Categorical spectral analysis of periodicity in human and viral genomes

An Adaptive Mapping Method Using Spectral Envelope Approach for DNA Spectral Analysis

The digital signal processing approaches were investigated as a preliminary indicator for discriminating between the protein coding and non-coding regions of DNA. This is because a three-base periodicity (TBP) has already been proven to exist in protein-coding regions arising from the length of codons (three nucleic acids). This demonstrates that there is a prominent peak in the energy spectrum of a DNA coding sequence at frequency 13 rad/sample. However, because DNA sequences are symbolic sequences, these should be mapped into one or more signals such that the hidden information is highlighted. We propose, therefore, two new algorithms for computing adaptive mappings and, by using them, finding periodicities. Both such algorithms are based on the spectral envelope approach. This adaptive approach is essentially important since a single mapping for any DNA sequence may ignore its intrinsic properties. Finally, the improved performance of the new methods is verified by using them with synthetic and real DNA sequences as compared to the classical methods, especially the minimum entropy mapping (MEM) spectrum, which is also an adaptive method. We demonstrated that our method is both more accurate and more responsive than all its counterparts. This is especially important in this application since it reduces the risks of a coding sequence being missed.

The Heterogeneous Landscape and Early Evolution of Pathogen-Associated CpG Dinucleotides in SARS-CoV-2

COVID-19 can lead to acute respiratory syndrome, which can be due to dysregulated immune signaling. We analyze the distribution of CpG dinucleotides, a pathogen-associated molecular pattern, in the SARS-CoV-2 genome. We characterize CpG content by a CpG force that accounts for statistical constraints acting on the genome at the nucleotidic and amino acid levels. The CpG force, as the CpG content, is overall low compared with other pathogenic betacoronaviruses; however, it widely fluctuates along the genome, with a particularly low value, comparable with the circulating seasonal HKU1, in the spike coding region and a greater value, comparable with SARS and MERS, in the highly expressed nucleocapside coding region (N ORF), whose transcripts are relatively abundant in the cytoplasm of infected cells and present in the 3'UTRs of all subgenomic RNA. This dual nature of CpG content could confer to SARS-CoV-2 the ability to avoid triggering pattern recognition receptors upon entry, while eliciting a stronger response during replication. We then investigate the evolution of synonymous mutations since the outbreak of the COVID-19 pandemic, finding a signature of CpG loss in regions with a greater CpG force. Sequence motifs preceding the CpG-loss-associated loci in the N ORF match recently identified binding patterns of the zinc finger antiviral protein. Using a model of the viral gene evolution under human host pressure, we find that synonymous mutations seem driven in the SARS-CoV-2 genome, and particularly in the N ORF, by the viral codon bias, the transition-transversion bias, and the pressure to lower CpG content.

periodicDNA: an R/Bioconductor package to investigate k-mer periodicity in DNA

Periodic occurrences of oligonucleotide sequences can impact the physical properties of DNA. For example, DNA bendability is modulated by 10-bp periodic occurrences of WW (W = A/T) dinucleotides. We present periodicDNA, an R package to identify k-mer periodicity and generate continuous tracks of k-mer periodicity over genomic loci of interest, such as regulatory elements. periodicDNA will facilitate investigation and improve understanding of how periodic DNA sequence features impact function.

The heterogeneous landscape and early evolution of pathogen-associated CpG dinucleotides in SARS-CoV-2

COVID-19 can lead to acute respiratory syndrome, which can be due to dysregulated immune signaling. We analyze the distribution of CpG dinucleotides, a pathogen-associated molecular pattern, in the SARS-CoV-2 genome. We find that the CpG content, which we characterize by a force parameter that accounts for statistical constraints acting on the genome at the nucleotidic and amino-acid levels, is, on average, low compared to other pathogenic betacoronaviruses. However, the CpG force widely fluctuates along the genome, with a particularly low value, comparable to the circulating seasonal HKU1, in the spike coding region and a greater value, comparable to SARS and MERS, in the highly expressed nucleocapside coding region (N ORF), whose transcripts are relatively abundant in the cytoplasm of infected cells and present in the 3'UTRs of all subgenomic RNA. This dual nature of CpG content could confer to SARS-CoV-2 the ability to avoid triggering pattern recognition receptors upon entry, while eliciting a stronger response during replication. We then investigate the evolution of synonymous mutations since the outbreak of the COVID-19 pandemic, finding a signature of CpG loss in regions with a greater CpG force. Sequence motifs preceding the CpG-loss-associated loci in the N ORF match recently identified binding patterns of the Zinc finger Anti-viral Protein. Using a model of the viral gene evolution under human host pressure, we find that synonymous mutations seem driven in the SARS-CoV-2 genome, and particularly in the N ORF, by the viral codon bias, the transition-transversion bias and the pressure to lower CpG content.

The Heterogeneous Landscape and Early Evolution of Pathogen-Associated CpG Dinucleotides in SARS-CoV-2

SARS-CoV-2 infection can lead to acute respiratory syndrome in patients, which can be due in part to dysregulated immune signalling. We analyze here the occurrences of CpG dinucleotides, which are putative pathogen-associated molecular patterns, along the viral sequence. Carrying out a comparative analysis with other ssRNA viruses and within the Coronaviridae family, we find the CpG content of SARS-CoV-2, while low compared to other betacoronaviruses, widely fluctuates along its primary sequence. While the CpG relative abundance and its associated CpG force parameter are low for the spike protein (S) and comparable to circulating seasonal coronaviruses such as HKU1, they are much greater and comparable to SARS and MERS for the 3'-end of the viral genome. In particular, the nucleocapsid protein (N), whose transcripts are relatively abundant in the cytoplasm of infected cells and present in the 3'UTRs of all subgenomic RNA, has high CpG content. We speculate this dual  nature of CpG content can confer to SARS-CoV-2 high ability to both enter the host and trigger pattern recognition receptors (PRRs) in different contexts. We then investigate the evolution of synonymous mutations since the outbreak of the COVID-19 pandemic. Using a new application of selective forces on dinucleotides to estimate context driven mutational processes, we find that synonymous mutations seem driven both by the viral codon bias and by the high value of the CpG force in the N protein, leading to a loss in CpG content. Sequence motifs preceding these CpG-loss-associated loci match recently identified binding patterns of the Zinc Finger anti-viral Protein (ZAP) protein. Funding: This work was partially supported by the ANR19 Decrypted CE30-0021-01 grants. B.G. was supported by National Institutes of Health grants 7R01AI081848-04, 1R01CA240924-01, a Stand Up to Cancer - Lustgarten Foundation Convergence Dream Team Grant, and The Pershing Square Sohn Prize - Mark Foundation Fellow supported by funding from The Mark Foundation for Cancer Research.

A degeneration-reducing criterion for optimal digital mapping of genetic codes

Bioinformatics may seem to be a scientific field processing primarily large string datasets, as nucleotides and amino acids are represented with dedicated characters. On the other hand, many computational tasks that bioinformatics challenges are mathematical problems understandable as operations with digits. In fact, many computational tasks are solved this way in the background. One of the most widely used digital representations is mapping of nucleotides and amino acids with integers 0–3 and 0–20, respectively. The limitation of this mapping occurs when the digital signal of nucleotides has to be translated into a digital signal of amino acids as the genetic code is degenerated. This causes non-monotonies in a mapping function. Although map for reducing this undesirable effect has already been proposed, it is defined theoretically and for standard genetic codes only. In this study, we derived a novel optimal criterion for reducing the influence of degeneration by utilizing a large dataset of real sequences with various genetic codes. As a result, we proposed a new robust global optimal map suitable for any genetic code as well as specialized optimal maps for particular genetic codes.

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Optimization of 1D numerical representation for DNA to protein translation.

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Reducing genetic code degeneracy in numerical representation of DNA sequences.

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More robust numerical conversion used for genomic-proteomic analysis.

Three-base periodicity of sites of sequence variation in Pseudomonas aeruginosa and Staphylococcus aureus core genomes

The three-base periodicity property is characteristic of protein-coding sequences. Here, we report on three-base periodicity of sequence variation in the core genome of bacteria. Single nucleotide polymorphism (SNP) syntenies were extracted from pairwise genome alignments of 41 Staphylococcus aureus or 20 Pseudomonas aeruginosa strains. The length of fragment pairs with identical nucleotides at all SNP positions showed a length-dependent overrepresentation of multiples of three nucleotides at corresponding codon positions of the AT-rich S. aureus and the GC-rich P. aeruginosa. Three-base SNP periodicity seems to be a characteristic feature of the tightly arranged bacterial core genome.

Categorical spectral analysis of periodicity in nucleosomal DNA

DNA helical twist imposes geometric constraints on the location of histone–DNA interaction sites along nucleosomal DNA. Certain 10.5-bp periodic nucleotides in phase with these geometric constraints have been suggested to facilitate nucleosome positioning. However, the extent of nucleotide periodicity in nucleosomal DNA and its significance in directing nucleosome positioning still remain unclear. We clarify these issues by applying categorical spectral analysis to high-resolution nucleosome maps in two yeast species. We find that only a small fraction of nucleosomal sequences contain significant 10.5-bp periodicity. We further develop a spectral decomposition method to show that the previously observed periodicity in aligned nucleosomal sequences mainly results from proper phasing among nucleosomal sequences, and not from a preponderant occurrence of periodicity within individual sequences. Importantly, we show that this phasing may arise from the histones’ proclivity for putting preferred nucleotides at some of the evenly spaced histone–DNA contact points with respect to the dyad axis. We demonstrate that 10.5-bp periodicity, when present, significantly facilitates rotational, but not translational, nucleosome positioning. Finally, although periodicity only moderately affects nucleosome occupancy genome wide, reduced periodicity is an evolutionarily conserved signature of nucleosome-depleted regions around transcription start/termination sites.

Comparative analysis of periodicity search methods in DNA sequences

To determine the periodicity of a DNA sequence, different spectral approaches are applied (discrete Fourier transform (DFT), autocorrelation (CORR), information decomposition (ID), hybrid method (HYB), concept of spectral envelope for spectral analysis (SE), normalized autocorrelation (CORR_N) and profile analysis (PA). In this work, we investigated the possibility of finding the true period length, by depending on the average number of accumulated changes in DNA bases (PM) for the methods stated above. The results show that for periods with short length (≤4 b.p), it is possible to use the hybrid method (HYB), which combines properties of autocorrelation, Fourier transform, and information decomposition (ID). For larger period lengths (>4) with values of point mutation (PM) equal to 1.0 or more per one nucleotide, it is preferable to use information of decomposition method (ID), as the other spectral approaches cannot achieve correct determination of the period length present in the analyzed sequence.