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The ITS2 Database
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Homologous synteny block detection based on suffix tree algorithms.

Yu-Lun Chen1, Chien-Ming Chen, Tun-Wen Pai

  • 1Department of Computer Science and Engineering and Center of Excellence for the Oceans, National Taiwan Ocean University, No. 2 Peining Road, Keelung, Taiwan 20224, Republic of China.

Journal of Bioinformatics and Computational Biology
|December 31, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a novel suffix tree algorithm for detecting conserved synteny blocks, which are groups of genes that remain in the same order across species. This method aids in understanding evolutionary diversity and identifying homologous genes.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Evolutionary Biology

Background:

  • Synteny blocks, sets of contiguous and conserved genes across species, are crucial for tracing life's diversity and identifying homologous genes.
  • Genome rearrangements can alter gene order, making synteny block identification challenging.
  • Efficient methods are needed to detect conserved gene orders for evolutionary and genomic analyses.

Purpose of the Study:

  • To develop an efficient algorithm for detecting collinear synteny blocks across multiple species.
  • To introduce a novel metric, the Synteny Block Conserved Index (SBCI), for evaluating interspecies synteny relationships.
  • To provide a computationally efficient alternative to whole genome alignment for phylogenetic analysis.

Main Methods:

  • Modified suffix tree algorithms by encoding genes as characters in a chromosome string.
  • Built suffix trees for chromosomes from different species to identify homologous synteny blocks.
  • Modeled conserved synteny blocks as overlapped contiguous edges within the suffix tree.
  • Defined and applied the Synteny Block Conserved Index (SBCI) to quantify synteny conservation.

Main Results:

  • Successfully identified conserved synteny blocks using the modified suffix tree approach.
  • Demonstrated the efficiency of the suffix tree-based algorithm for synteny detection.
  • The proposed SBCI effectively evaluates synteny block distribution between species.

Conclusions:

  • The suffix tree-based algorithm provides an efficient method for detecting collinear synteny blocks.
  • The SBCI serves as a valuable evolutionary indicator for phylogenetic tree construction.
  • This approach offers a computationally feasible alternative for comparative genomics and evolutionary studies.