Loading...
Profiles of low complexity regions in Apicomplexa Genome evolution and evolutionary systems biology
Battistuzzi, FU Schneider, KA Spencer, MK Fisher, D Chaudhry, S Escalante, AA
Battistuzzi, FU
Schneider, KA
Spencer, MK
Fisher, D
Chaudhry, S
Escalante, AA
Citations
Altmetric:
Genre
Journal Article
Date
2016-02-29
Advisor
Committee member
Group
Department
Permanent link to this record
Collections
Research Projects
Organizational Units
Journal Issue
DOI
10.1186/s12862-016-0625-0
Abstract
© 2016 Battistuzzi et al. Background: Low complexity regions (LCRs) are a ubiquitous feature in genomes and yet their evolutionary history and functional roles are unclear. Previous studies have shown contrasting evidence in favor of both neutral and selective mechanisms of evolution for different sets of LCRs suggesting that modes of identification of these regions may play a role in our ability to discern their evolutionary history. To further investigate this issue, we used a multiple threshold approach to identify species-specific profiles of proteome complexity and, by comparing properties of these sets, determine the influence that starting parameters have on evolutionary inferences. Results: We find that, although qualitatively similar, quantitatively each species has a unique LCR profile which represents the frequency of these regions within each genome. Inferences based on these profiles are more accurate in comparative analyses of genome complexity as they allow to determine the relative complexity of multiple genomes as well as the type of repetitiveness that is most common in each. Based on the multiple threshold LCR sets obtained, we identified predominant evolutionary mechanisms at different complexity levels, which show neutral mechanisms acting on highly repetitive LCRs (e.g., homopolymers) and selective forces becoming more important as heterogeneity of the LCRs increases. Conclusions: Our results show how inferences based on LCRs are influenced by the parameters used to identify these regions. Sets of LCRs are heterogeneous aggregates of regions that include homo-and heteropolymers and, as such, evolve according to different mechanisms. LCR profiles provide a new way to investigate genome complexity across species and to determine the driving mechanism of their evolution.
Description
Citation
Citation to related work
Springer Science and Business Media LLC
Has part
BMC Evolutionary Biology
ADA compliance
For Americans with Disabilities Act (ADA) accommodation, including help with reading this content, please contact scholarshare@temple.edu