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1. Valid Bootstraps for Networks with Applications to Network Visualisation

Author

Dilworth, Emerald, Davis, Ed, and Lawson, Daniel J.

Subjects
Statistics - Computation, Statistics - Applications, Statistics - Machine Learning
Abstract

Quantifying uncertainty in networks is an important step in modelling relationships and interactions between entities. We consider the challenge of bootstrapping an inhomogeneous random graph when only a single observation of the network is made and the underlying data generating function is unknown. We utilise an exchangeable network test that can empirically validate bootstrap samples generated by any method, by testing if the observed and bootstrapped networks are statistically distinguishable. We find that existing methods fail this test. To address this, we propose a principled, novel, distribution-free network bootstrap using k-nearest neighbour smoothing, that can regularly pass this exchangeable network test in both synthetic and real-data scenarios. We demonstrate the utility of this work in combination with the popular data visualisation method t-SNE, where uncertainty estimates from bootstrapping are used to explain whether visible structures represent real statistically sound structures.

Published
2024

2. SB-ETAS: using simulation based inference for scalable, likelihood-free inference for the ETAS model of earthquake occurrences

Author

Stockman, Samuel, Lawson, Daniel J., and Werner, Maximilian J.

Subjects
Statistics - Applications
Abstract

Performing Bayesian inference for the Epidemic-Type Aftershock Sequence (ETAS) model of earthquakes typically requires MCMC sampling using the likelihood function or estimating the latent branching structure. These tasks have computational complexity $O(n^2)$ with the number of earthquakes and therefore do not scale well with new enhanced catalogs, which can now contain an order of $10^6$ events. On the other hand, simulation from the ETAS model can be done more quickly $O(n \log n )$. We present SB-ETAS: simulation-based inference for the ETAS model. This is an approximate Bayesian method which uses Sequential Neural Posterior Estimation (SNPE), a machine learning based algorithm for learning posterior distributions from simulations. SB-ETAS can successfully approximate ETAS posterior distributions on shorter catalogues where it is computationally feasible to compare with MCMC sampling. Furthermore, the scaling of SB-ETAS makes it feasible to fit to very large earthquake catalogs, such as one for Southern California dating back to 1932. SB-ETAS can find Bayesian estimates of ETAS parameters for this catalog in less than 10 hours on a standard laptop, which would have taken over 2 weeks using MCMC. Looking beyond the standard ETAS model, this simulation based framework would allow earthquake modellers to define and infer parameters for much more complex models that have intractable likelihood functions.

Published
2024

4. The selection landscape and genetic legacy of ancient Eurasians

Author

Irving-Pease, Evan K, Refoyo-Martínez, Alba, Barrie, William, Ingason, Andrés, Pearson, Alice, Fischer, Anders, Sjögren, Karl-Göran, Halgren, Alma S, Macleod, Ruairidh, Demeter, Fabrice, Henriksen, Rasmus A, Vimala, Tharsika, McColl, Hugh, Vaughn, Andrew H, Speidel, Leo, Stern, Aaron J, Scorrano, Gabriele, Ramsøe, Abigail, Schork, Andrew J, Rosengren, Anders, Zhao, Lei, Kristiansen, Kristian, Iversen, Astrid KN, Fugger, Lars, Sudmant, Peter H, Lawson, Daniel J, Durbin, Richard, Korneliussen, Thorfinn, Werge, Thomas, Allentoft, Morten E, Sikora, Martin, Nielsen, Rasmus, Racimo, Fernando, and Willerslev, Eske

Subjects
Biological Sciences, Genetics, History, Heritage and Archaeology, Human Society, Archaeology, Historical Studies, Anthropology, Good Health and Well Being, Humans, Alzheimer Disease, Affect, Alleles, Agriculture, Europe, General Science & Technology
Abstract

The Holocene (beginning around 12,000 years ago) encompassed some of the most significant changes in human evolution, with far-reaching consequences for the dietary, physical and mental health of present-day populations. Using a dataset of more than 1,600 imputed ancient genomes1, we modelled the selection landscape during the transition from hunting and gathering, to farming and pastoralism across West Eurasia. We identify key selection signals related to metabolism, including that selection at the FADS cluster began earlier than previously reported and that selection near the LCT locus predates the emergence of the lactase persistence allele by thousands of years. We also find strong selection in the HLA region, possibly due to increased exposure to pathogens during the Bronze Age. Using ancient individuals to infer local ancestry tracts in over 400,000 samples from the UK Biobank, we identify widespread differences in the distribution of Mesolithic, Neolithic and Bronze Age ancestries across Eurasia. By calculating ancestry-specific polygenic risk scores, we show that height differences between Northern and Southern Europe are associated with differential Steppe ancestry, rather than selection, and that risk alleles for mood-related phenotypes are enriched for Neolithic farmer ancestry, whereas risk alleles for diabetes and Alzheimer's disease are enriched for Western hunter-gatherer ancestry. Our results indicate that ancient selection and migration were large contributors to the distribution of phenotypic diversity in present-day Europeans.

Published
2024

5. Elevated genetic risk for multiple sclerosis emerged in steppe pastoralist populations

Author

Barrie, William, Yang, Yaoling, Irving-Pease, Evan K, Attfield, Kathrine E, Scorrano, Gabriele, Jensen, Lise Torp, Armen, Angelos P, Dimopoulos, Evangelos Antonios, Stern, Aaron, Refoyo-Martinez, Alba, Pearson, Alice, Ramsøe, Abigail, Gaunitz, Charleen, Demeter, Fabrice, Jørkov, Marie Louise S, Møller, Stig Bermann, Springborg, Bente, Klassen, Lutz, Hyldgård, Inger Marie, Wickmann, Niels, Vinner, Lasse, Korneliussen, Thorfinn Sand, Allentoft, Morten E, Sikora, Martin, Kristiansen, Kristian, Rodriguez, Santiago, Nielsen, Rasmus, Iversen, Astrid KN, Lawson, Daniel J, Fugger, Lars, and Willerslev, Eske

Subjects
Biological Sciences, Genetics, History, Heritage and Archaeology, Archaeology, Historical Studies, Neurosciences, Autoimmune Disease, Multiple Sclerosis, Brain Disorders, Neurodegenerative, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Inflammatory and immune system, Neurological, Humans, Neurodegenerative Diseases, Cluster Analysis, Population Density, Child, Preschool, Europe, General Science & Technology
Abstract

Multiple sclerosis (MS) is a neuro-inflammatory and neurodegenerative disease that is most prevalent in Northern Europe. Although it is known that inherited risk for MS is located within or in close proximity to immune-related genes, it is unknown when, where and how this genetic risk originated1. Here, by using a large ancient genome dataset from the Mesolithic period to the Bronze Age2, along with new Medieval and post-Medieval genomes, we show that the genetic risk for MS rose among pastoralists from the Pontic steppe and was brought into Europe by the Yamnaya-related migration approximately 5,000 years ago. We further show that these MS-associated immunogenetic variants underwent positive selection both within the steppe population and later in Europe, probably driven by pathogenic challenges coinciding with changes in diet, lifestyle and population density. This study highlights the critical importance of the Neolithic period and Bronze Age as determinants of modern immune responses and their subsequent effect on the risk of developing MS in a changing environment.

Published
2024

6. 100 ancient genomes show repeated population turnovers in Neolithic Denmark

Author

Allentoft, Morten E, Sikora, Martin, Fischer, Anders, Sjögren, Karl-Göran, Ingason, Andrés, Macleod, Ruairidh, Rosengren, Anders, Schulz Paulsson, Bettina, Jørkov, Marie Louise Schjellerup, Novosolov, Maria, Stenderup, Jesper, Price, T Douglas, Fischer Mortensen, Morten, Nielsen, Anne Birgitte, Ulfeldt Hede, Mikkel, Sørensen, Lasse, Nielsen, Poul Otto, Rasmussen, Peter, Jensen, Theis Zetner Trolle, Refoyo-Martínez, Alba, Irving-Pease, Evan K, Barrie, William, Pearson, Alice, Sousa da Mota, Bárbara, Demeter, Fabrice, Henriksen, Rasmus A, Vimala, Tharsika, McColl, Hugh, Vaughn, Andrew, Vinner, Lasse, Renaud, Gabriel, Stern, Aaron, Johannsen, Niels Nørkjær, Ramsøe, Abigail Daisy, Schork, Andrew Joseph, Ruter, Anthony, Gotfredsen, Anne Birgitte, Henning Nielsen, Bjarne, Brinch Petersen, Erik, Kannegaard, Esben, Hansen, Jesper, Buck Pedersen, Kristoffer, Pedersen, Lisbeth, Klassen, Lutz, Meldgaard, Morten, Johansen, Morten, Uldum, Otto Christian, Lotz, Per, Lysdahl, Per, Bangsgaard, Pernille, Petersen, Peter Vang, Maring, Rikke, Iversen, Rune, Wåhlin, Sidsel, Anker Sørensen, Søren, Andersen, Søren H, Jørgensen, Thomas, Lynnerup, Niels, Lawson, Daniel J, Rasmussen, Simon, Korneliussen, Thorfinn Sand, Kjær, Kurt H, Durbin, Richard, Nielsen, Rasmus, Delaneau, Olivier, Werge, Thomas, Kristiansen, Kristian, and Willerslev, Eske

Subjects
Biological Sciences, Genetics, History, Heritage and Archaeology, Human Society, Archaeology, Historical Studies, Anthropology, Humans, Genomics, Genotype, Denmark, Emigrants and Immigrants, Scandinavians and Nordic People, General Science & Technology
Abstract

Major migration events in Holocene Eurasia have been characterized genetically at broad regional scales1-4. However, insights into the population dynamics in the contact zones are hampered by a lack of ancient genomic data sampled at high spatiotemporal resolution5-7. Here, to address this, we analysed shotgun-sequenced genomes from 100 skeletons spanning 7,300 years of the Mesolithic period, Neolithic period and Early Bronze Age in Denmark and integrated these with proxies for diet (13C and 15N content), mobility (87Sr/86Sr ratio) and vegetation cover (pollen). We observe that Danish Mesolithic individuals of the Maglemose, Kongemose and Ertebølle cultures form a distinct genetic cluster related to other Western European hunter-gatherers. Despite shifts in material culture they displayed genetic homogeneity from around 10,500 to 5,900 calibrated years before present, when Neolithic farmers with Anatolian-derived ancestry arrived. Although the Neolithic transition was delayed by more than a millennium relative to Central Europe, it was very abrupt and resulted in a population turnover with limited genetic contribution from local hunter-gatherers. The succeeding Neolithic population, associated with the Funnel Beaker culture, persisted for only about 1,000 years before immigrants with eastern Steppe-derived ancestry arrived. This second and equally rapid population replacement gave rise to the Single Grave culture with an ancestry profile more similar to present-day Danes. In our multiproxy dataset, these major demographic events are manifested as parallel shifts in genotype, phenotype, diet and land use.

Published
2024

7. Forecasting the 2016-2017 Central Apennines Earthquake Sequence with a Neural Point Process

Author

Stockman, Samuel, Lawson, Daniel J., and Werner, Maximilian J.

Subjects
Physics - Geophysics, Statistics - Applications, Statistics - Machine Learning
Abstract

Point processes have been dominant in modeling the evolution of seismicity for decades, with the Epidemic Type Aftershock Sequence (ETAS) model being most popular. Recent advances in machine learning have constructed highly flexible point process models using neural networks to improve upon existing parametric models. We investigate whether these flexible point process models can be applied to short-term seismicity forecasting by extending an existing temporal neural model to the magnitude domain and we show how this model can forecast earthquakes above a target magnitude threshold. We first demonstrate that the neural model can fit synthetic ETAS data, however, requiring less computational time because it is not dependent on the full history of the sequence. By artificially emulating short-term aftershock incompleteness in the synthetic dataset, we find that the neural model outperforms ETAS. Using a new enhanced catalog from the 2016-2017 Central Apennines earthquake sequence, we investigate the predictive skill of ETAS and the neural model with respect to the lowest input magnitude. Constructing multiple forecasting experiments using the Visso, Norcia and Campotosto earthquakes to partition training and testing data, we target M3+ events. We find both models perform similarly at previously explored thresholds (e.g., above M3), but lowering the threshold to M1.2 reduces the performance of ETAS unlike the neural model. We argue that some of these gains are due to the neural model's ability to handle incomplete data. The robustness to missing data and speed to train the neural model present it as an encouraging competitor in earthquake forecasting.

Published
2023

8. Population genomics of post-glacial western Eurasia

Author

Allentoft, Morten E., Sikora, Martin, Refoyo-Martínez, Alba, Irving-Pease, Evan K., Fischer, Anders, Barrie, William, Ingason, Andrés, Stenderup, Jesper, Sjögren, Karl-Göran, Pearson, Alice, Sousa da Mota, Bárbara, Schulz Paulsson, Bettina, Halgren, Alma, Macleod, Ruairidh, Jørkov, Marie Louise Schjellerup, Demeter, Fabrice, Sørensen, Lasse, Nielsen, Poul Otto, Henriksen, Rasmus A., Vimala, Tharsika, McColl, Hugh, Margaryan, Ashot, Ilardo, Melissa, Vaughn, Andrew, Fischer Mortensen, Morten, Nielsen, Anne Birgitte, Ulfeldt Hede, Mikkel, Johannsen, Niels Nørkjær, Rasmussen, Peter, Vinner, Lasse, Renaud, Gabriel, Stern, Aaron, Jensen, Theis Zetner Trolle, Scorrano, Gabriele, Schroeder, Hannes, Lysdahl, Per, Ramsøe, Abigail Daisy, Skorobogatov, Andrei, Schork, Andrew Joseph, Rosengren, Anders, Ruter, Anthony, Outram, Alan, Timoshenko, Aleksey A., Buzhilova, Alexandra, Coppa, Alfredo, Zubova, Alisa, Silva, Ana Maria, Hansen, Anders J., Gromov, Andrey, Logvin, Andrey, Gotfredsen, Anne Birgitte, Henning Nielsen, Bjarne, González-Rabanal, Borja, Lalueza-Fox, Carles, McKenzie, Catriona J., Gaunitz, Charleen, Blasco, Concepción, Liesau, Corina, Martinez-Labarga, Cristina, Pozdnyakov, Dmitri V., Cuenca-Solana, David, Lordkipanidze, David O., En’shin, Dmitri, Salazar-García, Domingo C., Price, T. Douglas, Borić, Dušan, Kostyleva, Elena, Veselovskaya, Elizaveta V., Usmanova, Emma R., Cappellini, Enrico, Brinch Petersen, Erik, Kannegaard, Esben, Radina, Francesca, Eylem Yediay, Fulya, Duday, Henri, Gutiérrez-Zugasti, Igor, Merts, Ilya, Potekhina, Inna, Shevnina, Irina, Altinkaya, Isin, Guilaine, Jean, Hansen, Jesper, Aura Tortosa, Joan Emili, Zilhão, João, Vega, Jorge, Buck Pedersen, Kristoffer, Tunia, Krzysztof, Zhao, Lei, Mylnikova, Liudmila N., Larsson, Lars, Metz, Laure, Yepiskoposyan, Levon, Pedersen, Lisbeth, Sarti, Lucia, Orlando, Ludovic, Slimak, Ludovic, Klassen, Lutz, Blank, Malou, González-Morales, Manuel, Silvestrini, Mara, Vretemark, Maria, Nesterova, Marina S., Rykun, Marina, Rolfo, Mario Federico, Szmyt, Marzena, Przybyła, Marcin, Calattini, Mauro, Sablin, Mikhail, Dobisíková, Miluše, Meldgaard, Morten, Johansen, Morten, Berezina, Natalia, Card, Nick, Saveliev, Nikolai A., Poshekhonova, Olga, Rickards, Olga, Lozovskaya, Olga V., Gábor, Olivér, Uldum, Otto Christian, Aurino, Paola, Kosintsev, Pavel, Courtaud, Patrice, Ríos, Patricia, Mortensen, Peder, Lotz, Per, Persson, Per, Bangsgaard, Pernille, de Barros Damgaard, Peter, Vang Petersen, Peter, Martinez, Pilar Prieto, Włodarczak, Piotr, Smolyaninov, Roman V., Maring, Rikke, Menduiña, Roberto, Badalyan, Ruben, Iversen, Rune, Turin, Ruslan, Vasilyev, Sergey, Wåhlin, Sidsel, Borutskaya, Svetlana, Skochina, Svetlana, Sørensen, Søren Anker, Andersen, Søren H., Jørgensen, Thomas, Serikov, Yuri B., Molodin, Vyacheslav I., Smrcka, Vaclav, Merts, Victor, Appadurai, Vivek, Moiseyev, Vyacheslav, Magnusson, Yvonne, Kjær, Kurt H., Lynnerup, Niels, Lawson, Daniel J., Sudmant, Peter H., Rasmussen, Simon, Korneliussen, Thorfinn Sand, Durbin, Richard, Nielsen, Rasmus, Delaneau, Olivier, Werge, Thomas, Racimo, Fernando, Kristiansen, Kristian, and Willerslev, Eske

Published
2024
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9. CLARITY -- Comparing heterogeneous data using dissimiLARITY

Author

Lawson, Daniel J., Solanki, Vinesh, Yanovich, Igor, Dellert, Johannes, Ruck, Damian, and Endicott, Phillip

Subjects
Statistics - Methodology, Statistics - Machine Learning
Abstract

Integrating datasets from different disciplines is hard because the data are often qualitatively different in meaning, scale, and reliability. When two datasets describe the same entities, many scientific questions can be phrased around whether the (dis)similarities between entities are conserved across such different data. Our method, CLARITY, quantifies consistency across datasets, identifies where inconsistencies arise, and aids in their interpretation. We illustrate this using three diverse comparisons: gene methylation vs expression, evolution of language sounds vs word use, and country-level economic metrics vs cultural beliefs. The non-parametric approach is robust to noise and differences in scaling, and makes only weak assumptions about how the data were generated. It operates by decomposing similarities into two components: a `structural' component analogous to a clustering, and an underlying `relationship' between those structures. This allows a `structural comparison' between two similarity matrices using their predictability from `structure'. Significance is assessed with the help of re-sampling appropriate for each dataset. The software, CLARITY, is available as an R package from https://github.com/danjlawson/CLARITY., Comment: R package available from https://github.com/danjlawson/CLARITY . 30 pages, 8 Figures

Published
2020

10. Publisher Correction: Population genomics of post-glacial western Eurasia

Author

Allentoft, Morten E., Sikora, Martin, Refoyo-Martínez, Alba, Irving-Pease, Evan K., Fischer, Anders, Barrie, William, Ingason, Andrés, Stenderup, Jesper, Sjögren, Karl-Göran, Pearson, Alice, Sousa da Mota, Bárbara, Schulz Paulsson, Bettina, Halgren, Alma, Macleod, Ruairidh, Jørkov, Marie Louise Schjellerup, Demeter, Fabrice, Sørensen, Lasse, Nielsen, Poul Otto, Henriksen, Rasmus A., Vimala, Tharsika, McColl, Hugh, Margaryan, Ashot, Ilardo, Melissa, Vaughn, Andrew, Fischer Mortensen, Morten, Nielsen, Anne Birgitte, Ulfeldt Hede, Mikkel, Johannsen, Niels Nørkjær, Rasmussen, Peter, Vinner, Lasse, Renaud, Gabriel, Stern, Aaron, Jensen, Theis Zetner Trolle, Scorrano, Gabriele, Schroeder, Hannes, Lysdahl, Per, Ramsøe, Abigail Daisy, Skorobogatov, Andrei, Schork, Andrew Joseph, Rosengren, Anders, Ruter, Anthony, Outram, Alan, Timoshenko, Aleksey A., Buzhilova, Alexandra, Coppa, Alfredo, Zubova, Alisa, Silva, Ana Maria, Hansen, Anders J., Gromov, Andrey, Logvin, Andrey, Gotfredsen, Anne Birgitte, Henning Nielsen, Bjarne, González-Rabanal, Borja, Lalueza-Fox, Carles, McKenzie, Catriona J., Gaunitz, Charleen, Blasco, Concepción, Liesau, Corina, Martinez-Labarga, Cristina, Pozdnyakov, Dmitri V., Cuenca-Solana, David, Lordkipanidze, David O., En’shin, Dmitri, Salazar-García, Domingo C., Price, T. Douglas, Borić, Dušan, Kostyleva, Elena, Veselovskaya, Elizaveta V., Usmanova, Emma R., Cappellini, Enrico, Brinch Petersen, Erik, Kannegaard, Esben, Radina, Francesca, Eylem Yediay, Fulya, Duday, Henri, Gutiérrez-Zugasti, Igor, Merts, Ilya, Potekhina, Inna, Shevnina, Irina, Altinkaya, Isin, Guilaine, Jean, Hansen, Jesper, Aura Tortosa, Joan Emili, Zilhão, João, Vega, Jorge, Buck Pedersen, Kristoffer, Tunia, Krzysztof, Zhao, Lei, Mylnikova, Liudmila N., Larsson, Lars, Metz, Laure, Yepiskoposyan, Levon, Pedersen, Lisbeth, Sarti, Lucia, Orlando, Ludovic, Slimak, Ludovic, Klassen, Lutz, Blank, Malou, González-Morales, Manuel, Silvestrini, Mara, Vretemark, Maria, Nesterova, Marina S., Rykun, Marina, Rolfo, Mario Federico, Szmyt, Marzena, Przybyła, Marcin, Calattini, Mauro, Sablin, Mikhail, Dobisíková, Miluše, Meldgaard, Morten, Johansen, Morten, Berezina, Natalia, Card, Nick, Saveliev, Nikolai A., Poshekhonova, Olga, Rickards, Olga, Lozovskaya, Olga V., Gábor, Olivér, Uldum, Otto Christian, Aurino, Paola, Kosintsev, Pavel, Courtaud, Patrice, Ríos, Patricia, Mortensen, Peder, Lotz, Per, Persson, Per, Bangsgaard, Pernille, de Barros Damgaard, Peter, Vang Petersen, Peter, Martinez, Pilar Prieto, Włodarczak, Piotr, Smolyaninov, Roman V., Maring, Rikke, Menduiña, Roberto, Badalyan, Ruben, Iversen, Rune, Turin, Ruslan, Vasilyev, Sergey, Wåhlin, Sidsel, Borutskaya, Svetlana, Skochina, Svetlana, Sørensen, Søren Anker, Andersen, Søren H., Jørgensen, Thomas, Serikov, Yuri B., Molodin, Vyacheslav I., Smrcka, Vaclav, Merts, Victor, Appadurai, Vivek, Moiseyev, Vyacheslav, Magnusson, Yvonne, Kjær, Kurt H., Lynnerup, Niels, Lawson, Daniel J., Sudmant, Peter H., Rasmussen, Simon, Korneliussen, Thorfinn Sand, Durbin, Richard, Nielsen, Rasmus, Delaneau, Olivier, Werge, Thomas, Racimo, Fernando, Kristiansen, Kristian, and Willerslev, Eske

Published
2024
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11. Population genomics of the Viking world

Author

Margaryan, Ashot, Lawson, Daniel J, Sikora, Martin, Racimo, Fernando, Rasmussen, Simon, Moltke, Ida, Cassidy, Lara M, Jørsboe, Emil, Ingason, Andrés, Pedersen, Mikkel W, Korneliussen, Thorfinn, Wilhelmson, Helene, Buś, Magdalena M, de Barros Damgaard, Peter, Martiniano, Rui, Renaud, Gabriel, Bhérer, Claude, Moreno-Mayar, J Víctor, Fotakis, Anna K, Allen, Marie, Allmäe, Raili, Molak, Martyna, Cappellini, Enrico, Scorrano, Gabriele, McColl, Hugh, Buzhilova, Alexandra, Fox, Allison, Albrechtsen, Anders, Schütz, Berit, Skar, Birgitte, Arcini, Caroline, Falys, Ceri, Jonson, Charlotte Hedenstierna, Błaszczyk, Dariusz, Pezhemsky, Denis, Turner-Walker, Gordon, Gestsdóttir, Hildur, Lundstrøm, Inge, Gustin, Ingrid, Mainland, Ingrid, Potekhina, Inna, Muntoni, Italo M, Cheng, Jade, Stenderup, Jesper, Ma, Jilong, Gibson, Julie, Peets, Jüri, Gustafsson, Jörgen, Iversen, Katrine H, Simpson, Linzi, Strand, Lisa, Loe, Louise, Sikora, Maeve, Florek, Marek, Vretemark, Maria, Redknap, Mark, Bajka, Monika, Pushkina, Tamara, Søvsø, Morten, Grigoreva, Natalia, Christensen, Tom, Kastholm, Ole, Uldum, Otto, Favia, Pasquale, Holck, Per, Sten, Sabine, Arge, Símun V, Ellingvåg, Sturla, Moiseyev, Vayacheslav, Bogdanowicz, Wiesław, Magnusson, Yvonne, Orlando, Ludovic, Pentz, Peter, Jessen, Mads Dengsø, Pedersen, Anne, Collard, Mark, Bradley, Daniel G, Jørkov, Marie Louise, Arneborg, Jette, Lynnerup, Niels, Price, Neil, Gilbert, M Thomas P, Allentoft, Morten E, Bill, Jan, Sindbæk, Søren M, Hedeager, Lotte, Kristiansen, Kristian, Nielsen, Rasmus, Werge, Thomas, and Willerslev, Eske

Subjects
Biological Sciences, Genetics, History, Heritage and Archaeology, Archaeology, Historical Studies, Human Genome, Underpinning research, 1.1 Normal biological development and functioning, Alleles, Datasets as Topic, England, Evolution, Molecular, Gene Flow, Genetics, Population, Genome, Human, Genomics, Greenland, History, Medieval, Human Migration, Humans, Immunity, Ireland, Lactase, Male, Scandinavian and Nordic Countries, Selection, Genetic, Spatio-Temporal Analysis, Young Adult, General Science & Technology
Abstract

The maritime expansion of Scandinavian populations during the Viking Age (about AD 750-1050) was a far-flung transformation in world history1,2. Here we sequenced the genomes of 442 humans from archaeological sites across Europe and Greenland (to a median depth of about 1×) to understand the global influence of this expansion. We find the Viking period involved gene flow into Scandinavia from the south and east. We observe genetic structure within Scandinavia, with diversity hotspots in the south and restricted gene flow within Scandinavia. We find evidence for a major influx of Danish ancestry into England; a Swedish influx into the Baltic; and Norwegian influx into Ireland, Iceland and Greenland. Additionally, we see substantial ancestry from elsewhere in Europe entering Scandinavia during the Viking Age. Our ancient DNA analysis also revealed that a Viking expedition included close family members. By comparing with modern populations, we find that pigmentation-associated loci have undergone strong population differentiation during the past millennium, and trace positively selected loci-including the lactase-persistence allele of LCT and alleles of ANKA that are associated with the immune response-in detail. We conclude that the Viking diaspora was characterized by substantial transregional engagement: distinct populations influenced the genomic makeup of different regions of Europe, and Scandinavia experienced increased contact with the rest of the continent.

Published
2020

12. Disentangling Immediate Adaptive Introgression from Selection on Standing Introgressed Variation in Humans

Author

Jagoda, Evelyn, Lawson, Daniel J, Wall, Jeffrey D, Lambert, David, Muller, Craig, Westaway, Michael, Leavesley, Matthew, Capellini, Terence D, Mirazón Lahr, Marta, Gerbault, Pascale, Thomas, Mark G, Migliano, Andrea Bamberg, Willerslev, Eske, Metspalu, Mait, and Pagani, Luca

Subjects
Generic health relevance, adaptive introgression, Neanderthal, positive selection, archaic genomes, interferon, toll-like receptor, Biochemistry and Cell Biology, Evolutionary Biology, Genetics
Abstract

Recent studies have reported evidence suggesting that portions of contemporary human genomes introgressed from archaic hominin populations went to high frequencies due to positive selection. However, no study to date has specifically addressed the postintrogression population dynamics of these putative cases of adaptive introgression. Here, for the first time, we specifically define cases of immediate adaptive introgression (iAI) in which archaic haplotypes rose to high frequencies in humans as a result of a selective sweep that occurred shortly after the introgression event. We define these cases as distinct from instances of selection on standing introgressed variation (SI), in which an introgressed haplotype initially segregated neutrally and subsequently underwent positive selection. Using a geographically diverse data set, we report novel cases of selection on introgressed variation in living humans and shortlist among these cases those whose selective sweeps are more consistent with having been the product of iAI rather than SI. Many of these novel inferred iAI haplotypes have potential biological relevance, including three that contain immune-related genes in West Siberians, South Asians, and West Eurasians. Overall, our results suggest that iAI may not represent the full picture of positive selection on archaically introgressed haplotypes in humans and that more work needs to be done to analyze the role of SI in the archaic introgression landscape of living humans.

Published
2018

13. 100 ancient genomes show repeated population turnovers in Neolithic Denmark

Author

Allentoft, Morten E., Sikora, Martin, Fischer, Anders, Sjögren, Karl Göran, Ingason, Andrés, Macleod, Ruairidh, Rosengren, Anders, Schulz Paulsson, Bettina, Jørkov, Marie Louise Schjellerup, Novosolov, Maria, Stenderup, Jesper, Price, T. Douglas, Fischer Mortensen, Morten, Nielsen, Anne Birgitte, Ulfeldt Hede, Mikkel, Sørensen, Lasse, Nielsen, Poul Otto, Rasmussen, Peter, Jensen, Theis Zetner Trolle, Refoyo-Martínez, Alba, Irving-Pease, Evan K., Barrie, William, Pearson, Alice, Sousa da Mota, Bárbara, Demeter, Fabrice, Henriksen, Rasmus A., Vimala, Tharsika, McColl, Hugh, Vaughn, Andrew, Vinner, Lasse, Renaud, Gabriel, Stern, Aaron, Johannsen, Niels Nørkjær, Ramsøe, Abigail Daisy, Schork, Andrew Joseph, Ruter, Anthony, Gotfredsen, Anne Birgitte, Henning Nielsen, Bjarne, Brinch Petersen, Erik, Kannegaard, Esben, Hansen, Jesper, Buck Pedersen, Kristoffer, Pedersen, Lisbeth, Klassen, Lutz, Meldgaard, Morten, Johansen, Morten, Uldum, Otto Christian, Lotz, Per, Lysdahl, Per, Bangsgaard, Pernille, Petersen, Peter Vang, Maring, Rikke, Iversen, Rune, Wåhlin, Sidsel, Anker Sørensen, Søren, Andersen, Søren H., Jørgensen, Thomas, Lynnerup, Niels, Lawson, Daniel J., Rasmussen, Simon, Korneliussen, Thorfinn Sand, Kjær, Kurt H., Durbin, Richard, Nielsen, Rasmus, Delaneau, Olivier, Werge, Thomas, Kristiansen, Kristian, Willerslev, Eske, Allentoft, Morten E., Sikora, Martin, Fischer, Anders, Sjögren, Karl Göran, Ingason, Andrés, Macleod, Ruairidh, Rosengren, Anders, Schulz Paulsson, Bettina, Jørkov, Marie Louise Schjellerup, Novosolov, Maria, Stenderup, Jesper, Price, T. Douglas, Fischer Mortensen, Morten, Nielsen, Anne Birgitte, Ulfeldt Hede, Mikkel, Sørensen, Lasse, Nielsen, Poul Otto, Rasmussen, Peter, Jensen, Theis Zetner Trolle, Refoyo-Martínez, Alba, Irving-Pease, Evan K., Barrie, William, Pearson, Alice, Sousa da Mota, Bárbara, Demeter, Fabrice, Henriksen, Rasmus A., Vimala, Tharsika, McColl, Hugh, Vaughn, Andrew, Vinner, Lasse, Renaud, Gabriel, Stern, Aaron, Johannsen, Niels Nørkjær, Ramsøe, Abigail Daisy, Schork, Andrew Joseph, Ruter, Anthony, Gotfredsen, Anne Birgitte, Henning Nielsen, Bjarne, Brinch Petersen, Erik, Kannegaard, Esben, Hansen, Jesper, Buck Pedersen, Kristoffer, Pedersen, Lisbeth, Klassen, Lutz, Meldgaard, Morten, Johansen, Morten, Uldum, Otto Christian, Lotz, Per, Lysdahl, Per, Bangsgaard, Pernille, Petersen, Peter Vang, Maring, Rikke, Iversen, Rune, Wåhlin, Sidsel, Anker Sørensen, Søren, Andersen, Søren H., Jørgensen, Thomas, Lynnerup, Niels, Lawson, Daniel J., Rasmussen, Simon, Korneliussen, Thorfinn Sand, Kjær, Kurt H., Durbin, Richard, Nielsen, Rasmus, Delaneau, Olivier, Werge, Thomas, Kristiansen, Kristian, and Willerslev, Eske

Abstract

Major migration events in Holocene Eurasia have been characterized genetically at broad regional scales1–4. However, insights into the population dynamics in the contact zones are hampered by a lack of ancient genomic data sampled at high spatiotemporal resolution5–7. Here, to address this, we analysed shotgun-sequenced genomes from 100 skeletons spanning 7,300 years of the Mesolithic period, Neolithic period and Early Bronze Age in Denmark and integrated these with proxies for diet (13C and 15N content), mobility (87Sr/86Sr ratio) and vegetation cover (pollen). We observe that Danish Mesolithic individuals of the Maglemose, Kongemose and Ertebølle cultures form a distinct genetic cluster related to other Western European hunter-gatherers. Despite shifts in material culture they displayed genetic homogeneity from around 10,500 to 5,900 calibrated years before present, when Neolithic farmers with Anatolian-derived ancestry arrived. Although the Neolithic transition was delayed by more than a millennium relative to Central Europe, it was very abrupt and resulted in a population turnover with limited genetic contribution from local hunter-gatherers. The succeeding Neolithic population, associated with the Funnel Beaker culture, persisted for only about 1,000 years before immigrants with eastern Steppe-derived ancestry arrived. This second and equally rapid population replacement gave rise to the Single Grave culture with an ancestry profile more similar to present-day Danes. In our multiproxy dataset, these major demographic events are manifested as parallel shifts in genotype, phenotype, diet and land use.

Published
2024

14. Population genomics of post-glacial western Eurasia

Author

Lundbeck Foundation, Novo Nordisk Foundation, Wellcome Trust, Carlsberg Foundation, Danish National Research Foundation, University of Copenhagen, Ferring Pharmaceuticals, Swedish Foundation for Humanities and Social Sciences, Villum Fonden, Independent Research Fund Denmark, Hanne and Torkel Weis-Fogh Fund, Wellcome, Swiss National Science Foundation, European Research Council, Aarhus University Research Foundation, Ministry of Education and Science (Kazakhstan), Ministerio de Economía y Competitividad (España), Ministero dell'Istruzione, dell'Università e della Ricerca, Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), Generalitat Valenciana, Nomis Foundation, European Commission, Ministry of Science and Higher Education of the Russian Federation, Ministry of Education, Science, Culture and Sports of the Republic of Armenia, National Institute of General Medical Sciences (US), Sikora, Martin [0000-0003-2818-8319], Lalueza-Fox, Carles [0000-0002-1730-5914], Allentoft, Morten, Sikora, Martin, Refoyo-Martínez, Alba, Irving-Pease, Evan K., Fischer, Anders, Barrie, William, Ingason, Andrés, Stenderup, Jesper, Sjögren, Karl-Göran, Pearson, Alice, Mota, Bárbara Sousa da, Schulz Paulsson, Bettina, Halgren, Alma, Macleod, Ruairidh, Jørkov, Marie Louise S., Demeter, Fabrice, Sørensen, Lasse, Nielsen, Poul Otto, Henriksen, Rasmus A., Vimala, Tharsika, McColl, Hugh, Margaryan, Ashot, Ilardo, Melissa, Vaughn, Andrew, Fischer Mortensen, Morten, Nielsen, Anne Birgitte, Ulfeldt Hede, Mikkel, Johannsen, Niels Nørkjær, Rasmussen, Peter, Vinner, Lasse, Renaud, Gabriel, Stern, Aaron, Trolle Jensen, Theis Zetner, Scorrano, Gabriele, Schroeder, Hannes, Lysdahl, Per, Ramsøe, Abigail Daisy, Skorobogatov, Andrei, Schork, Andrew Joseph, Rosengren, Anders, Ruter, Anthony, Outram, Alan, Timoshenko, Aleksey A., Buzhilova, Alexandra, Coppa, Alfredo, Zubova, Alisa, Silva, Ana María, Hansen, Anders J., Gromov, Andrey, Logvin, Andrey, Gotfredsen, Anne Birgitte, Nielsen, Bjarne Henning, González-Rabanal, Borja, Lalueza-Fox, Carles, McKenzie, Catriona J., Gaunitz, Charleen, Blasco, Concepción, Liesau, Corina, Martínez-Labarga, Cristina, Pozdnyakov, Dmitri V., Cuenca-Solana, David, Lordkipanidze, David O., En’shin, Dmitri, Salazar García, Domingo Carlos, Price, T. Douglas, Borić, Dušan, Kostyleva, Elena, Veselovskaya, Elizaveta V., Usmanova, Emma R., Cappellini, Enrico, Petersen, Erik Brinch, Kannegaard, Esben, Radina, Francesca, Yediay, Fulya Eylem, Duday, Henri, Gutiérrez-Zugasti, Igor, Merts, Ilya, Potekhina, Inna, Shevnina, Irina, Altinkaya, Isin, Guilaine, Jean, Hansen, Jesper, Aura Tortosa, Joan Emili, Zilhão, João, Vega, Jorge, Pedersen, Kristoffer Buck, Tunia, Krzysztof, Zhao, Lei, Mylnikova, Liudmila N., Larsson, Lars, Metz, Laure, Yepiskoposyan, Levon, Pedersen, Lisbeth, Sarti, Lucia, Orlando, Ludovic, Slimak, Ludovic, Klassen, Lutz, Blank, Malou, González-Morales, Manuel, Silvestrini, Mara, Vretemark, Maria, Nesterova, Marina S., Rykun, Marina, Rolfo, Mario Federico, Szmyt, Marzena, Przybyła, Marcin, Calattini, Mauro, Sablin, Mikhail, Dobisíková, Miluše, Meldgaard, Morten, Johansen, Morten, Berezina, Natalia, Card, Nick, Saveliev, Nikolai A., Poshekhonova, Olga, Rickards, Olga, Lozovskaya, Olga V., Gábor, Olivér, Uldum, Otto Christian, Aurino, Paola, Kosintsev, Pavel, Courtaud, Patrice, Ríos, Patricia, Mortensen, Peder, Lotz, Per, Persson, Per, Bangsgaard, Pernille, Barros Damgaard, Peter de, Petersen, Peter Vang, Prieto Martínez, Pilar, Włodarczak, Piotr, Smolyaninov, Roman V., Maring, Rikke, Menduiña, Roberto, Badalyan, Ruben, Iversen, Rune, Turin, Ruslan, Vasilyev, Sergey, Wåhlin, Sidsel, Borutskaya, Svetlana, Skochina, Svetlana, Sørensen, Søren Anker, Andersen, Søren H., Jørgensen, Thomas, Serikov, Yuri B., Molodin, Vyacheslav I., Smrcka, Vaclav, Merts, Victor, Appadurai, Vivek, Moiseyev, Vyacheslav, Magnusson, Yvonne, Kjær, Kurt H., Lynnerup, Niels, Lawson, Daniel J., Sudmant, Peter H., Rasmussen, Simon, Korneliussen, Thorfinn Sand, Durbin, Richard, Nielsen, Rasmus, Delaneau, Olivier, Werge, Thomas, Racimo, Fernando, Kristiansen, Kristian, Willerslev, Eske, Lundbeck Foundation, Novo Nordisk Foundation, Wellcome Trust, Carlsberg Foundation, Danish National Research Foundation, University of Copenhagen, Ferring Pharmaceuticals, Swedish Foundation for Humanities and Social Sciences, Villum Fonden, Independent Research Fund Denmark, Hanne and Torkel Weis-Fogh Fund, Wellcome, Swiss National Science Foundation, European Research Council, Aarhus University Research Foundation, Ministry of Education and Science (Kazakhstan), Ministerio de Economía y Competitividad (España), Ministero dell'Istruzione, dell'Università e della Ricerca, Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), Generalitat Valenciana, Nomis Foundation, European Commission, Ministry of Science and Higher Education of the Russian Federation, Ministry of Education, Science, Culture and Sports of the Republic of Armenia, National Institute of General Medical Sciences (US), Sikora, Martin [0000-0003-2818-8319], Lalueza-Fox, Carles [0000-0002-1730-5914], Allentoft, Morten, Sikora, Martin, Refoyo-Martínez, Alba, Irving-Pease, Evan K., Fischer, Anders, Barrie, William, Ingason, Andrés, Stenderup, Jesper, Sjögren, Karl-Göran, Pearson, Alice, Mota, Bárbara Sousa da, Schulz Paulsson, Bettina, Halgren, Alma, Macleod, Ruairidh, Jørkov, Marie Louise S., Demeter, Fabrice, Sørensen, Lasse, Nielsen, Poul Otto, Henriksen, Rasmus A., Vimala, Tharsika, McColl, Hugh, Margaryan, Ashot, Ilardo, Melissa, Vaughn, Andrew, Fischer Mortensen, Morten, Nielsen, Anne Birgitte, Ulfeldt Hede, Mikkel, Johannsen, Niels Nørkjær, Rasmussen, Peter, Vinner, Lasse, Renaud, Gabriel, Stern, Aaron, Trolle Jensen, Theis Zetner, Scorrano, Gabriele, Schroeder, Hannes, Lysdahl, Per, Ramsøe, Abigail Daisy, Skorobogatov, Andrei, Schork, Andrew Joseph, Rosengren, Anders, Ruter, Anthony, Outram, Alan, Timoshenko, Aleksey A., Buzhilova, Alexandra, Coppa, Alfredo, Zubova, Alisa, Silva, Ana María, Hansen, Anders J., Gromov, Andrey, Logvin, Andrey, Gotfredsen, Anne Birgitte, Nielsen, Bjarne Henning, González-Rabanal, Borja, Lalueza-Fox, Carles, McKenzie, Catriona J., Gaunitz, Charleen, Blasco, Concepción, Liesau, Corina, Martínez-Labarga, Cristina, Pozdnyakov, Dmitri V., Cuenca-Solana, David, Lordkipanidze, David O., En’shin, Dmitri, Salazar García, Domingo Carlos, Price, T. Douglas, Borić, Dušan, Kostyleva, Elena, Veselovskaya, Elizaveta V., Usmanova, Emma R., Cappellini, Enrico, Petersen, Erik Brinch, Kannegaard, Esben, Radina, Francesca, Yediay, Fulya Eylem, Duday, Henri, Gutiérrez-Zugasti, Igor, Merts, Ilya, Potekhina, Inna, Shevnina, Irina, Altinkaya, Isin, Guilaine, Jean, Hansen, Jesper, Aura Tortosa, Joan Emili, Zilhão, João, Vega, Jorge, Pedersen, Kristoffer Buck, Tunia, Krzysztof, Zhao, Lei, Mylnikova, Liudmila N., Larsson, Lars, Metz, Laure, Yepiskoposyan, Levon, Pedersen, Lisbeth, Sarti, Lucia, Orlando, Ludovic, Slimak, Ludovic, Klassen, Lutz, Blank, Malou, González-Morales, Manuel, Silvestrini, Mara, Vretemark, Maria, Nesterova, Marina S., Rykun, Marina, Rolfo, Mario Federico, Szmyt, Marzena, Przybyła, Marcin, Calattini, Mauro, Sablin, Mikhail, Dobisíková, Miluše, Meldgaard, Morten, Johansen, Morten, Berezina, Natalia, Card, Nick, Saveliev, Nikolai A., Poshekhonova, Olga, Rickards, Olga, Lozovskaya, Olga V., Gábor, Olivér, Uldum, Otto Christian, Aurino, Paola, Kosintsev, Pavel, Courtaud, Patrice, Ríos, Patricia, Mortensen, Peder, Lotz, Per, Persson, Per, Bangsgaard, Pernille, Barros Damgaard, Peter de, Petersen, Peter Vang, Prieto Martínez, Pilar, Włodarczak, Piotr, Smolyaninov, Roman V., Maring, Rikke, Menduiña, Roberto, Badalyan, Ruben, Iversen, Rune, Turin, Ruslan, Vasilyev, Sergey, Wåhlin, Sidsel, Borutskaya, Svetlana, Skochina, Svetlana, Sørensen, Søren Anker, Andersen, Søren H., Jørgensen, Thomas, Serikov, Yuri B., Molodin, Vyacheslav I., Smrcka, Vaclav, Merts, Victor, Appadurai, Vivek, Moiseyev, Vyacheslav, Magnusson, Yvonne, Kjær, Kurt H., Lynnerup, Niels, Lawson, Daniel J., Sudmant, Peter H., Rasmussen, Simon, Korneliussen, Thorfinn Sand, Durbin, Richard, Nielsen, Rasmus, Delaneau, Olivier, Werge, Thomas, Racimo, Fernando, Kristiansen, Kristian, and Willerslev, Eske

Abstract

Western Eurasia witnessed several large-scale human migrations during the Holocene1,2,3,4,5. Here, to investigate the cross-continental effects of these migrations, we shotgun-sequenced 317 genomes—mainly from the Mesolithic and Neolithic periods—from across northern and western Eurasia. These were imputed alongside published data to obtain diploid genotypes from more than 1,600 ancient humans. Our analyses revealed a ‘great divide’ genomic boundary extending from the Black Sea to the Baltic. Mesolithic hunter-gatherers were highly genetically differentiated east and west of this zone, and the effect of the neolithization was equally disparate. Large-scale ancestry shifts occurred in the west as farming was introduced, including near-total replacement of hunter-gatherers in many areas, whereas no substantial ancestry shifts happened east of the zone during the same period. Similarly, relatedness decreased in the west from the Neolithic transition onwards, whereas, east of the Urals, relatedness remained high until around 4,000 BP, consistent with the persistence of localized groups of hunter-gatherers. The boundary dissolved when Yamnaya-related ancestry spread across western Eurasia around 5,000 BP, resulting in a second major turnover that reached most parts of Europe within a 1,000-year span. The genetic origin and fate of the Yamnaya have remained elusive, but we show that hunter-gatherers from the Middle Don region contributed ancestry to them. Yamnaya groups later admixed with individuals associated with the Globular Amphora culture before expanding into Europe. Similar turnovers occurred in western Siberia, where we report new genomic data from a ‘Neolithic steppe’ cline spanning the Siberian forest steppe to Lake Baikal. These prehistoric migrations had profound and lasting effects on the genetic diversity of Eurasian populations.

Published
2024

16. A Selective Sweep on a Deleterious Mutation in CPT1A in Arctic Populations

Author

Clemente, Florian J, Cardona, Alexia, Inchley, Charlotte E, Peter, Benjamin M, Jacobs, Guy, Pagani, Luca, Lawson, Daniel J, Antão, Tiago, Vicente, Mário, Mitt, Mario, DeGiorgio, Michael, Faltyskova, Zuzana, Xue, Yali, Ayub, Qasim, Szpak, Michal, Mägi, Reedik, Eriksson, Anders, Manica, Andrea, Raghavan, Maanasa, Rasmussen, Morten, Rasmussen, Simon, Willerslev, Eske, Vidal-Puig, Antonio, Tyler-Smith, Chris, Villems, Richard, Nielsen, Rasmus, Metspalu, Mait, Malyarchuk, Boris, Derenko, Miroslava, and Kivisild, Toomas

Subjects
Biological Sciences, Genetics, Human Genome, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Arctic populations live in an environment characterized by extreme cold and the absence of plant foods for much of the year and are likely to have undergone genetic adaptations to these environmental conditions in the time they have been living there. Genome-wide selection scans based on genotype data from native Siberians have previously highlighted a 3 Mb chromosome 11 region containing 79 protein-coding genes as the strongest candidates for positive selection in Northeast Siberians. However, it was not possible to determine which of the genes might be driving the selection signal. Here, using whole-genome high-coverage sequence data, we identified the most likely causative variant as a nonsynonymous G>A transition (rs80356779; c.1436C>T [p.Pro479Leu] on the reverse strand) in CPT1A, a key regulator of mitochondrial long-chain fatty-acid oxidation. Remarkably, the derived allele is associated with hypoketotic hypoglycemia and high infant mortality yet occurs at high frequency in Canadian and Greenland Inuits and was also found at 68% frequency in our Northeast Siberian sample. We provide evidence of one of the strongest selective sweeps reported in humans; this sweep has driven this variant to high frequency in circum-Arctic populations within the last 6-23 ka despite associated deleterious consequences, possibly as a result of the selective advantage it originally provided to either a high-fat diet or a cold environment.

Published
2014

17. How admixed captive breeding populations could be rescued using local ancestry information.

Author

Lawson, Daniel J., Howard‐McCombe, Jo, Beaumont, Mark, and Senn, Helen

Abstract

This paper asks the question: can genomic information be used to recover a species that is already on the pathway to extinction due to genetic swamping from a related and more numerous population? We show that a breeding strategy in a captive breeding program can use whole genome sequencing to identify and remove segments of DNA introgressed through hybridisation. The proposed policy uses a generalized measure of kinship or heterozygosity accounting for local ancestry, that is, whether a specific genetic location was inherited from the target of conservation. We then show that optimizing these measures would minimize undesired ancestry while also controlling kinship and/or heterozygosity, in a simulated breeding population. The process is applied to real data representing the hybridized Scottish wildcat breeding population, with the result that it should be possible to breed out domestic cat ancestry. The ability to reverse introgression is a powerful tool brought about through the combination of sequencing with computational advances in ancestry estimation. Since it works best when applied early in the process, important decisions need to be made about which genetically distinct populations should benefit from it and which should be left to reform into a single population. [ABSTRACT FROM AUTHOR]

Published
2024
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18. Relationships Between Anthropometric Measures and Body Composition With Individual ACFT Event Performance Among Army Reserve Officers' Training Corps Cadets.

Author

Thompson, Megan B., Lawson, Daniel J., Orr, Robin M., Lockie, Robert G., and Dawes, J. Jay

Subjects
*PEARSON correlation (Statistics), *BODY mass index, *T-test (Statistics), *BODY composition, *RETROSPECTIVE studies, *BIOELECTRIC impedance, *DESCRIPTIVE statistics, *PHYSICAL fitness, *ANTHROPOMETRY, *BODY movement, *DATA analysis software, *MILITARY personnel, *MILITARY education
Abstract

The U.S. military commonly uses body composition as an indicator of a soldier's potential to meet the physical demands required of their occupation. The purpose of this study was to determine whether significant relationships existed between select body composition variables and Army Combat Fitness Test (ACFT) performance among a cohort of university Army Reserve Officers' Training Corps (ROTC) cadets. Twenty-six male (20.4 ± 1.6 years, 81.8 ± 8.5 kg, 178.3 ± 7.8 cm) and 12 female (19.9 ± 1.4 years, 64.2 ± 6.7 kg, 161.9 ± 4.9 cm) cadets voluntarily participated in this study. Body composition was measured using bioelectrical impedance analysis, and ACFT event scores were recorded by the cadre using the U.S. Army standard protocol and provided to the investigators. Pearson's correlations were used to identify relationships between body composition variables and ACFT event performance with an alpha level of p ≤ 0.05. Moderate to strong relationships were observed between total body water, dry lean mass, lean body mass, skeletal muscle mass, body fat mass (FM), and body fat percentage and all event scores for the sample as a whole. Body mass index showed weak to moderate significant positive relationships with hand-release push-up and maximum hexagonal bar deadlift in the sample as a whole. No relationships were observed in the men of this sample. All body composition variables showed moderate, nonsignificant relationships with at least 1 ACFT event within the women of this sample. Considering the findings of this study, a multitude of variables could be useful to assess ROTC cadets as predictors for ACFT performance. Reserve Officers' Training Corps programs should emphasize attaining and maintaining functional lean mass, whereas reducing nonfunctional body mass (i.e., excess FM) among cadets to enhance health and performance across the occupational life span. [ABSTRACT FROM AUTHOR]

Published
2024
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21. Genetic swamping of the critically endangered Scottish wildcat was recent and accelerated by disease

Author

Howard-McCombe, Jo, Jamieson, Alexandra, Carmagnini, Alberto, Russo, Isa-Rita M., Ghazali, Muhammad, Campbell, Ruairidh, Driscoll, Carlos, Murphy, William J., Nowak, Carsten, O’Connor, Terry, Tomsett, Louise, Lyons, Leslie A., Muñoz-Fuentes, Violeta, Bruford, Michael W., Kitchener, Andrew C., Larson, Greger, Frantz, Laurent, Senn, Helen, Lawson, Daniel J., and Beaumont, Mark A.

Published
2023
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22. Author Correction: Population genomics of the Viking world

Author

Margaryan, Ashot, Lawson, Daniel J., Sikora, Martin, Racimo, Fernando, Rasmussen, Simon, Moltke, Ida, Cassidy, Lara M., Jørsboe, Emil, Ingason, Andrés, Pedersen, Mikkel W., Korneliussen, Thorfinn, Wilhelmson, Helene, Buś, Magdalena M., de Barros Damgaard, Peter, Martiniano, Rui, Renaud, Gabriel, Bhérer, Claude, Moreno-Mayar, J. Víctor, Fotakis, Anna K., Allen, Marie, Allmäe, Raili, Molak, Martyna, Cappellini, Enrico, Scorrano, Gabriele, McColl, Hugh, Buzhilova, Alexandra, Fox, Allison, Albrechtsen, Anders, Schütz, Berit, Skar, Birgitte, Arcini, Caroline, Falys, Ceri, Jonson, Charlotte Hedenstierna, Błaszczyk, Dariusz, Pezhemsky, Denis, Turner-Walker, Gordon, Gestsdóttir, Hildur, Lundstrøm, Inge, Gustin, Ingrid, Mainland, Ingrid, Potekhina, Inna, Muntoni, Italo M., Cheng, Jade, Stenderup, Jesper, Ma, Jilong, Gibson, Julie, Peets, Jüri, Gustafsson, Jörgen, Iversen, Katrine H., Simpson, Linzi, Strand, Lisa, Loe, Louise, Sikora, Maeve, Florek, Marek, Vretemark, Maria, Redknap, Mark, Bajka, Monika, Pushkina, Tamara, Søvsø, Morten, Grigoreva, Natalia, Christensen, Tom, Kastholm, Ole, Uldum, Otto, Favia, Pasquale, Holck, Per, Sten, Sabine, Arge, Símun V., Ellingvåg, Sturla, Moiseyev, Vayacheslav, Bogdanowicz, Wiesław, Magnusson, Yvonne, Orlando, Ludovic, Pentz, Peter, Jessen, Mads Dengsø, Pedersen, Anne, Collard, Mark, Bradley, Daniel G., Jørkov, Marie Louise, Arneborg, Jette, Lynnerup, Niels, Price, Neil, Gilbert, M. Thomas P., Allentoft, Morten E., Bill, Jan, Sindbæk, Søren M., Hedeager, Lotte, Kristiansen, Kristian, Nielsen, Rasmus, Werge, Thomas, and Willerslev, Eske

Published
2021
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24. Genetic risk for Multiple Sclerosis originated in Pastoralist Steppe populations

Author

Barrie, William, primary, Yang, Yaoling, additional, Attfield, Kathrine E., additional, Irving-Pease, Evan, additional, Scorrano, Gabriele, additional, Jensen, Lise Torp, additional, Armen, Angelos P., additional, Dimopoulos, Evangelos Antonios, additional, Stern, Aaron, additional, Refoyo-Martinez, Alba, additional, Ramsøe, Abigail, additional, Gaunitz, Charleen, additional, Demeter, Fabrice, additional, Jørkov, Marie Louise S., additional, Møller, Stig Bermann, additional, Springborg, Bente, additional, Klassen, Lutz, additional, Hyldgård, Inger Marie, additional, Wickmann, Niels, additional, Vinner, Lasse, additional, Korneliussen, Thorfinn Sand, additional, Sikora, Martin, additional, Kristiansen, Kristian, additional, Rodriguez, Santiago, additional, Nielsen, Rasmus, additional, Iversen, Astrid K. N., additional, Lawson, Daniel J., additional, Fugger, Lars, additional, and Willerslev, Eske, additional

Published
2022
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25. The Selection Landscape and Genetic Legacy of Ancient Eurasians

Author

Irving-Pease, Evan K., primary, Refoyo-Martínez, Alba, additional, Ingason, Andrés, additional, Pearson, Alice, additional, Fischer, Anders, additional, Barrie, William, additional, Sjögren, Karl-Göran, additional, Halgren, Alma S., additional, Macleod, Ruairidh, additional, Demeter, Fabrice, additional, Henriksen, Rasmus A., additional, Vimala, Tharsika, additional, McColl, Hugh, additional, Vaughn, Andrew, additional, Stern, Aaron J., additional, Speidel, Leo, additional, Scorrano, Gabriele, additional, Ramsøe, Abigail, additional, Schork, Andrew J., additional, Rosengren, Anders, additional, Zhao, Lei, additional, Kristiansen, Kristian, additional, Sudmant, Peter H., additional, Lawson, Daniel J., additional, Durbin, Richard, additional, Korneliussen, Thorfinn, additional, Werge, Thomas, additional, Allentoft, Morten E., additional, Sikora, Martin, additional, Nielsen, Rasmus, additional, Racimo, Fernando, additional, and Willerslev, Eske, additional

Published
2022
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26. Relationships between Lower-body Power, Sprint and Change of Direction Speed among Collegiate Basketball Players by Sex

Author

ZARAGOZA, JAVIER A., JOHNSON, QUINCY R., LAWSON, DANIEL J., ALFARO, ELIZABETH L., DAWES, J. JAY, and SMITH, DOUG B.

Subjects
Original Research
Abstract

The purpose of this study was to determine if significant relationships exist between absolute and relative lower-body power and selected measures of speed among male and female collegiate basketball players. Archived performance testing data from 29 (male = 14; female = 15) NCAA division II collegiate basketball players were used for this analysis. These measures included lane agility, 10-yard sprint, and shuttle run time (sec). A Pearson’s correlation coefficient was used to determine if significant relationships existed between measures of lower-body power and linear sprint time, change of direction speed (CODS), and shuttle performance. Statistical significance was set a priori at p ≤ 0.05. A significant large correlation was found between absolute power and lane agility (r = 0.54, p = 0.05) among male players. No significant correlations were found between absolute or relative power for 10-yard sprint times, lane agility, or shuttle run performance (p > 0.05). Females showed no significant correlations between relative power and lane agility (r = −0.25, p = 0.37) or 10-yard sprint (r = −0.47, p = 0.08), but did show a significant large correlation (r = −0.64, p = 0.01) between relative power and shuttle run performance. Generating high amounts of relative power is vital in intermittent team sports such as basketball. In particular, this study provided evidence that relative power in female collegiate basketball players is significantly related to shuttle run ability.

Published
2022

27. The Selection Landscape and Genetic Legacy of Ancient Eurasians

Author

Irving-Pease, Evan, Refoyo Martínez, Alba, Ingason, Andrés, Pearson, Alice, Fischer, Anders, Barrie, William, Sjögren, Karl-Göran, Halgren, Alma S., Macleod, Ruairidh, Demeter, Fabrice, Henriksen, Rasmus Henrik Amund, Vimala, Tharsika, McColl, Hugh, Vaughn, Andrew, Stern, Aaron J., Speidel, Leo, Scorrano, Gabriele, Ramsøe, Abigail, Schork, Andrew J., Rosengren, Anders, Zhao, Lei, Kristiansen, Kristian, Sudmant, Peter H., Lawson, Daniel J., Durbin, Richard, Korneliussen, Thorfinn, Werge, Thomas, Allentoft, Morten E., Sikora, Martin, Nielsen, Rasmus, Racimo, Fernando, Willerslev, Eske, Irving-Pease, Evan, Refoyo Martínez, Alba, Ingason, Andrés, Pearson, Alice, Fischer, Anders, Barrie, William, Sjögren, Karl-Göran, Halgren, Alma S., Macleod, Ruairidh, Demeter, Fabrice, Henriksen, Rasmus Henrik Amund, Vimala, Tharsika, McColl, Hugh, Vaughn, Andrew, Stern, Aaron J., Speidel, Leo, Scorrano, Gabriele, Ramsøe, Abigail, Schork, Andrew J., Rosengren, Anders, Zhao, Lei, Kristiansen, Kristian, Sudmant, Peter H., Lawson, Daniel J., Durbin, Richard, Korneliussen, Thorfinn, Werge, Thomas, Allentoft, Morten E., Sikora, Martin, Nielsen, Rasmus, Racimo, Fernando, and Willerslev, Eske

Abstract

The Eurasian Holocene (beginning c. 12 thousand years ago) encompassed some of the most significant changes in human evolution, with far-reaching consequences for the dietary, physical and mental health of present-day populations. Using an imputed dataset of >1600 complete ancient genome sequences, and new computational methods for locating selection in time and space, we reconstructed the selection landscape of the transition from hunting and gathering, to farming and pastoralism across West Eurasia. We identify major selection signals related to metabolism, possibly associated with the dietary shift occurring in this period. We show that the selection on loci such as the FADS cluster, associated with fatty acid metabolism, and the lactase persistence locus, began earlier than previously thought. A substantial amount of selection is also found in the HLA region and other loci associated with immunity, possibly due to the increased exposure to pathogens during the Neolithic, which may explain the current high prevalence of auto-immune disease, such as psoriasis, due to genetic trade-offs. By using ancient populations to infer local ancestry tracks in hundreds of thousands of samples from the UK Biobank, we find strong genetic differentiation among ancient Europeans in loci associated with anthropometric traits and susceptibility to several diseases that contribute to present-day disease burden. These were previously thought to be caused by local selection, but in fact can be attributed to differential genetic contributions from various source populations that are ancestral to present-day Europeans. Thus, alleles associated with increased height seem to have increased in frequency following the Yamnaya migration into northwestern Europe around 5,000 years ago. Alleles associated with increased risk of some mood-related phenotypes are overrepresented in the farmer ancestry component entering Europe from Anatolia around 11,000 years ago, while western hunter-gathere

Published
2022

28. Genetic risk for Multiple Sclerosis originated in Pastoralist Steppe populations

Author

Barrie, William, Yang, Yaoling, Attfield, Kathrine E., Irving-Pease, Evan, Scorrano, Gabriele, Jensen, Lise Torp, Armen, Angelos P., Dimopoulos, Evangelos Antonios, Stern, Aaron, Refoyo-Martínez, Alba, Ramsøe, Abigail, Gaunitz, Charleen, Demeter, Fabrice, Jørkov, Marie Louise S., Møller, Stig Bermann, Springborg, Bente, Klassen, Lutz, Hyldgård, Inger Marie, Wickmann, Niels, Vinner, Lasse, Korneliussen, Thorfinn Sand, Sikora, Martin, Kristiansen, Kristian, Rodriguez, Santiago, Nielsen, Rasmus, Iversen, Astrid K. N., Lawson, Daniel J., Fugger, Lars, Willerslev, Eske, Barrie, William, Yang, Yaoling, Attfield, Kathrine E., Irving-Pease, Evan, Scorrano, Gabriele, Jensen, Lise Torp, Armen, Angelos P., Dimopoulos, Evangelos Antonios, Stern, Aaron, Refoyo-Martínez, Alba, Ramsøe, Abigail, Gaunitz, Charleen, Demeter, Fabrice, Jørkov, Marie Louise S., Møller, Stig Bermann, Springborg, Bente, Klassen, Lutz, Hyldgård, Inger Marie, Wickmann, Niels, Vinner, Lasse, Korneliussen, Thorfinn Sand, Sikora, Martin, Kristiansen, Kristian, Rodriguez, Santiago, Nielsen, Rasmus, Iversen, Astrid K. N., Lawson, Daniel J., Fugger, Lars, and Willerslev, Eske

Abstract

Multiple sclerosis (MS) is a modern neuro-inflammatory and -degenerative disease, which is most prevalent in Northern Europe. Whilst it is known that inherited risk to MS is located within or within close proximity to immune genes it is unknown when, where and how this genetic risk originated. By using the largest ancient genome dataset from the Stone Age, along with new Medieval and post-Medieval genomes, we show that many of the genetic risk variants for MS rose to higher frequency among pastoralists located on the Pontic Steppe, and were brought into Europe by the Yamnaya-related migration approximately 5,000 years ago. We further show that these MS-associated immunogenetic variants underwent positive selection both within the Steppe population, and later in Europe, likely driven by pathogenic challenges coinciding with dietary and lifestyle environmental changes. This study highlights the critical importance of this period as a determinant of modern immune responses and its subsequent impact on the risk of developing MS in a changing environment.

Published
2022

29. Population Genomics of Stone Age Eurasia

Author

Allentoft, Morten E., Sikora, Martin, Refoyo-Martínez, Alba, Irving-Pease, Evan K., Fischer, Anders, Barrie, William, Ingason, Andrés, Stenderup, Jesper, Sjögren, Karl-Göran, Pearson, Alice, Mota, Barbara, Paulsson, Bettina Schulz, Halgren, Alma, Macleod, Ruairidh, Schjellerup Jørkov, Marie Louise, Demeter, Fabrice, Novosolov, Maria, Sørensen, Lasse, Nielsen, Poul-Otto, Henriksen, Rasmus H. A., Vimala, Tharsika, McColl, Hugh, Margaryan, Ashot, Ilardo, Melissa, Vaughn, Andrew, Mortensen, Morten Fischer, Nielsen, Anne Birgitte, Hede, Mikkel Ulfeldt, Rasmussen, Peter, Vinner, Lasse, Renaud, Gabriel, Stern, Aaron, Trolle Jensen, Theis Zetner, Johannsen, Niels Nørkjær, Scorrano, Gabriele, Schroeder, Hannes, Lysdahl, Per, Ramsøe, Abigail Daisy, Skorobogatov, Andrei, Schork, Andrew Joseph, Rosengren, Anders, Ruter, Anthony, Outram, Alan, Timoshenko, Aleksey A., Buzhilova, Alexandra, Coppa, Alfredo, Zubova, Alisa, Silva, Ana Maria, Hansen, Anders J., Gromov, Andrey, Logvin, Andrey, Gotfredsen, Anne Birgitte, Nielsen, Bjarne Henning, González-Rabanal, Borja, Lalueza-Fox, Carles, McKenzie, Catriona J., Gaunitz, Charleen, Blasco, Concepción, Liesau, Corina, Martinez-Labarga, Cristina, Pozdnyakov, Dmitri V., Cuenca-Solana, David, Lordkipanidze, David O., En’shin, Dmitri, Salazar-García, Domingo C, Price, T. Douglas, Borić, Dušan, Kostyleva, Elena, Veselovskaya, Elizaveta V., Usmanova, Emma R., Cappellini, Enrico, Petersen, Erik Brinch, Kannegaard, Esben, Radina, Francesca, Yediay, Fulya Eylem, Duday, Henri, Gutiérrez-Zugasti, Igor, Potekhina, Inna, Shevnina, Irina, Altinkaya, Isin, Guilaine, Jean, Hansen, Jesper, Tortosa, Joan Emili Aura, Zilhão, João, Vega, Jorge, Pedersen, Kristoffer Buck, Tunia, Krzysztof, Zhao, Lei, Mylnikova, Liudmila N., Larsson, Lars, Metz, Laure, Yeppiskoposyan, Levon, Pedersen, Lisbeth, Sarti, Lucia, Orlando, Ludovic, Slimak, Ludovic, Klassen, Lutz, Blank, Malou, González-Morales, Manuel, Silvestrini, Mara, Vretemark, Maria, Nesterova, Marina S., Rykun, Marina, Rolfo, Mario Federico, Szmyt, Marzena, Przybyła, Marcin, Calattini, Mauro, Sablin, Mikhail, Dobisíková, Miluše, Meldgaard, Morten, Johansen, Morten, Berezina, Natalia, Card, Nick, Saveliev, Nikolai A., Poshekhonova, Olga, Rickards, Olga, Lozovskaya, Olga V., Uldum, Otto Christian, Aurino, Paola, Kosintsev, Pavel, Courtaud, Patrice, Ríos, Patricia, Mortensen, Peder, Lotz, Per, Persson, Per Åke, Bangsgaard, Pernille, Damgaard, Peter de Barros, Petersen, Peter Vang, Martinez, Pilar Prieto, Włodarczak, Piotr, Smolyaninov, Roman V., Maring, Rikke, Menduiña, Roberto, Badalyan, Ruben, Iversen, Rune, Turin, Ruslan, Vasilyiev, Sergey, Wåhlin, Sidsel, Borutskaya, Svetlana, Skochina, Svetlana, Sørensen, Søren Anker, Andersen, Søren H., Jørgensen, Thomas, Serikov, Yuri B., Molodin, Vyacheslav I., Smrcka, Vaclav, Merz, Victor, Appadurai, Vivek, Moiseyev, Vyacheslav, Magnusson, Yvonne, Kjær, Kurt H., Lynnerup, Niels, Lawson, Daniel J., Sudmant, Peter H., Rasmussen, Simon, Korneliussen, Thorfinn, Durbin, Richard, Nielsen, Rasmus, Delaneau, Olivier, Werge, Thomas, Racimo, Fernando, Kristiansen, Kristian, Willerslev, Eske, Allentoft, Morten E., Sikora, Martin, Refoyo-Martínez, Alba, Irving-Pease, Evan K., Fischer, Anders, Barrie, William, Ingason, Andrés, Stenderup, Jesper, Sjögren, Karl-Göran, Pearson, Alice, Mota, Barbara, Paulsson, Bettina Schulz, Halgren, Alma, Macleod, Ruairidh, Schjellerup Jørkov, Marie Louise, Demeter, Fabrice, Novosolov, Maria, Sørensen, Lasse, Nielsen, Poul-Otto, Henriksen, Rasmus H. A., Vimala, Tharsika, McColl, Hugh, Margaryan, Ashot, Ilardo, Melissa, Vaughn, Andrew, Mortensen, Morten Fischer, Nielsen, Anne Birgitte, Hede, Mikkel Ulfeldt, Rasmussen, Peter, Vinner, Lasse, Renaud, Gabriel, Stern, Aaron, Trolle Jensen, Theis Zetner, Johannsen, Niels Nørkjær, Scorrano, Gabriele, Schroeder, Hannes, Lysdahl, Per, Ramsøe, Abigail Daisy, Skorobogatov, Andrei, Schork, Andrew Joseph, Rosengren, Anders, Ruter, Anthony, Outram, Alan, Timoshenko, Aleksey A., Buzhilova, Alexandra, Coppa, Alfredo, Zubova, Alisa, Silva, Ana Maria, Hansen, Anders J., Gromov, Andrey, Logvin, Andrey, Gotfredsen, Anne Birgitte, Nielsen, Bjarne Henning, González-Rabanal, Borja, Lalueza-Fox, Carles, McKenzie, Catriona J., Gaunitz, Charleen, Blasco, Concepción, Liesau, Corina, Martinez-Labarga, Cristina, Pozdnyakov, Dmitri V., Cuenca-Solana, David, Lordkipanidze, David O., En’shin, Dmitri, Salazar-García, Domingo C, Price, T. Douglas, Borić, Dušan, Kostyleva, Elena, Veselovskaya, Elizaveta V., Usmanova, Emma R., Cappellini, Enrico, Petersen, Erik Brinch, Kannegaard, Esben, Radina, Francesca, Yediay, Fulya Eylem, Duday, Henri, Gutiérrez-Zugasti, Igor, Potekhina, Inna, Shevnina, Irina, Altinkaya, Isin, Guilaine, Jean, Hansen, Jesper, Tortosa, Joan Emili Aura, Zilhão, João, Vega, Jorge, Pedersen, Kristoffer Buck, Tunia, Krzysztof, Zhao, Lei, Mylnikova, Liudmila N., Larsson, Lars, Metz, Laure, Yeppiskoposyan, Levon, Pedersen, Lisbeth, Sarti, Lucia, Orlando, Ludovic, Slimak, Ludovic, Klassen, Lutz, Blank, Malou, González-Morales, Manuel, Silvestrini, Mara, Vretemark, Maria, Nesterova, Marina S., Rykun, Marina, Rolfo, Mario Federico, Szmyt, Marzena, Przybyła, Marcin, Calattini, Mauro, Sablin, Mikhail, Dobisíková, Miluše, Meldgaard, Morten, Johansen, Morten, Berezina, Natalia, Card, Nick, Saveliev, Nikolai A., Poshekhonova, Olga, Rickards, Olga, Lozovskaya, Olga V., Uldum, Otto Christian, Aurino, Paola, Kosintsev, Pavel, Courtaud, Patrice, Ríos, Patricia, Mortensen, Peder, Lotz, Per, Persson, Per Åke, Bangsgaard, Pernille, Damgaard, Peter de Barros, Petersen, Peter Vang, Martinez, Pilar Prieto, Włodarczak, Piotr, Smolyaninov, Roman V., Maring, Rikke, Menduiña, Roberto, Badalyan, Ruben, Iversen, Rune, Turin, Ruslan, Vasilyiev, Sergey, Wåhlin, Sidsel, Borutskaya, Svetlana, Skochina, Svetlana, Sørensen, Søren Anker, Andersen, Søren H., Jørgensen, Thomas, Serikov, Yuri B., Molodin, Vyacheslav I., Smrcka, Vaclav, Merz, Victor, Appadurai, Vivek, Moiseyev, Vyacheslav, Magnusson, Yvonne, Kjær, Kurt H., Lynnerup, Niels, Lawson, Daniel J., Sudmant, Peter H., Rasmussen, Simon, Korneliussen, Thorfinn, Durbin, Richard, Nielsen, Rasmus, Delaneau, Olivier, Werge, Thomas, Racimo, Fernando, Kristiansen, Kristian, and Willerslev, Eske

Abstract

The transitions from foraging to farming and later to pastoralism in Stone Age Eurasia (c. 11-3 thousand years before present, BP) represent some of the most dramatic lifestyle changes in human evolution. We sequenced 317 genomes of primarily Mesolithic and Neolithic individuals from across Eurasia combined with radiocarbon dates, stable isotope data, and pollen records. Genome imputation and co-analysis with previously published shotgun sequencing data resulted in >1600 complete ancient genome sequences offering fine-grained resolution into the Stone Age populations. We observe that: 1) Hunter-gatherer groups were more genetically diverse than previously known, and deeply divergent between western and eastern Eurasia. 2) We identify hitherto genetically undescribed hunter-gatherers from the Middle Don region that contributed ancestry to the later Yamnaya steppe pastoralists; 3) The genetic impact of the Neolithic transition was highly distinct, east and west of a boundary zone extending from the Black Sea to the Baltic. Large-scale shifts in genetic ancestry occurred to the west of this “Great Divide”, including an almost complete replacement of hunter-gatherers in Denmark, while no substantial ancestry shifts took place during the same period to the east. This difference is also reflected in genetic relatedness within the populations, decreasing substantially in the west but not in the east where it remained high until c. 4,000 BP; 4) The second major genetic transformation around 5,000 BP happened at a much faster pace with Steppe-related ancestry reaching most parts of Europe within 1,000-years. Local Neolithic farmers admixed with incoming pastoralists in eastern, western, and southern Europe whereas Scandinavia experienced another near-complete population replacement. Similar dramatic turnover-patterns are evident in western Siberia; 5) Extensive regional differences in the ancestry components involved in these early events remain visible to this day, e

Published
2022

31. The fine-scale genetic structure of the British population

Author

Leslie, Stephen, Winney, Bruce, Hellenthal, Garrett, Davison, Dan, Boumertit, Abdelhamid, Day, Tammy, Hutnik, Katarzyna, Royrvik, Ellen C., Cunliffe, Barry, Lawson, Daniel J., Falush, Daniel, Freeman, Colin, Pirinen, Matti, Myers, Simon, Robinson, Mark, Donnelly, Peter, and Bodmer, Walter

Subjects
Genomics -- Research, Genetic research, British -- Genetic aspects, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Fine-scale genetic variation between human populations is interesting as a signature of historical demographic events and because of its potential for confounding disease studies. We use haplotype-based statistical methods to analyse genome-wide single nucleotide polymorphism (SNP) data from a carefully chosen geographically diverse sample of 39 individuals from the United Kingdom. This reveals a rich and detailed pattern of genetic differentiation with remarkable concordance between genetic clusters and geography. The regional genetic differentiation and differing patterns of shared ancestry with 09 individuals from across Europe carry clear signals of historical demographic events. We estimate the genetic contribution to southeastern England from Anglo-Saxon migrations to be under half, and identify the regions not carrying genetic material from these migrations. We suggest significant pre-Roman but post-Mesolithic movement into southeastern England from continental Europe, and show that in non-Saxon parts of the United Kingdom, there exist genetically differentiated subgroups rather than a general 'Celtic' population., The genetic composition of human populations varies throughout the world, as a result of the interplay between population movement, admixture, natural selection and genetic drift. Characterizing such geographical population structure [...]

Published
2015
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32. Population genomics of postglacial western eurasia

Author

Allentoft, Morten E., primary, Sikora, Martin, additional, Refoyo-Martínez, Alba, additional, Irving-Pease, Evan K., additional, Fischer, Anders, additional, Barrie, William, additional, Ingason, Andrés, additional, Stenderup, Jesper, additional, Sjögren, Karl-Göran, additional, Pearson, Alice, additional, Sousa da Mota, Bárbara, additional, Paulsson, Bettina Schulz, additional, Halgren, Alma, additional, Macleod, Ruairidh, additional, Schjellerup Jørkov, Marie Louise, additional, Demeter, Fabrice, additional, Sørensen, Lasse, additional, Nielsen, Poul Otto, additional, Henriksen, Rasmus A., additional, Vimala, Tharsika, additional, McColl, Hugh, additional, Margaryan, Ashot, additional, Ilardo, Melissa, additional, Vaughn, Andrew, additional, Mortensen, Morten Fischer, additional, Nielsen, Anne Birgitte, additional, Hede, Mikkel Ulfeldt, additional, Johannsen, Niels Nørkjær, additional, Rasmussen, Peter, additional, Vinner, Lasse, additional, Renaud, Gabriel, additional, Stern, Aaron, additional, Trolle Jensen, Theis Zetner, additional, Scorrano, Gabriele, additional, Schroeder, Hannes, additional, Lysdahl, Per, additional, Ramsøe, Abigail Daisy, additional, Skorobogatov, Andrei, additional, Schork, Andrew Joseph, additional, Rosengren, Anders, additional, Ruter, Anthony, additional, Outram, Alan, additional, Timoshenko, Aleksey A., additional, Buzhilova, Alexandra, additional, Coppa, Alfredo, additional, Zubova, Alisa, additional, Silva, Ana Maria, additional, Hansen, Anders J., additional, Gromov, Andrey, additional, Logvin, Andrey, additional, Gotfredsen, Anne Birgitte, additional, Nielsen, Bjarne Henning, additional, González-Rabanal, Borja, additional, Lalueza-Fox, Carles, additional, McKenzie, Catriona J., additional, Gaunitz, Charleen, additional, Blasco, Concepción, additional, Liesau, Corina, additional, Martinez-Labarga, Cristina, additional, Pozdnyakov, Dmitri V., additional, Cuenca-Solana, David, additional, Lordkipanidze, David O., additional, En’shin, Dmitri, additional, Salazar-García, Domingo C., additional, Price, T. Douglas, additional, Borić, Dušan, additional, Kostyleva, Elena, additional, Veselovskaya, Elizaveta V., additional, Usmanova, Emma R., additional, Cappellini, Enrico, additional, Petersen, Erik Brinch, additional, Kannegaard, Esben, additional, Radina, Francesca, additional, Yediay, Fulya Eylem, additional, Duday, Henri, additional, Gutiérrez-Zugasti, Igor, additional, Merts, Ilya, additional, Potekhina, Inna, additional, Shevnina, Irina, additional, Altinkaya, Isin, additional, Guilaine, Jean, additional, Hansen, Jesper, additional, Aura Tortosa, Joan Emili, additional, Zilhão, João, additional, Vega, Jorge, additional, Pedersen, Kristoffer Buck, additional, Tunia, Krzysztof, additional, Zhao, Lei, additional, Mylnikova, Liudmila N., additional, Larsson, Lars, additional, Metz, Laure, additional, Yepiskoposyan, Levon, additional, Pedersen, Lisbeth, additional, Sarti, Lucia, additional, Orlando, Ludovic, additional, Slimak, Ludovic, additional, Klassen, Lutz, additional, Blank, Malou, additional, González-Morales, Manuel, additional, Silvestrini, Mara, additional, Vretemark, Maria, additional, Nesterova, Marina S., additional, Rykun, Marina, additional, Rolfo, Mario Federico, additional, Szmyt, Marzena, additional, Przybyła, Marcin, additional, Calattini, Mauro, additional, Sablin, Mikhail, additional, Dobisíková, Miluše, additional, Meldgaard, Morten, additional, Johansen, Morten, additional, Berezina, Natalia, additional, Card, Nick, additional, Saveliev, Nikolai A., additional, Poshekhonova, Olga, additional, Rickards, Olga, additional, Lozovskaya, Olga V., additional, Gábor, Olivér, additional, Uldum, Otto Christian, additional, Aurino, Paola, additional, Kosintsev, Pavel, additional, Courtaud, Patrice, additional, Ríos, Patricia, additional, Mortensen, Peder, additional, Lotz, Per, additional, Persson, Per, additional, Bangsgaard, Pernille, additional, Barros Damgaard, Peter de, additional, Petersen, Peter Vang, additional, Martinez, Pilar Prieto, additional, Włodarczak, Piotr, additional, Smolyaninov, Roman V., additional, Maring, Rikke, additional, Menduiña, Roberto, additional, Badalyan, Ruben, additional, Iversen, Rune, additional, Turin, Ruslan, additional, Vasilyev, Sergey, additional, Wåhlin, Sidsel, additional, Borutskaya, Svetlana, additional, Skochina, Svetlana, additional, Sørensen, Søren Anker, additional, Andersen, Søren H., additional, Jørgensen, Thomas, additional, Serikov, Yuri B., additional, Molodin, Vyacheslav I., additional, Smrcka, Vaclav, additional, Merz, Victor, additional, Appadurai, Vivek, additional, Moiseyev, Vyacheslav, additional, Magnusson, Yvonne, additional, Kjær, Kurt H., additional, Lynnerup, Niels, additional, Lawson, Daniel J., additional, Sudmant, Peter H., additional, Rasmussen, Simon, additional, Korneliussen, Thorfinn, additional, Durbin, Richard, additional, Nielsen, Rasmus, additional, Delaneau, Olivier, additional, Werge, Thomas, additional, Racimo, Fernando, additional, Kristiansen, Kristian, additional, and Willerslev, Eske, additional

Published
2022
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35. Supporting Figure 2 from CLARITY: comparing heterogeneous data using dissimilarity

Author

Lawson, Daniel J., Solanki, Vinesh, Yanovich, Igor, Dellert, Johannes, Ruck, Damian, and Endicott, Phillip

Abstract

Figure S 2 Residual charts for either direction of prediction, for each complexity k for the CLARITY analysis in Figure 7 in Section 2.6. This type of chart is of the same type as the CLARITY residuals chart in Figure 8(c) discussed in Section 2.7.

Published
2021
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37. Cultural prerequisites of socioeconomic development

Author

Ruck, Damian J., Bentley, R. Alexander, Lawson, Daniel J., Ruck, Damian J., Bentley, R. Alexander, and Lawson, Daniel J.

Abstract

In the centuries since the enlightenment, the world has seen an increase in socioeconomic development, measured as increased life expectancy, education, economic development and democracy. While the co-occurrence of these features among nations is well documented, little is known about their origins or co-evolution. Here, we compare this growth of prosperity in nations to the historical record of cultural values in the twentieth century, derived from global survey data. We find that two cultural factors, secular-rationality and cosmopolitanism, predict future increases in GDP per capita, democratization and secondary education enrollment. The converse is not true, however, which indicates that secular-rationality and cosmopolitanism are among the preconditions for socioeconomic development to emerge.

Published
2021

38. Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation

Author

Min, Josine L., Hemani, Gibran, Hannon, Eilis, Dekkers, Koen F., Castillo-Fernandez, Juan, Luijk, René, Carnero-Montoro, Elena, Lawson, Daniel J., Burrows, Kimberley, Suderman, Matthew, Bretherick, Andrew D., Richardson, Tom G., Klughammer, Johanna, Iotchkova, Valentina, Sharp, Gemma, Al Khleifat, Ahmad, Shatunov, Aleksey, Iacoangeli, Alfredo, McArdle, Wendy L., Ho, Karen M., Kumar, Ashish, Söderhäll, Cilla, Soriano-Tárraga, Carolina, Giralt-Steinhauer, Eva, Kazmi, Nabila, Mason, Dan, McRae, Allan F., Corcoran, David L., Sugden, Karen, Kasela, Silva, Cardona, Alexia, Day, Felix R., Cugliari, Giovanni, Viberti, Clara, Guarrera, Simonetta, Lerro, Michael, Gupta, Richa, Bollepalli, Sailalitha, Mandaviya, Pooja, Hottenga, Jouke Jan, Bernard, Manon, Perry, John R.B., Felix, Janine F., Rivadeneira, Fernando, Tiemeier, Henning, Uitterlinden, André G., Jaddoe, Vincent W.V., Hansen, Torben, Ikram, M. Arfan, Bell, Jordana T., van Meurs, Joyce, van IJzendoorn, Marinus, Mill, Jonathan, Relton, Caroline L., Min, Josine L., Hemani, Gibran, Hannon, Eilis, Dekkers, Koen F., Castillo-Fernandez, Juan, Luijk, René, Carnero-Montoro, Elena, Lawson, Daniel J., Burrows, Kimberley, Suderman, Matthew, Bretherick, Andrew D., Richardson, Tom G., Klughammer, Johanna, Iotchkova, Valentina, Sharp, Gemma, Al Khleifat, Ahmad, Shatunov, Aleksey, Iacoangeli, Alfredo, McArdle, Wendy L., Ho, Karen M., Kumar, Ashish, Söderhäll, Cilla, Soriano-Tárraga, Carolina, Giralt-Steinhauer, Eva, Kazmi, Nabila, Mason, Dan, McRae, Allan F., Corcoran, David L., Sugden, Karen, Kasela, Silva, Cardona, Alexia, Day, Felix R., Cugliari, Giovanni, Viberti, Clara, Guarrera, Simonetta, Lerro, Michael, Gupta, Richa, Bollepalli, Sailalitha, Mandaviya, Pooja, Hottenga, Jouke Jan, Bernard, Manon, Perry, John R.B., Felix, Janine F., Rivadeneira, Fernando, Tiemeier, Henning, Uitterlinden, André G., Jaddoe, Vincent W.V., Hansen, Torben, Ikram, M. Arfan, Bell, Jordana T., van Meurs, Joyce, van IJzendoorn, Marinus, Mill, Jonathan, and Relton, Caroline L.

Abstract

Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15–17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype–phenotype map than previously anticipated.

Published
2021

39. Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation.

Author

UK Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Cancer Research UK Programme, Wellcome Trust and the Royal Society, Dutch Heart Foundation, Dutch Federation of University Medical Centres, Netherlands Organisation for Health Research and Development, Royal Netherlands Academy of Sciences, Economic and Social Research Council (grant no. ES/N000404/1), Austrian Academy of Sciences, Min, Josine L., Hemani, Gibran, Hannon, Eilis, Dekkers, Koen F., Castillo-Fernandez, Juan, Luijk, René, Carnero-Montoro, Elena, Lawson, Daniel J., Burrows, Kimberley, Suderman, Matthew, Bretherick, Andrew D., Richardson, Tom G., Klughammer, Johanna, Iotchkova, Valentina, Sharp, Gemma, Al Khleifat, Ahmad, Shatunov, Aleksey, Iacoangeli, Aldredo, McArdle, Wendy L., Ho, Karen M., Kumar, Ashish, Söderhäll, C., Soriano-Tárraga, Carolina, Giralt-Steinhauer, Eva, Kazmi, Nabila, Mason, Dan, McRae, Allan F., Corcoran, David L., Sugden, Karen, Kasela, Silva, Cardona, Alexia, Day, Felix R., Cugliari, Giovanni, Viberti, Clara, Guarrera, Simonetta, Lerro, Michael, Gupta, Richa, Bollepalli, Sailalita, Mandaviya, Pooja, Zeng, Yanni, Clarke, Toni-Kim, Walker, Rosie M., Schmoll, V., Czamara, D., Ruiz-Arenas, Carlos, Rezwan, F. I., Marioni, R. E., Lin, T., Awaloff, Y., Barturen, G., Català-Moll, Frances, Kerick, Martin, Jiménez-Conde, Jordi, Roquer, Jaume, Gonzalez, Juan Ramón, Bustamante, Mariona, Sunyer, Jordi, Alarcón-Riquelme, Marta, UK Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Cancer Research UK Programme, Wellcome Trust and the Royal Society, Dutch Heart Foundation, Dutch Federation of University Medical Centres, Netherlands Organisation for Health Research and Development, Royal Netherlands Academy of Sciences, Economic and Social Research Council (grant no. ES/N000404/1), Austrian Academy of Sciences, Min, Josine L., Hemani, Gibran, Hannon, Eilis, Dekkers, Koen F., Castillo-Fernandez, Juan, Luijk, René, Carnero-Montoro, Elena, Lawson, Daniel J., Burrows, Kimberley, Suderman, Matthew, Bretherick, Andrew D., Richardson, Tom G., Klughammer, Johanna, Iotchkova, Valentina, Sharp, Gemma, Al Khleifat, Ahmad, Shatunov, Aleksey, Iacoangeli, Aldredo, McArdle, Wendy L., Ho, Karen M., Kumar, Ashish, Söderhäll, C., Soriano-Tárraga, Carolina, Giralt-Steinhauer, Eva, Kazmi, Nabila, Mason, Dan, McRae, Allan F., Corcoran, David L., Sugden, Karen, Kasela, Silva, Cardona, Alexia, Day, Felix R., Cugliari, Giovanni, Viberti, Clara, Guarrera, Simonetta, Lerro, Michael, Gupta, Richa, Bollepalli, Sailalita, Mandaviya, Pooja, Zeng, Yanni, Clarke, Toni-Kim, Walker, Rosie M., Schmoll, V., Czamara, D., Ruiz-Arenas, Carlos, Rezwan, F. I., Marioni, R. E., Lin, T., Awaloff, Y., Barturen, G., Català-Moll, Frances, Kerick, Martin, Jiménez-Conde, Jordi, Roquer, Jaume, Gonzalez, Juan Ramón, Bustamante, Mariona, Sunyer, Jordi, and Alarcón-Riquelme, Marta

Abstract

Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15–17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype–phenotype map than previously anticipated.

Published
2021

41. Population genomics of the Viking world:[incl. correction]

Author

Margaryan, Ashot, Lawson, Daniel J, Sikora, Martin, Racimo, Fernando, Rasmussen, Simon, Moltke, Ida, Cassidy, Lara M, Jørsboe, Emil, Ingason, Andrés, Pedersen, Mikkel W, Korneliussen, Thorfinn, Wilhelmson, Helene, Buś, Magdalena M, de Barros Damgaard, Peter, Martiniano, Rui, Renaud, Gabriel, Bhérer, Claude, Moreno-Mayar, J Víctor, Fotakis, Anna K, Allen, Marie, Allmäe, Raili, Molak, Martyna, Cappellini, Enrico, Scorrano, Gabriele, McColl, Hugh, Buzhilova, Alexandra, Fox, Allison, Albrechtsen, Anders, Schütz, Berit, Skar, Birgitte, Arcini, Caroline, Lundstrøm, Inge, Cheng, Jade, Stenderup, Jesper, Iversen, Katrine H, Arge, Símun V, Ellingvåg, Sturla, Orlando, Ludovic, Pentz, Peter, Jessen, Mads Dengsø, Pedersen, Anne, Jørkov, Marie Louise, Lynnerup, Niels, Gilbert, M Thomas P, Allentoft, Morten E, Sindbæk, Søren M, Kristiansen, Kristian, Nielsen, Rasmus, Werge, Thomas, Willerslev, Eske, Margaryan, Ashot, Lawson, Daniel J, Sikora, Martin, Racimo, Fernando, Rasmussen, Simon, Moltke, Ida, Cassidy, Lara M, Jørsboe, Emil, Ingason, Andrés, Pedersen, Mikkel W, Korneliussen, Thorfinn, Wilhelmson, Helene, Buś, Magdalena M, de Barros Damgaard, Peter, Martiniano, Rui, Renaud, Gabriel, Bhérer, Claude, Moreno-Mayar, J Víctor, Fotakis, Anna K, Allen, Marie, Allmäe, Raili, Molak, Martyna, Cappellini, Enrico, Scorrano, Gabriele, McColl, Hugh, Buzhilova, Alexandra, Fox, Allison, Albrechtsen, Anders, Schütz, Berit, Skar, Birgitte, Arcini, Caroline, Lundstrøm, Inge, Cheng, Jade, Stenderup, Jesper, Iversen, Katrine H, Arge, Símun V, Ellingvåg, Sturla, Orlando, Ludovic, Pentz, Peter, Jessen, Mads Dengsø, Pedersen, Anne, Jørkov, Marie Louise, Lynnerup, Niels, Gilbert, M Thomas P, Allentoft, Morten E, Sindbæk, Søren M, Kristiansen, Kristian, Nielsen, Rasmus, Werge, Thomas, and Willerslev, Eske

Abstract

The maritime expansion of Scandinavian populations during the Viking Age (about AD 750-1050) was a far-flung transformation in world history1,2. Here we sequenced the genomes of 442 humans from archaeological sites across Europe and Greenland (to a median depth of about 1×) to understand the global influence of this expansion. We find the Viking period involved gene flow into Scandinavia from the south and east. We observe genetic structure within Scandinavia, with diversity hotspots in the south and restricted gene flow within Scandinavia. We find evidence for a major influx of Danish ancestry into England; a Swedish influx into the Baltic; and Norwegian influx into Ireland, Iceland and Greenland. Additionally, we see substantial ancestry from elsewhere in Europe entering Scandinavia during the Viking Age. Our ancient DNA analysis also revealed that a Viking expedition included close family members. By comparing with modern populations, we find that pigmentation-associated loci have undergone strong population differentiation during the past millennium, and trace positively selected loci-including the lactase-persistence allele of LCT and alleles of ANKA that are associated with the immune response-in detail. We conclude that the Viking diaspora was characterized by substantial transregional engagement: distinct populations influenced the genomic makeup of different regions of Europe, and Scandinavia experienced increased contact with the rest of the continent.

Published
2020

43. Religious change preceded economic change in the 20th century

Author

Ruck, Damian J., Bentley, R. Alexander, and Lawson, Daniel J.

Subjects
Religion, Linear Models, SciAdv r-articles, Social Sciences, Educational Status, Humans, Economic Development, History, 20th Century, Research Articles, Research Article
Abstract

Religious change predicted economic change in the 20th century, across the world., The decline in the everyday importance of religion with economic development is a well-known correlation, but which phenomenon comes first? Using unsupervised factor analysis and a birth cohort approach to create a retrospective time series, we present 100-year time series of secularization in different nations, derived from recent global values surveys, which we compare by decade to historical gross domestic product figures in those nations. We find evidence that a rise in secularization generally has preceded economic growth over the past century. Our multilevel, time-lagged regressions also indicate that tolerance for individual rights predicted 20th century economic growth even better than secularization. These findings hold when we control for education and shared cultural heritage.

Published
2018

45. Multiple Deeply Divergent Denisovan Ancestries in Papuans

Author

Jacobs, Guy S., primary, Hudjashov, Georgi, additional, Saag, Lauri, additional, Kusuma, Pradiptajati, additional, Darusallam, Chelzie C., additional, Lawson, Daniel J., additional, Mondal, Mayukh, additional, Pagani, Luca, additional, Ricaut, François-Xavier, additional, Stoneking, Mark, additional, Metspalu, Mait, additional, Sudoyo, Herawati, additional, Lansing, J. Stephen, additional, and Cox, Murray P., additional

Published
2019
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47. Rapid evolution of distinct Helicobacter pylori subpopulations in the Americas

Author

Coop, Graham, Thorell, Kaisa, Yahara, Koji, Berthenet, Elvire, Lawson, Daniel J., Mikhail, Jane, Kato, Ikuko, Mendez, Alfonso, Rizzato, Cosmeri, Bravo, María Mercedes, Suzuki, Rumiko, Yamaoka, Yoshio, Torres, Javier, Sheppard, Samuel K., and Falush, Daniel

Abstract

For the last 500 years, the Americas have been a melting pot both for genetically diverse humans and for the pathogenic and commensal organisms associated with them. One such organism is the stomach-dwelling bacterium Helicobacter pylori, which is highly prevalent in Latin America where it is a major current public health challenge because of its strong association with gastric cancer. By analyzing the genome sequence of H. pylori isolated in North, Central and South America, we found evidence for admixture between H. pylori of European and African origin throughout the Americas, without substantial input from pre-Columbian (hspAmerind) bacteria. In the US, strains of African and European origin have remained genetically distinct, while in Colombia and Nicaragua, bottlenecks and rampant genetic exchange amongst isolates have led to the formation of national gene pools. We found three outer membrane proteins with atypical levels of Asian ancestry in American strains, as well as alleles that were nearly fixed specifically in South American isolates, suggesting a role for the ethnic makeup of hosts in the colonization of incoming strains. Our results show that new H. pylori subpopulations can rapidly arise, spread and adapt during times of demographic flux, and suggest that differences in transmission ecology between high and low prevalence areas may substantially affect the composition of bacterial populations.

Published
2017

48. Rapid evolution of distinct Helicobacter pylori subpopulations in the Americas

Author

Thorell, Kaisa, Yahara, Koji, Berthenet, Elvire, Lawson, Daniel J., Mikhail, Jane, Kato, Ikuko, Mendez, Alfonso, Rizzato, Cosmeri, Bravo, María Mercedes, Suzuki, Rumiko, Yamaoka, Yoshio, Torres, Javier, Sheppard, Samuel K., and Falush, Daniel

Subjects
Cell Membranes, Pathology and Laboratory Medicine, Database and Informatics Methods, Helicobacter, Medicine and Health Sciences, Ethnicities, Phylogeny, In Situ Hybridization, Phylogenetic Analysis, Genomics, Population groupings, Genomic Databases, Latin Americans, Bacterial Pathogens, Medical Microbiology, admixture, Pathogens, Cellular Structures and Organelles, Sequence Analysis, Research Article, lcsh:QH426-470, Bioinformatics, selection, Molecular Probe Techniques, Research and Analysis Methods, DNA, Mitochondrial, Microbiology, White People, Helicobacter Infections, Evolution, Molecular, Stomach Neoplasms, Genetics, Humans, Molecular Biology Techniques, Microbial Pathogens, Molecular Biology, Alleles, Molecular Biology Assays and Analysis Techniques, Helicobacter pylori, Bacteria, Organisms, Correction, Biology and Life Sciences, Membrane Proteins, Computational Biology, population structure, Cell Biology, Outer Membrane Proteins, Genome Analysis, Helicobacter Pylori, Probe Hybridization, lcsh:Genetics, Latin America, Biological Databases, People and Places, Indians, North American, Sequence Alignment, Genome, Bacterial, chromosome painting, Africans
Abstract

For the last 500 years, the Americas have been a melting pot both for genetically diverse humans and for the pathogenic and commensal organisms associated with them. One such organism is the stomach-dwelling bacterium Helicobacter pylori, which is highly prevalent in Latin America where it is a major current public health challenge because of its strong association with gastric cancer. By analyzing the genome sequence of H. pylori isolated in North, Central and South America, we found evidence for admixture between H. pylori of European and African origin throughout the Americas, without substantial input from pre-Columbian (hspAmerind) bacteria. In the US, strains of African and European origin have remained genetically distinct, while in Colombia and Nicaragua, bottlenecks and rampant genetic exchange amongst isolates have led to the formation of national gene pools. We found three outer membrane proteins with atypical levels of Asian ancestry in American strains, as well as alleles that were nearly fixed specifically in South American isolates, suggesting a role for the ethnic makeup of hosts in the colonization of incoming strains. Our results show that new H. pylori subpopulations can rapidly arise, spread and adapt during times of demographic flux, and suggest that differences in transmission ecology between high and low prevalence areas may substantially affect the composition of bacterial populations., Author summary Helicobacter pylori is one of the best studied examples of an intimate association between bacteria and humans, due to its ability to colonize the stomach for decades and to transmit from generation to generation. A number of studies have sought to link diversity in H. pylori to human migrations but there are some discordant signals such as an “out of Africa” dispersal within the last few thousand years that has left a much stronger signal in bacterial genomes than in human ones. In order to understand how such discrepancies arise, we have investigated the evolution of H. pylori during the recent colonization of the Americas. We find that bacterial populations evolve quickly and can spread rapidly to people of different ethnicities. Distinct new bacterial subpopulations have formed in Colombia from a European source and in Nicaragua and the US from African sources. Genetic exchange between bacterial populations is rampant within Central and South America but is uncommon within North America, which may reflect differences in prevalence. Our results also suggest that adaptation of bacteria to particular human ethnic groups may be confined to a handful of genes involved in interaction with the immune system.

Published
2017

49. Is Dupuytren's disease really a 'disease of the Vikings'?

Author

Ng, Michael, Lawson, Daniel J, Winney, Bruce, and Furniss, Dominic

Subjects
SINGLE nucleotide polymorphisms, VIKINGS, BRITISH people
Abstract

It has been suggested that Dupuytren's disease has an origin in Norse countries. We harnessed data from a genome-wide association study of Dupuytren's disease and the People of the British Isles study to determine evidence for a Norse origin of Dupuytren's disease. We computed Wright's Fixation Index between Orkney (Norse ancestry), Wales (ancient British) and South East England (Anglo-Saxons); compared mean Wright's Fixation Index in cases versus controls; used permutation to determine any excess of Norse inheritance in disease associated variants; constructed a genetic risk score for Dupuytren's disease and applied this to the People of the British Isles dataset to look for systematic differences between counties with known high and low levels of Norse ancestry. Finally, chromosome painting was used to see whether Dupuytren's disease-associated single nucleotide polymorphisms are geographically structured. In all analyses, no evidence was found for an excess of Norse ancestry in Dupuytren's disease. We conclude that there is no genetic evidence for a 'Viking origin of Dupuytren's disease'. [ABSTRACT FROM AUTHOR]

Published
2020
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