Gene-centric functional dissection of human genetic variation uncovers regulators of hematopoiesis

  1. Satish K Nandakumar
  2. Sean K McFarland
  3. Laura Marlene Mateyka
  4. Caleb A Lareau
  5. Jacob C Ulirsch
  6. Leif S Ludwig
  7. Gaurav Agarwal
  8. Jesse M Engreitz
  9. Bartlomiej Przychodzen
  10. Marie McConkey
  11. Glenn S Cowley
  12. John G Doench
  13. Jaroslaw P Maciejewski
  14. Benjamin L Ebert
  15. David E Root
  16. Vijay G Sankaran  Is a corresponding author
  1. Boston Children's Hospital, United States
  2. Broad Institute of MIT and Harvard, United States
  3. Cleveland Clinic, United States
  4. Brigham and Women's Hospital, United States
  5. Broad Institute of Harvard and MIT, United States

Abstract

Genome-wide association studies (GWAS) have identified thousands of variants associated with human diseases and traits. However, the majority of GWAS-implicated variants are in non-coding regions of the genome and require in depth follow-up to identify target genes and decipher biological mechanisms. Here, rather than focusing on causal variants, we have undertaken a pooled loss-of-function screen in primary hematopoietic cells to interrogate 389 candidate genes contained in 75 loci associated with red blood cell traits. Using this approach, we identify 77 genes at 38 GWAS loci, with most loci harboring 1-2 candidate genes. Importantly, the hit set was strongly enriched for genes validated through orthogonal genetic approaches. Genes identified by this approach are enriched in specific and relevant biological pathways, allowing regulators of human erythropoiesis and modifiers of blood diseases to be defined. More generally, this functional screen provides a paradigm for gene-centric follow up of GWAS for a variety of human diseases and traits.

Data availability

1000 Genomes human variation datasetThe 1000 Genomes Project Consortium. (2015)Recombinant hotspots access at:ftp://ftp-trace.ncbi.nih.gov/1000genomes/ftp/pilot_data/technical/reference/Phase 1 data (for PLINK) accessed at: https://www.cog-genomics.org/plink/1.9/resourcesPhase 3 data accessed at: http://www.internationalgenome.org/category/phase-3/Pooled screen abundance data for shRNA targeting red blood cell trait GWAS-nominated genes during the course of in vitro differentiation of human CD34+ cellsSK Nandakumar, SK McFarland, et al. (2019)Available on the project's companion GitHub repository: https://github.com/sankaranlab/shRNA_screen/tree/master/ref/shref.csvEffects of shRNA knockdown of SF3A2 on splicing during human erythropoiesisSK Nandakumar, SK McFarland, et al. (2019)ID GSE129603. In the public domain at GEO https://www.ncbi.nlm.nih.gov/geo/Effects of SF3B1 mutants on splicing in human erythropoiesisEA Obeng et al. (2016)ID GSE85712. In the public domain at GEO https://www.ncbi.nlm.nih.gov/geo/SNP sets identified by GWAS of LDL, HDL, and triglyceride traitsCJ Willer et al. (2013)Accessed at: http://csg.sph.umich.edu/willer/public/lipids2013/Human hematopoietic lineage gene expressionMR Corces et al. (2016)ID GSE74912. In the public domain at GEO https://www.ncbi.nlm.nih.gov/geo/Human adult and fetal erythropoiesis gene expressionH Yan et al. (2018)ID GSE107218. In the public domain at GEO https://www.ncbi.nlm.nih.gov/geo/

Article and author information

Author details

  1. Satish K Nandakumar

    Division of Hematology/Oncology, Boston Children's Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Sean K McFarland

    Division of Hematology/Oncology, Boston Children's Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Laura Marlene Mateyka

    Division of Hematology/Oncology, Boston Children's Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Caleb A Lareau

    Division of Hematology/Oncology, Boston Children's Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4179-4807
  5. Jacob C Ulirsch

    Division of Hematology/Oncology, Boston Children's Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Leif S Ludwig

    Division of Hematology/Oncology, Boston Children's Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Gaurav Agarwal

    Division of Hematology/Oncology, Boston Children's Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Jesse M Engreitz

    Broad Institute of MIT and Harvard, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5754-1719
  9. Bartlomiej Przychodzen

    Department of Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Marie McConkey

    Division of Hematology, Brigham and Women's Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  11. Glenn S Cowley

    Broad Institute of MIT and Harvard, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  12. John G Doench

    Broad Institute of MIT and Harvard, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3707-9889
  13. Jaroslaw P Maciejewski

    Department of Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, United States
    Competing interests
    The authors declare that no competing interests exist.
  14. Benjamin L Ebert

    Division of Hematology, Brigham and Women's Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  15. David E Root

    Broad Institute of Harvard and MIT, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  16. Vijay G Sankaran

    Division of Hematology/Oncology, Boston Children's Hospital, Boston, United States
    For correspondence
    sankaran@broadinstitute.org
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0044-443X

Funding

National Institutes of Health (R33HL120791)

  • Vijay G Sankaran

New York Stem Cell Foundation

  • Vijay G Sankaran

National Institutes of Health (R01DK103794)

  • Vijay G Sankaran

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

Reviewing Editor

  1. Stephen Parker, University of Michigan, United States

Ethics

Animal experimentation: No human subjects were involved in the study. Human CD34+ HSPCs used in these experiments are deidentified and obtained from external sources. All mouse experiments were performed in full compliance with the approved Institutional Animal Care and Use Committee (IACUC) protocols at Boston Children's Hospital (Protocol # 18-05-3680R) and Brigham and Women's Hospital (Protocol # 2017N000060). These studies were approved by local regulatory committees in accordance with the highest ethical standards for biomedical research involving vertebrate animals.

Version history

  1. Received: December 2, 2018
  2. Accepted: May 8, 2019
  3. Accepted Manuscript published: May 9, 2019 (version 1)
  4. Version of Record published: May 24, 2019 (version 2)

Copyright

© 2019, Nandakumar 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

  • 2,814
    views
  • 432
    downloads
  • 13
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

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. Satish K Nandakumar
  2. Sean K McFarland
  3. Laura Marlene Mateyka
  4. Caleb A Lareau
  5. Jacob C Ulirsch
  6. Leif S Ludwig
  7. Gaurav Agarwal
  8. Jesse M Engreitz
  9. Bartlomiej Przychodzen
  10. Marie McConkey
  11. Glenn S Cowley
  12. John G Doench
  13. Jaroslaw P Maciejewski
  14. Benjamin L Ebert
  15. David E Root
  16. Vijay G Sankaran
(2019)
Gene-centric functional dissection of human genetic variation uncovers regulators of hematopoiesis
eLife 8:e44080.
https://doi.org/10.7554/eLife.44080

Share this article

https://doi.org/10.7554/eLife.44080

Further reading

    1. Computational and Systems Biology
    2. Genetics and Genomics
    Ardalan Naseri, Degui Zhi, Shaojie Zhang
    Research Article Updated

    Runs-of-homozygosity (ROH) segments, contiguous homozygous regions in a genome were traditionally linked to families and inbred populations. However, a growing literature suggests that ROHs are ubiquitous in outbred populations. Still, most existing genetic studies of ROH in populations are limited to aggregated ROH content across the genome, which does not offer the resolution for mapping causal loci. This limitation is mainly due to a lack of methods for the efficient identification of shared ROH diplotypes. Here, we present a new method, ROH-DICE (runs-of-homozygous diplotype cluster enumerator), to find large ROH diplotype clusters, sufficiently long ROHs shared by a sufficient number of individuals, in large cohorts. ROH-DICE identified over 1 million ROH diplotypes that span over 100 single nucleotide polymorphisms (SNPs) and are shared by more than 100 UK Biobank participants. Moreover, we found significant associations of clustered ROH diplotypes across the genome with various self-reported diseases, with the strongest associations found between the extended human leukocyte antigen (HLA) region and autoimmune disorders. We found an association between a diplotype covering the homeostatic iron regulator (HFE) gene and hemochromatosis, even though the well-known causal SNP was not directly genotyped or imputed. Using a genome-wide scan, we identified a putative association between carriers of an ROH diplotype in chromosome 4 and an increase in mortality among COVID-19 patients (p-value = 1.82 × 10−11). In summary, our ROH-DICE method, by calling out large ROH diplotypes in a large outbred population, enables further population genetics into the demographic history of large populations. More importantly, our method enables a new genome-wide mapping approach for finding disease-causing loci with multi-marker recessive effects at a population scale.

    1. Chromosomes and Gene Expression
    2. Genetics and Genomics
    Lisa Baumgartner, Jonathan J Ipsaro ... Julius Brennecke
    Research Advance

    Members of the diverse heterochromatin protein 1 (HP1) family play crucial roles in heterochromatin formation and maintenance. Despite the similar affinities of their chromodomains for di- and tri-methylated histone H3 lysine 9 (H3K9me2/3), different HP1 proteins exhibit distinct chromatin-binding patterns, likely due to interactions with various specificity factors. Previously, we showed that the chromatin-binding pattern of the HP1 protein Rhino, a crucial factor of the Drosophila PIWI-interacting RNA (piRNA) pathway, is largely defined by a DNA sequence-specific C2H2 zinc finger protein named Kipferl (Baumgartner et al., 2022). Here, we elucidate the molecular basis of the interaction between Rhino and its guidance factor Kipferl. Through phylogenetic analyses, structure prediction, and in vivo genetics, we identify a single amino acid change within Rhino’s chromodomain, G31D, that does not affect H3K9me2/3 binding but disrupts the interaction between Rhino and Kipferl. Flies carrying the rhinoG31D mutation phenocopy kipferl mutant flies, with Rhino redistributing from piRNA clusters to satellite repeats, causing pronounced changes in the ovarian piRNA profile of rhinoG31D flies. Thus, Rhino’s chromodomain functions as a dual-specificity module, facilitating interactions with both a histone mark and a DNA-binding protein.