How many sperm does it take to get a mare pregnant?
1 billion?...500 million?... One? Actually, any one of those answers could be correct under certain conditions. The only way to really answer that question is... "it depends". Fertilization is a complex process requiring that both the sperm and egg possess a myriad of functional attributes expressed at the right time and in the right place. A motile sperm is not necessarily a fertile sperm. So, how many sperm must be deposited in the mare for "acceptable" fertility? It would seem that this would be the logical basis for determining sperm numbers in an insemination dose for commercially distributed semen. To achieve the goals of both the mare and stallion owner it is necessary for each dose of semen to contain sufficient numbers of functionally competent sperm to maximize the probability of conception. The relationship between sperm number and fertility is expressed as a typical dose response curve (see figure1). However, the slope of the curve and the maximum level of fertility are different for individual stallions.

In figure 1, stallion A achieves maximum fertility with much fewer sperm per insemination than the other 3 stallions. Insemination of more sperm for this stallion does not further increase fertility. The appropriate dose for this stallion would be 100 million progressively motile sperm. Stallion B has a higher maximum level of fertility but it is only achieved following insemination of far more sperm. When inseminating 100 million sperm for all 4 stallions in our example, a wide range of fertility is obtained (53% for A, 42% for B, 32% for C and 15% for D). Increasing the number of sperm inseminated to 250 million for stallion A does not change fertility while increasing to 250 million sperm for stallions B and C results in a significant increase in fertility. Stallion C is capable of achieving similar fertility as stallions A and B however reaching this level of fertility requires the insemination of far more sperm. Stallion D has a low level of maximum fertility that cannot be overcome by insemination of far greater numbers of sperm. This is due to the fact that some defects of sperm are compensable and others are non-compensable.

Compensable vs. Non-Compensable Defects

"If 30% post-thaw motility is acceptable and this sample has 15%, then why can't you just double the number of straws inseminated?" For some stallions you can... but for others you can double, triple or increase by 10-fold the number of sperm inseminated without increasing fertility. In figure 1 we saw that doubling the number of sperm from100 million to 200 million for stallions B and C would significantly improve fertility but have no effect on fertility of stallion D. All semen samples contain some defective sperm. The ratio of defective to functional sperm in the sample determines the fertility of that sample. However not all defects are alike. Some defects impair the sperm's ability to penetrate the oocyte and initiate fertilization. These sperm never participate in the fertilization process and therefore do not compete with the other fully functional sperm in the sample. These defects are said to be "compensable" because one can compensate for low fertility of the sample by increasing the total number of sperm inseminated until the threshold number of fully functional sperm is reached.

Other defects do not prevent the sperm from binding to and penetrating the oocyte rather; these defects affect the
process after fertilization is initiated and lead to early embryonic death. These sperm compete with fully functional sperm to be the one sperm that fertilizes the oocyte. Increasing the total number of sperm inseminated does not increase the chances of  fertilization by a fully functional sperm because the ratio of defective to functional sperm is still the same. Therefore in this case lower fertility can not be compensated for by increasing the total number of  sperm inseminated

Motility Does Not Equal Fertility

Why do sperm from different stallions inseminated into mares under the same management conditions have such a wide range of fertility? Fertility is a result not simply of the total number of sperm inseminated but rather the number of functionally competent sperm inseminated. A functionally competent sperm must possess "enough" of each of the many functional attributes required for fertilization. A simple example is sperm motility. Most would agree that a sperm must be motile in order to be fertile following standard uterine insemination. So a stallion with 30% motility would require insemination of twice as many sperm as a stallion with 60% motility in order to achieve the same fertility. This simple example would only be true IF sperm motility were the only functional attribute required for fertilization. Unfortunately this is clearly not the case. Sperm motility (regardless of how sophisticated it is measured) does not equal fertility. A sperm that is not motile is likely not fertile but a sperm that is motile may or may not be fertile. In addition to progressive motility, a fertile sperm must possess acceptable morphological characteristics, intact plasma and acrosomal membranes in order to bind to and penetrate the oocyte and a whole host of other known and unknown functional attributes. See figure 2 for an illustration of this concept.

Figure 2: Let's assume that there are 7 functional attributes of a sperm that are required for successful fertilization (attributes A-G; A= motility, B = morphology, etc) and that we have laboratory assays that are capable of accurately measuring these attributes and distinguishing between normal and abnormal. (This is clearly a gross oversimplification as there are likely many more attributes required and our ability to accurately measure them and relate them to fertility is lacking.) If a sample contains mostly sperm that are normal in attributes A, B, C, D, E, and Fand abnormal in G, the sample will be infertile. Likewise if a sample has mostly sperm normal in A, B, C, D, E and G andabnormal in F, the sample will be infertile. Measuring only motility is measuring only A. Measuring motility and morphology is measuring only A and B and so on. In this example, most laboratories would reject this subfertile sample only if attribute F was motility or morphology. Predicting that a semen sample will be fertile requires the ability to measure all of the functional attributes.

The only realistic goal of semen evaluation then is to try and predict that a given semen sample or semen from a given stallion is likely to be subfertile because it is "abnormal" in one of the attributes that we can measure.

Most laboratories package semen doses based on the number of progressively motile sperm and in some cases take into account the percentage of sperm with "normal" morphology. Including adequate numbers of sperm that are normal in these two functional attributes still does not guarantee fertility (figure 2.) Another challenge to standardizing semen quality is the ability to accurately and precisely measure semen quality with standard laboratory assays. Frozen semen is often sold with a guarantee (or non-guaranteed claim) that after thawing each dose will contain a minimum of “n” million total sperm with “x”% progressive motility. Measuring sperm motility in many laboratories is performed using a subjective estimation of the percentage of sperm in a sample that are moving in a "progressive fashion". Such subjective estimates are prone to technician bias and are typically less precise and less accurate than computer assisted sperm analysis (CASA) methods of measuring motility.

Accurately measuring sperm concentration in both the initial sample and after centrifugation and dilution in extender is also critical if the resulting dose is to contain the correct number of sperm. Inaccuracies due to improper techniques and instrumentation used for counting sperm can lead to improper sperm concentration in the doses packaged for commercial distribution. For more information on how SBS ensures quality read Quality Control is at the Core of the SBS Difference from the Fall 2006 issue of Foundations. Ideally, commercial producers would determine the number of sperm required for each stallion to achieve maximum fertility and prepare doses of semen accordingly. This is impossible in horses as far too many mares would need to be inseminated under controlled conditions with doses of varying amounts to establish the number of sperm per dose required for maximum fertility. As a result, most doses contain more sperm than are required. In figure 1 if sperm from each of these stallions was packaged at 300 million motile sperm per dose, maximum fertility for all would be achieved.

What other factors influence the probability that a given mare will become pregnant following insemination with semen from a given stallion?

To this point we have focused mainly on the male factors that contribute to fertility however the probability that a mare will become pregnant following insemination is dependent upon numerous other variables. Remember, fertility is the product of (stallion fertility [or fertility of that semen sample]) times (mare fertility [or fertility of the oocyte ovulated during that particular cycle) times (all other variables). See the accompanying sidebar for an illustration of this concept. Many claim that the only true test of fertility of frozen semen (this actually applies to all semen, fresh or frozen) is to inseminate mares and measure pregnancy outcome. Actually, the only thing that can practically be determined with horses is whether or not semen from a particular stallion is capable of achieving a pregnancy. Some breeders will report pregnancy rates following insemination of 5 or 10 or 20 mares as demonstration that a particular stallion is either highly fertile or subfertile. Since observed fertility after insemination is a binomial function (either she is pregnant or not) it is like flipping a coin. If you flip a coin and measure the results you will find that the more times you flip the coin (observations) the closer you will get to the true probability (50%) of heads or tails in your measured result. For example, two stallions (A and B) of equal fertility (50%) are used to inseminate 10 mares each. The observed fertility of stallion (A) is 70% and the observed fertility of stallion B is 30%. Stallion A is statistically no more fertile than stallion B. This imprecision in the observed measurement of true fertility is due to binomial variation alone. In other words, there is an equal chance that if those same stallions were to breed another 10 mares each, stallion A would get 3 of 10 pregnant and stallion B would get 7 of 10 pregnant. So, as the number of matings (observations) is increased the observed result is closer to the true fertility.

The Mathematics of Fertility

For the purpose of this example, let's ignore the very significant effect of "other variables" and assume:
Observed Fertility = (stallion fertility) X (mare fertility)
So, an observed fertility of 50% (0.50) could be the result of stallion fertility of 55% times mare fertility of 90% or stallion fertility of 90% times mare fertility of 55%. Even when a highly fertile stallion is bred to a highly fertile mare (each with 90% fertility) the probability of that mating resulting in a pregnancy is not 100% (0.9 X 0.9 = 0.81 or 81%). And remember we are ignoring the significant "other variables" that influence the outcome. Breeding an older, perhaps subfertile mare to a subfertile stallion (or semen with poor quality) really decreases the probability of obtaining a pregnancy efficiently. Mare fertility (40%) X stallion fertility (40%) = 16% probability of pregnancy.

So what does all this mean? The take home messages here are:

1. Fertility is a complex process that is dependent upon numerous factors associated with the stallion and mare. Many of these factors are known but difficult to accurately measure and many other factors are likely important but unknown.
2. The optimum number of sperm per insemination is different for individual stallions and producers should strive to package sperm in doses well beyond the critical number required for maximum fertility to account for the effect of uncontrolled variables on fertility in the field.
3. Standard laboratory evaluations of semen quality can be misleading and may be subject to bias and inaccuracies.
4. The fertility of a semen sample cannot be predicted based on the results of standard laboratory assays. All laboratory assays are measuring some aspect of relative cell health but do not predict fertility.
5. The goal of evaluating semen quality should be to accurately and precisely measure attributes to identify stallions or semen samples that are likely to result in very poor fertility. Those samples or stallions can then be culled from the commercial breeding population.
6. Mare owners entering into an agreement to breed a mare to a particular stallion via cooled or frozen semen should be aware of the numerous factors that could influence the outcome. Purchasing frozen semen by the dose and without any guarantee of fertility or minimum semen quality is risky business and truly "buyer beware". If semen is purchased "by the dose" buyers should insist on a guarantee of a minimum number of sperm per dose and a minimum percentage of progressive motility after thawing. SBS recommends that frozen semen be used as a tool for efficiently delivering semen to a mare in fulfillment of a contract for pregnancy between a mare owner and stallion owner.

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