A new method for detecting signal regions in ordered sequences of real numbers, and application to viral genomic data

Locations and structures of influenza A virus packaging-associated signals and other functional elements via an in silico pipeline for predicting constrained features in RNA viruses

Influenza A virus contains regions of its segmented genome associated with ability to package the segments into virions, but many such regions are poorly characterised. We provide detailed predictions of the key locations within these packaging-associated regions, and their structures, by applying a recently-improved pipeline for delineating constrained regions in RNA viruses and applying structural prediction algorithms. We find and characterise other known constrained regions within influenza A genomes, including the region associated with the PA-X frameshift, regions associated with alternative splicing, and constraint around the initiation motif for a truncated PB1 protein, PB1-N92, associated with avian viruses. We further predict the presence of constrained regions that have not previously been described. The extra characterisation our work provides allows investigation of these key regions for drug target potential, and points towards determinants of packaging compatibility between segments.

A novel approach to finding conserved features in low-variability gene alignments characterises RNA motifs in SARS-CoV and SARS-CoV-2

Collections of genetic sequences belonging to related organisms contain information on the evolutionary constraints to which the organisms have been subjected. Heavily constrained regions can be investigated to understand their roles in an organism's life cycle, and drugs can be sought to disrupt these roles. In organisms with low genetic diversity, such as newly-emerged pathogens, it is key to obtain this information early to develop new treatments. Here, we present methods that ensure we can leverage all the information available in a low-signal, low-noise set of sequences, to find contiguous regions of relatively conserved nucleic acid. We demonstrate the application of these methods by analysing over 5 million genome sequences of the recently-emerged RNA virus SARS-CoV-2 and correlating these results with an analysis of 119 genome sequences of SARS-CoV. We propose the precise location of a previously described packaging signal, and discuss explanations for other regions of high conservation.

A scale-free analysis of the HIV-1 genome demonstrates multiple conserved regions of structural and functional importance

HIV-1 replicates via a low-fidelity polymerase with a high mutation rate; strong conservation of individual nucleotides is highly indicative of the presence of critical structural or functional properties. Identifying such conservation can reveal novel insights into viral behaviour. We analysed 3651 publicly available sequences for the presence of nucleic acid conservation beyond that required by amino acid constraints, using a novel scale-free method that identifies regions of outlying score together with a codon scoring algorithm. Sequences with outlying score were further analysed using an algorithm for producing local RNA folds whilst accounting for alignment properties. 11 different conserved regions were identified, some corresponding to well-known cis-acting functions of the HIV-1 genome but also others whose conservation has not previously been noted. We identify rational causes for many of these, including cis functions, possible additional reading frame usage, a plausible mechanism by which the central polypurine tract primes second-strand DNA synthesis and a conformational stabilising function of a region at the 5' end of env.