|Nicholas, Cryer - UNIV OF READING, UK|
|Ford, Caroline - UNIV OF READING, UK|
|Hemeida, Alaa - GEBRI, EGYPT|
|Saunders, James - MB3, TOWSON UNIV, MD|
Submitted to: Crop Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: April 14, 2006
Publication Date: September 8, 2006
Citation: Zhang, D., Mischke, B.S., Goenaga, R.J., Nicholas, C., Ford, C., Hemeida, A.A., Saunders, J.A. 2006. Accuracy and reliability of high-throughput microsatellite genotyping for cacao cultivar identification. Crop Science. 46:2084-2092. Interpretive Summary: Cocoa is the source of cocoa butter and powder for the confectionery industry. Conservation of cocoa genetic resources is of great importance for a sustainable cocoa economy in the world. DNA technology is a very powerful tool for management of cocoa genetic resources. However, this technique is not an error free science. Errors can cause misinterpretation of data and delay efforts in breeding new cocoa varities if they are not fixed. Through this study, we assessed the error rate using DNA technology and its impact on cocoa cultivar identification and developed an efficient protocol for the reduction of mislabeling in the cocoa collections. These results will contribute to a more efficient management of cocoa collections and breeding of better cocoa varieties thus benefiting the chocolate consumers and cocoa farmers in the world.
Technical Abstract: Microsatellite-based DNA fingerprinting has been increasingly applied to genotype identification in cacao research programs. Despite the use of highly robust fingerprinting protocols, the accuracy and reliability of cacao genotype identification have been affected by genotyping errors, which potentially mislead the downstream analysis. An optimal scheme that overcomes the genotyping errors is essential for cacao germplasm management. Such a scheme is determined by the discriminating power of the proposed set of microsatellite loci, and the rate of genotyping errors at each locus. In this paper, we quantified the genotyping error rate through repeated genotyping, and simulated the impact of the genotyping error on cacao individual identification. We then calculated the probability of identity for the 15 selected microsatellite loci. Allelic dropout (ADO) and false allele (FA) accounted for 49.42% and 50.6% of the genotyping inconsistencies, respectively. The result of simulation showed that a consensus genotype can be generated for the ambiguous loci through three PCR replications. We further verified the differentiation power of the 15 loci using 40 self-pollinated progenies derived from a single parent tree. The mismatch distribution demonstrates that when the 15 loci are genotyped, the self-pollinated progenies are likely to differ by at least three loci. Based on the error rate and probability of identity (PID), we designed a genotyping scheme and applied it to the cacao germplasm held in the USDA cacao collection in Mayaguez, Puerto Rico. Out of the 141 samples, we unambiguously identified nine duplicated groups consisting of 34 cacao accessions. This genotyping scheme is being implemented in large scale fingerprinting of cacao germplasm in order to reduce redundancies and mislabeling in these collections.