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Kyriazis CC, Serieys LE, Bishop JM, Drouilly M, Viljoen S, Wayne RK, Lohmueller KE. The influence of gene flow on population viability in an isolated urban caracal population. Mol Ecol 2024; 33:e17346. [PMID: 38581173 PMCID: PMC11035096 DOI: 10.1111/mec.17346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 01/23/2024] [Accepted: 03/26/2024] [Indexed: 04/08/2024]
Abstract
Wildlife populations are becoming increasingly fragmented by anthropogenic development. Small and isolated populations often face an elevated risk of extinction, in part due to inbreeding depression. Here, we examine the genomic consequences of urbanization in a caracal (Caracal caracal) population that has become isolated in the Cape Peninsula region of the City of Cape Town, South Africa, and is thought to number ~50 individuals. We document low levels of migration into the population over the past ~75 years, with an estimated rate of 1.3 effective migrants per generation. As a consequence of this isolation and small population size, levels of inbreeding are elevated in the contemporary Cape Peninsula population (mean FROH = 0.20). Inbreeding primarily manifests as long runs of homozygosity >10 Mb, consistent with the effects of isolation due to the rapid recent growth of Cape Town. To explore how reduced migration and elevated inbreeding may impact future population dynamics, we parameterized an eco-evolutionary simulation model. We find that if migration rates do not change in the future, the population is expected to decline, though with a low projected risk of extinction. However, if migration rates decline or anthropogenic mortality rates increase, the potential risk of extinction is greatly elevated. To avert a population decline, we suggest that translocating migrants into the Cape Peninsula to initiate a genetic rescue may be warranted in the near future. Our analysis highlights the utility of genomic datasets coupled with computational simulation models for investigating the influence of gene flow on population viability.
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Affiliation(s)
- Christopher C. Kyriazis
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095, USA
| | - Laurel E.K. Serieys
- Panthera, 8 W 40th St, 18th Floor, New York, NY 10018, USA
- Institute for Communities and Wildlife in Africa, Department of Biological Sciences, University of Cape Town, Rondebosch, 7701, South Africa
| | - Jacqueline M. Bishop
- Institute for Communities and Wildlife in Africa, Department of Biological Sciences, University of Cape Town, Rondebosch, 7701, South Africa
| | - Marine Drouilly
- Panthera, 8 W 40th St, 18th Floor, New York, NY 10018, USA
- Institute for Communities and Wildlife in Africa, Department of Biological Sciences, University of Cape Town, Rondebosch, 7701, South Africa
- Centre for Social Science Research, University of Cape Town, Rondebosch, 7701, South Africa
| | - Storme Viljoen
- Institute for Communities and Wildlife in Africa, Department of Biological Sciences, University of Cape Town, Rondebosch, 7701, South Africa
| | - Robert K. Wayne
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095, USA
| | - Kirk E. Lohmueller
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095, USA
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
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2
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Kyriazis CC, Lohmueller KE. Constraining models of dominance for nonsynonymous mutations in the human genome. bioRxiv 2024:2024.02.25.582010. [PMID: 38463985 PMCID: PMC10925099 DOI: 10.1101/2024.02.25.582010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Dominance is a fundamental parameter in genetics, determining the dynamics of natural selection on deleterious and beneficial mutations, the patterns of genetic variation in natural populations, and the severity of inbreeding depression in a population. Despite this importance, dominance parameters remain poorly known, particularly in humans or other non-model organisms. A key reason for this lack of information about dominance is that it is extremely challenging to disentangle the selection coefficient (s) of a mutation from its dominance coefficient (h). Here, we explore dominance and selection parameters in humans by fitting models to the site frequency spectrum (SFS) for nonsynonymous mutations. When assuming a single dominance coefficient for all nonsynonymous mutations, we find that numerous h values can fit the data, so long as h is greater than ~0.15. Moreover, we also observe that theoretically-predicted models with a negative relationship between h and s can also fit the data well, including models with h=0.05 for strongly deleterious mutations. Finally, we use our estimated dominance and selection parameters to inform simulations revisiting the question of whether the out-of-Africa bottleneck has led to differences in genetic load between African and non-African human populations. These simulations suggest that the relative burden of genetic load in non-African populations depends on the dominance model assumed, with slight increases for more weakly recessive models and slight decreases shown for more strongly recessive models. Moreover, these results also demonstrate that models of partially recessive nonsynonymous mutations can explain the observed severity of inbreeding depression in humans, bridging the gap between molecular population genetics and direct measures of fitness in humans. Our work represents a comprehensive assessment of dominance and deleterious variation in humans, with implications for parameterizing models of deleterious variation in humans and other mammalian species.
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Affiliation(s)
| | - Kirk E. Lohmueller
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, USA
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, USA
- Department of Human Genetics, David Geffen School of Medicine, Los Angeles, USA
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3
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Zurita AMI, Kyriazis CC, Lohmueller KE. The impact of non-neutral synonymous mutations when inferring selection on non-synonymous mutations. bioRxiv 2024:2024.02.07.579314. [PMID: 38370782 PMCID: PMC10871344 DOI: 10.1101/2024.02.07.579314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
The distribution of fitness effects (DFE) describes the proportions of new mutations that have different effects on reproductive fitness. Accurate measurements of the DFE are important because the DFE is a fundamental parameter in evolutionary genetics and has implications for our understanding of other phenomena like complex disease or inbreeding depression. Current computational methods to infer the DFE for nonsynonymous mutations from natural variation first estimate demographic parameters from synonymous variants to control for the effects of demography and background selection. Then, conditional on these parameters, the DFE is then inferred for nonsynonymous mutations. This approach relies on the assumption that synonymous variants are neutrally evolving. However, some evidence points toward synonymous mutations having measurable effects on fitness. To test whether selection on synonymous mutations affects inference of the DFE of nonsynonymous mutations, we simulated several possible models of selection on synonymous mutations using SLiM and attempted to recover the DFE of nonsynonymous mutations using Fit∂a∂i, a common method for DFE inference. Our results show that the presence of selection on synonymous variants leads to incorrect inferences of recent population growth. Furthermore, under certain parameter combinations, inferences of the DFE can have an inflated proportion of highly deleterious nonsynonymous mutations. However, this bias can be eliminated if the correct demographic parameters are used for DFE inference instead of the biased ones inferred from synonymous variants. Our work demonstrates how unmodeled selection on synonymous mutations may affect downstream inferences of the DFE.
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Affiliation(s)
- Aina Martinez I Zurita
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, USA
| | - Christopher C Kyriazis
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, USA
| | - Kirk E Lohmueller
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, USA
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, USA
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, USA
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4
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Kyriazis CC, Robinson JA, Lohmueller KE. Using Computational Simulations to Model Deleterious Variation and Genetic Load in Natural Populations. Am Nat 2023; 202:737-752. [PMID: 38033186 PMCID: PMC10897732 DOI: 10.1086/726736] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2023]
Abstract
AbstractDeleterious genetic variation is abundant in wild populations, and understanding the ecological and conservation implications of such variation is an area of active research. Genomic methods are increasingly used to quantify the impacts of deleterious variation in natural populations; however, these approaches remain limited by an inability to accurately predict the selective and dominance effects of mutations. Computational simulations of deleterious variation offer a complementary tool that can help overcome these limitations, although such approaches have yet to be widely employed. In this perspective article, we aim to encourage ecological and conservation genomics researchers to adopt greater use of computational simulations to aid in deepening our understanding of deleterious variation in natural populations. We first provide an overview of the components of a simulation of deleterious variation, describing the key parameters involved in such models. Next, we discuss several approaches for validating simulation models. Finally, we compare and validate several recently proposed deleterious mutation models, demonstrating that models based on estimates of selection parameters from experimental systems are biased toward highly deleterious mutations. We describe a new model that is supported by multiple orthogonal lines of evidence and provide example scripts for implementing this model (https://github.com/ckyriazis/simulations_review).
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Nigenda-Morales SF, Lin M, Nuñez-Valencia PG, Kyriazis CC, Beichman AC, Robinson JA, Ragsdale AP, Urbán R J, Archer FI, Viloria-Gómora L, Pérez-Álvarez MJ, Poulin E, Lohmueller KE, Moreno-Estrada A, Wayne RK. The genomic footprint of whaling and isolation in fin whale populations. Nat Commun 2023; 14:5465. [PMID: 37699896 PMCID: PMC10497599 DOI: 10.1038/s41467-023-40052-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 07/10/2023] [Indexed: 09/14/2023] Open
Abstract
Twentieth century industrial whaling pushed several species to the brink of extinction, with fin whales being the most impacted. However, a small, resident population in the Gulf of California was not targeted by whaling. Here, we analyzed 50 whole-genomes from the Eastern North Pacific (ENP) and Gulf of California (GOC) fin whale populations to investigate their demographic history and the genomic effects of natural and human-induced bottlenecks. We show that the two populations diverged ~16,000 years ago, after which the ENP population expanded and then suffered a 99% reduction in effective size during the whaling period. In contrast, the GOC population remained small and isolated, receiving less than one migrant per generation. However, this low level of migration has been crucial for maintaining its viability. Our study exposes the severity of whaling, emphasizes the importance of migration, and demonstrates the use of genome-based analyses and simulations to inform conservation strategies.
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Affiliation(s)
- Sergio F Nigenda-Morales
- Advanced Genomics Unit, National Laboratory of Genomics for Biodiversity (Langebio), Center for Research and Advanced Studies (Cinvestav), Irapuato, Guanajuato, 36824, Mexico.
- Department of Biological Sciences, California State University San Marcos, San Marcos, CA, 92096, USA.
| | - Meixi Lin
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Department of Plant Biology, Carnegie Institution for Science, Stanford, CA, 94305, USA.
| | - Paulina G Nuñez-Valencia
- Advanced Genomics Unit, National Laboratory of Genomics for Biodiversity (Langebio), Center for Research and Advanced Studies (Cinvestav), Irapuato, Guanajuato, 36824, Mexico
- Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México (UNAM), Cuernavaca, Morelos, México
| | - Christopher C Kyriazis
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Annabel C Beichman
- Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA
| | - Jacqueline A Robinson
- Institute for Human Genetics, University of California, San Francisco (UCSF), San Francisco, CA, 94143, USA
| | - Aaron P Ragsdale
- Advanced Genomics Unit, National Laboratory of Genomics for Biodiversity (Langebio), Center for Research and Advanced Studies (Cinvestav), Irapuato, Guanajuato, 36824, Mexico
- Department of Integrative Biology, University of Wisconsin, Madison, WI, 53706, USA
| | - Jorge Urbán R
- Departamento de Ciencias Marinas y Costeras, Universidad Autónoma de Baja California Sur (UABCS), La Paz, Baja California Sur, Mexico
| | - Frederick I Archer
- Marine Mammal and Turtle Division, Southwest Fisheries Science Center, La Jolla, CA, 92037, USA
| | - Lorena Viloria-Gómora
- Departamento de Ciencias Marinas y Costeras, Universidad Autónoma de Baja California Sur (UABCS), La Paz, Baja California Sur, Mexico
| | - María José Pérez-Álvarez
- Escuela de Medicina Veterinaria, Facultad de Medicina y Ciencias de la Salud, Universidad Mayor, Santiago, Chile
- Millennium Institute Biodiversity of Antarctic and Subantarctic Ecosystems (BASE), Universidad de Chile, Santiago, Chile
| | - Elie Poulin
- Millennium Institute Biodiversity of Antarctic and Subantarctic Ecosystems (BASE), Universidad de Chile, Santiago, Chile
| | - Kirk E Lohmueller
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, CA, 90095, USA.
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
| | - Andrés Moreno-Estrada
- Advanced Genomics Unit, National Laboratory of Genomics for Biodiversity (Langebio), Center for Research and Advanced Studies (Cinvestav), Irapuato, Guanajuato, 36824, Mexico.
| | - Robert K Wayne
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
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Wade EE, Kyriazis CC, Cavassim MIA, Lohmueller KE. Quantifying the fraction of new mutations that are recessive lethal. Evolution 2023; 77:1539-1549. [PMID: 37074880 PMCID: PMC10309970 DOI: 10.1093/evolut/qpad061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 03/21/2023] [Accepted: 04/14/2023] [Indexed: 04/20/2023]
Abstract
The presence and impact of recessive lethal mutations have been widely documented in diploid outcrossing species. However, precise estimates of the proportion of new mutations that are recessive lethal remain limited. Here, we evaluate the performance of Fit∂a∂i, a commonly used method for inferring the distribution of fitness effects (DFE), in the presence of lethal mutations. Using simulations, we demonstrate that in both additive and recessive cases, inference of the deleterious nonlethal portion of the DFE is minimally affected by a small proportion (<10%) of lethal mutations. Additionally, we demonstrate that while Fit∂a∂i cannot estimate the fraction of recessive lethal mutations, Fit∂a∂i can accurately infer the fraction of additive lethal mutations. Finally, as an alternative approach to estimate the proportion of mutations that are recessive lethal, we employ models of mutation-selection-drift balance using existing genomic parameters and estimates of segregating recessive lethals for humans and Drosophila melanogaster. In both species, the segregating recessive lethal load can be explained by a very small fraction (<1%) of new nonsynonymous mutations being recessive lethal. Our results refute recent assertions of a much higher proportion of mutations being recessive lethal (4%-5%), while highlighting the need for additional information on the joint distribution of selection and dominance coefficients.
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Affiliation(s)
- Emma E Wade
- Department of Ecology and Evolutionary Biology, University of California–Los Angeles, Los Angeles, CA, United States
- Department of Computer Science and Engineering, Mississippi State University, Starkville, MS, United States
| | - Christopher C Kyriazis
- Department of Ecology and Evolutionary Biology, University of California–Los Angeles, Los Angeles, CA, United States
| | - Maria Izabel A Cavassim
- Department of Ecology and Evolutionary Biology, University of California–Los Angeles, Los Angeles, CA, United States
| | - Kirk E Lohmueller
- Department of Ecology and Evolutionary Biology, University of California–Los Angeles, Los Angeles, CA, United States
- Interdepartmental Program in Bioinformatics, University of California–Los Angeles, Los Angeles, CA, United States
- Department of Human Genetics, David Geffen School of Medicine, University of California–Los Angeles, Los Angeles, CA, United States
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7
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Kyriazis CC, Robinson JA, Nigenda-Morales SF, Beichman AC, Rojas-Bracho L, Robertson KM, Fontaine MC, Wayne RK, Taylor BL, Lohmueller KE, Morin PA. Models based on best-available information support a low inbreeding load and potential for recovery in the vaquita. Heredity (Edinb) 2023; 130:183-187. [PMID: 36941409 PMCID: PMC10076335 DOI: 10.1038/s41437-023-00608-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 03/01/2023] [Accepted: 03/02/2023] [Indexed: 03/23/2023] Open
Affiliation(s)
- Christopher C Kyriazis
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA, USA.
| | - Jacqueline A Robinson
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.
| | - Sergio F Nigenda-Morales
- Advanced Genomics Unit, National Laboratory of Genomics for Biodiversity (Langebio), Center for Research and Advanced Studies (Cinvestav); Irapuato, Guanajuato, Mexico
| | - Annabel C Beichman
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | | | - Kelly M Robertson
- Southwest Fisheries Science Center, National Marine Fisheries Service, NOAA, La Jolla, CA, USA
| | - Michael C Fontaine
- MIVEGEC, Université de Montpellier, CNRS, IRD, Montpellier, France
- Centre de Recherche en Écologie et Évolution de la Santé (CREES), Montpellier, France
- Groningen Institute for Evolutionary Life Sciences (GELIFES), University of Groningen, Groningen, The Netherlands
| | - Robert K Wayne
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Barbara L Taylor
- Southwest Fisheries Science Center, National Marine Fisheries Service, NOAA, La Jolla, CA, USA
| | - Kirk E Lohmueller
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
| | - Phillip A Morin
- Southwest Fisheries Science Center, National Marine Fisheries Service, NOAA, La Jolla, CA, USA.
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Abstract
Deleterious mutations decrease reproductive fitness and are ubiquitous in genomes. Given that many organisms face ongoing threats of extinction, there is interest in elucidating the impact of deleterious variation on extinction risk and optimizing management strategies accounting for such mutations. Quantifying deleterious variation and understanding the effects of population history on deleterious variation are complex endeavors because we do not know the strength of selection acting on each mutation. Further, the effect of demographic history on deleterious mutations depends on the strength of selection against the mutation and the degree of dominance. Here we clarify how deleterious variation can be quantified and studied in natural populations. We then discuss how different demographic factors, such as small population size, nonequilibrium population size changes, inbreeding, and gene flow, affect deleterious variation. Lastly, we provide guidance on studying deleterious variation in nonmodel populations of conservation concern.
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Affiliation(s)
- Jacqueline Robinson
- Institute for Human Genetics, University of California, San Francisco, California, USA;
| | - Christopher C Kyriazis
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California, USA; , ,
| | - Stella C Yuan
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California, USA; , ,
| | - Kirk E Lohmueller
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California, USA; , , .,Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, California, USA
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Kyriazis CC, Beichman AC, Brzeski KE, Hoy SR, Peterson RO, Vucetich JA, Vucetich LM, Lohmueller KE, Wayne RK. Genomic Underpinnings of Population Persistence in Isle Royale Moose. Mol Biol Evol 2023; 40:7024794. [PMID: 36729989 PMCID: PMC9927576 DOI: 10.1093/molbev/msad021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 01/20/2023] [Accepted: 01/25/2023] [Indexed: 02/03/2023] Open
Abstract
Island ecosystems provide natural laboratories to assess the impacts of isolation on population persistence. However, most studies of persistence have focused on a single species, without comparisons to other organisms they interact with in the ecosystem. The case study of moose and gray wolves on Isle Royale allows for a direct contrast of genetic variation in isolated populations that have experienced dramatically differing population trajectories over the past decade. Whereas the Isle Royale wolf population recently declined nearly to extinction due to severe inbreeding depression, the moose population has thrived and continues to persist, despite having low genetic diversity and being isolated for ∼120 years. Here, we examine the patterns of genomic variation underlying the continued persistence of the Isle Royale moose population. We document high levels of inbreeding in the population, roughly as high as the wolf population at the time of its decline. However, inbreeding in the moose population manifests in the form of intermediate-length runs of homozygosity suggestive of historical inbreeding and purging, contrasting with the long runs of homozygosity observed in the smaller wolf population. Using simulations, we confirm that substantial purging has likely occurred in the moose population. However, we also document notable increases in genetic load, which could eventually threaten population viability over the long term. Overall, our results demonstrate a complex relationship between inbreeding, genetic diversity, and population viability that highlights the use of genomic datasets and computational simulation tools for understanding the factors enabling persistence in isolated populations.
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Affiliation(s)
| | | | - Kristin E Brzeski
- College of Forest Resources and Environmental Science, Michigan Technological University, Houghton, MI
| | - Sarah R Hoy
- College of Forest Resources and Environmental Science, Michigan Technological University, Houghton, MI
| | - Rolf O Peterson
- College of Forest Resources and Environmental Science, Michigan Technological University, Houghton, MI
| | - John A Vucetich
- College of Forest Resources and Environmental Science, Michigan Technological University, Houghton, MI
| | - Leah M Vucetich
- College of Forest Resources and Environmental Science, Michigan Technological University, Houghton, MI
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Beichman AC, Kalhori P, Kyriazis CC, DeVries AA, Nigenda-Morales S, Heckel G, Schramm Y, Moreno-Estrada A, Kennett DJ, Hylkema M, Bodkin J, Koepfli KP, Lohmueller KE, Wayne RK. Genomic analyses reveal range-wide devastation of sea otter populations. Mol Ecol 2023; 32:281-298. [PMID: 34967471 PMCID: PMC9875727 DOI: 10.1111/mec.16334] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 12/02/2021] [Accepted: 12/23/2021] [Indexed: 01/28/2023]
Abstract
The genetic consequences of species-wide declines are rarely quantified because the timing and extent of the decline varies across the species' range. The sea otter (Enhydra lutris) is a unique model in this regard. Their dramatic decline from thousands to fewer than 100 individuals per population occurred range-wide and nearly simultaneously due to the 18th-19th century fur trade. Consequently, each sea otter population represents an independent natural experiment of recovery after extreme population decline. We designed sequence capture probes for 50 Mb of sea otter exonic and neutral genomic regions. We sequenced 107 sea otters from five populations that span the species range to high coverage (18-76×) and three historical Californian samples from ~1500 and ~200 years ago to low coverage (1.5-3.5×). We observe distinct population structure and find that sea otters in California are the last survivors of a divergent lineage isolated for thousands of years and therefore warrant special conservation concern. We detect signals of extreme population decline in every surviving sea otter population and use this demographic history to design forward-in-time simulations of coding sequence. Our simulations indicate that this decline could lower the fitness of recovering populations for generations. However, the simulations also demonstrate how historically low effective population sizes prior to the fur trade may have mitigated the effects of population decline on genetic health. Our comprehensive approach shows how demographic inference from genomic data, coupled with simulations, allows assessment of extinction risk and different models of recovery.
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Affiliation(s)
- Annabel C. Beichman
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095, USA
| | - Pooneh Kalhori
- Department of Biology, San Francisco State University, San Francisco, CA 94132, USA
| | - Christopher C. Kyriazis
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095, USA
| | - Amber A. DeVries
- Center for Bioinformatics and Functional Genomics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Sergio Nigenda-Morales
- National Laboratory of Genomics for Biodiversity, Unit of Advanced Genomics (LANGEBIO), CINVESTAV, Irapuato, Guanajuato 36824, Mexico
| | - Gisela Heckel
- Centro de Investigación Científica y de Educación Superior de Ensenada (Ensenada Center for Scientific Research and Higher Education), Ensenada, Baja California 22860, Mexico
| | - Yolanda Schramm
- Universidad Autónoma de Baja California (Autonomous University of Baja California), Ensenada, Baja California 22860, Mexico
| | - Andrés Moreno-Estrada
- National Laboratory of Genomics for Biodiversity, Unit of Advanced Genomics (LANGEBIO), CINVESTAV, Irapuato, Guanajuato 36824, Mexico
| | - Douglas J. Kennett
- Department of Anthropology, University of California, Santa Barbara, CA 93106, USA
| | - Mark Hylkema
- Cultural Resources Program Manager and Tribal Liaison/Archaeologist, Santa Cruz District, California State Parks, Santa Cruz, California, USA
| | - James Bodkin
- Retired, Alaska Science Center, US Geological Survey, Anchorage Alaska, 99503, USA
| | - Klaus-Peter Koepfli
- Smithsonian-Mason School of Conservation, George Mason University, Front Royal, VA 22630, USA
- Smithsonian Conservation Biology Institute, Center for Species Survival, National Zoological Park, Washington, D.C., 20008, USA
- ITMO University, Computer Technologies Laboratory, St. Petersburg 197101, Russia
| | - Kirk E. Lohmueller
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095, USA
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Robert K. Wayne
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095, USA
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11
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Exposito-Alonso M, Booker TR, Czech L, Gillespie L, Hateley S, Kyriazis CC, Lang PLM, Leventhal L, Nogues-Bravo D, Pagowski V, Ruffley M, Spence JP, Toro Arana SE, Weiß CL, Zess E. Genetic diversity loss in the Anthropocene. Science 2022; 377:1431-1435. [PMID: 36137047 DOI: 10.1126/science.abn5642] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Anthropogenic habitat loss and climate change are reducing species' geographic ranges, increasing extinction risk and losses of species' genetic diversity. Although preserving genetic diversity is key to maintaining species' adaptability, we lack predictive tools and global estimates of genetic diversity loss across ecosystems. We introduce a mathematical framework that bridges biodiversity theory and population genetics to understand the loss of naturally occurring DNA mutations with decreasing habitat. By analyzing genomic variation of 10,095 georeferenced individuals from 20 plant and animal species, we show that genome-wide diversity follows a mutations-area relationship power law with geographic area, which can predict genetic diversity loss from local population extinctions. We estimate that more than 10% of genetic diversity may already be lost for many threatened and nonthreatened species, surpassing the United Nations' post-2020 targets for genetic preservation.
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Affiliation(s)
- Moises Exposito-Alonso
- Department of Plant Biology, Carnegie Institution for Science, Stanford, CA 94305, USA.,Department of Biology, Stanford University, Stanford, CA 94305, USA.,Department of Global Ecology, Carnegie Institution for Science, Stanford, CA 94305, USA
| | - Tom R Booker
- Department of Zoology, University of British Columbia, Vancouver, Canada.,Biodiversity Research Centre, University of British Columbia, Vancouver, Canada
| | - Lucas Czech
- Department of Plant Biology, Carnegie Institution for Science, Stanford, CA 94305, USA
| | - Lauren Gillespie
- Department of Plant Biology, Carnegie Institution for Science, Stanford, CA 94305, USA.,Department of Computer Science, Stanford University, Stanford, CA 94305, USA
| | - Shannon Hateley
- Department of Plant Biology, Carnegie Institution for Science, Stanford, CA 94305, USA
| | - Christopher C Kyriazis
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095, USA
| | | | - Laura Leventhal
- Department of Plant Biology, Carnegie Institution for Science, Stanford, CA 94305, USA.,Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - David Nogues-Bravo
- Center for Macroecology, Evolution and Climate, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
| | | | - Megan Ruffley
- Department of Plant Biology, Carnegie Institution for Science, Stanford, CA 94305, USA
| | - Jeffrey P Spence
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Sebastian E Toro Arana
- Department of Plant Biology, Carnegie Institution for Science, Stanford, CA 94305, USA.,Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Clemens L Weiß
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Erin Zess
- Department of Plant Biology, Carnegie Institution for Science, Stanford, CA 94305, USA
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12
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Robinson JA, Kyriazis CC, Nigenda-Morales SF, Beichman AC, Rojas-Bracho L, Robertson KM, Fontaine MC, Wayne RK, Lohmueller KE, Taylor BL, Morin PA. The critically endangered vaquita is not doomed to extinction by inbreeding depression. Science 2022; 376:635-639. [PMID: 35511971 PMCID: PMC9881057 DOI: 10.1126/science.abm1742] [Citation(s) in RCA: 38] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
In cases of severe wildlife population decline, a key question is whether recovery efforts will be impeded by genetic factors, such as inbreeding depression. Decades of excess mortality from gillnet fishing have driven Mexico's vaquita porpoise (Phocoena sinus) to ~10 remaining individuals. We analyzed whole-genome sequences from 20 vaquitas and integrated genomic and demographic information into stochastic, individual-based simulations to quantify the species' recovery potential. Our analysis suggests that the vaquita's historical rarity has resulted in a low burden of segregating deleterious variation, reducing the risk of inbreeding depression. Similarly, genome-informed simulations suggest that the vaquita can recover if bycatch mortality is immediately halted. This study provides hope for vaquitas and other naturally rare endangered species and highlights the utility of genomics in predicting extinction risk.
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Affiliation(s)
- Jacqueline A. Robinson
- Institute for Human Genetics, University of California, San Francisco; San Francisco, CA, USA
| | - Christopher C. Kyriazis
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles; Los Angeles, CA, USA
| | - Sergio F. Nigenda-Morales
- Advanced Genomics Unit, National Laboratory of Genomics for Biodiversity (Langebio), Center for Research and Advanced Studies (Cinvestav); Irapuato, Guanajuato, Mexico
| | | | - Lorenzo Rojas-Bracho
- Comisión Nacional de Áreas Naturales Protegidas/SEMARNAT; Ensenada, Mexico
- PNUD-Sinergia en la Comisión Nacional de Áreas Naturales Protegidas, Ensenada, B.C., México
| | - Kelly M. Robertson
- Southwest Fisheries Science Center, National Marine Fisheries Service, NOAA ; La Jolla, CA, USA
| | - Michael C. Fontaine
- MIVEGEC, Université de Montpellier, CNRS, IRD; Montpellier, France
- Centre de Recherche en Écologie et Évolution de la Santé (CREES); Montpellier, France
- Groningen Institute for Evolutionary Life Sciences (GELIFES), University of Groningen; Groningen, The Netherlands
| | - Robert K. Wayne
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles; Los Angeles, CA, USA
| | - Kirk E. Lohmueller
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles; Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles; Los Angeles, CA, USA
| | - Barbara L. Taylor
- Southwest Fisheries Science Center, National Marine Fisheries Service, NOAA ; La Jolla, CA, USA
| | - Phillip A. Morin
- Southwest Fisheries Science Center, National Marine Fisheries Service, NOAA ; La Jolla, CA, USA
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13
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Kyriazis CC, Wayne RK, Lohmueller KE. Strongly deleterious mutations are a primary determinant of extinction risk due to inbreeding depression. Evol Lett 2021; 5:33-47. [PMID: 33552534 PMCID: PMC7857301 DOI: 10.1002/evl3.209] [Citation(s) in RCA: 78] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 11/10/2020] [Accepted: 11/21/2020] [Indexed: 11/08/2022] Open
Abstract
Human-driven habitat fragmentation and loss have led to a proliferation of small and isolated plant and animal populations with high risk of extinction. One of the main threats to extinction in these populations is inbreeding depression, which is primarily caused by recessive deleterious mutations becoming homozygous due to inbreeding. The typical approach for managing these populations is to maintain high genetic diversity, increasingly by translocating individuals from large populations to initiate a "genetic rescue." However, the limitations of this approach have recently been highlighted by the demise of the gray wolf population on Isle Royale, which declined to the brink of extinction soon after the arrival of a migrant from the large mainland wolf population. Here, we use a novel population genetic simulation framework to investigate the role of genetic diversity, deleterious variation, and demographic history in mediating extinction risk due to inbreeding depression in small populations. We show that, under realistic models of dominance, large populations harbor high levels of recessive strongly deleterious variation due to these mutations being hidden from selection in the heterozygous state. As a result, when large populations contract, they experience a substantially elevated risk of extinction after these strongly deleterious mutations are exposed by inbreeding. Moreover, we demonstrate that, although genetic rescue is broadly effective as a means to reduce extinction risk, its effectiveness can be greatly increased by drawing migrants from small or moderate-sized source populations rather than large source populations due to smaller populations harboring lower levels of recessive strongly deleterious variation. Our findings challenge the traditional conservation paradigm that focuses on maximizing genetic diversity in small populations in favor of a view that emphasizes minimizing strongly deleterious variation. These insights have important implications for managing small and isolated populations in the increasingly fragmented landscape of the Anthropocene.
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Affiliation(s)
- Christopher C. Kyriazis
- Department of Ecology and Evolutionary BiologyUniversity of CaliforniaLos AngelesCalifornia90095
| | - Robert K. Wayne
- Department of Ecology and Evolutionary BiologyUniversity of CaliforniaLos AngelesCalifornia90095
| | - Kirk E. Lohmueller
- Department of Ecology and Evolutionary BiologyUniversity of CaliforniaLos AngelesCalifornia90095
- Interdepartmental Program in BioinformaticsUniversity of CaliforniaLos AngelesCalifornia90095
- Department of Human Genetics, David Geffen School of MedicineUniversity of CaliforniaLos AngelesCalifornia90095
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14
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Adrion JR, Cole CB, Dukler N, Galloway JG, Gladstein AL, Gower G, Kyriazis CC, Ragsdale AP, Tsambos G, Baumdicker F, Carlson J, Cartwright RA, Durvasula A, Gronau I, Kim BY, McKenzie P, Messer PW, Noskova E, Ortega-Del Vecchyo D, Racimo F, Struck TJ, Gravel S, Gutenkunst RN, Lohmueller KE, Ralph PL, Schrider DR, Siepel A, Kelleher J, Kern AD. A community-maintained standard library of population genetic models. eLife 2020; 9:e54967. [PMID: 32573438 PMCID: PMC7438115 DOI: 10.7554/elife.54967] [Citation(s) in RCA: 72] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Accepted: 06/15/2020] [Indexed: 12/18/2022] Open
Abstract
The explosion in population genomic data demands ever more complex modes of analysis, and increasingly, these analyses depend on sophisticated simulations. Recent advances in population genetic simulation have made it possible to simulate large and complex models, but specifying such models for a particular simulation engine remains a difficult and error-prone task. Computational genetics researchers currently re-implement simulation models independently, leading to inconsistency and duplication of effort. This situation presents a major barrier to empirical researchers seeking to use simulations for power analyses of upcoming studies or sanity checks on existing genomic data. Population genetics, as a field, also lacks standard benchmarks by which new tools for inference might be measured. Here, we describe a new resource, stdpopsim, that attempts to rectify this situation. Stdpopsim is a community-driven open source project, which provides easy access to a growing catalog of published simulation models from a range of organisms and supports multiple simulation engine backends. This resource is available as a well-documented python library with a simple command-line interface. We share some examples demonstrating how stdpopsim can be used to systematically compare demographic inference methods, and we encourage a broader community of developers to contribute to this growing resource.
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Affiliation(s)
- Jeffrey R Adrion
- Department of Biology and Institute of Ecology and Evolution, University of OregonEugeneUnited States
| | - Christopher B Cole
- Weatherall Institute of Molecular Medicine, University of OxfordOxfordUnited Kingdom
| | - Noah Dukler
- Simons Center for Quantitative Biology, Cold Spring Harbor LaboratoryCold Spring HarborUnited States
| | - Jared G Galloway
- Department of Biology and Institute of Ecology and Evolution, University of OregonEugeneUnited States
| | - Ariella L Gladstein
- Department of Genetics, University of North Carolina at Chapel HillChapel HillUnited States
| | - Graham Gower
- Lundbeck GeoGenetics Centre, Globe Institute, University of CopenhagenCopenhagenDenmark
| | - Christopher C Kyriazis
- Department of Ecology and Evolutionary Biology, University of California, Los AngelesLos AngelesUnited States
| | | | - Georgia Tsambos
- Melbourne Integrative Genomics, School of Mathematics and Statistics, University of MelbourneMelbourneAustralia
| | - Franz Baumdicker
- Department of Mathematical Stochastics, University of FreiburgFreiburgGermany
| | - Jedidiah Carlson
- Department of Genome Sciences, University of WashingtonSeattleUnited States
| | - Reed A Cartwright
- The Biodesign Institute and The School of Life Sciences, Arizona State UniversityTempeUnited States
| | - Arun Durvasula
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los AngelesLos AngelesUnited States
| | - Ilan Gronau
- The Efi Arazi School of Computer Science, Herzliya Interdisciplinary CenterHerzliyaIsrael
| | - Bernard Y Kim
- Department of Biology, Stanford UniversityStanfordUnited States
| | - Patrick McKenzie
- Department of Ecology, Evolution, and Environmental Biology, Columbia UniversityNew YorkUnited States
| | - Philipp W Messer
- Department of Computational BiologyCornell UniversityIthacaUnited States
| | - Ekaterina Noskova
- Computer Technologies Laboratory, ITMO UniversitySaint PetersburgRussian Federation
| | - Diego Ortega-Del Vecchyo
- International Laboratory for Human Genome Research, National Autonomous University of MexicoJuriquillaMexico
| | - Fernando Racimo
- Lundbeck GeoGenetics Centre, Globe Institute, University of CopenhagenCopenhagenDenmark
| | - Travis J Struck
- Departmentof Molecular and Cellular Biology, University of ArizonaTucsonUnited States
| | - Simon Gravel
- Department of Human Genetics, McGill UniversityMontrealCanada
| | - Ryan N Gutenkunst
- Departmentof Molecular and Cellular Biology, University of ArizonaTucsonUnited States
| | - Kirk E Lohmueller
- Department of Ecology and Evolutionary Biology, University of California, Los AngelesLos AngelesUnited States
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los AngelesLos AngelesUnited States
| | - Peter L Ralph
- Department of Biology and Institute of Ecology and Evolution, University of OregonEugeneUnited States
- Department of Mathematics, University of OregonEugeneUnited States
| | - Daniel R Schrider
- Department of Genetics, University of North Carolina at Chapel HillChapel HillUnited States
| | - Adam Siepel
- Simons Center for Quantitative Biology, Cold Spring Harbor LaboratoryCold Spring HarborUnited States
| | - Jerome Kelleher
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of OxfordOxfordUnited Kingdom
| | - Andrew D Kern
- Department of Biology and Institute of Ecology and Evolution, University of OregonEugeneUnited States
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15
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Kyriazis CC, Alam B, Wjodyla M, Hackett S, Hosner P, Mays HL, Heaney LR, Reddy S. Colonization and diversification of the white-browed shortwing (Aves: Muscicapidae: Brachypteryx montana) in the Philippines. Mol Phylogenet Evol 2018; 121:121-131. [PMID: 29305243 DOI: 10.1016/j.ympev.2017.12.025] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2017] [Revised: 12/01/2017] [Accepted: 12/24/2017] [Indexed: 10/18/2022]
Abstract
Molecular phylogenetic approaches have greatly improved our knowledge of the pattern and process of biological diversification across the globe; however, many regions remain poorly documented, even for well-studied vertebrate taxa. The Philippine archipelago, one of the least-studied 'biodiversity hotspots', is an ideal natural laboratory for investigating the factors driving diversification in an insular and geologically dynamic setting. We investigated the history and geography of diversification of the Philippine populations of a widespread montane bird, the White-browed Shortwing (Brachypteryx montana). Leveraging dense archipelago-wide sampling, we generated a multi-locus genetic dataset (one nuclear and two mtDNA markers), which we analyzed using phylogenetic, population genetic, and coalescent-based methods. Our results demonstrate that Philippine shortwings (1) likely colonized the Philippines from the Sunda Shelf to Mindanao in the late Miocene or Pliocene, (2) diversified across inter-island barriers into three divergent lineages during the Pliocene and early Pleistocene, (3) have not diversified within the largest island, Luzon, contrary to patterns observed in other montane taxa, and (4) colonized Palawan from the oceanic Philippines rather than from Borneo, challenging the assumption of Palawan functioning exclusively as a biogeographic extension of the Sunda Shelf. Additionally, our finding that divergent (c. 4.0 mya) lineages are coexisting in secondary sympatry on Mindanao without apparent gene flow suggests that the speciation process is likely complete for these shortwing lineages. Overall, these investigations provide insight into how topography and island boundaries influence diversification within remote oceanic archipelagos and echo the results of many other studies in demonstrating that taxonomic diversity continues to be underestimated in the Philippines.
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Affiliation(s)
- Christopher C Kyriazis
- Biology Department, Loyola University Chicago, 1050 W. Sheridan Road, Chicago, IL 60660, USA
| | - Bushra Alam
- Biology Department, Loyola University Chicago, 1050 W. Sheridan Road, Chicago, IL 60660, USA
| | - Mark Wjodyla
- Biology Department, Loyola University Chicago, 1050 W. Sheridan Road, Chicago, IL 60660, USA
| | - Shannon Hackett
- Field Museum of Natural History, 1400 S. Lake Shore Drive, Chicago, IL 60605, USA
| | - Peter Hosner
- Department of Biology, University of Florida, Gainesville, FL 32607, USA
| | - Herman L Mays
- Department of Biological Sciences, Marshall University, Huntington, WV 25755, USA; Cincinnati Museum Center, Cincinnati, OH 45203, USA
| | - Lawrence R Heaney
- Field Museum of Natural History, 1400 S. Lake Shore Drive, Chicago, IL 60605, USA
| | - Sushma Reddy
- Biology Department, Loyola University Chicago, 1050 W. Sheridan Road, Chicago, IL 60660, USA.
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