Evidence map›Paper›PMID 35587892›Full record

ArticleMolecular ecology resources2022

MHCtools - an R package for MHC high-throughput sequencing data: Genotyping, haplotype and supertype inference, and downstream genetic analyses in non-model organisms.

Jacob Roved, Bengt Hansson, Martin Stervander, Dennis Hasselquist, Helena Westerdahl

Open access · bronzeAbstract read
In one paragraph

Article in Molecular ecology resources, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

11 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. HiddenCurrent research in parasitology & vector-borne diseases · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Article
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

5 authors at 2 institutions in 2 countries.

Jacob RovedGLOBE Institute, Section for Evolutionary Genomics, University of Copenhagen, Copenhagen K, Denmark.ORCID https://orcid.org/0000-0001-6977-714X
Bengt HanssonDepartment of Biology, Molecular Ecology and Evolution Laboratory, Lund University, Lund, Sweden.ORCID https://orcid.org/0000-0001-6694-8169
Martin StervanderDepartment of Biology, Molecular Ecology and Evolution Laboratory, Lund University, Lund, Sweden.ORCID https://orcid.org/0000-0002-6139-7828
Dennis HasselquistDepartment of Biology, Molecular Ecology and Evolution Laboratory, Lund University, Lund, Sweden.ORCID https://orcid.org/0000-0002-0056-6616
Helena WesterdahlDepartment of Biology, Molecular Ecology and Evolution Laboratory, Lund University, Lund, Sweden.ORCID https://orcid.org/0000-0001-7167-9805
Lund University · SEUniversity of Copenhagen · DK

Funding

European Research CouncilEuropean UnionH2020 European Research Council 679799H2020 European Research Council 742646Horizon 2020Kungliga Fysiografiska Sällskapet i LundLunds DjurskyddsfondLund UniversityLund University, Department of BiologySwedish Research CouncilVetenskapsrådet 2015-05149Vetenskapsrådet 2016-00689Vetenskapsrådet 2016-04391Vetenskapsrådet 2020-03976Vetenskapsrådet 2020-04285Vetenskapsrådet 349-2007-8690Vetenskapsrådet 621-2014-5222
6 · The paper itself

Abstract

The major histocompatibility complex (MHC) plays a central role in the vertebrate adaptive immune system and has been of long-term interest in evolutionary biology. While several protocols have been developed for MHC genotyping, there is a lack of transparent and standardized tools for downstream analysis of MHC data. Here, we present the r package mhctools and demonstrate the use of its functions to (i) assist accurate MHC genotyping from high-throughput amplicon-sequencing data, (ii) infer functional MHC supertypes using bootstrapped clustering analysis, (iii) identify segregating MHC haplotypes from family data, and (iv) analyse functional and genetic distances between MHC sequences. We employed mhctools to analyse MHC class I (MHC-I) amplicon data of 559 great reed warblers (Acrocephalus arundinaceus). We identified 390 MHC-I alleles which clustered into 14 functional supertypes. A phylogenetic analysis and analyses of positive selection suggested that the MHC-I alleles belong to several distinct functional groups. We furthermore identified 107 segregating haplotypes among 116 families, and found substantial variation in diversity with 4-21 MHC-I alleles and 3-13 MHC-I supertypes per haplotype. Finally, we show that the great reed warbler haplotypes harboured combinations of MHC-I supertypes with greater functional divergence than observed in simulated populations of possible haplotypes, a result that is in accordance with the divergent allele advantage hypothesis. Our study demonstrates the power of mhctools to support genotyping and analysis of MHC in non-model species, which we hope will encourage broad implementation among researchers in MHC genetics and evolution.

Indexed as

Major Histocompatibility ComplexPasseriformesAllelesAnimalsGenotypeHaplotypesHigh-Throughput Nucleotide SequencingHumansPhylogenycluster analysisdivergent allele advantagefunctional divergencemajor histocompatibility complexMHC haplotypesMHC supertypes

Identifiers

PMID35587892
PMCPMC9543685
OpenAlexW4280652888

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.