| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
Regular Article |
a Department of Biochemistry and Molecular Biology, Royal Free & University College Medical School, London NW3 2PF, United Kingdom
b Institute of Zoology, Zoological Society of London, Regent's Park, London NW1 4RY, United Kingdom
c Veterinary Basic Sciences, Royal Veterinary College, Camden, London NW1 0TU, United Kingdom
d PIC International Group, Department of Pathology, Cambridge University, Cambridge CB2 1QP, United Kingdom
 |
ABSTRACT |
|---|
 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
gene regulation, male reproductive tract, reproductive technology, sperm, sperm motility and transport
|
INTRODUCTION |
|---|
|
TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
Accounts of individual variation in semen freezability apply across a range of species. Bull [1] and fowl spermatozoa [2] can be frozen successfully, whereas boar [3], ram [4], rodent [5], and marsupial spermatozoa [6] undergo extensive damage despite the development of species specific protocols.
Heterospermic insemination studies of cryopreserved bull spermatozoa clearly demonstrate interindividual differences within species. Trials inseminating mixed samples of bull spermatozoa showed that freezing the semen altered the proportions of calves sired by specific males, suggesting that spermatozoa with a fertility advantage were not necessarily those best adapted to survive cryopreservation [7]. This observation is particularly relevant as heterospermic insemination eliminates confounding variables such as female tract anatomy, which may give a false impression of relative fertility.
Following the advent of transgenic technology, extensive work has been carried out optimizing semen cryopreservation protocols in an attempt to preserve the genetics of important strains of mice. However, postthaw semen quality has been shown to be highly variable between mouse strains [8]. Between-strain variation in the cryosurvival of mouse spermatozoa has been observed for postthaw motility (23%–62%) and fertilization rates (26%–89%) [9]. Songsasen and Leibo [5] showed that depression in fertilizing ability after exposure to cryoprotective media was variable between strains of mice. Subsequent semen cryopreservation produced further variation between strains in the extent of freeze-thaw damage.
This study explored the hypothesis that consistent interindividual variation in sperm freezability is genetically determined. The identification of genetic differences between individuals, which may influence characteristics of the spermatozoa that are essential for successful cryopreservation, offers a new approach with which to explore sperm cryobiology.
A novel molecular technique, amplified restriction fragment length polymorphism (AFLP) [10] visualizes differences in DNA sequences between individuals and provides a means to identify DNA markers associated with desired traits. AFLP is an established molecular tool for quantifying genetic variation at the individual, population, and species levels in plant sciences [11, 12] and mycology [13, 14]. However, the potential application of AFLP technology for animal research has only been recognized in a limited number of studies [15, 16].
AFLP is based on the principle of selectively amplifying a subset of restriction fragments obtained after digestion of genomic DNA with restriction endonucleases. Markers are produced from a set of generic primers, which do not require prior knowledge of nucleotide sequence. Polymorphisms are detected by differences in the length of the amplified fragments in PAGE and are assessed as the presence or absence of bands. Compared with the widely used restriction fragment length polymorphism technique [17], AFLPs are faster, less labor-intensive, and provide more information. An additional advantage is excellent marker reproducibility, which is essential if screening protocols are to be established [18, 19]. AFLP screens high numbers of loci for polymorphism and simultaneously detects a greater number of DNA markers than any other polymerase chain reaction (PCR)-based detection system [10].
Commercial stud boars have not yet been genetically selected for sperm freezability, therefore, different breeds selected for particular traits such as lean meat quality, are expected to exhibit considerable genetic diversity if freezability is an inherited trait. The comparison of DNA from boars with good and poor semen freezability may highlight genetic differences, which will ultimately lead to the identification of molecular components of the spermatozoa that are essential for successful cryopreservation. This would transform semen freezing as a subject and allow the development of widely applicable principles across species.
The purpose of this study was to 1) investigate whether consistent variation in postthaw semen quality exists between boars, and 2) utilize AFLP to identify molecular markers showing an association with semen "freezability" in the boar.
|
MATERIALS AND METHODS |
|---|
|
TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
Five ejaculates were collected over a 5-wk time period from each of 129 boars (5 boars from each of 3 genetically distinct breeds; Large White, Landrace, and Duroc; PIC International Group, Abingdon, U.K.) using a manual collection method [20]. Only the sperm-rich fraction of the ejaculate was collected. All boars were 1–1.5 yr of age, known to be fertile, and were undergoing regular semen collection for commercial artificial inseminations. All animals received the same diet. Sperm concentration was determined by colorimetry.
Cryopreservation Protocol
Following collection, semen was diluted into a washing buffer (447 mOsm kg-1; catalog ZS993; IMV, L'Aigle, France) to a final concentration of 100 x 106/ml at 39°C, and allowed to cool to room temperature at approximately 0.2°C/min. Semen quality was assessed before freezing as detailed below. Fifty milliliters of semen (100 x 106/ml) was centrifuged at 15°C for 15 min at 500 x g, and the supernatant removed. The sperm pellet was diluted with 5 ml of a commercial freezing buffer (IMV; buffer 1: 700 mOsm/kg, 20% egg yolk) and cooled from 15°C to 5°C at approximately 0.2°C/min. At 5°C sperm were further diluted with 5 ml of a second commercial freezing buffer (IMV; 700 mOsm/kg, with final working concentrations of: 19% egg yolk, 3% glycerol, and 1% Orvus ES Paste) to a final concentration of 333 x 106/ml, and packaged in 0.5-ml straws (IMV).
Semen was cryopreserved using a controlled-rate freezer consisting of a mobile platform moving within the gas phase of liquid nitrogen, following a programmed cooling protocol [21]. Straws were cooled to -5°C at 6°C/min, then further cooled from -5°C to -80°C at 40°C/min. Straws were held for 30 sec at -80°C, then cooled at 70°C/min to -150°C, and plunged into liquid nitrogen. Five straws per ejaculate were thawed by plunging them into a 40°C water bath for 1 min.
Spermatozoa Assessment
Each ejaculate was assessed for sperm quality before freezing, and each straw was assessed after thawing.
Acrosome integrity Semen was diluted in prewarmed (39°C) Beltsville thawing solution (BTS; 37 g/L glucose monohydrate anhydrous, 6 g/L sodium citrate, 1.25 g/L sodium hydrogen carbonate, 1.25 g/L EDTA-disodium, 0.75 g/L KCl pH 7.2) to a final concentration of 3 x 106/ml, and one smear of spermatozoa per straw was prepared. Slides were air-dried and fixed for 10 min in absolute ethanol. Acrosomal damage was assessed using fluorescein-labeled PNA (FITC-PNA; lectin from Arachis hypogaea, peanut; Sigma Diagnostics, Poole, Dorset, U.K.) [22]. Spermatozoa were counterstained with propidium iodide (PI; Molecular Probes Europe, Leiden, The Netherlands) to allow identification of the spermatozoa without intact acrosomes. Twenty microliters of a solution containing FITC-PNA (100 µl/ml in PBS) and PI at a concentration of 2 µM was spread over each smear. Slides were incubated in a dark and moist chamber at 39°C for 30 min. Subsequently, slides were rinsed in PBS and mounted with 10 µl of citifluor (Citifluor Ltd., London, U.K.) under a coverslip. Two hundred cells were assessed under an epifluorescent microscope on each slide, and a percentage of cells with intact acrosomes was calculated.
Plasma membrane integrity Diluted semen was stained with the fluorescent probes SYBR-14 and PI according to the manufacturer's instructions (Live/Dead Sperm Viability Kit; Molecular Probes Europe) [23]. Plasma membrane integrity assessments were carried on a Coulter Epics XL instrument flow cytometer (Coulter Corporation, Miami, FL). Flow cytometry setup conditions for SYBR-14 and PI have been validated previously [21]. Three flow cytometry readings were taken from each thawed straw.
Motility evaluation Semen was diluted to a final concentration of 10 x 106/ml in a prewarmed (39°C), modified Tyrode-based medium [24] buffered with Hepes (Sigma Diagnostics), containing 5 mg/ml BSA (Sigma Diagnostics) and 15 mM bicarbonate. Spermatozoa were incubated for 1 h at 39°C in 5% CO2 in air. After incubation, a subsample was introduced into a prewarmed counting chamber (20 µl Micro Cell slide; Conception Technologies, San Diego, CA) by capillary action. Motile spermatozoa were video-recorded for 3 min from a negative-high phase contrast microscope (Olympus BH-2, 10x objective; Olympus, London, U.K.), equipped with a warm stage.
Sperm motility analysis was performed using the Hobson Sperm Tracker (Hobson Tracking Systems Ltd., Sheffield, U.K.) operating at 50 video frames per sec (50 Hz). Minimum track points were set at 50 frames, and the search radius at 5.9 µm. The validation of these settings has been described previously [25]. The measured parameters of sperm motion were curvilinear velocity (VCL), straight-line velocity (VSL), amplitude of lateral head displacement (ALH), and beat cross-frequency (BCF). Definitions of these parameters can be found in previous publications [26]. The percentage of motile spermatozoa was also measured by counting the number of sperm that showed any motility when viewed under a negative high-phase contrast microscope (Olympus BH-2, 10x objective).
AFLP Technology
The AFLP technique identifies genetic markers by detecting and evaluating variations in DNA sequence between good and bad freezers. Any phenotypic variation between sample animals, such as coat color, will be reflected in the animal's genotype, and therefore, the AFLP fragment profile. In order to identify informative markers, ideally the only variation between the two sample populations should be the presence of the trait in question. In this case, the only difference between the sample boars should be the freezability of their semen. Thus, in an attempt to minimize individual differences, AFLP analysis was carried out on DNA from a single breed.
DNA extraction Genomic DNA from 22 Large White boars (PIC International Group) was extracted from spermatozoa and purified according to the following protocol.
One hundred microliters of the sperm-rich fraction of raw semen was added to 300 µl of extraction buffer A (10 mM Tris-HCl, 5 mM sucrose, 5 mM MgCl2, 1% Triton X-100, adjusted to pH 8.0 using 1 M NaOH) and vortexed thoroughly. The diluted semen was centrifuged for 2 min at 3700 x g, and the supernatant was discarded. The sperm pellet was then resuspended in 300 µl of extraction buffer B (400 mM Tris-HCl, 60 mM EDTA, 150 mM NaCl, 1% SDS, adjusted to pH 8.0 using 1 M NaOH) and incubated for 1 h at 60°C. One hundred microliters of 5 M sodium-perchlorate solution was added to the sperm extraction reaction and mixed by inverting 10 times by hand. Chloroform (600 µl) was then added and further mixed for 10 min on a rotary mixer. Following centrifugation for 5 min at 7000 x g, the upper phase was transferred to a new tube, and the chloroform step was repeated to enhance DNA purification. An equal volume of isopropanol was added to the second aqueous phase and the samples were mixed by inversion to precipitate the DNA. The DNA pellet was recovered, washed in 70% EtOH, and air-dried. Following resuspension of the pellet in 10 mM Tris and 1 mM EDTA pH 8.0, DNA quality and concentration were assessed on a 1% agarose gel in comparison with known concentrations of phage 
DNA.
AFLP technique
The AFLP technique has been previously described in detail [10, 15, 27] and a schematic outline of the technique is shown in Figure 1. Genomic DNA is digested with two different restriction enzymes, a frequent cutter and a rare cutter. The frequent cutter, TaqI, (4 base pair [bp] recognition sequence T
CGA) generates small fragments that amplify efficiently and are in the optimal size range for separation on a denaturing gel.
|
The rare cutter, EcoRI, (6 bp recognition sequence GAATTC) reduces the number of amplified fragments, because only the rare cutter-frequent cutter fragments are amplified. Far more DNA fragments are produced by this digestion system than could be resolved on a gel, so a selective PCR amplification is carried out.
Two selective PCR amplification steps take place, preamplification and selective amplification. Adapter and restriction site sequences (and the single nucleotide adjacent internal to the two restriction sites) are used as targets for primer annealing during the preamplification stage. The AFLP preamplification primers (also termed +1 primers) are designed to be complementary to the adapter sequence plus the residual restriction site sequence. In addition, primers are synthesized with one extra nucleotide (hence +1), which is chosen by the experimenter; thus, there are four possible '+1' preamplification primers for Eco and for Taq. During preamplification, only those restriction fragments that match the +1 selective nucleotides will be amplified. Because the +1 primer is one of four possible nucleotide extensions (A, C, T, G) on the EcoRI and TaqI primers, the preamplification reduces fragment complexity by 1/16th (EcoRI 1/4 and TaqI 1/4).
The second selective PCR amplification uses primers with a +3 nucleotide extension. The first position must match that chosen as the +1 extension of the preamplification primer, but the second and third positions are chosen from all possible combinations. The additional two selective bases on each primer further reduce complexity by 1/256, giving a total reduction (preamplification and selective amplification) of 1/4096. This overall reduction of the restriction fragment complexity produces an optimal number of selectively amplified bands, which could be visualized on an appropriate gel system. By using different combinations of +3 primers, different subsets of restriction fragments can be amplified. The EcoRI primer is labeled with an infrared fluorescent dye (IRD 700 or IRD 800) that can be laser-scanned, and which allows the band patterns to be analyzed on a LI-COR automated sequencer (LI-COR, Lincoln, NE).
Restriction fragment patterns generated by the selective amplification are a rich source of polymorphisms or AFLP markers. The frequency with which markers are detected depends on the level of sequence polymorphism between the tested DNA samples. Using one primer combination, 50–200 fragments can be analyzed on a single lane of a gel if resolution is good. Polymorphisms are detected as the presence or absence of a fragment due to 1) a difference in restriction sites, 2) mutations involving the selective nucleotide extensions, or 3) insertions or deletions within the amplified DNA fragment. Each AFLP fragment corresponds to a specific position on the genome, and therefore it can be used as a genetic marker if it shows polymorphism, characterized by its size and the primers required for its amplification.
All adapters, primers, and infrared dyes were obtained from MWG-Biotech AG (Ebersberg, The Netherlands). Restriction enzymes, T4 DNA ligase, ATP, 10x PCR buffer, dNTPs and AmpliTaq polymerase were purchased from Gibco BRL (Life Technologies, Paisley, U.K.).
Preparation of AFLP adapters and primers The sequences of EcoRI and TaqI adapters and primers used in the experiment are shown in Table 1. EcoRI adapters were formed by annealing 5 pmole/µl of Eco top strand and 5 pmole/µl of Eco bottom strand. Final concentration is 5 pmole/µl. TaqI adapters were formed by annealing 50 pmole/µl of Taq top strand and 50 pmole/µl of Taq bottom strand. Final concentration was 50 pmole/µl.
|
Restriction digests of genomic DNA Restriction fragment digestion of extracted spermatozoa DNA was carried out by incubating 250 ng of DNA with 5 units TaqI for 2 h at 65°C in 38 µl of restriction/ligation (RL) buffer (50 mM Tris-acetate pH 7.5, 50 mM Mg acetate, 250 mM K acetate, 25 mM dithiothreitol [DTT], and 250 ng/µl BSA). Following this incubation, 2 µl of RL buffer containing 5 units of EcoRI was added, and the resulting 40 µl was incubated at 37°C for 2 h. Restriction digests were assessed on a 1% agarose gel to ensure the spermatozoa DNA was fully digested.
Ligation of adapters The adapters consist of a core sequence and a restriction enzyme-specific sequence. To ligate adapters, 10 µl of RL buffer containing 5 pmole EcoRI adapters, 50 pmole TaqI adapters, 1 Weiss unit T4 DNA ligase, and 1 µl of 10 mM ATP was added to the restriction digest reaction. This 50-µl RL reaction was incubated at 37°C overnight. Ligated template DNA was diluted 1:10 with 10 mM Tris-HCl, 0.1 mM EDTA pH 8.0, and stored at -20°C before preamplification.
Preamplification of template DNA AFLP preamplification primers were composed of a core sequence, an enzyme-specific sequence, and a single nucleotide extension (+A; Table 1). Five microliters of diluted, ligated template DNA was added to a PCR reaction mix containing 5 µl of 10x PCR buffer (200 mM Tris-HCl pH 8.4, 500 mM KCl), 3 µl MgCl2 (25 mM), 5 µl dNTPs (2 mM), 0.2 µl AmpliTaq polymerase, and 50 ng each of the EcoRI and TaqI preamplification primers carrying one selective nucleotide in a total volume of 50 µl.
The PCR preamplification consisted of 20 cycles with a profile of 30 sec at 94°C to denature the DNA, 1 min at 56°C for primer annealing, and 1 min at 72°C for primer extension, followed by 5 min at 72°C for the completion of partial amplifications. PCR amplification was carried out using the Gene Amp PCR system 9700 (PE Biosystems, Foster City, CA). The preamplified template was diluted 20-fold with 10 mM Tris-HCl and 0.1 mM EDTA pH 8.0 before the selective PCR amplification.
Selective amplification Five microliters of diluted preamplified template DNA was added to a 15-µl PCR reaction mix containing 2 µl of 10x PCR buffer (200 mM Tris-HCl pH 8.4, 500 mM KCl), 1.2 µl MgCl2 (25 mM), 2 µl dNTPs (2 mM), and 0.1 µl AmpliTaq polymerase. PCR primers carrying three arbitrarily chosen selective nucleotides (Table 1) were used in this amplification. Fifteen nanograms of EcoRI primer terminally labeled with infrared dye (IRD) and 30 ng unlabeled TaqI primer were added. Either of two IRDs, fluorescing at wavelengths of either 700 or 800 nm, were used to label the EcoRI primers, allowing two primer combinations to be run on a gel simultaneously. The LICOR 4200 sequencer incorporates two separate sets of optically tuned lasers and detectors that can distinguish between the fluorescence signals from restriction fragments labeled with IRD 700 and IRD 800, producing two independent AFLP profiles from a single gel run.
Amplification was performed for 13 cycles with the following profile: 30 sec at 94°C for DNA denaturation, 30 sec at 65°C as an annealing step, and 2 min at 72°C for primer extension. In each cycle, the annealing temperature was reduced by 0.7°C down to 56°C. This "touch down" reduction in annealing temperature promotes high-stringency amplification. Immediately following these 13 cycles, a further set of 23 cycles was performed for 30 sec at 94°C, 30 sec 56°C, and 2 min at 72°C. The PCR reaction was then cooled to a holding temperature of 6°C. PCR amplification was carried out using the Gene Amp PCR system 9700 (PE Biosystems).
Detection and scoring of AFLP markers Two microliters of labeled amplified DNA were mixed with 2 µl of microSTOP loading buffer (96% formamide, 20 mM EDTA, red and blue tracking dye; Microzone Ltd., Lewes, East Sussex, U.K.) and denatured by heating to 90°C for 2 min and snap-cooling on ice. Two microliters of this mix were loaded onto a 6% polyacrylamide denaturing gel.
Two microliters of SequaMark 10-bp ladder DNA size markers (Research Genetics Inc., Huntsville, AL) labeled with either IRD 700 or IRD 800 and prepared according to the manufacturer's instructions were also loaded onto the gel. Size markers serve as a reference point for scoring AFLP restriction fragments, and a general control for the resolving power of each gel. SequaMark produces a DNA ladder with bands every 10 bases up to 500 bp.
DNA fragments were separated on a 6% denaturing polyacrylamide sequencing gel. The gel was prepared using 6% acrylamide, 0.25% methylene bisacryl, 1x TBE (89 mM Tris-HCl, 89 mM boric acid, 2 mM EDTA), and 6 M urea pH 8.3 ("Sequagel 6" from National Diagnostics, Hull, U.K.). To 35 ml of gel solution, 280 µl of 10% ammonium persulphate (National Diagnostics) were added, and gels were cast using a LI-COR 41-cm gel assembly (LI-COR). Single-strength TBE (100 mM Tris-HCl, 100 mM boric acid, 2 mM EDTA) was used as a running buffer. Gels were run at a constant wattage (40 W) for 5 h.
LI-COR automated sequencer Gel electrophoresis was performed on a LI-COR automated sequencer. The AFLP fragment image data were collected and the image cropped using BaseImagIR software (version 4.0; LI-COR). The efficiency and repeatability of the LI-COR automated DNA sequencer and associated BaseImagIR software has been previously validated [28].
The LI-COR sequencer utilizes an extremely sensitive infrared detection system. Two sets of optically tuned lasers measure fluorescence signals from independent infrared fluorescent dyes (IRD 700 and IRD 800), each labeling one of two distinct AFLP profiles, running in parallel, on the same gel. The two-channel detection system avoids creating errors in profiles due to fluorescence overlap by using IRDs, which are separated by 100 nm.
Gel images, similar to autoradiograms, for each AFLP profile are collected in real time and displayed in BaseImagIR analysis software. These gel profiles are then imported into AFLP-Quantar image analysis software, which is developed and marketed by KeyGene (Wageningen, The Netherlands) to identify the presence of polymorphisms.
Image analysis software The AFLP-Quantar image analysis package is a specialized software application for the analysis of AFLP DNA fingerprints. Quantar is based on the Windows platform and can be used to analyze gels from fluorescent, radioactive, and infrared detection systems. Quantar was used to identify and measure specific AFLP band patterns in a gel pixel image produced by the LI-COR sequencer and exported from the BaseImagIR software.
The semiautomated Quantar software is used to score polymorphic marker bands identified in the AFLP profile on a dominant basis (presence/absence of a band); it does not score markers codominantly (present high intensity/present low intensity/absent band). Quantar uses information from "constant" bands (i.e., monomorphic bands, present in every sample/lane) such as position, shape, intensity, and relative mobility, to correct for variations in gel running and image artifacts, ensuring that marker classification is precise and reliable. Profiles were scored using the set software parameters, but band classifications were confirmed by the operator to ensure that no markers were misclassified. The band pattern of SequaMark DNA size markers was programmed into the Quantar software and evaluated on each sequence gel, to allow accurate automated sizing of polymorphic bands.
Marker reliability The reproducibility of the AFLP technique was tested across independent DNA extractions and at both the preamplification and selective amplification stages to check the PCR technique produced a consistent DNA template. Three AFLP band profiles were compared for each stage of the protocol.
Statistical Analysis
Summary statistics for each of the sperm assessment parameters from each boar, ejaculate, and straw were calculated. The Shapiro Wilks W-test was applied to assess statistical normality. Not all measurements of postthaw sperm integrity were normally distributed (P < 0.001), so subsequent one way ANOVA testing was carried out on log-transformed values that normalized the data. To investigate boar differences the ANOVA was calculated using the interejaculate mean square as an error term for the boar effect F value.
Multivariate pattern analysis was carried out using the PATN software package (CSIRO, Canberra, Australia) to identify naturally occurring subgroups within the data set. PATN analyses were applied to 1) CASA motion descriptors, and 2) the entire viability data set to identify groups of straws containing spermatozoa with varying susceptibility to cryoinjury. The proportion of straws in a specific freezability group was then used to classify each animal on the basis of resistance to cryoinjury (good, medium, and poor freezers). Untransformed data were used in the multivariate analysis. More detailed information on the statistical application of PATN analysis can be found in the program manual [29] and related manuscripts [30, 31]. Following the pattern analysis, untransformed relative frequencies of straws in each subgroup (good, medium, and poor freezers) were calculated and compared using Chi-square analysis to address specific questions set up within the experimental designs.
Summary statistics for AFLP gel profiles from each boar, DNA extraction, and primer combination were calculated. Logistic regression [32] was used to relate the dichotomous presence or absence of an AFLP marker band with classifications of semen freezability (good or bad) and individual assessments of semen quality after cryopreservation.
Statistical analyses were performed using Statistica for Windows, version 4.5 (Statsoft UK, Letchworth, U.K.).
|
RESULTS |
|---|
|
TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
All ejaculates were collected from sexually mature boars that were of proven fertility and were undergoing regular semen collection for commercial artificial inseminations. It was therefore expected that semen quality before freezing would be of a high standard. Semen quality was assessed before freezing as the percentage of spermatozoa with an intact plasma membrane (mean 99.1%, SD ± 0.9), percentage acrosome integrity (mean 98.3%, SD ± 1.1), and percentage of motile spermatozoa (mean 92.8%, SD ± 2.3).
There was no significant variation in semen quality between boars before freezing for the percentage of motile cells (F = 1.86, df = 128, P > 0.05), plasma membrane integrity (F = 1.34, df = 128, P > 0.05), and acrosome integrity (F = 0.33, df = 128, P > 0.05). No significant difference in sperm quality was observed between ejaculates before cryopreservation for any of the viability parameters measured (% motility, F = 1.65, df = 644, P > 0.05;% plasma membrane intact spermatozoa, F = 0.72, df = 644, P > 0.05; and % acrosome intact spermatozoa, F = 0.33, df = 644, P > 0.05).
Ejaculates from all boars consisted of spermatozoa with high quality and would be expected to maintain fertilizing ability after cryopreservation. There were no significant differences in semen quality either between boars or between ejaculates before freezing. Therefore, all subsequent assessments of postthaw sperm quality were evaluated assuming that prethaw measurements were sufficiently close to 100 percent intact/motile so as not to seriously influence postthaw absolute results.
Postthaw Spermatozoa Integrity Assessment
Variability between breeds was detected for postthaw sperm motility (ANOVA; F = 55.95, df = 2, P < 0.001), plasma membrane integrity (ANOVA; F = 12.94, df = 2, P < 0.001), and acrosome integrity (ANOVA; F = 42.59, df = 2, P < 0.001). Between-boar variability was observed for postthaw sperm motility, plasma membrane integrity, and acrosome integrity (Table 2). There was no significant variation in any of the sperm assessment parameters between ejaculates, within boars, or between straws, indicating that the freezing process was reproducible (Table 2).
|
Variation in CASA Motility Measurements
Between-boar variation was identified for mean VCL, VSL, BCF, and ALH (Table 3). However, there were no significant differences between ejaculates or straws for any of the motility parameters (Table 3).
|
The motility data set analyzed by PATN included four descriptors of sperm motion (VCL, VSL, BCF, and ALH) on each of 96 750 individual spermatozoa (observations). Three subpopulations of spermatozoa were identified, defined by their motion characteristics (Table 4). These were characterized as group 1, spermatozoa with active movement (high VCL) but reduced forward progression (low VSL, high ALH); group 2, spermatozoa with highly progressive movement (high VSL); and group 3, reduced movement, degenerating spermatozoa (low measurements for all parameters).
|
Subpopulation 2 appeared to be the "activated" population of spermatozoa. This activated proportion of the total motile sperm population was subsequently used to assess the quality of motility. The proportion of activated (group 2) sperm within the ejaculate was variable between breed (
2 = 18.11, df = 2, P < 0.01) and between boar (2 = 32.0, df = 128, P < 0.01). However, there was no significant difference between ejaculates (2 = 7.12, df = 644, P > 0.05) or straws (2 = 5.97, df = 3224, P > 0.05).
PATN Analysis of Sperm Quality Parameters to Determine Semen "Freezability"
PATN analysis objectively highlighted three groups of straws, defined by all sperm quality assessment results: 1) poor, 2) average, and 3) good freezers; (Table 5).
|
Classification of Boars as "Good" and "Bad" Freezers
The proportion of straws classified as good, average, and poor viability from each boar was calculated. Boars were classified as good, medium, or poor freezers (24, 63, and 42 boars, respectively; Table 5) depending on which group the majority of their straws fell into. The mean values of semen freezability for the newly defined groups of boars are shown in Table 5. The proportion of boars classified into each freezability group was variable between breeds (2 = 38.17, df = 2, P < 0.01) (Table 6), with boars from the Landrace breed producing more spermatozoa of good quality after cryopreservation.
|
Selection of Boars for AFLP Analysis
Approximately equal numbers of boars from each classification of good and bad freezability were required for the analysis. Landrace and Duroc boars were biased to specific freezability classifications (Landrace, 4 bad, 17 medium, 13 good; Duroc, 25 bad, 21 medium, 2 good; Table 6), and thus were of little use for within-breed comparison. The Large White breed consisted of boars more evenly divided between all three freezability groups (13 bad, 25 medium, and 9 good freezers; Table 6) and was chosen for the AFLP analysis. Animals with medium freezability were not used in the AFLP analysis, so the experimental Large White group consisted of 22 animals.
Marker Reliability
Independent DNA extractions and template preparations gave rise to identical AFLP profiles. The AFLP protocol proved to be highly reproducible with bands consistently identifiable between boars, gels, and primer combinations.
In this study, fragment profiles were investigated using Quantar dominant marker scoring. Although the fluorescence levels of amplified fragments were comparable between DNA samples, the variable operator skill when loading gels resulted in a small variation in the volume of DNA loaded onto each gel. Despite this minimal variation, the resulting difference in DNA volume between lanes prevented the use of codominant scoring, as fluorescence levels were not directly comparable.
Automated scoring of the gel profiles by the Quantar package proved to be fast (each gel evaluated in <30 min), accurate, and reproducible. Any questionable band pattern was identified by the package and the operator alerted, preventing inaccurate scoring.
Identification of Potential Markers of Semen "Freezability"
Twenty-eight primer combinations generated 2182 bands, of which 421 were polymorphic (where some animals were positive for an amplified restriction fragment and others were negative). The average number of polymorphic amplified fragments per primer combination was 15, with a range between 4 and 31 bands.
Distinct differences in AFLP profiles were observed between boars classified as "good" and "poor" freezers. AFLP markers were identified by logistic regression analyses correlating the presence or absence of an amplified fragment with the classification of good or bad freezability (Table 7). A marker was identified when one group of boars had statistically more amplified fragments than the other group of boars.
|
Logistic regression was also used to identify significant relationships between the AFLP freezability markers and individual sperm quality assessment tests (Table 7). Due to the large amount of data analyzed, only significant correlations are included in Table 7. All absent regression data can be assumed to be nonsignificant.
AFLP marker 11 was significantly related to the total percentage of motile spermatozoa and the percentage of progressively motile spermatozoa following cryopreservation, and markers 11, 7, 9, and 8 were related to the percentage of spermatozoa with intact plasma membranes (SYBR-14 positive; Table 7). There were no significant differences in any of the AFLP fragment profiles between the two lines of Large White boars (P > 0.05).
AFLP markers for semen freezability generated by different primer combinations and the size (base pairs) of each AFLP marker (logistic regression P < 0.005) is detailed in Table 8. A representative AFLP marker (logistic regression, P < 0.005) and the associated fragment profile is shown in Figure 2.
|
|
|
DISCUSSION |
|---|
|
TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
AFLP Markers and Sperm Quality Assessment
Three distinct and repeatable classifications of semen freezability were identified by PATN analysis and used to assign 129 boars into groups based on the ability of their spermatozoa to survive the freezing process (good, medium, and poor freezers; 24, 63, and 42 boars, respectively). A significant breed variation was observed between the three classifications of freezability, with boars from the Landrace breed producing superior quality spermatozoa after freezing. No significant variation in freezability was identified between ejaculates or between straws, indicating that semen collection frequency and boar health status were constant throughout the experiment. The lack of variation between straws showed the freezing process to be highly repeatable. The combination of a boar and breed effect influencing semen freezability builds a strong argument for the view that variation in sperm freezability is to some extent genetically determined.
Potential AFLP markers for semen freezability were identified by exploring relationships between the presence or absence of an amplified DNA fragment and classifications of good and bad freezers. It was important that the method of classifying a boar as a good or bad freezer was accurate. If the assessment of semen freezability and subsequent classification of animals was inadequate, differences in the AFLP profiles would not be discrete, preventing the identification of informative markers. Using a variety of sperm quality assessment techniques provided a more comprehensive assessment of semen quality following cryopreservation, and therefore improved the chances of identifying markers linked to genes controlling freezability.
It is important to note that although AFLP markers linked to semen freezability were identified, there were also relationships between the AFLP profile and certain individual assessments of sperm quality after thawing. No specific viability test correlated with all AFLP markers, indicating that semen freezability cannot be evaluated by a single assessment technique such as motility or acrosome integrity, but must be defined using a combination of all sperm quality assessments. This limited relationship between the AFLP profile and specific viability tests indicates that the genes responsible for good freezability may not act directly on a particular sperm function, but have a more subtle influence on the response of spermatozoa to the freeze-thaw process. Alternatively, an array of markers linked to different genes may all influence different biophysical aspects of the cellular freezing response.
Validation and Characterization of AFLP Markers
The markers found in this study are potential cryopreservation markers. However, given the small number of animals used (n = 22), there is not enough evidence that these markers are associated with genes or loci, which influence cryosurvival. Although these markers are reliable indicators of postthaw semen quality in this subpopulation, it will be necessary to increase the number of experimental animals and rigorously test the reliability of the markers involved.
Following confirmation of the repeatability of the candidate AFLP markers, it will be important to establish the source of the genetic variation in semen viability after cryopreservation. Sperm freezing is not a natural biological phenomenon, so it is unlikely that there will be a gene to control or regulate cryopreservation. However, the genes we are looking for certainly control or regulate features of the sperm structure or development, which in turn, influence how the spermatozoa can respond to the cryopreservation protocol. Approaches for characterizing where a molecular marker lies in the genome are constantly becoming more efficient. In the future, with progression of the human and pig genome projects, there will be more hope that marker sequences may match information stored on databases. Currently, we approach the characterization of the genetic marker and identification of the linked gene by genetically mapping the marker on reference pedigrees, providing a location on a particular pig chromosome. However, the identification of an actual gene is by no means trivial, and is potentially a very time-consuming process.
Practical Application of Genetic Markers for "Freezability"
Commercial stud boars have not yet been selected for sperm freezability, therefore it is reasonable to assume that different breeds selected for particular traits such as lean meat quality, would exhibit considerable genetic diversity related to inherited freezability traits. By identifying markers for genes regulating semen "freezability," we have the potential to influence all animal production systems. Current methods of sperm preservation impose significant costs on United Kingdom agriculture through wastage of semen held at ambient temperatures and loss of genetics from important boars, which cannot be preserved long-term. The identification of genetic markers linked to semen freezability will have a direct effect on methods of semen preservation in the artificial insemination industry promoting cryopreservation as a viable option for porcine artificial insemination. Rigorous validation of these molecular markers as a predictive measure of semen freezability will provide an opportunity to improve the quality of cryopreserved semen through selective breeding programs, leading to improved efficiency for agriculture.
The concept of preserving spermatozoa from endangered species in genetic resource banks is an attractive option, but the same problems that we have observed in boars apply across a range of species. The identification of genetic markers linked to "freezability" genes will allow us to promote genome banking as a viable conservation tool. Future work must aim to identify what aspects of sperm function are controlled by the freezability genes and develop protocols to minimize the effects of freezing on these cellular components.
Sixteen molecular markers linked to genes controlling semen freezability were identified using AFLP. Markers associated with semen freezability could be used in a marker-assisted selection program to help address the problem of poor freezers in pig breeding. However, careful validation of such markers by an assessment of their predictive value for semen freezability is required prior to their use in such a program.
|
ACKNOWLEDGMENTS |
|---|
|
FOOTNOTES |
|---|
1 This work was supported by the Biotechnology and Biological Sciences Research Council, U.K.; and the PIC International Group, Abingdon, Oxford, U.K. 
2 Correspondence: FAX: 44 20 7388 1027; lthurston{at}rvc.ac.uk
Accepted: October 2, 2001.
Received: August 7, 2001.
|
REFERENCES |
|---|
|
TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
This article has been cited by other articles:
|
|
 |
|
  P. Mazur, S.P Leibo, and G. E Seidel Jr. Cryopreservation of the Germplasm of Animals Used in Biological and Medical Research: Importance, Impact, Status, and Future Directions Biol Reprod, January 1, 2008; 78(1): 2 - 12. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. Hernandez, J. Roca, J. J. Calvete, L. Sanz, T. Muino-Blanco, J. A. Cebrian-Perez, J. M. Vazquez, and E. A. Martinez Cryosurvival and In Vitro Fertilizing Capacity Postthaw Is Improved When Boar Spermatozoa Are Frozen in the Presence of Seminal Plasma From Good Freezer Boars J Androl, September 1, 2007; 28(5): 689 - 697. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. Roca, M. Hernandez, G. Carvajal, J. M. Vazquez, and E. A. Martinez Factors influencing boar sperm cryosurvival J Anim Sci, October 1, 2006; 84(10): 2692 - 2699. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. C. Esteso, A. J. Soler, M. R. Fernandez-Santos, A. A. Quintero-Moreno, and J. J. Garde Functional Significance of the Sperm Head Morphometric Size and Shape for Determining Freezability in Iberian Red Deer (Cervus elaphus hispanicus) Epididymal Sperm Samples J Androl, September 1, 2006; 27(5): 662 - 670. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 G Li, J Saenz, R A Godke, and R V Devireddy Effect of glycerol and cholesterol-loaded cyclodextrin on freezing-induced water loss in bovine spermatozoa. Reproduction, May 1, 2006; 131(5): 875 - 886. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
K E Waterhouse, P O Hofmo, A Tverdal, and R R Miller Jr Within and between breed differences in freezing tolerance and plasma membrane fatty acid composition of boar sperm. Reproduction, May 1, 2006; 131(5): 887 - 894. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
F. J. Pena, F. Saravia, M. Garcia-Herreros, I. Nunezmartinez, J. A. Tapia, A. Johannisson, M. Wallgren, and H. Rodriguez-Martinez Identification of Sperm Morphometric Subpopulations in Two Different Portions of the Boar Ejaculate and Its Relation to Postthaw Quality J Androl, November 1, 2005; 26(6): 716 - 723. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
F. Martinez-Pastor, V. Garcia-Macias, M. Alvarez, P. Herraez, L. Anel, and P. de Paz Sperm Subpopulations in Iberian Red Deer Epididymal Sperm and Their Changes Through the Cryopreservation Process Biol Reprod, February 1, 2005; 72(2): 316 - 327. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
G. Q. Tong, B. C. Heng, N. Q. Chen, W. Y. Yip, and S. C. Ng Effects of elevated temperature in vivo on the maturational and developmental competence of porcine germinal vesicle stage oocytes J Anim Sci, November 1, 2004; 82(11): 3175 - 3180. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
V. Isachenko, E. Isachenko, I. I. Katkov, M. Montag, S. Dessole, F. Nawroth, and H. van der Ven Cryoprotectant-Free Cryopreservation of Human Spermatozoa by Vitrification and Freezing in Vapor: Effect on Motility, DNA Integrity, and Fertilization Ability Biol Reprod, October 1, 2004; 71(4): 1167 - 1173. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J.J. Garde, A.J. Soler, J. Cassinello, C. Crespo, A.F. Malo, G. Espeso, M. Gomendio, and E.R.S. Roldan Sperm Cryopreservation in Three Species of Endangered Gazelles (Gazella cuvieri, G. dama mhorr, and G. dorcas neglecta) Biol Reprod, August 1, 2003; 69(2): 602 - 611. [Abstract] [Full Text] [PDF]
|
|
| ||
