Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1122973 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR29368760.fastq.gz | Fastqsanger.gz | |||
| SRR29368761.fastq.gz | Fastqsanger.gz | |||
| SRR29368762.fastq.gz | Fastqsanger.gz |
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Project description:Single cell-based studies have revealed tremendous cellular heterogeneity in stem cell and progenitor compartments, suggesting continuous differentiation trajectories with intermixing of cells at various states of lineage commitment and notable degree of plasticity during organogenesis. The hepato-pancreato-biliary organ system relies on a small endoderm progenitor compartment that gives rise to a variety of different adult tissues, including liver, pancreas, gallbladder, and extra-hepatic bile ducts. Experimental manipulation of various developmental signals in the mouse embryo underscored important cellular plasticity in this embryonic territory. This is also reflected in the existence of human genetic syndromes as well as congenital or environmentally-caused human malformations featuring multiorgan phenotypes in liver, pancreas and gallbladder. Nevertheless, the precise lineage hierarchy and succession of events leading to the segregation of an endoderm progenitor compartment into hepatic, biliary, and pancreatic structures are not yet established. Here, we combine computational modelling approaches with genetic lineage tracing to assess the tissue dynamics accompanying the ontogeny of the hepato-pancreato-biliary organ system. We show that a multipotent progenitor domain persists at the border between liver and pancreas, even after pancreatic fate is specified, contributing to the formation of several organ derivatives, including the liver. Moreover, using single-cell RNA sequencing we define a specialized niche that possibly supports such extended cell fate plasticity.
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Primary outcome(s): For mRNA libraries, focus on mRNA studies. Data analysis includes sequencing data processing and basic sequencing data quality control, prediction of new transcripts, differential expression analysis of genes. Gene Ontology (GO) and the KEGG pathway database are used for annotation and enrichment analysis of up-regulated genes and down-regulated genes.
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