PhytoNet : comparative co-expression network analyses across phytoplankton and land plants
Phytoplankton consists of autotrophic, photosynthesizing microorganisms that are a crucial component of freshwater and ocean ecosystems. However, despite being the major primary producers of organic compounds, accounting for half of the photosynthetic activity worldwide and serving as the entry poin...
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sg-ntu-dr.10356-881432023-02-28T16:56:35Z PhytoNet : comparative co-expression network analyses across phytoplankton and land plants Ferrari, Camilla Proost, Sebastian Ruprecht, Colin Mutwil, Marek School of Biological Sciences Phytoplankton DRNTU::Science::Biological sciences Co-expression Network Phytoplankton consists of autotrophic, photosynthesizing microorganisms that are a crucial component of freshwater and ocean ecosystems. However, despite being the major primary producers of organic compounds, accounting for half of the photosynthetic activity worldwide and serving as the entry point to the food chain, functions of most of the genes of the model phytoplankton organisms remain unknown. To remedy this, we have gathered publicly available expression data for one chlorophyte, one rhodophyte, one haptophyte, two heterokonts and four cyanobacteria and integrated it into our PlaNet (Plant Networks) database, which now allows mining gene expression profiles and identification of co-expressed genes of 19 species. We exemplify how the co-expressed gene networks can be used to reveal functionally related genes and how the comparative features of PhytoNet allow detection of conserved transcriptional programs between cyanobacteria, green algae, and land plants. Additionally, we illustrate how the database allows detection of duplicated transcriptional programs within an organism, as exemplified by two putative DNA repair programs within Chlamydomonas reinhardtii. PhytoNet is available from www.gene2function.de. Published version 2018-08-23T05:39:01Z 2019-12-06T16:56:59Z 2018-08-23T05:39:01Z 2019-12-06T16:56:59Z 2018 Journal Article Ferrari, C., Proost, S., Ruprecht, C., & Mutwil, M. (2018). PhytoNet: comparative co-expression network analyses across phytoplankton and land plants. Nucleic Acids Research, 46(W1), W76-W83. doi:10.1093/nar/gky298 0305-1048 https://hdl.handle.net/10356/88143 http://hdl.handle.net/10220/45653 10.1093/nar/gky298 en Nucleic Acids Research © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com. 8 p. application/pdf |
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Phytoplankton DRNTU::Science::Biological sciences Co-expression Network Ferrari, Camilla Proost, Sebastian Ruprecht, Colin Mutwil, Marek PhytoNet : comparative co-expression network analyses across phytoplankton and land plants |
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Phytoplankton consists of autotrophic, photosynthesizing microorganisms that are a crucial component of freshwater and ocean ecosystems. However, despite being the major primary producers of organic compounds, accounting for half of the photosynthetic activity worldwide and serving as the entry point to the food chain, functions of most of the genes of the model phytoplankton organisms remain unknown. To remedy this, we have gathered publicly available expression data for one chlorophyte, one rhodophyte, one haptophyte, two heterokonts and four cyanobacteria and integrated it into our PlaNet (Plant Networks) database, which now allows mining gene expression profiles and identification of co-expressed genes of 19 species. We exemplify how the co-expressed gene networks can be used to reveal functionally related genes and how the comparative features of PhytoNet allow detection of conserved transcriptional programs between cyanobacteria, green algae, and land plants. Additionally, we illustrate how the database allows detection of duplicated transcriptional programs within an organism, as exemplified by two putative DNA repair programs within Chlamydomonas reinhardtii. PhytoNet is available from www.gene2function.de. |
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School of Biological Sciences |
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School of Biological Sciences Ferrari, Camilla Proost, Sebastian Ruprecht, Colin Mutwil, Marek |
format |
Article |
author |
Ferrari, Camilla Proost, Sebastian Ruprecht, Colin Mutwil, Marek |
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Ferrari, Camilla |
title |
PhytoNet : comparative co-expression network analyses across phytoplankton and land plants |
title_short |
PhytoNet : comparative co-expression network analyses across phytoplankton and land plants |
title_full |
PhytoNet : comparative co-expression network analyses across phytoplankton and land plants |
title_fullStr |
PhytoNet : comparative co-expression network analyses across phytoplankton and land plants |
title_full_unstemmed |
PhytoNet : comparative co-expression network analyses across phytoplankton and land plants |
title_sort |
phytonet : comparative co-expression network analyses across phytoplankton and land plants |
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2018 |
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https://hdl.handle.net/10356/88143 http://hdl.handle.net/10220/45653 |
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