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A new high-throughput sequencing method for determining diversity and similarity of T cell receptor (TCR) α and β repertoires and identifying potential new invariant TCR α chains

Overview of attention for article published in BMC Immunology, October 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 (80th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

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Title
A new high-throughput sequencing method for determining diversity and similarity of T cell receptor (TCR) α and β repertoires and identifying potential new invariant TCR α chains
Published in
BMC Immunology, October 2016
DOI 10.1186/s12865-016-0177-5
Pubmed ID
Authors

Kazutaka Kitaura, Tadasu Shini, Takaji Matsutani, Ryuji Suzuki

Abstract

High-throughput sequencing of T cell receptor (TCR) genes is a powerful tool for analyses of antigen specificity, clonality and diversity of T lymphocytes. Here, we developed a new TCR repertoire analysis method using 454 DNA sequencing technology in combination with an adaptor-ligation mediated polymerase chain reaction (PCR). This method allows the amplification of all TCR genes without PCR bias. To compare gene usage, diversity and similarity of expressed TCR repertoires among individuals, we conducted next-generation sequencing (NGS) of TRA and TRB genes in peripheral blood mononuclear cells from 20 healthy human individuals. From a total of 267,037 sequence reads from 20 individuals, 149,216 unique sequence reads were identified. Preferential usage of several V and J genes were observed while some recombinations of TRAV with TRAJ appeared to be restricted. The extent of TCR diversity was not significantly different between TRA and TRB, while TRA repertoires were more similar between individuals than TRB repertoires were. The interindividual similarity of TRA depended largely on the frequent presence of shared TCRs among two or more individuals. A publicly available TRA had a near-germline TCR with a shorter CDR3. Notably, shared TRA sequences, especially those shared among a large number of individuals', often contained TCRα related with invariant TCRα derived from invariant natural killer T cells and mucosal-associated invariant T cells. These results suggest that retrieval of shared TCRs by NGS would be useful for the identification of potential new invariant TCRα chains. This NGS method will enable the comprehensive quantitative analysis of TCR repertoires at a clonal level.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 120 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 120 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 21%
Researcher 20 17%
Student > Bachelor 15 13%
Student > Master 12 10%
Student > Doctoral Student 6 5%
Other 19 16%
Unknown 23 19%
Readers by discipline Count As %
Immunology and Microbiology 24 20%
Agricultural and Biological Sciences 24 20%
Biochemistry, Genetics and Molecular Biology 21 18%
Medicine and Dentistry 16 13%
Engineering 2 2%
Other 7 6%
Unknown 26 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 12 May 2022.
All research outputs
#3,948,266
of 23,881,329 outputs
Outputs from BMC Immunology
#53
of 582 outputs
Outputs of similar age
#64,388
of 322,838 outputs
Outputs of similar age from BMC Immunology
#1
of 7 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 582 research outputs from this source. They receive a mean Attention Score of 3.9. 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 322,838 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 80% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them