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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...

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Related Experiment Video

Updated: Mar 11, 2026

Competitive Genomic Screens of Barcoded Yeast Libraries

Competitive Genomic Screens of Barcoded Yeast Libraries

Published on: August 11, 2011

K-shuff: A Novel Algorithm for Characterizing Structural and Compositional Diversity in Gene Libraries.

Kamlesh Jangid^1,2, Ming-Hung Kao³, Aishwarya Lahamge⁴

¹Department of Microbiology, University of Georgia, Athens, Georgia, United States of America.

|December 3, 2016

Summary

This summary is machine-generated.

K-shuff is a novel algorithm that quantifies gene sequence library diversity and significance. It accurately measures structural and compositional differences, proving valuable for microbiome analysis and hypothesis testing.

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Area of Science:

Bioinformatics
Computational Biology
Microbial Ecology

Background:

Comparing gene sequence libraries is crucial for understanding microbial communities.
Existing methods may lack sensitivity for detecting subtle compositional differences.

Purpose of the Study:

Introduce K-shuff, a new algorithm for assessing gene sequence library similarity.
Evaluate K-shuff's ability to measure structural and compositional diversity and statistical significance.

Main Methods:

K-shuff utilizes Ripley's K-function, adapted as Intra K-function (IKF) for structural diversity and Cross K-function (CKF) for compositional diversity.
A Monte Carlo testing procedure provides statistical evaluation of diversity measures.
Algorithm performance was tested on 16S rRNA gene libraries, pyrosequencing, and Illumina® libraries.

Main Results:

K-shuff provides reproducible estimates for libraries with >50 sequences (16S rRNA), >300 (pyrosequencing), and >100 (Illumina®).
The algorithm demonstrates sensitivity to small differences in library composition.
K-shuff enables deeper taxonomic level analysis, including within abundant OTUs.

Conclusions:

K-shuff is a sensitive and reproducible tool for analyzing gene sequence library diversity.
Its ability to detect subtle differences aids in comparing similar yet functionally distinct communities.
K-shuff is beneficial for both general microbiome analysis and specific hypothesis testing.