↓ Skip to main content

Killer Immunoglobulin-Like Receptor Allele Determination Using Next-Generation Sequencing Technology

Overview of attention for article published in Frontiers in immunology, May 2017
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

twitter
13 X users
facebook
1 Facebook page

Citations

dimensions_citation
20 Dimensions

Readers on

mendeley
48 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Killer Immunoglobulin-Like Receptor Allele Determination Using Next-Generation Sequencing Technology
Published in
Frontiers in immunology, May 2017
DOI 10.3389/fimmu.2017.00547
Pubmed ID
Authors

Bercelin Maniangou, Nolwenn Legrand, Mehdi Alizadeh, Ulysse Guyet, Catherine Willem, Gaëlle David, Eric Charpentier, Alexandre Walencik, Christelle Retière, Katia Gagne

Abstract

The impact of natural killer (NK) cell alloreactivity on hematopoietic stem cell transplantation (HSCT) outcome is still debated due to the complexity of graft parameters, HLA class I environment, the nature of killer cell immunoglobulin-like receptor (KIR)/KIR ligand genetic combinations studied, and KIR(+) NK cell repertoire size. KIR genes are known to be polymorphic in terms of gene content, copy number variation, and number of alleles. These allelic polymorphisms may impact both the phenotype and function of KIR(+) NK cells. We, therefore, speculate that polymorphisms may alter donor KIR(+) NK cell phenotype/function thus modulating post-HSCT KIR(+) NK cell alloreactivity. To investigate KIR allele polymorphisms of all KIR genes, we developed a next-generation sequencing (NGS) technology on a MiSeq platform. To ensure the reliability and specificity of our method, genomic DNA from well-characterized cell lines were used; high-resolution KIR typing results obtained were then compared to those previously reported. Two different bioinformatic pipelines were used allowing the attribution of sequencing reads to specific KIR genes and the assignment of KIR alleles for each KIR gene. Our results demonstrated successful long-range KIR gene amplifications of all reference samples using intergenic KIR primers. The alignment of reads to the human genome reference (hg19) using BiRD pipeline or visualization of data using Profiler software demonstrated that all KIR genes were completely sequenced with a sufficient read depth (mean 317× for all loci) and a high percentage of mapping (mean 93% for all loci). Comparison of high-resolution KIR typing obtained to those published data using exome capture resulted in a reported concordance rate of 95% for centromeric and telomeric KIR genes. Overall, our results suggest that NGS can be used to investigate the broad KIR allelic polymorphism. Hence, these data improve our knowledge, not only on KIR(+) NK cell alloreactivity in HSCT but also on the role of KIR(+) NK cell populations in control of viral infections and diseases.

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 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 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Unknown 47 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 21%
Researcher 10 21%
Student > Master 6 13%
Student > Doctoral Student 3 6%
Student > Bachelor 3 6%
Other 7 15%
Unknown 9 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 23%
Biochemistry, Genetics and Molecular Biology 7 15%
Medicine and Dentistry 7 15%
Immunology and Microbiology 4 8%
Computer Science 4 8%
Other 3 6%
Unknown 12 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 June 2017.
All research outputs
#5,407,105
of 25,382,440 outputs
Outputs from Frontiers in immunology
#6,075
of 31,531 outputs
Outputs of similar age
#87,190
of 326,293 outputs
Outputs of similar age from Frontiers in immunology
#96
of 396 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 31,531 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one has done well, scoring higher than 80% 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 326,293 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 73% of its contemporaries.
We're also able to compare this research output to 396 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.