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Quantifying the variation in the effective population size within a genome
The effective population size (Ne) is one of the most fundamental parameters in population genetics. It is thought to vary across the genome as a consequence of differences in the rate of recombination and the density of selected sites due to the processes of genetic hitchhiking and background selection. Although it is known that there is intragenomic variation in the effective population size in some species, it is not known whether this is widespread or how much variation in the effective population size there is. Here, we test whether the effective population size varies across the genome, between protein-coding genes, in 10 eukaryotic species by considering whether there is significant variation in neutral diversity, taking into account differences in the mutation rate between loci by using the divergence between species. In most species we find significant evidence of variation. We investigate whether the variation in Ne is correlated to recombination rate and the density of selected sites in four species, for which these data are available. We find that Ne is positively correlated to recombination rate in one species, Drosophila melanogaster, and negatively correlated to a measure of the density of selected sites in two others, humans and Arabidopsis thaliana. However, much of the variation remains unexplained. We use a hierarchical Bayesian analysis to quantify the amount of variation in the effective population size and show that it is quite modest in all species—most genes have an Ne that is within a few fold of all other genes. Nonetheless we show that this modest variation in Ne is sufficient to cause significant differences in the efficiency of natural selection across the genome, by demonstrating that the ratio of the number of nonsynonymous to synonymous polymorphisms is significantly correlated to synonymous diversity and estimates of Ne, even taking into account the obvious nonindependence between these measures
Intrinsic virus replication rate is a determinant in WMVB.
<p>(A & B) WNV replication is inhibited by <i>Wolbachia</i>. (A) WNV positive and negative strands were quantified through RT-qPCR at different time points after infecting cells (MOI = 10), (n = 5). (B) At 5 dpi with WNV, cell supernatant was harvested and assayed for viral titre by plaque assay (n = 5). (C & D) Aag2-wMel cells infected with DENV and WNV were compared through one phase decay up to 8 dpi. (E-G) DENV blocking by <i>Wolbachia</i> is not serotype dependent. Aag2 and Aag2-<i>w</i>Mel cells were infected with various DENV isolates from serotype 1–4 at an MOI of 1 and analysed 5 dpi. (E) Viral RNA was isolated from cell culture supernatant and the number of virus copies were calculated using RT-qPCR. Dotted line denotes the minimum detection limit. (F) Total cellular RNA from cells were used to detect DENV using RT-qPCR and normalised with RPS-17. All Data are expressed as mean ± SEM. **<i>P</i> ≤ 0.01, *** <i>P</i>≤ 0.001. (G) Difference in blocking of different serotypes calculated from the ratio of DENV in Aag2-<i>w</i>Mel cells divided by the ratio of DENV in Aag2 cells (Aag2-<i>w</i>Mel/Aag2). Data are expressed as mean ± SEM (n = 3). * <i>P</i> ≤ 0.05, **<i>P</i> ≤ 0.01, ****<i>P</i> ≤ 0.0001 and compared using one-way ANOVA.</p
DENV RNA is quickly degraded in the presence of <i>Wolbachia</i>.
<p>(A) Schematic representation of the DENV genome with its 5’ & 3’ UTRs and different DENV proteins. The colours (other than pale blue) of genomic regions correspond to bars in graphs in B and C. (B and C) Aag2 and Aag2-<i>w</i>Mel cells were infected with DENV-2 (MOI = 10) and collected at different time points as shown. Total cellular RNA was used to analyse RNA degradation in different regions of the DENV genome (colour coded) from 5’ UTR to 3’ UTR through quantitative RT-qPCR and normalised to RPS-17 RNA levels. Data are analysed by comparing the 5’UTR with 3’UTR and expressed as mean ± SEM (n = 3). (D) Ratio of gRNA normalised to RPS-17 RNA levels at different time points after DENV infection. (E) Analysis of subgenomic RNA in DENV-infected Aag2 and Aag2-<i>w</i>Mel cells. Data are shown as relative fold change at different time points after DENV infection. All Data are expressed as mean ± SEM (n = 3). ns: not significant, * <i>P</i> ≤ 0.05 **<i>P</i> ≤ 0.01, *** <i>P</i> ≤ 0.001, ****<i>P</i> ≤ 0.0001.</p
Expression of miRNAs due to <i>Wolbachia</i> in Aag2 cells.
<p>The expression levels of host miRNAs were analysed in Aag2 and Aag2-<i>w</i>Mel cells through RT-qPCR and normalised with RPS-17. Data are expressed as mean ± SEM (n = 3).</p
Role of XRN1 in WMVB.
<p>(A-D) Insect Cellular mRNA stability is altered by DENV sfRNA. The half-life of ECR (A & B) and La (C&D) mRNA was determined in Aag2 and Aag2-<i>w</i>Mel cells mock infected or infected with DENV after Actinomycin-D treatment by RT-qPCR. Data are expressed as mean ± SEM (n = 3), * <i>P</i> ≤ 0.05 **<i>P</i> ≤ 0.01. (E & F) Effect of XRN1 depletion on WMVB. Aag2 and Aag2-<i>w</i>Mel cells were transfected with XRN1 specific siRNAs (siXRN1) or control (siCtrl) twice followed by infection with DENV at an MOI of 0.1. The cells were lysed after 48 h and viral RNA was quantified by RT-qPCR. (E) RT-qPCR showing the depletion of XRN1 RNA, 48 h after the siRNA transfection. (F) Relative intracellular DENV RNA abundances 48 h after infection. Data are expressed as mean ± SEM (n = 3). * <i>P</i> ≤ 0.05, **<i>P</i> ≤ 0.01, ****<i>P</i> ≤ 0.0001 and compared using one-way ANOVA.</p
<i>Wolbachia</i> does not affect DENV binding or internalisation but viral RNA replication.
<p>(A) Aag2 and Aag2-<i>w</i>Mel cells were infected with DENV (MOI = 1) and collected at different time points starting from 0 hpi (virus binding) to 1 hpi (virus replication). DENV RNA levels determined from total cellular RNA through quantitative RT-qPCR using primers DENV-G-F, DENV-G-R and DENV-G- FAM Probe and normalised to RPS-17 RNA levels using primers Rps17_TaqM_FW, Rps17_TaqM_RV, and rps17-LC640 probe (n = 3). (B) Strand-specific analysis of <i>Wolbachia</i>-mediated RNA degradation in DENV and WNV. Aag2 and Aag2-<i>w</i>Mel cells were infected with DENV (MOI = 10) and DENV positive and negative strands were quantified at different time points from total cellular RNA (n = 3). (C) At 5 dpi with DENV, cell culture supernatant was harvested and assayed for viral titre by plaque assay and plotted as plaque forming units/ml (n = 3). All Data are expressed as mean ± SEM (n = 3). * <i>P</i> ≤ 0.05 **<i>P</i> ≤ 0.01, *** <i>P</i> ≤ 0.001, ****<i>P</i> ≤ 0.0001. (D) Immunofluorescence microscopy of Aag2 and Aag2-<i>w</i>Mel cells infected with DENV at an MOI of 5 and analysed 24 hpi. DENV is labelled in green, <i>Wolbachia</i> in red and nucleus in blue.</p
ICE core genes in ICE<i>Hin</i>1056, ICE<i>Sb</i>1 and PAPI-1 and corresponding LGI homologues.
<p><b>α</b><i>ssb</i> is only present near LGI-1 clusters in <i>L. pneumophila</i> strains and LdrGI-c.<sup></sup></p><p><b>β</b><i>topB</i> is only present near LdrGI-c and LdrGI-d.</p><p><b>χ</b> all LGIs have integrases unrelated to those in ICE<i>Hin</i>1056, ICE<i>Sb</i>1 and PAPI-1.</p>**<p>Essential for conjugation.</p>*<p>Non-essential but deficiency significantly reduces conjugation.</p>∧<p>Not required for conjugation.</p
Comparison between GI-T4SS clusters in <i>Legionella</i> and SPI-7 family ICEs.
<p>LpcGI-2 from <i>L. pneumophila</i> strain Corby is representative of the conserved LGI cluster in <i>Legionella</i> spp. and compared to the well-characterised SPI-7 family ICEs from <i>Haemophilus influenzae</i> (ICE<i>Hin</i>1056), <i>Pseudomonas aeruginosa</i> (PAPI-1) and <i>Salmonella bongori</i> (ICE<i>Sb</i>1). Similarity between the different GI-T4SS clusters is represented by grey bars, shaded according to the percentage of amino acid identity as shown in the key. Genes are coloured according to category as described in the key.</p
Phylogeny of GI-T4SS across representative Proteobacterial genomes.
<p>Maximum likelihood tree of LgiN/VirB4/TraC homologues showing the divergent <i>Legionella</i> GI-T4SS clade (red). Representatives from the SPI-7 family of ICE are highlighted in blue, with representatives of the T4ASS (<i>A. tumefaciens</i> plasmid Ti, <i>E. coli</i> F plasmid and IncP-alpha plasmid) and T4BSS (Plasmid R64) in black. Asterisks indicate branches with percentage support from 1000 bootstrap replicates above 80% (** >90%, * >80%).</p
Phylogenetic relationship between LGI-T4SS clusters.
<p>A consensus network tree showing the relationship between the 14 <i>Legionella</i> GI-T4SS clusters, constructed from the individual maximum likelihood trees of 15 conserved <i>lgi</i> genes. Branch labels indicate the number of trees that support each branch. Branch lengths show the number of substitutions per site, as indicated by the scale bar, and are averaged across the trees that contain that branch.</p