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Gene expression correlated with delay in shell formation in larval Pacific oysters (Crassostrea gigas) exposed to experimental ocean acidification provides insights into shell formation mechanisms

Overview of attention for article published in BMC Genomics, February 2018
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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 (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

blogs
1 blog
twitter
7 tweeters

Citations

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22 Dimensions

Readers on

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69 Mendeley
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Title
Gene expression correlated with delay in shell formation in larval Pacific oysters (Crassostrea gigas) exposed to experimental ocean acidification provides insights into shell formation mechanisms
Published in
BMC Genomics, February 2018
DOI 10.1186/s12864-018-4519-y
Pubmed ID
Authors

Pierre De Wit, Evan Durland, Alexander Ventura, Chris J. Langdon

Abstract

Despite recent work to characterize gene expression changes associated with larval development in oysters, the mechanism by which the larval shell is first formed is still largely unknown. In Crassostrea gigas, this shell forms within the first 24 h post fertilization, and it has been demonstrated that changes in water chemistry can cause delays in shell formation, shell deformations and higher mortality rates. In this study, we use the delay in shell formation associated with exposure to CO2-acidified seawater to identify genes correlated with initial shell deposition. By fitting linear models to gene expression data in ambient and low aragonite saturation treatments, we are able to isolate 37 annotated genes correlated with initial larval shell formation, which can be categorized into 1) ion transporters, 2) shell matrix proteins and 3) protease inhibitors. Clustering of the gene expression data into co-expression networks further supports the result of the linear models, and also implies an important role of dynein motor proteins as transporters of cellular components during the initial shell formation process. Using an RNA-Seq approach with high temporal resolution allows us to identify a conceptual model for how oyster larval calcification is initiated. This work provides a foundation for further studies on how genetic variation in these identified genes could affect fitness of oyster populations subjected to future environmental changes, such as ocean acidification.

Twitter Demographics

The data shown below were collected from the profiles of 7 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 69 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 25%
Researcher 13 19%
Other 7 10%
Student > Bachelor 6 9%
Student > Master 5 7%
Other 6 9%
Unknown 15 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 27 39%
Environmental Science 9 13%
Biochemistry, Genetics and Molecular Biology 8 12%
Earth and Planetary Sciences 3 4%
Immunology and Microbiology 1 1%
Other 1 1%
Unknown 20 29%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 05 September 2018.
All research outputs
#1,361,547
of 13,472,025 outputs
Outputs from BMC Genomics
#636
of 7,900 outputs
Outputs of similar age
#46,169
of 269,583 outputs
Outputs of similar age from BMC Genomics
#1
of 12 outputs
Altmetric has tracked 13,472,025 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,900 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done particularly well, scoring higher than 91% 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 269,583 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 82% of its contemporaries.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.