Advertisement

A Method for Inferring Biological Functions Using Homologous Genes Among Three Genomes

  • Daniel A. S. Anjos
  • Gustavo G. Zerlotini
  • Guilherme A. Pinto
  • Maria Emilia M. T. Walter
  • Marcelo M. Brigido
  • Guilherme P. Telles
  • Carlos Juliano M. Viana
  • Nalvo F. Almeida
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4643)

Abstract

In this work, we propose n3GC, a method to infer a particular biological function in an organism, by finding homologous genes among three genomes, comparing the genes of the investigated organism with the genes of two other organisms, one having and the other not having this function. Our n3GC method takes as input previously identified families of paralogous genes in each one of the genomes, and produces a three set Venn diagram, each set representing a genome. The intersection of three (two) sets shows the families of similar genes having strong similarities among the three (two) genomes. The gene families of a genome not having strong similarities with any family of the other two genomes appear outside the intersections. We have used our method to determine potential pathogenic genes of the Paracoccidioides brasiliensis fungus, comparing it with seven fungi, three at a time, one pathogenic and the other non-pathogenic. To validate n3GC, we first investigate the Pfam classification of the families belonging to the intersections and compare with INPARANOID and 3GC methods.

Keywords

Homologous Gene Venn Diagram Strong Similarity Paralogous Gene Human Pathogenic Fungus 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Almeida, N.F.: Tools for genome comparison (in Portuguese). PhD thesis, IC-UNICAMP (2002)Google Scholar
  2. 2.
    Altschul, S.F., Lipman, D.J., Madden, T.L., Miller, W., Schaffer, A.A., Zhang, J., Zhang, Z.: Gapped blast and PSI-BLAST: a new generation of protein database search programs. Nucleic Acid Research 25(17), 3389–3402 (1997)CrossRefGoogle Scholar
  3. 3.
    Bateman, A., co-authors.: The Pfam protein families database. Nucleic Acids Research 30(1), 276–280 (2002)CrossRefGoogle Scholar
  4. 4.
    Birren, B.: Initiative Fungal Genome. A white paper for fungal comparative genomics. Whitehead Institute MIT Center for Genome (2003)Google Scholar
  5. 5.
    Braun, E.L., Halpern, A.L., Nelson, M.A., Natvig, D.O.: Large-scale comparison of fungal sequence information: mechanisms of innovation in Neurospora crassa and gene loss in Saccharomyces cerevisiae. Genome Research 10, 416–430 (2000)CrossRefGoogle Scholar
  6. 6.
    Cannon, S.B., Young, N.B.: Orthoparamap: Distinguishing orthologs from paralogs by integrating comparative genome data and gene phylogenies. BioMed. Central Bioinformatics 4, 35 (2003)CrossRefGoogle Scholar
  7. 7.
    Delcher, A.L., Kasif, S., Fleischmann, R.D., White, O., Peterson, J., Salzberg, S.L.: Alignments of whole genome. Nucleic Acid Research 27(11), 2369–2376 (1999)CrossRefGoogle Scholar
  8. 8.
    Felipe, M.S.S., co-authors: Transcriptional profiles of the human pathogenic fungus paracocidioides brasiliensis in mycelium and yeast cells. The Journal of Biological Chemistry 280(26), 24706–24714 (2005)CrossRefGoogle Scholar
  9. 9.
    Kellis, M., Patterson, N., Birren, B., Berger, B., Lander, E.S.: Methods in comparative genomics: genome correspondence, gene identification and motif discovery. Bioinformatics 11(2-3), 319–355 (2004)Google Scholar
  10. 10.
    Lee, Y., Sultana, R., Pertea, G., Cho, J., Karamycheva, S., Tsai, J., Parvizi, B., Cheung, F., Antonescu, V., White, J., Holt, I., Liang, F., Quacjenbush, J.: Cross-referencing eukaryotic genomes: TIGR orthologous gene alignments (TOGA). Genome Research 12(3), 493–502 (2002)CrossRefGoogle Scholar
  11. 11.
    Li, L., Stoeckert Jr, C.J., Roos, D.S.: OrthoMCL: Identification of ortholog groups for eukaryotic genomes. Genome Research 13(9), 2178–2189 (2003)CrossRefGoogle Scholar
  12. 12.
    Liu, Y., Liu, X.S., Wei, L., Altman, R.B., Batxoglou, S.: Eukariotic regulatory element conservation analysis and identification using comparative genomics. Genome Research 14, 451–458 (2004)CrossRefGoogle Scholar
  13. 13.
    Remm, M., Storm, C.E., Sonnhammer, E.L.: Automatic clustering of orthologs and in-paralogs from pairwise species comparisons. Journal of Molecular Biology 314(5), 1041–1052 (2001)CrossRefGoogle Scholar
  14. 14.
    Tatusov, R.L., Natale, D.A., Garkavtsev, I.V., Tatusova, T.A., Shankavaram, U.T, Rao, B.S., Kiryutin, B., Galperin, M.Y., Fedorova, N.D., Koonin, E.V.: The COG database: new developments in phylogenic classification of proteins from complete genomes. Nucleic Acids Res 29, 22–28 (2001)CrossRefGoogle Scholar
  15. 15.
    Telles, G.P., Brigido, M.M., Almeida, N.F., Viana, C.J.M., Anjos, D.A.S., Walter, M.E.M.T.: A method for comparing three genomes. Lecture Notes on Bioinformatics 3594, 160–169 (2005)Google Scholar
  16. 16.

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Daniel A. S. Anjos
    • 1
  • Gustavo G. Zerlotini
    • 1
  • Guilherme A. Pinto
    • 1
  • Maria Emilia M. T. Walter
    • 1
  • Marcelo M. Brigido
    • 2
  • Guilherme P. Telles
    • 3
  • Carlos Juliano M. Viana
    • 4
  • Nalvo F. Almeida
    • 4
  1. 1.Department of Computer Science, University of Brasília, BrasíliaBrazil
  2. 2.Institute of Biology, University of Brasília, BrasíliaBrazil
  3. 3.Institute of Mathematical Sciences and Computing, University of São Paulo, São CarlosBrazil
  4. 4.Department of Computer Science and Statistics, Federal University of Mato Grosso do Sul, Campo GrandeBrazil

Personalised recommendations