Skip to main content

Sampling in Landscape Genomics

  • Protocol
  • First Online:

Part of the book series: Methods in Molecular Biology ((MIMB,volume 888))

Abstract

Landscape genomics, based on the sampling of individuals genotyped for a large number of markers, may lead to the identification of regions of the genome correlated to selection pressures caused by the environment. In this chapter, we discuss sampling strategies to be used in a landscape genomics approach. We suggest that designs based on model-based stratification using the climatic and/or biological spaces are in general more efficient than designs based on the geographic space. More work is needed to identify designs that allow disentangling environmental selection pressures versus other processes such as range expansions or hierarchical population structure.

This is a preview of subscription content, log in via an institution.

Buying options

Protocol
USD   49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   139.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Springer Nature is developing a new tool to find and evaluate Protocols. Learn more

References

  1. Stinchcombe JR, Hoekstra HE (2008) Combining population genomics and quantitative genetics: finding the genes underlying ecologically important traits. Heredity 100:158–170

    Article  PubMed  CAS  Google Scholar 

  2. Joost S, Bonin A, Bruford MW et al (2007) A spatial analysis method (SAM) to detect candidate loci for selection: towards a landscape genomics approach to adaptation. Mol Ecol 16:3955–3969

    Article  PubMed  CAS  Google Scholar 

  3. Luikart G, England PR, Tallmon D et al (2003) The power and promise of population genomics: from genotyping to genome typing. Nat Rev Genet 4:981–994

    Article  PubMed  CAS  Google Scholar 

  4. Muirhead JR, Gray DK, Kelly DW et al (2008) Identifying the source of species invasions: sampling intensity vs. genetic diversity. Mol Ecol 17:1020–1035

    Article  PubMed  CAS  Google Scholar 

  5. Storfer A, Murphy MA, Evans JS et al (2007) Putting the ‘landscape’ in landscape genetics. Heredity 98:128–142

    Article  PubMed  CAS  Google Scholar 

  6. Schwartz MK, McKelvey KS (2009) Why sampling scheme matters: the effect of sampling scheme on landscape genetic results. Conserv Genet 10:441–452

    Article  Google Scholar 

  7. Ehrich D, Yoccoz NG, Ims RA (2009) Multi-annual density fluctuations and habitat size enhance genetic variability in two northern voles. Oikos 118:1441–1452

    Article  Google Scholar 

  8. Epperson BK, McRae B, Scribner K et al (2010) Utility of computer simulations in landscape genetics. Mol Ecol 19:3549–3564

    Article  PubMed  Google Scholar 

  9. Poncet B, Herrmann D, Gugerli F et al (2010) Tracking genes of ecological relevance using a genome scan: application to Arabis alpina. Mol Ecol 19:2896–2907

    Article  PubMed  CAS  Google Scholar 

  10. Turner JRG (2010) Population resequencing reveals local adaptation of Arabidopsis lyrata to serpentine soils. Nat Genet 42:260–263. doi:10.38/ng.515

    Google Scholar 

  11. Cushman SA, Landguth E (2010) Spurious correlations and inference in landscape genetics. Mol Ecol 19:4179–4191

    Article  Google Scholar 

  12. Williams BK, Nichols JD, Conroy MJ (2002) Analysis and management of animal populations. Academic, San Diego

    Google Scholar 

  13. Little RJ (2004) To model or not to model? Competing modes of inference for finite population sampling. J Am Stat Assoc 99:546–556

    Article  Google Scholar 

  14. Albert C, Yoccoz N, Edwards T et al (2010) Sampling in ecology and evolution – bridging the gap between theory and practice. Ecography 33:1028–1037

    Article  Google Scholar 

  15. Box G, Hunter W, Hunter J (2005) Statistics for experimenters. Design, innovation, and discovery, 2nd edn. Wiley, Hoboken

    Google Scholar 

  16. Inouye BD (2001) Response surface experimental designs for investigating interspecific competition. Ecology 82:2696–2706

    Article  Google Scholar 

  17. Excoffier L, Foll M, Petit RJ (2009) Genetic consequences of range expansions. Ann Rev Ecol Evol S40:481–501

    Article  Google Scholar 

  18. Excoffier L, Hofer T, Foll M (2009) Detecting loci under selection in a hierarchically structured population. Heredity 103:285–298

    Article  PubMed  CAS  Google Scholar 

  19. Bradbury PJ, Zhang Z, Kroon DE et al (2007) TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics 23:2633–2635

    Article  PubMed  CAS  Google Scholar 

  20. Yu JM, Pressoir G, Briggs WH et al (2006) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet 38:203–208

    Article  PubMed  CAS  Google Scholar 

  21. Hutchinson GE (1957) Concluding remarks. Cold Spring Harb Symp Quant Biol 22:145–159

    Article  Google Scholar 

  22. Diniz-Filho JAF, Nabout JC, Telles MPD et al (2009) A review of techniques for spatial modeling in geographical, conservation and landscape genetics. Genet Mol Biol 32:203–211

    Article  PubMed  Google Scholar 

  23. Manel S, Joost S, Epperson B et al (2010) Perspectives on the use of landscape genetics to detect genetic adaptive variation in the field. Mol Ecol 19:3760–3772

    Article  PubMed  CAS  Google Scholar 

  24. Borcard D, Legendre P (2002) All-scale spatial analysis of ecological data by means of principal coordinates of neighbour matrices. Ecol Model 153:51–68

    Article  Google Scholar 

  25. Dray S, Legendre P, Peres-Neto PR (2006) Spatial modelling: a comprehensive framework for principal coordinate analysis of neighbour matrices (PCNM). Ecol Model 196:483–493

    Article  Google Scholar 

  26. Dengler J, Oldeland J (2010) Effects of sampling protocol on the shapes of species richness curves. J Biogeogr 37:1698–1705

    Article  Google Scholar 

  27. Brito JC, Crespo EG, Paulo OS (1999) Modelling wildlife distributions: logistic multiple regression vs overlap analysis. Ecography 22:251–260

    Article  Google Scholar 

  28. Singh NJ, Yoccoz NG, Bhatnagar YV, Fox JL (2009) Using habitat suitability models to sample rare species in high-altitude ecosystems: a case study with Tibetan argali. Biodivers Conserv 18:2893–2908

    Article  Google Scholar 

  29. Guisan A, Broennimann O, Engler R et al (2006) Using niche-based models to improve the sampling of rare species. Conserv Biol 20:501–511

    Article  PubMed  Google Scholar 

  30. Bridle JR, Polechova J, Kawata M, Butlin RK (2010) Why is adaptation prevented at ecological margins? New insights from individual-based simulations. Ecol Lett 13:485–494

    Article  PubMed  Google Scholar 

  31. Kawecki TJ (2008) Adaptation to marginal habitats. Ann Rev Ecol Evol S39:321–342

    Article  Google Scholar 

  32. Petit RJ, Excoffier L (2009) Gene flow and species delimitation. Trends Ecol Evol 24:386–393

    Article  PubMed  Google Scholar 

  33. Storey JD, Tibshirani R (2003) Statistical significance for genome wide studies. Proc Natl Acad Sci USA 100:9440–9445

    Article  PubMed  CAS  Google Scholar 

  34. Manel S, Poncet B, Legendre P et al (2010) Common factors drive adaptive genetic variation at different spatial scales in Arabis alpina. Mol Ecol 19:3824–3835

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Stéphanie Manel .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer Science+Business Media New York

About this protocol

Cite this protocol

Manel, S., Albert, C.H., Yoccoz, N.G. (2012). Sampling in Landscape Genomics. In: Pompanon, F., Bonin, A. (eds) Data Production and Analysis in Population Genomics. Methods in Molecular Biology, vol 888. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-61779-870-2_1

Download citation

  • DOI: https://doi.org/10.1007/978-1-61779-870-2_1

  • Published:

  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-61779-869-6

  • Online ISBN: 978-1-61779-870-2

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics