Nonstructural Proteins Are Preferential Positive Selection Targets in Zika Virus and Related Flaviviruses

<div><p>The <i>Flavivirus</i> genus comprises several human pathogens such as dengue virus (DENV), Japanese encephalitis virus (JEV), and Zika virus (ZIKV). Although ZIKV usually causes mild symptoms, growing evidence is linking it to congenital birth defects and to increased risk of Guillain-Barré syndrome. ZIKV encodes a polyprotein that is processed to produce three structural and seven nonstructural (NS) proteins. We investigated the evolution of the viral polyprotein in ZIKV and in related flaviviruses (DENV, Spondweni virus, and Kedougou virus). After accounting for saturation issues, alignment uncertainties, and recombination, we found evidence of episodic positive selection on the branch that separates DENV from the other flaviviruses. NS1 emerged as the major selection target, and selected sites were located in immune epitopes or in functionally important protein regions. Three of these sites are located in an NS1 region that interacts with structural proteins and is essential for virion biogenesis. Analysis of the more recent evolutionary history of ZIKV lineages indicated that positive selection acted on NS5 and NS4B, this latter representing the preferential target. All selected sites were located in the N-terminal portion of NS4B, which inhibits interferon response. One of the positively selected sites (26M/I/T/V) in ZIKV also represents a selection target in sylvatic DENV2 isolates, and a nearby residue evolves adaptively in JEV. Two additional positively selected sites are within a protein region that interacts with host (e.g. STING) and viral (i.e. NS1, NS4A) proteins. Notably, mutations in the NS4B region of other flaviviruses modulate neurovirulence and/or neuroinvasiveness. These results suggest that the positively selected sites we identified modulate viral replication and contribute to immune evasion. These sites should be prioritized in future experimental studies. However, analyses herein detected no selective events associated to the spread of the Asian/American ZIKV lineage.</p></div

Positively selected sites in ZIKV polyprotein.

<p>Positively selected sites in ZIKV polyprotein.</p

Branch-site analyses of the flavivirus polyprotein (nonstructural region).

<p>Branch-site analyses of the flavivirus polyprotein (nonstructural region).</p

Ongoing positive selection in ZIKV isolates.

<p>(A) Maximum likelihood phylogeny for the nonstructural region (nucleotides 2371 to 8994). Amino acids at the five selected sites are shown for all ZIKV sequences. Viruses isolated from mosquitos and macaques are denoted with hash and asterisk symbols, respectively. Branch length is proportional to nucleotide substitutions per codon. Bootstrap values for internal branches >75% are shown. The phylogenetic tree is unrooted. (B) TMHMM prediction of transmembrane helices (TMH1-5) for the ZIKV NS4B protein and schematic representation of protein topology. Positively selected sites in the flavivirus phylogeny and in ZIKV strains are indicated by red and green triangles, respectively. Amino acid alignments of the regions surrounding selected sites are shown for 5 representative ZIKV, for DENV sequences belonging to the four serotypes, for JEV (NC_001437), and for WNV (strain NY-99, NC_001563). In the alignment, positively selected sites in ZIKV are shown in green; sites that are positively selected in other flaviviruses are marked in magenta. (C) Immune epitope mapping on NS5. Cyan bars indicate the number of epitopes overlapping each NS5 residue. Positively selected sites are colored as above. Mtase: methyltransferase domain; RdRp: RNA-dependent RNA polymerase domain.</p

Different selective pressures acting on flavivirus polyproteins.

<p>(A) Schematic representation of the ZIKV polyprotein. Proteins are colored in hues of blue depending on the percentage of negatively selected sites in ZIKV strains. The location of recombination breakpoints in flaviviruses and ZIKV is shown by striped rectangles. Positively selected sites in the flavivirus phylogeny and in ZIKV strains are colored in red and green, respectively. (B) Maximum likelihood unrooted tree for the flavivirus phylogeny. Branches analyzed in the branch-site tests are indicated with capital letters, with red indicating statistically significant evidence of positive selection. Branch length is proportional to nucleotide substitutions per codon. Bootstrap values for internal branches >75% are shown. See <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0004978#pntd.0004978.s002" target="_blank">S1 Table</a> for accession number and full names of analyzed viruses. (C) Immune epitope mapping and schematic representation of NS1 domains. Cyan bars indicate the number of epitopes overlapping each NS1 residue. Positively selected sites are also shown.</p

inter-species trees

Trees used in inter-species analyse

inter-species alignments

Alignments used in inter-species analyse

gammaMap_input_files

Input files used for the population genetics-phylogenetics analysi

Additional file 1: Table S1. of Determining multiallelic complex copy number and sequence variation from high coverage exome sequencing data

Frequency of rs200757797 and rs2740090 in the 1000 Genomes continental groups. (DOCX 13.4 kb

Determining multiallelic complex copy number and sequence variation from high coverage exome sequencing data

BACKGROUND: Copy number variation (CNV) is a major component of genomic variation, yet methods to accurately type genomic CNV lag behind methods that type single nucleotide variation. High-throughput sequencing can contribute to these methods by using sequence read depth, which takes the number of reads that map to a given part of the reference genome as a proxy for copy number of that region, and compares across samples. Furthermore, high-throughput sequencing also provides information on the sequence differences between copies within and between individuals. METHODS: In this study we use high-coverage phase 3 exome sequences of the 1000 Genomes project to infer diploid copy number of the beta-defensin genomic region, a well-studied CNV that carries several beta-defensin genes involved in the antimicrobial response, signalling, and fertility. We also use these data to call sequence variants, a particular challenge given the multicopy nature of the region. RESULTS: We confidently call copy number and sequence variation of the beta-defensin genes on 1285 samples from 26 global populations, validate copy number using Nanostring nCounter and triplex paralogue ratio test data. We use the copy number calls to verify the genomic extent of the CNV and validate sequence calls using analysis of cloned PCR products. We identify novel variation, mostly individually rare, predicted to alter amino-acid sequence in the beta-defensin genes. Such novel variants may alter antimicrobial properties or have off-target receptor interactions, and may contribute to individuality in immunological response and fertility. CONCLUSIONS: Given that 81 % of identified sequence variants were not previously in dbSNP, we show that sequence variation in multiallelic CNVs represent an unappreciated source of genomic diversity