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Differential Gene Expression in the Siphonophore Nanomia bijuga (Cnidaria) Assessed with Multiple Next-Generation Sequencing Workflows

Overview of attention for article published in PLOS ONE, July 2011
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

Mentioned by

blogs
1 blog

Citations

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47 Dimensions

Readers on

mendeley
171 Mendeley
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1 CiteULike
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Title
Differential Gene Expression in the Siphonophore Nanomia bijuga (Cnidaria) Assessed with Multiple Next-Generation Sequencing Workflows
Published in
PLOS ONE, July 2011
DOI 10.1371/journal.pone.0022953
Pubmed ID
Authors

Stefan Siebert, Mark D. Robinson, Sophia C. Tintori, Freya Goetz, Rebecca R. Helm, Stephen A. Smith, Nathan Shaner, Steven H. D. Haddock, Casey W. Dunn

Abstract

We investigated differential gene expression between functionally specialized feeding polyps and swimming medusae in the siphonophore Nanomia bijuga (Cnidaria) with a hybrid long-read/short-read sequencing strategy. We assembled a set of partial gene reference sequences from long-read data (Roche 454), and generated short-read sequences from replicated tissue samples that were mapped to the references to quantify expression. We collected and compared expression data with three short-read expression workflows that differ in sample preparation, sequencing technology, and mapping tools. These workflows were Illumina mRNA-Seq, which generates sequence reads from random locations along each transcript, and two tag-based approaches, SOLiD SAGE and Helicos DGE, which generate reads from particular tag sites. Differences in expression results across workflows were mostly due to the differential impact of missing data in the partial reference sequences. When all 454-derived gene reference sequences were considered, Illumina mRNA-Seq detected more than twice as many differentially expressed (DE) reference sequences as the tag-based workflows. This discrepancy was largely due to missing tag sites in the partial reference that led to false negatives in the tag-based workflows. When only the subset of reference sequences that unambiguously have tag sites was considered, we found broad congruence across workflows, and they all identified a similar set of DE sequences. Our results are promising in several regards for gene expression studies in non-model organisms. First, we demonstrate that a hybrid long-read/short-read sequencing strategy is an effective way to collect gene expression data when an annotated genome sequence is not available. Second, our replicated sampling indicates that expression profiles are highly consistent across field-collected animals in this case. Third, the impacts of partial reference sequences on the ability to detect DE can be mitigated through workflow choice and deeper reference sequencing.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 171 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 4%
Germany 3 2%
Spain 2 1%
Brazil 2 1%
Australia 2 1%
Chile 1 <1%
France 1 <1%
Norway 1 <1%
Netherlands 1 <1%
Other 4 2%
Unknown 147 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 44 26%
Researcher 42 25%
Professor > Associate Professor 15 9%
Student > Master 15 9%
Student > Bachelor 14 8%
Other 29 17%
Unknown 12 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 115 67%
Biochemistry, Genetics and Molecular Biology 17 10%
Environmental Science 10 6%
Sports and Recreations 2 1%
Engineering 2 1%
Other 8 5%
Unknown 17 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 12 December 2013.
All research outputs
#3,263,318
of 22,736,112 outputs
Outputs from PLOS ONE
#42,898
of 194,041 outputs
Outputs of similar age
#16,745
of 119,536 outputs
Outputs of similar age from PLOS ONE
#454
of 2,285 outputs
Altmetric has tracked 22,736,112 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 194,041 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one has done well, scoring higher than 77% 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 119,536 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 2,285 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.