↓ Skip to main content

Improved full-length killer cell immunoglobulin-like receptor transcript discovery in Mauritian cynomolgus macaques

Overview of attention for article published in Immunogenetics, March 2017
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

twitter
4 X users

Citations

dimensions_citation
21 Dimensions

Readers on

mendeley
25 Mendeley
Title
Improved full-length killer cell immunoglobulin-like receptor transcript discovery in Mauritian cynomolgus macaques
Published in
Immunogenetics, March 2017
DOI 10.1007/s00251-017-0977-7
Pubmed ID
Authors

Trent M. Prall, Michael E. Graham, Julie A. Karl, Roger W. Wiseman, Adam J. Ericsen, Muthuswamy Raveendran, R. Alan Harris, Donna M. Muzny, Richard A. Gibbs, Jeffrey Rogers, David H. O’Connor

Abstract

Killer cell immunoglobulin-like receptors (KIRs) modulate disease progression of pathogens including HIV, malaria, and hepatitis C. Cynomolgus and rhesus macaques are widely used as nonhuman primate models to study human pathogens, and so, considerable effort has been put into characterizing their KIR genetics. However, previous studies have relied on cDNA cloning and Sanger sequencing that lack the throughput of current sequencing platforms. In this study, we present a high throughput, full-length allele discovery method utilizing Pacific Biosciences circular consensus sequencing (CCS). We also describe a new approach to Macaque Exome Sequencing (MES) and the development of the Rhexome1.0, an adapted target capture reagent that includes macaque-specific capture probe sets. By using sequence reads generated by whole genome sequencing (WGS) and MES to inform primer design, we were able to increase the sensitivity of KIR allele discovery. We demonstrate this increased sensitivity by defining nine novel alleles within a cohort of Mauritian cynomolgus macaques (MCM), a geographically isolated population with restricted KIR genetics that was thought to be completely characterized. Finally, we describe an approach to genotyping KIRs directly from sequence reads generated using WGS/MES reads. The findings presented here expand our understanding of KIR genetics in MCM by associating new genes with all eight KIR haplotypes and demonstrating the existence of at least one KIR3DS gene associated with every haplotype.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 24%
Student > Doctoral Student 3 12%
Student > Ph. D. Student 3 12%
Professor > Associate Professor 3 12%
Student > Master 2 8%
Other 3 12%
Unknown 5 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 32%
Agricultural and Biological Sciences 6 24%
Immunology and Microbiology 3 12%
Medicine and Dentistry 2 8%
Energy 1 4%
Other 0 0%
Unknown 5 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 23 April 2017.
All research outputs
#13,032,628
of 22,961,203 outputs
Outputs from Immunogenetics
#876
of 1,201 outputs
Outputs of similar age
#149,817
of 309,177 outputs
Outputs of similar age from Immunogenetics
#5
of 11 outputs
Altmetric has tracked 22,961,203 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,201 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 26th percentile – i.e., 26% of its peers scored the same or lower than it.
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 309,177 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 50% of its contemporaries.
We're also able to compare this research output to 11 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 54% of its contemporaries.