Fourier spectral density of the coronavirus genome

Tan, H.S.

We present an analysis of the coronavirus RNA genome via a study of its Fourier spectral density based on a binary representation of the nucleotide sequence. We find that at low frequencies, the power spectrum presents a small and distinct departure from the behavior expected from an uncorrelated sequence. We provide a couple of simple models to characterize such deviations. Away from a small low-frequency domain, the spectrum presents largely stochastic fluctuations about fixed values which vary inversely with the genome size generally. It exhibits no other peaks apart from those associated with triplet codon usage. We uncover an interesting, new scaling law for the coronavirus genome: the complexity of the genome scales linearly with the power-law exponent that characterizes the enveloping curve of the low-frequency domain of the spectral density.