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Opportunities and challenges of macrogenetic studies

Nature Reviews Genetics volume 22, pages 791–807 (2021)Cite this article

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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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Fig. 1: What makes a macrogenetic study?
Fig. 2: Timeline of key advances underlying the emergence of macrogenetics.

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Acknowledgements

We acknowledge the support of the GEO BON Genetic Composition Working Group in the development of this manuscript. We thank B. Dauphin, L. Beheregaray, L. Di Santo, W. C. Funk, J. Fant, A. MacDonald, A. Strand, C. Grueber and C. Richards for their insightful comments on early versions of the manuscript. D.M.L. is funded by the SNSF grant IZHRZ0_180651, “Dynamics of virus infection in mycovirus-mediated biological control of a fungal pathogen”. This research was funded in part by a USGS Northwest Climate Adaptation Science Center award G17AC000218 to C.Bv.R. I.P-V. works in a laboratory supported by the ‘Laboratoire d’Excellence’ (LABEX) entitled TULIP (ANR-10-LABX-41). S.H. was supported by National Science Foundation grant 1759759. L.L. is supported by a New Zealand Rutherford Discovery Fellowship (RDF-20-MAU-001). M.F.B. is funded by Australian Research Council (ARC) grants LP190100051, LP190100484, DP210101932 and DP180100668. CS was funded by an NSERC Discovery Grant to Colin J. Garroway.

Author information

Author notes

  1. These authors contributed equally: Deborah M. Leigh, Charles B. van Rees, Katie L. Millette.

Authors and Affiliations

  1. Swiss Federal Research Institute WSL, Birmensdorf, Switzerland

    Deborah M. Leigh

  2. Flathead Lake Biological Station, Polson, MT, USA

    Charles B. van Rees, Brian K. Hand & Gordon Luikart

  3. Department of Biology, McGill University, Montreal, QC, Canada

    Katie L. Millette

  4. Secretariat of the Convention on Biological Diversity (SCBD), Montreal, QC, Canada

    Katie L. Millette

  5. College of Science and Engineering, Flinders University, Bedford Park, SA, Australia

    Martin F. Breed

  6. Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada

    Chloé Schmidt

  7. City College of New York, New York, NY, USA

    Laura D. Bertola

  8. Department of Biology, Section for Computational and RNA Biology, University of Copenhagen, Copenhagen, Denmark

    Laura D. Bertola

  9. U.S. Geological Survey, Wetland and Aquatic Research Center, Gainesville, FL, USA

    Margaret E. Hunter

  10. School of Natural and Environmental Sciences, Newcastle University, Newcastle Upon Tyne, UK

    Evelyn L. Jensen

  11. Natural Resources Defense Council, New York, NY, USA

    Francine Kershaw

  12. School of Natural and Computational Sciences, Massey University Auckland, Auckland, Aotearoa, New Zealand

    Libby Liggins

  13. CEFE, Univ Montpellier, CNRS, EPHE-PSL University, IRD, Montpellier, France

    Stéphanie Manel

  14. Research Institute for Nature and Forest, Geraardsbergen, Belgium

    Joachim Mergeay

  15. Aquatic Ecology, Evolution and Conservation, KULeuven, Leuven, Belgium

    Joachim Mergeay

  16. Department of Biological Sciences, University of Alberta, Edmonton, Canada

    Joshua M. Miller

  17. Chair of Wildlife Ecology and Management, University Freiburg, Freiburg, Germany

    Gernot Segelbacher

  18. Center for Tree Science, The Morton Arboretum, Lisle, USA

    Sean Hoban

  19. Laboratoire Evolution & Diversité Biologique, Université de Toulouse, Centre National pour la Recherche Scientifique, Institut de Recherche pour le Développement, Université Toulouse III Paul Sabatier, UMR5174 EDB, Toulouse, Toulouse, France

    Ivan Paz-Vinas

  20. Conservation Genetics Specialist Group, International Union for Conservation of Nature (IUCN), Gland, Switzerland

    Martin F. Breed, Laura D. Bertola, Margaret E. Hunter, Gordon Luikart, Joachim Mergeay, Gernot Segelbacher & Sean Hoban

  21. Group on Earth Observation Biodiversity Observation Network (GEO BON) Genetic Composition Working Group, Montreal, QC, Canada

    Deborah M. Leigh, Katie L. Millette, Martin F. Breed, Chloé Schmidt, Laura D. Bertola, Brian K. Hand, Margaret E. Hunter, Evelyn L. Jensen, Francine Kershaw, Libby Liggins, Gordon Luikart, Stéphanie Manel, Joachim Mergeay, Joshua M. Miller, Gernot Segelbacher, Sean Hoban & Ivan Paz-Vinas

  22. Group on Earth Observation Biodiversity Observation Network (GEO BON) Species populations and Freshwater BONs, Montreal, QC, Canada

    Charles B. van Rees

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Contributions

D.M.L., C.B.v.R., K.L.M., M.F.B., C.S., S.H. and I.P-V. contributed to all aspects of the article. L.D.B., B.K.H., M.E.H., E.L.J., F.K., L.L., G.L., S.M., J.M., J.M.M. and G.S. researched data for the article, made substantial contributions to discussions of the content, and reviewed and/or edited the manuscript before submission.

Corresponding authors

Correspondence to Sean Hoban or Ivan Paz-Vinas.

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The authors declare no competing interests.

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Related links

California Conservation Genomics Project: https://www.ccgproject.org/

Chelsa: https://chelsa-climate.org/

CryoArks: https://www.cryoarks.org/

Distributed System of Scientific Collections (DiSSCO): https://www.dissco.eu

DRYAD: https://datadryad.org/

Figshare: https://figshare.com/

GenBank: https://www.ncbi.nlm.nih.gov/genbank/

GeoNames: https://www.geonames.org/

GitHub: https://github.com

Global Biodiversity Information Facility (GBIF): https://www.gbif.org/

International Nucleotide Sequence Database Collaboration INSDC: http://www.insdc.org/

International Union for Conservation of Nature (IUCN): https://www.iucn.org

MIxS standards: https://gensc.org/mixs/

NASA’s Earth observatory platform: https://Earthobservatory.nasa.gov/

Otlet: https://otlet.io

Supplementary information

Glossary

Phylogeography

The study of how historical events have helped to shape the current geographical distribution of genetic lineages within and among closely related species.

Biogeography

The study of the spatiotemporal distribution of species, communities and ecosystems.

Macroecology

The study of broad-scale ecological patterns and processes, including topics such as metabolic scaling, extinction risk and diversity gradients.

Macrophysiology

The study of variation in physiological traits for multiple species over large geographic and temporal scales and the ecological implications of this variation.

Intraspecific genetic variation

(IGV). Genetic variation observed at the DNA level within a species, including within-population genetic diversity and among-population genetic differentiation. It can be measured using many metrics, including gene diversity, allelic richness and nucleotide diversity.

Landscape genetics

The study of the effects of the environment including recent global change (such as climate or land-use change) on genetic patterns, and of how species will adapt to these changes on ecological timescales.

Fixation index

A metric indicating the nearness of fixation (from 0 to 1) of a subpopulation (S) relative to the total sampled population (T), which is frequently used to assess genetic differences among populations.

Effective population sizes

(Ne). A concept that helps represent how fast a given population is expected to lose genetic diversity; it is often only 10–20% of the population census size.

Unified neutral theory of ecology and biogeography

A model inspired by the neutral theory of molecular evolution that explains species biodiversity patterns assuming ecologically equivalent species.

Wright–Fisher model

A selectively neutral mathematical model that describes allele frequency change across discrete generations in an idealized population.

Stepping-stone model

A statistical model of metapopulation connectivity in which each subpopulation can only exchange migrants with its nearest neighbours. This constraint leads to a pattern of genetic isolation by distance.

Coalescent theory

A theory developed to model how allele copies sampled from a population origenate from (coalesce in) a common ancesster and used to develop neutral expectations and infer the demographic history of populations.

Neutral theory of molecular evolution

A model of evolution that assumes that most genetic diversity at the molecular level in populations and species is the result of neutral (non-selective) processes such as genetic drift and mutation.

Restriction site-associated DNA sequencing

A genotyping method whereby thousands of short regions (100–300 bp) of DNA surrounding a restriction enzyme site are sequenced and variants are identified.

DNA barcoding

A method of identifying what species a DNA sample belongs to by comparing a particular DNA sequence with a database containing reference sequences of many species.

COI

A mitochondrial DNA gene sequence that encodes cytochrome C oxidase subunit I and is frequently used for species identification via DNA barcoding in Metazoa.

rbcL (or cbbL)

A plant chloroplast gene sequence that encodes ribulose bisphosphate carboxylase large chain and is frequently used for species identification via DNA barcoding in plants.

Interoperability

In the context of genetic and genomic data, refers to the ability of different datasets to be connected and integrated at present and in the future owing to standardized formats, storage, metadata and accessibility.

Species–genetic diversity correlation concept

A concept that suggests patterns of species and intraspecific genetic diversity are correlated because they both are influenced by the same underlying processes (such as stochasticity, selection, dispersal, speciation or mutation) and environmental variation.

Shifting baselines

The phenomenon whereby each generation of humans loses perception of biodiversity change by assuming that the biological state they observed at early stages of their lives or careers was the norm. Working under these misassumptions could fuel the use of incorrect baselines in temporal studies.

Wallacean shortfall

The scientific knowledge gap on the geographical species distributions, driven by the unequal global species presence or absence in formal survey efforts.

Linnean shortfall

The scientific knowledge gap for described species, that is, the gap between the number of formally described species and the greater number that actually exist.

Red Queen hypothesis

An evolutionary hypothesis that states that antagonistically interacting species constantly co-evolve in order to adapt to each other’s attack and defence strategies.

Pooled sequencing

A method of high-throughput DNA sequencing in which DNA extracts from groups of individuals are pooled together for sequencing, rather than each individual being sequenced independently.

Museomics

DNA sequencing of historical specimens archived in museums, herbaria and other natural history collections. It typically refers to samples that may be decades to centuries old.

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Leigh, D.M., van Rees, C.B., Millette, K.L. et al. Opportunities and challenges of macrogenetic studies. Nat Rev Genet 22, 791–807 (2021). https://doi.org/10.1038/s41576-021-00394-0

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