Multivariate cluster analysis to study motility activation of Solea senegalensis spermatozoa: a model for marine teleosts

Martínez‐Pastor, Felipe; Cabrita, Elsa; Soares, Florbela; Anel, L.; Dinis, María Teresa

doi:10.1530/rep-07-0376

Cited by 64 publications

(55 citation statements)

References 40 publications

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“…This approach 83 promises a deeper understanding of the inner dynamics of the sperm sample, since its intrinsic 84 heterogeneity is taken into account (Holt and Harrison, 2002;Martinez-Pastor et al, 2005a). 85 Subpopulation analysis has been applied in a few studies in fishes: Sole fish (Solea senegalensis) (Beirão 86 et al, 2009;Martínez-Pastor et al, 2008), sea bream (Sparus aurata) (Beirão et al, 2011), three-spined 87 stickleback (Gasterosteus aculeatus) (Le Comber et al, 2004) and steelhead (Oncorhynchus mykiss) 88 (Kanuga et al, 2012). In these studies, 3-4 subpopulations of spermatozoa were identified, one of them 89 being defined as more desirable (containing fast and linearly motile cells) (Beirão et al, 2009; 90 Martínez-Pastor et al, 2008).…”

Section: Csiro Publishingmentioning

confidence: 99%

“…In the present study, we have adapted an unsupervised cluster analysis from previous studies on 92 sperm classification (Martinez-Pastor et al, 2005b;Martínez-Pastor et al, 2008; Domínguez-Rebolledo 93 et al, 2011), in order to discover the subpopulation structure of European eel sperm, and to apply this 94 information to improve our knowledge on the effect of thermal and hormonal treatments on the 95 spermatogenesis and sperm quality in this species. Since there is no prior knowledge about the 96 subpopulational structure of eel spermatozoa, we performed a previous cluster analysis on sperm samples 97 obtained following a standard protocol, at different times after activation.…”

Section: Csiro Publishingmentioning

confidence: 99%

See 1 more Smart Citation

Subpopulation pattern of eel spermatozoa is affected by post-activation time, hormonal treatment and the thermal regimen

Gallego

Vílchez

Peñaranda

et al. 2015

Reprod. Fertil. Dev.

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CSIRO PublishingGallego Albiach, V.; Vilchez Olivencia, MC.; Peñaranda, D.; Pérez Igualada, LM.; Herraez, MP.; Asturiano Nemesio, JF.; Martinez-Pastor, F. (2015). The subpopulation pattern of eel sperm is affected by post-activation time, hormonal treatment and thermal regime. Reproduction, Fertility and Development. 27(3):529-543. doi:10.1071/RD13198. Natural stocks of eels (genus Anguilla) have suffered a dramatic reduction in the last 60 years, and 16 aquaculture is based in the capture of huge quantities of juveniles. It is necessary closing the life cycle in 17 captivity to lift the pressure on wild populations. We have aimed at the evaluation of sperm 18 subpopulations (cluster analysis of computer-assisted sperm analysis -CASA-data) in European eel 19 (Anguilla anguilla), assessing the effects of acquisition time (30, 60 and 90 s post-activation), thermal 20 regimes (variable: T10 and T15, constant: T20) and hormonal treatments (hCG, hCG rec or PMSG). In all 21 cases, we obtained three subpopulations: low velocity and linearity (S1), high velocity and low linearity 22 (S2) and high velocity and linearity (S3, considered high-quality). Total motility and S1 were affected by 23 acquisition time, thus recommending 30 s. T20 data fitted quadratic models, with the highest motility and 24 S3 between weeks 8 and 12 after the first injection. T10 and T15 delayed spermiation and the obtention 25 of high-quality sperm (S3), but did not seem to alter the spermiation process (similar subpopulation 26 pattern). Hormonal treatments differed greatly both on the onset of spermiation (PMSG delaying it) and 27 on the dynamics of the subpopulation pattern. Motility and S3 yield of the widely used hCG were very 28 variable. However, hCG rec allowed to obtain good motility for most of the study (weeks 7 to 20), and S3 29 yield was overall higher (61.8%±1.3) and more stable along time than the other hormonal treatments 30(averaging 53.0%±1.4). Economically, T20 and hCG rec were more effective, allowing to obtain a higher 31 number of S3 spermatozoa for an extended time. The genus Anguilla contains many species of great commercial importance, but wild stocks have been 35depleted. This has been due to overfishing (both of glass eels and reproductive eels) and other factors 36 such as parasites, global climate change and other human impacts (Feunteun, 2002;Halpin, 2007). To 37 these factors we must add the peculiar life cycle of these species: Adults spawn in the sea (an event not 38 witnessed yet); leptocephali larvae drift until they reach coastal waters; they metamorphose into glass eels 39 and move inland while they develop into elver and yellow elver stages; after that, they mature to silver 40 eels (the whole growth process could take years to decades), which are capable to recognize its way to the 41 spawning areas, where they fully mature, spawn once and die (Ginneken and Maes, 2005). The 42 complexity of this cycle has contributed to the difficulty of replicating it in captivity. Therefore, although 43 an increasing prop...

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Section: Csiro Publishingmentioning

confidence: 99%

Section: Csiro Publishingmentioning

confidence: 99%

Subpopulation pattern of eel spermatozoa is affected by post-activation time, hormonal treatment and the thermal regimen

Gallego

Vílchez

Peñaranda

et al. 2015

Reprod. Fertil. Dev.

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“…Motility parameters, obtained from a CASA system, can be represented using Chernoff faces [Martínez-Pastor et al 2008]. However, to our knowledge, this is the first time that Chernoff faces were used to represent individual measurements obtained from a CASA system.…”

Section: Discussionmentioning

confidence: 99%

“…Representation of multivariate data in the form of Chernoff faces has been used to detect outliers [Johnson 1998] and to describe data obtained from CASA systems [Martínez-Pastor et al 2008;Martínez-Pastor et al 2011]. In addition, multivariate statistics can be used to reduce the dimensionality of a dataset and to cluster observations based on similarities.…”

Section: Introductionmentioning

confidence: 99%

Use of multivariate statistics to identify unreliable data obtained using CASA

Martínez

Crispín

Mendoza

et al. 2013

Systems Biology in Reproductive Medicine

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In order to identify unreliable data in a dataset of motility parameters obtained from a pilot study acquired by a veterinarian with experience in boar semen handling, but without experience in the operation of a computer assisted sperm analysis (CASA) system, a multivariate graphical and statistical analysis was performed. Sixteen boar semen samples were aliquoted then incubated with varying concentrations of progesterone from 0 to 3.33 µg/ml and analyzed in a CASA system. After standardization of the data, Chernoff faces were pictured for each measurement, and a principal component analysis (PCA) was used to reduce the dimensionality and pre-process the data before hierarchical clustering. The first twelve individual measurements showed abnormal features when Chernoff faces were drawn. PCA revealed that principal components 1 and 2 explained 63.08% of the variance in the dataset. Values of principal components for each individual measurement of semen samples were mapped to identify differences among treatment or among boars. Twelve individual measurements presented low values of principal component 1. Confidence ellipses on the map of principal components showed no statistically significant effects for treatment or boar. Hierarchical clustering realized on two first principal components produced three clusters. Cluster 1 contained evaluations of the two first samples in each treatment, each one of a different boar. With the exception of one individual measurement, all other measurements in cluster 1 were the same as observed in abnormal Chernoff faces. Unreliable data in cluster 1 are probably related to the operator inexperience with a CASA system. These findings could be used to objectively evaluate the skill level of an operator of a CASA system. This may be particularly useful in the quality control of semen analysis using CASA systems.

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“…A recent development has been the application of cluster analysis to such data to reveal subpopulations with differing overall characteristics within the sample (42). By such means, subpopulations expressing hyperactive motility or rapid forward motion can be detected (64).…”

Section: Motilitymentioning

confidence: 99%

Cytometric solutions in veterinary andrology: Developments, advantages, and limitations

Petrunkina

Harrison²

2011

Cytometry Pt A

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Cytometric methodologies are becoming increasingly important in veterinary andrology as means of assessing sperm function. However, as yet, flow cytometric techniques in veterinary andrology have not kept up in sophistication with those in other areas of biology and medicine. In this brief review, we consider the present state of cytometry in andrological procedures for evaluating the fertility of domestic animal sires. We outline the aspects of sperm physiology, paying particular attention to the changes that take place during the process known as capacitation, which prepares the sperm for interaction with the egg. We then examine briefly but critically the cytometric techniques that are currently in commercial use or are being established in research laboratories for testing sperm characteristics. Current limitations and potential developments in semen assessment are discussed. Recent research knowledge offers possibilities for applying more subtle flow cytometric approaches to distinguish different levels of fertilizing potential in semen samples. For example, linking field fertility data to multiparametric kinetic studies of sperm capacitational changes rather than ''single parameter-single time point'' estimations may reveal that slower rather than rapid changes indicate high fertility. Moreover, the development of multicolor flow cytometric procedures as a means of evaluating multiple functional parameters in individual cells would reduce the uncertainties always inherent in predicting fertility from in vitro sperm evaluation tests. ' 2011 International Society for Advancement of Cytometry Key terms fertility; sperm evaluation; heterogeneity; subpopulations; multicolour cytometry THE main focus of an andrological assessment in veterinary medicine is to ascertain the fertility of a potential sire. Although the most obvious and indeed frequently used general veterinary test is to quantify the number of offspring born to the sire, this is a lengthy and very expensive process. For ''accuracy,'' many inseminations must be carried out, and results must await gestation and birth. Obviously, therefore, development of rapid tests that can be carried out in the laboratory has for long been important. However, as research into the reproductive process has advanced, it has become clear that the life of the fertilizing sperm between its release from the testis and its fusion with the egg is far from simple. Moreover, the population of sperm ejaculated into the female has been revealed as being heterogeneous in functional ability, even if morphologically normal [c.f. reviews (1,2)]. As a result of these findings, tests are being developed to examine functional ability within a heterogeneously responding population (3-5).Given that a normal male ejaculate contains many millions of individual sperm cells, it is natural that these tests are based on cytometry. In this short review, we will outline and comment upon a range of modern and still-developing cytometric methodologies in use or potentially useful for sperm...

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Multivariate cluster analysis to study motility activation of Solea senegalensis spermatozoa: a model for marine teleosts

Cited by 64 publications

References 40 publications

Subpopulation pattern of eel spermatozoa is affected by post-activation time, hormonal treatment and the thermal regimen

Subpopulation pattern of eel spermatozoa is affected by post-activation time, hormonal treatment and the thermal regimen

Use of multivariate statistics to identify unreliable data obtained using CASA

Cytometric solutions in veterinary andrology: Developments, advantages, and limitations

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