BMC GenomicsGenomicsPeer-reviewed journal article
Integrative genome-scale analyses reveal post-transcriptional signatures of early human smallintestinal development in a directed differentiation organoid model
Yu-Han HungiD, Meghan M. CapelingiD, Jonathan VillanuevaiD, Matt KankeiD, Michael T. ShanahaniD, Sha Huang, Rebecca L. CubittiD, Vera D. RinaldiiD, John C. SchimentiiD, Jason R. SpenceiD, Praveen SethupathyiD
Abstract
MicroRNAs (miRNAs) are important post-transcriptional gene regulators in organ development. To explore candidate roles for miRNAs in prenatal SI lineage specification in humans, we used a multi-omic analysis strategy in a directed differentiation model that programs human pluripotent stem cells toward the SI lineage. We leveraged small RNA-seq to define the changing miRNA landscape, and integrated chromatin run-on sequencing (ChRO-seq) and RNA-seq to define genes subject to significant post-transcriptional regulation across the different stages of differentiation. Our analyses showed that the elevation of miR-182 and reduction of miR-375 are key events during SI lineage specification. We demonstrated that loss of miR-182 leads to an increase in the foregut marker SOX2. We also used single-cell analyses in murine adult intestinal crypts to support a life-long role for miR-375 in the regulation of Zfp36l2. Finally, we uncovered opposing roles of SMAD4 and WNT signaling in regulating miR-375 expression during SI lineage specification. Beyond the mechanisms highlighted in this study, we also present a web-based application for exploration of post-transcriptional regulation and miRNA-mediated control in the context of early human SI development. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=158 HEIGHT=200 SRC="FIGDIR/small/499825v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@1ebf48eorg.highwire.dtl.DTLVardef@4a0d9org.highwire.dtl.DTLVardef@1dc3be9org.highwire.dtl.DTLVardef@1e14207_HPS_FORMAT_FIGEXP M_FIG C_FIG
- organism: human
- assay: bulk RNA-seq
- assay: ChIP-seq
- assay: spatial transcriptomics
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: database / resource
- approach: statistical model
- approach: experimental assay
- Citations
- 4
- FWCI
- 0.51
- Field percentile
- top 42%
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