SPATIAL EPIGENOMICS
Spatial-CUT&Tag: Spatially resolved chromatin
modification profiling at the cellular level
Yanxiang Deng1,2, Marek Bartosovic^3 , Petra Kukanja^3 , Di Zhang^1 , Yang Liu1,2, Graham Su1,2,
Archibald Enninful1,2, Zhiliang Bai^1 , Gonçalo Castelo-Branco3,4, Rong Fan1,2,5*
Spatial omics emerged as a new frontier of biological and biomedical research. Here, we present
spatial-CUT&Tag for spatially resolved genome-wide profiling of histone modifications by combining in
situ CUT&Tag chemistry, microfluidic deterministic barcoding, and next-generation sequencing. Spatially
resolved chromatin states in mouse embryos revealed tissue-type-specific epigenetic regulations in
concordance with ENCODE references and provide spatial information at tissue scale. Spatial-CUT&Tag
revealed epigenetic control of the cortical layer development and spatial patterning of cell types
determined by histone modification in mouse brain. Single-cell epigenomes can be derived in situ by
identifying 20-micrometer pixels containing only one nucleus using immunofluorescence imaging. Spatial
chromatin modification profiling in tissue may offer new opportunities to study epigenetic regulation,
cell function, and fate decision in normal physiology and pathogenesis.
C
hromatin state determines genome
function and is regulated in a cell-type-
specific manner ( 1 , 2 ). Despite recent
breakthroughs in single-cell sequenc-
ing ( 3 – 5 ) that have enabled the profil-
ing of the epigenome in single cells ( 6 – 11 ), it
remains challenging to integrate the spatial
information of individual cells in the tissue of
origin. Here, we report spatial-CUT&Tag for
spatial histone modification profiling, which
combines in-tissue deterministic barcoding
( 12 , 13 ) with the cleavage under targets and
tagmentation (CUT&Tag) chemistry ( 14 , 15 )
(Fig. 1A and fig. S1). First, antibody against
the target histone modification was added to
a fixed tissue section, followed by a secondary
antibody binding to enhance the tethering
of pA-Tn5 transposome. After activating the
transposome, adapters containing a ligation
linker were inserted to genomic DNA at the
histone mark antibody recognition sites. Next,
a set of DNA barcode solutions Ai(i= 1 to 50)
were flowed over the tissue surface through
microchannel-guided delivery to perform
in situ ligation to the adapters. Next, a second
set of barcodes Bj(j=1to50)wereflowedover
the same tissue surface through microchannels
perpendicular to those in the first barcoding
step. These barcodes were then ligated at the
intersections, resulting in a two-dimensional
(2D) grid of tissue pixels, each of which con-
tains a distinct combination of barcodes Ai
and Bj(i= 1 to 50,j= 1 to 50). The tissue
section was imaged after these steps to corre-
late the tissue morphology with the spatial
epigenomics map. Finally, DNA fragments
were collected by cross-link reversal to com-
plete library construction (see the supplemen-
tary materials and methods).
We performed spatial-CUT&Tag with anti-
bodies against H3K27me3 (repressing loci),
H3K4me3 (activating promoters), and H3K27ac
(activating enhancers and/or promoters) in
embryonic day 11 (E11) mouse embryos. With
50-mmpixelsize,weobtainedamedianof
9788 (H3K27me3), 16,777 (H3K4me3), or 19,721
(H3K27ac) unique fragments per pixel, of which
16% (H3K27me3), 67% (H3K4me3), or 16%
(H3K27ac) of fragments fell within peak re-
gions, indicating high coverage and low back-
ground [as a reference, the fraction of reads in
peaks (FRiP) of bulk CUT&Tag of E11 mouse
embryo with H3K27me3 was ~24%] (Fig. 1, B
and C). In addition, the proportion of mito-
chondrial fragments is low [a median of
0.16% (H3K27me3), 0.13% (H3K4me3), or
0.01% (H3K27ac) of fragments was from mito-
chondrial reads] (Fig. 1D). With a 20-mm pixel
size (cellular level), we obtained a median
of 10,064 (H3K27me3), 7310 (H3K4me3), or
13,171 (H3K27ac) unique fragments per pixel,
of which 20% (H3K27me3), 37% (H3K4me3),
or 12% (H3K27ac) of fragments fell within
peak regions (Fig. 1, B and C). The fractions
of read-pairs mapping to mitochondria were
0.01% (H3K27me3), 0.02% (H3K4me3), or 0%
(H3K27ac) (Fig. 1D). Additionally, the frag-
ment length distribution was consistent with
the capture of nucleosomal and subnucleo-
somal fragments (the subnucleosomal frag-
ments may represent background signal from
untethered Tn5) (fig. S2). To measure the ex-
tent of tagmentation by free Tn5, we compared
the spatial-CUT&Tag H3K27me3 signals with
reference chromatin immunoprecipitation se-
quencing (ChIP-seq) and assay for transposase-accessible chromatin using sequencing (ATAC-
seq) ( 2 ). The results showed that ~11.5% of
peaks that did not overlap with ChIP-seq
were observed in ATAC-seq (fig. S3), which
may correspond to the Tn5 insertion events
unrelated to the histone mark ( 16 ).
We compared spatial-CUT&Tag at the 20-mm
pixel size with published single-cell CUT&Tag
(scCUT&Tag) also on mouse brain at the same
sequencing depth ( 8 ) and found that spatial-
CUT&Tag detected more unique fragments
(H3K27me3: 9735; H3K4me3: 3686) than
scCUT&Tag (H3K27me3: 682; H3K4me3: 453)
(Fig. 1B). We also isolated tissue pixels con-
taining single nuclei that showed similar unique
fragment counts compared with scCUT&Tag.
However, the FRiP from spatial-CUT&Tag
(H3K27me3: 10%; H3K4me3: 53%) was lower
than that from scCUT&Tag (H3K27me3: 24%;
H3K4me3: 82%) (Fig. 1C), presumably because
of the use of frozen sections, which has been
reported to affect chromatin structures and
generate higher background noise ( 17 ).
The Pearson correlation coefficient from dif-
ferent spatial-CUT&Tag experiments was >0.95
(fig. S4, A to F), demonstrating a high degree
of reproductivity. Spatial-CUT&Tag also repro-
duced the chromatin state pattern and peaks
(fig. S4, G to I). Furthermore, the peaks called
from spatial-CUT&Tag aggregate data were
consistent with the ENCODE ChIP-seq data
(fig. S5A). Spatial-CUT&Tag also yielded high-
quality profiles in the liver comparable to the
reference data (fig. S5B).
Cell types were identified de novo by chro-
matin states. Mapping the clusters back to
spatial locations identified spatially distinct
patterns that agreed with the tissue histology
in a hematoxylin and eosin (H&E)–stained
adjacent tissue section (Fig. 1, E to G, and fig.
S6). Cluster 1 of H3K27me3 and cluster 6 of
H3K4me3 correspond to the heart; cluster 2
of H3K27me3 and H3K4me3 and cluster 4
of H3K27ac correspond to the liver region;
cluster 8 of H3K27me3, cluster 3 of H3K4me3,
and cluster 1 of H3K27ac correspond to the
forebrain; cluster 9 of H3K27me3, cluster 5 of
H3K4me3, and cluster 3 of H3K27ac corre-
spond to the brainstem, including the mid-
brain; and cluster 11 of H3K27me3, cluster 8
of H3K4me3, and cluster 2 of H3K27ac cor-
respond to the more posterior regions of
the central nervous system (CNS) such as the
spinal cord.
To benchmark spatial-CUT&Tag, we pro-
jected the organ-specific ChIP-seq data onto
our uniform manifold approximation and pro-
jection (UMAP) embedding ( 2 , 18 ). Overall,
cluster identification matched well with the
ChIP-seq projection (Fig. 1, G and H) and dis-
tinguished major cell types in E11 mouse em-
bryo. To identify spatial patterning during
development, we examined cell-type-specific
marker genes. For H3K27me3, the chromatinSCIENCEscience.org 11 FEBRUARY 2022•VOL 375 ISSUE 6581 681
(^1) Department of Biomedical Engineering, Yale University, New
Haven, CT 06520, USA.^2 Yale Stem Cell Center and Yale
Cancer Center, Yale School of Medicine, New Haven, CT
06520, USA.^3 Laboratory of Molecular Neurobiology,
Department of Medical Biochemistry and Biophysics,
Karolinska Institutet, 17177 Stockholm, Sweden.^4 Ming Wai
Lau Centre for Reparative Medicine, Karolinska Institutet,
17177 Stockholm, Sweden.^5 Human and Translational
Immunology Program, Yale School of Medicine, New Haven,
CT 06520, USA.
*Corresponding author. Email: [email protected]
RESEARCH | REPORTS