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Related Concept Videos

Overview of Transposition and Recombination02:13

Overview of Transposition and Recombination

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Transposons make up a significant part of genomes of various organisms. Therefore, it is believed that transposition played a major evolutionary role in speciation by changing genome sizes and modifying gene expression patterns. For example, in bacteria, transposition can lead to conferring antibiotic resistance. Movement of transposable elements within the genetic pool of pathogenic bacteria can aid in transfer of antibiotic-resistant genetic elements. In eukaryotes, transposons can carry out...
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DNA-only transposons are called autonomous transposons since they code for the enzyme transposase that is required for the transposition mechanism. Insertion of transposons can alter gene functions in multiple ways. They can mutate the gene, alter gene expression by introducing a novel promoter or insulator sequence, introduce new splice sites, and change the mRNA transcripts produced, or remodel chromatin structure.
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The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
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Because the DNA segments are cut and reorganized in a direction-specific manner, site-specific recombination has emerged as an efficient genetic engineering technique. Flippase and Cyclization recombinases or Flp and Cre, respectively, are two members of the tyrosine recombinase family derived from bacteriophages, that are used to mediate site-specific DNA insertions, deletions, and targeted expression of proteins in mammalian cell lines.
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Other than maintaining genome stability via DNA repair, homologous recombination plays an important role in diversifying the genome. In fact, the recombination of sequences forms the molecular basis of genomic evolution. Random and non-random permutations of genomic sequences create a library of new amalgamated sequences. These newly formed genomes can determine the fitness and survival of cells. In bacteria, homologous and non-homologous types of recombination lead to the evolution of new...
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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. 
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An O([Formula: see text]) algorithm for sorting signed genomes by reversals, transpositions, transreversals and

Shuzhi Yu1, Fanchang Hao2, Hon Wai Leong1

  • 1* Department of Computer Science, National University of Singapore, 13 Computing Drive, Singapore 117417, Republic of Singapore.

Journal of Bioinformatics and Computational Biology
|December 29, 2015
PubMed
Summary

This study introduces a faster O(n) algorithm for genome sorting by bridges (GSB), improving upon previous methods for analyzing large-scale genome rearrangements in species evolution. The new approach enhances computational efficiency for sorting signed permutations using various genomic operations.

Keywords:
Algorithmapproximation algorithmblock-interchangegenome rearrangementgenome sortingreversaltranspositiontransreversal

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Genomics

Background:

  • Genome rearrangement analysis is crucial for understanding species evolution.
  • Previous algorithms for sorting signed permutations by reversals, transpositions, and block-interchanges have limitations.
  • The genome sorting by bridges (GSB) scheme offers a 2-approximation for these problems.

Purpose of the Study:

  • To develop a more efficient algorithm for implementing the genome sorting by bridges (GSB) scheme.
  • To improve the computational complexity of sorting signed permutations using genomic operations.
  • To provide a faster method for analyzing large-scale genome rearrangements.

Main Methods:

  • Developed an O(n) algorithm for the GSB scheme.
  • Represented cycles in the breakpoint graph using canonical sequences.
  • Simplified the search for L-bridges, T-bridges, and X-bridges.

Main Results:

  • Achieved an O(n) time complexity for the GSB scheme, significantly faster than the previously mentioned straightforward algorithm.
  • The new algorithm simplifies the identification of bridge structures within the breakpoint graph.
  • Experimental comparisons demonstrate improved running times and computed distances against the original GSB implementation.

Conclusions:

  • The O(n) GSB algorithm provides a computationally efficient solution for sorting signed permutations.
  • This advancement facilitates more rapid analysis of genome evolution through large-scale rearrangement operations.
  • The method of representing cycles by canonical sequences is key to the algorithm's efficiency.