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Comparative transcriptomics enlarges the toolkit of known developmental genes in mollusks

Overview of attention for article published in BMC Genomics, November 2016
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  • 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 (88th percentile)

Mentioned by

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18 tweeters
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1 Facebook page

Citations

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15 Dimensions

Readers on

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53 Mendeley
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2 CiteULike
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Title
Comparative transcriptomics enlarges the toolkit of known developmental genes in mollusks
Published in
BMC Genomics, November 2016
DOI 10.1186/s12864-016-3080-9
Pubmed ID
Authors

A. L. De Oliveira, T. Wollesen, A. Kristof, M. Scherholz, E. Redl, C. Todt, C. Bleidorn, A. Wanninger

Abstract

Mollusks display a striking morphological disparity, including, among others, worm-like animals (the aplacophorans), snails and slugs, bivalves, and cephalopods. This phenotypic diversity renders them ideal for studies into animal evolution. Despite being one of the most species-rich phyla, molecular and in silico studies concerning specific key developmental gene families are still scarce, thus hampering deeper insights into the molecular machinery that governs the development and evolution of the various molluscan class-level taxa. Next-generation sequencing was used to retrieve transcriptomes of representatives of seven out of the eight recent class-level taxa of mollusks. Similarity searches, phylogenetic inferences, and a detailed manual curation were used to identify and confirm the orthology of numerous molluscan Hox and ParaHox genes, which resulted in a comprehensive catalog that highlights the evolution of these genes in Mollusca and other metazoans. The identification of a specific molluscan motif in the Hox paralog group 5 and a lophotrochozoan ParaHox motif in the Gsx gene is described. Functional analyses using KEGG and GO tools enabled a detailed description of key developmental genes expressed in important pathways such as Hedgehog, Wnt, and Notch during development of the respective species. The KEGG analysis revealed Wnt8, Wnt11, and Wnt16 as Wnt genes hitherto not reported for mollusks, thereby enlarging the known Wnt complement of the phylum. In addition, novel Hedgehog (Hh)-related genes were identified in the gastropod Lottia cf. kogamogai, demonstrating a more complex gene content in this species than in other mollusks. The use of de novo transcriptome assembly and well-designed in silico protocols proved to be a robust approach for surveying and mining large sequence data in a wide range of non-model mollusks. The data presented herein constitute only a small fraction of the information retrieved from the analysed molluscan transcriptomes, which can be promptly employed in the identification of novel genes and gene families, phylogenetic inferences, and other studies using molecular tools. As such, our study provides an important framework for understanding some of the underlying molecular mechanisms involved in molluscan body plan diversification and hints towards functions of key developmental genes in molluscan morphogenesis.

Twitter Demographics

The data shown below were collected from the profiles of 18 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 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
France 1 2%
Unknown 51 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 26%
Researcher 11 21%
Student > Master 9 17%
Student > Doctoral Student 3 6%
Professor > Associate Professor 3 6%
Other 6 11%
Unknown 7 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 32 60%
Biochemistry, Genetics and Molecular Biology 10 19%
Neuroscience 3 6%
Social Sciences 1 2%
Unknown 7 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 18 November 2016.
All research outputs
#1,627,824
of 13,854,033 outputs
Outputs from BMC Genomics
#788
of 8,139 outputs
Outputs of similar age
#50,064
of 288,076 outputs
Outputs of similar age from BMC Genomics
#98
of 873 outputs
Altmetric has tracked 13,854,033 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,139 research outputs from this source. They receive a mean Attention Score of 4.2. This one has done particularly well, scoring higher than 90% 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 288,076 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 873 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.