1
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Leigh DM, Vandergast AG, Hunter ME, Crandall ED, Funk WC, Garroway CJ, Hoban S, Oyler-McCance SJ, Rellstab C, Segelbacher G, Schmidt C, Vázquez-Domínguez E, Paz-Vinas I. Best practices for genetic and genomic data archiving. Nat Ecol Evol 2024; 8:1224-1232. [PMID: 38789640 DOI: 10.1038/s41559-024-02423-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 04/25/2024] [Indexed: 05/26/2024]
Abstract
Genetic and genomic data are collected for a vast array of scientific and applied purposes. Despite mandates for public archiving, data are typically used only by the generating authors. The reuse of genetic and genomic datasets remains uncommon because it is difficult, if not impossible, due to non-standard archiving practices and lack of contextual metadata. But as the new field of macrogenetics is demonstrating, if genetic data and their metadata were more accessible and FAIR (findable, accessible, interoperable and reusable) compliant, they could be reused for many additional purposes. We discuss the main challenges with existing genetic and genomic data archives, and suggest best practices for archiving genetic and genomic data. Recognizing that this is a longstanding issue due to little formal data management training within the fields of ecology and evolution, we highlight steps that research institutions and publishers could take to improve data archiving.
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Affiliation(s)
- Deborah M Leigh
- Swiss Federal Research Institute WSL, Birmensdorf, Switzerland.
| | - Amy G Vandergast
- US Geological Survey, Western Ecological Research Center, San Diego, CA, USA
| | - Margaret E Hunter
- US Geological Survey, Wetland & Aquatic Research Center, Gainesville, FL, USA
| | - Eric D Crandall
- Department of Biology, Pennsylvania State University, University Park, PA, USA
| | - W Chris Funk
- Department of Biology, Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO, USA
| | - Colin J Garroway
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Sean Hoban
- Center for Tree Science, The Morton Arboretum, Lisle, IL, USA
| | | | | | | | - Chloé Schmidt
- German Centre for Integrative Biodiversity Research Halle-Jena-Leipzig, Leipzig, Germany
| | - Ella Vázquez-Domínguez
- Departamento de Ecología de la Biodiversidad, Instituto de Ecología, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México
| | - Ivan Paz-Vinas
- Department of Biology, Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO, USA
- Universite Claude Bernard Lyon 1, LEHNA UMR 5023, CNRS, ENTPE, Villeurbanne, France
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2
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Ming Y, Ni G. A dataset of genetic diversity studies in the China Seas. Sci Data 2024; 11:235. [PMID: 38395909 PMCID: PMC10891114 DOI: 10.1038/s41597-024-03082-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 02/16/2024] [Indexed: 02/25/2024] Open
Abstract
Genetic diversity, a fundamental aspect of biodiversity, greatly influences the ecological and evolutionary characteristics of populations and species. Compiling genetic data is crucial as the initial step in comprehending and applying genetic resources; however, regional collating work is still insufficient, especially in marine ecosystems. Here, by conducting a thorough literature search and quality-control procedures, we provide a dataset of genetic diversity studies on marine species in the China Seas. The final dataset comprised a total of 746 studies (encompassing 840 data sets and 3658 populations) across 343 species from 1998 to 2022. For each data set, information including publication year, publication language, studied species, belonged taxonomic group, applied molecular markers, and sampling strategies (number of populations, total number of individuals, etc.) was collated to analyse the scope, strengths, and omissions of these works. This dataset offers a comprehensive overview of genetic diversity studies in the China Seas, which may help to adjust future research focuses, promote conservation and macrogenetics studies in this region, and also facilitate regional cooperation.
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Affiliation(s)
- Yaqian Ming
- Ministry of Education Key Laboratory of Mariculture, Ocean University of China, Qingdao, 266003, China
| | - Gang Ni
- Ministry of Education Key Laboratory of Mariculture, Ocean University of China, Qingdao, 266003, China.
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3
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Schmidt C, Hoban S, Jetz W. Conservation macrogenetics: harnessing genetic data to meet conservation commitments. Trends Genet 2023; 39:816-829. [PMID: 37648576 DOI: 10.1016/j.tig.2023.08.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 08/03/2023] [Accepted: 08/03/2023] [Indexed: 09/01/2023]
Abstract
Genetic biodiversity is rapidly gaining attention in global conservation policy. However, for almost all species, conservation relevant, population-level genetic data are lacking, limiting the extent to which genetic diversity can be used for conservation policy and decision-making. Macrogenetics is an emerging discipline that explores the patterns and processes underlying population genetic composition at broad taxonomic and spatial scales by aggregating and reanalyzing thousands of published genetic datasets. Here we argue that focusing macrogenetic tools on conservation needs, or conservation macrogenetics, will enhance decision-making for conservation practice and fill key data gaps for global policy. Conservation macrogenetics provides an empirical basis for better understanding the complexity and resilience of biological systems and, thus, how anthropogenic drivers and policy decisions affect biodiversity.
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Affiliation(s)
- Chloé Schmidt
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA; Center for Biodiversity and Global Change, Yale University, New Haven, CT, USA; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.
| | - Sean Hoban
- The Center for Tree Science, The Morton Arboretum, Lisle, IL, USA
| | - Walter Jetz
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA; Center for Biodiversity and Global Change, Yale University, New Haven, CT, USA
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4
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Schmidt C, Hoban S, Hunter M, Paz-Vinas I, Garroway CJ. Genetic diversity and IUCN Red List status. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2023:e14064. [PMID: 36751982 DOI: 10.1111/cobi.14064] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 01/11/2023] [Accepted: 01/18/2023] [Indexed: 06/18/2023]
Abstract
The International Union for Conservation of Nature (IUCN) Red List is an important and widely used tool for conservation assessment. The IUCN uses information about a species' range, population size, habitat quality and fragmentation levels, and trends in abundance to assess extinction risk. Genetic diversity is not considered, although it affects extinction risk. Declining populations are more strongly affected by genetic drift and higher rates of inbreeding, which can reduce the efficiency of selection, lead to fitness declines, and hinder species' capacities to adapt to environmental change. Given the importance of conserving genetic diversity, attempts have been made to find relationships between red-list status and genetic diversity. Yet, there is still no consensus on whether genetic diversity is captured by the current IUCN Red List categories in a way that is informative for conservation. To assess the predictive power of correlations between genetic diversity and IUCN Red List status in vertebrates, we synthesized previous work and reanalyzed data sets based on 3 types of genetic data: mitochondrial DNA, microsatellites, and whole genomes. Consistent with previous work, species with higher extinction risk status tended to have lower genetic diversity for all marker types, but these relationships were weak and varied across taxa. Regardless of marker type, genetic diversity did not accurately identify threatened species for any taxonomic group. Our results indicate that red-list status is not a useful metric for informing species-specific decisions about the protection of genetic diversity and that genetic data cannot be used to identify threat status in the absence of demographic data. Thus, there is a need to develop and assess metrics specifically designed to assess genetic diversity and inform conservation policy, including policies recently adopted by the UN's Convention on Biological Diversity Kunming-Montreal Global Biodiversity Framework.
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Affiliation(s)
- Chloé Schmidt
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut, USA
- Center for Biodiversity and Global Change, Yale University, New Haven, Connecticut, USA
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
| | - Sean Hoban
- The Center for Tree Science, The Morton Arboretum, Lisle, Illinois, USA
| | - Margaret Hunter
- Wetland and Aquatic Research Center, U.S. Geological Survey, Gainesville, Florida, USA
| | - Ivan Paz-Vinas
- Laboratoire Evolution et Diversité Biologique (EDB), UMR5174, Université Toulouse 3 Paul Sabatier, CNRS, IRD, Toulouse, France
| | - Colin J Garroway
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
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5
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Liggins L, Arranz V, Braid HE, Carmelet-Rescan D, Elleouet J, Egorova E, Gemmell MR, Hills SFK, Holland LP, Koot EM, Lischka A, Maxwell KH, McCartney LJ, Nguyen HTT, Noble C, Olmedo Rojas P, Parvizi E, Pearman WS, Sweatman JAN, Kaihoro TR, Walton K, Aguirre JD, Stewart LC. The future of molecular ecology in Aotearoa New Zealand: an early career perspective. J R Soc N Z 2022. [DOI: 10.1080/03036758.2022.2097709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Affiliation(s)
- Libby Liggins
- School of Natural Sciences, Massey University, Auckland, New Zealand
| | - Vanessa Arranz
- School of Natural Sciences, Massey University, Auckland, New Zealand
| | - Heather E. Braid
- AUT Lab for Cephalopod Ecology and Systematics, School of Science, Auckland University of Technology, Auckland, New Zealand
| | | | | | - Ekaterina Egorova
- Massey Geoinformatics Collaboratory, School of Mathematical and Computational Sciences, Auckland, New Zealand
| | - Michael R. Gemmell
- Plant Health and Environment Lab, Ministry for Primary Industries, Auckland, New Zealand
| | - Simon F. K. Hills
- Ngāti Porou
- School of Natural Sciences, Massey University, Palmerston North, New Zealand
| | | | - Emily M. Koot
- The New Zealand Institute for Plant and Food Research Ltd, Palmerston North, New Zealand
| | - Alexandra Lischka
- AUT Lab for Cephalopod Ecology and Systematics, School of Science, Auckland University of Technology, Auckland, New Zealand
| | - Kimberley H. Maxwell
- Ngāti Porou
- Te Whakatōhea, Te Whānau-a-Apanui, Ngāitai, Ngāti Tūwharetoa
- Te Kōtahi Research Institute, Faculty of Māori and Indigenous Studies, University of Waikato, Hamilton, New Zealand
| | | | - Hang T. T. Nguyen
- Faculty of Fisheries, University of Agriculture and Forestry, Hue University, Vietnam
| | - Cory Noble
- School of Natural Sciences, Massey University, Auckland, New Zealand
| | | | - Elahe Parvizi
- School of Science, University of Waikato, Hamilton, New Zealand
| | | | | | | | - Kerry Walton
- Department of Zoology, University of Otago, Dunedin, New Zealand
| | - J. David Aguirre
- School of Natural Sciences, Massey University, Auckland, New Zealand
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6
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CaliPopGen: A genetic and life history database for the fauna and flora of California. Sci Data 2022; 9:380. [PMID: 35790740 PMCID: PMC9256587 DOI: 10.1038/s41597-022-01479-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 06/20/2022] [Indexed: 11/13/2022] Open
Abstract
CaliPopGen is a database of population genetic data for native and naturalized eukaryotic species in California, USA. It summarizes the published literature (1985–2020) for 5,453 unique populations with genetic data from more than 187,394 individuals and 448 species (513 species plus subspecies) across molecular markers including allozymes, RFLPs, mtDNA, microsatellites, nDNA, and SNPs. Terrestrial habitats accounted for the majority (46.4%) of the genetic data. Taxonomic groups with the greatest representation were Magnoliophyta (20.31%), Insecta (13.4%), and Actinopterygii (12.85%). CaliPopGen also reports life-history data for most included species to enable analyses of the drivers of genetic diversity across the state. The large number of populations and wide taxonomic breadth will facilitate explorations of ecological patterns and processes across the varied geography of California. CaliPopGen covers all terrestrial and marine ecoregions of California and has a greater density of species and georeferenced populations than any previously published population genetic database. It is thus uniquely suited to inform conservation management at the regional and state levels across taxonomic groups. Measurement(s) | genetic variation | Technology Type(s) | DNA sequencing | Factor Type(s) | Kingdom • Phylum • TaxonGroup • MarkerType • SampleSize • GeneTarget • NumMarkers • YearStart • YearEnd • PopName • LongitudeDD • LatitudeDD • CoordError • HabitatType • Lifespan • Fecundity • LifetimeReprodOutput • AgeSexMat • NumBreedingEvents • ReprodMode • BodyLength • AdultMass • CANativeStatus • CESAStatus • SSCStatus • ESAStatus • LifeCycle • AdultHeight • SelfCompatibility • MonoeciousDioecious • Asexual • PollinationMode • SeedDispMode • MassPerSeed • CAEndemicStatus | Sample Characteristic - Organism | eukaryota | Sample Characteristic - Location | California |
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7
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Schmidt C, Muñoz G, Lancaster LT, Lessard JP, Marske KA, Marshall KE, Garroway CJ. Population demography maintains biogeographic boundaries. Ecol Lett 2022; 25:1905-1913. [PMID: 35753949 DOI: 10.1111/ele.14058] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 05/11/2022] [Accepted: 05/24/2022] [Indexed: 11/27/2022]
Abstract
Global biodiversity is organised into biogeographic regions that comprise distinct biotas. The contemporary factors maintaining differences in species composition between regions are poorly understood. Given evidence that populations with sufficient genetic variation can adapt to fill new habitats, it is surprising that more homogenisation of species assemblages across regions has not occurred. Theory suggests that expansion across biogeographic regions could be limited by reduced adaptive capacity due to demographic variation along environmental gradients, but this possibility has not been empirically explored. Using three independently curated data sets describing continental patterns of mammalian demography and population genetics, we show that populations near biogeographic boundaries have lower effective population sizes and genetic diversity, and are more genetically differentiated. These patterns are consistent with reduced adaptive capacity in areas where one biogeographic region transitions into the next. That these patterns are replicated across mammals suggests they are stable and generalisable in their contribution to long-term limits on biodiversity homogenisation. Understanding the contemporary processes that maintain compositional differences among regional biotas is crucial for our understanding of the current and future organisation of global biodiversity.
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Affiliation(s)
- Chloé Schmidt
- Department of Biological Sciences, University of Manitoba, Winnipeg, Canada
| | - Gabriel Muñoz
- Faculty of Arts and Sciences, Department of Biology, Concordia University, Montréal, Canada
| | | | - Jean-Philippe Lessard
- Faculty of Arts and Sciences, Department of Biology, Concordia University, Montréal, Canada
| | | | - Katie E Marshall
- Department of Zoology, University of British Columbia, Vancouver, Canada
| | - Colin J Garroway
- Department of Biological Sciences, University of Manitoba, Winnipeg, Canada
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8
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Hoban S, Archer FI, Bertola LD, Bragg JG, Breed MF, Bruford MW, Coleman MA, Ekblom R, Funk WC, Grueber CE, Hand BK, Jaffé R, Jensen E, Johnson JS, Kershaw F, Liggins L, MacDonald AJ, Mergeay J, Miller JM, Muller-Karger F, O'Brien D, Paz-Vinas I, Potter KM, Razgour O, Vernesi C, Hunter ME. Global genetic diversity status and trends: towards a suite of Essential Biodiversity Variables (EBVs) for genetic composition. Biol Rev Camb Philos Soc 2022; 97:1511-1538. [PMID: 35415952 PMCID: PMC9545166 DOI: 10.1111/brv.12852] [Citation(s) in RCA: 39] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Revised: 02/25/2022] [Accepted: 03/02/2022] [Indexed: 12/14/2022]
Abstract
Biodiversity underlies ecosystem resilience, ecosystem function, sustainable economies, and human well‐being. Understanding how biodiversity sustains ecosystems under anthropogenic stressors and global environmental change will require new ways of deriving and applying biodiversity data. A major challenge is that biodiversity data and knowledge are scattered, biased, collected with numerous methods, and stored in inconsistent ways. The Group on Earth Observations Biodiversity Observation Network (GEO BON) has developed the Essential Biodiversity Variables (EBVs) as fundamental metrics to help aggregate, harmonize, and interpret biodiversity observation data from diverse sources. Mapping and analyzing EBVs can help to evaluate how aspects of biodiversity are distributed geographically and how they change over time. EBVs are also intended to serve as inputs and validation to forecast the status and trends of biodiversity, and to support policy and decision making. Here, we assess the feasibility of implementing Genetic Composition EBVs (Genetic EBVs), which are metrics of within‐species genetic variation. We review and bring together numerous areas of the field of genetics and evaluate how each contributes to global and regional genetic biodiversity monitoring with respect to theory, sampling logistics, metadata, archiving, data aggregation, modeling, and technological advances. We propose four Genetic EBVs: (i) Genetic Diversity; (ii) Genetic Differentiation; (iii) Inbreeding; and (iv) Effective Population Size (Ne). We rank Genetic EBVs according to their relevance, sensitivity to change, generalizability, scalability, feasibility and data availability. We outline the workflow for generating genetic data underlying the Genetic EBVs, and review advances and needs in archiving genetic composition data and metadata. We discuss how Genetic EBVs can be operationalized by visualizing EBVs in space and time across species and by forecasting Genetic EBVs beyond current observations using various modeling approaches. Our review then explores challenges of aggregation, standardization, and costs of operationalizing the Genetic EBVs, as well as future directions and opportunities to maximize their uptake globally in research and policy. The collection, annotation, and availability of genetic data has made major advances in the past decade, each of which contributes to the practical and standardized framework for large‐scale genetic observation reporting. Rapid advances in DNA sequencing technology present new opportunities, but also challenges for operationalizing Genetic EBVs for biodiversity monitoring regionally and globally. With these advances, genetic composition monitoring is starting to be integrated into global conservation policy, which can help support the foundation of all biodiversity and species' long‐term persistence in the face of environmental change. We conclude with a summary of concrete steps for researchers and policy makers for advancing operationalization of Genetic EBVs. The technical and analytical foundations of Genetic EBVs are well developed, and conservation practitioners should anticipate their increasing application as efforts emerge to scale up genetic biodiversity monitoring regionally and globally.
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Affiliation(s)
- Sean Hoban
- Center for Tree Science, The Morton Arboretum, 4100 Illinois Rt 53, Lisle, IL, 60532, USA
| | - Frederick I Archer
- Southwest Fisheries Science Center, NOAA/NMFS, 8901 La Jolla Shores Drive, La Jolla, CA, 92037, USA
| | - Laura D Bertola
- City College of New York, 160 Convent Avenue, New York, NY, 10031, USA
| | - Jason G Bragg
- Research Centre for Ecosystem Resilience, Australian Institute of Botanical Science, The Royal Botanic Garden Sydney, Mrs Macquaries Rd, Sydney, NSW, 2000, Australia
| | - Martin F Breed
- College of Science and Engineering, Flinders University, University Drive, Bedford Park, SA, 5042, Australia
| | - Michael W Bruford
- School of Biosciences, Cardiff University, Cathays Park, Cardiff, CF10 3AX, Wales, UK
| | - Melinda A Coleman
- Department of Primary Industries, New South Wales Fisheries, National Marine Science Centre, 2 Bay Drive, Coffs Harbour, NSW, 2450, Australia
| | - Robert Ekblom
- Wildlife Analysis Unit, Swedish Environmental Protection Agency, Blekholmsterrassen 36, Stockholm, SE-106 48, Sweden
| | - W Chris Funk
- Department of Biology, Graduate Degree in Ecology, Colorado State University, 1878 Campus Delivery, Fort Collins, CO, 80523-1878, USA
| | - Catherine E Grueber
- School of Life and Environmental Sciences, Faculty of Science, The University of Sydney, Carslaw Building, Sydney, NSW, 2006, Australia
| | - Brian K Hand
- Flathead Lake Biological Station, 32125 Bio Station Ln, Polson, MT, 59860, USA
| | - Rodolfo Jaffé
- Exponent, 15375 SE 30th Place, Suite 250, Bellevue, WA, 98007, USA
| | - Evelyn Jensen
- School of Natural and Environmental Sciences, Newcastle University, Agriculture Building, Newcastle Upon Tyne, NE1 7RU, UK
| | - Jeremy S Johnson
- Department of Environmental Studies, Prescott College, 220 Grove Avenue, Prescott, AZ, 86303, USA
| | - Francine Kershaw
- Natural Resources Defense Council, 40 West 20th Street, New York, NY, 10011, USA
| | - Libby Liggins
- School of Natural Sciences, Massey University, Ōtehā Rohe campus, Gate 4 Albany Highway, Auckland, Aotearoa, 0745, New Zealand
| | - Anna J MacDonald
- Research School of Biology, The Australian National University, Acton, ACT, 2601, Australia
| | - Joachim Mergeay
- Research Institute for Nature and Forest, Gaverstraat 4, 9500, Geraardsbergen, Belgium.,Aquatic Ecology, Evolution and Conservation, KULeuven, Charles Deberiotstraat 32, box 2439, 3000, Leuven, Belgium
| | - Joshua M Miller
- Department of Biological Sciences, MacEwan University, 10700 104 Avenue, Edmonton, AB, T5J 4S2, Canada
| | - Frank Muller-Karger
- College of Marine Science, University of South Florida, 140 7th Avenue South, Saint Petersburg, Florida, 33701, USA
| | - David O'Brien
- NatureScot, Great Glen House, Leachkin Road, Inverness, IV3 8NW, UK
| | - Ivan Paz-Vinas
- Laboratoire Evolution et Diversité Biologique, Université de Toulouse, CNRS, IRD, UPS, UMR-5174 EDB, 118 route de Narbonne, Toulouse, 31062, France
| | - Kevin M Potter
- Department of Forestry and Environmental Resources, North Carolina State University, 3041 Cornwallis Road, Research Triangle Park, NC, 27709, USA
| | - Orly Razgour
- Biosciences, University of Exeter, Streatham Campus, Hatherly Laboratories, Prince of Wales Road, Exeter, EX4 4PS, UK
| | - Cristiano Vernesi
- Forest Ecology Unit, Research and Innovation Centre- Fondazione Edmund Mach, Via E. Mach, 1, San Michele all'Adige, 38010, (TN), Italy
| | - Margaret E Hunter
- U.S. Geological Survey, Wetland and Aquatic Research Center, 7920 NW 71st Street, Gainesville, FL, 32653, USA
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Diversity of Land Snail Tribe Helicini (Gastropoda: Stylommatophora: Helicidae): Where Do We Stand after 20 Years of Sequencing Mitochondrial Markers? DIVERSITY 2021. [DOI: 10.3390/d14010024] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Sequences of mitochondrial genes revolutionized the understanding of animal diversity and continue to be an important tool in biodiversity research. In the tribe Helicini, a prominent group of the western Palaearctic land snail fauna, mitochondrial data accumulating since the 2000s helped to newly delimit genera, inform species-level taxonomy and reconstruct past range dynamics. We combined the published data with own unpublished sequences and provide a detailed overview of what they revealed about the diversity of the group. The delimitation of Helix is revised by placing Helix godetiana back in the genus and new synonymies are suggested within the genera Codringtonia and Helix. The spatial distribution of intraspecific mitochondrial lineages of several species is shown for the first time. Comparisons between species reveal considerable variation in distribution patterns of intraspecific lineages, from broad postglacial distributions to regions with a fine-scale pattern of allopatric lineage replacement. To provide a baseline for further research and information for anyone re-using the data, we thoroughly discuss the gaps in the current dataset, focusing on both taxonomic and geographic coverage. Thanks to the wealth of data already amassed and the relative ease with which they can be obtained, mitochondrial sequences remain an important source of information on intraspecific diversity over large areas and taxa.
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Kittlein MJ, Mora MS, Mapelli FJ, Austrich A, Gaggiotti OE. Deep learning and satellite imagery predict genetic diversity and differentiation. Methods Ecol Evol 2021. [DOI: 10.1111/2041-210x.13775] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Marcelo J. Kittlein
- Departamento de Biología Instituto de Investigaciones Marinas y Costeras (IIMyC) Facultad de Ciencias Exáctas y Naturales Universidad Nacional de Mar del Plata Consejo Nacional de Investigaciones Científica y Técnicas (CONICET) Mar del Plata Argentina
| | - Matías S. Mora
- Departamento de Biología Instituto de Investigaciones Marinas y Costeras (IIMyC) Facultad de Ciencias Exáctas y Naturales Universidad Nacional de Mar del Plata Consejo Nacional de Investigaciones Científica y Técnicas (CONICET) Mar del Plata Argentina
| | - Fernando J. Mapelli
- Grupo de Genética y Ecología en Conservación y Biodiversidad (GECOBI) División Mastozoología Museo Argentino de Ciencias Naturales ‘Bernardino Rivadavia’ (CONICET) Ciudad de Buenos Aires Argentina
| | - Ailín Austrich
- Departamento de Biología Instituto de Investigaciones Marinas y Costeras (IIMyC) Facultad de Ciencias Exáctas y Naturales Universidad Nacional de Mar del Plata Consejo Nacional de Investigaciones Científica y Técnicas (CONICET) Mar del Plata Argentina
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11
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Puckett EE, Davis IS. Spatial patterns of genetic diversity in eight bear (Ursidae) species. URSUS 2021. [DOI: 10.2192/ursus-d-20-00029.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Affiliation(s)
- Emily E. Puckett
- Department of Biological Sciences, University of Memphis, Memphis, TN 38152, USA
| | - Isis S. Davis
- Department of Biological Sciences, University of Memphis, Memphis, TN 38152, USA
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12
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Overcast I, Ruffley M, Rosindell J, Harmon L, Borges PAV, Emerson BC, Etienne RS, Gillespie R, Krehenwinkel H, Mahler DL, Massol F, Parent CE, Patiño J, Peter B, Week B, Wagner C, Hickerson MJ, Rominger A. A unified model of species abundance, genetic diversity, and functional diversity reveals the mechanisms structuring ecological communities. Mol Ecol Resour 2021; 21:2782-2800. [PMID: 34569715 PMCID: PMC9297962 DOI: 10.1111/1755-0998.13514] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 09/01/2021] [Accepted: 09/07/2021] [Indexed: 11/30/2022]
Abstract
Biodiversity accumulates hierarchically by means of ecological and evolutionary processes and feedbacks. Within ecological communities drift, dispersal, speciation, and selection operate simultaneously to shape patterns of biodiversity. Reconciling the relative importance of these is hindered by current models and inference methods, which tend to focus on a subset of processes and their resulting predictions. Here we introduce massive ecoevolutionary synthesis simulations (MESS), a unified mechanistic model of community assembly, rooted in classic island biogeography theory, which makes temporally explicit joint predictions across three biodiversity data axes: (i) species richness and abundances, (ii) population genetic diversities, and (iii) trait variation in a phylogenetic context. Using simulations we demonstrate that each data axis captures information at different timescales, and that integrating these axes enables discriminating among previously unidentifiable community assembly models. MESS is unique in generating predictions of community-scale genetic diversity, and in characterizing joint patterns of genetic diversity, abundance, and trait values. MESS unlocks the full potential for investigation of biodiversity processes using multidimensional community data including a genetic component, such as might be produced by contemporary eDNA or metabarcoding studies. We combine MESS with supervised machine learning to fit the parameters of the model to real data and infer processes underlying how biodiversity accumulates, using communities of tropical trees, arthropods, and gastropods as case studies that span a range of data availability scenarios, and spatial and taxonomic scales.
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Affiliation(s)
- Isaac Overcast
- Biology DepartmentGraduate Center of the City University of New YorkNew YorkNew YorkUSA
- Biology DepartmentCity College of New YorkNew YorkNew YorkUSA
- Division of Vertebrate ZoologyAmerican Museum of Natural HistoryNew YorkUSA
| | - Megan Ruffley
- Department of Biological SciencesUniversity of IdahoMoscowIdahoUSA
- Institute for Bioinformatics and Evolutionary Studies (IBEST)University of IdahoMoscowIdahoUSA
| | - James Rosindell
- Department of Life SciencesImperial College LondonAscotBerkshireUK
| | - Luke Harmon
- Department of Biological SciencesUniversity of IdahoMoscowIdahoUSA
| | - Paulo A. V. Borges
- Centre for Ecology, Evolution and Environmental Changes/Azorean Biodiversity GroupFaculdade de Ciências Agrárias e do AmbienteUniversidade dos AçoresAçoresPortugal
| | - Brent C. Emerson
- Island Ecology and Evolution Research GroupInstitute of Natural Products and AgrobiologyIPNA‐CSIC)La Laguna, TenerifeCanary IslandsSpain
| | - Rampal S. Etienne
- Groningen Institute for Evolutionary Life SciencesUniversity of GroningenGroningenThe Netherlands
| | - Rosemary Gillespie
- Department of Environmental Science, Policy, and ManagementUniversity of CaliforniaBerkeleyCaliforniaUSA
| | | | - D. Luke Mahler
- Department of Ecology and Evolutionary BiologyUniversity of TorontoTorontoOntarioCanada
| | - Francois Massol
- CNRSInsermCHU LilleUniversity of LilleLilleFrance
- Center for Infection and Immunity of LilleInstitut Pasteur de LilleLilleFrance
- CNRSEvo‐Eco‐PaleoSPICI GroupUniversity of LilleLilleFrance
| | - Christine E. Parent
- Department of Biological SciencesUniversity of IdahoMoscowIdahoUSA
- Institute for Bioinformatics and Evolutionary Studies (IBEST)University of IdahoMoscowIdahoUSA
| | - Jairo Patiño
- Island Ecology and Evolution Research GroupInstitute of Natural Products and AgrobiologyIPNA‐CSIC)La Laguna, TenerifeCanary IslandsSpain
- Plant Conservation and Biogeography GroupDepartamento de BotánicaEcología y Fisiología VegetalFacultad de CienciasUniversidad de La LagunaTenerifeIslas CanariasSpain
| | - Ben Peter
- Group of Genetic Diversity through Space and TimeDepartment of Evolutionary GeneticsMax Planck Institute for Evolutionary AnthropologyLeipzigGermany
| | - Bob Week
- Department of Biological SciencesUniversity of IdahoMoscowIdahoUSA
| | - Catherine Wagner
- Department of Botany and Biodiversity InstituteUniversity of WyomingLaramieWyomingUSA
| | - Michael J. Hickerson
- Biology DepartmentGraduate Center of the City University of New YorkNew YorkNew YorkUSA
- Biology DepartmentCity College of New YorkNew YorkNew YorkUSA
- Division of Invertebrate ZoologyAmerican Museum of Natural HistoryNew YorkNew YorkUSA
| | - Andrew Rominger
- School of Biology and EcologyUniversity of MaineOronoMaineUSA
- Maine Center for Genetics in the EnvironmentUniversity of MaineOronoMaineUSA
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13
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Abstract
The rapidly emerging field of macrogenetics focuses on analysing publicly accessible genetic datasets from thousands of species to explore large-scale patterns and predictors of intraspecific genetic variation. Facilitated by advances in evolutionary biology, technology, data infrastructure, statistics and open science, macrogenetics addresses core evolutionary hypotheses (such as disentangling environmental and life-history effects on genetic variation) with a global focus. Yet, there are important, often overlooked, limitations to this approach and best practices need to be considered and adopted if macrogenetics is to continue its exciting trajectory and reach its full potential in fields such as biodiversity monitoring and conservation. Here, we review the history of this rapidly growing field, highlight knowledge gaps and future directions, and provide guidelines for further research.
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Habrich AK, Lawrence ER, Fraser DJ. Varying genetic imprints of road networks and human density in North American mammal populations. Evol Appl 2021; 14:1659-1672. [PMID: 34178111 PMCID: PMC8210797 DOI: 10.1111/eva.13232] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2020] [Revised: 03/10/2021] [Accepted: 03/12/2021] [Indexed: 11/28/2022] Open
Abstract
Road networks and human density are major factors contributing to habitat fragmentation and loss, isolation of wildlife populations, and reduced genetic diversity. Terrestrial mammals are particularly sensitive to road networks and encroachment by human populations. However, there are limited assessments of the impacts of road networks and human density on population-specific nuclear genetic diversity, and it remains unclear how these impacts are modulated by life-history traits. Using generalized linear mixed models and microsatellite data from 1444 North American terrestrial mammal populations, we show that taxa with large home range sizes, dense populations, and large body sizes had reduced nuclear genetic diversity with increasing road impacts and human density, but the overall influence of life-history traits was generally weak. Instead, we observed a high degree of genus-specific variation in genetic responses to road impacts and human density. Human density negatively affected allelic diversity or heterozygosity more than road networks (13 vs. 5-7 of 25 assessed genera, respectively); increased road networks and human density also positively affected allelic diversity and heterozygosity in 15 and 6-9 genera, respectively. Large-bodied, human-averse species were generally more negatively impacted than small, urban-adapted species. Genus-specific responses to habitat fragmentation by ongoing road development and human encroachment likely depend on the specific capability to (i) navigate roads as either barriers or movement corridors, and (ii) exploit resource-rich urban environments. The nonuniform genetic response to roads and human density highlights the need to implement efforts to mitigate the risk of vehicular collisions, while also facilitating gene flow between populations of particularly vulnerable taxa.
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Affiliation(s)
- Andrew K. Habrich
- Department of BiologyConcordia UniversityMontrealQuebecCanada
- Department of BiologyCarleton UniversityOttawaOntarioCanada
| | | | - Dylan J. Fraser
- Department of BiologyConcordia UniversityMontrealQuebecCanada
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15
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Authors’ Reply to Letter to the Editor: Continued improvement to genetic diversity indicator for CBD. CONSERV GENET 2021. [DOI: 10.1007/s10592-021-01359-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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16
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Hanson JO, Veríssimo A, Velo‐Antón G, Marques A, Camacho‐Sanchez M, Martínez‐Solano Í, Gonçalves H, Sequeira F, Possingham HP, Carvalho SB. Evaluating surrogates of genetic diversity for conservation planning. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2021; 35:634-642. [PMID: 32761662 PMCID: PMC8048567 DOI: 10.1111/cobi.13602] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 07/16/2020] [Accepted: 07/23/2020] [Indexed: 05/13/2023]
Abstract
Protected-area systems should conserve intraspecific genetic diversity. Because genetic data require resources to obtain, several approaches have been proposed for generating plans for protected-area systems (prioritizations) when genetic data are not available. Yet such surrogate-based approaches remain poorly tested. We evaluated the effectiveness of potential surrogate-based approaches based on microsatellite genetic data collected across the Iberian Peninsula for 7 amphibian and 3 reptilian species. Long-term environmental suitability did not effectively represent sites containing high genetic diversity (allelic richness). Prioritizations based on long-term environmental suitability had similar performance to random prioritizations. Geographic distances and resistance distances based on contemporary environmental suitability were not always effective surrogates for identification of combinations of sites that contain individuals with different genetic compositions. Our results demonstrate that population genetic data based on commonly used neutral markers can inform prioritizations, and we could not find an adequate substitute. Conservation planners need to weigh the potential benefits of genetic data against their acquisition costs.
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Affiliation(s)
- Jeffrey O. Hanson
- CIBIO/InBIO, Centro de Investigação em Biodiversidade e Recursos GenéticosUniversidade do PortoCampus de Vairão, Rua Padre Armando Quintas, no. 7Vairão4485‐661Portugal
| | - Ana Veríssimo
- CIBIO/InBIO, Centro de Investigação em Biodiversidade e Recursos GenéticosUniversidade do PortoCampus de Vairão, Rua Padre Armando Quintas, no. 7Vairão4485‐661Portugal
| | - Guillermo Velo‐Antón
- CIBIO/InBIO, Centro de Investigação em Biodiversidade e Recursos GenéticosUniversidade do PortoCampus de Vairão, Rua Padre Armando Quintas, no. 7Vairão4485‐661Portugal
| | - Adam Marques
- CIBIO/InBIO, Centro de Investigação em Biodiversidade e Recursos GenéticosUniversidade do PortoCampus de Vairão, Rua Padre Armando Quintas, no. 7Vairão4485‐661Portugal
| | - Miguel Camacho‐Sanchez
- CIBIO/InBIO, Centro de Investigação em Biodiversidade e Recursos GenéticosUniversidade do PortoCampus de Vairão, Rua Padre Armando Quintas, no. 7Vairão4485‐661Portugal
| | - Íñigo Martínez‐Solano
- CIBIO/InBIO, Centro de Investigação em Biodiversidade e Recursos GenéticosUniversidade do PortoCampus de Vairão, Rua Padre Armando Quintas, no. 7Vairão4485‐661Portugal
- Museo Nacional de Ciencias Naturales‐CSICCalle de José Gutiérrez Abascal2Madrid28006Spain
| | - Helena Gonçalves
- CIBIO/InBIO, Centro de Investigação em Biodiversidade e Recursos GenéticosUniversidade do PortoCampus de Vairão, Rua Padre Armando Quintas, no. 7Vairão4485‐661Portugal
- Museu de História Natural e da CiênciaUniversidade do PortoPraça Gomes TeixeiraPorto4099‐002Portugal
| | - Fernando Sequeira
- CIBIO/InBIO, Centro de Investigação em Biodiversidade e Recursos GenéticosUniversidade do PortoCampus de Vairão, Rua Padre Armando Quintas, no. 7Vairão4485‐661Portugal
| | - Hugh P. Possingham
- The Nature ConservancyMinneapolisMN55415U.S.A.
- Centre for Biodiversity and Conservation Science, School of Biological SciencesThe University of QueenslandBrisbaneQLD 4072Australia
| | - Silvia B. Carvalho
- CIBIO/InBIO, Centro de Investigação em Biodiversidade e Recursos GenéticosUniversidade do PortoCampus de Vairão, Rua Padre Armando Quintas, no. 7Vairão4485‐661Portugal
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17
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Paz-Vinas I, Jensen EL, Bertola LD, Breed MF, Hand BK, Hunter ME, Kershaw F, Leigh DM, Luikart G, Mergeay J, Miller JM, Van Rees CB, Segelbacher G, Hoban S. Macrogenetic studies must not ignore limitations of genetic markers and scale. Ecol Lett 2021; 24:1282-1284. [PMID: 33749962 DOI: 10.1111/ele.13732] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 11/14/2020] [Accepted: 12/06/2020] [Indexed: 11/30/2022]
Abstract
Millette et al. (Ecology Letters, 2020, 23:55-67) reported no consistent worldwide anthropogenic effects on animal genetic diversity using repurposed mitochondrial DNA sequences. We reexamine data from this study, describe genetic marker and scale limitations which might lead to misinterpretations with conservation implications, and provide advice to improve future macrogenetic studies.
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Affiliation(s)
- Ivan Paz-Vinas
- Laboratoire Evolution & Diversité Biologique, Centre National pour la Recherche Scientifique, Institut de Recherche pour le Développement, Université de Toulouse, UPS, CNRS, IRD, UMR 5174, 118 route de Narbonne, Toulouse, 31062, France.,Laboratoire Ecologie Fonctionnelle et Environnement, Université de Toulouse, UPS, CNRS, INP, UMR 5245, 118 route de Narbonne, Toulouse, 31062, France
| | - Evelyn L Jensen
- Department of Ecology and Evolutionary Biology, Yale University, 21 Sachem St, New Haven, CT, 06520, USA
| | - Laura D Bertola
- City College of New York, 160 Convent Ave, New York, NY, 10031, USA
| | - Martin F Breed
- College of Science and Engineering, Flinders University, Bedford Park, SA, 5042, Australia
| | - Brian K Hand
- Flathead Lake Biological Station, 32125 Bio Station Ln, Polson, MT, 59860, USA
| | - Margaret E Hunter
- U.S. Geological Survey, Wetland and Aquatic Research Center, 7920 NW 71st St, Gainesville, FL, 32653, USA
| | - Francine Kershaw
- Natural Resources Defense Council, 40 West 20th Street, New York, NY, 10011, USA
| | - Deborah M Leigh
- WSL Swiss Federal Research Institute, Zürcherstrasse 111, Birmensdorf, 8903, Switzerland
| | - Gordon Luikart
- Flathead Lake Biological Station, 32125 Bio Station Ln, Polson, MT, 59860, USA
| | - Joachim Mergeay
- Research Institute for Nature and Forest, Gaverstraat 4, Geraardsbergen, 9500, Belgium.,Aquatic Ecology, Evolution and Conservation, KULeuven, Charles Deberiotstraat 32, box 2439, Leuven, 3000, Belgium
| | - Joshua M Miller
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
| | - Charles B Van Rees
- Flathead Lake Biological Station, 32125 Bio Station Ln, Polson, MT, 59860, USA
| | - Gernot Segelbacher
- Chair of Wildlife Ecology and Management, University Freiburg, Tennenbacher Str. 4, Freiburg, D-79106, Germany
| | - Sean Hoban
- Center for Tree Science, The Morton Arboretum, 4100 Illinois Rt 53, Lisle, 60532, USA
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18
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Riginos C, Crandall ED, Liggins L, Gaither MR, Ewing RB, Meyer C, Andrews KR, Euclide PT, Titus BM, Therkildsen NO, Salces-Castellano A, Stewart LC, Toonen RJ, Deck J. Building a global genomics observatory: Using GEOME (the Genomic Observatories Metadatabase) to expedite and improve deposition and retrieval of genetic data and metadata for biodiversity research. Mol Ecol Resour 2020; 20:1458-1469. [PMID: 33031625 DOI: 10.1111/1755-0998.13269] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2020] [Revised: 07/22/2020] [Accepted: 09/09/2020] [Indexed: 11/30/2022]
Abstract
Genetic data represent a relatively new frontier for our understanding of global biodiversity. Ideally, such data should include both organismal DNA-based genotypes and the ecological context where the organisms were sampled. Yet most tools and standards for data deposition focus exclusively either on genetic or ecological attributes. The Genomic Observatories Metadatabase (GEOME: geome-db.org) provides an intuitive solution for maintaining links between genetic data sets stored by the International Nucleotide Sequence Database Collaboration (INSDC) and their associated ecological metadata. GEOME facilitates the deposition of raw genetic data to INSDCs sequence read archive (SRA) while maintaining persistent links to standards-compliant ecological metadata held in the GEOME database. This approach facilitates findable, accessible, interoperable and reusable data archival practices. Moreover, GEOME enables data management solutions for large collaborative groups and expedites batch retrieval of genetic data from the SRA. The article that follows describes how GEOME can enable genuinely open data workflows for researchers in the field of molecular ecology.
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Affiliation(s)
- Cynthia Riginos
- School of Biological Sciences, The University of Queensland, St Lucia, Qld, Australia
| | - Eric D Crandall
- Department of Biology and Chemistry, California State University, Seaside, CA, USA.,Department of Biology, Pennsylvania State University, University Park, PA, USA
| | - Libby Liggins
- School of Natural and Computational Sciences, Massey University, Auckland, New Zealand
| | - Michelle R Gaither
- Department of Biology, Genomics and Bioinformatics Cluster, The University of Central Florida, Orlando, FL, USA
| | | | - Christopher Meyer
- Smithsonian Institution, National Museum of Natural History, Washington, DC, USA
| | - Kimberly R Andrews
- Institute for Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, Moscow, ID, USA
| | - Peter T Euclide
- Wisconsin Cooperative Fishery Research Unit, College of Natural Resources, University of Wisconsin-Stevens Point, Stevens Point, WI, USA
| | - Benjamin M Titus
- Division of Invertebrate Zoology, American Museum of Natural History, New York, NY, USA
| | | | - Antonia Salces-Castellano
- Island Ecology and Evolution Research Group, Instituto de Productos Naturales y Agrobiología (IPNA-CSIC), Santa Cruz de Tenerife, Spain
| | | | - Robert J Toonen
- Hawai'i Institute of Marine Biology, University of Hawai'i at Mānoa, Kāne'ohe, HI, USA
| | - John Deck
- University of California at Berkeley, Berkeley, CA, USA
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19
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Auliya M, Hofmann S, Segniagbeto GH, Assou D, Ronfot D, Astrin JJ, Forat S, Koffivi K. Ketoh G, D’Cruze N. The first genetic assessment of wild and farmed ball pythons (Reptilia, Serpentes, Pythonidae) in southern Togo. NATURE CONSERVATION 2020. [DOI: 10.3897/natureconservation.38.49478] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
The ball python (Python regius) is the world’s most commonly traded python species for the “exotic” pet industry. The majority of these live snakes are produced via a number of python farms in West Africa that have been in operation since the 1960s and involved with “ranching” operations since the 1990s. However, to date no thorough taxonomic review or genetic studies have been conducted within its range, despite the fact that the evaluation of a species’ genetic variability is generally considered mandatory for effective management. We used mtDNA sequence data and eight polymorphic microsatellite markers to assess the underlying population genetic structure and to test the potential of the nuclear markers to assign farm individuals to wild reference populations in southern Togo. Despite the relatively large distances between sample locations, no significant genetic population structure was found, either in mtDNA sequence data or in the microsatellite data. Instead, our data indicate considerable gene flow among the locations. The absence of a distinct population subdivision may have resulted from an anthropogenic driven admixture of populations associated with commercial wildlife trade activity in recent decades. Given the ongoing largely unregulated nature of the commercial ranching of ball pythons in West Africa, should a wild release component continue, as a first measure we recommend that the Management Authorities should develop an action plan with specific release protocols for python farms to minimise any potential negative conservation impacts resulting from admixture (genetic pollution) between farmed and wild individuals.
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20
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Dash HR, Shrivastava P, Das S. Expediency of Tetra- and Pentanucleotide Repeat Autosomal STR Markers for DNA Typing in Central Indian Population. ACTA ACUST UNITED AC 2019. [DOI: 10.1007/s40011-019-01156-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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21
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Lawrence ER, Benavente JN, Matte JM, Marin K, Wells ZRR, Bernos TA, Krasteva N, Habrich A, Nessel GA, Koumrouyan RA, Fraser DJ. Geo-referenced population-specific microsatellite data across American continents, the MacroPopGen Database. Sci Data 2019; 6:14. [PMID: 30944329 PMCID: PMC6472428 DOI: 10.1038/s41597-019-0024-7] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2018] [Accepted: 02/25/2019] [Indexed: 01/20/2023] Open
Abstract
Population genetic data from nuclear DNA has yet to be synthesized to allow broad scale comparisons of intraspecific diversity versus species diversity. The MacroPopGen database collates and geo-references vertebrate population genetic data across the Americas from 1,308 nuclear microsatellite DNA studies, 897 species, and 9,090 genetically distinct populations where genetic differentiation (FST) was measured. Caribbean populations were particularly distinguished from North, Central, and South American populations, in having higher differentiation (FST = 0.12 vs. 0.07-0.09) and lower mean numbers of alleles (MNA = 4.11 vs. 4.84-5.54). While mammalian populations had lower MNA (4.86) than anadromous fish, reptiles, amphibians, freshwater fish, and birds (5.34-7.81), mean heterozygosity was largely similar across groups (0.57-0.63). Mean FST was consistently lowest in anadromous fishes (0.06) and birds (0.05) relative to all other groups (0.09-0.11). Significant differences in Family/Genera variance among continental regions or taxonomic groups were also observed. MacroPopGen can be used in many future applications including latitudinal analyses, spatial analyses (e.g. central-margin), taxonomic comparisons, regional assessments of anthropogenic impacts on biodiversity, and conservation of wild populations.
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Affiliation(s)
- Elizabeth R Lawrence
- Department of Biology, Concordia University, 7141 Sherbrooke Street W., Montreal, Quebec, H4B 1R6, Canada.
| | - Javiera N Benavente
- Department of Biology, Concordia University, 7141 Sherbrooke Street W., Montreal, Quebec, H4B 1R6, Canada
- School of Environment, University of Auckland, PO Box 92019, Auckland, 1142, New Zealand
| | - Jean-Michel Matte
- Department of Biology, Concordia University, 7141 Sherbrooke Street W., Montreal, Quebec, H4B 1R6, Canada
| | - Kia Marin
- Department of Biology, Concordia University, 7141 Sherbrooke Street W., Montreal, Quebec, H4B 1R6, Canada
- Golder Associates, 7250, rue du Mile End, 3e étage, Montréal, Québec, H2R 3A4, Canada
| | - Zachery R R Wells
- Department of Biology, Concordia University, 7141 Sherbrooke Street W., Montreal, Quebec, H4B 1R6, Canada
- BT Engineering Inc., 100 Craig Henry Drive, Suite 201, Nepean, Ontario, K2G 5W3, Canada
| | - Thaïs A Bernos
- Department of Biology, Concordia University, 7141 Sherbrooke Street W., Montreal, Quebec, H4B 1R6, Canada
| | - Nia Krasteva
- Department of Biology, Concordia University, 7141 Sherbrooke Street W., Montreal, Quebec, H4B 1R6, Canada
| | - Andrew Habrich
- Department of Biology, Concordia University, 7141 Sherbrooke Street W., Montreal, Quebec, H4B 1R6, Canada
- Department of Biology and Centre for Forest-Interdisciplinary Research, University of Winnipeg, Winnipeg, Manitoba, R3B 2E9, Canada
| | - Gabrielle A Nessel
- Department of Biology, Concordia University, 7141 Sherbrooke Street W., Montreal, Quebec, H4B 1R6, Canada
| | - Ramela Arax Koumrouyan
- Department of Biology, Concordia University, 7141 Sherbrooke Street W., Montreal, Quebec, H4B 1R6, Canada
| | - Dylan J Fraser
- Department of Biology, Concordia University, 7141 Sherbrooke Street W., Montreal, Quebec, H4B 1R6, Canada
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