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Network-based bioinformatics analysis of spatio-temporal RNA-Seq data reveals transcriptional programs underpinning normal and aberrant retinal development

BACKGROUND: The retina as a model system with extensive information on genes involved in development/maintenance is of great value for investigations employing deep sequencing to capture transcriptome change over time. This in turn could enable us to find patterns in gene expression across time to r...

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Autores principales: Karunakaran, Devi Krishna Priya, Al Seesi, Sahar, Banday, Abdul Rouf, Baumgartner, Marybeth, Olthof, Anouk, Lemoine, Christopher, Măndoiu, Ion I., Kanadia, Rahul N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5009874/
https://www.ncbi.nlm.nih.gov/pubmed/27586787
http://dx.doi.org/10.1186/s12864-016-2822-z
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author Karunakaran, Devi Krishna Priya
Al Seesi, Sahar
Banday, Abdul Rouf
Baumgartner, Marybeth
Olthof, Anouk
Lemoine, Christopher
Măndoiu, Ion I.
Kanadia, Rahul N.
author_facet Karunakaran, Devi Krishna Priya
Al Seesi, Sahar
Banday, Abdul Rouf
Baumgartner, Marybeth
Olthof, Anouk
Lemoine, Christopher
Măndoiu, Ion I.
Kanadia, Rahul N.
author_sort Karunakaran, Devi Krishna Priya
collection PubMed
description BACKGROUND: The retina as a model system with extensive information on genes involved in development/maintenance is of great value for investigations employing deep sequencing to capture transcriptome change over time. This in turn could enable us to find patterns in gene expression across time to reveal transition in biological processes. METHODS: We developed a bioinformatics pipeline to categorize genes based on their differential expression and their alternative splicing status across time by binning genes based on their transcriptional kinetics. Genes within same bins were then leveraged to query gene annotation databases to discover molecular programs employed by the developing retina. RESULTS: Using our pipeline on RNA-Seq data obtained from fractionated (nucleus/cytoplasm) developing retina at embryonic day (E) 16 and postnatal day (P) 0, we captured high-resolution as in the difference between the cytoplasm and the nucleus at the same developmental time. We found de novo transcription of genes whose transcripts were exclusively found in the nuclear transcriptome at P0. Further analysis showed that these genes enriched for functions that are known to be executed during postnatal development, thus showing that the P0 nuclear transcriptome is temporally ahead of that of its cytoplasm. We extended our strategy to perform temporal analysis comparing P0 data to either P21-Nrl-wildtype (WT) or P21-Nrl-knockout (KO) retinae, which predicted that the KO retina would have compromised vasculature. Indeed, histological manifestation of vasodilation has been reported at a later time point (P60). CONCLUSIONS: Thus, our approach was predictive of a phenotype before it presented histologically. Our strategy can be extended to investigating the development and/or disease progression of other tissue types. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-2822-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-50098742016-09-09 Network-based bioinformatics analysis of spatio-temporal RNA-Seq data reveals transcriptional programs underpinning normal and aberrant retinal development Karunakaran, Devi Krishna Priya Al Seesi, Sahar Banday, Abdul Rouf Baumgartner, Marybeth Olthof, Anouk Lemoine, Christopher Măndoiu, Ion I. Kanadia, Rahul N. BMC Genomics Research BACKGROUND: The retina as a model system with extensive information on genes involved in development/maintenance is of great value for investigations employing deep sequencing to capture transcriptome change over time. This in turn could enable us to find patterns in gene expression across time to reveal transition in biological processes. METHODS: We developed a bioinformatics pipeline to categorize genes based on their differential expression and their alternative splicing status across time by binning genes based on their transcriptional kinetics. Genes within same bins were then leveraged to query gene annotation databases to discover molecular programs employed by the developing retina. RESULTS: Using our pipeline on RNA-Seq data obtained from fractionated (nucleus/cytoplasm) developing retina at embryonic day (E) 16 and postnatal day (P) 0, we captured high-resolution as in the difference between the cytoplasm and the nucleus at the same developmental time. We found de novo transcription of genes whose transcripts were exclusively found in the nuclear transcriptome at P0. Further analysis showed that these genes enriched for functions that are known to be executed during postnatal development, thus showing that the P0 nuclear transcriptome is temporally ahead of that of its cytoplasm. We extended our strategy to perform temporal analysis comparing P0 data to either P21-Nrl-wildtype (WT) or P21-Nrl-knockout (KO) retinae, which predicted that the KO retina would have compromised vasculature. Indeed, histological manifestation of vasodilation has been reported at a later time point (P60). CONCLUSIONS: Thus, our approach was predictive of a phenotype before it presented histologically. Our strategy can be extended to investigating the development and/or disease progression of other tissue types. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-2822-z) contains supplementary material, which is available to authorized users. BioMed Central 2016-08-31 /pmc/articles/PMC5009874/ /pubmed/27586787 http://dx.doi.org/10.1186/s12864-016-2822-z Text en © The Author(s). 2016 Open AccessThis article is 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 you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Karunakaran, Devi Krishna Priya
Al Seesi, Sahar
Banday, Abdul Rouf
Baumgartner, Marybeth
Olthof, Anouk
Lemoine, Christopher
Măndoiu, Ion I.
Kanadia, Rahul N.
Network-based bioinformatics analysis of spatio-temporal RNA-Seq data reveals transcriptional programs underpinning normal and aberrant retinal development
title Network-based bioinformatics analysis of spatio-temporal RNA-Seq data reveals transcriptional programs underpinning normal and aberrant retinal development
title_full Network-based bioinformatics analysis of spatio-temporal RNA-Seq data reveals transcriptional programs underpinning normal and aberrant retinal development
title_fullStr Network-based bioinformatics analysis of spatio-temporal RNA-Seq data reveals transcriptional programs underpinning normal and aberrant retinal development
title_full_unstemmed Network-based bioinformatics analysis of spatio-temporal RNA-Seq data reveals transcriptional programs underpinning normal and aberrant retinal development
title_short Network-based bioinformatics analysis of spatio-temporal RNA-Seq data reveals transcriptional programs underpinning normal and aberrant retinal development
title_sort network-based bioinformatics analysis of spatio-temporal rna-seq data reveals transcriptional programs underpinning normal and aberrant retinal development
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5009874/
https://www.ncbi.nlm.nih.gov/pubmed/27586787
http://dx.doi.org/10.1186/s12864-016-2822-z
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