Profiles of low complexity regions in Apicomplexa

Abstract

BackgroundLow 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.ResultsWe 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.ConclusionsOur 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12862-016-0625-0) contains supplementary material, which is available to authorized users.

Evolution of the merozoite surface protein 7 ( msp7 ) family in Plasmodium vivax and P . falciparum : A comparative approach

“…Whereas the overall genetic polymorphism of msp7 paralogs appears to be under functional constraint (purifying selection), positive selection may also interact with low complexity regions (Battistuzzi et al, 2016). However, this hypothesis cannot be tested with the evolutionary genetic analyses used in this investigation.…”

“…Low complexity regions were not included because their alignment is unreliable (Battistuzzi et al, 2016) and cannot be studied with the type of genetic and phylogenetic analyses used in this investigation. Genetic diversity was calculated as ྐ among different isolates and for each msp7 paralog of P. falciparum, P. vivax, P. cynomolgi, P. inui and P. knowlesi using MEGA 6.06 (Tamura et al, 2013).…”

“…These two species differ in many epidemiologic and biologic characteristics including features in their genomes. In particular, they markedly diverge in terms of G+C content in their exons, frequency of low complexity regions, and some distinctive multigene families (Battistuzzi et al, 2016; Frech and Chen, 2011). …”

Evolution of the Transmission-Blocking Vaccine Candidates Pvs28 and Pvs25 in Plasmodium vivax: Geographic Differentiation and Evidence of Positive Selection

“…The evolutionary and functional implications of LCR in P28 proteins are still elusive. In the case of asexual Plasmodium stages, they may have a role interacting with the host adaptive immune system [ 66 , 67 ]. However, such adaptive immune responses are absent in Anopheles vectors with the exception of some components from the vertebrate immune system contained in the blood bolus.…”

Interrelation of Prions With Non-Coding Rnas

“…LCRs can differ by their recapitulation degree (periodic or aperiodic motifs) and by their composition (homogeneous or heterogeneous). LCRs commonly include micro-and minisatellites, simple repeated sequences, homopolymers, genome heteropolymers, and amino-acid repeated sequences in proteins (Battistuzzi et al, 2016), e.g. glutamine/asparagines (Q/N)-rich domains.…”