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Related Concept Videos

Gene Duplication and Divergence02:37

Gene Duplication and Divergence

The seminal work of Ohno in 1970 popularized the idea of gene duplication and divergence. DNA sequence comparison studies reveal that a large portion of the genes in bacteria, archaebacteria, and eukaryotes was  generated by gene duplication and divergence, indicating its critical role in evolution.
The duplicated copies of the gene are called Paralogs. Paralogs with similar sequences and functions form a gene family. Across several species, a large number of gene families are characterized.
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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
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Phylogenetic Trees03:21

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Phylogenetic trees come in many forms. It matters in which sequence the organisms are arranged from the bottom to the top of the tree, but the branches can rotate at their nodes without altering the information. The lines connecting individual nodes can be straight, angled, or even curved.
Phylogenetic Trees03:21

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Related Experiment Video

Updated: May 14, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
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Published on: August 14, 2018

Inferring optimal species trees under gene duplication and loss.

M S Bayzid1, S Mirarab, T Warnow

  • 1Department of Computer Science, The University of Texas at Austin, Austin, Texas 78712, USA.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|February 21, 2013
PubMed
Summary

Estimating species trees is challenging due to gene duplication and loss. This study introduces a novel dynamic programming approach using subtree-bipartitions to efficiently solve minimize gene duplications (MGD) and minimize gene duplications and losses (MGDL) problems.

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Area of Science:

  • Computational Biology
  • Phylogenetics
  • Bioinformatics

Background:

  • Species tree estimation is complex due to gene tree incongruence.
  • Gene duplication and loss are significant factors causing gene tree variation.
  • Current methods like local search heuristics for MGD and MGDL are computationally intensive.

Purpose of the Study:

  • To develop an alternative, efficient approach for species tree estimation under gene duplication and loss.
  • To introduce and utilize the concept of "subtree-bipartitions" for tree characterization.
  • To solve the minimize gene duplications (MGD) and minimize gene duplications and losses (MGDL) problems.

Main Methods:

  • Characterizing gene trees using a novel concept: "subtree-bipartitions".
  • Formulating MGD and MGDL as maximum and minimum weight clique problems on vertex-weighted graphs.
  • Applying a dynamic programming algorithm to efficiently find optimal cliques in polynomial time.
  • Developing a constrained version solvable in time polynomial to the number of gene trees and taxa.

Main Results:

  • The MGD species tree corresponds to a maximum weight clique.
  • The MGDL species tree corresponds to a minimum weight clique.
  • The dynamic programming algorithm efficiently solves these clique problems due to graph structure.
  • A constrained version of the problem is also efficiently solvable.

Conclusions:

  • The proposed subtree-bipartition approach provides an efficient method for species tree estimation.
  • Dynamic programming offers a polynomial-time solution for MGD and MGDL problems.
  • A publicly available software tool implementing this algorithm has been developed.