Back

Porcine Intestinal Organoids as Models of Regional Gut and Animal Identities: a Transcriptomic Approach

Blanc, F.; CHALABI, S.; Pepke, F.; Mongelaz, M.; Rau, A.; Djebali, S.; Egidy-Maskos, G.; Giuffra, E.

2025-10-30 genomics
10.1101/2025.10.29.679705 bioRxiv
Show abstract

Organoids are emerging in vitro systems that are expected to bridge the gap between knowledge at the cellular, tissue, and whole-animal levels, with ethical benefits for animal science (3Rs). They offer promise for genotype-to-phenotype research; however, efforts are needed to assess their effective ability and reliability in reflecting the phenotypes of the original tissues from which they are derived. We generated RNA-seq profiles from intestinal organoids and matched tissues from the duodenum, jejunum, ileum, and colon of four pigs at slaughter age. Although organoids were globally distinct from tissues, they retained segment specificity--clearly separating large from small intestine and, to a lesser extent, discriminating among small-intestinal regions. Epithelial programmes remained regionally patterned, whereas innate immune signatures were reduced and less spatially resolved in vitro. Developmental mapping of ileum samples indicated that organoids only partially recapitulate native tissue programmes, consistent with a comparatively immature state. Across gut segments, organoids preserved key transcriptional and functional hallmarks, including immune regulation, metabolism, and developmental pathways. Inter-individual variability was detectable but modest relative to segment-driven differences. Notably, organoids maintained animal-specific epithelial specialisations, including glycosylation pathways involving FUT2 and B4GALNT2. In summary, intestinal organoids retain native tissue identity while displaying immature epithelial and innate immune signatures. They preserve principal segment-defined and animal-specific molecular programmes. These features support further complexification with stromal components and luminal microbiota, underscoring the utility of organoids as a model for genotype-to-phenotype research.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

1
Physiological Genomics
16 papers in training set
Top 0.1%
13.0%
2
Scientific Reports
3612 papers in training set
Top 2%
13.0%
3
Cellular and Molecular Gastroenterology and Hepatology
46 papers in training set
Top 0.2%
6.8%
4
American Journal of Physiology-Gastrointestinal and Liver Physiology
14 papers in training set
Top 0.1%
4.4%
5
Frontiers in Immunology
638 papers in training set
Top 3%
4.1%
6
iScience
1154 papers in training set
Top 6%
3.3%
7
PLOS ONE
5266 papers in training set
Top 37%
3.3%
8
BMC Genomics
406 papers in training set
Top 2%
3.2%
50% of probability mass above
9
eLife
5828 papers in training set
Top 37%
2.8%
10
Frontiers in Veterinary Science
32 papers in training set
Top 0.2%
2.7%
11
Nature Communications
5641 papers in training set
Top 40%
2.4%
12
The FASEB Journal
194 papers in training set
Top 2%
2.1%
13
BMC Biology
265 papers in training set
Top 1%
2.1%
14
Communications Biology
993 papers in training set
Top 11%
2.1%
15
Genomics
64 papers in training set
Top 0.7%
1.7%
16
Journal of Cellular and Molecular Medicine
20 papers in training set
Top 0.2%
1.7%
17
Genome Medicine
183 papers in training set
Top 3%
1.7%
18
Animal Microbiome
31 papers in training set
Top 0.3%
1.7%
19
International Journal of Molecular Sciences
494 papers in training set
Top 9%
1.5%
20
Frontiers in Genetics
230 papers in training set
Top 4%
1.1%
21
Frontiers in Cell and Developmental Biology
233 papers in training set
Top 3%
1.1%
22
Molecular Medicine
11 papers in training set
Top 0.2%
1.1%
23
Microbiology Spectrum
469 papers in training set
Top 9%
0.9%
24
Genome Biology
637 papers in training set
Top 8%
0.9%
25
Molecular Metabolism
112 papers in training set
Top 2%
0.9%
26
JCI Insight
277 papers in training set
Top 7%
0.9%
27
Frontiers in Endocrinology
58 papers in training set
Top 1%
0.9%
28
Journal of Virology
499 papers in training set
Top 3%
0.9%
29
Genes
144 papers in training set
Top 5%
0.6%
30
Life Science Alliance
285 papers in training set
Top 9%
0.6%