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Gene Duplication and Divergence02:37

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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.
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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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Phylogeny is concerned with the evolutionary diversification of organisms or groups of organisms. A group of organisms with a name is called a taxon (singular). Taxa (plural) can span different levels of the evolutionary hierarchy. For instance, the group containing all birds is a taxon (comprising the class Aves), and the group of all species of daisies (the genus Bellis) is a taxon. Phylogenies can likewise include just one genus (i.e., depict species relationships) or span an entire kingdom.
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Synteny and Evolution02:31

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The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
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Eukaryotes have large genomes compared to prokaryotes. To fit their genomes into a cell, eukaryotic DNA is packaged extraordinarily tightly inside the nucleus. To achieve this, DNA is tightly wound around proteins called histones, which are packaged into nucleosomes that are joined by linker DNA and coil into chromatin fibers. Additional fibrous proteins further compact the chromatin, which is recognizable as chromosomes during certain phases of cell division.
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Related Experiment Video

Updated: Dec 28, 2025

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

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A unified ILP framework for core ancestral genome reconstruction problems.

Pavel Avdeyev1, Nikita Alexeev2, Yongwu Rong3

  • 1Department of Mathematics, The George Washington University, Washington, DC 20052, USA.

Bioinformatics (Oxford, England)
|February 15, 2020
PubMed
Summary

This study introduces integer linear programming formulations for ancestral genome reconstruction, addressing genome median and halving problems. These methods accurately reconstruct ancestral genomes, combining homology and rearrangement approaches for improved biological relevance.

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Area of Science:

  • Computational genomics
  • Bioinformatics
  • Evolutionary biology

Background:

  • Reconstructing ancestral genomes is crucial for understanding evolutionary history.
  • Genome rearrangements and whole-genome duplications (WGDs) are major drivers of genomic change.
  • Existing methods for ancestral genome reconstruction face challenges in biological relevance and accuracy.

Purpose of the Study:

  • To develop novel computational methods for ancestral genome reconstruction.
  • To address the genome median, genome halving, and genome aliquoting problems.
  • To improve the biological relevance and accuracy of ancestral genome reconstruction.

Main Methods:

  • Integer linear programming (ILP) formulations were developed for ancestral genome reconstruction problems.
  • Polynomial-size ILP formulations were created for the genome median and genome halving problems.
  • Restricted and conserved versions of these problems were formulated to enhance biological relevance.

Main Results:

  • The proposed ILP formulations demonstrated good accuracy in reconstructing ancestral genomes.
  • The ILP formulations for conserved versions of the problems have linear size, enabling practical application.
  • The developed approach effectively combines homology- and rearrangements-based methods for ancestral reconstruction.

Conclusions:

  • Integer linear programming provides a powerful and accurate framework for ancestral genome reconstruction.
  • The novel ILP formulations, particularly for conserved versions, offer a practical and biologically relevant approach.
  • This work advances the field of comparative genomics by providing robust tools for studying genome evolution.