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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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Towards a Consistent, Quantitative Evaluation of MicroRNA Evolution.

Ali M Yazbeck1, Kifah R Tout1, Peter F Stadler1

  • 1.

Journal of Integrative Bioinformatics
|June 23, 2017
PubMed
Summary
This summary is machine-generated.

Developing an automated pipeline is crucial for studying microRNA (miRNA) gene evolution. This system enhances sequence alignments and homology searches for comprehensive genomic analysis.

Keywords:
AlignmentsHomology Searchascertainment biasesmiRBase

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Area of Science:

  • Genomics
  • Bioinformatics
  • Evolutionary Biology

Background:

  • The miRBase database contains over 25,000 microRNAs (miRNAs) across numerous genomes, organized into homologous sequence families.
  • Studying miRNA gene evolution necessitates consistent, comprehensive genomic datasets.
  • The complexity and scale of miRNA data require automated solutions for accurate analysis.

Purpose of the Study:

  • To describe progress in developing a fully automated pipeline for miRNA gene evolution studies.
  • To improve the accuracy and completeness of initial seed alignments for homology searches.
  • To enhance the identification of true positive homology search results.

Main Methods:

  • Developing a fully automatic computational pipeline.
  • Improving existing seed alignments for microRNA families.
  • Extending sequence datasets using homology search algorithms.
  • Implementing reliable methods for identifying true positive homology results.

Main Results:

  • Significant progress has been made towards a fully automated system for analyzing miRNA gene evolution.
  • The pipeline effectively improves initial seed alignments, a critical step for accurate homology detection.
  • The system is designed to reliably identify homologous sequences across diverse genomes.

Conclusions:

  • An automated pipeline is essential for scalable and accurate quantitative investigations of miRNA gene evolution.
  • Improvements in seed alignment and homology searching are key to building robust miRNA evolution datasets.
  • This work represents a significant step towards a comprehensive system for exploring miRNA evolutionary dynamics.