Coevolutionary landscape inference and the context-dependence of mutations in beta-lactamase TEM-1

Coevolutionary landscape inference and the context-dependence of mutations in beta-lactamase TEM-1
Matteo Figliuzzi, Hervé Jacquier, Alexander Schug, Olivier Tenaillon, Martin Weigt

The quantitative characterization of mutational landscapes is a task of outstanding importance in evolutionary and medical biology: It is, e.g., of central importance for our understanding of the phenotypic effect of mutations related to disease and antibiotic drug resistance. Here we develop a novel inference scheme for mutational landscapes, which is based on the statistical analysis of large alignments of homologs of the protein of interest. Our method is able to capture epistatic couplings between residues, and therefore to assess the dependence of mutational effects on the sequence context where they appear. Compared to recent large-scale mutagenesis data of the beta-lactamase TEM-1, a protein providing resistance against beta-lactam antibiotics, our method leads to an increase of about 40% in explicative power as compared to approaches neglecting epistasis. We find that the informative sequence context extends to residues at native distances of about 20{\AA} from the mutated site, reaching thus far beyond residues in direct physical contact.

Genetic structure of the stingless bee Tetragonisca angustula

Genetic structure of the stingless bee Tetragonisca angustula
Flavio O Francisco, Leandro R Santiago, Yuri M Mizusawa, Benjamin P Oldroyd, Maria C Arias

Evaluating the performance of selection scans to detect selective sweeps in domestic dogs

Evaluating the performance of selection scans to detect selective sweeps in domestic dogs

Florencia Schlamp, Julian van der Made, Rebecca Stambler, Lewis Chesebrough, Adam R Boyko, Philipp W Messer

A segregating inversion generates fitness variation in a yellow monkeyflower (Mimulus guttatus) population

A segregating inversion generates fitness variation in a yellow monkeyflower (Mimulus guttatus) population

John Kelly, John Willis, Young Wha Lee, Lila Fishman

Genetic interactions contribute less than additive effects to quantitative trait variation in yeast

Genetic interactions contribute less than additive effects to quantitative trait variation in yeast

Joshua S Bloom, Iulia Kotenko, Meru J Sadhu, Sebastian Treusch, Frank W Albert, Leonid Kruglyak

Biogeographic dating of speciation times using paleogeographically informed processes

Biogeographic dating of speciation times using paleogeographically informed processes

Michael J Landis

Life history evolution in response to changes in metapopulation structure in an arthropod herbivore

Life history evolution in response to changes in metapopulation structure in an arthropod herbivore

Annelies De Roissart, Nicky Wybouw, David Renault, Thomas Van Leeuwen, Dries Bonte

3D RNA from evolutionary couplings

3D RNA from evolutionary couplings
Caleb Weinreb, Torsten Gross, Chris Sander, Debora S. Marks

RNA genes are ubiquitous in cell physiology, with a diverse repertoire of known functions. In fact, the majority of the eukaryotic genome does not code for proteins, and thousands of conserved RNAs of currently unknown function have been identified. Knowledge of 3D structure could can help elucidate the function of these RNAs but despite outstanding word using X-ray crystallography, NMR and cryoEM, structure determination remains low-throughput. RNA structure prediction in silico is a promising alternative. However, 3D structure prediction for large RNAs requires tertiary contacts between distant secondary structural elements that are difficult to infer with existing methods. Here, based only on sequences, we use a global statistical probability model of co-variation to detect 3D contacts, in analogy to recently developed breakthrough methods for computational protein folding. In blinded tests on 22 known RNA structures ranging in size from 65 to 1800 nucleotides, the predicted contacts matched physical interactions with 65-95% prediction accuracy. Importantly, we infer many long-range tertiary contacts, including non-Watson-Crick interactions. When used as restraints in molecular dynamics simulations, the inferred contacts improve RNA 3D structure prediction to a coordinate error as low as 6 to 10 Angstrom rmsd with potential for use with other constraints. These contacts include functionally important interactions, such as those that distinguish the active and inactive conformations of four riboswitches. In blind prediction mode, we present evolutionary couplings for 180 RNAs of unknown structure (available at this https URL). We anticipate that this approach will shed light on the structure and function of as yet less known RNA genes.

The species problem and its logic: Inescapable Ambiguity and Framework-relativity

The species problem and its logic: Inescapable Ambiguity and Framework-relativity
Steven James Bartlett

For more than fifty years, taxonomists have proposed numerous alternative definitions of species while they searched for a unique, comprehensive, and persuasive definition. This monograph shows that these efforts have been unnecessary, and indeed have provably been a pursuit of a will o’ the wisp because they have failed to recognize the theoretical impossibility of what they seek to accomplish. A clear and rigorous understanding of the logic underlying species definition leads both to a recognition of the inescapable ambiguity that affects the definition of species, and to a framework-relative approach to species definition that is logically compelling, i.e., cannot not be accepted without inconsistency. An appendix reflects upon the conclusions reached, applying them in an intellectually whimsical taxonomic thought experiment that conjectures the possibility of an emerging new human species.

Clustering genes of common evolutionary history

Clustering genes of common evolutionary history
Kevin Gori, Tomasz Suchan, Nadir Alvarez, Nick Goldman, Christophe Dessimoz

Phylogenetic inference can potentially result in a more accurate tree using data from multiple loci. However, if the loci are incongruent–due to events such as incomplete lineage sorting or horizontal gene transfer–it can be misleading to infer a single tree. To address this, many previous contributions have taken a mechanistic approach, by modelling specific processes. Alternatively, one can cluster loci without assuming how these incongruencies might arise. Such “process-agnostic” approaches typically infer a tree for each locus and cluster these. There are, however, many possible combinations of tree distance and clustering methods; their comparative performance in the context of tree incongruence is largely unknown. Furthermore, because standard model selection criteria such as AIC cannot be applied to problems with a variable number of topologies, the issue of inferring the optimal number of clusters is poorly understood. Here, we perform a large-scale simulation study of phylogenetic distances and clustering methods to infer loci of common evolutionary history. We observe that the best-performing combinations are distances accounting for branch lengths followed by spectral clustering or Ward’s method. We also introduce two statistical tests to infer the optimal number of clusters and show that they strongly outperform the silhouette criterion, a general-purpose heuristic. We illustrate the usefulness of the approach by (i) identifying errors in a previous phylogenetic analysis of yeast species and (ii) identifying topological incongruence among newly sequenced loci of the globeflower fly genus Chiastocheta. We release treeCl, a new program to cluster genes of common evolutionary history.