Virus removal from semen with a pinched flow fractionation microfluidic chip

Nowadays pigs are bred with artificial insemination to reduce costs and transportation. To prevent the spread of diseases, it is important to test semen samples for viruses. Screening techniques applied are enzyme-linked immunosorbent assays and/or polymerase chain reaction, which are labor-intensive and expensive methods. In contrast to the current used screening techniques, it is possible to remove viruses physically from semen. However, existing methods for virus removal techniques have a low yield of spermatozoa. Therefore, we have developed a microfluidic chip that performs size-based separation of viruses and spermatozoa in boar semen samples, thereby having the potential to reduce the risk of disease spreading in the context of artificial insemination in the veterinary industry. As the head of a spermatozoon is at least twenty times larger than a virus particle, the particle size can be used to achieve separation, resulting in a semen sample with lower viral load and of higher quality. To achieve the size separation, our microfluidic device is based on pinched-flow fractionation. A model virus, cowpea chlorotic mottle virus, was used and spiked to porcine semen samples. With the proposed microfluidic chip and the optimized flow parameters, at least 84 ± 4% of the model viruses were removed from the semen. The remaining virus contamination is caused by the model virus adhering to spermatozoa instead of the separation technique. The spermatozoa recovery was 86 ± 6%, which is an enormous improvement in yield compared to existing virus removal techniques.

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.

Relationship between ovulation rate and embryonic characteristics in gilts at 35 d of pregnancy

This study investigated the relationship between ovulation rate (OR) and embryonic characteristics in gilts. Landrace ( = 86) and Yorkshire x Landrace ( = 212) gilts were inseminated with semen stored for 3 to 5 d (SS1, = 59), 6 to7 d (SS2, = 133), or 8 to 10 d (SS3, = 106), and slaughtered at 35 d of pregnancy. Ovulation rate was assessed by dissection of the corpora lutea on both ovaries. Embryos were classified as vital (VE) by visual appearance and individually weighed (VEg) and the SD of the weight calculated (SDVEg). Early embryonic mortality (EM) was estimated as the difference between OR and the number of vital plus nonvital embryos. Embryonic characteristics were analyzed with a model that included linear and quadratic terms of OR and fixed class effects of semen storage duration (SS) and genetic line (GL). Landrace gilts had a higher OR than Yorkshire x Landrace gilts (22.1 ± 0.4 vs. 20.3 ± 0.2, ≤ 0.05) and also a higher EM (6.1 ± 0.4 vs. 3.5 ± 0.3, ≤ 0.05). EM was also higher in gilts inseminated with semen stored for more than 8 d. Also, Yorkshire x Landrace gilts had a higher number of VE (16.9 ± 0.7) than the Landrace gilts (13.3 ± 0.8) when inseminations were done with semen stored for up to 5 d. Yorkshire x Landrace gilts had the highest VEg when inseminated with semen stored for 3 to 5 d (SS1: 4.9 ± 0.2 g, SS2: 4.1 ± 0.1 g, and SS3: 4.0 ± 0.2 g; ≤ 0.05). VE and VEg did not differ within Landrace gilts between different SS classes. A quadratic relationship of OR ( ≤ 0.05) was found with VE: a maximum of 16.8 VE was observed at 26 ovulations [(2.5 (± 0.6)*OR- 0.05 (± 0.01)*OR]. A quadratic relationship of OR ( ≤ 0.05) was also found for EM: a minimum of 3.33 EM was observed at 15 ovulations [(-1.1 (± 0.6)*OR -0.03 (± 0.01)*OR]. VEg was not related with OR, but SDVEg had a positive linear relationship with OR [0.01 (± 0.003)*OR, ≤ 0.05]. Results show that Yorkshire x Landrace gilts perform better than Landrace when inseminated with fresh semen, but not with semen stored for longer time. Also, the VE increases with an increase in OR up to 26, but at a lower level at higher OR, which is likely related with the increase in EM. The higher EM at higher OR might arise from a higher variation in follicular/oocyte quality leading to a higher variation in embryonic quality and development, increasing mortality before uterine implantation and the variation in embryonic weight already at 35 d of pregnancy.

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.

Efficient Boar Semen Production and Genetic Contribution: The Impact of Low-Dose Artificial Insemination on Fertility

Diluting semen from high fertile breeding boars, and by that inseminating many sows, is the core business for artificial insemination (AI) companies worldwide. Knowledge about fertility results is the reason by which an AI company can lower the concentration of a dose. Efficient use of AI boars with high genetic merit by decreasing the number of sperm cells per insemination dose is important to maximize dissemination of the genetic progress made in the breeding nucleus. However, a potential decrease in fertility performance in the field should be weighed against the added value of improved genetics and, in general, is not tolerated in commercial production. This overview provides some important aspects that influence the impact of low-dose AI on fertility: (i) the importance of monitoring field fertility, (ii) the need for accurate and precise semen assessment, (iii) the parameters that are taken into account, (iv) the application of information from genetic and genomic selection and (v) the optimization when using different AI techniques. Efficient semen production, processing and insemination in combination with increasing use of genetic and genomic applications result in maximum impact of genetic trend.

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.

The practical use of density of whole bull semen to determine the volume of an ejaculate at AI laboratories

Determining the volume of an ejaculate is an important part of processing semen in bovine AI laboratory practice. A multi-AI laboratory study was performed to estimate the density of whole bull semen, and whether the use of this value as a standard is suitable for practical use when semen of different breeds is processed at different AI laboratories. The density of whole bull semen had been determined for 90 ejaculates at five AI laboratories (five breeds). The results showed no effect of bull (p=0.766), breed (p=0.279) and laboratory (p=0.183). All duplicate measurements within the same sample were within the level of agreement (5%). Using the mean value of 1.053g/ml as a golden standard for the density of whole bull semen is therefore suitable for use in routine bovine AI laboratory practice.

Field data analysis of boar semen quality

This contribution provides an overview of approaches to correlate sow fertility data with boar semen quality characteristics. Large data sets of fertility data and ejaculate data are more suitable to analyse effects of semen quality characteristics on field fertility. Variation in fertility in sows is large. The effect of semen factors is relatively small and therefore impossible to find in smaller data sets. Large data sets allow for statistical corrections on both sow- and boar-related parameters. Remaining sow fertility variation can then be assigned to semen quality parameters, which is of huge interest to AI (artificial insemination) companies. Previous studies of Varkens KI Nederland to find the contribution to field fertility of (i) the number of sperm cells in an insemination dose, (ii) the sperm motility and morphological defects and (iii) the age of semen at the moment of insemination are discussed in context of the possibility to apply such knowledge to select boars on the basis of their sperm parameters for AI purposes.