SpringerProtocols: Abstract: 6. Positive Selection Scanning of Parasite DNA Sequences

6. Positive Selection Scanning of Parasite DNA Sequences

By: Winston A. Hide², Raphael D. Isokpehi²

Abstract

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Parasites successfully exist within the host as a result of highly specific genetic adaptations. Therefore, detecting genes that contain relevant adaptive mutations can provide a guide to biological processes that are potentially essential to the parasite. Random genetic mutations that confer selective advantage can act to alter amino acids so as to confer gain of function that has positive impact on the survival of the parasite. Directional selection of advantageous mutations results from an elevated rate of nonsynonymous substitutions in rapidly evolving genes. Genes on which this positive selection operates are considered to have an evolutionary characteristic such that the normalized number of nonsynonymous (dn) substitutions is greater than that of synonymous (ds) substitutions. By searching in a statistically robust way for genes that contain this characteristic, it is possible to apply a stringent method to identify genes that may be under positive selection and thus to identify biological processes involving those genes that are essential to the survival of the parasite. Genes detected typically class into those under host immune surveillance and those intrinsic to pathways essential to survival of the parasite within the host. Depending on their function and location of protein expression, such genes have the potential to provide exceptional vaccine and drug candidates.

Affiliation(s): (2) Pathogen Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa

Book Title: Parasite Genomics Protocols

Series: Methods in Molecular Biology | Volume: 270 | Pub. Date: May-17-2004 | Page Range: 127-150 | DOI: 10.1385/1-59259-793-9:127

Subject: Genetics/Genomics

Key Words: Drug targets - parasites - pathogenicity: positive selection - vaccine candidates - virulence

References

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1.	Nei, M. and Gojobori, T. (1986) Simple methods for estimating the numbers of synonymous and nonsynonymous nucleotide substitutions. Mol. Biol. Evol. 3, 418–426.

2.	Hughes, A. L. (1992) Positive selection and intra-allelic recombination at the merozoite surface antigen-1 (MSA-1) locus of Plasmodium falciparum. Mol. Biol. Evol. 9, 381–393.

3.	Yang, Z. and Bielawski, J. P. (2000) Statistical methods for detecting molecular adaptation. Trends Ecol. Evol. 15, 496–503.

4.	Zhang, J., Kumar, S., and Nei, M. (1997) Small-sample tests of episodic adaptive evolution: a case study of primate lysozymes. Mol. Biol. Evol. 14, 1335–1338.

5.	Zhang, J., Rosenberg, H. F., and Nei, M. (1998) Positive Darwinian selection after gene duplication in primate ribonuclease genes. Proc. Natl. Acad. Sci. USA 95, 3708–3713.

6.	Endo, T., Ikeo, K., and Gojobori, T. (1996) Large-scale search for genes on which positive selection may operate. Mol. Biol. Evol. 13, 685–690.

7.	Benner, S. A., Chamberlin, S. G., Liberles, D. A., et al. (2000) Functional inferences from reconstructed evolutionary biology involving rectified databases—an evolutionarily grounded approach to functional genomics. Res. Microbiol. 151, 97–106.

8.	Liberles, D. A., Schreiber, D. R., Govindarajan, S., et al. (2001) The adaptive evolution database (TAED). Genome Biol. 2, RESEARCH0028.

9.	Davids, W., Gamieldien, J., Liberles, D. A., et al. (2002) Positive selection scanning reveals decoupling of enzymatic activities of carbamoyl phosphate synthetase in Helicobacter pylori. J. Mol. Evol. 54, 458–464.

10.	Coppel, R. L. (2001) Bioinformatics and the malaria genome: facilitating access and exploitation of sequence information. Mol. Biochem. Parasitol. 118, 139–145.

11.	Prichard, R. and Tait, A (2001) The role of molecular biology in veterinary parasitology. Vet. Parasitol. 98, 169–194.

12.	Gardner, M. J., Hall, N., Fung, E., et al. (2002) Genome sequence of the human malaria parasite Plasmodium falciparum. Nature 419, 498–511.

13.	Carlton, J. M., Angiuoli, S. V., Suh, B. B., et al. (2002) Genome sequence and comparative analysis of the model rodent malaria parasite Plasmodium yoelii yoelii. Nature 419, 512–519.

14.	Escalante, A. A., Lal, A. A., and Ayala, F. (1998) Genetic polymorphism and natural selection in the malaria parasite Plasmodium falciparum. Genetics 149, 189–202.

15.	Black, C. G. and Coppel, R. L. (2000) Synonymous and nonsynonymous mutations in a region of the Plasmodium chabaudi genome and evidence for selection acting on a malaria vaccine candidate. Mol. Biochem. Parasitol. 111, 447–451.

16.	Tatusov, R. L., Galperin, M. Y., Natale, D. A., et al. (2000) The COG database: a tool for genome-scale analysis of protein functions and evolution. Nucleic Acids Res. 28, 33–36.

17.	Pearson, W. R. (1990) Rapid and sensitive comparison with FASTA and FASTP. Methods Enzymol. 183, 63–68.

18.	Altschul, S. F., Madden. T. L., Schaffer, A. A., et al. (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25, 338–3402.

19.	Heinkoff, S. and Heinkoff, C. (1993) Performance evaluation of amino acid substitution matrices. Proteins 17, 49–61.

20.	Clarke, B., Lambrecht, M., and Rhee, S. Y. (2003) Arabidopsis genomic information for interpreting wheat EST sequences. Funct. Integr. Genomics 3, 33–38.

21.	Fay, J. C. and Wu, C.-I. (2003) Sequence divergence, functional constraint and selection in protein evolution. Annu. Rev. Genomics Hum. Genet. 4, 213–235.

22.	Remm, M., Storm, C. V., and Sonnhammer, E. L. L. (2001) Automatic clustering of orthologs and in-paralogs from pairwise species comparisons. J. Mol. Biol. 314, 1041–1052.

23.	Eisen, J. A. and Wu, M. (2002) Phylogenetic analysis and gene functional predictions: phylogenomics in action. Theor. Popul. Biol. 61, 481–487.

24.	Storm, C. E. and Sonnhammer, E. L. (2002) Automated ortholog inference from phylogenetic trees and calculation of orthology reliability. Bioinformatics 18, 92–99.

25.	Zdobnov, E. M. and Apweiler, R. (2001) InterProScan—an integration platform for the signature-recognition methods in InterPro. Bioinformatics 17, 847–848.

26.	Thompson, J. D., Gibson, T. J., Plewniak, F., et al. (1997) The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res. 25, 4876–4882.

27.	Bielawski, J. P., Dunn, K. A., and Yang, Z. (2000) Rates of nucleotide substitution and mammalian nuclear gene evolution: approximate and maximum-likelihood methods lead to different conclusions. Genetics 156, 1299–1308.

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