Phylodynamic analysis of porcine circovirus type 2: Methodological approach and datasets

Since its first description, PCV2 has emerged as one of the most economically relevant diseases for the swine industry. Despite the introduction of vaccines effective in controlling clinical syndromes, PCV2 spread was not prevented and some potential evidences of vaccine immuno escape have recently been reported (“Complete genome sequence of a novel porcine circovirus type 2b variant present in cases of vaccine failures in the United States” (Xiao and Halbur, 2012) [1], “Genetic and antigenic characterization of a newly emerging porcine circovirus type 2b mutant first isolated in cases of vaccine failure in Korea” (Seo et al., 2014) [2]). In this article, we used a collection of PCV2 full genomes, provided in the present manuscript, and several phylogentic, phylodynamic and bioinformatic methods to investigate different aspects of PCV2 epidemiology, history and evolution (more thoroughly described in “PHYLODYNAMIC ANALYSIS of PORCINE CIRCOVIRUS TYPE 2 REVEALS GLOBAL WAVES of EMERGING GENOTYPES and the CIRCULATION of RECOMBINANT FORMS”[3]). The methodological approaches used to consistently detect recombiantion events and estimate population dymanics and spreading patterns of rapidly evolving ssDNA viruses are herein reported. Programs used are described and original scripts have been provided. Ensembled databases used are also made available. These consist of a broad collection of complete genome sequences (i.e. 843 sequences; 63 complete genomes of PCV2a, 310 of PCV2b, 4 of PCV2c, 217 of PCV2d, 64 of CRF01, 140 of CRF02 and 45 of CRF03.), divided in differnt ORF (i.e. ORF1, ORF2 and intergenic regions), of PCV2 genotypes and major Circulating Recombinat Forms (CRF) properly annotated with respective collection data and country. Globally, all of these data can be used as a starting point for further studies and for classification purpose

Correlation between sHLA-G levels and age in women.

<p>Statistical correlation between age and sHLA-G levels was tested using Spearman's rank test (rS = −0.1905, p = 0.004).</p

Comparison between A*02≈UTR-5≈G*01:03 (n = 24) and A*x≈UTR-5≈G*01:03 (n = 15, x corresponds to all HLA-A alleles except A*02).

<p>Statistical comparison was based on Mann-Whitney t-test (A*02≈UTR-5≈G*01:03 154.9±28.9 UI/ml; A*x≈UTR-5≈G*01:03 133.9±22.5 UI/ml). When outer points were excluded (212.4 UI/ml, 201.9 UI/ml, 92.2 UI/ml and 92.2 UI/ml for A*02≈UTR-5≈G*01:03; 86.4 UI/ml for A*x≈UTR-5≈G*01:03), the difference remained significant (p<0.05).</p

Frequencies (Fq) and absolute value (N) of coding HLA-G alleles, 5′URR and 3′UTR SNPs in the Malian population.

<p>Results are compared with previously published results on VBMD <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082517#pone.0082517-DiCristofaro1" target="_blank">[41]</a>. Statistical differences between the two populations frequencies were measured using a chi-squared test (NS: not significant; *: p<0.05; **: p<0.01; ***: p<0.001).</p

Comparison between UTR-2 (n = 103) and non-UTR-2 (n = 116) individuals related to sHLA-G production.

<p>Statistical comparison was based on Mann-Whitney t-test. (UTR-2 137.5±30.6 UI/ml vs. all except UTR-2 148.2±30.7 UI/ml). When six outer points were excluded (238.6 UI/ml, 217.6 UI/ml and 53.8 UI/ml for UTR-2; 242.2 UI/ml, 229.8 UI/ml and 226.5 UI/ml for non-UTR-2) UTR-2 individuals still displayed significantly lower values (p<0.05).</p

Two-locus linkage disequilibrium (LD) in the Malian population (n = 230) between polymorphisms in the 5′URR (−725 C/G or T; −716 G/T; −201 G/A and −56 C/T), in the coding region (codons 13C/T; 31 A/T; 54 A/G; 110 C/A; 130 C/T; 159 T/C; 219 C/T and 258 C/T) and in the 3′UTR (<i>ins/del</i> exon 8; 3142 C/G; 3187 G/A and 3196 C/G).

<p>Statistical significance (p value at junction between two loci) is indicated by color (light gray: p<0.05, gray: p<0.01 and black p<0.001).</p

Comparison between UTR-2 alleles G*01:05N/G*01:05N (n = 5 141.4±13.9 UI/ml) and all except G*01:05N/G*01:05N (n = 9 129.5±16.8 UI/ml).

<p>Statistical comparison was based on Kruskal-Wallis one-way ANOVA followed by Dunn post-hoc test.</p

Comparison between two groups of women (3–25 years old n = 39 and over 26 years old n = 60) and men (3–25 years old n = 41 and over 26 years old n = 79) related to sHLA-G levels.

<p>Statistical comparison was based on Kruskal-Wallis one-way ANOVA followed by Dunn post-hoc test (girls 3–25 years old: 158.4±31.6 UI/ml; boys 3–25 years old: 152.0±31.6 UI/ml; women over 26 years old: 137.5±26.6 UI/ml; men over 26 years old: 135.5±26.4 UI/ml). NS: not significant; *: p>0.05; **: p<0.01; ***: p<0.001).</p

Description of the UTR haplotypes in the Malian population: nomenclature, polymorphism composition, estimated frequencies (Fq) with EM algorithm and association with coding HLA-G alleles.

<p>Comparison with previously published results on VBMD <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082517#pone.0082517-DiCristofaro1" target="_blank">[41]</a>. Statistical differences between the two population frequencies were measured using chi-squared test (NS: no significant; *: p<0.05; **: p<0.01; ***: p<0.001).</p

HLA-G UTR Haplotype Conservation in the Malian Population: Association with Soluble HLA-G

International audienceThe HLA-G molecule plays an important role in immunomodulation. In a previous study carried out on a southern French population our team showed that HLA-G haplotypes, defined by SNPs in the coding region and specific SNPs located in 5'URR and 3'UTR regulatory regions, are associated with differential soluble HLA-G expression (sHLA-G). Furthermore, the structure of these HLA-G haplotypes appears to be conserved in geographically distant populations. The aim of our study is to confirm these expectations in a sub-Saharan African population and to explore additional factors, such as HLA-A alleles, that might influence sHLA-G expression. DNA and plasma samples were collected from 229 Malians; HLA-G and HLA-A genotyping were respectively performed by the Snap Shot® method and by Luminex™ technology. sHLA-G dosage was performed using an ELISA kit. HLA-G and HLA-A allelic and haplotypic frequencies were estimated using an EM algorithm from the Gene[Rate] program. Associations between genetic and non genetic parameters with sHLA-G were performed using a non-parametric test with GRAPH PAD Prism 5. Our results reveal a good conservation of the HLA-G UTR haplotype structure in populations with different origins and demographic histories. These UTR haplotypes appear to be involved in different sHLA-G expression patterns. Specifically, the UTR-2 haplotype was associated with low sHLA-G levels, displaying a dominant negative effect. Furthermore, an allelic effect of both HLA-G and HLA-A, as well as non genetic parameters, such as age and gender possibly linked to osteogenesis and sexual hormones, also seem to be involved in the modulation of sHLA-G. These data suggest that further investigation in larger cohorts and in populations from various ethnical backgrounds is necessary not only to detect new functional polymorphism in HLA-G regulatory regions, but also to reveal the extent of biological phenomena that influence sHLA-G secretion and this might therefore have an impact on transplantation practice