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Multiple organism algorithm for finding ultraconserved elements.

Scott Christley1, Neil F Lobo, Greg Madey

  • 1Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA. schristl@nd.edu

BMC Bioinformatics
|January 12, 2008
PubMed
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This study introduces a novel algorithm and software for efficiently identifying ultraconserved elements across multiple genomes. The tool enables rapid, whole-genome comparative analysis, aiding in the discovery of functionally significant conserved sequences.

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Ultraconserved elements are highly identical nucleotide or protein sequences crucial for biological functions.
  • These conserved regions are implicated in microRNA regulation, mRNA processing, development, and gene transcription.
  • Identifying and characterizing ultraconserved elements across genomes is vital for understanding their roles.

Purpose of the Study:

  • To develop and present a novel algorithm and freely available software for detecting ultraconserved sequences among multiple organisms.
  • To provide an efficient computational tool for large-scale, comparative genomic analyses.

Main Methods:

  • A combinatorial approach is employed to find all ultraconserved sequences without prior genome alignment.

Related Experiment Videos

  • The algorithm is optimized for speed and efficiency, outperforming BLAST for large genomes.
  • A memory-space trade-off design allows for efficient computation using modest computational resources.

    • Main Results:

    • The algorithm successfully identified 123 ultraconserved elements longer than 40 base pairs shared across 17 vertebrate genomes.
    • Thousands of non-coding, potentially functional sequences were discovered in comparisons involving the human body louse and other insects.
    • The software demonstrates significant speed advantages over existing tools like BLAST for large-scale genomic comparisons.

    Conclusions:

    • Whole-genome comparative analysis across multiple organisms is a feasible and valuable approach for biological discovery.
    • Bioinformatic tools should be designed with future-oriented considerations for analyzing multiple and large genomes.
    • The developed algorithm offers efficient computation and unique benefits for identifying ultraconserved sequences, even with limited resources.