Impact of genetic selection on management of boar replacement

Genomic, transcriptomic and epigenomic analysis towards the understanding of porcine semen quality traits. Past, current and future trends

The importance of boar reproductive traits, including semen quality, in the sustainability of pig production system is increasingly being acknowledged by academic and industrial sectors. Research is needed to understand the biology and genetic components underlying these traits so that they can be incorporated into selection schemes and managerial decisions. This article reviews our current understanding of genome biology and technologies for genome, transcriptome and epigenome analysis which now facilitate the identification of causal variants affecting phenotypes more than ever before. Genetic and transcriptomic analysis of candidate genes, Genome-Wide Association Studies, expression microarrays, RNA-Seq of coding and noncoding genes and epigenomic evaluations have been conducted to profile the molecular makeups of pig sperm. These studies have provided insightful information for a several semen-related parameters. Nonetheless, this research is still incipient. The spermatozoon harbors a reduced transcriptome and highly modified epigenome, and it is assumed to be transcriptionally silent for nuclear gene expression. For this reason, the extent to which the sperm's RNA and epigenome recapitulate sperm biology and function is unclear. Hence, we anticipate that single-cell level analyses of the testicle and other male reproductive organs, which can reveal active transcription and epigenomic profiles in cells influencing sperm quality, will gain popularity and markedly advance our understanding of sperm-related traits. Future research will delve deeper into sperm fertility, boar resilience to environmental changes or harsh conditions, especially in the context of global warming, and also in transgenerational inheritance and how the environment influences the sperm transcriptome and epigenome.

Selection and direct biomarkers of reproductive capacity of breeding boars

Efficient management of pig reproduction is paramount for the sustainability and productivity of the global pork industry. Modern artificial insemination (AI) breeding programs have greatly benefited from the integration of advanced selection methods and biomarkers to enhance the reproductive performance of boars. While traditional selection methods have relied soley on boar phenotype, such as growth rate and conformation, modern pig breeding has shifted more and more toward molecular and genetic tools, which are still complemented by phenotypic traits. These methods encompass genomics, transcriptomics, and proteomics. Biomarkers serve as critical indicators of boar reproductive capacity. They can help to identify individuals with superior fertility and aid in the early identification of potential fertility issues, allowing for proactive management strategies. This review summarizes current knowledge of various biomarkers associated with semen quality, sperm function, and overall reproductive fitness in boars. Furthermore, we explore advanced technologies and their potential applications in uncovering novel selection methods and biomarkers for predicting boar fertility. A comprehensive understanding of selection criteria and biomarkers governing boar reproductive capacity is essential for developing effective breeding programs to enhance swine reproductive performance.

Application of sperm motion kinematics and motility-related proteins for prediction of male fertility

The selection of superior sires is paramount for enhancing the efficiency of animal production in the livestock industry. However, semen quality assessment still relies on conventional semen analysis techniques in both animals and humans. Despite extensive efforts to develop various biomarkers for more accurate and precise predictions of male fertility potential, more effective physiological indicators and advance potential biomarkers are needed. Herein, we aimed to develop new potential biomarkers related to sperm motion kinematics for male fertility prediction. We first evaluated sperm motion kinematic parameters and expression levels of sperm motility-related proteins of 30 Duroc boars. We then explored the correlation between litter size, sperm motion kinematics parameters, and sperm motility-related proteins. Progressive sperm motility (%), rapid sperm motility (%), slow sperm motility (%), straight-line velocity (μm/s), linearity (%), beat cross frequency (Hz), mean angular displacement (degree), wobble (%) were correlated with litter size. Furthermore, the expression of axonemal dynein light intermediate polypeptide 1 (DNALI1) and radial spoke head protein 9 homolog (RSPH9) correlated with litter size. The overall accuracy exceeded 60% for predicting litter size using these sperm motion parameters and proteins. Notably, our study observed an increase in litter size after predicting litter size using these parameters and proteins. Thus, sperm motion kinematic parameters and protein expression, particularly of DNALI1 and RSPH9, could serve as new biomarkers for male fertility. These results may contribute to improved understanding of the mechanisms underlying sperm motility.

Genome-Wide Association Analysis of Semen Characteristics in Piétrain Boars

Since artificial insemination is common practice in pig breeding, the quality and persistence of the semen are decisive for the usability of individual boars. In the current study, genome-wide association analyses were performed to investigate the genetic variability underlying phenotypic variations in semen characteristics. These traits comprise sperm morphology and sperm motility under different temporal and thermal storage conditions, in addition to standard semen quality parameters. Two consecutive samples of the fourth and fifth ejaculates from the same boar were comprehensively analyzed in a genotyped Piétrain boar population. A total of 13 genomic regions on different chromosomes were identified that contain single-nucleotide polymorphisms significantly associated with these traits. Subsequent analysis of the genomic regions revealed candidate genes described to be involved in spermatogenesis, such as FOXL3, GPER1, PDGFA, PRKAR1B, SNRK, SUN1, and TSPO, and sperm motility, including ARRDC4, CEP78, DNAAF5, and GPER1. Some of these genes were also associated with male fertility or infertility in mammals (e.g., CEP78, GPER1). The analyses based on these laboriously determined and valuable phenotypes contribute to a better understanding of the genetic background of male fertility traits in pigs and could prospectively contribute to the improvement of sperm quality through breeding approaches.

Cluster analysis and potential influencing factors of boars with different fertility

The fertility of boars is intimately tied to the pig farm's economic benefits. This study aimed to rapidly categorize boars of different fertility and investigate the factors influencing the categorization using the production data in a large pig farm in northern China, including 11,163 semen collection records of Yorkshire boars (215), 11,163 breeding records and 8770 records of farrowing performance of Yorkshire sows (4505), as well as 4720 records of selection indices (sire line index and dam line index) for boars and sows (215 and 4505) between 2017 and 2020. The boar population was classified by two-step cluster analysis, followed by factor analysis to minimize the dimensionality of data variables and eliminate multicollinearity, and then using ordinal logistic regression model to investigate the risk variables impacting boar fertility categorization. Results showed that the two-step clustering divided the 215 boars into three subgroups: high-fertility (n = 61, 28.4%), medium-fertility (n = 127, 59.1%) and low-fertility (n = 27, 12.6%). The high-fertility boars were shown to be substantially greater than the medium-fertility or low-fertility boars (p < 0.05) in average total litter size, number of born alive, and number of healthy piglets of mated sows. Compared with low-fertility boars, the high-fertility boars were also significantly higher (p < 0.05) in the pregnancy rate and farrowing rate of mated sows. However, the three boar subgroups showed no difference (p > 0.05) in semen quality information (average sperm motility, average sperm density, and average sperm volume). Collinearity diagnosis indicated severe multicollinearity among the 20 data variables, which were reduced to 8 factor variables (factors 1-8) by factor analysis, and further collinearity diagnosis exhibited no multicollinearity among the 8 factor variables. Ordered logistic regression analysis revealed a significant and positive correlation (p < 0.05) of boar fertility with factor 2 (average total litter size, number of born alive, number of healthy piglets), factor 4 (average number of weak piglets and average weak piglet rate), factor 6 (sire line index of boars and dam line index of boars), factor 8 (pregnancy rate and farrowing rate), highlighting factor 2 as the most important factor influencing the classification of boar fertility. Our results indicate that the two-step cluster analysis can be used as a simple and effective method to screen boars with different fertility and that farm producers should pay attention to the recording of the reproductive performance of the mated sows due to its role as the risk factor for classification of boar fertility.

Identification of New Candidate Genes Related to Semen Traits in Duroc Pigs through Weighted Single-Step GWAS

Semen traits play a key role in the pig industry because boar semen is widely used in purebred and crossbred pigs. The production of high-quality semen is crucial to ensuring a good result in artificial insemination. With the wide application of artificial insemination in the pig industry, more and more attention has been paid to the improvement of semen traits by genetic selection. The purpose of this study was to identify the genetic regions and candidate genes associated with semen traits of Duroc boars. We used weighted single-step GWAS to identify candidate genes associated with sperm motility, sperm progressive motility, sperm abnormality rate and total sperm count in Duroc pigs. In Duroc pigs, the three most important windows for sperm motility-sperm progressive motility, sperm abnormality rate, and total sperm count-explained 12.45%, 9.77%, 15.80%, and 12.15% of the genetic variance, respectively. Some genes that are reported to be associated with spermatogenesis, testicular function and male fertility in mammals have been detected previously. The candidate genes CATSPER1, STRA8, ZSWIM7, TEKT3, UBB, PTBP2, EIF2B2, MLH3, and CCDC70 were associated with semen traits in Duroc pigs. We found a common candidate gene, STRA8, in sperm motility and sperm progressive motility, and common candidate genes ZSWIM7, TEKT3 and UBB in sperm motility and sperm abnormality rate, which confirms the hypothesis of gene pleiotropy. Gene network enrichment analysis showed that STRA8, UBB and CATSPER1 were enriched in the common biological process and participated in male meiosis and spermatogenesis. The SNPs of candidate genes can be given more weight in genome selection to improve the ability of genome prediction. This study provides further insight into the understanding the genetic structure of semen traits in Duroc boars.

Lifetime and removal reasons for Pietrain boars in European AI centers: a retrospective analysis

Currently, artificial insemination (AI) is the most common reproductive method used in swine production. The economic profitability of AI centers is closely linked to a boar's retention rate and the purchase of replacement boars. The objectives of this study were to examine data of selection process and lifetime of a total of 6,496 purebred Pietrain AI boars and to analyze the frequency and reasons of removal in eight European countries. Data were obtained from two German boar multiplication farms as well as 53 AI centers from 2018 to 2022. The retention time was analyzed from the selection process until replacement and to the end of the examination, respectively. The selection process of the boars took place at 168 ± 5 (mean ± SD) days of age. For further calculations, the removal reasons were divided into nine groups: breeding (BR), died (DI), euthanasia (EU), health (HE), genetics (GE), low libido (LI), sperm quality (SQ), structure (ST), and other (OT). Overall, 56.1% of the examined boars were removed, with 17.5% being removed within the same year they entered the AI center. The annual removal rate for the 53 AI centers averaged 42.4%. The most frequent removal reason was low SQ (45.1%), followed by genetics (28.6%) and low libido (10.6%). The highest relative frequency of removals was observed for an age of 2 yr (34.0%). The highest removal risk was calculated for boars in Czech AI centers (P < 0.001), while the lowest removal risk occurred in Dutch (P = 0.006) and Portuguese AI centers (P = 0.01). The comparison of removal groups revealed, inter alia, higher body weight at selection process for the BR group (117.9 ± 9.0 kg) and longer quarantine periods for LI group (45.9 ± 17.6 d). Boars in the GE group were characterized by the oldest age at removal (934.0 ± 272.8 d) and longest period of exploitation (672.5 ± 266.8 d). The results could be helpful to detect the most common reasons for production failure of AI Pietrain boars and beneficial for establishing an economical removal policy in AI centers and for improving boar management through problem-based selection in boar multiplication farms.

Welfare of pigs during transport

In the framework of its Farm to Fork Strategy, the Commission is undertaking a comprehensive evaluation of the animal welfare legislation. The present Opinion deals with protection of pigs during transport. The welfare of pigs during transport by road is the main focus, but other means of transport are also covered. Current practices related to transport of pigs during the different stages (preparation, loading/unloading, transit and journey breaks) are described. Overall, 10 welfare consequences were identified as highly relevant for the welfare of pigs during transport based on the severity, duration and frequency of occurrence: group stress, handling stress, heat stress, injuries, motion stress, prolonged hunger, prolonged thirst, restriction of movement, resting problems and sensory overstimulation. These welfare consequences and their animal‐based measures are described. A variety of hazards were identified, mainly relating to factors such as mixing of unfamiliar pigs, inappropriate handling methods and devices, the use of pick‐up pens, inexperienced/untrained handlers, structural deficiencies of vehicles and facilities, poor driving conditions, unfavourable microclimatic and environmental conditions and poor husbandry practices leading to these welfare consequences. The Opinion contains general and specific conclusions relating to the different stages of transport of pigs. Recommendations to prevent hazards and to correct or mitigate welfare consequences are made. Recommendations were also developed to define quantitative thresholds for microclimatic conditions and minimum space allowance within means of transport. The development of the welfare consequences over time was assessed in relation to maximum journey duration. The Opinion covers specific animal transport scenarios identified by the European Commission relating to transport of cull sows and ‘special health status animals’, and lists welfare concerns associated with these.

Comparison of NUCLEOCOUNTER, ANDROVISION with Leja chambers and the newly developed ANDROVISION eFlow for sperm concentration analysis in boars

Exact analysis of sperm concentration in raw and diluted semen is of major importance in swine artificial insemination, as sperm concentration is one of the most important characteristics of an ejaculate determining the value of the ejaculate and the productive life of the boar. The study compares different methods for sperm concentration analysis in raw and diluted boar semen: NUCLEOCOUNTER SP-100, the ANDROVISION with Leja chambers and the new ANDROVISION eFlow system. The Concordance Correlation Coefficient (CCC) between NUCLEOCOUNTER and ANDROVISION eFlow was 0.955 for raw (n = 185 ejaculates) and 0.94 for diluted semen (n = 109 ejaculates). The CCC between NUCLEOCOUNTER and ANDROVISION with Leja chambers was 0.66. A Bland-Altman plot of split-sample measurements of sperm concentration with NUCLEOCOUNTER and ANDROVISION eFlow showed that 95.1% of all measurements lay within ± 1.96 standard deviation. The coefficients of variance were 1.6 ± 1.3%, 3.6 ± 3.6% and 7.3 ± 6.3% for NUCLEOCOUNTER, ANDROVISION eFlow and ANDROVISION with Leja chambers in diluted semen, respectively. NUCLEOCOUNTER and ANDROVISION eFlow are comparable tools to measure the concentration of raw and diluted boar semen. In comparison to ANDROVISION with Leja chambers, concentration analyses of diluted semen using NUCLEOCOUNTER or ANDROVISION eFlow show a higher repeatability within and a higher concordance between the methods.

Concentrations of Boar Taint Compounds Are Weakly Associated with Sexual Behavior of Young Boars

Strategies to control boar taint (BT) in meat relies on the reduction of skatole, indole, and androstenone concentration. This might have unfavorable effects on the libido of breeding boars. The association between BT compound concentration in backfat and libido was investigated in 391 commercial breeding boars. Six sexual behavior traits (SBT; sexual arousal, salivation, mounting performance, interest in the dummy sow, penis unsheathing, and overall libido score) were scored during the training of the boars with the dummy sow. Variation in SBT was analyzed by proportional-odds cumulative logistic models. Overall, indole, skatole, and androstenone concentrations were weakly associated with libido. Farm of origin, age at training or body weight, and BT compound levels were poor predictors of boar performance (the area under the ROC curve ranged from 0.60 to 0.69). This indicates that BT compound concentrations were weakly associated with libido, even though the probability of observing good SBT scores increased with high levels of androstenone, intermediate or low levels of skatole, and intermediate to high levels of indole. Hence, practices aiming at reducing androstenone, and controlling the concentrations of skatole and indole to intermediate levels are not expected to impair the libido of young boars.

Suitability of semen stress tests for predicting fertilizing capacity of boar ejaculates

Besides classical semen parameters, semen stress tests (SSTs) are helpful tools to assess the fertilizing capacity of sperm. However, valid studies on SSTs in relation to fertility are rare because several corrections of common fertility parameters for female and male effects are required. Therefore, over a one-year period, we analyzed semen parameters of 260 ejaculates obtained from 130 Pietrain boars aged between 8 and 9 months in one AI center as well as 1521 corresponding insemination records for these ejaculates. Two consecutive ejaculates (4th and 5th) were collected from each boar and extended in DiluPorc™ BTS. In addition to routine semen evaluation, sperm motility was assessed after heat-resistance test (300 min incubation at 38 °C after seven days storage at 16 °C, HRT) and cold-resistance test (10 min incubation at 38 °C after three days storage at 6 °C, CRT). Generalized linear models (GLMs) were applied to analyze effects for the following predictors of farrowing rate (FR), number of total born (NTB) and live born (NLB) piglets: farm (P = 0.013 [FR], P = 0.001 [NTB], P = 0.023 [NLB]), parity (P = 0.679, P = 0.01, P < 0.001), weekday (P = 0.012, P = 0.08, P = 0.009) and year × season (P < 0.001, P = 0.688, P = 0.574). On boar level, GLMs revealed significant effects on FR, NTB and NLB for the predictors sow (all P < 0.001), total sperm number per dose (P = 0.007, P = 0.002, P < 0.001), total sperm motility (P = 0.002, P = 0.2, P = 0.003) and mitochondrial activity (P = 0.004, P < 0.001, P = 0.002). Moreover, FR and NTB were influenced by membrane integrity (both P < 0.001), FR and NLB by cold-resistance (P < 0.001, P = 0.043), and NTB and NLB by sperm morphology (P = 0.001, P < 0.001) and boar (both P < 0.001). NLB was additionally influenced by heat-resistance (P = 0.004) and farm (P = 0.018) and solely NTB was influenced by sperm output (P = 0.03). Boar and semen related factors explained 9% of the total variation in NTB and 7% of the total variation in NLB. Only 14.2% (n = 37) of the samples were both cold- and heat-resistant (≥65% of motile sperm). Cold- and heat-resistance were dependent factors (Chi-square, P = 0.001) and sperm motility after CRT and HRT showed a moderate positive correlation (r_s = 0.40, P < 0.001, Spearman's rho). Finally, ROC curves demonstrated that neither SST can be used as a sole test for predicting the fertilizing capacity of boar ejaculates.

Identification of new semen trait-related candidate genes in Duroc boars through genome-wide association and weighted gene co-expression network analyses

Semen traits are crucial in commercial pig production since semen from boars is widely used in artificial insemination for both purebred and crossbred pig production. Revealing the genetic architecture of semen traits potentially promotes the efficiencies of improving semen traits through artificial selection. This study is aimed to identify candidate genes related to the semen traits in Duroc boars. First, we identified the genes that were significantly associated with three semen traits, including sperm motility (MO), sperm concentration (CON), and semen volume (VOL) in a Duroc boar population through a genome-wide association study (GWAS). Second, we performed a weighted gene co-expression network analysis (WGCNA). A total of 2, 3, and 20 single-nucleotide polymorphisms were found to be significantly associated with MO, CON, and VOL, respectively. Based on the haplotype block analysis, we identified one genetic region associated with MO, which explained 6.15% of the genetic trait variance. ENSSSCG00000018823 located within this region was considered as the candidate gene for regulating MO. Another genetic region explaining 1.95% of CON genetic variance was identified, and, in this region, B9D2, PAFAH1B3, TMEM145, and CIC were detected as the CON-related candidate genes. Two genetic regions that accounted for 2.23% and 2.48% of VOL genetic variance were identified, and, in these two regions, WWC2, CDKN2AIP, ING2, TRAPPC11, STOX2, and PELO were identified as VOL-related candidate genes. WGCNA analysis showed that, among these candidate genes, B9D2, TMEM145, WWC2, CDKN2AIP, TRAPPC11, and PELO were located within the most significant module eigengenes, confirming these candidate genes' role in regulating semen traits in Duroc boars. The identification of these candidate genes can help to better understand the genetic architecture of semen traits in boars. Our findings can be applied for semen traits improvement in Duroc boars.

Classical, Molecular, and Genomic Cytogenetics of the Pig, a Clinical Perspective

The chromosomes of the domestic pig (Sus scrofa domesticus) are known to be prone to reciprocal chromosome translocations and other balanced chromosome rearrangements with concomitant fertility impairment of carriers. In response to the remarkable prevalence of chromosome rearrangements in swine herds, clinical cytogenetics laboratories have been established in several countries in order to screen young boars for chromosome rearrangements prior to service. At present, clinical cytogenetics laboratories typically apply classical cytogenetics techniques such as giemsa-trypsin (GTG)-banding to produce high-quality karyotypes and reveal large-scale chromosome ectopic exchanges. Further refinements to clinical cytogenetics practices have led to the implementation of molecular cytogenetics techniques such as fluorescent in-situ hybridization (FISH), allowing for rearrangements to be visualized and breakpoints refined using fluorescently labelled painting probes. The next-generation of clinical cytogenetics include the implementation of DNA microarrays, and next-generation sequencing (NGS) technologies such as DNA sequencing to better explore tentative genome architecture changes. The implementation of these cytogenomics techniques allow the genomes of rearrangement carriers to be deciphered at the highest resolution, allowing rearrangements to be detected; breakpoints to be delineated; and, most importantly, potential gene implications of those chromosome rearrangements to be interrogated. Clinical cytogenetics has become an integral tool in the livestock industry, identifying rearrangements and allowing breeders to make informed breeding decisions.

A systems biology framework integrating GWAS and RNA-seq to shed light on the molecular basis of sperm quality in swine

BACKGROUND

Genetic pressure in animal breeding is sparking the interest of breeders for selecting elite boars with higher sperm quality to optimize ejaculate doses and fertility rates. However, the molecular basis of sperm quality is not yet fully understood. Our aim was to identify candidate genes, pathways and DNA variants associated to sperm quality in swine by analysing 25 sperm-related phenotypes and integrating genome-wide association studies (GWAS) and RNA-seq under a systems biology framework.

RESULTS

By GWAS, we identified 12 quantitative trait loci (QTL) associated to the percentage of head and neck abnormalities, abnormal acrosomes and motile spermatozoa. Candidate genes included CHD2, KATNAL2, SLC14A2 and ABCA1. By RNA-seq, we identified a wide repertoire of mRNAs (e.g. PRM1, OAZ3, DNAJB8, TPPP2 and TNP1) and miRNAs (e.g. ssc-miR-30d, ssc-miR-34c, ssc-miR-30c-5p, ssc-miR-191, members of the let-7 family and ssc-miR-425-5p) with functions related to sperm biology. We detected 6128 significant correlations (P-value ≤ 0.05) between sperm traits and mRNA abundances. By expression (e)GWAS, we identified three trans-expression QTL involving the genes IQCJ, ACTR2 and HARS. Using the GWAS and RNA-seq data, we built a gene interaction network. We considered that the genes and interactions that were present in both the GWAS and RNA-seq networks had a higher probability of being actually involved in sperm quality and used them to build a robust gene interaction network. In addition, in the final network we included genes with RNA abundances correlated with more than four semen traits and miRNAs interacting with the genes on the network. The final network was enriched for genes involved in gamete generation and development, meiotic cell cycle, DNA repair or embryo implantation. Finally, we designed a panel of 73 SNPs based on the GWAS, eGWAS and final network data, that explains between 5% (for sperm cell concentration) and 36% (for percentage of neck abnormalities) of the phenotypic variance of the sperm traits.

CONCLUSIONS

By applying a systems biology approach, we identified genes that potentially affect sperm quality and constructed a SNP panel that explains a substantial part of the phenotypic variance for semen quality in our study and that should be tested in other swine populations to evaluate its relevance for the pig breeding sector.

Relationship between pubertal testicular ultrasonographic evaluation and future reproductive performance potential in Piétrain boars

New ways of predicting sperm quality and output performance in young artificial insemination (AI) boars are important for breeding companies to ensure that the pubertal boars delivered to the AI studs have a high chance of meeting minimum quality standards to be used for insemination and therewith dissemination of desirable characteristics. The aim of the current study was to characterize the testicular development of 218 pubertal Piétrain boars (Line 408, Pig Improvement Company) to identify traits with predictable characteristics relative to their sperm quality as an adult AI boar. Scrotum, testes and epididymis were examined ultrasonographically at day (d) 100 (on-test) and 170 (off-test) followed by a computer-assisted grayscale analysis (GSA). Over the test period, paired testicular volume increased 7.3-fold from 22.7 ± 10.8 cm³ to 166.6 ± 62.2 cm³. The right testis was significantly (P = 0.014) larger than the left one at the off-test. Based on the sperm quality (ejaculate volume, sperm concentration, total sperm number, morphologically abnormal sperm and total sperm motility at day 3 of semen storage), 82.11% (n = 179) of the boars were classified as "productive" boars. These boars had a significantly (P = 0.039) larger paired testicular volume than "non-productive" boars (45.9 ± 19.9 cm³vs. 38.5 ± 12.6 cm³) at the on-test. For the right testis at on-test, significant differences for the standard deviation of mean gray value (P = 0.022), area under the curve (P = 0.004) and mean gradient value (GRAD, P = 0.030) regarding the future sperm production capacity (SPC) were shown. At off-test, there was a significant difference for minimum gray value (MIN GV, P = 0.003) and mean gray value (P = 0.001) related to SPC. To find SPC related cut-off values for GSA data, a two segmental non-linear regression analysis was carried out indicating breakpoints for GRAD ≥12 and MIN GV ≥ 40 for boars with low SPC. Off-test boars with MIN GV ≥ 40 showed a 2.4 higher risk to display low SPC (Odds ratio = 2.4 [1.1, 5.4]; P = 0.024). The results may enable breeding companies to include new sperm quality associated traits in their boar testing and selection programs.

Analysis of testicular variables, semen motility and kinematics-derived indexes in boar using a CASA-Mot system

The present study aimed to evaluate differences in area, volume and testicular weight among groups related to breed and age of boar and establish associations between testicular parameters and seminal characteristics. Seminal quality has been studied using computer-assisted semen analysis (CASA) systems that reduce the subjectivity of kinematic parameters. Based on the data obtained through this system, sperm quality indexes and their derived parameters have been assessed to identify a better estimator for determining movement and velocity parameters. We also established indexes of velocity and sperm movement for boar semen. To this end, we evaluated 191 ejaculate samples from 63 boars. Differences related to the effects of season and age on quality boar semen were found (p ≤ .05) in the animal groups. Indexes were established for velocity and sperm movement based on CASA-Mot, and we proposed a sperm movement index (SMI) and sperm velocity index (SVI) with the CASA-Mot variables. Correlations were found (p < .05) among sperm indexes and CASA-Mot variables. Boar characteristics were found to be associated with some CASA-Mot variables, and the estimated SMI and SVI indexes predicted a greater variation in kinematic characteristics compared to the parameters evaluated separately using the CASA-Mot system.

New trends in production management in European pig AI centers

Reducing the number of spermatozoa per artificial insemination (AI) dose and managing semen in ways to ensure greater quality at the same time represents current challenges with sperm processing in pig AI centers. Based on a multi-year comparative analysis of process steps in different pig AI centers, and complementary experimental studies under standardized laboratory conditions, current process standards for the preservation of boar semen have been updated and new ones developed. Currently, these standards represent an integral part of the quality assurance of 29 European pig AI centers in ten different organizations in Germany, Switzerland and Austria. Improvement of hygiene management and guidelines for prudent use of antibiotics have become key issues. Furthermore, new quality control tools have been implemented in the processing and transport of boar semen: e.g. refractometry as an easy-to-use tool to estimate extender osmolarity and 'mobile sensing' apps for continuous monitoring of various environmental parameters. Moreover, based on a series of experiments under laboratory and field conditions, guidelines for optimizing the dilution process, and time and temperature management during boar semen processing, have been developed and implemented. Similarly, recommendations for the handling of semen doses during storage have been renewed. Over the years, the efficiency of the quality assurance system has been reflected by a decrease of bacterial contamination and a concomitant increase in the quality of semen doses. In conclusion, science-based quality assurance is an effective way to improve the production performance in pig AI centers, resulting in high quality and economically-priced semen for pig producers. Increasing knowledge of sperm physiology together with computational and technical innovations will continue to develop and modify quality assurance concepts in the future.

Estimation of genetic parameters and season effects for semen traits in three pig breeds of South China

The economic profitability of a boar station largely depends on semen quantity and quality traits. However, genetic analysis of semen traits has not yet been done in the boar population in China. In this study, we aimed to estimate genetic parameters for semen traits and the influence of seasons on these traits by using data of Duroc, Landrace and Yorkshire boars in South China. The following four semen traits were analysed: semen volume (ml; VOL), sperm concentration (10⁶ /ml; DEN), sperm motility (MOT) and percentage of abnormal sperm (ABN). Genetic parameters and season effects were estimated simultaneously for each breed by using a multiple-trait (4 × 4) repeatability animal model. The four traits had a moderate heritability with average estimates of 0.23, 0.28, 0.26 and 0.17 across the three breeds, respectively. The estimates of genetic correlations among four traits differed in the three breeds. In particular, in Yorkshire, the four traits were nearly genetically independent. The season of collecting semen had a significant impact on these four semen traits except ABN in Duroc (Bonferroni adjusted p < 0.05/6). The moderate heritabilities indicate the possibility of effective selection of boars for semen traits. Different genetic correlations for the three breeds suggest that the selection strategy for the four traits should be investigated separately for each breed. Some necessary actions should be taken to reduce the influence of seasons on semen traits.

Logistic regression analysis of the related factors in discarded semen of boars in Southern China

This study aimed to investigate factors affecting the discarded semen of boars. A total of 176,368 ejaculates of boars from nine AI centers were collected from January 2013 to May 2016 in Southern China. The criteria for determining whether their semen was abnormal included cytoplasmic droplets, coiling tail, sperm agglutination, impurity, poor motility, oligozoospermia, necrozoospermia, azoospermia, and hemospermia. The cause of discarded semen was evaluated with a Chi-square test, and the effects of housing type, breed, age at collection, season identified in the northern hemisphere, and age at herd entry of the discarded semen of boars were analyzed with a logistic regression model. Results indicated the proportion of the discarded semen (PDS) in the nine AI centers was 13.09%. Chi-square test showed the greatest PDS among all causes was found in semen discarded due to cytoplasmic droplets (31.60%), followed by impurity (25.96%), sperm agglutination (20.31%), coiling tail (17.72%), oligozoospermia (10.86%), and others (6.78%; P < 0.0001). Logistic regression analysis revealed the PDS was affected by all these five factors (P < 0.0001). The PDS of boars raised individually in stalls was greater than that of boars raised individually in pens (OR: 1.657; 95% CI: 1.607 to 1.709). The PDSs of Duroc boars (OR: 1.130; 95% CI: 1.093 to 1.167) and Yorkshire boars (OR: 1.432; 95% CI: 1.380 to 1.486) were greater than that of Landrace boars. The PDSs of adult boars (aged from 13 to 24 mo, from 25 to 36 mo, and more than 37 mo with OR: 0.800, 0.941, and 0.838, respectively; 95% CI: 0.771 to 0.831, 0.902 to 0.983, and 0.790 to 0.889, respectively) were lower than those of young boars (aged less than 12 mo). The PDSs of semen collected in summer (OR: 1.367; 95% CI: 1.314 to 1.422), autumn (OR: 1.185; 95% CI: 1.138 to 1.234), and winter (OR: 1.159; 95% CI: 1.115 to 1.206) were greater than those of semen obtained in spring. The PDSs of boars introduced at ages of 5-7 mo (OR: 1.432; 95% CI: 1.380 to 1.486) and 10-12 mo (OR: 1.432; 95% CI: 1.380 to 1.486) were greater than those of boars introduced at an age of 8 and 9 mo. In conclusion, logistic regression analysis reveals discarded semen is affected by housing type, breed, age at collection, season, and age at herd entry. More importantly, cytoplasmic droplets is the primary reason for discarding boar semen, and 8 months at herd entry is the most suitable age for boar introduction.

Linear growth model analysis of factors affecting boar semen characteristics in Southern China

This study investigated the factors affecting the semen traits of boars in Southern China. A total of 172,408 ejaculates of boars from 9 AI centers were collected from January 2013 to May 2016. A linear growth model was used to analyze the effects of leve1 1 (boar breed, age, season, and boar age at herd entry) and level 2 (housing type) factors on semen quality. The intraclass correlation coefficients of semen volume, total sperm number, functional sperm number, sperm concentration, motility, and abnormal sperm were 0.62, 0.62, 0.61, 0.60, 0.54, and 0.70, respectively. Boars reared in ordinary houses had lower total and functional sperm numbers than those reared in air filtration houses ( < 0.05). The functional sperm number of Duroc boars was lower than that of Landrace and Yorkshire boars ( < 0.05). The total and functional sperm numbers were lowest from May to September and peaked at the age of 34.1 and 37.7 mo, respectively. Furthermore, boars aged 8 and 9 mo at herd entry had greater functional sperm numbers than those aged 5, 6, 7, and 12 mo at herd entry ( < 0.05), whereas no significant difference was observed between boars aged 8 mo and boars aged 9 mo at herd entry ( > 0.05). In conclusion, the linear growth model is suitable for longitudinal data analysis. To improve boar breeding, sunstroke prevention in the early spring should be given greater attention. Importantly, 8 mo appears to be the most suitable age for boar introduction, especially for Duroc boars.

Genetic parameters for semen quality and quantity traits in five pig lines

We aimed to estimate genetic parameters for semen quality and quantity traits as well as for within-boar variation of these traits to evaluate their inclusion in breeding goals. Genetic parameters were estimated within line using a multiple-trait (4 × 4) repeatability animal model fitted for 5 pig lines, considering 4 semen traits: sperm motility (MOT), sperm progressive motility (PROMOT), log-transformed number of sperm cells per ejaculate (lnN), and total morphological abnormalities (ABN). The within-boar variation of these traits was analyzed based on a multiple-trait (2 × 2) approach for SD and average (AVG) and a single-trait analysis for CV. The average heritabilities across the 5 lines estimated by multiple-trait analysis were 0.18 ± 0.07 (MOT), 0.22 ± 0.08 (PROMOT), 0.16 ± 0.04 (lnN), and 0.20 ± 0.04 (ABN). The average genetic correlations were favorable between MOT and PROMOT (0.86 ± 0.10), between MOT and ABN (-0.66 ± 0.25), and between PROMOT and ABN (-0.65 ± 0.25). As determined by within-boar variation analysis, AVG exhibited the greatest heritabilities followed by SD and CV, respectively, for the traits MOT and ABN. For PROMOT, average SD heritability was lower than CV heritability, whereas for lnN, they were the same. The average genetic correlations between AVG and SD were favorable for MOT (-0.60 ± 0.13), PROMOT (-0.79 ± 0.14), and ABN (0.78 ± 0.17). The moderate heritabilities indicate the possibility of effective selection of boars based on semen traits. Average and SD are proposed as appropriate traits for selection regarding uniformity.

Effect of production management on semen quality during long-term storage in different European boar studs

The processing of ejaculates is a fundamental step for the fertilizing capacity of boar spermatozoa. The aim of the present study was to identify factors that affect quality of boar semen doses. The production process during 1 day of semen processing in 26 European boar studs was monitored. In each boar stud, nine to 19 randomly selected ejaculates from 372 Pietrain boars were analyzed for sperm motility, acrosome and plasma membrane integrity, mitochondrial activity and thermo-resistance (TRT). Each ejaculate was monitored for production time and temperature for each step in semen processing using the special programmed software SEQU (version 1.7, Minitüb, Tiefenbach, Germany). The dilution of ejaculates with a short-term extender was completed in one step in 10 AI centers (n = 135 ejaculates), in two steps in 11 AI centers (n = 158 ejaculates) and in three steps in five AI centers (n = 79 ejaculates). Results indicated there was a greater semen quality with one-step isothermal dilution compared with the multi-step dilution of AI semen doses (total motility TRT d7: 71.1 ± 19.2%, 64.6 ± 20.0%, 47.1 ± 27.1%; one-step compared with two-step compared with the three-step dilution; P < .05). There was a marked advantage when using the one-step isothermal dilution regarding time management, preservation suitability, stability and stress resistance. One-step dilution caused significant lower holding times of raw ejaculates and reduced the possible risk of making mistakes due to a lower number of processing steps. These results lead to refined recommendations for boar semen processing.

Applications of capacitation status for litter size enhancement in various pig breeds

Objective

Several studies have reported the development of new molecular methods for the prognosis and diagnosis of male fertility based on biomarkers aimed at overcoming the limitations of conventional male fertility analysis tools. However, further studies are needed for the field application of these methods. Therefore, alternative methods based on existing semen analysis methods are required to improve production efficiency in the animal industry.

Methods

we examined the possibility of improving litter size in various pig breeds using combined Hoechst 33258/chlortetracycline fluorescence (H33258/CTC) staining. The correlation between field fertility and capacitation status by combined H33258/CTC staining in different ejaculates spermatozoa (n = 3) from an individual boar (20 Landrace, 20 Yorkshire, and 20 Duroc) was evaluated as well as overall accuracy.

Results

The acrosome reacted (AR) pattern after capacitation (%) was positively correlated with the litter size of Landrace, Yorkshire, and Duroc pigs and the overall accuracy was 75%, 75%, and 70% in Landrace, Yorkshire, and Duroc pigs, respectively. The difference (Δ) in AR pattern before and after capacitation was positively correlated with the litter size of Landrace, Yorkshire, and Duroc pigs and the overall accuracy was 80%, 65%, and 55% in Landrace, Yorkshire, and Duroc pigs, respectively. However, the difference (Δ) in capacitated (B) pattern before and after capacitation was negatively correlated with the litter size of Landrace pigs and the overall accuracy was 75%. Moreover, average litter size was significantly altered according to different combined H33258/CTC staining parameters.

Conclusion

These results show that combined H33258/CTC staining may be used to predict male fertility in various breeds. However, the selection of specific efficiency combined H33258/CTC staining parameters requires further consideration. Taken together, these findings suggest that combined H33258/CTC staining may constitute an alternative method for predicting male fertility until such time as fertility-related biomarkers are further validated.

Boar management and semen handling factors affect the quality of boar extended semen

Artificial insemination (AI) is the preferred method for reproduction in the majority of the intensive pig production systems Worldwide. To this end, fresh extended ready-to-use semen doses are either purchased from AI-centres or produced by boars kept on-farm. For profitable semen production, it is necessary to obtain a maximum amount of high quality semen from each boar. This paper reviews current knowledge on factors that may affect semen quality by influencing the boar or the semen during processing. Genetic markers could be used for early detection of boars with the highest fertility potential. Genetic selection for fast growth might jeopardize semen quality. Early detection of boars no longer fit for semen production might be possible by ultrasonography of the testes. Seasonal variation in sperm quality could be associated with changes in photoperiod and heat stress during summer. Comfortable housing, with appropiate bedding material to avoid locomotion problems is essential. In some areas, cooling systems may be necessary to avoid heat stress. The sperm quality can be manipulated by feeding strategies aiming, for instance, to increase sperm resistance to oxidative stress and extend storage duration. High collection frequency will negatively influence sperm quality. Also, if collection is not hygienically performed it will result in bacterial contamination of the semen doses. The concern over bacterial contamination has risen not only because of its negative effect on semen quality but also due to the detection of antimicrobial resistance in isolates from extended semen. Moreover, bacterial and viral pathogens must be monitored because they affect semen production and quality and constitute a risk of herd infection. During processing, boar sperm are submitted to many stress factors that can cause oxidative stress and capacitation-like changes potentially reducing their fertility potential. Dilution rate or dilution temperature affects the quality of the semen doses. Some packaging might preserve semen better than others and some plastic components might be toxic for sperm. Standard operation procedures and quality assurance systems in AI centres are needed.

Analysis of the lifetime and culling reasons for AI boars

BACKGROUND

The aim of the study was to analyze the lifetime and culling reasons for boars used in insemination centers (AI centers).

METHODS

The data collected from 355 culled boars from 1998 to 2013 included: age at start of semen collection, boar herd life, culling reason, daily gain and lean meat content, and number of ejaculates not meeting sales requirements after dilution. Culling reasons were divided into 7 groups: low semen value (LSV), low or lack of libido (LL), leg problems (LP), infectious diseases (ID), old age (OA), reduced demand for semen from the given boar (RD), and others (OT).

RESULTS

The most common culling reasons for boars were LSV (23.7%) and RD (22.5%). It was observed that the lowest daily gains were noted in boars culled due to OA. Boars culled due to OA and RD were maintained in production for the longest time (over 1000 d), for LSV and ID retention was about 700 d, and due to LL below 400 d. The survival probability was over 0.9 until 1.5 yr, and just over 0.2 until 4 yr. The highest relative frequency was observed in the 36th and 42nd mo of life (over 16%). Hazard risk analysis revealed a more than 10 times higher risk of culling in the case of LL, ID or OT, in comparison to OA.

CONCLUSIONS

The results can be used as a direct point of reference for the identification of emerging problems in AI boar exploitation and the development of an appropriate culling policy in AI centers.

Boar genotype as a factor shaping age-related changes in semen parameters and reproduction longevity simulations

The aim of this study was a detailed analysis of the boar genotypes used in AI stations with an indication of their production capacity, including age and a precise analysis of their culling time and reason. The study included 334 boars: 81 Polish Large White (PLW), 108 Polish Landrace (PL), 49 Pietrain (P), 56 Duroc × Pietrain (D × P) and 40 Hampshire × Pietrain (H × P). Semen volume, spermatozoa concentration, total number of spermatozoa, number of motile spermatozoa, and number of insemination doses were analyzed. Quadratic regression was used to illustrate the selected sperm parameters at specific ages. Among all the studied boars the lowest motilities of spermatozoa were identified in white breeds PLW and PL, and the difference between motility extremes was 3.53% (P ≤ 0.01). The highest number of insemination doses were produced from D × P crossbreed boars: about 0.7 portions more compared to PL, 1.13 to PLW, 1.18 to H × P and 1.8 to P (all differences P ≤ 0.01). It has been shown in the case of ejaculate volume that for PLW and H × P boars the culling moment was far too early in terms of production capacity and differences were, respectively, 16.35 ml for PLW and 12.61 ml for H × P. Based on the developed regression equations, the earliest maximum number of motile sperm (73.82 × 10⁹) was obtained by H × P crossbreed boars as early as at age 24 months. The highest values for this parameter were achieved, however, by other D × P crossbreed boars: 74.30 × 10⁹ at the later age of 32 months. A consequence of the high number of motile sperm in young H × P boars was that the theoretical maximum value of the number of AI doses was produced as early as the 14th month (25.59 portions). Curves of similar shape were obtained for PL and D × P boars; the difference in maximal values was 0.54 portions in favor of crossbreeds, at a later age of 7 months. It was noted that for PLW and D × P boars the highest number of cullings were due to reduced demand (24.47% and even 31.19%, respectively). Other boars - PL, P and H × P - were most frequently culled because of low semen values. Regardless of the genotype, high survival probabilities (over 0.96) were noted for the age of 12 months. The highest probabilities (still over 0.96) were noted in the longest time period (up to 18 months) for P boars. The results of our study can be used in AI stations as reference points for the exploitation and culling of boars with different genotypes.

The dependence of the growth rate and meat content of young boars on semen parameters and conception rate

Boars have a decisive impact on the progress in pig production, however, there is no recent information about the optimal growth parameters during the rearing period for modern breed later used in artificial insemination (AI) stations. Therefore, the objective of the research was to conduct semen parameter and conception rate analyses on the basis of growth rate and meat content assessments made during the rearing of AI boars of different genotypes. The study was carried out between 2010 and 2014 and included 184 boars in five breed combinations: 46 Polish Large White, 50 Polish Landrace, 27 Pietrain, 36 Duroc×Pietrain and 25 Hampshire×Pietrain. Boars were qualified by daily gains and meat content assessment (between 170 and 210 days of life). A total number of 38 272 ejaculates were examined (semen volume (ml), spermatozoa concentration (×106 ml-1), total number of spermatozoa (×109) and number of insemination doses from one ejaculate (n)). The fertility was determined by the conception rate (%). Semen volume, spermatozoa concentration and conception rate (P<0.01), followed by the total number of spermatozoa and insemination doses (P<0.05) were characterized by the highest variability in relation to breed of boars. The effect of daily gains was reported for spermatozoa concentration, number of insemination doses, conception rate (all P<0.01) and total number of spermatozoa (P<0.05). The peak of growth for spermatozoa concentration, total number of spermatozoa, insemination doses and conception rate was achieved for 800 to 850 g gains. Meat content affected semen volume, number of insemination doses and conception rate (P<0.05). Rearing boars while maintaining daily gains at the 800 to 850 g level and 62.5% to 65% meat content helps AI stations to increase the efficiency and economic profitability, and the number of insemination doses to increase by up to 300 doses/boar within a year. The analyses of growth parameters may help increase the efficiency and economic viability of AI stations.

MicroRNA in sperm from Duroc, Landrace and Yorkshire boars

Sperm contain microRNAs (miRNAs), which may have roles in epigenetic control. Regarding phylogenetic relationships among various swine breeds, Yorkshire and Landrace, are considered phenotypically and genetically very similar, but distinctly different from Duroc. The objective of the present study was to compare abundance of boar sperm miRNAs in these three breeds. Overall, 252 prioritized miRNAs were investigated using real-time PCR; relative expression of miRNAs in sperm was similar in Yorkshire and Landrace boars, but significantly different compared to Duroc. Seventeen miRNAs (hsa-miR-196a-5p, hsa-miR-514a-3p, hsa-miR-938, hsa-miR-372-3p, hsa-miR-558, hsa-miR-579-3p, hsa-miR-595, hsa-miR-648, hsa-miR-524-3p, hsa-miR-512-3p, hsa-miR-429, hsa-miR-639, hsa-miR-551a, hsa-miR-624-5p, hsa-miR-585-3p, hsa-miR-508-3p and hsa-miR-626) were down-regulated (P < 0.05; fold regulation ≤-2) in Yorkshire and Landrace sperm, compared to Duroc sperm. Furthermore, three miRNAs (hsa-miR-9-5p, hsa-miR-150-5p, and hsa-miR-99a-5p) were significantly up-regulated in Yorkshire and Landrace sperm compared to Duroc sperm, However, 240 miRNAs were not significantly different (within + 2 fold) between Yorkshire and Landrace sperm. We concluded that miRNAs in sperm were not significantly different between Yorkshire and Landrace boars, but there were significant differences between those two breeds and Duroc boars. Furthermore, integrated target genes for selected down-regulated miRNAs (identified via an in-silico method) appeared to participate in spermatogenesis and sperm functions.

Genetic relationships between length of productive life and lifetime production efficiency in a commercial swine herd in Northern Thailand

Genetic parameters and trends for length of productive life (LPL), lifetime number of piglets born alive per year (LBAY), lifetime number of piglets weaned per year (LPWY), lifetime litter birth weight per year (LBWY) and lifetime litter weaning weight per year (LWWY) were estimated using phenotypic records of 3085 sows collected from 1989 to 2013 in a commercial swine farm in Northern Thailand. The five-trait animal model included the fixed effects of first farrowing year-season, breed group and age at first farrowing. Random effects were animal and residual. Heritability estimates ranged from 0.04 ± 0.02 for LBWY to 0.17 ± 0.04 for LPL. Genetic correlations ranged from 0.66 ± 0.14 between LPL and LBAY to 0.95 ± 0.02 between LPWY and LWWY. Spearman rank correlations among estimated breeding values for LPL and lifetime production efficiency traits tended to be higher for boars than for sows. Sire genetic trends were negative and significant for all traits, except for LPWY. Dam genetic trends were positive and significant for all traits. Sow genetic trends were mostly positive and significant only for LPWY and LBWY. Improvement of LPL and lifetime production efficiency traits will require these traits to be included in the selection indexes used to choose replacement boars and gilts in this population.

Boar Differences In Artificial Insemination Outcomes: Can They Be Minimized?

In Western countries, where pig breeding and production are intensive, there is a documented variability in fertility between farms with boar-related parameters only accounting to 6% of this total variation of in vivo fertility. Such low boar effect could be a result of the rigorous control of sires and ejaculates yielding AI-doses exerted by the highly specialized AI-centres that monopolize the market. However, some subfertile boars pass through these rigorous controls and consequently reach the AI-programmes. Here, we discuss why testing young boars for chromosomal defects, sperm nuclear chromatin integrity and in vitro fertilizing ability can be discriminative and economically sound for removing these less fertile boars. Alongside, we discuss why boars differ in the ability of their sperm to tolerate cryopreservation or sex sorting.

Artificial insemination in pigs today

Use of artificial insemination (AI) for breeding pigs has been instrumental for facilitating global improvements in fertility, genetics, labor, and herd health. The establishment of AI centers for management of boars and production of semen has allowed for selection of boars for fertility and sperm production using in vitro and in vivo measures. Today, boars can be managed for production of 20 to 40 traditional AI doses containing 2.5 to 3.0 billion motile sperm in 75 to 100 mL of extender or 40 to 60 doses with 1.5 to 2.0 billion sperm in similar or reduced volumes for use in cervical or intrauterine AI. Regardless of the sperm dose, in liquid form, extenders are designed to sustain sperm fertility for 3 to 7 days. On farm, AI is the predominant form for commercial sow breeding and relies on manual detection of estrus with sows receiving two cervical or two intrauterine inseminations of the traditional or low sperm doses on each day detected in standing estrus. New approaches for increasing rates of genetic improvement through use of AI are aimed at methods to continue to lower the number of sperm in an AI dose and reducing the number of inseminations through use of a single, fixed-time AI after ovulation induction. Both approaches allow greater selection pressure for economically important swine traits in the sires and help extend the genetic advantages through AI on to more production farms.

Improving litter size by boar spermatozoa: application of combined H33258/CTC staining in field trial with artificial insemination

Conventional semen analysis offers basic information on infertility; however, its clinical value in predicting fertility status is unclear. To establish an accurate diagnosis of male fertility, semen analysis under capacitation condition is necessary because only capacitated spermatozoa are capable of fertilizing oocytes. The objective of this study was to verify male fertility based on conventional semen analysis before and after capacitation, including the assessment of motility (%), motion kinematics, and capacitation status of spermatozoa. A computer-assisted sperm analysis system and chlortetracycline staining were applied to evaluate the motility parameters and capacitation status, respectively. To enable efficacy of the two methods for predicting fertility, correlation analysis was performed with the historic litter size. Our results showed that sperm motility (%), motion kinematics, and their variations before and after capacitation represented a statistical non-significant correlation with litter size. Litter size showed significant correlation with acrosome reaction (AR) after capacitation (r = 0.375), as well as differences (Δ) in AR (r = 0.333) and capacitated (B) pattern (r = -0.447) before and after capacitation. The overall accuracy of the assay for predicting litter sizes using the AR and differences (Δ) in the AR and B pattern was 70%. On the basis of these results, we propose that capacitation status of spermatozoa is a more reliable indicator for evaluating male fertility status compared to motility parameters. Therefore, we suggest that analysis of capacitation status in company with conventional semen analysis may accept to evaluate more accurate diagnosis or prognosis of male fertility.

A genome-wide association study reveals a novel candidate gene for sperm motility in pigs

Sperm motility is one of the most widely used parameters in order to evaluate boar semen quality. However, this trait can only be measured after puberty. Thus, the use of genomic information appears as an appealing alternative to evaluate and improve selection for boar fertility traits earlier in life. With this study we aimed to identify SNPs with significant association with sperm motility in two different commercial pig populations and to identify possible candidate genes within the identified QTL regions. We performed a single-SNP genome-wide association study using genotyped animals from a Landrace-based (L1) and a Large White-based (L2) pig populations. For L1, a total of 602 animals genotyped for 42,551 SNPs were used in the association analysis. For L2, a total of 525 animals genotyped for 40,890 SNPs were available. After the association analysis, a false discovery rate q-value ≤0.05 was used as the threshold for significant association. No SNPs were significantly associated with sperm motility in L1, while six SNPs on Sus scrofa chromosome 1 (position 117.26-119.56Mb) were significant in L2. The mitochondrial methionyl-tRNA formyltransferase (MTFMT) gene, which affects translation efficiency of proteins in sperm cells, was identified as a putative candidate gene. The significant markers identified in this study may be useful to enhance the genetic improvement of sperm motility by selection of boars at an earlier age under a marker assisted selection strategy.

Pig Spermatozoa Defect in Acrosome Formation Caused Poor Motion Parameters and Fertilization Failure through Artificial Insemination and In vitro Fertilization

The selection of morphologically normal spermatozoa is critical to obtain high breeding performances in boar breeding farms and artificial insemination (AI) centers. Parameters for the selection of semen mainly include total sperm motility, concentration, and morphology. However, these primary parameters are often not reliable for discriminating between normal and abnormal, non-fertilizable spermatozoa. The present study was designed to compare the motion characteristics, fertilization ability using in vitro fertilization (IVF), and acrosome formation of the semen from boars having low (boar number 2012) and normal (boar number 2004 and 2023) breeding performances. The ultimate goal was to identify additional simple and easy criteria for the selection of normal sperm. There was no significant difference between boar 2004 and boar 2023 sperm total motility in computer assisted sperm analysis. However, boar number 2012 semen presented a significantly reduced population of rapid moving spermatozoa and an increased population of slow moving spermatozoa compared to boar numbers 2004 and 2023. Analysis of detailed motion characteristics revealed that sperm from boar number 2012 had significantly reduced motility in progressiveness, average path velocity, straight-line velocity (VSL), curvilinear velocity (VCL), straightness, and linearity. The assessment of the fertilizing ability by IVF also showed that sperm from boar number 2012 showed a fertility rate of 3.4%, whereas sperm from boar number 2023 had a fertility rate of 75.45%. Interestingly, most of the sperm nuclei were found on the peripheral area of the oocytes, suggesting that the sperm from boar number 2012 lacked penetration ability into the oocyte zonapellucida. The acrosome formation analysis using Pisum sativum agglutinin staining demonstrated that the sperm from boar number 2012 had a defect in acrosome formation. Consequently, primary parameters for selecting semen before AI such as motility are not sufficient to select normal and fertilizable spermatozoa. In conclusion, the present study suggests that the acrosome staining and detailed motion characteristics such as progressiveness, VCL, and VSL should be included in determining semen quality together with primary parameters for successful AI and high breeding performance in the swine industry.

Effects of altering the dose and timing of triptorelin when given as an intravaginal gel for advancing and synchronizing ovulation in weaned sows

Previous studies have shown that triptorelin gel (TG) given intravaginally in gel form is effective for advancing the time of ovulation in weaned sows. Three experiments were performed to determine the effects of altering the dose and timing of administration of intravaginal TG for advancing and synchronizing ovulation in weaned sows. In all experiments, estrus was detected twice or three times daily and ultrasound was performed to determine ovulation at 8-hour intervals. In experiment 1, sows (n = 131) received intravaginal gel containing 0 (Placebo), 25, 100, or 200 μg of TG at 96 hours after weaning and sows were inseminated on each day of standing estrus. Wean-to-estrus interval and duration of estrus were correlated (P < 0.0001) with estrus duration longer in TG (P < 0.05) compared with Placebo. More sows ovulated (P < 0.001) by 48 hours after treatment with 200 (81%), 100 (64%), and 25 μg (63%) of TG compared with Placebo (42%). The farrowing rate and total pigs born did not differ (P > 0.10). In experiment 2, sows (n = 126) received 200 μg of TG at 72, 84, or 96 hours after weaning or were untreated (Control-96). Sows receiving TG were inseminated once 24 to 28 hours after treatment. Control-96 sows were inseminated on each day of standing estrus. Wean-to-estrus interval was not affected by treatment, but wean-to-ovulation interval was reduced (P < 0.05) by TG-72 and TG-84 compared with TG-96 and Control-96. More sows ovulated 40 hours after treatment (P < 0.001) with TG-72 (56.5%) and TG-84 (32.2%) compared with TG-96 and Control-96 (13%) and for all TG treatments 48 hours after treatment (64%) compared with Control-96 (34%, P < 0.05). The farrowing rate was lower (P < 0.05) for sows assigned to TG-72 and TG-84 compared with TG-96 and Control-96, whereas the number of liveborn pigs did not differ (P > 0.10). In experiment 3, sows (n = 113) were assigned to receive no treatment (Control), intravaginal gel alone (Placebo), or 200 μg of TG given intravaginally (OvuGel) at 96 hours after weaning. Wean-to-estrus interval did not differ, but the duration of estrus tended (P < 0.10) to be reduced with OvuGel compared with the other treatments. More sows ovulated (P < 0.001) by 48 hours after OvuGel treatment (79.1%) compared with Control (46.4%) and Placebo (37.9%) and by 56 hours (P < 0.05). The farrowing rate and the number of liveborn pigs did not differ among treatments. The results of these studies indicate that 200 μg of TG given intravaginally at 96 hours after weaning (OvuGel) synchronizes ovulation and results in fertility similar to Controls.

Genetic correlations between production and semen traits in pig

Genetic correlations between production traits (average daily gain from birth till the end of the field test and ultrasonically predicted lean meat content at the end of the field test) and semen traits (semen volume, sperm concentration, motility, percentage of abnormal spermatozoa, total number of spermatozoa and number of functional spermatozoa) were estimated from a large dataset (44 500 observations for production traits and more than 150 000 ejaculates from 2077 boars). The boars belonged to the breeds Duroc, Piétrain and Large White or were crossbreds between them. All estimated genetic correlations were low (maximal absolute value 0.13). Therefore, selection on production traits is expected to have only low effects on semen traits.

Differences in the ability of spermatozoa from individual boar ejaculates to withstand different semen-processing techniques

The present study aimed to evaluate the ability of spermatozoa from individual boar ejaculates to withstand different semen-processing techniques. Eighteen sperm-rich ejaculate samples from six boars (three per boar) were diluted in Beltsville Thawing Solution and split into three aliquots. The aliquots were (1) further diluted to 3×10(7) sperm/mL and stored as a liquid at 17°C for 72 h, (2) frozen-thawed (FT) at 1×10(9) sperm/mL using standard 0.5-mL straw protocols, or (3) sex-sorted with subsequent liquid storage (at 17°C for 6 h) or FT (2×10(7) sperm/mL using a standard 0.25-mL straw protocol). The sperm quality was evaluated based on total sperm motility (the CASA system), viability (plasma membrane integrity assessed using flow cytometry and the LIVE/DEAD Sperm Viability Kit), lipid peroxidation (assessed via indirect measurement of the generation of malondialdehyde (MDA) using the BIOXYTECH MDA-586 Assay Kit) and DNA fragmentation (sperm chromatin dispersion assessed using the Sperm-Sus-Halomax(®) test). Data were normalized to the values assessed for the fresh (for liquid-stored and FT samples) or the sorted semen samples (for liquid stored and the FT sorted spermatozoa). All of the four sperm-processing techniques affected sperm quality (P<0.01), regardless of the semen donor, with reduced percentages of motile and viable sperm and increased MDA generation and percentages of sperm with fragmented DNA. Significant (P<0.05) inter-boar (effect of boars within each semen-processing technique) and intra-boar (effect of semen-processing techniques within each boar) differences were evident for all of the sperm quality parameters assessed, indicating differences in the ability of spermatozoa from individual boars to withstand the semen-processing techniques. These results are the first evidence that ejaculate spermatozoa from individual boars can respond in a boar-dependent manner to different semen-processing techniques.