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2. Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations

Author

Lauterbur, M Elise, Cavassim, Maria Izabel A, Gladstein, Ariella L, Gower, Graham, Pope, Nathaniel S, Tsambos, Georgia, Adrion, Jeffrey, Belsare, Saurabh, Biddanda, Arjun, Caudill, Victoria, Cury, Jean, Echevarria, Ignacio, Haller, Benjamin C, Hasan, Ahmed R, Huang, Xin, Iasi, Leonardo Nicola Martin, Noskova, Ekaterina, Obsteter, Jana, Pavinato, Vitor Antonio Correa, Pearson, Alice, Peede, David, Perez, Manolo F, Rodrigues, Murillo F, Smith, Chris CR, Spence, Jeffrey P, Teterina, Anastasia, Tittes, Silas, Unneberg, Per, Vazquez, Juan Manuel, Waples, Ryan K, Wohns, Anthony Wilder, Wong, Yan, Baumdicker, Franz, Cartwright, Reed A, Gorjanc, Gregor, Gutenkunst, Ryan N, Kelleher, Jerome, Kern, Andrew D, Ragsdale, Aaron P, Ralph, Peter L, Schrider, Daniel R, and Gronau, Ilan

Subjects
Genetics, Biotechnology, Human Genome, Generic health relevance, Software, Computer Simulation, Genome, Genetics, Population, Genomics, population genetics, simulations, open source, None, genetics, genomics, none, Biochemistry and Cell Biology
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.

Published
2023

3. Efficient ancestry and mutation simulation with msprime 1.0

Author

Baumdicker, Franz, Bisschop, Gertjan, Goldstein, Daniel, Gower, Graham, Ragsdale, Aaron P, Tsambos, Georgia, Zhu, Sha, Eldon, Bjarki, Ellerman, E Castedo, Galloway, Jared G, Gladstein, Ariella L, Gorjanc, Gregor, Guo, Bing, Jeffery, Ben, Kretzschumar, Warren W, Lohse, Konrad, Matschiner, Michael, Nelson, Dominic, Pope, Nathaniel S, Quinto-Cortés, Consuelo D, Rodrigues, Murillo F, Saunack, Kumar, Sellinger, Thibaut, Thornton, Kevin, van Kemenade, Hugo, Wohns, Anthony W, Wong, Yan, Gravel, Simon, Kern, Andrew D, Koskela, Jere, Ralph, Peter L, and Kelleher, Jerome

Subjects
Algorithms, Computer Simulation, Genetics, Population, Models, Genetic, Mutation, Software, simulation, coalescent, mutations, Ancestral Recombination Graphs, Genetics, Developmental Biology
Abstract

Stochastic simulation is a key tool in population genetics, since the models involved are often analytically intractable and simulation is usually the only way of obtaining ground-truth data to evaluate inferences. Because of this, a large number of specialized simulation programs have been developed, each filling a particular niche, but with largely overlapping functionality and a substantial duplication of effort. Here, we introduce msprime version 1.0, which efficiently implements ancestry and mutation simulations based on the succinct tree sequence data structure and the tskit library. We summarize msprime's many features, and show that its performance is excellent, often many times faster and more memory efficient than specialized alternatives. These high-performance features have been thoroughly tested and validated, and built using a collaborative, open source development model, which reduces duplication of effort and promotes software quality via community engagement.

Published
2022

6. Mating frequency estimation and its importance for colony abundance analyses in eusocial pollinators: a case study of Bombus impatiens (Hymenoptera: Apidae).

Author

Bird, Sydney A, Pope, Nathaniel S, McGrady, Carley M, Fleischer, Shelby J, and López-Uribe, Margarita M

Subjects
BUMBLEBEES, WILDLIFE conservation, POLYANDRY, QUEENS (Insects), AGRICULTURE, BEE colonies
Abstract

The genus Bombus (bumble bees) includes approximately 265 species, many of which are in decline in North America and Europe. To estimate colony abundance of bumble bees in natural and agricultural habitats, sibship relationships are often reconstructed from genetic data with the assumption that colonies have 1 monandrous queen. However, some species such as the North American common eastern bumble bee (Bombus impatiens Cresson) can display low levels of polyandry, which may bias estimates of colony abundance based on monandrous sibship reconstructions. To accurately quantify rates of polyandry in wild and commercially mated queens of this species, we empirically estimated mating frequencies using a novel statistical model and genotypes from 730 bees. To genotype individuals, we used a highly polymorphic set of microsatellites on colonies established from 20 wild-caught gynes and 10 commercial colonies. We found multiple fathers in 3 of the wild colonies and 3 of the commercial colonies. This resulted in average effective mating frequencies of 1.075 ± 0.18 and 1.154 ± 0.25 for wild and commercial colonies, respectively. These findings agree with previous reports of low rates of polyandry for B. impatiens. Using a large empirical dataset, we demonstrate that assuming monandry for colony abundance estimation in species that violate this assumption results in an overestimation of the number of colonies. Our results emphasize the importance of studying mating frequencies in social species of conservation concern and economic importance for the accuracy of colony abundance estimation and for understanding their ecology and sociobiology. [ABSTRACT FROM AUTHOR]

Published
2024
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8. Mating frequency estimation and its importance for colony abundance analyses in eusocial pollinators: a case study of Bombus impatiens(Hymenoptera: Apidae)

Author

Bird, Sydney A, Pope, Nathaniel S, McGrady, Carley M, Fleischer, Shelby J, and López-Uribe, Margarita M

Abstract

The genus Bombus(bumble bees) includes approximately 265 species, many of which are in decline in North America and Europe. To estimate colony abundance of bumble bees in natural and agricultural habitats, sibship relationships are often reconstructed from genetic data with the assumption that colonies have 1 monandrous queen. However, some species such as the North American common eastern bumble bee (Bombus impatiensCresson) can display low levels of polyandry, which may bias estimates of colony abundance based on monandrous sibship reconstructions. To accurately quantify rates of polyandry in wild and commercially mated queens of this species, we empirically estimated mating frequencies using a novel statistical model and genotypes from 730 bees. To genotype individuals, we used a highly polymorphic set of microsatellites on colonies established from 20 wild-caught gynes and 10 commercial colonies. We found multiple fathers in 3 of the wild colonies and 3 of the commercial colonies. This resulted in average effective mating frequencies of 1.075 ± 0.18 and 1.154 ± 0.25 for wild and commercial colonies, respectively. These findings agree with previous reports of low rates of polyandry for B. impatiens. Using a large empirical dataset, we demonstrate that assuming monandry for colony abundance estimation in species that violate this assumption results in an overestimation of the number of colonies. Our results emphasize the importance of studying mating frequencies in social species of conservation concern and economic importance for the accuracy of colony abundance estimation and for understanding their ecology and sociobiology.

Published
2024
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12. Genetic structure and landscape effects on gene flow in the Neotropical lizard Norops brasiliensis(Squamata: Dactyloidae)

Author

Fonseca, Emanuel M., Pope, Nathaniel S., Peterman, William E., Werneck, Fernanda P., Colli, Guarino R., and Carstens, Bryan C.

Abstract

One key research goal of evolutionary biology is to understand the origin and maintenance of genetic variation. In the Cerrado, the South American savanna located primarily in the Central Brazilian Plateau, many hypotheses have been proposed to explain how landscape features (e.g., geographic distance, river barriers, topographic compartmentalization, and historical climatic fluctuations) have promoted genetic structure by mediating gene flow. Here, we asked whether these landscape features have influenced the genetic structure and differentiation in the lizard species Norops brasiliensis(Squamata: Dactyloidae). To achieve our goal, we used a genetic clustering analysis and estimate an effective migration surface to assess genetic structure in the focal species. Optimized isolation-by-resistance models and a simulation-based approach combined with machine learning (convolutional neural network; CNN) were then used to infer current and historical effects on population genetic structure through 12 unique landscape models. We recovered five geographically distributed populations that are separated by regions of lower-than-expected gene flow. The results of the CNN showed that geographic distance is the sole predictor of genetic variation in N. brasiliensis, and that slope, rivers, and historical climate had no discernible influence on gene flow. Our novel CNN approach was accurate (89.5%) in differentiating each landscape model. CNN and other machine learning approaches are still largely unexplored in landscape genetics studies, representing promising avenues for future research with increasingly accessible genomic datasets.

Published
2024
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13. Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations

Author

Lauterbur, M Elise, primary, Cavassim, Maria Izabel A, additional, Gladstein, Ariella L, additional, Gower, Graham, additional, Pope, Nathaniel S, additional, Tsambos, Georgia, additional, Adrion, Jeffrey, additional, Belsare, Saurabh, additional, Biddanda, Arjun, additional, Caudill, Victoria, additional, Cury, Jean, additional, Echevarria, Ignacio, additional, Haller, Benjamin C, additional, Hasan, Ahmed R, additional, Huang, Xin, additional, Iasi, Leonardo Nicola Martin, additional, Noskova, Ekaterina, additional, Obsteter, Jana, additional, Pavinato, Vitor Antonio Correa, additional, Pearson, Alice, additional, Peede, David, additional, Perez, Manolo F, additional, Rodrigues, Murillo F, additional, Smith, Chris CR, additional, Spence, Jeffrey P, additional, Teterina, Anastasia, additional, Tittes, Silas, additional, Unneberg, Per, additional, Vazquez, Juan Manuel, additional, Waples, Ryan K, additional, Wohns, Anthony Wilder, additional, Wong, Yan, additional, Baumdicker, Franz, additional, Cartwright, Reed A, additional, Gorjanc, Gregor, additional, Gutenkunst, Ryan N, additional, Kelleher, Jerome, additional, Kern, Andrew D, additional, Ragsdale, Aaron P, additional, Ralph, Peter L, additional, Schrider, Daniel R, additional, and Gronau, Ilan, additional

Published
2023
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14. Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations

Author

Lauterbur, M. Elise, primary, Cavassim, Maria Izabel A., additional, Gladstein, Ariella L., additional, Gower, Graham, additional, Pope, Nathaniel S., additional, Tsambos, Georgia, additional, Adrion, Jeff, additional, Belsare, Saurabh, additional, Biddanda, Arjun, additional, Caudill, Victoria, additional, Cury, Jean, additional, Echevarria, Ignacio, additional, Haller, Benjamin C., additional, Hasan, Ahmed R., additional, Huang, Xin, additional, Iasi, Leonardo Nicola Martin, additional, Noskova, Ekaterina, additional, Obšteter, Jana, additional, Pavinato, Vitor Antonio Corrêa, additional, Pearson, Alice, additional, Peede, David, additional, Perez, Manolo F., additional, Rodrigues, Murillo F., additional, Smith, Chris C. R., additional, Spence, Jeffrey P., additional, Teterina, Anastasia, additional, Tittes, Silas, additional, Unneberg, Per, additional, Vazquez, Juan Manuel, additional, Waples, Ryan K., additional, Wohns, Anthony Wilder, additional, Wong, Yan, additional, Baumdicker, Franz, additional, Cartwright, Reed A., additional, Gorjanc, Gregor, additional, Gutenkunst, Ryan N., additional, Kelleher, Jerome, additional, Kern, Andrew D., additional, Ragsdale, Aaron P., additional, Ralph, Peter L., additional, Schrider, Daniel R., additional, and Gronau, Ilan, additional

Published
2023
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16. Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations

Author

Lauterbur, M. Elise, Cavassim, Maria Izabel A., Gladstein, Ariella L., Gower, Graham, Pope, Nathaniel S., Tsambos, Georgia, Adrion, Jeffrey, Belsare, Saurabh, Biddanda, Arjun, Caudill, Victoria, Cury, Jean, Echevarria, Ignacio, Haller, Benjamin C., Hasan, Ahmed R., Huang, Xin, Iasi, Leonardo Nicola Martin, Noskova, Ekaterina, Obsteter, Jana, Pavinato, Vitor Antonio Correa, Pearson, Alice, Peede, David, Perez, Manolo F., Rodrigues, Murillo F., Smith, Chris C. R., Spence, Jeffrey P., Teterina, Anastasia, Tittes, Silas, Unneberg, Per, Vazquez, Juan Manuel, Waples, Ryan K., Wohns, Anthony Wilder, Wong, Yan, Baumdicker, Franz, Cartwright, Reed A., Gorjanc, Gregor, Gutenkunst, Ryan N., Kelleher, Jerome, Kern, Andrew D., Ragsdale, Aaron P., Ralph, Peter L., Schrider, Daniel R., Gronau, Ilan, Lauterbur, M. Elise, Cavassim, Maria Izabel A., Gladstein, Ariella L., Gower, Graham, Pope, Nathaniel S., Tsambos, Georgia, Adrion, Jeffrey, Belsare, Saurabh, Biddanda, Arjun, Caudill, Victoria, Cury, Jean, Echevarria, Ignacio, Haller, Benjamin C., Hasan, Ahmed R., Huang, Xin, Iasi, Leonardo Nicola Martin, Noskova, Ekaterina, Obsteter, Jana, Pavinato, Vitor Antonio Correa, Pearson, Alice, Peede, David, Perez, Manolo F., Rodrigues, Murillo F., Smith, Chris C. R., Spence, Jeffrey P., Teterina, Anastasia, Tittes, Silas, Unneberg, Per, Vazquez, Juan Manuel, Waples, Ryan K., Wohns, Anthony Wilder, Wong, Yan, Baumdicker, Franz, Cartwright, Reed A., Gorjanc, Gregor, Gutenkunst, Ryan N., Kelleher, Jerome, Kern, Andrew D., Ragsdale, Aaron P., Ralph, Peter L., Schrider, Daniel R., and Gronau, Ilan

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 pro

Published
2023
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26. Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations

Author

Lauterbur, M. Elise, primary, Cavassim, Maria Izabel A., additional, Gladstein, Ariella L., additional, Gower, Graham, additional, Pope, Nathaniel S., additional, Tsambos, Georgia, additional, Adrion, Jeff, additional, Belsare, Saurabh, additional, Biddanda, Arjun, additional, Caudill, Victoria, additional, Cury, Jean, additional, Echevarria, Ignacio, additional, Haller, Benjamin C., additional, Hasan, Ahmed R., additional, Huang, Xin, additional, Iasi, Leonardo Nicola Martin, additional, Noskova, Ekaterina, additional, Obšteter, Jana, additional, Pavinato, Vitor Antonio Corrêa, additional, Pearson, Alice, additional, Peede, David, additional, Perez, Manolo F., additional, Rodrigues, Murillo F., additional, Smith, Chris C. R., additional, Spence, Jeffrey P., additional, Teterina, Anastasia, additional, Tittes, Silas, additional, Unneberg, Per, additional, Vazquez, Juan Manuel, additional, Waples, Ryan K., additional, Wohns, Anthony Wilder, additional, Wong, Yan, additional, Baumdicker, Franz, additional, Cartwright, Reed A., additional, Gorjanc, Gregor, additional, Gutenkunst, Ryan N., additional, Kelleher, Jerome, additional, Kern, Andrew D., additional, Ragsdale, Aaron P., additional, Ralph, Peter L., additional, Schrider, Daniel R., additional, and Gronau, Ilan, additional

Published
2022
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35. Efficient ancestry and mutation simulation with msprime 1.0

Author

Baumdicker, Franz, Bisschop, Gertjan, Goldstein, Daniel, Gower, Graham, Ragsdale, Aaron P., Tsambos, Georgia, Zhu, Sha, Eldon, Bjarki, Ellerman, Castedo E., Galloway, Jared G., Gladstein, Ariella L., Gorjanc, Gregor, Guo, Bing, Jeffery, Ben, Kretzschmar, Warren W., Lohse, Konrad, Matschiner, Michael, Nelson, Dominic, Pope, Nathaniel S., Quinto-Cortés, Consuelo D., Rodrigues, Murillo F., Saunack, Kumar, Sellinger, Thibaut, Thornton, Kevin, van Kemenade, Hugo, Wohns, Anthony W., Wong, H. Yan, Gravel, Simon, Kern, Andrew D., Koskela, Jere, Ralph, Peter L., and Kelleher, Jerome

Abstract

Stochastic simulation is a key tool in population genetics, since the models involved are often analytically intractable and simulation is usually the only way of obtaining ground-truth data to evaluate inferences. Because of this necessity, a large number of specialised simulation programs have been developed, each filling a particular niche, but with largely overlapping functionality and a substantial duplication of effort. Here, we introduce msprime version 1.0, which efficiently implements ancestry and mutation simulations based on the succinct tree sequence data structure and tskit library. We summarise msprime’s many features, and show that its performance is excellent, often many times faster and more memory efficient than specialised alternatives. These high-performance features have been thoroughly tested and validated, and built using a collaborative, open source development model, which reduces duplication of effort and promotes software quality via community engagement.

Published
2021
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36. Efficient ancestry and mutation simulation with msprime 1.0

Author

Baumdicker, Franz, primary, Bisschop, Gertjan, additional, Goldstein, Daniel, additional, Gower, Graham, additional, Ragsdale, Aaron P, additional, Tsambos, Georgia, additional, Zhu, Sha, additional, Eldon, Bjarki, additional, Ellerman, E Castedo, additional, Galloway, Jared G, additional, Gladstein, Ariella L, additional, Gorjanc, Gregor, additional, Guo, Bing, additional, Jeffery, Ben, additional, Kretzschumar, Warren W, additional, Lohse, Konrad, additional, Matschiner, Michael, additional, Nelson, Dominic, additional, Pope, Nathaniel S, additional, Quinto-Cortés, Consuelo D, additional, Rodrigues, Murillo F, additional, Saunack, Kumar, additional, Sellinger, Thibaut, additional, Thornton, Kevin, additional, van Kemenade, Hugo, additional, Wohns, Anthony W, additional, Wong, Yan, additional, Gravel, Simon, additional, Kern, Andrew D, additional, Koskela, Jere, additional, Ralph, Peter L, additional, and Kelleher, Jerome, additional

Published
2021
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44. Burrowsia, a new genus of lichenized fungi (Caliciaceae), plus the new species B. cataractae and Scoliciosporum fabisporum, from Mpumalanga, South Africa

Author

12204145 - Siebert, Stefan John, 24678104 - Rajakaruna, Nishanta, Fryday, Alan M., Siebert, Stefan J., Rajakaruna, Nishanta, Medeiros, Ian D., Pope, Nathaniel, 12204145 - Siebert, Stefan John, 24678104 - Rajakaruna, Nishanta, Fryday, Alan M., Siebert, Stefan J., Rajakaruna, Nishanta, Medeiros, Ian D., and Pope, Nathaniel

Abstract

The new genus Burrowsia (Caliciaceae) is proposed to accommodate the new species B. cataractae, which is known from only a single locality in Mpumalanga, South Africa. Burrowsia is characterized by its pigmented, submuriform ascospores and ascus with an apical tube structure, and also by its DNA sequence data that place it outside related buellioid genera. We also describe the new species Scoliciosporum fabisporum, also known from a single locality in Mpumalanga, which differs from all other species of that genus in having distinctive kidney-shaped, 0–1-septate ascospores. It is most closely related to the Northern Hemisphere species S. intrusum, which is here confirmed by molecular data as belonging to this genus in a well-supported Scoliciosporaceae. The potential of the region to yield additional novel lichen taxa is explored

Published
2020

46. Landscape genomics to the rescue of a tropical bee threatened by habitat loss and climate change

Author

Jaffé, Rodolfo, primary, Veiga, Jamille C., additional, Pope, Nathaniel S., additional, Lanes, Éder C. M., additional, Carvalho, Carolina S., additional, Alves, Ronnie, additional, Andrade, Sónia C. S., additional, Arias, Maria C., additional, Bonatti, Vanessa, additional, Carvalho, Airton T., additional, Castro, Marina S., additional, Contrera, Felipe A. L., additional, Francoy, Tiago M., additional, Freitas, Breno M., additional, Giannini, Tereza C., additional, Hrncir, Michael, additional, Martins, Celso F., additional, Oliveira, Guilherme, additional, Saraiva, Antonio M., additional, Souza, Bruno A., additional, and Imperatriz‐Fonseca, Vera L., additional

Published
2019
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