Location: Plant, Soil and Nutrition ResearchTitle: Mining conifers’ mega-genome using rapid and efficient multiplexed high-throughput genotyping-by-sequencing (GBS) SNP discovery platform
|CHARLES, CHEN - Cornell University - New York|
|MITCHELL, SHARON - Cornell University - New York|
|ELSHIRE, ROBERT - Cornell University - New York|
|Buckler, Edward - Ed|
|EL-KASSABY, YOUSRY - University Of British Columbia|
Submitted to: Tree Genetics and Genomes
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/5/2013
Publication Date: 9/14/2013
Citation: Charles, C., Mitchell, S., Elshire, R.J., Buckler IV, E.S., El-Kassaby, Y.A. 2013. Mining conifers’ mega-genome using rapid and efficient multiplexed high-throughput genotyping-by-sequencing (GBS) SNP discovery platform. Tree Genetics and Genomes. 9(6):1537-1544.
Interpretive Summary: Conifers are of immense economic value, primarily for timber and paper production. However, due to the size and complexity of the genome, coniferous tree species present an unparalleled challenge in obtaining high genome-wide coverage molecular markers. Many of the modern genomic techniques, for example of genomic selection, are inapplicable, as a result. In this research, we develop the next-generation sequencing technology, namely Genotyping-by-sequencing (GBS), for two unreferenced conifer species, lodgepole pine and white spruce. Without the aid of reference information, GBS technique successfully generates about 60,000 single nucleotide polymorphisms (SNPs) for each of the species, and further enables a number of large-scale genomic prediction projects for forestry and forest management.
Technical Abstract: Next-generation sequencing (NGS) technologies are revolutionizing both medical and biological research through generation of massive SNP data sets for identifying heritable genome variation underlying key traits, from rare human diseases to important agronomic phenotypes in crop species. We evaluated the performance of genotyping-by-sequencing (GBS), one of the emerging NGS-based platforms, for genotyping two economically important conifer species, lodgepole pine (Pinus contorta) and white spruce (Picea glauca). Both species have very large genomes (>20,000 Mbp), are highly heterozygous, and lack reference sequences. From a small set (six accessions each) of independent replicated DNA samples and a 48-plex read depth, we obtained ~60,000 SNPs per species. After stringent filtering, we obtained 17,765 and 17,845 high-coverage SNPs without missing data for lodgepole pine and white spruce, respectively. Our results demonstrated that GBS is a robust and suitable method for genotyping conifers. The application of GBS to forest tree breeding and genomic selection is discussed.