Opportunities and challenges of macrogenetic studies

Leigh, Deborah M.; Rees, Charles B. van; Millette, Katie L.; Breed, Martin F.; Schmidt, Chloé; Bertola, Laura D.; Hand, Brian K.; Hunter, Margaret E.; Jensen, Evelyn L.; Kershaw, Francine; Liggins, Libby; Luikart, Gordon; Manel, StÃ©phanie; Mergeay, Joachim; Miller, Joshua M.; Segelbacher, Gernot; Hoban, Sean; Paz‐Vinas, Ivan

doi:10.1038/s41576-021-00394-0

Cited by 90 publications

(120 citation statements)

References 170 publications

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“…We will continue to make recommendations and supply users with guidance in data checking before analysis. We encourage continued natural history work to better populate biodiversity databases as the benefits of publicly available data are numerous and experts are needed to correct database errors and decide where data deficiencies lie (Groom et al 2020;Leigh et al 2021). Further, making data easy to access and reuse is important for researchers and educators who do not have the skills or resources for large-scale projects, or expensive and timeconsuming field and lab work, increasing participation from underprivileged groups and minorities (Estrada et al 2016;Whittington & Pelletier 2021).…”

Section: Discussionmentioning

confidence: 99%

“…However, the considerable variation in study design and statistical analyses used across studies render meta-analysis in population genetics and phylogeography difficult (Garrick et al 2015). A more productive strategy is the repurposing of data (Sidlauskas et al 2010;Blanchet et al 2017;Leigh et al 2021), where data from previously published work are reanalyzed in large groups in order to extract insight about global processes. Combining similar types of data from multiple studies and then re-analyzing these data under a common framework has the power to elucidate factors that drive evolution on both small and large scales.…”

Section: Introductionmentioning

confidence: 99%

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phylogatR: Phylogeographic data aggregation and repurposing

Pelletier

Parsons

Decker

et al. 2021

Preprint

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Patterns of genetic diversity within species contain information about the history of that species, including how they have responded to historical climate change and how easily the organism is able to disperse across its habitat. More than 40,000 phylogeographic and population genetic investigations have been published to date, each collecting genetic data from hundreds of samples. Despite these millions of data points, meta-analyses are challenging because the synthesis of results across hundreds of studies, each using different methods and forms of analysis, is a daunting and time-consuming task. It is more efficient to proceed by repurposing existing data and using automated data analysis. To facilitate data repurposing, we created a database (phylogatR) that aggregates data from different sources and conducts automated multiple sequence alignments and data curation to provide users with nearly ready-to-analyze sets of data for thousands of species. Two types of scientific research will be made easier by phylogatR, large meta-analyses of thousands of species that can address classic questions in evolutionary biology and ecology and student- or citizen- science based investigations that will introduce a broad range of people to the analysis of genetic data. phylogatR enhances the value of existing data via the creation of software and web-based tools that enable these data to be recycled and reanalyzed and increase accessibility to big data for research labs and classroom instructors with limited computational expertise and resources.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

phylogatR: Phylogeographic data aggregation and repurposing

Pelletier

Parsons

Decker

et al. 2021

Preprint

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“…Now with increased technology and data accumulation, intraspecific diversity – such as genetic diversity within species – can be studied in the same way as species diversity. Understanding the distribution of genetic diversity is important for providing insights on the spatial distribution of biodiversity as a whole, with implications for conservation planning (De Kort et al, 2021; Lawrence & Fraser, 2020; Leigh et al, 2021; Theodoridis et al, 2020). Although still in its infancy, ‘macrogenetics’ – the study of genetic diversity across different taxa at broad scales – thus far has not revealed patterns as widespread or as obvious across latitudes as those found in species diversity (Adams & Hadly, 2013; Manel et al, 2020; Millette et al, 2020; Miraldo et al, 2016; Theodoridis et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…stronger trends in mammals) (Adams & Hadly, 2013; Gratton et al, 2017; Martin & Mckay, 2004; Millette et al, 2020; Miraldo et al, 2016). However, inconsistencies between archiving practices in mitochondrial DNA repositories have resulted in biased measures of genetic diversity when repurposed for macrogenetic research (Leigh et al, 2021; Paz-Vinas et al, 2021). Moreover, individual-based mitochondrial DNA variation in past studies was often grouped across sampling localities in analyses (e.g.…”

Section: Introductionmentioning

confidence: 99%

Macrogenetics reveals multifaceted influences of environmental variation on vertebrate population genetic diversity across the Americas

Lawrence

Fraser

2021

Preprint

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Relative to species diversity gradients, the broad scale distribution of population-specific genetic diversity (PGD) across taxa remains understudied. We used nuclear DNA data collected from 6285 vertebrate populations across the Americas to assess the role environmental variables play in structuring the spatial/latitudinal distribution of PGD, a key component of adaptive potential in the face of environmental change. Our results provide key evidence for taxa-specific responses and that temperature variability in addition to mean temperature may be a primary driver of PGD. Additionally, we found some positive influence of precipitation, productivity, and elevation on PGD; identified trends were dependent on the metric of PGD. In contrast to the classic negative relationship between species diversity and latitude, we report either a positive or taxa-dependent relationship between PGD and latitude, depending on the metric of PGD. The inconsistent latitudinal gradient in different metrics of PGD may be due to opposing processes diminishing patterns across latitudes that operate on different timescales, as well as the flattening of large-scale genetic gradients when assessing across species versus within species. Our study highlights the nuance required to assess broad patterns in genetic diversity, and the need for developing balanced conservation strategies that ensure population, species, and community persistence.

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“…2 The calculation of such genetic diversity measures relies upon the availability of population genetic datasets (e.g., DNA sequences, microsatellite fragment length data, and Single Nucleotide Polymorphisms, SNPs) which are sampled from populations across a species range. Over the past three decades, population genetic datasets have been amassed for thousands of species globally (Leigh et al, 2021). Furthermore, the rate at which we accrue these datasets has increased as the use of genetic data has diversified (such as for informing Essential Ocean Variables, EOVs; Muller-Karger et al, 2018), and the technologies used to generate DNA sequences and decode polymorphisms among individuals have become faster, cheaper, and higher through-put (Arribas et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

The Ira Moana Project: A Genetic Observatory for Aotearoa’s Marine Biodiversity

Liggins

Noble

2021

Front. Mar. Sci.

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The genetic diversity of populations plays a crucial role in ensuring species and ecosystem resilience to threats such as climate change and habitat degradation. Despite this recognized importance of genetic diversity, and its relevance to the Convention on Biological Diversity and the United Nations Sustainable Development Goals, it remains difficult to observe and synthesize genetic data at a national scale. The “Ira Moana—Genes of the Sea—Project” (https://sites.massey.ac.nz/iramoana/) has worked to improve stewardship of genetic data for Aotearoa New Zealand’s (NZ) marine organisms to facilitate marine genetic biodiversity observation, research, and conservation. The Ira Moana Project has established interoperable data infrastructures and tools that help researchers follow international best-practice (including the FAIR Principles for Data Stewardship and CARE Principles for Indigenous Data Governance) and contribute to a national genetic data resource. Where possible, the Project has employed existing infrastructures (such as the Genomic Observatories Metadatabase, GEOME) to allow interoperability with similar research activities, but has also innovated to accommodate the national interests of NZ. The Ira Moana Project has an inclusive model, and through presentations, workshops, and datathons, it has provided training, education, and opportunities for collaboration among NZ researchers. Here, we outline the motivations for the Ira Moana Project, describe the Project activities and outcomes, and plans for future development. As a timely response to national and international pressures on genetic biodiversity research, it is hoped that the Ira Moana Project will facilitate NZ researchers, communities, and conservation practitioners to navigate this crucial period, and provide tangible solutions nationally and globally.

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Opportunities and challenges of macrogenetic studies

Cited by 90 publications

References 170 publications

phylogatR: Phylogeographic data aggregation and repurposing

phylogatR: Phylogeographic data aggregation and repurposing

Macrogenetics reveals multifaceted influences of environmental variation on vertebrate population genetic diversity across the Americas

The Ira Moana Project: A Genetic Observatory for Aotearoa’s Marine Biodiversity

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