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Joint Inference of Selection and Demography

Applicant Wegmann Daniel
Number 149920
Funding scheme Project funding (Div. I-III)
Research institution Département de Biologie Faculté des Sciences Université de Fribourg
Institution of higher education University of Fribourg - FR
Main discipline Genetics
Start/End 01.11.2013 - 31.05.2017
Approved amount 594'746.00
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All Disciplines (4)

Discipline
Genetics
Zoology
Medical Statistics
Molecular Biology

Keywords (6)

Numerical Approximations; Evolutionary History; Natural Selection; Population Genetics; Human Genetics; Machine Learning

Lay Summary (German)

Lead
Gemeinsames Schätzen der demographischen Geschichte und der Rolle der Selektion
Lay summary
Die genetische Diversität, welche wir heute Beobachten, ist stark von der demographischen Geschichte einer Population oder Art geprägt. In einer kleinen Population, zum Beispiel, sind die meisten Individuen nahe miteinander verwandt und unterscheiden sich genetisch daher nur sehr gering. Im Gegensatz dazu sind Individuen einer grossen Population nur entfernt verwandt und die genetische Diversität ist in einer solchen Population deutlich grösser. Allerdings ist die demographische Geschichte nicht der einzige Prozess, welche die genetische Diversität beeinflusst. Eine weitere, ebenfalls potentiell starke Kraft ist Selektion, welche eine Mutation gegenüber einer anderen favorisiert so dass an dieser Stelle selbst die meisten Individuen einer grossen Population die genau gleiche Mutation tragen. Leider ist es mit gegenwärtigen statistischen Methoden sehr schwierig den Beitrag von Demographie und Selektion in der Vergangenheit aus der beobachteten genetischen Diversität zu schätzen. In diesem Projekt suchen wir deshalb nach neuen statistischen Methoden, welche die evolutive Geschichte mit Hilfe von numerischen Simulation schätzen. Dabei versuchen wir ins besondere nach Möglichkeiten auch Daten von gekoppelten Genen wie sie in genomischen Experimenten produziert werden einzubeziehen. Es ist weiter geplant unsere neuen Methoden auf eine Vielzahl existierender Datensätze anzuwenden, mit einem besonderen Fokus auf die Geschichte des Menschen und einem seiner Parasiten, dem Cytomegalovirus, von welchem weltweit rund 30% aller Menschen betroffen sind. Eine genaues Verständnis wie sich diese Virus auf Grund von Selektion an unser Immunsystem anpasst und ihm dadurch entgeht, so hoffen wir, wird es in der Zukunft ermöglichen gezielte Impfstoffe oder Behandlungen zu entwickeln.
Direct link to Lay Summary Last update: 30.09.2013

Responsible applicant and co-applicants

Employees

Publications

Publication
An Approximate Markov Model for the Wright-Fisher Diffusion and Its Application to Time Series Data.
Ferrer-Admetlla Anna, Leuenberger Christoph, Jensen Jeffrey D, Wegmann Daniel (2016), An Approximate Markov Model for the Wright-Fisher Diffusion and Its Application to Time Series Data., in Genetics, 203(2), 831-46.
Early farmers from across Europe directly descended from Neolithic Aegeans.
Hofmanová Zuzana, Kreutzer Susanne, Hellenthal Garrett, Sell Christian, Diekmann Yoan, Díez-Del-Molino David, van Dorp Lucy, López Saioa, Kousathanas Athanasios, Link Vivian, Kirsanow Karola, Cassidy Lara M, Martiniano Rui, Strobel Melanie, Scheu Amelie, Kotsakis Kostas, Halstead Paul, Shennan Stephen J, Bradley Daniel G, Currat Mathias, Veeramah Krishna R, Wegmann Daniel, Thomas Mark G, Papageorgopoulou Christina, Burger Joachim (2016), Early farmers from across Europe directly descended from Neolithic Aegeans., in Proceedings of the National Academy of Sciences of the United States of America, 113(25), 6886-91.
Early Neolithic genomes from the eastern Fertile Crescent
Broushaki Farnaz, Thomas Mark G, Link Vivian, López Saioa, van Dorp Lucy, Kirsanow Karola, Hofmanová Zuzana, Diekmann Yoan, Cassidy Lara M, Díez-del-Molino David, Kousathanas Athanasios, Sell Christian, Robson Harry K, Martiniano Rui, Blöcher Jens, Scheu Amelie, Kreutzer Susanne, Bollongino Ruth, Bradley Daniel G, Shennan Stephen, Veeramah Krishna R, Mashkour Marjan, Wegmann Daniel, Hellenthal Garrett, Burger Joachim (2016), Early Neolithic genomes from the eastern Fertile Crescent, in Science (New York, N.Y.), 353(6298), 499-503.
Likelihood-Free Inference in High-Dimensional Models.
Kousathanas Athanasios, Leuenberger Christoph, Helfer Jonas, Quinodoz Mathieu, Foll Matthieu, Wegmann Daniel (2016), Likelihood-Free Inference in High-Dimensional Models., in Genetics, 203(2), 893-904.
Influenza virus drug resistance: a time-sampled population genetics perspective.
Foll Matthieu, Poh Yu-Ping, Renzette Nicholas, Ferrer-Admetlla Anna, Bank Claudia, Shim Hyunjin, Malaspinas Anna-Sapfo, Ewing Gregory, Liu Ping, Wegmann Daniel, Caffrey Daniel R, Zeldovich Konstantin B, Bolon Daniel N, Wang Jennifer P, Kowalik Timothy F, Schiffer Celia A, Finberg Robert W, Jensen Jeffrey D (2014), Influenza virus drug resistance: a time-sampled population genetics perspective., in PLoS genetics, 10(2), 1004185-1004185.
Inference of evolutionary jumps in large phylogenies using Lévy processes
Duchen-Bocangle Pablo, Leuenberger Christoph, Szilágyi Sándor M, Harmon Luke, Eastman Jonathan, Schweizer Manuel, Wegmann Daniel, Inference of evolutionary jumps in large phylogenies using Lévy processes, in Systematic Biology.
Inferring Heterozygosity from Ancient and Low Coverage Genomes.
Kousathanas Athanasios, Leuenberger Christoph, Link Vivian, Sell Christian, Burger Joachim, Wegmann Daniel, Inferring Heterozygosity from Ancient and Low Coverage Genomes., in Genetics.

Collaboration

Group / person Country
Types of collaboration
Matthieu Foll, EPFL Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Christoph Leuenberger, University of Fribourg Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Mark G Thomas, University College London Great Britain and Northern Ireland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Jeffrey Jensen, EPFL Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Garrett Hellenthal, University college London Great Britain and Northern Ireland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Joachim Burger, University of Mainz, Germany Germany (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
Adaption to a Changing Environment Talk given at a conference The Demography of Adaptation 05.06.2016 Ascona, Switzerland Wegmann Daniel;
Institut universitaire de médecine sociale et préventive, Lausanne Individual talk Model based inference of mutation rates and selection strengths in humans and in- fluenza 01.12.2015 Lausanne, Switzerland Wegmann Daniel;
Department of EvolutionaryBiology and Environmental Studies, University of Zürich Individual talk Model based infrence of evolutionary histories 20.10.2015 Zürich, Switzerland Wegmann Daniel;
SMBE 2015 Poster Joint likelihood-free inference of the distribution of fitness effects, locus-specific selection and demographic history. 12.07.2015 Viennna, Austria Wegmann Daniel; Kousathanas Athanasios;
The coalescent: theory and applications Talk given at a conference Approximate Bayesian Computation 24.03.2015 Uppsala, Sweden Wegmann Daniel;
Environmental systems Sci- ence, ETH Zürich Individual talk Model based inference of evolutionary historie 19.11.2014 Zürich, Switzerland Wegmann Daniel;
Biological Sequence Analysis and Probabilistic Models Talk given at a conference Approximate Wright-Fisher processes and their application to time series data 19.07.2014 Ocford, Great Britain and Northern Ireland Wegmann Daniel;
SMBE 14 Poster The domestication history of Date Palms 08.06.2014 San Juan, Puerto Rico Gros-Balthazard Muriel; Wegmann Daniel;
AMBE 2014 Poster ABC with parameter specific statistics for joint inference of selection and demography 08.06.2014 San Juan, Puerto Rico Wegmann Daniel; Kousathanas Athanasios;
Vetmeduni Vienna Individual talk Model based inference of evolutionary histories 27.05.2014 Vienna, Austria Wegmann Daniel;
Systems genetics and evolution of nonhuman organisms Poster ABC with parameter specific statistics for joint inference of selection and demography 05.05.2014 Ascona, Switzerland Kousathanas Athanasios; Wegmann Daniel;
Aarhus University Individual talk Model based inference of evolutionary histories 05.12.2013 Aarhus, Denmark Wegmann Daniel;


Communication with the public

Communication Title Media Place Year
Media relations: print media, online media Ancient skeletons change views on origins of farming Science Daily International 2016
Media relations: print media, online media Europas erste Bauern waren Einwanderer Basler Zeitung German-speaking Switzerland 2016
Media relations: print media, online media First farmers’ motley roots Science International 2016
Media relations: print media, online media Jungsteinzeitliche Bauern Europas stammten aus der Ägäis Aargauer Zeitung German-speaking Switzerland 2016
Talks/events/exhibitions Kaffeesatz lesen aus altem Knochenmehl German-speaking Switzerland Western Switzerland 2016
Talks/events/exhibitions L’Homme, une espèce en évolution? Western Switzerland 2016
Media relations: print media, online media Les premiers paysans du Néolithique venaient de la mer Égée Swiss Info International German-speaking Switzerland Western Switzerland 2016
Media relations: print media, online media Two groups spread early agriculture Science News International 2016
Media relations: print media, online media What did the first farmers look like? The Christian Science Monitor International 2016
Media relations: print media, online media Zivilisation kam mit den Migranten Die Zeit International 2016

Awards

Title Year
Roux-Cantarini postdoc fellowship 2016
Award for best contribution in the meeting Systems genetics and evolution of nonhuman organisms (SGE 2014), Ascona, Switzerland 2014

Associated projects

Number Title Start Funding scheme
142643 Coestimating selection and demography 01.10.2012 Ambizione
173062 Identifying selection in the presence of gene flow 01.06.2017 Project funding (Div. I-III)

Abstract

Detecting signatures of past selective events provides insights into the evolutionary history of a species by evidencing adaptive events. The identification of molecular targets of selection in humans, for instance, pinpoints biologically relevant differences between us and other apes. In addition, inferences regarding selection provide important functional information by elucidating the interaction between genotype and phenotype. Since positions in the genome that are under selection must be functionally important, detecting signatures of selection has also been used extensively to identify functional regions or protein residues. Finally, inferring the molecular locations at which selection is acting may help us to predict responses to selective pressures in organisms such as viruses, which would revolutionize the management of pandemics and the development of drugs. Unfortunately, the demographic history is a major confounding factor when inferring past selective events. Indeed, neutrality tests are very sensitive to violations of the underlying assumption of constant population size, with false positive rates found to be as high as 90\% after a severe population bottleneck. Current approaches to deal with this problem rely on the assumption that selection is acting on a few loci only, while demography affects all loci equally. A two step procedure has been proposed in which a set of neutral loci are used to calibrate a demographic model against which putatively selected loci are compared. However, recent evidence suggests that selection may be common in the genome of many organisms and a priori knowledge on the neutrality of markers is often difficult to obtain. As a result, such an approach relies on very strong assumptions regarding the pervasiveness of adaptive mutations and may hence suffer from high false negative rates.There is currently no approach to estimate demography and selection jointly. However, recent advances in computational approaches offer new hopes to tackle such an inference. A particularly promising approach is Approximate Bayesian Computation (ABC), a technique to sidestep analytical likelihood calculations with simulations. To this end, ABC has been used to infer a wide range of evolutionary scenarios such as population bottlenecks, population splits and migration, but also to distinguish between a classic selective sweep and recurrent selective events.Here we propose to develop new approaches to genuinely estimate demography and selection jointly. We will begin by developing an ABC framework to estimate demography and selection jointly from unlinked loci, and to apply it to a variety of organisms with very different evolutionary histories. Since an application of ABC to large scale data sets is tenuous, major new developments are needed to reach this goal. Here we propose to develop a new ABC-MCMC algorithms with increased performance, an efficient recycling of simulations, and extending recent approaches to hybridize ABC with traditional full-likelihood methods. Next, we will develop new approaches to infer selection and demography genome-wide from a large set of linked loci. To achieve this, we will make extensive use of auto-regressive hidden Markov models (arHMM), an extension of a classic hidden Markov model that will allow us to take linkage between site more accurately into account. We will first use this technique to extend an existing approach to estimate parameters of an island model along with locus specific strengths of selection. Besides inferring the distribution of selective effects genome wide, such a model will also be readily applicable to genome-wide association studies by treating cases and controls as separate, yet related populations. Finally, we will attempt to include models allowing population size changes (e.g. bottlenecks) into the proposed arHMM by approximating emission probabilities using simulations, similar to the ABC framework. The proposed innovations will allow us to work towards answering some of the most controversial questions in evolutionary biology, namely the importance of adaptation in shaping genomic variation. We will approach these questions by inferring genome-wide selection coefficients of four organisms representing various selective and demographic histories: Drosophila melanogaster, humans and the human cytomegalovirus. These estimates will not only have broad implications for the development of new drugs, but will also greatly improve our understanding of the mode and tempo of adaptation.
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