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Preprint
Around the world in 1500 SNPs: cross-kingdom genomics across global taxa highlights optimised sampling for accurate genetic diversity assessments
Research Square, Vol.6 January 2025
Research Square Company
2025
Abstract
Population genetics is rapidly evolving in the genomics era, with next-generation sequencing providing researchers with access to vast and diverse genetic datasets. While these advancements present significant opportunities, key questions remain about the optimal sample sizes and number of genetic markers, such as single nucleotide polymorphisms (SNPs), needed for robust studies. This is particularly relevant to conservation genetics, where large sample sizes may be impractical for rare species or fragmented populations. To address these challenges, we analysed a global dataset of genotypes derived from various DNA sources (scat, blood, animal tissue, leaf) to explore how sample size and SNP count affect estimates of genetic diversity. Our findings showed that a sample size of ten individuals, combined with 1500 SNP markers, can provide accurate genetic diversity estimates across diverse taxa and sequencing approaches. Sensitivity analysis and random resampling revealed that a small sample size can reliably capture within-population diversity with minimal error, challenging traditional assumptions that larger sample sizes are always necessary for meaningful genomic insights. Although some taxa displayed instability in heterozygosity indices at smaller sample sizes, stability was typically reached within two to ten individuals and between 500-1500 SNPs. This study not only provides practical guidelines for efficient genomic assessments but also emphasises the potential for smaller, more targeted sampling strategies in biodiversity conservation. By integrating empirical findings with theoretical frameworks, we lay the groundwork for future research and resource-efficient approaches that address contemporary conservation challenges without compromising data accuracy.
Details
- Title
- Around the world in 1500 SNPs: cross-kingdom genomics across global taxa highlights optimised sampling for accurate genetic diversity assessments
- Authors
- Aaron Brunton (Corresponding Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringKeaka Farleigh - University of VirginiaElizabeth Brunton - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringRomane Cristescu - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringRoss G Dwyer - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringKatrin Hohwieler - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringBonnie Holmes - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringChris Kozakiewicz - Michigan State UniversityAlexis L Levengood - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringDavid Schoeman - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringSteven Ogbourne - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringGabriel Conroy - University of the Sunshine Coast, Queensland, Centre for Bioinnovation
- Publication details
- Research Square, Vol.6 January 2025
- Publisher
- Research Square Company
- Date published
- 2025
- DOI
- 10.21203/rs.3.rs-5760748/v1
- ISSN
- 2693-5015
- Copyright note
- This work is licensed under a CC BY 4.0 License
- Data Availability
- All raw genetic data (.rds files) and R scripts are available at: https://github.com/AaronBrunton/SNP_analysis.
- Grant note
- KF is supported by the following funding sources - NSF GRF (Award #2037786) and PRFB (DBI-2409958).
- Organisation Unit
- School of Science, Technology and Engineering; Centre for Bioinnovation
- Language
- English
- Record Identifier
- 991103244702621
- Output Type
- Preprint
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