Evidence map›Paper›PMID 34339413›Full record

ArticlePLoS computational biology2021

High-throughput Interpretation of Killer-cell Immunoglobulin-like Receptor Short-read Sequencing Data with PING.

Wesley M Marin, Ravi Dandekar, Danillo G Augusto, Tasneem Yusufali, Bianca Heyn, Jan Hofmann, Vinzenz Lange, Jürgen Sauter, Paul J Norman, Jill A Hollenbach

Open access · goldAbstract readValidation Study
In one paragraph

Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
2.5field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 35 citations in OpenAlex.

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  18. KIR-HLA interactions extend human CD8+ T cell lifespan in vivo.The Journal of clinical investigation · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 2 countries.

Wesley M MarinUCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, California, United States of America.ORCID 0000-0002-2334-0396
Ravi DandekarUCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, California, United States of America.
Danillo G AugustoUCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, California, United States of America.ORCID 0000-0001-5665-8547
Tasneem YusufaliUCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, California, United States of America.
Bianca HeynDKMS Life Science Lab, Dresden, Germany.ORCID 0000-0002-4730-5165
Jan HofmannDKMS, Tübingen, Germany.ORCID 0000-0002-3397-2514
Vinzenz LangeDKMS Life Science Lab, Dresden, Germany.ORCID 0000-0002-6442-9573
Jürgen SauterDKMS, Tübingen, Germany.ORCID 0000-0001-8485-2945
Paul J NormanDivision of Biomedical Informatics and Personalized Medicine, and Department of Immunology and Microbiology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States of America.
Jill A HollenbachUCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, California, United States of America.
University of California, San Francisco · USDeutsche Knochenmarkspenderdatei · DEUniversity of Colorado Anschutz Medical Campus · US

Funding

Insights Into Immune-Related Diseases Born from Population GenomicsU01AI090905 · NIAID · UNIVERSITY OF COLORADO DENVER · PI Paul John Norman · 2010 to 2026
$10.9M
BMI Bioinformatics Training GrantsT32GM067547 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HERNANDEZ, RYAN D. · 2003 to 2022
$6.6M
Integrated Exchange and Storage of Current- and Future-Generation Immunogenomic DataR01AI128775 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI JILL Allison HOLLENBACH, STEVEN JOHN MACK · 2017 to 2026
$4.5M
NIAID NIH HHS R01 AI128775NIAID NIH HHS U01 AI090905NIGMS NIH HHS T32 GM067547
6 · The paper itself

Abstract

The killer-cell immunoglobulin-like receptor (KIR) complex on chromosome 19 encodes receptors that modulate the activity of natural killer cells, and variation in these genes has been linked to infectious and autoimmune disease, as well as having bearing on pregnancy and transplant outcomes. The medical relevance and high variability of KIR genes makes short-read sequencing an attractive technology for interrogating the region, providing a high-throughput, high-fidelity sequencing method that is cost-effective. However, because this gene complex is characterized by extensive nucleotide polymorphism, structural variation including gene fusions and deletions, and a high level of homology between genes, its interrogation at high resolution has been thwarted by bioinformatic challenges, with most studies limited to examining presence or absence of specific genes. Here, we present the PING (Pushing Immunogenetics to the Next Generation) pipeline, which incorporates empirical data, novel alignment strategies and a custom alignment processing workflow to enable high-throughput KIR sequence analysis from short-read data. PING provides KIR gene copy number classification functionality for all KIR genes through use of a comprehensive alignment reference. The gene copy number determined per individual enables an innovative genotype determination workflow using genotype-matched references. Together, these methods address the challenges imposed by the structural complexity and overall homology of the KIR complex. To determine copy number and genotype determination accuracy, we applied PING to European and African validation cohorts and a synthetic dataset. PING demonstrated exceptional copy number determination performance across all datasets and robust genotype determination performance. Finally, an investigation into discordant genotypes for the synthetic dataset provides insight into misaligned reads, advancing our understanding in interpretation of short-read sequencing data in complex genomic regions. PING promises to support a new era of studies of KIR polymorphism, delivering high-resolution KIR genotypes that are highly accurate, enabling high-quality, high-throughput KIR genotyping for disease and population studies.

Indexed as

Africa, SouthernAllelesComputational BiologyComputer SimulationDatabases, Nucleic AcidEuropeGene DosageGenetics, PopulationGenotypeHigh-Throughput Nucleotide SequencingHumansImmunogeneticsPolymorphism, GeneticReceptors, KIRSequence AlignmentSoftware DesignReceptors, KIR

Identifiers

PMID34339413
PMCPMC8360517
OpenAlexW3190200374

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.