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

Overview of attention for article published in BMC Genomics, September 2016
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Title
The green ash transcriptome and identification of genes responding to abiotic and biotic stresses
Published in
BMC Genomics, September 2016
DOI 10.1186/s12864-016-3052-0
Pubmed ID
Authors

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

Abstract

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. 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. 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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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Unknown 59 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 22%
Researcher 12 20%
Student > Bachelor 5 8%
Student > Postgraduate 5 8%
Student > Master 4 7%
Other 7 12%
Unknown 14 23%
Readers by discipline Count As %
Agricultural and Biological Sciences 24 40%
Biochemistry, Genetics and Molecular Biology 8 13%
Environmental Science 5 8%
Psychology 2 3%
Social Sciences 2 3%
Other 5 8%
Unknown 14 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 December 2018.
All research outputs
#12,769,362
of 22,886,568 outputs
Outputs from BMC Genomics
#4,411
of 10,668 outputs
Outputs of similar age
#167,621
of 337,011 outputs
Outputs of similar age from BMC Genomics
#93
of 285 outputs
Altmetric has tracked 22,886,568 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,668 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 57% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 337,011 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 285 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.