(2024) 22:36
Öling et al. BMC Biology
https://doi.org/10.1186/s12915-024-01812-5

RESEARCH ARTICLE

BMC Biology

Open AccessA human stomach cell type transcriptomeatlas
S. Öling1, E. Struck1, M. Noreen‑Thorsen1, M. Zwahlen2, K. von Feilitzen2, J. Odeberg1,2,3,4, F. Pontén5,
C. Lindskog5, M. Uhlén2, P. Dusart2,6,7 and L. M. Butler1,2,6,7*   

Abstract
Background The identification of cell type-specific genes and their modification under different conditions is central
to our understanding of human health and disease. The stomach, a hollow organ in the upper gastrointestinal tract,provides an acidic environment that contributes to microbial defence and facilitates the activity of secreted digestive
enzymes to process food and nutrients into chyme. In contrast to other sections of the gastrointestinal tract, detailed
descriptions of cell type gene enrichment profiles in the stomach are absent from the major single-cell sequencingbased atlases.
Results Here, we use an integrative correlation analysis method to predict human stomach cell type transcriptome
signatures using unfractionated stomach RNAseq data from 359 individuals. We profile parietal, chief, gastric mucous,
gastric enteroendocrine, mitotic, endothelial, fibroblast, macrophage, neutrophil, T-cell, and plasma cells, identifying
over 1600 cell type-enriched genes.
Conclusions We uncover the cell type expression profile of several non-coding genes strongly associatedwith the progression of gastric cancer and, using a sex-based subset analysis, uncover a panel of male-only chief cellenriched genes. This study provides a roadmap to further understand human stomach biology.
Keywords Cell profiling, Gene enrichment, Bulk RNAseq, Stomach*Correspondence:
L. M. Butler
Lynn.butler@ki.se
1
Department of Clinical Medicine, Translational Vascular Research, The
Arctic University of Norway, 9019 Tromsø, Norway
2
Science for Life Laboratory, Department of Protein Science, RoyalInstitute of Technology (KTH), 171 21 Stockholm, Sweden
3
The University Hospital of North Norway (UNN), 9019 Tromsø, Norway
4
Department of Haematology, Coagulation Unit, Karolinska University
Hospital, 171 76 Stockholm, Sweden
5
Department of Immunology, Genetics and Pathology, Science for Life
Laboratory, Uppsala University, 752 37 Uppsala, Sweden
6
Clinical Chemistry and Blood Coagulation Research, Departmentof Molecular Medicine and Surgery, Karolinska Institute, 171
76 Stockholm, Sweden
7
Clinical Chemistry, Karolinska University Laboratory, Karolinska University
Hospital, 171 76 Stockholm, Sweden

BackgroundThe gastrointestinal (GI) tract is a multiple organ system which can be divided into upper and lower parts,
the physical properties and cellular characteristics ofwhich reflect their different roles in digestion, absorption of nutrients, and excretion of waste products [1–3].
The stomach, a hollow muscular organ in the upper GI
tract, produces an array of acids and gastric enzymes, acting as a reservoir for the mechanical and chemical digestion of ingested food [4]. The constituent cell types of thestomach include parietal cells, chief cells, gastric mucous
cells, gastric enteroendocrine cells, mitotic cells, endothelial cells, fibroblasts, and various immune cells [5, 6]. In
contrast to lower sections of the GI tract, descriptions of
the cellular transcriptional landscape in the stomach arelacking, with this organ absent from large-scale single-cellsequencing (scRNAseq) initiatives, such as Tabula Sapiens© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to theoriginal author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images orother third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line
to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of thislicence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. The Creative Commons Public Domain Dedication waiver (http://​creat​iveco​
mmons.​org/​publi​cdoma​in/​zero/1.​0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Öling et al. BMC Biology(2024) 22:36[7] and the Human Cell Atlas [8]. Where scRNAseq has
been used to profile gene expression in the adult stomach, studies have typically focused on specific cell types,
such as the epithelia [9, 10], or in pathological statessuch as gastric cancer [11–14]. Whilst scRNAseq studies
provide high resolution of individual cell (sub)type gene
expression profiles, challenges remain, including artefactual modification of gene expression due to cell removal
and processing [15–17], compromised read depth, anddifficulties with data interpretation [18, 19]. As a limited
number of biological replicates are typically analysed,
underestimation of biological variance can increase thelikelihood of potential false discoveries [20, 21].
Non-coding RNA is emerging as a novel, important class of molecules, involved in the maintenance of
healthy stomach tissue and the development and progression of gastric cancer [22, 23], but to date, there is no
overall description of stomach cell type-enriched noncoding RNAs.
Here, we analysed 359 bulk RNAseq human stomach samples to identify over 1600 genes with cell typeenriched expression, using our previously developed
integrative correlation analysis [24–26]. Gastric mucous
cells had the highest number of predicted protein-coding
and non-coding enriched genes and represented the primary site of expression of genes that were tissue enrichedin the stomach over other tissue types. Gastric enteroendocrine cells expressed a panel of non-coding genes thatare also selectively expressed in pancreatic and intestinal
endocrine cells, indicating a common function in thesecell types. Several of the identified cell type-enriched
non-coding genes have previously been associated withthe progression of gastric cancer, but until now, the cell
type site of expression had not been described. Sex subset analysis revealed a high global similarity in cell typetranscriptomes between males and females, but a panelof chief cell-enriched Y-linked genes were identified.
Data is available through the Human Protein Atlas (HPA)
portal (www.​prote​inatl​as.​org/​human​prote​ome/​tissue+​cell+​type/​stoma​ch).

Results
Identification of cell type transcriptome profiles in stomach
Cell type reference transcripts correlate across unfractionatedRNAseq data

To identify stomach cell type-enriched transcriptome
profiles, we conducted an analysis based on our previously developed method [24–26], using human stomachbulk RNAseq data (N = 359) from the Genotype-Tissue
Expression (GTEx) portal V8 [27] (see Additional file 1:
Fig. S1 for the method overview). Each sample was
unfractionated and thus contained a mix of cell types(Fig. 1A.i), which contribute differing proportions ofPage 2 of 21

transcripts subsequently measured by RNAseq (Fig. 1A.
ii) (Additional file 1: Fig. S1A). For each major constituent stomach cell type, candidate cell type-specific genes(termed ‘reference transcripts’ [Ref.T.]) were selectedbased on (i) our in-house proteomic profiling of stomach tissue [5, 6], (ii) older ‘none-omics’ studies [28], (iii)
scRNAseq data were available [9, 29], or (iv) databases
collated from multiple sources, e.g. Cell Marker [30]and PanglaoDB [31] (Fig. 1B and Additional file 1: Fig.
S1B). Three markers were selected for each cell type,based on the following criteria: (i) a high corr. (> 0.85)
between Ref.T. within each cell type panel (Fig. 1C and
Additional file 2: Table S1, Tab 1), indicating cell typeco-expression: parietal cells (PAC) [ATP4B, MFSD4A,
ATP4A mean corr. ± STD 0.94 ± 0.013], chief cells (CC)
[PGC, LIPF, AZGP1, 0.89 ± 0.013], gastric enteroendocrine cells (GEEC) [ST18, INSM1, ARX, 0.89 ± 0.021],
gastric mucous cells (GMC) [LGALS4, VILL, CAPN8,
0.94 ± 0.008], mitotic cells (MTC) [NCAPG, KIFC1,
NCAPH, 0.93 ± 0.009], endothelial cells (EC) [PECAM1,
CDH5, ERG, 0.89 ± 0.013], fibroblasts (FB) [PCOLCE,
CLEC11A, MMP2, 0.87 ± 0.027], macrophages (MC)[C1QB, FCGR3A, ITGB2, 0.86 ± 0.015], neutrophils(NP) [CXCR2, FCGR3B, CXCR1, 0.86 ± 0.009], T-cells(TC) [CD3E, CD2, CD3G, 0.9 ± 0.019], and plasma cells(PC) [IGKC, JCHAIN, IGLC1, 0.97 ± 0.009]; (ii) a low
corr. between Ref.T. across the different cell type panels(Fig. 1C) (Additional file 2: Table S1, Tab 1), indicating cell
type specificity (mean inter-panel corr. ± STD 0.08 ± 0.14);
and (iii) a normal distribution of Ref.T. expression acrossthe samples (Additional file 3: Fig. S2A).
Using reference transcript analysis to identify cell
type‑enriched genes

Correlation coefficients (corr.) between each selected
Ref.T. and all other sequenced transcripts (> 56,000) were
calculated across stomach RNAseq samples (Additional
file 1: Fig. S1C). The proportion of cell types represented
in each sample varies, due to biological and sampling
variability, but ratios should remain consistent between
constitutively expressed cell-enriched genes. Thus, a highcorr. of a given transcript with all Ref.T. in only one cell
type panel is consistent with enrichment in the corresponding cell type. For each cell type, a list of enrichedgenes was generated (Fig. 1D (i–xi)), with inclusion basedon (i) the gene having a mean corr. > 0.50 with the Ref.T.
panel representing the cell type (Additional file 1: Fig.
S1C.ii) and (ii) a differential correlation between thisvalue and the maximum mean corr. with any other Ref.T.
panel > 0.15 (Additional file 1: Fig. S1D-E). This excluded
genes that were potentially co-enriched in two or morecell types, as we previously described [26] (all data in
Additional file 2: Table S1, Tab 2). For certain cell types,

Öling et al. BMC Biology(2024) 22:36

enriched genes were less well separated by corr. valuethat others, e.g. those most highly correlating with thefibroblast Ref.T. panel (Fig. 1D (vii)) tended to show elevated corr. with the Ref.T. panel for endothelial cells, andvice versa (Fig. 1D (vi)). However, all cell type-enrichedgenes were well separated when the individual gene differential correlations vs. other Ref.T. panels were plotted(Additional file 3: Fig. S2B), and Gene Ontology (GO)and reactome analysis [32, 33] revealed over-represented
terms for these cell types were consistent with known
functions e.g. for endothelial cells most significantly
enriched terms included vascular development and angiogenesis (Fig. 1E.i), for fibroblasts extracellular matrixorganisation and collagen fibril organisation (Fig. 1E.ii),
and for T-cells T-cell activation and immune response(Fig. 1E (iii)) (Additional file 2: Table S1, Tab 8, 9 and 12).
Principal component analysis of the corr. values of cell
type-enriched genes [34] revealed the largest variancewas between stomach-specific cell types vs. stromal/vasculature-related ones (Fig. 1F).
Stomach cell type‑enriched gene signatures
The majority of stomach cell type‑enriched genes are protein
coding

A total of 1694 genes were predicted to be cell typeenriched (Fig. 2A and Additional file 2: Table S1, Tab 2).
Gastric mucous cells, plasma cells, and fibroblasts had
the highest number of predicted enriched genes (n = 517,
214, and 186, respectively) (Fig. 2A (i–iii)). Of the othercell types found in all, or most, tissue types, mitotic cells,
and macrophages had the most enriched genes (n = 171
and 158, respectively) (Fig. 1A (iv, v)). Other stomachspecialised cell types, parietal cells, chief cells, and gastricenteroendocrine cells, had significantly fewer enrichedgenes (n = 123, 103, and 86, respectively) (Fig. 2A (vi, vii,
and ix), and T-cells and neutrophils had the fewest overall(n = 24 and 20, respectively) (Fig. 2A (x, xi)). In all cases,
the majority of cell type-enriched genes were classified asprotein coding [35], with the exception of plasma cells, inwhich the immunoglobulin (IG) gene was the most common classification (Fig. 2A (ii)). Long non-coding RNA

Page 3 of 21(lncRNA) were the most common type of non-coding cell
type-enriched transcript, with the exception of plasma
cells, where IG pseudogene was the most common noncoding classification (Fig. 2A.ii).
Alternative analysis and protein profiling support cell‑typeclassifications
Unsupervised weighted network correlation analysis
is consistent with Ref.T. analysis

As our analysis is based on manually selected Ref.T. panels, cell type classification is subject to an input bias. As acomparison, we subjected the same GTEx RNAseq dataset to a weighted network correlation analysis (WGCNA)[36], an unbiased method that does not require any
manual input or marker gene selection. WGCNA generates corr. coefficients between all transcripts and subsequently clusters them into related groups, based on
expression similarity (Fig. 2B). In general, Ref.T. belonging to the same cell type panel were found in the same
WGCNA cluster (Fig. 2B (i), coloured boxes represent
the modules in which the Ref.T. appeared), e.g. gastric enteroendocrine cells (cluster 50) or clusters on thesame branch, e.g. gastric mucous cells (clusters 25 and22) and macrophages (clusters 47 and 59) (Fig. 2B (i)).
Protein coding genes that we predicted to be cell type
enriched were predominantly clustered into the same
WGCNA group as the corresponding Ref.T. but werealso frequently classified into related modules on thesame branch, consistent with our classifications (Fig. 2B(ii)). Most genes in the Ref.T. panels representing parietal and chief cells appeared in the same large group(cluster 3) (Fig. 2B (ii)), as were the genes in the respective predicted enriched gene lists, despite clear separation in our Ref.T-based method (Fig. 1C, D). Despite
the lack of separation for the enriched gene signatures
for parietal and chief cells by WGCNA, each contained
several well-described marker genes for the respective cell type, e.g. GIF, SLC26A7 (parietal) and PGA4,SLC1A2 (chief cell). Indeed, we have previously shownthat Ref.T.-based analysis can have a higher sensitivity
than WGCNA for cell type gene enrichment analysis(See figure on next page.)
Fig. 1 Integrative co-expression analysis can resolve constituent cell type identities from unfractionated human stomach tissue RNAseq data.
(A) RNAseq data for 359 unfractionated human stomach samples were retrieved from GTEx V8. Each sample contained (i) mixed cell types, which
contributed (ii) differing proportions of sequenced mRNA. (B) To profile cell type-enriched transcriptomes, constituent cell types were identified
and candidate marker genes (´reference transcripts´ [Ref.T.]) for virtual tagging of each were selected, based on in house tissue protein profiling
and/or existing literature and datasets. (C) Matrix of correlation coefficients between selected Ref.T. across the sample set. (D) Mean correlation
coefficients of genes above designated thresholds for classification as cell-type enriched in stomach: (i) parietal cells [PC], (ii) chief cells [CC], (iii)
gastric enteroendocrine cells [GEEC], (iv) gastric mucous cells [GMC], (v) mitotic cells [MTC], (vi) endothelial cells [EC], (vii) fibroblasts [FB], (viii)
macrophages [MC], (ix) neutrophils [NP], (x) T-cells [TC], (xi) plasma cells [PC] with all Ref.T. panels. (E) Over-represented gene ontology terms
among genes predicted to be: (i) endothelial cell, (ii) fibroblast or (iii) T-cell enriched. (F) Principal component analysis of correlation profiles of cell
type enriched genes. See also Table S1 Tab 1 and 2 and Figure S1 for method overview

(2024) 22:36

B

C
Ref.T.

Chief cell (CC)
Gastric enteroendocrine (GEEC)
Gastric mucous cell (GMC)
Mitotic cell (MTC)
Endothelial cell (EC)Fibroblast (FB)
Macrophage (MC)
Neutrophil (NP)T-cell (TC)
Plasma cell (PC)

0.5

0

-0.5

i. PAC

ii. CCiii. GEEC

iv. GMCv. MTCvi. EC

PAC
CC
GEEC
GMC
MTC
EC
FB
MC
NP
TC
PC

PAC
CC
GEEC
GMC
MTC
EC
FB
MC
NP
TC
PC

PAC
CC
GEEC
GMC
MTC
EC
FB
MC
NP
TC
PC

PAC
CC
GEEC
GMC
MTC
EC
FB
MC
NP
TC
PC

PAC
CC
GEEC
GMC
MTC
EC
FB
MC
NP
TC
PC

Cell type enriched transcripts

PAC
CC
GEEC
GMC
MTC
EC
FB
MC
NP
TC
PC

1.0

1.0

ATP4B
MFSD4A
ATP4A
PGC
LIPF
AZGP1
ST18
INSM1
ARX
LGALS4
VILL
CAPN8
NCAPG
KIFC1
NCAPH
PECAM1
CDH5ERG
PCOLCE
CLEC11A
MMP2
C1QB
FCGR3AITGB2
CXCR2
FCGR3B
CXCR1
CD3E
CD2
CD3G
IGKC
JCHAIN
IGLC1

Parietal cell (PAC)D

IGKC
JCHAINIGLC1

APage 4 of 21

ATP4B
MFSD4A
ATP4A
PGC
LIPF
AZGP1
ST18
I NSM1ARX
LGALS4
VILL
CAPN8
NCAPG
KIFC1
NCAPH
PECAM1
CDH5ERG
PCOLCE
CLEC11A
MMP2
C1QB
FCGR3AITGB2
CXCR2
FCGR3B
CXCR1
CD3E
CD2
CD3G

Öling et al. BMC Biologyviii. MCix. NPx. TC

0.8

vii. FB

Mean correlation

0.6
0.4
0.2
0.0

-0.2
-0.4
-0.6

-1.0

1.0

xi. PC40

Mitotic cell

0.4

20

0.2
0.0

-0.2
-0.4
-0.6

Ref.T. Panel

PAC
CC
GEEC
GMC
MTC
EC
FB
MC
NP
TC
PC

Ref.T. Panel

PAC
CC
GEEC
GMC
MTC
EC
FB
MC
NP
TC
PC

Ref.T. Panel

PAC
CC
GEEC
GMC
MTC
EC
FB
MC
NP
TC
PC

PAC
CC
GEEC
GMC
MTC
EC
FB
MC
NP
TC
PC

-1.0

Ref.T. Panel0

Endothelial cell
Gastric enteroendocrine cell
Parietal cell
Chief cell

Fibroblast-40

ii. Fibroblast

vasculature development
blood vessel development
circulatory system development
blood vessel morphogenesis
angiogenesis
anatomical structure formation in morphogenesis
tube development
Log p.adj Number of genes
tube morphogenesis−6
tissue development−7
cell adhesion−8
epithelial cell development
endothelium development
positive regulation of cell motility
positive regulation of cell migration
positive regulation of locomotion
regulation of cell motility
regulation of cell migration
regulation of locomotion
endothelial cell migration
ameboidal−type cell migration

Fig. 1 (See legend on previous page.)

10
15
20
25

collagen fibril organization
supramolecular fiber organization
external encapsulating structure organization
extracellular matrix organization
extracellular structure organization
intramembranous ossification
Log_p.adj Number of genes
direct ossification
10−5
collagen catabolic process
20−10extracellular matrix disassembly30−15collagen metabolic processcollagen biosynthetic process−20
elastic fiber assembly
extracellular matrix assembly
circulatory system development
blood vessel development
vasculature development
cell adhesion
regulation of cell adhesion
ossification
regulation of multicellular organismal development

T-cellPlasma cell

Neutrophil

Gene ontology terms for predicted cell-type enriched genes
i. Endothelial cell (EC)

Gastric mucous cell

Macrophage

-20

-0.8

E

F

0.6

Principal Component 2(13.9%)

Mean correlation

0.8

PAC
CC
GEEC
GMC
MTC
EC
FB
MC
NP
TC
PC

-0.8

-60

-40

-20

0

20

40

Principal Component 1 (81.4%)

iii. T-cell
adaptive immune response
regulation of immune response
regulation of immune system process
positive regulation of immune system process
immune response
cell activation
leukocyte activation
Log p.adj Number of genes
5.0
lymphocyte activation
−7
7.5
−8
T cell activation
10.0−9
T cell selection
12.5−10
positive T cell selection
15.0−11
lymphocyte differentiation
immune response−activating signal transduction
immune response−activating signaling pathway
immune response−regulating signaling pathway
activation of immune response
immune response−regulating signaling pathway
positive regulation of immune response
antigen receptor−mediated signaling pathway
T cell receptor signaling pathwayÖling et al. BMC Biology(2024) 22:36[25]. Stomach tissue protein profiling revealed staining
consistent with expression in the respective cell types forproteins encoded by genes predicted to be gastric enteroendocrine cell (Fig. 2C (i)), mitotic cell (Fig. 2C (ii)),
parietal cell (Fig. 2C (iii)), chief cell (Fig. 2C (iv)), or gastric mucous cell (Fig. 2C (v)) enriched. GO and reactome
analysis [32, 33] revealed that over-represented terms forpredicted stomach specialised cell type-enriched genes
were consistent with known cell functions, e.g. for gastricenteroendocrine cells enteroendocrine cell differentiation (Fig. 2D (i)), for parietal cells inorganic ion transport
across the plasma membrane and gastric acid secretion(Fig. 2D (ii)), and for gastric mucous cells lipid metabolic
processes (Fig. 2D (iii)) (for all cell types see Additional
file 2: Table S1, Tab 3–13).
Stomach cell type gene enrichment signatures

Figure 3 highlights 25 examples of enriched protein coding enriched genes for each cell type, ordered by highest corr. with the relevant Ref.T. panel (Fig. 3A (i)–K (i)),
with differential corr. values and expression levels inthe bulk RNAseq dataset (mean TPM). The mean TPM
levels were generally highest for genes predicted to beenriched in parietal cells (Fig. 3A (i(), chief cells (Fig. 3B(i)), gastric mucous cells (Fig. 3D (i)), fibroblasts (Fig. 3G(i)), and plasma cells (Fig. 3K (i)) and lowest for thosein mitotic cells (Fig. 3E (i)), neutrophils (Fig. 3I (i)), andT-cells (Fig. 3J (i)). This likely reflects differing numbersof each given cell type with the samples; however, asa range of expression values are observed within eachgiven cell type, there is likely also individual gene variation in factors such as regulation and transcript stability.
The highest differential values, and thus relative uniqueness among the profiled cell types, were observed for
mitotic cell-enriched genes (Fig. 3E.i), most of whichhave well-studied roles in the regulation of the cell cycle,
such as TOP2A and BUB1B. For all other cell types, top
enriched genes included both known cell type-specificgenes, together with those that have not been previously reported as such, e.g. PECAM1 and SHE were bothpredicted to be endothelial cell-enriched (Fig. 3F (i));
PECAM1 is a commonly used marker gene for this cell

Page 5 of 21

type, whilst there are no existing reports for the selective expression of SHE in this context. Tissue profilingfor proteins encoded by representative cell type-enrichedgenes showed expression consistent with our classifications (Fig. 3A (ii)–K (ii)).
Ref.T. analysis can predict the source of stomach‑enriched
protein‑coding genes

Genes with enriched expression in the human stomach
vs. other tissue types can be identified by a comparative analysis of unfractionated tissue RNAseq data. We
extracted the top 200 human stomach-enriched genes
from the HPA [6] and GTEx project [27], through theHarminozome database [37] (Fig. 4). Of the 78 genes
classified as stomach-enriched in both datasets, 46/78(59.0%) were classified as cell type enriched in our analysis, 28/46 (61.0%) in gastric mucous cells, 11/46 (24.0%)
in parietal cells, 6/46 (13.0%) in chief cells, and 1/46
(2.2%) in gastric enteroendocrine cells (Fig. 4B (i, ii),
respectively, large symbols). Of those not classified as cell
type-enriched in our analysis (n = 32), 11/32 (34.4%), only
narrowly failed to reach one of the thresholds for classification as either parietal-, chief-, or gastric mucous cellenriched (Fig. 4B (i, ii), medium symbols). The majorityof the remaining genes most highly correlated with Ref.T.
panel representing one, or more, of the same cell types:
parietal, chief, or gastric mucous, but were excluded fromthe cell type classifications due to shared enrichment.
None of the stomach-enriched genes was predicted to
be enriched in any cell type found across multiple tissue types, such as endothelial or immune cells, consistent with the lack of specificity of these cell types to thestomach. Thus, our analysis indicates that most stomach
tissue-enriched genes are primarily expressed in gastricmucous, parietal, or chief cells.
Cell type‑enriched non‑coding genes in the stomach

A total of 252 non-coding genes were identified as cell
type-enriched in the stomach (Fig. 5A), the greatest number of which were in gastric mucous cells, plasma cells, or(See figure on next page.)
Fig. 2 Integrative co-expression analysis of unfractionated RNAseq reveals enriched genes in human stomach cell types. (A) Total number
and proportional representation of class for cell type enriched genes in: (i) gastric mucous cells, (ii) plasma cells, (iii) fibroblasts, (iv) mitotic cells,(v) macrophages, (vi) parietal cells, (vii) chief cells, (viii) endothelial cells, (ix) gastric enteroendocrine cells, (x) T-cells and (xi) neutrophils. (cells, (viii)
endothelial cells, (ix) gastric enteroendocrine cells, (x) T-cells and (xi) neutrophils. (B) RNAseq data for) RNAseq data for 359 unfractionated humanstomach samples was subject to weighted correlation network analysis (WGCNA). (i) Coloured squares indicate cell type Ref.T. positions on resultant
dendrogram. (ii) Coloured bars show distribution of protein coding genes classified as cell type-enriched across dendrogram groups. (C) Human
stomach tissue profiling for proteins encoded by genes classified as: (i) gastric enteroendocrine cell, (ii) mitotic cell, (iii) parietal cell, (iv) chief cellor (v) gastric mucous cell enriched. (D) Over-represented gene ontology terms among genes predicted to be (i) gastric enteroendocrine cell, (ii)parietal cell or (iii) gastric mucous cell enriched. See also Table S1 Tab 2, 3, 5 and 6Öling et al. BMC Biology(2024) 22:36

Page 6 of 21

A i. Gastric mucous cell ii. Plasma cell
Total = 517

iv. Mitotic cellv. Macrophage

vi. Parietal cellvii. Chief cell

Total = 186

Total = 171

Total = 158

Total = 123

Total = 103

Protein coding
LncRNA
Pseudogene
IG geneIG pseudogene
TEC

viii.Endothelial cellix. Gastricenteroendocrine cell

Total = 92

Total = 86iii. Fibroblast

Total = 214

xi. Neutophil

Total = 24

Total = 20

Cell-enriched genes
Coverage (%)

ii.

ME66
ME50
ME60
ME19
ME32
ME10
ME3
ME25
ME18
ME22
ME44
ME63
ME64
ME67
ME43
ME58
ME40
ME62
ME49
ME47
ME59
ME51
ME65
ME42
ME57
ME37
ME1
ME5
ME28
ME14
ME36
ME45
ME20
ME26
ME39
ME52
ME33
ME6
ME56
ME23
ME46
ME53
ME55
ME30
ME9
ME61
ME15
ME8
ME12
ME4
ME2
ME27
ME13
ME48
ME17
ME31
ME35
ME21
ME29
ME38
ME54
ME34
ME7
ME41
ME0
ME24
ME11
ME16

WGCNA dendrogram

B
i. i.

x. T-cell

0

Boxes indicate Ref.T. position
20

Parietal cell
Chief cell
Gastric enteroendocrine cell
Gastric mucous cell
Mitotic cell

40

60Endothelial cell
Fibroblast
Macrophage
Neutrophil
T-cellPlasma cell
80

C
i. Gastric enteroendocrine cell

SLC18A1

ii. Mitotic celliii. Parietal celliv. Chief cellv. Gastric mucous cell

CHGA

BIRC5

CDC20

ACSS1

SLC9A3

AZGP1

CEBPA

CTSE

LGALS4

DPEP1

CCNB1

TOP2A

ATP4B

MFSD4ASPTBN2PGC

FER1L6

PLAC8

50µm

SCG5

D

i. Gastric enteroendocrine cell
enteroendocrine cell differentiation
pancreatic A cell differentiation
endocrine pancreas development
glandular epithelial cell differentiation
pancreas development
type B pancreatic cell differentiation
pancreatic A cell fate commitment
pancreatic PP cell differentiation
pancreatic PP cell fate commitment
epithelial cell fate commitment
secretion by cell
export from cell
Log p.adj Number of genes
secretion5−2.0
signal release
−2.5
10
−3.0
15
regulated exocytosis−3.5cell−cell signaling−4.0
regulation of localization
regulation of transport
neuron differentiation
leukotriene catabolic process

Fig. 2 (See legend on previous page.)ii. Parietal cell
inorganic ion import across plasma membrane
inorganic cation import across plasma membranepotassium ion transmembrane transport
potassium ion transport
potassium ion import across plasma membrane
import across plasma membrane
import into cell
cation homeostasis
monovalent inorganic cation homeostasis
potassium ion homeostasis
sodium ion transmembrane transport
digestion
Log p.adj Number of genes
gastric acid secretion−3.0
5
tricarboxylic acid cycle
−3.5
10
−4.0
chloride transport
15−4.5
inorganic anion transport
20−5.0
transmembrane transport
ion transmembrane transport
ion transport
inorganic ion transmembrane transportiii. Gastric mucous cellepithelial cell differentiation
epithelium development
arachidonic acid metabolic processunsaturated fatty acid metabolic process
icosanoid metabolic process
lipid metabolic process
cellular lipid metabolic process
cellular response to xenobiotic stimulus
xenobiotic metabolic process
Number of
Log p.adj genes
terpenoid metabolic process
20−5isoprenoid metabolic process
40−6retinol metabolic process60−7retinoid metabolic process−8
diterpenoid metabolic processorganic hydroxy compound metabolic processregulation of hormone levels
olefinic compound metabolic process
primary alcohol metabolic process
hormone metabolic process
cellular hormone metabolic processÖling et al. BMC Biology(2024) 22:36

fibroblasts (n = 100, 44, and 30, respectively). When thesample set was analysed by WGCNA (Fig. 5B (i)), noncoding genes that we predicted to be cell type enriched
predominantly clustered into the same WGCNA groupas the corresponding Ref.T., or into adjacent groups on
the same branch (Fig. 5B (ii)). Up to 25 examples of noncoding enriched genes in gastric enteroendocrine cells(Fig. 5C (i)), gastric mucous cells (Fig. 5D (i)), endothelial cells (Fig. 5E (i)), parietal cells (Fig. 6A (i)), chief cells(Fig. 6B (i)), plasma cells (Fig. 6C (i)), and fibroblasts(Fig. 6D (i)), ordered by corr. with the relevant Ref.T
panel, are displayed with differential corr. values vs.
other profiled cell types, expression in the bulk RNAseq
data (mean TPM), and transcript type. In all cell types,
with the exception of plasma cells, where the most common type of enriched non-coding gene was IG pseudogene (Fig. 6C (i)), long non-coding RNAs made up the
majority of the predicted enriched genes. Generally, gastric mucous cell (Fig. 5D (i)) and fibroblast (Fig. 6D (i))
enriched non-coding genes were expressed at the highest levels in the stomach bulk RNAseq. This likely reflects
the differing numbers of each given cell type within thesamples, but the intra-cell type variation also indicates
individual gene regulation.
There is currently no existing dataset of non-coding
enriched genes in stomach cell types that could be used
to validate our predictions. However, we sourced scRNAseq data from the analysis of 24 tissue types in Tabula
Sapiens [7] (data for the stomach was not available) that
had been classified into endothelial, epithelial, immune,and stromal cell functional compartments (for Tabula
Sapiens UMAP cell type classifications, see Additional
file 4: Fig. S3 A-D). We generated UMAP plots for eachof these compartments to determine expression profiles for selected non-coding genes that we predicted tobe cell type enriched. The predicted gastric enteroendocrine enriched genes MIR7-3HG and RP5-984P4.6 wereexpressed only in the epithelial cell compartment, specifically in the clusters annotated as intestinal enteroendocrine and pancreatic alpha and beta cells (Fig. 5C (ii, iii)),
consistent with a specialised role in endocrine cells, notonly in the stomach, but also in the pancreas and otherparts of the GI tract. The predicted gastric mucous cellenriched genes CTD-2396E7.11 and RP11-27G14.4 were
widely expressed in the epithelial compartment but not inPage 7 of 21

the endothelial, immune, or stromal cell compartments(Fig. 5D (ii, iii)). The predicted endothelial cell-enrichedgenes GATA2-AS1 and AC007743.1 were expressed predominantly in the endothelial cell compartment (Fig. 5E(ii, iii)), also consistent with our classifications. Genes
predicted to be parietal cell enriched, LINC00671 andAC008268.1 (Fig. 6A (ii, iii)), and chief cell enriched,
RP11-526I8.2 and AZGP1P1 (Fig. 6B (ii, iii)), were predominantly expressed in the epithelial compartment. The
type of epithelial cell in which the genes were expressedvaried, e.g. the chief cell enriched gene AZGP1P1 (Fig. 6B(ii)) was expressed predominantly in luminal cells of theprostate and hepatocytes; one could speculate that thisgene indicates a shared secretory function between these
specific cell types, whilst RP11-526I8.2 was more generally expressed in the epithelial compartment (Fig. 6B(iii)) perhaps indicating a more general role. The predicted plasma cell-enriched genes IGLV2-5 and IGLVI70 were expressed only in the immune cell compartment(Fig. 6C (ii, iii)) in clusters annotated as either plasma
cells or B-cells. The predicted fibroblast-enriched genes
LINC01140 and AC006007.1 were expressed predominantly in the stromal cell compartment (Fig. 6D (ii, iii)),
also consistent with our classifications. Thus, the Tabula
Sapiens scRNAseq data provides supportive evidence forour cell type classifications, despite the lack of stomach
cell type analysis in this dataset.
Of those non-coding genes that we classified as cell
type enriched, 17 had relatively high expression in thebulk RNAseq stomach samples (mean TPM > 10) andwere most frequently predicted to be gastric mucous cellenriched (Fig. 6E). To determine the expression profile ofthese genes in different organ types, we sourced data frombulk RNAseq of other tissues in GTEx (Fig. 6F). The mosthighly expressed parietal cell enriched non-coding genes,
LINC00982 and PP7080 (mean TPM 99 and 49, respectively), both had high relative expression in stomach tissue (Fig. 6F (i, ii)), consistent with a specialised functionin this organ. IGLC6, the most highly expressed non-coding transcript we predicted to be enriched in plasma cells,
was highly expressed in the spleen and salivary gland: tissues that contain high numbers of plasma cells (Fig. 6F(iii)). The most highly expressed non-coding genes we
predicted to be enriched in gastric mucous cells, FER1L4
and RP11-363E7.4, both had high relative expression in(See figure on next page.)
Fig. 3 Protein coding gene signatures of human stomach cell types. Cell type-enriched protein coding genes in: (A) parietal cells, (B) chief cells,(C) gastric enteroendocrine cells, (D) gastric mucous cells, (E) mitotic cells, (F) endothelial cells, (G) fibroblasts, (H) macrophages, (I) neutrophils (J)T-cells and (K) plasma cells, showing: (i) differential correlation score (correlation with cell type Ref.T., panel minus max correlation with any other
Ref.T. panel) and mean expression in bulk RNAseq. (ii) Human stomach tissue protein profiling for selected cell type enriched genes. See
also Table S1 Tab 2

Öling et al. BMC Biology(2024) 22:36

Page 8 of 21

Enriched protein coding genes

A. Parietal cell

B. Chief cell

C. Gastric enteroendocrine cell

ILI

N1

LUM

CCDC80

RA
8
CTSK

2

J. T-cell

ASE

R2

6

nti
a
Me l Coan rr.
TP
M.

SPI1
TYR
OBP
MS
4A
VS
4A
IG
4

IGHJ6
−15

3
IGKV

CD3E

Fig. 3 (See legend on previous page.)

LRRC

8C

CDH5
PEC
AM1
ER
G
M
M
RN
2

1

F

YR

JCHAINIGKV3−20
IGKJ
5
MZ
B1
IG
MZB1
LJ
1

5

HJ

IG

i.

S1PR1

PADI4

APOBEC3A
S100
A12
CE
AC
PR
AM
3 S100A12O
K2Mean TPM
1000

0.3
0.1

JCH
AIN
IG
LC
IG
1
KJ
4

IGKC

1
KJ
IG
J2
IGK
IGHJ4

4

−1

V2
IGL

5
P2
MM
E2
F
N
PADI4

0.5

i.

IG
HA
1
V4
−1
IGKV
3−11

C8
KLRC
4

12

TM

KV
1−
39
IGL
V1−
44
IGKV2−
28

IGKV1−5FN

ITGB2

SLC26A8
M2
CMT
1
RP
LY
3
PG
RE
G
AD

Differential

IGKJ3

JAML

SL

nti
a
Me l Coan rr.
TPM.

ntia
Me l Coan rr.
TP
M.

LRRC25

2
LC
IG
J3
IGH

SLAMF6
CCR
5
TH
EM
SI
IS
RP
G

CD8A

A
M
GZ 26
2
CD
IKZF1

L

i.

8B
CD
AC
TR
SPN

ffe
re

IG

IGK

NLRC3
APOBEC3
A2
APB
4
PR
S1
1
RD
KL

FCGR3AK
HC

ii. IGHA1
Di

CD3E
CD2
CD
CD 3G
8A

re
nti
a
Me l Coan rr.
TP
M.

CH
GA
FE
V
RIMB
P2

PGC

LIPF
AZ
PG GP1A4C

i.

SIGLEC9
4
CD1
R8
TL
3
HK

re

K. Plasma cell

ffe

ROBO4
TGF
BR2
TE
K
S1
PR
1

ii. CXCR2
Di
ffe

A
1Q

ii. CD2
Di

L4
GR
AD
E
CD93
SH
A
CLEC14

i.

ESAM
K1
NUA
2
5A
NR
5
RF
G
D
A

CY

UB

RN

re

CCR1

EMILIN1

18
SOX7

CD177

ES

EFEMP2
LGA
LS1
RC
PL N3
AC
9

MFAP4

X

2
AR
FF
1
EM
TR
VNN3

RR

M
2
L1A
CO
MFAP2

LNT

I. Neutrophil

BB
CY
6A
4A
MS
1G
FCER
C3AR1

PDLIM2

RA

HA
VC

AM
RC
CE 1
T
BS
1
FBLN

MX

ffe

2
MP

i.

TRO
L1
HHIP
Y1
TH
A1
L1
CO

TPX2

GA

re
nti
a
Me l Coan rr.
TP
M.

BM

ii. AIF1Di

NKX2-2

CXCR1
CXC
R2
FC
AQ GR3BP9tia
Me l Coan rr.
TP
M.

CDK1

ITGB2
C1Q
B
C1
QC
FC
G
R3
A

re
n

MS4A8
VWA
5B2
KIR
LH REL2
X5

ii. PECAM1

VW

TROAP
E1
GTS
1
PL
ES
PM
AS

P1
SA

NU
P55
CE
TPX2
KIF18B
RRM
2
BU
B1
B
BU
B1

i.

LI
LR
B4
NF
AM
1
AIF1

EM

M2
CA
PA
HE 2−2
X
MS4A8
NK
D1
NEURO

i.

BAIAP3
M2L
VST
A
A1
CN
L
CA
PJ
RB

ffe

H. Macrophage

PCOLCE
CLE
C11
A
FK
BP
M
10
RC
2

ffe

1

Di

ii. MFAP2Di

SLC35D

3

DOCK9

177
B
S100P

F2

LK
AP5

DLG

L

G. Fibroblast

HS

93
CD
355
A0
KIA
32
LRRC

FA
M

re
nti
a
Me l Coan rr.
TP
M.

ME

CKAP2

VILL

NP

F. Endothelial cell

P
UR
HJ
C5
BIR
B
ASF1
AURKB

TF

ffe

TFF2

nti
a
Me l Coan rr.
TP
M.

ii. DLGAP5
Di

IG
83E
FAM
3
EPS8L
TFF1
PLAC
8
CY
CY P2S1
P2
C1
8

re

DN
3

PGA5
SLC
16A1
0
RP
11
−4
C5
0A KIAA1324
or
7.2
f3
8

ii. TFF1

E2
IR
SP rf106
o
C1
T6
GALN
TSPAN1

FER1L6
BP2
SDC
SE
CT L1
SA
A
R

EPB41L4
1B
ERO
A3
13
C
IA
SL
CH

LIPF

E. Mitotic cell

9
SF

i.

BH
R
KA
CC
1
B3GAT

i.

CD

nti
a
Me l Coan rr.
L2
TP
M.
GK
N2
AGR3

BD

LGALS4VILL
CAST PN8
YK
1

re

RH

4
30

TBC1D

CL

AR
G1
HA
L
TREM
L2

AN
GP
TL
3
PX
MP
2
FAM2
22A
ffe

58

3ST

15

A
LH

B
K2
M
CA
R7
XK
6
KCNH
AMER3

Di

HS

GPHA2

D. Gastric mucous cellntia
Me l Coan rr.
TP
M.

ffe

24
13
AA
KI
2
I RX
6
RAB2

GRIP2

5
QR
PA
2
I DH
CPA2

PNPLA1
RB
ESR
L
NJ
CC
L2
3G
H
S

ATP4A

FRMD1
TME
M17
1
GR
I
RA A4
TPCN2
P1
G
AP

re

19

ii. VWA5B2
Di

NCAPG
KIFC
1
NC
AP
M
H
KI
67

i.

AA

KNL1

SYT13

SL
6
CLIC
GIF

KI

or
f5
3
1A
2
GPT2

2

50

50 µm

C1
1

TRIM

A7

6
C2

SL
C

nti
a
Me l Coan rr.
TP
M.

ffe

K1
C

AH

Di

E2

re

AS

ATP4B
ATP
4A
MF
SD
SI
4A
G
LE
C1
1

ffe

ARX
INS
M1
ST
RF 18
X6

ii. BHLHA15

ii. SH3GL2
Di

0Öling et al. BMC Biology(2024) 22:36

Page 9 of 21

A
Stomach enriched genes(vs. other tissue types)

Stomach enriched genes(vs. other tissue types)

Top 200

78 common
stomach enrichedgenes

Top 200

B
i.

ii.
ATP4B
CCKBR
CLIC6
GIF
MFSD4A
SLC4A2
TMEM161B
TRIM50
TRIM73
TRIM74
GPR155
DUSP19
KCNE2
CNTD1
CCKAR
CHIA
LIPF
PGA4
PGA5
PGC
PGA3
XYLT2
MBOAT4
ALDH3A1
ANXA10CAPN8CAPN9
CLDN18CTSE
CYP2S1CYSTM1DPCR1FAM177B
FER1L6
GALE
GKN1
GKN2
MUC1
MUC5ACNQO1OSBPL7REP15RFLNA
SLC5A5
SLC9A1
SULT1C2
TEX35
TFF1
TFF2
TRNP1
VSIG1
VSIG2
ADAM28BAIAP2L1IFRD2
B4GALNT3
BARX1
COL2A1GHRL
FBXL13
CA9
SSTR1
DGKD
ZFPM1
SLC9A4
BEND3
TSTA3
FUT9
PSCA
CDC42EP1CXCL17
A4GNT
FOXP4
MUC6
FMO6P
NKX6-3
ZNF579

ATP4B
CCKBR
CLIC6
GIF
MFSD4A
SLC4A2
TMEM161B
TRIM50
TRIM73
TRIM74
GPR155
DUSP19
KCNE2
CNTD1
CCKAR
CHIA
LIPF
PGA4
PGA5
PGC
PGA3
XYLT2
MBOAT4
ALDH3A1
ANXA10
CAPN8
CAPN9
CTSE
CYP2S1DPCR1FAM177B
FER1L6
GALE
GKN1
GKN2
MUC5ACNQO1
RFLNA
SLC5A5
SLC9A1
TEX35
TFF1
TFF2
VSIG1
SULT1C2TRNP1OSBPL7MUC1
REP15
CLDN18CYSTM1
VSIG2
ADAM28BAIAP2L1IFRD2
B4GALNT3
BARX1
COL2A1GHRL
FBXL13
CA9
SSTR1
DGKD
ZFPM1
SLC9A4
BEND3
TSTA3
FUT9
PSCA
CDC42EP1CXCL17
A4GNT
FOXP4
MUC6
FMO6P
NKX6-3
ZNF579
-0.5

0.0

0.5

Mean correlation with corresponding Ref.T. panel

1.0

-1.5

-1.0

-0.5

0.0

Differential correlation score(mean corr. with Ref.T. panel - max corr. with other Ref.T. panel)

Cell type Ref.T. panel
Parietal cell
Chief cell
Gastric enteroendocrine cell
Gastric mucous cell
Mitotic cell
Endothelial cell

Fibroblast
Macrophage
Neutrophil
T-cellPlasma cellFig. 4 Gastric mucous cells, parietal cells and chief cells are the primary source of stomach tissue enriched genes. (A) The top 200 stomachenriched genes (vs. other tissue types) in RNAseq data from the GTEx Portal or Human Protein Atlas (HPA) were compared to identify genes
common to both datasets (n=78). For each, the following was plotted: (B) (i) the mean correlation with each cell type Ref.T. panel, and (ii)the differential value vs. the next most highly correlating Ref.T. panel (dotted line indicates threshold for classification as cell type enriched).
Enlarged circles represent genes with predicted cell type enrichmentÖling et al. BMC Biology(2024) 22:36

the stomach and bladder (Fig. 6F (iv, v)); one could speculate these genes have specific functions in the mucous
cells found in these tissue types. HSPA7, the most highly
expressed predicted fibroblast-enriched gene had variable expression across tissue types (Fig. 6F (vi)), consistent with the ubiquitous presence of this cell type acrossorgans, whilst the chief cell enriched transcript, C9orf147,
had high relative expression only in stomach tissue(Fig. 6F (vii)). Thus, the most highly expressed non-coding
genes predicted to be enriched in the stomach specialised
cell types were detected at relatively high levels in stomach tissue (and in relatively few other tissue types), consistent with a specialised function here. Conversely, thosepredicted to be enriched in less specialised cell types,
such as plasma cells, were more broadly expressed acrosstissue types, consistent with a common cell type function
in multiple organs. All data for non-coding genes can besearched via the web portal https://​cell-​enric​hment.​shiny​
apps.​io/​nonco​ding_​stoma​ch/.
Stomach tissue scRNAseq supports Ref.T. analysis

To our knowledge, there is no existing comprehensive
scRNAseq dataset where all healthy stomach cell types
have been analysed and compared, to use for further
confirmation of our findings. However, we performed
a comparison between our results and two stomach
RNAseq studies, one with a focus on the analysis of
stomach epithelial cell types [9] and another where cell
types from gastric mucosa samples in premalignant andearly-malignant lesions were characterized [11] (Additional file 2: Table S1, Tab 14). Neither study contained
all cell types we profiled and for some cell types, such as
gastric enteroendocrine cells, classification and/or terminology varied, as is typical [38]. Therefore, we madecomparisons between closely related cells or cell subtypes across studies, e.g. those annotated as D cells, G
cells, X cells, antral enterochromaffin cells, and oxyntic
enterochromaffin-like cells in Busslinger et. al. [9] wereconsidered together as a single group and compared todata for ‘enteroendocrine cells’ in the current study, andPage 10 of 21

that by Zhang et. al. [11]. Where data was available, we
also compared our results to those from our HPA single
cell section [29] and to cell type marker genes defined by
the analysis of multiple human and murine datasets [31](Additional file 2: Table S1, Tab 14 [row 2 states source
and cell type annotation]). Independent verification ofgenes we classified as cell type enriched (i.e. those that
had a comparable classification in at least one otherindependent dataset) varied between cell types (Additional file 2: Table S1, Tab 14). Macrophages and T-cells
had the highest agreement with one or more of the independent studies (71 and 96%, respectively). As expected,
cell types with a higher proportion of non-coding and/or lowly expressed predicted enriched genes, such as
gastric mucous cells, fibroblasts, and parietal cells (thelatter of which were also only represented in one study)tended to have a lower level of independent validation(40%, 38%, and 30%, respectively). However, Gene Ontology and reactome analysis of genes that were not validated in the other datasets were significantly enriched
for terms linked to the predicted cell type, e.g. for gastric mucous cells lipid metabolic processes (adjusted FDR
1.9 × ­10−03), for fibroblasts extracellular structure organisation (adjusted FDR 3.8 × ­10−02), and for parietal cells
monoatomic ion transport (adjusted FDR 2.4 × ­10−03) andgastric acid secretion (adjusted FDR 1.1 × ­10−02), consistent with these genes having specialised roles in these cell
types.
To compare global cell profiles from the stomach
RNAseq datasets [9, 11] with our study and each other,
we calculated the significance of the overlap between cell
type-enriched genes, using a hypergeometric test (Additional file 4: Fig. S3 E). Genes predicted to be cell type
enriched in our study were significantly overrepresented
in enriched genes in the corresponding cell types in both
scRNAseq studies (Additional file 4: Fig. S3 E). This overlap was comparable to, or more significant than, thatbetween the two scRNAseq studies themselves. Whilst
such comparisons can be helpful, the variability between
these studies (i.e. general vs. specific cell type focus,(See figure on next page.)
Fig. 5 Non-coding gene signatures of human stomach cell types. (A) Heat map of non-coding genes predicted to be cell type enriched,showing differential score between mean correlation coefficient with the corresponding Ref.T. panel vs. highest mean correlation coefficientamongst the other Ref.T. panels. (B) RNAseq data for 359 unfractionated human stomach samples was subject to weighted correlation
network analysis (WGCNA). (i) Coloured squares indicate cell type Ref.T. positions on resultant dendrogram. (ii) Coloured bars show distributionof non-coding genes classified as cell type-enriched across dendrogram groups. Non-coding gene enrichment signatures for: (C) gastricenteroendocrine cells, (D) gastric mucous cells and (E) endothelial cells, detailing: (i) up to 25 examples of cell type enriched non-coding genes,
ordered by correlation coefficient with the Ref.T. panel, showing differential correlation scores (correlation with corresponding cell type Ref.T., panel
minus max correlation with any other Ref.T. panel), mean expression in bulk RNAseq and transcript type. (ii and iii) scRNAseq data from analysis
of epithelial, endothelial, immune or stromal cell compartments across 24 human tissues was sourced from Tabula Sapiens (Tabula Sapiens et al.,[7]), and used to generate UMAP plots showing the expression profiles of example cell type enriched non-coding genes. The largest plot shows
the compartment with the highest expression. See also Table S1 Tab 2 and Figure S3 (for all UMAP plot annotations)Öling et al. BMC Biology(2024) 22:36

Page 11 of 21A

Non-coding transcripts predicted to be cell type enriched

Ref.T. Panel
Gastric mucous cell (n=100)
Plasma cell (n=44)
Fibroblast (n=30)
Parietal cell (n=28)
Chief cell (n=18)
Gastric enteroendocrine (n=11)
Endothelial cell (n=8)
Macrophage (n=7)
Mitotic cell (n=5)
T-cell (n=1)
Neutrophil (n=0)

Differential correlation score

B i.

-0.5

-1.0

-1.5

Non-coding cell type enriched transcript distribution

0

Mitotic cell
Endothelial cell
Fibroblast
Macrophage
T-cellPlasma cell

ME66
ME50
ME60
ME19
ME32
ME10
ME3
ME25
ME18
ME22
ME44
ME63
ME64
ME67
ME43
ME58
ME40
ME62
ME49
ME47
ME59
ME51
ME65
ME42
ME57
ME37
ME1
ME5
ME28
ME14
ME36
ME45
ME20
ME26
ME39
ME52
ME33
ME6
ME56
ME23
ME46
ME53
ME55
ME30
ME9
ME61
ME15
ME8
ME12
ME4
ME2
ME27
ME13
ME48
ME17
ME31
ME35
ME21
ME29
ME38
ME54
ME34
ME7
ME41
ME0
ME24
ME11
ME16

Boxes indicate protein
coding Ref.T. postion

10

.1
17
4P

−1

02

AS1

AC
0

07
7

HAGLR

G
2H
4-

RP

IR
M

GAT
A2−

1L4

4P
ND

19

Transcript TypeRP

185
LINC02

AB1P

LI

RP11−389C8.2
AP00

3E7.4

1189

.4

K2

01
55
9

3.2

14

RP
1

23

A2.4
672

11−

1L

10

10.0
7.5
5.0
2.5

1-36

3-5

.3

91

9
03

0
AC

-7

Epithelial

15

11

ii. CTD-2396E7.11

Endothelial

20

4P19

Epithelial

3P

10.0
7.5
5.0
2.5

ii. MIR7-3HG

RP11-99J16_A

CT

.7

51

23

D-

C8

NC

1

E7
96

CYP2

RP

LI

24

-4
11

5.3

−1

RP

0

2
8O

OH
MR

11

RP1

L22

-881

RP5

Differential
Mean TPM

AC021218.2

RP

RP

C−
23
5G

1
AS
1X2
SO
E14
196
D-2
CT
7H18
CTD-254

RP11-800A18

MTND

Transcript type
Pseudogene
LncRNA
TEC

7L5.4

5-AS1

00

1−11

S1

SLC25A2

36K

RP1
CT

Mean TPM
Transcript
Type

NC

RP11−416N2.4

9P

P-A

1-3

G

MIR7−3H

Differential

KR
T8
MB

MT

2
J1
8.
−4

78

.4

1C8

11−

RP

Transcript Type

DN

FER

.2

4P4

18
9P

−98

79
4−

11

43

06
C0

LIN

Mean TPM
Mean TPM

genes

RP

Differential

RP

RP5

Differential

20

i. Non-coding enriched genes

LINC01133

E Endothelial celli. Non-coding enriched.6

D Gastric mucous celli. Non-coding enriched genes
LHX5−AS1

C Gastric enteroendocrine cell

43
.1

20

11

Group coverage (%)

Parietal cell
Chief cell
Gastric enteroendocrine cell
Gastric mucous cell

ii.

0

20

10.0
7.5 Epithelial
5.0
2.5

ii. GATA2-AS1

Endothelial

15

20

10

Endothelial

20

10

5

5

20

20

0

0

−5
−5

0

5

10

0

5

10

−10

15

−10

15

Immune20

015Immune

20

20

0

10

Stromal

10

10
10

10

10

10
0
0

0

−10
−10

−10
−10

20

0

Intestinal enteroendocrine cell
Pancreatic endocrine cell

0

10

0

10

5

20

0

20

StromalStromal

20

0

20

10

20

Immune

10

10

10

0
0
0

0

−10

−10
−10

0

0

10

ii i. RP5-984P4.6

20

−10

0

−10

10.0
7.5
5.0
2.5

Epithelial

10

20

15

5

20

0

20

−10

−5

10.0
7.5
5.0
2.5

Epithelial

10

10

10

ii i. RP11-27G14.4

Endothelial

20

0

20

Endothelial

15

20

0

5

10

iii . AC007743.1

10

20

10.0
7.5 Epithelial
5.0
2.5Endothelial

10

0

15

20

10

5

15

0

0

−10
−5

15
−5

0

5

Immune

20

0

5

10

15

−10

10

Immune

20

20

0

10

Stromal

10
10

10

10

10

10
0

0

0

−10

−10

−10

20

0

0

10

5
−10

20

Stromal

20

0

0

10

0

20

Stromal

20

10

20

Immune10Intestinal enteroendocrine cell
Pancreatic endocrine cell

10

10

0

0

0

−10

−10

20

−10

0

10

Fig. 5 (See legend on previous page.)

0

0

10

−10
−10

0

10

0

10

20

−5

0

5

10

15

−10

0

10

20

Öling et al. BMC Biology(2024) 22:36

healthy vs. diseased tissue) means the data can only be
used as supported evidence, as opposed to a definitive
validation.
Comparison of predicted sex‑specific stomach cell
type‑enriched genes

We performed a subset analysis of the stomach RNAseq
dataset (male n = 227, female n = 132,), to identify sexspecific cell type-enriched genes. Similar to the full
dataset, intra-panel cell type Ref.T. correlated well insingle-sex sample subsets (all > 0.84) (Additional file 5:
Table S2, Tab 1, Table A and B). Cell type-enriched genes
were calculated for the whole dataset. To compare geneenrichment profiles in males and females, the following was calculated for any gene that was classified as cell
type enriched in either subset: (i) the differential correlation score, defined as the difference between the meancorr. coefficient with the cell type Ref.T, in the male andfemale sample subsets (to highlight potential differencesin enrichment between the sexes) and (ii) the enrichmentscore, based on the mean corr. value with the Ref.T. panel(highest score = highest corr.) (to give an overview of therelative degree of enrichment of highlighted genes). Cell
profiles were mainly comparable between sexes, for bothstomach-specialised cell types (Fig. 7A (i–iv)) and others(Additional file 6: Fig. S4 A-G) (genes enriched in bothmales and females represented by square symbols). For
those genes classified as enriched only in males or females(represented by differently coloured triangle and circle
symbols, respectively), most had differential corr. scores
close to 0; indicating that they fell marginally below thedesignated threshold for classification as enriched in theother sex. A small number of distinct male-only enrichedgenes were identified in chief cells: ARSFP1, TBL1Y, andRP11-115H13.1 (Fig. 7A (iv)), all of which were Y-linked,
with expression levels above background level only inmale samples (Fig. 7B (i–iii)). As described above, wesourced scRNAseq data from Tabula Sapiens [7] for cells
classified as endothelial, epithelial, immune, or stromal(Additional file 4: Fig. S3 A-D). We generated UMAP
plots (using cell data from male donors only) to show the

Page 12 of 21

expression profiles of the male-only chief cell-enrichedgenes. ARSFP1 was detected only at low levels in the epithelial compartment (Fig. 7C (i)), whilst TBL1Y (Fig. 7C(ii)) and RP11-115H13.1 (Fig. 7C (iii)) had strikingly similar expression profiles, with the highest levels in bothcases detected in prostate epithelial cells. All three maleonly chief cell-enrichened genes had low/no expression
in the endothelial, immune, or stromal compartments(Fig. 7C (i–iii)). To determine the broad expression profile of the most highly expressed non-coding enrichedgenes across organs (from male donors), we sourced datafrom GTEx (Fig. 7D). ARSFP1 had enhanced expression
only in the stomach and oesophagus (Fig. 7D (i)); both ofwhich are tissue types not included in the Tabula Sapiens dataset, consistent with the low detection observed
there. TBL1Y and RP11-115H13.1 had similar expression
profiles across tissue types, with enhanced expression in
the thyroid (which was also absent from the Tabula Sapiens dataset) followed by the prostate, in keeping with thehigh expression observed in prostate epithelial cells inthe scRNAseq (Fig. 7D (ii, iii)). Thus, one could speculate that male-only chief cell-enriched gene ARSFP1 hasa stomach-specific function, whilst TBL1Y and RP11115H13.1 appear to be co-expressed also in cell types
outside the stomach, suggesting a broader function in
multiple cell types.

Discussion
Here, we present a genome-wide cell type-enriched transcriptome atlas for the human stomach, using our previously described method to resolve unfractionated tissue
RNAseq data to the cell type level [24–26]. Our method
circumvents some challenges associated with scRNAseq
analysis, including issues associated with cell isolation,material amplification [18, 39, 40], and induction of
expression artefacts, due to loss of tissue-specific cues orprocessing [15]. Our analysis incorporates a high numberof biological replicates, reducing the impact of individual
variation and allowing for well-powered subgroup comparisons, e.g. female vs. male. As data for gene enrichment signatures of stomach cell types are lacking in the(See figure on next page.)
Fig. 6 Core non-coding gene signatures of human stomach cell types and tissue distribution patterns. Non-coding gene enrichment signatures
for: (A) parietal cells, (B) chief cells, (C) plasma cells and (D) endothelial cells, detailing (i) up to 25 examples of cell type enriched non-coding genes,
ordered by correlation coefficient with the Ref.T. panel, showing differential correlation scores (correlation with corresponding cell type Ref.T.,
panel minus max correlation with any other Ref.T. panel), mean expression in bulk RNAseq and gene type. (ii and iii) scRNAseq data from analysis
of epithelial, endothelial, immune, or stromal cell compartments across 24 human tissues was sourced from Tabula Sapiens (Tabula Sapiens et al.,2022), and used to generate UMAP plots showing the expression profiles of example cell type enriched non-coding genes. The largest plot shows
the compartment with the highest expression. (E) The most highly expressed cell type enriched non‐coding genes in stomach bulk RNAseq. (F)Expression of genes classified as enriched in parietal cells: (i) LINC00982 and (ii) PP7080, plasma cells: (iii) IGLC6, gastric mucous cells: (vi) FER1L4
and (v) RP11-363E7.4, fibroblasts: (vi) HSPA7 and chief cells: (vii) C9orf147, in bulk RNAseq of different human organs. Mean TMP expression
is annotated for selected organs on each plot. See also Table S1 Tab 2 and Figure S2 (for all UMAP plot annotations)Öling et al. BMC Biology(2024) 22:36

Page 13 of 21

A Parietal cell

C Plasma cell

B Chief celli. Non-coding

i. Non-coding

i. Non-coding

enriched genes

enriched genes

enriched genes

Differential

L
T

Type

T

Mean TPM

NC

Type

Type

Transcript type
Pseudogene
LncRNATEC
IG Pseudogene

ii. LINC00671

ii. AZGP1P1

Endothelial

Epithelial

LT

Epithelial

7.5

Endothelial

7.5

ii. IGLV2-5
ImmuneEndothelial

7.5

5

2.5

Kidney epithelial cell

Plasma cell

2.5

5

2.5

5

5
5

Immune5

Immune5

Epithelial

Luminal cell
prostate epithelium

Pancreatic acinar cell

StromalStromalPancreatic ductal cell

StromalB cellHepatocyte

iii . AC008268.1
EpithelialType II pneumocyte

iii. RP11-526I8.2
Epithelial

Endothelial

7.5
2.5

Endothelial

7.5
2.5

5

iii. IGLVI-70
Plasma cell

2.5

5

ImmuneImmuneStromalStromal5Endothelial

7.5

Immune555Epithelial

StromalB cellD Fibroblast

Most highly expressed cell enriched non-coding genes

i. Non-coding

enriched genes

LINC00982
PP7080 (48.9)
IGLC6 (44.3)
FER1L4 (42.6)
RP11-617F23.1
RP11-363E7.4 (27.2)
CTD-2396E7.11 (24.9)
GOLGA2P10
HSPA7

Type

P

ii. LINC01140
Stromal

7.5
2.5

F

Endothelialv.

RP11-363E7.4

43 TPM
(Stomach)

63 TPM(Bladder)TPM(Kidney cortex)

99 TPM
(Stomach)

79 TPM(Bladder)27 TPM
(Stomach)5

Epithelial

ImmuneExpression (TPM)

5

vi.

HSPA7

vii.

C9orf147

46 TPM
Kidney cortex

54 TPM(Lung)

21 TPM
(Stomach)

49 TPM
(Stomach)
TPM(Small intestine)iii.

Endothelial

7.5

Fig. 6 (See legend on previous page.)

FER1L4

Plasma cell
Chief cellC9orf147

PP7080

Expression (TPM)

Immune2.5

iv.

Parietal cell
Fibroblast

53 TPM
(Thyroid)ii.

5Stromal

LINC00982

Cell type enrichment
Gastric mucosal cell

CYP2AB1P
RP5-1039K5.12
RP5-115904.1
SLC25A25-AS1
MTND4P20
LINC01133
RP11-20I20.4 (5Epithelialiii. AC006007.1

i.

Expression (TPM)

T

E Top 17 (mean TPM in stomach bulk RNAseq)

IGLC6

44 TPM
(Stomach)
TPM
69 TPM(Salivary gland) (Spleen)

11 TPM
(Stomach)Blood

Ad Ad BlaBr Br Br Br Ce Ce Co Co Es Es Es Fa He KidLiv Lu MinMuOv Pa Pit Pr Sk SmSp StoTe Th UteVa Blo
ipo re ddain ain ain ea rv rv lon lonop op op llo ar ne er ng o sc ar nc uit ostain all lee m stisyro ru gin odr S le y re ar tesenal er - C - C - Cst -ix - ix - - - haghaghagpia t - Ly Inten ach id s a
ali - S as y
- SGla er er or MaEc EnSigTra us us usn T eft Co
va ke
sti
ub nd ebeebetex mmtoc do monsv - G- M- Mube Ve rte
nery lee ce id ecu
n x
lla llu
Glataltan
rH m aryrvix rvix rseastruocousscu tricle
nd
Tis
em
eo
es a lar
su
us
op is
isp
Tissue type
e
ha
he
ge
re
al
Ju
nc
tio
n

Ad Ad BlaBr Br Br Br Ce Ce Co Co Es Es Es Fa He KidLiv Lu MinMuOv Pa Pit Pr Sk SmSp StoTe Th UteVa
ipo re ddain ain ain ea rv rv lon lonop op op llo ar ne er ng o sc ar nc uit ostain all lee m stisyro ru gin
r S le y re ar tesenal er - C - C - Cst -ix - ix - - - haghaghagpia t - Ly Inten ach id s a
ali - S as y
- SGla er er or MaEc EnSigTra us us usn T eft Co
sti
va ke
ub nd ebeebetex mmtoc do monsv - G- M- Mube Ve rte
nery lee ce id ecu
n x
lla llu
Glataltan
rH m aryrvix rvix rseastruocousscu tricle
nd
Tis
em
eo
es a lar
su
us
op is
isp
Tissue type
e
ha
he
ge
re
al
Ju
nc
tio
n

Öling et al. BMC Biology(2024) 22:36

existing literature, with this organ absent from large-scale
scRNAseq initiatives, such as Tabula Sapiens [7] andthe Human Cell Atlas [8], our study provides a useful
resource, which can be searched on a gene-by-gene basison the HPA (www.​prote​inatl​as.​org/​human​prote​ome/​tissue+​cell+​type/​stoma​ch) or https://​cell-​enric​hment.​shiny​
apps.​io/​nonco​ding_​stoma​ch/, for protein coding andnon-coding genes, respectively.
Of the 11 cell types we profiled in the stomach, gastric mucous cells had the highest number of predictedenriched genes, which included those encoding for proteins with known cell type-specific functions, such as inmucosal defence, e.g. CAPN8, CAPN9 [41], GKN1 [42],
MUC13 [43], TFF1, and TFF2 [44], and lipid metabolism,
e.g. PLPP2 [45], PPARG​[46], and PLA2G10 [47]. In addition, several genes we identified have no reported role inthis cell type, including FAM83E, CYP2S1, and PLAC8.
It was not possible to identify discrete expression signatures for gastric mucous cell subsets, i.e. MUC6 + gland
mucous cells vs. MUC5AC + pit mucous cells. As
MUC5AC was classified as strongly gastric mucous cellenriched in our analysis, one could speculate that the
profiled population is primarily composed of pit mucous
cells, which is consistent with the higher prevalence of
this sub-type in the region of the stomach (body) that
was analysed [48].
Predicted gastric enteroendocrine-enriched genes also
included those with known cell type function, such as
CAMK2B, which is involved in intracellular calcium signalling [49], and the neuroendocrine secretory protein
CHGA [50]. Other predicted gastric enteroendocrine
enriched genes had not been described in gastric enteroendocrine cells previously, such as LHX5, SERPINA10,
and KCNH6. LHX5 has mainly been studied in the context of neuronal development [51, 52], but in the GTEx
database, the only tissue type, outside the brain, where
LHX5 had elevated expression compared to others was
the stomach [27]; thus, one could speculate that this genealso has a specific functional role here. SERPINA10 wasPage 14 of 21

previously identified as a biomarker for gastrointestinal
neuroendocrine carcinoma [53], and KCNH6 has a rolein the regulation of insulin secretion in the pancreas [54];both were consistent with our prediction that these genes
have an endocrine cell enriched profile.
Many genes we predicted to be parietal cell enrichedwere well-known markers of this cell type, such as GIF[55] and SLC26A7 [56]. However, others had no reported
cell type-specific expression or function, such as ACSS1,
a mitochondrial matrix protein functioning as a catalystof acetyl-CoA synthesis [57] and MFSD4, a marker forhepatic metastasis in gastric cancer [58]. Our classifications were supported by a scRNAseq study that showedelevated expression of ACSS1 and MFSD4 in parietal cells
vs. other stomach epithelial cells [9]. Other predictedenriched genes for which a function in parietal cells has
not yet been described included SLC12A3, ETNPPL,FNDC10, TUBA3C, TRIM73, TRIM74, and CLCNKA.
Chief cell-enriched genes included BHLHA15, a known
chief cell marker [59], and KIAA1324, which is requiredfor chief cell secretory granule maturation [60]. Novelpredicted chief cell-enriched genes included the orphan
receptor GPR150, a G-protein coupled receptor in whichaberrant methylation has been linked to ovarian cancer[61]; MOGAT1, a monoacylglycerol acyltransferase thatfunctions in the absorption of dietary fat in the intestine[62]; and LIPK, previously identified in the epidermis
with a function in lipid metabolism [63].
Whilst there is no existing database of non-coding
gene enrichment profiles in the cell types of the stomach, and a lack of information regarding the functionof any such genes in normal tissue, increasing evidenceof the involvement of non-coding genes in the development of gastric cancer [22, 64, 65] and associated drug
resistance [66] indicates that this transcript class has
important functions in this tissue type. Of the stomachspecialised cell types we profiled, gastric mucous cells
had the highest number of predicted enriched non-coding genes, which included several antisense transcripts(See figure on next page.)
Fig. 7 Identification of sex-specific cell-enriched genes in human stomach tissue. (A) Human stomach RNAseq data (n=359 individuals)
was retrieved from GTEx V8 and divided into female (n=132) and male (n=227) subgroups before classification of cell type-enriched genes.
For genes classified as: (i) parietal, (ii) gastric mucous, (iii) gastric enteroendocrine or (vi) chief cell enriched in either sex, the ´sex differential corr.
score’ (difference between mean corr. with the Ref.T. panel in females vs. males) was plotted vs. ‘enrichment score´ (position in each respectiveenriched list, highest score = highest corr.). On each plot, genes enriched in both females and males are represented by common-coloured squaresymbols, and genes classified as enriched only in females or males are represented by differently coloured circle and triangle symbols, respectively.
(B) Expression in female or male samples for genes classified as male-only enriched in chief cells: (i) ARSFP1, (iii) TBL1Y and (iii) RP11-115H13.1. (C)scRNAseq data from analysis of epithelial, endothelial, immune or stromal cell compartments across human tissues from male donors was sourced
from Tabula Sapiens (Tabula Sapiens et al., [7]), and used to generate UMAP plots showing the expression profiles of: (i) ARSFP1, (iii) TBL1Y and (iii)
RP11-115H13.1. (D) Expression of: (i) ARSFP1, (iii) TBL1Y and (iii) RP11-115H13.1 in bulk RNAseq of different human organs from male donors. The
largest plot shows the compartment with the highest expression. Mean expression is annotated for selected organs on each plot. See also Table S2
Tab 1, Figure S2 (for all UMAP plot annotations) and Figure S3

Öling et al. BMC Biology(2024) 22:36

Fig. 7   (See legend on previous page.)

Page 15 of 21

Öling et al. BMC Biology(2024) 22:36

to corresponding gastric mucous cell-enriched proteincoding genes, such as SOX21-AS1 and TRIM31-AS1,
suggesting a local regulation of gene transcription.
Many gastric mucous cell enriched non-coding genes
were expressed at relatively high levels, compared toother non-coding genes in the same or other cell types,
including LINC01133, FER1L4, RP11-363E7.4, and CTD2396E7.11. LINC01133 and the pseudogene FER1L4 are
inhibitors of gastric cancer progression, with reduced
expression associated with a more aggressive tumour
phenotype [67, 68]. To date, there is a single publication on RP11-363E7.4, where a genome-wide screen ofgastric cancer samples identified it as a key regulator of
disease progression, with higher expression associatedwith overall survival [69]. All the aforementioned studies
were based on analysis of bulk RNAseq cancer samples,
and the cell type in which these genes primarily function in healthy tissue is not reported; our data strongly
indicates that this site is the mucous cell compartment.
CTD-2396E7.11 has not been described in the context
of gastric cancer, but it was identified as one of four hub
lncRNAs associated with reduced colon adenocarcinoma
progression [70]. As this tumour type also arises from themucosa, one could speculate CTD-2396E7.11 has a similar expression profile in healthy colon tissue. LIN00982,
the highest expressed of all classified non-coding genes,
was enriched in parietal cells and had, similar to those
discussed above been shown to have a role in the inhibition of gastric cancer progression [71].
Examples of non-coding genes we predicted to havegastric enteroendocrine cell-enriched expression
included MIR7-3HG and RP5-984P4.6. The selective
expression of these genes in pancreatic and intestinal
endocrine cells [7] is consistent with them having a conserved endocrine function. MIR7-3HG can act as an
autophagy inhibitor [72], but there are no reports of its
function in an endocrine context. RP5-984P4.6 is currently completely uncharacterised. Other gastric enteroendocrine cell enriched non-coding genes included
LHX5-AS1, an antisense transcript to the gastric enteroendocrine cell enriched corresponding protein-coding
gene.
Despite reported differences in stomach function
between males and females, such as in speed of gastric emptying [73], gastrointestinal motility [74], incidence of gastric cancer [75], and gastric cancer survival[76], there are no studies of sex differences between
stomach cell-type gene enrichment profiles. We foundthat global cell type gene enrichment signatures weresimilar between sexes, but we did identify 3 male-only
chief cell-enriched genes—ARSFP1, RP11-115H13.1,

Page 16 of 21

and TBL1Y, all of which were Y-linked [77, 78]. In the
GTEx database, the pseudogene ARSFP1 was mosthighly expressed in male stomach samples, compared tothe other 53 tissue types profiled from males [27], supportive of a currently unknown sex and tissue-specificrole, and consistent with our predicted enrichment in a
stomach-specific cell type in males. Although it is often
assumed that pseudogenes lack function, recent studies have shown that they can have key roles, functioning as antisense, interference or competing endogenoustranscripts [79–81]. RP11-115H13.1 was one of only
eight lncRNAs identified as associated with a high riskof gastric cancer [82], but the dataset analysed in thisstudy contained both male and female samples, meaning
the prognostic value of RP11-115H13.1 in male patientswas likely underestimated. To our knowledge, there are
no existing reports of the potential cellular function of
RP11-115H13.1 or ARSFP1. TBL1Y has been reported as
involved in syndromic hearing loss [83] and cardiac differentiation [84], but studies of its function in the stomach are lacking.
There are limitations in our study. The RNAseq data
we analysed is generated from samples taken from thecorpus (body) of the stomach, so specialised cell profiles
found in other regions of the stomach may not be represented in our dataset. We do not profile cell subtypes,
such as those included under the umbrella term of ‘gastricenteroendocrine cells’ including D-cells and G-cells, forwhich it was not possible to identify Ref.T. that fulfilled therequired criteria. Our observations are consistent withthese sub-cell types being typically defined by the expression of a limited number of specialised proteins [85–87],
rather than large distinct gene signature panels. Gene
expression in the stomach can be modified by genetic or
environmental factors, such as the individual variation in
the gastrointestinal microbiome [88]. Strongly regulated
genes may therefore not correlate with the more constitutively expressed Ref.T. selected to represent the cell typein which they are primarily expressed, as variation acrosssamples could be independent of cell type proportions.
Thus, such genes could be false negatives in our analysis.
Furthermore, we have used high thresholds for the classification of genes as cell type-enriched, which could lead toincorrect exclusion. For example, tissue profiling showedthat proteins encoded by MUC4 and MUC5B are selectively expressed in gastric mucous cells [89], but they fall
just below the threshold for classification as such in our
analysis. In addition, the exclusion of lowly expressed
genes from the analysis may also result in false-negativeclassifications for rarer cell types, for example, PAX6,
which controls endocrine cell differentiation [90], andÖling et al. BMC Biology(2024) 22:36

proglucagon [91] and gastric inhibitory polypeptide [92]production, was excluded from classification as a gastricenteroendocrine enriched gene only due to expression
level below the designated cut off. However, in all cases
the individual enrichment scores clearly indicate a celltype enriched expression; thus, our classifications should
be regarded as a guide, and the data should be consideredon a gene-by-gene basis.

Conclusions
Here, we present a genome-wide cell type-enriched transcriptome atlas for the human stomach and provide anopen access database for the research community.
Methods
Lead contact

Further information and requests for resources and reagents should be directed to and will be fulfilled by the leadcontact: Dr. Lynn Marie Butler (email: Lynn.butler@ki.se).
Experimental model and subject details

Bulk RNAseq data analysed in this study was obtained
from the Genotype-Tissue Expression (GTEx) Project(gtexportal.org) [27] accessed on 2021/04/26 (dbGaP
Accession phs000424.v8.p2). Transcript types were categorised according to Biotype definitions in ENSEMBL
release 102 [35]. Human tissue protein profiling was performed in-house as part of the HPA project [6, 93, 94](www.​prote​inatl​as.​org). Human stomach tissue samples
were obtained from the Department of Pathology, Uppsala University Hospital, Uppsala, Sweden, as part of theUppsala Biobank. Samples were handled in accordancewith Swedish laws and regulations, with approval fromthe Uppsala Ethical Review Board [6].
Method details
Tissue profiling: human tissue sections

Stomach tissue sections were stained, as previously
described [6, 93]. Briefly, formalin-fixed and paraffin-embedded tissue samples were sectioned, de-paraffinised in xylene, hydrated in graded alcohols, andblocked for endogenous peroxidase in 0.3% hydrogen
peroxide diluted in 95% ethanol. For antigen retrieval, a
Decloaking chamber® (Biocare Medical, CA) was used.
Slides were boiled in Citrate buffer®, pH6 (Lab Vision,CA). Primary antibodies and a dextran polymer visualisation system (UltraVision LP HRP polymer®, Lab
Vision) were incubated for 30 min each at room temperature, and slides were developed for 10 min using

Page 17 of 21

Diaminobenzidine (Lab Vision) as the chromogen. Slides
were counterstained in Mayers haematoxylin (Histolab) and scanned using Scanscope XT (Aperio). Primary antibodies, source, target, and identifier are as
follows: atlas antibodies: ACSS1 (Cat#HPA043228,
RRID:AB_2678372), ATP4A (Cat#HPA076684, RRID:AB_
10672772), ATP4B (Cat#HPA045400, RRID:AB_2679314),
MFSD4A (Cat#055407), SH3GL2 (Cat#HPA026685, RRID:
AB_1856817), SLC9A3 (Cat#HPA036493, RRID:AB_10673353), TPCN2 (Cat#HPA027080, RRID:AB_10600917),
CEBPA (Cat#HPA065037, RRID:AB_2685410), LIPF (Cat#HPA045930, RRID:AB_10959518), SPTBN2 (Cat#HPA
043529, RRID:AB_2678531), BHLHA15 (Cat#HPA047834,
RRID:AB_2680172), KIAA1324 (Cat#HPA029869, RRID:
AB_10794320), PGC (Cat#HPA031717, RRID:AB_106
70130), CAMK2B (Cat#HPA053973, RRID:AB_2682328),
SLC18A1 (Cat#HPA063797, RRID:AB_2685125), MS4A8(Cat#HPA007319, RRID:AB_1854138), NKX2-2 (Cat#HPA003468, RRID:AB_1079490), TFF2 (Cat#HPA036705,
RRID:AB_2675263), VILL (Cat#HPA035675, RRID:AB_
10671223), CTSE (Cat#HPA012940, RRID:AB_2668773),
FER1L6 (Cat#HPA054117, RRID:AB_2682387), LGALS4(Cat#HPA031186, RRID:AB_2673778), PLAC8 (Cat#HPA
040465, RRID:AB_10794875), CCNB1 (Cat#HPA061448,
RRID:AB_2684522), DLGAP5 (Cat#HPA005546, RRID:
AB_1078677), TPX2 (Cat#HPA005487, RRID:AB_1858223),
PECAM1 (Cat#HPA004690, RRID:AB_1078462), CD93
(Cat#HPA009300, RRID:AB_1846342), MFAP2 (Cat#HPA007354, RRID:AB_1079365), MFAP4 (Cat#HPA
054097, RRID:AB_2682378) EMILIN1 (Cat#HPA002822,
RRID:AB_1078738), AIF1 (Cat#HPA049234, RRID:AB_
2680685), ITGB2 (Cat#HPA016894, RRID:AB_1846257),
CXCR2 (Cat#HPA032017, RRID:AB_2674112), PADI4(Cat#HPA017007, RRID:AB_1854921), S100A12 (Cat#HPA002881, RRID:AB_1848175), CD2 (Cat#HPA003883,
RRID:AB_1846263), CD3E (Cat#HPA043955, RRID:AB_
2678747), IGHA1 (Cat#HPA001217, RRID:AB_1079120),JCHAIN (Cat#HPA044132, RRID:AB_2678826) and MZB1
(Cat#HPA043745, RRID:AB_10960359) SCG5 (Cat#HPA013136, RRID:AB_1856657), DPEP1 (Cat#HPA01278,
RRID:AB_1847842), VWA5B2 (atlas antibodies Cat#HPA036823, RRID:AB_10672269), from Santa Cruz Biotechnology: AZGP1 (Cat#sc-13585, RRID:AB_667849),
BIRC5 (Cat#sc-17779, RRID:AB_628302), CDC20 (Cat#sc13162, RRID:AB_628089), S1PR1 (Cat#sc-48356, RRID:AB_
2238920), FCGR3A (Cat#sc-20052, RRID:AB_626925)
from Agilent: CD8A (Cat#M7103, RRID:AB_2075537)
from Leica Biosystems: TOP2A (Cat#NCL-TOPOIIA,RRID:AB_564035), TFF1 (Cat#NCL-pS2, RRID:AB_563985)
from Epitomics an AbCam company: CDK1 (Cat#1161–1, RRID:AB_344898) and from Roche: CHGA
(Product name: 1199 021).

Öling et al. BMC Biology(2024) 22:36

Quantification and statistical analysis
Reference transcript‑based correlation analysis and criteria
for cell type enrichment

This method was adapted and expanded from that previously developed to determine the cross-tissue panEC-enriched transcriptome [24] and human brain andadipose tissue cell-enriched genes [25, 26].
Human stomach bulk RNAseq data (N = 359) was
downloaded from the Genotype-Tissue Expression(GTEx) portal V8 (https://​gtexp​ortal.​org). Analysedsamples were collected from the corpus (body) of thestomach, and donor age groups were represented as follows: 2029 years n = 44, 30–39 years n = 39, 40–49 years
n = 64, 50–59 years n = 128, and 60–70 years n = 84. Pairwise Spearman correlation coefficients were calculated
between reference transcripts selected as proxy markers (‘Ref.T. panels’) for parietal cells [ATP4B, MFSD4A,
ATP4A], chief cells [PGC, LIPF, AZGP1], gastric enteroendocrine cells [ST18, INSM1, ARX], gastric mucous
cells [LGALS4, VILL, CAPN8], mitotic cells [NCAPG,KIFC1, NCAPH], endothelial cells [PECAM1, CDH5,
ERG], fibroblasts [PCOLCE, CLEC11A, MMP2], macrophages [C1QB, FCGR3A, ITGB2], neutrophils [CXCR2,
FCGR3B, CXCR1], T-cells [CD3E, CD2, CD3G], andplasma cells [IGKC, JCHAIN, IGLC1] and all othersequenced transcripts. Correlation coefficients were calculated in R using the corr.test function from the psych
package (v 1.8.4) and false discovery rate (FDR) adjusted
p-values (using Bonferroni correction), and raw p-values were calculated. Genes were classified as cell type
enriched when the following criteria were fulfilled: (i) amean correlation > 0.50 (FDR < 0.0001) with the Ref.T.
panel representing that cell type, (ii) a minimum ‘differential correlation’ between this value and the next
highest mean correlation with any other Ref.T. panel (representing another cell type) > 0.15, and (iii) TPM expression < 0.1 in over 50% of samples. See Additional file 1:
Fig. S1 for the method overview.
Weighted correlation network (WGCNA) analysis

The R package WGCNA [36] was used to perform coexpression network analysis for gene clustering, on log2
expression TPM values. Transcripts with a TPM = 0
in > 50% of samples were excluded prior to WGCNA
analysis, leaving 28,254 gene transcripts for analysis. The
soft threshold power was chosen based on the scale-free
topology index and was set at 19; clustering of genes was
performed with modules having a minimum size of 15
genes, resulting in 67 separate modules using the selectedsoft thresholding power. Dendrogram plots were also
created using the WGCNA package.

Page 18 of 21

Gene Ontology and reactome analysis

The Gene Ontology Consortium [32] and PANTHER
classification resource [95] were used to identify overrepresented terms (biological processes) in each set ofpredicted cell type enriched genes from the GO ontology (release date 2022–10-13) or reactome (version 77,
release date 2021–10-01) databases. Dendrogram plots
showing over-represented GO terms in selected cell types
were created using the R package clusterProfiler [96, 97].
Additional datasets and analysis

Single-cell RNAseq data was downloaded from Tabula
Sapiens [7] and analysed using the Seurat package inR [98], which was also used to create the UMAP plots.
Information on tissue-enriched gene expression was
downloaded from the HPA tissue atlas [6] or GTEx database [27], as collated in the Harminozome database [37].
Stomach cell type classifications from Zhang et al. [11],based on the analysis of gastric mucosae in premalignant
and early-malignant lesions, or Busslinger et al. [9] basedon the analysis of healthy stomach epithelia were sourced
from the respective supplemental material sections (celltype enrichment = log FC gene expression vs. other cell
types > 0.58 and > 1.0, respectively [adjusted p-value
cut off < 0.01], see Additional file 2: Table S1 Key Tab
for further details). The statistical significance of overlap between predicted cell type-enriched genes in thisstudy and these scRNAseq studies was calculated using a
hypergeometric test (Additional file 4: Fig. S3 E).
The HPA Single Cell Type Section [29] (www.​prote​inatl​
as.​org/​human​prote​ome/​single+​cell+​type) and Panglao
DB [31] were used to identify cell type marker genes (seeAdditional file 2: Table S1, Key Tab for further details) forcomparisons with cell type enriched gene predictions.
Visualisation

Unless otherwise indicated, plots and graphs were created using GraphPad Prism version 10, GraphPad Software, Boston, MA, USA, www.​graph​pad.​com. Circulargraphs were constructed using the R package circlize[99]. The principle component analysis plot was generated using https://​biit.​cs.​ut.​ee/​clust​vis/ [34]. Some figure
sections were created with BioRender.com.
Additional resources

Analysed data for all protein-coding genes is provided on
the HPA website: (https://​www.​prote​inatl​as.​org/​human​prote​ome/​tissue+​cell+​type/​stoma​ch). Data for non-coding
genes is provided at https://​cell-​enric​hment.​shiny​apps.​io/​nonco​ding_​stoma​ch/. The published article includes alldatasets generated during this study (Tables S1 and S2).

Öling et al. BMC Biology(2024) 22:36

Abbreviations
CC	Chief cell
Corr	Correlation coefficientsEC	Endothelial cell
FB	Fibroblast
FDR	False discovery rate
GEEC	Gastric enteroendocrine cellGI	Gastrointestinal
GMC	Gastric mucous cellGO	Gene Ontology
GTEx	Genotype-Tissue Expression
HPA	Human Protein Atlas
IG	Immunoglobulin
lncRNA	Long non-coding RNAMC	Macrophage
MTC	Mitotic cellNP	Neutrophil
PAC	Parietal cellPC	Plasma cell
Ref.T.	Reference transcripts
scRNAseq	Single-cell RNA sequencing
STD	Standard deviationTC	T-cell
TPM	Transcripts per million
UMAP	Uniform Manifold Approximation and Projection
WGCNA	Weighted network correlation analysis

Supplementary Information
The online version contains supplementary material available at https://​doi.​
org/​10.​1186/​s12915-​024-​01812-5.

Page 19 of 21

Funding
Funding was granted to LMB from Hjärt Lungfonden (20170759, 20170537,
20200544) and Swedish Research Council (2019–01493) and to JO from Stock‑
holm County Council (SLL 2017–0842).
Availability of data and materials
This study did not generate new unique reagents.
• This paper analyses existing, publicly available data from the Genotype-Tissue
Expression (GTEx) Project (https://​gtexp​ortal.​org) with accession number
phs000424.v8.p2 [27] and single-cell RNAseq data from Tabula Sapiens[7] retrieved on 2022/07/29.
• All original code has been deposited at GitHub and is publicly available as of thedate of publication, link: https://​github.​com/​Phili​pDusa​rt/​cell-​enric​hment [100].
• No additional information should be required to reanalyse the data reported
in this paper, but any necessary clarifications or queries can be directed
towards the lead contact.

Declarations
Ethics approval and consent to participate
See Genotype-Tissue Expression (GTEx) Project (https://​gtexp​ortal.​org) [27]and Tabula Sapiens (https://​tabula-​sapie​ns-​portal.​ds.​czbio​hub.​org/) [7].
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Received: 17 May 2023 Accepted: 2 January 2024

Additional file 1:Supplementary Fig. S1.
Additional file 2:Table S1. Reference transcript selection and analysis
criteria. (Tab 1): Correlation coefficient values were calculated between
selected Ref.T. to represent constituent stomach cell types. (Tab 2): Cor‑
relation coefficient values were calculated between selected Ref.T. andall other sequenced transcripts in GTEx stomach mRNAseq data (TableA) and the mean differential vs. all Ref.T. panels (Table B). Genes classified
as enriched in: (Tab 3) parietal cells, (Tab 4) chief cells, (Tab 5) gastricenteroendocrine cells, (Tab 6) gastric mucous cells, (Tab 7) mitotic cells,(Tab 8) endothelial cells, (Tab 9) fibroblasts, (Tab 10) macrophages, (Tab11) neutrophils, (Tab 12) T-cells and (Tab 13) plasma cells were analysed to
identify over-represented terms in the (Table A) gene ontology or (Table
B). (Tab 14) Comparison of our cell type enrichment predictions with
scRNAseq datasets. See key for column details. Related to all Figures.
Additional file 3: Supplementary Fig. S2.
Additional file 4: Supplementary Fig. S3.
Additional file 5: Table S2. Sex stratified subset analysis of cell-enrichedgenes in human stomach. (Tab 1): Correlation coefficient values were
calculated between selected Ref.T. to represent constituent stomach cell types
in females (Table A) or males (Table B). (Tab 2) Correlation coefficient values
were calculated between selected Ref.T. and all other sequenced transcripts instomach mRNAseq data (GTEx), subdivided into (Table A) female or (Table B)
male only sample sets. See key for column details. Related to Fig. 7 and Fig. S4.
Acknowledgements
The Human Protein Atlas is funded by the Knut and Alice Wallenberg Foun‑dation. We used data from the Genotype-Tissue Expression (GTEx) Project(gtexportal.org) [27] supported by the Office of the Director of the National
Institutes of Health and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS.
Authors’ contributions
Conceptualisation: LMB. Methodology: SÖ, ES, MNT, and PD. Formal analysis:
SÖ, PD, and LMB. Investigation SÖ, PD, LMB, and CL. Resources: MU, FP, JO, LB,
and CL. Writing—original draft: SÖ and LMB. Writing—review and editing: all.
Visualisation: SÖ, LMB, PD, MZ, and KVF. Supervision: LMB and PD. Funding
acquisition: LMB and JO. All authors read and approved the final manuscript.

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