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miR-335 promotes mesendodermal lineage segregation and shapes a transcription factor gradient in the endoderm

Development(2014)10.1242/dev.104232Source: DataRank Database

miR-335 promotes mesendodermal lineage segregation and shapes a transcription factor gradient in the endoderm is a research paper published in Development (2014). On theSindex it has a DataRank of 0.449. It has been cited 19 times.

N/A
0.449DataRank · unranked
0.449
19 citations · base score 3.0
Cite:
datarank_citation_only_1hop_v6· scope data_onlyMethodology

Abstract

Transcription factors (TFs) pattern developing tissues and determine cell fates; however, how spatio-temporal TF gradients are generated is ill defined. Here we show that miR-335 fine-tunes TF gradients in the endoderm and promotes mesendodermal lineage segregation. Initially, we identified miR-335 as a regulated intronic miRNA in differentiating embryonic stem cells (ESCs). miR-335 is encoded in the mesoderm-specific transcript (Mest) and targets the 3'-UTRs of the endoderm-determining TFs Foxa2 and Sox17. Mest and miR-335 are co-expressed and highly accumulate in the mesoderm, but are transiently expressed in endoderm progenitors. Overexpression of miR-335 does not affect initial mesendoderm induction, but blocks Foxa2- and Sox17-mediated endoderm differentiation in ESCs and ESC-derived embryos. Conversely, inhibition of miR-335 activity leads to increased Foxa2 and Sox17 protein accumulation and endoderm formation. Mathematical modeling predicts that transient miR-335 expression in endoderm progenitors shapes a TF gradient in the endoderm, which we confirm by functional studies in vivo. Taken together, our results suggest that miR-335 targets endoderm TFs for spatio-temporal gradient formation in the endoderm and to stabilize lineage decisions during mesendoderm formation.

Data sources & pipeline
Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring
Enrichment:Pending

FAIR Checklist

Context only (not used in score)
Findable (1/2)
  • Has DOI
Accessible (0/2)
    Interoperable (0/2)
      Reusable (0/3)

        FAIR checklist signals are shown for context only and do not affect DataRank scoring.

        DataRank Breakdown

        Base Score 100%Citation Network 0%

        Base Score Contribution

        0.449

        From this paper's citation signal

        Citation Network Contribution

        0

        Citation network not refreshed for this result

        This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.

        Learn more about DataRank methodology →
        Why this DataRank?

        DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 100% comes from its base citations and 0% from the citation network.

        Base score B(p)
        log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
        Network N(p)
        Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
        Damping factor d = 0.85
        DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
        Self-citations excluded
        Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.

        Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.

        Read the full methodology →

        Authors (6)

        Dominik LutterORCID,Ingo Burtscher,Lena Uetzmann,Fabian Joachim TheisORCID,Heiko LickertORCID