Theory Inspired Analysis of Time-Resolved Expression Data Reveals Key Players Guiding P. patens Stem Cell Development |
title | Network Theory Inspired Analysis of Time-Resolved Expression Data Reveals Key Players Guiding P. patens Stem Cell Development |
title_full | Network Theory Inspired Analysis of Time-Resolved Expression Data Reveals Key Players Guiding P. patens Stem Cell Development |
title_fullStr | Network Theory Inspired Analysis of Time-Resolved Expression Data Reveals Key Players Guiding P. patens Stem Cell Development |
title_full_unstemmed | Network Theory Inspired Analysis of Time-Resolved Expression Data Reveals Key Players Guiding P. patens Stem Cell Development |
title_short | Network Theory Inspired Analysis of Time-Resolved Expression Data Reveals Key Players Guiding P. patens Stem Cell Development |
title_sort | network theory inspired analysis of time-resolved expression data reveals key players guiding p. patens stem cell development |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3630159/ https://www.ncbi.nlm.nih.gov/pubmed/23637751 http://dx.doi.org/10.1371/journal.pone.0060494 |
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