Profiles of low complexity regions in Apicomplexa.

Area of Science:

• Genomics
• Evolutionary Biology
• Bioinformatics

Background:

• Low complexity regions (LCRs) are common in genomes, but their evolutionary paths and functions remain poorly understood.
• Prior research presents conflicting evidence regarding neutral versus selective evolutionary forces acting on LCRs, potentially due to identification methods.
• Investigating LCRs requires robust methods to clarify their evolutionary dynamics.

Purpose of the Study:

• To explore the impact of parameter choices on evolutionary inferences of LCRs.
• To establish species-specific proteome complexity profiles using a multi-threshold approach.
• To compare LCR sets and understand how identification parameters influence evolutionary conclusions.

Main Methods:

• Employed a multiple threshold strategy to define species-specific LCR profiles.
• Analyzed the properties of identified LCR sets to assess parameter influence.
• Compared LCR profiles across species to infer evolutionary mechanisms.

Main Results:

• Each species exhibits a unique quantitative LCR profile, despite qualitative similarities.
• LCR profiles enable accurate comparative analyses of genome complexity and repetitiveness.
• Neutral evolution predominates in highly repetitive LCRs (homopolymers), while selective forces increase with LCR heterogeneity.

Conclusions:

• Evolutionary inferences drawn from LCRs are sensitive to the parameters used for their identification.
• LCRs comprise diverse regions (homo- and heteropolymers) with distinct evolutionary drivers.
• LCR profiles offer a novel framework for cross-species genome complexity research and evolutionary mechanism determination.