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Large-Scale Evolutionary Patterns of Protein Domain Distributions in Eukaryotes

View ORCID ProfileArli A. Parikesit, Peter F. Stadler, Sonja J. Prohaska
doi: https://doi.org/10.1101/142182
Arli A. Parikesit
1Computational EvoDevo Research Group, Institute of Computer Science, University of Leipzig, Härtelstraße 16–18, D-04103, Leipzig, Germany
2Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstraße 16–18, D-04107 Leipzig, Germany
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  • For correspondence: sonja@bioinf.uni-leipzig.de
Peter F. Stadler
2Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstraße 16–18, D-04107 Leipzig, Germany
3Bioinformatics Group, Institute of Computer Science, University of Leipzig, Härtelstraße 16-18, D-04103, Leipzig, Germany
4Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, D-04103 Leipzig, Germany
5Fraunhofer Institut für Zelltherapie und Immunologie Perlickstraße 1, D-04103 Leipzig, Germany
6Department of Theoretical Chemistry, University of Vienna, Währingerstraße 17, A-1090 Wien, Austria
7Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, DK-1870 Frederiksberg C, Denmark
8Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USA
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  • For correspondence: Peter.Stadler@bioinf.uni-leipzig.de
Sonja J. Prohaska
1Computational EvoDevo Research Group, Institute of Computer Science, University of Leipzig, Härtelstraße 16–18, D-04103, Leipzig, Germany
2Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstraße 16–18, D-04107 Leipzig, Germany
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  • For correspondence: sonja@bioinf.uni-leipzig.de
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Abstract

The genomic inventory of protein domains is an important indicator of an organism’s regulatory and metabolic capabilities. Existing gene annotations, however, can be plagued by substantial ascertainment biases that make it difficult to obtain and compare quantitative domain data. We find that quantitative trends across the Eukarya can be investigated based on a combination of gene prediction and standard domain annotation pipelines. Species-specific training is required, however, to account for the genomic peculiarities in many lineages. In contrast to earlier studies we find wide-spread statistically significant avoidance of protein domains associated with distinct functional high-level gene-ontology terms.

1998 ACM Subject Classification J.3 Life and Medical Sciences

Footnotes

  • * This work was supported in part by DAAD (German Academic Exchange Service).

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted May 27, 2017.
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Large-Scale Evolutionary Patterns of Protein Domain Distributions in Eukaryotes
Arli A. Parikesit, Peter F. Stadler, Sonja J. Prohaska
bioRxiv 142182; doi: https://doi.org/10.1101/142182
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Large-Scale Evolutionary Patterns of Protein Domain Distributions in Eukaryotes
Arli A. Parikesit, Peter F. Stadler, Sonja J. Prohaska
bioRxiv 142182; doi: https://doi.org/10.1101/142182

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