Biomedical subjects

Sergei L Kosakovsky Pond

Publications and source records attributed to Sergei L Kosakovsky Pond.

18 recordsLinked to original sources

PubMed2025

Viral genome sequence datasets display pervasive evidence of strand-specific substitution biases that are best described using non-reversible nucleotide substitution models.

Most phylogenetic trees are inferred using time-reversible evolutionary models that assume that the relative rates of substitution for any given pair of nucleotides are the same regardless of the direction of the substitutions. However, there is no reason to assume that the underlying biochemical mutational processes that cause substitutions are similarly symmetrical. We consider two non-reversible nucleotide substitution models: (1) a 6-rate non-reversible model (NREV6) that is applicable to analyzing mutational processes in double-stranded genomes in that complementary substitutions occur at identical rates; and (2) a 12-rate non-reversible model (NREV12) that is applicable to analyzing mutational processes in single-stranded (ss) genomes in that all substitution types are free to occur at different rates. Using likelihood ratio and Akaike Information Criterion-based model tests, we show that, surprisingly, NREV12 provided a significantly better fit than the General Time Reversible (GTR) and NREV6 models to 21/31 dsRNA and 20/30 dsDNA datasets. As expected, however, NREV12 provided a significantly better fit to 24/33 ssDNA and 40/47 ssRNA datasets. We tested how non-reversibility impacts the accuracy with which phylogenetic trees are inferred. As simulated degrees of non-reversibility (DNR) increased, the tree topology inferences using both NREV12 and GTR became more accurate, whereas inferred tree branch lengths became less accurate. We conclude that while non-reversible models should be helpful in the analysis of mutational processes in most virus species, there is no pressing need to use these models for routine phylogenetic inference.

Models of evolution↗

PubMed2006

GARD: a genetic algorithm for recombination detection.

MOTIVATION: Phylogenetic and evolutionary inference can be severely misled if recombination is not accounted for, hence screening for it should be an essential component of nearly every comparative study. The evolution of recombinant sequences can not be properly explained by a single phylogenetic tree, but several phylogenies may be used to correctly model the evolution of non-recombinant fragments. RESULTS: We developed a likelihood-based model selection procedure that uses a genetic algorithm to search multiple sequence alignments for evidence of recombination breakpoints and identify putative recombinant sequences. GARD is an extensible and intuitive method that can be run efficiently in parallel. Extensive simulation studies show that the method nearly always outperforms other available tools, both in terms of power and accuracy and that the use of GARD to screen sequences for recombination ensures good statistical properties for methods aimed at detecting positive selection. AVAILABILITY: Freely available http://www.datamonkey.org/GARD/

Algorithms↗

PubMed2006

Evolutionary model selection with a genetic algorithm: a case study using stem RNA.

The choice of a probabilistic model to describe sequence evolution can and should be justified. Underfitting the data through the use of overly simplistic models may miss out on interesting phenomena and lead to incorrect inferences. Overfitting the data with models that are too complex may ascribe biological meaning to statistical artifacts and result in falsely significant findings. We describe a likelihood-based approach for evolutionary model selection. The procedure employs a genetic algorithm (GA) to quickly explore a combinatorially large set of all possible time-reversible Markov models with a fixed number of substitution rates. When applied to stem RNA data subject to well-understood evolutionary forces, the models found by the GA 1) capture the expected overall rate patterns a priori; 2) fit the data better than the best available models based on a priori assumptions, suggesting subtle substitution patterns not previously recognized; 3) cannot be rejected in favor of the general reversible model, implying that the evolution of stem RNA sequences can be explained well with only a few substitution rate parameters; and 4) perform well on simulated data, both in terms of goodness of fit and the ability to estimate evolutionary rates. We also investigate the utility of several distance measures for comparing and contrasting inferred evolutionary models. Using widely available small computer clusters, our approach allows, for the first time, to evaluate the performance of existing RNA evolutionary models by comparing them with a large pool of candidate models and to validate common modeling assumptions. In addition, the new method provides the foundation for rigorous selection and comparison of substitution models for other types of sequence data.

Algorithms↗

PubMed2006

Evidence for positive selection on a sexual reproduction gene in the diatom genus Thalassiosira (Bacillariophyta).

Single likelihood ancestor counting (SLAC), fixed effects likelihood (FEL), and several random effects likelihood (REL) methods were utilized to identify positively and negatively selected sites in sexually induced gene 1 (Sig1) of four different Thalassiosira species. The SLAC analysis did not find any sites affected by positive selection but suggested 13 sites influenced by negative selection. The SLAC approach may be too conservative because of low sequence divergence. The FEL and REL analyses revealed over 60 negatively selected sites and two positively selected sites that were unique to each method. The REL method may not be able to reliably identify individual sites under selection when applied to short sequences with low divergence. Instead, we proposed a new alignment-wide test for adaptive evolution based on codon models with variation in synonymous and nonsynonymous substitution rates among sites and found evidence for diversifying evolution without relying on site-by-site testing. The performance of the FEL and REL approaches was evaluated by subjecting the tests to a type I error rate simulation analysis, using the specific characteristics of the Sig1 data set. Simulation results indicated that the FEL test had reasonable Type I errors, while REL might have been too liberal, suggesting that the two positively selected sites identified by FEL (codons 94 and 174) are not likely to be false positives. The evolution of these codon sites, one of which is located in functional domain II, appears to be associated with divergence among the three major Thalassiosira lineages.

Animals↗

PubMed2006

Automated phylogenetic detection of recombination using a genetic algorithm.

The evolution of homologous sequences affected by recombination or gene conversion cannot be adequately explained by a single phylogenetic tree. Many tree-based methods for sequence analysis, for example, those used for detecting sites evolving nonneutrally, have been shown to fail if such phylogenetic incongruity is ignored. However, it may be possible to propose several phylogenies that can correctly model the evolution of nonrecombinant fragments. We propose a model-based framework that uses a genetic algorithm to search a multiple-sequence alignment for putative recombination break points, quantifies the level of support for their locations, and identifies sequences or clades involved in putative recombination events. The software implementation can be run quickly and efficiently in a distributed computing environment, and various components of the methods can be chosen for computational expediency or statistical rigor. We evaluate the performance of the new method on simulated alignments and on an array of published benchmark data sets. Finally, we demonstrate that prescreening alignments with our method allows one to analyze recombinant sequences for positive selection.

Algorithms↗

PubMed2006

Adaptation to different human populations by HIV-1 revealed by codon-based analyses.

Several codon-based methods are available for detecting adaptive evolution in protein-coding sequences, but to date none specifically identify sites that are selected differentially in two populations, although such comparisons between populations have been historically useful in identifying the action of natural selection. We have developed two fixed effects maximum likelihood methods: one for identifying codon positions showing selection patterns that persist in a population and another for detecting whether selection is operating differentially on individual codons of a gene sampled from two different populations. Applying these methods to two HIV populations infecting genetically distinct human hosts, we have found that few of the positively selected amino acid sites persist in the population; the other changes are detected only at the tips of the phylogenetic tree and appear deleterious in the long term. Additionally, we have identified seven amino acid sites in protease and reverse transcriptase that are selected differentially in the two samples, demonstrating specific population-level adaptation of HIV to human populations.

Adaptation, Physiological↗

PubMed2006

Genetic attributes of cerebrospinal fluid-derived HIV-1 env.

HIV-1 often invades the CNS during primary infection, eventually resulting in neurological disorders in up to 50% of untreated patients. The CNS is a distinct viral reservoir, differing from peripheral tissues in immunological surveillance, target cell characteristics and antiretroviral penetration. Neurotropic HIV-1 likely develops distinct genotypic characteristics in response to this unique selective environment. We sought to catalogue the genetic features of CNS-derived HIV-1 by analysing 456 clonal RNA sequences of the C2-V3 env subregion generated from CSF and plasma of 18 chronically infected individuals. Neuropsychological performance of all subjects was evaluated and summarized as a global deficit score. A battery of phylogenetic, statistical and machine learning tools was applied to these data to identify genetic features associated with HIV-1 neurotropism and neurovirulence. Eleven of 18 individuals exhibited significant viral compartmentalization between blood and CSF (P < 0.01, Slatkin-Maddison test). A CSF-specific genetic signature was identified, comprising positions 9, 13 and 19 of the V3 loop. The residue at position 5 of the V3 loop was highly correlated with neurocognitive deficit (P < 0.0025, Fisher's exact test). Antibody-mediated HIV-1 neutralizing activity was significantly reduced in CSF with respect to autologous blood plasma (P < 0.042, Student's t-test). Accordingly, CSF-derived sequences exhibited constrained diversity and contained fewer glycosylated and positively selected sites. Our results suggest that there are several genetic features that distinguish CSF- and plasma-derived HIV-1 populations, probably reflecting altered cellular entry requirements and decreased immune pressure in the CNS. Furthermore, neurological impairment may be influenced by mutations within the viral V3 loop sequence.

Amino Acid Sequence↗

PubMed2006

A Dirichlet process model for detecting positive selection in protein-coding DNA sequences.

Most methods for detecting Darwinian natural selection at the molecular level rely on estimating the rates or numbers of nonsynonymous and synonymous changes in an alignment of protein-coding DNA sequences. In some of these methods, the nonsynonymous rate of substitution is allowed to vary across the sequence, permitting the identification of single amino acid positions that are under positive natural selection. However, it is unclear which probability distribution should be used to describe how the nonsynonymous rate of substitution varies across the sequence. One widely used solution is to model variation in the nonsynonymous rate across the sequence as a mixture of several discrete or continuous probability distributions. Unfortunately, there is little population genetics theory to inform us of the appropriate probability distribution for among-site variation in the nonsynonymous rate of substitution. Here, we describe an approach to modeling variation in the nonsynonymous rate of substitution by using a Dirichlet process mixture model. The Dirichlet process allows there to be a countably infinite number of nonsynonymous rate classes and is very flexible in accommodating different potential distributions for the nonsynonymous rate of substitution. We implemented the model in a fully Bayesian approach, with all parameters of the model considered as random variables.

Animals↗

PubMed2005

Neutralizing antibody responses drive the evolution of human immunodeficiency virus type 1 envelope during recent HIV infection.

HIV type 1 (HIV-1) can rapidly escape from neutralizing antibody responses. The genetic basis of this escape in vivo is poorly understood. We compared the pattern of evolution of the HIV-1 env gene between individuals with recent HIV infection whose virus exhibited either a low or a high rate of escape from neutralizing antibody responses. We demonstrate that the rate of viral escape at a phenotypic level is highly variable among individuals, and is strongly correlated with the rate of amino acid substitutions. We show that dramatic escape from neutralizing antibodies can occur in the relative absence of changes in glycosylation or insertions and deletions ("indels") in the envelope; conversely, changes in glycosylation and indels occur even in the absence of neutralizing antibody responses. Comparison of our data with the predictions of a mathematical model support a mechanism in which escape from neutralizing antibodies occurs via many amino acid substitutions, with low cross-neutralization between closely related viral strains. Our results suggest that autologous neutralizing antibody responses may play a pivotal role in the diversification of HIV-1 envelope during the early stages of infection.

Adult↗

PubMed2005

Codon volatility does not reflect selective pressure on the HIV-1 genome.

Codon volatility is defined as the proportion of a codon's point-mutation neighbors that encode different amino acids. The cumulative volatility of a gene in relation to its associated genome was recently reported to be an indicator of selection pressure. We used this approach to measure selection on all available full-length HIV-1 subtype B genomes in the Los Alamos HIV Sequence Database, and compared these estimates against those obtained via established likelihood- and distance-based comparative methods. Volatility failed to correlate with the results of any of the comparative methods demonstrating that it is not a reliable indicator of selection pressure.

Biological Evolution↗

PubMed2005

Datamonkey: rapid detection of selective pressure on individual sites of codon alignments.

UNLABELLED: Datamonkey is a web interface to a suite of cutting edge maximum likelihood-based tools for identification of sites subject to positive or negative selection. The methods range from very fast data exploration to the some of the most complex models available in public domain software, and are implemented to run in parallel on a cluster of computers. AVAILABILITY: http://www.datamonkey.org. In the future, we plan to expand the collection of available analytic tools, and provide a package for installation on other systems.

Algorithms↗

PubMed2005

Not so different after all: a comparison of methods for detecting amino acid sites under selection.

We consider three approaches for estimating the rates of nonsynonymous and synonymous changes at each site in a sequence alignment in order to identify sites under positive or negative selection: (1) a suite of fast likelihood-based "counting methods" that employ either a single most likely ancestral reconstruction, weighting across all possible ancestral reconstructions, or sampling from ancestral reconstructions; (2) a random effects likelihood (REL) approach, which models variation in nonsynonymous and synonymous rates across sites according to a predefined distribution, with the selection pressure at an individual site inferred using an empirical Bayes approach; and (3) a fixed effects likelihood (FEL) method that directly estimates nonsynonymous and synonymous substitution rates at each site. All three methods incorporate flexible models of nucleotide substitution bias and variation in both nonsynonymous and synonymous substitution rates across sites, facilitating the comparison between the methods. We demonstrate that the results obtained using these approaches show broad agreement in levels of Type I and Type II error and in estimates of substitution rates. Counting methods are well suited for large alignments, for which there is high power to detect positive and negative selection, but appear to underestimate the substitution rate. A REL approach, which is more computationally intensive than counting methods, has higher power than counting methods to detect selection in data sets of intermediate size but may suffer from higher rates of false positives for small data sets. A FEL approach appears to capture the pattern of rate variation better than counting methods or random effects models, does not suffer from as many false positives as random effects models for data sets comprising few sequences, and can be efficiently parallelized. Our results suggest that previously reported differences between results obtained by counting methods and random effects models arise due to a combination of the conservative nature of counting-based methods, the failure of current random effects models to allow for variation in synonymous substitution rates, and the naive application of random effects models to extremely sparse data sets. We demonstrate our methods on sequence data from the human immunodeficiency virus type 1 env and pol genes and simulated alignments.

Amino Acids↗

PubMed2005

Characterization of human immunodeficiency virus type 1 (HIV-1) envelope variation and neutralizing antibody responses during transmission of HIV-1 subtype B.

We analyzed neutralization sensitivity and genetic variation of transmitted subtype B human immunodeficiency virus type 1 (HIV-1) in eight recently infected men who have sex with men and the virus from the six subjects who infected them. In contrast to reports of heterosexual transmission of subtype C HIV-1, in which the transmitted virus appears to be more neutralization sensitive, we demonstrate that in our study population, relatively few phenotypic changes in neutralization sensitivity or genotypic changes in envelope occurred during transmission of subtype B HIV-1. We suggest that limited genetic variation within the infecting host reduces the likelihood of selective transmission of neutralization-sensitive HIV.

Acute Disease↗

PubMed2004

HyPhy: hypothesis testing using phylogenies.

UNLABELLED: The HyPhypackage is designed to provide a flexible and unified platform for carrying out likelihood-based analyses on multiple alignments of molecular sequence data, with the emphasis on studies of rates and patterns of sequence evolution. AVAILABILITY: http://www.hyphy.org CONTACT: muse@stat.ncsu.edu SUPPLEMENTARY INFORMATION: HyPhydocumentation and tutorials are available at http://www.hyphy.org.

Algorithms↗

PubMed2004

A genetic algorithm approach to detecting lineage-specific variation in selection pressure.

The ratio of nonsynonymous (dN) to synonymous (dS) substitution rates, omega, provides a measure of selection at the protein level. Models have been developed that allow omega to vary among lineages. However, these models require the lineages in which differential selection has acted to be specified a priori. We propose a genetic algorithm approach to assign lineages in a phylogeny to a fixed number of different classes of omega, thus allowing variable selection pressure without a priori specification of particular lineages. This approach can identify models with a better fit than a single-ratio model, and with fits that are better than (in an information theoretic sense) a fully local model, in which all lineages are assumed to evolve under different values of omega, but with far fewer parameters. By averaging over models which explain the data reasonably well, we can assess the robustness of our conclusions to uncertainty in model estimation. Our approach can also be used to compare results from models in which branch classes are specified a priori with a wide range of credible models. We illustrate our methods on primate lysozyme sequences and compare them with previous methods applied to the same data sets.

Algorithms↗

PubMed2004

A simple hierarchical approach to modeling distributions of substitution rates.

Genetic sequence data typically exhibit variability in substitution rates across sites. In practice, there is often too little variation to fit a different rate for each site in the alignment, but the distribution of rates across sites may not be well modeled using simple parametric families. Mixtures of different distributions can capture more complex patterns of rate variation, but are often parameter-rich and difficult to fit. We present a simple hierarchical model in which a baseline rate distribution, such as a gamma distribution, is discretized into several categories, the quantiles of which are estimated using a discretized beta distribution. Although this approach involves adding only two extra parameters to a standard distribution, a wide range of rate distributions can be captured. Using simulated data, we demonstrate that a "beta-" model can reproduce the moments of the rate distribution more accurately than the distribution used to simulate the data, even when the baseline rate distribution is misspecified. Using hepatitis C virus and mammalian mitochondrial sequences, we show that a beta- model can fit as well or better than a model with multiple discrete rate categories, and compares favorably with a model which fits a separate rate category to each site. We also demonstrate this discretization scheme in the context of codon models specifically aimed at identifying individual sites undergoing adaptive or purifying evolution.

Animals↗

PubMed2004

Column sorting: rapid calculation of the phylogenetic likelihood function.

Likelihood applications have become a central approach for molecular evolutionary analyses since the first computationally tractable treatment two decades ago. Although Felsenstein's original pruning algorithm makes likelihood calculations feasible, it is usually possible to take advantage of repetitive structure present in the data to arrive at even greater computational reductions. In particular, alignment columns with certain similarities have components of the likelihood calculation that are identical and need not be recomputed if columns are evaluated in an optimal order. We develop an algorithm for exploiting this speed improvement via an application of graph theory. The reductions provided by the method depend on both the tree and the data, but typical savings range between 15%and 50%. Real-data examples with time reductions of 80%have been identified. The overhead costs associated with implementing the algorithm are minimal, and they are recovered in all but the smallest data sets. The modifications will provide faster likelihood algorithms, which will allow likelihood methods to be applied to larger sets of taxa and to include more thorough searches of the tree topology space.

Algorithms↗

PubMed2002

Evolution of duplicated alpha-tubulin genes in ciliates.

Ciliates provide a powerful system to analyze the evolution of duplicated alpha-tubulin genes in the context of single-celled organisms. Genealogical analyses of ciliate alpha-tubulin sequences reveal five apparently recent gene duplications. Comparisons of paralogs in different ciliates implicate differing patterns of substitutions (e.g., ratios of replacement/synonymous nucleotides and radical/conservative amino acids) following duplication. Most substitutions between paralogs in Euplotes crassus, Halteria grandinella and Paramecium tetraurelia are synonymous. In contrast, alpha-tubulin paralogs within Stylonychia lemnae and Chilodonella uncinata are evolving at significantly different rates and have higher ratios of both replacement substitutions to synonymous substitutions and radical amino acid changes to conservative amino acid changes. Moreover, the amino acid substitutions in C. uncinata and S. lemnae paralogs are limited to short stretches that correspond to functionally important regions of the alpha-tubulin protein. The topology of ciliate alpha-tubulin genealogies are inconsistent with taxonomy based on morphology and other molecular markers, which may be due to taxonomic sampling, gene conversion, unequal rates of evolution, or asymmetric patterns of gene duplication and loss.

Amino Acid Sequence↗