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Abstract Detail

Population Genetics/Genomics

Wessinger, Carolyn [1], Kelly, John [2], Hileman, Lena [3].

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

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 non-model species has been generating dense genome-wide markers that satisfy the key requirement that marker data is 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 dataset 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.

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1 - University Of Kansas, EEB, 1200 Sunnyside Avenue, Lawrence, KS, 66045, United States
2 - University of Kansas, EEB, 1200 Sunnyside Ave, Lawrence, KS, 66045, USA
3 - University Of Kansas, Ecology And Evolutionary Biology, 1200 Sunnyside Avenue, Lawrence, KS, 66045, United States

multiplexed shotgun genotyping
quantitative trait loci

Presentation Type: Oral Paper
Session: 47, Population Genetics and Genomics II
Location: 101/Mayo Civic Center
Date: Wednesday, July 25th, 2018
Time: 1:45 PM
Number: 47002
Abstract ID:449
Candidate for Awards:None

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