Label-Free Microfluidic Impedance Cytometry for Acrosome Integrity Assessment of Boar Spermatozoa.

Microfluidics and lab-on-chip technologies have been used in a wide range of biomedical applications. They are known as versatile, rapid, and low-cost alternatives for expensive equipment and time-intensive processing. The veterinary industry and human fertility clinics could greatly benefit from label-free and standardized methods for semen analysis.

The effect of adjusting settings within a Computer-Assisted Sperm Analysis (CASA) system on bovine sperm motility and morphology results.

Semen motility is the most widely recognized semen quality parameter used by Artificial Insemination (AI) centers. With the increasing worldwide export of semen between AI centers there is an increasing need for standardized motility assessment methods. Computer-Assisted Sperm Analysis (CASA) technology is thought to provide an objective motility evaluation; however, results can still vary between laboratories.

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.

Using short read sequencing to characterise balanced reciprocal translocations in pigs.

Background: A balanced constitutional reciprocal translocation (RT) is a mutual exchange of terminal segments of two non-homologous chromosomes without any loss or gain of DNA in germline cells. Carriers of balanced RTs are viable individuals with no apparent phenotypical consequences. These animals produce, however, unbalanced gametes and show therefore reduced fertility and offspring with congenital abnormalities.

Effect of microfluidic processing on the viability of boar and bull spermatozoa.

The use of microfluidics in artificial reproductive technologies for manipulation or assessment of spermatozoa is unique in the sense that it is not always an end point measurement and the sample may be used afterward. During microfluidic processing, spermatozoa are exposed to shear stress, which may harm viability and functioning of spermatozoa. The shear stresses during general microfluidic processing steps were calculated and compared to estimated shear stresses during ejaculation.

Machine learning to further improve the decision which boar ejaculates to process into artificial insemination doses.

Current artificial insemination (AI) laboratory practices assess semen quality of each boar ejaculate to decide which ones to process into AI doses. This decision is aided with two, world-wide used, motility parameters that come available through computer assisted semen analysis (CASA). This decision process, however, still results in AI doses with variable and sometimes suboptimal fertility outcomes (e.

Exposing dairy bulls to high temperature-humidity index during spermatogenesis compromises subsequent embryo development in vitro.

The possible impact of natural heat stress on animal fertility is currently a major concern for breeding companies. Here, we aimed to address this concern by determining the effects of natural heat stress on the fertility of Holstein bulls located in the Netherlands. Semen samples were collected from six bulls at two locations in March 2016 (low temperature-humidity index (THI) group; maximum THI of 51.

Weighted single-step GWAS and gene network analysis reveal new candidate genes for semen traits in pigs.

Background: In recent years, there has been increased interest in the study of the molecular processes that affect semen traits. In this study, our aim was to identify quantitative trait loci (QTL) regions associated with four semen traits (motility, progressive motility, number of sperm cells per ejaculate and total morphological defects) in two commercial pig lines (L1: Large White type and L2: Landrace type). Since the number of animals with both phenotypes and genotypes was relatively small in our dataset, we conducted a weighted single-step genome-wide association study, which also allows unequal variances for single nucleotide polymorphisms.

Relationship Between the Estimated Breeding Values for Litter Traits at Birth and Ovarian and Embryonic Traits and Their Additive Genetic Variance in Gilts at 35 Days of Pregnancy.

We investigated (1) the relationship between the estimated breeding values (EBVs) for litter traits at birth and ovulation rate (OR), average corpora luteal weight, uterine length and embryonic survival and development traits in gilts at 35 days of pregnancy by linear regression, (2) the genetic variance of OR, average corpora lutea (CL) weight, uterine length and embryonic survival and development traits at 35 days of pregnancy, and (3) the genetic correlations between these traits. Landrace ( = 86) and Yorkshire × Landrace ( = 304) gilts were inseminated and slaughtered at 35 days of pregnancy. OR was assessed by dissection of the CL on both ovaries.

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.

Genetic control of complex traits, with a focus on reproduction in pigs.

Reproductive traits are complex, and desirable reproductive phenotypes, such as litter size or semen quality, are true polygenetic traits determined by multiple gene regulatory pathways. Each individual gene contributes to the overall variation in these traits, so genetic improvements can be achieved using conventional selection methodology. In the past, a pedigree-based-relationship matrix was used; this is now replaced by a combination of pedigree-based- and genomic-relationship matrices.

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.

Relationships between ovulation rate and embryonic and placental characteristics in multiparous sows at 35 days of pregnancy.

The objective of this study was to investigate relationships between ovulation rate (OR) and embryonic and placental development in sows. Topigs Norsvin® sows (n=91, parity 2 to 17) from three different genetic backgrounds were slaughtered at 35 days of pregnancy and the reproductive tract was collected. The corpora lutea (CL) were counted and the number of vital and non-vital embryos, embryonic spacing (distance between two embryos), implantation length, placental length, placental weight and embryonic weight were assessed.

Use of combinations of in vitro quality assessments to predict fertility of bovine semen.

Predicting in vivo fertility of bull ejaculates using in vitro-assessed semen quality criteria remains challenging for the breeding industry. New technologies such as computer-assisted semen analysis (CASA) and flow cytometry may provide accurate and objective methods to improve semen quality control. The aim of this study was to evaluate the relationship between semen quality parameters and field fertility of bull ejaculates.

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.

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.

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.

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).

Relationship of flow cytometric sperm integrity assessments with boar fertility performance under optimized field conditions.

The number of intact and functional spermatozoa in semen can be assessed with flow cytometry and is believed to relate to male fertility. The aim of this study was to examine whether currently used sperm integrity assessments with flow cytometry correlate with field fertility data obtained for boar semen. For this purpose, 20 boars were followed for a 20-wk period (with a total average production of 33 ejaculates per boar) and the obtained fertility results (farrowing rate and number of piglets born) of commercial artificial insemination doses made from these ejaculates were recorded.

Artificial insemination in pigs: predicting male fertility.

Efficient artificial insemination (AI) is essential for future challenges in the pig industry. Knowledge on the exact relation between semen quality characteristics and fertility can have a major impact on both the genetic merit of future animals and the efficiency of AI. Variation in fertility is caused not only by farm- or sow-related parameters but also by boar- and semen-related parameters.

The value of microscopic semen motility assessment at collection for a commercial artificial insemination center, a retrospective study on factors explaining variation in pig fertility.

This study was conducted to evaluate the relationship between boar and semen related parameters and the variation in field fertility results. In 8 years time semen insemination doses from 110 186 ejaculates of 7429 boars were merged to fertility parameters of inseminations of 165 000 sows and these records were used for analysis. From all ejaculates boar and semen related data were recorded at the artificial insemination (AI) centers.

Application of computer-assisted semen analysis to explain variations in pig fertility.

Sperm quality is often evaluated through computer-assisted semen analysis (CASA) and is an indicator of boar fertility. The aim of this research was to study the relationship between CASA motility parameters and fertility results in pigs. Insemination records and semen parameters from a total of 45,532 ejaculates collected over a 3-yr period were used.

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.

Do CASA systems satisfy consumers demands? A critical analysis.

Boar studs are often offered new technologies including several CASA (computer-assisted semen analysis) systems. However, independent information to assist their purchase decisions is not available. The systems accuracy and repeatability variation because of different factors can be evaluated through duplicate testing of semen samples and comparison of the results according to WHO standards for humans.