|Lutz, J. -|
|Rubenfield, M. -|
|Tinker, N. -|
|Anderson, J. -|
|Wisniewski-Morehead, N. -|
|Adhikary, D. -|
|Jellen, E. -|
|Maughan, P. -|
|Beattie, A. -|
|Rines, H. -|
Submitted to: Biomed Central (BMC) Genomics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: January 27, 2011
Publication Date: January 27, 2011
Citation: Oliver, R.E., Lazo, G.R., Lutz, J.D., Rubenfield, M.J., Tinker, N.A., Anderson, J.M., Wisniewski-Morehead, N.H., Adhikary, D., Jellen, E.N., Maughan, P.J., Brown Guedira, G.L., Chao, S., Beattie, A.D., Carson, M.L., Rines, H.W., Obert, D.E., Bonman, J.M., Jackson, E.W. 2011. Model SNP development based on the complex oat genome using high-throughput 454 sequencing technology. Biomed Central (BMC) Genomics. 12:77. Interpretive Summary: Many complications including size and complexity have hindered the development of molecular “mile” markers and the construction of a complete set of “road maps” to the oat genome. Scientist from across the globe led by the ARS Aberdeen molecular biology laboratory have developed a new method for discovering the genetic mile markers known as SNPs. This research has opened the way for large-scale discovery of additional SNP markers in oat and other crops with complex genomes. Overall this work will provide the foundation for developing genetic “road signs” for key traits affecting crop productivity and benefits to human health.
Technical Abstract: Genetic markers are pivotal to modern genomics research; however, discovery and genotyping of molecular markers in oat has been hindered by the size and complexity of the genome, and by a scarcity of sequence data. The purpose of this study was to generate oat expressed sequence tag (EST) information, develop a bioinformatics pipeline for SNP discovery, and establish a method for rapid and cost-effective genotyping of SNP markers for complex polyploid genomes. Based on cDNA libraries of four cultivated oat genotypes, approximately 127,000 contigs were assembled from over one million Roche 454 sequence reads. Contigs were filtered through a novel bioinformatics pipeline to eliminate ambiguous polymorphism caused by subgenome homology, and 96 in silico SNPs were selected from 9,448 candidate loci for validation using high-resolution melting (HRM) analysis. Of these, 53 (55%) were polymorphic on the ‘Ogle1040’ x ‘TAM-O-301’ (OT) mapping population comprising 134 recombinant inbred lines. Forty-eight of the 55 SNP markers were clearly differentiated as a single locus and 44 loci were firmly placed on the existing OT linkage map. Ogle and TAM amplicons from 12 primers were sequenced for false discovery analysis, revealing complex polymorphism in seven amplicons but general sequence conservation within SNP loci. Whole-amplicon interrogation with HRM revealed insertions, deletions, and heterozygotes in secondary oat germplasm pools, generating multiple alleles at some primer targets. Based on this observation, 36 polymorphic markers were used to analyze the genetic diversity of 34 diverse oat genotypes. Dendrogram clusters corresponded generally to genome composition and genetic ancestry. The high-throughput SNP discovery pipeline presented here is a relatively fast and effective method for identification of oat SNP markers. Additionally, current-generation HRM is a simple and highly-informative platform for SNP genotyping. These techniques provide a model for SNP discovery in other species with complex and little-characterized genomes.