Phase transition on the convergence rate of parameter estimation under an Ornstein-Uhlenbeck diffusion on a tree

Cécile Ané, Lam Si Tung Ho, Sebastien Roch
(Submitted on 6 Jun 2014)

Diffusion processes on trees are commonly used in evolutionary biology to model the joint distribution of continuous traits, such as body mass, across species. Estimating the parameters of such processes from tip values presents challenges because of the intrinsic correlation between the observations produced by the shared evolutionary history, thus violating the standard independence assumption of large-sample theory. For instance Ho and An\’e \cite{HoAne13} recently proved that the mean (also known in this context as selection optimum) of an Ornstein-Uhlenbeck process on a tree cannot be estimated consistently from an increasing number of tip observations if the tree height is bounded. Here, using a fruitful connection to the so-called reconstruction problem in probability theory, we study the convergence rate of parameter estimation in the unbounded height case. For the mean of the process, we provide a necessary and sufficient condition for the consistency of the maximum likelihood estimator (MLE) and establish a phase transition on its convergence rate in terms of the growth of the tree. In particular we show that a loss of n‾‾√-consistency (i.e., the variance of the MLE becomes Ω(n−1), where n is the number of tips) occurs when the tree growth is larger than a threshold related to the phase transition of the reconstruction problem. For the covariance parameters, we give a novel, efficient estimation method which achieves n‾‾√-consistency under natural assumptions on the tree.

Testing the Toxicofera: comparative reptile transcriptomics casts doubt on the single, early evolution of the reptile venom system

Adam D Hargreaves, Martin T Swain, Darren W Logan, John F Mulley

Background The identification of apparently conserved gene complements in the venom and salivary glands of a diverse set of reptiles led to the development of the Toxicofera hypothesis – the idea that there was a single, early evolution of the venom system in reptiles. However, this hypothesis is based largely on relatively small scale EST-based studies of only venom or salivary glands and toxic effects have been assigned to only some of these putative Toxcoferan toxins in some species. We set out to investigate the distribution of these putative venom toxin transcripts in order to investigate to what extent conservation of gene complements may reflect a bias in previous sampling efforts. Results We have carried out the first large-scale test of the Toxicofera hypothesis and found it lacking in a number of regards. Our quantitative transcriptomic analyses of venom and salivary glands and other body tissues in five species of reptile, together with the use of available RNA-Seq datasets for additional species shows that the majority of genes used to support the establishment and expansion of the Toxicofera are in fact expressed in multiple body tissues and most likely represent general maintenance or “housekeeping” genes. The apparent conservation of gene complements across the Toxicofera therefore reflects an artefact of incomplete tissue sampling. In other cases, the identification of a non-toxic paralog of a gene encoding a true venom toxin has led to confusion about the phylogenetic distribution of that venom component. Conclusions Venom has evolved multiple times in reptiles. In addition, the misunderstanding regarding what constitutes a toxic venom component, together with the misidentification of genes and the classification of identical or near-identical sequences as distinct genes has led to an overestimation of the complexity of reptile venoms in general, and snake venom in particular, with implications for our understanding of (and development of treatments to counter) the molecules responsible for the physiological consequences of snakebite.

Predicting evolution from the shape of genealogical trees

Richard A. Neher, Colin A. Russell, Boris I. Shraiman
(Submitted on 3 Jun 2014)

Given a sample of genome sequences from an asexual population, can one predict its evolutionary future? Here we demonstrate that the branching pattern of reconstructed genealogical trees contains information about the relative fitness of the sampled sequences and that this information can be used to infer the closest extant relative of future populations. Our approach is based on the assumption that evolution proceeds predominantly by accumulation of small effect mutations and does not require any species specific input. Hence, the resulting inference algorithm can be applied to any asexual population under persistent selection pressure. We demonstrate its performance using historical data on seasonal influenza A/H3N2 virus. We predict the progenitor lineage of the upcoming influenza season with near optimal performance in 30% of cases and makes informative predictions in 16 out of 18 years. Beyond providing a practical tool for prediction, our results suggest that continuous adaptation by small effect mutations is a major component of influenza virus evolution.

Epidemic reconstruction in a phylogenetics framework: transmission trees as partitions

Matthew Hall, Andrew Rambaut
(Submitted on 2 Jun 2014)

The reconstruction of transmission trees for epidemics from genetic data has been the subject of some recent interest. It has been demonstrated that the transmission tree structure can be investigated by augmenting internal nodes of a phylogenetic tree constructed using pathogen sequences from the epidemic with information about the host that held the corresponding lineage. In this paper, we note that this augmentation is equivalent to a correspondence between transmission trees and partitions of the phylogenetic tree into connected subtrees each containing one tip, and provide a framework for Markov Chain Monte Carlo inference of phylogenies that are partitioned in this way, giving a new method to co-estimate both trees. The procedure is integrated in the existing phylogenetic inference package BEAST.

The most parsimonious tree for random data

Mareike Fischer, Michelle Galla, Lina Herbst, Mike Steel
(Submitted on 1 Jun 2014)

Applying a method to reconstruct a phylogenetic tree from random data provides a way to detect whether that method has an inherent bias towards certain tree `shapes’. For maximum parsimony, applied to a sequence of random 2-state data, each possible binary phylogenetic tree has exactly the same distribution for its parsimony score. Despite this pleasing and slightly surprising symmetry, some binary phylogenetic trees are more likely than others to be a most parsimonious (MP) tree for a sequence of k such characters, as we show. For k=2, and unrooted binary trees on six taxa, any tree with a caterpillar shape has a higher chance of being an MP tree than any tree with a symmetric shape. On the other hand, if we take any two binary trees, on any number of taxa, we prove that this bias between the two trees vanishes as the number of characters grows. However, again there is a twist: MP trees on six taxa are more likely to have certain shapes than a uniform distribution on binary phylogenetic trees predicts, and this difference does not appear to dissipate as k grows.

Phylogenetic Identification and Functional Characterization of Orthologs and Paralogs across Human, Mouse, Fly, and Worm

Yi-Chieh Wu, Mukul S Bansal, Matthew D Rasmussen, Javier Herrero, Manolis Kellis

Model organisms can serve the biological and medical community by enabling the study of conserved gene families and pathways in experimentally-tractable systems. Their use, however, hinges on the ability to reliably identify evolutionary orthologs and paralogs with high accuracy, which can be a great challenge at both small and large evolutionary distances. Here, we present a phylogenomics-based approach for the identification of orthologous and paralogous genes in human, mouse, fly, and worm, which forms the foundation of the comparative analyses of the modENCODE and mouse ENCODE projects. We study a median of 16,101 genes across 2 mammalian genomes (human, mouse), 12 Drosophila genomes, 5 Caenorhabditis genomes, and an outgroup yeast genome, and demonstrate that accurate inference of evolutionary relationships and events across these species must account for frequent gene-tree topology errors due to both incomplete lineage sorting and insufficient phylogenetic signal. Furthermore, we show that integration of two separate phylogenomic pipelines yields increased accuracy, suggesting that their sources of error are independent, and finally, we leverage the resulting annotation of homologous genes to study the functional impact of gene duplication and loss in the context of rich gene expression and functional genomic datasets of the modENCODE, mouse ENCODE, and human ENCODE projects.

Quantifying the effects of anagenetic and cladogenetic evolution
Krzysztof Bartoszek

An ongoing debate in evolutionary biology is whether phenotypic change occurs predominantly around the time of speciation or whether it instead accumulates gradually over time. In this work I propose a general framework incorporating both types of change, quantify the effects of speciational change via the correlation between species and attribute the proportion of change to each type. I discuss results of parameter estimation of Hominoid body size in this light. I derive mathematical formulae related to this problem, the probability generating functions of the number of speciation events along a randomly drawn lineage and from the most recent common ancestor of two randomly chosen tip species for a conditioned Yule tree. Additionally I obtain in closed form the variance of the distance from the root to the most recent common ancestor of two randomly chosen tip species.

The Dawn of Open Access to Phylogenetic Data
Andrew F. Magee, Michael R. May, Brian R. Moore
(Submitted on 23 May 2014)

The scientific enterprise depends critically on the preservation of and open access to published data. This basic tenet applies acutely to phylogenies (estimates of evolutionary relationships among species). Increasingly, phylogenies are estimated from increasingly large, genome-scale datasets using increasingly complex statistical methods that require increasing levels of expertise and computational investment. Moreover, the resulting phylogenetic data provide an explicit historical perspective that critically informs research in a vast and growing number of scientific disciplines. One such use is the study of changes in rates of lineage diversification (speciation – extinction) through time. As part of a meta-analysis in this area, we sought to collect phylogenetic data (comprising nucleotide sequence alignment and tree files) from 217 studies published in 46 journals over a 13-year period. We document our attempts to procure those data (from online archives and by direct request to corresponding authors), and report results of analyses (using Bayesian logistic regression) to assess the impact of various factors on the success of our efforts. Overall, complete phylogenetic data for ~60% of these studies are effectively lost to science. Our study indicates that phylogenetic data are more likely to be deposited in online archives and/or shared upon request when: (1) the publishing journal has a strong data-sharing policy; (2) the publishing journal has a higher impact factor, and; (3) the data are requested from faculty rather than students. Although the situation appears dire, our analyses suggest that it is far from hopeless: recent initiatives by the scientific community — including policy changes by journals and funding agencies — are improving the state of affairs.

Evidence for strong co-evolution of mitochondrial and somatic genomes

Michael G.Sadovsky
(Submitted on 20 May 2014)

We studied a relations between the triplet frequency composition of mitochondria genomes, and the phylogeny of their bearers. First, the clusters in 63dimensional space were developed due to K-means. Second, the clade composition of those clusters has been studied. It was found that genomes are distributed among the clusters very regularly, with strong correlation to taxonomy. Strong co-evolution manifests through this correlation: the proximity in frequency space was determined over the mitochondrion genomes, while the proximity in taxonomy was determined morphologically.