Recent advances in DNA sequencing and genotyping technologies are rapidly building our capacity to address ecological, evolutionary, and conservation questions for wildlife species. However, a large portion of wildlife genetic research relies on samples containing low quantities and quality of DNA, such as non-invasive, archival, and environmental DNA (eDNA) samples. These samples present unique methodological challenges that are largely responsible for a lag in the adoption of new genetic technologies for many areas of wildlife research. Nonetheless, steady progress is being made as researchers test and refine laboratory protocols and bioinformatic methods tailored to low-quality samples. Here we provide an overview of the progress toward low-quality sample applications for amplicon sequencing, single nucleotide polymorphism (SNP) genotyping, DNA capture, mitogenome sequencing, restriction site-associated DNA sequencing (RADseq), and whole-genome sequencing. We also review methods for generating DNA sequence data from samples comprised of multiple individuals and species, such as eDNA or fecal samples, including metagenome sequencing, metabarcoding, metagenome skimming, and metatranscriptomics. The implementation of these approaches has provided insight into a wide range of questions such as modern and historic population genetic structure and diversity, adaptation, inbreeding, ancient hybridization, occupancy, diet composition, microbiome composition, and many more. As the development of methods tailored for low-quality DNA sources continues to advance over the coming years, we expect these samples to provide unprecedented insight into the ecology, evolution, and conservation of wildlife species.
Ancient DNA Historical DNA Metagenomics Museum samples Next-generation sequencing
This is a preview of subscription content, log in to check access.
We thank Brendan Epstein and Paul Hohenlohe for helpful comments on the manuscript. K.R.A. and L.P.W. were funded by the College of Natural Resources at the University of Idaho. M.D.B. acknowledges the support of the Laboratoire d’Ecologie Alpine, Grenoble, France. M.A.R acknowledges the support of the NSERC Discovery program (grant # 2014-04736). This is PMEL contribution number 4805 and Joint Institute for the Study of the Atmosphere and Ocean (JISAO) under NOAA Cooperative Agreement NA15OAR4320063 contribution number 2018-0160.
High-throughput sequencing of PCR products from multiple individuals simultaneously
Historic (collected within the last ~200 years) or ancient (usually up to ~100,000 years old) tissue sample
Inference bias resulting from the process by which genetic loci were selected
Biotinylated oligonucleotide probe used to isolate or “capture” target DNA for sequencing
Method relying on baits to isolate or “capture” target DNA prior to high-throughput sequencing
DNA that has been prepared for high-throughput sequencing, with DNA fragments the appropriate length, and with sequencing adapters ligated to ends of fragments
Environmental DNA (eDNA)
DNA present in environmental samples such as water, soil, and air
Genetic non-invasive sample (gNIS)
DNA sample collected without handling the study organism, e.g., shed hair or fecal sample
Using low quantities of sequence data from genomic DNA libraries to study high-copy loci like mitogenomes, nuclear ribosomal genes, histone genes, and plastomes
High-throughput sequencing of PCR products generated from taxonomic-informative markers for an environmental sample
Using shotgun sequencing data from samples comprised of multiple individuals and/or species (e.g., environmental samples) to study high-copy loci like mitogenomes, nuclear ribosomal genes, histone genes, and plastomes. Often focuses on taxonomic-informative markers to identify community composition
Sequencing RNA extracted from an environmental sample
A variety of high-throughput DNA sequencing technologies developed over the last decade
Nextera-tagmented, reductively amplified DNA (NextRAD)
High-throughput sequencing of PCR products from genomic regions containing a preselected 9 bp sequence
Restriction site-associated DNA sequencing (RADseq)
High-throughput sequencing of genomic regions adjacent to restriction cut sites
“Traditional” low-throughput DNA sequencing technology developed in 1977
Sequencing by synthesis
High-throughput sequencing technology used by Illumina that detects the incorporation of single bases into replicating DNA strands
Direct sequencing of genomic DNA libraries
Single nucleotide polymorphism (SNP)
Variant at a single nucleotide site
SNP genotyping platforms
A variety of technologies that generate SNP genotype data rather than sequence reads
Bohmann K, Monadjem A, Noer CL, Rasmussen M, Zeale MRK, Clare E, et al. Molecular diet analysis of two African free-tailed bats (Molossidae) using high throughput sequencing. PLoS One 2011;6. https://doi.org/10.1371/journal.pone.0021441.
Bon C, Caudy N, de Dieuleveult M, Fosse P, Philippe M, Maksud F, et al. Deciphering the complete mitochondrial genome and phylogeny of the extinct cave bear in the Paleolithic painted cave of Chauvet. Proc Natl Acad Sci U S A. 2008;105:17447–52. https://doi.org/10.1073/pnas.0806143105.CrossRefGoogle Scholar
Bricker J. Purification of high quality DNA from shed skin. Herpetol Rev. 1996;27.Google Scholar
Cahill JA, Green RE, Fulton TL, Stiller M, Jay F, Ovsyanikov N, et al. Genomic evidence for island population conversion resolves conflicting theories of polar bear evolution. PLoS Genet. 2013;9. https://doi.org/10.1371/journal.pgen.1003345.
Chaitanya L, Ralf A, van Oven M, Kupiec T, Chang J, Lagace R, et al. Simultaneous whole mitochondrial genome sequencing with short overlapping amplicons suitable for degraded DNA using the ion torrent personal genome machine. Hum Mutat. 2015;36:1236–47. https://doi.org/10.1002/humu.22905.CrossRefGoogle Scholar
De Barba M, Miquel C, Lobreaux S, Quenette PY, Swenson JE, Taberlet P. High-throughput microsatellite genotyping in ecology: improved accuracy, efficiency, standardization and success with low-quantity and degraded DNA. Mol Ecol Res. 2017;17:492–507. https://doi.org/10.1111/1755-0998.12594.CrossRefGoogle Scholar
Deagle BE, Jarman SN, Coissac E, Pompanon F, Taberlet P. DNA metabarcoding and the cytochrome c oxidase subunit I marker: not a perfect match Biol Lett 2014;10(9). https://doi.org/10.1098/rsbl.2014.0562.
Duchêne S, Archer FI, Vilstrup J, Caballero S, Morin PA. Mitogenome phylogenetics: the impact of using single regions and partitioning schemes on topology, substitution rate and divergence time estimation. PLoS One 2011;6. https://doi.org/10.1371/journal.pone.0027138.
Edwards CJ, Magee DA, Park SDE, McGettigan PA, Lohan AJ, Murphy A, et al. A complete mitochondrial genome sequence from a mesolithic wild aurochs (Bos primigenius). PLoS One 2010;5. https://doi.org/10.1371/journal.pone.0009255.
Escobar-Zepeda A, de Leon AVP, Sanchez-Flores A. The road to metagenomics: from microbiology to DNA sequencing technologies and bioinformatics. Front Genet. 2015;6. https://doi.org/10.3389/fgene.2015.00348.
Farrell ED, Carlsson JEL, Carlsson J. Next Gen Pop Gen: implementing a high-throughput approach to population genetics in boarfish (Capros aper). R Soc Open Sci. 2016;3. https://doi.org/10.1098/rsos.160651.
Gonzalez EG, Blanco JC, Ballesteros F, Alcaraz L, Palomero G, Doadrio I. Genetic and demographic recovery of an isolated population of brown bear Ursus arctos L., 1758. PeerJ. 2016;4. https://doi.org/10.7717/peerj.1928.
Hoffman JI, Tucker R, Bridgett SJ, Clark MS, Forcada J, Slate J. Rates of assay success and genotyping error when single nucleotide polymorphism genotyping in non-model organisms: a case study in the antarctic fur seal. Mol Ecol Res. 2012;12:861–72. https://doi.org/10.1111/j.1755-0998.2012.03158.x.
Hoffmann A, Griffin P, Dillon S, Catullo R, Rane R, Byrne M, et al. A framework for incorporating evolutionary genomics into biodiversity conservation and management. Clim Change Responses 2015;2. https://doi.org/10.1186/s40665-014-0009-x.
Holland PM, Abramson RD, Watson R, Gelfand DH. Detection of specific polymerase chain-reaction product by utilizing the 5′-3′ exonuclease activity of Thermus aquaticus DNA polymerase. Proc Natl Acad Sci U S A 1991;88:7276–80. https://doi.org/10.1073/pnas.88.16.7276.
Ilmberger N, Gullert S, Dannenberg J, Rabausch U, Torres J, Wemheuer B, et al. A comparative metagenome survey of the fecal microbiota of a breast- and a plant-fed Asian elephant reveals an unexpectedly high diversity of glycoside hydrolase family enzymes. PLoS One 2014;9. https://doi.org/10.1371/journal.pone.0106707.
Jensen EL, Edwards DL, Garrick RC, Miller JM, Gibbs JP, Cayot LJ, et al. Population genomics through time provides insights into the consequences of decline and rapid demographic recovery through head-starting in a Galapagos giant tortoise. Evol Appl. 2018a;In press. https://doi.org/10.1111/eva.12682.
Jensen EL, Miller JM, Edwards DL, Garrick RC, Tapia W, Caccone A, Russello MA. Temporal mitogenomics of the Galapagos giant tortoise from Pinzón reveals potential biases in population genetic inference. J Hered. 2018b;In press. https://doi.org/10.1093/jhered/esy016/4963692.
Kistler L, Johnson SM, Irwin MT, Louis EE, Ratan A, Perry GH. A massively parallel strategy for STR marker development, capture, and genotyping. Nucleic Acids Res. 2017. https://doi.org/10.1093/nar/gkx574.
Kolby JE, Smith KM, Ramirez SD, Rabemananjara F, Pessier AP, Brunner JL, et al. Rapid response to evaluate the presence of amphibian chytrid fungus (Batrachochytrium dendrobatidis) and ranavirus in wild amphibian populations in Madagascar. PLoS One 2015;10. https://doi.org/10.1371/journal.pone.0125330.
Kraus RHS, Vonholdt B, Cocchiararo B, Harms V, Bayerl H, Kuhn R, et al. A single-nucleotide polymorphism-based approach for rapid and cost-effective genetic wolf monitoring in Europe based on noninvasively collected samples. Mol Ecol Res. 2015;15:295–305. https://doi.org/10.1111/1755-0998.12307.CrossRefGoogle Scholar
Meimberg H, Schachtler C, Curto M, Husemann M, Habel JC. A new amplicon based approach of whole mitogenome sequencing for phylogenetic and phylogeographic analysis: an example of East African white-eyes (Aves, Zosteropidae). Mol Phylogenet Evol. 2016;102:74–85. https://doi.org/10.1016/j.ympev.2016.05.023.CrossRefGoogle Scholar
Morin PA, Woodruff DS. Paternity exclusion using multiple hypervariable microsatellite loci amplified from nuclear DNA of hair cells. In: Martin RD, Dixson AF, Wickings EJ, editors. Paternity in primates: genetic tests and theories. Basel, Switzerland: Karger; 1992. p. 63–81.Google Scholar
Morin PA, Messier J, Woodruff DS. DNA extraction, amplification, and direct sequencing from Hornbill feathers. J Sci Soc Thail. 1994a;20:31–41.Google Scholar
Morin PA, Moore JJ, Chakraborty R, Jin L, Goodall J, Woodruff DS. Kin selection, social structure, gene flow, and the evolution of chimpanzees. Science. 1994b;265:1193–201.Google Scholar
Pearce JM, Fields RL, Scribner KT. Nest materials as a source of genetic data for avian ecological studies. J Field Ornithol. 1997;68:471–81.Google Scholar
Pedersen MW, Overballe-Petersen S, Ermini L, Sarkissian CD, Haile J, Hellstrom M, et al. Ancient and modern environmental DNA. Phil Trans Roy Soc B Biol Sci. 2015;370. https://doi.org/10.1098/rstb.2013.0383.
Piaggio AJ, Engeman RM, Hopken MW, Humphrey JS, Keacher KL, Bruce WE, et al. Detecting an elusive invasive species: a diagnostic PCR to detect Burmese python in Florida waters and an assessment of persistence of environmental DNA. Mol Ecol Res. 2014;14:374–80. https://doi.org/10.1111/1755-0998.12180.CrossRefGoogle Scholar
Rebollar EA, Antwis RE, Becker MH, Belden LK, Bletz MC, Brucker RM, et al. Using “omics” and integrated multi-omics approaches to guide probiotic selection to mitigate chytridiomycosis and other emerging infectious diseases. Front Microbiol. 2016;7. https://doi.org/10.3389/fmicb.2016.00063.
Rudnick JA, Katzner TE, Bragin EA, Rhodes OE, Dewoody JA. Using naturally shed feathers for individual identification, genetic parentage analyses, and population monitoring in an endangered Eastern imperial eagle (Aquila heliaca) population from Kazakhstan. Mol Ecol. 2005;14:2959–67. https://doi.org/10.1111/j.1365-294X.2005.02641.x.CrossRefGoogle Scholar
Schoville SD, Bonin A, Francois O, Lobreaux S, Melodelima C, Manel S. Adaptive genetic variation on the landscape: methods and cases. In: Futuyma DJ, editor. Annual review of ecology, evolution, and systematics. Annual review of ecology evolution and systematics, vol 43. 2012; p. 23–43. https://doi.org/10.1146/annurev-ecolsys-110411-160248.
Srivathsan A, Ang A, Vogler AP, Meier R. Fecal metagenomics for the simultaneous assessment of diet, parasites, and population genetics of an understudied primate. Front Zool. 2016;13. https://doi.org/10.1186/s12983-016-0150-4.
Suchan T, Pitteloud C, Gerasimova NS, Kostikova A, Schmid S, Arrigo N, et al. Hybridization capture using RAD probes (hyRAD), a new tool for performing genomic analyses on collection specimens. PLoS One 2016;11. https://doi.org/10.1371/journal.pone.0151651.
Thomsen PF, Kielgast J, Iversen LL, Moller PR, Rasmussen M, Willerslev E. Detection of a diverse marine fish fauna using environmental DNA from seawater samples. PLoS One 2012;7. https://doi.org/10.1371/journal.pone.0041732.
Tin MMY, Economo EP, Mikheyev AS. Sequencing degraded DNA from non-destructively sampled museum specimens for RAD-tagging and low-coverage shotgun phylogenetics. PLoS One 2014;9. https://doi.org/10.1371/journal.pone.0096793.
Vartia S, Villanueva-Canas JL, Finarelli J, Farrell ED, Collins PC, Hughes GM, et al. A novel method of microsatellite genotyping-by-sequencing using individual combinatorial barcoding. R Soc Open Sci. 2016;3. https://doi.org/10.1098/rsos.150565.
Wagner CE, Keller I, Wittwer S, Selz OM, Mwaiko S, Greuter L, et al. Genome-wide RAD sequence data provide unprecedented resolution of species boundaries and relationships in the Lake Victoria cichlid adaptive radiation. Mol Ecol. 2013;22:787–98. https://doi.org/10.1111/mec.12023.CrossRefGoogle Scholar
Wheat RE, Allen JM, Miller SDL, Wilmers CC, Levi T. Environmental DNA from residual saliva for efficient noninvasive genetic monitoring of brown bears (Ursus arctos). PLoS One 2016;11. https://doi.org/10.1371/journal.pone.0165259.
Willerslev E, Gilbert MTP, Binladen J, Ho SYW, Campos PF, Ratan A, et al. Analysis of complete mitochondrial genomes from extinct and extant rhinoceroses reveals lack of phylogenetic resolution. BMC Evol Biol. 2009;9. https://doi.org/10.1186/1471-2148-9-95.
Williams CL, Blejwas K, Johnston JJ, Jaeger MM. A coyote in sheep’s clothing: predator identification from saliva. Wildl Soc Bull. 2003;31:926–32.Google Scholar
Wultsch C, Waits LP, Kelly MJ. A Comparative analysis of genetic diversity and structure in jaguars (Panthera onca), pumas (Puma concolor), and ocelots (Leopardus pardalis) in fragmented landscapes of a critical Mesoamerican linkage zone. PLoS One 2016;11. https://doi.org/10.1371/journal.pone.0151043.
Xu B, Xu WJ, Li JJ, Dai LM, Xiong CY, Tang XH, et al. Metagenomic analysis of the Rhinopithecus bieti fecal microbiome reveals a broad diversity of bacterial and glycoside hydrolase profiles related to lignocellulose degradation. BMC Genomics 2015;16. https://doi.org/10.1186/s12864-015-1378-7.