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chapter 3 - RiuNet

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GENERAL DISCUSSION<br />

more studies on multifactorial sperm biomarkers. For example, Lahnsteiner<br />

el al. (1998) reported that in rainbow trout motile spermatozoa, seminal<br />

plasma pH and sperm metabolism were able to explain a high percentage of<br />

variance in fertilization rates. In fact, some sperm traits in that trial were<br />

linked, and subsequently high quality semen was characterised by high<br />

sperm motility (≥75%), medium sperm swimming velocities (100–120 μm/s)<br />

and optimal seminal fluid protonic composition (pH of 8.0–8.2). In this<br />

respect, it suggests that in-depth knowledge of as many sperm traits as<br />

possible allows us to establish the relationships between them, making it<br />

possible to assess sperm quality though a small set of species-specific<br />

biomarkers able to predict both fertilization and hatching rates.<br />

Following on from this basic idea, CASA systems are able to provide us with<br />

many spermatozoa motion parameters, and each one can be correlated<br />

with the spermatozoa ability to fertilize the oocyte. In fact, positive<br />

correlations between fertilization and hatching rates and many CASA<br />

parameters (8 out of 13) were found in pufferfish (see Chapter 5). The<br />

subsequent questions are: which should we choose? Which are the most<br />

important? Really, the answer is to choose those which show the highest<br />

correlations, and checking a so far not very extensive bibliography on this<br />

topic in fish can help us make this choice. However, another approach could<br />

be to study sperm subpopulations. This kind of study uses data mining<br />

techniques such as cluster analysis, grouping the spermatozoa in<br />

subpopulations that have a biological meaning (Martinez-Pastor et al.,<br />

2011). In this respect, although there are scarce reports in fish, other recent<br />

trials have reported the coexistence of several subpopulations in different<br />

species. For example, 3 sperm subpopulations have been described in<br />

European eel sperm, and they have been used to evaluate different<br />

treatments for the induction of maturation in this species (Gallego et al.,<br />

submitted). In this case, subpopulations were made by taking some CASA<br />

parameters, not often used for assessing directly the sperm quality, as a<br />

basis (LIN, WOB, ALH and DNC). For this reason, it is important to note that<br />

all the sperm parameters analyzed by CASA systems must be taken into<br />

account in order to generate powerful and useful information to detect<br />

new sperm quality biomarkers in fish species.<br />

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