i-ADHoRe 3.0 - Fast and Sensitive Detection of Genomic Homology in Extremely Large Data Sets
Comparative genomics is a powerful means to gain insight into the
evolutionary processes that shape the genomes of related species. As the
number of sequenced genomes increases rapidly, the development of
efficient
software applications to perform accurate cross-species analyses becomes
indispensable. However, many implementations that have the ability to
compare multiple genomes exhibit unfavorable computational and memory
requirements, effectively limiting the number of genomes that can be
analyzed in one single run. Here, we present a software package to unveil
genomic homology based on the identification of conservation of gene
content and gene order (collinearity), i-ADHoRe 3.0, and its application
to
eukaryotic genomes. The use of efficient algorithms and support for a
parallel computing environment enable the analysis of large-scale data
sets. Unlike other tools, i-ADHoRe is capable of processing the complete
Ensembl data set, containing 49 species, in less than one hour.
Furthermore, the profile search is more sensitive to detect degenerate
genomic homology than chaining pairwise collinearity information based on
transitive homology. From ultra-conserved collinear regions between
mammals
and birds, by integrating coexpression information and experimental
protein-protein interactions, we identified more than 400 regions in the
human genome showing significant functional coherence. Finally, the impact
of low coverage and fragmented genomes on the detection of collinearity
was
examined. The different algorithmic improvements ensure that i-ADHoRe 3.0
will continue to be a powerful tool to study genome evolution.
* Proost, S., * Fostier, J., De Witte, D., Dhoedt, B., Demeester, P., Van de Peer, Y., Vandepoele, K. (2012) i-ADHoRe 3.0 - Fast and Sensitive Detection of Genomic Homology in Extremely Large Data Sets. Nucleic Acids Res. 40(2):e11. *contributed equally |
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