|Freeman, Barbara - Barbie|
Submitted to: HortScience
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/1/2009
Publication Date: 8/1/2009
Citation: Livingstone, D., Freeman, B.L., Tondo, C.L., Cariaga, K.A., Kuhn, D.N. 2009. Improvement of High-throughput Genotype Analysis After Implementation of a Dual-curve Sybr Green I-based Quantification and Normalization Procedure. HortScience. 44: 1228-1232.
Interpretive Summary: Researchers working to improve breeding programs using marker-assisted selection often need to obtain DNA from a large number of samples. To evaluate this DNA, whether for genotyping or sequence analysis, it is often helpful to measure the amount of DNA present in each sample. Due to the large number of samples, this quantification process can be prohibitively time consuming, leading to estimations based on the average of a subset of samples. These estimates are inaccurate and as such will negatively effect downstream applications. We describe a quantification method that uses a fluorescent dye, is performed in a 96 well plate format, and has been automated. This method provides a rapid and simple way to quantify and normalize all DNA samples. The downstream effects of using this protocol are detailed. This method can be applied to any system not just plants. Thus, this work could prove beneficial to any researcher working with a large number of DNA samples.
Technical Abstract: The ability to rapidly screen a large number of individuals is the key to any successful plant breeding program. One of the primary bottlenecks in high throughput screening is the preparation of DNA samples, particularly the quantification and normalization of samples for downstream processing. A rapid and simple Sybr Green I based quantification procedure that can be performed in a 96 well format is outlined. In this procedure a dual standard curve method is employed to allow better resolution of dilute samples, and to reduce fluorescence value variation between samplings. A way to quickly normalize samples, and the importance of the normalization of samples, is also explored. We demonstrate that successful microsatellite amplification of a Theobroma grandiflora population is increased from 70% to 98% when quantifying every sample, as opposed to a random subset. Additionally, when a Persea americana population is normalized to 4ng/ul, 97% of the samples amplify at least 3 out of 6 microsatellite markers, where as only 30% of the samples below 4ng/ul amplify at least 3 markers. This manuscript describes an undemanding method, that has been automated, to quantify and normalize a large number of samples.