efficient high-throughput flow cytometric method for estimating DNA ploidy level in plants

• Published in: Cytometry. Part A Vol. 75A; no. 12; pp. 1015 - 1019
• Main Authors: Cousin, A, Heel, K, Cowling, W.A, Nelson, M.N
• Format: Journal Article
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.12.2009
• Subjects: Brassica napus; Brassica napus - cytology; Brassica napus - genetics; canola; Cell Nucleus - metabolism; DNA, Plant - genetics; doubled haploid; endopolyploidy; flow cytometry; Flow Cytometry - methods; Fluorescence; Germ Cells, Plant - metabolism; High-Throughput Screening Assays - methods; high‐throughput method; microspore culture; plant breeding; Ploidies; ploidy analysis; Propidium - metabolism; taxonomy
• ISSN: 1552-4922; 1552-4930
• DOI: 10.1002/cyto.a.20816

We present an efficient high-throughput flow cytometric method that builds on previously published methods and permits rapid ploidy discrimination in plants. By using Brassica napus L. microspore-derived plants as an example, we describe how 192 leaf tissue samples may be processed and analyzed comfortably by one operator in 6 h from tissue sampling to ploidy determination. The technique involves placing young leaf samples in two 96-well racks, using a bead-beating procedure to release nuclei into a lysis solution, filtering the samples on 96-well filter plates, staining with propidium iodide, and then rapidly estimating DNA ploidy using a plate loader on a BD FACSCanto II flow cytometer. Throughout the sample preparation process, multichannel pipetting allows faster and less error-prone sample handling. In two 96-well plates of samples, the histogram peaks of DNA content from flow cytometry were wellresolved in 189 of 192 samples tested (98.4%), with CV values ranging from 2.98% to 6.20% with an average CV of 4.35% (SD = 0.68%). This new method is usefulin doubled haploid plant breeding programs where early discrimination of haploid and doubled haploid (i.e., diploid) plantlets can confer significantly improved operational efficiencies. We discuss how this method could be further refined including adapting the method to robotic sample processing. © 2009 International Society for Advancement of Cytometry