Intrinsic Disorder in Human Proteins Encoded by Core Duplicon Gene Families

Independent expansion, selection and hypervariability of the TBC1D3 gene family in humans

TBC1D3 is a primate-specific gene family that has expanded in the human lineage and has been implicated in neuronal progenitor proliferation and expansion of the frontal cortex. The gene family and its expression have been challenging to investigate because it is embedded in high-identity and highly variable segmental duplications. We sequenced and assembled the gene family using long-read sequencing data from 34 humans and 11 nonhuman primate species. Our analysis shows that this particular gene family has independently duplicated in at least five primate lineages, and the duplicated loci are enriched at sites of large-scale chromosomal rearrangements on chromosome 17. We find that most humans vary along two TBC1D3 clusters where human haplotypes are highly variable in copy number, differing by as many as 20 copies, and structure (structural heterozygosity 90%). We also show evidence of positive selection, as well as a significant change in the predicted human TBC1D3 protein sequence. Lastly, we find that, despite multiple duplications, human TBC1D3 expression is limited to a subset of copies and, most notably, from a single paralog group: TBC1D3-CDKL. These observations may help explain why a gene potentially important in cortical development can be so variable in the human population.

Biological soft matter: intrinsically disordered proteins in liquid-liquid phase separation and biomolecular condensates

The facts that many proteins with crucial biological functions do not have unique structures and that many biological processes are compartmentalized into the liquid-like biomolecular condensates, which are formed via liquid-liquid phase separation (LLPS) and are not surrounded by the membrane, are revolutionizing the modern biology. These phenomena are interlinked, as the presence of intrinsic disorder represents an important requirement for a protein to undergo LLPS that drives biogenesis of numerous membrane-less organelles (MLOs). Therefore, one can consider these phenomena as crucial constituents of a new IDP-LLPS-MLO field. Furthermore, intrinsically disordered proteins (IDPs), LLPS, and MLOs represent a clear link between molecular and cellular biology and soft matter and condensed soft matter physics. Both IDP and LLPS/MLO fields are undergoing explosive development and generate the ever-increasing mountain of crucial data. These new data provide answers to so many long-standing questions that it is difficult to imagine that in the very recent past, protein scientists and cellular biologists operated without taking these revolutionary concepts into account. The goal of this essay is not to deliver a comprehensive review of the IDP-LLPS-MLO field but to provide a brief and rather subjective outline of some of the recent developments in these exciting fields.

Rapid prediction and analysis of protein intrinsic disorder

Protein intrinsic disorder is found in all kingdoms of life and is known to underpin numerous physiological and pathological processes. Computational methods play an important role in characterizing and identifying intrinsically disordered proteins and protein regions. Herein, we present a new high-efficiency web-based disorder predictor named Rapid Intrinsic Disorder Analysis Online (RIDAO) that is designed to facilitate the application of protein intrinsic disorder analysis in genome-scale structural bioinformatics and comparative genomics/proteomics. RIDAO integrates six established disorder predictors into a single, unified platform that reproduces the results of individual predictors with near-perfect fidelity. To demonstrate the potential applications, we construct a test set containing more than one million sequences from one hundred organisms comprising over 420 million residues. Using this test set, we compare the efficiency and accessibility (i.e., ease of use) of RIDAO to five well-known and popular disorder predictors, namely: AUCpreD, IUPred3, metapredict V2, flDPnn, and SPOT-Disorder2. We show that RIDAO yields per-residue predictions at a rate two to six orders of magnitude greater than the other predictors and completely processes the test set in under an hour. RIDAO can be accessed free of charge at https://ridao.app.