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The green ash transcriptome and identification of genes responding to abiotic and biotic stresses

Posted on 2016-09-02 - 05:00
Abstract 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.

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BMC Genomics

AUTHORS (14)

Thomas Lane
Teodora Best
Nicole Zembower
Jack Davitt
Nathan Henry
Yi Xu
Jennifer Koch
Haiying Liang
John McGraw
Stephan Schuster
Donghwan Shim
Mark Coggeshall
John Carlson
Margaret Staton
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