Genome-wide association study in quinoa reveals selection pattern typical for crops with a short breeding history

  1. Dilan Sarange Rajapaksha Patiranage
  2. Elodie Rey
  3. Nazgol Emrani  Is a corresponding author
  4. Gordon Wellman
  5. Karl Schmid
  6. Sandra M Schmöckel
  7. Mark Tester
  8. Christian Jung  Is a corresponding author
  1. Christian-Albrechts University of Kiel, Germany
  2. King Abdullah University of Science and Technology, Saudi Arabia
  3. University of Hohenheim, Germany

Abstract

Quinoa germplasm preserves useful and substantial genetic variation, yet it remains untapped due to a lack of implementation of modern breeding tools. We have integrated field and sequence data to characterize a large diversity panel of quinoa. Whole-genome sequencing of 310 accessions revealed 2.9 million polymorphic high confidence SNP loci. Highland and Lowland quinoa were clustered into two main groups, with FST divergence of 0.36 and LD decay of 6.5 and 49.8 Kb, respectively. A genome-wide association study using multi-year phenotyping trials uncovered 600 SNPs stably associated with 17 traits. Two candidate genes are associated with thousand seed weight, and a resistance gene analog is associated with downy mildew resistance. We also identified pleiotropically acting loci for four agronomic traits important for adaptation. This work demonstrates the use of re-sequencing data of an orphan crop, which is partially domesticated to rapidly identify marker-trait association and provides the underpinning elements for genomics-enabled quinoa breeding.

Data availability

The raw sequencing data have been submitted to the NCBI Sequence Read Archive (SRA) under the BioProject PRJNA673789. Quinoa reference genome version 2 is available at CoGe database under genome id 53523. Phenotype data and ready-use genotype data (vcf file) are available at https://doi.org/10.5061/dryad.zgmsbcc9m. A detailed description of the germplasm, phenotyping methods, and phenotypes are available at https://quinoa.kaust.edu.sa/#/ (Stanschewski et al., 2021). Seeds are available from the public gene banks such as IPK Gatersleben (https://www.ipk-gatersleben.de/en/genebank/) and the U.S. National Plant Germplasm System (https://npgsweb.ars-grin.gov/gringlobal/search).Custom scripts used for SNP calling are available on GitHub: https://github.com/IBEXCluster/ IBEX-SNPcaller/blob/master/workflow.sh. Additional information of other custom scripts used for making plots are available at https://github.com/DilanSarange/quinoaDPgwas

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Dilan Sarange Rajapaksha Patiranage

    Plant Breeding Institute, Christian-Albrechts University of Kiel, Kiel, Germany
    Competing interests
    The authors declare that no competing interests exist.
  2. Elodie Rey

    Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
    Competing interests
    The authors declare that no competing interests exist.
  3. Nazgol Emrani

    Plant Breeding Institute, Christian-Albrechts University of Kiel, Kiel, Germany
    For correspondence
    n.emrani@plantbreeding.uni-kiel.de
    Competing interests
    The authors declare that no competing interests exist.
  4. Gordon Wellman

    Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
    Competing interests
    The authors declare that no competing interests exist.
  5. Karl Schmid

    Institute of Plant Breeding, Seed Science and Population Genetics, University of Hohenheim, Stuttgart, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5129-895X
  6. Sandra M Schmöckel

    Department of Physiology of Yield Stability, University of Hohenheim, Stuttgart, Germany
    Competing interests
    The authors declare that no competing interests exist.
  7. Mark Tester

    Biological and Environmental Sciences and Engineering, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5085-8801
  8. Christian Jung

    Plant Breeding Institute, Christian-Albrechts University of Kiel, Kiel, Germany
    For correspondence
    c.jung@plantbreeding.uni-kiel.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8149-7976

Funding

King Abdullah University of Science and Technology (OSR-2016-CRG5- 466 2966-02)

  • Dilan Sarange Rajapaksha Patiranage

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Vincent Castric, Université de Lille, France

Publication history

  1. Received: January 25, 2021
  2. Accepted: July 7, 2022
  3. Accepted Manuscript published: July 8, 2022 (version 1)

Copyright

© 2022, Patiranage et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 332
    Page views
  • 199
    Downloads
  • 0
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Dilan Sarange Rajapaksha Patiranage
  2. Elodie Rey
  3. Nazgol Emrani
  4. Gordon Wellman
  5. Karl Schmid
  6. Sandra M Schmöckel
  7. Mark Tester
  8. Christian Jung
(2022)
Genome-wide association study in quinoa reveals selection pattern typical for crops with a short breeding history
eLife 11:e66873.
https://doi.org/10.7554/eLife.66873

Further reading

    1. Genetics and Genomics
    2. Microbiology and Infectious Disease
    Liselot Dewachter et al.
    Research Article Updated

    Antibiotic resistance in the important opportunistic human pathogen Streptococcus pneumoniae is on the rise. This is particularly problematic in the case of the β-lactam antibiotic amoxicillin, which is the first-line therapy. It is therefore crucial to uncover targets that would kill or resensitize amoxicillin-resistant pneumococci. To do so, we developed a genome-wide, single-cell based, gene silencing screen using CRISPR interference called sCRilecs-seq (subsets of CRISPR interference libraries extracted by fluorescence activated cell sorting coupled to next generation sequencing). Since amoxicillin affects growth and division, sCRilecs-seq was used to identify targets that are responsible for maintaining proper cell size. Our screen revealed that downregulation of the mevalonate pathway leads to extensive cell elongation. Further investigation into this phenotype indicates that it is caused by a reduced availability of cell wall precursors at the site of cell wall synthesis due to a limitation in the production of undecaprenyl phosphate (Und-P), the lipid carrier that is responsible for transporting these precursors across the cell membrane. The data suggest that, whereas peptidoglycan synthesis continues even with reduced Und-P levels, cell constriction is specifically halted. We successfully exploited this knowledge to create a combination treatment strategy where the FDA-approved drug clomiphene, an inhibitor of Und-P synthesis, is paired up with amoxicillin. Our results show that clomiphene potentiates the antimicrobial activity of amoxicillin and that combination therapy resensitizes amoxicillin-resistant S. pneumoniae. These findings could provide a starting point to develop a solution for the increasing amount of hard-to-treat amoxicillin-resistant pneumococcal infections.

    1. Genetics and Genomics
    Mohammed Janahi et al.
    Research Article

    Nomograms are important clinical tools applied widely in both developing and aging populations. They are generally constructed as normative models identifying cases as outliers to a distribution of healthy controls. Currently used normative models do not account for genetic heterogeneity. Hippocampal Volume (HV) is a key endophenotype for many brain disorders. Here, we examine the impact of genetic adjustment on HV nomograms and the translational ability to detect dementia patients. Using imaging data from 35,686 healthy subjects aged 44 to 82 from the UK BioBank (UKB), we built HV nomograms using gaussian process regression (GPR), which - compared to a previous method - extended the application age by 20 years, including dementia critical age ranges. Using HV Polygenic Scores (HV-PGS), we built genetically adjusted nomograms from participants stratified into the top and bottom 30% of HV-PGS. This shifted the nomograms in the expected directions by ~100 mm3 (2.3% of the average HV), which equates to 3 years of normal aging for a person aged ~65. Clinical impact of genetically adjusted nomograms was investigated by comparing 818 subjects from the AD neuroimaging (ADNI) database diagnosed as either cognitively normal (CN), having mild cognitive impairment (MCI) or Alzheimer’s disease patients (AD). While no significant change in the survival analysis was found for MCI-to-AD conversion, an average of 68% relative decrease was found in intra-diagnostic-group variance, highlighting the importance of genetic adjustment in untangling phenotypic heterogeneity.