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38 Publications visible to you, out of a total of 38
Treerecs: an integrated phylogenetic tool, from sequences to reconciliations

Abstract (Expand)

Motivation Gene and species tree reconciliation methods can be used to root gene trees and correct uncertainties that are due to scarcity of signal in multiple sequence alignments. So far, reconciliation … tools have not been integrated in standard phylogenetic software and they either lack of performance on certain functions, or usability for biologists. Results We present Treerecs, a phylogenetic software based on duplication-loss reconciliation. Treerecs is simple to install and to use, fast, versatile, with a graphic output, and can be used along with methods for phylogenetic inference on multiple alignments like PLL and Seaview. Availability Treerecs is open-source. Its source code (C++, AGPLv3) and manuals are available from https://project.inria.fr/treerecs/

Authors: Nicolas Comte, Benoit Morel, Damir Hasic, Laurent Guéguen, Bastien Boussau, Vincent Daubin, Simon Penel, Celine Scornavacca, Manolo Gouy, Alexandros Stamatakis, Eric Tannier, David P. Parsons

Date Published: 11th Oct 2019

Publication Type: Journal

GeneRax: A tool for species tree-aware maximum likelihood based gene tree inference under gene duplication, transfer, and loss

Abstract (Expand)

Inferring gene trees is difficult because alignments are often too short, and thus contain insufficient signal, while substitution models inevitably fail to capture the complexity of the evolutionary … processes. To overcome these challenges species tree-aware methods seek to use information from a putative species tree. However, there are few methods available that implement a full likelihood framework or account for horizontal gene transfers. Furthermore, these methods often require expensive data pre-processing (e.g., computing bootstrap trees), and rely on approximations and heuristics that limit the exploration of tree space. Here we present GeneRax, the first maximum likelihood species tree-aware gene tree inference software. It simultaneously accounts for substitutions at the sequence level and gene level events, such as duplication, transfer and loss and uses established maximum likelihood optimization algorithms. GeneRax can infer rooted gene trees for an arbitrary number of gene families, directly from the per-gene sequence alignments and a rooted, but undated, species tree. We show that compared to competing tools, on simulated data GeneRax infers trees that are the closest to the true tree in 90% of the simulations in terms relative Robinson-Foulds distance. While, on empirical datasets, GeneRax is the fastest among all tested methods when starting from aligned sequences, and that it infers trees with the highest likelihood score, based on our model. GeneRax completed tree inferences and reconciliations for 1099 Cyanobacteria families in eight minutes on 512 CPU cores. Thus, its advanced parallelization scheme enables large-scale analyses. GeneRax is available under GNU GPL at https://github.com/BenoitMorel/GeneRax.

Authors: Benoit Morel, Alexey M. Kozlov, Alexandros Stamatakis, Gergely J. Szöllősi

Date Published: 26th Sep 2019

Publication Type: Journal

Modeling Structural Constraints on Protein Evolution via Side-Chain Conformational States

Abstract (Expand)

Few models of sequence evolution incorporate parameters describing protein structure, despite its high conservation, essential functional role and increasing availability. We present a structurally … a structurally aware empirical substitution model for amino acid sequence evolution in which proteins are expressed using an expanded alphabet that relays both amino acid identity and structural information. Each character specifies an amino acid as well as information about the rotamer configuration of its side-chain: the discrete geometric pattern of permitted side-chain atomic positions, as defined by the dihedral angles between covalently linked atoms. By assigning rotamer states in 251,194 protein structures and identifying 4,508,390 substitutions between closely related sequences, we generate a 55-state “Dayhoff-like” model that shows that the evolutionary properties of amino acids depend strongly upon side-chain geometry. The model performs as well as or better than traditional 20-state models for divergence time estimation, tree inference, and ancestral state reconstruction. We conclude that not only is rotamer configuration a valuable source of information for phylogenetic studies, but that modeling the concomitant evolution of sequence and structure may have important implications for understanding protein folding and function.

Authors: Umberto Perron, Alexey M Kozlov, Alexandros Stamatakis, Nick Goldman, Iain H Moal

Date Published: 1st Sep 2019

Publication Type: Journal

12 Grand Challenges in Single-Cell Data Science

Abstract (Expand)

The recent upswing of microfluidics and combinatorial indexing strategies, further enhanced by very low sequencing costs, have turned single cell sequencing into an empowering technology; analyzing …zing thousands—or even millions—of cells per experimental run is becoming a routine assignment in laboratories worldwide. As a consequence, we are witnessing a data revolution in single cell biology. Although some issues are similar in spirit to those experienced in bulk sequencing, many of the emerging data science problems are unique to single cell analysis; together, they give rise to the new realm of 'Single-Cell Data Science'. Here, we outline twelve challenges that will be central in bringing this new field forward. For each challenge, the current state of the art in terms of prior work is reviewed, and open problems are formulated, with an emphasis on the research goals that motivate them. This compendium is meant to serve as a guideline for established researchers, newcomers and students alike, highlighting interesting and rewarding problems in 'Single-Cell Data Science' for the coming years.

Authors: David Laehnemann, Johannes Köster, Ewa Szczurek, Davis J McCarthy, Stephanie C Hicks, Mark D Robinson, Catalina A Vallejos, Niko Beerenwinkel, Kieran R Campbell, Ahmed Mahfouz, Luca Pinello, Pavel Skums, Alexandros Stamatakis, Camille Stephan-Otto Attolini, Samuel Aparicio, Jasmijn Baaijens, Marleen Balvert, Buys de Barbanson, Antonio Cappuccio, Giacomo Corleone, Bas E Dutilh, Maria Florescu, Victor Guryev, Rens Holmer, Katharina Jahn, Thamar Jessurun Lobo, Emma M Keizer, Indu Khatri, Szymon M Kiełbasa, Jan O Korbel, Alexey M Kozlov, Tzu-Hao Kuo, Boudewijn PF Lelieveldt, Ion I Mandoiu, John C Marioni, Tobias Marschall, Felix Mölder, Amir Niknejad, Łukasz Rączkowski, Marcel Reinders, Jeroen de Ridder, Antoine-Emmanuel Saliba, Antonios Somarakis, Oliver Stegle, Fabian J Theis, Huan Yang, Alex Zelikovsky, Alice C McHardy, Benjamin J Raphael, Sohrab P Shah, Alexander Schönhuth

Date Published: 23rd Aug 2019

Publication Type: Journal

ModelTest-NG: A New and Scalable Tool for the Selection of DNA and Protein Evolutionary Models

Abstract (Expand)

ModelTest-NG is a reimplementation from scratch of jModelTest and ProtTest, two popular tools for selecting the best-fit nucleotide and amino acid substitution models, respectively. ModelTest-NG is one … to two orders of magnitude faster than jModelTest and ProtTest but equally accurate and introduces several new features, such as ascertainment bias correction, mixture, and free-rate models, or the automatic processing of single partitions. ModelTest-NG is available under a GNU GPL3 license at https://github.com/ddarriba/modeltest , last accessed September 2, 2019.

Authors: Diego Darriba, David Posada, Alexey M Kozlov, Alexandros Stamatakis, Benoit Morel, Tomas Flouri

Date Published: 21st Aug 2019

Publication Type: Journal

Genesis and Gappa: Processing, Analyzing and Visualizing Phylogenetic (Placement) Data

Abstract (Expand)

The ever increasing amount of genomic and meta-genomic sequence data has transformed biology into a data-driven and compute-intensive discipline. Hence, there is a need for efficient algorithms and … scalable implementations thereof for analysing such data. We present GENESIS, a library for working with phylogenetic data, and GAPPA, an accompanying command line tool for conducting typical analyses on such data. While our tools primarily target phylogenetic trees and phylogenetic placements, they also offer a plethora of functions for handling genetic sequences, taxonomies, and other relevant data types. The tools aim at improved usability at the production stage (conducting data analyses) as well as the development stage (rapid prototyping): The modular interface of GENESIS simplifies numerous standard high-level tasks and analyses, while allowing for low-level customization at the same time. Our implementation relies on modern, multi-threaded C++11, and is substantially more com-putationally efficient than analogous tools. We already employed the core GENESIS library in several of our tools and publications, thereby proving its flexibility and utility. GENESIS and GAPPA are freely available under GPLv3 at http://github.com/lczech/genesis and http://github.com/lczech/gappa.

Authors: Lucas Czech, Pierre Barbera, Alexandros Stamatakis

Date Published: 28th May 2019

Publication Type: Journal

Long metabarcoding of the eukaryotic rDNA operon to phylogenetically and taxonomically resolve environmental diversity

Abstract (Expand)

High-throughput environmental DNA metabarcoding has revolutionized the analysis of microbial diversity, but this approach is generally restricted to amplicon sizes below 500 base pairs. These short … regions contain limited phylogenetic signal, which makes it impractical to use environmental DNA in full phylogenetic inferences. However, new long-read sequencing technologies such as the Pacific Biosciences platform may provide sufficiently large sequence lengths to overcome the poor phylogenetic resolution of short amplicons. To test this idea, we amplified soil DNA and used PacBio Circular Consensus Sequencing (CCS) to obtain a ~4500 bp region of the eukaryotic rDNA operon spanning most of the small (18S) and large subunit (28S) ribosomal RNA genes. The CCS reads were first treated with a novel curation workflow that generated 650 high-quality OTUs containing the physically linked 18S and 28S regions of the long amplicons. In order to assign taxonomy to these OTUs, we developed a phylogeny-aware approach based on the 18S region that showed greater accuracy and sensitivity than similarity-based and phylogenetic placement-based methods using shorter reads. The taxonomically-annotated OTUs were then combined with available 18S and 28S reference sequences to infer a well-resolved phylogeny spanning all major groups of eukaryotes, allowing to accurately derive the evolutionary origin of environmental diversity. A total of 1019 sequences were included, of which a majority (58%) corresponded to the new long environmental CCS reads. Comparisons to the 18S-only region of our amplicons revealed that the combined 18S-28S genes globally increased the phylogenetic resolution, recovering specific groupings otherwise missing. The long-reads also allowed to directly investigate the relationships among environmental sequences themselves, which represents a key advantage over the placement of short reads on a reference phylogeny. Altogether, our results show that long amplicons can be treated in a full phylogenetic framework to provide greater taxonomic resolution and a robust evolutionary perspective to environmental DNA.

Authors: Mahwash Jamy, Rachel Foster, Pierre Barbera, Lucas Czech, Alexey Kozlov, Alexandros Stamatakis, David Baß, Fabien Burki

Date Published: 5th May 2019

Publication Type: Journal

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