Distinguishing regional from within-codon rate heterogeneity in DNA sequence alignments

We present an improved phylogenetic factorial hidden Markov model (FHMM) for detecting two types of mosaic structures in DNA sequence alignments, related to (1) recombination and (2) rate heterogeneity. The focus of the present work is on improving the modelling of the latter aspect. Earlier papers have modelled different degrees of rate heterogeneity with separate hidden states of the FHMM. This approach fails to appreciate the intrinsic difference between two types of rate heterogeneity: long-range regional effects, which are potentially related to differences in the selective pressure, and the short-term periodic patterns within the codons, which merely capture the signature of the genetic code. We propose an improved model that explicitly distinguishes between these two effects, and we assess its performance on a set of simulated DNA sequence alignments

Measuring the prevalence of regional mutation rates: an analysis of silent substitutions in mammals, fungi, and insects

BackgroundThe patterns of mutation vary both within and across genomes. It has been shown for a few mammals that mutation rates vary within the genome, while for unknown reasons, the sensu stricto yeasts have uniform rates instead. The generality of these observations has been unknown. Here we examine silent site substitutions in a more expansive set (20 mammals, 27 fungi, 4 insects) to determine why some genomes demonstrate this mosaic distribution and why others are uniform.ResultsWe applied several intragene and intergene correlation tests to measure regional substitution patterns. Assuming that silent sites are a reasonable approximation to neutrally mutating sequence, our results show that all multicellular eukaryotes exhibit mutational heterogeneity. In striking contrast, all fungi are mutationally uniform - with the exception of three Candida species: C. albicans, C. dubliniensis, and C. tropicalis. We speculate that aspects of replication timing may be responsible for distinguishing these species. Our analysis also reveals classes of genes whose silent sites behave anomalously with respect to the mutational background in many species, indicating prevalent selective pressures. Genes associated with nucleotide binding or gene regulation have consistently low silent substitution rates in every mammalian species, as well as multiple fungi. On the other hand, receptor genes repeatedly exhibit high silent substitution rates, suggesting they have been influenced by diversifying selection.ConclusionOur findings provide a framework for understanding the regional mutational properties of eukaryotes, revealing a sharp difference between fungi and multicellular species. They also elucidate common selective pressures acting on eukaryotic silent sites, with frequent evidence for both purifying and diversifying selection

Improved Bayesian methods for detecting recombination and rate heterogeneity in DNA sequence alignments

DNA sequence alignments are usually not homogeneous. Mosaic structures may result as a consequence of recombination or rate heterogeneity. Interspecific recombination, in which DNA subsequences are transferred between different (typically viral or bacterial) strains may result in a change of the topology of the underlying phylogenetic tree. Rate heterogeneity corresponds to a change of the nucleotide substitution rate. Various methods for simultaneously detecting recombination and rate heterogeneity in DNA sequence alignments have recently been proposed, based on complex probabilistic models that combine phylogenetic trees with factorial hidden Markov models or multiple changepoint processes. The objective of my thesis is to identify potential shortcomings of these models and explore ways of how to improve them. One shortcoming that I have identified is related to an approximation made in various recently proposed Bayesian models. The Bayesian paradigm requires the solution of an integral over the space of parameters. To render this integration analytically tractable, these models assume that the vectors of branch lengths of the phylogenetic tree are independent among sites. While this approximation reduces the computational complexity considerably, I show that it leads to the systematic prediction of spurious topology changes in the Felsenstein zone, that is, the area in the branch lengths configuration space where maximum parsimony consistently infers the wrong topology due to long-branch attraction. I demonstrate these failures by using two Bayesian hypothesis tests, based on an inter- and an intra-model approach to estimating the marginal likelihood. I then propose a revised model that addresses these shortcomings, and demonstrate its improved performance on a set of synthetic DNA sequence alignments systematically generated around the Felsenstein zone. The core model explored in my thesis is a phylogenetic factorial hidden Markov model (FHMM) for detecting two types of mosaic structures in DNA sequence alignments, related to recombination and rate heterogeneity. The focus of my work is on improving the modelling of the latter aspect. Earlier research efforts by other authors have modelled different degrees of rate heterogeneity with separate hidden states of the FHMM. Their work fails to appreciate the intrinsic difference between two types of rate heterogeneity: long-range regional effects, which are potentially related to differences in the selective pressure, and the short-term periodic patterns within the codons, which merely capture the signature of the genetic code. I have improved these earlier phylogenetic FHMMs in two respects. Firstly, by sampling the rate vector from the posterior distribution with RJMCMC I have made the modelling of regional rate heterogeneity more flexible, and I infer the number of different degrees of divergence directly from the DNA sequence alignment, thereby dispensing with the need to arbitrarily select this quantity in advance. Secondly, I explicitly model within-codon rate heterogeneity via a separate rate modification vector. In this way, the within-codon effect of rate heterogeneity is imposed on the model a priori, which facilitates the learning of the biologically more interesting effect of regional rate heterogeneity a posteriori. I have carried out simulations on synthetic DNA sequence alignments, which have borne out my conjecture. The existing model, which does not explicitly include the within-codon rate variation, has to model both effects with the same modelling mechanism. As expected, it was found to fail to disentangle these two effects. On the contrary, I have found that my new model clearly separates within-codon rate variation from regional rate heterogeneity, resulting in more accurate predictions

Population genomic analysis of base composition evolution in Drosophila melanogaster.

The relative importance of mutation, selection, and biased gene conversion to patterns of base composition variation in Drosophila melanogaster, and to a lesser extent, D. simulans, has been investigated for many years. However, genomic data from sufficiently large samples to thoroughly characterize patterns of base composition polymorphism within species have been lacking. Here, we report a genome-wide analysis of coding and noncoding polymorphism in a large sample of inbred D. melanogaster strains from Raleigh, North Carolina. Consistent with previous results, we observed that AT mutations fix more frequently than GC mutations in D. melanogaster. Contrary to predictions of previous models of codon usage in D. melanogaster, we found that synonymous sites segregating for derived AT polymorphisms were less skewed toward low frequencies compared with sites segregating a derived GC polymorphism. However, no such pattern was observed for comparable base composition polymorphisms in noncoding DNA. These results suggest that AT-ending codons could currently be favored by natural selection in the D. melanogaster lineage

Improved Bayesian methods for detecting recombination and rate heterogeneity in DNA sequence alignments

DNA sequence alignments are usually not homogeneous. Mosaic structures may result as a consequence of recombination or rate heterogeneity. Interspecific recombination, in which DNA subsequences are transferred between different (typically viral or bacterial) strains may result in a change of the topology of the underlying phylogenetic tree. Rate heterogeneity corresponds to a change of the nucleotide substitution rate. Various methods for simultaneously detecting recombination and rate heterogeneity in DNA sequence alignments have recently been proposed, based on complex probabilistic models that combine phylogenetic trees with factorial hidden Markov models or multiple changepoint processes. The objective of my thesis is to identify potential shortcomings of these models and explore ways of how to improve them. One shortcoming that I have identified is related to an approximation made in various recently proposed Bayesian models. The Bayesian paradigm requires the solution of an integral over the space of parameters. To render this integration analytically tractable, these models assume that the vectors of branch lengths of the phylogenetic tree are independent among sites. While this approximation reduces the computational complexity considerably, I show that it leads to the systematic prediction of spurious topology changes in the Felsenstein zone, that is, the area in the branch lengths configuration space where maximum parsimony consistently infers the wrong topology due to long-branch attraction. I demonstrate these failures by using two Bayesian hypothesis tests, based on an inter- and an intra-model approach to estimating the marginal likelihood. I then propose a revised model that addresses these shortcomings, and demonstrate its improved performance on a set of synthetic DNA sequence alignments systematically generated around the Felsenstein zone. The core model explored in my thesis is a phylogenetic factorial hidden Markov model (FHMM) for detecting two types of mosaic structures in DNA sequence alignments, related to recombination and rate heterogeneity. The focus of my work is on improving the modelling of the latter aspect. Earlier research efforts by other authors have modelled different degrees of rate heterogeneity with separate hidden states of the FHMM. Their work fails to appreciate the intrinsic difference between two types of rate heterogeneity: long-range regional effects, which are potentially related to differences in the selective pressure, and the short-term periodic patterns within the codons, which merely capture the signature of the genetic code. I have improved these earlier phylogenetic FHMMs in two respects. Firstly, by sampling the rate vector from the posterior distribution with RJMCMC I have made the modelling of regional rate heterogeneity more flexible, and I infer the number of different degrees of divergence directly from the DNA sequence alignment, thereby dispensing with the need to arbitrarily select this quantity in advance. Secondly, I explicitly model within-codon rate heterogeneity via a separate rate modification vector. In this way, the within-codon effect of rate heterogeneity is imposed on the model a priori, which facilitates the learning of the biologically more interesting effect of regional rate heterogeneity a posteriori. I have carried out simulations on synthetic DNA sequence alignments, which have borne out my conjecture. The existing model, which does not explicitly include the within-codon rate variation, has to model both effects with the same modelling mechanism. As expected, it was found to fail to disentangle these two effects. On the contrary, I have found that my new model clearly separates within-codon rate variation from regional rate heterogeneity, resulting in more accurate predictions

COMIT: identification of noncoding motifs under selection in coding sequences

COMIT is presented; an algorithm for detecting functional non-coding motifs in coding regions, separating nucleotide and amino acid effects

Context-dependent codon partition models provide significant increases in model fit in atpB and rbcL protein-coding genes

BACKGROUND: Accurate modelling of substitution processes in protein-coding sequences is often hampered by the computational burdens associated with full codon models. Lately, codon partition models have been proposed as a viable alternative, mimicking the substitution behaviour of codon models at a low computational cost. Such codon partition models however impose independent evolution of the different codon positions, which is overly restrictive from a biological point of view. Given that empirical research has provided indications of context-dependent substitution patterns at four-fold degenerate sites, we take those indications into account in this paper. RESULTS: We present so-called context-dependent codon partition models to assess previous empirical claims that the evolution of four-fold degenerate sites is strongly dependent on the composition of its two flanking bases. To this end, we have estimated and compared various existing independent models, codon models, codon partition models and context-dependent codon partition models for the atpB and rbcL genes of the chloroplast genome, which are frequently used in plant systematics. Such context-dependent codon partition models employ a full dependency scheme for four-fold degenerate sites, whilst maintaining the independence assumption for the first and second codon positions. CONCLUSIONS: We show that, both in the atpB and rbcL alignments of a collection of land plants, these context-dependent codon partition models significantly improve model fit over existing codon partition models. Using Bayes factors based on thermodynamic integration, we show that in both datasets the same context-dependent codon partition model yields the largest increase in model fit compared to an independent evolutionary model. Context-dependent codon partition models hence perform closer to codon models, which remain the best performing models at a drastically increased computational cost, compared to codon partition models, but remain computationally interesting alternatives to codon models. Finally, we observe that the substitution patterns in both datasets are drastically different, leading to the conclusion that combined analysis of these two genes using a single model may not be advisable from a context-dependent point of view

Phylogenetic Relationships Among Fishes in the Order Zeiformes Based on Molecular Data from Three Mitochondrial Loci

The Zeiformes (dories) are mid-water or deep (to 1000 m) marine acanthomorph fishes with a global, circumtropical, and circumtemperate distribution. Some species have a near-worldwide distribution, while others appear to be regional endemics, e.g., near New Zealand. Six families, 16 genera, and 33 species are currently recognized as valid. Relationships among them, however, remain unsettled, especially in light of recent proposals concerning the phylogenetic placement of zeiforms within the Paracanthopterygii rather than allied with beryciforms or percomorphs. The present study uses mtDNA characters to investigate zeiform interrelationships given their revised phylogenetic placement and attendant changes to their close outgroups, carried out as part of a larger study by Grande et al. (2018) also including nDNA + morphological characters in their assessment of zeiform phylogeny. Results indicate that revised outgroups affected the phylogenetic conclusions, particularly among genus and species level relationships, and that mtDNA analyses recover a different arrangement of family and genus relationships than proposed by prior morphology-only hypotheses. All analyses recovered monophyletic Zeidae, Cyttidae, and Oreosomatidae, and Zeniontidae, and non-monophyletic Parazenidae. Overall, results reflect the particular usefulness of mtDNA characters for examination of recent evolutionary events that shaped genus and species level relationships within Zeiformes, and the necessity of considering multiple lines of evidence to reveal the wider picture of zeiform evolution

Analysis of Sequence Conservation at Nucleotide Resolution

One of the major goals of comparative genomics is to understand the evolutionary history of each nucleotide in the human genome sequence, and the degree to which it is under selective pressure. Ascertainment of selective constraint at nucleotide resolution is particularly important for predicting the functional significance of human genetic variation and for analyzing the sequence substructure of cis-regulatory sequences and other functional elements. Current methods for analysis of sequence conservation are focused on delineation of conserved regions comprising tens or even hundreds of consecutive nucleotides. We therefore developed a novel computational approach designed specifically for scoring evolutionary conservation at individual base-pair resolution. Our approach estimates the rate at which each nucleotide position is evolving, computes the probability of neutrality given this rate estimate, and summarizes the result in a Sequence CONservation Evaluation (SCONE) score. We computed SCONE scores in a continuous fashion across 1% of the human genome for which high-quality sequence information from up to 23 genomes are available. We show that SCONE scores are clearly correlated with the allele frequency of human polymorphisms in both coding and noncoding regions. We find that the majority of noncoding conserved nucleotides lie outside of longer conserved elements predicted by other conservation analyses, and are experiencing ongoing selection in modern humans as evident from the allele frequency spectrum of human polymorphism. We also applied SCONE to analyze the distribution of conserved nucleotides within functional regions. These regions are markedly enriched in individually conserved positions and short (<15 bp) conserved “chunks.” Our results collectively suggest that the majority of functionally important noncoding conserved positions are highly fragmented and reside outside of canonically defined long conserved noncoding sequences. A small subset of these fragmented positions may be identified with high confidence