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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...
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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
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Related Experiment Video

Updated: Aug 19, 2025

A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants
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A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants

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Plant MicroRNA Identification and Annotation Using Deep Sequencing Data.

Zheng Kuang1, Yongxin Zhao1, Xiaozeng Yang2

  • 1Beijing Agro-biotechnology Research Center, Beijing Key Laboratory of Agricultural Genetic Resources and Biotechnology, Beijing Academy of Agriculture and Forestry Sciences, Beijing, P.R. China.

Methods in Molecular Biology (Clifton, N.J.)
|November 28, 2022
PubMed
Summary
This summary is machine-generated.

This study details plant microRNA (miRNA) annotation using miRDeep-P2 and deep sequencing data. It provides a step-by-step guide to identifying these crucial small RNAs in plants.

Keywords:
Deep sequencingPlant miRNAmiRDeep-P2miRNA annotationmiRNA prediction

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Area of Science:

  • Molecular Biology
  • Genomics
  • Bioinformatics

Background:

  • MicroRNAs (miRNAs) are vital non-coding small RNAs regulating gene expression post-transcriptionally.
  • miRNAs are essential for various biological processes, including plant growth and development.
  • Deep sequencing has produced vast amounts of small RNA sequencing (sRNA-Seq) data.

Purpose of the Study:

  • To provide a comprehensive, step-by-step demonstration of plant miRNA annotation.
  • To illustrate the application of the miRDeep-P2 tool for miRNA identification from sRNA-Seq data.
  • To enhance the understanding and utilization of plant miRNA annotation tools.

Main Methods:

  • Utilized small RNA sequencing (sRNA-Seq) data from plants.
  • Employed the miRDeep-P2 software tool for miRNA prediction and annotation.
  • Performed a detailed, sequential analysis of the annotation process.

Main Results:

  • Successfully demonstrated the workflow for plant miRNA annotation using miRDeep-P2.
  • Generated insights into the step-by-step process of identifying novel and known miRNAs.
  • Highlighted the utility of miRDeep-P2 in analyzing sRNA-Seq data for plant genomics.

Conclusions:

  • miRDeep-P2 is an effective tool for plant miRNA annotation.
  • The step-by-step approach facilitates accurate identification of plant miRNAs from sequencing data.
  • This work aids researchers in exploring the roles of miRNAs in plant biology.