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Deep, multi-stage transcriptome of the schistosomiasis vector Biomphalaria glabrata provides platform for understanding molluscan disease-related pathways

Overview of attention for article published in BMC Infectious Diseases, October 2016
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

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4 X users
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3 Wikipedia pages

Citations

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22 Dimensions

Readers on

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31 Mendeley
Title
Deep, multi-stage transcriptome of the schistosomiasis vector Biomphalaria glabrata provides platform for understanding molluscan disease-related pathways
Published in
BMC Infectious Diseases, October 2016
DOI 10.1186/s12879-016-1944-x
Pubmed ID
Authors

Nathan J Kenny, Marta Truchado-García, Cristina Grande

Abstract

The gastropod mollusc Biomphalaria glabrata is well known as a vector for the tropical disease schistosomiasis, which affects nearly 200 million people worldwide. Despite intensive study, our understanding of the genetic basis of B. glabrata development, growth and disease resistance is constrained by limited genetic resources, constraints for which next-generation sequencing methods provide a ready solution. Illumina sequencing and de novo assembly using the Trinity program was used to generate a high-quality transcriptomic dataset spanning the entirety of in ovo development in schistosomiasis-free B. glabrata. This was subjected to automated (KEGG, BLAST2GO) and manual annotation efforts, allowing insight into the gene complements of this species in a number of contexts. Excellent dataset recovery was observed, with 133,084 contigs produced of mean size 2219.48 bp. 80,952 (60.8 %) returned a BLASTx hit with an E value of less than 10(-3), and 74,492 (55.97 %) were either mapped or assigned a GO identity using the BLAST2GO program. The CEGMA set of core eukaryotic genes was found to be 99.6 % present, indicating exceptional transcriptome completeness. We were able to identify a wealth of disease-pathway related genes within our dataset, including the Wnt, apoptosis and Notch pathways. This provides an invaluable reference point for further work into molluscan development and evolution, for studying the impact of schistosomiasis in this species, and perhaps providing targets for the treatment of this widespread disease. Here we present a deep transcriptome of an embryonic sample of schistosomiasis-free B. glabrata, presenting a comprehensive dataset for comparison to disease-affected specimens and from which conclusions can be drawn about the genetics of this widespread medical model. Furthermore, the dataset provided by this sequencing provides a useful reference point for comparison to other mollusc species, which can be used to better understand the evolution of this commercially, ecologically and medically important phylum.

X Demographics

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The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 6 19%
Student > Master 6 19%
Student > Ph. D. Student 6 19%
Researcher 4 13%
Professor 2 6%
Other 3 10%
Unknown 4 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 26%
Biochemistry, Genetics and Molecular Biology 7 23%
Neuroscience 3 10%
Environmental Science 2 6%
Medicine and Dentistry 2 6%
Other 3 10%
Unknown 6 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 16 December 2022.
All research outputs
#5,814,504
of 23,351,247 outputs
Outputs from BMC Infectious Diseases
#1,747
of 7,814 outputs
Outputs of similar age
#87,137
of 315,313 outputs
Outputs of similar age from BMC Infectious Diseases
#52
of 235 outputs
Altmetric has tracked 23,351,247 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 7,814 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. 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 315,313 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 235 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.