Assessing the low complexity of protein sequences via the low complexity triangle

Terminal regions of a protein are a hotspot for low complexity regions and selection

Volatile low complexity regions (LCRs) are a novel source of adaptive variation, functional diversification and evolutionary novelty. An interplay of selection and mutation governs the composition and length of low complexity regions. High %GC and mutations provide length variability because of mechanisms like replication slippage. Owing to the complex dynamics between selection and mutation, we need a better understanding of their coexistence. Our findings underscore that positively selected sites (PSS) and low complexity regions prefer the terminal regions of genes, co-occurring in most Tetrapoda clades. We observed that positively selected sites within a gene have position-specific roles. Central-positively selected site genes primarily participate in defence responses, whereas terminal-positively selected site genes exhibit non-specific functions. Low complexity region-containing genes in the Tetrapoda clade exhibit a significantly higher %GC and lower ω (dN/dS: non-synonymous substitution rate/synonymous substitution rate) compared with genes without low complexity regions. This lower ω implies that despite providing rapid functional diversity, low complexity region-containing genes are subjected to intense purifying selection. Furthermore, we observe that low complexity regions consistently display ubiquitous prevalence at lower purity levels, but exhibit a preference for specific positions within a gene as the purity of the low complexity region stretch increases, implying a composition-dependent evolutionary role. Our findings collectively contribute to the understanding of how genetic diversity and adaptation are shaped by the interplay of selection and low complexity regions in the Tetrapoda clade.

Optimizing strategy for the discovery of compositionally-biased or low-complexity regions in proteins

Proteins can contain tracts dominated by a subset of amino acids and that have a functional significance. These are often termed 'low-complexity regions' (LCRs) or 'compositionally-biased regions' (CBRs). However, a wide spectrum of compositional bias is possible, and program parameters used to annotate these regions are often arbitrarily chosen. Also, investigators are sometimes interested in longer regions, or sometimes very short ones. Here, two programs for annotating LCRs/CBRs, namely SEG and fLPS, are investigated in detail across the whole expanse of their parameter spaces. In doing so, boundary behaviours are resolved that are used to derive an optimized systematic strategy for annotating LCRs/CBRs. Sets of parameters that progressively annotate or 'cover' more of protein sequence space and are optimized for a given target length have been derived. This progressive annotation can be applied to discern the biological relevance of CBRs, e.g., in parsing domains for experimental constructs and in generating hypotheses. It is also useful for picking out candidate regions of interest of a given target length and bias signature, and for assessing the parameter dependence of annotations. This latter application is demonstrated for a set of human intrinsically-disordered proteins associated with cancer.

fLPS 2.0: rapid annotation of compositionally-biased regions in biological sequences

Compositionally-biased (CB) regions in biological sequences are enriched for a subset of sequence residue types. These can be shorter regions with a concentrated bias (i.e., those termed ‘low-complexity’), or longer regions that have a compositional skew. These regions comprise a prominent class of the uncharacterized ‘dark matter’ of the protein universe. Here, I report the latest version of the fLPS package for the annotation of CB regions, which includes added consideration of DNA sequences, to label the eight possible biased regions of DNA. In this version, the user is now able to restrict analysis to a specified subset of residue types, and also to filter for previously annotated domains to enable detection of discontinuous CB regions. A ‘thorough’ option has been added which enables the labelling of subtler biases, typically made from a skew for several residue types. In the output, protein CB regions are now labelled with bias classes reflecting the physico-chemical character of the biasing residues. The fLPS 2.0 package is available from: https://github.com/pmharrison/flps2 or in a Supplemental File of this paper.

The Conservation of Low Complexity Regions in Bacterial Proteins Depends on the Pathogenicity of the Strain and Subcellular Location of the Protein

Low complexity regions (LCRs) in proteins are characterized by amino acid frequencies that differ from the average. These regions evolve faster and tend to be less conserved between homologs than globular domains. They are not common in bacteria, as compared to their prevalence in eukaryotes. Studying their conservation could help provide hypotheses about their function. To obtain the appropriate evolutionary focus for this rapidly evolving feature, here we study the conservation of LCRs in bacterial strains and compare their high variability to the closeness of the strains. For this, we selected 20 taxonomically diverse bacterial species and obtained the completely sequenced proteomes of two strains per species. We calculated all orthologous pairs for each of the 20 strain pairs. Per orthologous pair, we computed the conservation of two types of LCRs: compositionally biased regions (CBRs) and homorepeats (polyX). Our results show that, in bacteria, Q-rich CBRs are the most conserved, while A-rich CBRs and polyA are the most variable. LCRs have generally higher conservation when comparing pathogenic strains. However, this result depends on protein subcellular location: LCRs accumulate in extracellular and outer membrane proteins, with conservation increased in the extracellular proteins of pathogens, and decreased for polyX in the outer membrane proteins of pathogens. We conclude that these dependencies support the functional importance of LCRs in host–pathogen interactions.

The Role of Low Complexity Regions in Protein Interaction Modes: An Illustration in Huntingtin

Low complexity regions (LCRs) are very frequent in protein sequences, generally having a lower propensity to form structured domains and tending to be much less evolutionarily conserved than globular domains. Their higher abundance in eukaryotes and in species with more cellular types agrees with a growing number of reports on their function in protein interactions regulated by post-translational modifications. LCRs facilitate the increase of regulatory and network complexity required with the emergence of organisms with more complex tissue distribution and development. Although the low conservation and structural flexibility of LCRs complicate their study, evolutionary studies of proteins across species have been used to evaluate their significance and function. To investigate how to apply this evolutionary approach to the study of LCR function in protein-protein interactions, we performed a detailed analysis for Huntingtin (HTT), a large protein that is a hub for interaction with hundreds of proteins, has a variety of LCRs, and for which partial structural information (in complex with HAP40) is available. We hypothesize that proteins RASA1, SYN2, and KAT2B may compete with HAP40 for their attachment to the core of HTT using similar LCRs. Our results illustrate how evolution might favor the interplay of LCRs with domains, and the possibility of detecting multiple modes of LCR-mediated protein-protein interactions with a large hub such as HTT when enough protein interaction data is available.