Conservation Genetics Resources

, Volume 9, Issue 2, pp 289–304 | Cite as

Variability in total project and per sample genotyping costs under varying study designs including with microsatellites or SNPs to answer conservation genetic questions

  • Emily E. Puckett
Methods and Resources Article


The field of conservation genetics is in the midst of transitioning from microsatellites to single nucleotide polymorphisms (SNPs) as part of a broader transition from genetic to genomic studies. Genomics offers the potential for more accurate estimation of individual and population parameters but at higher project costs. I calculated cost curves for multi-locus genotypes to describe how total project and per sample costs varied between microsatellite and SNP genotyping. Cost curves were calculated varying multiple parameters which influenced costs, including: number of microsatellite loci, primer multiplexing, number of samples pooled per library, sequencing costs, and variation in laborer salaries. Sequencing costs had the greatest effect on total project costs for both markers, suggesting a way to achieve the greatest savings. For microsatellites, increasing loci number had a small effect on increasing costs, although using an increasing number of multiplex panels had a significant effect. For SNPs, increasing the number of samples pooled per genotyping library resulted in the greatest cost savings; however, this was tempered somewhat by species genome size and study design parameters which could decrease per locus sequencing depth below thresholds needed for robust SNP calling. Thus, this study highlights multiple parameters to consider when designing conservation genotyping studies to maximize information while minimizing costs. I also surveyed studies that compared microsatellites and SNPs. SNPs had greater accuracy than microsatellites when SNP loci were 3–2800 fold greater. Cost curves are provided as changing parameter assumptions effects estimates.


Conservation genomics Cost analysis ddRAD 



Sheena Feist, Jane Park, and three anonymous reviewers provided constructive feedback which improved the manuscript.

Supplementary material

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Supplementary material 1 (TXT 19 KB)
12686_2016_643_MOESM2_ESM.txt (38 kb)
Supplementary material 2 (TXT 39 KB)
12686_2016_643_MOESM3_ESM.docx (845 kb)
Supplementary material 3 (DOCX 846 KB)


  1. Ali OA, O’Rourke SM, Amish SJ, Meek MH, Luikart G, Jeffres C, Miller MR (2016) RAD capture (Rapture): flexible and efficient sequence-based genotyping. Genetics 202:389–400CrossRefPubMedGoogle Scholar
  2. Allendorf FW, Hohenlohe PA, Luikart G (2010) Genomics and the future of conservation genetics. Nat Rev Genet 11:697–709CrossRefPubMedGoogle Scholar
  3. Amos W, Harwood J (1998) Factors affecting levels of genetic diversity in natural populations. Philos Trans R Soc Lond B Biol Sci 353:177–186CrossRefPubMedPubMedCentralGoogle Scholar
  4. Andrews KR, Good JM, Miller MR, Luikart G, Hohenlohe PA (2016) Harnessing the power of RADseq for ecological and evolutionary genomics. Nat Rev Genet 17:81–92CrossRefPubMedPubMedCentralGoogle Scholar
  5. Antao T, Pérez-Figueroa A, Luikart G (2011) Early detection of population declines: high power of genetic monitoring using effective population size estimators. Evol Appl 4:144–154CrossRefPubMedGoogle Scholar
  6. Bidot C, Lamboni M, Monod H (2016) Multisensi: Multivariate sensitivity analysis.
  7. Blouin MS (2003) DNA-based methods for pedigree reconstruction and kinship analysis in natural populations. Trends Ecol Evol 18:503–511CrossRefGoogle Scholar
  8. Bradbury IR, Hamilton LC, Dempson B et al (2015) Transatlantic secondary contact in Atlantic Salmon, comparing microsatellites, a single nucleotide polymorphism array and restriction-site associated DNA sequencing for the resolution of complex spatial structure. Mol Ecol 24:5130–5144CrossRefPubMedGoogle Scholar
  9. Candy JR, Campbell NR, Grinnell MH et al (2015) Population differentiation determined from putative neutral and divergent adaptive genetic markers in Eulachon (Thaleichthys pacificus, Osmeridae), an anadromous Pacific smelt. Mol Ecol Res 15:1421–1434CrossRefGoogle Scholar
  10. Charlesworth D (2003) Effects of inbreeding on the genetic diversity of populations. Philos Trans R Soc Lond B Biol Sci 358:1051–1070CrossRefPubMedPubMedCentralGoogle Scholar
  11. Davey JW, Hohenlohe PA, Etter PD, Boone JQ, Catchen JM, Blaxter ML (2011) Genome-wide genetic marker discovery and genotyping using next-generation sequencing. Nat Rev Genet 12:499–510CrossRefPubMedGoogle Scholar
  12. DeFaveri J, Viitaniemi H, Leder E, Merilä J (2013) Characterizing genic and nongenic molecular markers: comparison of microsatellites and SNPs. Mol Ecol Res 13:377–392CrossRefGoogle Scholar
  13. de Groot GA, Nowak C, Skrbinšek T, Andersen LW, Aspi J, Fumagalli L, Godinho R, Harms V, Jansman HAH, Liberg O, Marucco F, Mysłajek RW, Nowak S, Pilot M, Randi E, Reinhardt I, Śmietana W, Szewczyk M, Taberlet P, Vilà C, Muñoz-Fuentes V (2016) Decades of population genetic research reveal the need for harmonization of molecular markers: the grey wolf Canis lupus as a case study. Mamm Rev 46:44–59CrossRefGoogle Scholar
  14. Ellegren H (2000) Microsatellite mutations in the germline: implications for evolutionary inference. Trends Genet 16:551–558CrossRefPubMedGoogle Scholar
  15. Forstmeier W, Schielzeth H, Mueller JC, Ellegren H, Kempenaers B (2012) Heterozygosity–fitness correlations in zebra finches: microsatellite markers can be better than their reputation. Mol Ecol 21:3237–3249CrossRefPubMedGoogle Scholar
  16. Frankham R (2010) Where are we in conservation genetics and where do we need to go? Conserv Genet 11:661–663CrossRefGoogle Scholar
  17. Gärke C, Ytournel F, Bed’hom B et al (2012) Comparison of SNPs and microsatellites for assessing the genetic structure of chicken populations. Anim Genet 43:419–428CrossRefPubMedGoogle Scholar
  18. Garrick RC, Bonatelli IAS, Hyseni C, Morales A, Pelletier TA, Perez MF, Rice E, Satler JD, Symula RE, Thomé MTC, Carstens BC (2015) The evolution of phylogeographic data sets. Mol Ecol 24:1164–1171CrossRefPubMedGoogle Scholar
  19. Haasl RJ, Payseur BA (2011) Multi-locus inference of population structure: a comparison between single nucleotide polymorphisms and microsatellites. Heredity 106:158–171CrossRefPubMedGoogle Scholar
  20. Hauser L, Baird M, Hilborn R, Seeb LW, Seeb JE (2011) An empirical comparison of SNPs and microsatellites for parentage and kinship assignment in a wild sockeye salmon (Oncorhynchus nerka) population. Mol Ecol Resour 11(Suppl 1):150–161CrossRefPubMedGoogle Scholar
  21. He X, Johansson ML, Heath DD (2016) Role of genomics and transcriptomics in selection of reintroduction source populations. Conserv Biol 30:1010–1018CrossRefPubMedGoogle Scholar
  22. Hefti-Gautschi B, Pfunder M, Jenni L, Keller V, Ellegren H (2009) Identification of conservation units in the European Mergus merganser based on nuclear and mitochondrial DNA markers. Conserv Genet 10:87–89 CrossRefGoogle Scholar
  23. Hess JE, Matala AP, Narum SR (2011) Comparison of SNPs and microsatellites for fine-scale application of genetic stock identification of Chinook salmon in the Columbia River Basin. Mol Ecol Res 11:137–149CrossRefGoogle Scholar
  24. Hoban S, Arntzen JA, Bruford MW et al (2014) Comparative evaluation of potential indicators and temporal sampling protocols for monitoring genetic erosion. Evol Appl 7:984–998CrossRefPubMedPubMedCentralGoogle Scholar
  25. Hohenlohe PA, Amish SJ, Catchen JM, Allendorf FW, Luikart G (2011) Next-generation RAD sequencing identifies thousands of SNPs for assessing hybridization between rainbow and westslope cutthroat trout. Mol Ecol Resour 11:117–122CrossRefPubMedGoogle Scholar
  26. Jeffries DL, Copp GH, Lawson Handley L, Olsén KH, Sayer CD, Hänfling B (2016) Comparing RADseq and microsatellites to infer complex phylogeographic patterns, an empirical perspective in the Crucian carp, Carassius carassius, L. Mol Ecol 25:2997–3018CrossRefPubMedGoogle Scholar
  27. Kaiser SA, Taylor SA, Chen N, Sillett TS, Bondra ER, Webster MS (2016) A comparative assessment of SNP and microsatellite markers for assigning parentage in a socially monogamous bird. Mol Ecol Resour. doi: 10.1111/1755-0998.12589 PubMedGoogle Scholar
  28. Kardos M, Allendorf FW, Luikart G (2014) Evaluating the role of inbreeding depression in heterozygosity-fitness correlations: how useful are tests for identity disequilibrium? Mol Ecol Res 14:519–530CrossRefGoogle Scholar
  29. Kraus RHS, vonHoldt B, Cocchiararo B, Harms V, Bayerl H, Kühn R, Förster DW, Fickel J, Roos C, Nowak C (2015) A single-nucleotide polymorphism-based approach for rapid and cost-effective genetic wolf monitoring in Europe based on noninvasively collected samples. Mol Ecol Resour 15:295–305CrossRefPubMedGoogle Scholar
  30. Labuschagne C, Nupen L, Kotzé A, Grobler PJ, Dalton DL (2015) Assessment of microsatellite and SNP markers for parentage assignment in ex situ African Penguin (Spheniscus demersus) populations. Ecol Evol 5:4389–4399CrossRefPubMedPubMedCentralGoogle Scholar
  31. Liu N, Chen L, Wang S, Oh C, Zhao H (2005) Comparison of single-nucleotide polymorphisms and microsatellites in inference of population structure. BMC Genet 6:S26CrossRefPubMedPubMedCentralGoogle Scholar
  32. Lozier JD (2014) Revisiting comparisons of genetic diversity in stable and declining species: assessing genome-wide polymorphism in North American bumble bees using RAD sequencing. Mol Ecol 23:788–801CrossRefPubMedGoogle Scholar
  33. Malenfant RM, Coltman DW, Davis CS (2015) Design of a 9K illumina BeadChip for polar bears (Ursus maritimus) from RAD and transcriptome sequencing. Mol Ecol Res 15:587–600CrossRefGoogle Scholar
  34. McMahon BJ, Teeling EC, Höglund J (2014) How and why should we implement genomics into conservation? Evol Appl 7:999–1007CrossRefPubMedPubMedCentralGoogle Scholar
  35. Mesnick SL, Taylor BL, Archer FI et al (2011) Sperm whale population structure in the eastern and central North Pacific inferred by the use of single-nucleotide polymorphisms, microsatellites and mitochondrial DNA. Mol Ecol Res 11:278–298CrossRefGoogle Scholar
  36. Miller JM, Malenfant RM, David P, Davis CS, Poissant J, Hogg JT, Festa-Bianchet M, Coltman DW (2014) Estimating genome-wide heterozygosity: effects of demographic history and marker type. Heredity 112:240–247CrossRefPubMedGoogle Scholar
  37. Miller AD, van Rooyen A, Rašić G et al (2016) Contrasting patterns of population connectivity between regions in a commercially important mollusc Haliotis rubra: integrating population genetics, genomics and marine LiDAR data. Mol Ecol 25:3845–3864CrossRefPubMedGoogle Scholar
  38. Moore JA, Draheim HM, Etter D, Winterstein S, Scribner KT (2014) Application of large-scale parentage analysis for investigating natal dispersal in highly vagile vertebrates: a case study of American black bears (Ursus americanus). PLoS One 9:e91168CrossRefPubMedPubMedCentralGoogle Scholar
  39. Morin PA, Archer FI, Pease VL et al (2012) Empirical comparison of single nucleotide polymorphisms and microsatellites for population and demographic analyses of bowhead whales. Endanger Species Res 19:129–147CrossRefGoogle Scholar
  40. Narum SR, Banks M, Beacham TD et al (2008) Differentiating salmon populations at broad and fine geographical scales with microsatellites and single nucleotide polymorphisms. Mol Ecol 17:3464–3477 PubMedGoogle Scholar
  41. Nussberger B, Greminger MP, Grossen C, Keller LF, Wandeler P (2013) Development of SNP markers identifying European wildcats, domestic cats, and their admixed progeny. Mol Ecol Res 13:447–460CrossRefGoogle Scholar
  42. Peterson BK, Weber JN, Kay EH, Fisher HS, Hoekstra HE (2012) Double digest RADseq: an inexpensive method for de novo SNP discovery and genotyping in model and non-model species. PLoS One 7:e37135CrossRefPubMedPubMedCentralGoogle Scholar
  43. Puckett EE, Eggert LS (2016) Comparison of SNP and microsatellite genotyping panels for spatial assignment of individuals to natal range: a case study using the American black bear (Ursus americanus). Biol Conserv 193:86–93CrossRefGoogle Scholar
  44. R Core Team (2013) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
  45. Rasic G, Filipovic I, Weeks AR, Hoffmann AA (2014) Genome-wide SNPs lead to strong signals of geographic structure and relatedness patterns in the major arbovirus vector, Aedes aegypti. BMC Genom 15:275CrossRefGoogle Scholar
  46. Rengmark AH, Slettan A, Skaala Ø, Lie Ø, Lingaas F (2006) Genetic variability in wild and farmed Atlantic salmon (Salmo salar) strains estimated by SNP and microsatellites. Aquaculture 253:229–237CrossRefGoogle Scholar
  47. Roden SE, Morin PA, Frey A et al (2013) Green turtle population structure in the Pacific: new insights from single nucleotide polymorphisms and microsatellites. Endanger Species Res 20:227–234Google Scholar
  48. Russello MA, Waterhouse MD, Etter PD, Johnson EA (2015) From promise to practice: pairing non-invasive sampling with genomics in conservation. PeerJ 3:e1106CrossRefPubMedPubMedCentralGoogle Scholar
  49. Ryynanen HJ, Tonteri A, Vasemagi A, Primmer CR (2007) A comparison of biallelic markers and microsatellites for the estimation of population and conservation genetic parameters in Atlantic salmon (Salmo salar). J Hered 98:692–704Google Scholar
  50. Santure AW, Stapley J, Ball AD, Birkhead TR, Burke T, Slate JON (2010) On the use of large marker panels to estimate inbreeding and relatedness: empirical and simulation studies of a pedigreed zebra finch population typed at 771 SNPs. Mol Ecol 19:1439–1451CrossRefPubMedGoogle Scholar
  51. Sboner A, Mu XJ, Greenbaum D, Auerbach RK, Gerstein MB (2011) The real cost of sequencing: higher than you think! Genome Biol 12:125CrossRefPubMedPubMedCentralGoogle Scholar
  52. Schopen GCB, Bovenhuis H, Visker MHPW, Van Arendonk JAM (2008) Comparison of information content for microsatellites and SNPs in poultry and cattle. Anim Genet 39:451–453CrossRefPubMedGoogle Scholar
  53. Seddon JM, Parker HG, Ostrander EA, Ellegren H (2005) SNPs in ecological and conservation studies: a test in the Scandinavian wolf population. Mol Ecol 14:503–511CrossRefPubMedGoogle Scholar
  54. Sellars MJ, Dierens L, McWilliam S, Little B, Murphy B, Coman GJ, Barendse W, Henshall J (2014) Comparison of microsatellite and SNP DNA markers for pedigree assignment in Black Tiger shrimp, Penaeus monodon. Aquac Res 45:417–426CrossRefGoogle Scholar
  55. Shafer ABA, Wolf JBW, Alves PC, Bergström L, Bruford MW, Brännström I, Colling G, Dalén L, De Meester L, Ekblom R, Fawcett KD, Fior S, Hajibabaei M, Hill JA, Hoezel AR, Höglund J, Jensen EL, Krause J, Kristensen TN, Krützen M, McKay JK, Norman AJ, Ogden R, Österling EM, Ouborg NJ, Piccolo J, Popović D, Primmer CR, Reed FA, Roumet M, Salmona J, Schenekar T, Schwartz MK, Segelbacher G, Senn H, Thaulow J, Valtonen M, Veale A, Vergeer P, Vijay N, Vilà C, Weissensteiner M, Wennerström L, Wheat CW, Zieliński P (2015) Genomics and the challenging translation into conservation practice. Trends Ecol Evol 30:78–87CrossRefPubMedGoogle Scholar
  56. Smith CT, Seeb LW (2008) Number of alleles as a predictor of the relative assignment accuracy of short tandem repeat (STR) and single-nucleotide-polymorphism (SNP) baselines for chum salmon. Trans Am Fish Soc 137:751–762CrossRefGoogle Scholar
  57. Stölting KN, Nipper R, Lindtke D, Caseys C, Waeber S, Castiglione S, Lexer C (2013) Genomic scan for single nucleotide polymorphisms reveals patterns of divergence and gene flow between ecologically divergent species. Mol Ecol 22:842–855CrossRefPubMedGoogle Scholar
  58. Tokarska M, Marshall T, Kowalczyk R, Wojcik JM, Pertoldi C, Kristensen TN, Loeschcke V, Gregersen VR, Bendixen C (2009) Effectiveness of microsatellite and SNP markers for parentage and identity analysis in species with low genetic diversity: the case of European bison. Heredity 103:326–332CrossRefPubMedGoogle Scholar
  59. Vali U, Saag P, Dombrovski V et al (2010) Microsatellites and single nucleotide polymorphisms in avian hybrid identification: a comparative case study. J Avian Biol 41:34–49Google Scholar
  60. Weinman LR, Solomon JW, Rubenstein DR (2015) A comparison of single nucleotide polymorphism and microsatellite markers for analysis of parentage and kinship in a cooperatively breeding bird. Mol Ecol Resour 15:502–511CrossRefPubMedGoogle Scholar
  61. Winton CL, Hegarty MJ, McMahon R et al (2013) Genetic diversity and phylogenetic analysis of native mountain ponies of Britain and Ireland reveals a novel rare population. Ecol Evol 3:934–947Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.Department of Biological Sciences and the Louis Calder Center-Biological Field StationFordham UniversityArmonkUSA

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