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Identification of sperm morphometric subpopulations in the canineejaculate: do they reflect different subpopulations in sperm chromatinintegrity?

Published online by Cambridge University Press:  01 August 2007

I. Núñez-Martinez
Affiliation:
Veterinary Teaching Hospital, Section of Reproduction and Obstetrics, Department of Herd Health and Medicine, Faculty of Veterinary Medicine, Avd de la Universidad s/n 10071 Cáceres, Spain
J.M. Moran
Affiliation:
Veterinary Teaching Hospital, Section of Reproduction and Obstetrics, Department of Herd Health and Medicine, Faculty of Veterinary Medicine, Avd de la Universidad s/n 10071 Cáceres, Spain
F.J. Peña*
Affiliation:
Veterinary Teaching Hospital, Section of Reproduction and Obstetrics, Department of Herd Health and Medicine, Faculty of Veterinary Medicine, Avd de la Universidad s/n 10071 Cáceres, Spain
*
All correspondence to: F.J. Peña, Sectionof Reproduction and Obstetrics, Department of HerdHealth and Medicine, Faculty of VeterinaryMedicine, Avd de la Universidad s/n10071, Cáceres,Spain. e-mail: fjuanpvega@unex.es
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Summary

A statistical approach using sequentially principal component analysis (PCA)clustering and discriminant analysis was developed to disclose morphometricsperm subpopulations. In addition, we used a similar approach to disclosesubpopulations of spermatozoa with different degrees of DNA fragmentation. It iswidely accepted that sperm morphology is a strong indicator of semen quality andsince the sperm head mainly comprises the sperm DNA, it has been proposed thatsubtle changes in sperm head morphology may be related to abnormal DNA content.Semen from four mongrel dogs (five replicates per dog) were used to investigateDNA quality by means of the sperm chromatin structure assay (SCSA), and forcomputerized sperm morphometry (ASMA). Each sperm head was measured for nineprimary parameters: head area (A), head perimeter (P), head length (L), headwidth (W), acrosome area (%), midpiece width (w), midpiece area (a), distance(d) between the major axes of the head and midpiece, angle (θ) ofdivergence of the midpiece from the head axis; and four parameters of headshape: FUN1 (L/W), FUN2 (4π A/P2),FUN3 ((L – W)/(L + W)) and FUN 4 (πLW/4A). The data matrix consisted of 2361 observations, (morphometricanalysis on individual spermatozoa) and 63 815 observations for the DNAintegrity. The PCA analysis revealed five variables with Eigen values over 1,representing more than 79% of the cumulative variance. The morphometric datarevealed five sperm subpopulations, while the DNA data gave six subpopulationsof spermatozoa with different DNA integrity. Significant differences were foundin the percentage of spermatozoa falling in each cluster among dogs (p < 0.05). Linear regression modelsincluding sperm head shape factors 2, 3 and 4 predicted the amount of denaturedDNA within each individual spermatozoon (p< 0.001). We conclude that the ASMA analysis can be considered apowerful tool to improve the spermiogram.

Information

Type
Research Article
Copyright
Copyright © Cambridge University Press 2007
Figure 0

Table 1 Results of the principal components analysis (PCA) performed on the ASMA data

Figure 1

Figure 1 Example of the subpopulations obtained after the discriminant analysis. Dot plots of the morphometric data defined by the two first principal components (PRIN1 and PRIN2). Each event represents an individual spermatozoon. Clusters are presented individually to facilitate its visualization.

Figure 2

Table 2 Summary of the selected morphometric parameters obtained in this study

Figure 3

Table 3 Distribution of spermatozoa (%) falling in each subpopulation derived from the morphometric analysis within each dog

Figure 4

Table 4 Frequency of distribution of spermatozoa with different degrees of DNA fragmentation

Figure 5

Table 5 Frequency of distribution of spermatozoa in each dog with the low, medium or high percentage of fragmented DNA

Figure 6

Table 6 Distribution of spermatozoa (%) falling into each subpopulation derived from the SCSA analysis within each dog

Figure 7

Table 7 Variables in the equation obtained from a two-stage least squares regression analysis model for the prediction of the relationship between the percentage of denatured DNA within each individual spermatozoa (αt) and ASMA-derived morphometric variables

Figure 8

Figure 2 Predictive value of FUN3 ((L – W)/(L + W)), as a diagnostic test of normality in the amount of fragmented DNA.