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HiChIRP reveals RNA-associated chromosome conformation

Abstract

Modular domains of long non-coding RNAs can serve as scaffolds to bring distant regions of the linear genome into spatial proximity. Here, we present HiChIRP, a method leveraging bio-orthogonal chemistry and optimized chromosome conformation capture conditions, which enables interrogation of chromatin architecture focused around a specific RNA of interest down to approximately ten copies per cell. HiChIRP of three nuclear RNAs reveals insights into promoter interactions (7SK), telomere biology (telomerase RNA component) and inflammatory gene regulation (lincRNA-EPS).

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Data availability

Raw and processed data are available at NCBI Gene Expression Omnibus, accession number GSE115524.

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Acknowledgements

We thank members of the Chang and Greenleaf laboratories for helpful discussions, and J. Tumey for artwork. We thank Jena Biosciences for design and synthesis of the 5-azido-PEG4-dCTP nucleotide. We thank X. Ji and J. Coller at the Stanford Functional Genomics Facility. This work was supported by National Institutes of Health (NIH) grants (no. P50-HG007735 to H.Y.C. and W.J.G.; no. R35-CA209919 to H.Y.C.; no. U19-AI057266 to W.J.G.; no. K08CA23188-01 to A.T.S.); the Human Frontier Science Program (to W.J.G.); the Rita Allen Foundation (W.J.G.); and the Scleroderma Research Foundation (H.Y.C). M.R.M. acknowledges support from the National Science Foundation Graduate Research Fellowship. A.T.S. was supported by a Parker Bridge Scholar Award from the Parker Institute for Cancer Immunotherapy, a Career Award for Medical Scientists from the Burroughs Wellcome Fund and the Human Vaccines Project Michelson Prize for Human Immunology and Vaccine Research. M.R.C. is supported by a grant from the Leukemia & Lymphoma Society Career Development Program. W.J.G. is a Chan Zuckerberg Biohub investigator. Sequencing was performed by the Stanford Functional Genomics Facility (NIH grant no. S10OD018220). H.Y.C. is an Investigator of the Howard Hughes Medical Institute.

Author information

M.R.M., J.M.G., R.A.F. and H.Y.C. developed the method. M.R.M., J.M.G., R.A.F., S.S., B.H.L., J.K.G., D.G.G. and M.R.C. performed experiments. M.K.A., A.T.S., Y.Q. and Z.J. cultured bone-marrow-derived macrophages. C.M.R. generated TERC knockout cell lines. J.M.G., M.R.M. and A.J.R. analyzed HiChIRP and HiChIP datasets. M.R.M., J.M.G., W.J.G. and H.Y.C. wrote the manuscript with input from all authors.

Correspondence to William J. Greenleaf or Howard Y. Chang.

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Competing interests

H.Y.C. has affiliation with Accent Therapeutics (Founder, SAB), 10X Genomics (SAB) and Spring Discovery (SAB). W.J.G. has affiliation with 10X Genomics (SAB) and Guardant Health (Consultant).

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Integrated supplementary information

Supplementary Fig. 1 Applications of the HiChIRP 3C protocol to HiChIP of CTCF and Oct4.

a, Streptavidin dot blot to test for biotin or azido incorporation in a 3C library (n = 2). F = formaldehyde, G = glutaraldehyde, bA = biotin-14-dATP, aA = N6-(6-Azido)hexyl-dATP, and aC = 5-azido-PEG4-PAdCTP. b, Percentage of cis short (< 20 kb), cis long, and trans contacts for CTCF and Oct4 HiChIP using the standard 3C protocol and modified HiChIRP (HC) 3C conditions. c, HC 3C versus 3C differential interaction heatmaps. d, metav4C visualization of Oct4 HiChIP using 3C and HC 3C protocols as well as Hi-C on all loops containing an Oct4 ChIP peak (n = 2; mean and standard deviation shading). e, Virtual 4C visualizations of Oct4 HiChIP using 3C and HC 3C protocols as well as Hi-C (n = 2; mean and standard deviation shading).

Supplementary Fig. 2 Quality metrics of HiChIRP libraries.

a, Proportion of the target RNA and negative control RNAs recovered post HiChIRP relative to the input by qRT-PCR (n = 4; mean with standard deviation). b, Total number of reads sequenced and unique contacts from HiC-Pro for all HiChIRP libraries and their corresponding negative controls. c, HiChIRP loop filtering strategy. (Left) Removal of HiChIRP loops lower in signal than a background anchor permuted loop set across both replicates. (Right) Removal of HiChIRP loops significantly (FDR < 0.1) higher in RNase control signal over a background anchor permuted loop set. d, Replicate signal reproducibility at loop calls (n = 5508, 3182, 3029 from top to bottom). e, Aggregate Peak Analysis of loops for the 7SK, TERC, and lincRNA-EPS HiChIRP libraries.

Supplementary Fig. 3 7SK HiChIRP enriches for promoter-centric chromosome conformation.

a, Pearson signal correlation at 7SK HiChIRP loop calls (n = 5508) between 7SK HiChIRP experiments with distinct even and odd probe sets. b, Library gel of a 7SK HiChIRP experiment and it’s corresponding RNase background interaction control. c, (Left) Loop overlap between 7SK HiChIRP and published mES Hi-C datasets. (Right) Differential signal analysis by edgeR of the union set of loops between 7SK HiChIRP and Hi-C. d, metav4C visualization of 7SK HiChIRP, H3K27ac HiChIP, and Hi-C signal at 7SK HiChIRP-enriched loops (n = 2; mean and standard deviation shading). e, Aggregate Peak Analysis of Hi-C signal at 7SK HiChIRP-enriched loops. f, metav4C visualization of 7SK HiChIRP, H3K27ac HiChIP, and Hi-C signal at 7SK HiChIRP-depleted loops (n = 2; mean and standard deviation shading). g, Overlap of 7SK HiChIRP-enriched and depleted loops with 7SK HiChIRP interactions called by FitHiChIP. h, 7SK ChIRP-seq signal within 7SK HiChIRP-enriched (n = 2421) and depleted (n = 3794) loop anchors. Box is median with quartiles and significance (p < 2.2x10−16) was assessed using a Kolmogorov-Smirnov test. i, Loop length distributions of 7SK HiChIRP-enriched (n = 2421) and depleted (n = 3794) loop sets. Box is median with quartiles and significance (p < 2.2x10−16) was assessed using a Kolmogorov-Smirnov test. j, chromHMM annotation of 7SK HiChIRP-enriched and depleted (Hi-C) loops as well as background annotations (shuffling bed annotations genome-wide 100 times; scales are matched). For each loop set, each anchor was first intersected with chromHMM annotations and then the fraction of total loops containing an annotation in one anchor and an annotation in the second anchor is shown. k, Virtual 4C visualization of 7SK HiChIRP signal depletion at a loop with no gene activity (n = 2; mean and standard deviation shading). l, metav4C visualization of 7SK HiChIRP, H3K27ac HiChIP, and Hi-C signal at all loops containing a 7SK ChIRP peak within a loop anchor, a Pol II ChIP peak within a loop anchor, and all loops containing no active marks within their loop anchors (n = 2; mean and standard deviation shading).

Supplementary Fig. 4 HiChIRP of TERC reveals enrichment of telomeric and subtelomeric chromosome regions.

a, Genotyping of the TERC locus in TERC knockout clones and wild-type parental lines (n = 2). b, TERC expression relative to the wild-type parental lines in the TERC knockout clones by qRT-PCR (n = 3; mean with standard deviation). For the no RT negative control, no reverse transcriptase was added. c, Telomere repeat sequence enrichment over the 95th percentile of a permuted set of background sequences (nucleotide content maintained) in TERC HiChIRP relative to its knockout and RNase controls as well as GM12878 Hi-C (n = 2; mean is denoted as the line). d, Distance to the nearest chromosome end for non-telomeric reads that are interacting with telomeric repeats. Pearson correlation between biological replicates (n = 2). e, Read distribution changes across all chromosomes in TERC HiChIRP and published GM12878 Hi-C experiments (n = 2; mean and standard deviation shading). f, Top TERC HiChIRP interactions with the chromosome 14q subtelomeric region containing the IGH locus. Pearson correlation between biological replicates (n = 2) and with published GM12878 Hi-C.

Supplementary Fig. 5 HiChIRP of TERC identifies non-canonical enhancer–promoter looping at oncogenes.

a, (Left) Loop overlap between TERC HiChIRP and Hi-C datasets. (Right) Differential signal analysis by edgeR of the union set of loops between TERC HiChIRP and Hi-C. b, metav4C visualization of TERC HiChIRP and Hi-C signal at TERC HiChIRP-enriched and depleted loops (n = 2; mean and standard deviation shading). c, Aggregate Peak Analysis of Hi-C signal at TERC HiChIRP-enriched loops. d, Overlap of TERC HiChIRP-enriched and depleted loops with TERC HiChIRP interactions called by FitHiChIP. e, chromHMM annotation of TERC HiChIRP-enriched and depleted (Hi-C) loops as well as background annotations (shuffling bed annotations genome-wide 100 times). For each loop set, each anchor was first intersected with chromHMM annotations and then the fraction of total loops containing an annotation in one anchor and an annotation in the second anchor is shown. f, (Top) Loop length distributions of TERC HiChIRP-enriched (n = 794) and depleted (n = 770) loop sets. Box is median with quartiles and significance (p < 2.2x10-16) was assessed using a Kolmogorov-Smirnov test. (Bottom) TERC ChIRP-seq signal within TERC HiChIRP-enriched (n = 794) and depleted (n = 770) loop anchors. Box is median with quartiles and significance (p < 2.2x10-16) was assessed using a Kolmogorov-Smirnov test. g, Virtual 4C visualization of TERC HiChIRP signal depletion at a loop with no gene activity (n = 2; mean and standard deviation shading).

Supplementary Fig. 6 lincRNA-EPS HiChIRP captures interactions between domain boundaries and immune response genes.

a, (Left) Loop overlap between lincRNA-EPS HiChIRP and Hi-C datasets. (Right) Differential signal analysis by edgeR of the union set of loops between lincRNA-EPS HiChIRP and Hi-C. b, metav4C visualization of lincRNA-EPS HiChIRP and Hi-C signal at lincRNA-EPS HiChIRP-enriched loops (n = 2; mean and standard deviation shading). c, Aggregate Peak Analysis of Hi-C signal at lincRNA-EPS HiChIRP-enriched loops. d, metav4C visualization of lincRNA-EPS HiChIRP and Hi-C signal at lincRNA-EPS HiChIRP-depleted loops (n = 2; mean and standard deviation shading). e, Overlap of lincRNA-EPS HiChIRP-enriched and depleted loops with lincRNA-EPS HiChIRP interactions called by FitHiChIP. f, chromHMM annotation of lincRNA-EPS HiChIRP-enriched and depleted (Hi-C) loops as well as background annotations (shuffling bed annotations genome-wide 100 times; scales are matched). For each loop set, each anchor was first intersected with chromHMM annotations and then the fraction of total loops containing an annotation in one anchor and an annotation in the second anchor is shown. g, lincRNA-EPS ChIRP-seq signal within lincRNA-EPS HiChIRP-enriched (n = 543) and depleted (n = 650) loop anchors. Box is median with quartiles and significance (p < 2.2x10-16) was assessed using a Kolmogorov-Smirnov test. h, lincRNA-EPS 1D signal at gene promoters repressed by lincRNA-EPS (n = 218), promoters activated by lincRNA-EPS (n = 60), active Ensembl TSS (n = 25695), and all Ensembl TSS (n = 131063). Box is median with quartiles and significance (p = 0.0002 between repressed and active) was assessed using a Kolmogorov-Smirnov test. i, metav4C visualization of lincRNA-EPS HiChIRP and Hi-C signal at interactions between lincRNA-EPS repressed gene promoters and CTCF (n = 2; mean and standard deviation shading). j, Virtual 4C visualization of lincRNA-EPS HiChIRP signal depletion at an enhancer-enhancer loop outside of a promoter or boundary region (n = 2; mean and standard deviation shading). k, Pearson correlogram of lincRNA-EPS HiChIRP library replicates with lincRNA-EPS WT and KO HiChIP of SMC1a and H3K27ac. l, Proposed mechanism of lincRNA-EPS regulation, where lincRNA-EPS exploits existing chromatin architecture at topological domain boundaries to regulate target immune response genes.

Supplementary information

Supplementary Information

Supplementary Figs. 1–6 and Supplementary Note 1

Reporting Summary

Supplementary Protocol

Supplementary Table 1

HiChIRP and HiChIP data processing metrics

Supplementary Table 2

HiCCUPS high-confidence loop calls

Supplementary Table 3

HiCCUPS differential looping by edgeR

Supplementary Table 4

HiChIRP interactions identified by FitHiChIP

Supplementary Table 5

Probe and primer oligonucleotide sequences

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Fig. 1: HiChIRP enables RNA-centric chromosome conformation associated with 7SK.
Fig. 2: HiChIRP of TERC and low-abundance lincRNA-EPS.
Supplementary Fig. 1: Applications of the HiChIRP 3C protocol to HiChIP of CTCF and Oct4.
Supplementary Fig. 2: Quality metrics of HiChIRP libraries.
Supplementary Fig. 3: 7SK HiChIRP enriches for promoter-centric chromosome conformation.
Supplementary Fig. 4: HiChIRP of TERC reveals enrichment of telomeric and subtelomeric chromosome regions.
Supplementary Fig. 5: HiChIRP of TERC identifies non-canonical enhancer–promoter looping at oncogenes.
Supplementary Fig. 6: lincRNA-EPS HiChIRP captures interactions between domain boundaries and immune response genes.