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MEPDB: Database of microExons in plants.

Yakub Islamov1, Huihui Yu2, Hongfeng Yu3

  • 1Department of Biochemistry, University of Nebraska, Lincoln, NE, 68588, USA.

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|August 16, 2025
PubMed
Summary
This summary is machine-generated.

Scientists discovered thousands of previously unknown plant microexons, which are tiny gene segments. A new database and prediction tool will aid research into these small but important genetic elements.

Keywords:
gene structure annotationmicroexon predictionmicroexonsmicroexon‐tagsplant genomes

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Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Microexons, especially ultra-short ones (1-15 nucleotides), are difficult to identify due to their small size and poor annotation in reference genomes.
  • This lack of identification hinders understanding of their crucial biological roles in various organisms.

Purpose of the Study:

  • To develop a pipeline for identifying small internal microexons in plants.
  • To create a comprehensive database and predictive tool for plant microexons to facilitate research.

Main Methods:

  • Developed a computational pipeline to identify small internal microexons (≤51 nucleotides).
  • Identified microexons in 10 diverse plant species and grouped them into conserved clusters.
  • Leveraged these clusters to develop a predictive method for identifying microexons across 132 plant genomes.
  • Created the Database of MicroExons in Plants (MEPDB) with detailed annotations and an RNA-seq-independent prediction tool.

Main Results:

  • Identified 2398 novel small internal microexons in 10 plant species, with most not present in existing annotations.
  • Grouped these microexons into 45 conserved microexon clusters.
  • Developed a predictive method that identified 20,224 microexons across 132 plant genomes.
  • Established the MEPDB, a valuable resource for plant microexon research.

Conclusions:

  • The developed pipeline and database significantly expand the known repertoire of plant microexons.
  • The MEPDB provides a comprehensive resource for studying microexon function and evolution in plants.
  • The RNA-seq-independent prediction tool offers a novel approach for microexon discovery.