Effective temperature of mutations.

Biological macromolecules experience two seemingly very different types of noise acting on different time scales: (i) point mutations corresponding to changes in molecular sequence and (ii) thermal fluctuations. Examining the secondary structures of a large number of microRNA precursor sequences and model lattice proteins, we show that the effects of single point mutations are statistically indistinguishable from those of an increase in temperature by a few tens of kelvins. The existence of such an effective mutational temperature establishes a quantitative connection between robustness to genetic (mutational) and environmental (thermal) perturbations

Efficient Exploration of the Space of Reconciled Gene Trees

Gene trees record the combination of gene level events, such as duplication, transfer and loss, and species level events, such as speciation and extinction. Gene tree-species tree reconciliation methods model these processes by drawing gene trees into the species tree using a series of gene and species level events. The reconstruction of gene trees based on sequence alone almost always involves choosing between statistically equivalent or weakly distinguishable relationships that could be much better resolved based on a putative species tree. To exploit this potential for accurate reconstruction of gene trees the space of reconciled gene trees must be explored according to a joint model of sequence evolution and gene tree-species tree reconciliation. Here we present amalgamated likelihood estimation (ALE), a probabilistic approach to exhaustively explore all reconciled gene trees that can be amalgamated as a combination of clades observed in a sample of trees. We implement ALE in the context of a reconciliation model, which allows for the duplication, transfer and loss of genes. We use ALE to efficiently approximate the sum of the joint likelihood over amalgamations and to find the reconciled gene tree that maximizes the joint likelihood. We demonstrate using simulations that gene trees reconstructed using the joint likelihood are substantially more accurate than those reconstructed using sequence alone. Using realistic topologies, branch lengths and alignment sizes, we demonstrate that ALE produces more accurate gene trees even if the model of sequence evolution is greatly simplified. Finally, examining 1099 gene families from 36 cyanobacterial genomes we find that joint likelihood-based inference results in a striking reduction in apparent phylogenetic discord, with 24%, 59% and 46% percent reductions in the mean numbers of duplications, transfers and losses.Comment: Manuscript accepted pending revision in Systematic Biolog

Joint amalgamation of most parsimonious reconciled gene trees.

MOTIVATION Traditionally, gene phylogenies have been reconstructed solely on the basis of molecular sequences; this, however, often does not provide enough information to distinguish between statistically equivalent relationships. To address this problem, several recent methods have incorporated information on the species phylogeny in gene tree reconstruction, leading to dramatic improvements in accuracy. Although probabilistic methods are able to estimate all model parameters but are computationally expensive, parsimony methods-generally computationally more efficient-require a prior estimate of parameters and of the statistical support. RESULTS Here, we present the Tree Estimation using Reconciliation (TERA) algorithm, a parsimony based, species tree aware method for gene tree reconstruction based on a scoring scheme combining duplication, transfer and loss costs with an estimate of the sequence likelihood. TERA explores all reconciled gene trees that can be amalgamated from a sample of gene trees. Using a large scale simulated dataset, we demonstrate that TERA achieves the same accuracy as the corresponding probabilistic method while being faster, and outperforms other parsimony-based methods in both accuracy and speed. Running TERA on a set of 1099 homologous gene families from complete cyanobacterial genomes, we find that incorporating knowledge of the species tree results in a two thirds reduction in the number of apparent transfer events

Genome-scale phylogenetic analysis finds extensive gene transfer among Fungi

Although the role of lateral gene transfer is well recognized in the evolution of bacteria, it is generally assumed that it has had less influence among eukaryotes. To explore this hypothesis we compare the dynamics of genome evolution in two groups of organisms: Cyanobacteria and Fungi. Ancestral genomes are inferred in both clades using two types of methods. First, Count, a gene tree unaware method that models gene duplications, gains and losses to explain the observed numbers of genes present in a genome. Second, ALE, a more recent gene tree-aware method that reconciles gene trees with a species tree using a model of gene duplication, loss, and transfer. We compare their merits and their ability to quantify the role of transfers, and assess the impact of taxonomic sampling on their inferences. We present what we believe is compelling evidence that gene transfer plays a significant role in the evolution of Fungi

Horizontal Gene Transfer and the History of Life

Microbes acquire DNA from a variety of sources. The last decades, which have seen the development of genome sequencing, have revealed that horizontal gene transfer has been a major evolutionary force that has constantly reshaped genomes throughout evolution. However, because the history of life must ultimately be deduced from gene phylogenies, the lack of methods to account for horizontal gene transfer has thrown into confusion the very concept of the tree of life. As a result, many questions remain open, but emerging method- ological developments promise to use information conveyed by horizontal gene transfer that remains unexploited today

The inference of gene trees with species trees.

This article reviews the various models that have been used to describe the relationships between gene trees and species trees. Molecular phylogeny has focused mainly on improving models for the reconstruction of gene trees based on sequence alignments. Yet, most phylogeneticists seek to reveal the history of species. Although the histories of genes and species are tightly linked, they are seldom identical, because genes duplicate, are lost or horizontally transferred, and because alleles can coexist in populations for periods that may span several speciation events. Building models describing the relationship between gene and species trees can thus improve the reconstruction of gene trees when a species tree is known, and vice versa. Several approaches have been proposed to solve the problem in one direction or the other, but in general neither gene trees nor species trees are known. Only a few studies have attempted to jointly infer gene trees and species trees. These models account for gene duplication and loss, transfer or incomplete lineage sorting. Some of them consider several types of events together, but none exists currently that considers the full repertoire of processes that generate gene trees along the species tree. Simulations as well as empirical studies on genomic data show that combining gene tree-species tree models with models of sequence evolution improves gene tree reconstruction. In turn, these better gene trees provide a more reliable basis for studying genome evolution or reconstructing ancestral chromosomes and ancestral gene sequences. We predict that gene tree-species tree methods that can deal with genomic data sets will be instrumental to advancing our understanding of genomic evolution

Nucleotide usage biases distort inferences of the species tree

This work was supported by the Vienna Science and Technology Fund (WWTF) [MA16-061] and partially supported by the Austrian Science Fund (FWF) [P34524-B]. GJS received funding from the European Research Council under the European Union’s Horizon 2020 research and innovation program under grant agreement no. 714774 and the grant GINOP-2.3.2.-15-2016-00057.Despite the importance of natural selection in species' evolutionary history, phylogenetic methods that take into account population-level processes typically ignore selection. The assumption of neutrality is often based on the idea that selection occurs at a minority of loci in the genome and is unlikely to compromise phylogenetic inferences significantly. However, genome-wide processes like GC-bias and some variation segregating at the coding regions are known to evolve in the nearly neutral range. As we are now using genome-wide data to estimate species trees, it is natural to ask whether weak but pervasive selection is likely to blur species tree inferences. We developed a polymorphism-aware phylogenetic model tailored for measuring signatures of nucleotide usage biases to test the impact of selection in the species tree. Our analyses indicate that while the inferred relationships among species are not significantly compromised, the genetic distances are systematically underestimated in a node-height dependent manner: i.e., the deeper nodes tend to be more underestimated than the shallow ones. Such biases have implications for molecular dating. We dated the evolutionary history of 30 worldwide fruit fly populations, and we found signatures of GC-bias considerably affecting the estimated divergence times (up to 23%) in the neutral model. Our findings call for the need to account for selection when quantifying divergence or dating species evolution.Publisher PDFPeer reviewe