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The Wheat GENIE3 Network Provides Biologically-Relevant Information in Polyploid Wheat

Gene regulatory networks are powerful tools which facilitate hypothesis generation and candidate gene discovery. However, the extent to which the network predictions are biologically relevant is often unclear. Recently a GENIE3 network which predicted targets of wheat transcription factors was produ...

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Detalles Bibliográficos
Autores principales: Harrington, Sophie A., Backhaus, Anna E., Singh, Ajit, Hassani-Pak, Keywan, Uauy, Cristobal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Genetics Society of America 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7534433/
https://www.ncbi.nlm.nih.gov/pubmed/32747342
http://dx.doi.org/10.1534/g3.120.401436
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author Harrington, Sophie A.
Backhaus, Anna E.
Singh, Ajit
Hassani-Pak, Keywan
Uauy, Cristobal
author_facet Harrington, Sophie A.
Backhaus, Anna E.
Singh, Ajit
Hassani-Pak, Keywan
Uauy, Cristobal
author_sort Harrington, Sophie A.
collection PubMed
description Gene regulatory networks are powerful tools which facilitate hypothesis generation and candidate gene discovery. However, the extent to which the network predictions are biologically relevant is often unclear. Recently a GENIE3 network which predicted targets of wheat transcription factors was produced. Here we used an independent RNA-Seq dataset to test the predictions of the wheat GENIE3 network for the senescence-regulating transcription factor NAM-A1 (TraesCS6A02G108300). We re-analyzed the RNA-Seq data against the RefSeqv1.0 genome and identified a set of differentially expressed genes (DEGs) between the wild-type and nam-a1 mutant which recapitulated the known role of NAM-A1 in senescence and nutrient remobilisation. We found that the GENIE3-predicted target genes of NAM-A1 overlap significantly with the DEGs, more than would be expected by chance. Based on high levels of overlap between GENIE3-predicted target genes and the DEGs, we identified candidate senescence regulators. We then explored genome-wide trends in the network related to polyploidy and found that only homeologous transcription factors are likely to share predicted targets in common. However, homeologs which vary in expression levels across tissues are less likely to share predicted targets than those that do not, suggesting that they may be more likely to act in distinct pathways. This work demonstrates that the wheat GENIE3 network can provide biologically-relevant predictions of transcription factor targets, which can be used for candidate gene prediction and for global analyses of transcription factor function. The GENIE3 network has now been integrated into the KnetMiner web application, facilitating its use in future studies.
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spelling pubmed-75344332020-10-13 The Wheat GENIE3 Network Provides Biologically-Relevant Information in Polyploid Wheat Harrington, Sophie A. Backhaus, Anna E. Singh, Ajit Hassani-Pak, Keywan Uauy, Cristobal G3 (Bethesda) Investigations Gene regulatory networks are powerful tools which facilitate hypothesis generation and candidate gene discovery. However, the extent to which the network predictions are biologically relevant is often unclear. Recently a GENIE3 network which predicted targets of wheat transcription factors was produced. Here we used an independent RNA-Seq dataset to test the predictions of the wheat GENIE3 network for the senescence-regulating transcription factor NAM-A1 (TraesCS6A02G108300). We re-analyzed the RNA-Seq data against the RefSeqv1.0 genome and identified a set of differentially expressed genes (DEGs) between the wild-type and nam-a1 mutant which recapitulated the known role of NAM-A1 in senescence and nutrient remobilisation. We found that the GENIE3-predicted target genes of NAM-A1 overlap significantly with the DEGs, more than would be expected by chance. Based on high levels of overlap between GENIE3-predicted target genes and the DEGs, we identified candidate senescence regulators. We then explored genome-wide trends in the network related to polyploidy and found that only homeologous transcription factors are likely to share predicted targets in common. However, homeologs which vary in expression levels across tissues are less likely to share predicted targets than those that do not, suggesting that they may be more likely to act in distinct pathways. This work demonstrates that the wheat GENIE3 network can provide biologically-relevant predictions of transcription factor targets, which can be used for candidate gene prediction and for global analyses of transcription factor function. The GENIE3 network has now been integrated into the KnetMiner web application, facilitating its use in future studies. Genetics Society of America 2020-08-03 /pmc/articles/PMC7534433/ /pubmed/32747342 http://dx.doi.org/10.1534/g3.120.401436 Text en Copyright © 2020 Harrington et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Investigations
Harrington, Sophie A.
Backhaus, Anna E.
Singh, Ajit
Hassani-Pak, Keywan
Uauy, Cristobal
The Wheat GENIE3 Network Provides Biologically-Relevant Information in Polyploid Wheat
title The Wheat GENIE3 Network Provides Biologically-Relevant Information in Polyploid Wheat
title_full The Wheat GENIE3 Network Provides Biologically-Relevant Information in Polyploid Wheat
title_fullStr The Wheat GENIE3 Network Provides Biologically-Relevant Information in Polyploid Wheat
title_full_unstemmed The Wheat GENIE3 Network Provides Biologically-Relevant Information in Polyploid Wheat
title_short The Wheat GENIE3 Network Provides Biologically-Relevant Information in Polyploid Wheat
title_sort wheat genie3 network provides biologically-relevant information in polyploid wheat
topic Investigations
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7534433/
https://www.ncbi.nlm.nih.gov/pubmed/32747342
http://dx.doi.org/10.1534/g3.120.401436
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