Location: Sustainable Perennial Crops LaboratoryTitle: Selecting a core set of nuclear SNP markers for molecular characterization of Arabica coffee (Coffea arabica L.) genetic resources
|SOLANO, WILLIAM - Catie Tropical Agricultural Research|
|FUYUAN, SU - Wuhan University|
|INFANTE, FRANCISCO - Ecosur|
Submitted to: Conservation Genetics Resources
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/28/2021
Publication Date: 3/5/2021
Citation: Zhang, D., Vega, F.E., Solano, W., Fuyuan, S., Infante, F., Meinhardt, L.W. 2021. Selecting a core set of nuclear SNP markers for molecular characterization of Arabica coffee (Coffea arabica L.) genetic resources. Conservation Genetics Resources. https://doi.org/10.1007/s12686-021-01201-y.
Interpretive Summary: Accuracy and efficiency are essential for coffee germplasm management, exchange and utilization in breeding new varieties. Technology of DNA fingerprinting that allows high through-put genotyping and data comparison across different laboratories has not been available for Arabica coffee. The present study screened 672 candidate SNPs from a public database and validated them using 130 coffee varieties sampled from the international coffee collection maintained in Costa Rica. A core panel of 96 markers was selected, based on their stability, differentiation power and diversity representativeness. This genotyping panel is suitable for coffee germplasm conservation and crop improvement, including varietal identification, seeds testing and nursery accreditation and coffee bean authentication. This information will be used by scientist, coffee breeders and extension staff to conserve and use coffee genetic resources. It also has significant implications for improved efficiency in seeds system, varietal registration and nursery accreditation for Arabica coffee.
Technical Abstract: Coffee is the most important beverage crops in the world in terms of commercial value. The economic impact to the coffee industry in the United States is over 200 billion. Conservation of coffee germplasm is being done by maintaining living trees in field genebanks in tropical regions. Accuracy and efficiency are essential for coffee germplasm management, exchange and utilization in breeding new varieties. However, accurate identification of Arabica coffee germplasm has not been fully achieved. Specifically, a universal platform that allows data comparison across different laboratories and genotyping platforms has not been available. Here, we screened 672 candidate SNPs using Nano-Fluidic Array genotyping. Based on call rate, Minor Allele Frequency (MAF) and Linkage Disequilibrium (LD), we selected a set of 96 SNPs for genotyping Coffea Arabica. This panel is suitable for coffee germplasm conservation and crop improvement, including varietal identification, seeds and nursery accreditation and coffee bean authentication.