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SNP-skimming: A fast approach to map loci generating quantitative variation in natural populations.

Publication ,  Journal Article
Wessinger, CA; Kelly, JK; Jiang, P; Rausher, MD; Hileman, LC
Published in: Molecular ecology resources
November 2018

Genome-wide association mapping (GWAS) is a method to estimate the contribution of segregating genetic loci to trait variation. A major challenge for applying GWAS to nonmodel species has been generating dense genome-wide markers that satisfy the key requirement that marker data are error-free. Here, we present an approach to map loci within natural populations using inexpensive shallow genome sequencing. This "SNP-skimming" approach involves two steps: an initial genome-wide scan to identify putative targets followed by deep sequencing for confirmation of targeted loci. We apply our method to a test data set of floral dimension variation in the plant Penstemon virgatus, a member of a genus that has experienced dynamic floral adaptation that reflects repeated transitions in primary pollinator. The ability to detect SNPs that generate phenotypic variation depends on population genetic factors such as population allele frequency, effect size and epistasis, as well as sampling effects contingent on missing data and genotype uncertainty. However, both simulations and the Penstemon data suggest that the most significant tests from the initial SNP skim are likely to be true positives-loci with subtle but significant quantitative effects on phenotype. We discuss the promise and limitations of this method and consider optimal experimental design for a given sequencing effort. Simulations demonstrate that sampling a larger number of individual at the expense of average read depth per individual maximizes the power to detect loci.

Duke Scholars

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Published In

Molecular ecology resources

DOI

EISSN

1755-0998

ISSN

1755-098X

Publication Date

November 2018

Volume

18

Issue

6

Start / End Page

1402 / 1414

Related Subject Headings

  • Sequence Analysis, DNA
  • Polymorphism, Single Nucleotide
  • Phenotype
  • Penstemon
  • High-Throughput Nucleotide Sequencing
  • Genotype
  • Genome-Wide Association Study
  • Flowers
  • Evolutionary Biology
  • 06 Biological Sciences
 

Citation

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Wessinger, C. A., Kelly, J. K., Jiang, P., Rausher, M. D., & Hileman, L. C. (2018). SNP-skimming: A fast approach to map loci generating quantitative variation in natural populations. Molecular Ecology Resources, 18(6), 1402–1414. https://doi.org/10.1111/1755-0998.12930
Wessinger, Carolyn A., John K. Kelly, Peng Jiang, Mark D. Rausher, and Lena C. Hileman. “SNP-skimming: A fast approach to map loci generating quantitative variation in natural populations.Molecular Ecology Resources 18, no. 6 (November 2018): 1402–14. https://doi.org/10.1111/1755-0998.12930.
Wessinger CA, Kelly JK, Jiang P, Rausher MD, Hileman LC. SNP-skimming: A fast approach to map loci generating quantitative variation in natural populations. Molecular ecology resources. 2018 Nov;18(6):1402–14.
Wessinger, Carolyn A., et al. “SNP-skimming: A fast approach to map loci generating quantitative variation in natural populations.Molecular Ecology Resources, vol. 18, no. 6, Nov. 2018, pp. 1402–14. Epmc, doi:10.1111/1755-0998.12930.
Wessinger CA, Kelly JK, Jiang P, Rausher MD, Hileman LC. SNP-skimming: A fast approach to map loci generating quantitative variation in natural populations. Molecular ecology resources. 2018 Nov;18(6):1402–1414.
Journal cover image

Published In

Molecular ecology resources

DOI

EISSN

1755-0998

ISSN

1755-098X

Publication Date

November 2018

Volume

18

Issue

6

Start / End Page

1402 / 1414

Related Subject Headings

  • Sequence Analysis, DNA
  • Polymorphism, Single Nucleotide
  • Phenotype
  • Penstemon
  • High-Throughput Nucleotide Sequencing
  • Genotype
  • Genome-Wide Association Study
  • Flowers
  • Evolutionary Biology
  • 06 Biological Sciences