Multiplexed shotgun genotyping for rapid and efficient genetic mapping

  1. David L. Stern1,4
  1. 1 Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey 08544, USA;
  2. 2 The Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544, USA;
  3. 3 Department of Statistics, Oxford University, Oxford OX1 3TG, United Kingdom;
  4. 4 Howard Hughes Medical Institute, Princeton University, Princeton, New Jersey 08544, USA

    Abstract

    We present a new approach to genotyping based on multiplexed shotgun sequencing that can identify recombination breakpoints in a large number of individuals simultaneously at a resolution sufficient for most mapping purposes, such as quantitative trait locus (QTL) mapping and mapping of induced mutations. We first describe a simple library construction protocol that uses just 10 ng of genomic DNA per individual and makes the approach accessible to any laboratory with standard molecular biology equipment. Sequencing this library results in a large number of sequence reads widely distributed across the genomes of multiplexed bar-coded individuals. We develop a Hidden Markov Model to estimate ancestry at all genomic locations in all individuals using these data. We demonstrate the utility of the approach by mapping a dominant marker allele in D. simulans to within 105 kb of its true position using 96 F1-backcross individuals genotyped in a single lane on an Illumina Genome Analyzer. We further demonstrate the utility of our method by genetically mapping more than 400 previously unassembled D. simulans contigs to linkage groups and by evaluating the quality of targeted introgression lines. At this level of multiplexing and divergence between strains, our method allows estimation of recombination breakpoints to a median of 38-kb intervals. Our analysis suggests that higher levels of multiplexing and/or use of strains with lower levels of divergence are practicable.

    Footnotes

    • Received September 16, 2010.
    • Accepted January 5, 2011.
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