A SNP resource for Douglas-fir: De novo transcriptome assembly and SNP detection and validation

Glenn T. Howe, Jianbin Yu, Brian Knaus, Richard Cronn, Scott Kolpak, Peter Dolan, W. Walter Lorenz, Jeffrey F.D. Dean

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    52 Scopus citations

    Abstract

    Background: Douglas-fir (Pseudotsuga menziesii), one of the most economically and ecologically important tree species in the world, also has one of the largest tree breeding programs. Although the coastal and interior varieties of Douglas-fir (vars. menziesii and glauca) are native to North America, the coastal variety is also widely planted for timber production in Europe, New Zealand, Australia, and Chile. Our main goal was to develop a SNP resource large enough to facilitate genomic selection in Douglas-fir breeding programs. To accomplish this, we developed a 454-based reference transcriptome for coastal Douglas-fir, annotated and evaluated the quality of the reference, identified putative SNPs, and then validated a sample of those SNPs using the Illumina Infinium genotyping platform.Results: We assembled a reference transcriptome consisting of 25,002 isogroups (unique gene models) and 102,623 singletons from 2.76 million 454 and Sanger cDNA sequences from coastal Douglas-fir. We identified 278,979 unique SNPs by mapping the 454 and Sanger sequences to the reference, and by mapping four datasets of Illumina cDNA sequences from multiple seed sources, genotypes, and tissues. The Illumina datasets represented coastal Douglas-fir (64.00 and 13.41 million reads), interior Douglas-fir (80.45 million reads), and a Yakima population similar to interior Douglas-fir (8.99 million reads). We assayed 8067 SNPs on 260 trees using an Illumina Infinium SNP genotyping array. Of these SNPs, 5847 (72.5%) were called successfully and were polymorphic.Conclusions: Based on our validation efficiency, our SNP database may contain as many as ~200,000 true SNPs, and as many as ~69,000 SNPs that could be genotyped at ~20,000 gene loci using an Infinium II array-more SNPs than are needed to use genomic selection in tree breeding programs. Ultimately, these genomic resources will enhance Douglas-fir breeding and allow us to better understand landscape-scale patterns of genetic variation and potential responses to climate change.

    Original languageEnglish (US)
    Article number137
    JournalBMC Genomics
    Volume14
    Issue number1
    DOIs
    StatePublished - Feb 28 2013

    Bibliographical note

    Funding Information:
    This work was funded by the US Department of Agriculture (USDA) National Research Initiative CSREES (Plant Genomics Coordinated Agricultural Project Award #2007-55300-18603); USDA National Institute of Food and Agriculture, Agriculture and Food Research Initiative (Applied Plant Genomics CAP Award #2009-85606-05680 and Plant Genome, Genetics and Breeding Program Award #2010-65300-20166); USDA Forest Service Rocky Mountain Research Station; US Department of Energy Joint Genome Institute (JGI) Community Sequencing Program; and the members of the Pacific Northwest Tree Improvement Research Cooperative. We thank Samuel Cushman, Barry Jaquish, Marc Rust, and Andrew Shirk for helping with the Interior Douglas-fir collections; Jim Smith, Mike Albrecht, and Joanna Warren for helping with the coastal Douglas-fir collections; Dana Howe for preparing the CBIL and YKIL RNA samples and organizing the Sanger sequencing; George Newcombe for information on the bacterial and fungal contaminants; David Neale, Gancho Slavov, Nicholas Wheeler, and Jill Wegrzyn for methodological suggestions; Randi Famula for isolating the DNA used for SNP genotyping; Vanessa Rashbrook for helping with the SNP genotyping; Alvaro Hernandez and other staff of the University of Illinois Roy J. Carver Biotechnology Center for performing 454 and Illumina sequencing; Aaron Liston and Christopher Sullivan for guidance on the use of the computing facilities at OSU’s Center for Genome Research and Biocomputing; Elaine Blampied and Annie Simmonds for help with manuscript preparation; and the other co-PIs on the JGI project that produced one of the 454 datasets (Kathleen Jermstad, David Neale, and Deborah Rogers).

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