MAST: Phylogenetic Inference with Mixtures Across Sites and Trees.

Hundreds or thousands of loci are now routinely used in modern phylogenomic studies. Concatenation approaches to tree inference assume that there is a single topology for the entire dataset, but different loci may have different evolutionary histories due to incomplete lineage sorting (ILS), introgression, and/or horizontal gene transfer; even single loci may not be treelike due to recombination. To overcome this shortcoming, we introduce an implementation of a multi-tree mixture model that we call mixtures across sites and trees (MAST). This model extends a prior implementation by Boussau et al. (2009) by allowing users to estimate the weight of each of a set of pre-specified bifurcating trees in a single alignment. The MAST model allows each tree to have its own weight, topology, branch lengths, substitution model, nucleotide or amino acid frequencies, and model of rate heterogeneity across sites. We implemented the MAST model in a maximum-likelihood framework in the popular phylogenetic software, IQ-TREE. Simulations show that we can accurately recover the true model parameters, including branch lengths and tree weights for a given set of tree topologies, under a wide range of biologically realistic scenarios. We also show that we can use standard statistical inference approaches to reject a single-tree model when data are simulated under multiple trees (and vice versa). We applied the MAST model to multiple primate datasets and found that it can recover the signal of ILS in the Great Apes, as well as the asymmetry in minor trees caused by introgression among several macaque species. When applied to a dataset of 4 Platyrrhine species for which standard concatenated maximum likelihood (ML) and gene tree approaches disagree, we observe that MAST gives the highest weight (i.e., the largest proportion of sites) to the tree also supported by gene tree approaches. These results suggest that the MAST model is able to analyze a concatenated alignment using ML while avoiding some of the biases that come with assuming there is only a single tree. We discuss how the MAST model can be extended in the future.

Mugen-UMAP: UMAP visualization and clustering of mutated genes in single-cell DNA sequencing data.

BACKGROUND: The application of Uniform Manifold Approximation and Projection (UMAP) for dimensionality reduction and visualization has revolutionized the analysis of single-cell RNA expression and population genetics. However, its potential in single-cell DNA sequencing data analysis, particularly for visualizing gene mutation information, has not been fully explored. RESULTS: We introduce Mugen-UMAP, a novel Python-based program that extends UMAP's utility to single-cell DNA sequencing data. This innovative tool provides a comprehensive pipeline for processing gene annotation files of single-cell somatic single-nucleotide variants and metadata to the visualization of UMAP projections for identifying clusters, along with various statistical analyses. Employing Mugen-UMAP, we analyzed whole-exome sequencing data from 365 single-cell samples across 12 non-small cell lung cancer (NSCLC) patients, revealing distinct clusters associated with histological subtypes of NSCLC. Moreover, to demonstrate the general utility of Mugen-UMAP, we applied the program to 9 additional single-cell WES datasets from various cancer types, uncovering interesting patterns of cell clusters that warrant further investigation. In summary, Mugen-UMAP provides a quick and effective visualization method to uncover cell cluster patterns based on the gene mutation information from single-cell DNA sequencing data. CONCLUSIONS: The application of Mugen-UMAP demonstrates its capacity to provide valuable insights into the visualization and interpretation of single-cell DNA sequencing data. Mugen-UMAP can be found at https://github.com/tengchn/Mugen-UMAP.

An assembly-free method of phylogeny reconstruction using short-read sequences from pooled samples without barcodes.

A current strategy for obtaining haplotype information from several individuals involves short-read sequencing of pooled amplicons, where fragments from each individual is identified by a unique DNA barcode. In this paper, we report a new method to recover the phylogeny of haplotypes from short-read sequences obtained using pooled amplicons from a mixture of individuals, without barcoding. The method, AFPhyloMix, accepts an alignment of the mixture of reads against a reference sequence, obtains the single-nucleotide-polymorphisms (SNP) patterns along the alignment, and constructs the phylogenetic tree according to the SNP patterns. AFPhyloMix adopts a Bayesian inference model to estimate the phylogeny of the haplotypes and their relative abundances, given that the number of haplotypes is known. In our simulations, AFPhyloMix achieved at least 80% accuracy at recovering the phylogenies and relative abundances of the constituent haplotypes, for mixtures with up to 15 haplotypes. AFPhyloMix also worked well on a real data set of kangaroo mitochondrial DNA sequences.

Correction to: Effective machine-learning assembly for next-generation amplicon sequencing with very low coverage.

Following publication of the original article [1], the author reported that there are several errors in the original article.

Effective machine-learning assembly for next-generation amplicon sequencing with very low coverage.

BACKGROUND: In short-read DNA sequencing experiments, the read coverage is a key parameter to successfully assemble the reads and reconstruct the sequence of the input DNA. When coverage is very low, the original sequence reconstruction from the reads can be difficult because of the occurrence of uncovered gaps. Reference guided assembly can then improve these assemblies. However, when the available reference is phylogenetically distant from the sequencing reads, the mapping rate of the reads can be extremely low. Some recent improvements in read mapping approaches aim at modifying the reference according to the reads dynamically. Such approaches can significantly improve the alignment rate of the reads onto distant references but the processing of insertions and deletions remains challenging. RESULTS: Here, we introduce a new algorithm to update the reference sequence according to previously aligned reads. Substitutions, insertions and deletions are performed in the reference sequence dynamically. We evaluate this approach to assemble a western-grey kangaroo mitochondrial amplicon. Our results show that more reads can be aligned and that this method produces assemblies of length comparable to the truth while limiting error rate when classic approaches fail to recover the correct length. Finally, we discuss how the core algorithm of this method could be improved and combined with other approaches to analyse larger genomic sequences. CONCLUSIONS: We introduced an algorithm to perform dynamic alignment of reads on a distant reference. We showed that such approach can improve the reconstruction of an amplicon compared to classically used bioinformatic pipelines. Although not portable to genomic scale in the current form, we suggested several improvements to be investigated to make this method more flexible and allow dynamic alignment to be used for large genome assemblies.

HaploJuice : accurate haplotype assembly from a pool of sequences with known relative concentrations.

BACKGROUND: Pooling techniques, where multiple sub-samples are mixed in a single sample, are widely used to take full advantage of high-throughput DNA sequencing. Recently, Ranjard et al. (PLoS ONE 13:0195090, 2018) proposed a pooling strategy without the use of barcodes. Three sub-samples were mixed in different known proportions (i.e. 62.5%, 25% and 12.5%), and a method was developed to use these proportions to reconstruct the three haplotypes effectively. RESULTS: HaploJuice provides an alternative haplotype reconstruction algorithm for Ranjard et al.'s pooling strategy. HaploJuice significantly increases the accuracy by first identifying the empirical proportions of the three mixed sub-samples and then assembling the haplotypes using a dynamic programming approach. HaploJuice was evaluated against five different assembly algorithms, Hmmfreq (Ranjard et al., PLoS ONE 13:0195090, 2018), ShoRAH (Zagordi et al., BMC Bioinformatics 12:119, 2011), SAVAGE (Baaijens et al., Genome Res 27:835-848, 2017), PredictHaplo (Prabhakaran et al., IEEE/ACM Trans Comput Biol Bioinform 11:182-91, 2014) and QuRe (Prosperi and Salemi, Bioinformatics 28:132-3, 2012). Using simulated and real data sets, HaploJuice reconstructed the true sequences with the highest coverage and the lowest error rate. CONCLUSION: HaploJuice provides high accuracy in haplotype reconstruction, making Ranjard et al.'s pooling strategy more efficient, feasible, and applicable, with the benefit of reducing the sequencing cost.

Bamboo Specialists from Two Mammalian Orders (Primates, Carnivora) Share a High Number of Low-Abundance Gut Microbes.

Bamboo specialization is one of the most extreme examples of convergent herbivory, yet it is unclear how this specific high-fiber diet might selectively shape the composition of the gut microbiome compared to host phylogeny. To address these questions, we used deep sequencing to investigate the nature and comparative impact of phylogenetic and dietary selection for specific gut microbial membership in three bamboo specialists-the bamboo lemur (Hapalemur griseus, Primates: Lemuridae), giant panda (Ailuropoda melanoleuca, Carnivora: Ursidae), and red panda (Ailurus fulgens, Carnivora: Musteloideadae), as well as two phylogenetic controls-the ringtail lemur (Lemur catta) and the Asian black bear (Ursus thibetanus). We detected significantly higher Shannon diversity in the bamboo lemur (10.029) compared to both the giant panda (8.256; p = 0.0001936) and the red panda (6.484; p = 0.0000029). We also detected significantly enriched bacterial taxa that distinguished each species. Our results complement previous work in finding that phylogeny predominantly governs high-level microbiome community structure. However, we also find that 48 low-abundance OTUs are shared among bamboo specialists, compared to only 8 OTUs shared by the bamboo lemur and its sister species, the ringtail lemur (Lemur catta, a generalist). Our results suggest that deep sequencing is necessary to detect low-abundance bacterial OTUs, which may be specifically adapted to a high-fiber diet. These findings provide a more comprehensive framework for understanding the evolution and ecology of the microbiome as well as the host.

Science incubators: synthesis centers and their role in the research ecosystem.

How should funding agencies enable researchers to explore high-risk but potentially high-reward science? One model that appears to work is the NSF-funded synthesis center, an incubator for community-led, innovative science.

Neutral Models of Microbiome Evolution.

There has been an explosion of research on host-associated microbial communities (i.e.,microbiomes). Much of this research has focused on surveys of microbial diversities across a variety of host species, including humans, with a view to understanding how these microbiomes are distributed across space and time, and how they correlate with host health, disease, phenotype, physiology and ecology. Fewer studies have focused on how these microbiomes may have evolved. In this paper, we develop an agent-based framework to study the dynamics of microbiome evolution. Our framework incorporates neutral models of how hosts acquire their microbiomes, and how the environmental microbial community that is available to the hosts is assembled. Most importantly, our framework also incorporates a Wright-Fisher genealogical model of hosts, so that the dynamics of microbiome evolution is studied on an evolutionary timescale. Our results indicate that the extent of parental contribution to microbial availability from one generation to the next significantly impacts the diversity of microbiomes: the greater the parental contribution, the less diverse the microbiomes. In contrast, even when there is only a very small contribution from a constant environmental pool, microbial communities can remain highly diverse. Finally, we show that our models may be used to construct hypotheses about the types of processes that operate to assemble microbiomes over evolutionary time.

Estimation of evolutionary parameters using short, random and partial sequences from mixed samples of anonymous individuals.

BACKGROUND: Over the last decade, next generation sequencing (NGS) has become widely available, and is now the sequencing technology of choice for most researchers. Nonetheless, NGS presents a challenge for the evolutionary biologists who wish to estimate evolutionary genetic parameters from a mixed sample of unlabelled or untagged individuals, especially when the reconstruction of full length haplotypes can be unreliable. We propose two novel approaches, least squares estimation (LS) and Approximate Bayesian Computation Markov chain Monte Carlo estimation (ABC-MCMC), to infer evolutionary genetic parameters from a collection of short-read sequences obtained from a mixed sample of anonymous DNA using the frequencies of nucleotides at each site only without reconstructing the full-length alignment nor the phylogeny. RESULTS: We used simulations to evaluate the performance of these algorithms, and our results demonstrate that LS performs poorly because bootstrap 95% Confidence Intervals (CIs) tend to under- or over-estimate the true values of the parameters. In contrast, ABC-MCMC 95% Highest Posterior Density (HPD) intervals recovered from ABC-MCMC enclosed the true parameter values with a rate approximately equivalent to that obtained using BEAST, a program that implements a Bayesian MCMC estimation of evolutionary parameters using full-length sequences. Because there is a loss of information with the use of sitewise nucleotide frequencies alone, the ABC-MCMC 95% HPDs are larger than those obtained by BEAST. CONCLUSION: We propose two novel algorithms to estimate evolutionary genetic parameters based on the proportion of each nucleotide. The LS method cannot be recommended as a standalone method for evolutionary parameter estimation. On the other hand, parameters recovered by ABC-MCMC are comparable to those obtained using BEAST, but with larger 95% HPDs. One major advantage of ABC-MCMC is that computational time scales linearly with the number of short-read sequences, and is independent of the number of full-length sequences in the original data. This allows us to perform the analysis on NGS datasets with large numbers of short read fragments. The source code for ABC-MCMC is available at https://github.com/stevenhwu/SF-ABC.

Ultrafast evolution and loss of CRISPRs following a host shift in a novel wildlife pathogen, Mycoplasma gallisepticum.

Measureable rates of genome evolution are well documented in human pathogens but are less well understood in bacterial pathogens in the wild, particularly during and after host switches. Mycoplasma gallisepticum (MG) is a pathogenic bacterium that has evolved predominantly in poultry and recently jumped to wild house finches (Carpodacus mexicanus), a common North American songbird. For the first time we characterize the genome and measure rates of genome evolution in House Finch isolates of MG, as well as in poultry outgroups. Using whole-genome sequences of 12 House Finch isolates across a 13-year serial sample and an additional four newly sequenced poultry strains, we estimate a nucleotide diversity in House Finch isolates of only ∼2% of ancestral poultry strains and a nucleotide substitution rate of 0.8-1.2×10(-5) per site per year both in poultry and in House Finches, an exceptionally fast rate rivaling some of the highest estimates reported thus far for bacteria. We also found high diversity and complete turnover of CRISPR arrays in poultry MG strains prior to the switch to the House Finch host, but after the invasion of House Finches there is progressive loss of CRISPR repeat diversity, and recruitment of novel CRISPR repeats ceases. Recent (2007) House Finch MG strains retain only ∼50% of the CRISPR repertoire founding (1994-95) strains and have lost the CRISPR-associated genes required for CRISPR function. Our results suggest that genome evolution in bacterial pathogens of wild birds can be extremely rapid and in this case is accompanied by apparent functional loss of CRISPRs.

Transient compartmentalization of simian immunodeficiency virus variants in the breast milk of african green monkeys.

Natural hosts of simian immunodeficiency virus (SIV), African green monkeys (AGMs), rarely transmit SIV via breast-feeding. In order to examine the genetic diversity of breast milk SIV variants in this limited-transmission setting, we performed phylogenetic analysis on envelope sequences of milk and plasma SIV variants of AGMs. Low-diversity milk virus populations were compartmentalized from that in plasma. However, this compartmentalization was transient, as the milk virus lineages did not persist longitudinally.

Cumulative viral evolutionary changes in chronic hepatitis B virus infection precedes hepatitis B e antigen seroconversion.

OBJECTIVE: To examine viral evolutionary changes and their relationship to hepatitis B e antigen (HBeAg) seroconversion. DESIGN: A matched case-control study of HBeAg seroconverters (n = 8) and non-seroconverters (n = 7) with adequate stored sera before seroconversion was performed. Nested PCR, cloning and sequencing of hepatitis B virus (HBV) precore/core gene was performed. Sequences were aligned using Clustal X2.0, followed by construction of phylogenetic trees using Pebble 1.0. Viral diversity, evolutionary rates and positive selection were then analysed. RESULTS: Baseline HBV quasispecies viral diversity was identical in seroconverters and non-seroconverters 10 years before seroconversion but started to increase approximately 3 years later. Concurrently, precore stop codon (PSC) mutations appeared. Some 2 years later, HBV-DNA declined, together with a dramatic reduction in HBeAg titres. Just before HBeAg seroconversion, seroconverters had HBV-DNA levels 2 log lower (p = 0.008), HBeAg titres 310-fold smaller (p = 0.02), PSC mutations > 25% (p < 0.001), viral evolution 8.1-fold higher (p = 0.01) and viral diversity 2.9-fold higher (p < 0.001), compared to non-seroconverters, with a 9.3-fold higher viral diversity than baseline (p = 0.011). Phylogenetic trees in seroconverters showed clustering of separate time points and longer branch lengths than non-seroconverters (p = 0.01). Positive selection was detected in five of eight seroconverters but none in non-seroconverters (p = 0.026). There was significant negative correlation between viral diversity (rs = -0.60, p < 0.001) and HBV-DNA or HBeAg (rs = -0.58, p = 0.006) levels; and positive correlation with PSC mutations (rs = 0.38, p = 0.009). Over time, the significant positive correlation was viral diversity (rs = 0.65, p < 0.001), while negative correlation was HBV-DNA (rs = -0.627, p < 0.001) and HBeAg levels (rs = -0.512, p =0.015). CONCLUSIONS: Cumulative viral evolutionary changes that precede HBeAg seroconversion provide insights into this event that may have implications for therapy.

ViPRA-Haplo: De Novo Reconstruction of Viral Populations Using Paired End Sequencing Data.

We present ViPRA-Haplo, a de novo strain-specific assembly workflow for reconstructing viral haplotypes in a viral population from paired-end next generation sequencing (NGS) data. The proposed Viral Path Reconstruction Algorithm (ViPRA) generates a subset of paths from a De Bruijn graph of reads using the pairing information of reads. The paths generated by ViPRA are an over-estimation of the true contigs. We propose two refinement methods to obtain an optimal set of contigs representing viral haplotypes. The first method clusters paths reconstructed by ViPRA using VSEARCH Deorowicz et al. 2015 based on sequence similarity, while the second method, MLEHaplo, generates a maximum likelihood estimate of viral populations. We evaluated our pipeline on both simulated and real viral quasispecies data from HIV (and real data from SARS-COV-2). Experimental results show that ViPRA-Haplo, although still an overestimation in the number of true contigs, outperforms the existing tool, PEHaplo, providing up to 9% better genome coverage on HIV real data. In addition, ViPRA-Haplo also retains higher diversity of the viral population as demonstrated by the presence of a higher percentage of contigs less than 1000 base pairs (bps), which also contain k-mers with counts less than 100 (representing rarer sequences), which are absent in PEHaplo. For SARS-CoV-2 sequencing data, ViPRA-Haplo reconstructs contigs that cover more than 90% of the reference genome and were able to validate known SARS-CoV-2 strains in the sequencing data.

Increased viral quasispecies evolution in HBeAg seroconverter patients treated with oral nucleoside therapy.

BACKGROUND & AIMS: Increased viral diversity and evolution appear to be a pre-HBeAg-seroconversion feature in spontaneous and interferon-treated seroconverters. The aim of this study was to examine the viral evolution pattern in nucleoside analogue related HBeAg-seroconversion. METHODS: This was a case control study consisting of ten lamivudine-treated HBeAg-seroconverters and ten lamivudine-treated non-seroconverters as matching controls. All patients in this study were followed as long as 6 years after starting lamivudine, and cases had three serum time points before HBeAg-seroconversion while controls had three matching serum time points. Nested PCR, cloning and sequencing of HBV precore/core gene were performed. Sequences were aligned with Clustal X 2.0. Phylogenetic trees were constructed and viral diversity, evolutionary rates and patterns of positive selection were evaluated. RESULTS: After starting lamivudine treatment, HBV viral diversity increased in both seroconverters and non-seroconverters, but seroconverters showed a significantly higher level of viral diversity that persisted over time by 2.1-fold (p = 0.009). The increased viral diversity correlated with reduced HBV DNA levels (p <0.001). Lamivudine-treated seroconverters had significant reduced HBV DNA concurrent with increased viral diversity after starting treatment (p = 0.001, compared to non-seroconverters, and resembled those of interferon-seroconverters published previously). There was evidence of positive selection in seroconverters with significantly increased amino acid changes compared to non-seroconverters (p <0.001), occurring in recognized T-cell and B-cell epitopes. CONCLUSIONS: Lamivudine-treated HBeAg-seroconverters showed a higher viral diversity than non-seroconverters, and the pattern resembled that of interferon-treated seroconverters. The findings strengthen the evidence that increased viral diversity is strongly associated with HBeAg-seroconversion.

Coalescent entanglement and the conditional dependence of the times to common ancestry of mutually exclusive pairs of individuals.

The Kingman coalescent is a continuous-time diffusion approximation of the times to common ancestry of a sample of individuals drawn from a Wright-Fisher population. Here, we use the coalescent to answer a simple question: if we know the ancestry of 2 randomly sampled individuals in the population, what does it tell us about the ancestry of 2 other randomly sampled individuals? We show that there is a conditional dependency between the times to common ancestry between pairs of randomly sampled individuals. We call this "coalescent entanglement," and we demonstrate its effects through simulation. The effects of entanglement extend beyond the coalescent to phylogenetic birth-death processes in general. Entanglement also exerts its effects when the pairs of individuals chosen share no common lineages in the paths that connect the individuals in each pair.

A Bayesian model for classifying all differentially expressed proteins simultaneously in 2D PAGE gels.

BACKGROUND: Two-dimensional polyacrylamide gel electrophoresis (2D PAGE) is commonly used to identify differentially expressed proteins under two or more experimental or observational conditions. Wu et al (2009) developed a univariate probabilistic model which was used to identify differential expression between Case and Control groups, by applying a Likelihood Ratio Test (LRT) to each protein on a 2D PAGE. In contrast to commonly used statistical approaches, this model takes into account the two possible causes of missing values in 2D PAGE: either (1) the non-expression of a protein; or (2) a level of expression that falls below the limit of detection. RESULTS: We develop a global Bayesian model which extends the previously described model. Unlike the univariate approach, the model reported here is able treat all differentially expressed proteins simultaneously. Whereas each protein is modelled by the univariate likelihood function previously described, several global distributions are used to model the underlying relationship between the parameters associated with individual proteins. These global distributions are able to combine information from each protein to give more accurate estimates of the true parameters. In our implementation of the procedure, all parameters are recovered by Markov chain Monte Carlo (MCMC) integration. The 95% highest posterior density (HPD) intervals for the marginal posterior distributions are used to determine whether differences in protein expression are due to differences in mean expression intensities, and/or differences in the probabilities of expression. CONCLUSIONS: Simulation analyses showed that the global model is able to accurately recover the underlying global distributions, and identify more differentially expressed proteins than the simple application of a LRT. Additionally, simulations also indicate that the probability of incorrectly identifying a protein as differentially expressed (i.e., the False Discovery Rate) is very low. The source code is available at https://github.com/stevenhwu/BIDE-2D.

pgHMA: Application of the heteroduplex mobility assay analysis in phylogenetics and population genetics.

The heteroduplex mobility assay (HMA) has proven to be a robust tool for the detection of genetic variation. Here, we describe a simple and rapid application of the HMA by microfluidic capillary electrophoresis, for phylogenetics and population genetic analyses (pgHMA). We show how commonly applied techniques in phylogenetics and population genetics have equivalents with pgHMA: phylogenetic reconstruction with bootstrapping, skyline plots, and mismatch distribution analysis. We assess the performance and accuracy of pgHMA by comparing the results obtained against those obtained using standard methods of analyses applied to sequencing data. The resulting comparisons demonstrate that: (a) there is a significant linear relationship (R2  = .992) between heteroduplex mobility and genetic distance, (b) phylogenetic trees obtained by HMA and nucleotide sequences present nearly identical topologies, (c) clades with high pgHMA parametric bootstrap support also have high bootstrap support on nucleotide phylogenies, (d) skyline plots estimated from the UPGMA trees of HMA and Bayesian trees of nucleotide data reveal similar trends, especially for the median trend estimate of effective population size, and (e) optimized mismatch distributions of HMA are closely fitted to the mismatch distributions of nucleotide sequences. In summary, pgHMA is an easily-applied method for approximating phylogenetic diversity and population trends.

Evidence for reduced selection pressure on the hepatitis B virus core gene in hepatitis B e antigen-negative chronic hepatitis B.

The mechanisms underlying the high levels of hepatitis B virus (HBV) replication that cause hepatitis B e antigen (HBeAg)-negative chronic hepatitis B (e-CHB) are unknown. Impaired anti-HBV immunity, which may be measurable as a relaxation of selection pressure on the virus, is possible. A group of Tongans (n = 345) with a chronic HBV infection, including seven with e-CHB, were genotyped at HLA class I. The repertoire of HBV core-gene codons under positive selection pressure was defined by phylogenetic analysis (by using the paml program) of 708 cloned sequences extracted from the 67 of these 345 subjects with the same repertoire of HLA class I alleles as the seven e-CHB individuals and matched controls (see below). The frequency of non-synonymous mutations at these codons was measured in longitudinal data from 15 subjects. Finally, the number of non-synonymous mutations at these codons was compared in seven groups comprised of one subject with e-CHB and 1-3 HLA class I-matched controls with an inactive, HBeAg-negative chronic HBV infection (e-InD). Nineteen codons in the core gene were under positive selection pressure. There was a high frequency of new non-synonymous mutations at these codons (P<0.0001) in longitudinal data. The mean number of these 19 codons with non-synonymous mutations was lower (P = 0.02) in HBV from subjects with e-CHB (4.4±0.5 codons per subject) versus those with e-InD (6.4±0.4 codons per subject). There is a subtle relaxation in selection pressure on the HBV core gene in e-CHB. This may be due to impaired antiviral immunity, and could contribute to the high levels of viral replication that cause liver inflammation in this disease.

Associations between HLA class I alleles and escape mutations in the hepatitis B virus core gene in New Zealand-resident Tongans.

The full repertoire of hepatitis B virus (HBV) peptides that bind to the common HLA class I molecules found in areas with a high prevalence of chronic HBV infection has not been determined. This information may be useful for designing immunotherapies for chronic hepatitis B. We identified amino acid residues under positive selection pressure in the HBV core gene by phylogenetic analysis of cloned DNA sequences obtained from HBV DNA extracted from the sera of Tongan subjects with inactive, HBeAg-negative chronic HBV infections. The repertoires of positively selected sites in groups of subjects who were homozygous for either HLA-B*4001 (n = 10) or HLA-B*5602 (n = 7) were compared. We identified 13 amino acid sites under positive selection pressure. A significant association between an HLA class I allele and the presence of nonsynonymous mutations was found at five of these sites. HLA-B*4001 was associated with mutations at E77 (P = 0.05) and E113 (P = 0.002), and HLA-B*5602 was associated with mutations at S21 (P = 0.02). In addition, amino acid mutations at V13 (P = 0.03) and E14 (P = 0.01) were more common in the seven subjects with an HLA-A*02 allele. In summary, we have developed an assay that can identify associations between HLA class I alleles and HBV core gene amino acids that mutate in response to selection pressure. This is consistent with published evidence that CD8(+) T cells have a role in suppressing viral replication in inactive, HBeAg-negative chronic HBV infection. This assay may be useful for identifying the clinically significant HBV peptides that bind to common HLA class I molecules.