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Multi-species Conserved Sequences

Multi-species Conserved Sequences

Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale studies have provided new insights into the evolutionary relationship between organisms.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved DNA...

MicroRNAs

MicroRNAs

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...

MicroRNAs

MicroRNAs

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 ends...

MicroRNAs

MicroRNAs

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 ends...

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Isolation of microRNAs from Tick Ex Vivo Salivary Gland Cultures and Extracellular Vesicles

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Discovering conserved insect microRNAs from expressed sequence tags.

Qidong Jia¹, Kejian Lin, Jingdong Liang

¹Department of Entomology, College of Plant Protection, Nanjing Agricultural University, Nanjing 210095, China.

Journal of Insect Physiology

|July 27, 2010

Summary

This study introduces a computational pipeline to identify microRNA (miRNA) genes in insects using expressed sequence tags (ESTs). Researchers discovered numerous novel insect miRNAs, with eight confirmed through RT-PCR in the migratory locust.

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Published on: October 7, 2025

Area of Science:

Genomics and Bioinformatics
Molecular Biology
Entomology

Background:

MicroRNAs (miRNAs) are crucial regulators of gene expression in animals, impacting diverse biological pathways.
Despite their importance, miRNA gene identification in agriculturally significant insect pests remains underexplored.
Insect miRNA precursors (pri-miRNAs) possess poly(A) tails, making them detectable in expressed sequence tags (ESTs).

Purpose of the Study:

To develop and implement an efficient computational pipeline for identifying novel miRNA genes from insect ESTs.
To discover and characterize miRNAs across various insect species, including agriculturally relevant pests.
To validate the expression of predicted insect miRNAs in a model organism, Locusta migratoria.

Main Methods:

Collected and filtered 980,697 insect ESTs to identify non-coding sequences.
Aligned known mature miRNAs against non-coding ESTs to find candidate miRNA sequences.
Extracted putative miRNA precursors and evaluated them using the Triplet-SVM algorithm.

Main Results:

Identified 86 miRNAs in 30 insect species (strict criterion) and 330 miRNAs in 51 species (loose criterion).
Discovered conserved miRNA families, including mir-467, mir-297, and mir-466, as highly conserved in insects.
Confirmed the expression of eight out of nine predicted miRNAs in Locusta migratoria via RT-PCR, with one miRNA showing specific thoracic expression.

Conclusions:

The developed computational strategy is effective for predicting miRNA genes from insect ESTs.
The study presents a significant number of novel miRNAs across diverse insect species.
These newly identified miRNAs are anticipated to play vital roles in essential insect physiological processes.