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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...
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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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A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
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In Silico Identification and Characterization of circRNAs During Host-Pathogen Interactions
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Discovering circRNA-microRNA Interactions from CLIP-Seq Data.

Xiao-Qin Zhang1,2, Jian-Hua Yang3,4

  • 1School of Medicine, South China University of Technology, Guangzhou, People's Republic of China.

Methods in Molecular Biology (Clifton, N.J.)
|January 12, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces computational tools to identify circular RNA-microRNA interactions using CLIP-Seq and RNA-Seq data. The starBase platform aids in discovering regulatory networks involving these noncoding RNAs.

Keywords:
CLIP-SeqInteractomeRNA-SeqcircRNAmiRNA spongemicroRNA

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Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Genomics

Background:

  • Circular RNAs (circRNAs) are abundant noncoding RNAs with largely unknown regulatory mechanisms.
  • Understanding circRNA functions is crucial for comprehending physiological and pathological processes.

Purpose of the Study:

  • To describe methods for identifying circRNA-microRNA interactions using CLIP-Seq and RNA-Seq data.
  • To introduce computational software and a platform for analyzing these interactions.

Main Methods:

  • Utilized Argonaute (AGO) cross-linking and immunoprecipitation followed by sequencing (CLIP-Seq) and RNA-Seq data.
  • Developed three computational software: circSeeker, circAnno, and clipSearch.
  • Employed the starBase platform with a genome browser for comparative analysis and interactive web applications.

Main Results:

  • Successfully identified and annotated circRNAs and their interactions with microRNAs (miRNAs).
  • Enabled evaluation of circRNA-miRNA interactions from CLIP-Seq data and discovery of miRNA-sponge circRNAs.
  • Integrated CLIP-Seq and RNA-Seq data to reveal regulatory networks involving miRNAs and circRNAs.

Conclusions:

  • The developed software and starBase platform provide a comprehensive approach to study circRNA-miRNA interactions.
  • These tools are expected to significantly advance the understanding of regulatory networks involving noncoding RNAs.
  • The resources are publicly available for researchers to explore circRNA functions.