Comparison of Canine Spermatozoal RNA Concentrations and Purity Using Two Density Gradient Centrifugation Solutions

Introduction
Sperm must be separated from other cells in the ejaculate prior to RNA isolation in order to provide a pure sample for analysis of genetic causes of infertility. Several methods for elimination of contaminating somatic cells have been described, including swim-up and density gradient centrifugation (DGC). In a previous study, we found the swim-up method yielded fewer morphologically normal sperm than DGC.1 The objective of this study was to compare RNA concentration and purity following separation of dog sperm by DGC products commercialized for horses and cattle. Because of the two layer density gradient, we hypothesized that the cattle product would be more effective at removing somatic cells, yielding a purer sperm RNA sample.

Methods
Semen was manually collected up to six times from eight dogs and divided into three aliquots of equal volume. Two DGC products were used according to the manufacturer’s instructions (Equipure™ and Bovipure™, Nidacon International, Mölndal, Sweden), while no cell separation technique was applied to the control samples. Total RNA was isolated using Trizol® reagent (Ambion®, Carlsbad, CA) according to the manufacturer’s instructions. RNA concentration was determined spectrophotometrically with a NanoPhotometer® (IMPLEN, Munich, Germany). Primers specific for canine sperm gene protamine-2 (PRM2) were designed using Primer3 software and information from the NCBI gene bank. Primers were synthesized by Sigma-Aldrich (St. Louis, MO). Gene specific transcripts were reversetranscribed from the total RNA using Superscript® One-Step RT-PCR with Platinum® Taq kit (Invitrogen™, Carlsbad, CA) according to the manufacturer’s instructions. Results were visualized on 2% agarose gels stained with SYBR® Green nucleic acid gel stain (Invitrogen™, Carlsbad, CA) utilizing the GelLogic 212 Pro Imaging System (Carestream Health, Woodbridge, CT). RNA concentrations and purity were compared between separation methods using a PROC MIXED platform in SAS (V.9.3, SAS Institute Inc, Cary, NC). Data were reported as least squares means±SEM.  […]