Genetic and genomic monitoring with minimally invasive sampling methods

School of Biology and Scottish Oceans Institute, University of St. Andrews, St Andrews, United Kingdom
Cardiff School of Biosciences and Sustainable Places Research Institute, Cardiff University, Cardiff, United Kingdom
Department of Forestry and Natural Resources and Department of Biological Science, Purdue University, West Lafayette, United States
Animal Production and Health Division, Food and Agriculture Organization of the United Nations, Rome, Italy
Department of Biology, Grice Marine Laboratory, College of Charleston, Charleston, United States
Department of Fish and Wildlife Sciences, University of Idaho, Moscow, United States
Institute of Zoology, Zoological Society of London, London, United Kingdomm
DOI
10.7287/peerj.preprints.3209v1
Subject Areas
Conservation Biology, Ecology, Genetics, Genomics, Zoology
Keywords
DNA fingerprinting, conservation genetics, individual identification, wildlife forensics, population demography, eDNA, genotyping
Copyright
© 2017 Carroll et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Carroll EL, Bruford M, DeWoody JA, Leroy G, Strand A, Waits L, Wang J. 2017. Genetic and genomic monitoring with minimally invasive sampling methods. PeerJ Preprints 5:e3209v1

Abstract

Emerging genomic technologies are reshaping the field of molecular ecology. However, many modern genomic approaches (e.g., RAD-seq) require large amounts of high quality template DNA. This poses a problem for an active branch of conservation biology: genetic monitoring using minimally invasive sampling (MIS) methods. Without handling or even observing an animal, MIS methods (e.g. collection of hair, skin, faeces) can provide genetic information on individuals or populations. Such samples typically yield low quality and/or quantities of DNA, restricting the type of molecular methods that can be used. Despite this limitation, genetic monitoring using MIS is an effective tool for estimating population demographic parameters and monitoring genetic diversity in natural populations. Genetic monitoring is likely to become more important in the future as many natural populations are undergoing anthropogenically-driven declines, which are unlikely to abate without intensive management efforts that often include MIS approaches. Here we profile the expanding suite of genomic methods and platforms compatible with producing genotypes from MIS, considering factors such as development costs and error rates. We evaluate how powerful new approaches will enhance our ability to investigate questions typically answered using genetic monitoring, such as estimating abundance, genetic structure and relatedness. As the field is in a period of unusually rapid transition, we also highlight the importance of legacy datasets and recommend how to address the challenges of moving between traditional and next generation genetic monitoring platforms. Finally, we consider how genetic monitoring could move beyond genotypes in the future. For example, assessing microbiomes or epigenetic markers could provide a greater understanding of the relationship between individuals and their environment.

Author Comment

This is a preprint submission to PeerJ