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, 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 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 incomplete lineage sorting 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 four Platyrrhine species for which standard concatenated maximum likelihood 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 analyse a concatenated alignment using maximum likelihood, 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.

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.

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.

Reassembling haplotypes in a mixture of pooled amplicons when the relative concentrations are known: A proof-of-concept study on the efficient design of next-generation sequencing strategies.

Next-generation sequencing can be costly and labour intensive. Usually, the sequencing cost per sample is reduced by pooling amplified DNA = amplicons) derived from different individuals on the same sequencing lane. Barcodes unique to each amplicon permit short-read sequences to be assigned appropriately. However, the cost of the library preparation increases with the number of barcodes used. We propose an alternative to barcoding: by using different known proportions of individually-derived amplicons in a pooled sample, each is characterised a priori by an expected depth of coverage. We have developed a Hidden Markov Model that uses these expected proportions to reconstruct the input sequences. We apply this method to pools of mitochondrial DNA amplicons extracted from kangaroo meat, genus Macropus. Our experiments indicate that the sequence coverage can be efficiently used to index the short-reads and that we can reassemble the input haplotypes when secondary factors impacting the coverage are controlled. We therefore demonstrate that, by combining our approach with standard barcoding, the cost of the library preparation is reduced to a third.

Complete mitochondrial genome of the green-lipped mussel, Perna canaliculus (Mollusca: Mytiloidea), from long nanopore sequencing reads.

We describe here the first complete genome assembly of the New Zealand green-lipped mussel, Perna canaliculus, mitochondrion. The assembly was performed de novo from a mix of long nanopore sequencing reads and short sequencing reads. The genome is 16,005 bp long. Comparison to other Mytiloidea mitochondrial genomes indicates important gene rearrangements in this family.

Identifying predictors of time-inhomogeneous viral evolutionary processes.

Various factors determine the rate at which mutations are generated and fixed in viral genomes. Viral evolutionary rates may vary over the course of a single persistent infection and can reflect changes in replication rates and selective dynamics. Dedicated statistical inference approaches are required to understand how the complex interplay of these processes shapes the genetic diversity and divergence in viral populations. Although evolutionary models accommodating a high degree of complexity can now be formalized, adequately informing these models by potentially sparse data, and assessing the association of the resulting estimates with external predictors, remains a major challenge. In this article, we present a novel Bayesian evolutionary inference method, which integrates multiple potential predictors and tests their association with variation in the absolute rates of synonymous and non-synonymous substitutions along the evolutionary history. We consider clinical and virological measures as predictors, but also changes in population size trajectories that are simultaneously inferred using coalescent modelling. We demonstrate the potential of our method in an application to within-host HIV-1 sequence data sampled throughout the infection of multiple patients. While analyses of individual patient populations lack statistical power, we detect significant evidence for an abrupt drop in non-synonymous rates in late stage infection and a more gradual increase in synonymous rates over the course of infection in a joint analysis across all patients. The former is predicted by the immune relaxation hypothesis while the latter may be in line with increasing replicative fitness during the asymptomatic stage.

Computational Evaluation of the Strict Master and Random Template Models of Endogenous Retrovirus Evolution.

Transposable elements (TEs) are DNA sequences that are able to replicate and move within and between host genomes. Their mechanism of replication is also shared with endogenous retroviruses (ERVs), which are also a type of TE that represent an ancient retroviral infection within animal genomes. Two models have been proposed to explain TE proliferation in host genomes: the strict master model (SMM), and the random template (or transposon) model (TM). In SMM only a single copy of a given TE lineage is able to replicate, and all other genomic copies of TEs are derived from that master copy. In TM, any element of a given family is able to replicate in the host genome. In this paper, we simulated ERV phylogenetic trees under variations of SMM and TM. To test whether current phylogenetic programs can recover the simulated ERV phylogenies, DNA sequence alignments were simulated and maximum likelihood trees were reconstructed and compared to the simulated phylogenies. Results indicate that visual inspection of phylogenetic trees alone can be misleading. However, if a set of statistical summaries is calculated, we are able to distinguish between models with high accuracy by using a data mining algorithm that we introduce here. We also demonstrate the use of our data mining algorithm with empirical data for the porcine endogenous retrovirus (PERV), an ERV that is able to replicate in human and pig cells in vitro.

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.

Frequency-dependent selection drives HBeAg seroconversion in chronic hepatitis B virus infection.

HBeAg seroconversion is an important stage in the evolution of a chronic hepatitis B virus (HBV) infection that usually leads to control of viral replication and a reduced risk for liver cirrhosis and cancer. Since current therapies for the HBV-associated liver inflammation that is known as chronic hepatitis B (CHB). Rarely induce permanent HBeAg seroconversion, there is a need to understand the mechanisms responsible for the purpose of identifying new therapeutic targets. Currently, the most widely accepted hypothesis is that the patient's humoral and cellular immune responses to the HBV initiate HBeAg seroconversion. Although we accept that this hypothesis cannot be excluded, we propose an alternative that is consistent with published data on HBeAg seroconversion. We postulate, as others have, that the HBeAg suppresses the immune response to the HBV. However, production of the HBeAg incurs a metabolic cost to the hepatocyte which reduces the replicative capacity of the virus. Consequently, HBeAg-negative viruses replicate faster than HBeAg-positive viruses. HBeAg-negative variants arise de novo; and when their frequency in the population is low they have a replicative advantage. However, they also benefit from the immunosuppressive effects of the HBeAg-positive viruses in the population. As HBeAg-negative variants increase in frequency and HBeAg levels fall, the immune system recognizes the HBV, and HBeAg seroconversion occurs as a consequence of frequency-dependent selection acting on HBeAg-negative variants. This hypothesis explains the wide inter-individual variation in age of seroconversion, the increased rate of seroconversion during anti-viral treatment and the phenomena of both spontaneous and post-treatment HBeAg reversions (in which patients cycle between the HBeAg-positive and negative phases of their infection).

HIV-1 transmission during early antiretroviral therapy: evaluation of two HIV-1 transmission events in the HPTN 052 prevention study.

In the HPTN 052 study, transmission between HIV-discordant couples was reduced by 96% when the HIV-infected partner received suppressive antiretroviral therapy (ART). We examined two transmission events where the newly infected partner was diagnosed after the HIV-infected partner (index) initiated therapy. We evaluated the sequence complexity of the viral populations and antibody reactivity in the newly infected partner to estimate the dates of transmission to the newly infected partners. In both cases, transmission most likely occurred significantly before HIV-1 diagnosis of the newly infected partner, and either just before the initiation of therapy or before viral replication was adequately suppressed by therapy of the index. This study further strengthens the conclusion about the efficacy of blocking transmission by treating the infected partner of discordant couples. However, this study does not rule out the potential for HIV-1 transmission to occur shortly after initiation of ART, and this should be recognized when antiretroviral therapy is used for HIV-1 prevention.

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.

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.

Time-dependent rates of molecular evolution.

For over half a century, it has been known that the rate of morphological evolution appears to vary with the time frame of measurement. Rates of microevolutionary change, measured between successive generations, were found to be far higher than rates of macroevolutionary change inferred from the fossil record. More recently, it has been suggested that rates of molecular evolution are also time dependent, with the estimated rate depending on the timescale of measurement. This followed surprising observations that estimates of mutation rates, obtained in studies of pedigrees and laboratory mutation-accumulation lines, exceeded long-term substitution rates by an order of magnitude or more. Although a range of studies have provided evidence for such a pattern, the hypothesis remains relatively contentious. Furthermore, there is ongoing discussion about the factors that can cause molecular rate estimates to be dependent on time. Here we present an overview of our current understanding of time-dependent rates. We provide a summary of the evidence for time-dependent rates in animals, bacteria and viruses. We review the various biological and methodological factors that can cause rates to be time dependent, including the effects of natural selection, calibration errors, model misspecification and other artefacts. We also describe the challenges in calibrating estimates of molecular rates, particularly on the intermediate timescales that are critical for an accurate characterization of time-dependent rates. This has important consequences for the use of molecular-clock methods to estimate timescales of recent evolutionary events.

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.

Molecular epidemiology of feline immunodeficiency virus in the domestic cat (Felis catus).

Studying the evolutionary mechanisms of feline immunodeficiency virus in the domestic cat (Felis catus), FIV(Fca), provides a good comparison to other lentiviruses, such as HIV and FIV(Pco) in the cougar (Puma concolor). We review the current epidemiological and evolutionary findings of FIV(Fca). In addition to the five accepted FIV(Fca), subtypes, several recent phylogenetic studies have found strains that form separate clades, indicative of novel subtypes. In New Zealand cats, these strains of unknown subtype have been found to be involved in complex patterns of intergenic recombination, and whole genome sequences are required to resolve these. Evidence of recombination events has been documented with the highest levels in the env gene, the region involved in host cell receptor recognition. Several cases of FIV(Fca) multiple infections, both inter- and intra-subtype, have been reported. The findings of both unknown subtypes and relatively high levels of recombination suggest the need for further testing of the current vaccine. Limited studies on the evolutionary rate of FIV(Fca) document a value twice to three times that of FIV in the cougar, a result suggesting the different levels of co-adaptation between the viruses and their respective hosts. We studied the tissue distribution of FIV(Fca) in feral domestic cats, finding the first case of FIV compartmentalisation, a phenomenon well documented in HIV-1 patients.