eLife (Jun 2023)
Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations
- M Elise Lauterbur,
- Maria Izabel A Cavassim,
- Ariella L Gladstein,
- Graham Gower,
- Nathaniel S Pope,
- Georgia Tsambos,
- Jeffrey Adrion,
- Saurabh Belsare,
- Arjun Biddanda,
- Victoria Caudill,
- Jean Cury,
- Ignacio Echevarria,
- Benjamin C Haller,
- Ahmed R Hasan,
- Xin Huang,
- Leonardo Nicola Martin Iasi,
- Ekaterina Noskova,
- Jana Obsteter,
- Vitor Antonio Correa Pavinato,
- Alice Pearson,
- David Peede,
- Manolo F Perez,
- Murillo F Rodrigues,
- Chris CR Smith,
- Jeffrey P Spence,
- Anastasia Teterina,
- Silas Tittes,
- Per Unneberg,
- Juan Manuel Vazquez,
- Ryan K Waples,
- Anthony Wilder Wohns,
- Yan Wong,
- Franz Baumdicker,
- Reed A Cartwright,
- Gregor Gorjanc,
- Ryan N Gutenkunst,
- Jerome Kelleher,
- Andrew D Kern,
- Aaron P Ragsdale,
- Peter L Ralph,
- Daniel R Schrider,
- Ilan Gronau
Affiliations
- M Elise Lauterbur
- ORCiD
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, United States
- Maria Izabel A Cavassim
- ORCiD
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, United States
- Ariella L Gladstein
- ORCiD
- Embark Veterinary, Inc, Boston, United States
- Graham Gower
- ORCiD
- Section for Molecular Ecology and Evolution, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Nathaniel S Pope
- Institute of Ecology and Evolution, University of Oregon, Eugene, United States
- Georgia Tsambos
- ORCiD
- School of Mathematics and Statistics, University of Melbourne, Melbourne, Australia
- Jeffrey Adrion
- ORCiD
- Institute of Ecology and Evolution, University of Oregon, Eugene, United States; Ancestry DNA, San Francisco, United States
- Saurabh Belsare
- ORCiD
- Institute of Ecology and Evolution, University of Oregon, Eugene, United States
- Arjun Biddanda
- ORCiD
- 54Gene, Inc, Washington, United States
- Victoria Caudill
- ORCiD
- Institute of Ecology and Evolution, University of Oregon, Eugene, United States
- Jean Cury
- Universite Paris-Saclay, CNRS, INRIA, Laboratoire Interdisciplinaire des Sciences du Numerique, Orsay, France
- Ignacio Echevarria
- School of Life Sciences, University of Glasgow, Glasgow, United Kingdom
- Benjamin C Haller
- ORCiD
- Department of Computational Biology, Cornell University, Ithaca, United States
- Ahmed R Hasan
- ORCiD
- Department of Cell and Systems Biology, University of Toronto, Toronto, Canada; Department of Biology, University of Toronto Mississauga, Mississauga, Canada
- Xin Huang
- Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria; Human Evolution and Archaeological Sciences (HEAS), University of Vienna, Vienna, Austria
- Leonardo Nicola Martin Iasi
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- Ekaterina Noskova
- ORCiD
- Computer Technologies Laboratory, ITMO University, St Petersburg, Russian Federation
- Jana Obsteter
- Agricultural Institute of Slovenia, Department of Animal Science, Ljubljana, Slovenia
- Vitor Antonio Correa Pavinato
- ORCiD
- Entomology Department, The Ohio State University, Wooster, United States
- Alice Pearson
- Department of Genetics, University of Cambridge, Cambridge, United Kingdom; Department of Zoology, University of Cambridge, Cambridge, United Kingdom
- David Peede
- Department of Ecology, Evolution, and Organismal Biology, Brown University, Providence, United States; Center for Computational Molecular Biology, Brown University, Providence, United States
- Manolo F Perez
- Department of Genetics and Evolution, Federal University of Sao Carlos, Sao Carlos, Brazil
- Murillo F Rodrigues
- Institute of Ecology and Evolution, University of Oregon, Eugene, United States
- Chris CR Smith
- Institute of Ecology and Evolution, University of Oregon, Eugene, United States
- Jeffrey P Spence
- ORCiD
- Department of Genetics, Stanford University School of Medicine, Stanford, United States
- Anastasia Teterina
- Institute of Ecology and Evolution, University of Oregon, Eugene, United States
- Silas Tittes
- ORCiD
- Institute of Ecology and Evolution, University of Oregon, Eugene, United States
- Per Unneberg
- Department of Cell and Molecular Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
- Juan Manuel Vazquez
- ORCiD
- Department of Integrative Biology, University of California, Berkeley, Berkeley, United States
- Ryan K Waples
- Department of Biostatistics, University of Washington, Seattle, United States
- Anthony Wilder Wohns
- Broad Institute of MIT and Harvard, Cambridge, United States
- Yan Wong
- ORCiD
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
- Franz Baumdicker
- Cluster of Excellence - Controlling Microbes to Fight Infections, Eberhard Karls Universit¨at Tubingen, Tubingen, Germany
- Reed A Cartwright
- ORCiD
- School of Life Sciences and The Biodesign Institute, Arizona State University, Tempe, United States
- Gregor Gorjanc
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, United Kingdom
- Ryan N Gutenkunst
- ORCiD
- Department of Molecular and Cellular Biology, University of Arizona, Tucson, United States
- Jerome Kelleher
- ORCiD
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
- Andrew D Kern
- ORCiD
- Institute of Ecology and Evolution, University of Oregon, Eugene, United States
- Aaron P Ragsdale
- Department of Integrative Biology, University of Wisconsin–Madison, Madison, United States
- Peter L Ralph
- ORCiD
- Institute of Ecology and Evolution, University of Oregon, Eugene, United States; Department of Mathematics, University of Oregon, Eugene, United States
- Daniel R Schrider
- ORCiD
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, United States
- Ilan Gronau
- ORCiD
- Efi Arazi School of Computer Science, Reichman University, Herzliya, Israel
- DOI
- https://doi.org/10.7554/eLife.84874
- Journal volume & issue
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Vol. 12
Abstract
Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic datasets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed framework stdpopsim seeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version of stdpopsim focused on establishing this framework using six well-characterized model species (Adrion et al., 2020). Here, we report on major improvements made in the new release of stdpopsim (version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than threefold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed the best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements to stdpopsim aim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone.
Keywords
