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A comprehensive hybridization model allows whole HERV transcriptome profiling using high density microarray

Overview of attention for article published in BMC Genomics, April 2017
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  • Good Attention Score compared to outputs of the same age (65th percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

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Title
A comprehensive hybridization model allows whole HERV transcriptome profiling using high density microarray
Published in
BMC Genomics, April 2017
DOI 10.1186/s12864-017-3669-7
Pubmed ID
Authors

Jérémie Becker, Philippe Pérot, Valérie Cheynet, Guy Oriol, Nathalie Mugnier, Marine Mommert, Olivier Tabone, Julien Textoris, Jean-Baptiste Veyrieras, François Mallet

Abstract

Human endogenous retroviruses (HERVs) have received much attention for their implications in the etiology of many human diseases and their profound effect on evolution. Notably, recent studies have highlighted associations between HERVs expression and cancers (Yu et al., Int J Mol Med 32, 2013), autoimmunity (Balada et al., Int Rev Immunol 29:351-370, 2010) and neurological (Christensen, J Neuroimmune Pharmacol 5:326-335, 2010) conditions. Their repetitive nature makes their study particularly challenging, where expression studies have largely focused on individual loci (De Parseval et al., J Virol 77:10414-10422, 2003) or general trends within families (Forsman et al., J Virol Methods 129:16-30, 2005; Seifarth et al., J Virol 79:341-352, 2005; Pichon et al., Nucleic Acids Res 34:e46, 2006). To refine our understanding of HERVs activity, we introduce here a new microarray, HERV-V3. This work was made possible by the careful detection and annotation of genomic HERV/MaLR sequences as well as the development of a new hybridization model, allowing the optimization of probe performances and the control of cross-reactions. RESULTS: HERV-V3 offers an almost complete coverage of HERVs and their ancestors (mammalian apparent LTR-retrotransposons, MaLRs) at the locus level along with four other repertoires (active LINE-1 elements, lncRNA, a selection of 1559 human genes and common infectious viruses). We demonstrate that HERV-V3 analytical performances are comparable with commercial Affymetrix arrays, and that for a selection of tissue/pathological specific loci, the patterns of expression measured on HERV-V3 is consistent with those reported in the literature. Given its large HERVs/MaLRs coverage and additional repertoires, HERV-V3 opens the door to multiple applications such as enhancers and alternative promoters identification, biomarkers identification as well as the characterization of genes and HERVs/MaLRs modulation caused by viral infection.

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The data shown below were collected from the profiles of 3 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 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 22%
Student > Bachelor 6 16%
Researcher 6 16%
Student > Master 4 11%
Student > Doctoral Student 2 5%
Other 3 8%
Unknown 8 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 30%
Agricultural and Biological Sciences 6 16%
Immunology and Microbiology 2 5%
Computer Science 2 5%
Engineering 2 5%
Other 6 16%
Unknown 8 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 13 March 2020.
All research outputs
#6,473,847
of 22,963,381 outputs
Outputs from BMC Genomics
#2,899
of 10,686 outputs
Outputs of similar age
#104,766
of 309,848 outputs
Outputs of similar age from BMC Genomics
#57
of 188 outputs
Altmetric has tracked 22,963,381 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 10,686 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 71% 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 309,848 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 65% of its contemporaries.
We're also able to compare this research output to 188 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 68% of its contemporaries.