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Exon Recombination

Exon Recombination

The evolution of new genes is critical for speciation. Exon recombination, also known as exon shuffling or domain shuffling, is an important means of new gene formation. It is observed across vertebrates, invertebrates, and in some plants such as potatoes and sunflowers. During exon recombination, exons from the same or different genes recombine and produce new exon-intron combinations, which might evolve into new genes.
Exon shuffling follows “splice frame rules.” Each exon...

Organization of Genes

Organization of Genes

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Related Experiment Video

Updated: Jul 5, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

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Published on: December 15, 2023

Predicting Alu exonization in the human genome with a deep learning model.

Zitong He¹, Ou Chen², Noelani Phillips³

¹Department of Computer Science, Johns Hopkins University, Baltimore, MD 21205.

Biorxiv : the Preprint Server for Biology

|January 23, 2024

Summary

Alu exonization, the integration of Alu elements into genes, is more widespread than previously thought. Our deep learning model, eXAlu, identifies numerous novel Alu exonization events, advancing our understanding of gene regulation.

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Use of Alu Element Containing Minigenes to Analyze Circular RNAs

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Use of Alu Element Containing Minigenes to Analyze Circular RNAs

Use of Alu Element Containing Minigenes to Analyze Circular RNAs

Published on: March 10, 2020

Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

Alu exonization contributes to functional gene diversification but its full extent and regulatory impact remain unclear.
Existing methods for identifying Alu exonization are limited by tissue specificity and computational demands.

Approach:

Developed eXAlu, a deep learning model for unbiased prediction of Alu exonization from genomic sequences.
eXAlu overcomes limitations of RNA-seq analysis and tissue specificity.
The model identifies key sequence elements driving Alu exonization.

Key Points:

eXAlu predicts 55-110K Alu elements undergo exonization, 11-21 times more than current databases.
RT-PCR validation confirms the accuracy of eXAlu predictions.
Identified potential for eXAlu in detecting polymorphic Alu insertion exonizations.

Conclusions:

Alu exonization is a more significant genomic phenomenon than previously estimated.
eXAlu provides a powerful, computationally efficient tool for discovering Alu exonization events.
This approach has implications for understanding gene regulation and human genetic variation.