PMID- 30907867
OWN - NLM
STAT- MEDLINE
DCOM- 20200131
LR  - 20220129
IS  - 1940-087X (Electronic)
IS  - 1940-087X (Linking)
IP  - 145
DP  - 2019 Mar 6
TI  - qKAT: Quantitative Semi-automated Typing of Killer-cell Immunoglobulin-like 
      Receptor Genes.
LID - 10.3791/58646 [doi]
AB  - Killer cell immunoglobulin-like receptors (KIRs) are a set of inhibitory and 
      activating immune receptors, on natural killer (NK) and T cells, encoded by a 
      polymorphic cluster of genes on chromosome 19. Their best-characterized ligands 
      are the human leukocyte antigen (HLA) molecules that are encoded within the major 
      histocompatibility complex (MHC) locus on chromosome 6. There is substantial 
      evidence that they play a significant role in immunity, reproduction, and 
      transplantation, making it crucial to have techniques that can accurately 
      genotype them. However, high-sequence homology, as well as allelic and copy 
      number variation, make it difficult to design methods that can accurately and 
      efficiently genotype all KIR genes. Traditional methods are usually limited in 
      the resolution of data obtained, throughput, cost-effectiveness, and the time 
      taken for setting up and running the experiments. We describe a method called 
      quantitative KIR semi-automated typing (qKAT), which is a high-throughput 
      multiplex real-time polymerase chain reaction method that can determine the gene 
      copy numbers for all genes in the KIR locus. qKAT is a simple high-throughput 
      method that can provide high-resolution KIR copy number data, which can be 
      further used to infer the variations in the structurally polymorphic haplotypes 
      that encompass them. This copy number and haplotype data can be beneficial for 
      studies on large-scale disease associations, population genetics, as well as 
      investigations on expression and functional interactions between KIR and HLA.
FAU - Jayaraman, Jyothi
AU  - Jayaraman J
AD  - Department of Pathology, University of Cambridge; Department of Physiology, 
      Development and Neuroscience, University of Cambridge; Department of Obstetrics 
      and Gynaecology, University of Cambridge School of Medicine, NIHR Cambridge 
      Biomedical Research Centre; Centre for Trophoblast Research, University of 
      Cambridge.
FAU - Kirgizova, Vitalina
AU  - Kirgizova V
AD  - Department of Pathology, University of Cambridge.
FAU - Di, Da
AU  - Di D
AD  - Department of Pathology, University of Cambridge; Department of Genetics & 
      Evolution, University of Geneva.
FAU - Johnson, Christopher
AU  - Johnson C
AD  - Department of Pathology, University of Cambridge; Royal Papworth Hospital.
FAU - Jiang, Wei
AU  - Jiang W
AD  - Department of Pathology, University of Cambridge; Department of Plant Sciences, 
      University of Cambridge.
FAU - Traherne, James A
AU  - Traherne JA
AD  - Department of Pathology, University of Cambridge; jat51@cam.ac.uk.
LA  - eng
GR  - 695551/ERC_/European Research Council/International
GR  - G0901682/MRC_/Medical Research Council/United Kingdom
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
PT  - Video-Audio Media
DEP - 20190306
PL  - United States
TA  - J Vis Exp
JT  - Journal of visualized experiments : JoVE
JID - 101313252
RN  - 0 (Receptors, KIR)
SB  - IM
MH  - Automation
MH  - DNA Copy Number Variations/genetics
MH  - Haplotypes
MH  - Humans
MH  - Linkage Disequilibrium/genetics
MH  - Receptors, KIR/*genetics
MH  - *Software
PMC - PMC6794157
MID - EMS84585
EDAT- 2019/03/26 06:00
MHDA- 2020/02/01 06:00
PMCR- 2019/10/15
CRDT- 2019/03/26 06:00
PHST- 2019/03/26 06:00 [entrez]
PHST- 2019/03/26 06:00 [pubmed]
PHST- 2020/02/01 06:00 [medline]
PHST- 2019/10/15 00:00 [pmc-release]
AID - 10.3791/58646 [doi]
PST - epublish
SO  - J Vis Exp. 2019 Mar 6;(145):10.3791/58646. doi: 10.3791/58646.