Literature DB >> 25736992

Detection of orphan domains in Drosophila using "hydrophobic cluster analysis".

Tristan Bitard-Feildel1, Magdalena Heberlein1, Erich Bornberg-Bauer2, Isabelle Callebaut3.   

Abstract

INTRODUCTION: Comparative genomics has become an important strategy in life science research. While many genes, and the proteins they code for, can be well characterized by assigning orthologs, a significant amount of proteins or domains remain obscure "orphans". Some orphans are overlooked by current computational methods because they rapidly diverged, others emerged relatively recently (de novo). Recent research has demonstrated the importance of orphans, and of de novo proteins and domains for development of new phenotypic traits and adaptation. New approaches for detecting novel domains are thus of paramount importance.
RESULTS: The hydrophobic cluster analysis (HCA) method delineates globular-like domains from the information of a protein sequence and thereby allows bypassing some of the established methods limitations based on conserved sequence similarity. In this study, HCA is tested for orphan domain detection on 12 Drosophila genomes. After their detection, the oprhan domains are classified into two categories, depending on their presence/absence in distantly related species. The two categories show significantly different physico-chemical properties when compared to previously characterized domains from the Pfam database. The newly detected domains have a higher degree of intrinsic disorder and a particular hydrophobic cluster composition. The older the domains are, the more similar their hydrophobic cluster content is to the cluster content of Pfam domains. The results suggest that, over time, newly created domains acquire a canonical set of hydrophobic clusters but conserve some features of intrinsically disordered regions.
CONCLUSION: Our results agree with previous findings on orphan domains and suggest that the physico-chemical properties of domains change over evolutionary long time scale. The presented HCA-based method is able to detect domains with unusual properties without relying on prior knowledge, such as the availability of homologs. Therefore, the method has large potential for complementing existing strategies to annotate genomes, and for better understanding how molecular features emerge.
Copyright © 2015 Elsevier B.V. and Société Française de Biochimie et Biologie Moléculaire (SFBBM). All rights reserved.

Entities:  

Keywords:  Domain detection; Domain evolution; Intrinsically disordered domain; Protein domain

Mesh:

Substances:

Year:  2015        PMID: 25736992     DOI: 10.1016/j.biochi.2015.02.019

Source DB:  PubMed          Journal:  Biochimie        ISSN: 0300-9084            Impact factor:   4.079


  11 in total

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Review 2.  Computational Identification of Novel Genes: Current and Future Perspectives.

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Journal:  Bioinform Biol Insights       Date:  2016-08-01

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Authors:  Jonathan F Schmitz; Erich Bornberg-Bauer
Journal:  F1000Res       Date:  2017-01-19

4.  Improving pairwise comparison of protein sequences with domain co-occurrence.

Authors:  Christophe Menichelli; Olivier Gascuel; Laurent Bréhélin
Journal:  PLoS Comput Biol       Date:  2018-01-02       Impact factor: 4.475

5.  High GC content causes orphan proteins to be intrinsically disordered.

Authors:  Walter Basile; Oxana Sachenkova; Sara Light; Arne Elofsson
Journal:  PLoS Comput Biol       Date:  2017-03-29       Impact factor: 4.475

6.  Exploring the dark foldable proteome by considering hydrophobic amino acids topology.

Authors:  Tristan Bitard-Feildel; Isabelle Callebaut
Journal:  Sci Rep       Date:  2017-01-30       Impact factor: 4.379

7.  De novo gene birth.

Authors:  Stephen Branden Van Oss; Anne-Ruxandra Carvunis
Journal:  PLoS Genet       Date:  2019-05-23       Impact factor: 5.917

8.  A Continuum of Evolving De Novo Genes Drives Protein-Coding Novelty in Drosophila.

Authors:  Brennen Heames; Jonathan Schmitz; Erich Bornberg-Bauer
Journal:  J Mol Evol       Date:  2020-04-07       Impact factor: 2.395

9.  Structural and functional characterization of a putative de novo gene in Drosophila.

Authors:  Andreas Lange; Prajal H Patel; Brennen Heames; Adam M Damry; Thorsten Saenger; Colin J Jackson; Geoffrey D Findlay; Erich Bornberg-Bauer
Journal:  Nat Commun       Date:  2021-03-12       Impact factor: 14.919

10.  Robustness by intrinsically disordered C-termini and translational readthrough.

Authors:  April Snofrid Kleppe; Erich Bornberg-Bauer
Journal:  Nucleic Acids Res       Date:  2018-11-02       Impact factor: 16.971

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