DOI: 10.5061/dryad.n8pk0p2sd
title: Footprint of the host restriction factors APOBEC3 on the genome of human viruses

description: APOBEC3 enzymes are innate immune effectors that introduce mutations into
 viral genomes. These enzymes are cytidine deaminases which transform
 cytosine into uracil. They preferentially mutate cytidine preceded by
 thymidine making the 5’TC motif their favored target. Viruses have evolved
 different strategies to evade APOBEC3 restriction. Certain viruses
 actively encode viral proteins antagonizing the APOBEC3s, others passively
 face the APOBEC3 selection pressure thanks to a depleted genome for
 APOBEC3-targeted motifs. Hence, the APOBEC3s left on the genome of certain
 viruses an evolutionary footprint. The aim of our study is the
 identification of these viruses having a genome shaped by the APOBEC3s. We
 analyzed the genome of 33,400 human viruses for the depletion of
 APOBEC3-favored motifs. We demonstrate that the APOBEC3 selection pressure
 impacts at least 22% of all currently annotated human viral species. The
 papillomaviridae and polyomaviridae are the most intensively footprinted
 families; evidencing a selection pressure acting genome-wide and on both
 strands. Members of the parvoviridae family are differentially targeted in
 term of both magnitude and localization of the footprint. Interestingly, a
 massive APOBEC3 footprint is present on both strands of the B19
 erythroparvovirus; making this viral genome one of the most cleaned
 sequences for APOBEC3-favored motifs. We also identified the endemic
 coronaviridae as significantly footprinted. Interestingly, no such
 footprint has been detected on the zoonotic MERS-CoV, SARS-CoV-1 and
 SARS-CoV-2 coronaviruses. In addition to viruses that are footprinted
 genome-wide, certain viruses are footprinted only on very short sections
 of their genome. That is the case for the gamma-herpesviridae and
 adenoviridae where the footprint is localized on the lytic origins of
 replication. A mild footprint can also be detected on the negative strand
 of the reverse transcribing HIV-1, HIV-2, HTLV-1 and HBV viruses.
 Together, our data illustrate the extent of the APOBEC3 selection pressure
 on the human viruses and identify new putatively APOBEC3-targeted viruses.
description: The A3 evolutionary footprint
 left on viral genomes is defined as the under-representation of
 A3-targeted motifs. Because most of the A3
 proteins favors deamination of cytosine to uracil in a 5’TC dinucleotide
 context, we have chosen to look for the under-representation of the 5’TC
 motif. We differentiate three K-mers containing the TC motif; one K-mer
 having the C in the first position of the codon
 (NNTCNN), one K-mer having the C in the second position
 of the codon (TCN) and one K-mer having the C in the
 third position of the codon (NTC). A3-introduced
 deamination of cytosine in viral
 genome produces an uracil that can be fixed in the form of thymidine after
 genome replication. This transition will have different impacts depending
 on the position of the mutated C. The C to T mutation will be
 non-synonymous if the C is at the first or second position of the codon.
 However, if the mutated C occupies the third position of the codon, the C
 to T mutation will always be synonymous. Therefore, A3-driven natural
 selection should deplete more intensively NTC codons than TCN or NNTCNN
 motifs (as in those cases the C to U mutation will impact the encoded
 amino acid). Obviously, A3 editing can also target the template strand
 where a C to T mutation will translate into G to A transition in the
 coding strand. Again, this transition will have different impacts
 depending on the position of the mutated G. The G to A mutation will be
 non-synonymous if the G is at the first or second position of the codon
 (Fig 1A, GAN and NGA K-mers). However, if the mutated G occupies the third
 position of the codon the mutation will be most of the time synonymous.
 Because synonymous mutations are presumably more likely to be retained
 than non-synonymous, we define the A3 footprint  as the depletion of NTC
 or NNGANN K-mers. We downloaded
 complete viral genomes from the “NCBI Virus” database (as released in
 April 2020) and computed observed vs expected K-mer
 ratios. Briefly, a
 synthetic coding genome was generated by concatenating the different
 coding sequences allowing the counting of the occurrence of a given K-mer
 (n obs (K-mer)). Each synthetic coding genome has been randomly shuffled a
 thousand times. The expected count is calculated as the average of the
 occurrences of this K-mer over the thousand iterations (n exp (K-mer)). A
 negative K-mer ratio indicates depletion of that K-mer. The observed vs
 expected ratio of the NTC K-mer will be compared to those of the NNTCNN
 and TCN K-mers. Similarly, the observed vs expected ratio of the NNGANN
 K-mer will be compared to those of the GAN and NGA
 K-mers.
description: S1 Table:
 Genomic K-mer ratios for human viruses. Observed/expected K-mer ratios
 for each genomic human viral sequence.   S2 Table:
 Genic K-mer ratios for human viruses. Observed/expected K-mer ratios
 for each genic human viral sequence.   S3 Table:
 Genomic K-mer ratios for non-human viruses. Observed/expected K-mer ratios
 for each genomic and genic non-human viral
 sequence.