Abstract
Chromatin status is critical for sperm fertility and reflects spermatogenic success. We tested a multivariate approach for studying pig sperm chromatin structure to capture its complexity with a set of quick and simple techniques, going beyond the usual assessment of DNA damage. Sperm doses from 36 boars (3 ejaculates/boar) were stored at 17 °C and analyzed on days 0 and 11. Analyses were: CASA (motility) and flow cytometry to assess sperm functionality and chromatin structure by SCSA (%DFI, DNA fragmentation; %HDS, chromatin maturity), monobromobimane (mBBr, tiol status/disulfide bridges between protamines), chromomycin A3 (CMA3, protamination), and 8-hydroxy-2'-deoxyguanosine (8-oxo-dG, DNA oxidative damage). Data were analyzed using linear models for the effects of boar and storage, correlations, and multivariate analysis as hierarchical clustering and principal component analysis (PCA). Storage reduced sperm quality parameters, mainly motility, with no critical oxidative stress increases, while chromatin status worsened slightly (%DFI and 8-oxo-dG increased while mBBr MFI-median fluorescence intensity-and disulfide bridge levels decreased). Boar significantly affected most chromatin variables except CMA3; storage also affected most variables except %HDS. At day 0, sperm chromatin variables clustered closely, except for CMA3, and %HDS and 8-oxo-dG correlated with many variables (notably, mBBr). After storage, the relation between %HDS and 8-oxo-dG remained, but correlations among other variables disappeared, and mBBr variables clustered separately. The PCA suggested a considerable influence of mBBr on sample variance, especially regarding storage, with SCSA and 8-oxo-dG affecting between-sample variability. Overall, CMA3 was the least informative, in contrast with results in other species. The combination of DNA fragmentation, DNA oxidation, chromatin compaction, and tiol status seems a good candidate for obtaining a complete picture of pig sperm nucleus status. It raises many questions for future molecular studies and deserves further research to establish its usefulness as a fertility predictor in multivariate models. The usefulness of CMA3 should be clarified.