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Related Concept Videos

MicroRNAs01:22

MicroRNAs

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MicroRNA (miRNA) are short, regulatory RNA transcribed from introns (non-coding regions of a gene) or intergenic regions (stretches of DNA present between genes). Several processing steps are required to form biologically active, mature miRNA. The initial transcript, called primary miRNA (pri-mRNA), base-pairs with itself, forming a stem-loop structure. Within the nucleus, an endonuclease enzyme, called Drosha, shortens the stem-loop structure into hairpin-shaped pre-miRNA. After the pre-miRNA...
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Separation of Mouse Embryonic Facial Ectoderm and Mesenchyme
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Spatiotemporal MicroRNA-Gene Expression Network Related to Orofacial Clefts.

F Yan1, L M Simon2, A Suzuki3,4

  • 1Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA.

Journal of Dental Research
|July 1, 2022
PubMed
Summary
This summary is machine-generated.

This study maps gene and microRNA expression during craniofacial development, identifying key regulators of orofacial clefts and providing a web tool for data exploration.

Keywords:
cleft lipdevelopmental biologygene expression profilinggene regulatory networksnonlinear dynamicsspatiotemporal analysis

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Area of Science:

  • Developmental Biology
  • Genomics
  • Bioinformatics

Background:

  • Craniofacial development involves complex spatiotemporal regulation of cellular molecules.
  • Understanding these regulatory mechanisms is crucial for identifying causes of craniofacial abnormalities.

Purpose of the Study:

  • To model and analyze gene and microRNA expression patterns during mouse craniofacial development.
  • To construct regulatory networks and identify key molecules involved in orofacial clefts.

Main Methods:

  • Applied natural cubic splines to model gene and microRNA expression from embryonic day 10.5 to 14.5.
  • Integrated CleftGeneDB data to construct regulatory networks for orofacial cleft-related genes.
  • Utilized unsupervised clustering to identify distinct expression patterns of differentially expressed genes and microRNAs.

Main Results:

  • Identified 3,927 temporal, 314 spatial, and 494 spatiotemporal differentially expressed genes (DEGs).
  • Discovered two clusters of differentially expressed microRNAs, with 80 decreasing and 97 increasing over developmental stages.
  • Revealed four hub microRNAs (mmu-miR-325-3p, mmu-miR-384-5p, mmu-miR-218-5p, mmu-miR-338-5p) regulating cleft-related genes, with experimental validation of their role in cell proliferation.

Conclusions:

  • Developed a comprehensive spatiotemporal map of gene and microRNA expression in craniofacial development.
  • Identified specific microRNAs as key regulators in orofacial cleft development.
  • Created a web tool for interactive exploration of craniofacial development data, serving as a valuable resource for future research.