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The green ash transcriptome and identification of genes responding to abiotic and biotic stresses
BACKGROUND: To develop a set of transcriptome sequences to support research on environmental stress responses in green ash (Fraxinus pennsylvanica), we undertook deep RNA sequencing of green ash tissues under various stress treatments. The treatments, including emerald ash borer (EAB) feeding, heat,...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5009568/ https://www.ncbi.nlm.nih.gov/pubmed/27589953 http://dx.doi.org/10.1186/s12864-016-3052-0 |
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author | Lane, Thomas Best, Teodora Zembower, Nicole Davitt, Jack Henry, Nathan Xu, Yi Koch, Jennifer Liang, Haiying McGraw, John Schuster, Stephan Shim, Donghwan Coggeshall, Mark V. Carlson, John E. Staton, Margaret E. |
author_facet | Lane, Thomas Best, Teodora Zembower, Nicole Davitt, Jack Henry, Nathan Xu, Yi Koch, Jennifer Liang, Haiying McGraw, John Schuster, Stephan Shim, Donghwan Coggeshall, Mark V. Carlson, John E. Staton, Margaret E. |
author_sort | Lane, Thomas |
collection | PubMed |
description | BACKGROUND: To develop a set of transcriptome sequences to support research on environmental stress responses in green ash (Fraxinus pennsylvanica), we undertook deep RNA sequencing of green ash tissues under various stress treatments. The treatments, including emerald ash borer (EAB) feeding, heat, drought, cold and ozone, were selected to mimic the increasing threats of climate change and invasive pests faced by green ash across its native habitat. RESULTS: We report the generation and assembly of RNA sequences from 55 green ash samples into 107,611 putative unique transcripts (PUTs). 52,899 open reading frames were identified. Functional annotation of the PUTs by comparison to the Uniprot protein database identified matches for 63 % of transcripts and for 98 % of transcripts with ORFs. Further functional annotation identified conserved protein domains and assigned gene ontology terms to the PUTs. Examination of transcript expression across different RNA libraries revealed that expression patterns clustered based on tissues regardless of stress treatment. The transcripts from stress treatments were further examined to identify differential expression. Tens to hundreds of differentially expressed PUTs were identified for each stress treatment. A set of 109 PUTs were found to be consistently up or down regulated across three or more different stress treatments, representing basal stress response candidate genes in green ash. In addition, 1956 simple sequence repeats were identified in the PUTs, of which we identified 465 high quality DNA markers and designed flanking PCR primers. CONCLUSIONS: North American native ash trees have suffered extensive mortality due to EAB infestation, creating a need to breed or select for resistant green ash genotypes. Stress from climate change is an additional concern for longevity of native ash populations. The use of genomics could accelerate management efforts. The green ash transcriptome we have developed provides important sequence information, genetic markers and stress-response candidate genes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-3052-0) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5009568 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-50095682016-09-03 The green ash transcriptome and identification of genes responding to abiotic and biotic stresses Lane, Thomas Best, Teodora Zembower, Nicole Davitt, Jack Henry, Nathan Xu, Yi Koch, Jennifer Liang, Haiying McGraw, John Schuster, Stephan Shim, Donghwan Coggeshall, Mark V. Carlson, John E. Staton, Margaret E. BMC Genomics Research Article BACKGROUND: To develop a set of transcriptome sequences to support research on environmental stress responses in green ash (Fraxinus pennsylvanica), we undertook deep RNA sequencing of green ash tissues under various stress treatments. The treatments, including emerald ash borer (EAB) feeding, heat, drought, cold and ozone, were selected to mimic the increasing threats of climate change and invasive pests faced by green ash across its native habitat. RESULTS: We report the generation and assembly of RNA sequences from 55 green ash samples into 107,611 putative unique transcripts (PUTs). 52,899 open reading frames were identified. Functional annotation of the PUTs by comparison to the Uniprot protein database identified matches for 63 % of transcripts and for 98 % of transcripts with ORFs. Further functional annotation identified conserved protein domains and assigned gene ontology terms to the PUTs. Examination of transcript expression across different RNA libraries revealed that expression patterns clustered based on tissues regardless of stress treatment. The transcripts from stress treatments were further examined to identify differential expression. Tens to hundreds of differentially expressed PUTs were identified for each stress treatment. A set of 109 PUTs were found to be consistently up or down regulated across three or more different stress treatments, representing basal stress response candidate genes in green ash. In addition, 1956 simple sequence repeats were identified in the PUTs, of which we identified 465 high quality DNA markers and designed flanking PCR primers. CONCLUSIONS: North American native ash trees have suffered extensive mortality due to EAB infestation, creating a need to breed or select for resistant green ash genotypes. Stress from climate change is an additional concern for longevity of native ash populations. The use of genomics could accelerate management efforts. The green ash transcriptome we have developed provides important sequence information, genetic markers and stress-response candidate genes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-3052-0) contains supplementary material, which is available to authorized users. BioMed Central 2016-09-02 /pmc/articles/PMC5009568/ /pubmed/27589953 http://dx.doi.org/10.1186/s12864-016-3052-0 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 Article Lane, Thomas Best, Teodora Zembower, Nicole Davitt, Jack Henry, Nathan Xu, Yi Koch, Jennifer Liang, Haiying McGraw, John Schuster, Stephan Shim, Donghwan Coggeshall, Mark V. Carlson, John E. Staton, Margaret E. The green ash transcriptome and identification of genes responding to abiotic and biotic stresses |
title | The green ash transcriptome and identification of genes responding to abiotic and biotic stresses |
title_full | The green ash transcriptome and identification of genes responding to abiotic and biotic stresses |
title_fullStr | The green ash transcriptome and identification of genes responding to abiotic and biotic stresses |
title_full_unstemmed | The green ash transcriptome and identification of genes responding to abiotic and biotic stresses |
title_short | The green ash transcriptome and identification of genes responding to abiotic and biotic stresses |
title_sort | green ash transcriptome and identification of genes responding to abiotic and biotic stresses |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5009568/ https://www.ncbi.nlm.nih.gov/pubmed/27589953 http://dx.doi.org/10.1186/s12864-016-3052-0 |
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