An Accurate Method for Measuring Triploidy of Larval Fish Spawns

Abstract

A standard flow cytometric protocol was developed for estimating triploid induction in batches of larval fish. Polyploid induction treatments are not guaranteed to be 100% efficient, thus the ability to quantify the proportion of triploid larvae generated by a particular treatment helps managers to stock high-percentage spawns and researchers to select treatments for efficient triploid induction. At 3 d posthatch, individual Grass Carp Ctenopharyngodon idella were mechanically dissociated into single-cell suspensions; nuclear DNA was stained with propidium iodide then analyzed by flow cytometry. Following ploidy identification of individuals, aliquots of diploid and triploid cell suspensions were mixed to generate 15 levels (0–100%) of known triploidy (n = 10). Using either 20 or 50 larvae per level, the observed triploid percentages were lower than the known, actual values. Using nonlinear regression analyses, quadratic equations solved for triploid proportions in mixed samples and corresponding estimation reference plots allowed for predicting triploidy. Thus, an accurate prediction of the proportion of triploids in a spawn can be made by following a standard larval processing and analysis protocol with either 20 or 50 larvae from a single spawn, coupled with applying the quadratic equations or reference plots to observed flow cytometry results. Due to the universality of triploid DNA content being 1.5 times the diploid level and because triploid fish consist of fewer cells than diploids, this method should be applicable to other produced triploid fish species, and it may be adapted for use with bivalves or other species where batch analysis is appropriate.

Received August 15, 2016; accepted February 13, 2017Published online May 22, 2017

ACKNOWLEDGMENTS

The authors respectfully recognize the previous contributions of the late Dr. E. Barry Moser, Department of Experimental Statistics, Louisiana State University, Baton Rouge. The collaborations with Keo Fish Farms, Inc., Keo, Arkansas and Claude E. Reeves of Auburn University are appreciated. Assistance with graphics was graciously provided by Bogdan Chivoiu and Lori Randall, WARC. Anonymous reviewers are thanked for helpful suggestions. This project was in part supported by the U.S. Geological Survey Invasive Species Program. The authors declare no competing financial interest. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.