Genome-enabled hitchhiking mapping identifies QTLs for stress resistance in natural Drosophila

S. V. Nuzhdin, L. G. Harshman, M. Zhou, K. Harmon

Research output: Contribution to journalArticlepeer-review

25 Scopus citations


Identification of genes underlying complex traits is an important problem. Quantitative trait loci (QTL) are mapped using marker-trait co-segregation in large panels of recombinant genotypes. Most frequently, recombinant inbred lines derived from two isogenic parents are used. Segregation patterns are also studied in pedigrees from multiple families. Great advances have been made through creative use of these techniques, but narrow sampling and inadequate power represent strong limitations. Here, we propose an approach combining the strengths of both techniques. We established a mapping population from a sample of natural genotypes, and applied artificial selection for a complex character. Selection changed the frequencies of alleles in QTLs contributing to the selection response. We infer QTLs with dense genotyping microarrays by identifying blocks of linked markers undergoing selective changes in allele frequency. We demonstrated this approach with an experimental population composed from 20 isogenic strains. Selection for starvation survival was executed in three replicated populations with three control non-selected populations. Three individuals per population were genotyped using Affymetrix GeneChips. Two regions of the genome, one each on the left arms of the second and third chromosomes, showed significant divergence between control and selected populations. For the former region, we inferred allele frequencies in selected and control populations by pyrosequencing. We conclude that the allele frequency difference, averaging approximately 40% between selected and control lines, contributed to selection response. Our approach can contribute to the fine scale decomposition of the genetics of direct and indirect selection responses, and genotype by environment interactions.

Original languageEnglish (US)
Pages (from-to)313-321
Number of pages9
Issue number3
StatePublished - Sep 30 2007


  • Complex traits
  • Natural variation
  • Stress resistance

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

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