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Annotation of pseudogenic gene segments by massively parallel sequencing of rearranged lymphocyte receptor loci.

Overview of attention for article published in Genome Medicine, January 2015
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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)
  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

Mentioned by

blogs
1 blog
twitter
4 tweeters

Citations

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28 Dimensions

Readers on

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34 Mendeley
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Title
Annotation of pseudogenic gene segments by massively parallel sequencing of rearranged lymphocyte receptor loci.
Published in
Genome Medicine, January 2015
DOI 10.1186/s13073-015-0238-z
Pubmed ID
Authors

Jared Dean, Ryan O Emerson, Marissa Vignali, Anna M Sherwood, Mark J Rieder, Christopher S Carlson, Harlan S Robins, Ryan O. Emerson, Anna M. Sherwood, Mark J. Rieder, Christopher S. Carlson, Harlan S. Robins

Abstract

The adaptive immune system generates a remarkable range of antigen-specific T-cell receptors (TCRs), allowing the recognition of a diverse set of antigens. Most of this diversity is encoded in the complementarity determining region 3 (CDR3) of the β chain of the αβ TCR, which is generated by somatic recombination of noncontiguous variable (V), diversity (D), and joining (J) gene segments. Deletion and non-templated insertion of nucleotides at the D-J and V-DJ junctions further increases diversity. Many of these gene segments are annotated as non-functional owing to defects in their primary sequence, the absence of motifs necessary for rearrangement, or chromosomal locations outside the TCR locus. We sought to utilize a novel method, based on high-throughput sequencing of rearranged TCR genes in a large cohort of individuals, to evaluate the use of functional and non-functional alleles. We amplified and sequenced genomic DNA from the peripheral blood of 587 healthy volunteers using a multiplexed polymerase chain reaction assay that targets the variable region of the rearranged TCRβ locus, and we determined the presence and the proportion of productive rearrangements for each TCRβ V gene segment in each individual. We then used this information to annotate the functional status of TCRβ V gene segments in this cohort. For most TCRβ V gene segments, our method agrees with previously reported functional annotations. However, we identified novel non-functional alleles for several gene segments, some of which were used exclusively in our cohort to the detriment of reported functional alleles. We also saw that some gene segments reported to have both functional and non-functional alleles consistently behaved in our cohort as either functional or non-functional, suggesting that some reported alleles were not present in the population studied. In this proof-of-principle study, we used high-throughput sequencing of the TCRβ locus of a large cohort of healthy volunteers to evaluate the use of functional and non-functional alleles of individual TCRβ V gene segments. With some modifications, our method has the potential to be extended to gene segments in the α, γ, and δ TCR loci, as well as the genes encoding for B-cell receptor chains.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Unknown 33 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 24%
Student > Master 8 24%
Student > Ph. D. Student 6 18%
Professor 3 9%
Other 2 6%
Other 4 12%
Unknown 3 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 38%
Biochemistry, Genetics and Molecular Biology 5 15%
Immunology and Microbiology 4 12%
Medicine and Dentistry 4 12%
Physics and Astronomy 1 3%
Other 3 9%
Unknown 4 12%

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 11 December 2015.
All research outputs
#2,341,363
of 17,358,590 outputs
Outputs from Genome Medicine
#536
of 1,156 outputs
Outputs of similar age
#56,262
of 373,214 outputs
Outputs of similar age from Genome Medicine
#48
of 108 outputs
Altmetric has tracked 17,358,590 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,156 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.4. This one has gotten more attention than average, scoring higher than 53% 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 373,214 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 108 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 55% of its contemporaries.