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Promoter-interacting expression quantitative trait loci are enriched for functional genetic variants

Nature Genetics volume 53, pages 110–119 (2021)Cite this article

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Abstract

Expression quantitative trait loci (eQTLs) studies provide associations of genetic variants with gene expression but fall short of pinpointing functionally important eQTLs. Here, using H3K27ac HiChIP assays, we mapped eQTLs overlapping active cis-regulatory elements that interact with their target gene promoters (promoter-interacting eQTLs, pieQTLs) in five common immune cell types (Database of Immune Cell Expression, Expression quantitative trait loci and Epigenomics (DICE) cis-interactome project). This approach allowed us to identify functionally important eQTLs and show mechanisms that explain their cell-type restriction. We also devised an approach to eQTL discovery that relies on HiChIP-based promoter interaction maps as a structural framework for deciding which SNPs to test for association with gene expression, and observe ultra-long-distance pieQTLs (>1 megabase away), including several disease-risk variants. We validated the functional role of pieQTLs using reporter assays, CRISPRi, dCas9-tiling guides and Cas9-mediated base-pair editing. In this article we present a method for functional eQTL discovery and provide insights into relevance of noncoding variants for cell-specific gene regulation and for disease association beyond conventional eQTL mapping.

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Fig. 1: Active cis-regulatory interaction maps in human immune cell types from DICE.
Fig. 2: pieQTLs define potentially functional eQTLs.
Fig. 3: Ultra-long-distance cis-interactions define target genes of eQTLs.
Fig. 4: Nontranscribing promoters have enhancer activity.
Fig. 5: Mechanisms of cell-specific expression QTLs.

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Data availability

The DICE project provides anonymized data for public access at http://dice-database.org. Individual-specific RNA-sequencing and genotype data are available from the database of Genotypes and Phenotypes (dbGaP) (accession number: phs001703.v1.p1). Individual-specific HiChIP and ChIP–seq data are available from dbGaP (accession number: phs001703.v3.p1). The list of pieQTLs for each cell type is available through https://dice-database.org. All downloaded data are available through public repositories such as Gencode, dbGaP, PheGenI, 1000 Genomes Project, IHEC data portal, GEO and SRA. Further information and requests for reagents may be directed to the corresponding author/lead contacts, Pandurangan Vijayanand (vijay@lji.org) and Ferhat Ay (ferhatay@lji.org).

Code availability

The code developed for the analyses performed in this study is available upon request as well as from GitHub at https://github.com/ay-lab/pieQTL_NG.

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Acknowledgements

We thank the La Jolla Institute (LJI) Flow Cytometry Core for assisting with cell sorting; the LJI’s Clinical Studies Core for organizing sample collection; and the IGM Genomics Center at the University of California in San Diego for technical support with genotyping of tissue donors. We thank J.A. Greenbaum (LJI) and B. Ha (LJI) for data submission to dbGaP. We also thank the members of Ay and Vijayanand laboratories for their valuable comments and suggestions. This work was funded by NIH grants no. R24-AI108564 (P.V., F.A., B.P., M.K.) and no. R01-HL114093 (P.V.), the William K. Bowes Jr Foundation (P.V.), grant no. R35-GM128938 (F.A.) and grant no. UL1-TR002550 (P.M.). Utilized equipment was supported by the NIH grants no. S10RR027366 (BD FACSAria II) and no. S10-OD016262 (Illumina HiSeq 2500).

Author information

Author notes

  1. These authors contributed equally: Vivek Chandra, Sourya Bhattacharyya.

  2. These authors jointly supervised this work: Ferhat Ay, Pandurangan Vijayanand.

Authors and Affiliations

  1. La Jolla Institute for Immunology, La Jolla, CA, USA

    Vivek Chandra, Sourya Bhattacharyya, Benjamin J. Schmiedel, Ariel Madrigal, Cristian Gonzalez-Colin, Stephanie Fotsing, Austin Crinklaw, Gregory Seumois, Mitchell Kronenberg, Bjoern Peters, Ferhat Ay & Pandurangan Vijayanand

  2. Department of Integrative Structural and Computational Biology, Scripps Research, La Jolla, CA, USA

    Pejman Mohammadi

  3. Scripps Translational Science Institute, La Jolla, CA, USA

    Pejman Mohammadi

  4. Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA

    Mitchell Kronenberg

  5. Department of Medicine, University of California San Diego, La Jolla, CA, USA

    Bjoern Peters, Ferhat Ay & Pandurangan Vijayanand

  6. Faculty of Medicine, University of Southampton, Southampton, UK

    Pandurangan Vijayanand

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Contributions

V.C., S.B., B.J.S., M.K., B.P., F.A. and P.V. conceived the work. V.C., F.A. and P.V. designed the study and wrote the manuscript. V.C. designed and performed all of the experiments under the supervision of F.A. and P.V. B.J.S. isolated the primary immune cells by FACS, and, along with G.S. and P.V., supervised H3K27ac ChIP–seq assays. G.S. supervised sequencing of HiChIP and ChIP–seq libraries. S.B., A.M., C.G.-C., A.C. and S.F. performed bioinformatic analyses under the supervision of V.C., P.V. and F.A. P.M. provided advice for conditional analysis.

Corresponding authors

Correspondence to Ferhat Ay or Pandurangan Vijayanand.

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Extended data

Extended Data Fig. 1 Active cis-regulatory interaction maps in human immune cell types from DICE, Related to Fig. 1.

a, The number of H3K27ac ChIP-seq peaks detected in each cell type (left panel); center and right panel shows number of significant cis-regulatory interactions using two different background models (FitHiChIP-L and FitHiChIP-S, see Methods) from 70 million unique paired-end reads for each type. b, Correlation of log transformed HiChIP contact counts for assessing the reproducibility between two replicates of the same donor for naïve CD4+ T cells (top, n=3) and for classical monocytes (bottom, n=3). c, The distribution of genome-wide interaction distances for active cis-regulatory elements in each cell type. d, Percentage of all H3K27ac peaks with long-range (>10 Kb) interactions (FitHiChIP-L and FitHiChIP-S) identified using two different background models.

Extended Data Fig. 2 Promoter interacting eQTLs, Related to Fig. 2.

a, Pearson correlations of TPM counts between expression quantification methods applied to naïve CD4+ T cell RNA-seq data for nine HLA genes. Blue lines indicate linear regression between TPM counts. Gray shaded areas indicate 95% confidence intervals. b, Total number of HLA eGenes (left panel), eQTLs (middle panel) and eGene-eQTL pairs (right panel) in initial DICE study and with our revised HLA analysis using the HLApers pipeline (see Supplementary Methods). c, Total count of GWAS-pieQTLs and their percentage among all eQTLs and pieQTLs in each cell type. d, Percentage of all eQTLs (left panel) and GWAS-eQTLs (right panel) that are pieQTLs.

Extended Data Fig. 3 Conditional analysis of eQTLs, Related to Fig. 2.

a, Percentage of eGenes with pieQTLs that has no significant SNP in the second iteration of conditional analysis. b, Percentage of eGenes with pieQTLs that has a pieQTL or a promoter eQTL as the top conditionally independent SNP in any iteration. c, Distribution of LD values (R2) for promoter eQTLs and pieQTLs (the highest value per gene for each) with respect to the lead SNPs of conditional analysis in the first (E1 - upper panel) or the second (E2 - bottom panel) iteration for different cell types. d, Percentage of eGenes with pieQTLs that have at least one pieQTL or a promoter eQTL in strong LD (R2>0.8) with top conditionally independent SNP in any iteration. e, Percentage of eGenes with pieQTLs for which no SNP remains significant in conditional analysis after removing the effect of the top pieQTL. f, Percentage of eGenes with pieQTLs where promoter eQTL remains significant (that is, conditionally independent) after removing the effect of the top pieQTL in the conditional analysis.

Extended Data Fig. 4 Validation of Promoter interacting eQTLs, Related to Fig. 2.

a, Number of computationally fine-mapped eQTLs in different cell types, and the percentage of them located in genomic regions with H3K27ac peaks. b, Percentage of genetic variants deemed to have genotype-dependent enhancer activity (at different FDR thresholds) in lymphoblastoid B cell lines by MPRA assay among the pieQTLs from naïve B cells, pieQTLs that are specific to classical monocytes as well as among distal eQTLs (>10Kb from TSS) from both cell types. c, Left panels, mean expression levels (TPM) of CBR3, HEATR3, SMDT1 and XRRA1, eGenes in naïve CD4+ T cells from subjects (n>85) categorized based on the genotype at the indicated pieQTL; each symbol represents an individual subject; * adj. association P value < 0.05, calculated by Benjamini-Hochberg method. Middle panel, WashU Epigenome browser tracks for the extended CBR3, HEATR3, SMDT1 and XRRA1 locus, adj. association P value for naïve CD4+ T cells eQTLs linked to respective gene expression, H3K27ac ChIP-seq tracks, and HiChIP interactions for the indicated gene locus. Right panels, real-time PCR quantification of respective gene transcript levels (relative to the housekeeping gene YWHAZ) in Jurkat cells 48 hour after CRISPRi-mediated silencing of indicated enhancer (n=3). d, Real-time PCR quantification of GAB2 transcript levels (relative to the housekeeping gene YWHAZ) in GM12878 cells 48 hours after CRISPRi-mediated silencing of indicated enhancers (E1, E2, E3 and E2-E3 combined) with two independent crRNAs (cr1 and cr2); bar graph shows the percentage reduction in GAB2 transcript levels compared to control guide RNA, each dot represents an independent assay (n=3).

Extended Data Fig. 5 HiChIP-based eQTL discovery, Related to Fig. 3.

a, Distribution of interaction distances between promoters and cis-regulatory elements, right panel shows the number of promoters that have a statistically significant interaction (FitHiChIP-L) with cis-regulatory elements located >1 Mb to <10 Mb distance away. b, The number of ultra-long pieQTLs and eGenes identified by HiChIP-based eQTL discovery method in different cell types. c, Pie chart (left panel) shows the proportion of new eGenes that are shared among varying number of cell types and Venn diagram shows their cell type specificity (right panel). d, Percentage of previously identified eGenes7 with ultra-long pieQTLs (as mapped here) that have any such ultra-long pieQTL in LD (R2>0.8) with any eQTL within 1Mb of TSS. e, Number of new GWAS eQTLs identified by HiChIP-based eQTL discovery method in different cell types. Right panel, pie chart (bottom) shows the proportion of new GWAS eQTLs that are shared among varying number of cell types and Venn diagram (top) shows their cell type specificity.

Extended Data Fig. 6 HiChIP-based eQTL discovery prioritizes the testing of ultra-long distance genetic variants with more significant associations to target gene expression, Related to Fig. 3.

Distribution of eQTL association P values in each cell type for SNPs tested in our ultra-long pieQTL discovery method (that is, overlapping promoter interacting regulatory regions within 1 Mb to 10 Mb of the TSS), and for genomic distance-matched set of SNPs either randomly sampled or sampled from H3K27ac peak-overlapping regions. All association P values were computed using MatrixEQTL package as described in Methods. Two-sided Wilcoxon rank-sum test was used to determine the significance of difference between a pair of distributions (** indicates P value < 1e-6).

Extended Data Fig. 7 Validation of ultra-long pieQTL, Related to Fig. 3.

a, WashU Epigenome browser tracks for the extended NPIPB15 locus and H3K27ac ChIP-seq tracks for the indicated locus. Bottom left panel, mean expression levels (TPM) of NPIPB15, eGenes in naïve B cells from subjects (n=91) categorized based on the genotype at the indicated cis-eQTL; each symbol represents an individual subject; * adj. association P value: 0.007, calculated by Benjamini-Hochberg method. Bottom right panel, real-time PCR quantification of NPIPB15 transcript levels (relative to the housekeeping gene YWHAZ) in GM12878 cells 48 hour after CRISPRi-mediated silencing of indicated enhancer (n=3). b, WashU Epigenome browser tracks for the extended TSPO locus and H3K27ac ChIP-seq tracks for the indicated locus. Bottom left panel, mean expression levels (TPM) of TSPO, eGenes in naïve B cells from subjects (n=86) categorized based on the genotype at the indicated cis-eQTL; each symbol represents an individual subject; * adj. association P: 0.03, calculated by Benjamini-Hochberg method. Bottom right panel, real-time PCR quantification of TSPO transcript levels (relative to the housekeeping gene YWHAZ) in GM12878 cells 48 hours after CRISPRi-mediated silencing of indicated enhancer (n=3). c, CRISPR-mediated homology-directed recombination (HDR) in primary human T cells from a donor homozygous for the rs11130745G/G allele for the FHIT-related 1.2 Mb away ultra-long pieQTL. The sanger sequencing result of CRISPR-mediated genome editing of rs11130745G/G allele to rs11130745A/A allele with a deletion of the adjacent 3 bp PAM sequence by three independent methods using control RNA, sgRNA and crRNA is shown.

Extended Data Fig. 8 Non-transcribed promoters that function as potential enhancers, Related to Fig. 4.

a, Left panels, WashU Epigenome browser tracks for the extended TMBIM4 locus, H3K27ac ChIP-seq tracks and HiChIP interactions in naïve B cells. Target promoter is highlighted in salmon color and other interacting cis-regulatory elements (promoter and enhancers) are highlighted in grey color. Right panels, Percentage of chromatin interactions belonging to each biotype. b, Left panels, WashU Epigenome browser tracks for H3K27ac ChIP-seq tracks, and HiChIP interactions of the extended AXDND1 and UMODL1 locus for naïve CD4+ T cells; FEM1A and GTSE1 locus for naïve B cells. Right panels, real-time PCR quantification of respective gene transcript levels (relative to the housekeeping gene YWHAZ) in Jurkat cells or GM12878 cells 48 hour after CRISPRi-mediated silencing of indicated enhancer (n=3).

Extended Data Fig. 9 Properties of non-transcribed promoters that function as potential enhancers, Related to Fig. 4.

Enrichment heatmap (upper panel) and distribution frequency (bottom panel) of H3K27ac, H3K27me3, H3K4me3, H3K9me3, H3K36me3 and H3K4me1 modifications centered on TSS + 5 Kb for non-transcribed promoters, transcribed promoters and enhancers with interactions. ChIP-seq bigwig tracks of the histone marks H3K27me3, H3K36me3, H3K4me1, H3K4me3, and H3K9me3 were downloaded from the IHEC data portal (https://epigenomesportal.ca/ihec/grid.html?build=2017-10&assembly=1&cellTypeCategories=1).

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Chandra, V., Bhattacharyya, S., Schmiedel, B.J. et al. Promoter-interacting expression quantitative trait loci are enriched for functional genetic variants. Nat Genet 53, 110–119 (2021). https://doi.org/10.1038/s41588-020-00745-3

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