Genome Annotation and Analysis

  • Eugene V. Koonin
  • Michael Y. Galperin
Chapter

Abstract

In the preceding chapter, we gave a brief overview of the methods that are commonly used for identification of protein-coding genes and analysis of protein sequences. Here, we turn to one of the main subjects of this book, namely how these methods are applied to the task of primary analysis of genomes, which often goes under the name of “genome annotation”. Many researchers still view genome annotation as a notoriously unreliable and inaccurate process. There are excellent reasons for this opinion: genome annotation produces a considerable number of errors and some outright ridiculous “identifications” (see ♦3.1.3 and further discussion in this chapter). These errors are highly visible, even when the error rate is quite low: because of the large number of genes in most genomes, the errors are also rather numerous. Some of the problems and challenges faced by genome annotation are an issue of quantity turning into quality: an analysis that can be easily and reliably done by a qualified researcher for one or ten protein sequences becomes difficult and error-prone for the same scientist and much more so for an automated tool when the task is scaled up to 10,000 sequences. We discuss here the performance of manual, automated and mixed approaches in genome annotation and ways to avoid some common pitfalls.

Keywords

Genome Annotation Functional Prediction Archaeal Genome Domain Fusion Phosphoglycerate Mutase 
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.

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Further Reading

  1. 1.
    Brenner S. 1999. Errors in genome annotation. Trends in Genetics 15: 132–133.PubMedCrossRefGoogle Scholar
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    Galperin MY, Koonin EV 2000. Who’s your neighbor? New computational approaches for functional genomics. Nature Biotechnology 18: 609–613.PubMedCrossRefGoogle Scholar
  3. 3.
    Huynen, MA, Snel B. 2000. Gene and context: integrative approaches to genome analysis. Advances in Protein Chemistry 54: 345–379.PubMedCrossRefGoogle Scholar
  4. 4.
    Huynen MA, Snel B, Lathe W, Bork P. 2000. Predicting protein function by genomic context: quantitative evaluation and qualitative inferences. Genome Research 10: 1204–1210.PubMedCrossRefGoogle Scholar
  5. 5.
    Wolf YI, Rogozin IB, Kondrashov AS, Koonin EV. 2001. Genome alignment, evolution of prokaryotic genome organization and prediction of gene function using genomic context. Genome Research 11: 356–372.PubMedCrossRefGoogle Scholar
  6. 6.
    Makarova KS, Aravind L, Grishin NV, Rogozin IB, Koonin EV. 2002. A DNA repair system specific for thermophilic Archaea and bacteria predicted by genomic context analysis. Nucleic Acids Research 30: 482–496.PubMedCrossRefGoogle Scholar
  7. 7.
    Ouzounis CA, Karp PD. 2002. The past, present and future of genomewide re-annotation. Genome Biology 3, COMMENT2001.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2003

Authors and Affiliations

  • Eugene V. Koonin
    • 1
  • Michael Y. Galperin
    • 1
  1. 1.National Center for Biotechnology Information, National Library of MedicineNational Institutes of HealthUSA

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